Friday, 22 January 2021

03:03 AM

FLGUARD: Secure and Private Federated Learning. (arXiv:2101.02281v2 [cs.CR] UPDATED) [cs.CR updates on arXiv.org]

Recently, a number of backdoor attacks against Federated Learning (FL) have been proposed. In such attacks, an adversary injects poisoned model updates into the federated model aggregation process with the goal of manipulating the aggregated model to provide false predictions on specific adversary-chosen inputs. A number of defenses have been proposed; but none of them can effectively protect the FL process also against so-called multi-backdoor attacks in which multiple different backdoors are injected by the adversary simultaneously without severely impacting the benign performance of the aggregated model. To overcome this challenge, we introduce FLGUARD, a poisoning defense framework that is able to defend FL against state-of-the-art backdoor attacks while simultaneously maintaining the benign performance of the aggregated model. Moreover, FL is also vulnerable to inference attacks, in which a malicious aggregator can infer information about clients' training data from their model updates. To thwart such attacks, we augment FLGUARD with state-of-the-art secure computation techniques that securely evaluate the FLGUARD algorithm. We provide formal argumentation for the effectiveness of our FLGUARD and extensively evaluate it against known backdoor attacks on several datasets and applications (including image classification, word prediction, and IoT intrusion detection), demonstrating that FLGUARD can entirely remove backdoors with a negligible effect on accuracy. We also show that private FLGUARD achieves practical runtimes.

[Editorial] COVID-19: the intersection of education and health [The Lancet]

What lessons does the COVID-19 syndemic offer when considering the convergence between health and education? The International Day of Education, on Jan 24, provides an opportunity to reflect on the weaknesses of the education system before COVID-19, and on the impact of school closures and education disruptions on children and adolescents. Since March, 2020, more than 1·5 billion students worldwide—an unprecedented number—have been affected by school or university closures. The implications of these closures are enormous.

[Correspondence] Reaffirming health and safety precautionary principles for COVID-19 in the UK [The Lancet]

In their case for a sustainable UK strategy for COVID-19, Deepti Gurdasani and colleagues1 recommend “restoration of an adequate health and safety inspectorate”. We do not believe that the UK Health and Safety Executive (HSE) should, like Public Health England, be made a scapegoat for lack of ministerial direction2 but rather that the HSE should be restored the wherewithal to fulfil its mandate.

Bilateral Attention Network for RGB-D Salient Object Detection [IEEE Transactions on Image Processing - new TOC]

RGB-D salient object detection (SOD) aims to segment the most attractive objects in a pair of cross-modal RGB and depth images. Currently, most existing RGB-D SOD methods focus on the foreground region when utilizing the depth images. However, the background also provides important information in traditional SOD methods for promising performance. To better explore salient information in both foreground and background regions, this paper proposes a Bilateral Attention Network (BiANet) for the RGB-D SOD task. Specifically, we introduce a Bilateral Attention Module (BAM) with a complementary attention mechanism: foreground-first (FF) attention and background-first (BF) attention. The FF attention focuses on the foreground region with a gradual refinement style, while the BF one recovers potentially useful salient information in the background region. Benefited from the proposed BAM module, our BiANet can capture more meaningful foreground and background cues, and shift more attention to refining the uncertain details between foreground and background regions. Additionally, we extend our BAM by leveraging the multi-scale techniques for better SOD performance. Extensive experiments on six benchmark datasets demonstrate that our BiANet outperforms other state-of-the-art RGB-D SOD methods in terms of objective metrics and subjective visual comparison. Our BiANet can run up to 80 fps on $224times 224$ RGB-D images, with an NVIDIA GeForce RTX 2080Ti GPU. Comprehensive ablation studies also validate our contributions.

Thursday, 21 January 2021

06:43 PM

Drinking Water in the United States: Implications of Water Safety, Access, and Consumption [Annual Reviews: Annual Review of Nutrition: Table of Contents]

Annual Review of Nutrition, Volume 40, Issue 1, Page 345-373, September 2020.

Size of connections between nerve cells determines their signaling strength [EurekAlert! - Breaking News]

Nerve cells communicate with one another via synapses. Neuroscientists at the University of Zurich and ETH Zurich have now found that these connections seem to be much more powerful than previously thought. The larger the synapse, the stronger the signal it transmits. These findings will enable a better understanding of how the brain functions and how neurological disorders arise.

10:36 AM

Gendered accountability: when and why do women’s policy priorities get implemented? [European Political Science Review]

Recent decades have seen a surge in women occupying positions of political power. This has been welcomed in part as a means of achieving better policy outcomes for women. We interrogate this proposition, developing a “gendered accountability” framework to explain when and how female representation promotes the implementation of policies that women prioritize. Our empirical analysis applies this framework to sub-Saharan Africa, home to the largest recent expansion in women’s political representation. We find that increased female representation in the legislature is robustly associated with reduced infant and child mortality as well as greater spending on health. Effects are magnified when women are more active in civil society and appear primarily in countries that have gender quotas and proportional electoral systems. Thus, while female representation can lead to improved policy outcomes for women, the process is not automatic and is unlikely to occur absent key institutional and societal conditions.

Elite cueing and attitudes towards trade agreements: the case of TTIP [European Political Science Review]

How does elite communication affect citizens’ attitudes towards trade agreements? Building on a growing literature on context factors influencing public opinion about trade and trade agreements; we argue that citizens rely on cues provided by political elites, especially political parties, when forming their views towards these agreements. Such cueing effects are most likely for citizens with little information about a trade agreement and for citizens receiving cues from trusted elites. In addition, citizens exposed to cues from non-trusted elites should exhibit a source-opposing effect. Our key contribution is to test these expectations relying on a survey experiment on the Transatlantic Trade and Investment Partnership (TTIP) carried out in Germany and Spain. The findings from our experiment support the existence of elite cueing effects, although to a limited degree. Overall, the paper contributes to a better understanding of public opinion towards TTIP, trade policy attitudes, and public opinion more generally.

