bluuebunny/crossref_metadata_2025 huggingface dataset:
Real-World Effectiveness and Predictors of Nurse-Led Individual Cognitive Behavioral Therapy for Mental Disorders: An Updated Pragmatic Retrospective Cohort Study
Authors: Yoshinaga Naoki , Obara Yoko , Kawano Naohisa , Kondo Kazuki , Hayashi Yuta , Nakai Michikazu , Takeda Ryuichiro , Tanoue Hiroki
Published: July 2024

The importance of nurses integrating effective psychological techniques into their clinical practice is widely recognized. Nevertheless, further evidence from real-world settings is needed to establish nurse-led cognitive behavioural therapy (CBT) as an effective approach in clinical practice. This study aimed to examine the clinical effectiveness and predictors of individual CBT for mental disorders delivered by nurses in various routine clinical settings. This pragmatic retrospective cohort study collected data from participants who received nurse-led individual CBT at four institutions from different prefectures in Japan between April 2015 and March 2023. During the study period, 280 clients were referred to nurses for CBT, 240 of whom received nurse-led individual CBT of at least one session. The common primary diagnoses among participants were major depressive disorder (33.8%), social phobia (12.9%), and obsessive–compulsive disorder (10.0%). Of these, 23 participants were ongoing cases at the end of the observation period, and 217 who had completed the course of therapy or discontinued/dropped out from the therapy were included in the analysis (173 completed and 44 discontinued/dropped out (i.e., dropout rate = 20.3%)). Based on the clinical significance definition (primary outcome), 62.4% of the participants who completed the therapy were judged to demonstrate positive clinical significance (recovered or improved), with only a few participants (6.9%) demonstrating deterioration. Significant improvements were observed before and after nurse-led individual CBT across all secondary outcomes, including depression and anxiety symptoms, health-related quality of life, and functional disability (all ps ≤ 0.001). Univariate logistic regression revealed that clients with higher baseline severity of depression and anxiety symptoms were less likely to achieve positive clinical significance following nurse-led individual CBT. The real-world evidence gained through this study will encourage frontline nurses and motivate institutional/organizational leaders and policymakers to employ nurse-led individual CBT, especially for depression and anxiety-related disorders.
Cognitive Control/Flexibility, Social Isolation, and Intrinsic Job Satisfaction of Intensive Care Unit Nurses
Authors: Allahverdi Fatima Zehra , Bayer Nukhet
Published: July 2024

Although cognitive control and flexibility have been examined in the past, this study examines their relationship in a stressful working environment, focusing on intrinsic job satisfaction using cognitive behavioral theory as a framework. This study examined cognitive factors (cognitive control and cognitive flexibility) and emotional state (intrinsic job satisfaction) while assessing the mediating role of social isolation, an external work environment variable. The study focused on intrinsic job satisfaction with extrinsic job satisfaction as a covariate. A cross-sectional questionnaire method was used. Two hundred and ten nurses from twelve intensive care units participated. Model one examined cognitive control while model two examined cognitive flexibility, accounting for 32% and 38% of the variance in intrinsic job satisfaction, respectively. Model one accounted for 13% of the variance in social isolation through cognitive control and extrinsic job satisfaction while model two accounted for approximately 14.91% of the variance in social isolation through cognitive flexibility and extrinsic job satisfaction. Combining the two models accounted for 17% of the variance in social isolation and 37.4% of the variation in intrinsic job satisfaction. The results emphasize the importance of training nurses in cognitive control and flexibility to increase intrinsic job satisfaction.
Empirical Study on Real Estate Mass Appraisal Based on Dynamic Neural Networks
Authors: Chen Chao , Ma Xinsheng , Zhang Xiaojia
Published: July 2024

Real estate mass appraisal is increasingly gaining popularity as a critical issue, reflecting its growing importance and widespread adoption in economic spheres. And data-driven machine learning methods have made new contributions to enhancing the accuracy and intelligence level of mass appraisal. This study employs python web scraping technology to collect raw data on second-hand house transactions spanning from January 2015 to June 2023 in China. Through a series of data processing procedures, including feature indicator acquisition, the removal of irrelevant sample cases, feature indicator quantification, the handling of missing and outlier values, and normalization, a dataset suitable for direct use by mass appraisal models is constructed. A dynamic neural network model composed of three cascaded sub-models is designed, and the optimal parameter combination for model training is identified using grid searching. The appraisal results demonstrate the reliability of the dynamic neural network model proposed in this study, which is applicable to real estate mass appraisal. A comparison with the common methods indicates that the proposed model exhibits a superior performance in real estate mass appraisal.
Enriching Building Information Modeling Models through Information Delivery Specification
Authors: de Marco Giancarlo , Slongo Cinzia , Siegele Dietmar
Published: July 2024

