bluuebunny/crossref_metadata_2025 huggingface dataset:
Gas Reservoir Identification Based on Nonstationary and Anisotropic FFT-MA Stochastic Modeling
Authors: Zeng Fanxin , Zhang Hongbing , Zhang Lingyuan , Zhang Dailu , Zhao Xiang , Ren Quan , Zhu Xinyi , Zhu Xinjie
Published: September 2024

High-resolution reservoir modeling is a crucial technique for the precise identification of gas reservoirs, holding significant importance in guiding natural gas development. However, the nonstationarity and statistical anisotropy of subsurface media present immense challenges to the reliable implementation of high-resolution reservoir modeling. In response to the nonstationarity and anisotropy of complex reservoirs, we propose a novel stochastic modeling method based on fast Fourier transform moving average (FFT-MA). In this method, variational mode decomposition (VMD) is introduced to decompose logging curves into a series of sparse components with specific center frequencies and narrow bandwidths. Subsequently, the autocorrelation functions of each component are computed and synthesized, thereby inferring the nonstationary vertical autocorrelation functions of logging curves. In addition, to characterize the anisotropic and lateral nonstationary features of the reservoir, angle parameters and lateral autocorrelation functions are extracted from seismic records. Lastly, considering the high sensitivity of Lamé constants (λ and μ) and their density-combined counterparts (λρ and μρ) to gas-bearing reservoirs, FFT-MA stochastic modeling is applied to λρ, μρ, and ρ. Gas identification is then performed based on the joint probability distribution extracted from logging data. The proposed method is tested in the sand-shale reservoirs of the Yinggehai Basin, China. The results indicate that the stochastic models for λρ, μρ, and ρ effectively characterize the nonstationary and anisotropic features of complex reservoirs, significantly enhancing the resolution and accuracy of gas identification.
Wheat peptides alleviate constipation by promoting enteric neurogenesis via mAChR-mediated calcium signaling pathways in mice
Authors: Wang Qianqian , Shen Fei , He Guanghua , Du Juan , Cai Haiying , Zhao Minjie , Wang Jing , Zhao Haobin , Wang Lida , Feng Fengqin
Published: September 2024

Constipation is a prevalent gastrointestinal issue. Wheat peptides (WP) effectively alleviate loperamide-induced constipation in mice. Oral administration of WP (0.5 mg/g.bw) improved defecation, small intestinal propulsion, and intestinal barrier function in mice. WP also modulated gut inflammation and enteric nervous system factors. Additionally, WP intervention effectively rectified gut microbiota dysbiosis by restoring microbial diversity and modulating gut bacteria to approach normal levels. Of particular significance, transcriptome data indicated alterations in gene expressions related to the calcium signaling pathway in the colon of constipated mice. RT-qPCR analysis further corroborated that WP upregulated the gene expression of cholinergic receptor (Chrm1), Itpr2/3, Calml3, and Calm4. Furthermore, 3D microscopy revealed that WP increased the number of enteric nerves in the colon of constipated mice. These findings suggest WP mitigate constipation by activating muscarinic acetylcholine receptors, enhancing calcium signaling, and promoting enteric neurogenesis to improve intestinal peristalsis. Overall, WP demonstrate therapeutic potential for treating constipation.
Deep learning-based building and road detection reveals higher permafrost thaw-related damage costs than previously estimated for Alaska
Authors: Manos Elias , Witharana Chandi , Liljedahl Anna
Published: September 2024

Arctic infrastructure is challenged by ice-rich permafrost thaw that causes differential ground subsidence. Economic impact estimates of permafrost thaw damages require accurate infrastructure inventories. We developed a deep learning-based mapping pipeline, HABITAT (High-resolution Arctic Built Infrastructure and Terrain Analysis Tool), to automatically detect infrastructure from Maxar satellite imagery in 285 Alaskan communities. Combining HABITAT with OpenStreetMap (OSM), we mapped a building footprint of 53M m 2 and a road network of 50,477 km across Alaska. HABITAT adds 17M m 2 to the statewide building footprint not accounted for by OSM and 6M m 2 within discontinuous and continuous permafrost. We identified at-risk infrastructure on discontinuous and continuous permafrost with bearing capacity loss and ground subsidence between the decades 2015–2024 and 2055–2064 projected by a permafrost geotechnical model. Projected permafrost thaw damages to buildings and roads could cost Alaska $51.4B. This is $21.7 to $43.2B more than estimates from previous literature due to the additional building footprint mapped by HABITAT. Several communities bearing the highest of this cost are identified in a government report as already experiencing the effects of permafrost thaw. Additionally, communities with high social vulnerability may experience higher economic losses that further challenge mitigation and disaster recovery efforts.
Arginine vasopressin promotes transient contractile responses through distinct mechanisms in rat aorta and mesenteric resistant arteries
Authors: Yang Aihua , Zhang Yifeng , Wang Yuhang , Wang Xiaojun , Bao Haiyong , Ren Jun , Zhu Weizhong
Published: September 2024

