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Transition state calculation is a critical technique to understand and predict versatile dynamical phenomena in solids. However, the transition state results obtained at 0 K are often utilized for the prediction or interpretation of dynamical processes at high temperatures, and the error bars of such an approximation are largely unknown. In this benchmark study, all the major temperature effects, including lattice expansion, lattice vibration, electron excitation, and band-edge shift, are evaluated with first-principles calculations for defect diffusion in solids. With the inclusion of these temperature effects, the notable discrepancies between theoretical predictions at 0 K and the experimental diffusivities at high temperatures are dramatically reduced. In particular, we find that lattice expansion and lattice vibration are the dominant factors lowering the defect formation energies and hopping barriers at high temperatures, but the electron excitation exhibits minor effects. In sharp contrast to typical assumptions, the attempt frequency with lattice expansion and vibration varies significantly with materials: several THz for aluminum bulk but surprisingly over 500 THz for 4H-SiC. For defects in semiconductors, the band-edge shift is also significant at high temperatures and plays a vital role in defect diffusion. We expect that this study would help accurately predict the dynamical processes at high temperatures. [ABSTRACT FROM AUTHOR]

The successful large-scale fabrication of perovskite solar modules at the square meter level represents a significant milestone in the industrialization process of perovskite photovoltaic technology. In the fabrication of perovskite solar modules, cost-effective solution-based methods are commonly employed for the preparation of the perovskite layer due to their ability to ensure film uniformity with a thickness of approximately 500 nm. However, achieving uniformly coated charge transport layers (CTLs) at square meter levels using solution methods remains a formidable challenge due to the ultrathin nature of the CTLs, which is a few tens of nanometers thick. The fulfillment of this requirement necessitates the exclusive utilization of vacuum deposition technology for CTL preparation. This review focuses on vacuum deposition methods, including magnetron sputtering, atomic layer deposition, electron-beam evaporation, thermal evaporation, chemical vapor deposition and pulsed laser deposition for the fabrication of CTLs in perovskite solar cells and modules. We highlight the advantages and drawbacks of various deposition techniques, while summarizing the CTLs that can be deposited via each method, encompassing thin film characteristics and optimization strategies. Finally, we conclude with some perspectives and challenges for future research on vacuum methods for CTLs in perovskite solar cells. [ABSTRACT FROM AUTHOR]

Perovskite-based tandem solar cells (PTSCs) have made remarkable achievements in recent years, and the highest certified power conversion efficiency (PCE) of 33.9% has been achieved in perovskite/silicon tandem solar cells (PSTSCs), indicating their great commercialization potential. Nevertheless, the performance of PTSCs continues to be hindered by the compromised performance of wide-bandgap perovskite solar cells (WPSCs), particularly the high VOC deficit of WPSCs. Therefore, numerous strategies have been developed to minimize the VOC loss of WPSCs. Herein, we sort to comprehensively review about the reported studies on reducing the VOC deficit of WPSCs, focusing on interface modification, charge transport material (CTM) exploration, and additive engineering, with the aim of providing guidelines for increasing the VOC of WPSCs. Finally, we will provide a conclusive outlook on WPSCs, sharing our perspectives to inspire further advancements in both WPSCs and PTSCs. [ABSTRACT FROM AUTHOR]

Background: Numerous national and international nursing research studies have used the 13-item Chronic Illness Therapy Functional Assessment Chronic Illness Therapy (fatigue) (FACIT‐F) scale to measure the level of self-reported fatigue among the elderly population. Nonetheless, a culturally adapted Arabic version of the scale of the same quality was required to boost its use in Arabic-speaking nations. This study cross-culturally validated the Arabic version of the FACIT-F scale and tested its validity and reliability in an Arabic-speaking population. Materials and Methods: We conducted the study among an elderly Jordanian population using a methodological cross-sectional approach. Using a cluster random selection technique, we randomly selected 250 older adults from a larger pool. We evaluated the scale's validity, internal consistency, and acceptability. We analyzed the construct validity using both confirmatory and exploratory factor analysis. Results: The Arabic version of FACIT-F was proven to be acceptable for the one-factor model in the elderly Jordanian population. Cronbach's alpha coefficient for the Arabic FACIT-F was 0.95, which indicated good reliability. Evidence suggested that construct validity for the FACIT-F was generally quite acceptable. Conclusions: With regard to evaluating fatigue in an older Jordanian population, the Arabic translations of the FACIT-F have been shown to be reliable and valid. [ABSTRACT FROM AUTHOR]

