bluuebunny/crossref_metadata_2025 huggingface dataset:
Dynamic X-chromosomal reactivation enhances female brain resilience
Authors: Käseberg S , Bertin M , Menon R , Gabassi E , Todorov H , Frank S , Brennenstuhl H , Lohrer B , Winter J , Krummeich J , Winkler J , Winner B , Weis E , Hartwich D , Diederich S , Luck K , Gerber S , Lunt P , Berninger B , Falk S , Schweiger S , Karow M
Published: June 2023

While random X-chromosome inactivation in female cells of placental mammalians silences one allele of the majority of X-chromosomal genes, a considerable fraction is only incompletely and variably inactivated resulting in a tissue-specific pattern of mono- and biallelic expression. Here we used clonal human female induced pluripotent stem cells (iPSCs) allowing to trace the (in)activation status of the two X-chromosomes individually along neural differentiation trajectories. We discovered X-chromosome-wide locus- and lineage-specific dynamic usage of the two X-chromosomal alleles in female cells induced by differentiation. Leveraging iPSCs derived from patients with an X-linked neurodevelopmental disorder, we demonstrate that activation of alleles on the inactive X-chromosome can exert protective effects on the manifestation of disease phenotypes in female neural cells and tissue. Taken together, our data demonstrate that alleles on the inactive X-chromosome can serve as a critical reservoir reactivated during differentiation, thereby enhancing resilience of female neural tissue.
Dating the bacterial tree of life based on ancient symbiosis
Authors: Wang Sishuo , Luo Haiwei
Published: June 2023

Obtaining a timescale for bacterial evolution is crucial to understand early life evolution but is difficult owing to the scarcity of bacterial fossils and absence of maximum age constraints of the available fossils. Here, we introduce multiple new time constraints to calibrate bacterial evolution based on ancient symbiosis. This idea is implemented using a bacterial tree constructed with mitochondria-originated genes where the mitochondrial lineage representing eukaryotes is embedded within Proteobacteria, such that the date constraints of eukaryotes established by their abundant fossils are propagated to ancient co-evolving bacterial symbionts and across the bacterial tree of life. Importantly, we formulate a new probabilistic framework that considers uncertainty in inference of the ancestral lifestyle of modern symbionts to apply 19 relative time constraints (RTC) each informed by host-symbiont association to constrain bacterial symbionts no older than their eukaryotic host. Moreover, we develop an approach to incorporating substitution mixture models that better accommodate substitutional saturation and compositional heterogeneity for dating deep phylogenies. Our analysis estimates that the last bacterial common ancestor (LBCA) occurred approximately 4.0-3.5 billion years ago (Ga), followed by rapid divergence of major bacterial clades. It is robust to alternative root ages, root positions, tree topologies, fossil ages, ancestral lifestyle reconstruction, gene sets, among other factors. The timetree obtained enables the validation of various hypotheses, such as the survival of life during the late heavy bombardment, the absence of a connection between ancient stromatolites and cyanobacteria, and the presence of aerobic enzymes before the oldest geochemical records of molecular oxygen.

Significance Statement

Bacteria, with their vast diversity and ancient history, play a crucial role in shaping Earth’s biogeochemistry. However, the scarcity of fossils complicates the determination of their evolution timescale and its link to Earth’s history. To address this issue, we have devised and implemented novel methods that utilize ancient symbiosis and eukaryotic fossils to calibrate bacterial evolution by molecular clock. We obtain a comprehensive genus-level evolutionary timeline of bacteria that sheds light on their profound influence on the development and diversity of life on our planet, as well as its environmental dynamics. This research greatly contributes to our understanding of microbial evolution and its implications for Earth’s past and present.
Combination therapy with oral antiviral and anti-inflammatory drugs improves the efficacy of delayed treatment in severe COVID-19
Authors: Sasaki Michihito , Sugi Tatsuki , Iida Shun , Hirata Yuichiro , Kusakabe Shinji , Konishi Kei , Itakura Yukari , Tabata Koshiro , Kishimoto Mai , Kobayashi Hiroko , Ariizumi Takuma , Intaruck Kittiya , Nobori Haruaki , Toba Shinsuke , Sato Akihiko , Matsuno Keita , Yamagishi Junya , Suzuki Tadaki , Hall William W. , Orba Yasuko , Sawa Hirofumi
Published: June 2023

Pulmonary infection with SARS-CoV-2 stimulates host immune responses and can also result in the progression of dysregulated and critical inflammation. Throughout the pandemic, the management and treatment of COVID-19 has been continuously updated with a range of antiviral drugs and immunomodulators. Monotherapy with oral antivirals has proven to be effective in the treatment of COVID-19. However, the treatment should be initiated in the early stages of infection to ensure beneficial therapeutic outcomes, and there is still room for further consideration on therapeutic strategies using antivirals. Here, we show that the oral antiviral ensitrelvir combined with the anti-inflammatory corticosteroid methylprednisolone has higher therapeutic effects and better outcomes in a delayed dosing model of SARS-CoV-2 infected hamsters compared to the monotherapy with ensitrelvir or methylprednisolone alone. Combination therapy with these drugs improved respiratory conditions and the development of pneumonia in hamsters even when the treatment was started after 2 days post infection. The combination therapy led to a differential histological and transcriptomic pattern in comparison to either of the monotherapies, with reduced lung damage and down-regulated expressions of genes involved in inflammatory response. Furthermore, we found that the combination treatment is effective in infection with both highly pathogenic delta and circulating omicron variants. Our results demonstrate the advantage of combination therapy with antiviral and corticosteroid drugs in COVID-19 treatment. Since both drugs are available as oral medications, this combination therapy could provide a clinical and potent therapeutic option for COVID-19.
Genetic evidence for functional diversification of gram-negative intermembrane phospholipid transporters
Authors: Rai Ashutosh K. , Sawasato Katsuhiro , Bennett Haley C. , Kozlova Anastasiia , Sparagna Genevieve C. , Bogdanov Mikhail , Mitchell Angela M
Published: June 2023

