bluuebunny/crossref_metadata_2025 huggingface dataset:
SW-SiStA2: A New-Generation Semi-Wearable Device for Sit-to-Stand Assistance
Authors: Afsar Md Rayhan , Ashiquzzaman Ashiq , Martelli Dario , Shen Xiangrong
Published: April 2023

Mobility impairment is a major problem that affects the quality of life of numerous older adults. With impaired mobility, such individuals usually have significant difficulty in standing up from a seated position, and thus often suffer from the lack of physical activities in their daily life. To address this problem, the authors present a new assistive device, namely, Semi-Wearable Sit-to-Stand Assist Generation-2 (SW-SiStA2), in this paper. Similar to the original (first generation) SW-SiStA, this novel semiwearable device can be easily attached to the user to provide sit-to-stand assistance, and can also be easily detached after reaching the standing posture to facilitate the subsequent ambulation. The new SW-SiStA2 is powered with a remote-release gas spring, which serves the dual purpose of actuation and energy storage (i.e.,, storing the energy accumulated during compression and powering the sit-to-stand assistance through extension). The remote release feature enables a user to easily control the SW-SiStA2 assistance through the locking and unlocking of the gas spring. The SW-SiStA2 was experimentally tested with human participants. Under the device's assistance, the participants were able to stand up much more easily, with significant reduction (up to 28% compared with the unassisted condition) of the muscle efforts in the process.
Complete Genome Sequence of a Canadian Strain of Escherichia coli with Multiple Metal and Antimicrobial Resistance Genes That Was Isolated from Municipal Biosolids
Authors: Kang Mingsong , Charron Philippe , Hoover Emily , Guan Jiewen , Firth Isaac , Naushad Sohail , Huang Hongsheng
Published: April 2023

This announcement reports the complete genome sequence of a non-Shiga toxin-producing
Escherichia coli
strain that was isolated from municipal biosolids collected from a Canadian wastewater treatment plant. This strain contains multiple metal, antimicrobial, and heat resistance genes, as determined by genome sequencing, and could be a useful bacterial model for future studies.
Draft Genome Sequences of Two Dothideomycetes Strains, NU30 and NU200, Derived from the Marine Environment around Sugashima, Japan
Authors: Kurita Gakuho , Goshima Gohta , Uesaka Kazuma
Published: April 2023

Several marine-derived black yeast species belonging to the class Dothideomycetes grow and divide in an unconventional manner, thereby attracting the interest of cell biologists. Here, we report the draft genome sequences of two black yeast strains, which comprised 25.5 Mb and 27.7 Mb and 172 and 65 contigs, respectively.
Draft Genome Sequences of 11 Rhodopsin Gene-Containing Actinobacteria (
Geodermatophilaceae
) from Saline Arid Habitats in the Central Asian Deserts
Authors: Tarlachkov Sergey V. , Starodumova Irina P. , Boueva Olga V. , Lysak Lyudmila V. , Subbotin Sergei A. , Evtushenko Lyudmila I.
Published: April 2023

Draft genome sequences of 11 strains of putative new species of
Geodermatophilaceae
were generated using Illumina technology. The genome sizes ranged from 4.19 to 4.99 Mb, with G+C contents of 73.5% to 74.6%, and contained genes for microbial rhodopsins. This study will contribute to our knowledge of the ecology and diversity of members of the family
Geodermatophilaceae
.
Principles for increasing equity in WASH research: understanding barriers faced by LMIC WASH researchers
Authors: Lue J'Anna-Mare , Bah Salamata , Grant Kaelah , Lee Justine , Nzekele Leila , Tidwell James B.
Published: April 2023

Introduction

There have long been critiques of colonial legacies influencing global health. With growing public awareness of unjust systems in recent years, a new wave of calls for antiracist and decolonisation initiatives has emerged within the sector. This study examined research inequities in the water, sanitation and hygiene (WASH) sector, centring the perspectives of researchers from low-income and middle-income countries (LMICs), to identify barriers faced by WASH researchers in order to support more equitable changes in this subsector of global health.

Methods

Nineteen semistructured interviews were conducted with researchers of different backgrounds regarding nationality, gender and research experience. Researchers from eight countries were asked about their experiences and direct observations of discrimination across various stages of the research process. Five interviews were conducted with key WASH research funders to assess perceptions of obstacles faced by LMIC researchers, successes achieved and challenges faced by these organisations when working towards more equitable research processes within the WASH sector.

Results

The results were analysed using an emergent framework that categorised experiences based on power differentials and abuse of power; structural barriers due to organisational policies; institutional and individual indifference; othering speech, action and practices; and context-specific discrimination. The social-ecological model was combined with this framework to identify the types of actors and the level of co-ordination needed to address these issues. Researchers who worked in both LMICs and high-income countries at different career stages were particularly aware of discrimination. Ensuring pro-equity authorship and funding practices were identified as two significant actions to catalyse change within the sector.