Introduction: Anandamide (AEA) is an endocannabinoid that has recently been recognized as a regulator of various inflammatory diseases as well as cancer. While AEA was thought to predominantly engage cannabinoid (CB) receptors, recent findings suggest that, given its protective anti-inflammatory role in pathological conditions, anandamide may engage not only CB receptors. Methods: In this study, we studied the role of exogenous AEA in a mouse AirPouch model of acute inflammation by examining immune cell infiltrates by flow cytometry. Human primary immune cells were used to validate findings towards immune cell activation and migration by flow cytometry and bead-based ELISA. Results: We found that AEA decreases the acute infiltration of myeloid cells including granulocytes and monocytes into the inflamed area, but unexpectedly increases the number of T cells at the site of inflammation. This was related to AEA signaling through nuclear receptor subfamily 4A (NR4A) transcription factors rather than CB receptors. Exploring regulatory mechanisms in the human system, we found that AEA broadly inhibits the migratory capacity of immune cells, arguing for blocked emigration of T cells from the inflamed tissue. Taking a closer look at the impact of AEA on T cells revealed that AEA profoundly alters the activation and exhaustion status of CD4+ T and CD8+ T cells, thereby strongly inhibiting TH17 responses, while not altering TH1 differentiation. Discussion: These data suggest that AEA has the potential to block chronic inflammation without influencing crucial anti-viral and anti-microbial immune defense mechanisms, and may therefore be an attractive molecule to interfere with the establishment of chronic inflammation. [ABSTRACT FROM AUTHOR]

The relationship between mechanistic target of rapamycin complex 1 (mTORC1) activation after resistance exercise and acetylcholine receptor (AChR) subunit gene expression remains largely unknown. Therefore, we aimed to investigate the effect of electrical stimulation‐induced intense muscle contraction, which mimics acute resistance exercise, on the mRNA expression of AChR genes and the signalling pathways involved in neuromuscular junction (NMJ) maintenance, such as mTORC1 and muscle‐specific kinase (MuSK). The gastrocnemius muscle of male adult Sprague–Dawley rats was isometrically exercised. Upon completion of muscle contraction, the rats were euthanized in the early (after 0, 1, 3, 6 or 24 h) and late (after 48 or 72 h) recovery phases and the gastrocnemius muscles were removed. Non‐exercised control animals were euthanized in the basal state (control group). In the early recovery phase, Agrn gene expression increased whereas LRP4 decreased without any change in the protein and gene expression of AChR gene subunits. In the late recovery phase, Agrn, Musk, Chrnb1, Chrnd and Chrne gene expression were altered and agrin and MuSK protein expression increased. Moreover, mTORC1 and protein kinase B/Akt‐histone deacetylase 4 (HDAC) were activated in the early phase but not in the late recovery phase. Furthermore, rapamycin, an inhibitor of mTORC1, did not disturb changes in AChR subunit gene expression after muscle contraction. However, rapamycin addition slightly increased AChR gene expression, while insulin did not impact it in rat L6 myotube. These results suggest that changes in the AChR subunits after muscle contraction are independent of the rapamycin‐sensitive mTORC1 pathway. What is the central question of this study?Can muscle contraction‐induced activation of mechanistic target of rapamycin complex 1 (mTORC1) be linked to changes in acetylcholine receptor (AChR) gene expression and molecular signalling for maintaining neuromuscular junctions (NMJs)?What is the main finding and its importance?An acute high‐intensity muscle contraction dynamically changes AChR gene expression and muscle‐specific kinase (MuSK) signalling proteins at the late recovery phase of the contraction. Additionally, pharmacological inhibition of mTORC1 via rapamycin does not affect muscle contraction‐induced alterations in AChR genes. Our findings indicate that an acute high‐intensity muscle contraction induces changes in MuSK signalling and mTORC1‐independent changes in expression of AChR genes. [ABSTRACT FROM AUTHOR]

Background and Aims: Coronary heart disease (CHD), hypertension (HTN), depression (Dep), and Type 2 diabetes mellitus (T2DM) are often comorbid, resulting in an exacerbated patient condition and worsened prognosis. A lack of systematic metabolomic studies on comorbidities of CHD remains. Therefore, comprehensive metabolomic‐based evaluation of comorbidities of CHD is necessary. Methods and Results: In the current study, 169 healthy subjects, 149 CHD subjects, 107 CHD + HTN subjects, 126 CHD + Dep subjects, and 58 CHD + T2DM subjects were recruited. Gas chromatography–mass spectrometry was used for metabolite determination, and multivariate statistical analysis was conducted to identify metabolites that are differentially expressed with the comorbidities of CHD. There were 9, 16, 14, and 10 metabolites identified in the healthy and CHD group, the CHD and CHD + HTN group, the CHD and CHD + Dep group, and the CHD and CHD + T2DM group, respectively. Six metabolic pathways were affected, involving starch and sucrose metabolism; fructose and mannose metabolism; citrate cycle; alanine, aspartate, and glutamate metabolism; fatty acid biosynthesis; and glycolysis. Conclusion: Our study has systematically elucidated the metabolic changes underlying the comorbidities of CHD, thereby providing insight into the mechanisms associated with these alterations. [ABSTRACT FROM AUTHOR]

