bluuebunny/crossref_metadata_2025 huggingface dataset:
Dimensions of organizational justice on employee commitment – moderating effect of gender
Authors: Supriya C. , Dadhabai Sundari
Published: March 2024

Organizational justice has been a critical dimension for employee commitment towards the origination in educational sector. Organizational justice has three critical component s namely: distributive justice, procedural justice and interactional justice. The research was aimed to study the various factors of organizational justice on the impact of employee commitment towards the organization in education sector among faculty in higher education. Data were obtained from academicians working in educational institutions and to measure their commitment towards the organization. The data were collected using convenience sampling method. A survey was conducted among 165 respondents. SPSS software was adopted to conduct exploratory factor analysis and multiple regression to analyze the data. Results of the study revealed that distributive justice, procedural justice and interracial justice have exhibited a positive impact on employee commitment. Further gender has shown significant influence on employee commitment. The research provides useful implications for research and academia.
Progressive Collaborative Method for Protecting Users Privacy in Location-Based Services
Authors: Ramakrishna Reddy K. , Sharma V.K. , Anusha M. , Jhade Srinivas , Dhanasekaran B.
Published: March 2024

The development of new mobile communication and information service technologies has opened up exciting possibilities for location-based services. Users of location-based services (LBS) can access vital data from their service providers by utilizing their location data. Maps and navigation, information services, tourist information services, social networking, and many more popular applications are available. A user's location and other personal details must be submitted to the providers of location-based services in order for them to work. For example, details about one's whereabouts and identity. By "location privacy," we mean the idea that third parties shouldn't be able to track a user's precise whereabouts. It is important that users' sensitive information be hidden from unauthorized individuals when communicating. Most difficult in LBS location-based are concerns about communications and data. Each peer does their duty reciprocally in a collaborative method, which is a completely distributed technique. For the most secure and private location-based services (LBS), it employs cryptographic methods. The number of people using LBS is growing at a rapid pace these days. At this time, there isn't a single method available that has scalability capabilities. Building a realistic and computationally efficient solution that offers high privacy while decreasing processing overhead and improving scalability is a challenging task. The suggested method is cost-effective, supports scaling, is highly resilient against security and privacy assaults, and ensures privacy.
Model for recognizing human behavior via feature and classifier selection
Authors: Rao Yanamadni Venkata , Karthikeya Telakapalli , Shiva Reddy Rajamuri , Gowtham Somarouthu , Kiran Goud Shivaghoni , Vijendar Reddy G. , Vladimirovich Kotov Evgeny
Published: March 2024

Motion or inertial sensors, like the accelerometer and gyroscope that are frequently found in smartphones and smartwatches, can measure the acceleration and angular velocity of bodily movements and be used to teach bots so that they may guess human activities. These models can be selected to a variety of fields, including biometrics and remote patient health monitoring. Because deep learning-based methods employ representing teaching methods, those may automatically identify hidden patterns in data and generate optimal objects from basic information generated from sensors without human intervention, they got popular in earlier in recognizing human activities. Along with recognize human activity, this paper suggests a novel called HDDN-model called CNN-GRU, which combines convolutional units. This model exhibited accuracy that is suggestively better than other state-of-the-art DNN models like Inception Time and Deep Conv LSTM developed using Auto ML, and was successfully verified on the WISDM dataset.
Securing IoT networks: A fog-based framework for malicious device detection
Authors: Kumar Lingamallu Raghu , Balasubramani Pradeep , Arvind S. , Rao P. Srinivasa , Ammisetty Veeraswamy , Gurnadha Gupta Koppuravuri , Sharath M.N. , Nagendra Kumar Y.J. , Mittal Vaibhav
Published: March 2024

Ensuring device security is a significant obstacle to effectively implementing the Internet of Things (IoT) and fog computing in today's Information Technology (IT) landscape. Researchers and IT firms have investigated many strategies to safeguard systems against unauthorized device assaults, often known as outside device assaults. Cyber-attacks and data thefts have significantly risen in many corporations, organizations, and sectors due to exploiting vulnerabilities in safeguarding IoT gadgets. The rise in the variety of IoT gadgets and their diverse protocols has increased zero-day assaults. Deep Learning (DL) is very effective in big data and cyber-security. Implementing a DL-based Gated Recurrent Unit (GRU) on IoT devices with constrained resources is unfeasible due to the need for substantial computational power and robust storage capacities. This study introduces an IoT-based Malicious Device Detection (IoT-MDD) that is dispersed, resilient, and has a high detecting rate for identifying various IoT cyber-attacks using deep learning. The suggested design incorporates an Intrusion Detection System (IDS) on fog nodes because of its decentralized structure, substantial processing capabilities, and proximity to edge gadgets. Tests demonstrate that the IoT-MDD model surpasses the performance of the other models. The study found that the cybersecurity architecture effectively detects malicious gadgets and decreases the percentage of false IDS alarms.
A review on fixed threshold based and adaptive threshold based auto-scaling techniques in cloud computing
Authors: Ali Khan Asif , vidhyadhari CH. , Kumar Suresh
Published: March 2024