A tough trade-off? The asymmetrical impact of populist radical right inclusion on satisfaction with democracy and government [European Political Science Review]

Populist radical right (PRR) parties are increasingly included in coalition governments across Western Europe. How does such inclusion affect satisfaction with democracy (SWD) in these societies? While some citizens will feel democracy has grown more responsive, others will abhor the inclusion of such controversial parties. Using data from the European Social Survey (2002–2018) and panel data from the Netherlands, we investigate how nativists’ and non-nativists’ SWD depends on mainstream parties’ strategies towards PRR parties. We show that the effect is asymmetrical: at moments of inclusion nativists become substantially more satisfied with democracy, while such satisfaction among non-nativists decreases less or not at all. This pattern, which we attribute to Easton’s ‘reservoir of goodwill’, that is, a buffer of political support generated by a track-record of good performance and responsiveness, can account for the seemingly contradictory increase in SWD in many Western European countries in times of populism.

03:03 AM

Safer Illinois and RokWall: Privacy Preserving University Health Apps for COVID-19. (arXiv:2101.07897v1 [cs.CR]) [cs.CR updates on arXiv.org]

COVID-19 has fundamentally disrupted the way we live. Government bodies, universities, and companies worldwide are rapidly developing technologies to combat the COVID-19 pandemic and safely reopen society. Essential analytics tools such as contact tracing, super-spreader event detection, and exposure mapping require collecting and analyzing sensitive user information. The increasing use of such powerful data-driven applications necessitates a secure, privacy-preserving infrastructure for computation on personal data. In this paper, we analyze two such computing infrastructures under development at the University of Illinois at Urbana-Champaign to track and mitigate the spread of COVID-19. First, we present Safer Illinois, a system for decentralized health analytics supporting two applications currently deployed with widespread adoption: digital contact tracing and COVID-19 status cards. Second, we introduce the RokWall architecture for privacy-preserving centralized data analytics on sensitive user data. We discuss the architecture of these systems, design choices, threat models considered, and the challenges we experienced in developing production-ready systems for sensitive data analysis.

MIT SafePaths Card (MiSaCa): Augmenting Paper Based Vaccination Cards with Printed Codes. (arXiv:2101.07931v1 [cs.CY]) [cs.CR updates on arXiv.org]

In this early draft, we describe a user-centric, card-based system for vaccine distribution. Our system makes use of digitally signed QR codes and their use for phased vaccine distribution, vaccine administration/record-keeping, immunization verification, and follow-up symptom reporting. Furthermore, we propose and describe a complementary scanner app system to be used by vaccination clinics, public health officials, and immunization verification parties to effectively utilize card-based framework. We believe that the proposed system provides a privacy-preserving and efficient framework for vaccine distribution in both developed and developing regions.

Inference under Information Constraints III: Local Privacy Constraints. (arXiv:2101.07981v1 [cs.DS]) [cs.CR updates on arXiv.org]

We study goodness-of-fit and independence testing of discrete distributions in a setting where samples are distributed across multiple users. The users wish to preserve the privacy of their data while enabling a central server to perform the tests. Under the notion of local differential privacy, we propose simple, sample-optimal, and communication-efficient protocols for these two questions in the noninteractive setting, where in addition users may or may not share a common random seed. In particular, we show that the availability of shared (public) randomness greatly reduces the sample complexity. Underlying our public-coin protocols are privacy-preserving mappings which, when applied to the samples, minimally contract the distance between their respective probability distributions.

Adversarial Attacks for Tabular Data: Application to Fraud Detection and Imbalanced Data. (arXiv:2101.08030v1 [cs.CR]) [cs.CR updates on arXiv.org]

Guaranteeing the security of transactional systems is a crucial priority of all institutions that process transactions, in order to protect their businesses against cyberattacks and fraudulent attempts. Adversarial attacks are novel techniques that, other than being proven to be effective to fool image classification models, can also be applied to tabular data. Adversarial attacks aim at producing adversarial examples, in other words, slightly modified inputs that induce the Artificial Intelligence (AI) system to return incorrect outputs that are advantageous for the attacker. In this paper we illustrate a novel approach to modify and adapt state-of-the-art algorithms to imbalanced tabular data, in the context of fraud detection. Experimental results show that the proposed modifications lead to a perfect attack success rate, obtaining adversarial examples that are also less perceptible when analyzed by humans. Moreover, when applied to a real-world production system, the proposed techniques shows the possibility of posing a serious threat to the robustness of advanced AI-based fraud detection procedures.

Wednesday, 20 January 2021

06:44 PM

Dopamine-based mechanism for transient forgetting [Nature - Issue - nature.com science feeds]

Nature, Published online: 20 January 2021; doi:10.1038/s41586-020-03154-y

A dopamine neuron that underpins transient forgetting in Drosophila is activated by the presentation of interfering stimuli immediately before memory retrieval, modulating this retrieval by stimulating a dopamine receptor in mushroom body neurons.

Fear of the empty [Nature - Issue - nature.com science feeds]

Nature, Published online: 20 January 2021; doi:10.1038/d41586-021-00122-y

Broken dreams.

10:37 AM

Breakthrough in understanding 'tummy bug' bacteria [EurekAlert! - Breaking News]

Scientists have discovered how bacteria commonly responsible for seafood-related stomach upsets can go dormant and then "wake up".

Severe menopause symptoms often accompany premature ovarian insufficiency [EurekAlert! - Breaking News]

Hot flashes, insomnia, and vaginal dryness are commonly reported symptoms that accompany the menopause transition. A new study suggests that such symptoms--especially psychological and sexual problems--are worse for women who have premature ovarian insufficiency (POI) than for women undergoing natural menopause. Study results are published online today in Menopause, the journal of The North American Menopause Society (NAMS).

