bluuebunny/crossref_metadata_2025 huggingface dataset:
Non-targeted proteomic analysis of Asian elephant (Elephas maximus) seminal plasma using an in-solution digestion technique and liquid chromatography tandem-mass spectrometry
Authors: Wattananit Podjana , Yingchutrakul Yodying , Kornkaewrat Kornchai , Mahasawangkul Sittidet , Roytrakul Sittiruk , Pinyopummin Anuchai
Published: September 2023

Seminal plasma proteins have recently been reported to play a significant role as valuable materials for understanding male reproductive biology, identifying causes of fertility problems, and developing reproductive biomarkers. Proteomic analysis of seminal plasma holds promise in advancing the understanding of male Asian elephant reproductive biology. This study aims to explore seminal plasma proteins of Asian elephants and their probable functions to provide fundamental information about male reproduction in this species. The protein solution from pooled seminal plasma from 10 bulls (a total of 33 ejaculates) was digested into peptides and identified using LC-MS/MS. Out of 986 proteins, 597 were mapped and matched with 58 species in UniProt databases, including Elephas maximus. These mapped proteins were mostly involved in binding function, catalytic activity, cellular process, and metabolic process. Only 29 mapped proteins were recognized to be related in reproductive process, mainly associated in spermatogenesis and sperm capacitation. Additionally, several seminal plasma proteins related to fertility or semen quality in other mammals were also found in Asian elephant semen, such as keratin type I, aldose reductase, thrombospondon-1, fibronectin 1, platelet-activating factor acetyl hydrolase, mannosidase, and semenogelin-2. This discovery clearly reveals the beneficial protein profile in seminal plasma of the Asian elephant and serves as a crucial step in investigating infertility and poor semen quality in this valuable species.
Effectiveness of silver diamine fluoride 38% on reduction of gingivitis in dogs: a randomized clinical trial
Authors: Kern Amarett , Renteria Tammy (White) , Rothen Marilynn L. , Mancl Lloyd A. , Milgrom Peter
Published: September 2023

Introduction

Periodontal disease is a ubiquitous disease in small animal veterinary medicine. Currently regular professional dental cleaning and daily tooth brushing are considered gold standards in the prevention of periodontal disease. Efforts to find a noninvasive, cost effective and easy to use preventative for periodontal disease are ongoing. The primary objective of this double-blind randomized clinical trial was to determine if a single application of silver diamine fluoride (SDF) 38% on the buccal surface of all teeth would reduce gingivitis within 3 months in dogs with stage two periodontal disease.

Methods

Twenty-nine client-owned dogs 3–12 years old, 6–35 pounds were randomized 1:1 into active and placebo-control groups. Both groups underwent a baseline treatment and a three-month follow-up under general anesthesia. Gingival Index (GI), Plaque Index (PI), and Calculus Index (CI) were assessed and recorded at each event.

Results

A single application of SDF 38% did not significantly lower GI relative to the control group. However, the GI score dropped significantly in both groups relative to baseline, with a 53% reduction in the average GI score for dogs that received SDF 38% treatment and a 44% reduction for dogs that received placebo treatment. There were no differences in PI or CI scores compared to control groups.

Conclusion

Further research is needed to determine if a more frequent application or a longer study duration would yield a different outcome.
Expression of vitamin D receptor, CYP24A1, and CYP27B1 in normal and inflamed canine pancreases
Authors: Lee Dohee , Kim Sanggu , Koo Yoonhoi , Chae Yeon , Wang Juwon , Kim Soochong , Yun Taesik , Yang Mhan-Pyo , Kang Byeong-Teck , Kim Hakhyun
Published: September 2023

Vitamin D plays a role in anti-inflammatory processes, and the alteration of its metabolism is associated with the inflammatory processes of pancreatitis. This study was performed to evaluate the expression of the vitamin D receptor (VDR) and the two major enzymes that regulate vitamin D metabolism, 1α-hydroxylase (CYP27B1) and 24-hydroxylase (CYP24A1), in the canine pancreas and to compare their degrees of immunoreactivity between normal and inflamed pancreases. Five normal and inflamed pancreatic tissues each were obtained from six dogs. The expression of VDR, CYP24A1, and CYP27B1 were determined immunohistochemically, and the degree of immunostaining was assessed semiquantitatively. The VDR was expressed in the ducts, acini, and islets of Langerhans of normal pancreases and in the ducts and acini of inflamed ones. There was a significant difference in the immunoreactivity score for VDR in the islets of Langerhans between normal (median, 3 [interquartile range, 2–7.5] score) and inflamed pancreatic tissues (0 [0–0.5] score, p = 0.03). CYP24A1 was expressed in the ducts and islets of Langerhans in both normal and inflamed pancreases, whereas CYP27B1 was expressed in the ducts and acini in only some normal and inflamed pancreatic tissues. This study showed that VDR expression decreased in inflamed pancreases and demonstrated CYP24A1 and CYP27B1 expression in the canine pancreas for the first time. These findings indicate that the pancreas could regulate the metabolism and biological activity of vitamin D and suggest that a decrease in these might be related to the pathophysiology of pancreatitis.
Improved YOLOv5-Based Real-Time Road Pavement Damage Detection in Road Infrastructure Management
Authors: Sami Abdullah As , Sakib Saadman , Deb Kaushik , Sarker Iqbal H.
Published: September 2023