Purpose Neurohormone-regulated peripheral vascular resistance is considered one of the factors governing blood pressure. This study was designed to evaluate the effect of arginine vasopressin (AVP) on contraction of endothelium-intact or -denuded rat aorta and mesenteric resistant arteries.
Methods The wire myograph technique was used to assess the contractility of the vascular smooth muscles in response to a high-K+, phenylephrine, AVP, and inhibitors, etc. The time-course of agonist-evoked contraction was then recorded. The endothelium of the mesenteric resistance arteries and abdominal aorta were denuded by physical abrasion, as evidenced by acetylcholine-induced vasodilation dysfunction.
Results Our result revealed that (1) AVP, but neither high K+ nor phenylephrine, evoked transient contraction of abdominal aorta and mesenteric resistance arteries; (2) Endothelial removal, V2 receptor antagonists, sGC inhibitors, or nitric oxide(NO) synthase inhibitors reversed the transient contraction of mesenteric resistance arteries into sustained contraction, but not in aorta;(3) Pharmacological inhibition of GRK2 altered AVP-elicited temporal contractile response into a sustained contraction in denuded aortic endothelium;(4) The vasopressin receptor V1A blocker abolished AVP-induced contractile responses in both vessel preparations.
Conclusion V2-mediated NO pathway in endothelium and the V1A-mediated GRK2 signaling pathways in smooth muscle are involved in AVP-induced transient contractions in rat mesenteric resistance and aortic vessels, respectively.
Utilization of Satellite Imagery and Machine Learning for Mapping Landslide-Prone Areas in Banjarnegara Regency, Central Java Province
Authors: Alifka Almastiana , Prasetyo Rindang Bangun
Published: September 2024

The high risk of landslides in Banjarnegara Regency requires preparedness for the potential for landslides. One way that can be utilized by the government and the community is to use a mitigation map that illustrates the vulnerability of landslides in Banjarnegara Regency. This study aims to produce a landslide sus-ceptibility map with satellite imagery and the best machine learning model. The variables used in this study include rainfall, soil type, geology, aspect, curvature, slope gradient, elevation, TWI, NDWI, NDVI, NDBI, and land cover. Based on the results obtained using the Random Forest, Support Vector Machine, Logistic Regression, and Artificial Neural Network models, in 2021 and 2022, the Random Forest model had the best performance with an accuracy of 82.50% and 88.46%, respectively, while in 2022 the model with the best performance was the Support Vector Machine with an accuracy of 86.84%.
Comparative Study on the Effects of High-Fat Diet and Capsicum Diet on the Digestive Organs of Guinea Pigs
Authors: Guan Wen-Xiang , Lan Zhuo , Luo Xiao-Jun , Gao Jing-Xian , Bai Chang-xi
Published: September 2024

Research Objective: To clarify the different effects of high-fat diet and capsicum diet on the digestive organs of guinea pigs. Experimental Methods: A total of 24 male Hartley guinea pigs were apportioned randomly and equally into three groups: the control group (n=8), the high-fat diet group (n=8), and the capsicum diet group (n=8). After 12 weeks of modeling, samples were collected from the abdominal aorta serum, liver, gallbladder, stomach, and colon. Biochemical analysis for the serum total cholesterol, triglycerides, low-density lipoprotein, and high-density lipoprotein cholesterol. Inflammatory markers in the serum, such as interleukin-1β, interleukin-6, and tumor necrosis factor-α, were measured by enzyme-linked immunosorbent assay. Hematoxylin-eosin staining (H-E) was used to observe morphological changes in the liver, gallbladder, stomach, and colon tissues. Compared with the normal control group, both high-fat and capsicum diets significantly elevated blood lipid levels and inflammatory indexes in the serum of guinea pigs (P<0.01), with the effects being more pronounced in the high-fat diet group (P<0.001). Pathological results indicated that both high-fat and capsicum diets induce damage to the liver, stomach, gallbladder, and colon, with the high-fat diet showing particularly significant effects. Conclusion: Consuming high-fat and capsicum foods may induce damage to the digestive system, resulting in abnormal lipid metabolism.
Landslide susceptibility assessment based on ConvNext in Longyang district of Baoshan city, China
Authors: Zhao Xiangwei , Ma Haoquan , Niu Chong , Gao Lei , Kong Xianghui
Published: September 2024

Landslide is a common type of geological disaster in the world, which causes great harm to people's life and financial security. The evaluation of landslide susceptibility plays an important role in the prevention of landslide disaster, and has always been the focus of research in this field. In order to establish an accurate landslide susceptibility evaluation model, this paper takes Longyang District, Baoshan City, Yunnan Province, China as the research area, and comprehensively considers 10 evaluation factors such as elevation, slope, slope direction, lithology, water system, residential area, highway, terrain, Normalized Difference Vegetation Index(NDVI) and rainfall to establish a landslide susceptibility evaluation model based on ConvNeXt. More than 27000 sample data were used for model training, and the spatial distribution map of landslide susceptibility was obtained by using the trained model to predict the study area. Comparing this model with three typical landslide susceptibility evaluation models based on ResNet and Support Vector Machine(SVM), the performance indicators Area Under Curve(AUC) values of the three models were 0.97, 0.77, and 0.65, respectively, with accuracies of 0.92, 0.70, and 0.69, indicating that the landslide susceptibility evaluation model based on ConvNeXt proposed in this paper has significant advantages.The landslide susceptibility can be accurately evaluated, and the scientific basis for the prevention and control of landslide disasters can be provided.
Intercropping effects of agro-crops under walnut forests in Wuxi, Chongqing, China: soil environment, walnut growth and intercropping benefits
Authors: Liu Jianke , Wang Jingru , Wu Shuang , Zhang Jiatian , Zhang Xiaodan , Chang Jun , Yang Shuiping
Published: September 2024

