Numerical and computational analysis on a dissipative dynamical system: Slow invariant manifold for complex chemical mechanism.

This article presents the notion about Slow Invariant Manifold (SIM) and their fundamental role in model reduction techniques (MRTs) for challenges encountered in mechanical engineering within dissipative systems of chemical kinetics. Focusing on the reaction routes of complex mechanisms, we construct and compare primary approximations of the SIM through MRTs, including the Spectral Quasi Equilibrium Manifold (SQEM) and Intrinsic Low Dimensional Manifold (ILDM). These methods effectively transform high-dimensional complex problems into lower dimensions, solving them without compromising crucial information about the complex systems modified for homogeneous reactive systems. Employing the sensitivity analysis by using the MATLAB's toolbox, we present the numerical findings in a tabular format obtained through MRTs. This study provides the understanding about the accessible exploration of numerical solutions, improving insights of the complex variation within the system.

Hybrid attention-based deep neural networks for short-term wind power forecasting using meteorological data in desert regions.

This study introduces an optimized hybrid deep learning approach that leverages meteorological data to improve short-term wind energy forecasting in desert regions. Over a year, various machine learning and deep learning models have been tested across different wind speed categories, with multiple performance metrics used for evaluation. Hyperparameter optimization for the LSTM and Conv-Dual Attention Long Short-Term Memory (Conv-DA-LSTM) architectures was performed. A comparison of the techniques indicates that the deep learning methods consistently outperform the classical techniques, with Conv-DA-LSTM yielding the best overall performance with a clear margin. This method obtained the lowest error rates (RMSE: 71.866) and the highest level of accuracy (R2: 0.93). The optimization clearly works for higher wind speeds, achieving a remarkable improvement of 22.9%. When we look at the monthly performance, all the months presented at least some level of consistent enhancement (RRMSE reductions from 1.6 to 10.2%). These findings highlight the potential of advanced deep learning techniques in enhancing wind energy forecasting accuracy, particularly in challenging desert environments. The hybrid method developed in this study presents a promising direction for improving renewable energy management. This allows for more efficient resource allocation and improves wind resource predictability.

Enhancing deep learning-based slope stability classification using a novel metaheuristic optimization algorithm for feature selection.

The evaluation of slope stability is of crucial importance in geotechnical engineering and has significant implications for infrastructure safety, natural hazard mitigation, and environmental protection. This study aimed to identify the most influential factors affecting slope stability and evaluate the performance of various machine learning models for classifying slope stability. Through correlation analysis and feature importance evaluation using a random forest regressor, cohesion, unit weight, slope height, and friction angle were identified as the most critical parameters influencing slope stability. This research assessed the effectiveness of machine learning techniques combined with modern feature selection algorithms and conventional feature analysis methods. The performance of deep learning models, including recurrent neural networks (RNNs), long short-term memory (LSTM) networks, and generative adversarial networks (GANs), in slope stability classification was evaluated. The GAN model demonstrated superior performance, achieving the highest overall accuracy of 0.913 and the highest area under the ROC curve (AUC) of 0.9285. Integration of the binary bGGO technique for feature selection with the GAN model led to significant improvements in classification performance, with the bGGO-GAN model showing enhanced sensitivity, positive predictive value, negative predictive value, and F1 score compared to the classical GAN model. The bGGO-GAN model achieved 95% accuracy on a substantial dataset of 627 samples, demonstrating competitive performance against other models in the literature while offering strong generalizability. This study highlights the potential of advanced machine learning techniques and feature selection methods for improving slope stability classification and provides valuable insights for geotechnical engineering applications.

Integrating machine and deep learning technologies in green buildings for enhanced energy efficiency and environmental sustainability.

A green building (GB) is a design idea that integrates environmentally conscious technology and sustainable procedures throughout the building's life cycle. However, because different green requirements and performances are integrated into the building design, the GB design procedure typically takes longer than conventional structures. Machine learning (ML) and other advanced artificial intelligence (AI), such as DL techniques, are frequently utilized to assist designers in completing their work more quickly and precisely. Therefore, this study aims to develop a GB design predictive model utilizing ML and DL techniques to optimize resource consumption, improve occupant comfort, and lessen the environmental effect of the built environment of the GB design process. A dataset ASHARE-884 is applied to the suggested models. An Exploratory Data Analysis (EDA) is applied, which involves cleaning, sorting, and converting the category data into numerical values utilizing label encoding. In data preprocessing, the Z-Score normalization technique is applied to normalize the data. After data analysis and preprocessing, preprocessed data is used as input for Machine learning (ML) such as RF, DT, and Extreme GB, and Stacking and Deep Learning (DL) such as GNN, LSTM, and RNN techniques for green building design to enhance environmental sustainability by addressing different criteria of the GB design process. The performance of the proposed models is assessed using different evaluation metrics such as accuracy, precision, recall and F1-score. The experiment results indicate that the proposed GNN and LSTM models function more accurately and efficiently than conventional DL techniques for environmental sustainability in green buildings.

