bluuebunny/crossref_metadata_2025 huggingface dataset:
The GgcxK325Q Mutation Does Not Affect the Calcium Homeostasis of the Epididymis and Male Fertility in Mice
Authors: Xiong Mingxiang , Cheng Pang , Liu Bo , Zhao Yanqiu , Gao Ting , Li Zhen
Published: May 2024

A low-calcium microenvironment is imperative for spermatozoa maturation within the epididymis. Our previous work has shown that γ-glutamyl carboxylase (GGCX), the carboxylation enzyme of the matrix Gla protein (MGP), plays an essential role in epididymal calcium homeostasis and sperm maturation in rats and that the GGCX SNP mutation rs699664 was associated with asthenozoospermia (AZS) in humans. Here, we investigated the expression patterns of GGCX and MGP in the mouse epididymis and generated GgcxK325Q knock-in (KI) mice. We also tested the effects of this mutation on epididymal calcium homeostasis, sperm function, and male fertility in GgcxK325Q−/− mice. The results showed that both GGCX and MGP were enriched in all regions of the mouse epididymis, especially in the initial segment of the epididymis. Double immunofluorescence staining revealed that GGCX colocalized with MGP in the epithelial cells of the initial segment and caput regions as well as in the lumen of the corpus and cauda regions of the mouse epididymis. However, the GgcxK325Q−/− mice were fertile with normal epididymal morphology, sperm functions, and epididymal calcium concentration. Overall, our findings revealed that the GgcxK325Q mutation does not exert any discernible effect on male fertility in mice.
Low Cell Bioenergetic Metabolism Characterizes Chronic Lymphocytic Leukemia Patients with Unfavorable Genetic Factors and with a Better Response to BTK Inhibition
Authors: Mirabilii Simone , Piedimonte Monica , Conte Esmeralda , Mirabilii Daniele , Rossi Francesca Maria , Bomben Riccardo , Zucchetto Antonella , Gattei Valter , Tafuri Agostino , Ricciardi Maria Rosaria
Published: May 2024

Chronic Lymphocytic Leukemia (CLL) is an indolent malignancy characterized by the accumulation of quiescent mature B cells. However, these cells are transcriptionally and translationally active, implicating an active metabolism. The recent literature suggests that CLL cells have an oxidative-type phenotype. Given the role of cell metabolism, which is able to influence the outcome of treatments, in other neoplasms, we aimed to assess its prognostic role in CLL patients by determining the ex vivo bioenergetic metabolic profile of CLL cells, evaluating the correlation with the patient clinical/biological characteristics and the in vivo response to BTK inhibitor treatment. Clustering analysis of primary samples identified two groups, characterized by low (CLL low) or high (CLL high) bioenergetic metabolic rates. Compared to the CLL high, CLL with lower bioenergetic metabolic rates belonged to patients characterized by a statistically significant higher white blood cell count and by unfavorable molecular genetics. More importantly, patients in the CLL low cluster displayed a better and more durable response to the BTK inhibitor ibrutinib, thus defining a bioenergetic metabolic subgroup that can benefit the most from this therapy.
HIV-1 Structural Proteins or Cell-Signaling Factors? That Is the Question!
Authors: Pellegrino Michele , Giordano Francesca , De Amicis Francesca , Marra Maria , Tucci Paola , Marsico Stefania , Aquaro Stefano
Published: May 2024

The biological activity of structural HIV-1 proteins is not limited to ensuring a productive viral infection but also interferes with cellular homeostasis through intra- and extracellular signaling activation. This interference induces genomic instability, increases the lifespan of the infected cell by inhibiting apoptosis, and subverts cell senescence, resulting in unrestricted cell proliferation. HIV structural proteins are present in a soluble form in the lymphoid tissues and blood of infected individuals, even without active viral replication. The HIV matrix protein p17, the envelope glycoprotein gp120, the transenvelope protein gp41, and the capsid protein p24 interact with immune cells and deregulate the biological activity of the immune system. The biological activity of HIV structural proteins is also demonstrated in endothelial cells and some tumor cell lines, confirming the ability of viral proteins to promote cell proliferation and cancer progression, even in the absence of active viral replication. This review corroborates the hypothesis that HIV structural proteins, by interacting with different cell types, contribute to creating a microenvironment that is favorable to the evolution of cancerous pathologies not classically related to AIDS.
An Improved Ensemble-Based Cardiovascular Disease Detection System with Chi-Square Feature Selection
Authors: Korial Ayad E. , Gorial Ivan Isho , Humaidi Amjad J.
Published: May 2024

Cardiovascular disease (CVD) is a leading cause of death globally; therefore, early detection of CVD is crucial. Many intelligent technologies, including deep learning and machine learning (ML), are being integrated into healthcare systems for disease prediction. This paper uses a voting ensemble ML with chi-square feature selection to detect CVD early. Our approach involved applying multiple ML classifiers, including naïve Bayes, random forest, logistic regression (LR), and k-nearest neighbor. These classifiers were evaluated through metrics including accuracy, specificity, sensitivity, F1-score, confusion matrix, and area under the curve (AUC). We created an ensemble model by combining predictions from the different ML classifiers through a voting mechanism, whose performance was then measured against individual classifiers. Furthermore, we applied chi-square feature selection method to the 303 records across 13 clinical features in the Cleveland cardiac disease dataset to identify the 5 most important features. This approach improved the overall accuracy of our ensemble model and reduced the computational load considerably by more than 50%. Demonstrating superior effectiveness, our voting ensemble model achieved a remarkable accuracy of 92.11%, representing an average improvement of 2.95% over the single highest classifier (LR). These results indicate the ensemble method as a viable and practical approach to improve the accuracy of CVD prediction.
Demonstration of HCl-Based Selective Wet Etching for N-Polar GaN with 42:1 Selectivity to Al0.24Ga0.76N
Authors: Kayede Emmanuel , Akso Emre , Romanczyk Brian , Hatui Nirupam , Sayed Islam , Khan Kamruzzaman , Collins Henry , Keller Stacia , Mishra Umesh K.
Published: May 2024

