Sunday, 24 May 2020

02:02 AM

New studies reveal extent and risks of laughing gas & stimulant abuse among young people [EurekAlert! - Breaking News]

In one study, researchers from Turkey reported increasing stimulant use among medical students approaching their final exams, despite the substantial risks to their health. In the second study, researchers from the Netherlands detailed the neurological outcomes associated with recreational use of laughing gas (nitrous oxide), suggesting that, for some individuals, permanent neurological damage can occur.

Saturday, 23 May 2020

06:02 PM

John Horton Conway (1937–2020) [Nature - Issue - nature.com science feeds]

Nature, Published online: 23 May 2020; doi:10.1038/d41586-020-01515-1

Playful master of games who transformed mathematics.

02:01 AM

Coronavirus diaries: finding a place to have new ideas [Nature - Issue - nature.com science feeds]

Nature, Published online: 22 May 2020; doi:10.1038/d41586-020-01555-7

John Tregoning finds inspiration in conferences, music and running.

‘Medications should be prescribed by doctors, not the president’: leading Brazilian scientist discusses the pandemic [Nature - Issue - nature.com science feeds]

Nature, Published online: 22 May 2020; doi:10.1038/d41586-020-01506-2

Scientists across the country are battling anti-science sentiment alongside a rapid increase in COVID-19 cases.

Blood test could predict diabetes years before it strikes [EurekAlert! - Breaking News]

Metabolite signature composed of sugars, amino acids and lipids can predict with over 85 per cent accuracy whether a women will develop diabetes after pregnancy marked with gestational diabetes.

Glucose levels linked to maternal mortality even in non-diabetic women [EurekAlert! - Breaking News]

An elevated pre-pregnancy hemoglobin A1c--which measures average blood glucose concentration--is associated with a higher risk of adverse pregnancy outcomes even in women without known diabetes, according to a new study published this week in PLOS Medicine by Joel Ray of ICES and the University of Toronto, Canada, and colleagues.

New technology can detect anti-virus antibody in 20 minutes [EurekAlert! - Breaking News]

Researchers have succeeded in detecting anti-avian influenza virus antibody in blood serum within 20 minutes, using a portable analyzer they have developed to conduct rapid on-site bio tests. If a suitable reagent is developed, this technology could be used to detect antibodies against SARS-CoV-2, the causative virus of COVID-19.

Friday, 22 May 2020

02:01 AM

A Privacy-Preserving Solution for Proximity Tracing Avoiding Identifier Exchanging. (arXiv:2005.10309v1 [cs.CR]) [cs.CR updates on arXiv.org]

Digital contact tracing is one of the actions useful, in combination with other measures, to manage an epidemic diffusion of an infection disease in an after-lock-down phase. This is a very timely issue, due to the pandemic of COVID-19 we are unfortunately living. Apps for contact tracing aim to detect proximity of users and to evaluate the related risk in terms of possible contagious. Existing approaches leverage Bluetooth or GPS, or their combination, even though the prevailing approach is Bluetooth-based and relies on a decentralized model requiring the mutual exchange of ephemeral identifiers among users' smartphones. Unfortunately, a number of security and privacy concerns exist in this kind of solutions, mainly due to the exchange of identifiers, while GPS-based solutions (inherently centralized) may suffer from threats concerning massive surveillance. In this paper, we propose a solution leveraging GPS to detect proximity, and Bluetooth only to improve accuracy, without enabling exchange of identifiers. Unlike related existing solutions, no complex cryptographic mechanism is adopted, while ensuring that the server does not learn anything about locations of users.

Near Instance-Optimality in Differential Privacy. (arXiv:2005.10630v1 [cs.CR]) [cs.CR updates on arXiv.org]

We develop two notions of instance optimality in differential privacy, inspired by classical statistical theory: one by defining a local minimax risk and the other by considering unbiased mechanisms and analogizing the Cramer-Rao bound, and we show that the local modulus of continuity of the estimand of interest completely determines these quantities. We also develop a complementary collection mechanisms, which we term the inverse sensitivity mechanisms, which are instance optimal (or nearly instance optimal) for a large class of estimands. Moreover, these mechanisms uniformly outperform the smooth sensitivity framework on each instance for several function classes of interest, including real-valued continuous functions. We carefully present two instantiations of the mechanisms for median and robust regression estimation with corresponding experiments.

A Note on Cryptographic Algorithms for Private Data Analysis in Contact Tracing Applications. (arXiv:2005.10634v1 [cs.CR]) [cs.CR updates on arXiv.org]

Contact tracing is an important measure to counter the COVID-19 pandemic. In the early phase, many countries employed manual contact tracing to contain the rate of disease spread, however it has many issues. The manual approach is cumbersome, time consuming and also requires active participation of a large number of people to realize it. In order to overcome these drawbacks, digital contact tracing has been proposed that typically involves deploying a contact tracing application on people's mobile devices which can track their movements and close social interactions. While studies suggest that digital contact tracing is more effective than manual contact tracing, it has been observed that higher adoption rates of the contact tracing app may result in a better controlled epidemic. This also increases the confidence in the accuracy of the collected data and the subsequent analytics. One key reason for low adoption rate of contact tracing applications is the concern about individual privacy. In fact, several studies report that contact tracing applications deployed in multiple countries are not privacy friendly and have potential to be used for mass surveillance by the concerned governments. Hence, privacy respecting contact tracing application is the need of the hour that can lead to highly effective, efficient contact tracing. As part of this study, we focus on various cryptographic techniques that can help in addressing the Private Set Intersection problem which lies at the heart of privacy respecting contact tracing. We analyze the computation and communication complexities of these techniques under the typical client-server architecture utilized by contact tracing applications. Further we evaluate those computation and communication complexity expressions for India scenario and thus identify cryptographic techniques that can be more suitably deployed there.

