Cla4, an orthologous p21-activated kinase crucial for non-entomopathogenic fungal lifestyles, has two paralogs (Cla4A/B) functionally unknown in hypocrealean entomopathogens. Here, we report a regulatory role of Cla4A in gene expression networks of Beauveria bassiana required for asexual and entomopathogenic lifecycles while Cla4B is functionally redundant. The deletion of cla4A resulted in severe growth defects, reduced stress tolerance, delayed conidiation, altered conidiation mode, impaired conidial quality, and abolished pathogenicity through cuticular penetration, contrasting with no phenotype affected by cla4B deletion. In ∆cla4A, 5288 dysregulated genes were associated with phenotypic defects, which were restored by targeted gene complementation. Among those, 3699 genes were downregulated, including more than 1300 abolished at the transcriptomic level. Hundreds of those downregulated genes were involved in the regulation of transcription, translation, and post-translational modifications and the organization and function of the nuclear chromosome, chromatin, and protein–DNA complex. DNA-binding elements in promoter regions of 130 dysregulated genes were predicted to be targeted by Cla4A domains. Samples of purified Cla4A extract were proven to bind promoter DNAs of 12 predicted genes involved in multiple stress-responsive pathways. Therefore, Cla4A acts as a novel regulator of genomic expression and stability and mediates gene expression networks required for insect-pathogenic fungal adaptations to the host and environment. Full article

In this study, biochar derived from sewage sludge was applied to remediate Cu and Cd co-polluted soil in semi-arid areas for the first time, in which the effects of biochar on the improvement of soil physicochemical and biological properties as well as the immobilization of Cu and Cd were investigated. Soil water holding capacity increased by 0.22–2.74%, soil CEC increased by 0.52–4.06 units, soil SOM content increased by 1.41–5.97 times, and urease and catalase activities increased by 0.012–0.032 mg·g⁻¹·24 h⁻¹, 0.18–2.95 mg H₂O₂·g⁻¹, but soil pH increased only slightly by 0.69 units after biochar application. In addition, although the total content of these two metals in the soil increased with the use of biochar, the content of DTPA-Cu and Cd decreased by −0.128–0.291 mg/kg, 0–0.037 mg/kg, with the increase in biochar application, and the content of acid-soluble Cu in the soil decreased from 27.42 mg/kg to 3.76 mg/kg, the mobility and bioavailability of these two metals in the soil decreased. Finally, the complexation of organic functional groups with the soil dominates the immobilization process of metals, especially Cu. These findings suggest that biochar from sewage sludge can effectively improve soil quality and remediate heavy metal-contaminated soils in semi-arid regions. Meanwhile, the use of sludge-based biochar for the remediation of contaminated soils also provides a new method for the safe disposal of sewage sludge and a new way for sustainable development. In subsequent studies, methods such as modification are recommended to improve the efficiency of sludge-based biochar for the removal of Cu and Cd. Full article

Objectives: Cardiac telerehabilitation (TR) for coronary artery disease (CAD) is a feasible alternative to the center-based rehabilitation delivery model. However, the features of exercise-based cardiac TR are still heterogeneous among studies, making it difficult to disentangle the preferable reference strategies to be recommended for the adoption of this new delivery of care. In addition, little is known about the effectiveness of different models, such as the hybrid model (CRh) including both center-based and home-based telerehabilitation approaches, and the solely home-based telerehabilitation (CTR). Methods: We conducted a systematic review of randomized controlled trials (RCTs) that included TR intervention in patients with CAD to profile the features of the telerehabilitation approach for CAD. We also conducted a meta-analysis to separately assess the effectiveness of CTR and CRh on medical benefit outcome measures compared to conventional intervention (CI). Results: Out of 17.692 studies, 28 RCTs involving 2.662 CAD patients were included in the review. The studies presented an equal proportion of the CTR and CRh models. The interventions were mainly multidimensional, with a frequency of 1 month to 6 months, with each session ranging between 20 to 70 min. In CRh, the intervention was mainly consecutive to center-based rehabilitation. All studies adopted asynchronous communication in TR, mainly providing monitoring/assessment, decisions, and offline feedback. Few studies reported mortality, and none reported data about re-hospitalization or morbidity. Adherence to the CTR and CRh interventions was high (over 80%). The meta-analyses showed the superior effect of CTR compared to CI in exercise capacity. An overall noninferiority effect of both CTR and CRh compared to CI was found with factors including risk control and participation. Conclusions: The results of the review and meta-analyses indicated that CTR and CRh are equally effective, safe, convenient, and valid alternatives to cardiac conventional interventions. The evidence suggests that telerehabilitation may represent a valid alternative to overcome cardiac rehabilitation barriers. Full article