Walnut is an important woody oil-bearing tree crops, and the compound planting with agro-crops can provide a solution to food shortages. This study focuses on two monoculture planting patterns (bare soil and retaining grass) and four common local intercropping planting patterns in Wuxi County, Chongqing City, China, investigating soil physical and chemical properties, microbial diversity, walnut growth and mineral nutrition, as well as the yield and benefit of walnuts and agro-crops. The results showed that: (1) Intercropping treatments and retaining grass can reduce soil bulk density, increase soil moisture content, and significantly enhance both soil total porosity and capillary porosity. (2) Intercropping treatments and retaining grass can significantly lower soil pH and increase the content of soil organic matter, total nitrogen, total phosphorus, available phosphorus, available potassium, available zinc, and available manganese. Intercropping with soybeans can significantly decrease the available copper content in soil, while intercropping with chili peppers can significantly reduce the alkaline hydrolyzable nitrogen content in the soil. (3) Except for the intercropping with tobacco, which slightly reduces soil fungal community diversity, retaining grass and other intercropping treatments can significantly increase both the richness and diversity of soil bacterial and fungal communities. (4) Retaining grass and intercropping treatments increased the annual increment in walnut tree meter diameter, spring shoot length, and the nitrogen and manganese content of leaves. They also significantly increased leaf length, width, thickness, and magnesium content. Intercropping with soybeans significantly increased the length of summer shoots and significantly reduced leaf moisture content as well as the content of potassium, calcium, and copper. Intercropping with chili peppers significantly increased the length of summer shoots and significantly reduced leaf moisture content and potassium, copper, and zinc content. (5) Intercropping treatments significantly increased the yields and benefits of walnuts. Among these treatments, intercropping with chili peppers provides the highest benefits, while intercropping offers the lowest. However, retaining grass resulted in no output or benefits from agro-crops. Intercropping planting patterns not only significantly improve the soil environment and promote walnut growth but also increase yield and benefits. Additionally, retaining grass contributes to the improvement of soil environment to a certain extent, further promoting walnut growth.
Bioinformatical Enrichment Analysis Reveals Key Differentially Expressed Genes in Endometriosis Pathogenesis
Authors: Kusum¹ Kusum , Ashish Ashish , Singh Royana , Bhushan Ravi , Chaube Radha , Rai Sangeeta
Published: September 2024

Endometriosis is a gynecological disease characterized by the presence of uterine (eutopic) endometrial glands and tissues outside the intra-uterine locations, in ectopic regions such as the pelvic peritoneum, fallopian tubes, or ovaries. Approximately 5–10% of reproductive and 20–50% of infertile women are affected by endometriosis. The pathogenesis of endometriosis involves various factors, including hormonal, environmental, genetic, and immune system components, directly or indirectly altering estrogen levels and impacting women's reproductive health. This study aimed to identify novel and potential biomarkers for endometriosis using mRNA seq analysis. Differentially expressed genes (DEGs) were identified from raw gene expression profiles, and their functional analysis was subsequently conducted. A total of 552 DEGs (312 upregulated and 240 downregulated) were identified in samples from women with endometriosis compared to control subjects. Major DEGs, such as C3, PSAP, APP, GNG12, were identified as hub nodes and found to be involved in various functions, including epithelial cell differentiation and development, proteolysis, gland development, muscle fiber development, and response to hormone stimulus. These DEGs may play a direct or indirect role in the pathogenesis of endometriosis, serving as potential biomarkers for ectopic endometrium. While this study provides a preliminary insight into the mechanism of endometriosis, further detailed studies are necessary to fully understand its path of action.
The impact of salt consumption on cardiometabolic and cognitive health in aged female rats
Authors: SUN FEN , Zhao Lu-Ping , Jin Qi , Wang Qiu-Xiang , Jin Shi-Han , Xie Ji-Zhi , Xu Jun-Tao , Yin Meng-Jia , Jin Chao , Wang Jing-Hua
Published: September 2024

Health concerns about excess dietary salt have traditionally focused on its relationship with hypertension and the increased risk of cognitive impairment. However, research has often overlooked the unique health concerns and physiological differences between men and women, leading to gaps in knowledge, particularly regarding disease prevention and treatment strategies for women. The present study examined aged female rats over 12 weeks, using control, low, and high salt diets to mimic the post-menopausal phase in human females when cardiovascular risks typically increase. Cardiometabolic parameters and cognition were monitored. The findings revealed the impact of varying salt diets on blood lipids, blood pressure (BP) and heart rate (HR) levels and variability, anxiety, and cognition. Specifically, intake of a low-salt diet led to a significant reduction in BP levels but an increase in BP variability starting from the eighth week of the diet onset. Moreover, HR levels and variability were notably higher with the low-salt diet. Aged female rats exhibited increased anxiety on the low-salt diet at the fourth week, but the anxiety began to improve starting from the eighth week. Additionally, a trend suggested that the low salt intake worsened short-term memory while improving long-term memory. Furthermore, plasma lipids decreased significantly in aged female rats on a high-salt diet compared to those on a low-salt diet. The study provides valuable insights into the effects of salt intake on cardiometabolic parameters and cognitive function in aged female rats, highlighting the importance of considering sex-specific dietary guidelines for cardiometabolic and cognitive health.
An improved CNN model in image classification application on water turbidity
Authors: Nie Ying , Chen Yuqiang , Guo Jianlan , Li Shufei , Xiao Yu , Gong Wendong , Lan Ruirong
Published: September 2024