Key Event Receipt Infrastructure (KERI). (arXiv:1907.02143v7 [cs.CR] UPDATED) [cs.CR updates on arXiv.org]

An identity system based secure overlay for the Internet is presented. This includes a primary root-of-trust in self-certifying identifiers. It presents a formalism for Autonomic Identifiers (AIDs) and Autonomic Namespaces (ANs). They are part of an Autonomic Identity System (AIS). This system uses the design principle of minimally sufficient means to provide a candidate trust spanning layer for the internet. Associated with this system is a decentralized key management infrastructure (DKMI). The primary root-of-trust are self-certifying identifiers that are strongly bound at issuance to a cryptographic signing (public, private) key-pair. These are self-contained until/unless control needs to be transferred to a new key-pair. In that event an append only chained key-event log of signed transfer statements provides end verifiable control provenance. This makes intervening operational infrastructure replaceable because the event logs may be therefore be served up by ambient infrastructure. End verifiable logs on ambient infrastructure enables ambient verifiability (verifiable by anyone, anywhere, at anytime). The primary key management operation is key rotation (transference) via a novel key pre-rotation scheme. Two primary trust modalities motivated the design, these are a direct (one-to-one) mode and an indirect (one-to-any) mode. In the direct mode, the identity controller establishes control via verified signatures of the controlling key-pair. The indirect mode extends that trust basis with witnessed key event receipt logs (KERLs) for validating events. The security and accountability guarantees of indirect mode are provided by KERIs Agreement Algorithm for Control Establishment (KACE) among a set of witnesses.

BeepTrace: Blockchain-enabled Privacy-preserving Contact Tracing for COVID-19 Pandemic and Beyond. (arXiv:2005.10103v2 [cs.DC] UPDATED) [cs.CR updates on arXiv.org]

The outbreak of COVID-19 pandemic has exposed an urgent need for effective contact tracing solutions through mobile phone applications to prevent the infection from spreading further. However, due to the nature of contact tracing, public concern on privacy issues has been a bottleneck to the existing solutions, which is significantly affecting the uptake of contact tracing applications across the globe. In this paper, we present a blockchain-enabled privacy-preserving contact tracing scheme: BeepTrace, where we propose to adopt blockchain bridging the user/patient and the authorized solvers to desensitize the user ID and location information. Compared with recently proposed contract tracing solutions, our approach shows higher security and privacy with the additional advantages of being battery friendly and globally accessible. Results show viability in terms of the required resource at both server and mobile phone perspectives. Through breaking the privacy concerns of the public, the proposed BeepTrace solution can provide a timely framework for authorities, companies, software developers and researchers to fast develop and deploy effective digital contact tracing applications, to conquer COVID-19 pandemic soon. Meanwhile, the open initiative of BeepTrace allows worldwide collaborations, integrate existing tracing and positioning solutions with the help of blockchain technology.

[Comment] Mapping neonatal and under-5 mortality in India [The Lancet]

India is one of the world's largest and most populous countries, made up of more than 700 diverse districts. Variations in mortality in the country are known at the macro level, and now the India State-Level Disease Burden Initiative Child Mortality Collaborators1 have mapped neonatal and under-5 mortality rates from 2000 to 2017 for every district in India, going down to geospatial grids as small as 5 km × 5 km. In The Lancet, the study authors report that the under-5 mortality rate (U5MR) in India decreased from 83·1 deaths (95% uncertainty interval 76·7–90·1) in 2000 to 42·4 deaths (36·5–50·0) per 1000 livebirths in 2017, and the neonatal mortality rate (NMR) decreased from 38·0 deaths (34·2–41·6) to 23·5 deaths (20·1–27·8) per 1000 livebirths.

[Correspondence] Hyperinflammatory shock in children during COVID-19 pandemic [The Lancet]

South Thames Retrieval Service in London, UK, provides paediatric intensive care support and retrieval to 2 million children in South East England. During a period of 10 days in mid-April, 2020, we noted an unprecedented cluster of eight children with hyperinflammatory shock, showing features similar to atypical Kawasaki disease, Kawasaki disease shock syndrome,1 or toxic shock syndrome (typical number is one or two children per week). This case cluster formed the basis of a national alert.

[Correspondence] Personal protective equipment needs in the USA during the COVID-19 pandemic [The Lancet]

Personal protective equipment (PPE) shortages (eg, masks, gloves, gowns) endanger patients and health-care workers alike during the coronavirus disease 2019 (COVID-19) pandemic.1 Policymakers and experts have called for donations of existing PPE, increased production by manufacturers, and novel fabrication strategies, such as 3D printing of masks.2,3 However, even as PPE sources are identified, a critical information challenge remains: tracking evolving PPE needs and matching them with existing or emerging PPE stockpiles.

[Articles] Regulatory cell therapy in kidney transplantation (The ONE Study): a harmonised design and analysis of seven non-randomised, single-arm, phase 1/2A trials [The Lancet]

Regulatory cell therapy is achievable and safe in living-donor kidney transplant recipients, and is associated with fewer infectious complications, but similar rejection rates in the first year. Therefore, immune cell therapy is a potentially useful therapeutic approach in recipients of kidney transplant to minimise the burden of general immunosuppression.

