Showing papers by "University of Memphis published in 2021"

Patients with COVID-19: in the dark-NETs of neutrophils.

Abstract: SARS-CoV-2 infection poses a major threat to the lungs and multiple other organs, occasionally causing death. Until effective vaccines are developed to curb the pandemic, it is paramount to define the mechanisms and develop protective therapies to prevent organ dysfunction in patients with COVID-19. Individuals that develop severe manifestations have signs of dysregulated innate and adaptive immune responses. Emerging evidence implicates neutrophils and the disbalance between neutrophil extracellular trap (NET) formation and degradation plays a central role in the pathophysiology of inflammation, coagulopathy, organ damage, and immunothrombosis that characterize severe cases of COVID-19. Here, we discuss the evidence supporting a role for NETs in COVID-19 manifestations and present putative mechanisms, by which NETs promote tissue injury and immunothrombosis. We present therapeutic strategies, which have been successful in the treatment of immunο-inflammatory disorders and which target dysregulated NET formation or degradation, as potential approaches that may benefit patients with severe COVID-19.

Genomic and phenotypic insights from an atlas of genetic effects on DNA methylation

Abstract: Characterizing genetic influences on DNA methylation (DNAm) provides an opportunity to understand mechanisms underpinning gene regulation and disease. In the present study, we describe results of DNAm quantitative trait locus (mQTL) analyses on 32,851 participants, identifying genetic variants associated with DNAm at 420,509 DNAm sites in blood. We present a database of >270,000 independent mQTLs, of which 8.5% comprise long-range (trans) associations. Identified mQTL associations explain 15-17% of the additive genetic variance of DNAm. We show that the genetic architecture of DNAm levels is highly polygenic. Using shared genetic control between distal DNAm sites, we constructed networks, identifying 405 discrete genomic communities enriched for genomic annotations and complex traits. Shared genetic variants are associated with both DNAm levels and complex diseases, but only in a minority of cases do these associations reflect causal relationships from DNAm to trait or vice versa, indicating a more complex genotype-phenotype map than previously anticipated.

A systematic global stocktake of evidence on human adaptation to climate change

Abstract: Assessing global progress on human adaptation to climate change is an urgent priority. Although the literature on adaptation to climate change is rapidly expanding, little is known about the actual extent of implementation. We systematically screened >48,000 articles using machine learning methods and a global network of 126 researchers. Our synthesis of the resulting 1,682 articles presents a systematic and comprehensive global stocktake of implemented human adaptation to climate change. Documented adaptations were largely fragmented, local and incremental, with limited evidence of transformational adaptation and negligible evidence of risk reduction outcomes. We identify eight priorities for global adaptation research: assess the effectiveness of adaptation responses, enhance the understanding of limits to adaptation, enable individuals and civil society to adapt, include missing places, scholars and scholarship, understand private sector responses, improve methods for synthesizing different forms of evidence, assess the adaptation at different temperature thresholds, and improve the inclusion of timescale and the dynamics of responses. Determining progress in adaptation to climate change is challenging, yet critical as climate change impacts increase. A stocktake of the scientific literature on implemented adaptation now shows that adaptation is mostly fragmented and incremental, with evidence lacking for its impact on reducing risk.

Privacy-Preserving Task Recommendation Services for Crowdsourcing

Abstract: Crowdsourcing is a distributed computing paradigm that utilizes human intelligence or resources from a crowd of workers. Existing solutions of task recommendation in crowdsourcing may leak private and sensitive information about both tasks and workers. To protect privacy, information about tasks and workers should be encrypted before being outsourced to the crowdsourcing platform, which makes the task recommendation a challenging problem. In this paper, we propose a privacy-preserving task recommendation scheme (PPTR) for crowdsourcing, which achieves the task-worker matching while preserving both task privacy and worker privacy. In PPTR, we first exploit the polynomial function to express multiple keywords of task requirements and worker interests. Then, we design a key derivation method based on matrix decomposition, to realize the multi-keyword matching between multiple requesters and multiple workers. Through PPTR, user accountability and user revocation are achieved effectively and efficiently. Extensive privacy analysis and performance evaluation show that PPTR is secure and efficient.