Deep learning has enabled a straightforward, convenient method of road pavement infrastructure management that facilitates a secure, cost-effective, and efficient transportation network. Manual road pavement inspection is time-consuming and dangerous, making timely road repair difficult. This research showcases You Only Look Once version 5 (YOLOv5), the most commonly employed object detection model trained on the latest benchmark Road Damage Dataset, Road Damage Detection 2022 (RDD 2022). The RDD 2022 dataset includes four common types of road pavement damage, namely vertical cracks, horizontal cracks, alligator cracks, and potholes. This paper presents an improved deep neural network model based on YOLOv5 for real-time road pavement damage detection in photographic representations of outdoor road surfaces, making it an indispensable tool for efficient, real-time, and cost-effective road infrastructure management. The YOLOv5 model has been modified to incorporate several techniques that improve its accuracy and generalization performance. These techniques include the Efficient Channel Attention module (ECA-Net), label smoothing, the K-means++ algorithm, Focal Loss, and an additional prediction layer. In addition, a 1.9% improvement in mean average precision (mAP) and a 1.29% increase in F1-Score were attained by the model in comparison to YOLOv5s, with an increment of 1.1 million parameters. Moreover, a 0.11% improvement in mAP and 0.05% improvement in F1 score was achieved by the proposed model compared to YOLOv8s while having 3 million fewer parameters and 12 gigabytes fewer Giga Floating Point Operation per Second (GFlops).
An Improved Multi-Objective Particle Swarm Optimization Method for Rotor Airfoil Design
Authors: Wu Yongchuan , Sun Gang , Tao Jun
Published: September 2023

In this study, a multi-objective aerodynamic optimization is performed on the rotor airfoil via an improved MOPSO (multi-objective particle swarm optimization) method. A database of rotor airfoils containing both geometric and aerodynamic parameters is established, where the geometric parameters are obtained via the CST (class shape transformation) method and the aerodynamic parameters are obtained via CFD (computational fluid dynamics) simulations. On the basis of the database, a DBN (deep belief network) surrogate model is proposed and trained to accurately predict the aerodynamic parameters of the rotor airfoils. In order to improve the convergence rate and global searching ability of the standard MOPSO algorithm, an improved MOPSO framework is established. By embedding the DBN surrogate model into the improved MOPSO framework, multi-objective and multi-constraint aerodynamic optimization for the rotor airfoil is performed. Finally, the aerodynamic performance of the optimized rotor airfoil is validated through CFD simulations. The results indicate that the aerodynamic performance of the optimized rotor airfoil is improved dramatically compared with the baseline rotor airfoil.
Intelligent Detection of Lightweight “Yuluxiang” Pear in Non-Structural Environment Based on YOLO-GEW
Authors: Ren Rui , Sun Haixia , Zhang Shujuan , Wang Ning , Lu Xinyuan , Jing Jianping , Xin Mingming , Cui Tianyu
Published: September 2023

To detect quickly and accurately “Yuluxiang” pear fruits in non-structural environments, a lightweight YOLO-GEW detection model is proposed to address issues such as similar fruit color to leaves, fruit bagging, and complex environments. This model improves upon YOLOv8s by using GhostNet as its backbone for extracting features of the “Yuluxiang” pears. Additionally, an EMA attention mechanism was added before fusing each feature in the neck section to make the model focus more on the target information of “Yuluxiang” pear fruits, thereby improving target recognition ability and localization accuracy. Furthermore, the CIoU Loss was replaced with the WIoUv3 Loss as the loss function, which enhances the capability of bounding box fitting and improves model performance without increasing its size. Experimental results demonstrated that the enhanced YOLO-GEW achieves an F1 score of 84.47% and an AP of 88.83%, while only occupying 65.50% of the size of YOLOv8s. Compared to lightweight algorithms such as YOLOv8s, YOLOv7-Tiny, YOLOv6s, YOLOv5s, YOLOv4-Tiny, and YOLOv3-Tiny; there are improvements in AP by 2.32%, 1.51%, 2.95%, 2.06%, 2.92%, and 5.38% respectively. This improved model can efficiently detect “Yuluxiang” pears in non-structural environments in real-time and provides a theoretical basis for recognition systems used by picking robots.
Biochar for Sustainable Farming and Recultivation
Authors: Zhang Jiuquan , Li Caibin
Published: September 2023

Food shortage is a severe problem, with an estimated 720 to 811 million people globally facing hunger in 2020, as reported by the FAO [...]
Response of Liquid Water and Vapor Flow to Rainfall Events in Sandy Soil of Arid and Semi-Arid Regions
Authors: Lu Ting , Zheng Ce , Zhou Bao , Wu Jing , Wang Xueke , Zhao Yuan , Liu Xiuhua , Yuan Wenqian
Published: September 2023

