Among the pathophysiological correlates of schizophrenia, recent research suggests a potential role for the Hedgehog (Hh) signalling pathway, which has been traditionally studied in embryonic development and oncology. Its dysregulation may impact brain homeostasis, neuroplasticity, and potential involvement in neural processes. This systematic review provides an overview of the involvement of Hh signalling in the pathophysiology of schizophrenia and antipsychotic responses. We searched the PubMed and Scopus databases to identify peer-reviewed scientific studies focusing on Hh and schizophrenia, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement, finally including eight studies, including three articles focused on patients with schizophrenia, two animal models of schizophrenia, two animal embryo studies, and one cellular differentiation study. The Hh pathway is crucial in the development of midbrain dopaminergic neurons, neuroplasticity mechanisms, regulating astrocyte phenotype and function, brain-derived neurotrophic factor expression, brain glutamatergic neural transmission, and responses to antipsychotics. Overall, results indicate an involvement of Hh in the pathophysiology of schizophrenia and antipsychotic responses, although an exiguity of studies characterises the literature. The heterogeneity between animal and human studies is another main limitation. Further research can lead to better comprehension and the development of novel personalised drug treatments and therapeutic interventions. Full article

Partitioning soil water balance (SWB) is an effective approach for deciphering the impacts of vegetation change on soil hydrological processes. Growing apple trees on the Loess Plateau, China, leads to a substantial deep soil water deficit, posing a serious threat to the sustainable development of apple production. However, the impact of deep-rooted apple trees on SWB remains poorly understood. In this study, we conducted a “Paired Plot” experiment to achieve this objective by decoupling SWB components using water stable isotopes, tritium, and soil water contents from deep soil cores (up to 25 m) under apple orchards with a stand age gradient of 8–23 years. The results showed that deep soil water storage under apple orchards was notably reduced compared to nearby farmland, showing a stand age-related pattern of deep soil water deficit (R² = 0.91). By analyzing the changing patterns of SWB components, we found that the main factor driving this deficit is the water uptake process controlled by the deep root system. This process is triggered by the increased transpiration demand of apple trees and short-term water scarcity. These findings have implications for understanding soil water dynamics, sustainable agroforestry management, and soil water resources’ protection in this region and other similar water-limited areas. Full article

Diabetes, especially type 2 diabetes (T2D), poses an unprecedented challenge to global public health. Hydration status also plays a fundamental role in human health, especially in people with T2D, which is often overlooked. This study aimed to explore the longitudinal associations between hydration status and the risk of T2D among the Chinese population. This study used data from the large community-based Kailuan cohort, which included adults who attended physical examinations from 2006 to 2007 and were followed until 2020. A total of 71,526 participants who eventually met the standards were divided into five hydration-status groups based on their levels of urine specific gravity (USG). Multivariable and time-dependent Cox proportional hazards models were employed to evaluate the associations of baseline and time-dependent hydration status with T2D incidence. Restricted cubic splines (RCS) analysis was used to examine the dose–response relationship between hydration status and the risk of T2D. Over a median 12.22-year follow-up time, 11,804 of the participants developed T2D. Compared with the optimal hydration-status group, participants with dehydration and severe dehydration had a significantly increased risk of diabetes, with adjusted hazard ratios (95% CI) of 1.30 (1.04–1.63) and 1.38 (1.10–1.74). Time-dependent analyses further confirmed the adverse effects of impending dehydration, dehydration, and severe dehydration on T2D incidence by 16%, 26%, and 33% compared with the reference group. Inadequate hydration is significantly associated with increased risks of T2D among Chinese adults. Our findings provided new epidemiological evidence and highlighted the potential role of adequate hydration status in the early prevention of T2D development. Full article

