bluuebunny/crossref_metadata_2025 huggingface dataset:
A phenomenologically grounded specification of varieties of adolescent depression
Authors: Sánchez Guerrero H. Andrés , Wessing Ida
Published: February 2024

Researchers are increasingly acknowledging that psychopathological conditions usually grouped together under the generic label “depression” are highly diverse. However, no differential therapeutic approach currently exists that is sensitive to the varieties of depression afflicting young people. In fact, the discussion is missing something much more fundamental: a specification of the types of adolescent depression. Recent research that has aimed to classify different kinds of depression has mainly studied adult populations and predominantly used technically complicated measurements of biological markers. The neglect of the potential particularities of dysphoric disorders affecting youths is unfortunate, and the exclusive focus on biological parameters unnecessarily restrictive. Moreover, this one-sidedness obfuscates more directly available sources of clinically relevant data that could orient conceptualization efforts in child and adolescent psychiatry. Particularly, clues for discriminating different types of adolescent depression may be obtained by analyzing personally articulated accounts of how affected young people experience changes in their relation to the world and to themselves. Thus, here we present and discuss the findings of a study that explored the possibility of specifying types of adolescent depression in a phenomenological way. The study investigated the association between these types and the vicissitudes of personality development. In accounts given by youths diagnosed with depression during semi-structured interviews, we identified themes and examined their phenomenological centrality. Specifically, our qualitative analyses aimed to determine the relative importance of certain themes with respect to the overall intelligibility of the described changes to the relational space. Based on the findings of these analyses, we differentiate three specifiers of adolescent depression and suggest an association between particular types of experiences and the trajectory of affected adolescents’ personality development. To our knowledge, this is the first phenomenologically grounded specification of types of adolescent depression with potential therapeutic significance. Thus, based on this contribution, we propose that modes of scientific exploration that are close to phenomenological philosophy—which have been ignored in the context of developmental psychopathology—could offer a foundation to theories developed in the field of child and adolescent psychiatry.
Sleep quality, quality of life, fatigue, and mental health in COVID-19 post-pandemic Türkiye: a cross-sectional study
Authors: Bener Abdulbari , Morgul Ebru , Tokaç Mahmut , Ventriglio Antonio , Jordan Timothy R.
Published: February 2024

Aim

This study explores the predictors and associated risk factors of sleep quality, quality of life, fatigue, and mental health among the Turkish population during the COVID-19 post-pandemic period.

Materials and methods

A cross-sectional survey using multi-stage, stratified random sampling was employed. In total, 3,200 persons were approached. Of these, 2,624 (82%) completed the questionnaire package consisting of socio-demographic information, Pittsburgh Sleep Quality Index (PSQI), the WHO Quality of Life Brief Version (WHOQOL-BREF), Fatigue Assessment Scale (FAS), Patients Health Questionnaire (PHQ-15), GAD-7 anxiety scale, and the 21-item Depression, Anxiety, Stress Scale (DASS-21).

Results

Significant differences between genders were found regarding socio-demographic characteristics (p < 0.01). Using PHQ-15 for depressive disorders, significant differences were found between normal and high severity scores (≥ 10), regarding age group (p < 0.001), gender (p = 0.049), educational level (p < 0.001), occupational status (p = 0.019), cigarette smoking (p = 0.002), waterpipe-narghile smoking (p = 0.039), and co-morbidity (p = 0.003). The WHOQOL-BREF indicated strong correlations between public health, physical health, psychological status, social relationships, environmental conditions, and sleep disorders (p < 0.01). Furthermore, comparisons of the prevalence of mental health symptoms and sleeping with PHQ-15 scores ≥ 10 (p = 0.039), fatigue (p = 0.012), depression (p = 0.009), anxiety (p = 0.032), stress (p = 0.045), and GAD-7 (p < 0.001), were significantly higher among the mental health condition according to sleeping disorder status. Multiple regression analysis revealed that DASS21 stress (p < 0.001), DASS21 depression (p < 0.001), DASS21 anxiety (p = 0.002), physical health (WHOQOL-BREF) (p = 0.007), patient health depression-PHQ-15 (p = 0.011), psychological health (WHOQOL-BREF) (p = 0.012), fatigue (p = 0.017), and environmental factors (WHOQOL-BREF) (p = 0.041) were the main predictor risk factors associated with sleep when adjusted for gender and age.

