Ovarian cancer is the deadliest gynecologic malignancy. The majority of patients diagnosed with advanced ovarian cancer will relapse, at which point additional therapies can be administered but, for the most part, these are not curative. As such, a need exists for the development of novel therapeutic options for ovarian cancer patients. Research in the field of targeted protein degradation (TPD) through the use of proteolysis-targeting chimeras (PROTACs) has significantly increased in recent years. The ability of PROTACs to target proteins of interest (POI) for degradation, overcoming limitations such as the incomplete inhibition of POI function and the development of resistance seen with other inhibitors, is of particular interest in cancer research, including ovarian cancer research. This review provides a synopsis of PROTACs tested in ovarian cancer models and highlights PROTACs characterized in other types of cancers with potential high utility in ovarian cancer. Finally, we discuss methods that will help to enable the selective delivery of PROTACs to ovarian cancer and improve the pharmacodynamic properties of these agents. Full article

Hemodialysis (HD) is a life-sustaining membrane-based therapy that is essential for managing kidney failure. However, it can have significant physical and psychological effects on patients due to chronic or acute consequences related to membrane bioincompatibility. End-stage renal disease (ESRD) patients on hemodialysis have a high incidence of psychiatric illness, particularly depression and anxiety disorders, and poor quality of life has been observed. Dialysis can also lead to physical symptoms of its own, such as fatigue, loss of appetite, anemia, low blood pressure, and fluid overload, in addition to the symptoms associated with kidney failure. Therefore, this critical review aims to comprehensively understand the impact of dialysis membrane bioincompatibility and the use of varying molecular weight cut-off membranes on the physical and psychological symptoms experienced by dialysis patients. We analyzed the latest research on the correlation between major inflammatory biomarkers released in patients’ blood due to membrane incompatibility, as well as the critical influence of low levels of hemoglobin and vital proteins such as human serum albumin due to the use of high-cut-off membranes and correlated these factors with the physical and psychological symptoms experienced by dialysis patients. Furthermore, our study aims to provide valuable insights into the impact of dialysis on critical symptoms, higher hospitalization rates, and the quality of life of First Nations, as well as child and youth dialysis patients, in addition to diabetic dialysis patients. Our goal is to identify potential interventions aiming to optimize the dialysis membrane and minimize its negative effects on patients, ultimately improving their well-being and long-term outcomes. Full article

Weight bias internalization (WBI), the process of internalizing negative attitudes and stereotypes towards overweight individuals, significantly impacts self-worth and health behaviors, such as exercise avoidance. In the current study, we focused on the mediating role of fitness-related self-conscious emotions, particularly shame and guilt. A cross-sectional study involving 150 self-described overweight Dutch women (age M = 49.63 ± 10.72) was conducted online. Participants completed measures assessing weight bias internalization, exercise avoidance, and body/fitness-related self-conscious emotions. Data were analyzed using linear regression and mediation analysis, controlling for age, BMI, and exercise frequency. The results show that weight bias internalization, guilt-free shame, and shame-free guilt uniquely predict exercise avoidance. Guilt-free shame partially mediated the relationship between weight bias internalization and exercise avoidance, indicating that increased internalized weight bias led to higher levels of guilt-free shame, which in turn contributed to exercise avoidance. Shame-free guilt did not act as a unique mediator. These findings underscore the importance of addressing weight bias internalization and fitness-related self-conscious emotions, particularly guilt-free shame, in interventions targeting exercise avoidance among overweight individuals. Strategies promoting self-compassion and reducing shame may prove beneficial in improving exercise behaviors and overall well-being. Full article

The prediction and distribution of reservoir porosity and permeability are of paramount importance for the exploration and development of regional oil and gas resources. In order to optimize the prediction methods of porosity and permeability and better guide gas field development, it is necessary to identify the most effective approaches. Therefore, based on the extreme gradient boosting (XGBoost) algorithm, laboratory test data of the porosity and permeability of cores from the southern margin of the Ordos Basin were selected as the target labels, conventional logging curves were used as the input feature variables, and the mean absolute error (MAE) and the coefficient of determination (R²) were used as the evaluation indicators. Following the selection of the optimal feature variables and optimization of the hyper-parameters, an XGBoost porosity and permeability prediction model was established. Subsequently, the innovative application of homogeneous clustering (K-means) data preprocessing was applied to enhance the XGBoost model’s performance. The results show that logarithmically preprocessed (LOG(PERM)) target labels enhanced the performance of the XGBoost permeability prediction model, with an increase of 0.26 in its test set R². Furthermore, the application of K-means improved the performance of the XGBoost prediction model, with an increase of 0.15 in the R² of the model and a decrease of 0.017 in the MAE. Finally, the POR_0/POR_1 grouped porosity model was selected as the final predictive model for porosity in the study area, and the Arctan(PERM)_0/Arctan(PER0M)_1 grouped model was selected as the final predictive model for permeability, which has better prediction accuracy than logging curves. The combination of K-means and the XGBoost modeling method provides a new approach and reference for the efficient and relatively accurate evaluation of porosity and permeability in the study area. Full article

