bluuebunny/crossref_metadata_2025 huggingface dataset:
Nonsmooth Pitchfork Bifurcations in a Quasi-Periodically Forced Piecewise-Linear Map
Authors: Jorba Àngel , Tatjer Joan Carles , Zhang Yuan
Published: May 2024

We study a family of one-dimensional quasi-periodically forced maps [Formula: see text], where [Formula: see text] is real, [Formula: see text] is an angle, and [Formula: see text] is an irrational frequency, such that [Formula: see text] is a real piecewise-linear map with respect to [Formula: see text] of certain kind. The family depends on two real parameters, [Formula: see text] and [Formula: see text]. For this family, we prove the existence of nonsmooth pitchfork bifurcations. For [Formula: see text] and any [Formula: see text] there is only one continuous invariant curve. For [Formula: see text] there exists a smooth map [Formula: see text] such that: (a) For [Formula: see text], [Formula: see text] has two continuous attracting invariant curves and one continuous repelling curve; (b) For [Formula: see text] it has one continuous repelling invariant curve and two semi-continuous (noncontinuous) attracting invariant curves that intersect the unstable one in a zero-Lebesgue measure set of angles; (c) For [Formula: see text] it has one continuous attracting invariant curve. The case [Formula: see text] is a degenerate case that is also discussed in the paper. It is interesting to note that this family is a simplified version of the smooth family [Formula: see text] for which there is numerical evidence of a nonsmooth pitchfork bifurcation. Finally, we also discuss the limit case when [Formula: see text].
Global Stabilization of a Bounded Controlled Lorenz System
Authors: Martínez Pérez Héctor , Solís-Daun Julio
Published: May 2024

In this work, we present a method for the Global Asymptotic Stabilization (GAS) of an affine control chaotic Lorenz system, via admissible (bounded and regular) feedback controls, where the control bounds are given by a class of (convex) polytopes. The proposed control design method is based on the control Lyapunov function (CLF) theory introduced in [Artstein, 1983; Sontag, 1998]. Hence, we first recall, with parameters including those in [Lorenz, 1963], that these equations are point-dissipative, i.e. there is an explicit absorbing ball [Formula: see text] given by the level set of a certain Lyapunov function, [Formula: see text]. However, since the minimum point of [Formula: see text] does not coincide with any rest point of Lorenz system, we apply a modified solution to the “uniting CLF problem” (to unify local (possibly optimal) controls with global ones, proposed in [Andrieu & Prieur, 2010]) in order to obtain a CLF [Formula: see text] for the affine system with minimum at a desired equilibrium point. Finally, we achieve the GAS of “any” rest point of this system via bounded and regular feedback controls by using the proposed CLF method, which also contains the following controllers: (i) damping controls outside [Formula: see text], so they collaborate with the beneficial stable free dynamics, and (ii) (possibly optimal) feedback controls inside [Formula: see text] that stabilize the control system at “any” desired rest point of the (unforced) Lorenz system.
Measuring Public Preferences for Strategic Choices in an Era of Great Power Competition: Taiwan as a Case Study
Authors: LEE KUAN-CHEN
Published: May 2024

As the U.S.-China relationship tilts toward competition and confrontation, scholars and policymakers have focused on the strategic choices faced by the citizens of small and medium-sized countries caught between the two great powers. However, methodological deficiencies remain in how public preferences for these strategic choices are measured. This paper attempts to fill this gap by developing a new means of measuring public opinion regarding strategic choices. Using survey data collected in Taiwan in March 2023, we demonstrate how this measure is constructed and why it aligns more closely with the theoretical concept of strategic choices. Our findings indicate that preferences for different strategies in Taiwan follow a U-shaped distribution that is centered either on hedging with the United States or with China. Multivariate analyses show that factors such as the threat of China, the U.S. security commitment to Taiwan, skepticism toward the United States, confidence in Taiwan’s military, and partisanship are all correlated with public preferences for different strategies. This paper helps us understand these preferences among citizens in small and medium-sized countries and contributes to the literature on public opinion, international relations theory, and policymaking.
GROWING AN INFORMAL DIGITAL MICRO-ENTERPRISE: THE ROLE OF INDIVIDUAL ENTREPRENEURIAL ORIENTATION AND SOCIAL CAPITAL
Authors: TOP MODOU , ZHI YANG
Published: May 2024

This research examines the effects of individual entrepreneurial orientation (IEO) on informal sector digital micro-enterprise growth in developing countries and the moderating role of networking social capital. The majority of EO research on company growth has focused on registered traditional SMEs and larger enterprises in higher-income markets. A total of 248 informal online micro-enterprises from Senegal were studied. The findings show that IEO has distinct effects on informal digital microbusiness development. Individual risk-taking boosts digital micro-enterprise growth, whereas inventive behaviour hinders it. Proactiveness does not seem to increase growth. Different social capital’s moderating effects on IEO dimensions and online micro-enterprise growth are also found. This study is one of the first to examine individual entrepreneurial behaviour that may lead to the growth of informal digital micro-businesses and the differentiated role of SC. It has also expanded business contextualisation to better comprehend IEO in informal online micro-enterprises outside developed countries.
HUMAN JUDGMENT IN ARTIFICIAL INTELLIGENCE FOR BUSINESS DECISION-MAKING: AN EMPIRICAL STUDY
Authors: CHANDA ARUN KUMAR
Published: May 2024