The efficient acquisition and dissemination of information are crucial in building information modeling (BIM). Current BIM models face significant challenges, including inadequate modeling techniques, poorly defined information requirements, and low interoperability. These issues result in poor information quality and complicate the transition from information acquisition to model processing. Public authorities often provide documentation in various formats, requiring manual transfer to software, which is error-prone and burdensome. This process is particularly difficult for small and medium enterprises lacking resources and knowledge. To address these issues, the IDS (Information Delivery Specification) Collab Tool is under development. This tool aims to automate the import of requirements into authoring software, perform automated compliance checks, and enhance interoperability among stakeholders. It will assist designers in providing accurate information according to requirements through the IDS standard, improving model quality and efficiency from early design stages. Adapting BIM models to specific project requirements and aligning new IDS capabilities with traditional industry practices remain significant challenges. Preliminary evaluations indicate the tool’s potential to significantly improve workflow efficiency and compliance in BIM modeling. However, broader awareness and adoption of the IDS standard are needed. Further research and refinement are essential to fully realize the benefits of digital tools in revolutionizing design and construction practices.
Spontaneous Splenic Rupture Secondary to Infectious Mononucleosis
Authors: Kountouri Ismini , Vitkos Evangelos N. , Dimasis Periklis , Chandolias Miltiadis , Galani Manolakou Maria Martha , Gkiatas Nikolaos , Manolakaki Dimitra
Published: July 2024

Spontaneous splenic rupture (SSR) is a relatively rare but potentially lethal complication of infectious mononucleosis (IM). While SSR is extremely rare in patients with proven IM, it is the most lethal complication of the infection (9% mortality rate) and can present completely asymptomatically or with abdominal pain and hemodynamic instability. As adolescents and young adults are the most affected population group, with this case report, we intend to raise the vigilance of any doctor treating those patients in the emergency department. We present the case of a 16-year-old patient with an atraumatic splenic rupture and hemoperitoneum secondary to an Epstein–Barr virus (EBV) infection. The patient underwent an exploratory laparotomy, and a splenectomy was performed. This case demonstrates that, even if SSR in patients with IM is extremely rare, it should always be considered in a patient with a relevant clinical presentation.
Gestational Trophoblastic Disease: Complete versus Partial Hydatidiform Moles
Authors: Gonzalez Jeffrey , Popp Meagan , Ocejo Stephanie , Abreu Alvaro , Bahmad Hisham F. , Poppiti Robert
Published: July 2024

Hydatidiform moles, including both complete and partial moles, constitute a subset of gestational trophoblastic diseases characterized by abnormal fertilization resulting in villous hydrops and trophoblastic hyperplasia with or without embryonic development. This involves chromosomal abnormalities, where one or two sperms fertilize an empty oocyte (complete hydatidiform mole (CHM); mostly 46,XX) or two sperms fertilize one oocyte (partial hydatidiform mole (PHM); mostly 69,XXY). Notably, recurrent occurrences are associated with abnormal genomic imprinting of maternal effect genes such as NLRP7 (chromosome 19q13.4) and KHDC3L (chromosome 6q1). Ongoing efforts to enhance identification methods have led to the identification of growth-specific markers, including p57 (cyclin-dependent kinase inhibitor 1C; CDKN1C), which shows intact nuclear expression in the villous cytotrophoblast and villous stromal cells in PHMs and loss of expression in CHMs. Treatment of hydatidiform moles includes dilation and curettage for uterine evacuation of the molar pregnancy followed by surveillance of human chorionic gonadotropin (HCG) levels to confirm disease resolution and rule out the development of any gestational trophoblastic neoplasia. In this review, we provide a synopsis of the existing literature on hydatidiform moles, their diagnosis, histopathologic features, and management.
Control and Application of Tree Obstacle-Clearing Coaxial Octocopter with Flexible Suspension Saw
Authors: Liao Luwei , Yang Zhong , Zhuo Haoze , Xu Nuo , Wang Wei , Tao Kun , Liang Jiabing , Zhang Qiuyan
Published: July 2024

Aiming at the challenges of clearing tree obstacles along power transmission lines, the control and application of a novel Tree-Obstacle Clearing Coaxial Octocopter with Flexible Suspension Saw (TOCCO-FSS) have been investigated. Firstly, an overall scheme design and modeling of the TOCCO-FSS were conducted, and dynamic modeling of the TOCCO-FSS was performed using the Lagrange equation. Secondly, to address the interference encountered during the operation, a contact operation model was established to estimate the uncertainties and external disturbances during the contact operation process. Further, the Non-Singular Terminal Sliding-Mode Active Disturbance Rejection Control (NTSM-ADRC) method was researched based on the mathematical model of the TOCCO-FSS. Finally, the performance of the controller was verified through simulations and physical experiments. The results demonstrate that the design, control, and application of the entire TOCCO-FSS system are effective.
Modulated Radio Frequency Stealth Waveforms for Ultra-Wideband Radio Fuzes
Authors: Wu Kaiwei , Yang Bing , Hao Shijun , Liang Yanbin , Huang Zhonghua
Published: July 2024