Building energy efficiency in public institutions is crucial for achieving energy conservation and emissions reduction goals. The application of energy performance contracting (EPC) can effectively reduce energy consumption in these buildings and promote the development of the energy-saving service industry. However, there is a lack of initiative among public institutions to adopt EPC. This study aims to investigate the factors that drive the intention and behavior of public institutions to apply EPC and enhance their proactive engagement in building energy efficiency retrofitting. By considering the current status of EPC application in public institutions and drawing on relevant decision-making and behavioral theories, this paper identifies the key factors that drive the intention and behavior of public institutions, and constructs a theoretical model of the intentional and behavioral driving factors. In the empirical testing phase, research data are collected through online questionnaires. Structural equation modeling is employed to validate and analyze the extent of the driving factors and their interrelationships. The key findings are that (1) perceived usefulness, trust, and perceived risk significantly drive the behavior intention of public institutions to apply EPC; (2) perceived behavioral control and perceived ease of use significantly positively drive the behavior of public institutions, with behavior intention being the most influential factor; and (3) policy system and organizational support play a significant moderating role in the process from intention to behavior. Based on these findings, this paper proposes the critical tasks and suggests countermeasures for stakeholders in EPC projects. Full article

African swine fever virus (ASFV) poses a significant threat to the global pig industry, necessitating accurate and efficient diagnostic methods for its infection. Previous studies have often focused on a limited number of epitopes from a few proteins for detecting antibodies against ASFV. Therefore, the current study aimed to use multiple B-cell epitopes in developing an indirect Enzyme-Linked Immunosorbent Assay (ELISA) for enhanced detection of ASFV antibodies. For the expression of recombinant protein, k3 derived from 27 multiple peptides of 11 ASFV proteins, such as p72, pA104R, pB602L, p12, p14.5, p49, pE248R, p30, p54, pp62, and pp220, was used. To confirm the expression of the recombinant protein, we used the Western blotting analysis. The purified recombinant K3 protein served as the antigen in our study, and we employed the indirect ELISA technique to detect anti-ASFV antibodies. The present finding showed that there was no cross-reactivity with antibodies targeting Foot-and-mouth disease virus (FMDV), Porcine circovirus type 2 (PCV2), Pseudorabies virus (PRV), Porcine reproductive and respiratory syndrome virus (PRRSV), and Classical swine fever virus (CSFV). Moreover, the current finding was sensitive enough to find anti-ASFV in serum samples that had been diluted up to 32 times. The test (k3-iELISA) showed diagnostic specificity and sensitivity of 98.41% and 97.40%, respectively. Moreover, during the present investigation, we compared the Ingenasa kit and the k3-iELISA to test clinical pig serum, and the results revealed that there was 99.00% agreement between the two tests, showing good detection capability of the k3-iELISA method. Hence, the current finding showed that the ELISA kit we developed can be used for the rapid detection of ASFV antibodies and used as an alternative during serological investigation of ASF in endemic areas. Full article

