bluuebunny/crossref_metadata_2025 huggingface dataset:
Application of Machine Learning Algorithms in Predicting Rheological Behavior of BN-diamond/Thermal Oil Hybrid Nanofluids
Authors: Ali Abulhassan , Noshad Nawal , Kumar Abhishek , Ilyas Suhaib Umer , Phelan Patrick E. , Alsaady Mustafa , Nasir Rizwan , Yan Yuying
Published: January 2024

The use of nanofluids in heat transfer applications has significantly increased in recent times due to their enhanced thermal properties. It is therefore important to investigate the flow behavior and, thus, the rheology of different nanosuspensions to improve heat transfer performance. In this study, the viscosity of a BN-diamond/thermal oil hybrid nanofluid is predicted using four machine learning (ML) algorithms, i.e., random forest (RF), gradient boosting regression (GBR), Gaussian regression (GR) and artificial neural network (ANN), as a function of temperature (25–65 °C), particle concentration (0.2–0.6 wt.%), and shear rate (1–2000 s−1). Six different error matrices were employed to evaluate the performance of these models by providing a comparative analysis. The data were randomly divided into training and testing data. The algorithms were optimized for better prediction of 700 experimental data points. While all ML algorithms produced R2 values greater than 0.99, the most accurate predictions, with minimum error, were obtained by GBR. This study indicates that ML algorithms are highly accurate and reliable for the rheological predictions of nanofluids.
Continual Learning with Deep Neural Networks in Physiological Signal Data: A Survey
Authors: Li Ao , Li Huayu , Yuan Geng
Published: January 2024

Deep-learning algorithms hold promise in processing physiological signal data, including electrocardiograms (ECGs) and electroencephalograms (EEGs). However, healthcare often requires long-term monitoring, posing a challenge to traditional deep-learning models. These models are generally trained once and then deployed, which limits their ability to adapt to the dynamic and evolving nature of healthcare scenarios. Continual learning—known for its adaptive learning capabilities over time—offers a promising solution to these challenges. However, there remains an absence of consolidated literature, which reviews the techniques, applications, and challenges of continual learning specific to physiological signal analysis, as well as its future directions. Bridging this gap, our review seeks to provide an overview of the prevailing techniques and their implications for smart healthcare. We delineate the evolution from traditional approaches to the paradigms of continual learning. We aim to offer insights into the challenges faced and outline potential paths forward. Our discussion emphasizes the need for benchmarks, adaptability, computational efficiency, and user-centric design in the development of future healthcare systems.
A Sustainable Model for Healthcare Systems: The Innovative Approach of ESG and Digital Transformation
Authors: Sepetis Anastasios , Rizos Fotios , Pierrakos George , Karanikas Haralampos , Schallmo Daniel
Published: January 2024

In recent years, the globe has faced a series of topics of growing concern, such as the COVID-19 pandemic, the international financial crisis, rising socio-economic inequalities, the negative outcomes of greenhouse gas emissions, which resulted in climate change, and many others. Organizations worldwide have confronted these new challenges of sustainable finance by incorporating environmental, social, and corporate governance (ESG) factors and digital transformation (DT) in their innovation business strategies. The healthcare sector represents a large share of the global economy (about 10% of global economic output), employs a large number of workers, and needs to rely more on an open innovation model where interested parties, especially patients, are going to have a say in their own well-being. Thus, it is imperative that healthcare providers be efficient, effective, resilient, and sustainable in the face of significant challenges and risks. At the same time, they must offer sustainable development goals and digital transformation to healthcare users through limited governmental resources. This study investigates the role, importance, and correlation of ESG factors and digital transformation to the sustainable finance of healthcare systems through an innovative model. The main purpose of the paper is to present the already implemented ESG and DT factors in the healthcare sector and to propose a mutual and combined implementation strategy based on common evaluation tools, methods, and actions. A set of proposed actions and strategies are presented for the sustainability and resilience of the healthcare sector.
Transcription Factor MdPLT1 Involved Adventitious Root Initiation in Apple Rootstocks
Authors: Wang Hongming , Ba Guang , Uwamungu Jean Yves , Ma Wenjuan , Yang Linna
Published: January 2024

The induction of adventitious roots is a key factor restricting the vegetative propagation of apple dwarf rootstocks. PLETHORA (PLT) transcription factors are involved in the regulation of plant stem cell niche and adventitious root development. In this study, we identified the PLT1 gene in apples by bioinformatics and analyzed its evolutionary relationship. The MdPLT1 gene was cloned from M9-T337 to verify its subcellular localization and analyze its function in transgenic tobacco. The MdPLT1 protein contained two conserved AP2 domains which may be similar to those of poplar the PtrPLT2a and PtrPLT2b with 85% support. The CDS sequence of the MdPLT1 gene was 1638 bp, encoding 545 amino acids. The transcription factor MdPLT1 was localized in the nucleus. The number of adventitious roots of tobacco plants overexpressing MdPLT1 significantly increased. In the adventitious roots of MdPLT1-overexpressed plants, the expression levels of genes related to the NtPINs family and the NtYUCCAs family were significantly increased. The results showed that MdPLT1 positively regulated adventitious root formation. This study provided a theoretical basis for the establishment of the fast vegetative propagation of apple dwarf rootstocks.
Assessment of Phytotoxicity in Untreated and Electrochemically Treated Leachates through the Analysis of Early Seed Growth and Inductively Coupled Plasma-Optical Emission Spectroscopy Characterization
Authors: Martínez-Cruz Alfredo , Rojas-Valencia María Neftalí
Published: January 2024