Conclusion

The current study has shown that sleep quality was associated with the mental health symptoms of depression, anxiety, stress, and fatigue. In addition, insufficient sleep duration and unsatisfactory sleep quality seemed to affect physical and mental health functioning.
The Community Health Response Team: a culturally and linguistically tailored community response to COVID-19 addressing barriers to testing and vaccinations for refugee, immigrant and migrant communities in Atlanta, Georgia
Authors: Bekele Feven , Yu Kimberly , Archbold Sam , Mann Erin , Dawson-Hahn Elizabeth , Aziz Omar
Published: February 2024

The International Rescue Committee (IRC) in Atlanta and Community Organized Relief Effort (CORE) established a Community Health Response Team in May 2020. The team members represented refugee, immigrant and migrant populations and had expertise in health care and public health. These 18 individuals were recruited from IRC Atlanta's Career Development program, had a variety of backgrounds and spoke 20 languages. They implemented a community-centered COVID-response intervention model of pairing education and outreach efforts with testing and vaccination clinics. Due to their team makeup, the Community Health Response Team conducted tailored outreach and education that was culturally and linguistically congruent with their target communities. They administered over 16,000 COVID-19 tests at mobile community sites within the first 6 months. Once COVID-19 vaccinations were available, the Community Health Response Team coordinated a total of 834 vaccination events in communities with a high number of refugees and in partnership with refugee- and immigrant-trusted community-based organizations, resulting in 31,888 vaccinations. Hiring staff from refugee, immigrant and migrant populations created a sustainable staffing model. Also, embedding culturally specific strategies in their model of pairing education and outreach led to long-term relationships and greater trust with community members. This approach of engaging and empowering community members to create tailored public health responses should serve as guidance for future public health campaigns.
Including personal boundaries scale: development and psychometric properties of a measurement for nurses' self-efficacy toward intimate and sexual behavior in dementia care
Authors: Waterschoot Karien , Roelofs Tineke S. M. , van Dam Arno , Luijkx Katrien G.
Published: February 2024

Background

Person-centered nursing home care recognizes the intimate and sexual needs of residents with dementia but lacks guidance for nurses to address them while effectively respecting their personal boundaries. The Including Personal Boundaries (IPB) scale was developed to complement clinical and scientific efforts to support both nurse and resident wellbeing.

Methods

Through a co-creative process, theoretical principles, day-to-day experiences, and expert knowledge were integrated into an initial nineteen-item version of the IPB scale. The pilot sample comprised 297 Dutch (vocational) nurses in dementia nursing care.

Results

After Principal Component Analysis, nine items with strong factor loadings (>0.6) were retained. Internal reliability measures supported the item selection, such as high internal consistency (α = 0.866) and adequate corrected item-total correlations (0.532–0.781).

Conclusion

The presented IPB scale, a nine-item scale, is a short, robust measure to assess nurses' self-efficacy in their capabilities to include personal boundaries (physical and emotional) when confronted with the intimate and sexual behaviors of residents with dementia. Further validation is recommended. The IPB scale could provide valuable insights for research, clinical practice, and education.
Liquid application dosing alters the physiology of air-liquid interface (ALI) primary human bronchial epithelial cell/lung fibroblast co-cultures and in vitro testing relevant endpoints
Authors: Mallek Nicholas M. , Martin Elizabeth M. , Dailey Lisa A. , McCullough Shaun D.
Published: February 2024

Differentiated primary human bronchial epithelial cell (dpHBEC) cultures grown under air-liquid interface (ALI) conditions exhibit key features of the human respiratory tract and are thus critical for respiratory research as well as efficacy and toxicity testing of inhaled substances (e.g., consumer products, industrial chemicals, and pharmaceuticals). Many inhalable substances (e.g., particles, aerosols, hydrophobic substances, reactive substances) have physiochemical properties that challenge their evaluation under ALI conditions in vitro. Evaluation of the effects of these methodologically challenging chemicals (MCCs) in vitro is typically conducted by “liquid application,” involving the direct application of a solution containing the test substance to the apical, air-exposed surface of dpHBEC-ALI cultures. We report that the application of liquid to the apical surface of a dpHBEC-ALI co-culture model results in significant reprogramming of the dpHBEC transcriptome and biological pathway activity, alternative regulation of cellular signaling pathways, increased secretion of pro-inflammatory cytokines and growth factors, and decreased epithelial barrier integrity. Given the prevalence of liquid application in the delivery of test substances to ALI systems, understanding its effects provides critical infrastructure for the use of in vitro systems in respiratory research as well as in the safety and efficacy testing of inhalable substances.
Real-world effectiveness and safety of baricitinib including its effect on biomarkers and laboratory data in Japanese adult patients with atopic dermatitis: a single-center retrospective study
Authors: Watanabe Ayu , Kamata Masahiro , Okada Yoshiki , Suzuki Shoya , Ito Makoto , Mizukawa Itsumi , Uchida Hideaki , Egawa Shota , Chijiwa Chika , Hiura Azusa , Fukaya Saki , Hayashi Kotaro , Fukuyasu Atsuko , Tanaka Takamitsu , Ishikawa Takeko , Tada Yayoi
Published: February 2024