The increasingly complex electromagnetic environment of modern warfare and the proliferation of intelligent jamming threaten to reduce the survival rate of radio fuzes on the battlefield. Radio frequency (RF) stealth technology can fundamentally improve the anti-interception and reconnaissance capabilities of radio fuzes, thereby lessening the probability of them being intercepted, recognized, and jammed by the enemy. In this paper, an RF stealth waveform based on chaotic pulse-position modulation is proposed for ultra-wideband (UWB) radio fuzes. Adding a perturbation signal based on the Tent map ensures that the chaotic sequences have sufficiently long periods despite hardware byte limitations. Measuring the approximate entropy and sequence period shows that the Tent map with the addition of perturbation signals can maintain good randomness under byte constraints, closely approximating the Tent map with ideal precision. Simulations verify that the proposed chaotic mapping used to modulate the pulse position of an ultra-wideband radio fuze signal results in superior detection, anti-interception, and anti-jamming performance.
Thompson Sampling for Stochastic Bandits with Noisy Contexts: An Information-Theoretic Regret Analysis
Authors: Jose Sharu Theresa , Moothedath Shana
Published: July 2024

We study stochastic linear contextual bandits (CB) where the agent observes a noisy version of the true context through a noise channel with unknown channel parameters. Our objective is to design an action policy that can “approximate” that of a Bayesian oracle that has access to the reward model and the noise channel parameter. We introduce a modified Thompson sampling algorithm and analyze its Bayesian cumulative regret with respect to the oracle action policy via information-theoretic tools. For Gaussian bandits with Gaussian context noise, our information-theoretic analysis shows that under certain conditions on the prior variance, the Bayesian cumulative regret scales as O˜(mT), where m is the dimension of the feature vector and T is the time horizon. We also consider the problem setting where the agent observes the true context with some delay after receiving the reward, and show that delayed true contexts lead to lower regret. Finally, we empirically demonstrate the performance of the proposed algorithms against baselines.
Multisite Long-Term Photovoltaic Forecasting Model Based on VACI
Authors: Feng Siling , Chen Ruitao , Huang Mengxing , Wu Yuanyuan , Liu Huizhou
Published: July 2024

In the field of photovoltaic (PV) power prediction, long-term forecasting, which is more challenging than short-term forecasting, can provide more comprehensive and forward-looking guidance. Currently, significant achievements have been made in the field of short-term forecasting for PV power, but inadequate attention has been paid to long-term forecasting. Additionally, multivariate global forecasting across multiple sites and the limited historical time series data available further increase the difficulty of prediction. To address these challenges, we propose a variable–adaptive channel-independent architecture (VACI) and design a deep tree-structured multi-scale gated component named DTM block for this architecture. Subsequently, we construct a specific forecasting model called DTMGNet. Unlike channel-independent modeling and channel-dependent modeling, the VACI integrates the advantages of both and emphasizes the diversity of training data and the model’s adaptability to different variables across channels. Finally, the effectiveness of the DTM block is empirically validated using the real-world solar energy benchmark dataset. And on this dataset, the multivariate long-term forecasting performance of DTMGNet achieved state-of-the-art (SOTA) levels, particularly making significant breakthroughs in the 720-step ultra-long forecasting window, where it reduced the MSE metric below 0.2 for the first time (from 0.215 to 0.199), representing a reduction of 7.44%.
Attentive Review Semantics-Aware Recommendation Model for Rating Prediction
Authors: Kim Jihyeon , Li Xinzhe , Jin Li , Li Qinglong , Kim Jaekyeong
Published: July 2024

Online reviews are crucial when building a recommendation model because they contain the specific and rich preferences of users related to different aspects of a particular item. Incorporating these online reviews into the recommendation model mitigates the data sparsity issue to some extent and contributes to better recommendation performance. Despite this success, review-based recommender systems have the limitation that they do not fully consider the relevance of the review text to the target item. Specifically, the review text should reflect the user’s detailed opinion about the target item to extract detailed preference information. Meanwhile, the review content must be directly related to the target item to extract the customer’s specific preferences for the item. However, previous studies have overlooked both of these aspects. Therefore, it is necessary to build a recommendation model that considers the relevance of the review content to the target item. To address this issue, this study proposes a novel recommendation model that accurately estimates users’ preferences by carefully considering the relevance of the review content to the items. The proposed model effectively extracts feature representations from the text using bidirectional encoder representations from a transformer and obtains fused features by considering the importance of features through the attention mechanism. To evaluate the performance of the model, we used a publicly accessible dataset of reviews from Amazon.com and compared it to various baseline models. The experimental results demonstrated better recommendation performance of the proposed model compared to other baseline models.
Transformer-Based Deep Learning Models for State of Charge and State of Health Estimation of Li-Ion Batteries: A Survey Study
Authors: Guirguis John , Ahmed Ryan
Published: July 2024

The global transportation system’s need for electrification is driving research efforts to overcome the drawbacks of battery electric vehicles (BEVs). The accurate and reliable estimation of the states of charge (SOC) and health (SOH) of Li-Ion batteries (LIBs) is crucial for the widespread adoption of BEVs. Transformers, cutting-edge deep learning (DL) models, are demonstrating promising capabilities in addressing various sequence-processing problems. This manuscript presents a thorough survey study of previous research papers that introduced modifications in the development of Transformer-based architectures for the SOC and SOH estimation of LIBs. This study also highlights approximately 15 different real-world datasets that have been utilized for training and testing these models. A comparison is made between the architectures, addressing each state using the root mean square error (RMSE) and mean absolute error (MAE) metrics.
Gas Free Dissipation Characteristics Analysis and Safety Repair Time Determination of Buried Pipeline Leakage Based on CFD
Authors: Bu Fanxi , He Yuheng , Liu Ming , Lv Zhuoran , Bai Jinyu , Leng Chunmiao , Wang Zhihua
Published: July 2024

