The chalkiness, starch fine structure, and physiochemical properties of rice starch were analyzed and their correlations were investigated under different nighttime temperatures during the early grain-filling stage. Compared to MT, medium temperature (MT) and low (LNT) and high (HNT) nighttime temperatures resulted in an increased chalky grain rate (CGR) and chalkiness degree (CD). LNT mainly affected the chalkiness by increasing peak1 (short branch chains of amylopectin), the branching degree, and the proportion of small starch granules but decreasing peak2 (long branch chains of amylopectin) and peak3 (amylose branches). This altered the pasting properties, such as by increasing the peak viscosity and final viscosity. However, HNT mainly affected the chalkiness by increasing peak2 and the crystallinity degree but decreasing peak1 and peak3. Regarding the thermal properties, HNT also elevated peak and conclusion temperatures. The CGR and CD were significantly and positively correlated with the proportions of small and medium starch granules, peak1, branching degree, gelatinization enthalpy, setback viscosity, and pasting time but markedly and negatively correlated with the proportion of large starch granules, amylose content, peak3, peak viscosity, and breakdown viscosity. These findings suggest that LNT and HNT disrupted the starch structure, resulting in increased chalkiness. However, their mechanisms of action differ. Full article

Bending analysis was carried out for a laminated composite porous plate due to sinusoidal loading with various boundary conditions using improved third-order theory. Zero transverse shear stress provided a free surface at the top and bottom of the plate. Also, the authors developed a finite element formulation based on improved third-order shear deformation theory. To circumvent the C1 continuity requirement associated with improved third-order shear deformation theory, a C0 FE formulation was developed by replacing the out-of-plane derivatives with independent field variables. An in-house FORTRAN code was developed for the bending analysis of the laminated porous plate considering a 2D finite element model. The complete thickness of the plate was covered with different porosity patterns. The impacts of various modulus ratios, boundary conditions, thickness ratios, fiber orientation angles, and material parameters were examined for laminated porous plates. There was an 18.8% reduction in deflection in the case of the square plate as compared to rectangular plates, with a porosity value of 0.1, a thickness ratio of 10, and an orientation angle of 0°/90°/0°. According to the current research, adding porosities causes a relatively greater change in deflection rather than stress, thereby aiding in the development of a lightweight structure. Full article

Online anomaly detection is critical for industrial safety and security monitoring but is facing challenges due to the complexity of evolving data streams from working conditions and performance degradation. Unfortunately, existing approaches fall short of such challenges, and these models may be disabled, suffering from the evolving data distribution. The paper presents a framework for online anomaly detection of data streams, of which the baseline algorithm is the incremental learning method of Growing Neural Gas (GNG). It handles complex and evolving data streams via the proposed model Bayes-Optimized Adaptive Growing Neural Gas (BOA-GNG). Firstly, novel learning rate adjustment and neuron addition strategies are designed to enhance the model convergence and data presentation capability. Then, the Bayesian algorithm is adopted to realize the fine-grained search of BOA-GNG-based hyperparameters. Finally, comprehensive studies with six data sets verify the superiority of BOA-GNG in terms of detection accuracy and computational efficiency. Full article

This work presents a retrospective analysis of indoor CO₂ measurements obtained with a mobile robot in an educational building after the COVID-19 lockdown (May 2021), at a time when public activities resumed with mandatory local pandemic restrictions. The robot-based CO₂ measurement system was assessed as an alternative to the deployment of a net of sensors in a building in the pandemic period, in which there was a global stock outage of CO₂ sensors. The analysis of the obtained measurements confirms that a mobile system can be used to obtain interpretable information on the CO₂ levels inside the rooms of a building during a pandemic outbreak. Full article

