Global warming has a significant impact on the dairy farming industry, as heat stress causes reproductive endocrine imbalances and leads to substantial economic losses, particularly in tropical–subtropical regions. The Holstein breed, which is widely used for dairy production, is highly susceptible to heat stress, resulting in a dramatic reduction in milk production during hot seasons. However, previous studies have shown that cells of cows produced from reconstructed embryos containing cytoplasm (o) from Taiwan yellow cattle (Y) have improved thermotolerance despite their nuclei (n) being derived from heat-sensitive Holstein cattle (H). Using spindle transfer (ST) technology, we successfully produced ST-Yo-Hn cattle and proved that the thermotolerance of their ear fibroblasts is similar to that of Y and significantly better than that of H (p < 0.05). Despite these findings, the genes and molecules responsible for the different sensitivities of cells derived from ST-Yo-Hn and H cattle have not been extensively investigated. In the present study, ear fibroblasts from ST-Yo-Hn and H cattle were isolated, and differentially expressed protein and gene profiles were compared with or without heat stress (hs) (42 °C for 12 h). The results revealed that the relative protein expression levels of pro-apoptotic factors, including Caspase-3, -8, and -9, in the ear fibroblasts from the ST-Yo-Hn-hs group were significantly lower (p < 0.05) than those from the H-hs group. Conversely, the relative expression levels of anti-apoptotic factors, including GNA14 protein and the CRELD2 and PRKCQ genes, were significantly higher (p < 0.05) in the ear fibroblasts from the ST-Yo-Hn-hs group compared to those from the H-hs group. Analysis of oxidative phosphorylation-related factors revealed that the relative expression levels of the GPX1 gene and Complex-I, Complex-IV, CAT, and PGLS proteins were significantly higher (p < 0.05) in the ear fibroblasts from the ST-Yo-Hn-hs group compared to those from the H-hs group. Taken together, these findings suggest that ear fibroblasts from ST-Yo-Hn cattle have superior thermotolerance compared to those from H cattle due to their lower expression of pro-apoptotic factors and higher expression of oxidative phosphorylation and antioxidant factors. Moreover, this improved thermotolerance is attributed, at least partially, to the cytoplasm derived from more heat-tolerant Y cattle. Hence, using ST technology to produce more heat-tolerant H cattle containing Y cytoplasm could be a feasible approach to alleviate the negative impacts of heat stress on dairy cattle in tropical–subtropical regions. Full article

Traditionally, angle measurements have been performed using a goniometer, but the complex motion of shoulder movement has made these measurements intricate. The angle of rotation of the shoulder is particularly difficult to measure from an upright position because of the complicated base and moving axes. In this study, we attempted to estimate the shoulder joint internal/external rotation angle using the combination of pose estimation artificial intelligence (AI) and a machine learning model. Videos of the right shoulder of 10 healthy volunteers (10 males, mean age 37.7 years, mean height 168.3 cm, mean weight 72.7 kg, mean BMI 25.6) were recorded and processed into 10,608 images. Parameters were created using the coordinates measured from the posture estimation AI, and these were used to train the machine learning model. The measured values from the smartphone’s angle device were used as the true values to create a machine learning model. When measuring the parameters at each angle, we compared the performance of the machine learning model using both linear regression and Light GBM. When the pose estimation AI was trained using linear regression, a correlation coefficient of 0.971 was achieved, with a mean absolute error (MAE) of 5.778. When trained with Light GBM, the correlation coefficient was 0.999 and the MAE was 0.945. This method enables the estimation of internal and external rotation angles from a direct-facing position. This approach is considered to be valuable for analyzing motor movements during sports and rehabilitation. Full article