Baricitinib demonstrated efficacy and tolerable safety in clinical trials for atopic dermatitis (AD); however, real-world data are limited. We examined effectiveness and safety of baricitinib, and laboratory data in AD patients treated with baricitinib in our department. We also evaluated baseline clinical severity in responders and non-responders. All adult AD patients treated with baricitinib in our department between January 2021 and February 2023 were included. Data on 30 Japanese AD patients were analyzed. Objective severity scores and patient-reported outcomes improved at one and 3 months, except for the affected body surface area at 1 month. The proportions of patients who achieved eczema area and severity index-50% improvement were 30.0% (9/30) at 1 month and 53.3% (16/30) at 3 months. There were no significant changes in AD biomarkers. No significant difference was observed in baseline clinical severity between responders and non-responders. No significant changes were observed in laboratory results except for increased serum creatine phosphokinase levels at 3 months. One case of herpes zoster and one case of ocular herpes were observed. Baricitinib showed mild effectiveness and favorable safety including laboratory findings. Biomarkers did not reflect clinical improvement. Further study is needed to identify characteristics of responders.
Balancing Acts: Unveiling the Dynamics of Revitalization Policies in China’s Old Revolutionary Areas of Gannan
Authors: Liao Wenmei , Yuan Ruolan , Zhang Xu , Li Na , Qiu Hailan
Published: February 2024

A series of revitalization policies (RPs) have been implemented in China’s Old Revolutionary Areas (ORAs). Evaluating the impact of these RPs is of paramount importance for refining policy design and achieving the goal of common prosperity. This study focuses on the ORAs in Gannan (ORAG) and employs the Propensity Score Matching Difference-in-Differences (PSM-DID) method to assess the effects of the RPs from two perspectives: stimulating economic growth and increasing farmers’ income, utilizing county-level data spanning from 2006 to 2019. The findings of this study reveal that while the RP restrains the growth of per capita GDP in ORAG, it significantly promotes the growth of farmers’ income. Moreover, it plays a crucial role in reducing the income gap between ORAG and Jiangxi Province, thus promoting the common prosperity of farmers in ORAG. A detailed examination using quantile regression shows that the RP has a significant and consistent negative impact on GDP per capita GDP at different quantile points. At the same time, it has a significant positive effect on increasing farmers’ income at the 25% quantile point, effectively reducing income inequality among farmers at all quantile levels. The mechanism analysis shows that the RP has stimulated increased government investment in ORAG, leading to an increase in farmers’ incomes and a reduction in income disparities. However, the study also highlights the existence of a “policy trap” that has hindered the RP’s effectiveness in ORAG. Drawing upon these findings, this paper offers policy recommendations to enhance the impact of RP in ORAs.
UAV-Based Vegetation Indices to Evaluate Coffee Crop Response after Transplanting Seedlings Grown in Different Containers
Authors: Barata Rafael Alexandre Pena , Ferraz Gabriel Araújo e Silva , Bento Nicole Lopes , Santana Lucas Santos , Marin Diego Bedin , Mattos Drucylla Guerra , Schwerz Felipe , Rossi Giuseppe , Conti Leonardo , Bambi Gianluca
Published: February 2024

Brazil stands out among coffee-growing countries worldwide. The use of precision agriculture to monitor coffee plants after transplantation has become an important step in the coffee production chain. The objective of this study was to assess how coffee plants respond after transplanting seedlings grown in different containers, based on multispectral images acquired by Unmanned Aerial Vehicles (UAV). The study was conducted in Santo Antônio do Amparo, Minas Gerais, Brazil. The coffee plants were imaged by UAV, and their height, crown diameter, and chlorophyll content were measured in the field. The vegetation indices were compared to the field measurements through graphical and correlation analysis. According to the results, no significant differences were found between the studied variables. However, the area transplanted with seedlings grown in perforated bags showed a lower percentage of mortality than the treatment with root trainers (6.4% vs. 11.7%). Additionally, the vegetation indices, including normalized difference red-edge, normalized difference vegetation index, and canopy planar area calculated by vectorization (cm2), were strongly correlated with biophysical parameters. Linear models were successfully developed to predict biophysical parameters, such as the leaf area index. Moreover, UAV proved to be an effective tool for monitoring coffee using this approach.
Field Sprayer with Application Rate Control Using Fast Response Proportional Valves under Variable Speed Conditions
Authors: Karadol Hayrettin , Aybek Ali , Ucgul Mustafa , Kuzu Hamza , Gunes Mahit
Published: February 2024

In modern agriculture, which is characterised by dynamic field environments, challenges are faced in maintaining consistent application rates due to varying tractor speeds, field conditions, and certain calibration errors. Conventional control systems, which rely on slower valves, have difficulty adapting to these dynamic field conditions. By contrast, the integration of fast-acting proportional valves improves the precision and flexibility of flow rate adjustment during spraying applications. This research focused on evaluating the accuracy of spraying applications under different tractor speed conditions through field experiments and data analysis. This study involves a field sprayer with boom wings divided into right and left sections, where the flow rate of the liquid to each section is controlled by proportional valves with a 3 s full opening and closing time, dependent on speed information. Using a closed-loop control system consisting of a flow meter, proportional valve, and PLC, the valves are controlled by the PLC’s internal PID blocks. Observations reveal that as the tractor speed increases to a certain level, the system effectively adjusts the application rate close to the target value and maintains control against the changing ground speed during all field tests. The study included five different application tests, with target application rates of 100, 150, 200, 250, and 300 L ha−1, with each repeated three times, resulting in a total of 15 field tests at different ground speeds. During these tests, the data were meticulously recorded every second, covering the tractor speed, flow rate, and pressure values for both right and left boom sections, along with regulator pressure, proportional valve opening rates, and application rates. The durations for each application rate were documented alongside instances within specified periods where error boundaries of ±10% were exceeded. During the total test duration of 9734 s, the actual application rate value exceeded error boundaries during only 209 s. Within the application durations, the speed variation intervals ranged from 5.10 to 10.23 km h−1, 4.64 to 9.91 km h−1, 3.68 to 7.89 km h−1, 4.80 to 8.21 km h−1, and from 4.90 to 8.69 km h−1. The absolute percentage mean application errors were recorded as 2.81%, 2.68%, 2.28%, 2.14%, and 2.51% for respective application rates. Furthermore, statistically significant correlations (p < 0.01) were identified among the variables (speed, valve opening rate, flow rate, pressure) in both the right and left boom sections across all application rates.
Assessment of a Low-Cost Hydrogen Sensor for Detection and Monitoring of Biohydrogen Production during Sugarcane Straw/Vinasse Co-Digestion
Authors: Barrera Andrés , Gómez-Ríos David , Ramírez-Malule Howard
Published: February 2024