Background/Objectives: To evaluate radiation exposure in standard interventional radiology procedures using a twin robotic X-ray system compared to a state-of-the-art conventional angiography system. Methods: Standard interventional radiology procedures (port implantation, SIRT, and pelvic angiography) were simulated using an anthropomorphic Alderson RANDO phantom (Alderson Research Laboratories Inc. Stamford, CT, USA) on an above-the-table twin robotic X-ray scanner (Multitom Rax, Siemens Healthineers, Forchheim, Germany) and a conventional below-the-table angiography system (Artis Zeego, Siemens Healthineers, Forchheim, Germany). The phantom’s radiation exposure (representing the potential patient on the procedure table) was measured with thermoluminescent dosimeters. Height-dependent dose curves were generated for examiners and radiation technologists in representative positions using a RaySafe X2 system (RaySafe, Billdal, Sweden). Results: For all scenarios, the device-specific dose distribution differs depending on the imaging chain, with specific advantages and disadvantages. Radiation exposure for the patient is significantly increased when using the Multitom Rax for pelvic angiography compared to the Artis Zeego, which is evident in the dose progression through the phantom’s body as well as in the organ-related radiation exposure. In line with these findings, there is an increased radiation exposure for the performing proceduralist, especially at eye level, which can be significantly minimized by using protective equipment (p < 0.001). Conclusions: In this study, the state-of-the-art conventional below-the-table angiography system is associated with lower radiation dose exposures for both the patient and the interventional radiology physician compared to an above-the-table twin robotic X-ray system for pelvic angiographies. However, in other clinical scenarios (port implantation or SIRT), both devices are suitable options with acceptable radiation exposure. Full article

In recent years, the production of municipal sludge has gradually increased, and finding suitable sludge treatment and disposal technologies is an urgent problem that needs to be solved. Bio-drying of sludge is a relatively efficient and convenient drying method, but currently, there are still problems with unstable drying effects and high moisture content of dried products, which limits the subsequent utilization of bio-drying products. This article uses a thermal assisted bio-drying device that simulates carbonization waste heat reflux, and uses corncob, straw, sawdust, and rice husk as conditioners to carry out bio-drying of dehydrated sludge. The influence of the types and ratios of conditioner under thermal assistance on the bio-drying of dehydrated sludge is explored. The results showed that the moisture removal efficiency of the corncob and straw groups was better, and their material moisture content could be reduced to below 10% within 24 h. The lower calorific value of straw-sludge drying products was the highest, at 11,608.8 kJ/kg. The best conditioner under the conditions of this experiment was straw, and the drying effect was best when the mass ratio of dehydrated sludge to straw was 4:1. The research results contribute to promoting the development of sludge bio-drying technology. Full article

Mineralized materials are gaining increased interest recently in a number of fields, especially in bone tissue engineering as bone replacement materials as well as in the architecture-built environment as structural building materials. Until the moment, there has not been a unified sustainable approach that addresses this multi-scale application objective by developing a self-mineralized material with minimum consumption of materials and processes. Thus, in the current study, a hydrogel developed from sodium alginate, gelatine, and calcium phosphate dibasic (CPDB) was optimized in terms of rheological properties and mineralization capacity through the formation of hydroxyapatite crystals. The hydrogel composition process adopted a three-stage, thermally induced chemical cross-linking to achieve a stable and enhanced hydrogel. The 6% CPDB-modified SA–gelatine hydrogel achieved the best rheological properties in terms of elasticity and hardness. Different concentrations of epigallocatechin gallate were tested as well as a rheological enhancer to optimize the hydrogel and to boost its anti-microbial properties. However, the results from the addition of EPGCG were not considered significant; thus, the 6% CPDB-modified SA–gelatine hydrogel was further tested for mineralization by incubation in various media, without and with cells, for 7 and 14 days, respectively, using scanning electron microscopy. The results revealed significantly enhanced mineralization of the hydrogel by forming hydroxyapatite platelets of the air-incubated hydrogel (without cells) in non-sterile conditions, exhibiting antimicrobial properties as well. Similarly, the air-incubated bioink with osteosarcoma SaOs-2 cells exhibited dense mineralized topology with hydroxyapatite crystals in the form of faceted spheres. Finally, the FBS-incubated hydrogel and FBS-incubated bioink, incubated for 7 and 14 days, respectively, exhibited less densely mineralized topology and less distribution of the hydroxyapatite crystals. The degradation rate of the hydrogel and bioink incubated in FBS after 14 days was determined by the increase in dimensions of the 3D-printed samples, which was between 5 to 20%, with increase in the bioink samples dimensions in comparison to their dimensions post cross-linking. Meanwhile, after 14 days, the hydrogel and bioink samples incubated in air exhibited shrinkage: a 2% decrease in the dimensions of the 3D-printed samples in comparison to their dimensions post cross-linking. The results prove the capacity of the developed hydrogel in achieving mineralized material with anti-microbial properties and a slow-to-moderate degradation rate for application in bone tissue engineering as well as in the built environment as a structural material using a sustainable approach. Full article