Cloud computing has evolved as an effective technology in the past few years. It is playing an important role in information technology. The main characteristics and challenges of cloud computing are 100% availability and Scalability. To achieve these two things we have concepts like Load balancing and auto-scaling in the cloud. In this paper, we will discuss auto-scaling and the two different ways to achieve auto-scaling. The commonly used auto-scaling technique is fixed threshold-based auto-scaling and it is further modified as adaptive threshold-based auto-scaling. Auto-scaling can scale up or down the cloud resources based on demand, which means the virtual machines are automatically launched or deleted based on the requirement. As Auto-scaling provides better fault tolerance, better availability, and cost management, it improves an organization’s service level agreements.
A Machine Learning Chronicle in Airfares for Pricing the Clouds
Authors: Subbarayudu Yerragudipadu , Gurram Vijendar Reddy , Ritvik T.S. , Naveen Thota , Sai Shankar Goud S. , Rajasekhar N. , Ahuja Sunaina
Published: March 2024

The subject of airfare is examined in this paper. As a result, a collection of factors that characterize a typical flight are selected under the presumption that they have an impact on airline ticket costs. The price of a plane ticket is influenced by the length of the trip, the location, the schedule, and several other factors, like holidays or vacations. Therefore, many people will surely save time and effort by having a basic awareness of airline expenses prior to making trip arrangements. The performance of the seven different machine learning (ML) models used to anticipate the price of airline tickets is compared after three datasets were analysed to acquire insight into airline fares. The objective is to investigate the factors that influence flight prices. The data can then be used to build a system that can predict how much a flight will cost.
Metaheuristic Algorithms for Optimal Sizing of Renewable Energy Systems in Smart Grids
Authors: Iurevna Usanova Kseniia , Santoshi Kumari M.
Published: March 2024

This research thoroughly examines the effectiveness of several metaheuristic algorithms in optimizing the dimensions of renewable energy systems in smart grids. It focuses on the urgent need for sustainable and efficient integration of energy. This study examines several optimization strategies by analyzing simulated datasets that represent renewable energy production profiles, energy consumption patterns, and battery storage performance. The data illustrates variations in the availability of renewable energy, with solar energy fluctuating between 500 kWh and 600 kWh, wind energy ranging from 280 kWh to 320 kWh, and hydro energy varying from 180 kWh to 220 kWh. Moreover, energy consumption patterns remain stable sectors, with throughout consumption levels ranging from 400 kWh to 430 kWh, 450 kWh to 480 kWh, and 600 kWh to 630 kWh, respectively. The examination of battery storage performance indicates that the charging efficiency ranges from 90% to 94% and the discharging efficiency ranges from 85% to 89%. Additionally, the depth of discharge ranges from 80% to 84% and the cycle life spans from 2000 cycles to 2400 cycles. By using several metaheuristic algorithms, the research produces a wide range of ideal size arrangements for solar panels, wind turbines, hydro turbines, and battery capacity. These suggested solutions exhibit variances that span from 3.23% to 20%. The results highlight the susceptibility of these algorithms to optimization goals, underlining the need of selecting appropriate algorithms that align with particular limitations and aims. The study's results illuminate the potential of metaheuristic algorithms in attaining effective and sustainable integration of renewable energy systems inside smart grids. This paves the path for informed decision-making and future developments in renewable energy management methods.
Sales model and logistics selections for a manufacturer considering carbon emission and logistics levels
Authors: Liu Xin , Wu Xiaojie , Lin Xiaogang
Published: March 2024

Improving logistics levels requires mobilizing more resources, resulting in more carbon emissions. We consider a manufacturer selling its products through an e-commerce platform that sells them to customers (reselling) or directly accessing customers via the platform by paying a proportional fee (agency selling). Under reselling, the manufacturer first sets a wholesale price and then the platform sets a retail price and a logistics level. Under agency selling, if using third-party logistics, the manufacturer sets the retail price and logistics level. When using the platform logistics, the manufacturer sets the retail price and the platform sets the logistics level; moreover, the manufacturer bears part of the logistics cost. This study examines the manufacturer’s sales model and logistics selection and its impact on the platform’s profit and consumer surplus. We find that if the logistics-improving efficiency is sufficiently high (low), the manufacturer should employ reselling (agency selling and third-party logistics) when the manufacturer bears a sufficient small or large part of the logistics cost. However, regardless of the size of the logistics-improving efficiency, the manufacturer should adopt agency selling and platform logistics when the logistics cost borne by the manufacturer is intermediate. If consumers become more sensitive to carbon emission levels, the manufacturer is less (more) likely to adopt the reselling model and platform logistics (agency selling model and platform logistics). Choosing reselling or agency selling and platform logistics, or agency selling and third-party logistics could benefit both the platform and consumers, generating a “win-win-win” outcome.
Behavioral authentication for security and safety
Authors: Wang Cheng , Tang Hao , Zhu Hangyu , Zheng Junhan , Jiang Changjun
Published: March 2024