The outer membrane of Gram-negative bacteria is a barrier to chemical and physical stress. Phospholipid transport between the inner and outer membranes has been an area of intense investigation and, in E. coli K-12, it has recently been shown to be mediated by YhdP, TamB, and YdbH, which are suggested to provide hydrophobic channels for phospholipid diffusion, with YhdP and TamB playing the major roles. However, YhdP and TamB have different phenotypes suggesting distinct functions. We investigated these functions using synthetic cold sensitivity (at 30 °C) caused by deletion of yhdP and fadR, a transcriptional regulator controlling fatty acid degradation and unsaturated fatty acid production, but not by ΔtamB ΔfadR or ΔydbH ΔfadR,. Deletion of tamB suppresses the ΔyhdP ΔfadR cold sensitivity suggesting this phenotype is related to phospholipid transport. The ΔyhdP ΔfadR strain shows a greater increase in cardiolipin upon transfer to the non-permissive temperature and genetically lowering cardiolipin levels can suppress cold sensitivity. These data also reveal a qualitative difference between cardiolipin synthases in E. coli, as deletion of clsA and clsC suppresses cold sensitivity but deletion of clsB does not despite lower cardiolipin levels. In addition to increased cardiolipin, increased fatty acid saturation is necessary for cold sensitivity and lowering this level genetically or through supplementation of oleic acid suppresses the cold sensitivity of the ΔyhdP ΔfadR strain. Although indirect effects are possible, we favor the parsimonious hypothesis that YhdP and TamB have differential substrate transport preferences, most likely with YhdP preferentially transporting more saturated phospholipids and TamB preferentially transporting more unsaturated phospholipids. We envision cardiolipin contributing to this transport preference by sterically clogging TamB-mediated transport of saturated phospholipids. Thus, our data provide a potential mechanism for independent control of the phospholipid composition of the inner and outer membranes in response to changing conditions.
Green supplier selection and environmental performance of firms in the Chinese manufacturing industry: the roles of behavior and outcome controls
Authors: Lee Hanna , Wu Xiaobo
Published: June 2023

Purpose

Green supplier selection (GSS) is acknowledged as important governance in green supply chain management (GSCM). However, this paper argues that GSS is not a stand-alone GSCM governance mode that determines manufacturers' environmental performance but rather one that needs to be aligned with contractual governance, particularly contractual control and adaptation, to promote environmental performance effects. This paper adopts GSS as ex ante governance and introduces behavior and outcome controls as ex post contractual control and adaptation, respectively. Thus, this paper addresses how GSS affects environmental performance directly and indirectly through behavior and outcome controls within transaction cost economics (TCE) theory.

Design/methodology/approach

This research model was tested on 300 Chinese manufacturing firms, and multiple regression analysis was used to validate our hypotheses.

Findings

A direct relationship was observed between GSS and environmental performance. This direct relationship is positively mediated by behavior and outcome controls.

Originality/value

This paper develops and elucidates an integrative green supply chain process proceeding from the implementation of ex ante GSS and ex post contractual governance to the realization of environmental performance. Furthermore, this paper considers two different forms of contractual governance, specifically contractual control and adaptation, and explains how they can be implemented using behavior and outcome controls from the perspective of TCE theory.
Too much psychological capital? Exploring curvilinear relationships between OPsyCap and performance prior to and after the COVID-19 crisis
Authors: Jancenelle Vivien
Published: June 2023

Purpose

Past research has generally purported and tested for a positive linear relationship between psychological capital and organizational outcomes such as firm performance. Yet, recent conceptual work has started to recognize that for certain outcomes, too much psychological capital can be as detrimental as too little. In this study, the author hypothesizes that during a major crisis, organizational psychological capital (OPsyCap) may in fact exhibit an inverted U-shaped relationship with performance.

Design/methodology/approach

T leverages the revelatory power of a recent major crisis (the COVID-19 pandemic) to gather a pre-crisis and post-crisis matching sample of 952 earnings conference calls held by 476 S&P 500 firms with corresponding market performance data and use computer-assisted text analysis (CATA) methodology to assess OPsyCap from call transcripts.

Findings

T finds that OPsyCap has a statistically significant inverted U-shaped relationship with market performance after the crisis, but not prior—thereby suggesting that moderate OPsyCap is more beneficial to market performance than either insufficient or excessive OPsyCap in times of crisis.

Practical implications

Top managers should not display overly excessive psychological capital after a major crisis, as shareholders may interpret such cues as unwarranted optimism, overconfidence and an inability to accept the new reality brought about by the crisis.