The published data on the vitamin status of patients with phenylketonuria (PKU) is contradictory; therefore, this systematic review and meta-analysis evaluated the vitamin status of PKU patients. A comprehensive search of multiple databases (PubMed, Web of Sciences, Cochrane, and Scopus) was finished in March 2024. The included studies compared vitamin levels between individuals diagnosed with early-treated PKU and healthy controls while excluding pregnant and lactating women, untreated PKU or hyperphenylalaninemia cases, control groups receiving vitamin supplementation, PKU patients receiving tetrahydrobiopterin or pegvaliase, and conference abstracts. The risk of bias in the included studies was assessed by the Newcastle–Ottawa scale. The effect sizes were expressed as standardised mean differences. The calculation of effect sizes with 95% CI using fixed-effects models and random-effects models was performed. A p-value < 0.05 was considered statistically significant. The study protocol was registered in the PROSPERO database (CRD42024519589). Out of the initially identified 11,086 articles, 24 met the criteria. The total number of participants comprised 770 individuals with PKU and 2387 healthy controls. The meta-analyses of cross-sectional and case–control studies were conducted for vitamin B12, D, A, E, B6 and folate levels. PKU patients demonstrated significantly higher folate levels (random-effects model, SMD: 1.378, 95% CI: 0.436, 2.320, p = 0.004) and 1,25-dihydroxyvitamin D concentrations (random-effects model, SMD: 2.059, 95% CI: 0.250, 3.868, p = 0.026) compared to the controls. There were no significant differences in vitamin A, E, B6, B12 or 25-dihydroxyvitamin D levels. The main limitations of the evidence include a limited number of studies and their heterogeneity and variability in patients’ compliance. Our findings suggest that individuals with PKU under nutritional guidance can achieve a vitamin status comparable to that of healthy subjects. Our study provides valuable insights into the nutritional status of PKU patients, but further research is required to confirm these findings and explore additional factors influencing vitamin status in PKU. Full article

In view of Industry 4.0, data generation and analysis are challenges. For example, machine health monitoring and remaining useful life prediction use sensor signals, which are difficult to analyze using traditional methods and mathematical techniques. Machine and deep learning algorithms have been used extensively in Industry 4.0 to process sensor signals and improve the accuracy of predictions. Therefore, this paper proposes and validates the data-driven prediction model to analyze sensor data, including in the data transformation phase Principal Component Analysis tested by Fourier Transformation and Wavelet Transformation, and the modeling phase based on machine and deep learning algorithms. The machine learning algorithms used for tests in this research are Random Forest Regression (RFR), Multiple Linear Regression (MLR), and Decision Tree Regression (DTR). For the deep learning comparison, the algorithms are Deep Learning Regression and Convolutional network with LeNet-5 Architecture. The experimental results indicate that the models show promising results in predicting wear values and open the problem to further research, reaching peak values of 92.3% accuracy for the first dataset and 62.4% accuracy for the second dataset. Full article

The aim of our study was to develop a gas chromatographic method coupled with mass spectrometry (GC-MS) for the determination of underivatised neutral (CBDs-N) and acidic (CBDs-A) cannabinoids (CBDs) and cholesterol (Chol). Emphasis was also placed on comparing our original GC-MS method with the currently developed C18-high-performance liquid chromatography with photodiode detection (C18-HPLC-DAD). A combination of a long GC column, shallow temperature column programme, and mass-spectrometry was employed to avoid issues arising from the overlap between CBDs and Chol and background fluctuations. The pre-column procedure for CBDs and Chol in egg yolks consisted of hexane extractions, whereas the pre-column procedure for CBDs in non-animal samples involved methanol and hexane extractions. CBDs-A underwent decarboxylation to CBDs during GC-MS analyses, and pre-column extraction of the processed sample with NaOH solution allowed for CBD-A removal. No losses of CBDs-N were observed in the samples extracted with NaOH solution. GC-MS analyses of the samples before and after extraction with NaOH solution enabled the quantification of CBDs-A and CBDs-N. CBDs-A did not undergo decarboxylation to CBDs-N during C18-HPLC-DAD runs. The use of the C18-HPLC-DAD method allowed simultaneous determination of CBDs-N and CBDs-A. In comparison to the C18-HPLC-DAD method, our GC-MS technique offered improved sensitivity, precision, specificity, and satisfactory separation of underivatised CBDs and Chol from biological materials of endogenous species, especially in hemp and hen egg yolk. The scientific novelty of the present study is the application of the GC-MS method for quantifying underivatised CBDs-A, CBDs-N, and Chol in the samples of interest. Full article