In arid and semi-arid regions, rainfall takes on a critical significance to both agricultural and engineering construction activities, and the transport process and driving mechanism of soil water under rainfall conditions are in need of further investigation. To clarify the variations in soil moisture, temperature, and liquid and vapor flux under various rainfall scenarios, the Mu Us Sandy Land was selected as the study region, and a water–vapor–heat transport model was established using the Hydrus-1D software with in situ observed soil and meteorological data. The simulated results were in good agreement with the measured data during both the calibration and validation periods, suggesting that the model was accurate and applicable to the study region. The variations in the selected dry and rainy periods proved the significant effect of rainfall events on soil matric potential, temperature, and driving forces. When rainfall occurred, the hydraulic conductivity for liquid water rose by three to five orders of magnitude, driving the liquid water flow downward. In contrast, the vapor flux played a vital role in soil water movement, accounting for about 15% of the total water flux in the shallow layer when the soil was dry, while it became non-significant during rainy periods due to the reduction in hydraulic conductivity for vapor and the temperature gradient. These results clarified the mechanisms of soil liquid water and vapor movement in arid areas, which could provide scientific support for future studies on vegetation restoration and ecosystem sustainability in ecologically fragile areas.
Assessing the Potential of Old and Modern Serbian Wheat Genotypes: Yield Components and Nutritional Profiles in a Comprehensive Study
Authors: Urošević Dušan , Knežević Desimir , Đurić Nenad , Matković Stojšin Mirela , Kandić Vesna , Mićanović Danica , Stojiljković Jelena , Zečević Veselinka
Published: September 2023

Creating wheat genotypes characterized by high grain yield, high protein content, and favorable amino acid composition is the main goal of breeders, especially in developing countries where wheat is a staple food. An experiment with 20 wheat genotypes, released through breeding activities in the Serbian region at different periods and adapted to its pedoclimatic conditions, was conducted with the aim of determining the genetic potential of the analyzed genotypes for grain yield and quality. Due to the divergence of the examined wheat germplasm, the factor of genotype had the largest share in the variation of all yield parameters (>66%). The genotypes Zadruga and Agrounija exhibited superior abilities for overall grain yield. Also, genotype Zadruga stood out in a distinct cluster group due to high values of both thousand grain weight and grain yield per plant. A continuous improvement in protein content was found, with newer genotypes having 17.13% higher protein content compared with older genotypes. Genotype Sloga stood out with the highest protein content (13.93%). On the other hand, the old genotype Balkan was distinguished by the highest content of nonessential amino acids (61.5 g 100 g−1 protein), which makes it a good genetic resource. Genotypes Agrounija (32.62 g 100 g−1 protein) and Tanjugovka (32.47 g 100 g−1 protein) had the highest content of essential amino acids. The highest AAS value was established for tryptophan (1.81) and the lowest for lysine (0.61). Genotypes Tanjugovka and Zadruga had the highest AAS, i.e., protein completeness. The genotypes Zadruga, Tanjugovka, Agrounija, and Sloga have demonstrated high-yield capacity and possess a favorable amino acid profile, making them promising candidates for enhancing the nutritional quality of wheat and potentially benefiting human health.
Resistome and Genome Analysis of an Extensively Drug-Resistant Klebsiella michiganensis KMIB106: Characterization of a Novel KPC Plasmid pB106-1 and a Novel Cointegrate Plasmid pB106-IMP Harboring blaIMP-4 and blaSHV-12
Authors: Wang Linjing , Chen Haijun , Liu Wanting , Yang Ling , Xu Zhenbo , Chen Dingqiang
Published: September 2023

Klebsiella michiganensis is a recently emerging human pathogen causing nosocomial infections. This study aimed to characterize the complete genome sequence of a clinical Klebsiella michiganensis strain KMIB106 which exhibited extensive drug-resistance. The whole genome of the strain was sequenced using PacBio RS III systems and Illumina Nextseq 500. Annotation, transposable elements and resistance gene identification were analyzed by RAST, prokka and Plasmid Finder, respectively. According to the results, KMIB106 was resistant to multiple antimicrobials, including carbapenems, but it remained susceptible to aztreonam. The genome of KMIB106 consisted of a single chromosome and three predicted plasmids. Importantly, a novel KPC plasmid pB106-1 was found to carry the array of resistance genes in a highly different order in its variable regions, including mphA, msrE, mphE, ARR-3, addA16, sul1, dfrA27, tetD and fosA3. Plasmid pB106-2 is a typical IncFII plasmid with no resistant gene. Plasmid pB106-IMP consists of the IncN and IncX3 backbones, and two resistance genes, blaIMP-4 and blaSHV-12, were identified. Our study for the first time reported an extensively drug-resistant Klebsiella michiganensis strain recovered from a child with a respiratory infection in Southern China, which carries three mega plasmids, with pB106-1 firstly identified to carry an array of resistance genes in a distinctive order, and pB106-IMP identified as a novel IncN-IncX3 cointegrate plasmid harboring two resistance genes blaIMP-4 and blaSHV-12.
ICU-Acquired Colonization and Infection Related to Multidrug-Resistant Bacteria in COVID-19 Patients: A Narrative Review
Authors: Gaudet Alexandre , Kreitmann Louis , Nseir Saad
Published: September 2023

