bluuebunny/crossref_metadata_2025 huggingface dataset:
Spectral Analysis of Proton Eigenfunctions in Crystalline Environments
Authors: Gamberale Luca , Modanese Giovanni
Published: May 2024

The Schrödinger equation and Bloch theorem are applied to examine a system of protons confined within a periodic potential, accounting for deviations from ideal harmonic behavior due to real-world conditions like truncated and non-quadratic potentials, in both one-dimensional and three-dimensional scenarios. Numerical computation of the energy spectrum of bound eigenfunctions in both cases reveals intriguing structures, including bound states with degeneracy matching the site number Nw, reminiscent of a finite harmonic oscillator spectrum. In contrast to electronic energy bands, the proton system displays a greater number of possible bound states due to the significant mass of protons. Extending previous research, this study rigorously determines the constraints on the energy gap and oscillation amplitude of the previously identified coherent states. The deviations in energy level spacing identified in the computed spectrum, leading to the minor splitting of electromagnetic modes, are analyzed and found not to hinder the onset of coherence. Finally, a more precise value of the energy gap is determined for the proton coherent states, ensuring their stability against thermal decoherence up to the melting temperature of the hosting metal.
Multi-Scale Analysis of Lyme Disease Ecology
Authors: Bingham-Byrne Rebecca Michelle , Ozdenerol Esra
Published: May 2024

Lyme disease is a zoonotic infectious disease. Increased public interest in Lyme disease has caused increased efforts by researchers for its surveillance and control. The main concept for this paper is to determine the mammalian species composition of areas at high risk for Lyme disease utilizing GIS-based (Geographic Information Systems) techniques coupled with k-means clustering, random forest, and multinomial logistic regression. Cluster analysis results were similar to previous work involving maps that display areas where people are at high risk for developing Lyme disease. There were differences in which mammal species presence had associations with Lyme disease risk observed at the two different scales within this analysis, with some overlap observed between the national scale and the smaller regions, as well as some overlap between the Rocky Mountain and Southeast regions that was not found at the national scale. This is an investigative analysis to determine which species are needed for habitat suitability analyses in efforts to prioritize vaccine deployment locations. There has been limited research on vaccine deployment for Lyme disease. Increasing our understanding of not only the vaccine but also the interactions between the components of disease transmission is necessary to control this infectious disease successfully.
Pedestrian Pose Recognition Based on Frequency-Modulated Continuous-Wave Radar with Meta-Learning
Authors: Shi Jiajia , Zhang Qiang , Shi Quan , Chu Liu , Braun Robin
Published: May 2024

With the continuous advancement of autonomous driving and monitoring technologies, there is increasing attention on non-intrusive target monitoring and recognition. This paper proposes an ArcFace SE-attention model-agnostic meta-learning approach (AS-MAML) by integrating attention mechanisms into residual networks for pedestrian gait recognition using frequency-modulated continuous-wave (FMCW) millimeter-wave radar through meta-learning. We enhance the feature extraction capability of the base network using channel attention mechanisms and integrate the additive angular margin loss function (ArcFace loss) into the inner loop of MAML to constrain inner loop optimization and improve radar discrimination. Then, this network is used to classify small-sample micro-Doppler images obtained from millimeter-wave radar as the data source for pose recognition. Experimental tests were conducted on pose estimation and image classification tasks. The results demonstrate significant detection and recognition performance, with an accuracy of 94.5%, accompanied by a 95% confidence interval. Additionally, on the open-source dataset DIAT-μRadHAR, which is specially processed to increase classification difficulty, the network achieves a classification accuracy of 85.9%.
Matched Stochastic Resonance Enhanced Underwater Passive Sonar Detection under Non-Gaussian Impulsive Background Noise
Authors: Dong Haitao , Ma Shilei , Suo Jian , Zhu Zhigang
Published: May 2024

Remote passive sonar detection with low-frequency band spectral lines has attracted much attention, while complex low-frequency non-Gaussian impulsive noisy environments would strongly affect the detection performance. This is a challenging problem in weak signal detection, especially for the high false alarm rate caused by heavy-tailed impulsive noise. In this paper, a novel matched stochastic resonance (MSR)-based weak signal detection model is established, and two MSR-based detectors named MSR-PED and MSR-PSNR are proposed based on a theoretical analysis of the MSR output response. Comprehensive detection performance analyses in both Gasussian and non-Gaussian impulsive noise conditions are presented, which revealed the superior performance of our proposed detector under non-Gasussian impulsive noise. Numerical analysis and application verification have revealed the superior detection performance with the proposed MSR-PSNR detector compared with energy-based detection methods, which can break through the high false alarm rate problem caused by heavy-tailed impulsive noise. For a typical non-Gasussian impulsive noise assumption with α=1.5, the proposed MSR-PED and MSR-PSNR can achieve approximately 16 dB and 22 dB improvements, respectively, in the detection performance compared to the classical PED method. For stronger, non-Gaussian impulsive noise conditions corresponding to α=1, the improvement in detection performance can be more significant. Our proposed MSR-PSNR methods can overcome the challenging problem of a high false alarm rate caused by heavy-tailed impulsive noise. This work can lay a solid foundation for breaking through the challenges of underwater passive sonar detection under non-Gaussian impulsive background noise, and can provide important guidance for future research work.
Helping Blind People Grasp: Evaluating a Tactile Bracelet for Remotely Guiding Grasping Movements
Authors: Powell Piper , Pätzold Florian , Rouygari Milad , Furtak Marcin , Kärcher Silke M. , König Peter
Published: May 2024