In this study, the optimization problem for controlling the pivot steering function of tracked vehicles is addressed. Firstly, kinematic modeling of the pivot steering process of tracked vehicles is conducted. Secondly, the control system of tracked vehicles is decoupled, and PID control algorithms for vehicle speed and yaw rate are separately designed. Furthermore, the parameters of the PID controllers are optimized using the Grey Wolf Optimizer algorithm. Finally, by constructing a joint simulation model using Matlab/Simulink + RecurDyn (V9R4), the simulation results indicate that the above control algorithm can effectively improve the tracking speed of tracked vehicles on vehicle speed and yaw rate under the pivot steering condition, quickly respond to the driver’s driving intention, and ensure the stability of the pivot steering process, providing an effective basis for further research on the pivot steering function of tracked vehicles. Full article

Composite metal foam (CMF) is a new class of material based on a mixture of metal matrix composites and metal foams. While the mechanical properties of CMF are well studied, its thermal properties, particularly at extreme temperatures, are yet to be evaluated and established. This study investigates the specific heat capacity of stainless-steel composite metal foam at temperatures up to 1200 °C while comparing data obtained using the laser flash method and a differential scanning calorimetry method (DSC). Moreover, it outlines a detailed procedure for investigating the surface emissivity of composite metal foam (CMF) as a function of the emissivity of separate components (spheres and matrix). It uses experimental and analytical procedures to show how emissivity is directly affected by surface roughness, temperature, sphere curvature and viewing angles. The CMF used in this study consists of 316L stainless steel matrix and stainless-steel hollow spheres with varying sphere sizes. Full article

From the start of river incision onward, the abandoned terrace surface is only reached by floods during peak discharges. Two main flood facies are distinguished: a relatively high-energetic, coarse-grained facies and a relatively low-energetic, fine-grained facies. In general, the flood deposits become gradually finer-grained and the finer-grained facies relatively more prominent when the river incises progressively deeper. This signifies a delayed and prolonged effect of channel incision and flood deposition compared with the climate changes that initiated the incision. However, these long-term trends may be interrupted by shorter-term events of flooding or non-deposition. Those short events are expressed by cycles of coarse-grained deposits from small/shallow flooding channels due to short peak discharges or fine-grained suspended sediment and incipient soils during periods of low flow. These short events may be attributed to short climatic episodes or intermittent intrinsic river evolution. Full article

The unique aroma and flavor of extra virgin olive oil (EVOO) are generally associated with its volatile composition, which includes a variety of components responsible for positive attributes as well as sensory defects which result from chemical oxidation processes and the action of exogenous enzymes. In this study, a robust analytical method, headspace solid-phase microextraction combined with gas chromatography–mass spectrometry (HS-SPME-GC/MS), was developed to tentatively identify volatile organic compounds (VOCs) as markers of positive and negative attributes, correlating them with relative percentages to estimate the risk of disqualification during the shelf life of EVOO. Significant differences (p < 0.05) were identified in the levels of VOCs over time, mainly those derived from the lipoxygenase (LOX) pathway. Principal component analysis (PCA) was applied to process the experimental data. The ratio of E-2-hexenal to acetic acid allowed for the prediction of the disqualification of monovarietal EVOO by the sensory panel. Full article

Recent advancements in 3D modeling have revolutionized various fields, including virtual reality, computer-aided diagnosis, and architectural design, emphasizing the importance of accurate quality assessment for 3D point clouds. As these models undergo operations such as simplification and compression, introducing distortions can significantly impact their visual quality. There is a growing need for reliable and efficient objective quality evaluation methods to address this challenge. In this context, this paper introduces a novel methodology to assess the quality of 3D point clouds using a deep learning-based no-reference (NR) method. First, it extracts geometric and perceptual attributes from distorted point clouds and represent them as a set of 1D vectors. Then, transfer learning is applied to obtain high-level features using a 1D convolutional neural network (1D CNN) adapted from 2D CNN models through weight conversion from ImageNet. Finally, quality scores are predicted through regression utilizing fully connected layers. The effectiveness of the proposed approach is evaluated across diverse datasets, including the Colored Point Cloud Quality Assessment Database (SJTU_PCQA), the Waterloo Point Cloud Assessment Database (WPC), and the Colored Point Cloud Quality Assessment Database featured at ICIP2020. The outcomes reveal superior performance compared to several competing methodologies, as evidenced by enhanced correlation with average opinion scores. Full article