Depression is a pervasive issue among college students worldwide, yet there is a significant gap in the literature regarding its prevalence and coping strategies in the Ukrainian context. The present study aims to fill this gap by investigating how substance use and health-promoting behaviors relate to depressive symptoms among Ukrainian college students. Health-promoting behaviors are an important strategy to prevent depression, whereas substance use can contribute to depression or make it harder to manage. Given the substantial psychosocial problems and stressors related to the ongoing war in Ukraine and the limited availability of mental health services for college students, it is important to understand how we can encourage college students to keep themselves mentally healthy. A cross-sectional study was conducted among college students on 10 campuses in 2018. Almost 16% of participants met a cut-off for depression. Female students and those who were older reported significantly higher depressive symptoms. Participants were more likely to report depressive symptoms if they were more often involved with alcohol and cannabis use, were older, and engaged in fewer health-promoting behaviors. Tobacco use was not significantly associated with depressive symptoms. Our findings suggest a moderate prevalence of depressive symptoms in our study population. We recommend implementing balanced public health interventions that address risk factors (such as substance use) while also promoting protective behaviors and can be tailored to the specific cultural and environmental context of the region. Full article

Considering the diversity of battery data under dynamic test conditions, the stability of battery working data is affected due to the diversity of charge and discharge rates, variability of operating temperature, and randomness of the current state of charge, and the data types are multi-sourced, which increases the difficulty of estimating battery SOH based on data-driven methods. In this paper, a lithium-ion battery state of health estimation method with sample transfer learning under dynamic test conditions is proposed. Through the Tradaboost.R2 method, the weight of the source domain sample data is adjusted to complete the update of the sample data distribution. At the same time, considering the division methods of the six auxiliary and the source domain data set, aging features from different state of charge ranges are selected. It is verified that while the aging feature dimension and the demand for target domain label data are reduced, the estimation accuracy of the lithium-ion battery state of health is not affected by the initial value of the state of charge. By considering the mean absolute error, mean square error and root mean square error, the estimated error results do not exceed 1.2% on the experiment battery data, which highlights the advantages of the proposed methods. Full article

Background/Objectives: There is currently no guidance on how to interpret the global degrees of activity (worsening) and repigmentation (improvement) in vitiligo. Stratification into global degrees can be completed for static evaluations (e.g., visible disease activity signs) and dynamic assessments (e.g., evolution over time). For the latter, the Vitiligo Disease Activity Score (VDAS_15&60) and Vitiligo Disease Improvement Score (VDIS_15&60) were recently validated. Methods: In the current study, a Physician Global Assessment (PGA) for disease activity (worsening) and repigmentation (improvement) was evaluated for validity (construct) and reliability (inter- and intrarater) based on a photo set of 66 patients. Subsequently, the PGA activity (worsening) and repigmentation (improvement) were used to stratify the Vitiligo Extent Score plus (VESplus), VDAS_15&60 or VDIS_15&60 into three global categories (slightly, moderately and much worse/improved), based on ROC analysis. Results: For the VESplus, cut-off values for the categories ‘slightly, moderately and much worse’ were >0.3%, >27.71% and >128.75% BSA (relative changes in the affected total BSA), respectively. For the categories ‘slightly, moderately and much improved’, they were >0%, >4.87% and >36.88% BSA (relative changes in the affected total BSA), respectively. The optimal cut-off values of the number of active (VDAS₁₅) body areas were >0 areas for slightly worse, >2 areas for moderately worse and >7 for much worse. For VDIS₁₅, the cut-off values for slightly improved and moderately improved were >0 and >1. For VDAS₆₀ and VDIS₆₀, the cut-off points were >0.5, >3, >9.5 and >0.5 and >1.5, respectively. The results should be interpreted with caution in patients with extensive vitiligo due to the rather limited disease extent of the included patient population (VESplus (median: 3.2%)). Conclusions: This research will aid in the development of more detailed international definitions. Full article