Cone snails of the genus Conus have evolved to produce structurally distinct and functionally diverse venom peptides for defensive and predatory purposes. This nature-devised delicacy enlightened drug discovery and for decades, the bioactive cone snail venom peptides, known as conotoxins, have been widely explored for their therapeutic potential, yet we know very little about them. With the augmentation of computational algorithms from the realms of bioinformatics and machine learning, in silico strategies have made substantial contributions to facilitate conotoxin studies although still with certain limitations. In this review, we made a bibliometric analysis of in silico conotoxin studies from 2004 to 2024 and then discussed in silico strategies to not only efficiently classify conotoxin superfamilies but also speed up drug discovery from conotoxins, reveal binding modes of known conotoxin–ion channel interactions at a microscopic level and relate the mechanisms of ion channel modulation to its underlying molecular structure. We summarized the current progress of studies in this field and gave an outlook on prospects. [ABSTRACT FROM AUTHOR]

Knowledge about potential risk factors for animal health is crucial to achieve animal welfare. The aim of this study was to provide practical guidance for farmers to improve the health status of their youngstock by identifying and eliminating risk factors for omphalitis in neonatal calves. A cross-sectional study including 3,445 dairy calves from 567 farms located in three structurally different regions of Germany was performed from December 2016 to July 2019. On each farm calves aged five to 21 days underwent clinical examinations with special consideration of the umbilicus for signs of inflammation. Information regarding animal health, hygiene, and management was obtained via interviews with the farmers. Rearing conditions were recorded following visual inspection using written standard operating procedures. Multifactorial statistical analyses were performed to identify potential risk factors for omphalitis on animal and farm level. The overall omphalitis prevalence in calves aged five to 21 days was 30.9%. Across all regions and farms, every fourth calf per farm exhibited signs of omphalitis (median farm prevalence: 25.0%, interquartile range: 0.0–50.0%). According to the farmers, however, only 4.5% of the calves had been treated for omphalitis in the preceding 12 months. Risk factors for omphalitis identified included the dampness of the lying area in the first 2 weeks of life, a body condition score of the dam after calving outside the optimal range, and the time that calves spent with their dam after birth. Calves on farms providing dry lying areas in the first 2 weeks of life had 0.77 times the risk of omphalitis compared to calves on farms with predominantly damp bedding. When the dams were judged under- or over-conditioned after calving, their offspring had a 1.4 times higher omphalitis risk, respectively, compared to calves from dams optimal conditioned. Calves from farms separating calf and dam beyond 12 h after birth were 0.75 times as likely to develop omphalitis than calves from farms performing immediate separation. These results highlight the complexity of multifactorial diseases such as umbilical infection. The evidence presented can help to establish guidelines for dairy farmers to improve the umbilical health of their calves. [ABSTRACT FROM AUTHOR]

In order to decouple structural parameters of silica aerogels like particle size, pore size and fractal dimension on the one hand from aerogel properties such as aerogel density, thermal and mechanical characteristics on the other hand, the structural properties were varied in a wide range. It has been a challenging task to find synthesis parameters still resulting in gels, but also covering a wide property space. For this goal, three synthesis routes, based on the classical tetraalkoxysilane route, were chosen. The structural properties of the silica aerogels produced cover more than two orders of magnitude in particle and pore sizes, whereas the variation of density and porosity is limited by the Si-content of the silica source. Due to physical limitations, not all combinations of pore size correlated to an aerogel density are possible, leading to a gap for small densities and small pores as well as for high densities and large pores. For increasing particle sizes, the structure generation mechanism seems to alter from particle generation and subsequent cluster formation to phase separation. Along with that, the mechanical stiffness drops down for larger structures (pores and particles). For the mechanical and thermal properties, only the solid thermal conductivity scales roughly with the Young's modulus, thus giving the opportunity of decoupling mechanical and thermal conductivity at ambient pressure from each other. [ABSTRACT FROM AUTHOR]

As the world continues to urbanize at an unprecedented rate, the energy demand in cities is rising. Buildings account for over 75% of all the energy consumed in cities and are responsible for over two-thirds of the emissions. Assessment of energy demand in buildings is a highly integrative endeavour, bringing together the interdisciplinary fields of energy and urban studies, along with a host of technical domains namely, geography, engineering, economics, sociology, and planning. In the last decade, several urban building energy modelling tools (UBEMs) have been developed for estimation as well as prediction of energy demand in cities. These models are useful in policymaking as they can evaluate future urban energy scenarios. However, data acquisition for generating the input database for UBEM has been a major challenge. In this review, a comprehensive assessment of the potential of remote sensing and GIS techniques for UBEM has been presented. Firstly, the most common input variables of UBEM have been identified by reviewing recent publications on UBEM and then studies related to the acquisition of data corresponding to these variables have been explored. More than 140 research papers and review articles relevant to remote sensing and GIS applications for building level data extraction in urban areas and UBEM applications have been investigated for this purpose. After going through level of details required for each of the input components of UBEM and studying the possibility of acquiring some of those data using remote sensing, it has been inferred that satellite remote sensing and Unmanned Aerial Vehicles (UAVs) have a strong potential in enhancing the input data space for UBEM but their applicability has been limited. Further, the challenges of the usage of these technologies and the possible solutions have also been presented in this study. It is recommended to utilise the existing methodologies of extracting information from remote sensing and GIS for UBEM, along with newer techniques such as machine learning and artificial intelligence. [ABSTRACT FROM AUTHOR]