Originality/value

This study's findings contribute to extant literature by being the first to empirically highlight a curvilinear relationship between psychological capital and an important outcome variable—market performance. Furthermore, this study's lack of results prior to a major crisis, but not after, may suggest a new boundary condition.
Performance feedback and firms’ strategic actions: a cross-national meta-analysis
Authors: Xue Shan , Chen Honghui , Wu Jintao
Published: June 2023

Purpose

Although previous research has investigated how performance feedback may affect firms’ strategic actions, their findings has been inconsistent. The relationship between performance feedback and firms’ strategic activities thus appears complex. Moreover, the authors contend that it may vary with the measurement strategies employed (i.e. social or historical feedback, operationalizations of strategic actions or accounting- and market-based performance indicators) and the national contexts.

Design/methodology/approach

Therefore, the current article presents a comprehensive meta-analysis of prior research, including 1,637,817 sample observations from 101 studies that span more than 18 countries.

Findings

The results indicate that (1) performance that are below or above aspirational levels generally has a positive relationship with firms’ strategic actions; (2) these relationships are contingent on the implementation forms taken by the key variables, such as performance feedback, strategic actions and performance indicators; and (3) the relationships are much stronger in countries where managerial discretion is greater.

Originality/value

The findings contribute to the clarification of long-standing theoretical and empirical debates regarding the relationship between performance feedback and strategic actions, as well as some pertinent directions for future research.
The internationalization performance of Indonesian SMEs during COVID-19 pandemic: exploring a mediation model
Authors: Anggadwita Grisna , Indarti Nurul , Sinha Paresha , Manik Hardo Firmana Given Grace
Published: June 2023

Purpose

Small and medium enterprises (SMEs) in emerging economies face significant challenges in formulating effective strategies to enter international markets, particularly amid uncertain conditions such as the COVID-19 pandemic. Consequently, there is a pressing need to examine the performance of these SMEs and evaluate their internationalization process. This study aims to examine the effects of international entrepreneurial orientation on the internationalization performance of SMEs and the mediating effects of organizational dynamic capability and organizational culture in Indonesia.

Design/methodology/approach

This study used a quantitative method with a survey approach by distributing questionnaires to 206 SMEs in Indonesia that have implemented internationalization practices. Partial least squares-structural equation modeling (PLS-SEM) was used to predict and estimate relationships.

Findings

This study finds that one of the SMEs’ strategies to encounter the new normal era of COVID-19 is to improve their internationalization performance, especially by actively participating in international markets. The empirical results show that organizational dynamic capabilities and organizational culture are proven to fully mediate the relationship between international entrepreneurial orientation and the internationalization performance of SMEs. Meanwhile, international entrepreneurial orientation does not directly affect SMEs’ internationalization performance. This study confirms the mediating role of organizational dynamic capabilities and organizational culture in dynamic capabilities theory and their relevance to internationalization.

Originality/value

This study provides valuable insights and encourages owner-managers and policy-makers in emerging economies, particularly Indonesia, to develop organizational dynamic capabilities and organizational culture that align with the demands of internationalization.
Does uncertainty promote exchange rate volatility? Global evidence
Authors: Aftab Muhammad , Naeem Maham , Tahir Muhammad , Ismail Izlin
Published: June 2023

Purpose

Exchange rate volatility is an important factor affecting investors and policymakers. This study aims to examine the impact of uncertainties, in terms of changes in economic policy, monetary policy and global financial markets, on exchange rate volatility.

Design/methodology/approach

The study uses the GARCH (1,1) univariate model to calculate exchange rate volatility. Economic and monetary policy uncertainties are measured using news-based indices, while global financial market volatility is measured using the implied volatility index. Panel autoregressive distributed lag modeling is used to analyze the impact of uncertainty on exchange rate volatility in the short and long run. The sample consists of 26 developed and emerging markets from 2005 to 2020.

Findings

The study finds that economic policy uncertainty significantly increases exchange rate volatility. Similarly, global financial market uncertainty leads to increased exchange rate volatility. The effect of US monetary policy uncertainty reduces exchange rate volatility.

Originality/value

This research contributes to the existing literature on exchange rate fluctuations by examining the impact of uncertainties on exchange rate volatility. The study uses novel news-based indices for measuring economic and monetary policy uncertainties and includes a broader sample of emerging and advanced markets. The findings have important implications for investors and policymakers.
Research collaboration outputs between the European Union and Africa: the case of co-authored scientific articles between Finland and Africa
Authors: Jauhiainen Jussi
Published: June 2023

I analyzed co-authored international peer-reviewed scientific articles that resulted from research collaborations between scholars in the European Union (EU) and African countries, with a particular focus on the case of Finland. Among the 28 EU member states, Finland ranked 13th in terms of the quantity of co-authored scientific articles produced through these collaborations. I found that from 2015 to 2021, scholars from universities, research institutes, and other organizations in African countries and Finland co-authored more than 4,700 international peer-reviewed articles. Despite the doubling of co-authored Finland–Africa peer-reviewed scientific articles in international journals annually during this period, these articles accounted for less than one percent of all international peer-reviewed scientific articles in Africa, and their proportional share decreased over time. The most common fields of collaboration were medical sciences and natural science. Of Finland–Africa articles, almost 1,500 focused on Africa. The University of Helsinki and South African universities were the most active collaborators. Given these findings, it is crucial to address the implementation of the European Commission’s strategy for partnerships with Africa and Finland’s collaboration strategies with Africa to encourage more inclusive research collaboration among scholars from Finland, Europe, and Africa.
South Asian students’ migration to, within and from Finland and Sweden: connecting the dots to arrivals and departures
Authors: Abdin Zain Ul
Published: June 2023

