bluuebunny/crossref_metadata_2025 huggingface dataset:
Electrochemical Exfoliation and Thermal Deoxygenation of Pristine Graphene for Various Industrial Applications
Authors: Singh Pankaj Kumar , Singh Pradeep Kumar
Published: September 2023

The transition of graphene from the lab to consumer goods is still a challenging job that necessitates efficient and cost-effective large-scale graphene production. This study combines electrochemical exfoliation in an aqueous solution of sulfuric acid (1M H2SO[Formula: see text] and hydrogen peroxide (3% H2O[Formula: see text] followed by thermal deoxygenation at a temperature of 800[Formula: see text]C within the ambient environment. This method allows the inexpensive synthesis of pristine graphene for various industrial applications. X-Ray diffraction (XRD) results for pristine graphene showed a distinct peak at 2[Formula: see text] with a corresponding interplanar distance ([Formula: see text] of 3.3754 Å and a crystallite size of 18 nm. XRD statistics indicated that the crystal structure of the original graphene was preserved. The crystalline structure was recovered and the interplaner distance was decreased following the high temperature thermal reduction. According to Raman spectroscopy, the impurity degree (I[Formula: see text]/I[Formula: see text] region fraction of pristine graphene was 0.211. This indicates that the original graph produced by the current method has little distortion. Raman analysis shows that there is a linear red shift in peaks D-band (D), G-band (G), and second order of the D-band (2D) due to the increase in phonon–phonon nonlinear interactions with increasing temperature, so that peaks (D), (G) and (2D) shifts are shown. The majority of the functional groups were discovered to be eliminated after high temperature thermal treatment. The three-dimensional graphene sheet is highly defined and intricately coupled in the microstructure analysis, resulting in a laxer and porous structure. When treated at a temperature below 800[Formula: see text]C, there was only minor damage to the reduced graphene oxide (RGO) microstructure. The results of the Atom Force Microscope (AFM) demonstrated that the flaws spread over time from the layer boundaries and pores to the edges and eventually resulted in a separate RGO archipelago. According to TGA analysis, at temperatures up to 800[Formula: see text]C, the RGO sheet loses up to 45% of its weight.
The analysis of deterministic and stochastic SIM model with general information intervention
Authors: Tan Yang , Yang Lin
Published: September 2023

In this paper, we propose an epidemic model with the impact of information intervention and general incidence rate in deterministic and stochastic environment, respectively. The information intervention prompts susceptible individuals to change their behavior to protect themselves from infection. First, the asymptotic dynamics of the disease-free equilibrium and the unique endemic equilibrium are analyzed and the results indicate that the basic reproduction number is a pointy disease threshold about the stability under some conditions. Then, we formulate the corresponding stochastic model by perturbing the disease transmission rate and information response rate parameters by white noise terms and provide verifiable sufficient conditions for extinction and persistence in mean. Two sufficient conditions for extinction show that if the noise intensity of the disease transmission rate is large enough or small enough, the infected population of the stochastic system will tend to go extinct. For the persistence, we get the sufficient conditions which guarantee the infected population to be persistent in the mean. Finally, we perform some numerical simulations to compare the dynamic behaviors of the deterministic and the stochastic system.
On metric dimension of nil-graph of ideals of commutative rings
Authors: Selvakumar K. , Petchiammal N.
Published: September 2023

Let [Formula: see text] be a commutative ring with identity and [Formula: see text] be the ideal of all nilpotent elements of [Formula: see text]. Let [Formula: see text] be a nontrivial ideal of [Formula: see text] and there exists a nontrivial ideal [Formula: see text] such that [Formula: see text] The nil-graph of ideals of [Formula: see text] is defined as the graph [Formula: see text] whose vertex set is the set [Formula: see text] and two distinct vertices [Formula: see text] and [Formula: see text] are adjacent if and only if [Formula: see text]. A subset of vertices [Formula: see text] resolves a graph [Formula: see text] and [Formula: see text] is a resolving set of [Formula: see text] if every vertex is uniquely determined by its vector of distances to the vertices of [Formula: see text] In particular, for an ordered subset [Formula: see text] of vertices in a connected graph [Formula: see text] and a vertex [Formula: see text] of [Formula: see text] the metric representation of [Formula: see text] with respect to [Formula: see text] is the [Formula: see text]-vector [Formula: see text] The set [Formula: see text] is a resolving set for [Formula: see text] if [Formula: see text] implies that [Formula: see text] for all pair of vertices, [Formula: see text] A resolving set [Formula: see text] of minimum cardinality is the metric basis for [Formula: see text] and the number of elements in the resolving set of minimum cardinality is the metric dimension of [Formula: see text] If [Formula: see text] for every pair [Formula: see text] of adjacent vertices of [Formula: see text] then [Formula: see text] is called a local metric set of [Formula: see text]. The minimum [Formula: see text] for which [Formula: see text] has a local metric [Formula: see text]-set is the local metric dimension of [Formula: see text] which is denoted by [Formula: see text]. In this paper, we determine metric dimension and local metric dimension of nil-graph of ideals of commutative rings.
Majority double Roman domination in graphs
Authors: Anandha Prabhavathy S. , Sahul Hamid I.
Published: September 2023