Active learning-based machine learning approach for enhancing environmental sustainability in green building energy consumption.

Green building (GB) techniques are essential for reducing energy waste in the construction sector, which accounts for almost 40% of global energy consumption. Despite their importance, challenges such as occupant behavior and energy management gaps often result in GBs consuming up to 2.5 times more energy than intended. To address this, Building Automation Systems (BAS) play a crucial role in enhancing energy efficiency. This research develops a predictive model for GB design using machine learning to minimize energy consumption and improve indoor sustainability. The dataset is utilized to predict cooling and heating individually, with data visualization by graphically illustrating dataset features and preprocessing through Z-Score normalization and dataset splitting. The proposed model, based on active learning and utilizing ML regressors such as Random Forest (RF), Decision Tree (DT), Gradient Boosting (GB), Extreme Gradient Boosting (XGBoost), CatBoost (CB), Light Gradient Boosting Machine (LGBM), K-Nearest Neighbor (KNN), and Logistic Regressor (LR), shows significant performance improvements. The CBR-AL model achieves impressive results with values of 0.9975 for cooling (Y1) and 0.9883 for heating (Y2), indicating a high level of accuracy. The model's success in reducing energy consumption and improving sustainability has potential ripple effects, including substantial cost savings, reduced carbon footprints, and improved operational efficiency in green buildings. This approach not only enhances environmental sustainability but also sets a benchmark for future advancements in predictive modelling for energy management.

Bifurcation study, phase portraits and optical solitons of dual-mode resonant nonlinear Schrodinger dynamical equation with Kerr law non-linearity.

This study investigates the dynamic characteristics of the dual-mode resonant non-linear Schrodinger equation with a Bhom potential. Hydrodynamics, nonlinear optical fibre communication, elastic media, and plasma physics are just a few of the mathematical physics and engineering applications for this model. The study aims to achieve two main objectives: first, to discuss bifurcation analysis, and second, to extract optical soliton solutions using the extended hyperbolic function method. The study successfully derives various wave solutions, including bright, singular, periodic singular and dark solitons, based on the governing model. The findings conferred in this article show a crucial advancement in understanding the propagation of waves in non-linear media. Additionally, bifurcation of phase portraits of ordinary differential equation consistent with the partial differential equation under consideration is conducted. We also highlight specific constraint conditions that ensure the presence of these obtained solutions. The existing literature shows that these methods are first time applied on this model.

Alleviation of cadmium toxicity in soybean (Glycine max L.): Up-regulating antioxidant capacity and enzyme gene expressions and down-regulating cadmium uptake by organic or inorganic selenium.

Although much interest has been focused on the role of selenium (Se) in plant nutrition over the last 20 years, the influences of organic selenium (selenomethionine; Se-Met) and inorganic selenium (potassium selenite; Se-K) on the growth and physiological characters of cadmium (Cd)-stressed Glycine max L.) seedlings have not yet been studied. In this study, the impacts of Se-Met or Se-K on the growth, water physiological parameters (gaseous exchange and leaf water content), photosynthetic and antioxidant capacities, and hormonal balance of G. max seedlings grown under 1.0 mM Cd stress were studied. The results showed that 30 µM Se-K up-regulates water physiological parameters, photosynthetic indices, antioxidant systems, enzymatic gene expression, total antioxidant activity (TAA), and hormonal balance. In addition, it down-regulates levels of reactive oxygen species (ROS; superoxide free radicals and hydrogen peroxide), oxidative damage (malondialdehyde content as an indicator of lipid peroxidation and electrolyte leakage), Cd translocation factor, and Cd content of Cd-stressed G. max seedlings. These positive findings were in favor of seedling growth and development under Cd stress. However, 50 µM Se-Met was more efficient than 30 µM Se-K in promoting the above-mentioned parameters of Cd-stressed G. max seedlings. From the current results, we conclude Se-Met could represent a promising strategy to contribute to the development and sustainability of crop production on soils contaminated with Cd at a concentration of up to 1.0 mM. However, further work is warranted to better understand the precise mechanisms of Se-Met action under Cd stress conditions.

