Blended electrodes are becoming increasingly more popular in lithium-ion batteries, yet most modeling approaches are still lacking the ability to separate the blend components. This is problematic because the different components are unlikely to degrade at the same pace. This work investigated a new approach towards the simulation of blended electrodes by replicating the complex current distributions within the electrodes using a paralleling model rather than the traditional constant-current method. In addition, a blending model was used to generate three publicly available datasets with more than 260,000 unique degradations for three exemplary blended cells. These datasets allowed us to showcase the necessity of considering all active components of the blend separately for diagnosis and prognosis. Full article

We developed and tested MivacunaLA/MyshotLA, a community-informed mobile phone intervention, to increase COVID-19 vaccination among Latino parents/caretakers of minors in under-resourced areas of Los Angeles by addressing misinformation and building trust. We recruited Latino parents/caregivers with at least one unvaccinated child in East and South Los Angeles in the summer of 2021 and evaluated MivacunaLA as a randomized controlled trial with a wait-list control group. A difference-in-difference analysis showed Latino parents/caregivers that participated in MivacunaLA (n = 246), in comparison to the control group, were 15 percentage points more likely (p = 0.04) to report vaccination of minors aged 12–17 years, and 12 percentage points more likely (p = 0.03) to report a positive intention to vaccinate minors aged 2–11 years (when COVID-19 vaccines became available). Mobile phone-delivered digital interventions using videos and culturally tailored educational material to promote COVID-19 vaccine confidence can be an effective way to combat misinformation and deliver timely information to marginalized communities. Community-based participatory research approaches are crucial to advance health equity among minority communities, especially immigrant Spanish-speaking underserved communities. Full article

Large-scale crop phenology monitoring is critical for agronomic planning and yield prediction applications. Synthetic Aperture Radar (SAR) remote sensing is well-suited for crop growth monitoring due to its nearly all-weather observation capability. Yet, the capability of the dual-polarimetric SAR data for wheat phenology estimation has not been thoroughly investigated. Here, we conducted a comprehensive evaluation of Sentinel-1 SAR polarimetric parameters’ sensibilities on winter wheat’s key phenophases while considering the incidence angle. We extracted 12 polarimetric parameters based on the covariance matrix and a dual-pol-version H-α decomposition. All parameters were evaluated by their temporal profile and feature importance score of Gini impurity with a decremental random forest classification process. A final wheat phenology classification model was built using the best indicator combination. The result shows that the Normalized Shannon Entropy (NSE), Degree of Linear Polarization (DoLP), and Stokes Parameter g2 were the three most important indicators, while the Span, Average Alpha ($\overline{{\alpha }_2})$, and Backscatter Coefficient ${\sigma }_{VH}^0$ were the three least important features in discriminating wheat phenology for all three incidence angle groups. The smaller-incidence angle (30–35°) SAR images are better suited for estimating wheat phenology. The combination of NSE, DoLP, and two Stokes Parameters (g2 and g0) constitutes the most effective indicator ensemble. For all eight key phenophases, the average Precision and Recall scores were above 0.8. This study highlighted the potential of dual-polarimetric SAR data for wheat phenology estimation. The feature importance evaluation results provide a reference for future phenology estimation studies using dual-polarimetric SAR data in choosing better-informed indicators. Full article

