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Based on traditional peace communication scholarship, this study, embedded in journalism studies and visual politics literature, analyzes photographs of conflict using war and peace frames and explores the role social media can play in digital peacebuilding practices. A content analysis of 674 visuals of the second deadliest terrorist attack in Pakistan posted on Twitter revealed the dominance of war photographs. The majority of the visual tweets were related to the afflicted victims and the visiting elites. Our analysis revealed that the visual narrative predominantly adopted a war approach. Results also showed significant variations in the war and peace narrative over time. Overall, this study challenges the views of peace journalism scholars that social media would lead to a more peace-oriented approach. We argue that peace narratives may be difficult to occur on digital platforms in securitized national conflicts where elites and a dominant public opinion oppose alternative perspectives.

The COVID-19 pandemic spread across the world in several days. This disease has badly affected corporations, industries, and educational institutions worldwide. The education sector suffered several crises, around 77 million students were affected and absent from class during the pandemic. Using remote learning during the pandemic was beneficial, but it was difficult to find comfort and dependability. The present study examines the challenges faced by Pakistani students and teachers in remote learning, academic performance, and satisfaction levels of students and teachers who have participated in remote learning during the COVID-19 pandemic. Based on the respondents’ comments, analyzed the demographic data and remote learning data using statistical calculations in the R language, and displayed the results in graphs. It used machine-learning models to calculate sentiment analysis results using the R language. According to the calculation results, the proposed study performs well using a support vector machine (SVM) and neural network (NNET), which give an accuracy of 83.5, while the accuracy of the k-nearest neighbor (KNN) is 69.9. The proposed study formulates suggestions for future work that are useful for improving the outcomes of remote learning.

Elevated sodium level (Na+) poses significant threat to crop plant physio-biochemical processes, leading to impaired growth followed by decline in productivity. Addressing this challenge, requires an eco-friendly and cost-effective strategy that enhances plant salt stress tolerance capacity. In this context, the exogenous source of plant growth regulators (PGRs) proved to be an efficient approach. Of various PGRs, salicylic acid (SA) is an emerging signaling molecule that boosts plant stress endurance mechanism. This study investigates SA-mediated salt stress tolerance in maize (Zea mays L.) seedlings, by examining morpho-physiological and biochemical traits. Maize seedlings were subjected to varying levels of salt stress (0, 25, 50, 75, 100, and 150 mM NaCl) for a period of 10-days. The results revealed that, a substantial decline in germination percentage, shoot and root length, plant biomass, vigour index, and various other physiological parameters under salt stress causing concentrations. Conversely, salt stress increased oxidative stress indicators, including hydrogen peroxide (H2O2) and malondialdehyde (MDA), osmolytes and elemental concentrations as well as antioxident enzymes (SOD, CAT, POX, APX, GR, AsA). However, the exogenous supplementation of SA at 0.1 mM significantly restored most morpho-physiological attributes in maize under salt stress conditions. This suggests that SA actively triggers the ascorbate-glutathione (AsA-GSH) pathway and other key enzymes, leading to sodium extrusion and improving antioxidant defense in maize seedlings. This finding provides valuable insights for maize farmers that employing SA could lead to improved maize production in saline soils.

Metal alloys like stainless steel, titanium, and cobalt-chromium alloys are preferable for bio-implants due to their exceptional strength, tribological properties, and biocompatibility. However, long-term implantation of metal alloys can lead to inflammation, swelling, and itching because of ion leaching. To address this issue, polymers are increasingly being utilized in orthopedic applications, replacing metallic components such as bone fixation plates, screws, and scaffolds, as well as minimizing metal-on-metal contact in total hip and knee joint replacements. Ceramics, known for their hardness, thermal barrier, wear, and corrosion resistance, find extensive application in electrochemical, fuel, and biomedical industries. This review delves into a variety of biocompatible materials engineered to seamlessly integrate with the body, reducing adverse reactions like inflammation, toxicity, or immune responses. Additionally, this review examines the potential of various biomaterials including metals, polymers, and ceramics for implant applications. While metallic biomaterials remain indispensable, polymers and ceramics show promise as alternative options. However, surface-modified metallic materials offer a hybrid effect, combining the strengths of different constituents. The future of biomedical implant materials lies in advanced fabrication techniques and personalized designs, facilitating tailored solutions for complex medical needs.

The production of new pavements involving recycled asphalt pavement (RAP) is beneficial for preserving petroleum asphalt and natural aggregates. However, increasing the RAP content raises performance concerns in new pavement, thus necessitating the use of rejuvenators. This research examined the potential of using petroleum sludge (PS) as a rejuvenator for RAP recycling. Gas chromatography-mass spectrometry (GCMS) detected the PS hydrocarbons involved in rejuvenation. The dynamic shear rheometer (DSR) provided the rheological data of rejuvenated binders. The rheological data were subsequently processed using response surface methodology (RSM) to develop rutting and fatigue models. RSM was also employed to model the Marshall and volumetric properties of the asphalt mixture. Atomic force microscopy (AFM) of PS rejuvenated RAP binder revealed a new microstructure containing protrusions that resembled the morphology of lightweight bitumen fractions. These rejuvenating effects were attributed to lightweight hydrocarbons of PS, which supplement the maltenes fractions in aged asphalt. The multi-objective optimization provided the RAP and bitumen content of 90% and 4.79% to meet the required PWD specifications.

Millions of lives are lost in road accidents annually, underscoring the severity of traffic incidents. Despite numerous studies on crash severity forecasting with static ensemble machine learning, the potential of Dynamic Ensemble Selection (DES) for combining classifiers and improving performance remains relatively unexplored in this field. In contrast to previous research focused on static ensemble machine learning models, our study introduces an interpretable Bayesian Optimized Dynamic Ensemble Selection strategy, reinforced with instance hardness and region of competence considerations, for crash risk assessment. Utilizing six algorithms – Random Forest, Extra Tree, Cat Boost, Light GBM, KT Boost, and XGBoost – optimized through cross-validation, we employed bagging as a hybrid ensemble selection criterion to ensure ensemble diversity for DES models. Addressing class imbalance with cost-sensitive learning, we evaluated six DES algorithms, ‘KNORA-E, KNORA-U, DES-KNN, DES-RRC, DES-KL, and META-DES’ using a pool of input classifiers, based on key metrics such as Balanced Accuracy Score, Sensitivity, G-mean, and Matthews Correlation Coefficient. Our results revealed that the KNORA-E ensemble with Cat Boost achieved the highest performance, with a Balanced Accuracy (BCA) of 69.3%, Matthews Correlation Coefficient (MCC) of 0.36, and a G-mean score of 69.10%. DES-RRC demonstrated notable performance across all base classifiers, particularly in addressing imbalanced classes, and DES-RRC with LightGBM emerged as the second-best performer. SHAP analysis for the KNORAE-Cat Boost model identified key factors in crash severity as, road user gender, airbag deployment, vehicle age and road surface conditions. This approach could be a valuable tool for informed decision-making and targeted interventions.