The treatment of stabilized leachates with high refractory organic matter content, which are over 10 years old, presents a challenge. This study explored the potential of electro-coagulation (EC) and electro-oxidation (EO) treatment systems to address this issue. The objective of this study was to investigate the phytotoxicity of the proposed treatment system on seed growth and examine possible relationships between phytotoxicity results and the characterization of leachates, effluents, soil, and radicles. Phytotoxicity tests were conducted on seeds of Lactuca sativa, Cucumis sativus, and Phaseolus vulgaris, using Inductively Coupled Plasma-Optical analysis. The evolution of organic matter was monitored by fractionating the chemical oxygen demand (COD) and humic substances. The biodegradability index increased from 0.094 in raw leachate to 0.26 and 0.48 with EC and EO, respectively. Removal rates of 82%, 86%, 99%, and 81% were achieved for COD, dissolved organic carbon, color, and ammoniacal nitrogen, respectively. The biodegradable COD increased from 26% in raw leachate to 39% in the EC process and 58% in the EO process effluent. The proposed treatment system successfully broke the aromatic structures of the humic substances present in the raw leachate, thereby increasing the content of biodegradable material. Phytotoxicity tests revealed that the proposed treatment system significantly reduced the phytotoxicity of the generated effluents.
Does COVID-19 Vaccination Protect Contact Persons? A Systematic Review
Authors: Kampf Günter
Published: January 2024

The protective effect of COVID-19 vaccination for contact persons is controversial. Therefore, the aim of this review was to determine whether COVID-19 vaccination provides significant protection for them. A PubMed search was carried out using the terms “unvaccinated vaccinated covid” in combination with “viral load” and “transmission”. Studies were included if they reported original comparative data on the SARS-CoV-2 viral load, duration of SARS-CoV-2 detection, or SARS-CoV-2 transmission rates. A total of 332 articles were identified, of which 68 were included and analyzed. The differences in the viral load were equivocal in 57% of the 35 studies, significantly lower in the vaccinated in 11 studies and in the unvaccinated in 3 studies. The infectious virus levels were significantly lower in the vaccinated in two out of six studies. Virus clearance was significantly faster in vaccinated subjects in two of eight studies (detection of viral RNA) and two of four studies (detection of infectious virus). The secondary attack rates were significantly lower in vaccinated index cases in 6 of 15 studies. The vaccination status of contacts was described in two of the six studies and was 31.8% and 39.9% lower in households with an unvaccinated index case. The inconsistent and variable differences in the viral load, viral clearance and secondary attack rates between vaccinated and unvaccinated individuals, especially during the omicron predominance, suggests that COVID-19 vaccination is unlikely to prevent a relevant proportion of transmissions to contact persons, taking into account the relevance of the immunological status of the contact population (vaccination rates and previous infection).
An Improved Chromosome-Level Genome Assembly of the Firefly Pyrocoelia pectoralis
Authors: Fu Xinhua , Meyer-Rochow Victor Benno , Ballantyne Lesley , Zhu Xinlei
Published: January 2024

The endemic and endangered Chinese firefly Pyrocoelia pectoralis is a sexually dimorphic, nocturnal species. A previous attempt by this team to assemble a draft genome of P. pectoralis using PacBio and Illumina HiSeq X Ten platforms was limited in its usefulness by high redundancy and contamination. This prompted us to conduct an improved chromosome-level genome assembly of P. pectoralis. Ten chromosomes were further assembled based on Hi-C data to a 532.25 Mb final size with a 52.87 Mb scaffold N50. The total repeat lengths in the genome of P. pectoralis amount to 227.69 Mb; 42.78%. In total, 12,789 genes could be functionally annotated using at least one public database. Phylogenetic inference indicated that P. pectoralis and P. pyralis diverged ~51.41 million years ago. Gene family expansion and contraction analysis of 12 species were performed, and 546 expanded and 2660 contracted gene families were identified in P. pectoralis. We generated a high-quality draft of the P. pectoralis genome. This genome assembly should help promote research on the species’ sexual dimorphism and its unique courtship behavior, which involves a combination of pheromonal and bioluminescent signals. It also can serve as a resource for accelerating genome-assisted improvements in the conservation of this species.
Diagnostic Tool for the Identification of Bactrocera dorsalis (Hendel) (Diptera: Tephritidae) Using Real-Time PCR
Authors: Rizzo Domenico , Zubieta Claudia Gabriela , Sacchetti Patrizia , Marrucci Andrea , Miele Fortuna , Ascolese Roberta , Nugnes Francesco , Bernardo Umberto
Published: January 2024