Breast cancer incidence is on the rise regardless of several interventions available for its management. This scenario may be worse in resource-limited countries. This study, therefore, aimed to evaluate the knowledge and attitude of women towards Breast Cancer Screening (BCS) in Aminu Kano Teaching Hospital (AKTH), Kano State, a typically resource-limited state in Nigeria. This was a cross-sectional study. The study population comprised female individuals aged 18–45 years attending the Antenatal and Postnatal clinics of AKTH. An adopted questionnaire instrument was used to extract vital information on the knowledge and attitude of women towards breast cancer screening in the Antenatal and Postnatal clinics of AKTH. Our findings showed that there is much awareness about BCS, even though most participants' knowledge about the methods and timing of the scan is low. Much enlightenment is achieved through the availability of print and electronic media on BCS. A better attitude is shown when trained personnel conduct BCS. A good number of participants who have knowledge are yet to translate their knowledge and attitudes into practice. Based on our findings, coordinated and timely awareness campaigns should be organized by local health authorities to improve knowledge and attitude towards BCS. [ABSTRACT FROM AUTHOR]

There is no doubt that the proper development of the heart is important for its correct function, in addition, maturation processes of the heart are crucial as well. The actin-binding protein nexilin seems to take over central roles in the latter processes, as nexilin-deficient mice are phenotypically inconspicuous at birth but die within short time thereafter. Recently, it has been proposed that nexilin plays a role in the formation and function of transverse tubules (T-tubules), which are essential for excitation-contraction coupling in the hearts of mature animals. Although it has long been known that nexilin is subjected to alternative splicing, a molecular characterization of the respective isoforms is not yet available. Here, we describe novel nexilin splice variants and analyze their expression in tissues of mice and humans. Interestingly, nexilin isoforms segregate to myocyte- and epithelial-specific isoforms. Moreover, heart-specific isoforms of nexilin localize differently between atria and ventricles and are also expressed in the endothelial cells of blood vessels. Further, we narrowed down the critical exons in the actin-binding domains 1 and 2 (ABD1/2), and observed different self-interaction properties by recombinant protein interaction studies. Our results emphasize the diverse tissue and subcellular distribution of the individual nexilin isoforms and point to the importance of taking a closer look at the particular nexilin isoforms investigated. [ABSTRACT FROM AUTHOR]

Toxins from Conus snails are peptides characterized by a great structural and functional diversity. They have a high affinity for a wide range of membrane proteins such as ion channels, neurotransmitter transporters, and G protein-coupled receptors. Potassium ion channels are integral proteins of cell membranes that play vital roles in physiological processes in muscle and neuron cells, among others, and reports in the literature indicate that perturbation in their function (by mutations or ectopic expression) may result in the development and progression of different ailments in humans. This review aims to gather as much information as possible about Conus toxins (conotoxins) with an effect on potassium channels and/or currents, with a perspective of exploring the possibility of finding or developing a possible drug candidate from these toxins. The research indicates that, among the more than 900 species described for this genus, in only 14 species of the >100 studied to date have such toxins been found (classified according to the most specific evidence for each case), as follows: 17 toxins with activity on two groups of potassium channels (Kv and KCa), 4 toxins with activity on potassium currents, and 5 toxins that are thought to inhibit potassium channels by symptomatology and/or a high sequence similarity. [ABSTRACT FROM AUTHOR]

This paper presents an extensive review of techniques for plant feature extraction and segmentation, addressing the growing need for efficient plant phenotyping, which is increasingly recognized as a critical application for remote sensing in agriculture. As understanding and quantifying plant structures become essential for advancing precision agriculture and crop management, this survey explores a range of methodologies, both traditional and cutting-edge, for extracting features from plant images and point cloud data, as well as segmenting plant organs. The importance of accurate plant phenotyping in remote sensing is underscored, given its role in improving crop monitoring, yield prediction, and stress detection. The review highlights the challenges posed by complex plant morphologies and data noise, evaluating the performance of various techniques and emphasizing their strengths and limitations. The insights from this survey offer valuable guidance for researchers and practitioners in plant phenotyping, advancing the fields of plant science and agriculture. The experimental section focuses on three key tasks: 3D point cloud generation, 2D image-based feature extraction, and 3D shape classification, feature extraction, and segmentation. Comparative results are presented using collected plant data and several publicly available datasets, along with insightful observations and inspiring directions for future research. [ABSTRACT FROM AUTHOR]