Vehicle Trajectory Prediction Using LSTMs with Spatial-Temporal Attention Mechanisms

Abstract: Accurate vehicle trajectory prediction can benefit a variety of Intelligent Transportation System applications ranging from traffic simulation to driver assistance. The need of this ability is pronounced with the emergence of autonomous vehicles, as they require the prediction of nearby vehicles’ trajectories in order to navigate safely and efficiently. Recent studies based on deep learning have greatly improved the prediction accuracy. However, one prominent issue of these models is the lack of model explainability. We alleviate this issue by proposing STA-LSTM, an LSTM model with spatial-temporal attention mechanisms for explainability in vehicle trajectory prediction. STA-LSTM not only achieves comparable prediction performance against other state-of-the-art models, but more importantly, explains the influence of historical trajectories and neighboring vehicles on the target vehicle. We provide in-depth analyses of the learned spatial-temporal attention weights in various highway scenarios based on different vehicle and environment factors, including target vehicle class, target vehicle location, and traffic density. A demonstration showing that STA-LSTM can capture and explain fine-grained lane-changing behaviors is also provided. The data and implementation of STA-LSTM can be found at https://github.com/leilin-research/VTP.

HVDC Circuit Breakers: A Comprehensive Review

Abstract: High voltage direct current (HVDC) systems are now well integrated into AC systems in many jurisdictions. The integration of renewable energy sources (RESs) is a major focus and the role of HVDC systems is expanding. However, the protection of HVDC systems against DC faults is a challenging issue that can have negative impacts on the reliable and safe operation of power systems. Practical solutions to protect HVDC grids against DC faults without a widespread power outage include: 1) using DC circuit breakers (CBs) to isolate the faulty DC-link, 2) using a proper converter topology to interrupt the DC fault current, and/or 3) using high-power DC transformers and DC hubs at strategic points within DC grids. The application of HVDC CBs is identified as the best approach that satisfies both DC grids and connected AC grids’ requirements. This article reports a comprehensive review of HVDC CBs technologies, including recent significant attempts in the development of modern HVDC CBs. The functional analysis of each technology is presented. Additionally, different technologies based on information obtained from literature are compared. Finally, recommendations for the improvement of CBs are presented.

PROTECT: Efficient Password-Based Threshold Single-Sign-On Authentication for Mobile Users against Perpetual Leakage

Abstract: Password-based single-sign-on authentication has been widely applied in mobile environments. It enables an identity server to issue authentication tokens to mobile users holding correct passwords. With an authentication token, one can request mobile services from related service providers without multiple registrations. However, if an adversary compromises the identity server, he can retrieve users’ passwords by performing dictionary guessing attacks (DGA) and can overissue authentication tokens to break the security. In this paper, we propose a password-based threshold single-sign-on authentication scheme dubbed PROTECT that thwarts adversaries who can compromise identity server(s), where multiple identity servers are introduced to authenticate mobile users and issue authentication tokens in a threshold way. PROTECT supports key renewal that periodically updates the secret on each identity server to resist perpetual leakage of the secret. Furthermore, PROTECT is secure against off-line DGA: a credential used to authenticate a user is computed from the password and a server-side key. PROTECT is also resistant to online DGA and password testing attacks in an efficient way. We conduct a comprehensive performance evaluation of PROTECT, which demonstrates the high efficiency on the user side in terms of computation and communication and proves that it can be easily deployed on mobile devices.

Role of HSP90 in Cancer.

Abstract: HSP90 is a vital chaperone protein conserved across all organisms. As a chaperone protein, it correctly folds client proteins. Structurally, this protein is a dimer with monomer subunits that consist of three main conserved domains known as the N-terminal domain, middle domain, and the C-terminal domain. Multiple isoforms of HSP90 exist, and these isoforms share high homology. These isoforms are present both within the cell and outside the cell. Isoforms HSP90α and HSP90β are present in the cytoplasm; TRAP1 is present in the mitochondria; and GRP94 is present in the endoplasmic reticulum and is likely secreted due to post-translational modifications (PTM). HSP90 is also secreted into an extracellular environment via an exosome pathway that differs from the classic secretion pathway. Various co-chaperones are necessary for HSP90 to function. Elevated levels of HSP90 have been observed in patients with cancer. Despite this observation, the possible role of HSP90 in cancer was overlooked because the chaperone was also present in extreme amounts in normal cells and was vital to normal cell function, as observed when the drastic adverse effects resulting from gene knockout inhibited the production of this protein. Differences between normal HSP90 and HSP90 of the tumor phenotype have been better understood and have aided in making the chaperone protein a target for cancer drugs. One difference is in the conformation: HSP90 of the tumor phenotype is more susceptible to inhibitors. Since overexpression of HSP90 is a factor in tumorigenesis, HSP90 inhibitors have been studied to combat the adverse effects of HSP90 overexpression. Monotherapies using HSP90 inhibitors have shown some success; however, combination therapies have shown better results and are thus being studied for a more effective cancer treatment.