Accurate identification of Bactrocera dorsalis (Hendel) (Diptera: Tephritidae), commonly known as the Oriental fruit fly, is a significant challenge due to the morphological convergence and taxonomic uncertainties of species belonging to the same genus. This highly polyphagous species poses a significant threat to fruit crops. With its potential establishment in Europe becoming a growing concern, there is an urgent need for rapid and efficient diagnostic methods. The study presented here introduces a diagnostic protocol based on real-time PCR using a TaqMan probe for the early and reproducible identification of B. dorsalis. Specimens representing the genetic diversity of the Italian population were collected and analyzed. Specific primers and probe were designed based on the conserved regions and an in silico analysis confirmed their specificity. The assay conditions were optimized, and analytical sensitivity, specificity, repeatability, and reproducibility were evaluated. The protocol showed high sensitivity and specificity, accurately detecting low DNA concentrations of B. dorsalis. This standardized method provides a reliable tool for routine diagnostics, enhancing the accuracy and efficiency of identifying the Oriental fruit fly at all stages of its development, thereby facilitating effective pest management measures. The development of this diagnostic protocol is crucial for monitoring and supporting efforts to prevent the passive spread of B. dorsalis in Europe, particularly in light of the recent active infestations detected in Italy.
Well-Being, Self-Esteem and Temporal Perspective in Incels: An Italian Study
Authors: Scaffidi Abbate Costanza , Rapacciuolo Federica , Miceli Silvana
Published: January 2024

The global scholarly attention has shifted toward the phenomenon of inceldom (involuntary celibacy) due to violent incidents involving self-identified incels. There is a growing number of platforms promoting the proliferation of these ideologies, and cases of violence are becoming increasingly severe. This research constitutes one of the limited empirical investigations within an Italian context. This study aims to examine the mental well-being and its associations with self-esteem and temporal perspectives among individuals identifying as incels. Fifty-eighth male subjects aged between 18 and 45 years old participated in the study. Participants, recruited through online communication channels, completed three questionnaires focused on assessing mental well-being, self-esteem, and temporal orientation. The results reveal that incel subjects exhibit low self-esteem and are inclined toward a hedonistic present-focused perspective aimed at immediate gratification rather than future planning. Of note are the data related to the future temporal perspective, which does not show any predictive value on the well-being of incel subjects. Their ability to plan for the long term, defer immediate gratification, and control behavior through the anticipation and evaluation of possible consequences appears diminished. This study discusses the implications of developing targeted intervention programs, given that the incel phenomenon is becoming increasingly widespread. It is, therefore, crucial not to underestimate the potential threat that inceldom could pose in the future.
Development and Validation of Case-Finding Algorithms for Digestive Cancer in the Spanish Healthcare Database BIFAP
Authors: Fernández-Antón Encarnación , Rodríguez-Miguel Antonio , Gil Miguel , Castellano-López Amelia , de Abajo Francisco J.
Published: January 2024

Background: electronic health records (EHRs) are helpful tools in epidemiology despite not being primarily collected for research. In Spain, primary care physicians play a central role and manage patients even in specialized care. All of this introduces variability that may lead to diagnostic inconsistencies. Therefore, data validation studies are crucial, so we aimed to develop and validate case-finding algorithms for digestive cancer in the primary care database BIFAP. Methods: from 2001 to 2019, subjects aged 40–89 without a cancer history were included. Case-finding algorithms using diagnostic codes and text-mining were built. We randomly sampled, clustered, and manually reviewed 816 EHRs. Then, positive predictive values (PPVs) and 95% confidence intervals (95% CIs) for each cancer were computed. Age and sex standardized incidence rates (SIRs) were compared with those reported by the National Cancer Registry (REDECAN). Results: we identified 95,672 potential cases. After validation, the PPV (95% CI) for hepato-biliary cancer was 87.6% (81.8–93.4), for esophageal cancer, it was 96.2% (93.1–99.2), for pancreatic cancer, it was 89.4% (84.5–94.3), for gastric cancer, it was 92.5% (88.3–96.6), and for colorectal cancer, it was 95.2% (92.1–98.4). The SIRs were comparable to those reported by the REDECAN. Conclusions: the case-finding algorithms demonstrated high performance, supporting BIFAP as a suitable source of information to conduct epidemiologic studies of digestive cancer.
A Comprehensive Review of Risk Factors and Thrombophilia Evaluation in Venous Thromboembolism
Authors: Dicks Andrew B. , Moussallem Elie , Stanbro Marcus , Walls Jay , Gandhi Sagar , Gray Bruce H.
Published: January 2024

Venous thromboembolism (VTE), which encompasses deep vein thrombosis (DVT) and pulmonary embolism (PE), is a significant cause of morbidity and mortality worldwide. There are many factors, both acquired and inherited, known to increase the risk of VTE. Most of these result in increased risk via several common mechanisms including circulatory stasis, endothelial damage, or increased hypercoagulability. Overall, a risk factor can be identified in the majority of patients with VTE; however, not all risk factors carry the same predictive value. It is important for clinicians to understand the potency of each individual risk factor when managing patients who have a VTE or are at risk of developing VTE. With this, many providers consider performing a thrombophilia evaluation to further define a patient’s risk. However, guidance on who to test and when to test is controversial and not always clear. This comprehensive review attempts to address these aspects/concerns by providing an overview of the multifaceted risk factors associated with VTE as well as examining the role of performing a thrombophilia evaluation, including the indications and timing of performing such an evaluation.
Improved Loss Function for Mass Segmentation in Mammography Images Using Density and Mass Size
Authors: Aliniya Parvaneh , Nicolescu Mircea , Nicolescu Monica , Bebis George
Published: January 2024