A majority double Roman dominating function (MDRDF) on a graph [Formula: see text] is a function [Formula: see text] such that (i) every vertex [Formula: see text] with [Formula: see text] is adjacent to at least two vertices assigned with 2 or to at least one vertex [Formula: see text] with [Formula: see text], (ii) every vertex [Formula: see text] with [Formula: see text] is adjacent to at least one vertex [Formula: see text] with [Formula: see text] and (iii) [Formula: see text], for at least half of the vertices in [Formula: see text]. The weight of an MDRDF is the sum of its function values over all vertices. The majority double Roman domination number of a graph [Formula: see text], denoted by [Formula: see text], is defined as [Formula: see text]. In this paper, we introduce and study the majority double Roman domination number on some classes of graphs.
More on independent transversal domination
Authors: Roushini Leely Pushpam P. , Priya Bhanthavi K.
Published: September 2023

A set [Formula: see text] of vertices in a graph [Formula: see text] is called a dominating set if every vertex in [Formula: see text] is adjacent to a vertex in [Formula: see text]. Hamid defined a dominating set which intersects every maximum independent set in [Formula: see text] to be an independent transversal dominating set. The minimum cardinality of an independent transversal dominating set is called the independent transversal domination number of [Formula: see text] and is denoted by [Formula: see text]. In this paper we prove that for trees [Formula: see text], [Formula: see text] is bounded above by [Formula: see text] and characterize the extremal trees. Further, we characterize the class of all trees whose independent transversal domination number does not alter owing to the deletion of an edge.
Fair detour domination of graphs
Authors: Parthipan J. Vijaya Xavier , Jeba Ebenezer D.
Published: September 2023

A set [Formula: see text] of a connected graph [Formula: see text] is called a fair detour dominating set if D is a detour dominating set and every two vertices not in D has same number of neighbors in D. The fair detour domination number, [Formula: see text], of G is the minimum cardinality of fair detour dominating sets. A fair detour dominating set of cardinality [Formula: see text] is called a [Formula: see text]-set of G. The fair detour domination number of some well-known graphs are determined. We have shown that, If G is a connected graph with [Formula: see text] and [Formula: see text] then [Formula: see text]. It is shown that for given positive integers [Formula: see text], [Formula: see text], [Formula: see text] such that [Formula: see text] there exists a connected graph G of order [Formula: see text] such that [Formula: see text] and [Formula: see text].
Classification of a class of A3MDS code and applications in secret-sharing schemes
Authors: Pandey Bandana , Paul Prabal
Published: September 2023

A [Formula: see text]-ary linear [Formula: see text] code [Formula: see text] is known as [Formula: see text] code. If [Formula: see text] the code is called a maximum distance separable code. [Formula: see text] codes are known to be useful in the secret-sharing schemes and coding theory. In this paper, we classify all binary self-orthogonal [Formula: see text] codes. We have introduced a subclass of [Formula: see text] codes, called [Formula: see text] codes, to form a special type of secret-sharing scheme where for any participant, there exist [Formula: see text] other participants who can collectively reveal the secret by combining their shares and there exists another set of [Formula: see text] participants including the given participant, who cannot reveal the secret.
Nature and Causes of Economic Fluctuations: Evidence from the U.S. Based on a Nonlinear Autoregressive Integrated Process
Authors: Li Xiang , He Zonglu
Published: September 2023

Business cycles and economic growth have long been studied separately, hindering understanding of the nature and causes of economic fluctuations and growth. Here, we present an economic model that incorporates both deterministic trends and persistent fluctuations, derived from a general economic data generation process obtained using the dimensionless nonlinear autoregressive integrated (NLARI) process. To explore the nature and causes of economic fluctuations and growth, we develop a unified test to identify whether the economic data generation mechanism is stable fixed points, unit roots, cyclical oscillations, or chaos. Empirical studies show that as the economic resilience coefficient changes from strong to weak, the data-generating mechanism for U.S. economic indicators shifts from a stable fixed point (dynamic equilibrium) in the supply-side economy to an unstable unit root (divergence) in the demand-side economy involving income distribution. Therefore, the U.S. economy is in partial dynamic equilibrium of the supply-side economy. The low resilience of the demand-side economy allows for the accumulation of noise from exogenous shocks, leading to persistent fluctuations. We find that the economic deterministic trend is ([Formula: see text]/[Formula: see text])[Formula: see text], i.e., time [Formula: see text] multiplied by the ratio of the mean of exogenous supply, demand, and technological progress investment shocks to the economic resistance coefficient. A general dynamic equilibrium economy maximizes growth from investment by avoiding [Formula: see text] growth losses from permanently persistent fluctuations. Thus, ([Formula: see text]/[Formula: see text])[Formula: see text] is the maximum value obtained along the maximum profit growth at the von Neumann equilibrium price. The investment path that creates the maximum ratio [Formula: see text]/[Formula: see text] is the optimal growth path.
A Minimalistic Approach to Predict and Understand the Relation of App Usage with Students' Academic Performance
Authors: Ahmed Md Sabbir , Rony Rahat Jahangir , Hadi Mohammad Abdul , Hossain Ekram , Ahmed Nova
Published: September 2023