Much of the current research on international student migration is focused on home-to-host and stay-or-leave migration behaviours. However, there is a possibility that international students might migrate within the host country before making their final stay-or-leave migration decisions. This paper adapts stepwise migration theory as an analytical tool with which to investigate the migration behaviour of Indian and Pakistani students. Based on 57 interviews and extensive participant observation, it analyses the factors that prompt South Asian student migration to, within and, subsequently for some, from Finland and Sweden. The findings support the argument that international student migration is multistage. Initial origin-to-destination migration is often insufficient to meet the high-set ambitions of talented young migrants. Disappointment with perceived missing opportunities in the university city or town lays the basis for subsequent intercity and stay-or-leave migration stages. Subsequent migration within the destination country impacts on the students’ stay-or-leave aspirations, while the origin-country situation influences return-or-onward migration decisions.
Where is climate asylum?
Authors: Kallio Kirsi Pauliina , Riding James
Published: June 2023

This editorial discusses an alarming issue in the time of climate change: climate mobilities and, particularly, forced climate migration and the need for climate refuge and climate asylum. The focus is on the European Union (EU) where migration and asylum policies are being currently developed under the 'New Pact', yet with little intention to relate with climate mobilities of any kind. Neither does the EU's environmental and climate policy Green Deal give much attention to human mobility. At the same time, the EU has commenced many briefings on the topic, which shows that the subject matter itself is well known. The editorial hence asks, where is climate asylum if not in the EU, and when, if not at this juncture of creating new asylum policies?
Indium acetate analyzed by XPS
Authors: Rodriguez-Pereira Jhonatan , Miranda Mercado David Alejandro , Ospina Rogelio
Published: June 2023

Indium acetate was analyzed using x-ray photoelectron spectroscopy. The specimen is a powder purchased from Sigma Aldrich. The sample was fixed to a stainless-steel sample holder with copper 3MTM double-sided adhesive tape. Survey spectra, In 3d, O 1s, C 1s, In 3p, In MNN, and Cl 2p core levels spectra were acquired. Results showed how the elements in the structure of indium acetate are related.
The prospects of high-temperature superconductors
Authors: Molodyk Alexander , Larbalestier David C.
Published: June 2023

Overcoming cost barriers could make high-temperature superconductors pervasive
Into the dark
Authors: Clery Daniel
Published: June 2023

A European space telescope sets off to discover the nature of dark energy—the biggest ingredient in the universe
In Science Journals
Authors: Lopez Bianca , Lavine Marc S. , Funk Michael A. , Stajic Jelena , Ross Sarah H. , Stern Peter , Fogg Christiana N. , Hurtley Stella M. , Jiang Di , Hines Pamela J. , Wong Wei
Published: June 2023

Highlights from the
Science
family of journals
In Other Journals
Authors: Maroso Mattia , Lavine Marc S. , Jiang Di , Wible Brad , Nusinovich Yevgeniya , Hurtley Stella M. , Grocholski Brent
Published: June 2023

Editors’ selections from the current scientific literature
Programming correlated magnetic states with gate-controlled moiré geometry
Authors: Anderson Eric , Fan Feng-Ren , Cai Jiaqi , Holtzmann William , Taniguchi Takashi , Watanabe Kenji , Xiao Di , Yao Wang , Xu Xiaodong
Published: June 2023

The ability to control the underlying lattice geometry of a system may enable transitions between emergent quantum ground states. We report in situ gate switching between honeycomb and triangular lattice geometries of an electron many-body Hamiltonian in rhombohedral (R)–stacked molybdenum ditelluride (MoTe2) moiré bilayers, resulting in switchable magnetic exchange interactions. At zero electric field, we observed a correlated ferromagnetic insulator near one hole per moiré unit cell with a widely tunable Curie temperature up to 14 K. Applying an electric field switched the system into a half-filled triangular lattice with antiferromagnetic interactions; further doping this layer-polarized superlattice tuned the antiferromagnetic exchange interaction back to ferromagnetic. Our work demonstrates R-stacked MoTe2moirés to be a laboratory for engineering correlated states with nontrivial topology.
Perforin-2 is a pore-forming effector of endocytic escape in cross-presenting dendritic cells
Authors: Rodríguez-Silvestre Pablo , Laub Marco , Krawczyk Patrycja A. , Davies Alexandra K. , Schessner Julia P. , Parveen Reejuana , Tuck Benjamin J. , McEwan William A. , Borner Georg H. H. , Kozik Patrycja
Published: June 2023