Research on the identification of urban functional regions is of great significance for the understanding of urban structure, spatial planning, resource allocation, and promoting sustainable urban development. However, achieving high-precision urban functional region recognition has always been a research challenge in this field. For this purpose, this paper proposes an urban functional region identification method called ASOE (activity–scene–object–economy), which integrates the features from multi-source data to perceive the spatial differentiation of urban human and geographic elements. First, we utilize VGG16 (Visual Geometry Group 16) to extract high-level semantic features from the remote sensing images with 1.2 m spatial resolution. Then, using scraped building footprints, we extract building object features such as area, perimeter, and structural ratios. Socioeconomic features and population activity features are extracted from Point of Interest (POI) and Weibo data, respectively. Finally, integrating the aforementioned features and using the Random Forest method for classification, the identification results of urban functional regions in the main urban area of Xi’an are obtained. After comparing with the actual land use map, our method achieves an identification accuracy of 91.74%, which is higher than other comparative methods, making it effectively identify four typical urban functional regions in the main urban area of Xi’an (e.g., residential regions, industrial regions, commercial regions, and public regions). The research indicates that the method of fusing multi-source data can fully leverage the advantages of big data, achieving high-precision identification of urban functional regions. Full article

Celery seeds contain various bioactive compounds and are commonly used as a spice and nutritional supplement in people’s daily lives. The quality of celery seeds sold on the market varies, and their regions of production are unclear. This study evaluated the metabolites of Chinese celery seeds from three production regions using HS-SPME-GC-MS, HS-GC-IMS, and UPLC-ESI-MS/MS. The results indicate that GC-IMS analysis obtained a metabolic profile different from that detected using GC-MS. Terpenoids, polyphenols, coumarins, and phthalides are the main bioactive compounds in celery seeds. The production region significantly affects the metabolic characteristics of celery seeds. Based on GC-MS data, GC-IMS data, and LC-MS data, the variation analysis screened 6, 12, and 8 metabolites as potential characteristic metabolites in celery seeds related to the production region, respectively. According to the aromatic characteristics of the characteristic metabolites, seeds from the HCQ region and HZC region have a strong herbal, woody, celery, and turpentine aroma. The concentration of secondary metabolites was highest in the seeds from the HCQ region followed by the HZC region, and it was the lowest in the JJC region. Altogether, this study investigates how geographical origins influence the metabolomic profile of celery seeds. The results can be used to guide the planting and harvesting of celery seeds in suitable regions. Full article

Spatial graphene is a 3D structure of a 2D material that preserves its main features. Its production can be originated from the water solution of graphene oxide (GO). The main steps of the method include the crosslinking of flakes of graphene via treatment with hydrazine, followed by the reduction of the pillared graphene oxide (pGO) with hydrogen overpressure at 700 °C, and further decoration with catalytic metal (palladium). Experimental research achieved the formation of reduced pillared graphene oxide (r:pGO), a porous material with a surface area equal to 340 m²/g. The transition from pGO to r:pGO was associated with a 10-fold increase in pore volume and the further reduction of remaining oxides after the action of hydrazine. The open porosity of this material seems ideal for potential applications in the energy industry (for hydrogen storage, in batteries, or in electrochemical and catalytic processes). The hydrogen sorption potential of the spatial graphene-based material decorated with 6 wt.% of palladium reached 0.36 wt.%, over 10 times more than that of pure metal. The potential of this material for industrial use requires further refining of the elaborated procedure, especially concerning the parameters of substrate materials. Full article