In this work, hydrogen production from the co-digestion of sugarcane straw and sugarcane vinasse in the dark fermentation (DF) process was monitored using a cost-effective hydrogen detection system. This system included a sensor of the MQ-8 series, an Arduino Leonardo board, and a computer. For the DF, different concentrations of sugarcane vinasse and volumetric ratios of vinasse/hemicellulose hydrolysate were used together with a thermally pretreated inoculum, while the hydrogen detection system stored the hydrogen concentration data during the fermentation time. The results showed that a higher concentration of vinasse led to higher inhibitors for the DF, resulting in a longer lag phase. Additionally, the hydrogen detection system proved to be a useful tool in monitoring the DF, showcasing a rapid response time, and providing reliable information about the period of adaptation of the inoculum to the substrate. The measurement system was assessed using the error metrics SE, RMSE, and MBE, whose values ranged 0.6 and 5.0% as minimum and maximum values. The CV (1.0–8.0%) and SD (0.79–5.62 ppm) confirmed the sensor’s robustness, while the ANOVA at the 5% significance level affirmed the repeatability of measurements with this instrument. The RMSE values supported the accuracy of the sensor for online measurements (6.08–14.78 ppm). The adoption of this straightforward and affordable method sped up the analysis of hydrogen in secluded regions without incurring the expenses associated with traditional measuring instruments while offering a promising solution for biomass valorization, contributing to the advancement of rural green energy initiatives in remote areas.
Metabolomics Analysis of Variation in Grain Quality of High-Quality Japonica Rice
Authors: Shi Qiang , Wang Ruizhi , Lu Wenjie , Zhu Jinyan , Zhang Hongcheng , Xiong Qiangqiang , Zhou Nianbing
Published: February 2024

In recent years, the semi-glutinous japonica rice variety has been extensively utilized in Jiangsu Province to greatly increase rice quality. Nevertheless, the increasing occurrence of seed variation presented a major threat to rice quality. Enhancing the quality of rice grains has emerged as a critical factor in guaranteeing consumer acceptance. Throughout this investigation, five lines (VJ1, VJ2, VJ3, VJ4, and VJ5) selected from the Nanjing9108 population in Liyang were used as research materials, and original cultivars of Nanjing9108 (CKJ1) provided by the original breeder were utilized as control materials to compare rice quality and differential metabolites. VJ4 and VJ3 demonstrated a significant reduction in milled rice rate and head milled rice rate when contrasted to CKJ1. Compared with CKJ1, the amylose content of the five strains was significantly increased. Only VJ3 amplified the 106 bp target band, and its 2-AP content was 0 ng/g. Most metabolites are mainly enriched in cutin, suberine, wax biosynthesis, histidine, and tryptophan metabolism. The primary metabolites throughout the metabolic pathway involve lipids and lipid-like molecules (mono palmitin, alpha-eleostearic, and palmitic acid) and amino acid metabolites (L-glutamate, L-tryptophan, and L-serine). The identification of these key metabolites helps in the discovery of prospective biomarkers for screening seed variation throughout seed production.
GRU–Transformer: A Novel Hybrid Model for Predicting Soil Moisture Content in Root Zones
Authors: Zheng Wengang , Zheng Kai , Gao Lutao , Zhangzhong Lili , Lan Renping , Xu Linlin , Yu Jingxin
Published: February 2024