Detecting the crystal system of lithium-ion batteries is crucial for optimizing their performance and safety. Understanding the arrangement of atoms or ions within the battery’s electrodes and electrolyte allows for improvements in energy density, cycling stability, and safety features. This knowledge also guides material design and fabrication techniques, driving advancements in battery technology for various applications. In this paper, a publicly available dataset was utilized to develop mathematical equations (MEs) using a genetic programming symbolic classifier (GPSC) to determine the type of crystal structure in Li-ion batteries with a high classification performance. The dataset consists of three different classes transformed into three binary classification datasets using a one-versus-rest approach. Since the target variable of each dataset variation is imbalanced, several oversampling techniques were employed to achieve balanced dataset variations. The GPSC was trained on these balanced dataset variations using a five-fold cross-validation (5FCV) process, and the optimal GPSC hyperparameter values were searched for using a random hyperparameter value search (RHVS) method. The goal was to find the optimal combination of GPSC hyperparameter values to achieve the highest classification performance. After obtaining MEs using the GPSC with the highest classification performance, they were combined and tested on initial binary classification dataset variations. Based on the conducted investigation, the ensemble of MEs could detect the crystal system of Li-ion batteries with a high classification accuracy (1.0). Full article

The Transmission Control Protocol (TCP) serves as a cornerstone mechanism for implementing Congestion Control (CC) across the Internet. Designing a solution that provides high bandwidth utilization and mitigates the phenomenon of bufferbloat across a spectrum of diverse scenarios poses a considerable challenge. The introduction of Bottleneck Bandwidth and Round Trip propagation time (BBR) in 2016 marked a significant shift in congestion control methodology. Its improved performance and adaptability contributed to the initial acclaim and widespread interest that it received.. Unlike most currently used CCs, it operates around Kleinrock’s optimal point, thus offering high throughput even in lossy networks while preventing buffer saturation. Unfortunately, it quickly became evident that BBR was unable to fairly share bandwidth with flows characterized by different path delays, as well as loss-based CCs. In response, Google recently introduced a third iteration to address these shortcomings. This study explores the performance of BBRv3 across a wide range of scenarios, thereby considering different buffer sizes and paths with varying Round Trip Times (RTTs), and it evaluates its superiority over its predecessors. Through extensive simulations, this work assesses whether BBRv3 can finally play fair with other bandwidth contenders, which is a critical consideration given the widespread deployment of BBR. The framework is publicly available to facilitate additional validation and ensure the reproducibility of the study’s findings. The results indicate that while BBRv3 demonstrates enhanced fairness towards loss-based CC algorithms, it struggles when competing against other BBR flows, especially in multi-RTT networks, thus falling short even when compared to the initial version. Full article