[Clinical Picture] Alternative causes of ankle pain in a patient with enthesopathy and X-linked hypophosphataemia [The Lancet]

A 43-year-old Australian-born, white man was referred to our unit because of increasing pain in both his ankles. The pain had developed approximately 7 days earlier. 3 days before the pain started, he had been admitted to hospital with cellulitis of his upper arm; he had been treated for septicaemia and acute kidney injury caused by an infection with Streptococcus pyogenes.

Lungs of deceased COVID-19 patients show distinctive features [EurekAlert! - Breaking News]

In a new study in the New England Journal of Medicine (NEJM), senior author, Steven J. Mentzer, MD, thoracic surgeon at Brigham and Women's Hospital, and a team of international researchers examined seven lungs obtained during autopsy from patients who died of COVID-19.

Thursday, 21 May 2020

02:01 AM

Altered photoreceptor metabolism in mouse causes late stage age-related macular degeneration-like pathologies [Neuroscience] [Early Edition]

Age-related macular degeneration (AMD) is the leading cause of blindness in the elderly. While the histopathology of the different disease stages is well characterized, the cause underlying the progression, from the early drusen stage to the advanced macular degeneration stage that leads to blindness, remains unknown. Here, we show that...

Wednesday, 20 May 2020

06:02 PM

Deciphering human macrophage development at single-cell resolution [Nature - Issue - nature.com science feeds]

Nature, Published online: 20 May 2020; doi:10.1038/s41586-020-2316-7

Single-cell RNA sequencing of haematopoietic cells from human embryos at different developmental stages sheds light on the development and specification of macrophages in different tissues.

Tuesday, 19 May 2020

06:01 PM

Cognitive and brain development is independently influenced by socioeconomic status and polygenic scores for educational attainment [Psychological and Cognitive Sciences] [Early Edition]

Genetic factors and socioeconomic status (SES) inequalities play a large role in educational attainment, and both have been associated with variations in brain structure and cognition. However, genetics and SES are correlated, and no prior study has assessed their neural associations independently. Here we used a polygenic score for educational...

Study Suggests a Second Patient Has Been Cured of HIV [JAMA Current Issue]

For only the second time, a patient with HIV who received an allogeneic hematopoietic stem cell transplant from a donor with an HIV resistance gene appears to have been cured of the disease, according to a recent study.

Drospirenone (Slynd) — A New Progestin-Only Oral Contraceptive [JAMA Current Issue]

This Medical Letter review summarizes the mechanism of action and drug interactions of drospirenone, a new progestin-only oral contraceptive, and compares it with norethindrone, its competitor.

Therapy Approved for Hard-to-Treat Upper Tract Urothelial Cancer [JAMA Current Issue]

The first treatment for low-grade upper tract urothelial cancer (UTUC) has received FDA approval.

Antenatal Corticosteroids [JAMA Current Issue]

Antenatal corticosteroids, when administered to a pregnant woman before delivery of a very premature infant, accelerate fetal lung maturation and prevent neonatal mortality, respiratory distress syndrome, and brain injury. Even though the first trial to demonstrate benefits of antenatal corticosteroid exposure was published in 1972, widespread use of this therapy did not occur until 20 years later. The first systematic review of antenatal corticosteroid therapy was so influential in the obstetric and neonatal care communities that a forest plot from this study is depicted in the logo for the Cochrane Database of Systematic Reviews. Antenatal corticosteroid therapy has been one of the most important advances in perinatal care.

Ensuring Scientific Integrity and Public Confidence in the Search for Effective COVID-19 Treatment [JAMA Current Issue]

This Viewpoint discusses the risks to patients and public health posed by the FDA’s politically pressured Emergency Use Authorization (EUA) of chloroquine and hydroxychloroquine for COVID-19 treatment, and proposes principles to follow to ensure new therapies are studied properly and quickly to maximize benefits and minimize risks to patients.

02:01 AM

How to address the coronavirus’s outsized toll on people of colour [Nature - Issue - nature.com science feeds]

Nature, Published online: 18 May 2020; doi:10.1038/d41586-020-01470-x

US scientists say that better data, testing and hospital preparedness are key to erasing inequalities — and to defeating the pandemic overall.

Friday, 15 May 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.

Partisan Gerrymandering and Political Science [Annual Reviews: Annual Review of Political Science: Table of Contents]

Annual Review of Political Science, Volume 23, Issue 1, Page 171-185, May 2020.

The Fluidity of Racial Classifications [Annual Reviews: Annual Review of Political Science: Table of Contents]

Annual Review of Political Science, Volume 23, Issue 1, Page 221-240, May 2020.

Economic Development and Democracy: Predispositions and Triggers [Annual Reviews: Annual Review of Political Science: Table of Contents]

Annual Review of Political Science, Volume 23, Issue 1, Page 241-257, May 2020.

Survey Experiments in International Political Economy: What We (Don't) Know About the Backlash Against Globalization [Annual Reviews: Annual Review of Political Science: Table of Contents]

Annual Review of Political Science, Volume 23, Issue 1, Page 333-356, May 2020.

Seamless Dynamics for Wild-Frequency Active Rectifiers in More Electric Aircraft [IEEE Transactions on Industrial Electronics - new TOC]

In this article, a seamless dynamics controller for wild-frequency active rectifiers in more electric aircraft (MEA) is presented. The novelty of the proposed control scheme resides in its ability to seamlessly regulate the output dc-bus voltage and input reactive power in the presence of rapid frequency changes. These smooth dynamics are achieved through a multivariable direct model reference adaptive control (MRAC) formulation, which allows the gains of the controller to adjust themselves to the wild-frequency operation of the MEA power generation. The validity and performance effectiveness of the proposed seamless dynamics control scheme is verified experimentally through a laboratory-scaled three-phase 1.5-kW 270-V SiC two-level voltage-source-converter using a variable-frequency programmable grid emulator. Moreover, a traditional proportional-integral controller is implemented experimentally with the same converter as a benchmark to highlight the merits of the proposed MRAC.