The problem of supporting visually impaired and blind people in meaningful interactions with objects is often neglected. To address this issue, we adapted a tactile belt for enhanced spatial navigation into a bracelet worn on the wrist that allows visually impaired people to grasp target objects. Participants’ performance in locating and grasping target items when guided using the bracelet, which provides direction commands via vibrotactile signals, was compared to their performance when receiving auditory instructions. While participants were faster with the auditory commands, they also performed well with the bracelet, encouraging future development of this system and similar systems.
A Lightweight Remote Sensing Small Target Image Detection Algorithm Based on Improved YOLOv8
Authors: Nie Haijiao , Pang Huanli , Ma Mingyang , Zheng Ruikai
Published: May 2024

In response to the challenges posed by small objects in remote sensing images, such as low resolution, complex backgrounds, and severe occlusions, this paper proposes a lightweight improved model based on YOLOv8n. During the detection of small objects, the feature fusion part of the YOLOv8n algorithm retrieves relatively fewer features of small objects from the backbone network compared to large objects, resulting in low detection accuracy for small objects. To address this issue, firstly, this paper adds a dedicated small object detection layer in the feature fusion network to better integrate the features of small objects into the feature fusion part of the model. Secondly, the SSFF module is introduced to facilitate multi-scale feature fusion, enabling the model to capture more gradient paths and further improve accuracy while reducing model parameters. Finally, the HPANet structure is proposed, replacing the Path Aggregation Network with HPANet. Compared to the original YOLOv8n algorithm, the recognition accuracy of mAP@0.5 on the VisDrone data set and the AI-TOD data set has increased by 14.3% and 17.9%, respectively, while the recognition accuracy of mAP@0.5:0.95 has increased by 17.1% and 19.8%, respectively. The proposed method reduces the parameter count by 33% and the model size by 31.7% compared to the original model. Experimental results demonstrate that the proposed method can quickly and accurately identify small objects in complex backgrounds.
Decision Making in Service Shops Supported by Mining Enterprise Resource Planning Data
Authors: West Shaun , Powell Daryl , Ille Fabian , Behringer Stefan
Published: May 2024

This research examines the application of Enterprise Resource Planning (ERP) systems in service shops, focusing on the specific challenges unique to these environments compared to those in the manufacturing sector. Service shops, distinguished by their smaller scale and variable demands, often need different functionalities in ERP systems compared to manufacturing facilities. Our analysis is based on detailed billing records and monthly cash flow data to deliver critical insights into businesses’ performance for service shop managers. This study analyses ERP data from 27 service shops over 35 months. It is based on detailed billing records and monthly cash flow data to deliver critical insights into businesses’ performance for service shop managers that support managerial decision making. Our findings emphasise the importance of incorporating additional contextual information to augment the effectiveness of ERP systems in service contexts. Our analysis shows that simple, standardised data mining methods can significantly enhance operational management decision making when supported with visuals to support understanding and interpretation of the data. Moreover, this study suggests potential directions for future research aimed at improving business analytics and intelligence practices to optimise the use of ERP systems in service industries. This research contributes to the academic discourse by providing empirical evidence on utilising ERP data in service shops and offers practical recommendations for ongoing operational improvements.
Expression of Concern: Stephenson, M.J. A Differential Datalog Interpreter. Software 2023, 2, 427–446
Authors:   Software Editorial Office
Published: May 2024

With this notice, the Software Editorial Office states their awareness of the concerns regarding the appropriateness of the authorship and origins of the study of the published manuscript [...]
Effects of Heating Bituminous Mixtures in a Hot-Gas Drum Based on a Finite Volume Method
Authors: Li Xuan , Cheng Haiying , Liu Xiaohui , Zhu Wenfeng
Published: May 2024

Hot-gas drum heating (HDH) of bituminous mixtures is a new approach to heating bituminous mixtures that is influenced by the parameters of the hot gas and drum. A fluid thermal numerical model was developed to evaluate the effects of heating bituminous mixtures with HDH using a finite-volume method (FVM). The FVM was verified through the heating test of a bituminous mixture. The effects of the drum rotating speed and hot-gas speed on the efficiency of heating the bituminous mixture during HDH were analyzed using Fluent. The results indicated that the drum rotating speed directly influenced the formation of a bituminous-mixture curtain, which had a significant effect on the efficiency of heating the bituminous mixture. The efficiency of the heat exchange between the hot gas and the bituminous mixture was high, with full contact between the hot gas and the bituminous mixture. With an increase in the hot-gas speed, the heating time became shorter; however, the rate of hot-gas utilization was reduced. A symmetrical temperature distribution and a superior heating efficiency of the bituminous mixture were achieved when the drum rotating speed was 7 rpm and the hot-gas speed was 1.4 m/s.
Anisotropic Generalization of the ΛCDM Universe Model with Application to the Hubble Tension
Authors: Grøn Øyvind G.
Published: May 2024