Antibiotics play a crucial role in preserving and improving public health, saving millions of lives every year. However, their effectiveness is currently under threat due to the ability of bacteria to adapt and develop resistance to these treatments. Therefore, this study was carried out on two soil samples collected in two areas of Arba Aounate, Sidi Bennour province, Morocco, to identify natural antibiotic-producing Actinobacteria capable of combating multi-drug-resistant (MDR) bacteria. A primary screening revealed that of the 50 isolates, 16 exhibited antimicrobial activity against Pseudomonas aeruginosa ATCC 27,853, Staphylococcus aureus ATCC 25,923, Escherichia coli ATCC 25,922, and Candida albicans ATTC 60193. A secondary screening showed that of the 16 isolates, only EIZ1 and EIZ2 isolates displayed outstanding antimicrobial and antifungal activity against 6 MDR bacteria, including Escherichia coli 19L2418, Listeria monocytogenes, Proteus sp. 19K1313, Klebsiella pneumoniae 19K 929, Proteus vulgaris 16C1737, and Klebsiella pneumoniae 20B1572. These two isolates were also characterized culturally, morphologically, physiologically, and biochemically. Afterward, the amplification of 16S rRNA revealed that isolate EIZ2 was 99.06% strongly related to the genus Streptomyces. Furthermore, this extract exhibits strong antioxidant activity against DPPH and ABTS free radicals and elevated ferric-reducing antioxidant power. A significant (p < 0.0001) positive correlation was observed between antioxidant activities and total phenolic and flavonoid contents. A GC–MS analysis of the ethyl acetate extract revealed the presence of 10 compounds, mainly diethyl phthalate (97%) and benzeneacetic acid (94%). This research demonstrates that Streptomyces sp. strain EIZ2 represents a potential source of antimicrobial and antioxidant compounds. These compounds could offer considerable potential as therapeutic agents, paving the way for future developments in medical applications. Full article

According to current Brazilian regulations, if the volumes of oil produced used as a reference for the payment of government shares and third parties contain a water content greater than 2% v/v, these volumes must be arbitrarily increased between 1.44% and 10.89% due exclusively to water content, which has caused operational problems for oil companies such as differences between volumes produced and volumes sold, and additional payments from government shares and third parties. This study aimed to evaluate the metrological performance of oil measurement systems with ultrasonic, Coriolis and positive displacement flow meters when subjected to varied water content, fluid temperature and flow rate conditions using the Design of Experiments and the Response Surface Methodology. The analysis of variance showed that the models presented good fits for the ultrasonic meter (coefficient of determination R² of 97.96%, p-value of 0.001, and a standard deviation of 5.89 × 10⁻⁵); Coriolis meter (R² of 90.91%, p-value of 0.037, and a standard deviation of 5.88 × 10⁻⁵); and positive displacement meter (R² of 99.07%, p-value of 0.000, and a standard deviation of 4.85 × 10⁻⁵). The results of the experiments carried out indicate that the contribution of each parameter analyzed to the metrological performance of the measurement system varies depending on the measurement technology used by the flow meter. However, the fluid temperature proved to be a relevant parameter common to all flow measurement technologies evaluated. All measuring technologies evaluated were influenced by water content in the range of 0% to 10% v/v, with the measurement error being less than 0.2% when compared to a standard positive displacement type meter in almost all experimental conditions. The Coriolis-type flow meter was the one that presented the smallest error among the measuring technologies evaluated. Full article

This study aimed to evaluate the DSP method’s applicability to Romania’s contemporary population and to assess the accuracy and reliability of variables derived from CT images. A total of 80 pelvic CT scans were analyzed. Participants ranged from 22 to 93 years, with a mean age of 59.51 ± 22.7 years. All variables measured from the CT scans were analyzed using DSP software. The study found that sex estimation was possible in 71.25% of cases overall, with varying rates between males (57.50%) and females (85%). Despite encountering undetermined specimens comprising 42.5% males and 15% females, only one misclassification occurred. Regarding accuracy, the overall rate remained notably high at 98.24%. All female specimens that could be estimated were correctly classified (100% accuracy), while for males, the accuracy rate was 95.65%. Undetermined cases were noted to potentially impact the accuracy of sex classification, underscoring the critical role of precision in forensic contexts. In conclusion, the study highlights the importance of accuracy in forensic sex estimation. It emphasizes the confidence with which DSP software can be utilized, if not the only method, at least as a preliminary or adjuvantly accurate technique for sex estimation in forensic anthropology. Full article