Sweet potato leaf curl virus (SPLCV) is a whitefly-transmitted begomovirus infecting sweetpotato and other morning glory (Convolvulaceae) species worldwide. The virus is widespread at the USDA, ARS, U.S. Vegetable Laboratory (USVL), and testing of germplasm maintained in the breeding program indicates nearly 100% infection in storage roots of materials propagated for at least four years. Prior to the public release of new germplasm, viruses must be eliminated via laborious and time-consuming meristem-tip culture. The identification of virus-free seedlings early in the selection process can offer an alternative to meristem-tip culture. In this study, we investigated the transmission of SPLCV over two years of consecutive field plantings (early and late) of sweetpotato. While SPLCV is endemic at the USVL, virus transmission pressure over the typical cultivation season is unknown, and avoidance of virus transmission paired with the selection and maintenance of clean material may be a viable alternative to virus elimination. In 2022, the storage roots of 39 first-year seedling (FYS) selections were tested for SPLCV after early-season cultivation, revealing a single selection (2.6%) with a positive test. Similar testing was conducted in 2023 with no SPLCV-positive FYS selections detected. To further assess SPLCV acquisition in the field, replicated late-season plantings of each selected FYS (n = 37) were monitored from planting to harvest. Testing was conducted at 60 and 120 days after planting (DAP). Approximately 35% of the bulk samples were infected at 60 DAP, and infection increased to 52.3% by 120 DAP. Testing of individuals within selected positive bulked samples did not support 100% infection at harvest. Altogether, these results demonstrate that SPLCV transmission during early planting is sufficiently low to facilitate the maintenance of virus-free selections, offering an alternative to virus cleaning and a cultivation strategy that may be leveraged for production. Full article

Buildings are responsible for around 30% and 42% of the consumed energy at the global and European levels, respectively. Accurate building power consumption estimation is crucial for resource saving. This research investigates the combination of graph convolutional networks (GCNs) and long short-term memory networks (LSTMs) to analyze power building consumption, thereby focusing on predictive modeling. Specifically, by structuring graphs based on Pearson’s correlation and Euclidean distance methods, GCNs are employed to discern intricate spatial dependencies, and LSTM is used for temporal dependencies. The proposed models are applied to data from a multistory, multizone educational building, and they are then compared with baseline machine learning, deep learning, and statistical models. The performance of all models is evaluated using metrics such as the mean absolute error (MAE), mean squared error (MSE), R-squared (R²), and the coefficient of variation of the root mean squared error (CV(RMSE)). Among the proposed computation models, one of the Euclidean-based models consistently achieved the lowest MAE and MSE values, thus indicating superior prediction accuracy. The suggested methods seem promising and highlight the effectiveness of GCNs in improving accuracy and reliability in predicting power consumption. The results could be useful in the planning of building energy policies by engineers, as well as in the evaluation of the energy management of structures. Full article

Electroencephalogram (EEG) has emerged as the most favorable source for recognizing brain disorders like epileptic seizure (ES) using deep learning (DL) methods. This study investigated the well-performed EEG-based ES detection method by decomposing EEG signals. Specifically, empirical mode decomposition (EMD) decomposes EEG signals into six intrinsic mode functions (IMFs). Three distinct features, namely, fluctuation index, variance, and ellipse area of the second order difference plot (SODP), were extracted from each of the IMFs. The feature values from all EEG channels were arranged in two composite feature forms: a 1D (i.e., unidimensional) form and a 2D image-like form. For ES recognition, the convolutional neural network (CNN), the most prominent DL model for 2D input, was considered for the 2D feature form, and a 1D version of CNN was employed for the 1D feature form. The experiment was conducted on a benchmark CHB-MIT dataset as well as a dataset prepared from the EEG signals of ES patients from Prince Hospital Khulna (PHK), Bangladesh. The 2D feature-based CNN model outperformed the other 1D feature-based models, showing an accuracy of 99.78% for CHB-MIT and 95.26% for PHK. Furthermore, the cross-dataset evaluations also showed favorable outcomes. Therefore, the proposed method with 2D composite feature form can be a promising ES detection method. Full article