The issues of both system security and safety can be dissected integrally from the perspective of behavioralappropriateness. That is, a system that is secure or safe can be judged by whether the behavior of certain agent(s) isappropriateor not. Specifically, a so-calledappropriate behaviorinvolves the right agent performing the right actions at the right time under certain conditions. Then, according to different levels of appropriateness and degrees of custodies, behavioral authentication can be graded into three levels,i.e., the authentication of behavioralIdentity,Conformity, andBenignity. In a broad sense, for the security and safety issue, behavioral authentication is not only an innovative and promising method due to its inherent advantages but also a critical and fundamental problem due to the ubiquity of behavior generation and the necessity of behavior regulation in any system. By this classification, this review provides a comprehensive examination of the background and preliminaries of behavioral authentication. It further summarizes existing research based on their respective focus areas and characteristics. The challenges confronted by current behavioral authentication methods are analyzed, and potential research directions are discussed to promote the diversified and integrated development of behavioral authentication.
Politicians in a nutshell: four-minute documentary portraits of three Israeli leaders
Authors: Adler Silvia , Kohn Ayelet
Published: March 2024

In 2011, a leading investigative television program in Israel launched a series of short documentaries entitled “Four Minutes,” each dedicated to an Israeli political leader. This paper focuses on three of these documentaries, dedicated to then-president Shimon Peres; then-Knesset member Tzipi Livni, who 2 years earlier had won the elections but failed to form a government, and Rabbi Ovadia Yosef, the founder of the Ultra-Orthodox Sephardi “Shas” party. Our goal is to outline the means by which these films construct and deliver their condensed messages, and to explore how, despite the rigid constraints of the format, they create a cohesive and complex portrait of these political figures and their strategic agendas. We analyze how the films’ multimodal language is used to reflect the messages promoted by each of the figures as well as by the filmmakers themselves.
Exploring the two-neutrino exchange potential
Authors: Green Leigh Ann
Published: March 2024

Quantum technologies and precision measurements could shed new light on the nature of neutrinos.
Terahertz characterization of nano-scale high-entropy alloy films and their high-contrast grating applications
Authors: Lu Chia-Yen , Sung Yi-Chen , Yeh Cheng-Hsien , Chen Yu-Hua , Kuan Chen-Yun , Hung Kuang-Teng , Chen Wei-Hsiang , Hsu Wen-Dung , Shih Chuan-Feng , Yang Chan-Shan
Published: March 2024

We investigated the optical constants of thin films of the Nb25Mo25Ta25W25 alloy, which belongs to high-entropy alloys (HEAs), with a transmission terahertz (THz) measurement system and discovered that the refractive index, extinction coefficient, and conductivity of the HEA thin film measured in the range of 0.3–1.0 THz all increased as the thickness of the thin film increased (the thickness was maintained in the range between 10 and 40 nm). According to the experimental results, this alloy with a high refractive index is suitable for producing high-contrast gratings (HCGs). The principle behind achieving a high contrast with a high-reflection HEA grating is to harness the confined plasmonic energy within the grating, thereby enhancing the localized plasmonic energy within the grating. This work elucidates that we can not only fabricate THz components by controlling the thickness of the thin film but also utilize the high refractive index of this material to create HCGs.
Tetrahexahedral binary transition metal compound sub-nanoclusters
Authors: Park Sung Jin , Li Siqi
Published: March 2024

We explore new transition metal (TM) compound sub-nanoclusters, TM8X6 (TM = Mn, Fe, Co and X = P, B, As), using density functional theory. Their optimized geometric structures show the same polyhedral structure (tetrahexahedron) independent of a kind of TM and metalloid (X), where eight TM atoms form a cubic structure capped with six metalloid (X) atoms. Incorporating an extra TM atom into the TM cubic results in an endohedral structure, TM9X6. Encapsulation of an additional TM atom merely changes the binding energy except for the Co boride cluster. The binding energy of Co8B6 increases by incorporating an additional Co atom, in which it is observed that the electron density is accumulated between B and all Co atoms (Co atoms both at the center and at the edges), but in other clusters, the electron excess is found mainly between TM atoms. The MnnP6 (n = 8 and 9) clusters have a high adiabatic electron affinity (>6 eV) due to the relatively large difference in electronegativity between Mn and P. The highest occupied molecular orbital and lowest unoccupied molecular orbital gaps of all clusters lie in the visible range. The interaction between nanoclusters and graphene with a single vacancy is studied as a function of the different cluster landing site on the graphene, where the geometric structure change of the clusters strongly depends on the adsorption site.
Dynamical evolution of the two-qubit system with Ising spin-chain environment
Authors: Han Qi , Wang Huan , Zhang Rong , Gou Lijie , Wang Shuai
Published: March 2024