The construction industry plays a major role in the boost of the country’s economy, providing basic facilities for residential and creating thousands of job opportunities. During COVID-19, the construction sectors in Sindh Pakistan was highly suffered and leading to delays in the completion of projects. As the construction sector was globally affected, building construction projects were also affected by completing the projects on estimated time and cost. Thus, this research investigates the significant factors of time and cost that affected the Hyderabad building construction projects during COVID-19 situation. Questionnaire surveys were designed to collect data from the employees working on building projects in Sindh Pakistan. The collected data was analyzed through the Average Index method. Unsafe working environment; shortage of workers; and increasing project cost was observed as significant factors that were highly affected during COVID-19. The results and findings shall be supportive for stakeholders to take into consideration of factors in the early stage of the expected pandemic situation. This research suggested that the stakeholders shall modify or amend the contract clause regarding for pandemic situation and incorporate the identified factors in the contract that should be considered by stakeholders to save the time and cost of the projects.

The COVID-19 pandemic started in the last week of December, 2019. An emergency was declared throughout the globe as the virus spread over 208 counties within a short amount of time. This pandemic had significant negative impacts on common men living in densely populated countries, including Pakistan. Hence, this research aimed to record people’s perception of the 7th largest settlement in Pakistan, namely Hyderabad. This study mainly focused on socioeconomic and psychological parameters. The close-ended questionnaire was designed concerning the Depression, Anxiety, and Stress Scale (DASS-21). The DASS-21 is an optimal tool for recording the emotional values of depression, anxiety, and stress. A total of 400 questionnaires were filled out; they used a 5-point Likert scale. Significant socioeconomic issues were noted, such as lower household income, economic recession, job cuts, inaccessible Internet services during online teaching or working from home, etc. The primary challenges in the lockdown situation were Internet access (4.06) and anxiety (4.86) in the female population. There were higher levels of depression (N = 200), anxiety (N = 341), and stress (N = 125) in the local inhabitants. Other notable problems were illuminated, such as restrictions on social gatherings, electricity load shedding, and lower incomes. This study concludes that the degree of psychological problems varied according to the typology of gender. Based on study findings, this study recommends the prompt execution of policies considering possible future pandemics to restrain anxiety and depression in the female population. The local government is also advised to revitalize infrastructure to provide uninterrupted power supplies and Internet facilities. The income-generating channels should be open for lower-income households concerning future lockdowns.

Radial spokes (RS) are T-shaped multiprotein complexes on the axonemal microtubules. Repeated RS1, RS2, and RS3 couple the central pair to modulate ciliary and flagellar motility. Despite the cell type specificity of RS3 substructures, their molecular components remain largely unknown. Here, we report that a leucine-rich repeat-containing protein, LRRC23, is an RS3 head component essential for its head assembly and flagellar motility in mammalian spermatozoa. From infertile male patients with defective sperm motility, we identified a splice site variant of LRRC23. A mutant mouse model mimicking this variant produces a truncated LRRC23 at the C-terminus that fails to localize to the sperm tail, causing male infertility due to defective sperm motility. LRRC23 was previously proposed to be an ortholog of the RS stalk protein RSP15. However, we found that purified recombinant LRRC23 interacts with an RS head protein RSPH9, which is abolished by the C-terminal truncation. Evolutionary and structural comparison also shows that LRRC34, not LRRC23, is the RSP15 ortholog. Cryo-electron tomography clearly revealed that the absence of the RS3 head and the sperm-specific RS2-RS3 bridge structure in LRRC23 mutant spermatozoa. Our study provides new insights into the structure and function of RS3 in mammalian spermatozoa and the molecular pathogenicity of LRRC23 underlying reduced sperm motility in infertile human males.

In different heavy metals, cadmium is one of the acute toxins. It also interferes with various physiological processes in plants, such as photosynthesis, respiration, and enzyme activity. To improve the growth of plants in Cd stress, arbuscular mycorrhizae can play an imperative role. On the other hand, the use of quantum dots technology is also gaining the attention of scientists. That's why the current study investigates the effectiveness of using zinc quantum dot biochar (ZQDB) and arbuscular mycorrhizal fungi (AMF) in alleviating cadmium (Cd) stress in maize plants. The results showed that AMF+ZQDB performed significantly best at the highest level of 5Cd (5mgCd/kg soil) for enhancement in plant height (28.20 %), shoot dry weight (48.78 %), chlorophyll a (32.45 %), chlorophyll b (44.03 %) and total chlorophyll (22.02 %) compared to control (NoAMF+NoZQDB). A significant enhancement in photosynthetic rate (12.95 %) and transpiration rate (39.99 %) concentration of carbon dioxide also validated the effectiveness of AMF+ZQDB over control (NoAMF+NoZQDB) at 5Cd. For photochemical quenching decrease was 25.1 %, 2.98 %, 20.7 %, and 20.3 %, respectively, compared to the control group at 5Cd where NoAMF+NoZQDB, AMF, ZQDB, and AMF+ZQDB treatments were applied. AMF+ZQDB treatment of 5Cd showed a 30.22 % decrease in electron transport rate and 34.67 % decrease in non-photochemical quenching compared to control (NoAMF+NoZQDB). In conclusion, AMF + ZQDB is an effective amendment for alleviating Cd stress in maize by regulating biochemical and physiological attributes. Further investigations are recommended at the field level using different crops to validate the effectiveness of AMF + ZQDB as a promising amendment for minimizing Cd toxicity.

The present investigation was undertaken to standardize the media and the anti-browning regime in order to minimize the phenolic browning of an in vitro culture of Persian walnut cv. Sulaiman. The experiments involved two types of explants, forced and unforced shoot tips, two types of media, Driver and Kuniyuki Walnut (DKW) medium andMurashige and Skooģs (MS) medium, and three types of anti-browning agents, namely, Polyvinylpyrrolidone, ascorbic acid and activated charcoal at 150, 350 and 550 mg/L each. The investigation was replicated thrice under a completely randomized design. Forced shoot tips of cv. Sulaiman on DKW medium showed the best performance in terms of least browning (13.6 ± 10.5%) and highest survival percentage of explants (74.5 ± 2.4%) when treated with ascorbic acid at 550 mg/L. However, unforced shoot tips in MS medium did not perform well and manifested maximum browning (52.9 ± 5.2%). Based on the results, we conclude that incorporation of ascorbic acid in the DKW medium significantly reduced the media and explant browning, thus, it could set the basis of successful in vitro-propagation of walnuts.

In abiotic stresses, drought is the main problem in agricultural production which inhibits the plants to show off their genetic potential. Maize is not only the cereal crop of the world but also 3rd important cereal crop in Pakistan. Maize is drought-sensitive and affected at each growth and development stage. So, the organic amendment is not only the solution to mitigate the drought stress due to long-lasting moisture availability but also improves the growth, yield, quality, and nutrient uptake with improving soil properties. Therefore, a two-year field experiment during 2018 and 2019 was laid out at Agronomy Research Area, Department of Agronomy, Bahauddin Zakariya University, Multan, Pakistan. Treatments included pre-screened maize hybrids: P-1429 (drought-sensitive) and Dk-6724 (drought-tolerant); pre-optimized levels of each organic fertilizer source (OFS); recommended chemical fertilizer source (CS), 10 t/ha biochar (BC), 10 t/ha farmyard manure (F.M) and 10 t/ha poultry manure (P.M); and irrigation regimes i.e normal irrigation (Ck) 100 % field capacity and severe drought (SD) 50 % field capacity. The Experiment was designed in a randomized complete block design (RCBD) with a split-split plot arrangement and was replicated three times. Irrigation regimes were put in the main plot, organic fertilizer sources were put in the subplot and maize hybrids were put in the sub-sub plot. Different agronomic growth and yield attributes, quality attributes, crop physiology, soil physical properties, nutrient uptake, and activity of antioxidant enzymes were assessed. It resulted that in organic fertilizer sources application, 10 t/ha poultry manure and farmyard manure followed by biochar improved the growth and yield of maize hybrids significantly, under normal irrigation and severe drought. These also improve the quality of maize by improving the nutrient uptake and soil physical properties like increasing the soil porosity and decreasing the soil bulk density during consecutive years 2018 and 2019. It was also noticed that the application of organic fertilizers mitigated the adverse effect of drought by the antioxidant defense system with the production of SOD, POD and CAT.