This study focuses on mitigating the decrease in the quality of mulberry after harvest and increasing the value of mulberry products through microwave vacuum drying. The effects of mulberry moisture content on texture properties were investigated, and the test method was optimized through the membership function model and the central composite technique. The influences of the material surface temperature, vacuum degree, and microwave power on the quality of instant mulberry were analyzed comprehensively. A regression model was established to analyze the relationship between each test factor and quality index. The results show that, with increases in the moisture content, both the hardness and chewiness of mulberry present a decreasing trend; when elasticity increases gradually, adhesivity is presented in an inverted V-shaped variation trend, and the cohesiveness remains basically constant. Moreover, the moisture content of mulberry had significant correlations with elasticity, glueyness, chewiness, and hardness (R² > 0.9). When the moisture content of the samples reached ≤44.07%, the total plate count reached a minimum and changed gradually; thus, the moisture content (44.07%) of mulberry was determined for the technological optimization test. The combination of optimal technological parameters was as follows: material surface temperature = 51.0 °C, vacuum degree = 0.07 MPa, and microwave power = 370 W. Under these optimal technological parameters, the soluble solid content was 42.37%, chewiness was 9.08, and the Vc content was 0.725 mg·(100 g)⁻¹. The average error between the test results and software optimization parameters was 5.88%. The optimized microwave vacuum drying technological parameters improved the drying quality of mulberry significantly. The results can provide theoretical support for the microwave vacuum drying of berries. Full article

With the rapid development of data science, digital technology is integrating deeply with enterprise management, driving companies towards digital transformation to achieve sustainable development. However, digital transformation is a systematic and comprehensive process, posing challenges in accurately depicting firm-level digitalization. Hence, this study systematically reviews measurement methods for digital transformation across various themes related to enterprise digitalization. Existing literature predominantly employs questionnaire analysis, quantitative statistics, and text analysis to gauge the extent of digital transformation. In terms of indicator construction, existing literature mainly relies on input, process, and outcome variables to construct measurement indicators. Nevertheless, due to the subjectivity of questionnaires, the uniqueness of industry data, and the limitations of textual information, these methods and the indicators derived from them possess distinct applicability scopes. Refining the measurement of digital transformation should hinge on both the research objectives and the characteristics of the data. Furthermore, through the analysis of industry cases such as agriculture, manufacturing and service industries, this study also reveals the unique characteristics encountered by these industries in the process of digital transformation, provides a more detailed summary of measurement methods for these specific industries, and emphasizes the importance of selecting measurement methods according to industry characteristics. Full article

This paper presents the first assessment of dietary exposure to aflatoxin M1 (AFM1) and associated health risks through milk and dairy product consumption in Armenia. Data on AFM1 in raw milk were obtained from an annual residue monitoring program. Additionally, commonly consumed dairy products (pasteurized milk, cheese, sour cream, curd cheese) were sampled, considering the sources of raw milk used by dairy companies. Per capita consumption of raw milk was sourced from national food balance databases, while individual consumption data for dairy products was collected via a 24 h recall survey with 1400 adult respondents. Detectable levels of AFM1 were observed in 7.14% of raw milk samples (up to 0.334 μg/kg) and, albeit at lower amounts (up to 0.009 µg/kg), in 30% and 40% of sour cream and curd cheese, respectively. The AFM1 levels were lower than the national maximum permitted level (0.5 μg/kg); however, levels in raw milk exceeded the EU ML (0.05 μg/kg). The estimated margin of exposure values for dairy products indicated no significant risk, whereas a reasonable worst-case estimate, using the measurable levels of AFM1 in raw milk consumption indicated a potential public health concern. This study provides a scientific basis for evaluating aflatoxin issues in the Caucasus area. Full article