Due to usage of self-reported data which may contain biasness, the existing studies may not unveil the exact relation between academic grades and app categories such as Video. Additionally, the existing systems' requirement for data of prolonged period to predict grades may not facilitate early intervention to improve it. Thus, we presented an app that retrieves past 7 days' actual app usage data within a second (Mean=0.31s, SD=1.1s). Our analysis on 124 Bangladeshi students' real-time data demonstrates app usage sessions have a significant (p<0.05) negative association with CGPA. However, the Productivity and Books categories have a significant positive association whereas Video has a significant negative association. Moreover, the high and low CGPA holders have significantly different app usage behavior. Leveraging only the instantly accessed data, our machine learning model predicts CGPA within ±0.36 of the actual CGPA. We discuss the design implications that can be potential for students to improve grades.
A Mobile Augmented Reality App for Creating, Controlling, Recommending Automations in Smart Homes
Authors: Mattioli Andrea , Paternò Fabio
Published: September 2023

Automations in the context of smart homes have been adopted more and more frequently; thus, users should be able to control them and create automations most suitable to their needs. Current solutions for this purpose are based on visual apps with conceptual representations of possible automation elements. However, they tend to be static, abstract, and detached from the user's real context. In this paper, we propose a novel solution based on mobile augmented reality, which provides situated, dynamic representations associated with the physical objects available in the current users' context while they are freely moving about. It allows direct interaction with the objects of interest, monitoring nearby objects' automations while moving, and creating new automations or modifying existing ones. It also supports users with recommendations of object and service configurations relevant to complete the editing of the new automations. The paper also reports on a user test, which provided positive feedback.
Beyond Hiding and Revealing: Exploring Effects of Visibility and Form of Interaction on the Witness Experience
Authors: Uhde Alarith , Zum Hoff Tim , Hassenzahl Marc
Published: September 2023

Our interactions with technology do not just shape our individual experiences. They also affect people around us. Although previous research has addressed such "witness" experiences, the actual effect of interaction design on the witness experience remains largely unknown. In an online study (n = 407), we explored how witnesses perceive mid-air gesture-based interactions with a hearing aid, using four video vignettes. We studied witnesses' subjective visibility of manipulations and effects (following Reeves and colleagues' taxonomy), perceived form of interaction, subjective experience, and relationships between these measures. Although visibility patterns matched the intended form, they did not lead to the supposed experience (i.e., "suspenseful" gestures did not lead to suspenseful experiences). The paper illustrates gaps in current research about witness experiences, demonstrates the need to overcome basic hiding/revealing profiles, and indicates a path forward by focusing on aesthetic forms and experiences.
Effects of Urgency and Cognitive Load on Interaction in Highly Automated Vehicles
Authors: Colley Mark , Evangelista Cristina , Rubiano Tito Daza , Rukzio Enrico
Published: September 2023

In highly automated vehicles, passengers can engage in non-driving-related activities. Additionally, the technical advancement allows for novel interaction possibilities such as voice, gesture, gaze, touch, or multimodal interaction, both to refer to in-vehicle and outside objects (e.g., thermostat or restaurant). This interaction can be characterized by levels of urgency (e.g., based on late detection of objects) and cognitive load (e.g., because of watching a movie or working). Therefore, we implemented a Virtual Reality simulation and conducted a within-subjects study with N=11 participants evaluating the effects of urgency and cognitive load on modality usage in automated vehicles. We found that while all modalities were possible to use, participants relied on touch the most. This was followed by gaze, especially for external referencing. This work helps to further understand multimodal interaction and the requirements this poses on natural interaction in (automated) vehicles.
My Eyes Speak: Improving Perceived Sociability of Autonomous Vehicles in Shared Spaces Through Emotional Robotic Eyes
Authors: Wang Yiyuan , Wijenayake Senuri , Hoggenmüller Marius , Hespanhol Luke , Worrall Stewart , Tomitsch Martin
Published: September 2023

The ability of autonomous vehicles (AVs) to interact socially with pedestrians poses a significant impact on their integration with urban traffic. This is particularly important for vehicle-pedestrian shared spaces due to increased social requirements in comparison to vehicular roads. Current pedestrian experience in shared spaces suffers from negative attitudes towards AVs and the consequently low acceptability of AVs in these spaces. HRI work shows that the acceptability of robots in public spaces can be positively impacted by their perceived sociability (i.e., possessing social skills), which can be enhanced by their ability to express emotions. Inspired by this approach, we follow a systematic process to design emotional expressions for AVs using the headlight ("eye'') area and investigate their impact on perceived sociability of AVs in shared spaces, by conducting expert focus groups (N=12) and an online video-based user study (N=106). Our findings confirm that the perceived sociability of AVs can be enhanced by emotional expressions indicated through emotional eyes. We further discuss implications of our findings for improving pedestrian experience and attitude in shared spaces and highlight opportunities to use AVs' emotional expressions as a new external communication strategy for future research.
RingVKB: A Ring-Shaped Virtual Keyboard Using Low-Cost IMU
Authors: Li Zhenjiang , Zhang Xinglin , Wu Chenshu
Published: September 2023