Electric motorcycles (EMs) are gaining popularity in densely populated Asian countries, offering environmentally friendly solutions to combat traffic-related pollution. Governments and authorities are eager to promote EMs to reduce reliance on traditional fuel-based motorcycles. While prior research has explored the potential impacts of EMs, limited attention has been given to the adoption intentions of the Pakistani public. This study investigates the factors influencing the behavioral intentions of adopting EMs in Pakistan, employing an extended technology acceptance model (TAM) framework. The extended model incorporates perceived values and environmental concerns, along with perceived usefulness and perceived ease of use, to assess their impact on EM adoption intentions. Based on data collected from 228 respondents in Karachi, Pakistan, structural equation models were estimated to identify significant factors affecting EM adoption. Findings highlight the substantial influence of perceived value and environmental concern on behavioral intentions, with perceived ease of use playing a mediated role through perceived usefulness. Results suggest that effective marketing and user-friendly EM designs, coupled with well-crafted policies and education, can substantially boost EM adoption by the public, facilitating a shift toward sustainable transportation alternatives.

Genetic improvement of temperate fruit and nut crops through conventional breeding methods is not sufficient alone due to its extreme time-consuming, cost-intensive, and hard-to-handle approach. Again, few other constraints that are associated with these species, viz., their long juvenile period, high heterozygosity, sterility, presence of sexual incompatibility, polyploidy, etc., make their selection and improvement process more complicated. Therefore, to promote precise and accurate selection of plants based on their genotypes, supplement of advanced biotechnological tools, viz., molecular marker approaches along with traditional breeding methods, is highly required in these species. Different markers, especially the molecular ones, enable direct selection of genomic regions governing the trait of interest such as high quality, yield, and resistance to abiotic and biotic stresses instead of the trait itself, thus saving the overall time and space and helping screen fruit quality and other related desired traits at early stages. The availability of molecular markers like SNP (single-nucleotide polymorphism), DArT (Diversity Arrays Technology) markers, and dense molecular genetic maps in crop plants, including fruit and nut crops, led to a revelation of facts from genetic markers, thus assisting in precise line selection. This review highlighted several aspects of the molecular marker approach that opens up tremendous possibilities to reveal valuable information about genetic diversity and phylogeny to boost the efficacy of selection in temperate fruit crops through genome sequencing and thus cultivar improvement with respect to adaptability and biotic and abiotic stress resistance in temperate fruit and nut species.

Powdery mildews (PM) are common and severe pathogen groups that threaten plants, and PM resistance is complex and polygenic in cucumbers. Previously mlo-based resistance was reported in various plants, including cucumber, with generated loss-of CsaMLO function mutants. However, mlo-based resistance in cucumber is also complex and involves additional mechanisms such as hypersensitive response (HR) and papillae formation. For this reason, we focused on determining the mlo-based powdery mildew resistance mechanism in cucumber. CRISPR/Cas9 was used in the present study to generate loss-of-function mutants for CsaMLO1, CsaMLO8, and CsaMLO11 of PM susceptible ADR27 cucumber inbred lines and CsaMLO mutants were obtained and validated. Trypan Blue and DAB staining were performed to detect Podosphaera xanthii germination/penetration rates and accumulation of Reactive Oxygen Species (ROS). Our results indicate that PM-susceptibility associated CsaMLOs in cucumber are negative regulators in different defense mechanisms against powdery mildew at early and late stages of infection. Further, the experiment results indicated that CsaMLO8 mutation-based resistance was associated with the pre-invasive response, while CsaMLO1 and CsaMLO11 could be negative regulators in the post-invasive defense response in cucumber against P. xanthii. Although the loss-of CsaMLO8 function confers the highest penetration resistance, CsaMLO1 and CsaMLO11 double mutations could be potential candidates for HR-based resistance against PM pathogen in cucumber. These results highlighted the crucial role of CRISPR/Cas9 to develop PM resistant cucumber cultivars, possessing strong pre-invasive defense with CsaMLO8 or post-invasive with CsaMLO1/CsaMLO11 mutations.

Article highlights Lime columns can be used to increase load carrying capacity of soft soils, especially in soils having relatively higher shear strength. In case of group columns, the spacing should not be more than two times the diameter of the column. The length of the lime columns should not be more than four times the diameter for better results.

Human convey their message in different forms. Expressing their emotions and moods through their facial expression is one of them. In this work, to avoid the traditional process of feature extraction (Geometry based method, Template based method, and Appearance based method), CNN model is used as a feature extractor for emotion detection using facial expression. In this study we also used three pre-trained models VGG-16, ResNet-50, Inception-V3. This Experiment is done on Fer-2013 facial expression dataset and Cohn Extended (CK+) dataset. By using FER-2013 dataset the accuracy rates for CNN, ResNet-50, VGG-16 and Inception-V3 are 76.74%, 85.71%, 85.78%s, 97.93% respectively. Similarly, the experimental results using CK+ dataset showed the accuracy rates for CNN, ResNet- 50, VGG-16 and Inception-V3 are 84.18%, 92.91%, 91.07%, and 73.16% respectively. The experimental results showed exceptional results for Inception-V3 with 97.93% using FER-2013 dataset and ResNet-50 with 91.92% using CK+ dataset.

Soybean is one of the largest sources of protein and oil in the world and is also considered a “super crop” due to several industrial advantages. However, enhanced acreage and adoption of monoculture practices rendered the crop vulnerable to several diseases. Phytophthora root and stem rot (PRSR) caused by Phytophthora sojae is one of the most prevalent diseases adversely affecting soybean production globally. Deployment of genetic resistance is the most sustainable approach for avoiding yield losses due to this disease. PRSR resistance is complex in nature and difficult to address by conventional breeding alone. Genetic mapping through a cost-effective sequencing platform facilitates identification of candidate genes and associated molecular markers for genetic improvement against PRSR. Furthermore, with the help of novel genomic approaches, identification and functional characterization of Rps (resistance to Phytophthora sojae) have also progressed in the recent past, and more than 30 Rps genes imparting complete resistance to different PRSR pathotypes have been reported. In addition, many genomic regions imparting partial resistance have also been identified. Furthermore, the adoption of emerging approaches like genome editing, genomic-assisted breeding, and genomic selection can assist in the functional characterization of novel genes and their rapid introgression for PRSR resistance. Hence, in the near future, soybean growers will likely witness an increase in production by adopting PRSR-resistant cultivars. This review highlights the progress made in deciphering the genetic architecture of PRSR resistance, genomic advances, and future perspectives for the deployment of PRSR resistance in soybean for the sustainable management of PRSR disease.