Buried pipelines, as the most common method of natural gas transportation, are prone to pipeline leakage accidents and are difficult to detect due to their harsh and concealed environment. This paper focused on the problem regarding the free dissipation of residual gas in buried gas pipelines and soil after closing the gas supply end valve after a period of leakage by numerical simulation. A multiple non-linear regression model was established based on the least squares method and multiple regression theory, and MATLAB 2016b mathematical calculation software was used to solve the problem. The research results indicated that compared to the gas leakage diffusion stage, the pressure and velocity distribution during the free dissipation stage were significantly reduced. The increase in leakage time, pipeline pressure, leakage size, and pipeline burial depth led to a large accumulation of natural gas, which increased the concentration and distribution range of gas on the same free dissipation stage monitoring line. A prediction model for natural gas concentration in the free dissipation stage was established with an average error of 7.88%. A calculation model for the safety repair time of buried gas pipeline leakage accidents was further derived to determine the safety repair time of leakage accidents.
The Green Paradox in NEV Manufacturing: Regulatory Impacts on Innovation from a Stakeholder Perspective
Authors: Chen Qing , Li Chengjiang
Published: July 2024

This paper explores the paradoxical impact of environmental regulations on green innovation in the manufacturing of new energy vehicles (NEVs) from a stakeholder perspective. We address the dual challenge of accelerating green innovation across various diffusion stages and refining environmental regulations for effective stakeholder engagement, including the central government, upstream suppliers, and internal operations teams. First, we utilize Stackelberg game theory to analyze the strategic interaction and behavioral rationale between local governments and NEV manufacturers at different stages of innovation diffusion, represented by specific parameter sets. Second, we examine the roles of four key stakeholders, exploring their unique impact mechanisms and potential to influence the game’s Nash equilibrium. Finally, the game models’ validity and primary conclusions are corroborated with real-world case studies, prominently including the ongoing shift of Chinese automakers towards NEVs. Results demonstrate that: (1) environmental regulations should be calibrated according to the diffusion stages of green innovation, and (2) misaligned stakeholder interests can lead to environmental regulations that inadvertently hinder, rather than promote, NEV manufacturers’ green innovation efforts.
Probabilistic Path Planning for UAVs in Forest Fire Monitoring: Enhancing Patrol Efficiency through Risk Assessment
Authors: Wang Yuqin , Gao Fengsen , Li Minghui
Published: July 2024

Forest fire is a significant global natural disaster, and unmanned aerial vehicles (UAVs) have gained attention in wildfire prevention for their efficient and flexible monitoring capabilities. Proper UAV patrol path planning can enhance fire-monitoring accuracy and response speed. This paper proposes a probabilistic path planning (PPP) module that plans UAV patrol paths by combining real-time fire occurrence probabilities at different points. Initially, a forest fire risk logistic regression model is established to compute the fire probabilities at different patrol points. Subsequently, a patrol point filter is applied to remove points with low fire probabilities. Finally, combining fire probabilities with distances between patrol points, a dynamic programming (DP) algorithm is employed to generate an optimal UAV patrol route. Compared with conventional approaches, the experimental results demonstrate that the PPP module effectively improves the timeliness of fire monitoring and containment, and the introduction of DP, considering that the fire probabilities and the patrol point filter both contribute positively to the experimental outcomes. Different combinations of patrol point coordinates and their fire probabilities are further studied to summarize the applicability of this method, contributing to UAV applications in forest fire monitoring and prevention.
A Computational Analysis of Turbocharger Compressor Flow Field with a Focus on Impeller Stall
Authors: Banerjee Deb K. , Selamet Ahmet , Sriganesh Pranav
Published: July 2024