The accurate measurement of soil moisture content emerges as a critical parameter within the ambit of agricultural irrigation management, wherein the precise prediction of this variable plays an instrumental role in enhancing the efficiency and conservation of agricultural water resources. This study introduces an innovative, cutting-edge hybrid model that ingeniously integrates Gated Recirculation Unit (GRU) and Transformer technologies, meticulously crafted to amplify the precision and reliability of soil moisture content forecasts. Leveraging meteorological and soil moisture datasets amassed from eight monitoring stations in Hebei Province, China, over the period from 2011 to 2018, this investigation thoroughly assesses the model’s efficacy against a diverse array of input variables and forecast durations. This assessment is concurrently contrasted with a range of conventional machine learning and deep learning frameworks. The results demonstrate that (1) the GRU–Transformer model exhibits remarkable superiority across various aspects, particularly in short-term projections (1- to 2-day latency). The model’s mean square error (MSE) for a 1-day forecast is notably low at 5.22%, reducing further to a significant 2.71%, while the mean coefficient of determination (R2) reaches a high of 89.92%. Despite a gradual increase in predictive error over extended forecast periods, the model consistently maintains robust performance. Moreover, the model shows exceptional versatility in managing different soil depths, notably excelling in predicting moisture levels at greater depths, thereby surpassing its performance in shallower soils. (2) The model’s predictive error inversely correlates with the reduction in parameters. Remarkably, with a streamlined set of just six soil moisture content parameters, the model predicts an average MSE of 0.59% and an R2 of 98.86% for a three-day forecast, highlighting its resilience to varied parameter configurations. (3) In juxtaposition with prevalent models such as Support Vector Regression (SVR), K-Nearest Neighbors (KNN), Gradient Boosting Decision Tree (GBDT), XGBoost, Random Forest, and deep learning models like Deep Neural Network (DNN), Convolutional Neural Network (CNN), and standalone GRU-branch and Transformer-branch models, the GRU–Transformer framework demonstrates a significant advantage in predicting soil moisture content with enhanced precision for a five-day forecast. This underscores its exceptional capacity to navigate the intricacies of soil moisture data. This research not only provides a potent decision-support tool for agricultural irrigation planning but also makes a substantial contribution to the field of water resource conservation and optimization in agriculture, while concurrently imparting novel insights into the application of deep learning techniques in the spheres of agricultural and environmental sciences.
Effects of Weeding Frequency on the Yield and Quality of Glycyrrhiza uralensis Fisch in an Arid and Semi-Arid Area of Northwest China
Authors: Wang Dongqing , Ma Bin , Liu Hua , Bao Yangmei , Niu Ying , Li Ming
Published: February 2024

Weeds interfere with agricultural production activities worldwide and have a very serious impact on agriculture and animal husbandry. Identifying a safe and reliable weed control strategy may increase the yield and production net income, and improve crop quality. Licorice is one of the most popular traditional Chinese herbal medicines and has been used for over 2000 years in China. Liquiritin and glycyrrhizic acid are crucial active ingredients. A field experiment was carried out to explore the effects of weeding frequency on the yield and quality of Glycyrrhiza uralensis Fisch in an arid and semi-arid area of northwest China. The experiment consisted of seven treatments: (1) no weeding, marked as WF0, and (2)–(7) artificial weeding using a hoe once every 1, 2, 4, 6, 8 and 10 weeks after emergence, marked as WF1, WF2, WF4, WF6, WF8 and WF10, respectively. We found that a higher weeding frequency resulted in greater plant height, photosynthesis, yield and quality. The highest yield was obtained when the WF1 treatment was applied, while the cost of weeding was high among all treatments. The concentrations of liquiritin and glycyrrhizic acid were increased by 53.24% and 36.57%, with the highest nitrogen metabolism enzymatic activities and quality observed when the WF4 treatment was applied. The WF4 treatment resulted in the largest increase in the net income among all treatments in both growing seasons, with respective increases of up to 71.39% and 78.81%. These findings suggest that weeding once every four weeks could be an effective and sustainable measure to control weeds in an arid and semi-arid area.
Risk Factors Associated with Mortality in Acinetobacter baumannii Infections: Results of a Prospective Cohort Study in a Tertiary Public Hospital in Guayaquil, Ecuador
Authors: Abarca-Coloma Luz , Puga-Tejada Miguel , Nuñez-Quezada Tamara , Gómez-Cruz Otilia , Mawyin-Muñoz Carlos , Barungi Shivan , Perán Macarena
Published: February 2024

Antibiotic overuse and the resulting antimicrobial resistance pose significant global public health challenges, providing an avenue for opportunistic pathogens like Acinetobacter baumannii to thrive. This study will report the trends of Acinetobacter baumannii antimicrobial resistance patterns at the Hospital Teodoro Maldonado Carbo, Ecuador. An observational, analytical, longitudinal, and prospective study was conducted involving patients diagnosed with hospital-acquired infections. Antimicrobial susceptibility testing was performed, followed by molecular analysis of carbapenemase genes in Acinetobacter baumannii isolates. We included 180 patients aged from 16 to 93 years. The hospital mortality rate was 63/180 (35%). Invasive mechanical ventilation (IMV) was indicated in 91/180 patients (50.4%). The overall survival (OS) rate in patients on IMV was 49.5% (45/91), with a median survival of 65 days. The OS rate in patients not on IMV was 80.9% (72/89), with a median survival of 106 days (HR 2.094; 95% CI 1.174–3.737; p = 0.012). From multivariate analysis, we conclude that ventilator-associated pneumonia is the most related factor to OS.
The Impact of COVID-19 on Multidrug-Resistant Bacteria at a Slovenian Tertiary Medical Center
Authors: Mrvič Tatjana , Stevanoska Sintija , Beović Bojana , Logar Mateja , Gregorčič Sergeja , Žnidaršič Benica , Seme Katja , Velimirović Ivana , Švent Kučina Nataša , Maver Vodičar Polona , Križan Hergouth Veronika , Džeroski Sašo , Pirs Mateja
Published: February 2024