Wearable devices have been important components for ubiquitous computing. However, text input remains challenging on wearables due to the lack of a physical keyboard. In this paper, we propose a novel ring-shaped virtual keyboard system named RingVKB for convenient text input using low-cost IMUs available on any wearables. At the core of RingVKB are two novel designs: 1) A circular keyboard layout with 12 equal sectors, which assembles all common keys on classical keyboards while allowing users to type with only one finger effectively, and 2) an error control algorithm that calculates the relative displacement of keystrokes from the noisy IMU sensor data. The two components, coupled together, enable high-accuracy and efficient text input for ubiquitous scenarios.We implement RingVKB using a small device consisting of a microcontroller and a MEMS sensor, which can be attached to the user's index finger.Experimental results show that RingVKB can effectively improve the relative displacement estimation accuracy, and achieves an overall keystroke recognition accuracy of 93% for 25 key positions. A user study also shows that RingVKB is easy to learn and use. Using only low-cost IMU sensors, RingVKB provides a virtual keyboard solution that can be widely adopted on wearables.
Scanning or Simply Unengaged in Reading? Opportune Moments for Pushed News Notifications and Their Relationship with Smartphone Users' Choice of News-reading Modes
Authors: Lin Chen-Chin , Wu Chia-Chen , Huang Ping-Ju , Lai Yu-Hsin , Ho Yi-Ting , Chung Chih-Chi , Chang Yung-Ju
Published: September 2023

News notifications on smartphones provide a convenient way to stay informed, but their delivery timing can influence user engagement. Despite this, research on the impact of notification timing on reading behavior remains limited. Therefore, we developed NewsMoment, a news aggregation app that monitors user reading patterns and sends news notifications. Our experience sampling study with 46 NewsMoment users revealed four distinct reading modes: typical, comprehensive, scanning, and unengaged. Deep reading, encompassing typical and comprehensive modes, more often occurred during self-initiated browsing rather than through pushed news. Interestingly, shallow reading modes - unengaged and scanning - showed varying prevalence, associated triggers, and engagement, despite their similarities. Importantly, unengaged reading persisted regardless of users' perceived moment opportuneness, whereas scanning reading was more common during inopportune moments. These findings suggest that identifying opportune moments for news reading may primarily reduce scanning reading, without substantially impacting unengaged reading.
Senior Technology Learning Preferences Model for Mobile Technology
Authors: Sharifi Hasti , Chattopadhyay Debaleena
Published: September 2023

Far more older adults are using mobile devices now than a decade ago. However, the applications they use continue to lag in depth (features) and breadth (diversity). Despite the large body of research on designing technology with older adults and identifying their adoption difficulties, we know little about how older users prefer to learn or troubleshoot mobile technology following an initial adoption and ownership. In this paper, we first review the existing models of technology adoption by older adults that consider learning as a factor and discuss their limitations. Then we interview older adults who use mobile technology (n = 23) and younger adults who help them (n = 17), to identify how older adults prefer to learn and troubleshoot nowadays. Our participants represent three different cultures, North American, South Asian, and Middle Eastern. Findings suggest that in addition to mobile device proficiency, older adults' technology identity---different from their attitude toward technology---determines their learning preferences. We identify two types of learning preferences: self-exploration and social learning, and two types of support, general and social. Social support plays a role in both social learning and learning by self-exploration. Finally, we propose the senior technology learning preferences model for mobile technology (STELE) to describe how different learning preferences and support types influence older adults' mobile technology acceptance and use.
ViGather: Inclusive Virtual Conferencing with a Joint Experience Across Traditional Screen Devices and Mixed Reality Headsets
Authors: Qiu Huajian , Streli Paul , Luong Tiffany , Gebhardt Christoph , Holz Christian
Published: September 2023

Teleconferencing is poised to become one of the most frequent use cases of immersive platforms, since it supports high levels of presence and embodiment in collaborative settings. On desktop and mobile platforms, teleconferencing solutions are already among the most popular apps and accumulate significant usage time---not least due to the pandemic or as a desirable substitute for air travel or commuting.

In this paper, we present ViGather, an immersive teleconferencing system that integrates users of all platform types into a joint experience via equal representation and a first-person experience. ViGather renders all participants as embodied avatars in one shared scene to establish co-presence and elicit natural behavior during collocated conversations, including nonverbal communication cues such as eye contact between participants as well as body language such as turning one's body to another person or using hand gestures to emphasize parts of a conversation during the virtual hangout. Since each user embodies an avatar and experiences situated meetings from an egocentric perspective no matter the device they join from, ViGather alleviates potential concerns about self-perception and appearance while mitigating potential 'Zoom fatigue', as users' self-views are not shown. For participants in Mixed Reality, our system leverages the rich sensing and reconstruction capabilities of today's headsets. For users of tablets, laptops, or PCs, ViGather reconstructs the user's pose from the device's front-facing camera, estimates eye contact with other participants, and relates these non-verbal cues to immediate avatar animations in the shared scene.