Fruit size is crucial for growers as it influences consumer willingness to buy and the price of the fruit. Fruit size and growth along the seasons are two parameters that can lead to more precise orchard management favoring production sustainability. In this study, a Python-based computer vision system (CVS) for sizing apples directly on the tree was developed to ease fruit sizing tasks. The system is made of a consumer-grade depth camera and was tested at two distances among 17 timings throughout the season, in a Fuji apple orchard. The CVS exploited a specifically trained YOLOv5 detection algorithm, a circle detection algorithm, and a trigonometric approach based on depth information to size the fruits. Comparisons with standard-trained YOLOv5 models and with spherical objects were carried out. The algorithm showed good fruit detection and circle detection performance, with a sizing rate of 92%. Good correlations (r > 0.8) between estimated and actual fruit size were found. The sizing performance showed an overall mean error (mE) and RMSE of + 5.7 mm (9%) and 10 mm (15%). The best results of mE were always found at 1.0 m, compared to 1.5 m. Key factors for the presented methodology were: the fruit detectors customization; the HoughCircle parameters adaptability to object size, camera distance, and color; and the issue of field natural illumination. The study also highlighted the uncertainty of human operators in the reference data collection (5–6%) and the effect of random subsampling on the statistical analysis of fruit size estimation. Despite the high error values, the CVS shows potential for fruit sizing at the orchard scale. Future research will focus on improving and testing the CVS on a large scale, as well as investigating other image analysis methods and the ability to estimate fruit growth. [ABSTRACT FROM AUTHOR]

A hybrid Photovoltaic/Thermal(PV/T) approach is proposed in this study based on extensive research and a comparative analysis of several hyperparameter tuning methods. The models analyzed are Linear Regression (LR), Random Forest (RF), XGBoost Regression, AdaBoost Regression, Edge Regression, Support Vector Regression (SVR), elastic net, and lasso (L) models. Grid search optimisation approach was used to maximise all of the model's hyperparameters. A detailed analysis is presented as well as the strategies for tweaking the positive and negative hyperparameters. The suggested hybrid PV/T approach is evaluated in two ways. First, the cumulative yield of solar still was obtained. Second, support vector regression, followed by the hyperparameter tuning function was used to provide the maximum accuracy of the PV output. The findings show that RF and SVR achieved the uttermost precision both before and after the use of the hyperparameter tuning approach, with r2 scores of 0.9952, 0.9935, Root Mean Squared Error values of 0.2583 and 0.5087 while utilising grid search optimisation. [ABSTRACT FROM AUTHOR]

With the increasing proportion of renewable energy in China's energy structure, among which photovoltaic power generation is also developing rapidly. As the photovoltaic (PV) power output is highly unstable and subject to a variety of factors, it brings great challenges to the stable operation and dispatch of the power grid. Therefore, accurate short-term PV power prediction is of great significance to ensure the safe grid connection of PV energy. Currently, the short-term prediction of PV power has received extensive attention and research, but the accuracy and precision of the prediction have to be further improved. Therefore, this paper reviews the PV power prediction methods from five aspects: influencing factors, evaluation indexes, prediction status, difficulties and future trends. Then summarizes the current difficulties in prediction based on an in-depth analysis of the current research status of physical methods based on the classification of model features, statistical methods, artificial intelligence methods, and combined methods of prediction. Finally, the development trend of PV power generation prediction technology and possible future research directions are envisioned. [ABSTRACT FROM AUTHOR]

High-density lipoproteins (HDL) exist in various subclasses, with smaller HDL particles possessing the highest anti-oxidative and anti-inflammatory properties. Understanding the role of these specific subclasses in chronic kidney disease (CKD) could provide valuable insights into disease progression and potential therapeutic targets. In the present study, we assessed HDL subclass composition in 463 patients with CKD stage 2–4 using nuclear magnetic resonance spectroscopy. Over a mean follow-up period of 5.0 years, 18.6% of patients died. Compared to survivors, deceased patients exhibited significantly lower levels of cholesterol, ApoA-I, and ApoA-II within the small and extra-small (XS) HDL subclasses. Multivariable Cox regression analysis, adjusted for traditional cardiovascular and renal risk factors, demonstrated that reduced levels of XS-HDL-cholesterol, XS-HDL-ApoA-I, and XS-HDL-ApoA-II were independently associated with an increased risk of mortality. Furthermore, receiver operating characteristic analysis identified XS-HDL-ApoA-II as the most potent prognostic marker for mortality. In conclusion, reduced small and XS-HDL subclasses, especially XS-HDL-ApoA-II, are strongly associated with increased all-cause mortality risk in CKD patients. Assessment of HDL subclass distribution could provide valuable clinical information and help identify patients at high risk. [ABSTRACT FROM AUTHOR]