Despite their popularity, the construction and operation of hydropower reservoirs pose challenges to water resources. This study investigated the impacts of cascading dams on streamflow in Tanzania’s Rufiji River Basin. The SWAT model was developed to represent the entire Rufiji River Basin. The model simulated the streamflow for 41 years, from 1982 to 2022, and developed two main scenarios: with-dam and without-dam. To capture the influence of all dams, the results were emphasized from 2000 to 2022, when all three dams were operating. Calibration and validation were applied at the Rufiji-Stiegler and Kilombero-Swero stations with good performance. The results show that cascading dams annually decrease the streamflow by 1% at Rufiji-Stiegler station. In contrast, individually, the Mtera Dam displayed a 5% decrease while the Kidatu and Kihansi Dams exerted a 1% increase on the annual streamflow downstream at Rufiji-Stiegler. During 2000–2022, the Rufiji River Basin showed an annual reduction in streamflow contribution of 104.97 m³/s. Therefore, the reservoir’s operation significantly impacts the downstream streamflow. The findings are expected to guide policymakers, water resource managers, and environmentalists in mitigating potential adverse effects while optimizing the benefits of hydropower generation and water regulation within the region. Full article

Electronically Assisted Astronomy is a fascinating activity requiring suitable conditions and expertise to be fully appreciated. Complex equipment, light pollution around urban areas and lack of contextual information often prevents newcomers from making the most of their observations, restricting the field to a niche expert audience. With recent smart telescopes, amateur and professional astronomers can capture efficiently a large number of images. However, post-hoc verification is still necessary to check whether deep sky objects are visible in the produced images, depending on their magnitude and observation conditions. If this detection can be performed during data acquisition, it would be possible to configure the capture time more precisely. While state-of-the-art works are focused on detection techniques for large surveys produced by professional ground-based observatories, we propose in this paper several Deep Learning approaches to detect celestial targets in images captured with smart telescopes,with a F1-score between 0.4 and 0.62 on test data, and we experimented them during outreach sessions with public in Luxembourg Greater Region. Full article

Nuclear fusion is understood as an energy reaction that does not emit greenhouse gases, and it has been considered as a long-term source of low-carbon electricity that is favourable to curtail rapid climate change. Fusion offers a pathway to resolve energy security and the unequal distribution of energy resources since seawater is its ultimate fuel source and a few grams of fuel can generate mega kilowatts of power. The development and testing of new materials and technologies are unceasing to achieve the net fusion energy through national and international collaboration as well as private partnerships. The ever-growing number of research works report various designs and magnet-based fusion devices, such as stellarators, lasers, and tokamaks. This article provides an overview on the utilization of nuclear energy as a clean energy source, as well as the strategies and progress towards establishing successful commercial fusion energy to the grid and transition to a reliable clean energy source. The overview focuses on the fusion nuclear development in five major countries, UK, US, China, Japan, and Russia. Identified technical and financial challenges are also described at the end of this article. The International Thermonuclear Experimental Reactor (ITER) has been an international reference program for fusion energy development and most developed countries with nuclear development capacity are aiming to complete their in-house fusion energy facilities in parallel to ITER. Many fusion programs are finishing the conceptual design and shifting into the phase of engineering design for the planned DEMO fusion facilities. The significant challenges were identified from the perspective of device efficiency and robustness, sustainable funding, and facility maintenance and safety, which must be addressed diligently to realize fusion energy as alternative clean energy that mitigates climate change and supports the goals of energy security. Full article