A large proportion of ICU-acquired infections are related to multidrug-resistant bacteria (MDR). Infections caused by these bacteria are associated with increased mortality, and prolonged duration of mechanical ventilation and ICU stay. The aim of this narrative review is to report on the association between COVID-19 and ICU-acquired colonization or infection related to MDR bacteria. Although a huge amount of literature is available on COVID-19 and MDR bacteria, only a few clinical trials have properly evaluated the association between them using a non-COVID-19 control group and accurate design and statistical methods. The results of these studies suggest that COVID-19 patients are at a similar risk of ICU-acquired MDR colonization compared to non-COVID-19 controls. However, a higher risk of ICU-acquired infection related to MDR bacteria has been reported in several studies, mainly ventilator-associated pneumonia and bloodstream infection. Several potential explanations could be provided for the high incidence of ICU-acquired infections related to MDR. Immunomodulatory treatments, such as corticosteroids, JAK2 inhibitors, and IL-6 receptor antagonist, might play a role in the pathogenesis of these infections. Additionally, a longer stay in the ICU was reported in COVID-19 patients, resulting in higher exposure to well-known risk factors for ICU-acquired MDR infections, such as invasive procedures and antimicrobial treatment. Another possible explanation is the surge during successive COVID-19 waves, with excessive workload and low compliance with preventive measures. Further studies should evaluate the evolution of the incidence of ICU-acquired infections related to MDR bacteria, given the change in COVID-19 patient profiles. A better understanding of the immune status of critically ill COVID-19 patients is required to move to personalized treatment and reduce the risk of ICU-acquired infections. The role of specific preventive measures, such as targeted immunomodulation, should be investigated.
Isolation, Identification, and Antibacterial Properties of Prodigiosin, a Bioactive Product Produced by a New Serratia marcescens JSSCPM1 Strain: Exploring the Biosynthetic Gene Clusters of Serratia Species for Biological Applications
Authors: Arivuselvam Rajaguru , Dera Ayed A. , Parween Ali Syed , Alraey Yasser , Saif Ahmed , Hani Umme , Arumugam Ramakrishnan Sivaa , Azeeze Mohamed Sheik Tharik Abdul , Rajeshkumar Raman , Susil Aishwarya , Harindranath Haritha , Kumar B. R. Prashantha
Published: September 2023

Prodigiosin pigment has high medicinal value, so exploring this compound is a top priority. This report presents a prodigiosin bioactive compound isolated from Serratia marcescens JSSCPM1, a new strain. The purification process of this compound involves the application of different chromatographic methods, including UV-visible spectroscopy, high-performance liquid chromatography (HPLC), and liquid chromatography–mass spectrometry (LC/MS). Subsequent analysis was performed using nuclear magnetic resonance (NMR) to achieve a deeper understanding of the compound’s structure. Finally, through a comprehensive review of the existing literature, the structural composition of the isolated bioactive compound was found to correspond to that of the well-known compound prodigiosin. The isolated prodigiosin compound was screened for antibacterial activity against both Gram-positive and Gram-negative bacteria. The compound inhibited the growth of Gram-negative bacterial strains compared with Gram-positive bacterial strains. It showed a maximum minimum inhibitory concentration against Escherichia coli NCIM 2065 at a 15.9 ± 0.31 μg/mL concentration. The potential binding capabilities between prodigiosin and the OmpF porin proteins (4GCS, 4GCP, and 4GCQ) were determined using in silico studies, which are generally the primary targets of different antibiotics. Comparative molecular docking analysis indicated that prodigiosin exhibits a good binding affinity toward these selected drug targets.
Streptomyces rugosispiralis sp. nov., a Novel Actinobacterium Isolated from Peat Swamp Forest Soil That Produces Ansamycin Derivatives and Nocardamines
Authors: Weeraphan Trinset , Supong Khomsan , Sripreechasak Paranee , Jutakanoke Rumpa , Kowinthanaphat Supalerk , Tanasupawat Somboon , Pittayakhajonwut Pattama , Phongsopitanun Wongsakorn
Published: September 2023

Actinomycetes, especially the genus Streptomyces, are one of the most promising sources of bioactive natural products. In this study, a novel Streptomyces strain, RCU-064T, was isolated from a soil sample collected from a peat swamp forest in Thailand. Strain RCU-064T showed the highest 16S rRNA gene sequence similarity (99.06%) with Streptomyces malaysiensis NBRC 16446T. Based on a polyphasic approach, strain RCU-064T represents a novel species of the genus Streptomyces, for which the name Streptomyces rugosispiralis sp. nov. is proposed. The chemical isolation of the crude ethyl acetate extracts of the strain led to the isolation of six compounds: (1) geldanamycin, (2) 17-O-demethylgeldanamycin, (3) reblastatin, (4) 17-demethoxyreblastatin, (5) nocardamine, and (6) dehydroxynocardamine. These compounds were evaluated for their biological activities. All compounds showed no antimicrobial activity against tested microorganisms used in this study. Compounds (1)–(4) displayed cytotoxic activity against the NCI-H187 cell line, with IC50 values ranging from 0.045–4.250 µg/mL. Cytotoxicity against the MCF-7 cell line was found in compounds (1) and (3) with IC50 values of 3.51 and 1.27 µg/mL, respectively. Compounds (5) and (6) exhibited cytotoxicity only against Vero cells (IC50 of 16.57 µg/mL) and NCI-H187 cells (IC50 of 13.96 µg/mL), respectively. These results indicate that peat swamp forest soil remains a promising reservoir of novel actinomycetes capable of producing bioactive natural products.
Role of Oxidative Stress in Mitochondrial Function: Relevance for Liver Function
Authors: Xu Jie , Feng Zhihui
Published: September 2023

The traditional recognition of mitochondria as powerhouses that generate ATP and reactive oxygen species (ROS) via oxidative phosphorylation and the tricarboxylic acid cycle has ceased [...]
Smart Textiles: A Review and Bibliometric Mapping
Authors: Sajovic Irena , Kert Mateja , Boh Podgornik Bojana
Published: September 2023