Green radiography: Exploring perceptions, practices, and barriers to sustainability.

INTRODUCTION: Previous research has delved into the attitudes and behaviors of diverse professions regarding environmental sustainability. However, there needs to be more research specifically targeting radiographers. This study aims to survey radiographers' perceptions, practices, and barriers to change concerning environmental sustainability in radiology. METHODS: Institutional ethical approval was obtained (IRB-COHS-FAC-110-2024) and data collection was conducted using Google Forms (Google Inc., Mountain View, CA). The survey targeted 104 practicing radiographers across several countries. Questions were structured around five domains to gather insights into demographics, training in global warming and climate change, perceptions of sustainability and climate change, sustainability barriers, and current radiology practices on sustainability. Data analysis utilized descriptive and d inferential statistics. RESULTS: One hundred and four radiographers completed the study. Females had a significantly higher attendance rate in environmental protection campaigns (P = 0.01). The majority of respondents (68%) believe in climate change's knowledge and impact on the natural world. Our survey findings demonstrate that 74% of respondents believe there's a need to improve sustainability practices. The most commonly used strategies to decrease energy consumption and emissions were low-energy lighting (60%), real-time power monitoring tools (41%), and energy-efficient heating systems (32%). A significant concern regarding sustainability emerges among respondents: time (50%) and lack of leadership (48%) are prevalent concerns among the identified barriers. CONCLUSION: Participants are recognising the importance of environmental sustainability in radiology, but lack of leadership, support, authority, and facility limitations hinder their adoption. IMPACT ON PRACTICE: Radiology must prioritize environmental sustainability by providing resources and training for radiographers and collaborating with healthcare professionals, policymakers, and environmental experts to develop comprehensive strategies for a sustainable healthcare system.

Production and evaluation of novel functional cream cottage cheese fortified with bovine colostrum and probiotic bacteria.

Nutrient-dense colostrum can be employed as a functional food ingredient. This work aimed to produce novel functional probiotic Cream cottage cheese (FPC) using probiotic (ABT) culture and bovine colostrum powder (BCP) at levels of 1, 2, and 3%. Physicochemical and functional properties (antioxidant activity, fatty acid profile, and antibacterial activity) were analyzed. The outcome revealed that hardness, cohesiveness, and gumminess were increased while springiness and chewiness were decreased for the treated cheeses. In FPC, medium-chain fatty acids were the predominant forms, followed by short- and long-chain fatty acids, polyunsaturated (PUFA), and small amounts of monounsaturated (MUFA). The antioxidant activity of all the cheese samples was significantly (P < 0.05) increased by increasing the quantity of colostrum powder and lengthening storage time. Color parameters were influenced by enrichment with BCP, whether in fresh or stored samples. With the addition of BCP, the growth of lactic acid bacteria and Bifidobacteria was enhanced, whereas that of pathogenic bacteria, mold and yeast, and coliform groups was inhibited. Cheeses fortified with 2% BCP had significantly higher score values than those in the other treatments. Therefore, it could be concluded that cottage cheese fortified with 2% BCP has high nutritional value and health benefits. Supplementary Information: The online version contains supplementary material available at 10.1007/s13197-023-05910-0.

Taxonomic review, palaeoecological, and palaeobiogeographical significances of Campanian Tethyan oysters from the North Eastern Desert, Egypt.