During initiation of antiviral and antitumor T cell–mediated immune responses, dendritic cells (DCs) cross-present exogenous antigens on major histocompatibility complex (MHC) class I molecules. Cross-presentation relies on the unusual “leakiness” of endocytic compartments in DCs, whereby internalized proteins escape into the cytosol for proteasome-mediated generation of MHC I–binding peptides. Given that type 1 conventional DCs excel at cross-presentation, we searched for cell type–specific effectors of endocytic escape. We devised an assay suitable for genetic screening and identified a pore-forming protein, perforin-2 (
Mpeg1
), as a dedicated effector exclusive to cross-presenting cells. Perforin-2 was recruited to antigen-containing compartments, where it underwent maturation, releasing its pore-forming domain.
Mpeg1
−/−
mice failed to efficiently prime CD8
+
T cells to cell-associated antigens, revealing an important role for perforin-2 in cytosolic entry of antigens during cross-presentation.
Channeling antigens to CD8
+
T cells
Authors: Rawat Kavita , Jakubzick Claudia V.
Published: June 2023

Perforin-2 facilitates antigen translocation to the cytosol in cross-presenting dendritic cells
A bendable biological ceramic
Authors: Crane Rachel L. , Denny Mark W.
Published: June 2023

A fatigue-resistant mollusk hinge could inspire the development of new materials
Genetic and Physiological Probing of Cytoplasmic Bypasses for the Energy-Converting Methyltransferase Mtr in Methanosarcina acetivorans
Authors: Schöne Christian , Poehlein Anja , Rother Michael
Published: June 2023

Methanogenic archaea possess only a limited number of chemiosmotic coupling sites in their respiratory chains. Among them,

N
5

-methyl-H
4
SPT:HS-CoM methyltransferase (Mtr) is the most widely distributed.
Survey of glyphosate- and dicamba-resistant kochia (Bassia scoparia) in Saskatchewan
Authors: Sharpe Shaun M. , Leeson Julia Y. , Geddes Charles M. , Willenborg Christian J. , Beckie Hugh J.
Published: June 2023

Kochia ( Bassia scoparia (L.) A.J. Scott) is a problematic tumbleweed, which infests row crops and ruderal areas within western Canada. Herbicide resistance makes kochia management challenging for producers. Widespread resistance to acetolactate synthase-inhibitors, evolution and spread of glyphosate resistance, and the occurrence of dicamba resistance has been previously noted in Saskatchewan. This study's objective was to evaluate the occurrence and distribution of glyphosate- and dicamba-resistant kochia in central and southern Saskatchewan. A randomized, stratified survey was conducted in the fall of 2019 at 303 sites. Rotational history was obtained using the Agriculture and Agri-Food Canada Annual Crop Inventory. Kochia samples were collected from cropped fields (78%), ditches (17%), oil well sites (2%), and railway grades (3%). Glyphosate resistance was detected in 87% of samples ( n = 275) within 137 Rural Municipalities (RMs). Dicamba resistance was detected in 45% of kochia samples ( n = 255) in 87 RMs. Crops infested with herbicide-resistant kochia included wheat ( Triticum aestivum L. and T. durum Desf.), canola ( Brassica napus L.), lentils ( Lens culinaris Medik.), barley ( Hordeum vulgare L.), flax ( Linum usitatissimum L.), and peas ( Pisum sativum L.). Reducing the soil seedbank and preventing dispersal will be critical to mitigating resistance. Good herbicide stewardship including mixing multiple modes of action is paramount. Cultural strategies to increase canopy closure and crop competitiveness to limit biomass and seed production are recommended. Kochia occupies many environments outside of cropped fields, and a community-wide management approach may be necessary to reduce dispersal potential of tumbling plants that disperse seed.
Numerical investigation of convection–diffusion model by using the new upwind finite volume approach
Authors: Hussain Arafat , Ali Shah Murad
Published: June 2023

In this study, we constructed a numerical technique for the simulation of the convection–diffusion problem under convection dominancy. Lagrange interpolation technique is applied to obtain new expressions for the approximation of variable at the interfaces of control volume. Moreover, based on these interface approximations new numerical scheme is developed to approximate convection–diffusion phenomena. The Crank–Nicolson approach is applied for the temporal approximation. This newly constructed numerical scheme is unconditionally stable with second-order accuracy in time and space both. Numerical tests are carried out for the justification of the new algorithm. A comparison of numerical results produced by proposed technique and some other numerical approaches is presented. This comparison indicates that for convection dominant phenomena, the numerical solution of conventional finite volume method contains with non-physical oscillations which analyze that proposed numerical technique results in a high accurate and stable solution.
Effects of magnetic field and porosity on compressible flow in an asymmetric channel
Authors: Rafaqat R. , Khan A. A.
Published: June 2023

This study addressed the compressible flow of viscous fluid in an asymmetric channel under peristalsis. The difference in amplitudes and phase of traveling waves created the asymmetry of channel. Simultaneous effect of magnetic field is also incorporated. Fluid flows through a porous medium. The analytical treatment of the solution is carried out by considering upper wall amplitude as the small parameter. The expressions of flow rate and net axial velocity are constructed for the second-order approximation. Numerical integration is employed to calculate net flow rate. The role of sundry parameters is illustrated graphically. Trapping phenomenon is also taken into account by plotting streamlines against sundry parameters. The significant finding of this study is that flow rate and axial velocity enhance as fluid transitions from hydrodynamic to hydromagnetic. Enhancement in the compressibility parameter trims down the velocity and the flow rate as well. Also, asymmetry of the channel causes an enhancement in the flow rate. This model is the most prevailing version of compressible flow under peristalsis through an asymmetric channel. The findings of this study have worth mentioning yields, which can be applicable in numerous areas of fluid dynamics and aircraft industry.
To Secure the Cloud Application Using a Novel Efficient Deep Learning-Based Forensic Framework
Authors: Mohammed Sheena , Rangu Sridevi
Published: June 2023

