This study utilizes Thermal Infrared (TIR) imaging technology to detect hotspots in photovoltaic (PV) modules of solar power plants. Unmanned aerial vehicle (UAV)-based TIR imagery is crucial for efficiently analyzing fault detection in solar power plants. This research explores optimal operational parameters for generating high-quality TIR images using UAV technology. In addition to existing variables such as humidity, emissivity, height, wind speed, irradiance, and ambient temperature, newly considered variables including the angle of incidence between the target object and the thermal infrared camera are analyzed for their impact on TIR images. Based on the solar power plant’s tilt (20°) and the location coordinate data of the hotspot modules, the inner and outer products of the vectors were used to obtain the normal vector and angle of incidence of the solar power plant. It was discovered that the difference between measured TIR temperature data and Land Surface Temperature (LST) data varies with changes in the angle of incidence. The analysis presented in this study was conducted using multiple regression analysis to explore the relationships between dependent and independent variables. The Ordinary Least Squares (OLS) regression model employed was able to explain 63.6% of the variability in the dependent variable. Further, the use of the Condition Number (Cond. No.) and the Variance Inflation Factor (VIF) revealed that the multicollinearity among all variables was below 10, ensuring that the independence among variables was well-preserved while maintaining statistically significant correlations. Furthermore, a positive correlation was observed with the actual measured temperature values, while a negative correlation was observed between the TIR image data values and the angle of incidence. Moreover, it was found that an angle of incidence between 15° and 20° yields the closest similarity to LST temperature data. In conclusion, our research emphasizes the importance of adjusting the angle of incidence to 15–20° to enhance the accuracy of TIR imaging by mitigating overestimated TIR temperature values. Full article

Enteral nutrition (EN) therapy in ICU patients requiring oxygen therapy with high-flow nasal cannula (HFNC) and/or noninvasive mechanical ventilation (NIMV) is controversial. A prospective, cohort, observational, and multicenter study was conducted in 10 ICUs in Spain to analyze the 90-day mortality, tolerance, side effects, and infectious complications of trophic EN in patients requiring HFNC therapy and/or NIVM. A total of 149 patients were enrolled. The mean age, severity scores, tracheobronchitis, bacteremia, and antimicrobial therapy were significantly higher in deceased than in living patients (p < 0.05), and the mortality rate was 14.8%. A total of 110 patients received oral trophic feedings, 36 patients received nasogastric tube feedings (NGFs), and 3 received mixed feedings. Trophic EN was discontinued in only ten (14.9%) patients because of feeding-related complications. The variables selected for the multivariate logistic regression on feeding discontinuation were SOFA upon admission (OR per unit = 1.461) and urea (OR per mg/dL = 1.029). There were no significant differences in the development of new infections according to the route of EN administration. Early trophic feeding administered to patients with acute respiratory failure requiring noninvasive ventilation is safe and feasible, and is associated with few dietary and infectious complications in a mortality, setting comparable to similar studies. Full article

Carrageenan is a widely used food additive and is seen as a potential candidate in the pharmaceutical industry. However, there are two faces to carrageenan that allows it to be used positively for therapeutic purposes. Carrageenan can be used to create edible films and for encapsulating drugs, and there is also interest in the use of carrageenan for food printing. Carrageenan is a naturally occurring polysaccharide gum. Depending on the type of carrageenan, it is used in regulating the composition of intestinal microflora, including the increase in the population of Bifidobacterium bacteria. On the other hand, the studies have demonstrated the harmfulness of carrageenan in animal and human models, indicating a direct link between diet and intestinal inflammatory states. Carrageenan changes the intestinal microflora, especially Akkermansia muciniphilia, degrades the mucous barrier and breaks down the mucous barrier, causing an inflammatory reaction. It directly affects epithelial cells by activating the pro-inflammatory nuclear factor kappa-light-chain-enhancer of activated B cells (NF-kB) pathway. The mechanism is based on activation of the TLR4 receptor, alterations in macrophage activity, production of proinflammatory cytokines and activation of innate immune pathways. Carrageenan increases the content of Bacteroidetes bacteria, also causing a reduction in the number of short chain fatty acid (SCFA)-producing bacteria. The result is damage to the integrity of the intestinal membrane and reduction of the mucin layer. The group most exposed to the harmful effects of carrageenan are people suffering from intestinal inflammation, including Crohn disease (CD) and ulcerative colitis (UC). Full article