Mass segmentation is one of the fundamental tasks used when identifying breast cancer due to the comprehensive information it provides, including the location, size, and border of the masses. Despite significant improvement in the performance of the task, certain properties of the data, such as pixel class imbalance and the diverse appearance and sizes of masses, remain challenging. Recently, there has been a surge in articles proposing to address pixel class imbalance through the formulation of the loss function. While demonstrating an enhancement in performance, they mostly fail to address the problem comprehensively. In this paper, we propose a new perspective on the calculation of the loss that enables the binary segmentation loss to incorporate the sample-level information and region-level losses in a hybrid loss setting. We propose two variations of the loss to include mass size and density in the loss calculation. Also, we introduce a single loss variant using the idea of utilizing mass size and density to enhance focal loss. We tested the proposed method on benchmark datasets: CBIS-DDSM and INbreast. Our approach outperformed the baseline and state-of-the-art methods on both datasets.
Integrated Inbound and Outbound Scheduling for Coal Port: Constraint Programming and Adaptive Local Search
Authors: Lu Xuan , Zhang Yu , Zheng Lanbo , Yang Caiyun , Wang Junjie
Published: January 2024

The effective production scheduling of dry bulk ports is a challenging task that demands meticulous planning, task allocation based on customer requirements, as well as strategic route and timing scheduling. Dry bulk ports dedicated to handling commodities like coal and iron ore frequently engage in blending operations as a strategic imperative to gain market competitiveness. The process of blending coal and ore entails the timely arrival of the requisite raw materials at predetermined locations. Simultaneously, it necessitates the coordination of the sequencing of goods entering and departing the port to align with the operational demands associated with material stockpiles. This paper describes and analyzes an operational scheduling problem encountered by one of the largest coal blending sea ports in China. Specifically, a rich constraint programming model is presented to define operation sequences integrating daily inbound and outbound services provided by the port, minimizing the overall operation time. In order to enhance the practicality of the method, a CP-based adaptive simulated annealing local search algorithm has been designed and developed for the optimization problem. The empirical validation of the proposed method is conducted using both real production data and generated experimental data adhering to specific rules. The results conclusively demonstrate the efficacy and feasibility of the proposed method. This also substantiates its practicality and effectiveness in real-world applications, facilitating efficient production and energy-saving operations for the coal port.
UAV Path Planning for Container Terminal Yard Inspection in a Port Environment
Authors: Tang Gang , Wang Chenyuan , Zhang Zhao , Men Shaoyang
Published: January 2024

Container terminal yards are automated terminal yards. The rail-mounted gantry crane (RMGC) and rail-mounted gantry crane tracks (RMGCTs) that frequently operate in terminal yards need to be inspected regularly to ensure the safe operation of container transportation in the yard. This paper proposes a framework for the path planning of RMGCT visual inspection using a UAV in container terminal yards in a port environment. The framework consisted of two main aspects. First, a global path to all inspection viewpoints was planned according to the inspection requirements using the A* algorithm and the improved minimum snap method. Second, the intelligent bidirectional rapidly exploring random trees star (IB-RRT*) algorithm was introduced to plan the local path during the flight of the UAV. Finally, the feasibility of the path-planning framework was demonstrated using simulation experiments.
A Lightweight Network Based on Multi-Scale Asymmetric Convolutional Neural Networks with Attention Mechanism for Ship-Radiated Noise Classification
Authors: Yan Chenhong , Yan Shefeng , Yao Tianyi , Yu Yang , Pan Guang , Liu Lu , Wang Mou , Bai Jisheng
Published: January 2024

Ship-radiated noise classification is critical in ocean acoustics. Recently, the feature extraction method combined with time–frequency spectrograms and convolutional neural networks (CNNs) has effectively described the differences between various underwater targets. However, many existing CNNs are challenging to apply to embedded devices because of their high computational costs. This paper introduces a lightweight network based on multi-scale asymmetric CNNs with an attention mechanism (MA-CNN-A) for ship-radiated noise classification. Specifically, according to the multi-resolution analysis relying on the relationship between multi-scale convolution kernels and feature maps, MA-CNN-A can autonomously extract more fine-grained multi-scale features from the time–frequency domain. Meanwhile, the MA-CNN-A maintains its light weight by employing asymmetric convolutions to balance accuracy and efficiency. The number of parameters introduced by the attention mechanism only accounts for 0.02‰ of the model parameters. Experiments on the DeepShip dataset demonstrate that the MA-CNN-A outperforms some state-of-the-art networks with a recognition accuracy of 98.2% and significantly decreases the parameters. Compared with the CNN based on three-scale square convolutions, our method has a 68.1% reduction in parameters with improved recognition accuracy. The results of ablation explorations prove that the improvements benefit from asymmetric convolution, multi-scale block, and attention mechanism. Additionally, MA-CNN-A shows a robust performance against various interferences.
Propagation Velocity of Excitation Waves Caused by Turbidity Currents
Authors: Xu Guohui , Sun Shiqing , Ren Yupeng , Li Meng , Chen Zhiyuan
Published: January 2024