In this article, we study the evolution of the two-qubit system with Ising spin-chain environment by choosing the Lindblad equation to describe this process. First, we expand the Hamiltonian of a two-qubit system with its eigenstates and give the Lindblad equation for the evolution of the two-qubit system with Ising spin-chain as the environment. Compared with directly calculating the differential equation between elements of density matrix, we choose a method to solve the Lindblad equation with a smaller calculation dimension. Finally, by constructing an operator solution with operators, we obtain the dynamics of the two-qubit system with Ising spin-chain environment.
Microstructure and mechanical properties of Cu–10Al–4Ni–4.8Fe with MoS2 content prepared by powder metallurgy
Authors: Shou Derong , Deng Zhenghua , Zhang Chaoyang , Yan Juan , Chen Xuhao
Published: March 2024

In this study, the effect of different amounts of molybdenum disulfide (MoS2) content on the microstructure and mechanical properties of Cu–10Al–4Ni–4.8Fe powder alloys was investigated. The results showed that the alloy initially consisted of KⅠ, KⅡ, KⅢ, and α phases without MoS2. However, when 2% MoS2 content was added, the lamellar Cu1.84Mo6S8 phase appeared in the alloy, and with increasing MoS2 content, the lamellar Cu1.84Mo6S8 phase and the number of pores increased. A gradual increase in the MoS2 content initially increased the sintered density, hardness, and yield strength of the alloy and then decreased. The sintered density and hardness reached their maximum values at 2% MoS2 content, while the yield strength reached its maximum value at 4% MoS2 content. With increasing MoS2 content, the friction coefficient fluctuated, while the wear loss decreased after first increasing. By applying the study results, the wear resistance of aluminum-bronze powder alloys can be improved to meet its rapidly growing industrial requirements.
On the local aspect of valley magnetic moments
Authors: Huang Zheng-Han , Chen Feng-Wu , Wu Yu-Shu G.
Published: March 2024

Valley magnetic moments play a crucial role in valleytronics in 2D hexagonal materials. Traditionally, insights drawn from the study of quantum states in homogeneous bulks have led to a widespread belief that only materials with broken structural inversion symmetry can exhibit nonvanishing valley magnetic moments. This belief, however, limits the scope of relevant applications, especially for materials with inversion symmetry, such as gapless monolayer graphene, despite its advantage in routine growth and production. This work revisits valley-derived magnetic moments in a broad context covering inhomogeneous structures as well. It generalizes the notion of a valley magnetic moment for a state from an integrated quantity to the local field called the “local valley magnetic moment” with space-varying distribution. It explores the local magnetic moment analytically both within the Dirac model and through a symmetry argument. Numerical investigations are conducted within the tight-binding model. Overall, we demonstrate that the breaking of inversion symmetry in the electron probability distribution leads to nonvanishing local magnetic moments. This probability-based breaking can occur in both structural inversion symmetric and symmetry-broken structures. In suitable inversion-symmetric structures with inhomogeneity, e.g., zigzag nanoribbons of gapless monolayer graphene, it is shown that the local moment of a state can be nonvanishing while the corresponding integrated moment is subject to the broken symmetry constraint. Moreover, it is demonstrated that the local moment can interact with space-dependent magnetic fields, resulting in field effects such as valley Zeeman splitting. Such effects can be exploited for local valley control as a conduit for the implementation of valleytronics.
An online wear metal particles monitoring warning sensor based on electromagnetic induction in lubricating oil
Authors: Tao Hui , Zhong Yong , Qian KangWei , Feng Wei
Published: March 2024

The online monitoring of metal particles in lubricating oil plays an important role in equipment fault diagnosis technology. This paper designs an online wear monitoring warning sensor based on the electromagnetic induction of metal particles in lubricating oil. First, different from the traditional three-coil sensing and detection method, the sensor consists of two excitation coils and one detection coil. In addition, the parallel capacitance and detection capacitance parameters are obtained by COMSOL’s scanning frequency, and the best detection capacitance is 7.53 nF. Second, according to the obtained optimal detection parallel capacitance value, the amplitude data of the particle signal, as well as the ferromagnetic particles above 60 µm and the non-ferromagnetic particles above 80 µm, are obtained. Third, according to the principle of three-coil induction, a mapping relationship model was established between the size range of metal wear particles in lubricating oil. Finally, we set up an oil wear particle platform to verify the sensor performance. The ferromagnetic and non-ferromagnetic particles are divided into multiple size ranges, and the peak-to-peak values of the output signal of different-sized wear particles are measured. We developed a prototype sensor and verified the signal consistency and repeatability of the sensor to wear metal particles. In addition, we used the sensor to test a large number of metal particles of different sizes (14 ferromagnetic particle standard samples with particle sizes ranging from 20.64 to 457.59 µm and ten non-ferromagnetic particle standard samples with particle sizes ranging from 40.52 to 348.07 µm). The experimental results show that the sensor can directly achieve monitoring sensitivity for ferromagnetic particles greater than 64.57 µm and non-ferromagnetic (copper) particles greater than 82.83 µm under the 4.2 mm aperture flow channel. The sensor can effectively realize the sensitivity on monitoring of small ferromagnetic particles and non-ferromagnetic particles, and it is particularly sensitive to small non-ferromagnetic particles.
Variation of magnetic properties with current in ferrimagnetic semiconductor Mn3Si2Te6
Authors: Zhang Zhixin , Liu Gan , Qi Wuyi , Xie Hangkai , Guo Jingwen , Du Yu , Wang Tianqi , Zhang Heng , Zhou Fuwei , Li Jiajun , Zhang Yiying , Yu Yefan , Fei Fucong , Xi Xiaoxiang , Song Fengqi
Published: March 2024