The Late Cretaceous was a time of high eustatic sea level that enabled extensive epicontinental seaways and carbonate platforms across the Tethyan Realm, providing favorable habitats for oyster communities to flourish. This study focuses on the Campanian Tethyan oysters from the North Eastern Desert of Egypt regarding taxonomy, palaeoecology, and palaeobiogeography. Three oyster species, Nicaisolopha nicaisei (Coquand, 1862), Pycnodonte (Phygraea) vesicularis (Lamarck, 1806), and Ambigostrea bretoni (Thomas and Peron, 1891), were identified from the Campanian succession in two studied sections. The sampled specimens of the genus Nicaisolopha have undergone a systematic palaeontological revision. As a result, N. tissoti (Thomas and Peron, 1891) is considered herein a junior synonym of N. nicaisei (Coquand, 1862). Palaeobiogeographically, the likely primary migration pattern of the studied oysters suggests an east-west trend along the Southern Tethys margin. All identified oysters in this study exhibit a Tethyan affinity and are primarily abundant in two main provinces: the Southern Tethys and the Western Tethys. The macrofaunal contents are categorized into two fossil associations: the Nicaisolopha nicaisei association of the middle-late Campanian age and the Pycnodonte vesicularis association of the late Campanian age. These macrofaunal associations indicate a deepening trend during the middle-late Campanian age, suggesting a transition from shallow inner neritic to middle neritic environments. Additionally, it is observed that Pycnodonteinae tend to grow larger under eutrophic conditions, low-energy environments, and nutrient-rich waters with high carbonate contents.

Genetic diversity, chemical constituents and anatomical analysis of eight popular Olive (Olea europaea L.) cultivars in Al-Jouf region, Saudi Arabia.

In light of the multitude of olive trees cultivated and the lack of the genetic diversity of available genotypes to select varieties and lines that are characterized by high diversity and better performance under the corresponding conditions, A comparison analysis of the genotyping and morphological characteristics of eight olive cultivars growing in Saudi Arabia's Al-Jouf region was conducted and analyzed. Morpho-anatomical and chemical characteristics along with both inter-simple-sequence repeats (ISSRs) and start-codon-targeted (SCoT) markers were used to evaluate the genetic diversity among eight olive varieties in Al-Jouf, Saudi Arabia. Analyses of 27 morphological, chemical, and anatomical characteristics concluded the existence of genetic differences among the studied varieties. Moreover, six ISSR and eight SCoT primer combinations produced a total of 48 loci, of which 18 (10 ISSR and 8 SCoT) were polymorphic. The average polymorphism information content (PIC values of 0.48 and 0.44, respectively) and marker index (MI of 0.79 and 0.48, respectively) detected for ISSR and SCoT markers revealed the prevalence of high genetic diversity among the studied olive varieties. Based on chemical and anatomical characteristics and the selected molecular markers, the eight olive cultivars were grouped into two distinct clusters. Clusters in the adjacent joint dendrogram produced using ISSR, SCoT and combined data were similar, and grouped all individuals into two groups. However, the dendrogram generated on the basis of SCoT separated individuals into subgroups containing at least two varieties. The findings showed that both methods were effective in assessing diversity, and that SCoT markers can be used as a reliable and informative method for assessing genetic diversity and relationships among olive varieties and can serve as a complementary tool to provide a more complete understanding of the genetic diversity available in Olea europaea populations in Saudi Arabia.

Hydrogeochemical characteristics and air quality risks associated with gold mining operations in Egypt using geochemical modeling and risk indices.

The success of industrial operations depends on the effective identification, appraisal, and mitigation of possible hazards and associated environmental concerns. This report provides a complete review of environmental management techniques at the Sukari Gold Mine (SGM), located in the southeastern desert of Egypt. Extensive environmental measurements were taken to assess air and water quality, identify hazards, and analyze risks on the SGM premises. Air quality and noise intensity levels were measured at 39 places around the mine's working region. The findings found noncompliance with the Egyptian Environmental Law's (EEL4/94) noise exposure limitations, with the Power Generator House having the maximum noise levels at 107 dB. Remedial measures such as personal protective equipment (PPE) and exposure limit reduction strategies are being considered to address elevated noise levels. Measurements of particulate matter (PM10) and noxious gases (e.g., CO, SO2, NO2, HCN, and NH3) were conducted in workplace and ambient environments. Elevated PM10 concentrations were particularly concerning in underground regions, forcing the deployment of water depression techniques and improved PPE measures. While gas emissions from most activities remained under regulatory limits, select zones showed hydrogen cyanide (HCN) levels that exceeded permitted thresholds, necessitating specific control actions. Using hazard index (HI) and risk rating assessments, this study found different risk profiles across SGM's workplaces, focusing on high-risk regions for focused intervention. Additionally, a water assessment near a Tailing Storage Facility (TSF) was conducted to monitor the impact of mining activities on groundwater quality. The study revealed that groundwater in the region belongs to the Na-K-Cl-SO4 and Ca-Mg-Cl-SO4 water classes, with potential degradation attributed to high mineralization processes induced by aquifer materials and seawater intrusion. The findings underscore the importance of ongoing monitoring, control measures, and implementation of programs to ensure environmental sustainability and minimize risks associated with mining activities in the Sukari Gold Mines. This research highlights the imperative of continuous monitoring, proactive control measures, and the implementation of environmental initiatives to ensure the sustainability of mining operations within the Sukari Gold Mines.