According to ISO/TR 23383, smart textiles reversibly interact with their environment and respond or adapt to changes in the environment. The present review and bibliometric analysis was performed on 5810 documents (1989–2022) from the Scopus database, using VOSviewer and Bibliometrix/Biblioshiny for science mapping. The results show that the field of smart textiles is highly interdisciplinary and dynamic, with an average growth rate of 22% and exponential growth in the last 10 years. Beeby, S.P., and Torah, R.N. have published the highest number of papers, while Wang, Z.L. has the highest number of citations. The leading journals are Sensors, ACS Applied Materials and Interfaces, and Textile Research Journal, while Advanced Materials has the highest number of citations. China is the country with the most publications and the most extensive cooperative relationships with other countries. Research on smart textiles is largely concerned with new materials and technologies, particularly in relation to electronic textiles. Recent research focuses on energy generation (triboelectric nanogenerators, thermoelectrics, Joule heating), conductive materials (MXenes, liquid metal, silver nanoparticles), sensors (strain sensors, self-powered sensors, gait analysis), speciality products (artificial muscles, soft robotics, EMI shielding), and advanced properties of smart textiles (self-powered, self-cleaning, washable, sustainable smart textiles).
Limit Equilibrium Analysis of Landfill Instability Based on Actual Failure Surface
Authors: Li Junchao , Chen Ruiqi , Lin Haoyu
Published: September 2023

Slope stability is one of the key engineering problems in the whole lifetime of landfills. In this paper, combined with the wedge limit equilibrium analysis, a landfill stability analysis method based on the actual failure surface is proposed, and the model is verified according to the data of centrifuge model tests. It is found that this method can more accurately calculate the factor of safety (FS) of the slope of the landfill and evaluate the stability of the slope. Finally, sensitivity analysis was conducted to evaluate the effects of the actual failure surface angle, water level, soil parameters, and the presence or absence of a dam on the factor of safety.
Effective Fabric Defect Detection Model for High-Resolution Images
Authors: Li Long , Li Qi , Liu Zhiyuan , Xue Lin
Published: September 2023

The generation of defects during fabric production impacts fabric quality, and fabric production factories can greatly benefit from the automatic detection of fabric defects. Although object detection algorithms based on convolutional neural networks can be quickly developed, fabric defect detection encounters several problems. Accordingly, a fabric defect detection model based on Cascade R-CNN was proposed in this study. We also proposed block recognition and detection box merging algorithms to achieve complete defect detection in high-resolution images. We implemented a Switchable Atrous Convolution layer to enhance the feature extraction ability of ResNet-50 and upgraded the Feature Pyramid Network to improve the detection accuracy of small defects. Experimental results demonstrated that the proposed model can efficiently perform defect detection in fabric.
Pacing Strategy of 800 m and 1500 m Freestyle Swimming Finals in the World Championships According to the Performance in Males and Females of Different Age Groups
Authors: Demarie Sabrina , Pycke Jean Renaud , Pizzuti Alessia , Billat Veronique
Published: September 2023

Pacing strategy refers to the distribution of effort and speed throughout the race to achieve optimal performance. This study aims to understand whether the choice of pacing strategy in swimming depends on the length of competitions and how sex, age, and performance level influence this strategy. Participants were the finalists of the 800 m and 1500 m freestyle events at the elite and junior world championships in 2022–2023. Race outcomes and pacing parameters were compared between the two distances and across different groups of swimmers. Swimmers in both distances did not break world records. Pacing strategy generally followed a U-shape with significant differences in the frequency and duration of speed changes between the two distances. The 800 m exhibited more frequent changes in acceleration, while the 1500 m events generally followed a more consistent time-series pattern. There were differences in pacing strategies between males and females and between junior and elite swimmers. Swimmers closer to world records showed more consistent pacing patterns compared to those farther from records. This study suggests that pacing strategies are influenced by race distance, sex, age, and performance level. The research highlights the complex interplay between physiological and psychological factors that shape a swimmer’s decision-making during a race.
Determinants of Memory Encoding of Altruistic Messages: M-Delphi and F-DEMATEL Approach
Authors: Liao Chi-Horng
Published: September 2023

One of the key challenges of non-profit organizations is the effective communication of values beneficial to society, such as altruism. Communication can be deemed effective if the message is memory encoded by the recipient. This paper applies social cognitive theory to analyze the determinants of the memory encoding of altruistic messages transmitted to audiences via television. The data were analyzed by the modified Delphi [M-Delphi) and Fuzzy Decision-Making Trial and Evaluation Laboratory [F-DEMATEL). The researchers initially proposed ten factors, and two factors were added after the first Delphi round. The analysis revealed three causal factors and four effect factors. The findings provide several contributions to communication literature. They also provide managerial implications for managers in non-profit organizations on the effective communication of altruism.
Applying Deep Learning to Medical Imaging: A Review
Authors: Zhang Huanhuan , Qie Yufei
Published: September 2023

Deep learning (DL) has made significant strides in medical imaging. This review article presents an in-depth analysis of DL applications in medical imaging, focusing on the challenges, methods, and future perspectives. We discuss the impact of DL on the diagnosis and treatment of diseases and how it has revolutionized the medical imaging field. Furthermore, we examine the most recent DL techniques, such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), and generative adversarial networks (GANs), and their applications in medical imaging. Lastly, we provide insights into the future of DL in medical imaging, highlighting its potential advancements and challenges.
Epidemiological Characteristics of 101,471 Patients Hospitalized with Chronic Obstructive Pulmonary Disease (COPD) in Poland in 2019: Multimorbidity, Duration of Hospitalization, In-Hospital Mortality
Authors: Jankowski Mateusz , Bochenek Bogdan , Wieczorek Joanna , Figurski Mariusz , Gruszczyńska Marta , Goryński Paweł , Pinkas Jarosław
Published: September 2023