The incidence of ulcerative colitis (UC) is increasing annually, and UC has a serious impact on patients’ lives. Polysaccharides have gained attention as potential drug candidates for treating ulcerative colitis (UC) in recent years. Huaier (Trametes robiniophila Murr) is a fungus that has been used clinically for more than 1000 years, and its bioactive polysaccharide components have been reported to possess immunomodulatory effects, antitumour potential, and renoprotective effects. In this study, we aimed to examine the protective effects and mechanisms of Huaier polysaccharide (HP) against UC. Based on the H₂O₂-induced oxidative stress model in HT-29 cells and the dextran sulphate sodium salt (DSS)-induced UC model, we demonstrated that Huaier polysaccharides significantly alleviated DSS-induced colitis (weight loss, elevated disease activity index (DAI) scores, and colonic shortening). In addition, HP inhibited oxidative stress and inflammation and alleviated DSS-induced intestinal barrier damage. It also significantly promoted the expression of the mucin Muc2. Furthermore, HP reduced the abundance of harmful bacteria Escherichia-Shigella and promoted the abundance of beneficial bacteria Muribaculaceae_unclassified, Anaerotruncus, and Ruminococcaceae_unclassified to regulate the intestinal flora disturbance caused by DSS. Nontargeted metabolomics revealed that HP intervention would modulate metabolism by promoting levels of 3-hydroxybutyric acid, phosphatidylcholine (PC), and phosphatidylethanolamine (PE). These results demonstrated that HP had the ability to mitigate DSS-induced UC by suppressing oxidative stress and inflammation, maintaining the intestinal barrier, and modulating the intestinal flora. These findings will expand our knowledge of how HP functions and offer a theoretical foundation for using HP as a potential prebiotic to prevent UC. Full article

The development of multiple-drug-resistant (MDR) cancer all too often signals the need for alternative toxic therapy or palliative care. Our recent in vivo and in vitro studies using canine MDR lymphoma cancer cells demonstrate that the Anaphase Promoting Complex (APC) is impaired in MDR cells compared to normal canine control and drug-sensitive cancer cells. Here, we sought to establish whether this phenomena is a generalizable mechanism independent of species, malignancy type, or chemotherapy regime. To test the association of blunted APC activity with MDR cancer behavior, we used matched parental and MDR MCF7 human breast cancer cells, and a patient-derived xenograft (PDX) model of human triple-negative breast cancer. We show that APC activating mechanisms, such as APC subunit 1 (APC1) phosphorylation and CDC27/CDC20 protein associations, are reduced in MCF7 MDR cells when compared to chemo-sensitive matched cell lines. Consistent with impaired APC function in MDR cells, APC substrate proteins failed to be effectively degraded. Similar to our previous observations in canine MDR lymphoma cells, chemical activation of the APC using Mad2 Inhibitor-1 (M2I-1) in MCF7 MDR cells enhanced APC substrate degradation and resensitized MDR cells in vitro to the cytotoxic effects of the alkylating chemotherapeutic agent, doxorubicin (DOX). Using cell cycle arrest/release experiments, we show that mitosis is delayed in MDR cells with elevated substrate levels. When pretreated with M2I-1, MDR cells progress through mitosis at a faster rate that coincides with reduced levels of APC substrates. In our PDX model, mice growing a clinically MDR human triple-negative breast cancer tumor show significantly reduced tumor growth when treated with M2I-1, with evidence of increased DNA damage and apoptosis. Thus, our results strongly support the hypothesis that APC impairment is a driver of aggressive tumor development and that targeting the APC for activation has the potential for meaningful clinical benefits in treating recurrent cases of MDR malignancy. Full article