Background: Glioblastoma multiforme is an aggressive malignancy with a dismal 5-year survival rate of 5–10%. Current therapeutic options are limited, due in part to drug exclusion by the blood–brain barrier (BBB). We have previously shown that high-amplitude repetitive transcranial magnetic stimulation (rTMS) in rats allowed the delivery across the BBB of an IGF signaling inhibitor—IGF-Trap. The objective of this study was to assess the therapeutic effect of IGF-Trap when delivered in conjunction with rTMS on the intracerebral growth of glioma. Results: We found that systemic administration of IGF-Trap without rTMS had a minimal effect on the growth of orthotopically injected glioma cells in rats and mice, compared to control animals injected with vehicle only or treated with sham rTMS. In rats treated with a combination of rTMS and IGF-Trap, we observed a growth retardation of C6 tumors for up to 14 days post-tumor cell injection, although tumors eventually progressed. In mice, tumors were detectable in all control groups by 14–17 days post-injection of glioma GL261 cells and progressed rapidly thereafter. In mice treated with rTMS prior to IGF-Trap administration, tumor growth was inhibited or delayed, although the tumors also eventually progressed. Conclusion: The results showed that rTMS could increase the anti-tumor effect of IGF-Trap during the early phases of tumor growth. Further optimization of the rTMS protocol is required to improve survival outcomes. [ABSTRACT FROM AUTHOR]

Tapping line detection and rubber tapping pose estimation are challenging tasks in rubber plantation environments for rubber tapping robots. This study proposed a method for tapping line detection and rubber tapping pose estimation based on improved YOLOv8 and RGB-D information fusion. Firstly, YOLOv8n was improved by introducing the CFB module into the backbone, adding an output layer into the neck, fusing the EMA attention mechanism into the neck, and modifying the loss function as NWD to realize multi-object detection and segmentation. Secondly, the trunk skeleton line was extracted by combining level set and ellipse fitting. Then, the new tapping line was located by combining edge detection and geometric analysis. Finally, the rubber tapping pose was estimated based on the trunk skeleton line and the new tapping line. The detection results from 597 test images showed the improved YOLOv8n's detection mAP0.5, segmentation mAP0.5, and model size were 81.9%, 72.9%, and 6.06 MB, respectively. The improved YOLOv8n's effect and efficiency were superior compared to other networks, and it could better detect and segment natural rubber tree image targets in different scenes. The pose estimation results from 300 new tapping lines showed the average success rate and average time consumed for rubber tapping pose estimation were 96% and 0.2818 s, respectively. The positioning errors in x, y, and z directions were 0.69 ± 0.51 mm, 0.73 ± 0.4 mm, and 1.07 ± 0.56 mm, respectively. The error angles in a, o, and n directions were 1.65° ± 0.68°, 2.53° ± 0.88°, and 2.26° ± 0.89°, respectively. Therefore, this method offers an effective solution for rubber tapping pose estimation and provides theoretical support for the development of rubber tapping robots. [ABSTRACT FROM AUTHOR]

Environmental hypoxia, resulting from reduced oxygen supply, poses a significant risk of dysfunctioning and damaging the neurocognitive system, particularly in relation to anxiety and stress. Inadequate oxygenation can lead to acute and chronic brain damage. Scholars used behavioral, hemodynamic, and electromagnetic neurofunctional techniques to investigate the effects of normobaric and hypobaric hypoxia on neurocognitive systems. They found a correlation between hypoxia, altered psychomotor responses, and changes in EEG alpha, theta, beta, and gamma rhythms, which affect spatial attention and memory. Hypoxia affects event related potential (ERP) components differently depending on latency. Perceptual responses N1 and P2 remain largely unaffected, while the amplitudes of preattentive MMN, vMMN, and P3a are significantly altered. Late latency components related to attention, particularly P3b, are also altered. These changes illustrate the spectrum from sensory detection to more complex cognitive processing, highlighting the brain's efficiency in managing information. Interestingly, the amplitudes of P3b, ADAN and CNV can increase with increased cognitive demands in hypoxia. This suggests a compensatory response. Prolonged exposure exacerbates these effects, resulting in compensatory delayed behavioral responses and alterations in behavioral monitoring and conflict inhibitory control, as reflected by reduced amplitudes in some attention related ERP components, including N2, N2pc, and ERN. Thus, neurocognitive function and integrity are under stress. ERP sources and hemodynamic images reveal that vulnerable brain regions include the frontal prefrontal cortices, hippocampus, basal ganglia, and parietal and visual cortices, which are essential for attention related processes like decision making and spatial memory. The auditory system appears less affected. [ABSTRACT FROM AUTHOR]

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Malignant tumors are a category of diseases that possess invasive and metastatic capabilities, with global incidence and mortality rates remaining high. In recent years, the pivotal role of fibrosis in tumor progression, drug resistance, and immune evasion has increasingly been acknowledged. Fibrosis enhances the proliferation, migration, and invasion of tumor cells by modifying the composition and structure of the extracellular matrix, thereby offering protection for immune evasion by tumor cells. The activation of cancer-associated fibroblasts (CAFs) plays a significant role in this process, as they further exacerbate the malignant traits of tumors by secreting a variety of cytokines and growth factors. Anti-fibrotic tumor treatment strategies, including the use of anti-fibrotic drugs and inhibition of fibrosis-related signaling pathways such as Transforming Growth Factor-β (TGF-β), have demonstrated potential in delaying tumor progression and improving the effectiveness of chemotherapy, targeted therapy, and immunotherapy. In the future, by developing novel drugs that target the fibrotic microenvironment, new therapeutic options may be available for patients with various refractory tumors. [ABSTRACT FROM AUTHOR]