A wet-etching technique based on a mixture of hydrochloric (HCl) and nitric (HNO3) acids is introduced, demonstrating exceptional 42:1 selectivity for etching N-polar GaN over Al0.24Ga0.76N. In the absence of an AlGaN etch stop layer, the etchant primarily targets N-polar unintentionally doped (UID) GaN, indicating its potential as a suitable replacement for selective dry etches in the fabrication of GaN high-electron-mobility transistors (HEMTs). The efficacy and selectivity of this etchant were confirmed through its application to a gate recess module of a deep-recess HEMT, where, despite a 228% over-etch, the 2.6 nm AlGaN etch stop layer remained intact. We also evaluated the proposed method for the selective etching of the GaN cap in the n+ regrowth process, achieving a contact resistance matching that of a BCl3/SF6 ICP process. These findings underscore the applicability and versatility of the etchant in both the electronic and photonic domains and are particularly applicable to the development of N-polar deep-recess HEMTs.
Determinants of Butterfly Community Structure and Composition at the Local Habitat Level: Importance of Neighboring Vegetation and Management Status: A Case Study
Authors: Kitahara Masahiko , Yasuda Taisuke
Published: May 2024

Exploring the determinants of biological community structure is important not only for understanding the formation of the community, but also for promoting its biodiversity conservation. We monitored butterfly communities in a grassland and woodland area of Mount Fuji, Japan, and explored the environmental factors that influenced them. Multivariate regression tree (MRT) analysis generated a 3-leaved MRT (G1, G2, and G3) and showed the total explained variation of 64.4% in the species composition. The explanatory variables discriminating between the two branches in the first node and in the second node of the MRT were neighboring plant community and management status, respectively. The neighboring plant community was related to the distribution of butterfly dietary resources and contributed a lot in determining the species composition of the community while the management status was largely related to the amount of their dietary resources, affecting the species richness and diversity. The PCA results revealed that the three key groups (G1, G2, and G3) were formed along the gradients of these two factors. Consequently, maintaining mowing management and the diversity of neighboring vegetation is very important for the continuance of butterfly community diversity and composition and the conservation of Red Listed species in the area.
Changes in Freeze-Thaw Environments in a Cold Lake: Eliciting New Insights into the Activity and Composition of Bacterial Communities
Authors: Feng Chen , Lu Junping , Jia Yongqin , Tian Zhiqiang , Zhang Zixuan , Hu Yaxin , Liu Yinghui
Published: May 2024

This study explored the dynamics of bacterial community composition, response to environmental factors, and co-occurrence network models across different habitats of Wuliangsuhai Lake during the glacial period. Water quality analysis and high-throughput sequencing were performed at 14 monitoring sites within the lake. Additionally, a co-occurrence network between the two bacterial operational taxonomic unit (OTU)-OTUs was established. The results indicated significant differences in water quality indices, namely total nitrogen (TN), chemical oxygen demand (COD), total dissolved solids (TDS), salinity (SAL), chlorophyll-a (Chl.a), and electrical conductivity (EC), between the ice bodies of Wuliangsuhai Lake and subglacial water. Although there were no significant differences in α diversity across various media, substantial differences were observed in β diversity. The VIF and RDA analyses revealed that lake water quality factors significantly affected the microbial community structure and COD and TDS had the highest explanation for the community composition change. Network analysis demonstrated that competition dominated the bacterial community in water bodies with higher complexity and stability and ice body bacteria exhibited more reciprocal relationships and weaker resistance to external environmental disturbances. The co-occurrence network demonstrated a modular structure in the external environment, with g_Flavobacterium, f_Arcobacteraceae, and g_Sphingobacteriaceae being the main keystone species. Investigating the habitat heterogeneity of lake bacterial communities and identifying major groups and key species using molecular ecological network models and their topological effects can provide a theoretical foundation for monitoring and assessing the structural stability of lake ecosystems in cold regions.
Enhancing Person Re-Identification through Attention-Driven Global Features and Angular Loss Optimization
Authors: Bi Yihan , Wang Rong , Zhou Qianli , Lin Ronghui , Wang Mingjie
Published: May 2024