Privacy and security are the most concerning topics while using cloud-based applications. Malware detection in cloud applications is important in identifying application malware activity. So, a novel Goat-based Recurrent Forensic Mechanism (GbRFM) is used to detect the attack and provide the attack type in cloud-based applications. At first, the dataset is pre-processed in the hidden phase, and the errorless features are extracted. The proposed model also trains the output of the hidden layer to identify and classify the malware. The wild goat algorithm enhances the identification rate by accurately detecting the attack. Using the NSL-KDD data, the preset research was verified, and the outcomes were evaluated. The performance assessment indicates that the developed model gained a 99.26% accuracy rate for the NSL-KDD dataset. Moreover, to validate the efficiency of the proposed model, the outcomes are compared with other techniques. The comparison analysis proved that the proposed model attained better results.
Tight Toughness, Isolated Toughness and Binding Number Bounds for the [1,n]-Factors and the {K2,Ci≥4}-Factors
Authors: Xu Xiao , Gao Zhuoma , Meng Lei , Tong Qinghe
Published: June 2023

Let [Formula: see text] be an integer. The [Formula: see text]-factor of a graph [Formula: see text] is a spanning subgraph [Formula: see text] if [Formula: see text] for all [Formula: see text], and the [Formula: see text]-factor is a subgraph whose each component is either [Formula: see text] or [Formula: see text]. In this paper, we give the lower bounds with regard to tight toughness, isolated toughness and binding number to guarantee the existence of the [Formula: see text]-factors and [Formula: see text]-factors for a graph.
Erratum: Construction of Hyperbolic Fuzzy Set and Its Applications in Diverse COVID-19 Associated Problems
Authors: Dutta Palash , Borah Gourangajit
Published: June 2023

In this paper, we partially modify our definition of Hyperbolic Fuzzy Set (HFS), where we have mentioned about the indeterminateness degree of HFSs.
Data Science---A Systematic Treatment
Authors: Özsu M. Tamer
Published: June 2023

While the success of early data-science applications is evident, the full impact of data science has yet to be realized.
Two Essentials for Fostering Agency in Virtual Education
Authors: Mandernach Jean , Holbeck Rick
Published: June 2023

Learner agency, premised on making education meaningful and relevant, involves fostering two critical aspects in online classrooms: voice and choice. By providing students with a say in the teaching-learning dynamics (such as setting course policies or assignment deadlines) and offering them decision-making capacity in mastering course content (like choosing individual learning paths or formats to demonstrate understanding) educators can create a personalized learning experience that enhances student motivation, engagement, and investment.
Benchmarking Combinations of Learning and Testing Algorithms for Automata Learning
Authors: Aichernig Bernhard K. , Tappler Martin , Wallner Felix
Published: June 2023

Automata learning enables model-based analysis of black-box systems by automatically constructing models from system observations, which are often collected via testing. The required testing budget to learn adequate models heavily depends on the applied learning and testing techniques.

Test cases executed for learning (1) collect behavioural information and (2) falsify learned hypothesis automata. Falsification test-cases are commonly selected through conformance testing. Active learning algorithms additionally implement test-case selection strategies to gain information, whereas passive algorithms derive models solely from given data. In an active setting, such algorithms require external test-case selection, like repeated conformance testing to extend the available data.

There exist various approaches to learning and conformance testing, where interdependencies among them affect performance. We investigate the performance of combinations of six learning algorithms, including a passive algorithm, and seven testing algorithms by performing experiments using 153 benchmark models. We discuss insights regarding the performance of different configurations for various types of systems. Our findings may provide guidance for future users of automata learning. For example, counterexample processing during learning strongly impacts efficiency, which is further affected by testing approach and system type. Testing with the random Wp-method performs best overall, while mutation-based testing performs well on smaller models.
HGV4Risk: Hierarchical Global View-guided Sequence Representation Learning for Risk Prediction
Authors: Li Youru , Zhu Zhenfeng , Guo Xiaobo , Li Shaoshuai , Yang Yuchen , Zhao Yao
Published: June 2023

Risk prediction, usually achieved by learning representations from patient’s physiological sequence or user’s behavioral sequence data, and has been widely applied in healthcare and finance. Despite that, some recent time-aware deep learning methods have led to superior performances in such sequence representation learning tasks, such improvement is limited due to a lack of guidance from hierarchical global view. To address this issue, we propose a novel end-to-end
H
ierarchical
G
lobal
V
iew-guided (HGV) sequence representation learning framework. Specifically, the Global Graph Embedding (GGE) module is proposed to learn sequential clip-aware representations from temporal correlation graph (TCG) at instance level. Furthermore, following the way of key-query attention, the harmonic β-attention (β-Attn) is also developed for making a global tradeoff between time-aware decay and observation significance at channel level adaptively. Moreover, the hierarchical representations at both instance level and channel level can be coordinated by the heterogeneous information aggregation under the guidance of global view. Experimental results on both healthcare risk prediction benchmark and SMEs credit overdue risk prediction task from the real-world industrial scenario in MYBank, Ant Group, have illustrated that the proposed model can achieve competitive prediction performance compared with other known baselines. The code has been released public available at: https://github.com/LiYouru0228/HGV.
A Scalable Method for Enhancing the Crystallinity of Zn Powder to Reduce Corrosion and Boost Achievable Capacity
Authors: Lenhart Brian , Zuraw Mike , Mustain William
Published: June 2023