Introduction: Accurate and rapid identification of cabbage posture is crucial for minimizing damage to cabbage heads during mechanical harvesting. However, due to the structural complexity of cabbages, current methods encounter challenges in detecting and segmenting the heads and roots. Therefore, exploring efficient cabbage posture prediction methods is of great significance. Methods: This study introduces YOLOv5-POS, an innovative cabbage posture prediction approach. Building on the YOLOv5s backbone, this method enhances detection and segmentation capabilities for cabbage heads and roots by incorporating C-RepGFPN to replace the traditional Neck layer, optimizing feature extraction and upsampling strategies, and refining the C-Seg segmentation head. Additionally, a cabbage root growth prediction model based on Bézier curves is proposed, using the geometric moment method for key point identification and the anti-gravity stem-seeking principle to determine root-head junctions. It performs precision root growth curve fitting and prediction, effectively overcoming the challenge posed by the outer leaves completely enclosing the cabbage root stem. Results and discussion: YOLOv5-POS was tested on a multi-variety cabbage dataset, achieving an F1 score of 98.8% for head and root detection, with an instance segmentation accuracy of 93.5%. The posture recognition model demonstrated an average absolute error of 1.38° and an average relative error of 2.32%, while the root growth prediction model reached an accuracy of 98%. Cabbage posture recognition was completed within 28 milliseconds, enabling real-time harvesting. The enhanced model effectively addresses the challenges of cabbage segmentation and posture prediction, providing a highly accurate and efficient solution for automated harvesting, minimizing crop damage, and improving operational efficiency. [ABSTRACT FROM AUTHOR]

Venous thromboembolism presenting as deep vein thrombosis or pulmonary embolism (PE) remains to be an important cause of mortality and morbidity worldwide. Despite its significance and incidence, compared to many other cardiovascular conditions there are significant gaps in knowledge in many aspects of it, including its pathophysiology. A rare sequela of PE is chronic thromboembolic pulmonary hypertension (CTEPH). This complication has a poor outcome and data is scarce in this field. Many therapeutic approaches are based solely on clinical expertise, which can be explained by the complex and not fully understood pathobiology of this disease. Over the years, many theories have been proposed regarding its genesis. Although generally acute PE is accepted as a trigger for CTEPH, this condition is multifactorial and cannot be explained by recurring PEs only. By reviewing the current evidence, we have demonstrated that thrombus non-resolution in CTEPH is due to multiple mechanisms and predisposing factors including: inflammation, small-vessel disease, impaired angiogenesis, platelet dysfunction, coagulopathies, malignancy, impaired fibrinolysis, genetics and many other components. Based on the current evidence, we aimed to explain the pathophysiology CTEPH, PE and the connection between these two important diseases. Furthermore, we highlight the negative hemodynamic effects of CTEPH and PE on the right ventricle and its role in further exacerbation of these patients. [ABSTRACT FROM AUTHOR]

Cobalt-rich Co (1 - x) Ge x alloy thin films with various Ge concentrations (up to x = 0.09 ) have been investigated by vibrating sample magnetometry and ferromagnetic resonance techniques to understand the influence of Ge doping on magnetostatic and magnetodynamic properties. Room-temperature magnetization curves have shown that the addition of Ge atoms can reduce the saturation magnetization in a fast manner. Utilizing a conventional ferromagnetic resonance setup, the out-of-plane angular dependencies of the resonance spectra have been measured and data have been analyzed using a computer program to simulate the magnetic behavior of the thin-film alloys. The experimental findings demonstrate that the magnetic properties of Co (1 - x) Ge x alloys can be precisely adjusted by varying the Ge content. Both the g-factor and the Gilbert-damping parameter show correlated changes, highlighting the tunability of these magnetic characteristics. This ability to modify saturation magnetization and damping parameters by altering the Ge concentration enables the optimization and customization of the alloy for specific applications in spintronic devices. [ABSTRACT FROM AUTHOR]