Anonymous and Privacy-Preserving Federated Learning With Industrial Big Data

Abstract: Many artificial intelligence technologies have been applied for extracting useful information from massive industrial big data. However, the privacy issues are usually overlooked in many existing methods. In this article, we propose an anonymous and privacy-preserving federated learning scheme for the mining of industrial big data. We explored the effect of the proportion of shared parameters on the accuracy through experiments, and found that sharing partial parameters can almost achieve the accuracy of sharing all the parameters. On this basis, our proposed federated learning scheme reduces the privacy leakage by sharing fewer parameters between the server and each participant. Specifically, we leverage differential privacy on shared parameters with Gaussian mechanism to provide strict privacy preservation; the effect of different $\varepsilon$ and $\delta$ on accuracy is tested; and we keep track of $\delta$ —when it reaches a certain threshold, training shall be stopped. What's more, we employ a proxy server as the middle layer between the server and all the participants to achieve anonymity of participants; it is worth noting that this can also reduce the communication burden on the federated learning server. Finally, we provide the security analysis and performance evaluations by comparing with other schemes.

Robust Control Strategies for Microgrids: A Review

Abstract: Microgrids consisting of photovoltaic (PV) power plants and wind farms have been widely accepted in power systems for reliability enhancement and power loss reduction. Microgrids are capable of providing voltage and frequency support, improving power quality, and achieving proper power-sharing. To achieve such goals and deal with the nonlinear behavior in such systems, appropriate robust control strategies are required to be adopted. This article presents a comprehensive review of robust control methods for microgrids, including AC, DC, and hybrid microgrids, with different topologies and different types of interconnection to conventional power systems based on recently published research studies. The main control objectives, along with proposed control methods, are comparatively discussed for different types of microgrids. Furthermore, several research gaps in this area related to the scalability, robustness assessment, and evaluation approach are discussed. Recommendations are made that can potentially open new research lines to enhance the effectiveness of robust controllers for AC, DC, and hybrid microgrids.

Recent advances of polymer-based piezoelectric composites for biomedical applications.

Abstract: Over the past decades, electronics have become central to many aspects of biomedicine and wearable device technologies as a promising personalized healthcare platform. Lead-free piezoelectric materials for converting mechanical into electrical energy through piezoelectric transduction are of significant value in a diverse range of technological applications. Organic piezoelectric biomaterials have attracted widespread attention as the functional materials in the biomedical devices due to their advantages of excellent biocompatibility. They include synthetic and biological polymers. Many biopolymers have been discovered to possess piezoelectricity in an appreciable amount, however their investigation is still preliminary. Due to their piezoelectric properties, better known synthetic fluorinated polymers have been intensively investigated and applied in biomedical applications including controlled drug delivery systems, tissue engineering, microfluidic and artificial muscle actuators, among others. Piezoelectric polymers, especially poly (vinylidene fluoride) (PVDF) and its copolymers are increasingly receiving interest as smart biomaterials due to their ability to convert physiological movements to electrical signals when in a controllable and reproducible manner. Despite possessing the greatest piezoelectric coefficients among all piezoelectric polymers, it is often desirable to increase the electrical outputs. The most promising routes toward significant improvements in the piezoelectric response and energy-harvesting performance of such materials is loading them with various inorganic nanofillers and/or applying some modification during the fabrication process. This paper offers a comprehensive review of the principles, properties, and applications of organic piezoelectric biomaterials (polymers and polymer/ceramic composites) with special attention on PVDF-based polymers and their composites in sensors, drug delivery and tissue engineering. Subsequently focuses on the most common fabrication routes to produce piezoelectric scaffolds, tissue and sensors which is electrospinning process. Promising upcoming strategies and new piezoelectric materials and fabrication techniques for these applications are presented to enable a future integration among these applications.

ADHD-Related Neurodiversity and the Entrepreneurial Mindset:

Abstract: To better understand how neurodiversity (i.e., neurobiological/brain-related differences) is related to entrepreneurial cognition, this study draws on prior research from entrepreneurship and neuro...

Proxy-Free Privacy-Preserving Task Matching with Efficient Revocation in Crowdsourcing

Abstract: Task matching in crowdsourcing has been extensively explored with the increasing popularity of crowdsourcing. However, privacy of tasks and workers is usually ignored in most of exiting solutions. In this paper, we study the problem of privacy-preserving task matching for crowdsourcing with multiple requesters and multiple workers. Instead of utilizing proxy re-encryption, we propose a proxy-free task matching scheme for multi-requester/multi-worker crowdsourcing, which achieves task-worker matching over encrypted data with scalability and non-interaction. We further design two different mechanisms for worker revocation including Server-Local Revocation (SLR) and Global Revocation (GR), which realize efficient worker revocation with minimal overhead on the whole system. The proposed scheme is provably secure in the random oracle model under the Decisional $q$ q -Combined Bilinear Diffie-Hellman ( $q$ q -DCDBH) assumption. Comprehensive theoretical analysis and detailed simulation results show that the proposed scheme outperforms the state-of-the-art work.