The exponential growth in online reviews and recommendations availability drives sentiment classification, an interesting topic in industrial research. There is a vital requirement for organizations to explore client behaviour to assess the competitive business environment. This study aspires to examine and predict customer reviews using Transfer learning (TL) approaches. Reviews can span so many domains that it is challenging to gather annotated training data for all of them. Hence, this paper proposed an annotation algorithm to label a large unlabeled dataset. These reviews must be pulled and examined to predict the sentiment polarity, whether the review is positive, neutral, or negative. We propose a deep learning-based approach that learns to extract a meaningful representation for each review in an unsupervised fashion. Sentiment classifiers trained with this high-level feature representation outperform state-of-the-art methods on a benchmark of reviews of cosmetics brands on Amazon or other platforms. Using the BERT for sentiment analysis, we achieved the highest accuracy of 93.21% compared to previous studies.

Google Play Store is a popular distribution channel with millions of applications. WhatsApp is the most downloaded communication application on Play Store. A few months ago, WhatsApp changed its privacy policy, triggering a wave of user reviews outrage. Privacy is essential in the application; users are worried about their data security and privacy. A computational system must be required to analyze the user’s reviews for WhatsApp authority to make better policies. This study aims to develop a deep learning-based model for automatically assessing reviews that can be adapted for future data analysis. We proposed a deep learning methodology by using Aspect-based sentiment analysis (ABSA) utilizing the communication app reviews scraped from the Google play store using the Google Play scrapper application. This study uses the text mining technique for ABSA on the user’s reviews. For Topic extraction, we have used Latent Dirichlet Allocation (LDA) and the deep learning method Long Short-Term Memory (LSTM) for topic classification. The results show that our proposed model gives us a promising outcome with 90% accuracy by using the LSTM model. WhatsApp authority can use the results to optimize communication applications by adding more efficient features and updating them.

Bacterial adhesion potential constitutes the transition of bacteria from the planktonic to the static phase by promoting biofilm formation, which plays a significant role in plant-microbial interaction in the agriculture industry. In present study, the adhesion potential of five soil-borne bacterial strains belonging to different genera was studied. All bacterial strains were capable of forming colonies and biofilms of different levels of firmness on polystyrene. Significant variation was observed in hydrophobicity and motility assays. Among the five bacterial strains (SH-6, SH-8, SH-9, SH-10, and SH-19), SH-19 had a strong hydrophobic force, while SH-10 showed the most hydrophilic property. SH-6 showed great variability in motility; SH-8 had a swimming diffusion diameter of 70 mm, which was three times higher than that of SH-19. In the motility assay, SH-9 and SH-10 showed diffusion diameters of approximately 22 mm and 55 mm, respectively. Furthermore, among the five strains, four are predominately electron donors and one is electron acceptors. Overall, positive correlation was observed among Lewis acid base properties, hydrophobicity, and biofilm forming ability. However, no correlation of motility with bacterial adhesion could be found in present experimental work. Scanning electron microscopy images confirmed the adhesion potential and biofilm ability within extra polymeric substances. Research on the role of adhesion in biofilm formation of bacteria isolated from plants is potentially conducive for developing strategies such as plant–microbial interaction to mitigate the abiotic stress.

High-throughput sequencing technologies (HSTs) have revolutionized crop breeding. The advent of these technologies has enabled the identification of beneficial quantitative trait loci (QTL), genes, and alleles for crop improvement. Climate change have made a significant effect on the global maize yield. To date, the well-known omic approaches such as genomics, transcriptomics, proteomics, and metabolomics are being incorporated in maize breeding studies. These approaches have identified novel biological markers that are being utilized for maize improvement against various abiotic stresses. This review discusses the current information on the morpho-physiological and molecular mechanism of abiotic stress tolerance in maize. The utilization of omics approaches to improve abiotic stress tolerance in maize is highlighted. As compared to single approach, the integration of multi-omics offers a great potential in addressing the challenges of abiotic stresses of maize productivity.

Cadmium (Cd) is a heavy metal that neutrally occurs in soil. It is carcinogenic in humans and caused a significant decline in the plant’s growth when up has taken beyond the threshold limit. The fertilizers, manure, sewage sludge, and aerial deposition are the main source of cadmium contamination in soil. Furthermore, poor soil organic matter is also one of the allied factors which facilitate the development of Cd toxicity in soil. The decomposition resistance nature of biochar makes it an effective amendment for cadmium remediation. Through crop production, Cd enters the food system. Individual studies on biochar and compost are found in the literature but the combined effect of biochar and compost are rarely documented especially in maize crops. The current pot study was conducted in Pesticide Quality Control Laboratory, Multan, Pakistan. However, the current study was novel and conducted by using compost mixed biochar (CB) against Cd toxicity in maize. Four application rates of CB i.e., 0, 0.50, 0.75 and 1.00% (1.00CB) were applied under 3 levels of Cd i.e., 0 (0Cd), 2.5 (2.5Cd) and 5 mg Cd kg−1 soil (5.0Cd). Overall, results indicated that 1.00%CB remained significantly best at higher 5.0Cd for improvement in soil organic matter, plant height, root length, number of leaves, leaves fresh and dry weight, plant fresh and dry weight, chlorophyll a, b, total and carotenoids. A significant decrease in soil pHs, leaves anthocyanin and lycopene also validated the efficacious functioning of 1.00%CB over control in 2.5 and 5.0Cd. In conclusion, the use of 1.00%CB is a better approach to decrease Cd harmful effects to improve gas exchange attributes, growth and chlorophyll contents in maize. Long-term research is required on co-composted biochar toward mitigation of cadmium toxicity under different geographical locations.

Heavy metal (HM) contamination resulting from industrialization and urbanization during the Anthropocene along with plant invasion can severely threaten the growth and adaptation of local flora. Invasive alien plant species generally exhibit a growth pattern consistent with their functional traits in non-contaminated environments in the introduced range. However, it remains unclear whether invasive alien plants have an advantage over native plants in contaminated environments and whether this growth pattern is dependent on the adaptation of their leaf functional traits. Here, we selected two congeneric pairs of invasive alien and native grasses that naturally co-exist in China and are commonly found growing in contaminated soil. To evaluate the effect of cadmium (Cd) on the structural and physiological leaf traits, we grew all four species in soil contaminated without or with 80 mg/kg Cd. Invasive plants contained significantly higher concentrations of Cd in all three organs (leaf, stem, and root). They displayed a higher transfer factor and bioconcentration factor (BCF) of shoot and root than natives, indicating that invasive species are potential Cd hyperaccumulators. Invasive plants accumulated polyphenol oxidase (PPO) to higher levels than natives and showed similar patterns of leaf structural and physiological traits in response to changes in Cd bioconcentration. The quantifiable leaf structural traits of invasive plants were significantly greater (except for stomatal density and number of dead leaves) than native plants. Leaf physiological traits, chlorophyll content, and flavonoid content were also significantly higher in invasive plants than in natives under Cd stress conditions after 4 weeks, although nitrogen balance index (NBI) showed no significant difference between the two species. Chlorophyll fluorescence parameters decreased, except for the quantum yield of photosystem II (ΦPSII) and the proportion of open photosystem II (qP), which increased under Cd stress conditions in both species. However, invasive plants exhibited higher fluorescence parameters than natives under Cd stress, and the decrement observed in invasive plants under Cd stress was greater than that in natives. High Cd adaptation of invasive grasses over natives suggests that invasive plants possess optimal leaf structural and physiological traits, which enable them to adapt to stressful conditions and capture resources more quickly than natives. This study further emphasizes the potential invasion of alien plants in contaminated soil environments within the introduced range. To a certain extent, some non-invasive alien plants might adapt to metalliferous environments and serve as hyperaccumulator candidates in phytoremediation projects in contaminated environments.