Conclusion

Sector-wide efforts must centre LMIC voices when identifying research questions, conducting research, and in dissemination. Individuals, organisations and the entire WASH sector must examine how they participate in upholding inequitable systems of power to begin to dismantle the system through the intentional yielding of power and resources.
Disease ecology of bats—the Canadian scene
Authors: Davy Christina M. , Willis Craig K.R.
Published: April 2023

Bats are hosts to a range of pathogens, which include zoonotic pathogens and pathogens of conservation concern. Brock Fenton’s research on bat ecology has always balanced clear communication of potential health risks associated with bats and the need to communicate these risks precisely to avoid unnecessary persecution of bats. Here, we integrate Brock’s work in the field of disease ecology with that of his students and collaborators and consider the potential advantages of studying disease ecology of bats within the Canadian context. The broad distribution of a few common species across the vast landscape of present-day Canada provides an opportunity to untangle the impacts of environmental variation on host–pathogen interactions and disease severity, particularly in the context of climate change. The varying migratory strategies and social structure of the bat species found in Canada could also facilitate informative interspecific studies to better understand how bat health is affected by interactions among rapid environmental changes, physiological traits, and the social behaviour of different species. We propose a series of priority research questions and approaches that could further our understanding of bat health and disease ecology in Canada, inspired by the work of Brock, his colleagues, and students.
Similarity revisited: shock random walks in the asymmetric simple exclusion process with open boundaries
Authors: Schütz G. M.
Published: April 2023

A reverse duality between the asymmetric simple exclusion process (ASEP) with open boundary conditions and a biased random walk of a single particle is proved for a special manifold of boundary parameters of the ASEP. The duality function is given by the configuration probabilities of a family of Bernoulli shock measures with a microscopic shock at site x of the lattice. The boundary conditions of the dual random walk, which can be reflecting or absorbing, depend on the choice of the duality function. As a consequence of this duality, the full time-dependent distribution of the open ASEP starting from a fixed shock measure at x is given for any time $$t>0$$

t
>
0

by a convex combination of shock measures with shock at position y. The coefficients are the transition probabilities P(x, t|y, 0) at time t of the random walk starting at site y. It is also shown that this family of shock measures arises from a similarity transformation of the two-dimensional representation of the matrix algebra for the stationary matrix product measure of the open ASEP. This implies a further duality between random walks with different boundary conditions.
IN QUEST FOR POLICY “SILVER BULLETS” TOWARDS TRIGGERING A V-SHAPED RECOVERY
Authors: BHADURY SOUMYA , GHOSH SAURABH , GOPALAKRISHNAN PAWAN
Published: April 2023

In view of the interaction between demand and supply shocks and the nature of the disparity in business cycles between Advanced Economies (AEs) and Emerging Market Economies (EMEs), we reinvigorate policy “silver bullets” that ascertain a sustainable growth revival in the aftermath of the COVID-19 shock. Using a novel business cycle dating algorithm, we identify up-cycle and down-cycle phases in India’s gross domestic product growth rate and use dynamic factor analysis using several high-frequency indicators for tracking private investment activity in India. On the demand side, our empirical results indicate that a boost to private investment can arrest a growth deceleration during a down-cycle, via consumption and output channels. We also observe that both the quantum and quality of public expenditure play an important role in arresting the growth deceleration. On the supply side, however, global supply chain disruptions could dampen the pace of investment during the post-COVID investment-led recovery. For both channels to work, credit offtake is necessary for a bank-dominated EME like India. Finally, despite low-capacity utilization rates, we draw several policy conclusions to jump-start economic activity levels.
EGUP-corrected thermodynamics of BTZ black hole
Authors: Hamil B. , Lütfüoğlu B. C. , Dahbi L.
Published: April 2023

Recently, thermodynamics has given an important aspect of black hole physics, and it is being used as a solemn tool in characterizing the physicality and viability of many black hole (BH) solutions. On the other hand, Heisenberg algebraic deformations, which predict a lower bound to position and/or momentum, are interrogated to have a theory of quantum gravity. In this paper, we consider a combined deformation of the generalized uncertainty and extended generalized uncertainty principles (EGUP) and investigate the EGUP-corrected thermal quantities of the rotating charged BTZ BH.
Family Ownership and Value of Takeover: Evidence from India
Authors: Dixit Jyoti , Singh Poonam
Published: April 2023

We examine how family-ownership influences takeover probability and takeover public announcement abnormal return of Indian publicly traded firms between 2003 and 2019. We find that family ownership has a significantly negative effect on target takeover probability at various levels of family ownership, viz. 20%, 40%, and 51%. Announcement period abnormal returns for target firms are positive at a lower level of family ownership of 20% and negative at a higher level of family ownership of 51%. These results are consistent with the agency cost explanation where family ownership reduces owner-manager agency conflict but exacerbates conflict between majority and minority shareholders. Our results hold for Heckman two-stage model.
Economic Policy Uncertainty, Short-Term Reversals, and Investor Sentiment
Authors: Chui Andy C. W.
Published: April 2023