Norepinephrine (NE) modulates synaptic transmission and long-term plasticity through distinct subtype adrenergic receptor (AR)-mediated-intracellular signaling cascades. However, the role of NE modulates glutamatergic long-term potentiation (LTP) in the hypothalamic paraventricular nucleus (PVN) magnocellular neuroendocrine cells (MNCs) is unclear. We here investigate the effect of NE on high frequency stimulation (HFS)-induced glutamatergic LTP in rat hypothalamic PVN MNCs in vitro, by whole-cell patch-clamp recording, biocytin staining and pharmacological methods. Delivery of HFS induced glutamatergic LTP with a decrease in N2/N1 ratio in the PVN MNCs, which was enhanced by application of NE (100 nM). HFS-induced LTP was abolished by the blockade of N-methyl-D-aspartate receptors (NMDAR) with D-APV, but it was rescued by the application of NE. NE failed to rescue HFS-induced LTP of MNCs in the presence of a selective β1-AR antagonist, CGP 20712. However, application of β1-AR agonist, dobutamine HCl rescued HFS-induced LTP of MNCs in the absence of NMDAR activity. In the absence of NMDAR activity, NE failed to rescue HFS-induced MNC LTP when protein kinase A (PKA) was inhibited by extracellular applying KT5720 or intracellular administration of PKI. These results indicate that NE activates β1-AR and triggers HFS to induce a novel glutamatergic LTP of hypothalamic PVN NMCs via the postsynaptic PKA signaling pathway in vitro in rats. [ABSTRACT FROM AUTHOR]

Fast and accurate large‐eddy simulation (LES) of the atmospheric boundary layer plays a crucial role in advancing wind energy research. Long‐duration wind farm studies at turbine‐resolving scales have become increasingly important to understand the intricate interactions between large wind farms and the atmospheric boundary layer. However, the prohibitive computational cost of these turbulence‐ and turbine‐resolving simulations has precluded such modeling to be exercised on a regular basis. To that end, we implement and validate the generalized actuator disk (GAD) model in the computationally efficient, graphics processing unit (GPU)–resident, LES model FastEddy. We perform single‐turbine simulations under three atmospheric stabilities (neutral, unstable, and stable) and compare them against observations from the Scaled Wind Farm Technology (SWiFT) facility and other LES codes from the recent Wakebench turbine wake model benchmark. Our idealized LES results agree well with observed wake velocity deficit and downstream recovery across stability regimes. Turbine response in terms of rotational speed, generated power, torque, and thrust coefficient are well predicted across stability regimes and are consistent with the LES results from the benchmark. The FastEddy simulations are found to be at least two orders of magnitude more efficient than the traditional CPU‐based LES models, opening the door for realistic LES simulations of full wind plants as a viable standard practice. [ABSTRACT FROM AUTHOR]

Optimal upper extremity motor control and range of motion are necessary to achieve even the basic activities of daily living (ADL) function. Stroke, with resulting hemiparesis, can significantly and negatively impact an individual's ADL function. Functional Independence Measure (FIM) self-care score can provide an assessment of what aspects and to what degree ADL functions are impaired. FIM self-care assessment can also track changes in ADL function during stroke recovery and rehabilitation. Recently, the sensor-acquired 3D motion analysis of stroke patients' upper extremity has shown promise as a potential alternative to assess ADL function. This observational study evaluates whether the sensor-acquired upper extremity reachable workspace (RWS) measure correlates with clinician-evaluated FIM self-care score in stroke patients. Seventeen patients with stroke were enrolled in the study. FIM self-care, NeuroQoL upper extremity, and reachable workspace outcome measures (relative surface area, RSA) were collected upon rehabilitation hospital admission, at discharge, and at the 3-month visit. Pearson and Spearman's rank correlation coefficients as well as multiple linear regression analyses were used to determine the relationships between FIM self-care, NeuroQoL, and reachable workspace RSAs. Moderately strong correlation between total reachable workspace RSA and total FIM self-care score at discharge and at 3 months were noted (r = 0.619, r = 0.661, p < 0.05), and similarly strong correlation was also noted with the upper extremity NeuroQoL total score (r = 0.690, r = 0.815, p < 0.05). Multiple linear regression analyses revealed a change in average bilateral total RSA of 0.1 unit from admission to the 3-month follow-up correlated with a respective change in the FIM self-care score of 2.011 points (95%CI: 0.663–3.360). Longitudinal improvement in ADL function during stroke rehabilitation and recovery process is correlated with improvement in reachable workspace. [ABSTRACT FROM AUTHOR]

Meningoencephalitis of unknown origin (MUO) represents an umbrella term for inflammatory, non-infectious central nervous system (CNS) diseases in dogs. Current therapeutic approaches, involving long-term glucocorticosteroid use, often fail to provide adequate relief or cure, and the effectiveness of additional immunosuppressive medications remains uncertain. Future advancements in MUO treatment may benefit from patient-specific therapies, potentially enhancing treatment precision, efficacy, and minimizing side effects. However, significant challenges impede this progress, including ambiguity in MUO subtype classification, uncertainties regarding the autoimmune nature vs. infectious triggers, and the lack of reliable diagnostic biomarkers. Clinical heterogeneity and overlapping signs with other encephalopathies further complicate diagnosis and treatment. This review gives an overview about diagnostic findings and immunological features of MUO. It advocates for a more overall characterization of MUO by using a polythetic system to better characterize MUO subtypes, identify immunological treatment targets, and establish a conceptual foundation for future therapeutic trials. Addressing these themes may lead to more effective and less burdensome treatments, improving the quality of life for dogs afflicted with MUO and their owners. [ABSTRACT FROM AUTHOR]