Our evaluation compared participants' behavior and impressions while videoconferencing in groups of four inside ViGather with those in Meta Horizon as a baseline for a social VR setting. Participants who participated on traditional screen devices (e.g., laptops and desktops) using ViGather reported a significantly higher sense of physical, spatial, and self-presence than when using Horizon, while all perceived similar levels of active social presence when using Virtual Reality headsets. Our follow-up study confirmed the importance of representing users on traditional screen devices as reconstructed avatars for perceiving self-presence.
Exploiting Partially Context-sensitive Profiles to Improve Performance of Hot Code
Authors: Vukasovic Maja , Prokopec Aleksandar
Published: September 2023

Availability of profiling information is a major advantage of just-in-time (JIT) compilation. Profiles guide the compilation order and optimizations, thus substantially improving program performance. Ahead-of-time (AOT) compilation can also utilize profiles, obtained during separate profiling runs of the programs. Profiles can be context-sensitive, i.e., each profile entry is associated with a call-stack. To ease profile collection and reduce overheads, many systems collect partially context-sensitive profiles, which record only a call-stack suffix. Despite prior related work, partially context-sensitive profiles have the potential to further improve compiler optimizations.

In this article, we describe a novel technique that exploits partially context-sensitive profiles to determine which portions of code are hot and compile them with additional compilation budget. This technique is applicable to most AOT compilers that can access partially context-sensitive profiles, and its goal is to improve program performance without significantly increasing code size. The technique relies on a new hot-code-detection algorithm to reconstruct hot regions based on the partial profiles. The compilation ordering and the inlining of the compiler are modified to exploit the information about the hot code. We formally describe the proposed algorithm and its heuristics and then describe our implementation inside GraalVM Native Image, a state-of-the-art AOT compiler for Java. Evaluation of the proposed technique on 16 benchmarks from DaCapo, Scalabench, and Renaissance suites shows a performance improvement between 22% and 40% on 4 benchmarks, and between 2.5% and 10% on 5 benchmarks. Code-size increase ranges from 0.8%–9%, where 10 benchmarks exhibit an increase of less than 2.5%.
An Efficient FPGA-based Depthwise Separable Convolutional Neural Network Accelerator with Hardware Pruning
Authors: Liu Zhengyan , Liu Qiang , Yan Shun , Cheung Ray C. C.
Published: September 2023

Convolutional neural networks (CNNs) have been widely deployed in computer vision tasks. However, the computation and resource intensive characteristics of CNN bring obstacles to its application on embedded systems. This article proposes an efficient inference accelerator on Field Programmable Gate Array (FPGA) for CNNs with depthwise separable convolutions. To improve the accelerator efficiency, we make four contributions: (1) an efficient convolution engine with multiple strategies for exploiting parallelism and a configurable adder tree are designed to support three types of convolution operations; (2) a dedicated architecture combined with input buffers is designed for the bottleneck network structure to reduce data transmission time; (3) a hardware padding scheme to eliminate invalid padding operations is proposed; and (4) a hardware-assisted pruning method is developed to support online tradeoff between model accuracy and power consumption. Experimental results show that for MobileNetV2 the accelerator achieves 10× and 6× energy efficiency improvement over the CPU and GPU implementation, and 302.3 frames per second and 181.8 GOPS performance that is the best among several existing single-engine accelerators on FPGAs. The proposed hardware-assisted pruning method can effectively reduce 59.7% power consumption at the accuracy loss within 5%.
Meaning-Sensitive Text Data Augmentation with Intelligent Masking
Authors: Kasthuriarachchy Buddhika , Chetty Madhu , Shatte Adrian , Walls Darren
Published: September 2023

With the recent popularity of applying large-scale deep neural network-based models for natural language processing (NLP), attention to develop methods for text data augmentation is at its peak, since the limited size of training data tends to significantly affect the accuracy of these models. To this end, we propose a novel text data augmentation technique called Intelligent Masking with Optimal Substitutions Text Data Augmentation (IMOSA). IMOSA, developed for labelled sentences, can identify the most favourable sentences and locate the appropriate word combinations in a particular sentence to replace and generate synthetic sentences with a meaning closer to the original sentence, while also significantly increasing the diversity of the dataset. We demonstrate that the proposed technique notably improves the performance of classifiers based on attention-based transformer models through the extensive experiments for five different text classification tasks which are performed under the low data regime in a context-aware NLP setting. The analysis clearly shows that IMOSA effectively generates more sentences using favourable original examples and completely ignores undesirable examples. Furthermore, the experiments carried out confirm IMOSA’s ability to add diversity to the augmented dataset using multiple distinct masking patterns against the same original sentence, which remarkably adds variety to the training dataset. IMOSA consistently outperforms the two key masked language model-based text data augmentation techniques, and demonstrates a robust performance against the critical challenging NLP tasks.
Complex Scenario Image Retrieval via Deep Similarity-aware Hashing
Authors: Nie Xiushan , Shi Yang , Meng Ziyu , Huang Jin , Guan Weili , Yin Yilong
Published: September 2023