This study finds that the predictability of economic policy uncertainty on short-term reversals is stronger among stocks exposed more to the volatility index (VIX) and economic policy uncertainty index (EPU). In addition, the predictability of VIX on short-term reversals is stronger among stocks exposed more to this index and the Aruoba–Diebold–Scotti business conditions index (ADS). Furthermore, the finding is robust after controlling for the other popular investor sentiment indexes, the Fama–French five risk factors, financial crises, and firm size.
Closed Form Expressions for Nonlinear Analysis of FG-GPLRC Beam Under Thermal Loading: Thermal Postbuckling and Nonlinear Bending
Authors: Haghani Ahmad , Kiani Yaser
Published: April 2023

Considering that the exact solution for thermal buckling and post-buckling of the graphene platelets (GPLs)-reinforced composite beam in exposure to temperature changes has not been so far addressed, this problem is investigated in this research. The governing equations of the beam under thermal buckling load were acquired using the principle of virtual work, first-order shear deformation theory, and von Kármán strain field. The effective properties of the materials were then determined using the Halpin–Tsai model and rule of mixtures. Three coupled nonlinear equations are established and solved directly. Results are obtained for beams with clamped and simply supported edges. After validating the results, the effects of changing the GPLs distribution pattern and weight fraction changes on the critical thermal buckling load were evaluated. It is highlighted that for beams with simply supported edges and asymmetric distribution of material properties, the response is not of the bifurcation type.
A FRAMEWORK FOR THE ANALYSIS OF COMORBID CONDITIONS USING INTELLIGENT EXTRACTION OF MULTIPLE FLUID BIOMARKERS
Authors: JADHAV PRIYANKA , SELVARAJU VINOTHINI , SATHIAN SARITH P , SWAMINATHAN RAMAKRISHNAN
Published: April 2023

Fluid biomarkers extracted from many types of body fluids provide significant information that serve as indicators of the underlying physiological and pathological conditions of the human body. Analysis of multiple fluid biomarkers could help improve the early identification and progression of comorbid conditions to enhance the diagnostic accuracy, which can help in developing patient-specific treatment plans. In this work, an attempt has been made to differentiate the co-occurrence of diabetes, hypertension and cardiovascular disease (comorbid conditions) from non-comorbid using multiple fluid biomarkers. Fluid biomarkers are obtained from a public dataset under comorbid ([Formula: see text]) and non-comorbid ([Formula: see text]) conditions. Five features, such as serum creatinine, serum sodium, platelet count, creatine phosphokinase and ejection fraction, are extracted for further analysis. Machine learning algorithms namely, [Formula: see text]-nearest neighbor and linear discriminant analysis (LDA) are used to classify comorbid and non-comorbid conditions. The results show an increase in platelet count in comorbid subjects. This feature also exhibits significant difference ([Formula: see text]) between both the conditions. This study also uses the random undersampling technique to reduce bias associated with data imbalance. LDA classifier yields a maximum accuracy of 54.30% in classifying these two conditions. Further study can be carried out to improve the accuracy and might be helpful in clinical practice for prediction of comorbid conditions.
Spatial dynamics of a reaction–diffusion SIS epidemic model with mass-action-type nonlinearity
Authors: Wang Renhu , Wang Xuezhong
Published: April 2023

This work is devoted to investigate the global asymptotic stability of equilibriums for a reaction–diffusion susceptible-infected-susceptible (SIS) epidemic model with spatial heterogeneity and mass-action-type nonlinearity. By discretizing the spatial variables of the model, first, Lyapunov functions are constructed for the corresponding ordinary differential equations (ODEs) model of the original SIS PDEs model, and then the construction method is generalized to the PDEs model in which either the susceptible or the infectious individuals are spreading in spatial heterogeneity environment. For both the cases, we obtained the standard threshold dynamics results.
Regularity and Green’s relations for semigroups of transformations preserving a zigzag order and an equivalence
Authors: Prinyasart Thanakorn , Srithus Ratana , Malangpoo Chaleamrach
Published: April 2023

Consider a finite ordered set [Formula: see text] whose order forms a zigzag. For an equivalence [Formula: see text] on [Formula: see text], let [Formula: see text] be the set of all order homomorphism preserving [Formula: see text]. In this paper, we completely describe the regularity of elements and Green’s relations for [Formula: see text] under a certain condition.
High Impact Research in Finance: Role of Bisociation and Creativity
Authors: John Kose , Xu Emma
Published: April 2023

High impact research in our fields of banking and finance, and more broadly that of economics, can take three main forms: (1) solving the major unsolved problems in the field, (2) posing major questions/ problems to be solved, and (3) providing a new framework/ approach to synthesize current and extant knowledge in the field. We analyze some recent research in different areas of banking and finance (institutions, risk, governance, bank capital/ regulation, innovation) with a view to distil the creative processes at work. We find that the common themes that emerge are consistent with the theory of bisociation proposed by Koestler in his seminal 1964 book, “The Act of Creation”. We also provide a simple combinatorial exercise in the process of creativity that can be used by the reader by adapting to the topics and areas of her research.
Circular Economy, Stock Volatility, and Resilience to the COVID-19 Shock: Evidence from European Companies
Authors: Zara Claudio , Bellardini Luca , Gobbi Margherita
Published: April 2023