Water turbidity is an important indicator for evaluating water clarity and plays an important role in environmental protection and ecological balance. Due to the subtle changes in water turbidity images, the differences captured are often too subtle to be classified. Convolutional neural networks (CNNs) are widely used in image classification and perform well in feature extraction and classification. This study explored the application of convolutional neural networks in water turbidity classification. The innovation lies in applying CNN to water turbidity images, focusing on optimizing the CNN model to improve prediction accuracy and efficiency. The study proposed four CNN models for water turbidity classification based on artificial intelligence, and adjusted the number of model layers to improve prediction accuracy. Experiments were conducted on noise-free and noisy datasets to evaluate the accuracy and running time of the models. The results show that the CNN-10 model with a dropout layer has a classification accuracy of 96.5% under noisy conditions. This study has opened up new applications of CNN in fine-grained image classification, and further demonstrated the effectiveness of convolutional neural networks in water turbidity image classification through experiments.
Two distinct oscillatory auxin signals define the plasticity of lateral rooting in Arabidopsis thaliana
Authors: Kleine-Vehn Jürgen
Published: September 2024

The so-called root clock defines lateral root pre-branch sites (PBS) but how these sites contribute to the root system architecture remains incompletely understood1,2,3,4. Here we reveal in the model plant Arabidopsis thaliana that two distinct oscillatory systems for the phytohormone auxin coordinate the spatial and temporal identity of PBS, jointly defining the lateral root density. We followed auxin signalling dynamics for days and thereby detected a systemic auxin signal oscillating in the mature primary root, which is distinct from the previously described root clock at the root tip. While the root clock spatially primes the PBS in the growing root tip, the systemic oscillatory auxin signal temporally controls the auxin-dependent identity of these PBS. Light perception in the shoot defines the strength of the systemic auxin signal and thereby controls the auxin-reliant ability of PBS to develop into lateral roots. Moreover, PHYB and CRY1 mediate the light-dependent integration of other environmental signals, such as ambient temperature, into the control systemic auxin signalling and lateral root density. Our work reveals how two spatially distinct oscillatory auxin signals define the plasticity of plant root development in response to fluctuating conditions.
Understanding chinstrap penguin and elephant seal migrations in the Southern Ocean
Authors: Wilson Cara , Hinke Jefferson T. , Mazloff Matthew
Published: September 2024

Characterizing the high-latitude winter foraging habitats of migratory marine predators is necessary for conservation and management in Antarctica. Tracking data from chinstrap penguins (Pygoscelis antarcticus) and southern elephant seals (Mirounga leonina), key Antarctic predators with different diets and foraging habits, indicate that approximately 12% and 5%, respectively, of tagged penguins and seals undertake long-distance winter migrations to remote regions south of 60°S between 120°W and 170°W. Tracking data revealed reduced daily swimming speeds and two hotspots of increased use, consistent with increased foraging efforts, for both species in this region. Light limitation during winter, however, precludes the use of optical satellite data to characterize marine productivity here, but biogeochemical-Argo floats can provide year-round chlorophyll data. These data inform the Biogeochemical Southern Ocean State Estimate (B-SOSE), which provides year-round estimates of marine productivity. Overlapping the predator hotspots, B-SOSE predicts two areas with year-round elevated surface chlorophyll levels, consistent with previous studies indicating enhanced mixing in those areas. We hypothesize that persistent areas of elevated chlorophyll centered near 160°W and 120°W near the boundaries of the Ross Gyre and the southern boundary of the Antarctic circumpolar current support a productive food web capable of supporting the diverse foraging niches of pelagic species.
Non-cooperative Inference Method for the IoBT Topology Based on Flow Rate Estimation
Authors: Huang Jun , Dong Rongcheng , Niu Zhao , Peng Chao , Chen Jie
Published: September 2024

The widespread integration of Internet of Things (IoT) technology in the military domain has brought significant attention to the security concerns surrounding the Internet of Battlefield Things(IoBT). Given the limited communication resources within IoBT, there's a growing focus on conducting network security detection without disrupting normal network operations. Topology serves as a crucial foundation for conducting network security detection in IoBT, facilitating the discovery of abnormal devices and unauthorized access detection. Security detection based on topology can effectively enhance the information security and operational levels of IoBT. This paper utilizes matching analysis of time series for information exchanged between neighboring nodes and implements IoBT topology inference based on flow rate estimation, and a threshold parameter adaptive adjustment strategy is innovatively proposed to improve the accuracy of topology inference. The non-cooperative inference method proposed in this paper enables network topology inference without network access and information parsing, exhibiting strong generality and independence from the discovery of acknowledgment frames during information exchange processes. Simulation results demonstrate the feasibility and superiority of this method.
Cardiometabolic Index Correlations with Coronary Heart Disease among U.S. Adults: A NHANES 1999–2018 Analysis
Authors: Lei Yu , Luo Yu , Wang Yi , Luo Lei , Yang Yanhui , Chen Xin , Li Ji
Published: September 2024