Chronic obstructive pulmonary disease (COPD) is a common lung disease. There is a limited amount of nationwide data on COPD patients in Poland. This study aimed to characterize patients hospitalized with COPD in Poland in 2019 as well as to identify factors associated with the risk of in-hospital death and prolonged hospitalization among patients with COPD. This study is a retrospective database analysis. Data on patients hospitalized with COPD in Poland were obtained from the Nationwide General Hospital Morbidity Dataset. Data on all adults aged ≥40 years with a diagnosis of COPD from a physician (J44 code) were included in the analysis. Data were analyzed separately for patients hospitalized due to COPD (primary diagnosis) and patients with COPD as a comorbidity (secondary diagnosis). Completed medical records were available for 101,471 patients hospitalized with COPD (36.9% were females). Of those, 32% were hospitalized due to COPD. The mean age was 71.4 ± 9.7 years. The mean duration of hospitalization was 9.4 ± 11.4 days (median 7 days). Most of the COPD patients (89.3%) had at least one comorbidity. The in-hospital mortality rate was 6.8%. Older age, presence of cardiovascular diseases, and diseases of the genitourinary system (p < 0.05) were the most important factors associated with the risk of in-hospital death among patients hospitalized due to COPD.
COVID-19 Acute Respiratory Distress Syndrome: Treatment with Helmet CPAP in Respiratory Intermediate Care Unit by Pulmonologists in the Three Italian Pandemic Waves
Authors: Piluso Martina , Ferrari Clarissa , Pagani Silvia , Usai Pierfranco , Raschi Stefania , Parachini Luca , Oggionni Elisa , Melacini Chiara , D’Arcangelo Francesca , Cattaneo Roberta , Bonacina Cristiano , Bernareggi Monica , Bencini Serena , Nadalin Marta , Borelli Mara , Bellini Roberto , Salandini Maria Chiara , Scarpazza Paolo
Published: September 2023

COVID-19 Acute Respiratory Distress Syndrome (CARDS) is the most serious complication of COVID-19. The SARS-CoV-2 outbreaks rapidly saturated intensive care unit (ICU), forcing the application of non-invasive respiratory support (NIRS) in respiratory intermediate care unit (RICU). The primary aim of this study is to compare the patients’ clinical characteristics and outcomes (Helmet-Continuous Positive Airway Pressure (H-CPAP) success/failure and survival/death). The secondary aim is to evaluate and detect the main predictors of H-CPAP success and survival/death. A total of 515 patients were enrolled in our observational prospective study based on CARDS developed in RICU during the three Italian pandemic waves. All selected patients were treated with H-CPAP. The worst ratio of arterial partial pressure of oxygen (PaO2) and fraction of inspired oxygen (FiO2) PaO2/FiO2 during H-CPAP stratified the subjects into mild, moderate and severe CARDS. H-CPAP success has increased during the three waves (62%, 69% and 77%, respectively) and the mortality rate has decreased (28%, 21% and 13%). H-CPAP success/failure and survival/death were related to the PaO2/FiO2 (worst score) ratio in H-CPAP and to steroids’ administration. D-dimer at admission, FiO2 and positive end expiratory pressure (PEEP) were also associated with H-CPAP success. Our study suggests good outcomes with H-CPAP in CARDS in RICU. A widespread use of steroids could play a role.
Andalusi Defensive Architecture through Martín de Ximena Jurado’s Drawings (Mid-17th Century)
Authors: García-Pulido Luis José
Published: September 2023

The antiquarian Martín de Ximena Jurado was a pioneer in the historical cartography of the old Kingdom of Jaén (Andalusia, Spain), where he tried to represent emblematic areas with their military defences with his particular graphic language. Not surprisingly, this territory has a high concentration of medieval fortifications. The data and drawings that he made of castles, towers, and defensive enclosures show a special interest in the militarisation of sites and places. He went beyond a simple toponymic study aimed only at finding a correspondence between the ancient name and the location of a settlement based on the evidence provided by coins and inscriptions. The medieval fortifications that he mapped were not drawn in ruins as one would expect they would be in the mid-17th century, but with their most characteristic construction elements. This fact gives it great relevance, as it represents the idealised hypothesis of the state of these constructions at the time of the Castilian conquest in the decades following the Almohad debacle in the Battle of Las Navas de Tolosa (1212).
A Least Squares Estimator for Gradual Change-Point in Time Series with m-Asymptotically Almost Negatively Associated Errors
Authors: Xu Tianming , Wei Yuesong
Published: September 2023

As a new member of the NA (negative associated) family, the m-AANA (m-asymptotically almost negatively associated) sequence has many statistical properties that have not been developed. This paper mainly studies its properties in the gradual change point model. Firstly, we propose a least squares type change point estimator, then derive the convergence rates and consistency of the estimator, and provide the limit distributions of the estimator. It is interesting that the convergence rates of the estimator are the same as that of the change point estimator for independent identically distributed observations. Finally, the effectiveness of the estimator in limited samples can be verified through several sets of simulation experiments and an actual hydrological example.
New Results Achieved for Fractional Differential Equations with Riemann–Liouville Derivatives of Nonlinear Variable Order
Authors: Abdelhamid Hallouz , Stamov Gani , Souid Mohammed Said , Stamova Ivanka
Published: September 2023