Turbidity currents are important carriers for transporting terrestrial sediment into the deep sea, facilitating the transfer of matter and energy between land and the deep sea. Previous studies have suggested that turbidity currents can exhibit high velocities during their movement in submarine canyons. However, the maximum vertical descent velocity of high-concentration turbid water simulating turbidity currents does not exceed 1 m/s, which does not support the understanding that turbidity currents can reach speeds of over twenty meters per second in submarine canyons. During their movement, turbidity currents can compress and push the water ahead, generating propagating waves. These waves, known as excitation waves, exert a force on the seafloor, resuspending bottom sediments and potentially leading to the generation of secondary turbidity currents downstream. Therefore, the propagation distance of excitation waves is not the same as the initial journey of the turbidity currents, and the velocity of excitation waves within this journey has been mistakenly regarded as the velocity of the turbidity currents. Research on the propagation velocity of excitation waves is of great significance for understanding the sediment supply patterns of turbidity currents and the transport patterns of deep-sea sediments. In this study, numerical simulations were conducted to investigate the velocity of excitation waves induced by turbidity currents and to explore the factors that can affect their propagation velocity and amplitude. The relationship between the velocity and amplitude of excitation waves and different influencing factors was determined. The results indicate that the propagation velocity of excitation waves induced by turbidity currents is primarily determined by the water depth, and an expression (v2 = 0.63gh) for the propagation velocity of excitation waves is provided.
First Record of Flavocillium subprimulinum (Cordycipitaceae, Hypocreales) in Mexico: Morphological and Molecular Characterisation, Nematocidal Activity of Its Liquid Culture Filtrates against Haemonchus contortus and Protease Activity
Authors: Pérez-Anzúrez Gustavo , Mendoza-de Gives Pedro , Olmedo-Juárez Agustín , López-Arellano María Eugenia , Bautista-García Génesis Andrea , Ocampo-Gutiérrez Ana Yuridia , von Son-de Fernex Elke , Alonso-Díaz Miguel Ángel , Delgado-Núñez Edgar Jesús , Paz-Silva Adolfo
Published: January 2024

This is the first record of the fungus Flavocillium subprimulinum in Mexico. The isolate was taxonomically characterised and cultured in potato dextrose broth (PDB), Czapek–Dox broth (CzDoxB), and sweet potato dextrose broth (SPDB) to obtain its filtrates (FLCF). The nematocidal activity (NA) of three FLCF concentrations was assessed against Haemonchus contortus L3. Protease activity (PA) was assessed with SDS-PAGE, followed by a zymogram. The NA of the FLCF reached 94.43% in PDB and 95.82% in CzDoxB, respectively, at 100 mg/mL. Lower mortality (64%) was found in SPDB at 100 mg/mL. SDS-PAGE showed bands (in PBS) of ~25, ~40, and ~55 kDa. The zymogram showed protein bands (PBs) with PA in the media, including PBs of ~14, ~40, and ~55 kDa. This study establishes the basis for exploring the potential use of this fungus against H. contortus, which is considered the most pathogenic parasite affecting lambs.
Multi-Omics Reveals the Role of Osteopontin/Secreted Phosphoprotein 1 in Regulating Ovarian Aging
Authors: Hsu Li-Chuan , Li Chia-Jung , Lin Li-Te , Pan Li-Fei , Wen Zhi-Hong , Sheu Jim Jinn-Chyuan , Tsui Kuan-Hao
Published: January 2024

Secreted phosphoprotein 1 (SPP1), also known as osteopontin (OPN), is located on chromosome 4q22.1. This multifunctional secreted acidic glycoprotein is expressed intracellularly and extracellularly in various tissues, where it interacts with regulatory proteins and pro-inflammatory immune chemokines, contributing to the pathogenesis of multiple diseases. Nevertheless, the intricate genetic connections between SPP1 and ovarian aging remain largely unexplored. This study aims to bridge this knowledge gap by delving into ovarian aging and its associations with SPP1 using multi-omics data analysis. Our findings indicate that SPP1 is a potential gene related to ovarian aging. To comprehend the role of SPP1, we conducted spatial transcriptomic analyses on young and aged female mouse ovaries, revealing a significant decline in SPP1 expression in the aging group compared to the young group. Similarly, a significantly low level of SPP1 was found in the 73-year-old sample. Additionally, in-depth single-cell RNA-sequencing analysis identified associations between SPP1 and ITGAV, ITGB1, CD44, MMP3, and FN1. Notably, co-expression analysis highlighted a strong correlation between SPP1 and ITGB1. In summary, this study pioneers the identification of SPP1 as a gene implicated in ovarian aging. Further research into the role of SPP1 has the potential to advance precision medicine and improve treatment strategies for ovarian aging-related conditions.
Neighborhood Does Matter: Farmers’ Local Social Interactions and Land Rental Behaviors in China
Authors: Gu Jiafeng
Published: January 2024