Road pavement is a structure that expose to various climate conditions. To make it more durable, modification of asphalt binder with polymer is a popular option. However, to maintain the environmental sustainability, the mixing and compaction temperature needs to be reduced. Warm Mix Asphalt additive had been widely used for this purpose. In this research, the impact of a polymer modified asphalt binder, PG76 together with a chemical WMA additive, Rediset on groundwater and soil contamination was investigated. The effect of Rediset on PG76 in terms of viscosity and activation energy was also studied via the rotational viscosity test. Even though it was found that Rediset might affect the viscosity of PG76, the activation energy shows independent values. ATR-FTIR was employed to understand the reaction between these two substance. It was found that there had been no chemical reaction between PG76 and Rediset. As a complementary, AFM was utilised to observe the surface characteristics at micro-scale. It appeared that Rediset did contribute to the binder’s surface morphology. Finally, the modified tank leaching test together with analysis by ICP-MS, discovered that after 64 days submerged under flood, Rediset-PG76 had no effect on the adjacent water source and soil.

Percutaneous mitral valve edge-to-edge repair with MitraClip (Abbott, Abbott Park, Illinois) has emerged as an effective and safe treatment for symptomatic mitral regurgitation in suitable patients. The safety of the MitraClip procedure is well established, and the rate of major complications is 4.35%. We present 4 cases of mitral regurgitation in patients who had complications following the MitraClip procedure. (Level of Difficulty: Intermediate.)

Global warming and depletion of fossil fuels have urged the world to control their impacts and find clean and green energy sources. Due to this paradigm shift, renewable energy resources (RESs) have received tremendous attention around the globe and amongst other RESs, wind energy has been proving itself a promising renewable resource. However, still, the proper selection of wind turbines (WTs) and their installation is considered a major challenge. Presently, due to the economic boom of Pakistan as a regional power under the China Pakistan Economic Corridor (CPEC) and increasing energy demand, it needs to meet the energy shortage. This paper aims to conduct a pre-feasibility ainvestigation of wind farm exploitation at Gwadar and Quetta, major cities of Baluchistan province in Pakistan by harnessing the wind energy potential and electricity generation cost through different WT models. The wind speed (WS) data is recorded by a professional wind mast at different measurement heights during F.Y 2016 and analyzed using Five approaches, Modified Maximum Likelihood Method (MMLM), Graphical Method (GM), Empirical Method of Lysen (EML), Empirical Method of Jestus (EMJ) and Energy Pattern Factor Method (EPF) at the proposed site and EPF shows the best performance than other approaches. Different WTs models are also evaluated and out of them, the GW121 WT gives the lowest cost in dollars and lowest payback period at each site so it can be recommended as one of the most feasible WT for electricity generation for powering local communities at the proposed sites.

The critical care transport service (CCT) is an important factor in the successful delivery of high-quality services by any healthcare system or programme. It is conducted by well-trained, qualified paramedics, nurses and respiratory therapists. The cornerstone of CCT is to ensure, during the transport of patients, continuity of the critical care initiated by the referring provider until arrival at the receiving provider. We report a case of a patient with acute aortic dissection who presented to a general hospital in Riyadh, requiring emergent advanced surgical intervention that is available only in tertiary hospitals. The coordination of the patient’s transfer was arranged by the emergency medical services’ team leader within the health cluster that includes both the general and tertiary hospitals involved in the case. This process resulted in the required service being provided within record time, with excellent outcomes. This case report highlights the impact and importance of inter-facility critical care transport systems.

Plants defend themselves against ecological stresses including drought. Therefore, they adopt various strategies to cope with stress, such as seepage and drought tolerance mechanisms, which allow plant development under drought conditions. There is evidence that microbes play a role in plant drought tolerance. In this study, we presented a review of the literature describing the initiation of drought tolerance mediated by plant inoculation with fungi, bacteria, viruses, and several bacterial elements, as well as the plant transduction pathways identified via archetypal functional or morphological annotations and contemporary “omics” technologies. Overall, microbial associations play a potential role in mediating plant protection responses to drought, which is an important factor for agricultural manufacturing systems that are affected by fluctuating climate.

An increase in temperature and extreme heat stress is responsible for the global reduction in maize yield. Heat stress affects the integrity of the plasma membrane functioning of mitochondria and chloroplast, which further results in the over-accumulation of reactive oxygen species. The activation of a signal cascade subsequently induces the transcription of heat shock proteins. The denaturation and accumulation of misfolded or unfolded proteins generate cell toxicity, leading to death. Therefore, developing maize cultivars with significant heat tolerance is urgently required. Despite the explored molecular mechanism underlying heat stress response in some plant species, the precise genetic engineering of maize is required to develop high heat-tolerant varieties. Several agronomic management practices, such as soil and nutrient management, plantation rate, timing, crop rotation, and irrigation, are beneficial along with the advanced molecular strategies to counter the elevated heat stress experienced by maize. This review summarizes heat stress sensing, induction of signaling cascade, symptoms, heat stress-related genes, the molecular feature of maize response, and approaches used in developing heat-tolerant maize varieties.

Moringa oleifera, the best known of the thirteen species of the genus Moringacae, has achieved importance due to its multipurpose usage with high nutritional value. There is very little work has been done in the advancement of moringa varieties in Pakistan. Thus, it needs to develop a new variety of moringa with better nutritional value. The agrarian performs many experiments like interbreeding of Moringa oleifera germplasm with exotic germplasm. Furthermore, they grow it in the nursery and then move it on the field, which almost took six months in a traditional approach. It consumes various resources and time to access the quality of newly developed varieties. This work aims to use machine learning and deep learning approaches to reduce the utilization of various resources and time which is used by the agrarian to develop a new moringa variety. We used machine learning and deep learning approaches to make predictions about new varieties before their proper plantation. In this research work, we took two moringa parents’ varieties with their required features like plant height, protein, potassium. We trained machine learning and deep learning models on the feature values of parents’ varieties. Our proposed machine learning model made the best predictions, using parents’ plant features to determine these parameter values in their offspring varieties, which will help to choose the best interbreed variety of moringa oleifera.

Media is considered the forth pillar of any modern day state as it plays a very vital in creating and shaping of public opinion and building a society. This research focuses on the role of media in the upbringing of the young generation. The study comprises of few practical definitions and kinds of media. The research highlights the means and methods in which media influences the character building of little kids. The research brings to lights the positive and negative impacts of media on the character building of young kids.