Understanding the flow instabilities encountered by the turbocharger compressor is an important step toward improving its overall design for performance and efficiency. While an experimental study using Particle Image Velocimetry was previously conducted to examine the flow field at the inlet of the turbocharger compressor, the present work complements that effort by analyzing the flow structures leading to stall instability within the same impeller. Experimentally validated three-dimensional computational fluid dynamics predictions are carried out at three discrete mass flow rates, including 77 g/s (stable, maximum flow condition), 57 g/s (near peak efficiency), and 30 g/s (with strong reverse flow from the impeller) at a fixed rotational speed of 80,000 rpm. Large stationary stall cells were observed deep within the impeller at 30 g/s, occupying a significant portion of the blade passage near the shroud between the suction surface of the main blades and the pressure surface of the splitter blades. These stall cells are mainly created when a substantial portion of the inlet core flow is unable to follow the impeller’s axial to radial bend against the adverse pressure gradient and becomes entrained by the reverse flow and the tip leakage flow, giving rise to a region of low-momentum fluid in its wake. This phenomenon was observed to a lesser extent at 57 g/s and was completely absent at 77 g/s. On the other hand, the inducer rotating stall was found to be most dominant at 57 g/s. The entrainment of the tip leakage flow by the core flow moving into the impeller, leading to the generation of an unstable, wavy shear layer at the inducer plane, was instrumental in the generation of rotating stall. The present analyses provide a detailed characterization of both stationary and rotating stall cells and demonstrate the physics behind their formation, as well as their effect on compressor efficiency. The study also characterizes the entropy generation within the impeller under different operating conditions. While at 77 g/s, the entropy generation is mostly concentrated near the shroud of the impeller with the core flow being almost isentropic, at 30 g/s, there is a significant increase in the area within the blade passage that shows elevated entropy production. The tip leakage flow, its interaction with the blades and the core forward flow, and the reverse flow within the impeller are found to be the major sources of irreversibilities.
The Assessment of Iodine Concentrations in Colostrum and Breast Milk Using ICP-MS: The Impact of Delivery Type, Thyroid Function and Gestational Diabetes—A Pilot Study
Authors: Kryczyk-Kozioł Jadwiga , Moniak Paulina , Zagrodzki Paweł , Lauterbach Ryszard , Huras Hubert , Staśkiewicz Magdalena , Krośniak Mirosław , Paśko Paweł , Podsiadły Robert , Dobrowolska-Iwanek Justyna
Published: July 2024

Considering the spectrum of benefits of breast milk feeding, determining the essential components of an infant’s only food-mother’s milk-seems justified, especially in the case of those whose deficiency (e.g., iodine) may result in developmental disorders. The main aim of this study was the determination of the total iodine content of breast milk (including colostrum and mature milk). A secondary objective was to assess the influence of factors such as the type of delivery, hypothyroidism, gestational diabetes or the stage of lactation on this parameter. The study materials were colostrum and milk after 1 (n = 14), 2 and 3 months (n = 8) of lactation with a range of iodine concentrations (µg/L): 195–1648 and 170–842, 174–650 and 273–751, respectively. Iodine was determined using the inductively coupled plasma mass spectrometry (ICP-MS). Multivariate statistical analysis revealed, e.g., that delivery by caesarean section or dose of L-thyroxine taken by women to normalise thyroid hormones, had a significant effect on iodine concentrations in breast milk. Further research aimed at assessing the quality of breast milk should also include determining the factors influencing it.
Risk Perception, Risk Preference, and Timing of Food Sales: New Insights into Farmers’ Negativity in China
Authors: Tian Tan , Zhao Xia
Published: July 2024

Chinese farmers, especially small ones, always sell their food at low prices during harvest season rather than storing it for a better price. Based on a theoretical framework of expected utility, this paper examines the mechanism by which risk perception affects farmers’ timing choices of food sales and the role played by risk preference, utilizing data from the 2019 China Family Database and the China Household Finance Survey of farmers in six provinces of the main wheat-producing regions. This study shows that farmers with a high risk perception are more likely to choose current sales compared with intertemporal sales. The channel and mechanism analysis finds that increased risk perception leads to risky returns from intertemporal sales lower than certain returns from current sales in utility comparisons. It is further found that risk preference has a substitution effect on risk perception in farmers’ intertemporal food sales.
Revitalising Riboflavin: Unveiling Its Timeless Significance in Human Physiology and Health
Authors: Aragão M. Ângela , Pires Lara , Santos-Buelga Celestino , Barros Lillian , Calhelha Ricardo C.
Published: July 2024

Since the early twentieth century, research on vitamins has revealed their therapeutic potential beyond their role as essential micronutrients. Riboflavin, known as vitamin B2, stands out for its unique characteristics. Despite numerous studies, riboflavin remains vital, with implications for human health. Abundantly present in various foods, riboflavin acts as a coenzyme in numerous enzymatic reactions crucial for human metabolism. Its role in energy production, erythrocyte synthesis, and vitamin metabolism underscores its importance in maintaining homeostasis. The impact of riboflavin extends to neurological function, skin health, and cardiovascular well-being, with adequate levels linked to reduced risks of various ailments. However, inadequate intake or physiological stress can lead to deficiency, a condition that poses serious health risks, including severe complications. This underscores the importance of maintaining sufficient levels of riboflavin for general wellness. The essential role of riboflavin in immune function further emphasises its significance for human health and vitality. This paper examines the diverse effects of riboflavin on health and stresses the importance of maintaining sufficient levels for overall well-being.
A Low-Computational Burden Closed-Form Approximated Expression for MSE Applicable for PTP with gfGn Environment
Authors: Avraham Yehonatan , Pinchas Monika
Published: July 2024

The Precision Time Protocol (PTP) plays a pivotal role in achieving precise frequency and time synchronization in computer networks. However, network delays and jitter in real systems introduce uncertainties that can compromise synchronization accuracy. Three clock skew estimators designed for the PTP scenario were obtained in our earlier work, complemented by closed-form approximations for the Mean Squared Error (MSE) under the generalized fractional Gaussian noise (gfGn) model, incorporating the Hurst exponent parameter (H) and the a parameter. These expressions offer crucial insights for network designers, aiding in the strategic selection and implementation of clock skew estimators. However, substantial computational resources are required to fit each expression to the gfGn model parameters (H and a) from the MSE perspective requirement. This paper introduces new closed-form estimates that approximate the MSE tailored to match gfGn scenarios that have a lower computational burden compared to the literature-known expressions and that are easily adaptable from the computational burden point of view to different pairs of H and a parameters. Thus, the system requires less substantial computational resources and might be more cost-effective.
When the Poisson Ratio of Polymer Networks and Gels Is Larger Than 0.5?
Authors: Tian Yuan , Wang Zilu , Dobrynin Andrey V.
Published: July 2024