Tuesday, 19 January 2021

06:43 PM

Publisher Correction: COVID-19 vaccine BNT162b1 elicits human antibody and TH1 T cell responses [Nature - Issue - nature.com science feeds]

Nature, Published online: 19 January 2021; doi:10.1038/s41586-020-03102-w

Publisher Correction: COVID-19 vaccine BNT162b1 elicits human antibody and TH1 T cell responses

Publisher Correction: Seismic evidence for partial melt below tectonic plates [Nature - Issue - nature.com science feeds]

Nature, Published online: 19 January 2021; doi:10.1038/s41586-020-03103-9

Publisher Correction: Seismic evidence for partial melt below tectonic plates

Publisher Correction: Single-shot Ad26 vaccine protects against SARS-CoV-2 in rhesus macaques [Nature - Issue - nature.com science feeds]

Nature, Published online: 19 January 2021; doi:10.1038/s41586-020-03100-y

Publisher Correction: Single-shot Ad26 vaccine protects against SARS-CoV-2 in rhesus macaques

WHO Launches Global Push to Eliminate Cervical Cancer [JAMA Current Issue]

By boosting human papillomavirus vaccination, cervical cancer screening, diagnosis, and treatment, the World Health Organization (WHO) hopes to slash new cervical cancer cases by 40% and deaths by 5 million by 2050. The effort is the first time the World Health Assembly’s 194 member states have signed on to eliminate a type of cancer.

USPSTF Recommendation: Interventions to Promote Tobacco Cessation [JAMA Current Issue]

This JAMA Patient Page summarizes the USPSTF 2020 guideline recommending that physicians ask all adults about tobacco use, advise them to stop using tobacco, and provide behavioral interventions and drugs shown effective for stopping cigarette and other tobacco use.

Physician Performance in the Medicare Merit-based Incentive Payment System [JAMA Current Issue]

To the Editor In their recent article, Dr Johnston and colleagues reported that health system affiliation was associated with significantly better performance scores and more favorable value-based reimbursement for clinicians participating in the inaugural payment year (2019) of the Medicare Merit-based Incentive Payment System (MIPS). Even though this program may accelerate clinician consolidation within health systems, I believe their findings may be overstated for 3 reasons.

Effect of Tidal Volume on Pulmonary Outcomes After Surgery [JAMA Current Issue]

To the Editor The inherent physiological rationale for lowering tidal volume during mechanical ventilation is to decrease strain on the lung tissue to avoid ventilator-induced lung injury. In the study by Dr Karalapillai and colleagues, there was a considerable difference in tidal volumes between the groups (mean, 396.6 [SD, 83.5] mL vs 611.1 [SD, 111.9] mL). However, ventilator-induced lung injury is not only a function of static parameters such as strain from tidal volume or stress from inspiratory pressures, but also from the complex interplay between static and dynamic variables, including the rate of lung deformation (strain rate) and the cycling frequency, or respiratory rate. A measure that aims to integrate static and dynamic parameters of ventilation is mechanical power, which estimates the energy per minute that is applied to the respiratory system. Although controversies still exist regarding its computation, high mechanical power has been associated with increased lung injury and mortality.

Table Inversion Error [JAMA Current Issue]

In the Research Letter entitled “Pediatric Magnet Ingestions After Federal Rule Changes, 2009-2019,” published in the November 24, 2020, issue of JAMA, the percentages and P values were inverted between the rows for the age groups of 6 through 11 years and 12 through 17 years in the Table. This article was corrected online.

Lack of physical exercise during COVID-19 confinement may lead to a rise in mortality [EurekAlert! - Breaking News]

In a review article published in Frontiers of Endocrinology, Brazilian researchers estimate a reduction of 35% in levels of physical activity and a rise of 28% in sedentary behavior in the initial months of confinement imposed by the pandemic.

Spike proteins of SARS-CoV-2 relatives can evolve against immune responses [EurekAlert! - Breaking News]

Scientists have shown that two species of seasonal human coronavirus related to SARS-CoV-2 can evolve in certain proteins to escape recognition by the immune system, according to a study published today in eLife.

Friday, 15 January 2021

03:00 AM

[Perspectives] Anne Johnson: Dame of public health epidemiology [The Lancet]

In December, 2020, Dame Anne Johnson became the new President of the UK Academy of Medical Sciences (AMS), an appropriate appointment for a leading epidemiologist whose stellar career stretches back 35 years. Last year, Johnson co-launched Health of the Public—a virtual school that seeks to synergise research across specialties at her academic home University College London (UCL), UK, where she is Professor of Infectious Disease Epidemiology. “Health of the Public epitomises everything that is so rich at UCL, bringing together a community of expertise across many fields, including engineering, climate science, anthropology, law, and economics, in order to take a much broader view—for example, of the impact of COVID-19, and how we should approach our future health”, she says.

[Correspondence] Deep learning and cancer biomarkers: recognising lead-time bias – Authors' reply [The Lancet]

Michael Bretthauer and colleagues are concerned that our study1 of a deep learning system for the prediction of survival of patients with colorectal cancer did not consider potential lead-time bias. Cancers detected through screening tend to be less advanced (stage I) than those detected through symptoms.2 Early detection will also increase the survival time when measured from cancer diagnosis because the cancer would otherwise have been detected later or not at all and earlier intervention might extend life.

[Case Report] Novichok nerve agent poisoning [The Lancet]

On Aug 20, 2020, a 44-year-old man who was previously healthy suddenly became confused and began to sweat heavily on a domestic flight in Russia approximately 10 min after departure; he vomited, collapsed, and lost consciousness. After an emergency landing, the man was admitted to the toxicology unit of a local hospital in Omsk, Russia, approximately 2 h after symptom onset. According to the discharge report, the patient presented comatose with hypersalivation and increased diaphoresis and was diagnosed to have respiratory failure, myoclonic status, disturbed carbohydrate metabolism, electrolyte disorders, and metabolic encephalopathy.