Orbital currents play a fundamental role in a wide range of transport phenomena. Recently, the discovery of a novel chiral orbital current state in the ferrimagnetic nodal-line semiconductor Mn3Si2Te6 has attracted significant interest, supported by anomalous I–V characteristics and time-dependent bistable switching. However, the direct experimental verifications, combining electrical transport and magnetic measurement, that detect the variation of the magnetic properties vs the current are still rare. Here, we investigate the transport properties of Mn3Si2Te6 and track the current-induced dynamics of the magnetic moment. Reflective magnetic circular dichroism reveals that significant alterations in Mn3Si2Te6 magnetoresistance in response to an electric field are necessarily coupled with a magnetic phase transition, establishing a rare correlation. Our findings indicate the predominance of magnetic chiral orbital currents in the colossal angular magnetoresistance effect, offering a unique platform for advanced studies in orbital magnetism.
Reconstitution of a biofilm adhesin system from a sulfate-reducing bacterium in
Pseudomonas fluorescens
Authors: Karbelkar Amruta A. , Font Maria , Smith T. Jarrod , Sondermann Holger , O’Toole George A.
Published: March 2024

Biofilms of sulfate-reducing bacterium (SRB) like
Desulfovibrio vulgaris
Hildenborough (DvH) can facilitate metal corrosion in various industrial and environmental settings leading to substantial economic losses. Although the mechanisms of biofilm formation by DvH are not yet well understood, recent studies indicate the large adhesin, DvhA, is a key determinant of biofilm formation. The
dvhA
gene neighborhood resembles the biofilm-regulating Lap system of
Pseudomonas fluorescens
but is curiously missing the c-di-GMP-binding regulator LapD. Instead, DvH encodes an evolutionarily unrelated c-di-GMP-binding protein (DVU1020) that we hypothesized is functionally analogous to LapD. To study this unusual Lap system and overcome experimental limitations with the slow-growing anaerobe DvH, we reconstituted its predicted SRB Lap system in a
P. fluorescens
strain lacking its native Lap regulatory components (Δ
lapG
Δ
lapD
). Our data support the model that DvhA is a cell surface–associated LapA-like adhesin with a N-terminal “retention module” and that DvhA is released from the cell surface upon cleavage by the LapG-like protease DvhG. Further, we demonstrate DVU1020 (named here DvhD) represents a distinct class of c-di-GMP-binding, biofilm-regulating proteins that regulates DvhG activity in response to intracellular levels of this second messenger. This study provides insight into the key players responsible for biofilm formation by DvH, thereby expanding our understanding of Lap-like systems.
Meaning in interaction
Authors: Deppermann Arnulf , De Stefani Elwys
Published: March 2024

This editorial to the Special Issue on “Meaning in Interaction” introduces to the approach of Interactional Semantics, which has been developed over the last years within the framework of Interactional Linguistics. It discusses how “meaning” is understood and approached in this framework and lays out that Interactional Semantics is interested in how participants clarify and negotiate the meanings of the expressions that they are using in social interaction. Commonalities and differences of this approach with other approaches to meaning are flagged, and the intellectual origins and precursors of Interactional Semantics are introduced. The contributions to the Special Issue are located in the larger field of research.
Looking at human healthcare to improve agricultural service delivery: The case of online chatgroups
Authors: Jomantas Sarunas , Wood Anna , Munthali Nyamwaya , Ochilo Willis , Thakur Manju , Romney Dannie , Kadzamira Mariam
Published: March 2024

This study analyses the opportunities and pitfalls of using chatgroups for plant health systems. It also examines the conditions for strengthening chatroom functions and considers the possibility of replicating reported successes in healthcare settings to plant health systems. We use mixed qualitative methods, which include stakeholder surveys and observation of chatgroup activity interactions in Ghana, Kenya, Uganda and Sri Lanka. Our findings show that there is evidence of the benefits of chatgroups to human health which can be replicated in plant health. Replication should, however, not be a ‘copy and paste’ approach. This is due to the general lack of evidence-based guidelines and lessons learned to move beyond the initial adoption success of communication applications. Also, in practice, plant doctor chatgroups are generally much larger than groups in healthcare settings and it remains to be seen whether increasing chatroom activity could benefit specific plant health objectives; or whether it would lead to increased labour costs, and/or diminish the participation of plant doctors.