Introduction: The self-medication hypothesis (SMH) suggests that individuals consume alcohol to alleviate stressful emotions. Still, the underlying mechanisms between stress and heavy episodic drinking remain to be explored. Impaired control over drinking (IC) reflects a failure of self-regulation specific to the drinking context, with individuals exceeding self-prescribed limits. Parenting styles experienced during childhood have a lasting influence on the stress response, which may contribute to IC. Method: We examined the indirect influences of parenting styles (e.g., permissive, authoritarian, and authoritative) on heavy episodic drinking and alcohol-related problems through the mediating mechanisms of stress and IC. We fit a latent measurement model with 938 (473 men; 465 women) university students, utilizing bootstrap confidence intervals, in Mplus 8.0. Results: Higher levels of authoritative parenting (mother and father) were indirectly linked to fewer alcohol-related problems and less heavy episodic drinking through less stress and IC. Maternal permissiveness was indirectly linked to more alcohol-related problems and heavy episodic drinking through more stress and, in turn, more IC. Impaired control appeared to be a mediator for stress and alcohol-related problems. Conclusions: Maternal permissiveness contributes to the use of alcohol to alleviate stress. Thus, reducing stress may reduce problematic heavy drinking and alcohol problems among emerging adults with high IC who may also have experienced permissive parenting. Stress may exacerbate behavioral dysregulation of drinking within self-prescribed limits. Full article

Inflammatory bowel disease (IBD) is a group of chronic disorders characterized by pain, ulceration, and the inflammation of the gastrointestinal tract (GIT) and categorized into two major subtypes: ulcerative colitis (UC) and Crohn’s disease. The inflammation in UC is typically restricted to the mucosal surface, beginning in the rectum and extending through the entire colon. UC patients typically show increased levels of pro-inflammatory cytokines, leading to intestinal epithelial apoptosis and mucosal inflammation, which impair barrier integrity. Chronic inflammation is associated with the rapid recruitment and inappropriate retention of leukocytes at the site of inflammation, further amplifying the inflammation. While UC can be managed using a number of treatments, these drugs are expensive and cause unwanted side effects. Therefore, a safe and effective treatment for UC patients is needed. Palmitoylethanolamide (PEA) is an endogenous fatty acid amide and an analog of the endocannabinoid anandamine. PEA administration has been found to normalize intestinal GIT motility and reduce injury in rodents and humans. In the current study, we examined the efficacy of PEA encapsulated in phytosomes following oral administration in experimental ulcerative colitis. Here, we showed that PEA at a human-equivalent dose of 123 mg/kg (OD or BID) attenuated DSS-induced experimental colitis as represented by the reduction in clinical signs of colitis, reduction in gross mucosal injury, and suppression of leukocyte recruitment at inflamed venules. These findings add to the growing body of data demonstrating the beneficial effects of PEA to control the acute phase of intestinal inflammation occurring during UC. Full article

In this work, we derived a new type model for spatial Hill’s system considering the created perturbation by the parameter effect of the continuation fractional potential. The new model is considered a reduced system from the restricted three-body problem under the same effect for describing Hill’s problem. We identified the associated Lagrangian and Hamiltonian functions of the new system, and used them to verify the existence of the new equations of motion. We also proved that the new model has different six valid solutions under different six symmetries transformations as well as the original solution, where the new model is an invariant under these transformations. The several symmetries of Hill’s model can extremely simplify the calculation and analysis of preparatory studies for the dynamical behavior of the system. Finally, we confirm that these symmetries also authorize us to explore the similarities and differences among many classes of paths that otherwise differ from the obtained trajectories by restricted three-body problem. Full article