Tuesday, 12 January 2021

02:54 AM

Blind Deconvolution for Poissonian Blurred Image With Total Variation and <italic>L</italic><sub>0</sub>-Norm Gradient Regularizations [IEEE Transactions on Image Processing - new TOC]

This paper proposes a regularized blind deconvolution method for restoring Poissonian blurred image. The problem is formulated by utilizing the L0-norm of image gradients and total variation (TV) to regularize the latent image and point spread function (PSF), respectively, and combining them with the negative logarithmic Poisson log-likelihood. To solve the problem, we propose an approach which combines the methods of variable splitting and Lagrange multiplier to convert the original problem into three sub-problems, and then design an alternating minimization algorithm which incorporates the estimation of PSF and latent image as well as the updation of Lagrange multiplier into account. We also design a non-blind deconvolution method based on TV regularization to further improve the quality of the restored image. Experimental results on both synthetic and real-world Poissonian blurred images show that the proposed method can achieve restored images of very high quality, which is competitive with or even better than some state of the art methods.

Cpds: Enabling Compressed and Private Data Sharing for Industrial Internet of Things Over Blockchain [IEEE Transactions on Industrial Informatics - new TOC]

Internet of Things (IoT) is a promising technology to provide product traceability for industrial systems. By using sensing and networking techniques, an IoT-enabled industrial system enables its participants to efficiently track products and record their status during production process. Current industrial IoT systems lack a unified product data sharing service, which prevents the participants from acquiring trusted traceability of products. Using emerging blockchain technology to build such a service is a promising direction. However, directly storing product data on blockchain incurs in efficiency and privacy issues in data management due to its distributed infrastructure. In response, we propose Cpds, a compressed and private data sharing framework, that provides efficient and private data management for product data stored on the blockchain. Cpds devises two new mechanisms to store compressed and policy-enforced product data on the blockchain. As a result, multiple industrial participants can efficiently share product data with fine-grained access control in a distributed environment without relying on a trusted intermediary. We conduct extensive empirical studies and demonstrate the feasibility of Cpds in improving the efficiency and security protection of product data storage on the blockchain.

Peer-to-Peer Multienergy and Communication Resource Trading for Interconnected Microgrids Microgrids [IEEE Transactions on Industrial Informatics - new TOC]

This article proposes a peer-to-peer transactive multiresource trading framework for multiple multienergy microgrids. In this framework, the interconnected microgrids not only fulfil the multienergy demands of with local hybrid biogas-solar-wind renewables, but also proactively trade their available multienergy and communication resources with each other for delivering secured and high quality of services. The multimicrogrid multienergy and communication trading is an intractable optimization problem because of their inherent strong couplings of multiple resources and independent decision-makings. The original problem is thus formulated as a Nash bargaining problem and further decomposed into the subsequent social multiresource allocation subproblem and payoff allocation subproblem. Furthermore, fully-distributed alternating direction method of multipliers approaches with only limited trading information shared are developed to co-optimize the communication and energy flows while taking into account the local resource-autonomy of heterogeneous microgrids. The proposed methodology is implemented and benchmarked on a three-microgrid system over a 24-h scheduling periods. Numerical results show the superiority of the proposed scheme in system operational economy and resource utilization, and also demonstrate the effectiveness of the proposed distributed approach.

Precise Positioning of Circular Mark Points and Transistor Components in Surface Mounting Technology Applications [IEEE Transactions on Industrial Informatics - new TOC]

The visual inspection algorithms are the core of automatic optical inspection system on surface mounting machines. This article is concerned with the development of precise positioning algorithms for circular mark points and transistor (TR) components on surface mounting devices. To handle nonuniform illumination or occlusion of other components, a polar coordinate transform and smoothness selection based circular mark point location method is proposed. The TR components are fundamental chips in electronic products and have various package types. The illumination changes, background disturbance, and the diversity of package types have imposed great challenges on the development of the uniform algorithm for detection and location of TR components. To deal with these issues, the 1-D integral image based TR component detection and location algorithm is proposed and the coordinates and orientation of the component are calculated simultaneously. The efficiency of the proposed methods is tested on real images and compared with classical Hough transform method, commercial algorithms on SMT482 device, and two methods of Halcon software.

A Cascade Broad Neural Network for Concrete Structural Crack Damage Automated Classification [IEEE Transactions on Industrial Informatics - new TOC]

Crack is the earlier indication of concrete structural severe damage; it plays an important role in structure health monitoring (SHM) of industrial civil infrastructures (such as buildings, bridges, roads, dams, etc.). Crack damage classification is the first and critical stage for concrete SHM. However, commonly used human visual classification is costly, labor-intensive, and unreliable, other machine learning based classification methods also have some drawbacks. To address these problems, this article proposes a cascade broad neural network architecture for concrete surface structural crack damage automated classification, which generates an effective and efficient framework with much less hyper-parameters than deep neural networks, and sufficiently explores the advantages of multilevel cascades of classifier ensemble. Experimental results on four challenging datasets demonstrate that its performance is quite more excellent than current mainstream classification methods (both in testing accuracy and training time).

Fast and Accurate Convolution Neural Network for Detecting Manufacturing Data [IEEE Transactions on Industrial Informatics - new TOC]

This article introduces a technique known as clustering with particle for object detection (CPOD) for use in smart factories. CPOD builds on regional-based methods to identify smart object data using outlier detection, clustering, particle swarm optimization (PSO), and deep convolutional networks. The process starts by removing noise and errors from the images database by the local outlier factor (LOF) algorithm. Next, the algorithm studies different correlations from the set of images in the database. This creates homogeneous, and similar clusters using the well-known $k$-means algorithm, and the FastRCNN (fast region convolutional neural network) uses these clusters to design efficient and more focused models. PSO is used to optimize the different parameters including, the number of neighbors of LOF, the number of clusters of $k$-means, the number of epochs, and the error learning rate for FastRCNN. The inference process benefits from the knowledge provided by training. Instead of considering a complex single model of the whole images database, we consider a simple homogeneous model. To demonstrate the usefulness of our approach, intensive experiments have been carried out on standard images database, and real smart manufacturer data. Our results show that CPOD when compared to baseline object detection solutions is superior in terms of runtime and accuracy.