Resilience Following Child Maltreatment: Definitional Considerations and Developmental Variations:

Abstract: Resilience following childhood maltreatment has received substantial empirical attention, with the number of studies on this construct growing exponentially in the past decade. While there is ample interest, inconsistencies remain about how to conceptualize and assess resilience. Further, there is a lack of consensus on how developmental stage influences resilience and how protective factors affect its expression. The current systematic review uses a developmental lens to synthesize findings on resilience following child maltreatment. Specifically, this article consolidates the body of empirical literature in a developmentally oriented review, with the intention of inclusively assessing three key areas-the conceptualization of resilience, assessment of resilience, and factors associated with resilience in maltreatment research. A total of 67 peer-reviewed, quantitative empirical articles that examined child maltreatment and resilience were included in this review. Results indicate that some inconsistencies in the literature may be addressed by utilizing a developmental lens and considering the individual's life stage when selecting a definition of resilience and associated measurement tool. The findings also support developmental variations in factors associated with resilience, with different individual, relational, and community protective factors emerging based on life stage. Implications for practice, policy, and research are incorporated throughout this review.

Circumstances of the death and associated risk factors for severity and impairment of COVID-19 grief.

Abstract: This study examined the relationship between reactions of the bereaved to conditions of the pandemic and severity of their grief and levels of impairment. A total of 831 American adults who lost a loved one to COVID-19 responded to validated measures of dysfunctional grief and functional impairment, as well as items assessing unique complications associated with the pandemic (e.g. resentment toward doctors, social isolation). In combination, circumstantial risk factors accounted for 59% of the variance in social impairment and fully 71% of the variance in pandemic grief, leading to the development of an inventory of Pandemic Grief Risk Factors (PGRF), which displayed a unified factor structure, high reliability and strong convergent validity. Implications for psychological screening and intervention for those bereaved by COVID-19 are briefly noted.

Particle Swarm Optimization Variants for Solving Geotechnical Problems: Review and Comparative Analysis

Abstract: Optimization techniques have drawn much attention for solving geotechnical engineering problems in recent years. Particle swarm optimization (PSO) is one of the most widely used population-based optimizers with a wide range of applications. In this paper, we first provide a detailed review of applications of PSO on different geotechnical problems. Then, we present a comprehensive computational study using several variants of PSO to solve three specific geotechnical engineering benchmark problems: the retaining wall, shallow footing, and slope stability. Through the computational study, we aim to better understand the algorithm behavior, in particular on how to balance exploratory and exploitative mechanisms in these PSO variants. Experimental results show that, although there is no universal strategy to enhance the performance of PSO for all the problems tackled, accuracies for most of the PSO variants are significantly higher compared to the original PSO in a majority of cases.

Recognizing the cumulative burden of childhood adversities transforms science and practice for trauma and resilience.

Abstract: The Adverse Childhood Experiences (ACEs) studies transformed our understanding of the true burden of trauma. Notable elements of Felitti and colleagues' findings include the influence of adversity on many physical as well as psychological problems and the persistence of impacts decades after the traumas occurred. In this article, we make the case that the most revolutionary finding was the discovery of a strong dose-response effect, with marked increases in risk observed for individuals who reported four or more adversities. Over the past two decades, our understanding of the cumulative burden of trauma has expanded further, with recognition that experiences outside the family, including peer victimization, community violence, and racism, also contribute to trauma dose. Recent research has provided evidence for the pervasiveness of trauma, which we now realize affects most people, even by the end of adolescence. Extensive scientific evidence has documented that more than 40 biopsychosocial outcomes, including leading causes of adult morbidity and mortality, are associated with adverse childhood experiences, measured by dose. We summarize the state of science and explain how ACEs built a movement for uncovering mechanisms responsible for these relationships. Perhaps unexpectedly, the pervasiveness of trauma also expands our understanding of resilience, which is likewise more common than previously recognized. Emerging research on positive childhood experiences and poly-strengths suggests that individual, family, and community strengths may also contribute to outcomes in a dose-response relationship. We close with an agenda for research, intervention, and policy to reduce the societal burden of adversity and promote resilience. (PsycInfo Database Record (c) 2021 APA, all rights reserved).