The deployment of AI systems has increased across several industries as they exhibit progressively stronger predictive performance. Due to safety, moral, and legal considerations, full automation is frequently undesirable. However, fully manual methods might be erroneous and time-consuming. The idea of using AI to support human decision-making is therefore gaining popularity in the scientific community. The flourishing subject of AI decision-making needs to embrace empirical methodologies in addition to building AI technologies for that purpose to establish a solid understanding of how people interact and collaborate with AI to make decisions. This research intends to analyse how artificial intelligence uses human judgment for decision-making in business. Researchers gathered survey results from high-tech employees in India via email, media, and other means. The sample size was 196, and the sampling strategy most likely employed was convenience sampling. With the data collected measurement and structural model are performed and found that artificial intelligence-based decision-making impacts the organizations’ business value and artificial intelligence capability impacts the organization created with the moderating effect of business intelligence. Also, it is concluded that AI-based decision-making impacts knowledge management.
Improving Faithfulness and Factuality with Contrastive Learning in Explainable Recommendation
Authors: Zhuang Haojie , Zhang Wei , Chen Weitong , Yang Jian , Sheng Quan Z.
Published: May 2024

Recommender systems have become increasingly important in navigating the vast amount of information and options available in various domains. By tailoring and personalizing recommendations to user preferences and interests, these systems improve the user experience, efficiency, and satisfaction. With a growing demand for transparency and understanding of recommendation outputs, explainable recommender systems have gained growing attention in recent years. Additionally, as user reviews could be considered the rationales behind why the user likes (or dislikes) the products, generating informative and reliable reviews alongside recommendations has thus emerged as a research focus in explainable recommendation. However, the model-generated reviews might contain factually inconsistent contents (i.e., the hallucination issue), which would thus compromise the recommendation rationales. To address this issue, we propose a contrastive learning framework to improve the faithfulness and factuality in explainable recommendation in this article. We further develop different strategies of generating positive and negative examples for contrastive learning, such as back-translation or synonym substitution for positive examples, and editing positive examples or utilizing model-generated texts for negative examples. Our proposed method optimizes the model to distinguish faithful explanations (i.e., positive examples) and unfaithful ones with factual errors (i.e., negative examples), which thus drives the model to generate faithful reviews as explanations while avoiding inconsistent contents. Extensive experiments and analysis on three benchmark datasets show that our proposed model outperforms other review generation baselines in faithfulness and factuality. In addition, the proposed contrastive learning component could be easily incorporated into other explainable recommender systems in a plug-and-play manner.
Comparing Statistical, Analytical, and Learning-Based Routing Approaches for Delay-Tolerant Networks
Authors: D'Argenio Pedro R. , Fraire Juan , Hartmanns Arnd , Raverta Fernando
Published: May 2024

In delay-tolerant networks (DTNs) with uncertain contact plans, the communication episodes and their reliabilities are known a priori. To maximise the end-to-end delivery probability, a bounded network-wide number of message copies are allowed. The resulting multi-copy routing optimization problem is naturally modelled as a Markov decision process with distributed information. In this paper, we provide an in-depth comparison of three solution approaches: statistical model checking with scheduler sampling, the analytical RUCoP algorithm based on probabilistic model checking, and an implementation of concurrent Q-learning. We use an extensive benchmark set comprising random networks, scalable binomial topologies, and realistic ring-road low Earth orbit satellite networks. We evaluate the obtained message delivery probabilities as well as the computational effort. Our results show that all three approaches are suitable tools for obtaining reliable routes in DTN, and expose a trade-off between scalability and solution quality.
BUNNI: Learning Repair Actions in Rule-driven Data Cleaning
Authors: Mecca Giansalvatore , Papotti Paolo , Santoro Donatello , Veltri Enzo
Published: May 2024

In this work, we address the challenging and open problem of involving non-expert users in the data repairing problem as first-class citizens. Despite a large number of proposals that have been devoted to cleaning data from the point of view of expert users (IT staff and data scientists), there is a lack of studies from the perspective of non-expert ones. Given a set of available data quality rules, we exploit machine learning techniques to guide the user to identify the dirty values for each violation and repair them. We show that with a low user effort, it is possible to identify the values in tuples that can be trusted and the ones that are most likely errors. We show experimentally how this machine learning approach leads to a unique clean solution with high quality in scenarios where other approaches fail.
MizBERT: A Mizo BERT Model
Authors: Lalramhluna Robert , Dash Sandeep , Pakray Dr.Partha
Published: May 2024