B355252 is a small molecular compound known for potentiating neural growth factor and protecting against neuronal cell death induced by glutamate in vitro and cerebral ischemia in vivo. However, its other biological functions remain unclear. This study aims to investigate whether B355252 suppresses neuroinflammatory responses and cell death in the brain. C57BL/6j mice were intraperitoneally injected with a single dosage of lipopolysaccharide (LPS, 1 mg/kg) to induce inflammation. B355252 (1 mg/kg) intervention was started two days prior to the LPS injection. The animal behavioral changes were assessed pre- and post-LPS injections. The animal brains were harvested at 4 and 24 h post-LPS injection, and histological, biochemical, and cytokine array outcomes were examined. Results showed that B355252 improved LPS-induced behavioral deterioration, mitigated brain tissue damage, and suppressed the activation of microglial and astrocytes. Furthermore, B355252 reduced the protein levels of key pyroptotic markers TLR4, NLRP3, and caspase-1 and inhibited the LPS-induced increases in IL-1β, IL-18, and cytokines. In conclusion, B355252 demonstrates a potent anti-neuroinflammatory effect in vivo, suggesting that its potential therapeutic value warrants further investigation. Full article

Graphite, a critical raw material, prompts interest in assessing former quarries for volumetric content, driving the need for accurate prospection techniques. We explore the efficacy of spectral induced polarization (SIP) imaging at field scale for this purpose. Field measurements in a quarry with unknown graphite content underscore the need for assessment before drilling due to abrupt topography. Due to the lack of ground truth required to calibrate existing petrophysical models, we propose using SIP laboratory measurements to achieve the quantitative interpretation of the imaging results. We conducted experiments at two scales: rock plugs for material response and ground rocks of varying sizes for textural analysis. The rock plugs allow us to investigate the response of the material, while the ground samples permit us to understand changes in the SIP response for varying textural properties. Our lab work establishes power-law relationships between polarization (expressed in terms of normalized chargeability) and graphite content, as well as relaxation time and grain size. Salinity dependence is noted between chargeability, normalized chargeability, and relaxation time. Utilizing these findings, we provide a quantitative interpretation of field SIP imaging results. Full article

The unreasonable use of fertilizers is a significant cause of cultivated soil cadmium (Cd) accumulation. Although there is research about the effect of fertilizers on soil cadmium (Cd) accumulation under different crops, soils, and cultivation durations locally and specifically, its relative and determinant factors are seldom comprehensively and comparatively researched and evaluated. We used meta-analysis to analyze the effects of fertilizers (mineral fertilizer N, P, K (NPK) with manure (NPKM), NPK with straw (NPKS), and the mineral fertilizer N (N), NK (NK)), crops, duration, climate, and soil texture on the Chinese soil total and available Cd change during 1987–2022. The results showed that the order of the increased soil total and available Cd change was NPKM (total: 62%–104%, available: 61%–143%) > NPKS (50%–86%, 48%–116%) > NPK (25%–50%, 35%–75%) > NK (5%–19%, 19%–33%) > N (2%–6%, 7%–31%). NPKM and NPKS significantly increased the total Cd under maize (104%, 86%) and available Cd under rice (136%, 116%). Cd changed the fastest with the NPKM cultivation duration for total Cd under maize (slope: 5.9) and available Cd under rice (6.6). The change of the soil total and available Cd had the higher value in the semiarid region, clay soils, lower pH, and long cultivations. The change of the soil total and available Cd were highest (398%, 375%) in the semiarid region for clay loam after 20–25 years of NPKM fertilization, when the pH decreased to the lowest (−1.9). According to the aggregated boosted tree analysis, the fertilizers and duration were the best explanatory variable (>53%) for the soil total and available Cd. In conclusion, the soil Cd could be mitigated through reducing the long–term manure, straw, and P fertilizer content with Cd, and field managements such as liming, wetting, and drying according to the crops, climate, and soil texture. Full article

Rare earth elements (REEs) are essential raw materials for modern industries but mining them has caused severe environmental issues, particularly the recovery of heavy REEs (HREEs) from ion-adsorption deposits (IADs). Very recently, an emerging technology, electrokinetic mining (EKM), has been proposed for the green and efficient recovery of REEs from IADs. However, the conduction mechanism of the weathering crust soil, which is also a prerequisite for EKM, remains unclear, making the EKM process unpredictable. Here, we systematically investigated the conductivity of weathering crust soil in the presence of light REEs (LREEs, i.e., La³⁺ and Sm³⁺) and HREEs (Er³⁺ and Y³⁺), respectively. Results suggested that the voltage was dynamically and spatially redistributed by the movement of REEs and water during EKM, and the conventional assumption of the linear distribution of voltage leads to an inaccurate description of soil voltage. We proposed an improved Archie’s equation by coupling the mechanisms of liquid phase and solid-liquid interface conduction, which can predict soil conductivity more precisely. Moreover, the extended Archie’s equation is able to recalculate the voltage distribution at distinct times and spaces well during EKM. More importantly, the water content in field-scale weathered-crust soils can be retrieved by the newly proposed Archie’s equation, which helps optimize the leaching wells and improve the recovery rate of REE. This study focuses on the conduction mechanism of weathering crust soil, which provides a theoretical basis for better use of the EKM technology and promotes mining efficiency fundamentally. Full article