Introduction: Hepatitis E virus (HEV) genotype 3 is the major cause of acute viral hepatitis in several European countries. It is acquired mainly by ingesting contaminated pork, but has also been reported to be transmitted through blood transfusion. Although most HEV infections, including those via blood products, are usually self-limiting, they may become chronic in immunocompromised persons. It is thus essential to identify HEV-infected blood donations to prevent transmission to vulnerable recipients. Aims: Prior to the decision whether to introduce HEV RNA screening for all Swiss blood donations, a 2-year nationwide prevalence study was conducted. Methods: All blood donations were screened in pools of 12–24 samples at five regional blood donation services, and HEV RNA-positive pools were subsequently resolved to the individual donation index donation (X). The viral load, HEV IgG and IgM serology, and HEV genotype were determined. Follow-up investigations were conducted on future control donations (X + 1) and previous archived donations of the donor (X − 1) where available. Results: Between October 2018 and September 2020, 541,349 blood donations were screened and 125 confirmed positive donations were identified (prevalence 1:4331 donations). At the time of blood donation, the HEV RNA-positive individuals were symptom-free. The median viral load was 554 IU/mL (range: 2.01–2,500,000 IU/mL). Men (88; 70%) were more frequently infected than women (37; 30%), as compared with the sex distribution in the Swiss donor population (57% male/43% female, p < 0.01). Of the 106 genotyped cases (85%), all belonged to genotype 3. Two HEV sub-genotypes predominated; 3h3 (formerly 3s) and 3c. The remaining sub-genotypes are all known to circulate in Europe. Five 3ra genotypes were identified, this being a variant associated with rabbits. In total, 85 (68%) X donations were negative for HEV IgM and IgG. The remaining 40 (32%) were positive for HEV IgG and/or IgM, and consistent with an active infection. We found no markers of previous HEV in 87 of the 89 available and analyzed archive samples (X − 1). Two donors were HEV IgG-positive in the X − 1 donation suggesting insufficient immunity to prevent HEV reinfection. Time of collection of the 90 (72%) analyzed X + 1 donations varied between 2.9 and 101.9 weeks (median of 35 weeks) after X donation. As expected, none of those tested were positive for HEV RNA. Most donors (89; 99%) were positive for anti-HEV lgG/lgM (i.e., seroconversion). HEV lgM-positivity (23; 26%) indicates an often-long persistence of lgM antibodies post-HEV infection. Conclusion: The data collected during the first year of the study provided the basis for the decision to establish mandatory HEV RNA universal screening of all Swiss blood donations in minipools, a vital step in providing safer blood for all recipients, especially those who are immunosuppressed. Full article

Microgrids (MGs) have evolved as critical components of modern energy distribution networks, providing increased dependability, efficiency, and sustainability. Effective control strategies are essential for optimizing MG operation and maintaining stability in the face of changing environmental and load conditions. Traditional rule-based control systems are extensively used due to their interpretability and simplicity. However, these strategies frequently lack the flexibility for complex and changing system dynamics. This paper provides a novel method called hybrid intelligent control for adaptive MG that integrates basic rule-based control and deep learning techniques, including gated recurrent units (GRUs), basic recurrent neural networks (RNNs), and long short-term memory (LSTM). The main target of this hybrid approach is to improve MG management performance by combining the strengths of basic rule-based systems and deep learning techniques. These deep learning techniques readily enhance and adapt control decisions based on historical data and domain-specific rules, leading to increasing system efficiency, stability, and resilience in adaptive MG. Our results show that the proposed method optimizes MG operation, especially under demanding conditions such as variable renewable energy supply and unanticipated load fluctuations. This study investigates special RNN architectures and hyperparameter optimization techniques with the aim of predicting power consumption and generation within the adaptive MG system. Our promising results show the highest-performing models indicating high accuracy and efficiency in power prediction. The finest-performing model accomplishes an $R^2$ value close to 1, representing a strong correlation between predicted and actual power values. Specifically, the best model achieved an $R^2$ value of 0.999809, an MSE of 0.000002, and an MAE of 0.000831. Full article

A new ceramic dressing, free from active antimicrobial or pharmaceutical agents, uses physical binding mechanisms for its absorption capacities and bacterial-binding properties. The purpose of this study was to evaluate wound healing, bacterial-related retention, and diagnostic properties of ceramic dressings in patients with stagnated chronic wounds. Methods: In this monocentric, intra-individually controlled, prospective study, patients with conservatively treated refractory chronic wounds were enrolled. One week before the start of the application with ceramic dressing, it was ensured during a screening phase that chronic wounds showed less than a 10% reduction in wound size. During the 4-week ceramic dressing treatment wound size measurements, wound scoring, measurement of wound exudate amount, wound swabs, and ceramic dressing sonication (low-intensity ultrasound) were carried out. The sonication fluid of the removed ceramic dressing was used for analysis of bacterial retention and compared to wound swabs. Results: A total of 20 patients with a mean age of 64.6 years (±26.2) and 21 chronic wounds were included in this study. After a 4-week treatment, a significant reduction of median wound size from 1178 mm² (range 104–6300) to 751.5 mm² (range 16–4819) and better total wound scores were observed (p < 0.001). The sensitivity of bacteria detection was 90.7% in the sonication fluid from the ceramic dressings, while only 76.9% in the conventional wound swabs. Conclusion: The new ceramic dressing seems to have a positive impact on wound healing in chronic wounds. Bacteria-binding characteristics of the investigated ceramic dressing, in combination with its debridement, absorption, and detoxification properties, could contribute to its healing abilities. Based on those results, the investigated ceramic dressing seems to be a promising new treatment option for chronic wounds without the use of any active antimicrobial or pharmacological agents. Moreover, ceramic dressings can also be considered for microbiological diagnostic purposes. Full article