Background
Coronary heart disease (CHD) is a prevalent global health challenge, resulting in substantial morbidity and mortality, with atherosclerosis being its principal pathological characteristic. Recently, the interrelationship between CHD and cardiometabolic diseases has garnered significant attention in the research community. The cardiometabolic index (CMI), a composite indicator of lipid metabolism and obesity, has emerged as a potential predictor of cardiometabolic disorders. The principal aim of the research is to elucidate the correlation between CHD and CMI within a large-scale, nationally representative sample.
Methods
This study employed a cross-sectional methodology, examining datasets derived from the National Health and Nutrition Examination Survey (NHANES) conducted over the period of 1999 to 2018.. After applying the exclusion criteria, the study ultimately included 33,917 individuals. The CMI was calculated via the following formula: CMI = waist-to-height ratio (WHtR) × [triglyceride (TG)/high-density lipoprotein cholesterol (HDL-C)]. CHD status was determined by self-reported physician diagnosis. To evaluate the link between CMI and CHD, several weighted generalized linear models were utilized, adjusted for potential confounding variables.
Results
Considering the weights, the prevalence of CHD was 3.45%. The CMI values were significantly greater among participants with CHD than among those without CHD. Upon covariate adjustment, a significant and positive correlation was identified between elevated CMI and the incidence of CHD. Subgroup analysis elucidated a modification of the association by hypertension status, demonstrating a more pronounced correlation in non-hypertensiveindividuals.
Screening and validation of optimal real-time PCR reference genes for Abelmoschus manihot
Authors: Wu Qixuan , Deng Meixin , Zhao Xiaolan , Long Jianmei , Zhang Jianxia
Published: September 2024

Abelmoschus manihot is an important medicinal and edible plant known for its functional secondary metabolites. However, little is known about the key genes involved in production of secondary metabolites in A. manihot. This is largely due to a lack of effective gene expression detection systems for A. manihot, and thus screening of real-time PCR reference genes is a prerequisite. In this study, 11 candidate reference genes were screened and cloned from A. manihot, and their expression stability was evaluated in different tissues using four algorithms: geNorm, NormFinder, BestKeeper, and RefFinder. The expression stability of eIF and PP2A1 was the highest, while that of tubulin alpha (TUA) was the lowest. The combined use of the two most stable reference genes, eIF and PP2A1, met the experimental requirements for normalizing gene expression in A. manihot. Furthermore, the gene expression of transcription factors bHLH147 and bHLH148 was further validated by data normalization. This study identified potential reference genes in different A. manihot tissues, paving the way for functional gene analysis and dissecting metabolite regulation mechanisms in A. manihot.
CBRM: A Causal Approach to BalancingPopularity Bias with Global Quality inRecommendation Systems
Authors: Dong Rongsheng , Lv Dongting , Li Fengying
Published: September 2024

The popularity bias in recommendation systems leads to the over-recommendation of popular items, thereby neglecting high-quality but less popular items. This bias reduces both recommendation accuracy and user satisfaction. To address this issue, this paper proposes leveraging global quality to balance the popularity bias in recommendation systems, thereby improving recommendation accuracy. The key lies in how to eliminate the adverse effects of global quality on items during the training process and how to incorporate global quality in the recommendation phase to generate the top-K recommendations. To this end, this paper introduces the (Causal Balance Recommendation System) CBRM, which adopts a new training and inference strategy. CBRM utilizes the backdoor adjustment technique to cut off the backdoor path of global quality, thereby eliminating the bias introduced by global quality during model training. Additionally, it adjusts recommendation scores through causal intervention to introduce the desired global quality. Compared to four recommendation models—BPRMF, BPR-PC, MACR, and PDA,CBRM demonstrates superior performance on the Douban Movie and Netflix datasets, and particularly excels on the ML-10M dataset. Specifically, compared to the best-performing model, PDA, CBRM achieves improvements of 14.5%, 7.1%, 3.3%, and 8.9% in recall, precision, hit rate, and normalized discounted cumulative gain (NDCG), respectively. The experimental results demonstrate the effectiveness of CBRM in practical applications and validate the potential of causal theory in enhancing the accuracy of recommendation systems.
Prevalence And Risk Factors Of Depression In College Students in Northeast China During the COVID-19 Pandemic: A Cross-sectional Study
Authors: Cui Yanze , Yang Liying , Yang Wanqiu , Wang Xiaohong , Liu Jiazhou , Wang Yanqing , Liu Jiacheng , Leng Dan , Yang Borui , Zhao Na , Kang Chuanyi
Published: September 2024

Background
The Coronavirus disease 2019 pandemic spread rapidly worldwide, posing a serious health challenge to the global public. However, few studies exist on the association between health risk behaviors and depression among Chinese college students during the stage. Therefore, this study aimed to explore associated factors including health risk behaviors and life satisfaction among Chinese college students with depression.
Methods
A cross-sectional study was conducted in northeast China from April to June 2020 on purposively sampled from two colleges. Data were collected through the Adolescent Students' Life Satisfaction Scale, Health Risk Behavior Scale, Self-rating Anxiety Scale, and Self-rating Depression Scale. Binary logistic regression was conducted to analyze the risk factors of depression.
Results
The prevalence of depressive state of college students was 32.1%. Students with health-compromising behavior (OR = 1.128, p < 0.001) were positively correlated with depression. Furthermore, satisfaction with friendships (OR = 0.941, p < 0.001), freedom (OR = 0.955, p = 0.004), school (OR = 0.966, p = 0.010), and the environment (OR = 0.933, p < 0.001) were protective factors for students’ depression.
Conclusions
To reduce this depression, schools should increase publicity and education to promote a regular diet among college students, channel adolescents' destructive emotions to prevent them from self-injury and self-harm, enrich their after-school life to strengthen their interpersonal communication, and enhance friendship- building among them.
An Intelligent Framework for Modeling Nonlinear Irreversible Biochemical Reactions Using Artificial Neural Networks
Authors: Bilal Hazrat , shah Rehan Ali , Ahmad Hijaz , Jan Akhter , Radwan Taha
Published: September 2024