This research investigates the utilization of pre-trained BERT transformers within the context of the Mizo language. BERT, an abbreviation for Bidirectional Encoder Representations from Transformers, symbolizes Google’s forefront neural network approach to Natural Language Processing (NLP), renowned for its remarkable performance across various NLP tasks. However, its efficacy in handling low-resource languages such as Mizo remains largely unexplored. In this study, we introduce
MizBERT
, a specialized Mizo language model. Through extensive pre-training on a corpus collected from diverse online platforms,
MizBERT
has been tailored to accommodate the nuances of the Mizo language. Evaluation of
MizBERT’s
capabilities is conducted using two primary metrics: masked language modeling and perplexity, yielding scores of 76.12% and 3.2565, respectively. Additionally, its performance in a text classification task is examined. Results indicate that
MizBERT
outperforms both the Multilingual BERT model and the Support Vector Machine algorithm, achieving an accuracy of 98.92%. This underscores
MizBERT’s
proficiency in understanding and processing the intricacies inherent in the Mizo language.
Thinking in Categories: A Survey on Assessing the Quality for Time Series Synthesis
Authors: Stenger Michael , Bauer André , Prantl Thomas , Leppich Robert , Hudson Nathaniel , Chard Kyle , Foster Ian , Kounev Samuel
Published: May 2024

Time series data are widely used and provide a wealth of information for countless applications. However, some applications are faced with a limited amount of data, or the data cannot be used due to confidentiality concerns. To overcome these obstacles, time series can be generated synthetically. For example, electrocardiograms can be synthesized to make them available for building models to predict conditions such as cardiac arrhythmia without leaking patient information. Although many different approaches to time series synthesis have been proposed, evaluating the quality of synthetic time series data poses unique challenges and remains an open problem, as there is a lack of a clear definition of what constitutes a “good” synthesis. To this end, we present a comprehensive literature survey to identify different aspects of synthesis quality and their relationships. Based on this, we propose a definition of synthesis quality and a systematic evaluation procedure for assessing it. With this work, we aim to provide a common language and criteria for evaluating synthetic time series data. Our goal is to promote more rigorous and reproducible research in time series synthesis by enabling researchers and practitioners to generate high-quality synthetic time series data.
Comparison of Triglyceride–Glucose (TyG) Index and Homeostatic Model Assessment of Insulin Resistance (HOMA‐IR) Index in Prediction of Male Hypogonadism
Authors: Hazir Berk , Salonia Andrea , Giwercman Aleksander , Elenkov Angel
Published: May 2024

Several studies have shown the association between decreased insulin sensitivity and the risk of male hypogonadism. Homeostatic model assessment of insulin resistance (HOMA‐IR) is a well‐established marker of decreased insulin sensitivity. The triglyceride–glucose index (TyG), calculated as ln (fasting triglyceride (mg/dL) ×  fasting glucose (mg/dL)/2), was recently suggested to be a cheaper and a reliable surrogate marker to detect insulin resistance (IR). Our aim was to compare the performance of those two indexes in the prediction of male hypogonadism. The data on 192 men from infertile couples (18–50 years; sperm concentration <20 x 106/mL) and 199 population‐based matched controls collected during the years 2009–2012 (baseline) were evaluated retrospectively. Half of these subjects (72 subfertile men and 122 controls) were reinvestigated 5–10 years later (median year (range): 7 (5–10)). The patients receiving any hormonal therapy were excluded. Hypogonadism was defined as fasting, morning serum testosterone below 12 nmol/L. In receiver operating characteristic curve analysis, the optimal diagnostic cutoff values for baseline HOMA‐IR and TyG to predict MetS at re‐examination were 2.68 (Area Under Curve (AUC) = 0.886, p < 0.001) and 8.60 (AUC = 0.816, p  < 0.001), respectively. Moreover, in binary logistic regression analysis performed on the whole cohort using these thresholds for high values of HOMA‐IR and high TyG, the odds‐ratios (ORs) for hypogonadism were 6.48 (95% Confidence Interval (CI): 3.77–11.2; p  < 0.001) and 3.58 (95% CI: 2.17–5.94; p  < 0.001), respectively. Even though high HOMA‐IR levels provided better risk estimates, high TyG was also highly related to the risk of hypogonadism. These markers can be utilized to identify men being at high risk of hypogonadism.
Rapid, Efficient, and Universally Applicable Genetic Engineering of Intestinal Organoid with a Sequential Monolayer to Three‐Dimensional Strategy
Authors: Han Weili , Lu Guofang , Zhao Sheng , Wang Rui , Zhang Haohao , Liu Kun , Nie Yongzhan , Dong Jiaqiang
Published: May 2024

Genetically modified intestinal organoids are being explored as potential surrogates of immortalized cell lines and gene‐engineered animals. However, genetic manipulation of intestinal organoids is time‐consuming, and the efficiency is far beyond satisfactory. To ensure the yield of the genetically modified organoids, large quantity of starting materials is required, and the procedure usually takes more than 10 days. Two major obstacles that restrict the genetic delivery efficiency are the three‐dimensional culture condition and that the genetic delivery is carried out in cell suspensions. In the present study, we introduce a novel highly efficient strategy for building genetically modified intestinal organoids in which genetic delivery was performed in freshly established monolayer primary intestinal epithelial cells under two‐dimensional conditions and subsequentially transformed into three‐dimensional organoids. The total procedure can be finished within 10 hr while displaying much higher efficiency than the traditional methods. Furthermore, this strategy allowed for the selection of transgenic cells in monolayer conditions before establishing high‐purity genetically modified intestinal organoids.
Effect of Nonpharmaceutical Interventions in Preventing COVID‐19 on the Circulation of Avian Influenza Virus in Wuhan, Hubei Province, China
Authors: Wu Yixuan , Kong Wenhua , Zhang Yijie , Lu Sha , Liu Manqing
Published: May 2024