The transfer of farmland is an important area of rural development research; however, the impact of rural social networks has been neglected in studies. The aim of this study is to explore the effects, mechanisms, and heterogeneity of neighbors’ behavior on the process of land renting by farmers. Based on the data of the China Family Panel Studies in 2018, this research empirically analyzes the impact of community-level, local social interactions on the land rental behavior of farmers and its mechanisms using a spatial probit model. The results of this study indicate that neighbors’ land rental behavior positively and significantly affects that of other farmers in the same village. In addition, neighbors’ land rental encourages other farmers in the same village to follow suit through an increase in the perceived importance of the Internet among the farmers. In addition, there is heterogeneity in neighborhood influence. Notably, the impact of social networks on the renting out of the land by farmers, as evidenced in this study, is a key factor in accelerating the circulation of rural land and promoting rural development, thus contributing to the process of rural revitalization and its recording in the literature.
On the Asymptotic of Solutions of Odd-Order Two-Term Differential Equations
Authors: Sultanaev Yaudat T. , Valeev Nur F. , Nazirova Elvira A.
Published: January 2024

This work is devoted to the development of methods for constructing asymptotic formulas as x→∞ of a fundamental system of solutions of linear differential equations generated by a symmetric two-term differential expression of odd order. The coefficients of the differential expression belong to classes of functions that allow oscillation (for example, those that do not satisfy the classical Titchmarsh–Levitan regularity conditions). As a model equation, the fifth-order equation i2p(x)y‴″+p(x)y″‴+q(x)y=λy, along with various behaviors of coefficients p(x),q(x), is investigated. New asymptotic formulas are obtained for the case when the function h(x)=−1+p−1/2(x)∉L1[1,∞) significantly influences the asymptotics of solutions to the equation. The case when the equation contains a nontrivial bifurcation parameter is studied.
The Application of Residual Connection-Based State Normalization Method in GAIL
Authors: Ge Yanning , Huang Tao , Wang Xiaoding , Zheng Guolong , Yang Xu
Published: January 2024

In the domain of reinforcement learning (RL), deriving efficacious state representations and maintaining algorithmic stability are crucial for optimal agent performance. However, the inherent dynamism of state representations often complicates the normalization procedure. To overcome these challenges, we present an innovative RL framework that integrates state normalization techniques with residual connections and incorporates attention mechanisms into generative adversarial imitation learning (GAIL). This combination not only enhances the expressive capability of state representations, thereby improving the agent’s accuracy in state recognition, but also significantly mitigates the common issues of gradient dissipation and explosion. Compared to traditional RL algorithms, GAIL combined with the residual connection-based state normalization method empowers the agent to markedly reduce the exploration duration such that feedback concerning rewards in the current state can be provided in real time. Empirical evaluations demonstrate the superior efficacy of this methodology across various RL environments.
Classification Methods for the Serological Status Based on Mixtures of Skew-Normal and Skew-t Distributions
Authors: Dias-Domingues Tiago , Mouriño Helena , Sepúlveda Nuno
Published: January 2024

Gaussian mixture models are widely employed in serological data analysis to discern between seropositive and seronegative individuals. However, serological populations often exhibit significant skewness, making symmetric distributions like Normal or Student-t distributions unreliable. In this study, we propose finite mixture models based on Skew-Normal and Skew-t distributions for serological data analysis. Although these distributions are well established in the literature, their application to serological data needs further exploration, with emphasis on the determination of the threshold that distinguishes seronegative from seropositive populations. Our previous work proposed three methods to estimate the cutoff point when the true serological status is unknown. This paper aims to compare the three cutoff techniques in terms of their reliability to estimate the true threshold value. To attain this goal, we conducted a Monte Carlo simulation study. The proposed cutoff points were also applied to an antibody dataset against four SARS-CoV-2 virus antigens where the true serological status is known. For this real dataset, we also compared the performance of our estimated cutoff points with the ROC curve method, commonly used in situations where the true serological status is known.
Thermodynamic Modeling of the Drowning-Out Crystallization Process for LiOH and CHLiO2
Authors: González Raquel , Barrueto Yahaira , Jiménez Yecid P.
Published: January 2024

This study focuses on the thermodynamic modeling of the crystallization by the drowning process for two lithium salts: lithium hydroxide (LiOH) and lithium formate (CHLiO2). The modeling involves utilizing thermodynamic properties, such as the activity, osmotic, and solubility coefficients, within the ternary systems of LiOH + cosolvent + water and CHLiO2 + cosolvent + water, as well as their respective binary constituent systems. Ethanol is chosen as the cosolvent for both salts, facilitating a comparative analysis. Given the limited availability of thermodynamic data for lithium formate with different cosolvents, the study aims to address this gap. The modified Pitzer model was employed for the modeling process, where the parameters were successfully obtained for both systems, with a deviation of less than 1%. Additionally, the mass and energy balance for the drowning-out crystallization process of both salts was performed.
Screening of Microorganisms from Wastes and Identification of the Optimal Substrate for Biosurfactant Production
Authors: Biktasheva Liliya , Gordeev Alexander , Kirichenko Anastasia , Kuryntseva Polina , Selivanovskaya Svetlana
Published: January 2024