Variant H3.3, along with H2A.Z, is notably enriched at promoter regions and is commonly associated with transcriptional activation. However, the specific molecular mechanisms through which H3.3 influences chromatin dynamics at transcription start sites, and its role in gene regulation, remain elusive. Using a combination of biochemistry and cryo-electron microscopy (cryo-EM), we show that the inclusion of H3.3 alone does not induce discernible changes in nucleosome DNA dynamics. Conversely, the presence of both H3.3 and H2A.Z enhances DNA’s flexibility similarly to H2A.Z alone. Interestingly, our findings suggest that the presence of H3.3 in the H2A.Z nucleosome provides slightly increased protection to DNA at internal sites within the nucleosome. These results imply that while H2A.Z at active promoters promotes the formation of more accessible nucleosomes with increased DNA accessibility to facilitate transcription, the simultaneous presence of H3.3 offers an additional mechanism to fine-tune nucleosome accessibility and the chromatin environment. Full article

This study analyzed the statement “diversification is a free lunch”. We empirically showed that diversification is only a free lunch under uncertainty or ignorance, confirming Warren Buffett’s “diversification is protection against ignorance”. Using historical returns of the S&P500 constituents illustrated that diversification not only decreased the risk but also the returns if the expected returns could be estimated. The findings of this study highlight that diversification reduces risk but that the risk reduction is not for free. Full article

In the process of hydraulic fracturing, fracturing fluid invades the formation and reacts with shale. Water-sensitive clay minerals swell when exposed to water. This results in a change in the mechanical properties of shale. However, the influences of a long-term water–shale reaction on mechanical properties are still unclear, and an optimization strategy of the shut-in time is required. In this paper, an optimization strategy for the shut-in time based on a shale long-term hydration experiment is proposed. In this paper, the water–shale reaction is simulated by laboratory experiments under normal temperature and pressure. The experiments are performed based on specimens from a shale outcrop. Clay and mineral composition, Young’s modulus, surface hardness, and tensile strength parameters are measured at 30-day intervals for 90 days. A CT scan was performed for 180 days. The experimental results show that the mass fraction of clay increased by 14.719%. In addition, significant argillaceous shedding occurs during the water–shale reaction period of 3–4 months. By testing the tensile strength, uniaxial compression decreases by 90.481% in three months. The Young’s modulus of mineral points decreases to 40% after reaction for three months. The shale has softened. The softening process is nonlinear and there are inflection points. The diffusion behavior of clay minerals and the expansion behavior of new fractures are observed by CT during 3–4 months of water–shale reaction. The results show that the shale softening and pore fracture structure changes are non-linear and heterogeneous, resulting in critical water–shale reaction time. According to the experimental results, the critical water–shale reaction time can be summarized. In this time, the fracture volume increases significantly, which is conducive to increasing oil and gas production. However, the fracture volume is not significantly increased by prolonging the shut-in time. The experimental results can guide the design of hydraulic fracturing shut-in time of shale reservoirs. Full article

Breast cancer is the most common cancer among women. Currently, it poses a significant threat to the healthcare system due to the emerging resistance and toxicity of available drug candidates in clinical practice, thus generating an urgent need for the development of new potent and safer anti-breast cancer drug candidates. Coumarin (chromone-2-one) is an elite ring system widely distributed among natural products and possesses a broad range of pharmacological properties. The unique distribution and pharmacological efficacy of coumarins attract natural product hunters, resulting in the identification of numerous natural coumarins from different natural sources in the last three decades, especially those with anti-breast cancer properties. Inspired by this, numerous synthetic derivatives based on coumarins have been developed by medicinal chemists all around the globe, showing promising anti-breast cancer efficacy. This review is primarily focused on the development of coumarin-inspired anti-breast cancer agents in the last three decades, especially highlighting design strategies, mechanistic insights, and their structure–activity relationship. Natural coumarins having anti-breast cancer efficacy are also briefly highlighted. This review will act as a guideline for researchers and medicinal chemists in designing optimum coumarin-based potent and safer anti-breast cancer agents. Full article