To address challenges related to the inadequate representation and inaccurate discrimination of pedestrian attributes, we propose a novel method for person re-identification, which leverages global feature learning and classification optimization. Specifically, this approach integrates a Normalization-based Channel Attention Module into the fundamental ResNet50 backbone, utilizing a scaling factor to prioritize and enhance key pedestrian feature information. Furthermore, dynamic activation functions are employed to adaptively modulate the parameters of ReLU based on the input convolutional feature maps, thereby bolstering the nonlinear expression capabilities of the network model. By incorporating Arcface loss into the cross-entropy loss, the supervised model is trained to learn pedestrian features that exhibit significant inter-class variance while maintaining tight intra-class coherence. The evaluation of the enhanced model on two popular datasets, Market1501 and DukeMTMC-ReID, reveals improvements in Rank-1 accuracy by 1.28% and 1.4%, respectively, along with corresponding gains in the mean average precision (mAP) of 1.93% and 1.84%. These findings indicate that the proposed model is capable of extracting more robust pedestrian features, enhancing feature discriminability, and ultimately achieving superior recognition accuracy.
Loss Control-Based Key Distribution under Quantum Protection
Authors: Kirsanov Nikita , Pastushenko Valeria , Kodukhov Aleksei , Aliev Aziz , Yarovikov Michael , Strizhak Daniel , Zarubin Ilya , Smirnov Alexander , Pflitsch Markus , Vinokur Valerii
Published: May 2024

Quantum cryptography revolutionizes secure information transfer, providing defense against both quantum and classical computational attacks. The primary challenge in extending the reach of quantum communication comes from the exponential decay of signals over long distances. We meet this challenge by experimentally realizing the Quantum-Protected Control-Based Key Distribution (QCKD) protocol, utilizing physical control over signal losses. By ensuring significant non-orthogonality of the leaked quantum states, this control severely constrains eavesdroppers’ capacities. We demonstrate the performance and scale of our protocol by experiments over a 1707 km long fiber line. The scalability of the QCKD opens the route for globally secure quantum-resistant communication.
Transformer-Based User Charging Duration Prediction Using Privacy Protection and Data Aggregation
Authors: Zeng Fei , Pan Yi , Yuan Xiaodong , Wang Mingshen , Guo Yajuan
Published: May 2024

The current uneven deployment of charging stations for electric vehicles (EVs) requires a reliable prediction solution for smart grids. Existing traffic prediction assumes that users’ charging durations are constant in a given period and may not be realistic. In fact, the actual charging duration is affected by various factors including battery status, user behavior, and environment factors, leading to significant differences in charging duration among different charging stations. Ignoring these facts would severely affect the prediction accuracy. In this paper, a Transformer-based prediction of user charging durations is proposed. Moreover, a data aggregation scheme with privacy protection is designed. Specifically, the Transformer charging duration prediction dynamically selects active and reliable temporal nodes through a truncated attention mechanism. This effectively eliminates abnormal fluctuations in prediction accuracy. The proposed data aggregation scheme employs a federated learning framework, which centrally trains the Transformer without any prior knowledge and achieves reliable data aggregation through a dynamic data flow convergence mechanism. Furthermore, by leveraging the statistical characteristics of model parameters, an effective model parameter updating method is investigated to reduce the communication bandwidth requirements of federated learning. Experimental results show that the proposed algorithm can achieve the novel prediction accuracy of charging durations as well as protect user data privacy.
Thermodynamic Comparison of the Steam Ejectors Integrated at Different Locations in Cogeneration Systems
Authors: Zhao Shifei , Wang Chunlan , Duan Fan , Tian Ze
Published: May 2024

Under the challenge of global energy transition, coal-fired cogeneration systems are undergoing a technical revolution towards enhanced efficiency, heating capacity, and flexibility. In this paper, four schemes using a steam ejector integrated into a cogeneration system are designed. Considering operational safety, integrated locations are selected at the front and back of high- and medium-pressure turbines. Subsequently, the thermodynamic and operational characteristics under both design and off-design conditions are analyzed based on a model built in EBSILON Professional. Finally, a sensitivity analysis of the heating process is conducted. The results show that the integration of steam ejectors can increase the waste heat recovery ratio of exhaust steam by 18.42–45.61% under design conditions. The largest waste heat recovery ratio is obtained in System 4, resulting in the power generation efficiency (ηg) and gross energy utilization efficiency (ηp) of 81.95% and 65.53%, respectively. Meanwhile, the steam ejector can expand the power-load regulation range of the cogeneration system, and System 4 has the lowest lower power limit among all the systems. The ηp values of Systems 1–4 reach extreme values at different mixed steam pressures of the ejector. Increasing the pinch point temperature difference reduces the power load ηg and ηp of Systems 1–4. The results provide technical solutions for improving the heating capacity and efficient and flexible operation of cogeneration systems.
Wireless Charging Station Design for Electric Scooters: Case Study Analysis
Authors: Shevchenko Viktor , Pakhaliuk Bohdan , Husev Oleksandr , Vinnikov Dmitri , Strzelecki Ryszard
Published: May 2024

This study proposes an example of a wireless charging station design for a small-scale vehicle available on the market. The article analyzes basic transmitter inverter topologies and their compensation methods in terms of flexibility of control, tolerance to uncertainty in positioning, and the possibility of decreasing the integration price. Our comprehensive analysis focuses on the battery voltage range, energy capacity, cost, and travel distance. We evaluate the constraints of efficiency, transmitted power, amount of used material, and size of the energy delivery system based on our design example. The aim is to increase the penetration of wireless technology in terms of convenience and integration capabilities.
Assessing the Impact of Organic Loading Rate on Hydrogen Consumption Rates during In Situ Biomethanation
Authors: Dabestani-Rahmatabad Ali , Capson-Tojo Gabriel , Trably Eric , Delgenès Jean-Philippe , Escudié Renaud
Published: May 2024