The production of biosurfactants from organic wastes has received significant attention due to its potential cost savings. This study involved the isolation of biosurfactant-producing microorganisms from waste sources. The surfactant properties of the 37 studied isolates were assessed by reducing surface tension and their emulsifying properties, determined by the emulsification index E24. We assessed the ability of these isolated strains to produce biosurfactants using various waste substrates, namely potato peelings, waste cooking oil and sunflower cake. Our results showed that sunflower cake exhibited better growth and biosurfactant production for most of the strains studied. This highlights that sunflower cake is a potentially effective and economical substrate for the production of biosurfactants. The most effective strains allowing to achieve an emulsification index above 50% and reduce surface tension below 40 mN m−1 were Enterobacter sp. 2pp, strain 2wfo, Peribacillus sp. 1mo, Sphingomonas sp. 2mo, Ochrobactrum sp. 5mo, Shouchella sp. 6mo, Bacillus sp. 1os, Bacillus sp. 2os. Among these strains, both previously known strains as biosurfactant producers and previously unknown strains were found. Thus, we found that among representatives of the genus Sphingomonas there are effective producers of biosurfactants. The highest yield of biosurfactant on a medium with glycerol and glucose was shown by the Bacillus sp. 2os strain of 0.501 and 0.636 g L−1, respectively.
Monitoring of Mineral Processing Operations with Isolation Forests
Authors: Aldrich Chris , Liu Xiu
Published: January 2024

Reliable monitoring of mineral process systems is key to more efficient plant operation. Multivariate statistical process control based on principal component analysis is well-established in industry but may not be effective when dealing with dynamic nonlinear or transient processes, where process behavior may change rapidly from time to time. Although a large variety of nonlinear models have been proposed to address these problems, the monitoring of complex dynamic process systems remains challenging. Isolation forests are unsupervised machine learning models that provide an interesting approach to process monitoring that has not been explored extensively yet. In this investigation, this approach is compared with traditional multivariate statistical process monitoring based on principal component models. Three real-world case studies are considered. The first case study is based on coal flotation, the second is based on features extracted from a platinum group metal flotation froth; and the third is based on data from an industrial semi-autogenous grinding circuit. In each case, the models were trained on data representing normal operating conditions and then tested on new process data that were generally different from the training data to test their ability to identify these data as out-of-control. The isolation forest models performed better than the principal component models when the data were nonlinear, but not when the data associated with normal operation and faulty conditions were linearly separable, as was the case with the flotation data.
Determination of Save Excavation Criteria in Velenje Coal Mine
Authors: Vukelić Željko , Šporin Jurij
Published: January 2024

Ensuring safe conditions for mining coal under water-bearing sands in the Velenje coal mine depends on the designed parameters of hydrogeology, geomechanics and drainage. The purpose of the research is to predict and simulate the hydrostatic pressures above the excavation fields in order to determine the thickness of the insulation layers and the height of the excavation. Coal occurs in the Velenje basin in the form of a slightly concave lens. Directly above the coal seam is an insulating layer of marl or clay. Above the insulating layer are more or less permeable Pliocene sands in which water can accumulate under layer pressure, posing a potential risk of water ingress into underground spaces. In addition to the Pliocene sands, triad layers of different ages and lithology in the bedrock also pose a risk of water intrusion. In order to prevent the intrusion of water into the working areas of underground objects, the criteria for safe mining in the Velenje coal mine under aquifers were established. The scientific research approach to determining the criteria for safe mining enables the safety and determination of excavation heights in coal mining. The following data are required for such a calculation: the water pressure in the first sands, the excavation depth below the surface, the thickness of the insulating layer and the method of excavation or the course of the demolition processes.
The Effect of Adding CeO2 Nanoparticles to Cu–Ni–Al Alloy for High Temperatures Applications
Authors: Martínez Carola , Arcos Camila , Briones Francisco , Machado Izabel , Sancy Mamié , Bustamante Marion
Published: January 2024

This work presents the effect of CeO2 nanoparticles (CeO2–NPs) on Cu–50Ni–5Al alloys on morphological, microstructural, degradation, and electrochemical behavior at high temperatures. The samples obtained by mechanical alloying and spark plasma sintering were exposed to a molten eutectic mixture of Li2CO3–K2CO3 for 504 h. The degradation of the materials was analyzed using gravimetry measurements and electrochemical impedance spectroscopy. Different characterization techniques, such as X-ray diffraction and scanning electron microscopy, were used to investigate the phase composition, parameter lattice, and microstructure of Cu–Ni–Al alloys reinforced with CeO2–NPs. The hardness of the composite was also examined using the Vickers hardness test. Gravimetry measurements revealed that the sample with 1 wt.% CeO2–NPs presented the best response to degradation with a less drastic mass variation. Impedance analysis also revealed that by adding 1 wt.% CeO2–NPs, the impedance modulus increased, which is related to a lower porosity of the oxide film or a thicker oxide layer. The microhardness also significantly increased, incorporating 1 wt.% CeO2–NPs, which reduced with higher CeO2–NPs content, which is possibly associated with a more uniform distribution using 1 wt.% CeO2–NPs in the Cu–Ni–Al matrix that avoided the aggregation phenomenon.
Bicarbazole-Benzophenone-Based Twisted Donor-Acceptor-Donor Derivatives as Blue Emitters for Highly Efficient Fluorescent Organic Light-Emitting Diodes
Authors: Blazevicius Dovydas , Siddiqui Iram , Gautam Prakalp , Krucaite Gintare , Tavgeniene Daiva , Nagar Mangey Ram , Kumar Krishan , Banik Subrata , Jou Jwo-Huei , Grigalevicius Saulius
Published: January 2024