Insights into Grain Milling and Fractionation Practices for Improved Food Sustainability with Emphasis on Wheat and Peas.

Cereal grains and pulses are staple foods worldwide, being the primary supply of energy, protein, and fiber in human diets. The current practice of milling and fractionation yields large quantities of byproducts and waste, which are largely downgraded and end up as animal feeds or fertilizers. This adversely affects food security and the environment, and definitely implies an urgent need for a sustainable grain processing system to rectify the current issues, particularly the management of waste and excessive use of water and energy. The current review intends to discuss the limitations and flaws of the existing practice of grain milling and fractionation, along with potential solutions to make it more sustainable, with an emphasis on wheat and peas as common fractionation crops. This review discusses a proposed sustainable grain processing system for the fractionation of wheat or peas into flour, protein, starch, and value-added components. The proposed system is a hybrid model that combines dry and wet fractionation processes in conjunction with the implementation of three principles, namely, integration, recycling, and upcycling, to improve component separation efficiency and value addition and minimize grain milling waste. The three principles are critical in making grain processing more efficient in terms of the management of waste and resources. Overall, this review provides potential solutions for how to make the grain processing system more sustainable.

Synthesis, conformational analysis and antimicrobial activity of 10-benzyl-1,2,4-triazolo[4,3-b]1,2,4-triazino[5,6-b]indole acyclo C-nucleoside analogs.

Condensation of 5-benzyl-3-hydrazino-1,2,4-triazino[5,6-b]indole with various sugar aldoses or ketoses gave the corresponding sugar hydrazones as single geometrical isomer or exist in E/Z tautomeric isomers. The hydrazones underwent heterocyclization with Fe(Ш)Cl3 to give the N2-adduct acyclo C-nucleosides: 3-(alditol-1yl)-10-benzyl-1,2,4-triazolo[4,3-b]1,2,4-triazino[5,6-b]indoles rather than the N4-adduct: 10-(alditol-1-yl)-3-benzyl-1,2,4-triazolo[3,4-c]1,2,4-triazino[5,6-b] indoles on the basis of chemical and UV spectral proofs. Conformational analysis of their polyacetates were studied. The new acyclo C-nucleosides were evaluated for antimicrobial activity.

Linagliptin Mitigates TGF-ß1 Mediated Epithelial-Mesenchymal Transition in Tacrolimus-Induced Renal Interstitial Fibrosis via Smad/ERK/P38 and HIF-1α/LOXL2 Signaling Pathways.

The dipeptidyl peptidase-4 (DPP-4) inhibitors, a novel anti-diabetic medication family, are renoprotective in diabetes, but a comparable benefit in chronic non-diabetic kidney diseases is still under investigation. This study aimed to elucidate the molecular mechanisms of linagliptin's (Lina) protective role in a rat model of chronic kidney injury caused by tacrolimus (TAC) independent of blood glucose levels. Thirty-two adult male Sprague Dawley rats were equally randomized into four groups and treated daily for 28 d as follows: The control group; received olive oil (1 mL/kg/d, subcutaneously), group 2; received Lina (5 mg/kg/d, orally), group 3; received TAC (1.5 mg/kg/d, subcutaneously), group 4; received TAC plus Lina concomitantly in doses as the same previous groups. Blood and urine samples were collected to investigate renal function indices and tubular injury markers. Additionally, signaling molecules, epithelial-mesenchymal transition (EMT), and fibrotic-related proteins in kidney tissue were assessed by enzyme-linked immunosorbent assay (ELISA) and Western blot analysis, immunohistochemical and histological examinations. Tacrolimus markedly induced renal injury and fibrosis as indicated by renal dysfunction, histological damage, and deposition of extracellular matrix (ECM) proteins. It also increased transforming growth factor ß1 (TGF-ß1), Smad4, p-extracellular signal-regulated kinase (ERK)1/2/ERK1/2, and p-P38/P38 mitogen-activated protein kinase (MAPK) protein levels. These alterations were markedly attenuated by the Lina administration. Moreover, Lina significantly inhibited EMT, evidenced by inhibiting Vimentin and α-smooth muscle actin (α-SMA) and elevating E-cadherin. Furthermore, Lina diminished hypoxia-related protein levels with a subsequent reduction in Snail and Twist expressions. We concluded that Lina may protect against TAC-induced interstitial fibrosis by modulating TGF-ß1 mediated EMT via Smad-dependent and independent signaling pathways.