Friday, 01 January 2021

02:39 AM

Personal Fixations-Based Object Segmentation With Object Localization and Boundary Preservation [IEEE Transactions on Image Processing - new TOC]

As a natural way for human-computer interaction, fixation provides a promising solution for interactive image segmentation. In this paper, we focus on Personal Fixations-based Object Segmentation (PFOS) to address issues in previous studies, such as the lack of appropriate dataset and the ambiguity in fixations-based interaction. In particular, we first construct a new PFOS dataset by carefully collecting pixel-level binary annotation data over an existing fixation prediction dataset, such dataset is expected to greatly facilitate the study along the line. Then, considering characteristics of personal fixations, we propose a novel network based on Object Localization and Boundary Preservation (OLBP) to segment the gazed objects. Specifically, the OLBP network utilizes an Object Localization Module (OLM) to analyze personal fixations and locates the gazed objects based on the interpretation. Then, a Boundary Preservation Module (BPM) is designed to introduce additional boundary information to guard the completeness of the gazed objects. Moreover, OLBP is organized in the mixed bottom-up and top-down manner with multiple types of deep supervision. Extensive experiments on the constructed PFOS dataset show the superiority of the proposed OLBP network over 17 state-of-the-art methods, and demonstrate the effectiveness of the proposed OLM and BPM components. The constructed PFOS dataset and the proposed OLBP network are available at https://github.com/MathLee/OLBPNet4PFOS.

Wednesday, 30 December 2020

06:28 PM

Managing Load to Optimize Well-Being and Recovery During Short-Term Match Congestion in Elite Basketball [International Journal of Sports Physiology and Performance]

Journal Name: International Journal of Sports Physiology and Performance
Volume: 16
Issue: 1
Pages: 45-50

Muscle Fatigability After Hex-Bar Deadlift Exercise Performed With Fast or Slow Tempo [International Journal of Sports Physiology and Performance]

Journal Name: International Journal of Sports Physiology and Performance
Volume: 16
Issue: 1
Pages: 117-123

Training Distribution in 1500-m Speed Skating: A Case Study of an Olympic Gold Medalist [International Journal of Sports Physiology and Performance]

Journal Name: International Journal of Sports Physiology and Performance
Volume: 16
Issue: 1
Pages: 149-153

Tuesday, 22 December 2020

02:27 AM

Table of Contents [IEEE Transactions on Industrial Electronics - new TOC]

Presents the table of contents for this issue of the publication.

Friday, 18 December 2020

02:19 AM

An Improved Fault-Tolerant Control Scheme for Cascaded H-Bridge STATCOM With Higher Attainable Balanced Line-to-Line Voltages [IEEE Transactions on Industrial Electronics - new TOC]

Fault-tolerant operation ability is of great importance for stable operation of cascaded H-bridge (CHB) converters, under open-circuit (OC) or short-circuit (SC) switch failures in submodule (SM). In this article, an improved fault-tolerant control strategy is proposed for CHB-based static synchronous compensator (STATCOM) under SM faults. First of all, compared with the conventional fault-tolerant method of directly bypassing the faulty SMs, the proposed fault-tolerant method takes advantage of the healthy switches of the faulty SMs, where they are still able to generate either positive or negative voltage level. As a result, more output voltage levels can be generated, and it raises the attainable balanced line-to-line voltage, especially when different fault types exist at the same time. Then, based on the specific condition of OC fault or SC fault, when the output voltage reference of the faulty phase reaches its limit, the references of the other two healthy phases are redistributed to generate the desired line-to-line voltage. With the reconfiguration of modulation waves, the attainable balanced line-to-line voltage can be further improved. In addition, the proposed fault-tolerant method possesses the ability of cluster voltage balancing, which is an important issue for the STATCOM application. Simulation and experimental results validate the effectiveness of the proposed fault-tolerant method.

A Brushless Dual-Electrical-Port Dual-Mechanical-Port Machine With Integrated Winding Configuration [IEEE Transactions on Industrial Electronics - new TOC]

The brushless dual-electrical-port dual-mech-anical-port (BLDD) machine is a newly developed machine type which can replace conventional power split system based on planetary gear. BLDD machine always contains one stator and two coaxial rotors, and two sets of windings are required to control two rotors. In this article, a novel integrated winding configuration is proposed to replace two original windings with different pole number, i.e., the integrated winding should have the ability to produce two pole number, independent-control magnetomotive forces (MMFs). By carefully designing coil displacement and terminal configuration, two current components with different phases are skillfully injected to the integrated winding, which produces MMFs with different pole-pairs. Compared with original winding configuration, the proposed integrated winding has two main advantages. First, higher current can be injected under the same copper loss, which improves the torque density of BLDD machine indirectly; second, the configuration of the integrated winding is the same as one set of overlapping winding, which contains only one coil configuration and simplifies the manufacture process. In this article, the structure and operation principle of the integrated winding are detailedly introduced, and the electromagnetic performance of BLDD machine equipped with integrated winding is investigated by finite element analysis (FEA), finally a prototype is also manufactured and tested to verify the analysis.

Batteryless Tire Pressure Real-Time Monitoring System Driven by an Ultralow Frequency Piezoelectric Rotational Energy Harvester [IEEE Transactions on Industrial Electronics - new TOC]

Tire pressure monitoring system (TPMS) has been brought into the stringent regulatory frameworks of many countries in the automotive market. However, common commercial TPMSs must rely on a life-limited battery, which brings about some safety risks and environmental problems. It is worthy to note that energy harvesting approaches are promising to realize a batteryless TPMS. In this article, a rotation-driven piezoelectric energy harvester with eight typical nonlinear buckled bridges is proposed to effectively scavenge ultralow frequency kinetic energy. Thinned bulk PZT film is employed as the piezoelectric functional layer based on its excellent electromechanical factor. Gear-induced interwell oscillation mechanism ensures the effective deformation of the piezoelectric buckled bridges. The developed harvester can generate the effective output power of 8.9 mW under the optimal resistance of 3 kΩ at 8.3 Hz rotational frequency. The 47, 100, and 330 μF capacitors can be saturated at 14.5, 15.1, and 14.5 V during 10, 19, and 51 s, respectively. Additionally, a commercial TPMS can be effectively powered by this harvester when it works at more than a critical frequency locating at 3.0–3.7 Hz. The commercial TPMS can be operated in realtime when the applied rotational frequency is more than 8.3 Hz.