Biogas upgrading via biomethanation has been extensively studied recently, but the influence of organic loading rate on process performance remains to be fully understood. This is particularly significant because both organic loading rate and hydrogen injection can lead to volatile fatty acid accumulation during anaerobic digestion. This study investigated the impact of a wide range of organic loading rates (from 1.25 to 3.25 g VS/L/d) on hydrogen consumption rates, organic acid accumulation, and microbial communities during in situ biomethanation. It also provided kinetics data and metabolite production data for different control reactors, including anaerobic digestion, ex situ biomethanation, and endogenous control reactors. Hydrogen was injected into parallel batch reactors using digestate from a semi-continuous lab-scale reactor subjected to increasing organic loading rates (1.25–3.25 g VS/L/d) as an inoculum. The inoculum was well adapted to each tested organic loading rate. The batch experiments were replicated following a 12 h hydrogen starvation period to assess the stability of hydrogen consumption rates. High organic loading rate values resulted in increased hydrogen consumption rates, peaking at 68 mg COD/L/h at an organic loading rate of 3.25 g VS/L/d (maximum value tested), with no significant organic acid accumulation despite the high hydrogen partial pressures. The hydrogen consumption rates were maintained after the starvation period. Furthermore, the addition of an organic substrate did not impact the hydrogen consumption rate (i.e., the in situ and ex situ rates were similar). A higher organic loading rate resulted in higher relative abundances of hydrogenotrophic methanogens (i.e., Methanospirillum sp.). This study highlights that increasing the organic loading rate can accelerate the rate of hydrogen consumption during in situ biomethanation, consequently reducing both capital and operational costs.
Can Lagoons Serve as a Quaternary Treatment for Micropollutants in Wastewater Treatment Plants? Recent Implications for Compliance with the New Urban Wastewater Treatment Directive
Authors: Díaz-Gamboa Lissette , Martínez-López Sofía , Ayuso-García Luis Miguel , Lahora Agustín , Martínez-Alcalá Isabel
Published: May 2024

This study explores the potential of storage lagoons as a quaternary treatment step in wastewater treatment plants (WWTPs), focusing on compliance with the recent European Urban Wastewater Treatment Directive (UWWTD), which mandates an 80% reduction in specific micropollutants. While conventional treatments effectively remove residual nutrients and solids, the potential of storage lagoons as an additional treatment is not fully defined. This research aims to address this gap by assessing the efficacy of storage lagoons in refining the effluent quality at the Cabezo Beaza WWTP, considering recent UWWTD requirements. We conduct a comprehensive assessment of the water quality parameters and micropollutants, before and after the storage lagoon stage, at the Cabezo Beaza WWTP. The results indicate that this strategy of prolonged storage in lagoons manages to meet the reduction objectives established by the Directive, reaching elimination percentages greater than 80% for the majority of the analyzed micropollutants. Our findings suggest that lagoons significantly improve water quality and reduce contaminants beyond conventional treatments, offering environmental and economic benefits. This paper discusses the mechanisms behind these improvements, such as natural sedimentation, microbial activity, and potential phytoremediation. This study contributes to the research on advanced wastewater treatment and supports the integration of storage lagoons as a viable quaternary treatment solution that meets the UWWTD standards.
The Impact of Climate Change and Human Activities on the Spatial and Temporal Variations of Vegetation NPP in the Hilly-Plain Region of Shandong Province, China
Authors: Wu Yangyang , Yang Jinli , Li Siliang , Yu Honggang , Luo Guangjie , Yang Xiaodong , Yue Fujun , Guo Chunzi , Zhang Ying , Gu Lei , Wu Haobiao , Yuan Panli
Published: May 2024

Studying the spatio-temporal changes and driving mechanisms of vegetation’s net primary productivity (NPP) is critical for achieving green and low-carbon development, as well as the carbon peaking and carbon neutrality goals. This article employs various analytical approaches, including the Carnegie–Ames–Stanford approach (CASA) model, Theil–Sen median estimator, coefficient of variation, Hurst index, and land-use and land-cover change (LUCC) transition matrix, to conduct a thorough study of NPP variations in the Shandong Hilly Plain (SDHP) region. Furthermore, the geographic detector method was used to investigate the synergistic effects of meteorological changes and human activities on NPP in this region. Between 2000 and 2020, the vegetation NPP in the SDHP exhibited an average increase rate of 0.537 g C·m−2·a−1. However, the fluctuation in mean annual NPP, ranging from 203 to 230 g C·m−2·a−1, underscores an uneven growth pattern. Significant regional disparities are evident in vegetation NPP, gradually ascending from the southeast to the northwest and from the coastal areas to inland regions. The average Hurst index for the entire study area stands at 0.556, indicating an overall sustained growth trend in the time series of SDHP vegetation NPP. The vegetation NPP changes in SDHP can be well explained by climate variables (mean annual temperature, mean annual precipitation) and human activities (LUCC, night light index); of these, LUCC (q = 0.684) has the highest explanatory power on the impact of NPP and is a major influencing factor. This study deepens the understanding of the driving factors and patterns of vegetation’s dynamic response to climate change and human activities in the SDHP region. At the same time, it provides valuable scientific insights for improving ecosystem quality and promoting the carbon peaking and carbon neutrality goals.
Use of a Consumer-Grade UAV Laser Scanner to Identify Trees and Estimate Key Tree Attributes across a Point Density Range
Authors: Watt Michael S. , Jayathunga Sadeepa , Hartley Robin J. L. , Pearse Grant D. , Massam Peter D. , Cajes David , Steer Benjamin S. C. , Estarija Honey Jane C.
Published: May 2024