The recent millennium has witnessed a notable shift in consumer focus towards natural products for addressing lifestyle-related disorders, driven by their safety and cost-effectiveness. Nutraceuticals and functional foods play an imperative role by meeting nutritional needs and offering medicinal benefits. With increased scientific knowledge and awareness, the significance of a healthy lifestyle, including diet, in reducing disease risk is widely acknowledged, facilitating access to a diverse and safer diet for longevity. Plant-based foods rich in phytochemicals are increasingly popular and effectively utilized in disease management. Agricultural waste from plant-based foods is being recognized as a valuable source of nutraceuticals for dietary interventions. Citrus peels, known for their diverse flavonoids, are emerging as a promising health-promoting ingredient. Globally, citrus production yields approximately 15 million tons of by-products annually, highlighting the substantial potential for utilizing citrus waste in phyto-therapeutic and nutraceutical applications. Citrus peels are a rich source of flavonoids, with concentrations ranging from 2.5 to 5.5 g/100 g dry weight, depending on the citrus variety. The most abundant flavonoids in citrus peel include hesperidin and naringin, as well as essential oils rich in monoterpenes like limonene. The peel extracts exhibit high antioxidant capacity, with DPPH radical scavenging activities ranging from 70 to 90%, comparable to synthetic antioxidants like BHA and BHT. Additionally, the flavonoids present in citrus peel have been found to have antioxidant properties, which can help reduce oxidative stress by 30% and cardiovascular disease by 25%. Potent anti-inflammatory effects have also been demonstrated, reducing inflammatory markers such as IL-6 and TNF-α by up to 40% in cell culture studies. These findings highlight the potential of citrus peel as a valuable source of nutraceuticals in diet-based therapies. Full article

Numerous research studies have shown that moderate physical exercise exerts positive effects on gastrointestinal tract health and increases the variety and relative number of beneficial microorganisms in the intestinal microbiota. Increasingly, studies have shown that the gut microbiota is critical for energy metabolism, immunological response, oxidative stress, skeletal muscle metabolism, and the regulation of the neuroendocrine system, which are significant for the physiological function of exercise. Dietary modulation targeting the gut microbiota is an effective prescription for improving exercise performance and alleviating exercise fatigue. This article discusses the connection between exercise and the makeup of the gut microbiota, as well as the detrimental effects of excessive exercise on gut health. Herein, we elaborate on the possible mechanism of the gut microbiota in improving exercise performance, which involves enhancing skeletal muscle function, reducing oxidative stress, and regulating the neuroendocrine system. The effects of dietary nutrition strategies and probiotic supplementation on exercise from the perspective of the gut microbiota are also discussed in this paper. A deeper understanding of the potential mechanism by which the gut microbiota exerts positive effects on exercise and dietary nutrition recommendations targeting the gut microbiota is significant for improving exercise performance. However, further investigation is required to fully comprehend the intricate mechanisms at work. Full article

Dendrobium, a highly effective traditional Chinese medicinal herb, exhibits significant variations in efficacy and price among different varieties. Therefore, achieving an efficient classification of Dendrobium is crucial. However, most of the existing identification methods for Dendrobium make it difficult to simultaneously achieve both non-destructiveness and high efficiency, making it challenging to truly meet the needs of industrial production. In this study, we combined Laser-Induced Breakdown Spectroscopy (LIBS) with multivariate models to classify 10 varieties of Dendrobium. LIBS spectral data for each Dendrobium variety were collected from three circular medicinal blocks. During the data analysis phase, multivariate models to classify different Dendrobium varieties first preprocess the LIBS spectral data using Gaussian filtering and stacked correlation coefficient feature selection. Subsequently, the constructed fusion model is utilized for classification. The results demonstrate that the classification accuracy of 10 Dendrobium varieties reached 100%. Compared to Support Vector Machine (SVM), Random Forest (RF), and K-Nearest Neighbors (KNN), our method improved classification accuracy by 14%, 20%, and 20%, respectively. Additionally, it outperforms three models (SVM, RF, and KNN) with added Principal Component Analysis (PCA) by 10%, 10%, and 17%. This fully validates the excellent performance of our classification method. Finally, visualization analysis of the entire research process based on t-distributed Stochastic Neighbor Embedding (t-SNE) technology further enhances the interpretability of the model. This study, by combining LIBS and machine learning technologies, achieves efficient classification of Dendrobium, providing a feasible solution for the identification of Dendrobium and even traditional Chinese medicinal herbs. Full article