Voltage-Adjustable Capacitor Isolated Solid-State Transformer [IEEE Transactions on Industrial Electronics - new TOC]

This article proposes a voltage-adjustable capacitor isolated solid-state transformer (ACISST) to link the medium-voltage direct current distribution and low-voltage direct current distribution. Compared with traditional isolated bidirectional dc–dc converter, the proposed ACISST does not contain high-frequency transformer in base modules (BMs). The galvanic isolation between the primary side and the secondary side of the ACISST is realized by the isolation capacitor as quasi-isolation. The elimination of the high-frequency transformer eliminates the core losses of magnetic elements, improves the conversion efficiency to a certain extent, and reduces the weight of the ACISST. The voltage-adjustable unit realizes the secondary voltage regulation of stable control when the primary-side voltage fluctuates in an acceptable range or load power varies. Bidirectional power flowing is one of the features of ACISST, which is based on the bidirectional power flowing characteristic of BM and simplified dual active bridge. Simulation and experimental results are presented to validate the theoretical analysis.

Control of a Bowden-Cable Actuation System With Embedded BoASensor for Soft Wearable Robots [IEEE Transactions on Industrial Electronics - new TOC]

Control of a Bowden-cable transmission requires dealing with varying frictional nonlinearity of the cable, which varies as the bend angle of the cable changes and degrades the performance of the output tension control if not compensated for. This article proposes a novel method of compensating for the changing nonlinearity of the Bowden cable. The method enables controlling the tension of a Bowden cable without directly measuring the output tension. The output tension differs from the input tension because of friction along the cable, which changes with the cable's bend angle. The bend angle can be estimated by using a Bowden-cable Angle (BoA) Sensor and the input tension of the actuation wire to compensate for the friction change. Friction compensation allows for feedforward control of the output tension of the Bowden-cable transmission despite the varying shape of the cable. The results show that the control error of the output tension decrease from 5.21 to 0.50 N when the bend angle of the Bowden cable change from 0° to 400°. The proposed control method can be fully embedded into a Bowden-cable system without redesigning the original device, minimizing the complexity and size of the actuation system. A Bowden-cable implementing the proposed control method is demonstrated with a soft wearable robotic hand.

Torque Calculation of Permanent Magnet Spherical Motor Based on Virtual Work Method [IEEE Transactions on Industrial Electronics - new TOC]

A double-layer permanent magnet spherical motor (PMSM) with same spatial distribution of stator poles and rotor poles is designed based on spherical harmonic theory in this article. The stator coils are equivalent to permanent magnets to simplify the calculation, and the torque model based on virtual work method is derived. First, the torque model of single pair of poles is derived on the premise of considering the fundamental component of the magnetic field. Then, the relative positions of stator poles and rotor poles, the direction angles of torque components are discussed. Finally, the torque model is obtained by space vector theory and superposition theorem. Moreover, the simulation and experiment are implemented to verify the feasibility and correctness of the proposed torque model. The obtained torque model in this article has similar expression with that of traditional motor, which lays a theoretical foundation for the structure optimization and control strategy of PMSM.

Design and Experimental Evaluation of Immersion and Invariance Observer for Low-Cost Attitude-Heading Reference System [IEEE Transactions on Industrial Electronics - new TOC]

This article presents a new immersion and invariance (I&I) observer for inertial microelectromechanical systems (MEMS) sensors-based, low-cost attitude-heading reference systems (AHRSs). Using the I&I methodology, the observer design problem is formulated as finding a dynamics system, called the observer, and a differentiable manifold in the extended state space of the Euler angles-observer dynamics. The manifold is required to be practically stable with respect to the system trajectories. By imposing this requirement, an observer is derived to robustly estimate the Euler angles. To show the efficacy of the I&I observer and to compare its performance with the extended Kalman filter, rigorous simulations are performed using the raw data of a set of urban vehicular AHRS tests.

Saturday, 09 May 2020

09:49 PM

Dynamic morphoskeletons in development [Biophysics and Computational Biology] [Early Edition]

Morphogenetic flows in developmental biology are characterized by the coordinated motion of thousands of cells that organize into tissues, naturally raising the question of how this collective organization arises. Using only the kinematics of tissue deformation, which naturally integrates local and global mechanisms along cell paths, we identify the dynamic...

Decomposing loss aversion from gaze allocation and pupil dilation [Neuroscience] [Early Edition]

Loss-averse decisions, in which one avoids losses at the expense of gains, are highly prevalent. However, the underlying mechanisms remain controversial. The prevailing account highlights a valuation bias that overweighs losses relative to gains, but an alternative view stresses a response bias to avoid choices involving potential losses. Here we...

Friday, 01 May 2020

02:01 AM

Time-Delay Control Using a Novel Nonlinear Adaptive Law for Accurate Trajectory Tracking of Cable-Driven Robots [IEEE Transactions on Industrial Informatics - new TOC]

In this article, we propose a novel adaptive time-delay control (ATDC) for accurate trajectory tracking of cable-driven robots. The designed ATDC utilizes time-delay estimation (TDE) to estimate the lumped dynamics of the system and provides an attractive model-free structure. Then, a robust control is designed for ATDC with fractional-order nonsingular terminal sliding mode (FONTSM) dynamics. Afterward, a novel nonlinear adaptive law is proposed for the control gains to improve the control performance. Thanks to TDE and FONTSM dynamics, the proposed ATDC is model free and highly accurate. Benefiting from the proposed nonlinear adaptive law, suppression of chattering issue and enhanced control performance have been obtained simultaneously. Stability is analyzed based on the Lyapunov approach. Then, practical experiments have been performed to illustrate the advantages of the proposed ATDC.