Zinc corrosion is an unavoidable phenomenon in alkaline systems. Additives like surfactants and metals at the ppm level are typically included in the zinc-alkaline cell production process to help suppress corrosion. Though these inclusions have helped remediate the issue, the inclusions themselves bring forward new issues such as increased toxicity and cost. Therefore, a method for achieving reduced Zn corrosion that can either complement or replace additives is highly desirable. In this work, a method for the scalable improvement of zinc microparticle crystallinity, without the use of additives, is presented and detailed. The recrystallization process involves oxide film formation, thermal annealing, and oxide film removal. The process converts polycrystalline particles into either a single crystal or one with larger, fewer total grains while conserving particle shape and size. This paper demonstrates reduced corrosion and enhanced achievable capacity for the recrystallized particles as well as improved cyclability. More specifically, the recrystallized particles demonstrate a 19% reduction in corrosion current and a 12% increase in achievable capacity when probed by linear sweep voltammetry and constant current discharge, respectively. When cycled in charge-discharge experiments, the recrystallized particles boast up to a 114% improvement in cyclability.
Kinetic Analysis of Sodium-Ion Intercalation Reaction into Graphene-Like Graphite by Electrochemical Impedance Spectroscopy
Authors: Inamoto Junichi , Aga Koki , Inoo Akane , Matsuo Yoshiaki
Published: June 2023

Graphene-like graphite (GLG) is a promising anode material for sodium-ion batteries, which is believed to have unique kinetic properties compared to hard carbon due to its different intercalation mechanism. In this study, electrochemical impedance spectroscopy was used to investigate the kinetic properties of sodium-ion intercalation in GLG. Our results indicated that the activation energies for interfacial sodium-ion transfer of GLGs were nearly identical to those reported for graphite, regardless of the heat treatment temperature of the GLGs. Furthermore, these activation energies were lower than those observed for hard carbon, suggesting better sodium-ion intercalation kinetics. In addition, the diffusion coefficient of sodium ions in the GLG was similar to that of graphite, with the highest value observed for GLG800, the GLG heat-treated at the highest temperature of 800 °C. This may indicate that the diffusion coefficient increases with the presence of nanopores in the graphene layer of GLG. It has also been reported that GLG800 is superior in terms of reversible capacity and working potential compared to GLGs synthesized at other temperatures. Consequently, the results clearly demonstrated that GLG800 has the best electrochemical properties in terms of both thermodynamics and kinetics among the GLGs investigated in this study.
Inlaying Silicon in SiC-Derived Graphite with Unique Cavity Structure as a High-Capacity Anode for Li-Ion Batteries
Authors: Hu Mengfei , Ma Yujie , Wu Houzheng , Zhang Guo-Jun
Published: June 2023

Silicon-based anode in Li-ion batteries has received much attention due to its extremely high theoretical capacity which can support high-energy-density battery system. However it suffers seemingly insurmountable barriers including volume expansion and capacity fading during repetitive cycling. In this work, we demonstrated a new kind of silicon/carbon (Si/C) composite design to address the issues in the silicon-based anode application via building a three-dimensional structure of nano Si and carbide-derived-graphite (CDG). Unique cavity-structured CDG made from SiC powder via scalable high temperature treatment, could supply a conductive host for the well-dispersed nano Si particles. CDG/Si composite get improved cycle stability and maintained high capacity of 637 mAh g−1 after 500 cycles. Rate performance of CDG/Si was also enhanced, which should be attributed to good electrolyte accessibility and short ion diffusion distance of CDG to enhance electrode kinetics. In addition, CDG was verified to accommodate higher content of Si of 60%, to achieve higher capacity of 1800 mAh g−1. This work provided a good alternative of carbon matrix for Si/C anode, and it is anticipated that this kind of carbide derived graphite might be of great interest to the further development of high-capacity Si-based anode in Li-ion batteries.
Proximity-Driven DNA Nanosensors
Authors: Nixon Sara R. , Phukan Imon Kanta , Armijo Brian J. , Ebrahimi Sasha B. , Samanta Devleena
Published: June 2023

In proximity-driven sensing, interactions between a probe and an analyte produce a detectable signal by causing a change in distance of two probe components or signaling moieties. By interfacing such systems with DNA-based nanostructures, platforms that are highly sensitive, specific, and programmable can be designed. In this Perspective, we delineate the advantages of using DNA building blocks in proximity-driven nanosensors and provide an overview of recent progress in the field, from sensors that rapidly detect pesticides in food to probes that identify rare cancer cells in blood. We also discuss current challenges and identify key areas that need further development.
Elephant Flows Detection Using Deep Neural Network, Convolutional Neural Network, Long Short-Term Memory, and Autoencoder
Authors: Wassie Geremew Getahun , Ding Jianguo
Published: June 2023