A multifunctional switchable metamaterial device based on graphene, a gold layer, polyimide, vanadiµm dioxide (VO₂), and the sapphire substrate is designed in this paper. The top layer consists of a gold wire, graphene, and two split-ring resonators with the same parameters. By adjusting the Fermi level of graphene, the regulation of BIC and quasi-BIC is realized, and the conversion between BIC and absorber is realized by adjusting the conductivity of VO₂. When the device is converted into a wave-absorbing device with single-band absorption characteristics, the Fermi level of graphene at this time is 0.001 eV, the absorption peak at 0.820 THz is higher than 99.5%, and when the Fermi level of regulated graphene is 1 eV, the absorption peak at 0.667 THz is also higher than 99.5%. The peak frequency of the device is 0.640 THz when it converts to quasi-BIC. To the best of our knowledge, this is the first time that the conversion and regulation of BIC and absorber have been achieved using these two phase change materials. Moreover, by adjusting the parameters of the metamaterial structure, the working efficiency and frequency of BIC and absorber can be dynamically adjusted. The electric field distribution and surface current of metamaterials are further studied, and the physical mechanism of effective absorption and BIC is discussed. These results show that the metamaterials proposed in this paper have many advantages, such as terahertz absorption, BIC, and active device control, and are of great significance for developing terahertz multifunctional devices. Full article

The advancement of Numerical Weather Prediction (NWP) is pivotal for enhancing high-impact weather forecasting and warning systems. However, due to the high spatial and temporal inhomogeneity, the moisture field is difficult to describe by initial conditions in NWP models, which is the essential thermodynamic variable in the simulation of various physical processes. Data Assimilation techniques are central to addressing these challenges, integrating observational data with background fields to refine initial conditions and improve forecasting accuracy. This study evaluates the effectiveness of integrating observations from the Fengyun-4A (FY-4A) Advanced Geosynchronous Radiation Imager (AGRI) and ground-based microwave radiometer (MWR) in forecasts and mechanism analysis of a heavy rainfall event in the Kaifeng region of central China. Our findings reveal that jointly assimilating AGRI radiance and MWR data significantly enhances the model’s humidity profile accuracy across all atmospheric layers, resulting in improved heavy rainfall predictions. Analysis of the moisture sources indicates that the storm’s water vapor predominantly originates from westward air movement ahead of a high-altitude trough, with sustained channeling towards the rainfall zone, ensuring a continuous supply of moisture. The storm’s development is further facilitated by a series of atmospheric processes, including the interplay of high and low-level vorticity and divergence, vertical updrafts, the formation of a low-level jet, and the generation of unstable atmospheric energy. Additionally, this study examines the influence of Tai-hang Mountain’s terrain on precipitation patterns in the Kaifeng area. Our experiments, comparing a control setup (CTL) with varied terrain heights, demonstrate that reducing terrain height by 50–60% significantly decreases precipitation coverage and intensity. In contrast, increasing terrain height enhances precipitation, although this effect plateaus when the elevation increase exceeds 100%, closely mirroring the precipitation changes observed with a 75% terrain height increment. Full article

Advanced electronics technology is moving towards smaller footprints and higher computational power. In order to achieve this, advanced packaging techniques are currently being considered, including organic, glass, and semiconductor-based substrates that allow for 2.5D or 3D integration of chips and devices. Metal-core substrates are a new alternative with similar properties to those of semiconductor-based substrates but with the added benefits of higher flexibility and metal ductility. This work comprehensively compares the thermal properties of a novel metal-based substrate, molybdenum, and silicon and fused silica glass substrates in the context of system-on-foil (SoF) integration. A simple electronic technique is used to simulate the heat generated by a typical CPU and to measure the heat dissipation properties of the substrates. The results indicate that molybdenum and silicon are able to effectively dissipate a continuous power density of 2.3 W/mm² as the surface temperature only increases by ~15 °C. In contrast, the surface temperature of fused silica glass substrates increases by >140 °C for the same applied power. These simple techniques and measurements were validated with infrared camera measurements as well as through finite element analysis via COMSOL simulation. The results validate the use of molybdenum as an advanced packaging substrate and can be used to characterize new substrates and approaches for advanced packaging. Full article