This paper proposes new existence and uniqueness results for an initial value problem (IVP) of fractional differential equations of nonlinear variable order. Riemann–Liouville-type fractional derivatives are considered in the problem. The new fundamental results achieved in this work are obtained by using the inequalities technique and the fixed point theory. In addition, uniform stability criteria for the solutions are derived. The accomplished results are new and complement the scientific research in the field. A numerical example is composed to show the efficacy and potency of the proposed criteria.
A Two-Step Newton Algorithm for the Weighted Complementarity Problem with Local Biquadratic Convergence
Authors: Liu Xiangjing , Liu Yihan , Zhang Jianke
Published: September 2023

We discuss the weighted complementarity problem, extending the nonlinear complementarity problem on Rn. In contrast to the NCP, many equilibrium problems in science, engineering, and economics can be transformed into WCPs for more efficient methods. Smoothing Newton algorithms, known for their at least locally superlinear convergence properties, have been widely applied to solve WCPs. We suggest a two-step Newton approach with a local biquadratic order convergence rate to solve the WCP. The new method needs to calculate two Newton equations at each iteration. We also insert a new term, which is of crucial importance for the local biquadratic convergence properties when solving the Newton equation. We demonstrate that the solution to the WCP is the accumulation point of the iterative sequence produced by the approach. We further demonstrate that the algorithm possesses local biquadratic convergence properties. Numerical results indicate the method to be practical and efficient.
A Coupled Nonlinear Viscoelastic–Viscoplastic Thermomechanical Model for Polymeric Lithium-Ion Battery Separators
Authors: Ihuaenyi Royal Chibuzor , Deng Jie , Bae Chulheung , Xiao Xinran
Published: September 2023

One of the major concerns in ensuring lithium-ion battery (LIB) safety in abuse scenarios is the structural integrity of the battery separator. This paper presents a coupled viscoelastic–viscoplastic model for predicting the thermomechanical response of polymeric battery separators in abuse scenarios under combined mechanical and thermal loadings. The viscoplastic model is developed based on a rheological framework that considers the mechanisms involved in the initial yielding, change in viscosity, strain softening and strain hardening of polymeric separators. The viscoplastic model is then coupled with a previously developed orthotropic nonlinear thermoviscoelastic model to predict the thermomechanical response of polymeric separators before the onset of failure. The model parameters are determined for Celgard®2400, a polypropylene (PP) separator, and the model is implemented in the LS-DYNA® finite element (FE) package as a user-defined subroutine. Punch test simulations are employed to verify the model predictions under biaxial stress states. Simulations of uniaxial tensile stress–strain responses at different strain rates and temperatures are compared with experimental data to validate the model predictions. The model predictions of the material anisotropy, rate and temperature dependence agree well with experimental observations.
Intelligent Method for Classifying the Level of Anthropogenic Disasters
Authors: Lipianina-Honcharenko Khrystyna , Wolff Carsten , Sachenko Anatoliy , Kit Ivan , Zahorodnia Diana
Published: September 2023

Anthropogenic disasters pose a challenge to management in the modern world. At the same time, it is important to have accurate and timely information to assess the level of danger and take appropriate measures to eliminate disasters. Therefore, the purpose of the paper is to develop an effective method for assessing the level of anthropogenic disasters based on information from witnesses to the event. For this purpose, a conceptual model for assessing the consequences of anthropogenic disasters is proposed, the main components of which are the following ones: the analysis of collected data, modeling and assessment of their consequences. The main characteristics of the intelligent method for classifying the level of anthropogenic disasters are considered, in particular, exploratory data analysis using the EDA method, classification based on textual data using SMOTE, and data classification by the ensemble method of machine learning using boosting. The experimental results confirmed that for textual data, the best classification is at level V and level I with an error of 0.97 and 0.94, respectively, and the average error estimate is 0.68. For quantitative data, the classification accuracy of Potential Accident Level relative to Industry Sector is 77%, and the f1-score is 0.88, which indicates a fairly high accuracy of the model. The architecture of a mobile application for classifying the level of anthropogenic disasters has been developed, which reduces the time required to assess consequences of danger in the region. In addition, the proposed approach ensures interaction with dynamic and uncertain environments, which makes it an effective tool for classifying.
Bacterial Membrane Vesicles for In Vitro Catalysis
Authors: Thakur Meghna , Dean Scott N. , Caruana Julie C. , Walper Scott A. , Ellis Gregory A.
Published: September 2023

The use of biological systems in manufacturing and medical applications has seen a dramatic rise in recent years as scientists and engineers have gained a greater understanding of both the strengths and limitations of biological systems. Biomanufacturing, or the use of biology for the production of biomolecules, chemical precursors, and others, is one particular area on the rise as enzymatic systems have been shown to be highly advantageous in limiting the need for harsh chemical processes and the formation of toxic products. Unfortunately, biological production of some products can be limited due to their toxic nature or reduced reaction efficiency due to competing metabolic pathways. In nature, microbes often secrete enzymes directly into the environment or encapsulate them within membrane vesicles to allow catalysis to occur outside the cell for the purpose of environmental conditioning, nutrient acquisition, or community interactions. Of particular interest to biotechnology applications, researchers have shown that membrane vesicle encapsulation often confers improved stability, solvent tolerance, and other benefits that are highly conducive to industrial manufacturing practices. While still an emerging field, this review will provide an introduction to biocatalysis and bacterial membrane vesicles, highlight the use of vesicles in catalytic processes in nature, describe successes of engineering vesicle/enzyme systems for biocatalysis, and end with a perspective on future directions, using selected examples to illustrate these systems’ potential as an enabling tool for biotechnology and biomanufacturing.
A Cross-Domain Weakly Supervised Diabetic Retinopathy Lesion Identification Method Based on Multiple Instance Learning and Domain Adaptation
Authors: Li Renyu , Gu Yunchao , Wang Xinliang , Pan Junjun
Published: September 2023