I deduce an exact and analytic Bianchi type I solution of Einstein’s field equations, which generalizes the isotropic ΛCDM universe model to a corresponding model with anisotropic expansion. The main point of the article is to present the anisotropic generalization of the ΛCDM universe model in a way suitable for investigating how anisotropic expansion modifies observable properties of the ΛCDM universe model. Although such generalizations of the isotropic ΛCDM universe model have been considered earlier, they have never been presented in this form before. Several physical properties of the model are pointed out and compared with properties of special cases, such as the isotropic ΛCDM universe model. The solution is then used to investigate the Hubble tension. It has recently been suggested that the cosmic large-scale anisotropy may solve the Hubble tension. I consider those earlier suggestions and find that the formulae of these papers lead to the result that the anisotropy of the cosmic expansion is too small to solve the Hubble tension. Then, I investigate the problem in a new way, using the exact solution of the field equations. This gives the result that the cosmic expansion anisotropy is still too small to solve the Hubble tension in the general Bianchi type I universe with dust and LIVE (Lorentz Invariant Vacuum Energy with a constant energy density, which is represented by the cosmological constant) and anisotropic expansion in all three directions—even if one neglects the constraints coming from the requirement that the anisotropy should be sufficiently small so that it does not have any significant effect upon the results coming from the calculations of the comic nucleosynthesis during the first ten minutes of the universe. If this constraint is taken into account, the cosmic expansion anisotropy is much too small to solve the Hubble tension.
Digital Transformation, Gender Discrimination, and Female Employment
Authors: Ye Rendao , Cai Xinya
Published: May 2024

With the demographic dividend disappearing, the key to achieving high-quality development in China is to promote full employment of the workforce. Women are a significant group in the job market, but they frequently face greater pressure and higher employment thresholds. Ensuring high-quality employment for women will be one of the most important tasks in the future. Based on the China Family Panel Studies data, this paper uses two-way fixed effects models, causal stepwise regression analysis, and structural equation models to study the impact of digital transformation of households on female employment and how it works. The empirical results show that digital transformation of households significantly promotes female employment. For low-security employment and high-security employment, the promotion effect of digital transformation is significant. Further mechanism analysis shows that digital transformation of households mainly increases women’s human capital, improves their search for information, and stimulates improvements in social skills, thus effectively eliminating employment-related gender discrimination and ultimately promoting women’s employment. This paper can provide a significant reference for alleviating female employment pressure, promoting full employment, and achieving high-quality development in the context of digital transformation.
Amended Vegetation Filters as Nature-Based Solutions for the Treatment of Pharmaceuticals: Infiltration Experiments Coupled to Reactive Transport Modelling
Authors: Salvi-Taga Raisa Gabriela , Meffe Raffaella , Martínez-Hernández Virtudes , De Miguel Garcia Angel , De Bustamante Irene
Published: May 2024

In small populations and scattered communities, wastewater treatment through vegetation filters (VFs), a nature-based solution, has proved to be feasible, especially for nutrient and organic matter removal. However, the presence of pharmaceuticals in wastewater and their potential to infiltrate through the vadose zone and reach groundwater is a drawback in the evaluation of VF performances. Soil amended with readily labile carbon sources, such as woodchips, enhances microbial activity and sorption processes, which could improve pharmaceutical attenuation in VFs. The present study aims to assess if woodchip amendments to a VF’s soil are able to abate concentrations of selected pharmaceuticals in the infiltrating water by quantitatively describing the occurring processes through reactive transport modelling. Thus, a column experiment using soil collected from an operating VF and poplar woodchips was conducted, alongside a column containing only soil used as reference. The pharmaceuticals acetaminophen, naproxen, atenolol, caffeine, carbamazepine, ketoprofen and sulfamethoxazole were applied daily to the column inlet, mimicking a real irrigation pattern and periodically measured in the effluent. Ketoprofen was the only injected pharmaceutical that reached the column outlet of both systems within the experimental timeframe. The absence of acetaminophen, atenolol, caffeine, carbamazepine, naproxen and sulfamethoxazole in both column outlets indicates that they were attenuated even without woodchips. However, the presence of 10,11-epoxy carbamazepine and atenolol acid as transformation products (TPs) suggests that incomplete degradation also occurs and that the effect of the amendment on the infiltration of TPs is compound-specific. Modelling allowed us to generate breakthrough curves of ketoprofen in both columns and to obtain transport parameters during infiltration. Woodchip-amended columns exhibited Kd and μw values from one to two orders of magnitude higher compared to soil column. This augmentation of sorption and biodegradation processes significantly enhanced the removal of ketoprofen to over 96%.
Tert-Butylhydroquinone Mitigates T-2-Toxin-Induced Testicular Dysfunction by Targeting Oxidative Stress, Inflammation, and Apoptosis in Rats
Authors: Chen Yun , Zhang Xinke , Lan Shanshan , Liang Shuping , Zhang Manyu , Zhang Shuang , Liu Yijian , Li Li , Wei Hengxi , Zhang Shouquan
Published: May 2024