The management of plantation forests using precision forestry requires advanced inventory methods. Unmanned aerial vehicle laser scanning (ULS) offers a cost-effective approach to accurately estimate forest structural attributes at both plot and individual tree levels. We examined the utility of ULS data collected from a radiata pine stand for tree detection and prediction of diameter at breast height (DBH) and stem volume, using data thinned to 13-point densities (ranging from 10–12,200 points/m2). These datasets were created using a DTM with the highest pulse density and DTMs that used the native decimated point clouds. Models of DBH were constructed using partial least squares (PLS) and random forest (RF) from seven classes of metrics that characterized the horizontal and vertical structure of the canopy. Individual tree segmentation was consistently accurate across the 13-point densities and was insensitive to DTM type (F1 scores > 0.96). Predictions of DBH using PLS models were consistently more accurate than RF models and accuracy was insensitive to the DTM type. Using data from the native DTMs, DBH estimation using PLS had the lowest RMSE of 1.624 cm (R2 of 0.756) at a point density of 12,200 points/m2. Stem volume predictions made using PLS predictions of DBH and height from the ULS had the lowest RMSE of 0.0418 m3 (R2 of 0.792) at 12,200 points/m2. The RMSE values for DBH and volume remained relatively stable from 12,200 to between 750 and 400 points/m2, with reductions in accuracy occurring as point density declined below this threshold. Overall, these findings have significant implications, particularly for the precise estimation of DBH and stem volume at the individual tree level. They demonstrate the potential of cost-effective ULS sensors for rapid and frequent plantation forest assessment, thereby enhancing the application of light detection and ranging (LiDAR) technology in plantation forest management.
Cross-Layer Optimization for Enhanced IoT Connectivity: A Novel Routing Protocol for Opportunistic Networks
Authors: Khalil Ayman , Zeddini Besma
Published: May 2024

Opportunistic networks, an evolution of mobile Ad Hoc networks (MANETs), offer decentralized communication without relying on preinstalled infrastructure, enabling nodes to route packets through different mobile nodes dynamically. However, due to the absence of complete paths and rapidly changing connectivity, routing in opportunistic networks presents unique challenges. This paper proposes a novel probabilistic routing model for opportunistic networks, leveraging nodes’ meeting probabilities to route packets towards their destinations. Thismodel dynamically builds routes based on the likelihood of encountering the destination node, considering factors such as the last meeting time and acknowledgment tables to manage network overload. Additionally, an efficient message detection scheme is introduced to alleviate high overhead by selectively deleting messages from buffers during congestion. Furthermore, the proposed model incorporates cross-layer optimization techniques, integrating optimization strategies across multiple protocol layers to maximize energy efficiency, adaptability, and message delivery reliability. Through extensive simulations, the effectiveness of the proposed model is demonstrated, showing improved message delivery probability while maintaining reasonable overhead and latency. This research contributes to the advancement of opportunistic networks, particularly in enhancing connectivity and efficiency for Internet of Things (IoT) applications deployed in challenging environments.
Utilizing the Honeybees Mating-Inspired Firefly Algorithm to Extract Parameters of the Wind Speed Weibull Model
Authors: Younis Abubaker , Belabbes Fatima , Cotfas Petru Adrian , Cotfas Daniel Tudor
Published: May 2024

This study introduces a novel adjustment to the firefly algorithm (FA) through the integration of rare instances of cannibalism among fireflies, culminating in the development of the honeybee mating-based firefly algorithm (HBMFA). The IEEE Congress on Evolutionary Computation (CEC) 2005 benchmark functions served as a rigorous testing ground to evaluate the efficacy of the new algorithm in diverse optimization scenarios. Moreover, thorough statistical analyses, including two-sample t-tests and fitness function evaluation analysis, the algorithm’s optimization capabilities were robustly validated. Additionally, the coefficient of determination, used as an objective function, was utilized with real-world wind speed data from the SR-25 station in Brazil to assess the algorithm’s applicability in modeling wind speed parameters. Notably, HBMFA achieved superior solution accuracy, with enhancements averaging 0.025% compared to conventional FA, despite a moderate increase in execution time of approximately 18.74%. Furthermore, this dominance persisted when the algorithm’s performance was compared with other common optimization algorithms. However, some limitations exist, including the longer execution time of HBMFA, raising concerns about its practical applicability in scenarios where computational efficiency is critical. Additionally, while the new algorithm demonstrates improvements in fitness values, establishing the statistical significance of these differences compared to FA is not consistently achieved, which warrants further investigation. Nevertheless, the added value of this work lies in advancing the state-of-the-art in optimization algorithms, particularly in enhancing solution accuracy for critical engineering applications.
Information Transmission and Countervailing Biases in Organizations
Authors: Chiba Saori
Published: May 2024