Analytical Solution for Nonlinear Three-Dimensional Guidance With Impact Angle and Field-of-View Constraints [IEEE Transactions on Industrial Electronics - new TOC]

An analytical 3-D guidance law with impact angle and field-of-view (FOV) constraints considering nonlinear coupled dynamics is proposed. As a stepping stone, the guidance model is transformed to a set of nonlinear differential equations in terms of the relative range variable. To meet the desired impact angles in the pitch and yaw planes, two cubic polynomials including eight coefficients are developed with respect to the relative range for creating reference line-of-sight (LOS) profiles. The unknown coefficients are explicitly solved by initial and terminal conditions on the LOS angles and LOS rates in the mutually orthogonal planes. Then, the analytical 3-D impact angle guidance (IAG) law is derived via formulating the second-order LOS dynamics of the transformed model. Moreover, the relation between the seeker's look angle and the reference LOS profiles is developed, such that the achievable impact angle set can be obtained to handle the FOV limit. Numerical simulations with comparison study and a realistic model are conducted to verify effectiveness and robustness of the guidance law. Its feasibility is additionally validated by applying it to the guidance of unmanned aerial vehicles landing on surface moving carriers.

Tuesday, 15 December 2020

02:14 AM

HIV proviral DNA integration can drive T cell growth ex vivo [Microbiology] [Early Edition]

In vivo clonal expansion of HIV-infected T cells is an important mechanism of viral persistence. In some cases, clonal expansion is driven by HIV proviral DNA integrated into one of a handful of genes. To investigate this phenomenon in vitro, we infected primary CD4+ T cells with an HIV construct...

Identification of Z nucleotides as an ancient signal for two-component system activation in bacteria [Microbiology] [Early Edition]

Two-component systems (TCSs) in bacteria are molecular circuits that allow the perception of and response to diverse stimuli. These signaling circuits rely on phosphoryl-group transfers between transmitter and receiver domains of sensor kinase and response regulator proteins, and regulate several cellular processes in response to internal or external cues. Phosphorylation,...

Exopolysaccharide defects cause hyper-thymineless death in Escherichia coli via massive loss of chromosomal DNA and cell lysis [Microbiology] [Early Edition]

Thymineless death in Escherichia coli thyA mutants growing in the absence of thymidine (dT) is preceded by a substantial resistance phase, during which the culture titer remains static, as if the chromosome has to accumulate damage before ultimately failing. Significant chromosomal replication and fragmentation during the resistance phase could provide...

Tuesday, 08 December 2020

10:03 AM

Mesyl phosphoramidate backbone modified antisense oligonucleotides targeting miR-21 with enhanced in vivo therapeutic potency [Biochemistry] [Early Edition]

The design of modified oligonucleotides that combine in one molecule several therapeutically beneficial properties still poses a major challenge. Recently a new type of modified mesyl phosphoramidate (or µ-) oligonucleotide was described that demonstrates high affinity to RNA, exceptional nuclease resistance, efficient recruitment of RNase H, and potent inhibition of...

02:07 AM

Siamese Regression Tracking With Reinforced Template Updating [IEEE Transactions on Image Processing - new TOC]

Siamese networks are prevalent in visual tracking because of the efficient localization. The networks take both a search patch and a target template as inputs where the target template is usually from the initial frame. Meanwhile, Siamese trackers do not update network parameters online for real-time efficiency. The fixed target template and CNN parameters make Siamese trackers not effective to capture target appearance variations. In this paper, we propose a template updating method via reinforcement learning for Siamese regression trackers. We collect a series of templates and learn to maintain them based on an actor-critic framework. Among this framework, the actor network that is trained by deep reinforcement learning effectively updates the templates based on the tracking result on each frame. Besides the target template, we update the Siamese regression tracker online to adapt to target appearance variations. The experimental results on the standard benchmarks show the effectiveness of both template and network updating. The proposed tracker SiamRTU performs favorably against state-of-the-art approaches.

A Game Theory Based CTU-Level Bit Allocation Scheme for HEVC Region of Interest Coding [IEEE Transactions on Image Processing - new TOC]

In this article, a new CTU-level bit allocation scheme aimed at subjectively optimized video coding for video conferencing applications is presented, in which the non-cooperative Stackelberg game is used for formulating and solving the bit allocation problem during the encoding process. Videos are divided into the Region of interests (ROI) which attracts people more and the non-ROI. The two regions are defined as the players in the game, where the ROI is the leader who takes the priority in strategy making and the non-ROI follows the leader’s strategy. Based on the formulated game, the bit allocation problem can be expressed as a utility optimization problem. By solving the corresponding utility optimization problem, the bit allocation strategy between the ROI and the non-ROI will be established. Then the bits will be allocated to each CTU by a Newton-method-based algorithm for encoding, in which a trade-off between the ROI’s quality and the overall quality can be achieved. Both the objective and subjective experimental results show that our proposed bit allocation method can improve the quality of ROI significantly with an acceptable overall quality degradation, leading to a better visual experience.

Wednesday, 25 November 2020

02:02 AM

GenBank’s reliability is uncertain for biodiversity researchers seeking species-level assignment for eDNA [Letters (Online Only)] [Early Edition]

Leray et al. (1) reassuringly conclude that “GenBank is a reliable resource for 21st century biodiversity research” based on an important quantitative assessment of its taxonomic accuracy. However, their insightful analysis focuses only on taxonomic levels above species. GenBank (2) is the key reference database for the growing fields of...