Linagliptin ameliorates tacrolimus-induced renal injury: role of Nrf2/HO-1 and HIF-1α/CTGF/PAI-1.

BACKGROUND: Tacrolimus (TAC) is a frequently used immunosuppressive medication in organ transplantation. However, its nephrotoxic impact limits its long-term usage. This study aims to investigate the effect of linagliptin (Lina) on TAC-induced renal injury and its underlying mechanisms. METHODS AND RESULTS: Thirty-two Sprague Dawley rats were treated with TAC (1.5 mg/kg/day, subcutaneously) and/or Lina (5 mg/kg/day, orally) for 4 weeks. Histological examination was conducted, and serum and urinary biomarkers were measured to assess kidney function and integrity. Furthermore, ELISA, Western blot analysis and immunohistochemical assay were employed to determine signaling molecules of oxidative stress, profibrogenic, hypoxic, and apoptotic proteins. Tacrolimus caused renal dysfunction and histological deterioration evidenced by increased serum creatinine, blood urea nitrogen (BUN), urinary cystatin C, and decreased serum albumin as well as elevated tubular injury and interstitial fibrosis scores. Additionally, TAC significantly increased the expression of collagen type-1, alpha-smooth muscle actin (α-SMA), plasminogen activator inhibitor-1 (PAI-1), and transforming growth factor-beta1 (TGF-ß1) renal content. Moreover, TAC decreased the expression of nuclear factor erythroid-2-related factor2 (Nrf2), heme oxygenase 1 (HO-1), and mitochondrial superoxide dismutase (SOD2). In addition, TAC increased protein expression of hypoxia-inducible factor1-alpha (HIF-1α), connective tissue growth factor (CTGF), inducible nitric oxide synthase (iNOS), 8-hydroxy-2-deoxyguanosine (8-OHdG), as well as nitric oxide (NO), 4-hydroxynonenal, caspase-3 and Bax renal contents. Furthermore, TAC decreased Bcl-2 renal contents. The Lina administration markedly attenuated these alterations. CONCLUSION: Lina ameliorated TAC-induced kidney injury through modulation of oxidative stress, hypoxia, and apoptosis related proteins.

Ultrasound-Guided Suprazygomatic Sphenopalatine Ganglion Block for Postdural Puncture Headache Resistant to Epidural Blood Patch: A Case Report.

Even though epidural blood patch (EBP) is thought to be the definitive treatment for severe cases of postdural puncture headache (PDPH), it may be accompanied by complications like adhesion arachnoiditis, and cauda equina syndrome, especially if the injection is repeated. The sphenopalatine ganglion (SPG) block is a new minimally invasive technique for the treatment of PDPH, with variable results according to the clinical situation and deployed approach. We describe a case of PDPH resistant to EBP in which we successfully managed symptoms using ultrasound-guided suprazygomatic SPG block to deliver local anesthetic directly into pterygopalatine fossa, thus avoiding a second EBP.

Exploiting the role of plant growth promoting rhizobacteria in reducing heavy metal toxicity of pepper (Capsicum annuum L.).