The objective of this paper is to perform a comparative performance analysis of three different algorithms, namely Levenberg-Marquardt (LM), Bayesian Regularization (BR), and Scaled Conjugate Gradient (SCG), for nonlinear irreversible biochemical reaction (NIBR). These algorithms are based on artificial neural network (ANN) techniques. Nonlinear irreversible biochemical reactions are described by a set of nonlinear ordinary differential equations (ODE’s) that take into account the concentration of different compounds, such as products , substrate, enzyme-substrate complex, and enzyme-product complex. To develop the Backpropagation Levenberg Marquardt artificial neural networks (BLM-ANN) model, a dataset is created using the RK4 method, incorporating diverse NIBR models with varying reaction rates. A comparative analysis is presented, focusing on the performance of algorithms in handling the trained dataset. The design of the ODE’s system of the proposed model is done using the MATLAB/Simulink environment. To analyze the developed model, the artificial neural network toolbox is employed. The reliability and efficiency of the BLM-ANN model were evaluated by training, validation, and testing phase, it demonstrated an accurate prediction of irreversible biochemical reaction when compared to approximate result. The effectiveness of the proposed BLM-ANN model is measured using various metrics, such as state transition (ST), error-histograms (EH), mean square error (MSE), and regression analysis (R). These evaluation showed the value of the numerical solution provided by the BLM-ANN model for irreversible biological reactions. A comparison between the proposed BLM-ANN model and reference solution for the NIBR model demonstrated its effectiveness with observed convergence up to 10 −8 to 10 −3 .
Euregional Technology Award: An approach to inspire students for STEM
Authors: Breukelen Dave van , Smeets Maurice
Published: September 2024

The economy in the Meuse-Rhine Euroregion, encompassing parts of Belgium, Germany, and The Netherlands, strongly relies on scientific and industrial activities. However, the region faces a major shortage of employees, partly due to a low number of graduates in the fields of science, technology, engineering, and mathematics (STEM). This mixed-methods research studied the pedagogical design and impact of the Euregional Technology Award (EUTech Award). The EUTech Award is a technological design competition, based on inquiry- and design-based learning, aimed at promoting STEM among lower secondary school students. Utilizing pre- and post-testing, non-participatory observations, and focus groups, the study reveals a positive shift in students' STEM perceptions, making them more positive about STEM. Results show that emphasizing the social and creative aspects of STEM is crucial in fostering a positive mindset towards STEM, especially for student with an implicit STEM interest. It also highlights how divergent and creative thinking can enhance problem-solving skills. Furthermore, the study underscores the importance of design- and inquiry-based learning in STEM education, the need for a balance between different learning experiences, and the vital role of well-trained STEM teachers. Overall, this research unveils the potential of programs like the EUTech Award to positively influence STEM education.
Effect of moisture change on water retention behavior of unsaturated silty soil under loading- unloading conditions
Authors: Shah Syed Kamran Hussain , Malik Adnan Anwar , Haq Shay , Ahmad Waqar , Ali Umair , Chaudhry Rabia
Published: September 2024

Earthen embankments either natural or constructed artificially often comprise of unsaturated soils being considered stronger in terms of compressibility and permeability. However, the internal nomenclature of unsaturated soils due to the presence of air, water and soil particles makes it more complex while such soils interact with moisture under the circumstances of applied stress history during the earthen structure’s life span. To investigate this behavior this study is designed to understand the soil water interaction and quantify the retention behavior during loading and unloading conditions. To serve this idea custom designed static compaction tests were carried out under un-drained water and drained air condition at applied stress history. The results show sufficient impact on the soil water retention behavior with the application of loading unloading with varying soil water contents. During the initial stages of the loading process, suction increases with decreasing void ratio due to the heterogeneous distribution of water in the soil at the initial stage. Whereas there is a unique increasing trend in suction at the reloading or wetting phase of the water retention curve at all moisture contents. To examine the impact on void ratio the experimental data has been compared with the selected model incorporating suction, void ratio and degree of saturation for prediction of soil water retention behaviors. The model prediction deviates from the experimental data and shifts away from the model prediction indicating that loading-unloading sequence coupled with the variation in moisture does affect the soil behavior.
Detecting Human Activities In COMA Patients Using ML Algorithm
Authors: Singh Aditi , Singh Utkarsh , Pandey Vivek , Deotale Nilesh , Talekar Poorva
Published: September 2024