As a functional extraction medium, natural deep eutectic solvents (NADESs) can dissolve various plant metabolites. Those solvents provide untapped potential for creating novel green extracts with distinctive phytochemical signatures and unique biological activities. This is particularly relevant given the rising need for eco-friendly and sustainable skin care products. The main aim of this work was to optimize the most efficient natural deep eutectic solvents (NADESs) for extracting bioactives from 18 medicinal herbs applicable to the cosmetic industry. Selection of the most potent herbs involved assessing their conventional extracts for tyrosinase inhibition, antioxidant activity, and keratinocyte cytotoxicity. Moreover, we analyzed the phenolic profile using ultra-high-pressure liquid chromatography/mass spectrometry (UHPLC/MS) and spectrophotometric assays such as total phenolic (TPC) and flavonoid content (TFC). Using the COSMO-RS method, we modeled the solubility of 12 phenolics in 64 virtual NADESs and selected the 7 most promising ones for further experimental validation. NADESs, including betaine-urea, betaine-proline, and betaine-lysine, were computationally chosen and demonstrated the highest levels of TPC and antioxidative capacity, as confirmed by in vitro assays. The proposed combination of NADES herbal extracts represents a promising natural constituent for the cosmetic industry. Full article

Situation awareness (SA) describes an individual’s understanding of their surroundings and actions in the near future based on the individual’s comprehension and understanding of the surrounding inputs. SA measurements can be applied to improve system performance or human effectiveness in many fields of study, including driving. However, in some scenarios drivers might need to drive in unfamiliar traffic regulations (UFTRs), where the traffic rules and vehicle configurations are a bit different from what the drivers are used to under familiar traffic regulations. Such driving conditions require drivers to adapt their attention, knowledge, and reactions to safely reach the destination. This ability is influenced by the degree of handedness. In such tasks, mixed-/left-handed people show better performance than strong right-handed people. This paper aims to explore the influence of the degree of handedness on SA when driving under UFTRs. We analyzed the SA of two groups of drivers: strong right-handed drivers and mixed-/left-handed drivers. Both groups were not familiar with driving in keep-left traffic regulations. Using a driving simulator, all participants drove in a simulated keep-left traffic system. The participants’ SA was measured using a subjective assessment, named the Participant Situation Awareness Questionnaire PSAQ, and performance-based assessment. The results of the study indicate that mixed-/left-handed participants had significantly higher SA than strong right-handed participants when measured by performance-based assessment. Also, in the subjective assessment, mixed-/left-handed participants had significantly higher PSAQ performance scores than strong right-handed participants. The findings of this study suggest that advanced driver assistance systems (ADAS), which show improvement in road safety, should adapt the system functionality based on the driver’s degree of handedness when driving under UFTRs. Full article

China’s National Key Ecological Function Zones (NKEFZs) currently represent the largest and most extensive ecological conservation policy in China, with one of the core objectives of this policy being to improve eco-environmental quality (EEQ). This study regards the establishment of NKEFZs as a quasi-natural experiment. Based on panel data from 130 counties in Sichuan Province from 2001 to 2021, a multi-period difference-in-differences (DID) model was employed to evaluate the impact of NKEFZ establishment on EEQ. The findings indicate the following: ① The establishment of NKEFZs can significantly enhance the EEQ of the covered areas, albeit as a gradual long-term process. This conclusion not only meets the parallel-trends assumption but also holds true in a series of robustness tests such as placebo tests. ② Mechanism analysis reveals that NKEFZs can enhance EEQ through the effects of optimizing land spatial allocation and upgrading industrial structure. ③ Heterogeneity analysis demonstrates that the beneficial effect of NKEFZs on EEQ varies across different functional zone types, geographic spaces and ethnic regions. Our study not only contributes to the accumulation of empirical evidence and institutional refinement in the sustainable implementation of ecological policies in China but also offers valuable insights and references for other countries in formulating policies for eco-environmental protection. Full article