GH4169 is one of the key materials used to manufacture high-temperature load-bearing parts for aero-engines, and the surface integrity of these parts in service conditions significantly affects their high-temperature fatigue performance. Under a coupling effect of high temperature and alternating load, the evolution process of the machined surface integrity index of superalloy GH4169 specimens was studied, and fatigue performance tests at 20 °C, 450 °C, and 650 °C were carried out to analyze the primary factors affecting the high-temperature fatigue performance of specimens. The results indicated that the surface roughness of specimens remained essentially unchanged. However, the value of surface residual stress decreased significantly, with a release of more than 60% at the highest temperature. At 650 °C, the surface microhardness increased, while the degree of surface plastic deformation decreased under alternating loads. Simultaneously, when the surface roughness was less than R_a 0.4 μm, surface microhardness was the main factor affecting the high-temperature fatigue performance of specimens. The influence of surface microhardness on low-cycle fatigue performance was not consistent with that on high-cycle fatigue performance. The latter increased monotonically, whereas the former initially increased and then decreased with increasing surface microhardness. Full article

The use of instrumental methods of analysis in the assessment of indices that record changes in symmetry in the structure of grains to evaluate the quality of durum and soft wheat grain is currently considered a search tool that will allow us to obtain previously unavailable data by finding correlations associated with differences in the shape and ratio of starch granules in conditionally symmetrical and asymmetrical wheat fruits (kernels) formed in different field conditions and with different genotypes. Indicators that had previously shown their effectiveness were used to analyze the obviously complex unique material obtained as a result of growing under critically unique sowing conditions in 2022, which affected the stability of grain development and filling. For the evaluation, a typical agronomic comparative experiment was chosen, which was used to evaluate the soil tillage practices (fallow, non-moldboard loosening, and plowing) and sowing dates (early and after excessive rainfalls), which made it possible to analyze a wider range of factors influencing the studied indices. The soil tillage methods were found to affect the uniformity of kernel fullness and their symmetry, and the sowing dates did not lead to significant differences. This study presents detailed changes in the shape of the middle cut of a wheat kernel, associated with assessing the efficiency of kernel filling and the symmetrical distribution of storage substances under the influence of external and internal physical factors that affect the formation of the wheat kernel. The data obtained may be of interest to breeders and developers of predictive phenotyping programs for cereal grain and seeds of other crops, as well as plant physiologists. Full article

Polyetheretherketone (PEEK), an organic thermoplastic polymer, has gained interest in dentistry due to its excellent mechanical strength, flexibility, and biocompatibility. Furthermore, the ability to utilize CAD/CAM in the fabrication of PEEK enhances accuracy, reliability, and efficiency while also saving time. Hence, several orthodontic studies have explored the utilization of PEEK in various applications, such as archwires, brackets, fixed lingual retainers, palatal expansion devices, transpalatal arches, Tübingen palatal plates, different types of space maintainers, mini-implant insertion guides, and more. However, a complete systematic review of the available data comparing the performance of PEEK with traditional orthodontic materials has not yet been conducted. Therefore, this systematic review seeks to assess if PEEK material meets the required mechanical criteria to serve as an alternative to conventional orthodontic appliances. To ensure clarity and precision, this review will specifically concentrate on fixed appliances. This systemic review followed the PRISMA guidelines and utilized databases including PubMed/MEDLINE, Embase, Springer, Web of Science, and Wiley. Searches were restricted to English language articles from January 2013 to February 2024. Keywords such as “Polyetheretherketone” or “PEEK” and “Orthodontic” or “Orthodontic device” or “Orthodontic materials” were employed across all databases. Nine studies were incorporated, covering orthodontic archwires, brackets, and fixed lingual retainers. Based on the reviewed literature, PEEK demonstrates promising potential in orthodontic fixed appliances, offering advantages in force delivery, friction reduction, and aesthetic appeal. Further research is needed to fully explore its capabilities and optimize its application in clinical practice. Full article

This research focuses on the key aspects of the basis of women’s entrepreneurship in the particular case of the Ukrainian ecosystem of entrepreneurship. Even in wartime, entrepreneurship is a chance to overcome circumstances, and it should be developed for women and men. A correlation regression analysis and simulation modeling were carried out in order to rank the priorities for the development of types of economic activity of small business entities managed by women, making it possible to substantiate the forecast of the development of women’s entrepreneurship in Ukraine for 2024–2026. The findings show the positive impact of the entrepreneurial ecosystem and the need to continue to strengthen policies that encourage and facilitate female entrepreneurship. This analysis provides three types of development scenarios for women’s entrepreneurship in Ukraine. Full article