One Health impact statement

The article is relevant in a One Health context as it demonstrates that there is a lot to learn between sectors about interventions and approaches. The work used literature from human health interventions to shed light on how a similar intervention in plant health functioned and could be improved. It shows that if actors in the plant health sector had engaged early on with actors in the human health sector, they may have avoided pitfalls in the ways that chatgroups can be used to support plant health management. It is expected that human, animal and plant health sectors would benefit from the knowledge and recommendations in this article to establish new online chatgroups that can support transformative change.
Fascin-induced bundling protects actin filaments from disassembly by cofilin
Authors: Chikireddy Jahnavi , Lengagne Léana , Le Borgne Rémi , Durieu Catherine , Wioland Hugo , Romet-Lemonne Guillaume , Jégou Antoine
Published: March 2024

Actin filament turnover plays a central role in shaping actin networks, yet the feedback mechanism between network architecture and filament assembly dynamics remains unclear. The activity of ADF/cofilin, the main protein family responsible for filament disassembly, has been mainly studied at the single filament level. This study unveils that fascin, by crosslinking filaments into bundles, strongly slows down filament disassembly by cofilin. We show that this is due to a markedly slower initiation of the first cofilin clusters, which occurs up to 100-fold slower on large bundles compared with single filaments. In contrast, severing at cofilin cluster boundaries is unaffected by fascin bundling. After the formation of an initial cofilin cluster on a filament within a bundle, we observed the local removal of fascin. Notably, the formation of cofilin clusters on adjacent filaments is highly enhanced, locally. We propose that this interfilament cooperativity arises from the local propagation of the cofilin-induced change in helicity from one filament to the other filaments of the bundle. Overall, taking into account all the above reactions, we reveal that fascin crosslinking slows down the disassembly of actin filaments by cofilin. These findings highlight the important role played by crosslinkers in tuning actin network turnover by modulating the activity of other regulatory proteins.
Nonadiabatic Holonomic Quantum Computation Based on Rydberg Ground State Blockade
Authors: Su 苏 Shi-Lei 石磊 , Wang 王 Chen 琛 , Song 宋 P.-Y. 佩瑶 , Chen 陈 Gang 刚
Published: March 2024

Quantum gates are crucial for quantum computation and quantum information processing. However, their effectiveness is often hindered by systematic errors and decoherence. Therefore, achieving resilient quantum gates to these factors is of great significance. We present a method to construct nonadiabatic holonomic single- and two-qubit gates in a Rydberg ground-state-blockade regime. Our approach utilizes a far-off-resonant technique for the single-qubit gate and a modified Rydberg antiblockade for the two-qubit gate. The reduction of the population of single- and two-excitation Rydberg states and the nonadiabatic holonomic process during the construction of the gates ensure robustness to decoherence and systematic errors, respectively. Numerical results demonstrate the fidelity and robustness of our scheme. The proposed scheme holds promise for future applications in quantum computation and quantum information processing tasks.
Emerging complexity in the self-dual theory of superconductivity
Authors: Sarmento M A , Córdoba-Camacho W Y , Shanenko A A , Vagov A , Albino Aguiar J , Stolyarov V S
Published: March 2024

To describe the way complexity emerges in seemingly simple systems of nature, requires one to attend to two principal questions: how complex patterns appear spontaneously and why a single system can accommodate their inexhaustible variety. It is commonly assumed the pattern formation phenomenon is related to the competition of several types of interactions with disparate length scales. These multi-scale interactions also lead to frustration within the system, resulting in the existence of a manifold of configurations-patterns with qualitatively distinct morphologies. This work explores an alternative approach through a mechanism that leads to a wide range of intricate and topologically non-trivial patterns. The mechanism is described by the self-dual Ginzburg-Landau theory and, possibly, other Maxwell–Higgs models. It gives rise to unique spatial flux and condensate spatial profiles observed in superconductors between the two conventional superconductivity types I and II.
Porous FeNi Prussian blue cubes derived carbon-based phosphides as superior sulfur hosts for high-performance lithium–sulfur batteries
Authors: Zhang Yulong , Wei Dan , Liu Yuelin , Li Shunan , Lei Wanying , He Xiaowei , Qiao Mingtao
Published: March 2024

In contrast to lithium-ion batteries, lithium–sulfur batteries have higher theoretical energy density and lower cost, so they would become competitive in the practical application. However, the shuttle effect of polysulfides and slow oxidation–reduction kinetics can degrade their electrochemical performance and cycle life. In this work, we have first developed the porous FeNi Prussian blue cubes as precursors. The calcination in different atmospheres was employed to make precursors convert into common pyrolysis products or novel carbon-based phosphides, and sulfides, labeled as FeNiP/A-C, FeNiP/A-P, and FeNiP/A-S. When these products serve as host materials in the sulfur cathode, the electrochemical performance of lithium–sulfur batteries is in the order of S@FeNiP/A-P > S@FeNiP/A-S > S@FeNiP/A-C. Specifically, the initial discharge capacity of S@FeNiP/A-P can reach 679.1 mAh g−1 at 1 C, and the capacity would maintain 594.6 mAh g−1 after 300 cycles. That is because the combination of carbon-based porous structure and numerous well-dispersed Ni2P/Fe2P active sites contribute FeNiP/A-P to obtain larger lithium-ion diffusion, lower resistance, stronger chemisorption, and more excellent catalytic effect than other samples. This work may deliver that metal–organic framework-derived carbon-based phosphides are more suitable to serve as sulfur hosts than carbon-based sulfides or common pyrolysis products for enhancing Li–S batteries’ performance.
Dynamic control of the Bose–Einstein-like condensation transition in scalar active matter
Authors: Berx Jonas
Published: March 2024