Macrobrachium rosenbergii is a warm water species, and low temperature is a limiting factor for its growth and survival. In order to explore the role of the acetyl-CoA-carboxylase (ACC) gene in response to the cold stress of M. rosenbergii, we investigated the effects of RNA interference (RNAi) with the ACC gene on the expression of fatty acid metabolism-related genes and the mortality of M. rosenbergii under cold stress. The results showed that different siRNA sequences and different injection concentrations had different inhibiting effects on ACC gene expression, and siRNA-III with an injection concentration of 2.0 μg/g (siRNA/prawn body weight) had the best interference effect. With the optimal siRNA and the optimal concentration under cold stress, the expressions of three fatty acid metabolism-related genes, FabD, echA, and ACOT, were generally significantly down-regulated. Compared to negative (scrambled-siRNA) and blank (PBS) control groups, the expression of FabD in the interference group was extremely significantly down-regulated at 12 h in the hepatopancreas and at 18 h in the muscles and gills; EchA was highly significantly down-regulated at 6 and 12 h in the muscles and gills; and ACOT was extremely significantly down-regulated and kept declining in the gills. Within 6–18 h after injection under cold stress, the mortality rate of the siRNA interference group (75%) was much lower than that of the negative (95%) or blank control group (97.5%), and all prawns died after 24 h. In conclusion, RNA interference with the ACC gene inhibited the expression of some fatty acid metabolism-related genes, and could partly improve the tolerance of M. rosenbergii to cold stress, indicating that the ACC gene might play an important role in the response of M. rosenbergii to cold stress. Full article

The occurrence of contaminants of emerging concern (CECs) in several environmental compartments has raised significant concern given the extensive array of compounds and their consistent detection across various environmental matrices. Monitoring all potentially harmful compounds and identifying their sources is nearly impossible. However, providing data on their occurrence is crucial and lays the groundwork for decision makers to craft mitigation strategies toward a more sustainable water policy. Hence, the primary aim of this study was to conduct an evaluation study on CECs occurrence in the environment. The main novelty relies on understanding their specific pathway in three different environmental aquatic compartments. For that, a combined study of a systematic review and systemic analysis was performed. Initially, the five most common types of CECs found in aquatic ecosystems (groundwater and surface water) and wastewater were considered. For each group of CECs, five contaminants were identified. A bibliographic portfolio was generated through the application of a systematic review. Finally, a systemic analysis of the bibliographic portfolio was conducted. All classes of contaminants studied were identified in the environmental compartments evaluated. Except for pesticides, the degree of contamination by CECs followed a sequence based on the aquatic compartment (i.e., WW–SW–GW). Full article

A nonterminal liquid crystal epoxy monomer is used to create an epoxy–amine network with a typical diamine 4,4′diaminodiphenylmethane. The plain matrix is compared to matrices modified with inorganic fillers: TiO₂ or SiO₂. Conditions of the curing reaction and glass transition temperatures in the cured products are determined through differential scanning calorimetry and broadband dielectric spectroscopy. The curing process is also followed through optical and electrical observations. The dielectric response of all investigated networks reveals a segmental α-process related to structural reorientation (connected to the glass transition). In all products, a similar process associated with molecular motions of polar groups also appears. The matrix modified with TiO₂ exhibits two secondary relaxation processes (β and γ). Similar processes were observed in the pure monomer. An advantage of the network with the TiO₂ filler is a shorter time or lower temperature required for optimal curing conditions. The physical properties of cured matrices depend on the presence of a nematic phase in the monomer and nonterminal functional groups in the aliphatic chains. In effect, such cured matrices can have more flexibility and internal order than classical resins. Additional modifiers used in this work shift the glass transition above room temperature and influence the fragility index in both cases. Full article