Background: By decoupling economic growth from an intensive use of resources, preventing the impairment of natural capital, and enhancing resilience to system-wide shocks, the Circular Economy (CE) is a powerful opportunity to hedge against “linear” risk factors. In fact, it helps shielding against the risk of assets becoming stranded, can generate fresh and non-speculative demand for investments, and can improve investment results at both individual and portfolio levels. Problem: Therefore, equity investors into circular undertakings could benefit from (H1) reduced stock return volatility, as well as (H2) a greater ability to withstand exogenous negative events. Approach: For testing these hypotheses, we constructed a sample of 644 listed companies across EU-15 countries, plus Switzerland, and 17 different industries. We retrieved their market data in 2019–2020, as well as their accounting fundamentals in 2018–2019. By controlling for the latter, we investigated whether equity risk—either in total terms (i.e., the standard deviation of returns) or circumscribed to the systematic component thereof (i.e., the Beta against a European or global market index)—may be explained by a company’s degree of circularity, measured by the Circularity Score (CS). This is a novel indicator originally proposed by Zara and Ramkumar (2022), based on Refinitiv ESG data, the methodology whereof we significantly amended. As a core innovation, in weighting an entity’s performance on a CE framework, we assessed the latter’s “financial materiality” (i.e., relevance to the company’s business) at sub-industry level, applying the SASB Materiality Maps. Via OLS estimation, we tested our hypotheses (i) over the whole-time horizon, in a panel model; (ii) on specific timeframes, in a standard cross-sectional model. The latter was applied to either the entire 2020 or subperiods thereof: namely, with respect to the COVID-19 outbreak, we distinguished between a pre-shock, a shock and a post-shock phase. Our quest was refined to conduct a deeper investigation into the Oil & Gas industry, which is intrinsically the most exposed to linear risks and, also, did experience the widest volatility in 2020. Findings: Both H1 and H2 received widespread confirmation. The CS was found to exert a negative, significant and robust effect on all the three risk measures, over the whole timespan as well as in subperiods (particularly the post-shock phase). Also, amplifying effects were recorded on the Oil & Gas industry. Conclusions: Our results lend remarkable support to the idea that the CE is a powerful enabler of de-risking, also in case of a severe shock, with a view to mitigating the negative consequences and building back better. They call on firms and policymakers to foster the circular transition, thereby accelerating economic recovery in the aftermath of the pandemic crisis.
ABSOLUTE OR RELATIVE: THE DARK SIDE OF FUND RATING SYSTEMS
Authors: CARLUCCIO EMANUELE MARIA , CUCURACHI PAOLO ANTONIO , POMANTE UGO
Published: April 2023

Academic literature and market practitioners have always devoted great attention to the analysis of asset management products, with particular regard to fund classification and performance metrics. Less attention has been paid to rating methodologies and to the risk of attributing positive ratings to underperforming asset managers. The most widespread rating criterion is the ordinal one, which is based on the assumption that the best asset managers are those who have performed better than their competitors regardless of their ability to achieve a given threshold (i.e. a positive overperformance against the benchmark). Our study, after a description of the most common risk-adjusted performance measures, introduces the idea of attributing the rating on a cardinal basis, setting in advance a given threshold that should be achieved to receive a positive evaluation (i.e. a rating equal to or higher than 3 on a scale of 1–5). The empirical test conducted on a sample of funds (belonging to the main equity and bond asset classes) made it possible to quantify the effects of the cardinal approach on the attribution of the rating and on the probability of assigning a good rating to underperforming funds. Empirical analysis also highlighted how the cardinal method allows, on average, better performance than the ordinal one even in an out-of-sample framework. The differences between the two methodologies are particularly remarkable in efficient markets such as the North American equity market. The two rating assignment systems were also analyzed using contingency tables to test the ability to anticipate the default event (underperformance relative to the benchmark). The policy suggestion emerging from our study concerns the significant impact of the rating criterion in reducing the risk of recommending funds that, despite a good rating, have failed to perform satisfactorily and are unlikely to do so in the future either.
Low-rank Representation with Adaptive Dimensionality Reduction via Manifold Optimization for Clustering
Authors: Chen Haoran , Chen Xu , Tao Hongwei , Li Zuhe , Wang Xiao
Published: April 2023

The dimensionality reduction techniques are often used to reduce data dimensionality for computational efficiency or other purposes in existing low-rank representation (LRR)-based methods. However, the two steps of dimensionality reduction and learning low-rank representation coefficients are implemented in an independent way; thus, the adaptability of representation coefficients to the original data space may not be guaranteed. This article proposes a novel model, i.e., low-rank representation with adaptive dimensionality reduction (LRRARD) via manifold optimization for clustering, where dimensionality reduction and learning low-rank representation coefficients are integrated into a unified framework. This model introduces a low-dimensional projection matrix to find the projection that best fits the original data space. And the low-dimensional projection matrix and the low-rank representation coefficients interact with each other to simultaneously obtain the best projection matrix and representation coefficients. In addition, a manifold optimization method is employed to obtain the optimal projection matrix, which is an unconstrained optimization method in a constrained search space. The experimental results on several real datasets demonstrate the superiority of our proposed method.
Machine Learning Enabled Solutions for Design and Optimization Challenges in Networks-on-Chip based Multi/Many-Core Architectures
Authors: Reza Md Farhadur
Published: April 2023