The dynamics of a generic class of scalar active matter exhibiting a diffusivity edge is studied in a confining potential where the amplitude is governed by a time-dependent protocol. For such non-equilibrium systems, the diffusion coefficient vanishes when the single-particle density field reaches a critical threshold, inducing a condensation transition that is formally akin to Bose–Einstein condensation. We show that this transition arises even for systems that do not reach a steady state, leading to condensation in finite time. Since the transition can be induced for a fixed effective temperature by evolving the system, we effectively show that the temporal coordinate constitutes an alternative control parameter to tune the transition characteristics. For a constant-amplitude protocol, our generalised thermodynamics reduces in the steady-state limit to earlier results. Lastly, we show numerically that for periodic modulation of the potential amplitude, the condensation transition is reentrant.
Diffusion of nanochannel-confined knot along a tensioned polymer*
Authors: Cai Guobing , Li Yong , Feng Yuyu , Deng Zhouhui , Liu Yanhui
Published: March 2024

The knots frequently occur in biopolymer and their diffusion plays an active role in the gene regulation. In this work, Langevin dynamics simulations were carried out to detect the diffusion behaviours of a knot along a tensioned polymer in different spatial constraints. The polymer accommodating a knot was tethered to two macrospheres to block the unravelling of the knot. As a result, the curves for the diffusion coefficients of the knot with different bending stiffness as a function of the tension in different spatial constraints were obtained. In the space without constraints or with weak constraints, the corresponding curves for the knot with relatively large bending stiffness exhibited two turnover behaviours. On the contrary, for the knot with relatively small bending stiffness, the diffusion coefficients were monotonically reduced with increasing tension. However, in a space with strong constraints, all the curves showed one turnover behaviour regardless of the bending stiffness. The turnover behaviours divided the curves into different regimes, and the dominant diffusion mechanisms in the regimes, namely, knot-region breathing, self-reptation, and internal friction, were clearly identified. The effective friction coefficients ξ of the knots with 31, 41, 51 and 52 types as a function of the knot size N at a fixed tension were well fitted by the relation ξ ∝ N. The effective friction coefficients of the knots at relatively large tension f > 3 sharply increased with the knot complexity, which is not dependent on the spatial constraints. By contrast, the values of these coefficients at relatively small tension f ≤ 3 were remarkably dependent on the spatial constraints. Our work not only provides valuable simulation results to assist the understanding of the diffusion of DNA knot, but also highlights the single-molecule design for the manipulation of DNA knots in future.
High-entropy alloys in thermoelectric application: A selective review
Authors: Ren 任 Kai 凯 , Huo 霍 Wenyi 文燚 , Chen 陈 Shuai 帅 , Cheng 程 Yuan 渊 , Wang 王 Biao 彪 , Zhang 张 Gang 刚
Published: March 2024

Since the superior mechanical, chemical and physical properties of high-entropy alloys (HEAs) were discovered, they have gradually become new emerging candidates for renewable energy applications. This review presents the novel applications of HEAs in thermoelectric energy conversion. Firstly, the basic concepts and structural properties of HEAs are introduced. Then, we discuss a number of promising thermoelectric materials based on HEAs. Finally, the conclusion and outlook are presented. This article presents an advanced understanding of the thermoelectric properties of HEAs, which provides new opportunities for promoting their applications in renewable energy.
High-frequency microwave cavity design for high-mass dark matter axion searches
Authors: Zhang 张 Chi 驰 , Wang 王 Jia 佳 , Li 李 Chunguang 春光 , Chen 陈 Shiguang 石广 , Cheng 程 Hang 航 , Sun 孙 Liang 亮 , Wu 吴 Yun 云
Published: March 2024

The haloscope based on the TM010 mode cavity is a well-established technique for detecting QCD axions. However, the method has limitations in detecting high-mass axion due to significant volume loss in the high-frequency cavity. Utilizing a higher-order mode cavity can effectively reduce the volume loss of the high-frequency cavity. The rotatable dielectric pieces as a tuning mechanism can compensate for the degradation of the form factor of the higher-order mode. Nevertheless, the introduction of dielectric causes additional volume loss. To address these issues, this paper proposes a novel design scheme by adding a central metal rod to the higher-order mode cavity tuned by dielectrics, which improves the performance of the haloscope due to the increased effective volume of the cavity detector. The superiority of the novel design is demonstrated by comparing its simulated performance with previous designs. Moreover, the feasibility of the scheme is verified by the full-wave simulation results of the mechanical design model.
Constraints on real scalar inflation from preheating using LATTICEEASY*
Authors: Cheng 程 Wei 伟 , Qin 秦 Tong 通 , Jiang 姜 Jiujiang 玖江 , Zhou 周 Ruiyu 瑞雨
Published: March 2024