Chronic kidney disease poses a growing global health concern, as an increasing number of patients progress to end-stage kidney disease requiring kidney replacement therapy, presenting various challenges including shortage of care givers and cost-related issues. In this narrative essay, we explore innovative strategies based on in-depth literature analysis that may help healthcare systems face these challenges, with a focus on digital health technologies (DHTs), to enhance removal and ensure better control of broader spectrum of uremic toxins, to optimize resources, improve care and outcomes, and empower patients. Therefore, alternative strategies, such as self-care dialysis, home-based dialysis with the support of teledialysis, need to be developed. Managing ESKD requires an improvement in patient management, emphasizing patient education, caregiver knowledge, and robust digital support systems. The solution involves leveraging DHTs to automate HD, implement automated algorithm-driven controlled HD, remotely monitor patients, provide health education, and enable caregivers with data-driven decision-making. These technologies, including artificial intelligence, aim to enhance care quality, reduce practice variations, and improve treatment outcomes whilst supporting personalized kidney replacement therapy. This narrative essay offers an update on currently available digital health technologies used in the management of HD patients and envisions future technologies that, through digital solutions, potentially empower patients and will more effectively support their HD treatments. Full article

Adequate diet, physical activity, and dietary supplementation with muscle-targeted food for special medical purposes (FSMP) or dietary supplement (DS) are currently considered fundamental pillars in sarcopenia treatment. The aim of this study is to evaluate the effectiveness of a DS (containing hydroxy-methyl-butyrate, carnosine, and magnesium, for its action on muscle function and protein synthesis and butyrate and lactoferrin for their contribution to the regulation of gut permeability and antioxidant/anti-inflammation activity) on muscle mass (assessed by dual x-ray absorptiometry (DXA)), muscle function (by handgrip test, chair test, short physical performance battery (SPPB) test, and walking speed test), inflammation (tumor necrosis factor-alpha (TNF-a), C-reactive protein (CRP), and visceral adipose tissue (VAT)) and gut axis (by zonulin). A total of 59 participants (age 79.7 ± 4.8 years, body mass index 20.99 ± 2.12 kg/m²) were enrolled and randomly assigned to intervention (n = 30) or placebo (n = 28). The skeletal muscle index (SMI) significantly improved in the supplemented group compared to the placebo one, +1.02 (CI95%: −0.77; 1.26), p = 0.001; a significant reduction in VAT was observed in the intervention group, −70.91 g (−13.13; −4.70), p = 0.036. Regarding muscle function, all the tests significantly improved (p = 0.001) in the supplemented group compared to the placebo one. CRP, zonulin, and TNF-alpha significantly decreased (p = 0.001) in intervention, compared to placebo, −0.74 mg/dL (CI95%: −1.30; −0.18), −0.30 ng/mL (CI95%: −0.37; −0.23), −6.45 pg/mL (CI95%: −8.71; −4.18), respectively. This DS improves muscle mass and function, and the gut muscle has emerged as a new intervention target for sarcopenia. Full article