Porcine reproductive and respiratory syndrome virus (PRRVS) is a major swine viral pathogen that affects the pig industry worldwide. Control of early PRRSV infection is essential, and different types of PRRSV-positive samples can reflect the time point of PRRSV infection. This study aims to investigate the epidemiological characteristics of PRRSV in China from Q4 2021 to Q4 2022, which will be beneficial for porcine reproductive and respiratory syndrome virus (PRRSV)control in the swine production industry in the future. A total of 7518 samples (of processing fluid, weaning serum, and oral fluid) were collected from 100 intensive pig farms in 21 provinces, which covered all five pig production regions in China, on a quarterly basis starting from the fourth quarter of 2021 and ending on the fourth quarter of 2022. Independent of sample type, 32.1% (2416/7518) of the total samples were PCR-positive for PRRSV, including 73.6% (1780/2416) samples that were positive for wild PRRSV, and the remaining were positive for PRRSV vaccine strains. On the basis of the time of infection, 58.9% suckling piglets (processing fluid) and 30.8% weaning piglets (weaning serum) showed PRRSV infection at an early stage (approximately 90% of the farms). The sequencing analysis results indicate a wide range of diverse PRRSV wild strains in China, with lineage 1 as the dominant strain. Our study clearly demonstrates the prevalence, infection stage, and diversity of PRRSV in China. This study provides useful data for the epidemiological understanding of PRRSV, which can contribute to the strategic and systematic prevention and control of PRRSV in China. Full article

The inevitable impacts of climate change have reverberated across ecosystems and caused substantial global biodiversity loss. Climate-induced habitat loss has contributed to range shifts at both species and community levels. Given the importance of identifying suitable habitats for at-risk species, it is imperative to assess potential current and future distributions, and to understand influential environmental factors. Like many species, the Demoiselle crane is not immune to climatic pressures. Khyber Pakhtunkhwa and Balochistan provinces in Pakistan are known wintering grounds for this species. Given that Pakistan is among the top five countries facing devastating effects of climate change, this study sought to conduct species distribution modeling under climate change using data collected during 4 years of field surveys. We developed a Maximum Entropy distribution model to predict the current and projected future distribution of the species across the study area. Future habitat projections for 2050 and 2070 were carried out using two representative concentration pathways (RCP 4.5 and RCP 8.5) under three global circulation models, including HADGEM2-AO, BCC-CSM1-1, and CCSM4. The most influential factors shaping Demoiselle Crane habitat suitability included the temperature seasonality, annual mean temperature, terrain ruggedness index, and human population density, all of which contributed significantly to the suitability (81.3%). The model identified 35% of the study area as moderately suitable (134,068 km²) and highly suitable (27,911 km²) habitat for the species under current climatic conditions. Under changing climate scenarios, our model predicted a major loss of the species’ current suitable habitat, with shrinkage and shift towards western–central areas along the Pakistan–Afghanistan boarder. The RCP 8.5, which is the extreme climate change scenario, portrays particularly severe consequences, with habitat losses reaching 65% in 2050 and 85% in 2070. This comprehensive study provides useful insights into the Demoiselle Crane habitat’s current and future dynamics in Pakistan. Full article

The ultimate goal of China’s tourism industry is to create a flourishing sector that brings happiness. It is of immense theoretical and practical importance to investigate the impact of tourism development (TD) on urban welfare (UW) and uncover its spatial spillover characteristics from a macro perspective. Utilizing panel data from 41 cities in the Yangtze River Delta region from 2000 to 2021, this study applies the spatial panel Durbin model to explore the direct and spillover effects of TD on UW. The results show that TD significantly boosts UW in both local and neighboring areas, with the spillover effects taking a dominant position in the total effects. Examining the sub-dimensions of UW, the local welfare effects of TD primarily stem from economic welfare, whereas the spillover effects are characterized by the “three-wheel drive” of economic, social, and environmental welfare. This study can provide practical insights into the coordinated and sustainable development of the regional tourism industry. Full article