Due to the advancement of transistor technology, a single chip processor can now have hundreds of cores.
Network-on-Chip (NoC)
has been the superior interconnect fabric for multi/many-core on-chip systems because of its scalability and parallelism. Due to the rise of dark silicon with the end of Dennard Scaling, it becomes essential to design energy efficient and high performance heterogeneous NoC-based multi/many-core architectures. Because of the large and complex design space, the solution space becomes difficult to explore within a reasonable time for optimal trade-offs of energy-performance-reliability. Furthermore, reactive resource management is not effective in preventing problems from happening in adaptive systems. Therefore, in this work, we explore machine learning techniques to design and configure the NoC resources based on the learning of the system and applications workloads. Machine learning can automatically learn from past experiences and guide the NoC intelligently to achieve its objective on performance, power, and reliability. We present the challenges of NoC design and resource management and propose a generalized machine learning framework to uncover near-optimal solutions quickly. We propose and implement a NoC design and optimization solution enabled by neural networks, using the generalized machine learning framework. Simulation results demonstrated that the proposed neural networks-based design and optimization solution improves performance by 15% and reduces energy consumption by 6% compared to an existing non-machine learning-based solution while the proposed solution improves NoC latency and throughput compared to two existing machine learning-based NoC optimization solutions. The challenges of machine learning technique adaptation in multi/many-core NoC have been presented to guide future research.
Modeling Regime Shifts in Multiple Time Series
Authors: Tajeuna Etienne Gael , Bouguessa Mohamed , Wang Shengrui
Published: April 2023

We investigate the problem of discovering and modeling regime shifts in an ecosystem comprising multiple time series known as co-evolving time series. Regime shifts refer to the changing behaviors exhibited by series at different time intervals. Learning these changing behaviors is a key step toward time series forecasting. While advances have been made, existing methods suffer from one or more of the following shortcomings: (1) failure to take relationships between time series into consideration for discovering regimes in multiple time series; (2) lack of an effective approach that models time-dependent behaviors exhibited by series; (3) difficulties in handling data discontinuities which may be informative. Most of the existing methods are unable to handle all of these three issues in a unified framework. This, therefore, motivates our effort to devise a principled approach for modeling interactions and time-dependency in co-evolving time series. Specifically, we model an ecosystem of multiple time series by summarizing the heavy ensemble of time series into a lighter and more meaningful structure called a
mapping grid
. By using the mapping grid, our model first learns time series behavioral dependencies through a dynamic network representation, then learns the regime transition mechanism via a full time-dependent Cox regression model. The originality of our approach lies in modeling interactions between time series in regime identification and in modeling time-dependent regime transition probabilities, usually assumed to be static in existing work.
Multi-view Graph Representation Learning Beyond Homophily
Authors: Lin Bei , Li You , Gui Ning , Xu Zhuopeng , Yu Zhiwu
Published: April 2023

Unsupervised graph representation learning (GRL) aims at distilling diverse graph information into task-agnostic embeddings without label supervision. Due to a lack of support from labels, recent representation learning methods usually adopt self-supervised learning, and embeddings are learned by solving a handcrafted auxiliary task (so-called pretext task). However, partially due to the irregular non-Euclidean data in graphs, the pretext tasks are generally designed under homophily assumptions and cornered in the low-frequency signals, which results in significant loss of other signals, especially high-frequency signals widespread in graphs with heterophily. Motivated by this limitation, we propose a multi-view perspective and the usage of diverse pretext tasks to capture different signals in graphs into embeddings. A novel framework, denoted as Multi-view Graph Encoder (MVGE), is proposed, and a set of key designs are identified. More specifically, a set of new pretext tasks are designed to encode different types of signals, and a straightforward operation is proposed to maintain both the commodity and personalization in both the attribute and the structural levels. Extensive experiments on synthetic and real-world network datasets show that the node representations learned with MVGE achieve significant performance improvements in three different downstream tasks, especially on graphs with heterophily.
Beginner's Guide to Micro- and Nanoscale Electrochemical Additive Manufacturing
Authors: Hengsteler Julian , Kanes Karuna Aurel , Khasanova Liaisan , Momotenko Dmitry
Published: April 2023

Electrochemical additive manufacturing is an advanced microfabrication technology capable of producing features of almost unlimited geometrical complexity. A unique combination of the capacity to process conductive materials, design freedom, and micro- to nanoscale resolution offered by these electrochemical techniques promises tremendous opportunities for a multitude of future applications spanning microelectronics, sensing, robotics, and energy storage. This review aims to equip readers with the basic principles of electrochemical 3D printing at the small length scale. By describing the basic principles of electrochemical additive manufacturing technology and using the recent advances in the field, this beginner's guide illustrates how controlling the fundamental phenomena that underpin the print process can be used to vary dimensions, morphology, and microstructure of printed structures.
Thiolase: A Versatile Biocatalyst Employing Coenzyme A–Thioester Chemistry for Making and Breaking C–C Bonds
Authors: Harijan Rajesh K. , Dalwani Subhadra , Kiema Tiila-Riikka , Venkatesan Rajaram , Wierenga Rik K.
Published: April 2023