Background. In late 2019, several medical institutions in Wuhan, Hubei Province, China, reported cases of unexplained pneumonia. A novel coronavirus was isolated from human airway epithelial cells causing coronavirus disease‐2019 (COVID‐19). In recent years, many nonpharmaceutical interventions (NPIs) have been implemented to stop COVID‐19 epidemic. This study aimed to explore the effect of NPIs on the circulation of avian influenza virus (AIV) in Wuhan. Materials and Methods. External environmental samples were collected and subjected to viral RNA extraction. Real‐time quantitative polymerase chain reaction was used to detect the H5, H7, and H9 subtypes of AIV. Statistical analyses were performed using the chi‐square test and binary logistic regression in SPSS 20.0 software. Results. A total of 2,451 external environmental samples were collected from seven districts from 2018 to 2022 in Wuhan, comprising 1,041 samples collected before COVID‐19 and 1,410 samples after COVID‐19. After COVID‐19, the positive rate of AIV decreased significantly with the implementation of NPIs. The dominant subtype was the H9 subtype, followed by the H5 subtype. The positive rates of AIV in live poultry markets and poultry free‐range sites were reduced significantly through the implementation of NPIs. Among the different sample types, higher positive rates of AIV were found in chopping boards, sewage, and cages. The positive rate of AIV was higher in trafficked source samples than that in autotrophic source samples. Conclusions. This study identified the characteristics of AIV in terms of different districts, surveillance sites, sample types, and bird sources in Wuhan. This study conducted a multifactorial analysis of the factors affecting AIV infection and provided a theoretical basis and guidance for the future prevention and control of AIV in Wuhan.
Study on the Solutions of Impulsive Integrodifferential Equations of Mixed Type Based on Infectious Disease Dynamical Systems
Authors: Li Haiyan , Guo Yuheng , Wang Min
Published: May 2024

Since ancient times, infectious diseases have been a major source of harm to human health. Therefore, scientists have established many mathematical models in the history of fighting infectious diseases to study the law of infection and then analyzed the practicability and effectiveness of various prevention and control measures, providing a scientific basis for human prevention and research of infectious diseases. However, due to the great differences in the transmission mechanisms and modes of many diseases, there are many kinds of infectious disease dynamic models, which make the research more and more difficult. With the continuous progress of infectious disease research technology, people have adopted more ways to prevent and interfere with the derivation and spread of infectious disease, which will make the state of infectious disease system change in an instant. The mutation of this state can be described more scientifically and reasonably by the mathematical impulse dynamic system, which makes the research more practical. Based on this, a time-delay differential system model of infectious disease under impulse effect was established by means of impulse differential equation theory. A class of periodic boundary value problems for impulsive integrodifferential equations of mixed type with integral boundary conditions was studied. The existence of periodic solutions of these equations was obtained by using the comparison theorem, upper and lower solution methods, and the monotone iteration technique. Finally, combined with the practical application, the established time-delay differential system model was applied to the prediction of the stability and persistence of the infectious disease dynamic system, and the correctness of the conclusion was further verified. This study provides some reference for the prevention and treatment of infectious diseases.
Phytochemical Analysis, Antioxidant Potential and Antibacterial Activities of Different Anatomical Parts of Hypericum cordifolium Choisy
Authors: Sapkota Sujana , Maharjan Alishma , Tiwari Sanjeeta , Rajbhandari Meena
Published: May 2024