Currently, the widespread of real-time applications such as VoIP and videos-based applications require more data rates and reduced latency to ensure better quality of service (QoS). A well-designed traffic classification mechanism plays a major role for good QoS provision and network security verification. Port-based approaches and deep packet inspection (DPI) techniques have been used to classify and analyze network traffic flows. However, none of these methods can cope with the rapid growth of network traffic due to the increasing number of Internet users and the growth of real-time applications. As a result, these methods lead to network congestion, resulting in packet loss, delay, and inadequate QoS delivery. Recently, a deep learning approach has been explored to address the time-consumption and impracticality gaps of the abovementioned methods and maintain existing and future traffics of real-time applications. The aim of this research is then to design a dynamic traffic classifier that can detect elephant flows to prevent network congestion. Thus, we are motivated to provide efficient bandwidth and fast transmission requirements to many Internet users using SDN capability and the potential of deep learning. Specifically, DNN, CNN, LSTM, and Deep autoencoder are used to build elephant detection models that achieve an average accuracy of 99.12%, 98.17%, and 98.78%, respectively. Deep autoencoder is also one of the promising algorithms that do not require human class labeler. It achieves an accuracy of 97.95% with a loss of 0.13. Since the loss value is closer to zero, the performance of the model is good. Therefore, the study has a great importance to Internet service providers, Internet subscribers, as well as for future researchers in this area.
Calculations of Constant-Height STM Images of Fullerene C60 Adsorbed onto a Surface
Authors: Rashed Effat A.
Published: June 2023

Constant-height scanning tunneling microscopy (STM) images of a C60 molecule adsorbed onto a surface were calculated using symmetry-adapted Hückel molecular orbitals (HMOs). Three adsorption orientations of C60 are considered. The interaction between the C60 molecule and the surface was treated using symmetry arguments only. Projection operators were used to generate symmetry-adapted HMOs of the molecule. These orbitals were then used to construct idealized constant-height STM images using the simple tunneling theory of Tersoff and Hamann. A comparison is made with published experimental STM maps. The results show that, for each orientation of C60, split orbitals of the same symmetry have similar appearances in the constant-height maps. They also show that the map of a molecular orbital of a complete degeneracy is dominated by only one or two of its components.
Transcriptome Analysis of Human Vascular Smooth Muscle Cells Cultured on a Polyglycolic Acid Mesh Scaffold
Authors: Liu Jiang , Feng Zibei , Liu Peng , Fang Lijun , Wang Xichun , Lao Haiyan , Wu Yueheng , Lin Zhanyi
Published: June 2023

To construct tissue-engineered blood vessels (TEBVs) in vitro, it is necessary to transfer seed cells to three-dimensional (3D) scaffolds for culture. However, what happens to the behavior of the cells after they are transferred to the scaffold is unclear. Therefore, in this study, a transcriptome analysis was used to characterize the differentially expressed genes (DEGs) of vascular smooth muscle cells (VSMCs) before and after transfer to 3D polyglycolic acid (PGA) scaffolds and to understand the changes in functional gene expression in the early stage of 3D culture. Transcriptome sequencing results showed that DEGs in the seed cells were mainly enriched in cell proliferation and cell-cell adhesion. The DEGs of cells grown in a 3D PGA scaffold (PGA-VSMCs) were mainly enriched in signal transduction. Furthermore, we found that ERK1/2 was significantly activated in PGA-VSMCs and inhibiting the phosphorylation level of ERK 1/2 in PGA-VSMCs significantly increased the expression of elastin. In conclusion, the PGA scaffold material altered gene expression in VSMCs and affected the elastin production. This study advances our understanding of biomaterial-cell interactions and provides valuable insights for improving the cultivation of TEBVs.
Data from Wnt Signaling Stimulates Cooperation between GREB1 and HNF4α to Promote Proliferation in Hepatocellular Carcinoma
Authors: Matsumoto Shinji , Harada Akikazu , Seta Minami , Akita Masayuki , Gon Hidetoshi , Fukumoto Takumi , Kikuchi Akira
Published: June 2023

Abstract
Wnt signaling is known to maintain two cell states, hepatocyte differentiation and proliferation, in hepatocellular carcinoma (HCC). On the other hand, activation of Wnt signaling in colon cancer promotes uncontrollable stereotypic proliferation, whereas cells remain undifferentiated. To elucidate the unique mode of Wnt signaling in HCC, we comprehensively investigated HCC-specific Wnt pathway target genes and identified GREB1. Wnt signaling induced expression of GREB1 coupled with HNF4α and FOXA2, master transcription factors that maintain hepatic differentiation. Moreover, GREB1 was enriched at the regulatory region of atypical HNF4α target genes, including progrowth genes, thereby stimulating HCC proliferation. Therefore, GREB1 acts as a unique mediator of versatile Wnt signaling in HCC progression, bridging the roles of the Wnt pathway in differentiation and proliferation.
Significance:
GREB1 is a liver cancer–specific Wnt signaling target gene that induces an oncogenic shift of HNF4α, a putative tumor suppressor, and may represent a therapeutic target in Wnt-activated hepatocellular carcinoma.