Thiolases are CoA-dependent enzymes that catalyze the thiolytic cleavage of 3-ketoacyl-CoA, as well as its reverse reaction, which is the thioester-dependent Claisen condensation reaction. Thiolases are dimers or tetramers (dimers of dimers). All thiolases have two reactive cysteines: ( a) a nucleophilic cysteine, which forms a covalent intermediate, and ( b) an acid/base cysteine. The best characterized thiolase is the Zoogloea ramigera thiolase, which is a bacterial biosynthetic thiolase belonging to the CT-thiolase subfamily. The thiolase active site is also characterized by two oxyanion holes, two active site waters, and four catalytic loops with characteristic amino acid sequence fingerprints. Three thiolase subfamilies can be identified, each characterized by a unique sequence fingerprint for one of their catalytic loops, which causes unique active site properties. Recent insights concerning the thiolase reaction mechanism, as obtained from recent structural studies, as well as from classical and recent enzymological studies, are addressed, and open questions are discussed.
The emerging role of extracellular vesicles as communicators between adipose tissue and pathologic lungs with a special focus on asthma
Authors: Miethe Sarah , Potaczek Daniel P. , Bazan-Socha Stanislawa , Bachl Melanie , Schaefer Liliana , Wygrecka Malgorzata , Garn Holger
Published: April 2023

Extracellular vesicles (EVs) gain increasing attention due to their (patho-)physiological role in intercellular signaling, specifically in the communication between distant organs. Recent studies highlight a connection between the adipose tissue (AT) and the lung via (immuno-)modulatory EVs in disorders such as obesity-associated asthma and lung cancer-associated cachexia. Although lung cancer-derived EVs induce lipolysis and myotube atrophy in vivo, pathogenic effects were also reported in the opposite direction with the involvement of AT-derived EVs in cancer-promoting responses and potentially in asthma development. In contrast, the majority of studies on AT-derived EVs demonstrate their protective influence on the asthmatic lung. Beneficial effects, such as induction of anti-inflammatory pathways in vitro and in ovalbumin (OVA)-induced asthma mouse models, were particularly conveyed by EVs enriched from AT-derived mesenchymal stem/stromal cells (AT-MSCs), which therefore pose an interesting subject in possible future therapeutic applications. Likewise, AT-MSC-derived EVs exerted beneficial effects in several other pulmonary abnormalities, such as different types of lung injury or pathological changes related to chronic obstructive pulmonary disease. These contradictory findings highlight the need for extensive research to widen the understanding of the role of EVs in the development of diseases and interconnectivity between organs.
G protein-coupled receptors as targets for transformative neuropsychiatric therapeutics
Authors: Schmitz Gavin P. , Roth Bryan L.
Published: April 2023

G protein-coupled receptors (GPCRs) constitute the largest family of druggable genes in the human genome. Even though perhaps 30% of approved medications target GPCRs, they interact with only a small number of them. Here, we consider whether there might be new opportunities for transformative therapeutics for neuropsychiatric disorders by specifically targeting both known and understudied GPCRs. Using psychedelic drugs that target serotonin receptors as an example, we show how recent insights into the structure, function, signaling, and cell biology of these receptors have led to potentially novel therapeutics. We next focus on the possibility that nonpsychedelic 5-HT2A receptor agonists might prove to be safe and rapidly acting antidepressants. Finally, we examine understudied and orphan GPCRs using the MRGPR family of receptors as an example.
Analysis on Simplified Method of IoT-based HHL Algorithm Corresponding Quantum Circuit for Quantum Computer Application
Authors: Xu Jie , Qian Dingjun , Hu Gensheng
Published: April 2023

Whether it is a traditional industry or a Frontier field, it has unveiled the trend of industrial IoT construction and application, which plays a vital role in building a strong manufacturing country and promoting high-quality economic development in China. HHL algorithm has become one of the important quantum algorithms, but there are few researches on the construction of quantum circuits and the application of quantum sequencing. In this paper, a model based on the quantum circuit corresponding to the HHL algorithm to deal with the quantum application problem is proposed. A quantum circuit based on HHL algorithm is used to solve the linear system, and the numerical solution of the target partial differential equation is obtained. Finally, the experimental analysis shows that, in the process of processing quantum computer application problems based on quantum circuit, it can reduce the computation amount of quantum circuit corresponding to HHL algorithm, improve the simulation efficiency of quantum circuit, and reduce the occupation of hardware resources, which has a certain effectiveness and superiority. This discussion brings new ideas for intelligent IoT technology and provides implications for the study of simplified methods of HHL algorithms corresponding to quantum circuits to deal with computer application problems.
Approximate Relationship for the Bond-Slip Using a Concrete Damage-Plastic Model
Authors: Tabatabaei Mirhosseini Ramin , Araghizadeh Ehsan , Rashidi Soroush
Published: April 2023