In recent decades, the hydrological processes on the Loess Plateau have undergone significant changes due to the combined effects of climate change and human activities. This study investigates the Qin River basin, the core area of the Loess Plateau. Between 1971 and 2000, the hydrometeorology of the flood season in the Qin basin on the Loess Plateau in China changed abruptly in 1982 and 1992. This study uses distributed hydrologic modeling and statistical analysis to distinguish the spatial and temporal impacts of climate change and human activities. The fastest dynamic changes in land use occurred in grassland and construction land, accounting for 0.36% and −0.1%, respectively, from 1982 to 1991. From 1992 to 2000, it was 0.29% and 0.3%, respectively. The increase in basin area where the Normalized Difference Vegetation Index increased was 95%. However, except for significant changes in runoff from 1981 to 1992, there were no significant changes in precipitation, runoff, and temperature during other flood seasons. During the two studied variation periods, from 1982 to 1991 and from 1992 to 2000, the contribution rate of climate change to flood season runoff (${\mathrm{C}}_{\mathrm{C}\mathrm{l}\mathrm{i}\mathrm{m}\mathrm{a}\mathrm{t}\mathrm{e}}$) decreased from 83.26% to 74.47%, while the contribution rate of human activity disturbance to flood season runoff (${\mathrm{C}}_{\mathrm{h}\mathrm{u}\mathrm{m}\mathrm{a}\mathrm{n}}$) increased from 16.74% to 25.53%. In terms of spatial distribution, from 1982 to 1991, areas with a ${\mathrm{C}}_{\mathrm{h}\mathrm{u}\mathrm{m}\mathrm{a}\mathrm{n}}$ > 50% were primarily concentrated in the upper reaches of the basin, while from 1992–2000, these areas shifted to the lower reaches. This study offers valuable insights for water resource planning and soil conservation measures in the Loess Plateau and similar arid regions worldwide, aiming to ensure water resource safety and sustainability in response to climate change and human interference. Full article

The aim of this paper was to evaluate the fracture resistance of 3D-printed zirconia occlusal veneers (OVs) of different thicknesses and supported by different abutment materials. Materials and Methods: The standard OV of a natural molar was prepared and digitized using a laboratory 3D scanner. The resulting digital tooth abutment was milled either using cobalt–chromium (CoCr) or a fiber-reinforced composite (FRC). All the abutments were digitized and standardized OVs (30° tilt of all the cusps) designed with 0.4 mm, 0.6 mm, or 0.8 mm wall thicknesses. The OVs were fabricated using either the Programill PM7 milling device (Ivoclar Vivadent, PM) or one of two 3D zirconia printers, Cerafab 7500 (Lithoz, LC) or Zipro-D (AON, ZD). The ZD samples were only tested on CoCr abutments. The completed OVs were luted to their abutments and subjected to artificial aging, consisting of thermocycling and chewing simulation before fracture testing with a steel sphere (d = 8 mm) as an antagonist with three contact points on the occlusal OV surface. Besides the total fracture resistance F_u,tot, the lowest contact force F_u,cont leading to the local fracture of a cusp was of interest. The possible effects of the factors fabrication approach, wall thickness, and abutment material were evaluated using ANOVA (α = 0.05; SPSS Ver.28). Results: The total fracture resistance/contact forces leading to failure ranged from F_u,tot = 416 ± 83 N/F_u,cont = 140 ± 22 N for the 0.4 mm OVs fabricated using LC placed on the FRC abutments to F_u,tot = 3309 ± 394 N (ZD)/F_u,cont = 1206 ± 184 N (PM) for the 0.8 mm thick OVs on the CoCr abutments. All the factors (the fabrication approach, abutment material, and OV wall thickness) had an independent effect on F_u,tot as well as F_u,cont (p < 0.032). In pairwise comparisons for F_u,tot of the OVs luted to the CoCr abutments, the ZD samples statistically outperformed the LC- and PM-fabricated teeth irrespective of the thickness (p < 0.001). Conclusions: Within the limitations of this study, the printed occlusal veneers exhibited comparable fracture resistances to those of the milled variants. However, more resilient abutments (FRC as a simulation of dentine) as well as a thinner wall thickness led to reduced OV fracture resistance, suggesting that 0.4 mm thick zirconia OVs should not be unreservedly used in every clinical situation. Full article