Tert-butylhydroquinone (tBHQ) has emerged as a promising candidate for mitigating the adverse effects of T-2-induced reproductive toxicity. The protective effects of tBHQ on rat sperm quality, testicular injury, apoptosis, and inflammation induced by T-2 toxin exposure were investigated. Histopathological examination of testicular tissues revealed severe damage in the T-2-treated group, characterized by disorganized germ cell arrangement, thinning of the convoluted seminiferous tubule walls, and significant cellular necrosis. However, tBHQ administration, either as a preventive or therapeutic measure, mitigated this structural damage. Image analysis confirmed an increase in the cross-sectional area and height of the convoluted seminiferous tubules in the tBHQ-treated groups compared to the T-2-treated group (p < 0.05), indicating tBHQ’s efficacy in alleviating testicular damage. Additionally, tBHQ treatment significantly inhibited T-2-induced apoptosis of testicular tissue cells, as evidenced by the results showing reduced apoptotic cell counts and downregulation of the BAX/BCL2 ratio and caspase-3 expression (p < 0.05). tBHQ significantly increased the concentrations of the antioxidant factors SOD, CAT, TAC, and GSH-PX. Furthermore, tBHQ attenuated the inflammatory response induced by T-2 exposure, as indicated by the decreased mRNA expression of the proinflammatory cytokines Tnf, Il1, and Il10 in testicular tissue (p < 0.05). Additionally, tBHQ treatment alleviated the decline in serum testosterone induced by the T-2 and promoted testosterone synthesis gene expression, including for the genes 17β-HSD and Cyp11a1, in rat testes (p < 0.05). These findings underscore tBHQ’s role as a therapeutic agent combatting T-2-induced reproductive toxicity, highlighting its antioxidative, anti-apoptotic, and anti-inflammatory properties. Further elucidation of tBHQ’s mechanisms of action may offer novel strategies for preventing and treating reproductive disorders induced by environmental toxins.
Infectious Diseases and Secondary Antibody Deficiency in Patients from a Mesoregion of São Paulo State, Brazil
Authors: Prestes-Carneiro Luiz Euribel , Carrilho Paula Andreia Martins , Torelli Danielle Francisco Honorato de Barros , Bressa Jose Antonio Nascimento , Parizi Ana Carolina Gomes , Vieira Pedro Henrique Meireles , Sa Fernanda Miranda Caliani , Ferreira Mauricio Domingues
Published: May 2024

Our aim was to determine the secondary antibody deficiency (SAD) profiles of patients in a mesoregion of São Paulo state, Brazil, focusing on infectious diseases. Demographic characteristics, and clinical and laboratory data were obtained from electronic files; infections were classified as organ-specific and graded as mild, moderate, life-threatening, and fatal. Non-Hodgkin’s lymphoma (NHL) accounted for 30% of patients, nephrotic syndrome (NS) 25%, chronic lymphocyte leukemia 20%, and multiple myeloma 15%. Patients with NS were younger than those in other groups, and hypo-γ-globulinemia was detected in 94.1%, IgG < 400 mg/dL in 60.0%, IgA < 40 mg/dL in 55.0%, and CD19 < 20 cells/mm3 in 30.0%. One hundred and one infections were found; 82.1% were classified as mild or moderate, 7.9% as life-threatening, and 3.0% as fatal. Respiratory tract infections were more prevalent (41.5%), and pneumonia accounted for 19.8%. Lower levels of infections were found in patients with NS compared with NHL (p = 0.0001). Most patients progressed to hypo-γ-globulinemia and SAD after treatment with immunosuppressants, and mild and moderate infections were predominant. These therapies are increasing in patients with different diseases; therefore, monitoring hypo-γ-globulinemia and infections may help to identify patients at high risk for severe complications, antibiotic prophylaxis or treatment, and immunoglobulin replacement.
Safety and Immunogenicity of an Accelerated Ebola Vaccination Schedule in People with and without Human Immunodeficiency Virus: A Randomized Clinical Trial
Authors: Ake Julie A. , Paolino Kristopher , Hutter Jack N. , Cicatelli Susan Biggs , Eller Leigh Anne , Eller Michael A. , Costanzo Margaret C. , Paquin-Proulx Dominic , Robb Merlin L. , Tran Chi L. , Anova Lalaine , Jagodzinski Linda L. , Ward Lucy A. , Kilgore Nicole , Rusnak Janice , Bounds Callie , Badorrek Christopher S. , Hooper Jay W. , Kwilas Steven A. , Ilsbroux Ine , Anumendem Dickson Nkafu , Gaddah Auguste , Shukarev Georgi , Bockstal Viki , Luhn Kerstin , Douoguih Macaya , Robinson Cynthia
Published: May 2024