This paper presents an approximate multicontact model to study dynamic bond stress-slip based on the concrete damage-plastic model. To establish the bond stress-slip between rebar and concrete, an elastic-plastic steel cylinder contact element was used as the tube (ring contact element), and then, by reducing the bond strength, the amount of slip between rebar and concrete and its effect on concrete damage-plastic parameters were considered. When concrete cracks, the parameters of concrete cracking, the plasticity of rebar and concrete fracture, and the pull-out of rebar from concrete are used to consider the bond-slip relationship between rebar and concrete. Meanwhile, an external constraint in the cylinder model is taken into account. The bond strength calculated by the presented model is compared with the pull-out test specimen results, and the errors are generally within 15%. Finally, using the results obtained from the amount of slip in models, an approximate mathematical relationship between the slip of the rebar inside the concrete can be obtained in terms of the resistance of the ring contact element (instead of the concrete surrounding). This formula can be used to calculate the bond-slip rate of all the rebars of a structure. The results of the mentioned model using the ABAQUS software demonstrated that by reducing the strength of the ring contact element by 20%, slip increased by 4.2%. Also, with an 80% reduction in ring strength, the bond-slip rate increases by 45%. The proposed approximate relationship has reasonable accuracy and lower computational cost.
Experimental Investigation on Incorporation of Zinc-Ferrite Nanocoated Baffles for Improving the Performance of Field Power Electrical Transformer Integrated with a Solar Air Heater
Authors: Kannan Nithiyananthan , Vasantha Gowri N. , Muralikrishna T. , Kumar Avinash , Mary Anjalin F. , Ramesh M. , Muthuraj B. , Birhanu Habtewolde Ababu
Published: April 2023

Solar energy is the most accessible, eco-friendly, and renewable energy source available to meet the world’s expanding energy needs. Solar collectors are commonly utilized to convert solar energy directly into heat for purposes ranging from house heating to timber seasoning and crop drying. The purpose of this research is to design a modified solar air heater (SAH) with a baffle plate and to examine the performance due to the provision of zinc-ferrite nanocoated baffles. The entire system is mounted over a transformer for effective cooling and also produces hot air for industrial requirements. A flat plate collector and a centrifugal blower were used in the experiment. Maximum output air temperatures of 55°C, 62°C, and 72°C were measured for collectors without baffles, baffled collectors, and inverted baffled collectors, respectively. It was also found that the thermal efficiency of flat plate collectors without baffles was 36%, with baffles, it was 44%, and with inverted baffles it was 54%. This study shows that inverted SAH with zinc-ferrite nanocoated baffle plates works better than SAH without baffle plates or with baffle plates in the normal position.
Mathematical Modeling of MHD Flow of CNTs/Ag Nanoparticles Past a Heated Stretchy Surface with Nonuniform Heat Sink/Source and Thermal Radiation Impacts
Authors: Gandhimathi T. , Eswaramoorthi S. , Loganathan K. , Mishra Nirmith Kumar
Published: April 2023

This research communication intends to evaluate the impact of time‐dependent MHD Darcy–Forchheimer flow of CNTs/Ag nanoparticles on a heated stretchy surface. Water is employed as a base fluid, and two types of CNTs such as single‐ and multiwall carbon nanotubes are considered. The significance of nonlinear radiation and heat sink/source is added to our analysis. To accommodate the suitable variables, the governing nonlinear partial differential models are transformed into a set of ordinary differential models. These resulting models are solved analytically and numerically by utilizing the homotopy analysis technique and the bvp4c procedure in MATLAB. The distinctive behavior of pertinent physical parameters on the dimensionless profiles are displayed and discussed through diagrams, tables, and charts. It is discovered that the velocity profile decrepitude whenever there is a change in the unsteady, porosity, and injection/suction parameters. The space and temperature‐dependent heat sink/source parameter cause to elevate the thermal profile. The Ag nanoparticles have a lesser surface shear stress compared to both CNTs. The heat transfer gradient develops for larger quantities of radiation and temperature ratio parameters. This research has significant applications in many industrial sectors, such as thermal exchangers, chemical reactors, microelectronics, biomedical engineering, aerodynamics, and industrial production processes.
Severe Obesity in Women Can Lead to Worse Memory Function and Iron Dyshomeostasis Compared to Lower Grade Obesity
Authors: Pino Jessica M. V. , Silva Vitória F. , Mônico-Neto Marcos , Seva Danielle C. , Kato Melissa Y. , Alves July N. , Pereira Gabriela C. , Antunes Hanna Karen M. , Galvao Thales D. , Bitterncourt Lia R. A. , Tufik Sergio , Zambrano Lysien I. , Dâmaso Ana R. , Oyama Lila M. , Thivel David , Campos Raquel M. S. , Lee Kil S.
Published: April 2023