Deep Reinforcement Learning for Social-Aware Edge Computing and Caching in Urban Informatics [IEEE Transactions on Industrial Informatics - new TOC]

Empowered with urban informatics, transportation industry has witnessed a paradigm shift. These developments lead to the need of content processing and sharing between vehicles under strict delay constraints. Mobile edge services can help meet these demands through computation offloading and edge caching empowered transmission, while cache-enabled smart vehicles may also work as carriers for content dispatch. However, diverse capacities of edge servers and smart vehicles, as well as unpredictable vehicle routes, make efficient content distribution a challenge. To cope with this challenge, in this article we develop a social-aware nobile edge computing and caching mechanism by exploiting the relation between vehicles and roadside units. By leveraging a deep reinforcement learning approach, we propose optimal content processing and caching schemes that maximize the dispatch utility in an urban environment with diverse vehicular social characteristics. Numerical results based on real urban traffic datasets demonstrate the efficiency of our proposed schemes.

Signal Estimation in Underlay Cognitive Networks for Industrial Internet of Things [IEEE Transactions on Industrial Informatics - new TOC]

Underlay cognitive radio (CR) holds the promise to address spectrum scarcity and let industrial wireless sensor networks obtain spectrum extension from shared frequency band resources. However, underlay CR devices should be capable of properly adjusting wireless transmission parameters according to the sensing of wireless environments. To realize the goal, in this article, two different signal-to-noise ratio (SNR) estimation methods are proposed for time–frequency overlapped signal estimations in the underlay CR-based industrial Internet of Things (IoT). In the first method, normalized higher order cumulant equations and the theoretical value of normalized higher order cumulants are adopted to estimate the SNR of component signals and the SNR of received signals. In the second one, the power of each component signals and the received signals is estimated based on the second-order time-varying moments. For the performance analysis, the Cramer–Rao lower bound of the SNR estimation for the time–frequency overlapped signals is derived. Simulation results show that the proposed method based on normalized higher order cumulants not only can effectively estimate the SNR of the time–frequency overlapped signals, but also has the strong robustness to the spectrum overlapped rate and the hybrid power ratio. The proposed method with second-order time-varying moments is able to accurately estimate the SNR of the time–frequency overlapped signals effectively, especially in the low-SNR region. These features are extremely useful in the industrial IoT, which usually operate in low-SNR regimes.

A Dynamic Multipath Scheme for Protecting Source-Location Privacy Using Multiple Sinks in WSNs Intended for IIoT [IEEE Transactions on Industrial Informatics - new TOC]

Among several new technologies, such as social and cognitive mobile computing, wireless sensor networks (WSNs) constitute the founding pillar of the industrial Internet of Things. These networks are expected to play an increasingly important role in our daily lives. Social and cognitive mobile computing requires the sharing of data recorded by sensor nodes. However, the data can be vulnerable to attacks. It is of utmost importance to protect the users privacy while ensuring the security of the WSNs. This investigation is focused on the source-location privacy (SLP) of WSNs. This article proposes a dynamic multipath privacy-preserving routing (DMPPR) scheme based on multiple sinks for protecting the privacy. Different from single sink schemes, the technique of using multiple sink nodes to protect SLP is discussed in this article. Furthermore, a packet-slicing transmission scheme that generates a large number of dynamic routings based on multiple sink nodes is adopted for transmitting the packets. Local adversaries are considered, and to cope with these adversaries, a transmission loop, constructed using real and fake packets, is proposed to confuse the adversaries during the source detection process. The aim is to break the sociality between the sensor nodes. Simulations performed in MATLAB show that the proposed method outperforms similar existing schemes in terms of the secure time, adversary’s capture probability, and node utilization ratio. Moreover, the DMPPR scheme also reduces energy consumption by allowing more nodes in the nonhotspot areas to participate in the packet transmission process.

Towards High-Performance Wireless Control: <inline-formula><tex-math notation="LaTeX">$10^{-7}$</tex-math></inline-formula> Packet Error Rate in Real Factory Environments [IEEE Transactions on Industrial Informatics - new TOC]

To meet the extremely low latency constraints of industrial wireless control in critical applications, the wireless high-performance scheme (WirelessHP) has been introduced as a promising solution. The proposed design showed great improvements in terms of latency, but its performance in terms of reliability have not been fully tested yet. While traditional wireless systems achieve high reliability through packet retransmissions, this would impair the latency, and an approach based on channel coding is preferable in industrial applications. In this paper, a set of packet error rate (PER) tests is performed by applying concatenated Reed Solomon and convolutional codes to the WirelessHP physical layer, using a demonstrator based on a universal software radio peripheral platform. The effectiveness of channel coding to achieve $10^{-7}$ level PER without retransmissions is shown in typical laboratory and factory environments.