Complex aviation systems’ integrity deteriorates over time due to operational factors; hence, the ability to forecast component remaining useful life (RUL) is vital to their optimal operation. Data-driven prognostic models are essential for system RUL prediction. These models benefit run-to-failure datasets the most. Thus, significant factors that could affect systematic integrity must be examined to quantify the operational component of RUL. To expand predictive approaches, the authors of this research developed a novel method for calculating the RUL of a group of aircraft engines using the N-CMAPSS dataset, which provides simulated degradation trajectories under real flight conditions. They offered bootstrap trees and hyperbolic tangent NtanH(3)Boost(20) neural networks as prognostic alternatives. The hyperbolic tangent boosted neural network uses damage propagation modelling based on earlier research and adds two accuracy levels. The suggested neural network architecture activates with the hyperbolic tangent function. This extension links the deterioration process to its operating history, improving degradation modelling. During validation, models accurately predicted observed flight cycles with 95–97% accuracy. We can use this work to combine prognostic approaches to extend the lifespan of critical aircraft systems and assist maintenance approaches in reducing operational and environmental hazards, all while maintaining normal operation. The proposed methodology yields promising results, making it suitable for adoption due to its relevance to prognostic difficulties. Full article

The aim of this study was to analyse the cytotoxicity of heavy metals (HMs) and nanoparticles (NPs) on populations of the ciliated protist Euplotes aediculatus. We used ecotoxicological tests, antioxidant assays, and the MixTOX tool in Microsoft^® Excel to evaluate the toxic effect of HMs and NPs in single and binary mixtures on E. aediculatus and to detect the type of interaction between them. Based on our results, the order of toxicity was Cu > Cd >> Zn (1 h and 24 h) for HMs and ZnO > CuO >> TiO₂ >> SiO₂ (1 h) and CuO > ZnO >> TiO₂ >> SiO₂ (24 h) for NPs. The interaction between metals in binary mixtures was predominantly synergistic at low doses and antagonistic at high doses. The type of interaction depende on the metals present and their respective concentrations. Furthermore, both HMs and NPs were shown to trigger effective antioxidant responses in E. aediculatus. Our research highlights the importance of considering the combined effects of HMs and NP exposure and their potency in risk assessment. Full article

As urbanization continues to pose new challenges for cities around the world, the concept of smart cities is a promising solution, with artificial intelligence (AI) playing a central role in this transformation. This paper presents a literature review of AI solutions applied in smart cities, focusing on its six main areas: smart mobility, smart environment, smart governance, smart living, smart economy, and smart people. The analysis covers publications from 2021 to 2024 available on Scopus. This paper examines the application of AI in each area and identifies barriers, advances, and future directions. The authors set the following goals of the analysis: (1) to identify solutions and applications using artificial intelligence in smart cities; (2) to identify the barriers to implementation of artificial intelligence in smart cities; and (3) to explore directions of the usage of artificial intelligence in smart cities. Full article

Accurately segmenting grape clusters and detecting grape varieties in orchards is beneficial for orchard staff to accurately understand the distribution, yield, growth information, and efficient mechanical harvesting of different grapes. However, factors, such as lighting changes, grape overlap, branch and leaf occlusion, similarity in fruit and background colors, as well as the high similarity between some different grape varieties, bring tremendous difficulties in the identification and segmentation of different varieties of grape clusters. To resolve these difficulties, this study proposed an improved Mask R-CNN model by assembling an efficient channel attention (ECA) module into the residual layer of the backbone network and a dual attention network (DANet) into the mask branch. The experimental results showed that the improved Mask R-CNN model can accurately segment clusters of eight grape varieties under various conditions. The bbox_mAP and mask_mAP on the test set were 0.905 and 0.821, respectively. The results were 1.4% and 1.5% higher than the original Mask R-CNN model, respectively. The effectiveness of the ECA module and DANet module on other instance segmentation models was explored as comparison, which provided a certain ideological reference for model improvement and optimization. The results of the improved Mask R-CNN model in this study were superior to other classic instance segmentation models. It indicated that the improved model could effectively, rapidly, and accurately segment grape clusters and detect grape varieties in orchards. This study provides technical support for orchard staff and grape-picking robots to pick grapes intelligently. Full article