Solar photovoltaic (PV) systems stand out as a promising solution for generating clean, carbon-free energy. However, traditional solar panel installations often require extensive land resources, which could become scarce as the population grows. To address this challenge, innovative approaches are needed to maximize solar power generation within limited spaces. One promising concept involves the development of biological tree-like structures housing solar panels. These “solar trees” mimic the arrangement of branches and leaves found in natural trees, following patterns akin to phyllotaxy, which correlates with the Fibonacci sequence and golden ratio. By adopting an alternative 1:3 phyllotaxy pattern, three solar panels can be efficiently arranged along the stem of the solar tree structure, each rotated at a 120-degree displacement. Optimizing the performance of solar trees requires effective maximum power point tracking (MPPT), a crucial process for extracting the maximum available power from solar panels to enhance the overall efficiency. In this study, a novel metaheuristic algorithm called horse herd optimization (HHO) is employed for MPPT in solar tree applications. Moreover, to efficiently manage the generated power, a cascaded buck–boost converter is utilized. This converter is capable of adjusting the DC voltage levels to match the system requirements within a single topology. The algorithm is implemented using MATLAB and embedded within a Raspberry Pi Pico controller, which facilitates the generation of pulse-width modulation (PWM) signals to control the cascaded buck–boost converter. Through extensive validation, this study confirms the effectiveness of the proposed HHO algorithm integrated into the Raspberry Pi Pico controller for optimizing solar trees under various shading conditions. In essence, this research highlights the potential of solar tree structures coupled with advanced MPPT algorithms and power management systems to maximize solar energy utilization, offering a sustainable solution for clean energy generation within limited land resources. Full article

Phasor measurement units (PMUs) are deployed at power grid nodes around the transmission grid, determining precise power system monitoring conditions. In real life, it is not realistic to place a PMU at every power grid node; thus, the lowest PMU number is optimally selected for the full observation of the entire network. In this study, the PMU placement model is reconsidered, taking into account single- and multi-capacity placement models rather than the well-studied PMU placement model with an unrestricted number of channels. A restricted number of channels per monitoring device is used, instead of supposing that a PMU is able to observe all incident buses through the transmission connectivity lines. The optimization models are declared closely to the power dominating set and minimum edge cover problem in graph theory. These discrete optimization problems are directly related with the minimum set covering problem. Initially, the allocation model is declared as a constrained mixed-integer linear program implemented by mathematical and stochastic algorithms. Then, the integer linear problem is reformulated into a non-convex constraint program to find optimality. The mathematical models are solved either in binary form or in the continuous domain using specialized optimization libraries, and are all implemented in YALMIP software in conjunction with MATLAB. Mixed-integer linear solvers, nonlinear programming solvers, and heuristic algorithms are utilized in the aforementioned software packages to locate the global solution for each instance solved in this application, which considers the transformation of the existing power grids to smart grids. Full article

This review focuses on recent research on the phytochemicals found in bark from different trees and their potential to be used as substrates for the synthesis of thermosetting resins. Recent studies about the influence of each bark harvesting step on the extracted phytochemicals, from debarking to extraction, are investigated. A comparison of bark extracts in terms of the correlation between extraction conditions and efficiency (based on the total phenolic content (TPC) and extraction yield) is presented for six groups of trees (Norway spruce, pine species, other conifers, oak species, other deciduous trees of the north temperate zone, tropical and subtropical trees) and evaluated. The evaluation revealed that there is an interesting relationship between the extraction time and the type of solvent for some types of tree bark. It was found that a relatively short extraction time and a solvent temperature close to the boiling point are favourable. The latest research on the application of bark extracts in different types of thermosetting resins is described. This review discusses the attractiveness of bark extracts in terms of functional groups and the possibilities arising from extractable phytochemicals. In addition, different approaches (selective versus holistic) and methods of application are presented and compared. Full article

Disturbances often occur in transfer stations; however, little is known about the weaknesses of transfer stations and their ability to cope with passenger flows. Therefore, this paper introduces resilience into the study of transfer stations to enhance their emergency response processes and improve the sustainability of URT networks. It establishes a two-level fuzzy evaluation model, using the G1 weighting method, to assess resilience across various scenarios (daily operation, heavy passenger flow, and emergencies) and identify weaknesses; then, corresponding enhancement strategies are proposed. First, factor sets are established according to resilience stages, including rapidity before disturbance, robustness, redundancy, resourcefulness, and rapidity after disturbance. Using the G1 method, the weight matrix for each factor is calibrated, and a membership degree matrix is determined based on their affiliation with the review set. Multiplying the weight matrix and membership degree matrix yields the resilience value. We apply these steps to a representative station with the assistance of Anylogic simulation in calculating the hard-to-obtain data, yielding a peak-hour resilience value of 0.3425, which indicates a “poor” rating in the review set. By combining the peak-hour resilience with resilience curves under different multiples of peak-hour flows, an enhancement prioritization strategy is proposed for the station, which can act as a reference for the management of URT transfer stations. Full article