The safety and immunogenicity of the two-dose Ebola vaccine regimen MVA-BN-Filo, Ad26.ZEBOV, 14 days apart, was evaluated in people without HIV (PWOH) and living with HIV (PLWH). In this observer-blind, placebo-controlled, phase 2 trial, healthy adults were randomized (4:1) to receive MVA-BN-Filo (dose 1) and Ad26.ZEBOV (dose 2), or two doses of saline/placebo, administered intramuscularly 14 days apart. The primary endpoints were safety (adverse events (AEs)) and immunogenicity (Ebola virus (EBOV) glycoprotein-specific binding antibody responses). Among 75 participants (n = 50 PWOH; n = 25 PLWH), 37% were female, the mean age was 44 years, and 56% were Black/African American. AEs were generally mild/moderate, with no vaccine-related serious AEs. At 21 days post-dose 2, EBOV glycoprotein-specific binding antibody responder rates were 100% among PWOH and 95% among PLWH; geometric mean antibody concentrations were 6286 EU/mL (n = 36) and 2005 EU/mL (n = 19), respectively. A total of 45 neutralizing and other functional antibody responses were frequently observed. Ebola-specific CD4+ and CD8+ T-cell responses were polyfunctional and durable to at least 12 months post-dose 2. The regimen was well tolerated and generated robust, durable immune responses in PWOH and PLWH. Findings support continued evaluation of accelerated vaccine schedules for rapid deployment in populations at immediate risk. Trial registration: NCT02598388 (submitted 14 November 2015).
Neoantigen Identification and Dendritic Cell-Based Vaccines for Lung Cancer Immunotherapy
Authors: Kumari Komal , Singh Amarnath , Chaudhary Archana , Singh Rakesh Kumar , Shanker Asheesh , Kumar Vinay , Haque Rizwanul
Published: May 2024

Immunotherapies can treat many cancers, including difficult-to-treat cases such as lung cancer. Due to its tolerability, long-lasting therapeutic responses, and efficacy in a wide spectrum of patients, immunotherapy can also help to treat lung cancer, which has few treatment choices. Tumor-specific antigens (TSAs) for cancer vaccinations and T-cell therapies are difficult to discover. Neoantigens (NeoAgs) from genetic mutations, irregular RNA splicing, protein changes, or viral genetic sequences in tumor cells provide a solution. NeoAgs, unlike TSAs, are non-self and can cause an immunological response. Next-generation sequencing (NGS) and bioinformatics can swiftly detect and forecast tumor-specific NeoAgs. Highly immunogenic NeoAgs provide personalized or generalized cancer immunotherapies. Dendritic cells (DCs), which originate and regulate T-cell responses, are widely studied potential immunotherapeutic therapies for lung cancer and other cancers. DC vaccines are stable, reliable, and safe in clinical trials. The purpose of this article is to evaluate the current status, limitations, and prospective clinical applications of DC vaccines, as well as the identification and selection of major histocompatibility complex (MHC) class I and II genes for NeoAgs. Our goal is to explain DC biology and activate DC manipulation to help researchers create extremely potent cancer vaccines for patients.
Understanding Reasons for Vaccination Hesitancy and Implementing Effective Countermeasures: An Online Survey of Individuals Unvaccinated against COVID-19
Authors: Kobashi Yurie , Yoshida Makoto , Saito Hiroaki , Yoshimura Hiroki , Nonaka Saori , Yamamoto Chika , Zhao Tianchen , Tsubokura Masaharu
Published: May 2024

This online survey of unvaccinated people living in Japan aimed to identify the reasons for declining vaccination and to develop effective countermeasures. We conducted a hierarchical class analysis to classify participants, examine factors influencing their classification, and provide the information they needed about coronavirus disease 2019 (COVID-19) and trusted sources of COVID-19 information for each group. A total of 262 participants were classified into three groups: Group 1 with no specific reason (28 participants, 10.69%); Group 2 with clear concerns about trust in the vaccine (85 participants, 32.44%), and Group 3 with attitudinal barriers, such as distrust of the vaccine and complacency towards COVID-19, and structural barriers, such as vaccination appointments (149 participants, 56.87%). For each group, females tended to be classified in Group 2 more than Group 1 (Odds ratio (OR) [95% confidential intervals (95%CI)] = 1.64 (0.63 to 2.66), p = 0.001) and in Group 3 more than Group 1 (OR [95%CI] = 1.16 (0.19 to 2.12), p = 0.019). The information that the participants wanted to know about COVID-19 was different among each group (Safety: p < 0.001, Efficacy: p < 0.001, Genetic effects: p < 0.001). Those who did not receive the COVID-19 vaccine also had lower influenza vaccination coverage (8.02%). Additionally, 38 participants (14.50%) were subject to social disadvantages because they had not received the COVID-19 vaccine. Countermeasures should be carefully tailored according to the target population, reasons for hesitancy, and specific context. The findings of this study may help develop individualized countermeasures to address vaccine hesitancy.
Efficacy of Respiratory Syncytial Virus Vaccination to Prevent Lower Respiratory Tract Illness in Older Adults: A Systematic Review and Meta-Analysis of Randomized Controlled Trials
Authors: Riccò Matteo , Cascio Antonio , Corrado Silvia , Bottazzoli Marco , Marchesi Federico , Gili Renata , Giuri Pasquale Gianluca , Gori Davide , Manzoni Paolo
Published: May 2024