Classifying grapevine varieties is crucial in precision viticulture, as it allows for accurate estimation of vineyard row growth for different varieties and ensures authenticity in the wine industry. This task can be performed with time-consuming destructive methods, including data collection and analysis in the laboratory. In contrast, unmanned aerial vehicles (UAVs) offer a markedly more efficient and less restrictive method for gathering hyperspectral data, even though they may yield data with higher levels of noise. Therefore, the first task is the processing of these data to correct and downsample large amounts of data. In addition, the hyperspectral signatures of grape varieties are very similar. In this study, we propose the use of a convolutional neural network (CNN) to classify seventeen different varieties of red and white grape cultivars. Instead of classifying individual samples, our approach involves processing samples alongside their surrounding neighborhood for enhanced accuracy. The extraction of spatial and spectral features is addressed with (1) a spatial attention layer and (2) inception blocks. The pipeline goes from data preparation to dataset elaboration, finishing with the training phase. The fitted model is evaluated in terms of response time, accuracy and data separability and is compared with other state-of-the-art CNNs for classifying hyperspectral data. Our network was proven to be much more lightweight by using a limited number of input bands (40) and a reduced number of trainable weights (560k parameters). Hence, it reduced training time (1 h on average) over the collected hyperspectral dataset. In contrast, other state-of-the-art research requires large networks with several million parameters that require hours to be trained. Despite this, the evaluated metrics showed much better results for our network (approximately 99% overall accuracy), in comparison with previous works barely achieving 81% OA over UAV imagery. This notable OA was similarly observed over satellite data. These results demonstrate the efficiency and robustness of our proposed method across different hyperspectral data sources. Full article

Anaplastic thyroid cancer (ATC) is a rare but highly aggressive malignancy characterized by advanced disease at diagnosis and a poor prognosis. Despite multimodal therapeutic approaches that include surgery, radiotherapy, and chemotherapy, an optimal treatment strategy remains elusive. Current developments in targeted therapies and immunotherapy offer promising avenues for improved outcomes, particularly for BRAF-mutant patients. However, challenges remain regarding overcoming drug resistance and developing effective treatments for BRAF-wild-type tumors. This comprehensive review examines the clinical and biological features of ATC, outlines the current standards of care, and discusses recent developments with a focus on the evolving role of radiotherapy. Moreover, it emphasizes the necessity of a multidisciplinary approach and highlights the urgent need for further research to better understand ATC pathogenesis and identify new therapeutic targets. Collaborative efforts, including large-scale clinical trials, are essential for translating these findings into improved patient outcomes. Full article

Research on the microbiome has progressed from identifying specific microbial communities to exploring how these organisms produce and modify metabolites that impact a wide range of health conditions, including gastrointestinal, metabolic, autoimmune, and neurodegenerative diseases. This review provides an overview of the bacteria commonly found in the intestinal tract, focusing on their main functional outputs. We explore biomarkers that not only indicate a well-balanced microbiota but also potential dysbiosis, which could foreshadow susceptibility to future health conditions. Additionally, it discusses the establishment of the microbiota during the early years of life, examining factors such as gestational age at birth, type of delivery, antibiotic intake, and genetic and environmental influences. Through a comprehensive analysis of current research, this article aims to enhance our understanding of the microbiota’s foundational development and its long-term implications for health and disease management. Full article

The widespread use of novel psychoactive substances (NPSs)—defined as new narcotic or psychotropic agents not classified under the Single Convention on Narcotic Drugs of 1961 or the Convention on Psychotropic Substances of 1971—poses a significant challenge to contemporary mental health paradigms due to their impact on psychiatric disorders. This study revisits and expands upon the theory of mental automatism as proposed by Gaëtan Gatian de Clérambault, aiming to elucidate the psychopathological mechanisms underlying substance-induced psychoses (SIP) and their distinction from non-induced psychoses (schizophrenia and related disorders). Through a phenomenological and clinical investigation, we explore the relevance of mental automatism in the development of toxic psychoses, drawing upon the historical and contemporary literature. This research highlights the psychopathological distinctions between induced and non-induced psychoses and the transition mechanisms from acute to chronic psychosis states. De Clérambault’s theory, supplemented by Janet, Jackson, and Bonhoeffer’s contributions, provides a foundational framework for understanding the genesis of SIP. Our findings suggest that NPS consumption, particularly among adolescents and psychiatric patients, significantly correlates with increased risks of SIP, marked by a transition to chronicity influenced by biological lesions triggered by substance use. Furthermore, we propose a comprehensive framework for SIP, integrating mental automatism, psychopathological distinctions, and transition mechanisms. This framework aims to refine diagnostic criteria and therapeutic approaches, addressing gaps in clinical practice and research. The study underscores the need for a nuanced understanding of SIP, advocating for a paradigm shift in psychiatric assessment and treatment approaches to better address the complexities of substance-induced mental health disorders. Full article