Soil moisture is among the most essential variables in hydrology and earth science. Many satellite missions, such as AMSR-E/2, have been launched to observe it in broader spatial coverage to overcome the shortage of in situ observations. However, the satellite soil moisture products have been reported to comprise errors caused by the so-called “temperature effects” widely observed in dielectrically measured in situ volumetric soil water content (SWC). In this work, we confirmed the existence of these errors in AMSR2 soil moisture products. A new algorithm was developed to remove these errors using satellite data at ascending and descending overpasses. The application of this algorithm to both satellite and in situ data of SWC and soil temperature at the Mongolia site shows that the difference between SWC values at ascending and descending overpasses caused by temperature effects is effectively removed. We assess the impact of this removal method on satellite data by comparing it with in situ data, utilizing metrics such as the correlation coefficient and other widely adopted evaluation methods. It is shown that the difference between the original and corrected in situ SWC is much smaller than that between AMSR2 and in situ SWC, either corrected or not. The results indicate that the metric values between the corrected AMSR2 and in situ SWC, after removing apparent differences caused by temperature effects, slightly improved compared to those between the original AMSR2 and in situ SWC. Though these findings imply that the removed errors may not be the most dominant, considering the current significant difference between AMSR2 and in situ SWC, the removal makes the ascending and descending data have close characteristics. It may allow using data at both ascending and descending overpasses and double the temporal resolution of AMSR2 SWC data. Full article

Synthetic aperture radar tomography (TomoSAR) is an extension of synthetic aperture radar (SAR) imaging. It introduces the synthetic aperture principle into the elevation direction to achieve three-dimensional (3-D) reconstruction of the observed target. Compressive sensing (CS) is a favorable technology for sparse elevation recovery. However, for the non-sparse elevation distribution of the forested areas, if CS is selected to reconstruct it, it is necessary to utilize some orthogonal bases to first represent the elevation reflectivity sparsely. The iterative adaptive approach (IAA) is a non-parametric algorithm that enables super-resolution reconstruction with minimal snapshots, eliminates the need for hyperparameter optimization, and requires fewer iterations. This paper introduces IAA to tomographicinversion of the forested areas and proposes a novel multi-polarimetric-channel joint 3-D imaging method. The proposed method relies on the characteristics of the consistent support of the elevation distribution of different polarimetric channels and uses the $L_2$-norm to constrain the IAA-based 3-D reconstruction of each polarimetric channel. Compared with typical spectral estimation (SE)-based algorithms, the proposed method suppresses the elevation sidelobes and ambiguity and, hence, improves the quality of the recovered 3-D image. Compared with the wavelet-based CS algorithm, it reduces computational cost and avoids the influence of orthogonal basis selection. In addition, in comparison to the IAA, it demonstrates greater accuracy in identifying the support of the elevation distribution in forested areas. Experimental results based on BioSAR 2008 data are used to validate the proposed method. Full article

Due to their exceptional properties and diverse applications, including to magnetic devices, thermoelectric materials, catalysis, biomedicine, and energy storage, nanoscale metallic multilayer composites (NMMCs) have recently attracted great attention. The alternating layers of two or more metals that make up NMMCs are each just a few nanometers thick. The difficulties in producing and synthesizing new materials can be overcome by using nanoscale multilayer architectures. By adjusting the layer thickness, composition, and interface structure, the mechanical properties of these materials can be controlled. In addition, NMMCs exhibit unusually high strength at thin layer thicknesses because the multilayers have exceptionally high strength, as the individual layer thicknesses are reduced to the nanoscale. The properties of NMMCs depend on the individual layers. This means that the properties can be tuned by varying the layer thickness, composition, and interface structure. Therefore, this review article aims to provide a comprehensive overview of the mechanical properties and the application of high-performance NMMCs. The paper briefly discusses the fabrication methods used to produce these composites and highlights their potential in various fields, such as electronics, energy storage, aerospace, and biomedical engineering. Furthermore, the electrical conductivity, mechanical properties, and thermal stability of the above composite materials are analyzed in detail. The review concludes with a discussion of the future prospects and challenges associated with the development of NMMCs. Full article