Supply chain learning (SCL), which is reflected in organizational learning, referring to the learning between organizations in the supply chain, carries the promise to enable sustainable competitive advantages. Many large multinational companies, such as IKEA, Nestle, and Microsoft, have therefore integrated supply chain knowledge management and continuous learning into their corporate strategies. While there is evidence in extant research about a positive correlation between both the subjective attitude and learning ability of supply chain members and their performance improvement, areas where insight is still missing pertain to the relationship between supply chain members’ subjective psychological factors, and their relationship network structures. This is a serious omission, since these dimensions likely play a key role in the dynamics underlying SCL. In order to alleviate this void, we consider a multi-tier SCL network and develop a model in which a supply chain member’s attraction is weighted based on its previous learning experience. The game mechanism underlying SCL captured in this experience-weighted attraction (EWA) model is then tested using a simulation study of IKEA China’s multi-tier supply chain network for its sustainable cotton initiative. The results suggest that learning costs can be reduced and learning spillover befits can be increased by the provision of rewards to network member companies and better communication. In addition, the perception of and preference for SCL by suppliers can be influenced by initiating sustainable advocacy and providing knowledge and technology training, as well as fostering a range of subjective factors we investigate in our study, such as the strategic attractiveness the decline ratio due to forgetting, the attractiveness improvement ratio due to preferences, and the response sensitivity to strategies. The findings offer insight into the influence mechanisms of the supply chain network structure and subjective attitude about SCL, which are especially applicable to large, multinational enterprises. Full article

Rapid urbanization in many cities has produced massive amounts of problematic excavation soil. The direct disposal of untreated excavation soil often leads to significant land use and severe environmental concerns. A sustainable solution is to transform the soil waste into high-quality nano-calcined excavation soil (NCES) for application as a substitute for cement in construction. However, research in this area is very limited. This study presents a systematic investigation of the nano-sized calcined soil materials from preparation to application in cementitious material. The influence of milling parameters, including the rotational speed, milling duration, ball diameter, and milling strategy, was investigated to produce NCES with various specific surface areas. The effect of NCES substitution (15 wt% of Portland cement) in cementitious materials was then examined for mechanical performance, hydration dynamics, hydration products, and microstructure. A cement mix with very fine NCES (specific surface area of 108.76 m²/g) showed a 29.7% enhancement in mechanical strength and refined pore structure while a cement mix with un-grounded calcined soil showed a mechanical loss in comparison to the Control specimen. Delayed and reduced heat release at an early age was observed in a cement paste mixed with NCES. The underlying mechanism was investigated. The results of this work will contribute to the high-quality application of excavation soil waste. Full article

The endometrium, the inner mucosal lining of the uterus, undergoes complex molecular and cellular changes across the menstrual cycle in preparation for embryo implantation. Transcriptome-wide analyses have mainly been utilized to study endometrial receptivity, the prerequisite for successful implantation, with most studies, so far, comparing the endometrial transcriptomes between (i) secretory and proliferative endometrium or (ii) mid-secretory and early secretory endometrium. In the current study, we provide a complete transcriptome description of the endometrium across the entire menstrual cycle and, for the first time, comprehensively characterize the proliferative phase of the endometrium. Our temporal transcriptome analysis includes five time points including the mid-proliferative, late proliferative (peri-ovulatory phase), early secretory, mid-secretory, and late secretory phases. Thus, we unveil exhaustively the transitions between the consecutive proliferative and secretory phases, highlighting their unique gene expression profiles and possible distinct biological functions. The transcriptome analysis reveals many differentially expressed genes (DEGs) across the menstrual cycle, most of which are phase-specific. As an example of coordinated gene activity, the expression profile of histone-encoding genes within the HIST cluster on chromosome 6 shows an increase in cluster activity during the late proliferative and a decline during the mid-secretory phase. Moreover, numerous DEGs are shared among all phases. In conclusion, in the current study, we delineate the endometrial proliferative phase-centered view of transcriptome dynamics across the menstrual cycle. Our data analysis highlights significant transcriptomic and functional changes occurring during the late proliferative phase—an essential transition point from the proliferative phase to the secretory phase. Future studies should explore how the biology of the late proliferative phase endometrium impacts the achievement of mid-secretory endometrial receptivity or contributes to molecular aberrations leading to embryo implantation failure. Full article