The COVID-19 pandemic has strained healthcare systems globally. Shortages of hospital beds, reassignment of healthcare workers to COVID-19-dedicated wards, an increased workload, and evolving infection prevention and control measures have potentially contributed to the spread of multidrug-resistant bacteria (MDRB). To determine the impact of the COVID-19 pandemic at the University Medical Center Ljubljana, a tertiary teaching hospital, we analyzed the monthly incidence of select bacterial species per patient from 2018 to 2022. The analysis was performed for all isolates and for MDRB isolates. The data were analyzed separately for isolates from all clinical samples, from blood culture only, and from clinical and surveillance samples. Our findings revealed an increased incidence density of patients with Enterococcus faecium, Staphylococcus aureus, Escherichia coli, and Pseudomonas aeruginosa isolates from clinical samples during the COVID-19 period in the studied hospital. Notably, the incidence density of MDRB isolates—vancomycin-resistant E. faecium, extended-spectrum betalactamase-producing K. pneumoniae, and betalactam-resistant P. aeruginosa—from clinical samples increased during the COVID-19 period. There were no statistically significant differences in the incidence density of patients with blood culture MDRB isolates. We observed an increase in the overall MDRB burden (patients with MDRB isolates from both clinical and surveillance samples per 1000 patient days) in the COVID-19 period in the studied hospital for vancomycin-resistant E. faecium, carbapenem-resistant K. pneumoniae, and betalactam-resistant P. aeruginosa and a decrease in the methicillin-resistant S. aureus burden.
Evaluation of Glutathione in Spike Protein of SARS-CoV-2 Induced Immunothrombosis and Cytokine Dysregulation
Authors: Norris Brandon , Chorbajian Abraham , Dawi John , Mohan Aishvaryaa Shree , Glassman Ira , Ochsner Jacob , Misakyan Yura , Abnousian Arbi , Kiriaki Anthony , Sasaninia Kayvan , Avitia Edith , Ochoa Cesar , Venketaraman Vishwanath
Published: February 2024

Thrombotic microangiopathy has been identified as a dominant mechanism for increased mortality and morbidity in coronavirus disease 2019 (COVID-19). In the context of severe COVID-19, patients may develop immunothrombosis within the microvasculature of the lungs, which contributes to the development of acute respiratory distress syndrome (ARDS), a leading cause of death in the disease. Immunothrombosis is thought to be mediated in part by increased levels of cytokines, fibrin clot formation, and oxidative stress. Glutathione (GSH), a well-known antioxidant molecule, may have therapeutic effects in countering this pathway of immunothrombosis as decreased levels of (GSH) have been associated with increased viral replication, cytokine levels, and thrombosis, suggesting that glutathione supplementation may be therapeutic for COVID-19. GSH supplementation has never been explored as a means of treating COVID-19. This study investigated the effectiveness of liposomal glutathione (GSH) as an adjunctive therapy for peripheral blood mononuclear cells (PBMC) treated with SARS CoV-2 spike protein. Upon the addition of GSH to cell cultures, cytokine levels, fibrin clot formation, oxidative stress, and intracellular GSH levels were measured. The addition of liposomal-GSH to PBMCs caused a statistically significant decrease in cytokine levels, fibrin clot formation, and oxidative stress. The addition of L-GSH to spike protein and untreated PBMCs increased total intracellular GSH, decreased IL-6, TGF-beta, and TNF-alpha levels, decreased oxidative stress, as demonstrated through MDA, and decreased fibrin clot formation, as detected by fluorescence microscopy. These findings demonstrate that L-GSH supplementation within a spike protein-treated PBMC cell culture model reduces these factors, suggesting that GSH supplementation should be explored as a means of reducing mediators of immunothrombosis in COVID-19.
Identifying Emerging Issues in the Seafood Industry Based on a Text Mining Approach
Authors: Han Kiuk , Yeom Jaesun , Chung Keunsuk
Published: February 2024

Identification of emerging issues has garnered growing interest as a way to establish proactive policy formulation. However, in fisheries research, analyzing such issues has largely depended on the literature or researchers’ judgment. We use keyword analysis, targeting news application programming interfaces (News APIs) (72,981 news sources and blogs), to investigate issues in the global seafood industry from January 2019 to March 2022. Among a variety of topics identified by year and country, in general, seafood market function, health, and tariffs were the main issues in 2019, while COVID-19-related issues were primarily mentioned between 2020 and 2021. After 2022, the role of the market regained attention, and various new issues rose to the surface. To identify emerging issues, we jointly employ dynamic time warping (DTW) and growth models, which derive several keywords, including coercion, cuisines, food safety, ketones, plastic ingestions, seafood alcohol, urbanization, wastewater treatment, and the World Trade Organization (WTO). High interest in food safety, environmental change, trade conflict, and seafood value improvement reveal the need for proper policy responses.
Modeling and Numerical Computation of the Longitudinal Non-Linear Dynamics of High-Speed Elevators
Authors: Tian Zhongxu , He Hang , Zhou You
Published: February 2024