Expression of microRNAs, such as miR-365, is known to be dysregulated in many tumors, including oral cancers, although little is known about their role or functions. The objective of this project is to evaluate the downstream targets of miR-365 to determine any potential pathways or effects. Downstream targets for miR-365 (miRdatabase target scores >90) were used for qPCR screening of oral cancer cell lines (SCC4, SCC9, SCC15, SCC25, CAL27). Each oral cancer cell line expressed miR-365 downstream targets molybdenum cofactor synthesis-2 (MOCS2), erythropoietin receptor (EPOR), IQ motif containing-K (IQCK), carboxypeptidase A3 (CPA3), solute carrier family 24 member-3 (SLC24A3), and coiled-coil domain containing 47 (CCDC47)—although the expression levels varied somewhat. However, differential results were observed with ubiquitin protein ligase E3 component n-recognin-3 (UBR3), nudix hydrolase-12 (NUDT12), zinc finger CCHC-type containing-14 (ZCCHC14), and homeobox and leucine zipper encoding (HOMEZ). These data suggest that many of the miR-365 targets are expressed in the oral cancers screened, with the differential expression of UBR3, ZCCHC14, HOMEZ, and NUDT12, which may be correlated with chemoresistance among two specific oral cancer cell lines (SCC25, SCC9). These results suggest this differential expression may signal potential targets for patient treatment with tumors exhibiting miR-365 and chemotherapeutic resistance. Full article

Chronic liver disease is one of the main causes of morbidity and mortality in people living with HIV (PLWH). The increasing life expectancy of PLWH, effective treatment for viral hepatitis, and Western dietary patterns as well as the adverse effects of antiretroviral therapy (ART) have rendered metabolic dysfunction-associated steatotic liver disease (MASLD) the most common chronic liver disease in PLWH. The risk factors for MASLD in PLWH include traditional MASLD risk factors and additional virus-specific factors, including the adverse effects of ART. The management of patients suffering from HIV and MASLD is often challenging. Apart from the conventional management of MASLD, there are also certain limitations concerning the use of ART in this patient population. In general, the appropriate combination of antiretroviral drugs should be chosen to achieve the triad of effective viral suppression, avoidance of mitochondrial dysfunction, and deterrence of worsening the patient’s metabolic profile. In the current review, we discuss the epidemiology of MASLD in PLWH, the risk factors, and the disease pathogenesis, as well as the limitations in the use of ART in this patient population, while practical recommendations on how to overcome these limitations are also given. Full article

Modern electric motors developed for the automotive industry have an ever higher power density with a relatively compact size. Among the various existing solutions to improve torque and power density, a reduction in the dimensions of the end-windings has been explored, aiming to decrease volume, weight, and losses. However, more compact end-windings often lead to complex shapes of the conductors, especially when preformed hairpin windings are considered. The rectangular cross-section of hairpin conductors makes them prone to deviating out of the bending plane during the forming process. This phenomenon, known as torsional–flexural instability, is influenced by the specific aspect ratio of the cross-section dimensions and the bending direction. This study focuses on understanding this instability phenomenon, aiming to identify a potential threshold of the cross-section aspect ratio. The instability makes it difficult to predict the final geometry, potentially compromising the compliance with the geometric tolerances. A finite element model is developed to analyse a single planar bend in a hairpin conductor. Various cross-section dimensions with different aspect ratios are simulated identifying those that experience instability. Moreover, an experimental campaign is conducted to confirm the occurrence of instability by testing the same single planar bending. The experimental data obtained are used to validate the finite element model for the tested dimensions. The aim is to provide designers with a useful tool to select hairpin geometries that are more suitable for the folding process, contributing to successful assembly and improving the overall design process of preformed hairpin conductors. Full article