Vertical-axis wind turbines (VAWTs) are receiving more and more attention as they involve simple design, cope better with turbulence, and are insensitive to wind direction, which has a huge impact on their cost since a yaw mechanism is not needed. However, VAWTs still suffer from low conversion efficiency. As a result, tremendous efforts are being exerted to improve their efficiency, which mainly focus on two methods, regardless of whether the study is a CFD simulation, a field test, or a lab test experiment. An active approach involves modification of the rotor itself, such as the blade design, the angle, the trailing and leading edges, the inner blades, the chord thickness, the contra-rotating rotor, etc., while the second approach involves passive techniques where the flow is directed to optimally face the downwind rotor by mounting guiding vanes such as a diffuser or other shapes at the upwind position of the rotor. Among all the techniques undertaken, the counter-rotating wind turbine (CRWT) rotor technique seems to be the most effective, with an output comparable to that of horizontal-axis wind turbines (HAWTs), while the Savonius rotor has received more attention compared to other VAWT designs. Apart from technological issues, it has also been suggested that geographical issues, such as proper site siting of a wind turbine rotor at a particular location where a uniform flow can be guaranteed, are of paramount importance to ensure an effective conversion capacity of wind turbines. Thus, this study has successfully highlighted the latest improvements in augmentation methods and has established a solid foundation for future research aimed at improving the efficiency of VAWTs. Full article

An ARM Cortex simulation system for collaborative welding robots is presented in this paper. The components of the ARM Cortex SoC for embedded robot control, an OpenGL ES with image rendering, and a 3D geometry engine OpenCasCade for modeling are integrated for the purposes of simulating system self-controllability and cost effectiveness. This simulation of a collaborative welding robot achieved convenience while meeting the performance requirements; meanwhile, the auxiliary design was able to mark the trajectory of the robot’s end effector and reveal the collaborative robot’s inverse kinematic parameters, namely the position and Euler angle. An ARM Linux X11 Window environment that was set to create a 3D simulation rendering algorithm was built simultaneously. Then, the STEP model of the robot was loaded by using the OpenCasCade functionality. After that, the robot model and complex spline surface could be visualized by using the Qt QGLWidget. Finally, the correctness of the kinematic algorithm was verified by conducting simulations and analyzing the robot’s kinematics through the simulation results, which could verify the expected design and provide a set of fundamental samples for the robot trajectory industry regarding welding applications. Full article

Anemia is one of the most common chronic kidney disease (CKD) complications. It negatively affects patients’ quality of life and clinical outcomes. The pathophysiology of anemia in CKD involves the interplay of various factors such as erythropoietin (EPO) deficiency, iron dysregulation, chronic inflammation, bone marrow dysfunction, and nutritional deficiencies. Despite recent advances in understanding this condition, anemia still remains a serious clinical challenge in population of patients with CKD. Several guidelines have been published with the aim to systematize the diagnostic approach and treatment of anemia; however, due to emerging data, many recommendations vary between publications. Recent studies indicate a potential of novel biomarkers to evaluate anemia and related conditions such as iron deficiency, which is often present in CKD patients. Our article aims to summarize the pathophysiology of anemia in CKD, as well as the diagnosis and management of this condition, including novel therapeutic approaches such as hypoxia-inducible factor-prolyl hydroxylase inhibitors (HIF-PHI). Understanding these complex subjects is crucial for a targeted approach to diagnose and treat patients with anemia in CKD effectively. Full article