When performing hashing-based image retrieval, it is difficult to learn discriminative hash codes especially for the multi-label, zero-shot and fine-grained settings. This is due to the fact that the similarities vary, even within the same category, under the conditions of complex scenario settings. To address this problem, this study develops a deep similarity-aware hashing method for complex scenario image retrieval (DEPISH). DEPISH more focuses on the samples that are difficult to distinguish from other images (i.e., “difficult samples”), such as images that contain multiple semantics. It dynamically divides attention among samples according to their difficulty levels with a margin weighting strategy. Furthermore, by adding special terms in the model, DEPISH is capable of avoiding the inconsistency between the hash code representation and true similarity among negative samples. In addition, unlike the existing methods that use a pre-defined similarity matrix with fixed values, the DEPISH adopts an adaptive similarity matrix, which accurately captures the various similarities among all samples. The results of our experiment on multiple benchmark datasets containing complex scenarios (i.e., multi-label, zero-shot, and fine-grained datasets) verify the effectiveness of this method.
Biodiversity: A Conversation with Sir Partha Dasgupta
Authors: Dasgupta Partha , Besley Tim
Published: September 2023

This conversation with Sir Partha Dasgupta, moderated by Annual Review of Economics Editorial Commitee Member Tim Besley, focuses on biodiversity and its implications for economic thought and policy. A video of this interview is available online at https://www.annualreviews.org/r/partha_dasgupta_interview.
Micro Propagation and Macro Aggregation
Authors: Baqaee David , Rubbo Elisa
Published: September 2023

This article reviews a framework for studying the aggregation and propagation of microeconomic shocks in general equilibrium. We discuss the determinants of aggregate measures of real economic activity, like real GDP, real domestic absorption, and aggregate productivity in both efficient and inefficient environments. We also discuss how shocks from one set of producers are transmitted to other producers through prices and quantities. The framework we provide is amenable to generalization and can be used to study any collection of producers ranging from one isolated producer to an industry consisting of heterogeneous producers to an entire economy. We conclude with a brief survey of some of the applied questions that can be addressed using the analytical tools presented in this review and avenues for future work.
Non-CES Aggregators: A Guided Tour
Authors: Matsuyama Kiminori
Published: September 2023

The constant-elasticity-of-substitution (CES) aggregator and its demand system are ubiquitous in business cycles theory, macroeconomic growth and development, international trade and other general equilibrium fields; this is because the CES aggregator has many knife-edge properties that help to keep the analysis tractable in the presence of many goods and factors. However, this also makes it hard to tell which properties of CES are responsible for certain results. Furthermore, it is necessary to relax some of those properties for certain applications. In this article, I review several classes of non-CES aggregators, each of which removes some properties of CES and keeps the rest to introduce some flexibility while retaining the tractability of CES as much as possible. These classes are named after the properties of CES they keep. I explain how these classes are related to each other and discuss their relative strengths and weaknesses to indicate which classes are suited for which applications.
On Capacitance Enhancement at Decreasing Pore Width and its Relation with Solvent Concentration and Polarity
Authors: Zhou Shiqi
Published: September 2023

Classical density functional theory is used to study the capacitance enhancing issue of electrical double-layer using aqueous-like electrolyte and ionic liquid+solvent mixture (ILSM) as supporting electrolyte, respectively. The polar organic solvent and water-like solvent are described by an electric dipole dimer model. This study focuses on capacitance enhancing of counter-ion sized electrode pore (CISEP) relative to large pore capacitance and relation with electrode voltage applied, counter-ion relative size, solvent weight percentage in the bulk and its polarity depicted by electric dipole moment.
The Effect of Chlorides on the Performance of DME/Mg[B(HFIP)4]2 Solutions for Rechargeable Mg Batteries
Authors: Dlugatch Ben , Drews Janina , Attias Ran , Gavriel Bar , Ambar Adar , Danner Timo , Latz Arnulf , Aurbach Doron
Published: September 2023

One of the major issues in developing electrolyte solutions for rechargeable magnesium batteries is understanding the positive effect of chloride anions on Mg deposition-dissolution processes on the anode side, as well as intercalation-deintercalation of Mg2+ ions on the cathode side. Our previous results suggested that Cl− ions are adsorbed on the surface of Mg anodes and Chevrel phase MgxMo6S8 cathodes. This creates a surface add-layer that reduces the activation energy for the interfacial Mg ions transportation and related charge transfer, as well as promotes the transport of Mg2+ from the solution phase to the Mg anode surface and into the cathodes’ host materials. Here, this work further examines the effect of adding chlorides to the state-of-the-art Mg[B(HFIP)4]2/DME electrolyte solution, specifically focusing on reversible magnesium deposition, as well as the performance of Mg cells with benchmark Chevrel phase cathodes. It was observed that the presence of chlorides in these solutions facilitates both Mg deposition, and Mg2+ ions intercalation, whereby this effect is more pronounced as the purity level of the solution is lowered.
Electrochemical Characterization and Micromachining of Nitinol SMA by WECM Using Citric Acid Mixed H2SO4 Electrolyte
Authors: Besekar Naresh , Bhattacharyya B.
Published: September 2023