In this paper, we undertake a detailed study of real scalar inflation using LATTICEEASY simulations to investigate preheating phenomena. Generally, the scalar inflation potential with non-minimal coupling can be approximated using a quartic potential. We observe that the evolutionary behavior of this potential remains unaffected by the coupling coefficient. Furthermore, the theoretical predictions for the scalar spectral index (

) and tensor-to-scalar power ratio (r) are independent of this coefficient. Consequently, the coefficients of this model are not constrained by Planck observations. Fortunately, the properties of preheating after inflation provide a viable approach to examining these coefficients. Through LATTICEEASY simulations, we trace the evolution of particle number density, scale factor, and energy density during the preheating process. Subsequently, we derive the parameters, such as the energy ratio (γ) and the e-folding number of preheating (

), which facilitate further predictions of

and r. We successfully validate real scalar inflation model using preheating in LATTICEEASY simulations based on the analytical relationship between preheating and inflation models.
Observational appearance and extra photon rings of an asymmetric thin-shell wormhole with a Bardeen profile*
Authors: He 何 Ke-Jian 柯腱 , Luo 罗 Zhi 智 , Guo 郭 Sen 森 , Li 李 Guo-Ping 国平
Published: March 2024

In this work, the optical appearance of an asymmetric thin-shell wormhole with a Bardeen profile is studied. To initiate the process, we need to construct an asymmetric thin-shell wormhole utilizing the cut-and-paste technique proposed by Visser and subsequently ascertain its pertinent physical quantities such as the radius of the photon sphere and critical impact parameters for different values of magnetic charge g. Then, the effective potential and motion behavior of photons are also investigated within the framework of asymmetric thin-shell wormholes with a Bardeen profile. It can be found that the effective potential, ray trajectory, and azimuthal angle of the thin-shell wormhole exhibit a strong correlation with the mass ratio of black holes. By considering the accretion disk as the sole background light source, we observe additional photon rings and lensing bands in the optical appearance of the asymmetric thin-shell wormhole with a Bardeen profile compared to those exhibited by the Bardeen black hole. One can find that there is an increase in the size of the specific additional light bands with increasing magnetic charge g, which is different from the black hole case. These exceptionally luminous rings can serve as a robust criterion for the identification and characterization of the thin-shell wormhole spacetime.
Overview of multiscale turbulence studies covering ion-to-electron scales in magnetically confined fusion plasma
Authors: Maeyama S. , Howard N.T. , Citrin J. , Watanabe T.-H. , Tokuzawa T.
Published: March 2024

Turbulent transport in magnetically confined fusion plasma has conventionally been analyzed at the ion gyroradius scale based on the microturbulence theory. However, ion-scale turbulence analysis sometimes fails to predict the turbulent transport flux observed experimentally. Microturbulence at the electron gyroradius scale and cross-scale interactions between disparate-scale turbulences are possible mechanisms to resolve this issue. This overview discusses the recent progress in multiscale turbulence studies and presents future perspectives from recent experimental, theoretical, and numerical investigations. The following aspects are highlighted: (1) the importance of electron-scale effects in experiments, (2) the physical mechanisms of cross-scale interactions, (3) modeling electron-scale effects in quasilinear transport models, and (4) the impacts of cross-scale interactions on burning plasmas. Understanding multiscale turbulence is necessary to improve performance prediction and explore optimal operations for future burning plasmas.
Naringenin roled octacalcium phosphate reinforced with polyvinyl alcohol composite for sarcoma affected bone repair
Authors: Lin Qiang , Wang Xuzheng , Jia Bin , Bai Minghua , Wang Kunzheng
Published: March 2024

Osteosarcoma is a rare cancer affecting disease for children and young adults; complete healing from this condition is quite difficult. Recently, new regeneration materials have been preferred, including natural compound companied implants for affected bone repair, and it is effectively used to treat osteosarcoma disease. Hence, Octa calcium phosphate (OCP) reinforced with poly (vinyl alcohol) (PVA) and oleic acid (OA) with Naringenin (NRG) composite was prepared and studied to cure the sarcoma affected bone. The physicochemical nature of the prepared OCP, PVA/OA/OCP, and PVA/OA/OCP/NRG composite were characterized by FT-IR, SEM, and XRD techniques. The in vitro release of the NRG from the PVA/OA/OCP/NRG composite was evaluated by UV-visible spectroscopy and the NRG release rate was observed at 98.0 % over 24 h. Biocompatibility and cell viability of the prepared OCP, PVA/OA/OCP, and PVA/OA/OCP/NRG composite are investigated in adipose-derived stem cells (ASCs) on different days. Interestingly, the PVA/OCP/OA/NRG composite shows an increase of 74.0 % to 92.0 % in cell survival, indicating that the composite is biocompatible. Similarly, the ability of NRG in the composite is to suppress cancer cells and it was determined in lung cancer (A549) cells. NRG-loaded PVA/OCP/OA/NRG shows good inhibition ability, nearly 43 % at 72 h. From the results, the prepared composite materials can inhibit cancer cells and be viable in stem cell growth. Since the materials will serve as potential regenerative materials for sarcoma-affected bone recovery.