We use coarse-grained molecular dynamics simulations to study deformation of networks and gels of linear and brush strands in both linear and nonlinear deformation regimes under constant pressure conditions. The simulations show that the Poisson ratio of networks and gels could exceed 0.5 in the nonlinear deformation regime. This behavior is due to the ability of the network and gel strands to sustain large reversible deformation, which, in combination with the finite strand extensibility results in strand alignment and monomer density, increases with increasing strand elongation. We developed a nonlinear network and gel deformation model which defines conditions for the Poisson ratio to exceed 0.5. The model predictions are in good agreement with the simulation results.
Experimental Investigation on the Effect of Sequences of Unsteady Flows on Bedload Sediment Transport
Authors: Askari Zahra , Mao Luca , Khodashenas Saeed Reza , Esmaili Kazem
Published: July 2024

Flash floods in ephemeral streams are rare, short and difficult to forecast and thus to monitor. During these events, bedload transport reaches very high rates and most sediment transport occurs within a limited number of hours during the course of a year. Because monitoring of bedload in ephemeral rivers is challenging, here we present the results of a series of flume experiments designed to simulate short, flashy floods. Since most flume experiments usually involve single events, here we add to existing evidence by testing the effects of sequences of multiple floods in rapid succession. The flume is 10 m long, 0.3 m wide and 0.5 m deep. Two bed sediment mixtures (well sorted and poorly sorted) with similar median grain size but a different standard deviation were used. Bedload was monitored continuously during each hydrograph, but no sediment was fed. The flume experiments used six triangular hydrographs with peak flows ranging from 0.0147 to 0.02 m3s−1 and durations ranging from 150 to 400 s. Results indicate that the sediment transport rate decreases progressively from the first to the third hydrograph, and that this pattern is consistent for all permutations of peak discharge and flood duration. In all of the runs, the sediment transport rate at a specified flow was higher during the rising limb than the falling limb of the hydrograph, indicating clockwise hysteresis. Furthermore, in the subsequent repetitions of the same hydrograph, the degree of hysteresis generally diminishes in magnitude from the first to the last repetition for all the experiments, irrespective of their magnitude and duration.
Valuing Outpatients’ Perspective on Primary Health Care Services in Greece: A Cross-Sectional Survey on Satisfaction and Personal-Centered Care
Authors: Karaferis Dimitris Charalambos , Niakas Dimitris A. , Balaska Dimitra , Flokou Angeliki
Published: July 2024

Introduction: The aims of the study were to identify and analyze the determinants associated with outpatient satisfaction in Greek primary care. This is because there is a general consensus that primary care is the linchpin of effective person-centered care delivery. Methods: A cross-sectional survey was conducted with 1012 patients’ exit interviews; sociodemographic variables were included in the questionnaire to obtain data on the satisfaction of primary care users with 20 public primary healthcare centers in Athens between June 2019 and April 2021. Statistical analysis was applied to 55 items and eight dimensions of patient satisfaction, namely, arrival and admission, waiting before the appointment, cleanliness of toilets, medical examination and behavior of physician, behavior of nursing staff, laboratories, departure, and contribution of the PHCs. Descriptive analyses and multiple linear regression were used to analyze the factors influencing patient satisfaction through coefficients (β) with 95% confidence intervals and associated tests of statistical significance. Results: Τwo-thirds (74.21%) of this survey’s participants ranged from 45 to 74 years of age. More than half of the participants were women (62.15%). The most common reasons for visits were pathological (26.48%), followed by cardiological conditions (9.78%), orthopedics (9.49%), gynecologic conditions (8.70%), and ophthalmologic problems (7.31%). In the center of satisfaction with primary care was the medical care and the behavior of the physician (β = 0.427; p < 0.01), followed by the time during appointment (β = 0.390; p < 0.01). Dimensions like “accessibility and availability, 2.19/5”; “waiting times, 2.89/5”; “infrastructure of facilities (2.04/5) and cleanliness of them, (2/5)”; “laboratories, 2.99/5” and “bureaucracy in the departure, 2.29/5” were crucial for the trust and satisfaction of patients. Overall satisfaction was rated at a moderate level (2.62 ± 0.18) while person-centered care was rated as weak (2.49 ± 0.28). Conclusions: Greece is recommended to increase the sensitivity of the use of the primary health care system by patients as a first contact, continuous, comprehensive, and effective patient- and family-focused care.
P38α MAPK Coordinates Mitochondrial Adaptation to Caloric Surplus in Skeletal Muscle
Authors: Waingerten-Kedem Liron , Aviram Sharon , Blau Achinoam , Hayek Tony , Bengal Eyal
Published: July 2024