The genus Hypericum comprises a large number of species. The flower, leaf, stem, and root of the Hypericum species are widely used in traditional medicine in different cultures. Many Hypericum species have been well investigated phytochemically and pharmacologically. However, only a few reports are available on the H. cordifolium native to Nepal. The present study aims to evaluate the phytochemical composition of different extracts, qualitative analysis of methanol extract of the flower and leaf using thin-layer chromatography (TLC), and the antioxidant properties of components by the TLC-DPPH. assay. The phenolic and flavonoid contents were estimated in different extracts of the leaf and stem, and their antioxidant and antibacterial activities were evaluated. In the phytochemical screening, phenolics and flavonoids were present in ethyl acetate, methanol, and 50% aq methanol extracts of both the leaf and stem. In TLC analysis, the methanol extract of flowers showed the presence of 11 compounds and the leaf extract showed the presence of 8 compounds. Both extracts contained chlorogenic acid and mangiferin. Hyperoside and quercetin were present only in the flower extract. In the TLC-DPPH. assay, almost all of the flower extracts and 5 compounds of the leaf extract showed radical scavenging potential. Estimation of phenolics and flavonoids showed that all the leaf extracts showed higher amounts of phenolics and flavonoids than stem extracts. Among leaf extracts, greater amounts of phenolics were detected in 50% aqueous methanol extract (261.25 ± 1.66 GAE/g extract) and greater amounts of flavonoids were detected in methanol extract (232.60 ± 10.52 CE/g extract). Among stem extracts, greater amounts of flavonoids were detected in the methanol extract (155.12 ± 4.30 CE/g extract). In the DPPH radical scavenging assay, the methanol extract of the leaf showed IC50 60.85 ± 2.67 µg/ml and 50% aq. methanol extract of the leaf showed IC50 63.09 ± 2.98 µg/ml. The methanol extract of the stem showed IC50 89.39 ± 3.23 µg/ml, whereas ethyl acetate and 50% aq. methanol extract showed IC50 > 100 µg/ml. In the antibacterial assay, the methanol extract of the leaf showed the inhibition zone of 12-13 mm and the stem extract showed the inhibition zone of 7–11 mm against S. aureus, E. coli, and S. sonnei, whereas both extracts were inactive against S. typhi. The findings of this study support the traditional use of this plant in Nepal for the treatment of diseases associated with bacterial infections. The present study revealed that the underutilized anatomical parts of H. cordifolium could be the source of various bioactive phytochemicals like other Hypericum species.
Structure Elucidation of a Novel Polysaccharide Isolated from Euonymus fortunei and Establishing Its Antioxidant and Anticancer Properties
Authors: Luo Yu , Chen Hongtao , Huang Chunxi , He Shujia , Wen Qilong , Cai Danzhao
Published: May 2024

Euonymusfortunei polysaccharides (EFPs) have not been extensively investigated yet in terms of their extraction and biological activity. The orthogonal experimental design was employed in this study to evaluate the optimum yield of EFPs. A maximum yield of 2.63 ± 0.23% was attained using material-liquid ratios of 60 mL/g, extraction temperature of 80°C, ultrasonic power of 144 W, and extraction time of 75 mins. The polysaccharide content reached 53.47 ± 0.31% when deproteinized thrice. An analysis of monosaccharide composition revealed that these polysaccharides consist of Gal, Glc, Man, Fuc, and Rha with a molar ratio of 7.14 ∶ 23.99 ∶ 6.29 ∶ 6.55 ∶ 1.00, respectively, in EFPs. Subsequently, the in vitro scavenging capacities of 2,2-diphenylpicrylhydrazyl (DPPH) and ·OH and superoxide anion radicals, along with the reducing power of EFPs, were studied. Results revealed that EFPs have higher antioxidant activity, particularly ·OH scavenging, as well as reducing power, as compared to Astragalus polysaccharides (ASPs) and Lycium barbarum polysaccharides (LBPs). The Cell Counting Kit-8 (CCK-8) method was used to evaluate the effects of different concentrations of polysaccharides on SKOV3 cell proliferation, and the results revealed their inhibition at concentrations in the range of 200–800 μg/mL. In addition, findings from flow cytometry further confirmed that EFPs blocked the cell cycle at G0/G1 and S phases and induced SKOV3 cell apoptosis. In a word, EFPs could be exploited and used further based on the experimental results from this study.
Effectiveness of Using Gum Arabic for Co-Microencapsulation of Ruellia tuberosa L. and Tithonia diversifolia Extracts as Encapsulating Agent and Release Studies
Authors: Almayda Nabila , Masruri Masruri , Safitri Anna
Published: May 2024

This study used a combination of leaves extracts from Ruellia tuberosa L. and Tithonia diversifolia plants encapsulated using gum Arabic. The selection of leaves in medicinal plants because they are rich in bioactive compounds that provide health benefits. The encapsulation technique was microencapsulation through freeze-drying, since the nanoencapsulation for the plant extracts is unlikely to be conducted due to their large particle sizes. The resulting microcapsules were then tested their biological activities in vitro. Several conditions affect microcapsules’ production, including pH, gum Arabic concentration, and stirring time were assessed. The optimum conditions were chosen based on the highest encapsulation efficiency. The results showed that the optimum microcapsules preparation was achived at pH 5, gum Arabic concentration of 4% (w/v), and stirring time of 60 min with an encapsulation efficiency of 84.29%. The in vitro assays include inhibition of alpha-amylase and antioxidant activities, resulted in the respective IC50 values of 54.74 μg/mL and 152.74 μg/mL. Releases of bioactive compounds from the microcapsules were investigated under pH 2.2 and pH 7.4 from 30 to 120 min. Results indicated a release of 43.10% at pH 2.2 and 42.26% at pH 7.4 during 120 min, demonstrating the controlled release behavior of the encapsulated bioactive compounds; nonetheless, their release behavior was not pH-dependent. This study confirms that microencapsulation has an important role in the development of plant extracts with maintained biological functions as well as maintaining their stability.
Multi-UAV Cooperative Air Combat Target Assignment Method Based on VNS-IBPSO in Complex Dynamic Environment
Authors: Li Yiyuan , Chen Weiyi , Liu Shukan , Yang Guang , He Fan
Published: May 2024