High-speed elevator systems comprise numerous components, and vibration issues are prevalent. The evident non-linear behavior resulting from changes in the wire rope length adds complexity to the investigation of elevator dynamics issues. This paper investigates dynamics modeling and numerical solution methods for longitudinal vibrations in a typical high-speed elevator system. The primary contributions of this paper include constructing a dynamics model for high-speed elevators using a substructure dynamics modeling approach. This model incorporates Newton’s law and the Lagrange equation to comprehensively represent the dynamics of the elevator car, car frame, traction system, and tension system. Additionally, a non-linear dynamics model of the steel wire rope is developed using the centralized mass method. This paper also presents an algorithm to solve the time-domain dynamics based on the variable-step-length Runge–Kutta method. Furthermore, it investigates the non-linear dynamics of elevators considering variations in the elevator’s intrinsic frequency and different elevator control strategies, focusing on the response characteristics of high-speed elevator dynamics. The findings of this thesis hold significant importance in the field of high-speed elevator dynamics. They aid in the design and debugging of high-speed elevator systems and serve as a foundation for future research into the non-linear aspects of elevators.
Stability Analysis of the Exploitation System with Room and Pillar by Analytical Methods
Authors: Toderas Mihaela
Published: February 2024

The mining method that is still often used in salt deposits is the room-and-pillar mining method, in which the dimensioning of the most requested element in the system is followed. The pillars are the elements subjected to the greatest loads. Knowing the size and distribution mode of the secondary state of stress—deformation—is a necessity that can lead to the design and realization of stable, reliable underground excavations. This paper proposes an analytical assessment model of the secondary stress state in the pillars between the operating rooms, as well as in the whole system room–pillar–floor, based on the results obtained from laboratory research through modeling and in situ research. For this purpose, the evaluation of the secondary stress state was carried out considering the following methods: (1) the dimensioning method based on the theory of limit equilibrium, taking into account the effective stress in the pillars; and (2) the mechanics of the continuous environment based on the design of some analytical models for evaluating the secondary stress-deformation state in the pillar and floor. The exploitation of one of the largest salt deposits in Romania is used as a case study, and the stability of the exploitation system with rooms and pillars is evaluated by analytical methods. The secondary state of tension was calculated at different points on the height of the pillar. Through the proposed algorithm, the value of the axial component of the secondary stress state at different points along the axis of a pillar located at a depth of 100 m varies between 1.498 and 1.657 MPa, compared to the value obtained by the finite element method and in situ measurements, which was 1.64 MPa. The comparison revealed a high degree of agreement between the results obtained for the depth of 100 m using both the FEM and laboratory and in situ measurements. This suggests that the proposed algorithm is a reliable method for predicting the secondary stress state. The presented algorithm can be extended in the field of mining deposits, where mining methods with rooms and pillars are used.
Revitalizing the Canal de Castilla: A Community Approach to Sustainable Hydropower Assessed through Fuzzy Logic
Authors: Rodríguez Pérez Ángel Mariano , Rodríguez César A. , Olmo Rodríguez Lucía , Caparros Mancera Julio José
Published: February 2024

This study addresses the sustainable revitalization of the Canal de Castilla through a community-focused approach and an assessment via fuzzy logic of the implementation of hydroelectric turbines. The canal, built in the 18th century, played a key role in transportation and territorial unification, but the deterioration of the locks has limited its functionality. This research use surveys as tools to assess the impact of the Canal de Castilla in different areas. With more than 85% of the inhabitants analyzed supporting measures in the areas of building and research at a high or very high level, and specifically proposing sustainable improvements that respect historical heritage, the installation of axial turbines in the cross channels is proposed as an efficient solution, highlighting their adaptability and low environmental impact. The careful selection of turbines, considering the historic nature of the canal, is supported with a detailed analysis using fuzzy logic. The innovation lies in the synergistic integration of community perceptions and technical analysis, providing a balanced foundation for decision making in heritage revitalization projects. This proactive approach seeks not only to identify challenges but also to formulate solutions, committing to sustainable development and active community participation.
Influence of the Fear of Movement and Fatigue on Self-Efficacy for Physical Activity in Women with Fibromyalgia
Authors: Lavín-Pérez Ana Myriam , Collado-Mateo Daniel , Gil Arias Alexander , Gutiérrez Lorena , Écija Carmen , Catalá Patricia , Peñacoba Cecilia
Published: February 2024