Thursday, 19 November 2020

Tuesday, 17 November 2020

02:02 AM

When Automatic Voice Disguise Meets Automatic Speaker Verification [IEEE Transactions on Information Forensics and Security - new TOC]

The technique of transforming voices in order to hide the real identity of a speaker is called voice disguise, among which automatic voice disguise (AVD) by modifying the spectral and temporal characteristics of voices with miscellaneous algorithms are easily conducted with softwares accessible to the public. AVD has posed great threat to both human listening and automatic speaker verification (ASV). In this paper, we have found that ASV is not only a victim of AVD but could be a tool to beat some simple types of AVD. Firstly, three types of AVD, pitch scaling, vocal tract length normalization (VTLN) and voice conversion (VC), are introduced as representative methods. State-of-the-art ASV methods are subsequently utilized to objectively evaluate the impact of AVD on ASV by equal error rates (EER). Moreover, an approach to restore disguised voice to its original version is proposed by minimizing a function of ASV scores w.r.t. restoration parameters. Experiments are then conducted on disguised voices from Voxceleb, a dataset recorded in real-world noisy scenario. The results have shown that, for the voice disguise by pitch scaling, the proposed approach obtains an EER around 7% comparing to the 30% EER of a recently proposed baseline using the ratio of fundamental frequencies. The proposed approach generalizes well to restore the disguise with nonlinear frequency warping in VTLN by reducing its EER from 34.3% to 18.5%. However, it is difficult to restore the source speakers in VC by our approach, where more complex forms of restoration functions or other paralinguistic cues might be necessary to restore the nonlinear transform in VC. Finally, contrastive visualization on ASV features with and without restoration illustrate the role of the proposed approach in an intuitive way.

High Intrinsic Dimensionality Facilitates Adversarial Attack: Theoretical Evidence [IEEE Transactions on Information Forensics and Security - new TOC]

Machine learning systems are vulnerable to adversarial attack. By applying to the input object a small, carefully-designed perturbation, a classifier can be tricked into making an incorrect prediction. This phenomenon has drawn wide interest, with many attempts made to explain it. However, a complete understanding is yet to emerge. In this paper we adopt a slightly different perspective, still relevant to classification. We consider retrieval, where the output is a set of objects most similar to a user-supplied query object, corresponding to the set of k-nearest neighbors. We investigate the effect of adversarial perturbation on the ranking of objects with respect to a query. Through theoretical analysis, supported by experiments, we demonstrate that as the intrinsic dimensionality of the data domain rises, the amount of perturbation required to subvert neighborhood rankings diminishes, and the vulnerability to adversarial attack rises. We examine two modes of perturbation of the query: either `closer' to the target point, or `farther' from it. We also consider two perspectives: `query-centric', examining the effect of perturbation on the query's own neighborhood ranking, and `target-centric', considering the ranking of the query point in the target's neighborhood set. All four cases correspond to practical scenarios involving classification and retrieval.

NeuroAED: Towards Efficient Abnormal Event Detection in Visual Surveillance With Neuromorphic Vision Sensor [IEEE Transactions on Information Forensics and Security - new TOC]

Abnormal event detection is an important task in research and industrial applications, which has received considerable attention in recent years. Existing methods usually rely on standard frame-based cameras to record the data and process them with computer vision technologies. In contrast, this paper presents a novel neuromorphic vision based abnormal event detection system. Compared to the frame-based camera, neuromorphic vision sensors, such as Dynamic Vision Sensor (DVS), do not acquire full images at a fixed frame rate but rather have independent pixels that output intensity changes (called events) asynchronously at the time they occur. Thus, it avoids the design of the encryption scheme. Since events are triggered by moving edges on the scene, DVS is a natural motion detector for the abnormal objects and automatically filters out any temporally-redundant information. Based on this unique output, we first propose a highly efficient method based on the event density to select activated event cuboids and locate the foreground. We design a novel event-based multiscale spatio-temporal descriptor to extract features from the activated event cuboids for the abnormal event detection. Additionally, we build the NeuroAED dataset, the first public dataset dedicated to abnormal event detection with neuromorphic vision sensor. The NeuroAED dataset consists of four sub-datasets: Walking, Campus, Square, and Stair dataset. Experiments are conducted based on these datasets and demonstrate the high efficiency and accuracy of our method.

Thursday, 12 November 2020

Thursday, 29 October 2020

Friday, 23 October 2020

02:04 AM

Non-Additive Cost Functions for JPEG Steganography Based on Block Boundary Maintenance [IEEE Transactions on Information Forensics and Security - new TOC]

Recent advances show that a reasonable non-additive cost function can significantly improve the security level of additive cost based steganography. So far, there is only one principle, called block boundary continuity (BBC), that has been proposed to define the non-additive cost function for JPEG steganography, and it aims at synchronizing the modification direction of inter-block boundaries in the spatial domain. In this article, we found that JPEG steganography usually introduces more and larger modifications on the boundary than on the inside of each intra-block in the spatial domain, which is another important factor affecting security. Therefore, we present a new principle, called block boundary maintenance (BBM), to minimize the modifications on the spatial block boundaries. In theory, we deduce the BBM principle on how to modify a pair of DCT coefficients of the intra-block to reduce the modifications on the spatial block boundary. According to the BBM principle, we design a new strategy to define non-additive cost functions for JPEG steganography by exploiting the coefficient correlation of the intra-block in the DCT domain. The experimental results show that the BBM-based strategy can minimize modifications on the spatial block boundaries and thus achieve a high-security level when resisting modern JPEG steganalysis. Furthermore, the two principles of BBC and BBM can be fused to further improve the empirical security.

Tuesday, 13 October 2020

Thursday, 24 September 2020

02:03 AM

Nutrition and the 2020 Pandemic [Annual Reviews: Annual Review of Nutrition: Table of Contents]

Annual Review of Nutrition, Volume 40, Issue 1, Page v-vi, September 2020.

Calorie Restriction and Aging in Humans [Annual Reviews: Annual Review of Nutrition: Table of Contents]

Annual Review of Nutrition, Volume 40, Issue 1, Page 105-133, September 2020.

Short Bowel Syndrome: A Paradigm for Intestinal Adaptation to Nutrition? [Annual Reviews: Annual Review of Nutrition: Table of Contents]

Annual Review of Nutrition, Volume 40, Issue 1, Page 299-321, September 2020.

Drinking Water in the United States: Implications of Water Safety, Access, and Consumption [Annual Reviews: Annual Review of Nutrition: Table of Contents]

Annual Review of Nutrition, Volume 40, Issue 1, Page 345-373, September 2020.