Gradually rising atmospheric temperature is the vital component of the environment, which is anticipated as the riskiest abiotic stress for crop growth. Nanotechnology revolutionizing the agricultural sectors, notably, zinc oxide nanoparticles (nano-ZnO) has captured intensive research interests due to their distinctive properties and numerous applications against abiotic stresses. Mungbean (Vigna radiata L.), being a summer crop, is grown all over the world at an optimum temperature of 28–30°C. A rise in temperature above this range, particularly during the flowering stage, can jeopardize the potential performance of the plant. Hence, an outdoor study was performed to evaluate the effect of multiple suspensions of nano-ZnO (0, 15, 30, 45, and 60 mg l–1) on physicochemical attributes and yield of mungbean crop under heat stress. Heat stress was induced by fine-tuning of sowing time as: S1 is the optimal sowing time having day/night temperatures 40/25°C during the flowering stage. In vitro studies on Zn release from nano-ZnO by inductively coupled plasma mass spectroscopy (ICPMS) disclosed that the Zn release and particles uptake from nano-ZnO were concentration-dependent. Exogenous foliar application of nano-ZnO significantly upstreamed the production of antioxidants and osmolytes to attenuate the shocks of heat stress in S2 and S3. Likewise, nano-ZnO substantially rebated the production of reactive oxygen species in both S2 and S3 that was associated with curtailment in lipid peroxidation. Adding to that, foliar-applied nano-ZnO inflates not only the chlorophyll contents and gas exchange attributes, but also the seeds per pod (SPP) and pods per plant (PPP), which results in the better grain yield under heat stress. Thus, among all the sowing dates, S1 statistically performed better than S2 and S3, although foliar exposure of nano-ZnO boosted up mungbean performance under both the no heat and heat-induced environments. Hence, foliar application of nano-ZnO can be suggested as an efficient way to protect the crop from heat stress-mediated damages with the most negligible chances of nanoparticles delivery to environmental compartments that could be possible in case of soil application.

Recently food shortage has become the major flagging scenario around the globe. To resolve this challenge, there is dire need to significantly increase crop productivity per unit area. In the present study, 24 genotypes of rice were grown in pots to assess their tillering number, number of primary and secondary branches per panicle, number of grains per panicle, number of grains per plant, and grain yield, respectively. In addition, the potential function of miR156 was analyzed, regulating seed sequence in rice. Furthermore, OsSPL14 gene for miR156 was sequenced to identify additional mutations within studied region. The results demonstrated Bas-370 and L-77 showed highest and lowest tillers, respectively. Bas-370, Rachna basmati, Bas-2000, and Kashmir Basmati showed high panicle branches whereas, L-77, L-46, Dilrosh, L-48, and L-20 displayed lowest panicle branches. Bas-370 and four other studied accessions contained C allele whereas, L-77 and 18 other investigated accessions had heterozygous (C and T) alleles in their promoter region. C-T allelic mutation was found in 3rd exon of the OsSPL14 gene. The sequence analysis of 12 accessions revealed a novel mutation (C-T) present ~2bp upstream and substitution of C-A allele. However, no significant correlation for novel mutation was found for tillering and panicle branches in studied rice accessions. Taken together present results suggested novel insight into the binding of miR156 to detected mutation found in 3rd exon of the OsSPL14 gene. Nevertheless, L-77, L-46, Dilrosh, L-48, and L-20 could be used as potential breeding resource for improving panicle architecture contributing yield improvement of rice crop.

This experimental work explored the synergic effect of millet husk ash (MHA) and wheat straw ash (WSA) on the fresh and hardened properties of metakaolin-based self-compacting geopolymer concrete. An equal amount of MHA and WSA contents at 2.5%, 5%, 7.5% and 10% were utilized as a partial replacement of metakaolin in the mixes. The filling ability (slump flow, V-Funnel, and T50 flow) and passing ability (J-Ring and L-box) of fresh SCGC mixture were determined. The study further determined the density, compressive, split tensile and flexural strength and permeability of hardened SCGC mixes. The results showed that both MHA and WSA addition somewhat reduced in workability of fresh SCGC mixes. However, the hardened properties were significantly enhanced, a development that was more pronounced in the mix having 5% each of MHA and WSA with compressive strength, split tensile strength, and flexural strength of 53.80 MPa, 4.82 MPa, and 5.15 MPa, respectively. The water penetration depth and density of SCGC mixes lessen as the MHA and WSA contents were increased beyond 10%. Overall, the study recommends a combined use of 5% each of MHA and WSA for metakaolin-based geopolymer SCC production to ensure optimal performance.

Triticum aestivum, commonly known as bread wheat, is one of the most cultivated crops globally. Due to its increasing demand, wheat is the source of many nutritious products including bread, pasta, and noodles containing different types of seed storage proteins. Wheat seed storage proteins largely control the type and quality of any wheat product. Among various unique wheat products, bread is the most consumed product around the world due to its fast availability as compared to other traditional food commodities. The production of highly nutritious and superior quality bread is always a matter of concern because of its increasing industrial demand. Therefore, new and more advanced technologies are currently being applied to improve and enrich the bread, having increased fortified nutrients, gluten-free, highly stable with enhanced shelf-life, and long-lasting. This review focused on bread proteins with improving wheat qualities and nutritional properties using modern technologies. We also describe the recent innovations in processing technologies to improve various quality traits of wheat bread. We also highlight some modern forms of bread that are utilized in different industries for various purposes and future directions.

Plant pathology has been revolutionized by the emergence and intervention of next-generation sequencing technologies (NGS) which provide a fast, cost-effective, and reliable diagnostic for any class of pathogens. NGS has made tremendous advancements in the area of research and diagnostics of plant infecting viromes and has bridged plant virology with other advanced research fields like genome editing technologies. NGS in a broader perspective holds the potential for plant health improvement by diagnosing and mitigating the new or unusual symptoms caused by novel/unidentified viruses. CRISPR-based genome editing technologies can enable rapid engineering of efficient viral/viroid resistance by directly targeting specific nucleotide sites of plant viruses and viroids. Critical genes such as eIf (iso) 4E or eIF4E have been targeted via the CRISPR platform to produce plants resistant to single-stranded RNA (ssRNA) viruses. CRISPR/Cas-based multi-target DNA or RNA tests can be used for rapid and accurate diagnostic assays for plant viruses and viroids. Integrating NGS with CRISPR-based genome editing technologies may lead to a paradigm shift in combating deadly disease-causing plant viruses/viroids at the genomic level. Furthermore, the newly discovered CRISPR/Cas13 system has unprecedented potential in plant viroid diagnostics and interference. In this review, we have highlighted the application and importance of sequencing technologies on covering the viral genomes for precise modulations. This review also provides a snapshot vision of emerging developments in NGS technologies for the characterization of plant viruses and their potential utilities, advantages, and limitations in plant viral diagnostics. Furthermore, some of the notable advances like novel virus-inducible CRISPR/Cas9 system that confers virus resistance with no off-target effects have been discussed.

Global agriculture production is under serious threat from rapidly increasing population and adverse climate changes. Food security is currently a huge challenge to feed 10 billion people by 2050. Crop domestication through conventional approaches is not good enough to meet the food demands and unable to fast-track the crop yields. Also, intensive breeding and rigorous selection of superior traits causes genetic erosion and eliminates stress-responsive genes, which makes crops more prone to abiotic stresses. Salt stress is one of the most prevailing abiotic stresses that poses severe damages to crop yield around the globe. Recent innovations in state-of-the-art genomics and transcriptomics technologies have paved the way to develop salinity tolerant crops. De novo domestication is one of the promising strategies to produce superior new crop genotypes through exploiting the genetic diversity of crop wild relatives (CWRs). Next-generation sequencing (NGS) technologies open new avenues to identifying the unique salt-tolerant genes from the CWRs. It has also led to the assembly of highly annotated crop pan-genomes to snapshot the full landscape of genetic diversity and recapture the huge gene repertoire of a species. The identification of novel genes alongside the emergence of cutting-edge genome editing tools for targeted manipulation renders de novo domestication a way forward for developing salt-tolerance crops. However, some risk associated with gene-edited crops causes hurdles for its adoption worldwide. Halophytes-led breeding for salinity tolerance provides an alternative strategy to identify extremely salt tolerant varieties that can be used to develop new crops to mitigate salinity stress.