This paper provides a computationally efficient and novel four-step methodological approach for predicting volatility estimators derived from bitcoin prices. In the first step, open, high, low, and close bitcoin prices are transformed into volatility estimators using Brownian motion assumptions and logarithmic transformations. The second step determines the optimal number of time-series lags required for converting the series into an autoregressive model. This selection process utilizes random forest regression, evaluating the importance of each lag using the Mean Decrease in Impurity (MDI) criterion and optimizing the number of lags considering an 85% cumulative importance threshold. The third step of the developed methodological approach fits the Elastic Net Regression (ENR) to the volatility estimator’s dataset, while the final fourth step assesses the predictive accuracy of ENR, compared to decision tree (DTR), random forest (RFR), and support vector regression (SVR). The results reveal that the ENR prevails in its predictive accuracy for open and close prices, as these prices may be linear and less susceptible to sudden, non-linear shifts typically seen during trading hours. On the other hand, SVR prevails for high and low prices as these prices often experience spikes and drops driven by transient news and intra-day market sentiments, forming complex patterns that do not align well with linear modelling. Full article

Measurement error is common in many statistical problems and has received considerable attention in various regression contexts. In this study, we consider the random coefficient autoregressive model with measurement error possibly present in covariates. The least squares and weighted least squares methods are used to estimate the model parameters, and the consistency and asymptotic normality of the two kinds of estimators are proved. Furthermore, we propose an empirical likelihood method based on weighted score equations to construct confidence regions for the parameters. The simulation results show that the weighted least squares estimators are superior to the least squares estimators and that the confidence regions have good finite-sample behavior. At last, the model is applied to a real data example. Full article

In digital product and ion scheduling centers, order–factory allocation, factory–mold allocation, and mold routing can be performed centrally and efficiently to maximize the utilization of manufacturing resources (molds). Therefore, in this paper, a manufacturing resource (molds)-sharing mechanism based on the Internet of Things (IoT) and a cyber-physical production system (CPPS) is designed to realize the coordinated allocation of molds and production scheduling. A mixed-integer mathematical model is developed to optimize the cost structure and obtain a reasonable profit solution. A heuristic algorithm based on evolutionary reversal is used to solve the problem. The numerical results show that based on the digital coordinated production scheduling method, distributed two-stage assembly manufacturing with shared molds can effectively reduce the order delay time and increase potential benefits for distributed production enterprises. Full article

Previous investigations have found a correlation between abnormal curvatures and a variety of patient complaints such as cervical pain and disability. However, no study has shown that loss of the cervical curve is a direct result of exposure to a motor vehicle collision (MVC). This investigation presents a retrospective consecutive case series of patients with both a pre-injury cervical lateral radiograph (CLR) and a post-injury CLR after exposure to an MVC. Computer analysis of digitized vertebral body corners on CLRs was performed to investigate the possible alterations in the geometric alignment of the sagittal cervical curve. Methods: Three spine clinic records were reviewed over a 2-year period, looking for patients where both an initial lateral cervical X-ray and an examination were performed prior to the patient being exposed to a MVC; afterwards, an additional exam and radiographic analysis were obtained. A total of 41 patients met the inclusion criteria. Examination records of pain intensity on numerical pain rating scores (NPRS) and neck disability index (NDI), if available, were analyzed. The CLRs were digitized and modeled in the sagittal plane using curve fitting and the least squares error approach. Radiographic variables included total cervical curve (ARA C2–C7), Chamberlain’s line to horizontal (skull flexion), horizontal translation of C2 relative to C7, segmental translations (retrolisthesis and anterolisthesis), and circular modelling radii. Results: There were 15 males and 26 females with an age range of 8–65 years. Most participants were drivers (28) involved in rear-end impacts (30). The pre-injury NPRS was 2.7 while the post injury was 5.0; p < 0.001. The NDI was available on 24/41 (58.5%) patients and increased after the MVC from 15.7% to 32.8%, p < 0.001. An altered cervical curvature was identified following exposure to MVC, characterized by an increase in the mean radius of curvature (265.5 vs. 555.5, p < 0.001) and an approximate 8° reduction of lordosis from C2–C7; p < 0.001. The mid-cervical spine (C3–C5) showed the greatest curve reduction with an averaged localized mild kyphosis at these levels. Four participants (10%) developed segmental translations that were just below the threshold of instability, segmental translations < 3.5 mm. Conclusions: The post-exposure MVC cervical curvature was characterized by an increase in radius of curvature, an approximate 8° reduction in C2–C7 lordosis, a mild kyphosis of the mid-cervical spine, and a slight increase in anterior translation of C2–C7 sagittal balance. The modelling result indicates that the post-MVC cervical sagittal alignment approximates a second-order buckling alignment, indicating a significant alteration in curve geometry. Future biomechanics experiments and clinical investigations are needed to confirm these findings. Full article