This paper investigates the threat assessment method and target assignment algorithm in multi-UAV cooperative air combat decision-making. To address the uncertainty and dynamic changes in multiple threat attributes and attribute information of UAV targets, we propose a UAV target dynamic threat assessment method based on intuitionistic fuzzy multiattribute decision-making. Firstly, we propose a mixed situation information representation method to represent interval-valued fuzzy data appropriately. Secondly, we employ the normal distribution weight assignment method to fuse the multi-time situation information. Then, by incorporating the analytic hierarchy process and entropy method, we determine the normalized threat value of the target considering both objective situation data characteristics and decision-maker preferences. Finally, a simulation example is provided to validate the rationality of our proposed algorithm. For solving the multi-weapon multi-target assignment problem, a target assignment method based on the VNS-IBPSO algorithm is introduced. This method improves upon the limitations of the BPSO algorithm, such as limited local search capability and premature convergence, by combining variable neighborhood search and an improved binary particle swarm optimization algorithm. Simulation results show that the proposed threat assessment method can obtain reasonable threat assessment results under complex dynamic environments. The proposed VNS-IBPSO algorithm can solve the target assignment model quickly and efficiently based on the assessment results, therefore ensuring that the UAV mission planning system makes the correct combat plan.
Individual behavioural variation does not affect social organization or reproductive success in a cooperative small mammal
Authors: van der Marel Annemarie , Johnson Nicholas E. , Grillo Sara , Riquelme Juan , Vásquez Rodrigo A. , Gillam Erin H. , Ebensperger Luis A. , Hayes Loren D.
Published: May 2024

Recent evidence indicates that individual behavioural variation in animals, defined as consistent individual differences in behaviour across contexts and time, influence ecological and evolutionary processes, and a growing number of studies demonstrate that individual behavioural variation can play a large role in shaping grouping dynamics among social animals. We studied the common degu, Octodon degus, a social rodent, to evaluate whether individual behavioural variation underlies social organization and the reproductive success of individuals within groups. We examined social groups in a population in central-north Chile during one breeding season, tested 67 adults in an open field test (i.e., the propensity to explore an unfamiliar environment) and 62 adults in a poke test (i.e., the propensity to charge an object) to quantify individual behavioural variation, determined assortment based on individual behavioural differences across 19 social groups, and performed genetic analyses to assess reproductive success. We found that the response to the poke test was repeatable, while none of the behaviours from an open field test were. The repeatable behaviour during the poke test was not associated to components of social organization (group composition), or to reproductive success. These findings imply that individual behavioural variation did not affect grouping patterns or direct fitness in this degu population.
The influence of conspecific and heterospecific neighbours on avian reproductive success
Authors: Joly Stephen F. , McKellar Ann E. , Mahoney Sean M. , Flood Nancy J. , Möller Raven , Shaikh Mateen R. , Reudink Matthew W.
Published: May 2024

We investigated the influence of conspecific and heterospecific neighbours on the reproductive success of mountain bluebirds (Sialia currucoides) and tree swallows (Tachycineta bicolor) over eight breeding seasons. The abundance of heterospecific neighbours was negatively associated with reproductive success in mountain bluebirds but positively associated with reproductive success in tree swallows during the early nesting period (i.e., hatching rate). For bluebirds, conspecific and heterospecific neighbour abundance was associated with higher reproductive success (i.e., fledging rate) during the later stages of the nesting period; the same was true for conspecific abundance for tree swallows. These findings could be explained by either positive behavioural interactions (e.g., shared defence) or by habitat quality. We found contrasting effects of nearest neighbour distance. For both mountain bluebirds and tree swallows, having a tree swallow neighbour in close proximity was positively associated with reproductive success during the early nesting period, while having a mountain bluebird neighbour in close proximity was negatively associated with reproductive success during the late nesting period for mountain bluebirds. Together, these results indicate that the effects of conspecific and heterospecific neighbours on reproductive success are species-specific and vary depending on the phase of reproduction.
Inositol-6-phosphate mitigates deoxynivalenol nephrotoxicity in pig kidney explants
Authors: Suhett W.G. , Gerez J.R. , Hohmann M.S. , Staurengo-Ferrari L. , Verri W.A. , Pinho F.H.O. , de Barros L.D. , Flaiban K.K. , Bracarense A.P.F.R.L.
Published: May 2024

Deoxynivalenol (DON) is a mycotoxin that frequently contaminates food crops and negatively impacts human and animal health. While inositol-6-phosphate (IP6) is known to counteract DON-induced intestinal damage, inflammation, and oxidative stress, its ability to alleviate DON-caused kidney injury is yet unexplored. This study assessed DON’s kidney effects and IP6’s protective capability using an ex vivo renal explants model. From 360 explants taken from six pigs, four groups were formed: control (culture medium), DON (10 μM equivalent to 3 mg/kg of feed), IP6 group (5 mM), and DON + IP6 (10 μM + 5 mM). DON elevated creatinine levels and γ-glutamyl transferase activity in the culture medium. It led to cytoplasmic vacuolation in convoluted tubular epithelial cells and tubular necrosis, a drop in antioxidant potential (ABTS) and a rise in interleukin (IL)-8 mRNA. The introduction of IP6 restored renal histological and functional parameters, bolstered antioxidant status, enhanced IL-10 gene expression, and reduced superoxide anion levels. These results indicate that within the model of renal explants, IP6 significantly alleviates the nephrotoxic effects of DON while efficiently regulating the antioxidative and anti-inflammatory response within the kidneys.
No evidence that Mycoplasma infection causes cognitive impairment during foraging in Allenby’s gerbil (Gerbillus andersoni allenbyi)
Authors: Goeppner Scott R. , Sargunaraj Franklin , Kotler Burt P. , Srinivasan Jansirani , Khadka Janardan , Titus Jaison , Godwin James , Marriboina Sureshbabu , Grandhi Rohith , Singiri Jeevan R.
Published: May 2024