A systematic review and meta-analysis was designed in order to ascertain the effectiveness of respiratory syncytial virus (RSV) vaccination in preventing lower respiratory tract diseases (LRTD) in older adults (age ≥ 60 years). Studies reporting on randomized controlled trials (RCTs) were searched for in three databases (PubMed, Embase, and Scopus) and the preprint repository medRxiv until 31 March 2024. A total of nine studies were eventually included, two of which were conference proceedings. Our analysis included five RCTs on five RSV vaccines (RSVpreF, RSVPreF3, Ad26.RSV.preF, MEDI7510, and mRNA-1345). The meta-analysis documented a pooled vaccine efficacy of 81.38% (95% confidence interval (95% CI) 70.94 to 88.06) for prevention of LRTD with three or more signs/symptoms during the first RSV season after the delivery of the vaccine. Follow-up data were available for RSVPreF3 (2 RSV seasons), RSVpreF (mid-term estimates of second RSV season), and mRNA-1345 (12 months after the delivery of the primer), with a pooled VE of 61.15% (95% CI 45.29 to 72.40). After the first season, the overall risk for developing RSV-related LRTD was therefore substantially increased (risk ratio (RR) 4.326, 95% CI 2.415; 7.748). However, all estimates were affected by substantial heterogeneity, as suggested by the 95% CI of I2 statistics, which could be explained by inconsistencies in the design of the parent studies, particularly when dealing with case definition. In conclusion, adult RSV vaccination was quite effective in preventing LRTD in older adults, but the overall efficacy rapidly decreased in the second season after the delivery of the vaccine. Because of the heterogenous design of the parent studies, further analyses are required before tailoring specific public health interventions.
Direct-Injection UHPLC-MS/MS Method for Simultaneous Determination of 78 Illegal Drugs and Psychoactive Substances in Domestic Wastewater
Authors: Li Kan , Hu Yiling , Jiang Yuke , Han Xing , Liu Xin , Du Mingluo
Published: May 2024

The determination of illegal drugs and psychoactive substances in wastewater is increasingly being used to monitor the use of both by populations in specific areas. This article describes a method for the simultaneous determination of 78 illegal drugs and psychoactive substances in wastewater using direct-injection ultra-high-performance liquid chromatography–tandem mass spectrometry (UHPLC-MS/MS). This method includes the analysis of stimulants, opioids, antidepressants, antipsychotic drugs, anti-anxiety drugs, and hallucinogens. The method was validated in terms of the selectivity, calibration range, recovery, matrix effects, accuracy, precision, limit of detection (LOD), and limit of quantification (LOQ). The correlation coefficients were higher than 0.99 for all analytes, and the calibration range was from 0.2 to 500 ng/L. The LOD and LOQ of this method were 0.1–1 ng/L and 0.2–5 ng/L, respectively. The intra- and inter-day precisions were <9.3% and 11.4%, respectively, and the recovery ranged from 81.3% to 117.7%. The method was applied to real domestic wastewater collected from wastewater treatment plants, and the results showed that morphine, codeine, and ephedrine were detected in all samples. Some samples also contained other illegal drugs and psychoactive substances (such as etomidate, methamphetamine, ketamine, and tramadol). This indicates that the direct-injection UHPLC-MS/MS method can be used for the rapid determination of illegal drugs and psychoactive substances in wastewater.
Saudi firms' performance dynamics: Organizational learning, innovation, and the dual roles of firm size and type
Authors: Parveen Musrrat , Javaid Saima
Published: May 2024

The objective of this research paper is to propose a robust framework for understanding the correlation between organizational learning, innovation, and the performance of Saudi Arabian firms, encompassing both financial and non-financial aspects. Additionally, the study evaluates how factors such as “firm type” and “firm size” influence organizational learning, innovation, and overall firm performance. For this study, we distributed a questionnaire to Jeddah, Saudi Arabia's private firm employees for a year. Analysis involved 815 complete sets, utilizing Structural Equation Modeling (SEM) through Confirmatory Factor Analysis (CFA) to explore relationships among latent variables via path analysis. Organization learning significantly enhances both financial and non-financial performance. Additionally, innovation positively influences firm performance. The combined impact of organizational learning and innovation strongly influences overall firm performance. Introducing the mediating variable "type of firm" enhances the relationship between organizational learning, innovation, and firm performance, as depicted in Model 2. The result of path analysis shows that “firm size” as moderating variable is significantly negatively related with innovation and firm performance. This study contributes by exploring the interplay of organizational learning, innovation, and their impact on firm performance, particularly within the emerging Saudi context, enhancing existing knowledge.
Social and psychological assistance to children under martial law
Authors: Dichek Nataliia , Kravchenko Oksana
Published: May 2024

The purpose of the study is to identify the main psycho-emotional states and factors affecting the physical and mental well-being of schoolchildren, including during distance learning and in relationships with family members, as well as to develop areas of psychosocial assistance to children under martial law. To achieve the research purpose, an appropriate questionnaire was developed with multiple-choice questions about: dominant emotions and feelings, attitudes towards distance learning, reactions to external stimuli, the impact of martial law on the comfort of life, relationships with peers and parents, etc. A survey was conducted among 1303 schoolchildren aged 6–17, including 515 boys and 788 girls, 11 of whom live outside Ukraine. The survey found that the physical and psycho-emotional well-being of Ukrainian schoolchildren was characterised by sleep disturbances, agitation, fear, rapid mood changes, severe fatigue, sadness, longing, indignation, irritation, anger, increased conflicts (especially with parents), etc. An additional factor in the increased level of anxiety under martial law was distance learning, which makes it difficult for students to concentrate due to the difficulty of communication, shifted daily routines, worries about family and friends, changes in responsibilities and other distractions. The main directions of psycho-correctional work and recommendations for the use of psychosocial assistance technologies have been developed, which will allow children to assess their current life situation, identify their strengths (resources), which will ensure their self-healing and increase their resilience.
Presumptions as means of proof in criminal procedure law of states with continental and Anglo-American legal systems
Authors: Bobechko Nazar , Fihurskyi Volodymyr
Published: May 2024