Microorganisms are cost-effective and eco-friendly alternative methods for removing heavy metals (HM) from contaminated agricultural soils. Therefore, this study aims to identify and characterize HM-tolerant (HMT) plant growth-promoting rhizobacteria (PGPR) isolated from industry-contaminated soils to determine their impact as bioremediators on HM-stressed pepper plants. Four isolates [Pseudomonas azotoformans (Pa), Serratia rubidaea (Sr), Paenibacillus pabuli (Pp) and Bacillus velezensis (Bv)] were identified based on their remarkable levels of HM tolerance in vitro. Field studies were conducted to evaluate the growth promotion and tolerance to HM toxicity of pepper plants grown in HM-polluted soils. Plants exposed to HM stress showed improved growth, physio-biochemistry, and antioxidant defense system components when treated with any of the individual isolates, in contrast to the control group that did not receive PGPR. The combined treatment of the tested HMT PGPR was, however, relatively superior to other treatments. Compared to no or single PGPR treatment, the consortia (Pa+Sr+Pp+Bv) increased the photosynthetic pigment contents, relative water content, and membrane stability index but lowered the electrolyte leakage and contents of malondialdehyde and hydrogen peroxide by suppressing the (non) enzymatic antioxidants in plant tissues. In pepper, Cd, Cu, Pb, and Ni contents decreased by 88.0-88.5, 63.8-66.5, 66.2-67.0, and 90.2-90.9% in leaves, and 87.2-88.1, 69.4-70.0%, 80.0-81.3, and 92.3%% in fruits, respectively. Thus, these PGPR are highly effective at immobilizing HM and reducing translocation in planta. These findings indicate that the application of HMT PGPR could be a promising "bioremediation" strategy to enhance growth and productivity of crops cultivated in soils contaminated with HM for sustainable agricultural practices.

Characterization of Spodoptera littoralis (Lepidoptera: Noctuidae) resistance to indoxacarb: inheritance mode, realized heritability, and fitness costs.

Spodoptera littoralis (Boisd.) (Lepidoptera: Noctuidae) is a major economic pest attacking a variety of crops in Egypt and other Mediterranean countries. S. littoralis has developed resistance to both traditional and novel insecticides. The current study investigated S. littoralis resistance to indoxacarb regarding inheritance mode, realized heritability (h2), and fitness costs. An indoxacarb-resistant strain (Indoxa-SEL) was obtained by selecting a field strain with indoxacarb. Indoxa-SEL strain outperformed the susceptible one (Indoxa-S) by 29.77-fold after 16 consecutive generations of selection. Based on the LC50 values of the progenies of reciprocal crosses F1 (R♂ × S♀) and F1' (R♀ × S♂), S. littoralis resistance to indoxacarb was found to be autosomal and partially recessive. Chi-square tests for goodness-of-fit between observed and expected mortalities of self-bred F1 and resistant strain reciprocal crosses revealed that the resistance was controlled by multiple genes. The resistant strain had a relative fitness of 0.80, with significantly increased total preovipositional period of females, egg, larvae, pupae, preadult, adult, and total longevity period. The estimated realized heritability value in the Indoxa-SEL strain was 0.21. The current study will contribute to sustaining indoxacarb efficacy and designing effective resistance management programs against S. littoralis.

Climate controls on nitrate dynamics and gross nitrogen cycling response to nitrogen deposition in global forest soils.

Understanding the patterns and controls regulating nitrogen (N) transformation and its response to N enrichment is critical to re-evaluating soil N limitation or availability and its environmental consequences. Nevertheless, how climatic conditions affect nitrate dynamics and the response of gross N cycling rates to N enrichment in forest soils is still only rudimentarily known. Through collecting and analyzing 4426-single and 769-paired observations from 231 15N labeling studies, we found that nitrification capacity [the ratio of gross autotrophic nitrification (GAN) to gross N mineralization (GNM)] was significantly lower in tropical/subtropical (19%) than in temperate (68%) forest soils, mainly due to the higher GNM and lower GAN in tropical/subtropical regions resulting from low C/N ratio and high precipitation, respectively. However, nitrate retention capacity [the ratio of dissimilatory nitrate reduction to ammonium (DNRA) plus gross nitrate immobilization (INO3) to gross nitrification] was significantly higher in tropical/subtropical (86%) than in temperate (54%) forest soils, mainly due to the higher precipitation and GNM of tropical/subtropical regions, which stimulated DNRA and INO3. As a result, the ratio of GAN to ammonium immobilization (INH4) was significantly higher in temperate than in tropical/subtropical soils. Climatic rather than edaphic factors control heterotrophic nitrification rate (GHN) in forest soils. GHN significantly increased with increasing temperature in temperate regions and with decreasing precipitation in tropical/subtropical regions. In temperate forest soils, gross N transformation rates were insensitive to N enrichment. In tropical/subtropical forests, however, N enrichment significantly stimulated GNM, GAN and GAN to INH4 ratio, but inhibited INH4 and INO3 due to reduced microbial biomass and pH. We propose that temperate forest soils have higher nitrification capacity and lower nitrate retention capacity, implying a higher potential risk of N losses. However, tropical/subtropical forest systems shift from a conservative to a leaky N-cycling system in response to N enrichment.