Tuesday, 28 April 2020

Saturday, 25 April 2020

09:49 AM

Preparing a High-Quality and Impactful Sport Science Manuscript [International Journal of Sports Physiology and Performance]

Journal Name: International Journal of Sports Physiology and Performance
Volume: 15
Issue: 5
Pages: 598-599

Reply to Lolli et al [International Journal of Sports Physiology and Performance]

Journal Name: International Journal of Sports Physiology and Performance
Volume: 15
Issue: 5
Pages: 601-602

Insights for Blood Flow Restriction and Hypoxia in Leg Versus Arm Submaximal Exercise [International Journal of Sports Physiology and Performance]

Journal Name: International Journal of Sports Physiology and Performance
Volume: 15
Issue: 5
Pages: 714-719

The Effect of Carbohydrate Mouth Rinsing on Multiple Choice Reaction Time During Amateur Boxing [International Journal of Sports Physiology and Performance]

Journal Name: International Journal of Sports Physiology and Performance
Volume: 15
Issue: 5
Pages: 720-723

Friday, 24 April 2020

02:01 AM

MISSILE: A System of Mobile Inertial Sensor-Based Sensitive Indoor Location Eavesdropping [IEEE Transactions on Information Forensics and Security - new TOC]

Privacy concerns on smartphones have been raised by the public as more and more personal data are now stored on them. In this paper, we show that location information can be compromised through mobile inertial sensors which are considered insensitive and accessible by any mobile application in both iOS and Android without special privilege. We present MISSILE, an automatic system that can infer users’ indoor location using labeled sensor data as prior knowledge. The key idea is that when a user reaches a particular indoor location, it is very likely that he/she has passed through some unique interior structures of a building, such as winding corridors, fire stop doors or elevators. These structures exhibit repeatable motion and environment patterns in mobile sensors that can be recognized by supervised learning. In our MISSILE system, the location labels of training data are automatically attained by Bluetooth beacons deployed in sensitive locations. With effective feature extraction procedure robust modeling, MISSILE shows good success rate for inference attack. For example, in a university campus with 15 sensitive locations, MISSILE achieves up to 73% correct prediction score whereas a random guess can only achieve 1/(15 + 1) = 6.25%. Further improvements on system performance and countermeasures are also discussed.

Tuesday, 14 April 2020

Monday, 13 April 2020

02:00 PM

Dietary Fuels in Athletic Performance [Annual Reviews: Annual Review of Nutrition: Table of Contents]

Annual Review of Nutrition, Volume 39, Issue 1, Page 45-73, August 2019.

Copper Transport and Disease: What Can We Learn from Organoids? [Annual Reviews: Annual Review of Nutrition: Table of Contents]

Annual Review of Nutrition, Volume 39, Issue 1, Page 75-94, August 2019.

Bile Acids as Metabolic Regulators and Nutrient Sensors [Annual Reviews: Annual Review of Nutrition: Table of Contents]

Annual Review of Nutrition, Volume 39, Issue 1, Page 175-200, August 2019.

Time-Restricted Eating to Prevent and Manage Chronic Metabolic Diseases [Annual Reviews: Annual Review of Nutrition: Table of Contents]

Annual Review of Nutrition, Volume 39, Issue 1, Page 291-315, August 2019.

The Economics of Taxes on Sugar-Sweetened Beverages: A Review of the Effects on Prices, Sales, Cross-Border Shopping, and Consumption [Annual Reviews: Annual Review of Nutrition: Table of Contents]

Annual Review of Nutrition, Volume 39, Issue 1, Page 317-338, August 2019.

Tuesday, 17 March 2020

03:00 PM

KonIQ-10k: An Ecologically Valid Database for Deep Learning of Blind Image Quality Assessment [IEEE Transactions on Image Processing - new TOC]

Deep learning methods for image quality assessment (IQA) are limited due to the small size of existing datasets. Extensive datasets require substantial resources both for generating publishable content and annotating it accurately. We present a systematic and scalable approach to creating KonIQ-10k, the largest IQA dataset to date, consisting of 10,073 quality scored images. It is the first in-the-wild database aiming for ecological validity, concerning the authenticity of distortions, the diversity of content, and quality-related indicators. Through the use of crowdsourcing, we obtained 1.2 million reliable quality ratings from 1,459 crowd workers, paving the way for more general IQA models. We propose a novel, deep learning model (KonCept512), to show an excellent generalization beyond the test set (0.921 SROCC), to the current state-of-the-art database LIVE-in-the-Wild (0.825 SROCC). The model derives its core performance from the InceptionResNet architecture, being trained at a higher resolution than previous models (512 × 384 ). Correlation analysis shows that KonCept512 performs similar to having 9 subjective scores for each test image.

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.

Diurnal Regulation of Renal Electrolyte Excretion: The Role of Paracrine Factors [Annual Reviews: Annual Review of Physiology: Table of Contents]

Annual Review of Physiology, Volume 82, Issue 1, Page 343-363, 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.

The Osteocyte: New Insights [Annual Reviews: Annual Review of Physiology: Table of Contents]

Annual Review of Physiology, Volume 82, Issue 1, Page 485-506, February 2020.

Monday, 03 February 2020

03:00 PM

REMIND: Risk Estimation Mechanism for Images in Network Distribution [IEEE Transactions on Information Forensics and Security - new TOC]

People constantly share their photographs with others through various social media sites. With the aid of the privacy settings provided by social media sites, image owners can designate scope of sharing, e.g., close friends and acquaintances. However, even if the owner of a photograph carefully sets the privacy setting to exclude a given individual who is not supposed to see the photograph, the photograph may still eventually reach a wider audience, including those clearly undesired through unanticipated channels of disclosure, causing a privacy breach. Moreover, it is often the case that a given image involves multiple stakeholders who are also depicted in the photograph. Due to various personalities, it is even more challenging to reach agreement on the privacy settings for these multi-owner photographs. In this paper, we propose a privacy risk reminder system, called REMIND, which estimates the probability that a shared photograph may be seen by unwanted people-through the social graph-who are not included in the original sharing list. We tackle this problem from a novel angle by digging into the big data regarding image sharing history. Specifically, the social media providers possess a huge amount of image sharing information (e.g., what photographs are shared with whom) of their users. By analyzing and modeling such rich information, we build a sophisticated probability model that efficiently aggregates the image disclosure probabilities along different possible image propagation chains and loops. If the computed disclosure probability indicates high risks of privacy breach, a reminder is issued to the image owner to help revise the privacy settings (or, at least, inform the user about this accidental disclosure risk). The proposed REMIND system also has a nice feature of policy harmonization that helps resolve privacy differences in multi-owner photographs. We have carried out a user study to validate the rationale of our proposed solutions and also conducte- experimental studies to evaluate the efficiency of the proposed REMIND system.