This study aims to explore additional fluids beneficial for coastal thermal energy converter (CTEC) operation. Ammonia’s thermodynamic properties, characterized by higher condensation temperatures and pressures, demand significantly elevated operating pressures, resulting in a substantial energy load for efficient operation. Thus, exploring alternatives such as R134a becomes crucial, particularly considering its potential as a better working fluid for power generation in a Rankine cycle. The research methodology involves employing computational fluid dynamics (CFD) simulations alongside experimental investigations to examine the performance of an axial turbine concept under different working fluids. The results obtained indicate that R134a is the most appropriate working fluid for an axial turbine within a CTEC, outperforming ammonia, thereby implying significantly better operational efficiency. Full article

To verify medication-related osteonecrosis of the jaw (MRONJ) frequency among patients with plasma cell myeloma (PCM) that had been treated with bisphosphonates, to identify predisposing factors that could influence the development of osteonecrosis. Methods: This observational retrospective study was performed at the Department of Hematology of Hospital Center of Porto (CHUP), Portugal. Results: The study population (n = 112) had a 15.2% (n = 17) prevalence of osteonecrosis. Clinically, bone exposure was the most frequently observed sign, present in 100% (n = 17) of the patients, followed by inflammation in 82.4% (n = 14), orofacial pain in 70.6% (n = 12), suppuration in 47.1% (n = 8), and intra or extra-oral fistula in 17.6% (n = 3) of the cases. The most frequent triggering local factor was dental extraction (82.4%). There was a dependence between the presence of extractions and the development of MRONJ (p < 0.001) but not with the time elapsed from the initiation of infusions with BPs and dental extractions (p = 0.499). In the sample of patients with multiple myeloma (MM), 13.8% were found to be more likely to develop MRONJ after an extraction. Conclusions: The most common local predisposing factor was dental extraction. No dependence was observed between the development of osteonecrosis and the time elapsed from the beginning of treatment with bisphosphonates infusions to surgical procedures. Full article

Sustainable energy systems (SESs) occupy a prominent position in the modern global energy landscape. The purpose of this study is to explore the application of fuzzy control and neural network control in photovoltaic systems to improve the power generation efficiency and stability of the system. By establishing the mathematical model of a photovoltaic system, the nonlinear and uncertain characteristics of photovoltaic system are considered. Fuzzy control and neural network control are used to control the system, and their performance is verified by experiments. The experimental results show that under the conditions of low light and moderate temperature, the fuzzy neural network control achieves a 3.33% improvement in power generation efficiency compared with the single control strategy. Meanwhile, the system can still maintain relatively stable operation under different environmental conditions under this comprehensive control. This shows that fuzzy neural network control has significant advantages in improving power generation efficiency and provides beneficial technical support and guidance for the commercial development of SESs. Full article