Nitinol shape memory alloy (SMA) is a tough material to machine because it is difficult to cut. The results of the current research work demonstrate how two different electrolytes affect the electrochemical behavior in relation to electrochemical machining performance of nitinol. Potentiodynamic polarisation (PDP) and electrochemical impedance spectroscopy (EIS) tests have been conducted using 0.1 M H2SO4 and mixed 0.1 M H2SO4 + 0.1 M citric acid electrolyte. Further, the experimental investigation on the machining characteristics of nitinol during wire electrochemical machining (WECM) has been conducted. It is revealed that the grooves width and depth increase with increase in applied pulse voltage and surface roughness increase with increase in groove depth. The minimum width overcut of machined groove was 18.10 μm in 0.1 M H2SO4 + 0.1 M citric acid at 5 V pulse voltage which is less compared to width overcut of 24.85 μm produced in 0.1 M H2SO4 electrolyte for same parametric machining condition. This specific mixed electrolyte produced average surface roughness (Ra) of 0.0631 μm at 5 V which is lower compared to 0.09055 μm produced using 0.1 M H2SO4 electrolyte. The fabrication of homogeneous average slit width of 92.234 μm using citric acid mixed H2SO4 electrolyte with minimum average surface roughness (Ra) of 0.0691 μm shows the capability of WECM.
Adipocyte STAT5 (signal transducer and activator of transcription 5) is not required for glucocorticoid-induced metabolic dysfunction
Authors: Harvey Innocence , Richard Allison J. , Mendoza Tamra M. , Stephens Jacqueline M.
Published: September 2023

Both STAT5 and glucocorticoid receptor contribute to metabolic processes and type 2 diabetes, in large part, due to their functions in adipocytes. These two transcription factors can form a complex and function together. Our novel studies determined the role of adipocyte STAT5 in glucocorticoid-induced diabetes. We observed that STAT5 in adipocytes is not needed for glucocorticoid-induced diabetes.
3,6′-Disinapoyl sucrose alleviates cognitive deficits in APP/PS1 transgenic mice
Authors: Yuan Jiaqi , He Mengjie , Dai Xueling , Huo Qing , Chang Ping , Zhang Jing , Wang Shuo , Sun Yaxuan
Published: September 2023

In this study, for the first time, DISS was used in APP/PS1 transgenic mice to explore its neuroprotective effect. After gavage DISS for 1 mo, the impairment of learning and spatial memory ability and the loss of neurons in APP/PS1 mice were alleviated. DISS reduced a neuroprotective effect in AD mice via decreasing neuronal apoptosis, enhancing the expressions of CREB phosphorylation and BDNF, pointing to DISS as a new therapeutic target for AD.
Long-term dance training modifies eye-head coordination in response to passive head impulse
Authors: Moin-Darbari Karina , Nooristani Mujda , Bacon Benoit-Antoine , Champoux François , Maheu Maxime
Published: September 2023

This study demonstrates, for the first time, that long-term dance training results in a nonlinear relationship between eye and head velocity within the first milliseconds following passive head impulse. The data also suggest a larger VOR gain in dancers. This finding suggests that dance training may modify eye-head relationship in passive high-frequency head movements. This is of particular interest for vestibular rehabilitation.
Dynamic spinal reflex adaptation during locomotor adaptation
Authors: Refy Omar , Blanchard Belle , Miller-Peterson Abigail , Dalrymple Ashley N. , Bedoy Ernesto H. , Zaripova Amelia , Motaghedi Nadim , Mo Owen , Panthangi Shalini , Reinhart Alex , Torres-Oviedo Gelsy , Geyer Hartmut , Weber Douglas J.
Published: September 2023

This work presents direct evidence for spinal reflex modulation during locomotor adaptation. In particular, we show that reflexes can be modulated on-demand unilaterally during split-belt locomotor adaptation and speculate about reflex modulation as an underlying mechanism for adaptation of gait asymmetry in healthy adults.
Sound processing in the cricket brain: evidence for a pulse duration filter
Authors: Zhang Xinyang , Hedwig Berthold
Published: September 2023

Pulse period selectivity has been reported for the cricket delay-line and coincidence detector network, whereas pulse duration selectivity is evident from behavioral tests. Pulses of increasing duration elicit responses in the pattern recognition neurons, which do not parallel the behavioral responses and indicate additional processing mechanisms. Long sound pulses elicit rhythmic rebound activity and additional bursts, whereas the feature detector neuron reveals a pulse duration filter, expanding our understanding of the pattern recognition process.
Mathematical Modeling for Optimal Management of Human Resources in Banking Sector of Bangladesh
Authors: Mallick Uzzwal Kumar , Biswas Md. Haider Ali
Published: September 2023