Electromagnetic Side Channel Information Leakage Created by Execution of Series of Instructions in a Computer Processor [IEEE Transactions on Information Forensics and Security - new TOC]

The side-channel leakage is a consequence of program execution in a computer processor, and understanding relationship between code execution and information leakage is a necessary step in estimating information leakage and its capacity limits. This paper proposes a methodology to relate program execution to electromagnetic side-channel emanations and estimates side-channel information capacity created by execution of series of instructions (e.g., a function, a procedure, or a program) in a processor. To model dependence among program instructions in a code, we propose to use Markov source model, which includes the dependencies among sequence of instructions as well as dependencies among instructions as they pass through a pipeline of the processor. The emitted electromagnetic (EM) signals during instruction executions are natural choice for the inputs into the model. To obtain the channel inputs for the proposed model, we derive a mathematical relationship between the emanated instruction signal power (ESP) and total emanated signal power while running a program. Then, we derive the leakage capacity of EM side channels created by execution of series of instructions in a processor. Finally, we provide experimental results to demonstrate that leakages could be severe and that a dedicated attacker could obtain important information.

Information Theoretical Analysis of Unfair Rating Attacks Under Subjectivity [IEEE Transactions on Information Forensics and Security - new TOC]

Ratings provided by advisors can help an advisee to make decisions, e.g., which seller to select in e-commerce. Unfair rating attacks-where dishonest ratings are provided to mislead the advisee-impact the accuracy of decision making. Current literature focuses on specific classes of unfair rating attacks, which does not provide a complete picture of the attacks. We provide the first formal study that addresses all attack behavior that is possible within a given system. We propose a probabilistic modeling of rating behavior, and apply information theory to quantitatively measure the impact of attacks. In particular, we can identify the attack with the worst impact. In the simple case, honest advisors report the truth straightforwardly, and attackers rate strategically. In real systems, the truth (or an advisor's view on it) may be subjective, making even honest ratings inaccurate. Although there exist methods to deal with subjective ratings, whether subjectivity influences the effect of unfair rating attacks was an open question. We discover that subjectivity decreases the robustness against attacks.

Automatically Dismantling Online Dating Fraud [IEEE Transactions on Information Forensics and Security - new TOC]

Online romance scams are a prevalent form of mass-marketing fraud in the West, and yet few studies have presented data-driven responses to this problem. In this type of scam, fraudsters craft fake profiles and manually interact with their victims. Because of the characteristics of this type of fraud and how dating sites operate, traditional detection methods (e.g., those used in spam filtering) are ineffective. In this paper, we investigate the archetype of online dating profiles used in this form of fraud, including their use of demographics, profile descriptions, and images, shedding light on both the strategies deployed by scammers to appeal to victims and the traits of victims themselves. Furthermore, in response to the severe financial and psychological harm caused by dating fraud, we develop a system to detect romance scammers on online dating platforms. This paper presents the first fully described system for automatically detecting this fraud. Our aim is to provide an early detection system to stop romance scammers as they create fraudulent profiles or before they engage with potential victims. Previous research has indicated that the victims of romance scams score highly on scales for idealized romantic beliefs. We combine a range of structured, unstructured, and deep-learned features that capture these beliefs in order to build a detection system. Our ensemble machine-learning approach is robust to the omission of profile details and performs at high accuracy (97%) in a hold-out validation set. The system enables development of automated tools for dating site providers and individual users.

Reverse Attention-Based Residual Network for Salient Object Detection [IEEE Transactions on Image Processing - new TOC]

Benefiting from the quick development of deep convolutional neural networks, especially fully convolutional neural networks (FCNs), remarkable progresses have been achieved on salient object detection recently. Nevertheless, these FCNs based methods are still challenging to generate high resolution saliency maps, and also not applicable for subsequent applications due to their heavy model weights. In this paper, we propose a compact and efficient deep network with high accuracy for salient object detection. Firstly, we propose two strategies for initial prediction, one is a new designed multi-scale context module, the other is incorporating hand-crafted saliency priors. Secondly, we employ residual learning to refine it progressively by only learning the residual in each side-output, which can be achieved with few convolutional parameters, therefore leads to high compactness and high efficiency. Finally, we further design a novel top-down reverse attention block to guide the above side-output residual learning. Specifically, the current predicted salient regions are used to erase its side-output feature, thus the missing object parts and details can be efficiently learned from these unerased regions, which results in more complete detection and high accuracy. Extensive experimental results on seven benchmark datasets demonstrate that the proposed network performs favorably against the state-of-the-art approaches, and shows advantages in simplicity, compactness and efficiency.