Objective. Obesity is one of the modifiable risk factors for dementia. Insulin resistance, the abundance of advanced glycated end-products, and inflammation are some of the mechanisms associated with the lower cognitive performance observed in obesity. This study aims to evaluate the cognitive function of subjects with distinct degrees of obesity, comparing class I and II obesity (OBI/II) to class III obesity (OBIII), and to investigate metabolic markers that can distinguish OBIII from OBI/II. Study Design. This is a cross-sectional study, in which 45 females with BMI varying from 32.8 to 51.9 kg/m2 completed a set of 4 cognitive tests (verbal paired-associate test, stroop color, digit span, and Toulouse–Pieron cancellation test) and their plasma metabolites, enzymes, and hormones related to glycemia, dyslipidemia, and liver function, as well as the biomarkers of iron status, were concomitantly analyzed. Results. OBIII showed lower scores in the verbal paired-associate test compared to OBI/II. In other cognitive tests, both groups showed similar performance. OBIII presented a lower iron status compared to OBI/II based on total iron binding capacity, degree of transferrin saturation, hemoglobin, mean corpuscular volume, and mean corpuscular hemoglobin. The levels of indicators for glycemia, liver function, and lipid metabolism were similar in both groups. Analysis of plasma metabolites showed that OBIII had lower levels of pyroglutamic acid, myoinositol, and aspartic acid and higher levels of D-ribose than OBI/II. Conclusion. Iron is an essential micronutrient for several metabolic pathways. Thus, iron dyshomeostasis observed in severe obesity may aggravate the cognitive impairment by altering metabolic homeostasis and enhancing oxidative stress. These findings can contribute to searching for biomarkers that indicate cognitive performance in the population with obesity.
Effects of Herbs and Derived Natural Products on Lipopolysaccharide-Induced Toxicity: A Literature Review
Authors: Kianmehr Majid , Behdadfard Mohammad , Hedayati-Moghadam Mahdiyeh , Khazdair Mohammad Reza
Published: April 2023

Introduction. Oxidative stress (OS) during inflammation can increase inflammatory responses and damage tissue. Lipopolysaccharide (LPS) can induce oxidative stress and inflammation in several organs. Natural products have several biological activities including anti-inflammatory, antioxidant, and immunoregulatory properties. The aims of the study are to study the possible therapeutic effects of natural products on LPS inducing toxicity on the nervous system, lung, liver, and immune system. Methods. The in vitro and in vivo research articles that were published in the last 5 years were included in the current study. The keywords included “lipopolysaccharide,” “toxicity,” “natural products,” and “plant extract” were searched in different databases such as Scopus, PubMed, and Google Scholar until October 2021. Results. The results of most studies indicated that some medicinal herbs and their potent natural products can help to prevent, treat, and manage LPS-induced toxicity. Medicinal herbs and plant-derived natural products showed promising effects on managing and treating oxidative stress, inflammation, and immunomodulation by several mechanisms. Conclusion. However, these findings provide information about natural products for the prevention and treatment of LPS-induced toxicity, but the scientific validation of natural products requires more evidence on animal models to replace modern commercial medicine.
CBCT Evaluation of Quality and Quantity of Bones for Immediate Implant Treatment Planning in Central Incisor Area in relation to Arch Form
Authors: Hassan Nuhad A. , Al-radha Afya Sahib Diab
Published: April 2023

Understanding the quality of the ridge and facial cortical bone in the aesthetic zone is important for treatment with an immediate dental implant. This study aimed to analyze bone density and widths of the facial cortical bone and alveolar ridge at the central incisors in relation to arch form. A total of 400 teeth from 100 cone-beam CT images were divided equally between the upper and lower central incisors. The central incisor area was assessed for the width of the facial cortical and alveolar bones at three different points (3 mm, 6 mm, and 9 mm from the cementoenamel junction). Arch forms and densities of cortical and cancellous bones in the interradicular regions were evaluated. The difference in facial cortical bone thickness at 3 points was smaller for the upper teeth than for the lower teeth on both sides. The alveolar bone width was higher in the maxilla than the mandible with highly significant differences (

P
<
0.001

). The highest bone density was at the buccal aspect of the mandible (897.36 ± 136.72 HU), while the lowest density was at the cancellous bone of the maxilla (600.37 ± 126.63 HU). The dominant arch form was ovoid 71%, followed by square 20% and the tapering arch form 10%. The tapering arch form has the highest alveolar bone width in the upper jaw without statistical significance. The facial cortical bone thickness needs to be evaluated before implantation in the anterior region because it is less than two millimeters in both jaws. CBCT is important for the immediate implant. The ovoid shape was the dominant arch form.
Characterization of Retained Austenite in Advanced High-Strength Steel
Authors: Li Shouhua , Li Kejian , Zhang Longzhu , Feng Yi , Liu Ziquan , Cao Pengjun , Liu Bo , Dong Jiling
Published: April 2023

The retained austenite (RA) in advanced high-strength steels directly affects their plasticity. It is very important for the accurate characterization of their content and types. This paper prepared three specimens with three different Mn contents (1.0%, 1.4%, and 1.7%) that are used to obtain high-strength steel by ultrafast cooling heat treatment. The volume content and distribution of the RA were analysed by an X-ray Debye ring measurement system, electron backscatter diffraction (EBSD), and transmission electron microscopy (TEM). In addition, the mechanical tensile test provided the tensile properties and elongation of three specimens. It was finally concluded that when the content of Mn increased, the island-type and thin film-type RA both increased, which may effectively improve the plasticity of the martensitic steels.