The aim of this article is to study legal regulation, doctrinal approaches on understanding and using presumptions in criminal procedure proof of the states with continental and Anglo-American legal systems. The methodological basis of this research consists of general scientific and special legal methods, namely dialectical, analysis, generalization, structural and functional, hermeneutic, dogmatic and comparative legal methods. The article analyzes one of the means of criminal procedure proof – presumption. By analyzing the corresponding norms of CPC of Ukraine, legal positions of the European Court of Human Rights, Supreme Court of the USA and the views of fellow researchers, the authors present their vision of issues within the scope of the study. The significance of presumptions as means of proof in criminal proceedings is clarified and their types which are distinguished in the doctrine of criminal procedure of continental and Anglo-American legal systems are characterized.
Forensic-linguistic and religious expertise in the investigation of crimes committed by members of youth informal groups (associations) of extremist orientation
Authors: Larkin Mikhail , Boiarov Viktor , Pyrozhkova Yuliia , Melkovskyi Oleksandr , Loboda Yuliia
Published: May 2024

The article explores the unique challenges of conducting forensic-linguistic and religious expertise during the investigation of crimes committed by members of youth informal groups (associations) with extremist leanings. It outlines the specific investigative practices for these types of crimes. The research aims to analyze forensic-linguistic and religious expertise in investigating crimes perpetrated by members of these groups.

The importance of these types of expertise is underscored by the rising number of extremism cases among young people, which necessitates innovative identification and prevention methods. Linguistic analysis can reveal underlying meanings and manipulative language tools, crucial for effective crime investigation and maintaining justice and societal safety. As extremist crimes often transcend international borders, it is vital to develop adaptable research methods for different cultural and social contexts.

The study employs scientific methods such as observation, analysis, synthesis, comparison, generalization, and extrapolation. It reviews scientific literature on youth groups, anti-extremism, crime investigation, forensics, and religious studies, alongside examining investigation materials from crimes committed by youth extremist groups.

Promising avenues for future research include analyzing forensic examinations conducted during the investigation of crimes committed by youth informal groups with extremist orientations. This could enhance understanding and provide better strategies for tackling extremism in various contexts.
Arboreal behaviour and habitat use in the Nationally Critical Kapitia skink (Oligosoma salmo)
Authors: Kerrigan Marcel , Brill Sarah , Baling Marleen
Published: May 2024

The Kapitia skink (Oligosoma salmo) is only found on the west coast of the South Island, New Zealand. This critically endangered skink has a moderately prehensile tail that would be expected to contribute to an ability to climb as part of its natural history. However, its current only habitat, a highly modified pasture, lacks vegetation or natural structures that would promote arboreal behaviour. We conducted a pilot study investigating the behavioural activity of a captive, wild-born Kapitia skink at Auckland Zoo in 2020. Over 13 days (24 hours/day) of focal sampling climbing behaviour was observed for the first time in this species (8%, n=58/703 mins). The skink was most active in the middle of the day, especially in fine, sunny weather. We suggest further investigations into the range of habitat use for this species. This study supports the importance of exploring potential habitat types beyond what we typically assume as the ideal habitat type (based on its source location) for an organism.
Monitoring of North Island fantail / pīwakawaka fantail (Rhipidura fuliginosa placabilis Bangs, 1921, Rhipiduridae) distribution on Tiritiri Matangi Island: using several spatial methods for processing volunteer data
Authors: Aguilar Glenn , Galbraith Mel , Cooper Hester
Published: May 2024

The Aotearoa / New Zealand fantail / pīwakawaka (Rhipidura fuliginosa Sparrman, 1787, Rhipiduridae) is an iconic species and conspicuous in a range of habitats. However, island populations of the species are said to fluctuate dramatically. This project set out to investigate the population dynamics of the Te ika a Maui / North Island subspecies Rhipidura fuliginosa placabilis Bangs, 1921) on Tiritiri Matangi Island using a volunteer-based monitoring scheme. To achieve this goal we developed a pilot sampling grid and determined spatial distribution characteristics using several approaches including geostatistical tools in ArcMap, species distribution modelling and occupancy modelling. Fantail presence data was recorded twice a year by volunteers assigned to specific grids at different seasons for two years on Tiritiri Matangi Island. Recorded count data show distinctive differences between the sampling periods and different areas of the island. Significant hotspots as well as clustering of abundance show different patterns with significantly higher abundance and widespread distribution during May compared to November. Spatial analysis identified vegetation, particularly replanted areas, as influencing the fantail counts. Results of species distribution modelling showed areas of the island suitable for the species and occupancy models further described the seasonal spatial characteristics of fantail. The effort also highlights the importance of volunteers in providing bird count data to generate the knowledge base required for the management of an island sanctuary.
DIGITAL AUTHENTICATION “FRIEND-OR-FOE”
Authors:   Taras Shevchenko National University of Kyiv, Kyiv, Ukraine, a.v.anisimov@knu.ua, Anisimov A.V.
Published: May 2024