Pathogens can impose substantial ecological costs on infected individuals, including reduced cognition, foraging ability, and predator avoidance. In a prior experiment, gerbils infected with Mycoplasma haemomuris-like bacteria had higher giving up densities, despite spending more time foraging, and were more likely to be killed by predators. One hypothesis to explain this is that infected gerbils suffer from cognitive impairment that reduces their ability to forage efficiently, causing them to spend more time foraging and placing themselves at higher risk of predation. We tested this hypothesis by comparing the ability of gerbils uninfected, acutely infected, or chronically infected with Mycoplasma to equalize giving up densities (GUDs) in seed patches with different initial abundances and detect micropatches within seed patches in a semi-natural vivarium enclosure. We predicted that uninfected gerbils would equalize GUDs and detect micropatches better than infected gerbils. Contrary to our predictions, infected gerbils performed equally well as uninfected gerbils on both tasks. These experiments did not support the hypothesis that cognitive impairment explains past results regarding Mycoplasma and gerbil foraging.
The Influence of Media Democracy on Attitudes towards Homosexuality in Taiwan and China
Authors: Li Xinling , Hu Kang
Published: May 2024

Using data collected in the seventh wave of the World Values Survey, this article examines how traditional and new media consumption have had very different effects on attitudes towards homosexuality in Taiwan and China. It further explores how such differences reflect each society’s media democracy. A historical analysis of the democratic movements and their relations to media freedom in Taiwan and China is presented, which provides the research background and theoretical foundation for our assumptions as part of the literature review. The ensuing statistical analysis verifies these assumptions in depth. Our findings show that the effect of new media is generally positive in both societies, whereas that of traditional media varies: it is very negative in China yet statistically insignificant in Taiwan. Based on these results, we argue that the more democratised the media space, the more likely it is to promote tolerance of homosexuality.
Does the Timing of Surgical Intervention Impact Outcomes in Necrotizing Enterocolitis?
Authors: Rauh Jessica L. , Reddy Menaka N. , Santella Nicole L. , Ellison Maryssa A. , Weis Victoria G. , Zeller Kristen A. , Garg Parvesh M. , Ladd Mitchell R.
Published: May 2024

Objectives

The optimal time for intervention in surgical necrotizing enterocolitis (sNEC) remains to be elucidated. Surgical management varies between peritoneal drain (PD), laparotomy (LAP), and PD with subsequent LAP (PD + LAP). We propose that some infants with surgical NEC benefit from late (>48 h) operative intervention to allow for resuscitation.

Methods

A retrospective comparison of clinical information in infants with sNEC from 2012 to 2022 was performed. Early intervention was defined as less than 48 hours from time of NEC diagnosis to surgical intervention.

Results

118 infants were identified, 92 underwent early intervention (62 LAP; 22 PD; 8 PD + LAP) and 26 underwent late intervention (20 LAP; 2 PD; 4 PD + LAP). Infants with early intervention were diagnosed younger (DOL 8 [6, 15] vs 20 [11, 26]; P=< .05) with more pneumoperitoneum (76% vs 23%; P=< .05). The early intervention group had a higher mortality (35% vs 15%; P=< .05). When excluding infants with pneumoperitoneum, the early intervention group had a higher mortality rate (10/22 (45%), 4/26 (15%); P < .05) and had more bowel resected (29 ± 17 cm vs 9 ± 8 cm; P < .05), with the same number of patients scoring above 3 on the MD7 criteria.

Conclusion

Infants with NEC who underwent early surgical intervention had a higher mortality and more bowel resected. While this study has a provocative finding, it is severely limited by the non-specific 48-hour cut off. However, our data suggests that a period of medical optimization may improve outcomes in infants with sNEC and thus more in-depth studies are needed.
Deterrence icons as status symbols: American forces in NATO’s eastern flank
Authors: Mälksoo Maria
Published: May 2024