In this study, tomato seed (TS) samples were subjected to different roasting conditions (90–170 °C and 10–30 min) to compare their effects on the chemical composition and oxidative stability of tomato seed oil (TSO). Unroasted TS was considered as a control sample. Our results revealed that moderate roasting (130 °C/20 min) can significantly increase the content of linoleic acid (54.01–54.89%), linolenic acid (2.17–2.41%), phytosterols (2789.56–3037.31 mg/kg), squalene (5.06–13.10 mg/kg), total phenols (22.37–22.67 mg GAE/100 g), and other functional components (p < 0.05) in TSO, while the antioxidant activity (via DPPH, ABTS, and FRAP assays) also increased. In addition, the tocopherol content decreased significantly (758.53–729.50 mg/kg). Accelerated oxidation experiments showed that roasting (170 °C/30 min) increased the oxidative stability index (OSI) of TSO from 5.35 to 7.07 h (p < 0.05). Furthermore, roasting gradually increased the content of 5-hydroxymethylfurfural (HMF) (0–1.74 mg/kg), which indicates that the oxidative stability and the degree of the Maillard reaction increased upon roasting. Principal component analysis (PCA) and hierarchical cluster analysis (HCA) showed that moderate roasting (130 °C/20 min) improved the chemical composition, antioxidant activity, and oxidative stability of TSO. Furthermore, this work provides a useful theoretical basis for the processing and wide application of TSO in the pharmaceutical and food industries. Full article

This paper aims to enhance the existing Automatic Meter Reading (AMR) technologies for utilities in the public services sector, such as water, electricity, and gas, by allowing users to regularly upload images of their meters, which are then automatically processed by machines for digit recognition. We propose an end-to-end AMR approach designed explicitly for unconstrained environments, offering practical solutions to common failures encountered during the automatic recognition process, such as image blur, perspective distortion, partial reflection, poor lighting, missing digits, and intermediate digit states, to reduce the failure rate of automatic meter readings. The system’s first stage involves checking the quality of the user-uploaded images through the SVM method and requesting re-uploads for images unsuitable for digit extraction and recognition. The second stage employs deep learning models for digit localization and recognition, automatically detecting and correcting issues such as missing and intermediate digits to enhance the accuracy of automatic meter readings. Our research established a gas meter training dataset comprising 52,000 images, extensively annotated across various degrees, to train the deep learning models for high-precision digit recognition. Experimental results demonstrate that, with the simple SVM model, an accuracy of 87.03% is achieved for the classification of blurry image types. In addition, meter digit recognition (including intermediate digit states) can reach 97.6% (mAP), and the detection and correction of missing digits can be as high as 63.64%, showcasing the practical application value of the system developed in this study. Full article

This study examines mental health service providers who provided care to evacuees during the Israel–Hamas conflict. Utilizing a phenomenological qualitative method, the research delves into the psychological impact on the participants’ lived experiences. The sample included 25 mental health providers (13 female, age range 28–63, mean 42.4, SD 7.3; 15 psychologists and 10 social worker, average seniority 10.8 years, SD 5.2, range 2–18 years). Data were collected through semi-structured interviews conducted between December 2023 and March 2024. The data analysis revealed a dual narrative: Participants paid a major personal price and experienced secondary traumatization manifesting in emotional detachment, physical symptoms, and heightened arousal. They also derived a profound sense of meaning and fulfillment from their work, contributing to personal and professional growth. These findings underscore the complexity of their experiences, which were marked by the challenges of secondary trauma and the resilience fostered through their work. This study emphasizes the importance of support systems, including social and familial networks and professional supervision, in navigating these challenges. This study has several limitations, including small sample size and the use of virtual interviews, suggesting the need for further research with a broader participant base and in different contexts. Full article