Achromobacter insolitus and Achromobacter aegrifaciens, bacterial degraders of the herbicide glyphosate, were found to induce phosphonatase (phosphonoacetaldehyde hydrolase, EC 3.11.1.1) when grown on minimal media with glyphosate as the sole source of phosphorus. The phosphonatases of the strains were purified to an electrophoretically homogeneous state and characterized. The enzymes differed in their kinetic characteristics and some other parameters from the previously described phosphonatases. The phosphonatase of A. insolitus was first revealed to separate into two stable forms, which had similar kinetic characteristics but interacted differently with affinity and ion-exchange resins. The genomes of the investigated bacteria were sequenced. The phosphonatase genes were identified, and their context was determined: the bacteria were shown to have gene clusters, which, besides the phosphonatase operon, included genes for LysR-type transcription activator (substrate sensor) and putative iron-containing oxygenase PhnHD homologous to monooxygenases PhnY and TmpB of marine organophosphonate degraders. Genes of 2-aminoethylphosphonate aminotransferase (PhnW, EC 2.6.1.37) were absent in the achromobacterial phosphonatase operons; instead, we revealed the presence of genes encoding the putative flavin oxidase HpnW. In silico simulation showed 1-hydroxy-2-aminoethylphosphonate to be the most likely substrate of the new monooxygenase, and a number of glycine derivatives structurally similar to glyphosate to be substrates of flavin oxidase. Full article

The sweetpotato whitefly, Bemisia tabaci MEAM1, is a pest known to significantly impact tomato development and yields through direct damage and virus transmission. To manage this pest, the current study compared the effectiveness of various insecticide rotations. Field trials included rotations involving synthetic insecticides, biochemicals, and microbial agents, applied according to their highest labeled concentrations. The results indicated that while standard synthetic insecticides consistently reduced whitefly egg and nymph counts significantly, microbial biopesticide rotations also achieved reductions, although less consistently. This study demonstrated that while traditional chemical treatments remain highly effective, microbial biopesticides containing Beauveria bassiana and Cordyceps javanica present a viable alternative to manage MEAM1 in tomato fields. The data generated in this study provided baseline information for further investigations to determine the potential for optimizing integrated pest management (IPM) and insecticide resistance management (IRM) strategies by incorporating microbial biopesticides in rotations with a variety of modes of action to sustainably manage B. tabaci MEAM1 populations in agricultural settings. Full article

Artificial corner reflectors are widely used in the vegetated landslide for time series InSAR monitoring due to their permanent scattering features. This paper investigated the RCS features of a novel dihedral CR under multi-resource SAR datasets. An RCS reduction model for the novel dihedral corner reflector has been proposed to evaluate the energy loss caused by the deviation between the SAR incident angle and the CR’s axis. On the Huangtupo slope, Badong county, Hubei province, tens of dihedral CRs had been installed and the TSX–spotlight and Sentinel-TOPS data had been collected. Based on the observation results of CRs with more than ten deviation angles, the proposed reduction model was tested with preferable consistency under a real dataset, while 2 dBsm of systematic bias was verified in those datasets. The maximum incident angle deviation in the Sentinel data overlapping area is over 12°, which leads to a 2.4 dBsm RCS decrease for horizontally placed dihedral CRs estimated by the proposed model, which has also been testified by the observed results. The testing results from the Sentinel data show that in high, vegetation-covered mountain areas like the Huangtupo slope, the dihedral CRs with a 0.4 m slide length can be achieve 1 mm precision accuracy, while a side length of 0.2 m can achieve the same accuracy under TSX–spotlight data. Full article