Carbon footprint reduction, recompense depletion of natural resources, as well as waste recycling are nowadays focused research directions to achieve sustainability without compromising the concrete strength parameters. Therefore, the purpose of the present study is to utilize different dosages of marble waste aggregates (MWA) and stone dust (SD) as a replacement for coarse and fine aggregate, respectively. The MWA with 10 to 30% coarse aggregate replacement and SD with 40 to 50% fine aggregate replacement were used to evaluate the physical properties (workability and absorption), durability (acid attack resistance), and strength properties (compressive, flexural, and tensile strength) of concrete. Moreover, statistical modeling was also performed using response surface methodology (RSM) to design the experiment, optimize the MWA and SD dosages, and finally validate the experimental results. Increasing MWA substitutions resulted in higher workability, lower absorption, and lower resistance to acid attack as compared with controlled concrete. However, reduced compressive strength, flexural strength, and tensile strength at 7-day and 28-day cured specimens were observed as compared to the controlled specimen. On the other hand, increasing SD content causes a reduction in workability, higher absorption, and lower resistance to acid attack compared with controlled concrete. Similarly, 7-day and 28-day compressive strength, flexural strength, and tensile strength of SD-substituted concrete showed improvement up to 50% replacement and a slight reduction at 60% replacement. However, the strength of SD substituted concrete is higher than controlled concrete. Quadratic models were suggested based on a higher coefficient of determination (R2) for all responses. Quadratic RSM models yielded R2 equaling 0.90 and 0.94 for compressive strength at 7 days and 28 days, respectively. Similarly, 0.94 and 0.96 for 7-day and 28-day flexural strength and 0.89 for tensile strength. The optimization performed through RSM indicates that 15% MWA and 50% SD yielded higher strength compared to all other mixtures. The predicted optimized data was validated experimentally with an error of less than 5%.

In supervised machine learning, specifically in classification tasks, selecting and analyzing the feature vector to achieve better results is one of the most important tasks. Traditional methods such as comparing the features’ cosine similarity and exploring the datasets manually to check which feature vector is suitable is relatively time consuming. Many classification tasks failed to achieve better classification results because of poor feature vector selection and sparseness of data. In this paper, we proposed a novel framework, topic2features (T2F), to deal with short and sparse data using the topic distributions of hidden topics gathered from dataset and converting into feature vectors to build supervised classifier. For this we leveraged the unsupervised topic modelling LDA (latent dirichlet allocation) approach to retrieve the topic distributions employed in supervised learning algorithms. We made use of labelled data and topic distributions of hidden topics that were generated from that data. We explored how the representation based on topics affect the classification performance by applying supervised classification algorithms. Additionally, we did careful evaluation on two types of datasets and compared them with baseline approaches without topic distributions and other comparable methods. The results show that our framework performs significantly better in terms of classification performance compared to the baseline(without T2F) approaches and also yields improvement in terms of F1 score compared to other compared approaches.

In this study, we analyze the state of information warfare on Twittersphere between India and Pakistan in the wake of Pulwama attack in Kashmir region and the subsequent surgical strikes by Indian forces inside Pakistan. We selected two leading Twitter hashtags on the conflict from the two countries each. A total of 20,000 tweets were manually analyzed. Contrary to the existing scholarship on digital information warfare, we found citizens from both countries produced most of the content. Among the citizens, those Twitter handles that showed affiliations with the heads of governments that we consider as trolls were the leading contributors. Moreover, the study found that contributors from the two countries mainly posted on their own hashtags and did not engage in counter-arguments with the contributors from other country. This resulted in overwhelming support for the two countries in their own assorted hashtags and outright criticism in the hashtags originating from the other country.

Climate change is a threat to global food security due to the reduction of crop productivity around the globe. Food security is a matter of concern for stakeholders and policymakers as the global population is predicted to bypass 10 billion in the coming years. Crop improvement via modern breeding techniques along with efficient agronomic practices innovations in microbiome applications, and exploiting the natural variations in underutilized crops is an excellent way forward to fulfill future food requirements. In this review, we describe the next-generation breeding tools that can be used to increase crop production by developing climate-resilient superior genotypes to cope with the future challenges of global food security. Recent innovations in genomic-assisted breeding (GAB) strategies allow the construction of highly annotated crop pan-genomes to give a snapshot of the full landscape of genetic diversity (GD) and recapture the lost gene repertoire of a species. Pan-genomes provide new platforms to exploit these unique genes or genetic variation for optimizing breeding programs. The advent of next-generation clustered regularly interspaced short palindromic repeat/CRISPR-associated (CRISPR/Cas) systems, such as prime editing, base editing, and de nova domestication, has institutionalized the idea that genome editing is revamped for crop improvement. Also, the availability of versatile Cas orthologs, including Cas9, Cas12, Cas13, and Cas14, improved the editing efficiency. Now, the CRISPR/Cas systems have numerous applications in crop research and successfully edit the major crop to develop resistance against abiotic and biotic stress. By adopting high-throughput phenotyping approaches and big data analytics tools like artificial intelligence (AI) and machine learning (ML), agriculture is heading toward automation or digitalization. The integration of speed breeding with genomic and phenomic tools can allow rapid gene identifications and ultimately accelerate crop improvement programs. In addition, the integration of next-generation multidisciplinary breeding platforms can open exciting avenues to develop climate-ready crops toward global food security.

This article provides a comparative knowledge of predicted and measured settlements of road embankments with prefabricated vertical drains (PVDs). The emphasis of this study was to investigate and back-analyse the ratio of horizontal permeability in an undisturbed area to a smeared zone, which affects the behaviour of vertical drains. Two models of PVDs in soft ground were developed by utilising a plane strain 2D numerical approach based on the equivalent permeability. Suggestions for the improvement of numerical accuracy of the soft ground beneath road embankments have been made in regards to the obtained results. The employment of the equivalent horizontal permeability in numerical analysis produced significantly similar results to those of the measured values. Furthermore, a smear effect permeability ratio of 300 produced a considerably accurate result with a model based on the equivalent horizontal permeability and measured data. Lastly, the smear effect ratio of 6 using the equivalent horizontal permeability approach was employed in order to predict the behaviour of vertical drains in the soft grounds under road embankments.