How can a signal of extended deterrence, such as prepositioning of foreign military forces, signify status for the beneficiaries of the allied deterrence/reassurance chain? This article explores how the manifestation and communication of allied deterrence can concurrently constitute an affectively charged status symbol for the protégé states of this international security practice. It does so on the example of the Baltic states and Poland, probing the presence and functionality of the American forces as a status marker in North Atlantic Treaty Organization (NATO)’s eastern flank states after 2014. Engaging discourse analysis and expert interviews, the article shows (1) how the intersubjectively determined success of deterrence is dependent on historically potent symbols which have become emblematic of extended deterrence and (2) how deterrence icons can simultaneously serve as multifarious status symbols in intra-alliance politics. The self-identification of protégé states as worthy stakes to deter over emerges as an ambivalent status position defined by the shortage of attributes, rather than a function of their tally. The article contributes to the understanding of the symbolic form of (allied) deterrence and the multivocal status value ascribed to the American ‘boots on the ground’.
A review on the mechanical behaviour of microcellular and nanocellular polymeric foams: What is the effect of the cell size reduction?
Authors: Le Barbenchon Louise , Kopp Jean-Benoît
Published: May 2024

Research on nanocellular foams is motivated in part by the promise of physical properties, in particular mechanical properties, that can go beyond the classical mechanical framework. However, due to the difficulty in obtaining foams of a given density but different cell sizes, determining the effect of cell size on the mechanical properties of polymer foams remains a challenge. To overcome this difficulty, studies on the mechanical behaviour of mesocellular, microcellular and nanocellular polymer foams have been compiled in this review article. After describing the different cellular structures between meso-, micro- and nanocellular foams, the mechanical properties are examined as a function of relative density and cell size. It is shown that for small strains and at low strain rates, nanocellular foams exhibit mechanical behaviour predicted by the Gibson and Ashby model. Relative density remains the first important factor to be taken into account when studying the Young’s modulus and buckling stress of nanocellular foams. The focus then shifts to fracture properties, as microcellular foams have already been shown to be far superior to more conventional foams. As studies are still scarce and different methodologies have been used, no general conclusions can be drawn. However, the fracture and impact properties could be greatly improved by this change in scale. The local confinement of molecular chains in polymeric nanocellular foams or the relaxation of the triaxial stress state in front of the crack tip could explain these observations.
Theoretical analysis of J-transform decomposition method with applications of nonlinear ordinary differential equations
Authors: Obeidat Nazek A , Rawashdeh Mahmoud Saleh , Al Smadi Mohammad N
Published: May 2024

One of the most noteworthy differential equations of the first order is the Riccati differential equation. It is applied in various branches of mathematics, including algebraic geometry, physics, and conformal mapping theory. The [Formula: see text]-transform Adomian decomposition method is employed in the current study to find exact solutions for different kinds of nonlinear differential equations. We give thorough detailed proofs for new theorems related to the [Formula: see text]-transform technique. The Adomian decomposition method and the [Formula: see text]-transform method serve as the foundation for this technique. For certain differential equations, the theoretical analysis of the [Formula: see text]-transform Adomian decomposition method is examined and is computed using readily computed terms. Our findings are contrasted with exact solutions found in the literature that were produced using alternative techniques. The significant features of the [Formula: see text]-transform Adomian decomposition method are described in the article. It has been shown that the [Formula: see text]-transform Adomian decomposition method is very efficient, useful, and adaptable to a broad variety of linear and nonlinear differential equations. Most of the symbolic and numerical calculations were performed using Mathematica.
Improving Electricity Theft Detection Using Electricity Information Collection System and Customers’ Consumption Patterns
Authors: Kawoosa Asif Iqbal , Prashar Deepak , Anantha Raman G R , Bijalwan Anchit , Haq Mohd Anul , Aleisa Mohammed , Alenizi Abdullah
Published: May 2024

Electricity theft detection (ETD) techniques employed to identify fraudulent consumers often fail to accurately pinpoint electricity thieves in real time. The patterns associated with electricity use are leveraged to identify anomalies indicative of electricity theft. However, challenges in the benchmark ETD include overfitting and a high incidence of false positives (FPs) resulting from incorrect usage patterns formed by considering only electricity consumption patterns without accounting for external factors that contribute to variations in normal consumption patterns. Further investigation is required to precisely detect instances of electricity theft, thereby minimizing nontechnical losses and forecasting future electricity demand to maintain a stable supply. This study employs a master energy meter located on the transformer side to monitor the amount of energy distributed to the region. Zones with a high likelihood of energy theft are detected by comparing the sum of readings from all the smart meters with the readings from the master energy meter installed on the HV of the substation transformer within the same electric feeder. Ensemble XGBoost machine-learning algorithm and K-Means algorithm are used for the classification of malicious and nonmalicious samples and grouping similar types of consumers together, respectively. This makes the proposed model resistant to false-positive rates caused by changes in usage patterns that aren’t done on purpose. Furthermore, energy thieves are identified by detecting anomalies in consumption behavior while maintaining constant internal and external environmental variables. This novel model proposed here mitigates the FP rate found in the present research of electricity usage data. Our approach outperforms support vector machines, convolution neural network, and logistic regression in simulations. Precision, F1-score, recall, Matthews Correlation Coefficient, Receiver Operating Characteristics (ROC)-Area Under The Curve (AUC), and Precision Recal (PR)-Area Under The Curve (AUC) validate our model. The simulation results show that the proposed K-Means-LSTM-XGBoost model improved the classifier’s F1-score, precision, and recall to 93.75%, 95.16%, and 92.38%, respectively. Our model classifies huge time series data with high precision and can be utilized by the utility for real time electricity theft detection.