A decision maker (DM) must choose between two projects or decide on no project. The expected benefits of these projects are correlated. The DM seeks advice from an agent with private information about the projects’ benefits. However, the agent’s divergent preferences for projects and lack of consideration for the DM’s implementation costs may introduce two types of biases: project bias, favoring the agent’s project, or pandering bias, favoring the project preferred by the DM. Our findings reveal that project correlation leads to these biases countervailing each other, facilitating the transmission of information. The agent typically recommends a project based on private information to dissuade the DM from choosing no project, as this would be detrimental to the agent. Additionally, we explore optimal delegation within organizations. In contrast to the prevailing literature advocating for delegation to biased agents for enhanced information elicitation, our study suggests limited benefits in the context of project correlation.
Phytochemistry and Allelopathic Effects of Tanacetum vulgare L. (Tansy) Extracts on Lepidium sativum L. (Garden Pepper Cress) and Lactuca sativa L. (Lettuce)
Authors: Judžentienė Asta , Būdienė Jurga , Stancelytė Donata , Nedveckytė Irena
Published: May 2024

Tanacetum vulgare is a perennial plant growing wild along roadsides, pastures, and agricultural fields. Its prevalence is due to several factors: good climatic adaptability, high self-seeding potential, phenotypic plasticity, multiplying via underground rhizomes and its allelochemicals, which influence the seed germination, root development and the overall vegetation of the surrounding plants. The phytochemistry of tansy extracts and their allelopathic activity on the seed germination and growth of garden pepper cress (Lepidium sativum L.) and lettuce (Lactuca sativa L.) were investigated. The major volatile compounds, 1,8-cineole, camphor and borneol were determined in tansy flower extracts. The leaf extracts contained appreciable amounts of 1,8-cineole and borneol. Feruloylquinic, (di)ferulic and dehydrocaffeoyl-5-caffeoylquinic acids, acacetin, ludovicin C and tanacetin were determined both in leaf and inflorescence extracts. Root extracts contained minor quantities of some terpenoids and polyphenols. Extracts of T. vulgare’s aerial parts showed strong allelopathic effects on model plants. The flower and leaf water extracts inhibited lettuce and pepper cress seed germination and growth the most. According to the fractions, the acidic solution had the strongest effect, followed by neutral and alkaline solutions. At the highest relative concentrations of 0.5 and 1.0 tansy leaf acidic fraction, lettuce seed germination and growth decreased by 89.93% (from 35.07 ± 4.79 to 3.53 ± 2.10 mm) and by 98.46% (from 35.07 ± 4.79 to 0.57 ± 0.98 mm) compared to the control, respectively. Tansy root extracts showed weak effects. Our results demonstrated that the allelopathic inhibitory potential of tansy extracts was higher on garden pepper cress than on lettuce. The presence of allelochemicals in T. vulgare may have a significant impact on plant communities and ecosystems.
Seed Germination and Micropropagation of Ornamental Plants
Authors: Bertsouklis Konstantinos , Kartsonas Epaminondas , Carra Angela
Published: May 2024

Ornamental species can improve the environmental conditions in cities, serving the European Union’s biodiversity strategy to bring nature back into our lives [...]
Public Telemedicine Policy in Brazilian Unified Health System: An Impact Analysis
Authors: Oliveira Angela Maria de , Valadão Marcos Aurélio Pereira , Tabak Benjamin Miranda
Published: May 2024

There are several difficulties in evaluating interventions seeking to promote public health policies. In this article, we analyzed the promotion of the use of telemedicine during COVID-19 in Brazil. Using the random promotion method with instrumental variables, we showed that the policy of promoting telemedicine was adequate, with intense use of this type of care. Our results showed that telemedicine works if it is encouraged in the population. We contributed to the discussion of public health policies and their impact on the population’s health in times of health crisis, such as during the COVID-19 pandemic.
Effect of a Water, Sanitation, and Hygiene Program on Handwashing with a Cleansing Agent among Diarrhea Patients and Attendants in Healthcare Facilities in the Democratic Republic of the Congo: A Randomized Pilot of the PICHA7 Program
Authors: Mwishingo Alain , Endres Kelly , Bisimwa Lucien , Sanvura Presence , Banywesize Blessing Muderhwa , Bisimwa Jean-Claude , Williams Camille , Perin Jamie , Boroto Raissa , Nsimire Gisèle , Rugusha Feza , Endeleya Freddy , Kitumaini Pacifique , Lunyelunye Claude , Timsifu Jessy , Munyerenkana Brigitte , Bengehya Justin , Maheshe Ghislain , Cikomola Cirhuza , George Christine Marie
Published: May 2024

Healthcare-acquired infections are a major problem in healthcare facility settings around the world. The Democratic Republic of the Congo (DRC) has over 2 million diarrhea patients hospitalized each year. These healthcare settings become high-risk environments for spreading diarrheal illnesses such as cholera. The objective of the Preventative Intervention for Cholera for 7 Days (PICHA7) program is to develop evidence-based water, sanitation, and hygiene (WASH) interventions to reduce cholera and other severe diarrheal diseases in the DRC. The study objective was to evaluate the effectiveness of PICHA7 program delivery in increasing handwashing with a cleansing agent at stool/vomit- and food-related events in a healthcare facility setting among diarrhea patients and patient attendants. A pilot of the PICHA7 program was conducted among 284 participants in 27 healthcare facilities from March 2020 to November 2021 in urban Bukavu in the South Kivu Province of the DRC. The standard arm received the standard message provided in the DRC to diarrhea patients on the use of oral rehydration solution and a basic WASH message at healthcare facility discharge. The PICHA7 arm received the PICHA7 WASH pictorial module delivered by a health promoter focused on handwashing with a cleansing agent at the bedside of the diarrhea patient in the healthcare facility and provision of a soapy water bottle (water and detergent powder). Within 24 h of intervention delivery, a three-hour structured observation of handwashing practices at stool/vomit- and food-related events (key events) was conducted in healthcare facilities of diarrhea patients and their attendants. Compared to the standard arm, there was significantly more handwashing with a cleansing agent at key events in the PICHA7 arm (40% vs. 15%) (odds ratio: 5.04; (95% confidence interval (CI): 2.01, 12.7)). These findings demonstrate that delivery of the PICHA7 WASH pictorial module and provision of a soapy water bottle to diarrhea patients and their attendants presents a promising approach to increase handwashing with a cleansing agent among this high-risk population in healthcare facilities in the eastern DRC.
Relationship between Driving Ability and Physical Fitness Factors in Older Adults: A Multiple Linear Regression Analysis
Authors: Katayama Akihiko , Abe Takenori , Hase Ayako , Miyatake Nobuyuki
Published: May 2024