Ticks are involved in the transmission a plethora of pathogens. To effectively control ticks and mitigate the risks associated with tick-borne diseases, it is important to implement tick control measures. These may include the use of acaricides as well as the development and implementation of an alternative, environmentally friendly tick management program that include practices such as habitat modification or establishing biological control. Ixodiphagus hookeri Howard is a tick-specific parasitoid wasp that predates on several species of ixodid ticks and could contribute to the control of the tick population. This work aimed to detect the presence of parasitoid wasps in ticks (Ixodidae) using genetic approaches. Several tick species of the genera Ixodes, Haemaphysalis, and Dermacentor, with a sympatric occurrence in the Slovak Karst National Park in southeastern Slovakia, were screened for the presence of wasps of the genus Ixodiphagus. The DNA of the parasitoids was detected in four tick species from three genera. This work presents the first molecular detection of parasitoids in two Dermacentor tick species, as well as the first molecular identification of Ixodiphagus wasps in Ixodes ricinus and Haemaphysalis concinna ticks from the Karst area. In the given area, it was observed that I. ricinus and H. concinna ticks are hyper-parasitized by wasps. Moreover, it was observed that wasps here can parasitize several tick species, some of which are of less significance for human and animal health (as they transmit fewer pathogens). Full article

With the recent advent of research focusing on the body’s significance in music, the integration of physiological sensors in the context of empirical methodologies for music has also gained momentum. Given the recognition of covert muscular activity as a strong indicator of musical intentionality and the previously ascertained link between physical effort and various musical aspects, electromyography (EMG)—signals representing muscle activity—has also experienced a noticeable surge. While EMG technologies appear to hold good promise for sensing, capturing, and interpreting the dynamic properties of movement in music, which are considered innately linked to artistic expressive power, they also come with certain challenges, misconceptions, and predispositions. The paper engages in a critical examination regarding the utilisation of muscle force values from EMG sensors as indicators of physical effort and musical activity, particularly focusing on (the intuitively expected link to) sound levels. For this, it resides upon empirical work, namely practical insights drawn from a case study of music performance (Persian instrumental music) in the context of a music class. The findings indicate that muscle force can be explained by a small set of (six) statistically significant acoustic and movement features, the latter captured by a state-of-the-art (full-body inertial) motion capture system. However, no straightforward link to sound levels is evident. Full article

As the petroleum industry increasingly exploits unconventional reservoirs with low permeability and porosity, accurate predictions of post-fracture production are becoming critical for investment decisions, energy policy development, and environmental impact assessments. However, despite extensive research, accurately forecasting post-fracture production using well-log data continues to be a complex challenge. This study introduces a new method of data volume expansion, which is to subdivide the gas production of each well on the first day according to the depth of logging data, and to rely on the correlation model between petrophysical parameters and gas production to accurately combine the gas production data while matching the accuracy of the well-log data. Twelve pipelines were constructed utilizing a range of techniques to fit the regression relationship between logging parameters and post-fracture gas production These included data preprocessing methods (StandardScaler and RobustScaler), feature extraction approaches (PCA and PolynomialFeatures), and advanced machine learning models (XGBoost, Random Forest, and neural networks). Hyperparameter optimization was executed via GridSearchCV. To assess the efficacy of diverse models, metrics including the coefficient of determination (R2), standard deviation (SD), Pearson correlation coefficient (PCC), mean absolute error (MAE), mean squared error (MSE), and root-mean-square error (RMSE) were invoked. Among the several pipelines explored, the PFS-NN exhibited excellent predictive capability in specific reservoir contexts. In essence, integrating machine learning with logging parameters can be used to effectively assess reservoir productivity at multi-meter formation scales. This strategy not only mitigates uncertainties endemic to reservoir exploration but also equips petroleum engineers with the ability to monitor reservoir dynamics, thereby facilitating reservoir development. Additionally, this approach provides reservoir engineers with an efficient means of reservoir performance oversight. Full article