Tectonic features on the Moon can reflect the state of stress during the formation of the structure, and sinuous rilles can provide further insight into the tectonic-thermal evolution of the Moon. Manual visual interpretation is the primary method for extracting these linear structures due to their complex morphology. However, extracting these features from the vast amount of lunar remote sensing data requires significant time and effort from researchers, especially for small-scale tectonic features, such as wrinkle ridges, lobate scarps, and high-relief ridges. In order to enhance the efficiency of linear structure detection, this paper conducts research on the automatic detection method of linear structures using sinuous rilles as an example case. In this paper, a multimodal semantic segmentation method, “Sinuous Rille Network (SR-Net)”, for detecting sinuous rilles is proposed based on DeepLabv3+. This method combines advanced techniques such as ECA-ResNet and dynamic feature fusion. Compared to other networks, such as PSPNet, ResUNet, and DeepLabv3+, SR-Net demonstrates superior precision (95.20%) and recall (92.18%) on the multimodal sinuous rille test set. The trained SR-Net was applied in detecting lunar sinuous rilles within the range of 60°S to 60°N latitude. A new catalogue of sinuous rilles was generated based on the results of the detection process. The methodology proposed in this paper is not confined to the detection of sinuous rilles; with further improvements, it can be extended to the detection of other linear structures. Full article

This study provides pioneering research on the vegetation of archaeological areas in Iran to enhance its naturalistic and bioindication values by selecting the Pasargadae World Heritage Site (WHS). Vegetation surveys were carried out in different homogeneous habitats, analyzing the plant communities through statistical elaboration, syntaxonomic role, mapping, and enhancement of plants with conservation interest. In an ecological approach, the study included an analysis of the recent climate changes and human interventions influencing the water resources. Results revealed seven main vegetation types reflecting ecological gradients shaped by environmental, edaphic, and anthropogenic factors. The syntaxonomic analysis showed a primary subdivision in semi-natural grasslands and synanthropic vegetation. Several key species were identified as bioindicators of multiple factors, such as: Launaea acanthodes, Stipa barbata, Alhagi maurorum, Bellevalia saviczii, Glycyrrhiza glabra, Convolvulus arvensis, and Hordeum murinum. The vegetation map showed how the hilly grassland communities hosted the highest number of species with conservation interest and their need to be better protected. Bio-climatic data, such as the construction of dams and the exploitation for irrigation purposes, pointed to the increasing xeric conditions, which make urging conservation efforts for the site’s historical and naturalistic values. The study underscores the importance of preserving places with high plant diversity for effective site management, and enhances the intricate relationship between vegetation and natural features in the occurring environmental changes. Full article