The number of older drivers is increasing with the aging population; this has led to concerns about traffic accidents involving older drivers. For older adults, the automobile is not just a means of transportation, but a life necessity that promotes social activities and maintains and improves health-related quality of life. In this study, we aimed to clarify the relationship between driving ability and physical fitness factors among 70 older adult drivers using a single regression analysis and multiple regression models adjusted for age, sex, and other factors. Driving ability was evaluated by driving an actual car on an ordinary road without a simulator. The single regression analysis revealed no relationship between driving ability and any physical fitness factor. In the multiple regression model analysis, only grip strength was an important explanatory factor; however, the driving ability scores decreased as grip strength scores increased. By clarifying the physical fitness factors that influence the maintenance and improvement of driving ability, it is possible to propose more efficient intervention programs to maintain and improve driving ability. We could not identify the relevant physical fitness factors in this study; therefore, further research is required to improve safe driving among older adults.
Management of Rheumatoid Arthritis in Primary Care: A Scoping Review
Authors: Inchingolo Francesco , Inchingolo Angelo Michele , Fatone Maria Celeste , Avantario Pasquale , Del Vecchio Gaetano , Pezzolla Carmela , Mancini Antonio , Galante Francesco , Palermo Andrea , Inchingolo Alessio Danilo , Dipalma Gianna
Published: May 2024

Rheumatoid arthritis (RA) can lead to severe joint impairment and chronic disability. Primary care (PC), provided by general practitioners (GPs), is the first level of contact for the population with the healthcare system. The aim of this scoping review was to analyze the approach to RA in the PC setting. PubMed, Scopus, and Web of Science were searched using the MESH terms “rheumatoid arthritis” and “primary care” from 2013 to 2023. The search strategy followed the PRISMA-ScR guidelines. The 61 articles selected were analyzed qualitatively in a table and discussed in two sections, namely criticisms and strategies for the management of RA in PC. The main critical issues in the management of RA in PC are the following: difficulty and delay in diagnosis, in accessing rheumatological care, and in using DMARDs by GPs; ineffective communication between GPs and specialists; poor patient education; lack of cardiovascular prevention; and increase in healthcare costs. To overcome these criticisms, several management strategies have been identified, namely early diagnosis of RA, quick access to rheumatology care, effective communication between GPs and specialists, active patient involvement, screening for risk factors and comorbidities, clinical audit, interdisciplinary patient management, digital health, and cost analysis. PC appears to be the ideal healthcare setting to reduce the morbidity and mortality of chronic disease, including RA, if a widespread change in GPs’ approach to the disease and patients is mandatory.
The Intramolecular Charge Transfer Mechanism by Which Chiral Self-Assembled H8-BINOL Vesicles Enantioselectively Recognize Amino Alcohols
Authors: Wang Rong , Song Kaiyue , Wei Zhaoqin , Sun Yue , Sun Xiaoxia , Hu Yu
Published: May 2024

The chiral H8-BINOL derivatives R-1 and R-2 were efficiently synthesized via a Suzuki coupling reaction, and they can be used as novel dialdehyde fluorescent probes for the enantioselective recognition of R/S-2-amino-1-phenylethanol. In addition, R-1 is much more effective than R-2. Scanning electron microscope images and X-ray analyses show that R-1 can form supramolecular vesicles through the self-assembly effect of the π-π force and strong hydrogen bonding. As determined via analysis, the fluorescence of the probe was significantly enhanced by mixing a small amount of S-2-amino-1-phenylethanol into R-1, with a redshift of 38 nm, whereas no significant fluorescence response was observed in R-2-amino-1-phenylethanol. The enantioselective identification of S-2-amino-1-phenylethanol by the probe R-1 was further investigated through nuclear magnetic titration and fluorescence kinetic experiments and DFT calculations. The results showed that this mechanism was not only a simple reactive probe but also realized object recognition through an ICT mechanism. As the intramolecular hydrogen bond activated the carbonyl group on the probe R-1, the carbonyl carbon atom became positively charged. As a strong nucleophile, the amino group of S-2-amino-1-phenylethanol first transferred the amino electrons to a carbonyl carbocation, resulting in a significantly enhanced fluorescence of the probe R-1 and a 38 nm redshift. Similarly, S-2-amino-1-phenylethanol alone caused severe damage to the self-assembled vesicle structure of the probe molecule itself due to its spatial structure, which made R-1 highly enantioselective towards it.
Unveiling the Nature and Strength of Selenium-Centered Chalcogen Bonds in Binary Complexes of SeO2 with Oxygen-/Sulfur-Containing Lewis Bases: Insights from Theoretical Calculations
Authors: Lu Tao , Chen Renhua , Liu Qingyu , Zhong Yeshuang , Lei Fengying , Zeng Zhu
Published: May 2024