Wednesday, 29 January 2020

03:00 PM

Robust Seismic Image Interpolation With Mathematical Morphological Constraint [IEEE Transactions on Image Processing - new TOC]

Seismic image interpolation is a currently popular research subject in modern reflection seismology. The interpolation problem is generally treated as a process of inversion. Under the compressed sensing framework, various sparse transformations and low-rank constraints based methods have great performances in recovering irregularly missing traces. However, in the case of regularly missing traces, their applications are limited because of the strong spatial aliasing energies. In addition, the erratic noise always poses a serious impact on the interpolation results obtained by the sparse transformations and low-rank constraints-based methods,. This is because the erratic noise is far from satisfying the statistical assumption behind these methods. In this study, we propose a mathematical morphology-based interpolation technique, which constrains the morphological scale of the model in the inversion process. The inversion problem is solved by the shaping regularization approach. The mathematical morphological constraint (MMC)-based interpolation technique has a satisfactory robustness to the spatial aliasing and erratic energies. We provide a detailed algorithmic framework and discuss the extension from 2D to higher dimensional version and the back operator in the shaping inversion. A group of numerical examples demonstrates the successful performance of the proposed technique.

50 FPS Object-Level Saliency Detection via Maximally Stable Region [IEEE Transactions on Image Processing - new TOC]

The human visual system tends to consider saliency of an object as a whole. Some object-level saliency detection methods have been proposed by leveraging object proposals in bounding boxes, and regarding the entire bounding box as one candidate salient region. However, the bounding boxes can not provide exact object position and a lot of pixels in bounding boxes belong to the background. Consequently, background pixels in bounding box also show high saliency. Besides, acquiring object proposals needs high time cost. In order to compute object-level saliency, we consider region growing from some seed superpixels, to find one surrounding region which probably represents the whole object. The desired surrounding region has similar appearance inside and obvious difference with the outside, which is proposed as maximally stable region (MSR) in this paper. In addition, one effective seed superpixel selection strategy is presented to improve speed. MSR based saliency detection is more robust than pixel or superpixel level methods and object proposal based methods. The proposed method significantly outperforms the state-of-the-art unsupervised methods at 50 FPS. Compared with deep learning based methods, we show worse performance, but with about 1200-1600 times faster, which means better trade-off between performance and speed.

LCSCNet: Linear Compressing-Based Skip-Connecting Network for Image Super-Resolution [IEEE Transactions on Image Processing - new TOC]

In this paper, we develop a concise but efficient network architecture called linear compressing based skip-connecting network (LCSCNet) for image super-resolution. Compared with two representative network architectures with skip connections, ResNet and DenseNet, a linear compressing layer is designed in LCSCNet for skip connection, which connects former feature maps and distinguishes them from newly-explored feature maps. In this way, the proposed LCSCNet enjoys the merits of the distinguish feature treatment of DenseNet and the parameter-economic form of ResNet. Moreover, to better exploit hierarchical information from both low and high levels of various receptive fields in deep models, inspired by gate units in LSTM, we also propose an adaptive element-wise fusion strategy with multi-supervised training. Experimental results in comparison with state-of-the-art algorithms validate the effectiveness of LCSCNet.

Monday, 04 November 2019

03:50 PM

The PedBE clock accurately estimates DNA methylation age in pediatric buccal cells [Medical Sciences] [Early Edition]

The development of biological markers of aging has primarily focused on adult samples. Epigenetic clocks are a promising tool for measuring biological age that show impressive accuracy across most tissues and age ranges. In adults, deviations from the DNA methylation (DNAm) age prediction are correlated with several age-related phenotypes, such...

Monday, 26 August 2019

02:00 PM

Transitional Dynamics in Aggregate Models of Innovative Investment [Annual Reviews: Annual Review of Economics: Table of Contents]

Annual Review of Economics, Volume 11, Issue 1, Page 273-301, August 2019.

Echo Chambers and Their Effects on Economic and Political Outcomes [Annual Reviews: Annual Review of Economics: Table of Contents]

Annual Review of Economics, Volume 11, Issue 1, Page 303-328, August 2019.

Auction Market Design: Recent Innovations [Annual Reviews: Annual Review of Economics: Table of Contents]

Annual Review of Economics, Volume 11, Issue 1, Page 383-405, August 2019.

History, Microdata, and Endogenous Growth [Annual Reviews: Annual Review of Economics: Table of Contents]

Annual Review of Economics, Volume 11, Issue 1, Page 615-633, August 2019.

Has Dynamic Programming Improved Decision Making? [Annual Reviews: Annual Review of Economics: Table of Contents]

Annual Review of Economics, Volume 11, Issue 1, Page 833-858, August 2019.

Thursday, 08 August 2019

02:00 PM

Aging Populations, Mortality, and Life Expectancy [Annual Reviews: Annual Review of Sociology: Table of Contents]

Annual Review of Sociology, Volume 45, Issue 1, Page 69-89, July 2019.

Moral Cultures, Reputation Work, and the Politics of Scandal [Annual Reviews: Annual Review of Sociology: Table of Contents]

Annual Review of Sociology, Volume 45, Issue 1, Page 247-264, July 2019.

Divergent Destinies: Children of Immigrants Growing Up in the United States [Annual Reviews: Annual Review of Sociology: Table of Contents]

Annual Review of Sociology, Volume 45, Issue 1, Page 383-399, July 2019.

Examining Public Opinion About LGBTQ-Related Issues in the United States and Across Multiple Nations [Annual Reviews: Annual Review of Sociology: Table of Contents]

Annual Review of Sociology, Volume 45, Issue 1, Page 401-423, July 2019.

Family Instability in the Lives of American Children [Annual Reviews: Annual Review of Sociology: Table of Contents]

Annual Review of Sociology, Volume 45, Issue 1, Page 493-513, July 2019.

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