Optimizing production processes to conserve resources and reduce waste has become crucial in pursuing sustainable manufacturing practices. The solid wood panel industry, marked by substantial raw materials and energy consumption, stands at the forefront of addressing this challenge. This research delves into production scheduling and equipment utilization inefficiencies, offering innovative solutions for the solid wood panel processing line aimed at achieving environmental sustainability and operational efficiency. The study is articulated through two main segments: (1) an exhaustive analysis and the development of a simulation system for the solid wood panel processing line, delineating all production elements and operational logic, furnished with a user-friendly simulation interface, and (2) a comprehensive evaluation and enhancement of various scheduling algorithms specific to the Flexible Job-Shop Scheduling Problem (FJSP) encountered in solid wood panel workshops. A significant leap forward is made with the introduction of the Adaptive Intelligent Optimization Genetic Algorithm (AIOGA), an evolved version of the standard Genetic Algorithm (GA) engineered for optimal scheduling within the solid wood panel processing line. AIOGA incorporates advanced features such as encoding strategy, population initialization, objective function setting, selection strategy, crossover operation, and mutation operation, demonstrating the methodological depth of the study. We applied AIOGA in a designed FJSP, and AIOGA substantially reduced the maximum completion time to 90 min. It evidenced an improvement of 39.60% over the conventional GA, enhancing the equilibrium of the equipment workload across the system. This research presents a multifaceted strategy to address the scheduling complications inherent in solid wood panel production and highlights the extensive applicability of adaptive intelligent optimization in diverse industrial settings. This study establishes a new paradigm in manufacturing optimization, underlining the valuable integration of sustainability and efficiency in production methodologies. Full article

This study delves into the intricate interplay of economic growth components, specifically focusing on consumption and investment in Saudi Arabia from 2000 to 2022. Employing vector error correction models and co-integration techniques, we analyze the short- and long-term dynamics within the relationship of consumption, investment, and economic growth. Granger causality analysis is also used to discern these pivotal variables’ causal connections. Our empirical analysis reveals a persistent long-term cointegration relationship among the variables, underscoring the enduring nature of their interdependency. Furthermore, our findings highlight consumption and investment’s statistically significant positive impact on economic growth. Notably, the short-term analysis unveils a stable model characterized by an annual adjustment to equilibrium of 100%. Moreover, the Granger causality study demonstrates unidirectional causal linkages among consumption, investment, and economic growth. These findings hold substantial implications for policy formulation in Saudi Arabia. Policymakers must grasp the ramifications of burgeoning prosperity and evolving private consumption patterns on future environmental outcomes. Achieving sustainable long-term results necessitates equal emphasis on bolstering private consumption and fostering other facets of economic growth. Full article

A new approach is proposed that identifies three different zones of the Si-rich network structure (the cellular structure) in laser powder bed fused (LPBF) AlSi10Mg alloy, based on the variation in morphology, grain growth transition, and melt pool solidification conditions. The three identified zones are denoted in the present work as the liquid solidification zone (LSZ), the mushy solidification zone (MSZ), and the heat affected zone (HAZ). The LSZ is the result of liquid–solid transformation, showing small planar growth at the boundary and large cellular growth in the center, while the MSZ is related to a semisolid reaction, and the HAZ arises from a short-time aging process. The boundary between the LSZ and MSZ is identified by the change of grain growth direction and the Si-rich network advancing direction. The boundary between MSZ and HAZ is identified by the start of the breakdown of the Si-rich network. In addition, it is found that the fracture is generated in and propagates along the HAZ during tensile tests. Full article

In the summer of 2022, Pakistan experienced a severe flood event that brought great destruction to the local people and ecosystem. However, there is no comprehensive study on the process, spread and causes of this flood. Therefore, we combined multiple satellite gravity data, meteorological data, hydrological data, and satellite remote sensing data to conduct a thorough investigation and study of this flood. The results show that a 20-year time series of the terrestrial water storage change based multiple gravity data has the high accuracy and reliability, which is used for detecting the flood. The flood propagated through meteorological system (three months), agricultural system (six months) and terrestrial ecosystems (five months), respectively, and the two southern provinces (Balochistan and Sindh) are the most affected by the flood, whose flood severity is 6.955 and 9.557, respectively. The center of the severe flood is located at the border region between the above two province. The severe flood is attributed primarily to the global extreme climate events (La Niña and negative Indian Ocean Dipole events) that altered the transport path of water vapor in the Indian Ocean, causing large amounts of water vapor to converge over Pakistan, resulting in heavy precipitation, and secondarily to the melting of extensive glacier in the mountainous of northern Pakistan as a result of the high temperature in March-May 2022. The above results contribute to the understanding of the mechanism of the impact of extreme climate events on the regional climate, and provide some references for the study of severe floods. Full article