Among various non-covalent interactions, selenium-centered chalcogen bonds (SeChBs) have garnered considerable attention in recent years as a result of their important contributions to crystal engineering, organocatalysis, molecular recognition, materials science, and biological systems. Herein, we systematically investigated π–hole-type Se∙∙∙O/S ChBs in the binary complexes of SeO2 with a series of O-/S-containing Lewis bases by means of high-level ab initio computations. The results demonstrate that there exists an attractive interaction between the Se atom of SeO2 and the O/S atom of Lewis bases. The interaction energies computed at the MP2/aug-cc-pVTZ level range from −4.68 kcal/mol to −10.83 kcal/mol for the Se∙∙∙O chalcogen-bonded complexes and vary between −3.53 kcal/mol and −13.77 kcal/mol for the Se∙∙∙S chalcogen-bonded complexes. The Se∙∙∙O/S ChBs exhibit a relatively short binding distance in comparison to the sum of the van der Waals radii of two chalcogen atoms. The Se∙∙∙O/S ChBs in all of the studied complexes show significant strength and a closed-shell nature, with a partially covalent character in most cases. Furthermore, the strength of these Se∙∙∙O/S ChBs generally surpasses that of the C/O–H∙∙∙O hydrogen bonds within the same complex. It should be noted that additional C/O–H∙∙∙O interactions have a large effect on the geometric structures and strength of Se∙∙∙O/S ChBs. Two subunits are connected together mainly via the orbital interaction between the lone pair of O/S atoms in the Lewis bases and the BD*(OSe) anti-bonding orbital of SeO2, except for the SeO2∙∙∙HCSOH complex. The electrostatic component emerges as the largest attractive contributor for stabilizing the examined complexes, with significant contributions from induction and dispersion components as well.
Identifying the Morphological and Molecular Features of a Cell-Based Orthotopic Pancreatic Cancer Mouse Model during Growth over Time
Authors: Tansi Felista L. , Schrepper Andrea , Schwarzer Michael , Teichgräber Ulf , Hilger Ingrid
Published: May 2024

Pancreatic ductal adenocarcinoma (PDAC), characterized by hypovascularity, hypoxia, and desmoplastic stroma is one of the deadliest malignancies in humans, with a 5-year survival rate of only 7%. The anatomical location of the pancreas and lack of symptoms in patients with early onset of disease accounts for late diagnosis. Consequently, 85% of patients present with non-resectable, locally advanced, or advanced metastatic disease at diagnosis and rely on alternative therapies such as chemotherapy, immunotherapy, and others. The response to these therapies highly depends on the stage of disease at the start of therapy. It is, therefore, vital to consider the stages of PDAC models in preclinical studies when testing new therapeutics and treatment modalities. We report a standardized induction of cell-based orthotopic pancreatic cancer models in mice and the identification of vital features of their progression by ultrasound imaging and histological analysis of the level of pancreatic stellate cells, mature fibroblasts, and collagen. The results highlight that early-stage primary tumors are secluded in the pancreas and advance towards infiltrating the omentum at week 5–7 post implantation of the BxPC-3 and Panc-1 models investigated. Late stages show extensive growth, the infiltration of the omentum and/or stomach wall, metastases, augmented fibroblasts, and collagen levels. The findings can serve as suggestions for defining growth parameter-based stages of orthotopic pancreatic cancer models for the preclinical testing of drug efficacy in the future.
Characterization of Humanized Mouse Model of Organophosphate Poisoning and Detection of Countermeasures via MALDI-MSI
Authors: Tressler Caitlin M. , Wadsworth Benjamin , Carriero Samantha , Dillman Natalie , Crawford Rachel , Hahm Tae-Hun , Glunde Kristine , Cadieux C. Linn
Published: May 2024

Organophosphoate (OP) chemicals are known to inhibit the enzyme acetylcholinesterase (AChE). Studying OP poisoning is difficult because common small animal research models have serum carboxylesterase, which contributes to animals’ resistance to OP poisoning. Historically, guinea pigs have been used for this research; however, a novel genetically modified mouse strain (KIKO) was developed with nonfunctional serum carboxylase (Es1 KO) and an altered acetylcholinesterase (AChE) gene, which expresses the amino acid sequence of the human form of the same protein (AChE KI). KIKO mice were injected with 1xLD50 of an OP nerve agent or vehicle control with or without atropine. After one to three minutes, animals were injected with 35 mg/kg of the currently fielded Reactivator countermeasure for OP poisoning. Postmortem brains were imaged on a Bruker RapifleX ToF/ToF instrument. Data confirmed the presence of increased acetylcholine in OP-exposed animals, regardless of treatment or atropine status. More interestingly, we detected a small amount of Reactivator within the brain of both exposed and unexposed animals; it is currently debated if reactivators can cross the blood–brain barrier. Further, we were able to simultaneously image acetylcholine, the primary affected neurotransmitter, as well as determine the location of both Reactivator and acetylcholine in the brain. This study, which utilized sensitive MALDI-MSI methods, characterized KIKO mice as a functional model for OP countermeasure development.