This paper delves into the development of a group of twisted donor-acceptor-donor (D-A-D) derivatives incorporating bicarbazole as electron donor and benzophenone as electron acceptor for potential use as blue emitters in OLEDs. The derivatives were synthesized in a reaction of 4,4′-difluorobenzophenone with various 9-alkyl-9′H-3,3′-bicarbazoles. The materials, namely, DB14, DB23, and DB29, were designed with different alkyl side chains to enhance their solubility and film-forming properties of layers formed using the spin-coating from solution method. The new materials demonstrate high thermal stabilities with decomposition temperatures >383 °C, glass transition temperatures in the range of 95–145 °C, high blue photoluminescence quantum yields (>52%), and short decay times, which range in nanoseconds. Due to their characteristics, the derivatives were used as blue emitters in OLED devices. Some of the OLEDs incorporating the DB23 emitter demonstrated a high external quantum efficiency (EQEmax) of 5.3%, which is very similar to the theoretical limit of the first-generation devices.
Iron Intake and Human Health
Authors: Latunde-Dada Gladys O.
Published: January 2024

Iron deficiency anemia (IDA) is a global nutritional disorder affecting large population groups in varying magnitudes in different countries [...]
A Randomized Controlled Trial on the Effects of Leucine-Supplement Combined with Nutritional Counseling on Body Composition in Mix Cancer Older Men
Authors: Soares Jéssika D. P. , Siqueira Jéssika M. , Brito Flávia dos S. B. , Pimentel Gustavo D.
Published: January 2024

Background: Malnutrition and metabolic alterations of cancer cachexia are often associated with negative weight loss and muscle mass wasting. In this sense, protein supplementation can be a strategy to help counteract the loss and/or maintenance of mass in these patients. The aim of this study was to evaluate the effect of leucine supplementation on body composition in outpatients with gastrointestinal tract cancer. Methods: It was a randomized, blinded, controlled, parallel trial, performed in male patients with a cancer diagnosis of the gastrointestinal tract and appendix organs undergoing chemotherapy. All the patients were allocated to one of the protocol groups: L-leucine supplement or the control group, during 8 weeks of intervention. We evaluated the body composition through bioelectrical impedance analysis, the cancer cachexia classification, and the diet intake before and after the intervention protocol. The intention-to-treat approach was performed to predict the missing values for all patients who provide any observation data. Results: The patients were an average age of 65.11 ± 7.50 years old. In the body composition analysis with patients who finished all the supplementation, we observed a significant gain in body weight (61.79.9 ± 9.02 versus 64.06 ± 9.45, p = 0.01), ASMM (7.64 ± 1.24 versus 7.81 ± 1.20, p = 0.02) in the Leucine group, whereas patients in the control did not present significant variation in these parameters. There was no significant intergroup difference. While in the analysis included the patients with intention-to-treat, we found a significant increase in body weight (p = 0.01), BMI (p = 0.01), FFM (p = 0.03), and ASMM (p = 0.01) in the Leucine group. No significant intergroup differences. These results also similar among cachectic patients. Conclusion: A balanced diet enriched with free-Leucine supplementation was able to promotes gains in body weight and lean mass in older men diagnosticated with gastrointestinal and appendix organs of digestion cancer after 8 weeks. However, the fact that most men are non-cachectic or pre-cachectic is not clear if the increase in muscle mass was due to a high intake of leucine, since no difference between groups was detected. Moreover, we know that benefits on body composition are due to adequate calorie and macronutrients consumption and that balanced feeding according to nutrition Guidelines seems crucial and must be advised during the oncological treatment.
Examining How Postpartum Videoconferencing Support Sessions Can Facilitate Connections between Parents: A Poststructural and Sociomaterial Analysis
Authors: Aston Megan , Price Sheri , MacLeod Anna , Stone Kathryn , Benoit Britney , Joy Phillip , Ollivier Rachel , Sim Meaghan , Etowa Josephine , Jack Susan , Marcellus Lenora , Iduye Damilola
Published: January 2024

Postpartum support for new parents can normalize experiences, increase confidence, and lead to positive health outcomes. While in-person gatherings may be the preferred choice, not all parents can or want to join parenting groups in person. Online asynchronous chat spaces for parents have increased over the past 10 years, especially during the COVID pandemic, when “online” became the norm. However, synchronous postpartum support groups have not been as accessible. The purpose of our study was to examine how parents experienced postpartum videoconferencing support sessions. Seven one-hour videoconferencing sessions were conducted with 4–8 parents in each group (n = 37). Nineteen parents from these groups then participated in semi-structured interviews. Feminist poststructuralism and sociomaterialism were used to guide the research process and analysis. Parents used their agency to actively think about and interact using visual (camera) and audio (microphone) technologies to navigate socially constructed online discourses. Although videoconferencing fostered supportive connections and parents felt less alone and more confident, the participants also expressed a lack of opportunities for individual conversations. Nurses should be aware of the emerging opportunities that connecting online may present. This study was not registered.