Excessive calorie intake leads to mitochondrial overload and triggers metabolic inflexibility and insulin resistance. In this study, we examined how attenuated p38α activity affects glucose and fat metabolism in the skeletal muscles of mice on a high-fat diet (HFD). Mice exhibiting diminished p38α activity (referred to as p38αAF) gained more weight and displayed elevated serum insulin levels, as well as a compromised response in the insulin tolerance test, compared to the control mice. Additionally, their skeletal muscle tissue manifested impaired insulin signaling, leading to resistance in insulin-mediated glucose uptake. Examination of muscle metabolites in p38αAF mice revealed lower levels of glycolytic intermediates and decreased levels of acyl-carnitine metabolites, suggesting reduced glycolysis and β-oxidation compared to the controls. Additionally, muscles of p38αAF mice exhibited severe abnormalities in their mitochondria. Analysis of myotubes derived from p38αAF mice revealed reduced mitochondrial respiratory capacity relative to the myotubes of the control mice. Furthermore, these myotubes showed decreased expression of Acetyl CoA Carboxylase 2 (ACC2), leading to increased fatty acid oxidation and diminished inhibitory phosphorylation of pyruvate dehydrogenase (PDH), which resulted in elevated mitochondrial pyruvate oxidation. The expected consequence of reduced mitochondrial respiratory function and uncontrolled nutrient oxidation observed in p38αAF myotubes mitochondrial overload and metabolic inflexibility. This scenario explains the increased likelihood of insulin resistance development in the muscles of p38αAF mice compared to the control mice on a high-fat diet. In summary, within skeletal muscles, p38α assumes a crucial role in orchestrating the mitochondrial adaptation to caloric surplus by promoting mitochondrial biogenesis and regulating the selective oxidation of nutrients, thereby preventing mitochondrial overload, metabolic inflexibility, and insulin resistance.
Applications of Modified Mesenchymal Stem Cells as Targeted Systems against Tumor Cells
Authors: Garza Treviño Elsa N. , Quiroz Reyes Adriana G. , Delgado Gonzalez Paulina , Rojas Murillo Juan Antonio , Islas Jose Francisco , Alonso Santiago Saavedra , Gonzalez Villarreal Carlos A.
Published: July 2024

Combined gene and cell therapy are promising strategies for cancer treatment. Given the complexity of cancer, several approaches are actively studied to fight this disease. Using mesenchymal stem cells (MSCs) has demonstrated dual antitumor and protumor effects as they exert massive immune/regulatory effects on the tissue microenvironment. MSCs have been widely investigated to exploit their antitumor target delivery system. They can be genetically modified to overexpress genes and selectively or more efficiently eliminate tumor cells. Current approaches tend to produce more effective and safer therapies using MSCs or derivatives; however, the effect achieved by engineered MSCs in solid tumors is still limited and depends on several factors such as the cell source, transgene, and tumor target. This review describes the progress of gene and cell therapy focused on MSCs as a cornerstone against solid tumors, addressing the different MSC-engineering methods that have been approached over decades of research. Furthermore, we summarize the main objectives of engineered MSCs against the most common cancers and discuss the challenges, limitations, risks, and advantages of targeted treatments combined with conventional ones.
Comprehensive Analysis of a Six-Gene Signature Predicting Survival and Immune Infiltration of Liposarcoma Patients and Deciphering Its Therapeutic Significance
Authors: Han Jiayang , Zhao Binbin , Han Xu , Sun Tiantian , Yue Man , Hou Mengwen , Wu Jialin , Tu Mengjie , An Yang
Published: July 2024

Background: As a common soft tissue sarcoma, liposarcoma (LPS) is a heterogeneous malignant tumor derived from adipose tissue. Due to the high risk of metastasis and recurrence, the prognosis of LPS remains unfavorable. To improve clinical treatment, a robust risk prediction model is essential to evaluate the prognosis of LPS patients. Methods: By comprehensive analysis of data derived from GEO datasets, differentially expressed genes (DEGs) were obtained. Univariate and Lasso Cox regressions were subsequently employed to reveal distant recurrence-free survival (DRFS)-associated DEGs and develop a prognostic gene signature, which was assessed by Kaplan–Meier survival and ROC curve. GSEA and immune infiltration analyses were conducted to illuminate molecular mechanisms and immune correlations of this model in LPS progression. Furthermore, a correlation analysis was involved to decipher the therapeutic significance of this model for LPS. Results: A six-gene signature was developed to predict DRFS of LPS patients and showed higher precision performance in more aggressive LPS subtypes. Then, a nomogram was further established for clinical application based on this risk model. Via GSEA, the high-risk group was significantly enriched in cell cycle-related pathways. In the LPS microenvironment, neutrophils, memory B cells and resting mast cells exhibited significant differences in cell abundance between high-risk and low-risk patients. Moreover, this model was significantly correlated with therapeutic targets. Conclusion: A prognostic six-gene signature was developed and significantly associated with cell cycle pathways and therapeutic target genes, which could provide new insights into risk assessment of LPS progression and therapeutic strategies for LPS patients to improve their prognosis.
Insights into CLC-0’s Slow-Gating from Intracellular Proton Inhibition
Authors: Kwon Hwoi Chan , Fairclough Robert H. , Chen Tsung-Yu
Published: July 2024