Introduction and purpose: Self-efficacy is considered an antecedent for physical activity levels in fibromyalgia patients. However, the influence of the fear of movement and fatigue on the self-efficacy to reduce physical inactivity is still not clear and could be critical in improving the biopsychosocial benefits of therapeutic exercise. In this way, the present study aims to assess the relationship between self-efficacy, fatigue, fibromyalgia impact, the fear of movement, and physical activity. Additionally, it aims to explore differences among patients based on self-reported physical activity levels. Material and methods: A sample of 115 women diagnosed with fibromyalgia were evaluated in this prospective study. The variables were the impact of fibromyalgia, the fear of movement, fatigue, self-efficacy, and physical activity levels. Results: Patients with high and moderate physical activity levels had higher self-efficacy for physical function (p < 0.05), which is in line with the previously known model. Furthermore, a model was developed where the significant relationship between the fear of movement and self-efficacy for physical activity was significantly mediated by general fatigue and the impact of fibromyalgia on physical function. Conclusions: The fear of movement may influence self-efficacy, affecting physical activity levels; therapeutic exercises targeting the fear of movement can enhance self-efficacy and activity levels, while fatigue and fibromyalgia may mediate this relationship.
A Multi-Task Learning and Knowledge Selection Strategy for Environment-Induced Color-Distorted Image Restoration
Authors: Ding Yuan , Wu Kaijun
Published: February 2024

Existing methods for restoring color-distorted images in specific environments typically focus on a singular type of distortion, making it challenging to generalize their application across various types of color-distorted images. If it were possible to leverage the intrinsic connections between different types of color-distorted images and coordinate their interactions during model training, it would simultaneously enhance generalization, address potential overfitting and underfitting issues during data fitting, and consequently lead to a positive performance boost. In this paper, our approach primarily addresses three distinct types of color-distorted images, namely dust-laden images, hazy images, and underwater images. By thoroughly exploiting the unique characteristics and interrelationships of these types, we achieve the objective of multitask processing. Within this endeavor, identifying appropriate correlations is pivotal. To this end, we propose a knowledge selection and allocation strategy that optimally distributes the features and correlations acquired by the network from the images to different tasks, enabling a more refined task differentiation. Moreover, given the challenge of difficult dataset pairing, we employ unsupervised learning techniques and introduce novel Transformer blocks, feedforward networks, and hybrid modules to enhance context relevance. Through extensive experimentation, we demonstrate that our proposed method significantly enhances the performance of color-distorted image restoration.
Large Eddy Simulation of the Effect of Hydrogen Ratio on the Flame Stabilization and Blow-Off Dynamics of a Lean CH4/H2/Air Bluff-Body Flame
Authors: Cheng Lei , Zhang Meng , Peng Shiyao , Wang Jinhua , Huang Zuohua
Published: February 2024

This study investigated the flame structure and dynamics of a bluff-body flame when numerically close to blow-off conditions. This includes the impact of the hydrogen ratio on lean CH4/H2/air flame stabilization and blow-off characteristics. In this study, we assessed the impacts of four different hydrogen ratios: 0%, 30%, 60%, and 90%. Large eddy simulation (LES) was coupled with a thickened flame (TF) model to determine the turbulent combustion using a 30-species skeletal mechanism. The numerical results were progressively validated using OH-PLIF and PIV techniques. The results obtained from the numerical simulations showed minor differences with the experimental data on the velocity field and flame structure for all conditions. The presented results reveal that the flame is stabilized in higher-strain-rate spots more easily in the presence of high hydrogen ratios. Moreover, the flame location moves away from the concentrated vortex area with an increasing hydrogen ratio. The results of our blow-off investigation indicate that the blow-off sequence of a premixed bluff-body flame can be separated into two stages. The entire blow-off process becomes shorter with an increase in the hydrogen ratio. The primary reason for global extinction is a reduction in the heat release rate, and enstrophy analysis implies that blending hydrogen can reduce the enstrophy values of flames at the downstream locations. The dilatation and baroclinic torque terms decrease close to blow-off, but their decline is not significant in high-hydrogen-ratio conditions.
A Story-Based Random Structure Modeling Method for Regional Buildings Earthquake Loss Estimation
Authors: Yang Zhi , Lu Yang , Xiong Feng
Published: February 2024

To estimate earthquake losses for regional buildings, it is important to consider the varying seismic performances of different types of buildings. To achieve this, a dynamic elastic–plastic analysis based on detailed structural modeling is more accurate than the capacity spectrum method based on a single degree of freedom to obtain the response and damage of various structures under seismic activity and provide a more precise estimate of earthquake losses for buildings. Detailed information about the building facilities is necessary to create a fine structural model. However, obtaining precise actual structural details can be challenging with existing methods, especially when there are a large number of buildings to consider. This paper proposes a new method called story-based random structure (SBRS) modeling to address this issue, which is based on the common and reasonable layout of the structure. The process involves choosing design parameters that can represent the structural arrangement of a building as variables. These parameters include the materials’ type and strength, proportions, the components’ size, and other relevant factors. The values for these variables are determined based on engineering experience and design specifications. The range of values for these variables is also determined to ensure that all design requirements are met. Finally, the Latin Hypercubic Sampling (LHS) method is used to randomly sample and combine the variables, establishing a detailed structural model of the building with structural uncertainty. According to the results of the analysis, this method can simulate the structure and component information of a building by using a probabilistic approach, even without knowing the specific structural design. This method can be based on a small amount of readily available building information and solves the problem of the rapid and refined modeling of a large number of buildings at the regional scale. It also makes it possible to estimate the earthquake loss of regional buildings based on their seismic capacity.