Understanding the characteristics of coal spontaneous combustion (CSC) in goaf under different porosities is crucial for comprehending the mechanism of CSC and its prevention and control. In this paper, a multi-field coupled model of CSC in the goaf, considering porosity variation, is developed to investigate the effect of porosity on the CSC characteristics in the goaf. The results indicate that, as the goaf depth increases, both porosity and permeability decrease. When the highest goaf porosity is 25%, the average airflow velocity is between 0.00134 and 0.00139 m/s. In contrast, the average airflow velocity in the goaf with a porosity of 40% is approximately six times greater than that of the goaf with a porosity of 25%. As the goaf porosity increases, the overall oxygen concentration, temperature, and oxidized zone area also rise. Moreover, the oxidation zone area can be quantified and visualized, thereby enabling more effective prediction of the CSC risk in the goaf. The findings of the study have a positive significance in guiding the prevention and control of coal fires. Full article

The analytical generalization for N periodic potential wells coupled to a probe rectangular-like potential and a zero potential is extremely important in the study of one-dimensional periodic potentials in solid state physics, e.g., in the calculation of transport, optical, and magnetic properties. These findings raise the possibility of calculating equations for the generalization of N arbitrary potentials related to any potential $V\left(x\right)$ using special functions as a solution. In this work, a novel analytical generalization of the transcendental energy equation, group velocity, and effective mass for N-coupled potentials to a probe one-dimensional potential $V=V\left(x\right)$ was proposed. Initially, two well-known linear periodic potentials $V=V\left(x\right)$ were employed to obtain analytical solutions for rectangular-like and Dirac-delta potentials. Python libraries were used to easily represent the equations for one or two rectangular-like potentials coupled with an arbitrary potential, highlighting the transcendental energy, group velocity, and effective mass. The results showed that the group velocity behavior changed its orientation due to the sign of the potential, whereas the width of the potential $V\left(x\right)$ strongly influenced the group velocity behavior. The effective mass was also modified by the potential shapes, and their combinations, both effective mass and group velocity, exhibited similar physical behaviors to those found in ordinary rectangular-like potentials. Full article

Nowadays, magnetic materials are also drawing considerable attention in the development of innovative energy converters such as triboelectric nanogenerators (TENGs), where the introduction of magnetic materials at the triboelectric interface not only significantly enhances the energy harvesting efficiency but also promotes TENG entry into the era of intelligence and multifunction. In this review, we begin from the basic operating principle of TENGs and then summarize the recent progress in applications of magnetic materials in the design of TENG magnetic materials by categorizing them into soft ferrites and amorphous and nanocrystalline alloys. While highlighting key role of magnetic materials in and future opportunities for improving their performance in energy conversion, we also discuss the most promising choices available today and describe emerging approaches to create even better magnetic TENGs and TENG-based sensors as far as intelligence and multifunctionality are concerned. In addition, the paper also discusses the integration of magnetic TENGs as a power source for third-party sensors and briefly explains the self-powered applications in a wide range of related fields. Finally, the paper discusses the challenges and prospects of magnetic TENGs. Full article

Breast cancer is the most prevalent type of cancer in women. Risk factor assessment can aid in directing counseling regarding risk reduction and breast cancer surveillance. This research aims to (1) investigate the relationship between various risk factors and breast cancer incidence using the BCSC (Breast Cancer Surveillance Consortium) Risk Factor Dataset and create a prediction model for assessing the risk of developing breast cancer; (2) diagnose breast cancer using the Breast Cancer Wisconsin diagnostic dataset; and (3) analyze breast cancer survivability using the SEER (Surveillance, Epidemiology, and End Results) Breast Cancer Dataset. Applying resampling techniques on the training dataset before using various machine learning techniques can affect the performance of the classifiers. The three breast cancer datasets were examined using a variety of pre-processing approaches and classification models to assess their performance in terms of accuracy, precision, F-1 scores, etc. The PCA (principal component analysis) and resampling strategies produced remarkable results. For the BCSC Dataset, the Random Forest algorithm exhibited the best performance out of the applied classifiers, with an accuracy of 87.53%. Out of the different resampling techniques applied to the training dataset for training the Random Forest classifier, the Tomek Link exhibited the best test accuracy, at 87.47%. We compared all the models used with previously used techniques. After applying the resampling techniques, the accuracy scores of the test data decreased even if the training data accuracy increased. For the Breast Cancer Wisconsin diagnostic dataset, the K-Nearest Neighbor algorithm had the best accuracy with the original dataset test set, at 94.71%, and the PCA dataset test set exhibited 95.29% accuracy for detecting breast cancer. Using the SEER Dataset, this study also explores survival analysis, employing supervised and unsupervised learning approaches to offer insights into the variables affecting breast cancer survivability. This study emphasizes the significance of individualized approaches in the management and treatment of breast cancer by incorporating phenotypic variations and recognizing the heterogeneity of the disease. Through data-driven insights and advanced machine learning, this study contributes significantly to the ongoing efforts in breast cancer research, diagnostics, and personalized medicine. Full article