The opening of the Torpedo CLC-0 chloride (Cl−) channel is known to be regulated by two gating mechanisms: fast gating and slow (common) gating. The structural basis underlying the fast-gating mechanism is better understood than that of the slow-gating mechanism, which is still largely a mystery. Our previous study on the intracellular proton (H+i)-induced inhibition of the CLC-0 anionic current led to the conclusion that the inhibition results from the slow-gate closure (also called inactivation). The conclusion was made based on substantial evidence such as a large temperature dependence of the H+i inhibition similar to that of the channel inactivation, a resistance to the H+i inhibition in the inactivation-suppressed C212S mutant, and a similar voltage dependence between the current recovery from the H+i inhibition and the recovery from the channel inactivation. In this work, we further examine the mechanism of the H+i inhibition of wild-type CLC-0 and several mutants. We observe that an anion efflux through the pore of CLC-0 accelerates the recovery from the H+i-induced inhibition, a process corresponding to the slow-gate opening. Furthermore, various inactivation-suppressed mutants exhibit different current recovery kinetics, suggesting the existence of multiple inactivated states (namely, slow-gate closed states). We speculate that protonation of the pore of CLC-0 increases the binding affinity of permeant anions in the pore, thereby generating a pore blockage of ion flow as the first step of inactivation. Subsequent complex protein conformational changes further transition the CLC-0 channel to deeper inactivated states.
Changes in the Expression of Genes Regulating the Response to Hypoxia, Inflammation, Cell Cycle, Apoptosis, and Epithelial Barrier Functioning during Colitis-Associated Colorectal Cancer Depend on Individual Hypoxia Tolerance
Authors: Dzhalilova Dzhuliia , Silina Maria , Tsvetkov Ivan , Kosyreva Anna , Zolotova Natalia , Gantsova Elena , Kirillov Vladimir , Fokichev Nikolay , Makarova Olga
Published: July 2024

One of the factors contributing to colorectal cancer (CRC) development is inflammation, which is mostly hypoxia-associated. This study aimed to characterize the morphological and molecular biological features of colon tumors in mice that were tolerant and susceptible to hypoxia based on colitis-associated CRC (CAC). Hypoxia tolerance was assessed through a gasping time evaluation in a decompression chamber. One month later, the animals were experimentally modeled for colitis-associated CRC by intraperitoneal azoxymethane administration and three dextran sulfate sodium consumption cycles. The incidence of tumor development in the distal colon in the susceptible to hypoxia mice was two times higher and all tumors (100%) were represented by adenocarcinomas, while in the tolerant mice, only 14% were adenocarcinomas and 86% were glandular intraepithelial neoplasia. The tumor area assessed on serially stepped sections was statistically significantly higher in the susceptible animals. The number of macrophages, CD3−CD19+, CD3+CD4+, and NK cells in tumors did not differ between animals; however, the number of CD3+CD8+ and vimentin+ cells was higher in the susceptible mice. Changes in the expression of genes regulating the response to hypoxia, inflammation, cell cycle, apoptosis, and epithelial barrier functioning in tumors and the peritumoral area depended on the initial mouse’s hypoxia tolerance, which should be taken into account for new CAC diagnostics and treatment approaches development.
Analysis of the Correlation between Persimmon Fruit-Sugar Components and Taste Traits from Germplasm Evaluation
Authors: Dong Yi , Liu Cuiyu , Gong Bangchu , Yang Xu , Wu Kaiyun , Yue Zhihui , Xu Yang
Published: July 2024

Persimmon fruits are brightly colored and nutritious and are fruits that contain large amounts of sugar, vitamins, mineral elements, and phenolic substances. The aim of this study was to explore the differences in fruit-sugar components of different persimmon germplasms and their relationships with phenotypic and flavor indices through the determination of phenotypes and sugar components and through electronic-tongue indices, which provided the basis and inspiration for the selection of different sugar-accumulating types of persimmon fruits and the selection of high-sugar persimmon varieties. Our results showed that persimmon germplasm fruit-sugar components were dominated by sucrose, glucose and fructose and that the remaining sugar components were more diverse but less distributed among the various germplasm types. Based on the proportion of each sugar component in the fruit, persimmon germplasms can be categorized into sucrose-accumulating and reduced-sugar-accumulation types. Sucrose-accumulating types are dominated by sucrose, galactose, fucose and inositol, while reduced-sugar-accumulation types are dominated by glucose, fructose, mannose-6-phosphate, and xylose. The content of sugar components in the germplasm persimmon of fruits of different types and maturity periods of also differed, with significant differences in sugar components between PCNA (pollination-constant non-astringent) and PCA (pollination-constant astringent) fruits. Cluster analysis classified 81 persimmon germplasms into three clusters, including cluster I-A, with low glucose and fructose content, and cluster I-B, with medium glucose, fructose, and sucrose contents. Cluster II was high in sucrose and fructose. Cluster III had high contents of glucose and fructose and low contents of sucrose and inositol.