A new mathematical model on human resources divided employees into two compartments, namely, fresher and expert employees, has been designed and analyzed. A system of ordinary nonlinear differential equations has three state variables including vacancies. This model describes the dynamics of the number of fresher employees and expert employees as well as vacancies and shows the impacts of training programs and benefits of provided facilities for employees. The equilibria of this proposed model are determined, and its stability at these points is checked. Moreover, characteristics of state variables with respect to parameters have been discussed. Using two optimal control variables, this study finds the maximum number of experts including the minimum cost of provided facilities as well as the training program based on Pontryagin’s maximum principle.
Time to Recovery from COVID-19 and Its Predictors in Patients Hospitalized at Tibebe Ghion Specialized Hospital Care and Treatment Center, A Retrospective Follow-Up Study, North West Ethiopia
Authors: Habtamu Tamiru Desiyalew , Gedef Azene Abebaw , Wudie Tsegaye Gebeyaw , Mulatu Mihretie Kebadnew , Hunegnaw Asmare Samuel , Arega Gete Wudneh , Animen Bante Simachew
Published: September 2023

Background. Since the end of 2019, the world has been facing a new coronavirus disease 19 (COVID-19), which is considered a global pandemic. COVID-19 is considered a major public health burden due to the uncontrolled morbidity and mortality of the global community. The World Health Organization estimates the recovery time as 2 weeks for patients with mild infection and 3 to 6 weeks for those with serious illnesses. The recovery time and its predictors are not well studied in Ethiopia yet. Therefore, the aim of this study was to estimate time to recovery from COVID-19 and its predictors among COVID-19 patients admitted to Tibebe Ghion Specialized Hospital care and treatment center, North West Ethiopia. Methods. An institution-based retrospective follow-up study was conducted among 452 COVID-19 patients admitted to Tibebe Ghion Specialized Hospital from March 2020 to September 2021. Simple random sampling using a table of random number generators was used to select study units. Data entry and analysis were performed using EpiData 3.1 and Stata version 14, respectively. Bivariable and multivariable Cox proportional hazard analyses were used to identify predictors of recovery time. An AHR at a 5% level of significance was used to identify significant predictors. Results: Among 452 COVID-19 patients, 437 (88%) were recovered, with a median recovery time of 9 days. Recovery time was significantly related to age (AHR = 0.98; 95% CI = 0.97, 0.99), oxygen saturation (AHR = 0.42; 95% CI = 0.31, 0.56), shortness of breath (AHR = 0.65; 95% CI = 0.47, 0.85), disease severity (moderate (AHR = 0.63; 95% CI = 0.47, 0.85) and severe (AHR = 0.32; 95% CI = 0.22, 0.47)), and comorbidities (AHR = 0.67; 95% CI = 0.53, 0.84). Conclusions and recommendations: The overall median recovery time was 9 days. Older age, low oxygen saturation, shortness of breath, disease severity (moderate and severe), history of comorbidities, and high-level of WBC were predictors of delayed recovery time. On the other hand, corticosteroid use significantly shortens the median recovery time of COVID-19 patients. Thus, patients presented with older age, low oxygen saturation, shortness of breath, moderate and severe COVID-19 disease, comorbidities, and increased WBC need to be closely monitoring and followed up by healthcare providers. In addition, there should be special attention during the administration of corticosteroid.
Results on Solutions for Several Systems of Partial Differential-Difference Equations with Two Complex Variables
Authors: Chen Yuxian , Xie Libing , Xu Hongyan
Published: September 2023

This article is to describe the entire solutions of some partial differential-difference equations and systems. Some theorems about the forms of transcendental entire solutions with finite order for several high-order partial differential-difference equations (or systems) of the Fermat type with two complex variables are obtained. Moreover, some examples are provided to explain that our results are precise to some extent.
Intercept Guidance of Maneuvering Targets with Deep Reinforcement Learning
Authors: Hu Zhe , Xiao Liang , Guan Jun , Yi Wenjun , Yin Hongqiao
Published: September 2023

In this paper, a novel guidance law based on a reinforcement learning (RL) algorithm is presented to deal with the maneuvering target interception problem using a deep deterministic policy gradient descent neural network. We take the missile’s line-of-sight (LOS) rate as the observation of the RL algorithm and propose a novel reward function, which is constructed with the miss distance and LOS rate to train the neural network off-line. In the guidance process, the trained neural network has the capacity of mapping the missile’s LOS rate to the normal acceleration of the missile directly, so as to generate guidance commands in real time. Under the actor-critic (AC) framework, we adopt the twin-delayed deep deterministic policy gradient (TD3) algorithm by taking the minimum value between a pair of critics to reduce overestimation. Simulation results show that the proposed TD3-based RL guidance law outperforms the current state of the RL guidance law, has better performance to cope with continuous action and state space, and also has a faster convergence speed and higher reward. Furthermore, the proposed RL guidance law has better accuracy and robustness when intercepting a maneuvering target, and the LOS rate is converged.