(1) Background: Computed tomography (CT) plays a paramount role in the characterization and follow-up of COVID-19. Several score systems have been implemented to properly assess the lung parenchyma involved in patients suffering from SARS-CoV-2 infection, such as the visual quantitative assessment score (VQAS) and software-based quantitative assessment score (SBQAS) to help in managing patients with SARS-CoV-2 infection. This study aims to investigate and compare the diagnostic accuracy of the VQAS and SBQAS with two different types of software based on artificial intelligence (AI) in patients affected by SARS-CoV-2. (2) Methods: This is a retrospective study; a total of 90 patients were enrolled with the following criteria: patients’ age more than 18 years old, positive test for COVID-19 and unenhanced chest CT scan obtained between March and June 2021. The VQAS was independently assessed, and the SBQAS was performed with two different artificial intelligence-driven software programs (Icolung and CT-COPD). The Intraclass Correlation Coefficient (ICC) statistical index and Bland–Altman Plot were employed. (3) Results: The agreement scores between radiologists (R1 and R2) for the VQAS of the lung parenchyma involved in the CT images were good (ICC = 0.871). The agreement score between the two software types for the SBQAS was moderate (ICC = 0.584). The accordance between Icolung and the median of the visual evaluations (Median R1–R2) was good (ICC = 0.885). The correspondence between CT-COPD and the median of the VQAS (Median R1–R2) was moderate (ICC = 0.622). (4) Conclusions: This study showed moderate and good agreement upon the VQAS and the SBQAS; enhancing this approach as a valuable tool to manage COVID-19 patients and the combination of AI tools with physician expertise can lead to the most accurate diagnosis and treatment plans for patients. Full article

Since the launch of this Special Issue entitled “Cancer Immunotherapy: Tumor Microenvironment, Biomarker Discovery and Immune Resistance”, the field of cancer immunotherapy has continued to witness rapid growth in the development of novel agents, improvements in our understanding of mechanisms of response and resistance, and the maturation of emerging technologies such as artificial intelligence, machine learning, single-cell sequencing and spatial profiling [...] Full article

Background: Postoperative de novo atrial fibrillation (POAF) is one of the most frequently encountered complications following cardiac surgery. Despite the identification of several risk factors, the link between sleep-disordered breathing (SDB) and POAF has barely been examined. The objective of this prospective observational study was to determine whether severe SDB is associated with POAF in patients after elective coronary artery bypass grafting (CABG) surgery. Study design and methods: The incidence and preoperative predictors of in-hospital POAF were assessed in 272 patients undergoing CABG surgery at the University Medical Center Regensburg (Germany). In-hospital POAF was detected by continuous telemetry-ECG monitoring and 12-lead resting ECGs within the first seven postoperative days. POAF that occurred after hospital discharge within 60 days post CABG surgery was classified as post-hospital POAF and was ascertained by standardized phone interviews together with the patients’ medical files, including routinely performed Holter-ECG monitoring at 60 days post CABG surgery. The night before surgery, portable SDB monitoring was used to assess the presence and type of severe SDB, defined by an apnea–hypopnea index ≥ 30/h. Results: The incidence of in-hospital POAF was significantly higher in patients with severe SDB compared to those without severe SDB (30% vs. 15%, p = 0.009). Patients with severe SDB suffered significantly more often from POAF at 60 days post CABG surgery compared to patients without severe SDB (14% vs. 5%, p = 0.042). Multivariable logistic regression analysis showed that severe SDB (odds ratio, OR [95% confidence interval, CI]: 2.23 [1.08; 4.61], p = 0.030), age ≥ 65 years (2.17 [1.04; 4.53], p = 0.038), and diabetes mellitus (2.27 [1.15; 4.48], p = 0.018) were significantly associated with in-hospital POAF. After additional adjustment for heart failure, the association between sleep apnea and postoperative atrial fibrillation was attenuated (1.99 [0.92; 4.31], p = 0.081). Conclusions: Amongst established risk factors, severe SDB was significantly associated with in-hospital POAF in patients undergoing CABG surgery. Whether SDB contributes to POAF independently of heart failure and whether risk for POAF may be alleviated by proper treatment of SDB merits further investigation. Full article