Based on a modified one-time Winternitz signature scheme, we develop a multi-time two-round group authentication protocol of the type “friend-or-foe.” The main construction is as follows. At each authentication session, members of a group sign only designated w-blocks of a random message. The verifier checks the validity of the whole Winternitz signature. Session public keys are created and sent to the verifier at the previous session. This way, they form a hash-connected blockchain. Security of the Winternitz signature and blockchain structure of public keys imply the security of the suggested protocol. A trusted third party is needed for establishing first “genesis” keys. Also, the protocol has the property “honest verifier zero knowledge”. Keywords: authentication, coalition group, digital signature, the Winternitz signature, blockchain.
STOCHASTIC DESCRIPTOR PURSUITE GAME
Authors:   Kharkiv National University of Radio Electronics, Kharkiv, Ukraine, lara@rutrus.com, Vlasenko L.A. , Rutkas A.A. ,   Kharkiv National University of Radio Electronics, Kharkiv, Ukraine, andrew@rutrus.com, Rutkas A.G. ,   Kharkiv National University of Radio Electronics, Kharkiv, Ukraine, anatoly@rutrus.com, Chikrii A.A. ,   V.M. Glushkov Institute of Cybernetics, National Academy of Sciences of Ukraine, Kyiv, Ukraine, chik@insyg.kiev.ua
Published: May 2024

A differential pursuit game in a stochastic descriptor linear system is analyzed. The system dynamics is described by Ito’s stochastic differential algebraic equation. Solutions of the equation are presented by the formula of variation of constants in terms of the initial data and control unit. Constraints on the support functionals of two sets defined by the behaviors of the pursuer and evader are used to obtain the game completion conditions. The method of resolving functions is applied to construct a pursuer control bringing the dynamic vector of the system to a terminal set. The results are illustrated by an example of a stochastic descriptor system that describes transient states in a radio technical filter with random perturbations in the form of white noise. Keywords: stochastic differential algebraic equation, Wiener process, descriptor system, differential game, radio technical filter, white noise.
OPTIMIZATION OF CAPITAL INVESTMENT DISTRIBUTION BASED ON A DYNAMIC MATHEMATICAL MODEL
Authors:   V.M. Glushkov Institute of Cybernetics, National Academy of Sciences of Ukraine, Kyiv, Ukraine, gupalanatol@gmail.com, Gupal А.М. , Pashko S.V. ,   Institute of Software Systems, National Academy of Sciences of Ukraine, Kyiv, Ukraine, pashko55@yahoo.com
Published: May 2024

The article considers dynamic optimization problems for the distribution of investments between sectors of the country’s economy. Leontiev’s «input-output» and Solow’s models were used to construct extremum problems. The objective is to maximize the gross domestic product under limited investment volumes. The constructed mathematical programming problem is proved to belong to the class of smooth and convex extremum problems. By using the conditional gradient method, the optimal distribution of investments for the Ukrainian economy was calculated. Keywords: optimization, investment distribution, mathematical model, production function, gross domestic product, method.
SIMULATION OF 3D VOLUME FILLING WITH NON-SPHERICAL AND SPHERICAL TITANIUM ALLOY POWDER PARTICLES FOR ADDITIVE MANUFACTURING
Authors:   A. Pidgorny Institute of Mechanical Engineering Problems, National Academy of Sciences of Ukraine, Kharkiv, Ukraine, yustoyan19@gmail.com, Stoyan Yu. , Pankratov O. ,   A. Pidgorny Institute of Mechanical Engineering Problems, National Academy of Sciences of Ukraine, Kharkiv, Ukraine, pankratov2001@yahoo.com, Lemishka I. ,   Lviv Polytechnic National University, Lviv, Ukraine, mzihor@ukr.net, Duriagina Z. ,   Lviv Polytechnic National University, Lviv, Ukraine, zduriagina@gmail.com, Bennell J. ,   University of Leeds, Leeds, England, J.Bennell@leeds.ac.uk, Stetsyuk P. ,   V.M. Glushkov Institute of Cybernetics, National Academy of Sciences of Ukraine, Kyiv, Ukraine,  stetsyukp@gmail.com, Romanova T. ,   A. Pidgorny Institute of Mechanical Engineering Problems, National Academy of Sciences of Ukraine, Kharkiv, Ukraine; Kharkiv National University of Radio Electronics, Kharkiv, Ukraine; University of Leeds, Leeds, England, tarom27@yahoo.com
Published: May 2024

The authors developed an approach to modeling the layer-by-layer filling of a particular 3D volume with a combination of non-spherical and spherical powder particles of different fractional composition. A mathematical model of the problem of packing regular and irregular freely moving objects is provided using the phi-function technique. A heuristic algorithm that uses nonlinear optimization is proposed for calculating packing density factor/porosity. The results of numerical modeling are compared with experimental data obtained for a mixture of spherical and polyhedral powders of titanium alloys. It is established that the relative frequencies obtained by the developed algorithm correspond to the experimental results with high accuracy. This indicates the possibility of using numerical modeling results instead of costly experimental studies. The use of mathematical modeling and optimization techniques in additive manufacturing makes it possible to improve the efficiency of each stage of the technological process, reduce the number of defective products, and rationally plan the consumption of energy and material resources. Keywords: packing, spherical and non-spherical particles, 3D volume, mathematical modeling, nonlinear optimization, additive manufacturing.