This paper proposes a temperature-adaptive radiative cooling (TARC) coating with simple preparation, cost effectiveness, and large-scale application based on a thermochromic powder. To determine the energy efficiency of the proposed TARC coating, the heat transfer on the surface of the TARC coating was analyzed. Then, a typical two-story residential building with a roof area of 258.43 m² was modeled using EnergyPlus. Finally, the energy-saving potential and carbon emission reduction resulting from the application of the proposed TARC roof in buildings under different climates in China were discussed. The results showed that the average solar reflectivity under visible light wavelengths (0.38–0.78 μm) decreases from 0.71 to 0.37 when the TARC coating changes from cooling mode to heating mode. Furthermore, energy consumption can be reduced by approximately 17.8–43.0 MJ/m² and 2.0–32.6 MJ/m² for buildings with TARC roofs compared to those with asphalt shingle roofs and passive daytime radiative cooling (PDRC) roofs, respectively. This also leads to reductions in carbon emissions of 9.4–38.0 kgCO₂/m² and 1.0–28.9 kgCO₂/m² for the buildings located in the selected cities. To enhance building energy efficiency, TARC roofs and PDRC roofs are more suitable for use on buildings located in zones with high heating demands and high cooling demands, respectively. Full article

In this study, six different animal models were fitted, and the constrained maximum likelihood method was used to assess the genetic parameters and genetic trends of early growth traits in Luzhong mutton sheep. The experimental data of this study included the newborn weight (BWT, N = 2464), weaning weight (WWT, N = 2923), weight at 6 months of age (6WT, N = 2428), average daily weight gain from birth to weaning (ADG1, N = 2424), and average daily weight gain from weaning to 6 months of age (ADG2, N = 1836) in Luzhong mutton sheep (2015~2019). The best model for the genetic parameters of the five traits in Luzhong mutton sheep was identified as Model 4 using the Akaike information criterion (AIC) and likelihood ratio test (LRT) methods, in which the estimated values of direct heritability for the BWT, WWT, 6WT, ADG1, and ADG2 were 0.156 ± 0.057, 0.547 ± 0.031, 0.653 ± 0.031, 0.531 ± 0.035, and 0.052 ± 0.046, respectively, and the values for maternal heritability were 0.201 ± 0.100, 0.280 ± 0.047, 0.197 ± 0.053, 0.275 ± 0.052, and 0.081 ± 0.092, respectively. The genetic correlation between the ADG2 and WWT was negative, and the genetic and phenotypic correlations among the remaining traits were positive. In this study, maternal effects had a more significant influence on early growth traits in Luzhong mutton sheep. In conclusion, to effectively improve the accuracy of genetic parameter estimation, maternal effects must be fully considered to ensure more accurate and better breeding planning. Full article

This paper presents a new layered plaster-based material for building purposes. First, a new manufacturing machine was designed to make the elaboration process easier. This manufacturing machine and the way it works are described. In this study, perlite and recycled glass wool (RGW) were added to traditional plaster with the aim of improving the performance of this material. Two series (with and without perlite) and three different layer configurations were developed and assessed. Recycled glass wool layered materials were subjected to both physical and mechanical characterisation to determine their suitability for precast elaboration. The addition of perlite resulted in a significant improvement in flexural strength. Moreover, the addition of RGW also gave rise to extra flexural strength when added. The two-layered samples performed better than the one-layered samples. Mechanical properties increased up to 75% when both the perlite and RGW layers were added. Potential Global Warming Potential (GWP 100) savings were also analysed, reporting up to 49% savings. A complementary cost analysis was performed, aimed at establishing potential savings in production costs; thus, 13–57% potential cost savings were reported. After that, a comparative analysis within the literature was conducted to contextualise the results obtained in this study. Full article