Health monitoring systems employing machine learning facilitate the collection and collaboration of data from comatose patients, leveraging sensors in hospitals via IoT technology. This data aids doctors in enhancing and managing the health of comatose patients during emergency situations. The hardware platform for this project integrates sensors and cameras capable of internet communication, enabling remote access for doctors via smartphones. This innovative approach empowers doctors to access and monitor patients' health statuses globally. Sensors gather vital medical data including heart rate, blood pressure, and other relevant parameters, which is then transmitted to a medical server via the internet. A series of cameras further monitor the patient, with data being securely stored for access by doctors and patient relatives through a dedicated application. In the event of sensor values exceeding predefined thresholds, urgent alarms are triggered, alerting both patients and medical staff. Continuous monitoring of patient health parameters ensures prompt intervention when necessary. Routine monitoring data sent to doctors via servers aids in diagnostics, facilitating precise treatment strategies. By harnessing IoT for data collection, patients benefit from enhanced medical care at reduced costs, promoting easier recovery. The project boasts an impressive execution rate of 99.7%, indicative of its efficacy and reliability in real-world applications.
Hybrid encryption for image security using improved Henon map with sine and cosine and Arnold’s transformation
Authors: Aslam Iqra Aslam Muhammad , rashid Tabasam Rashid , Murtaza Ghulam Murtaza
Published: September 2024

This paper introduces a novel 2D chaotic map, the Two-DimensionalImproved Henon Map with sine and cosine (2D − IHMSC), which enhances chaotic behavior and security for image encryption by incorporating sine and cosine functions into the classic Henon map. The 2D-IHMSC produces improved sequences with higher sensitivity to initial conditions. The proposed encryption algorithm combines cryptographic techniques, including chaotic sequences from the improved Henonmap, bitwise XOR, diffusion, and Arnold’s transformation, resulting in inefficient and robust image encryption. These enhancements increase randomness, strengthen diffusion and nonlinearity, and enhance resistance to attacks. The method utilizes Arnold’s Transformation for pixel scrambling, addressing periodicity limitations by implementing additional security measures. It encrypts the image as a pixel distribution, demonstrating exceptional performance in critical areas, including sensitivity, correlation, and security.
Voices of Parents of Children with Major Congenital Anomalies:
Themes from Initial Diagnosis, NICU Hospitalization, and Discharge Home
Authors: Acharya Krishna , Lyon Jessica , McAndrew Natalie , Geich Alexis , AbuZahra Tala , Leuthner Steven , Lagatta Joanne
Published: September 2024

Objective: To describe the parent experience of having an infant with a congenital anomaly from prenatal diagnosis. NICU, and post-NICU care
Study design: Qualitative study
Results: We interviewed 18 parents (13 mothers, 5 fathers) whose children were in our NICU to explore challenges in care and identify strategies to improve care. During the prenatal period, key challenges were inadequate initial support, having to decide about medical procedures, impact on mental health, and loss of a “normal” baby. In the NICU, challenges were lack of interdisciplinary communication, isolation, and knowing how to parent. After discharge home, challenges were hypervigilance, burden of caregiving, adjusting to life at home, and financial impact.
Conclusion: Parents of infants with anomalies experience significant stress and isolation after initial diagnosis and NICU care. Key interventions helpful to families were empathetic and consistent healthcare teams; consistent communication,engagement in NICU care, and ongoing support after discharge home.
Vulnerability and resilience of rainforests to plant invasions in a tropical island of the South Pacific: a sixteen-year survey
Authors: MEYER Jean-Yves , BARROSO Solène FABRE , MAZOYER Louise , JORDAN Méryl , FRAISSE Julie , FOURDRIGNIEZ Marie , TAPUTUARAI Ravahere , POUTEAU Robin
Published: September 2024

Island biodiversity is considered to be particularly vulnerable to biological invasions. However, the direct impacts of invasive alien plants on native and endemic flora are often difficult to assess. Indeed, invasion by woody species is a relatively slow process, and natural or anthropogenic disturbances that favor some plant invaders, also contribute to biodiversity loss, and might act as confounding factors. Hence, we conducted a long-term monitoring of rainforest composition and structure in the small tropical high volcanic island of Moorea (French Polynesia, South Pacific) over a 16-year (2006–2022) period without any major disturbance. All endemic, native and alien woody species with a stem ≥ 1 cm in diameter were identified and measured with a 4-year frequency in ten 20 m × 20 m plots. The variation of species richness, Shannon diversity, Pielou evenness and abundance over time was analyzed using linear mixed-effects models with identities of the plots as random factors. Results revealed an increase in the number of stems of alien plants (+ 50% in 16 years), especially the two most common invasive alien trees, Miconia calvescens (Melastomataceae) and Spathodea campanulata (Bignoniaceae). In contrast, we found a decrease in the richness (from 28 species to 19) and abundance (-20% of stems) of endemic and native species, especially in the higher-elevation plots. Three plots remained relatively stable in terms of plant invasions according to Shannon and Pielou indices, and some common native and endemic woody species persisted over time. Although a continuous decline of plant diversity, including species extirpation, was observed, our results also suggest a relative resilience of certain forest types and associated communities to plant invasions. Efforts to control invasive alien plants should therefore target the most vulnerable native habitats.
The inactivation of E. coli and B. subtilis spores treated individually, sequentially and simultaneously with humified air dielectric barrier discharge plasma and ultraviolet
Authors: Wang Zhishang , Liang Xinlei , Feng Dongxue , Wu Jiang , Dou Di , Wan Huihui , Liu Weifeng , Liu Dongping
Published: September 2024