Accurate identification of lesions and their use across different medical institutions are the foundation and key to the clinical application of automatic diabetic retinopathy (DR) detection. Existing detection or segmentation methods can achieve acceptable results in DR lesion identification, but they strongly rely on a large number of fine-grained annotations that are not easily accessible and suffer severe performance degradation in the cross-domain application. In this paper, we propose a cross-domain weakly supervised DR lesion identification method using only easily accessible coarse-grained lesion attribute labels. We first propose the novel lesion-patch multiple instance learning method (LpMIL), which leverages the lesion attribute label for patch-level supervision to complete weakly supervised lesion identification. Then, we design a semantic constraint adaptation method (LpSCA) that improves the lesion identification performance of our model in different domains with semantic constraint loss. Finally, we perform secondary annotation on the open-source dataset EyePACS, to obtain the largest fine-grained annotated dataset EyePACS-pixel, and validate the performance of our model on it. Extensive experimental results on the public dataset FGADR and our EyePACS-pixel demonstrate that compared with the existing detection and segmentation methods, the proposed method can identify lesions accurately and comprehensively, and obtain competitive results using only coarse-grained annotations.
BLTR1 Is Decreased in Steroid Resistant Pro-Inflammatory CD28nullCD8+ T Lymphocytes in Patients with COPD—The Spillover Hypothesis Explained?
Authors: Hodge Greg , Jersmann Hubertus , Holmes Mark , Asare Patrick , Roscioli Eugene , Reynolds Paul N. , Hodge Sandra
Published: September 2023

Introduction: Pro-inflammatory CD8+ T cells are increased in the lungs and also in the peripheral circulation of both smokers and chronic obstructive pulmonary disease (COPD) patients. The reason for this is unclear but has been described as a spillover from cells in the lungs that may cause the systemic inflammation noted in COPD. We have recently shown an increase in steroid-resistant CD28nullCD8+ senescent lymphocytes in the lungs and peripheral blood in COPD. Leukotreine B4 (LB4) receptor 1 (BLTR1) is involved in recruitment of CD8+ T cells to sites of inflammation, and we hypothesized that it may be involved in the migration of these senescent lymphocytes from the lungs in COPD. Methods: Via flow cytometry and Western blot BLTR1, IFNγ, and TNFα expression were measured in peripheral blood, BAL, and large proximal and small distal airway CD28±, CD8± T, and NKT-like cells from COPD patients and healthy control subjects (±prednisolone) following in vitro stimulation. Chemotaxis of leucocyte subsets was determined (±LB4 ± prednisolone). Results: There was an increase in BLTR1-CD28nullCD8+ lymphocytes in the lungs and blood in patients with COPD compared with controls. BLTR1-CD28nullCD8+ T and NKT-like cells produce more IFN/TNF than BLTR+ cells and fail to migrate to LTB4. Treatment with 1 µM prednisolone in vitro resulted in upregulation of BLTR1 expression in pro-inflammatory CD28nullCD8+ cells and migration to LB4. Conclusions: Loss of BLTR1 is associated with an increased inflammatory potential of CD28nullCD8+ T cells and may allow these pro-inflammatory steroid-resistant cells to migrate to peripheral blood. Treatment strategies that upregulate BLTR1 may reduce systemic inflammation and associated co-morbidity in patients with COPD.
Exploring Longitudinal Gut Microbiome towards Metabolic Functional Changes Associated in Atopic Dermatitis in Early Childhood
Authors: Patumcharoenpol Preecha , Kingkaw Amornthep , Nakphaichit Massalin , Chatchatee Pantipa , Suratannon Narissara , Panagiotou Gianni , Vongsangnak Wanwipa
Published: September 2023

Atopic dermatitis (AD) is a prevalent inflammatory skin disease that has been associated with changes in gut microbial composition in early life. However, there are limited longitudinal studies examining the gut microbiome in AD. This study aimed to explore taxonomy and metabolic functions across longitudinal gut microbiomes associated with AD in early childhood from 9 to 30 months of age using integrative data analysis within the Thai population. Our analysis revealed that gut microbiome diversity was not different between healthy and AD groups; however, significant taxonomic differences were observed. Key gut bacteria with short-chain fatty acids (SCFAs) production potentials, such as Anaerostipes, Butyricicoccus, Ruminococcus, and Lactobacillus species, showed a higher abundance in the AD group. In addition, metabolic alterations between the healthy and AD groups associated with vitamin production and host immune response, such as biosynthesis of menaquinol, succinate, and (Kdo)2-lipid A, were observed. This study serves as the first framework for monitoring longitudinal microbial imbalances and metabolic functions associated with allergic diseases in Thai children during early childhood.