The aim of the study was to assess the impact of two lengths of Nordic walking (NW) training interventions combined with time-restricted eating (TRE) on improving body-composition parameters, lipid profiles, and levels of selected adipokines in women with elevated body mass. Overweight and obese women (n = 55, age: 21–85) were recruited. Four groups were selected: 6 weeks (SG6, n = 13) and 12 weeks intervention (SG12, n = 13); and two control groups: CON6 (n = 13) and CON12 (n = 13). The training sessions took place three times a week (60 min each) and were conducted outdoors under the supervision of a professional coach. The training intensity was determined individually. The extended NW program combined with TRE induced a significant weight reduction in SG12 by 1.96 kg (p = 0.010) and fat tissue by 1.64 kg (p = 0.05). The proposed interventions did not affect LBM, TBW [kg], VFA, and lipid profile. The LDL/HDL ratio changed with a small size effect. The leptin concentration differed between groups (p = 0.006), but not over time. For resistin, the differentiating factor was time (p = 0.019), with lower results observed after the intervention. The change in leptin concentration was negatively correlated with its baseline concentration (p = 0.025). Extended to 12 weeks, this intervention allows for an improvement in body composition. Neither 6 nor 12 weeks of training and fasting affected the lipoprotein profile. It is, therefore, indicated to recommend prolonged training protocols and to inform patients that beneficial effects will be seen only after prolonged use of training and time-restricted eating. Full article

Stress is a common denominator of complex disorders and the FK-506 binding protein (FKBP)51 plays a central role in stress. Hence, it is not surprising that multiple studies imply the involvement of the FKBP51 protein and/or its coding gene, FKBP5, in complex disorders. This review summarizes such reports concentrating on three disorder clusters—neuropsychiatric, cancer, and type 2 diabetes mellitus (T2DM). We also attempt to point to potential mechanisms suggested to mediate the effect of FKBP5/FKBP51 on these disorders. Neuropsychiatric diseases considered in this paper include (i) Huntington’s disease for which increased autophagic cellular clearance mechanisms related to decreased FKBP51 protein levels or activity is discussed, Alzheimer’s disease for which increased FKBP51 activity has been shown to induce Tau phosphorylation and aggregation, and Parkinson’s disease in the context of which FKBP12 is mentioned; and (ii) mental disorders, for which significant association with the single nucleotide polymorphism (SNP) rs1360780 of FKBP5 intron 7 along with decreased DNA methylation were revealed. Since cancer is a large group of diseases that can start in almost any organ or tissue of the body, FKBP51’s role depends on the tissue type and differences among pathways expressed in those tumors. The FKBP51–heat-shock protein-(Hsp)90–p23 super-chaperone complex might function as an oncogene or as a tumor suppressor by downregulating the serine/threonine protein kinase (AKt) pathway. In T2DM, two potential pathways for the involvement of FKBP51 are highlighted as affecting the pathogenesis of the disease—the peroxisome proliferator-activated receptor-γ (PPARγ) and AKt. Full article

This research explores the use of Q-Learning for real-time swarm (Q-RTS) multi-agent reinforcement learning (MARL) algorithm for robotic applications. This study investigates the efficacy of Q-RTS in the reducing convergence time to a satisfactory movement policy through the successful implementation of four and eight trained agents. Q-RTS has been shown to significantly reduce search time in terms of training iterations, from almost a million iterations with one agent to 650,000 iterations with four agents and 500,000 iterations with eight agents. The scalability of the algorithm was addressed by testing it on several agents’ configurations. A central focus was placed on the design of a sophisticated reward function, considering various postures of the agents and their critical role in optimizing the Q-learning algorithm. Additionally, this study delved into the robustness of trained agents, revealing their ability to adapt to dynamic environmental changes. The findings have broad implications for improving the efficiency and adaptability of robotic systems in various applications such as IoT and embedded systems. The algorithm was tested and implemented using the Georgia Tech Robotarium platform, showing its feasibility for the above-mentioned applications. Full article