The objective of this study was to evaluate the efficacy of humified air dielectric barrier discharge cold plasma (CP) and ultraviolet (UV) at a wavelength of 254 nm in inactivating Escherichia coli (E. coli) and Bacillus subtilis spores (B. subtilis spores). The experimental results showed that simultaneous treatment with CP and UV had the highest antimicrobial activity, followed by sequential and individual treatments. Individual treatment of CP and UV for 10 s decreased E. coli by 2.4 Logs and 1.3 Logs, respectively. After 60 s of CP and UV treatment, B. subtilis spores were decreased by 2.6 Logs and 1.1 Logs, respectively. Simultaneous treatment of CP and UV for 10 s reduced E. coli by 4.6 Logs and B. subtilis spores by 4.4 Logs after 60 s, which was attributed to their synergistic effects. To elucidate the mechanism of protein oxidation in simultaneous treatments, we investigated the chemical stability of simultaneous treatments with CP and UV on 11 amino acids and 4 nucleobases in aqueous solution. Phenylalanine (Phe), methionine (Met), tyrosine (Tyr), tryptophan (Trp), and histidine (His) were oxidized by plasma-generated reactive oxygen and nitrogen species (RONS). In addition, guanine (G) and thymine (T) exhibited structural instability; both the five- membered and six-membered rings of guanine can be oxidized, and thymine undergoes oxidative cross-linking by UV-induced formation of thymine dimers. The analysis showed that the chemical instability of amino acids and nucleobases was closely related to the synergistic inactivation effect of CP and UV.
Lower Child Opportunity Index is Associated with Lower Exercise Capacity Post-Fontan Palliation
Authors: Karolcik Brock A. , Wang Li , Ragavan Maya I. , Hoskoppal Arvind K. , Saraf Anita P. , Arora Gaurav , Kreutzer Jacqueline , Viegas Melita L. , Alsaied Tarek
Published: September 2024

Background
The Child Opportunity Index (COI) is a validated measurement that uses a composite index of 29 indicators of social determinants of health linked to the US Census. Patients post-Fontan palliation for single ventricle often have reduced exercise capacity compared to the general population. Our hypothesis is that COI levels are directly associated with exercise capacity and inversely with late outcomes.
Methods
A retrospective, single-center study was performed, including 99 patients post-Fontan procedure who had cardiac magnetic resonance imaging at our institution from January 2010 to July 2023, of which 78 had undergone an exercise test. Univariate analysis was performed with Pearson correlational testing and multivariable linear regression was then used to evaluate independent predictors of % predicted VO2.
Results
The mean age and sex were not different between the low and high COI groups (24.1 ± 8.5 y vs 22.5 ± 9.7 y; 34.5% vs 29.3% female). Patients with low COI had lower peak VO2 (25.7 vs 31.0 L/min/kg2, p = 0.002) and % predicted peak VO2 (61.9 vs 71.4%, p = 0.003). At follow up post-Fontan (mean of 17.9 ± 7.4 y) there was one mortality and two heart transplants. There were more interventions in the low COI group (1.5 vs 0.9 intervention occurrence/patient, p = 0.038). There was no difference in hospital admissions or significant comorbidities between COI groups.
Conclusion
Lower COI was associated with worse exercise capacity in Fontan patients and may negatively impact the need for late interventions. This highlights the need for efforts to provide community resources to promote equity in cardiac outcomes.
Caffeine and sclareol reduce the sedative effects of linalool, possibly through the GABA A interaction pathway: molecular insights through in vivo and in silico studies
Authors: Islam Muhammad Torequl , Hasan Md. Sakib Al , Ferdous Jannatul , Yana Noshin Tasnim , Mia Emon , Rakib Imam Hossen , Ansari Irfan Aamer , Ansari Siddique Akber , Islam Md. Amirul
Published: September 2024

Study background:
Linalool (LIN) has some important neuropharmacological activities, including anxiolytic and sedative effects. It is also clear that it protects experimental animals from convulsions and Alzheimer's disease. On the other hand, caffeine (CAF) and sclareol (SCL) have neurostimulatory potential.
Aim
To evaluate the sedative effect and possible molecular mechanisms of CAF with LIN and/or SCL through in vivo and in silico studies.
Methodology:
CAF (10 mg/kg) alone or with LIN (50 mg/kg) and/or SCL (10 mg/kg) were intraperitoneally (i.p.) treated before thirty minutes of pentobarbital sodium (TS) injection (40 mg/kg, i.p.) to the mice and observed for latency and duration of sleep up to 4 hours. To understand the possible action mechanisms of these drugs, we also performed molecular docking studies with GABAA receptor respective submits.
Results
Findings suggest that LIN exerted significant (p < 0.05) sedative effects on the animals. CAF and SCL alone or in their combinations significantly reduced LIN’s effects in mice. CAF, LIN, and SCL showed binding affinities of ‒5.7, ‒4.7, ‒7.4 kcal/mol with 6X3X of the GABAA receptor (α1 and β2 subunits), respectively.
Conclusion
LIN exerted significant sedative effects, while CAF and/or SCL reduced this effect in animals. We suppose these drugs may exert their sedative effects through the GABAA receptor intrecation pathway. Further studies are required to confirm these results.