Tuesday, 04 August 2020

02:02 AM

Trade Policy in American Economic History [Annual Reviews: Annual Review of Economics: Table of Contents]

Annual Review of Economics, Volume 12, Issue 1, Page 23-44, August 2020.

How Distortions Alter the Impacts of International Trade in Developing Countries [Annual Reviews: Annual Review of Economics: Table of Contents]

Annual Review of Economics, Volume 12, Issue 1, Page 213-238, August 2020.

Political Effects of the Internet and Social Media [Annual Reviews: Annual Review of Economics: Table of Contents]

Annual Review of Economics, Volume 12, Issue 1, Page 415-438, August 2020.

Peer Effects in Networks: A Survey [Annual Reviews: Annual Review of Economics: Table of Contents]

Annual Review of Economics, Volume 12, Issue 1, Page 603-629, August 2020.

Aspirations and Economic Behavior [Annual Reviews: Annual Review of Economics: Table of Contents]

Annual Review of Economics, Volume 12, Issue 1, Page 715-746, August 2020.

Friday, 31 July 2020

02:02 AM

Advances in the Science of Asking Questions [Annual Reviews: Annual Review of Sociology: Table of Contents]

Annual Review of Sociology, Volume 46, Issue 1, Page 37-60, July 2020.

Social Networks and Cognition [Annual Reviews: Annual Review of Sociology: Table of Contents]

Annual Review of Sociology, Volume 46, Issue 1, Page 159-174, July 2020.

Multiracial Categorization, Identity, and Policy in (Mixed) Racial Formations [Annual Reviews: Annual Review of Sociology: Table of Contents]

Annual Review of Sociology, Volume 46, Issue 1, Page 335-353, July 2020.

Contemporary Social Movements in a Hybrid Media Environment [Annual Reviews: Annual Review of Sociology: Table of Contents]

Annual Review of Sociology, Volume 46, Issue 1, Page 443-465, July 2020.

Enhanced Secrecy Performance of Multihop IoT Networks With Cooperative Hybrid-Duplex Jamming [IEEE Transactions on Information Forensics and Security - new TOC]

As the number of connected devices is exponentially increasing, security in Internet of Things (IoT) networks presents a major challenge. Accordingly, in this work we investigate the secrecy performance of multihop IoT networks assuming that each node is equipped with only two antennas, and can operate in both Half-Duplex (HD) and Full-Duplex (FD) modes. Moreover, we propose an FD Cooperative Jamming (CJ) scheme to provide higher security against randomly located eavesdroppers, where each information symbol is protected with two jamming signals by its two neighbouring nodes, one of which is the FD receiver. We demonstrate that under a total power constraint, the proposed FD-CJ scheme significantly outperforms the conventional FD Single Jamming (FD-SJ) approach, where only the receiving node acts as a jammer, especially when the number of hops is larger than two. Moreover, when the Channel State Information (CSI) is available at the transmitter, and transmit beamforming is applied, our results demonstrate that at low Signal-to-Noise Ratio (SNR), higher secrecy performance is obtained if the receiving node operates in HD and allocates both antennas for data reception, leaving only a single jammer active; while at high SNR, a significant secrecy enhancement can be achieved with FD jamming. Our proposed FD-CJ scheme is found to demonstrate a great resilience over multihop networks, as only a marginal performance loss is experienced as the number of hops increases. For each case, an integral closed-form expression is derived for the secrecy outage probability, and verified by Monte Carlo simulations.

Thursday, 30 July 2020

06:02 PM

Violence in Latin America: An Overview of Research and Issues [Annual Reviews: Annual Review of Sociology: Table of Contents]

Annual Review of Sociology, Volume 46, Issue 1, Page 693-706, July 2020.

Tuesday, 12 May 2020

02:02 AM

Understanding Multilateral Institutions in Easy and Hard Times [Annual Reviews: Annual Review of Political Science: Table of Contents]

Annual Review of Political Science, Volume 23, Issue 1, Page 1-18, May 2020.

Democratic Stability: A Long View [Annual Reviews: Annual Review of Political Science: Table of Contents]

Annual Review of Political Science, Volume 23, Issue 1, Page 59-75, May 2020.

Political Misinformation [Annual Reviews: Annual Review of Political Science: Table of Contents]

Annual Review of Political Science, Volume 23, Issue 1, Page 77-94, May 2020.

Transnational Actors and Transnational Governance in Global Environmental Politics [Annual Reviews: Annual Review of Political Science: Table of Contents]

Annual Review of Political Science, Volume 23, Issue 1, Page 203-220, May 2020.

The Changing Cleavage Politics of Western Europe [Annual Reviews: Annual Review of Political Science: Table of Contents]

Annual Review of Political Science, Volume 23, Issue 1, Page 295-314, May 2020.

Tuesday, 11 February 2020

03:00 PM

New Approaches to Target Inflammation in Heart Failure: Harnessing Insights from Studies of Immune Cell Diversity [Annual Reviews: Annual Review of Physiology: Table of Contents]

Annual Review of Physiology, Volume 82, Issue 1, Page 1-20, February 2020.

Neuronal Mechanisms that Drive Organismal Aging Through the Lens of Perception [Annual Reviews: Annual Review of Physiology: Table of Contents]

Annual Review of Physiology, Volume 82, Issue 1, Page 227-249, February 2020.

BMP Signaling in Development, Stem Cells, and Diseases of the Gastrointestinal Tract [Annual Reviews: Annual Review of Physiology: Table of Contents]

Annual Review of Physiology, Volume 82, Issue 1, Page 251-273, February 2020.

Regulation and Effects of FGF23 in Chronic Kidney Disease [Annual Reviews: Annual Review of Physiology: Table of Contents]

Annual Review of Physiology, Volume 82, Issue 1, Page 365-390, February 2020.

Marrow Adipocytes: Origin, Structure, and Function [Annual Reviews: Annual Review of Physiology: Table of Contents]

Annual Review of Physiology, Volume 82, Issue 1, Page 461-484, February 2020.

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