Powdery mildew is an omnipresent disease that reduces the yield and quality of pea crops (Pisum sativum L.). To examine the powdery mildew pathogen’s morphological, molecular, and genetic diversity, we collected samples of powdery mildew-affected pea crops from ten distinct locations in the Nilgiris district of Tamil Nadu, India. The pathogen Erysiphe pisi was identified morphologically based on anamorphic characters. Molecular identification of E. pisi isolates was befitted by targeting the internal transcribed spacer (ITS) region of rDNA and specific primers of powdery mildew fungi. The genetic variation between ten different E. pisi isolates collected from topographically distinct mountainous areas was studied using random amplified polymorphic (RAPD). Based on its morphological characteristics, the powdery mildew fungus presented high similarities to E. pisi. Molecular characterization of the ITS rDNA of E. pisi produced 650 bp nucleotides, PMITS (powdery mildew-internal transcribed region) primers produced 700 bp nucleotides, and an Erysiphe specific ITS primer pair amplified and synthesized 560 bp nucleotides. According to the findings, the collected E. pisi strains exhibited a low level of genetic diversity and only a slight differential in virulence on the host. In the study, E. pisi isolates from Anumapuram, Emerald Valley, Indira Nagar, and Thuneri showed a greater disease incidence in the natural field conditions and shared the same genetic lineage with other isolates in UPGMA hierarchical cluster analysis based on RAPD markers. There was no evidence of a link between the occurrence of the disease and these grouped populations.

Among abiotic stresses, heat stress is described as one of the major limiting factors of crop growth worldwide, as high temperatures elicit a series of physiological, molecular, and biochemical cascade events that ultimately result in reduced crop yield. There is growing interest among researchers in the use of beneficial microorganisms. Intricate and highly complex interactions between plants and microbes result in the alleviation of heat stress. Plant–microbe interactions are mediated by the production of phytohormones, siderophores, gene expression, osmolytes, and volatile compounds in plants. Their interaction improves antioxidant activity and accumulation of compatible osmolytes such as proline, glycine betaine, soluble sugar, and trehalose, and enriches the nutrient status of stressed plants. Therefore, this review aims to discuss the heat response of plants and to understand the mechanisms of microbe-mediated stress alleviation on a physio-molecular basis. This review indicates that microbes have a great potential to enhance the protection of plants from heat stress and enhance plant growth and yield. Owing to the metabolic diversity of microorganisms, they can be useful in mitigating heat stress in crop plants. In this regard, microorganisms do not present new threats to ecological systems. Overall, it is expected that continued research on microbe-mediated heat stress tolerance in plants will enable this technology to be used as an ecofriendly tool for sustainable agronomy.

Climate change continues to threaten global crop output by reducing annual productivity. As a result, global food security is now considered as one of the most important challenges facing humanity. To address this challenge, modern crop breeding approaches are required to create plants that can cope with increased abiotic/biotic stress. Metabolomics is rapidly gaining traction in plant breeding by predicting the metabolic marker for plant performance under a stressful environment and has emerged as a powerful tool for guiding crop improvement. The advent of more sensitive, automated, and high-throughput analytical tools combined with advanced bioinformatics and other omics techniques has laid the foundation to broadly characterize the genetic traits for crop improvement. Progress in metabolomics allows scientists to rapidly map specific metabolites to the genes that encode their metabolic pathways and offer plant scientists an excellent opportunity to fully explore and rationally harness the wealth of metabolites that plants biosynthesize. Here, we outline the current application of advanced metabolomics tools integrated with other OMICS techniques that can be used to: dissect the details of plant genotype–metabolite–phenotype interactions facilitating metabolomics-assisted plant breeding for probing the stress-responsive metabolic markers, explore the hidden metabolic networks associated with abiotic/biotic stress resistance, facilitate screening and selection of climate-smart crops at the metabolite level, and enable accurate risk-assessment and characterization of gene edited/transgenic plants to assist the regulatory process. The basic concept behind metabolic editing is to identify specific genes that govern the crucial metabolic pathways followed by the editing of one or more genes associated with those pathways. Thus, metabolomics provides a superb platform for not only rapid assessment and commercialization of future genome-edited crops, but also for accelerated metabolomics-assisted plant breeding. Furthermore, metabolomics can be a useful tool to expedite the crop research if integrated with speed breeding in future.

Maize is the third most common cereal crop worldwide, after rice and wheat, and plays a vital role in preventing global hunger crises. Approximately 50% of global crop yields are reduced by drought stress. Bacteria as biostimulants for biopriming can improve yield and enhance sustainable food production. Further, seed biopriming stimulates plant defense mechanisms. In this study, we isolated bacteria from the rhizosphere of Artemisia plants from Pohang beach, Daegu, South Korea. Twenty-three isolates were isolated and screened for growth promoting potential. Among them, bacterial isolate SH-6 was selected based on maximum induced tolerance to polyethylene glycol-simulated drought. SH-6 showed ABA concentration = 1.06 ± 0.04 ng/mL, phosphate solubilizing index = 3.7, and sucrose concentration = 0.51 ± 0.13 mg/mL. The novel isolate SH-6 markedly enhanced maize seedling tolerance to oxidative stress owing to the presence of superoxide dismutase, catalase, and ascorbate peroxidase activities in the culture media. Additionally, we quantified and standardized the biopriming effect of SH-6 on maize seeds. SH-6 significantly increased maize seedling drought tolerance by up to 20%, resulting in 80% germination potential. We concluded that the novel bacterium isolate SH-6 (gene accession number (OM757882) is a biostimulant that can improve germination performance under drought stress.

Asthenozoospermia accounts for over 80% of primary male infertility cases. Reduced sperm motility in asthenozoospermic patients are often accompanied by teratozoospermia, or defective sperm morphology, with varying severity. Multiple morphological abnormalities of the flagella (MMAF) is one of the most severe forms of asthenoteratozoospermia, characterized by heterogeneous flagellar abnormalities. Among various genetic factors known to cause MMAF, multiple variants in the DNAH2 gene are reported to underlie MMAF in humans. However, the pathogenicity by DNAH2 mutations remains largely unknown. In this study, we identified a novel recessive variant (NM_020877:c.12720G > T;p.W4240C) in DNAH2 by whole-exome sequencing, which fully co-segregated with the infertile male members in a consanguineous Pakistani family diagnosed with asthenozoospermia. 80–90% of the sperm from the patients are morphologically abnormal, and in silico analysis models reveal that the non-synonymous variant substitutes a residue in dynein heavy chain domain and destabilizes DNAH2. To better understand the pathogenicity of various DNAH2 variants underlying MMAF in general, we functionally characterized Dnah2-mutant mice generated by CRISPR/Cas9 genome editing. Dnah2-null males, but not females, are infertile. Dnah2-null sperm cells display absent, short, bent, coiled, and/or irregular flagella consistent with the MMAF phenotype. We found misexpression of centriolar proteins and delocalization of annulus proteins in Dnah2-null spermatids and sperm, suggesting dysregulated flagella development in spermiogenesis. Scanning and transmission electron microscopy analyses revealed that flagella ultrastructure is severely disorganized in Dnah2-null sperm. Absence of DNAH2 compromises the expression of other axonemal components such as DNAH1 and RSPH3. Our results demonstrate that DNAH2 is essential for multiple steps in sperm flagella formation and provide insights into molecular and cellular mechanisms of MMAF pathogenesis.

In terms of stability, the response of static cars in floodwaters has been widely investigated. However, the hydrodynamics of a non-static vehicle exposed to such events are less explored. Herein the study ponders the assessment of the hydrodynamic forces experienced by a non-static vehicle attempting to cross a low-lying flooded street. With that regards, a Perodua Viva was modeled (1:10) and tested in the Hydraulics Laboratory under partial submergence and sub-critical flows, fulfilling the similarity laws. Since the Froude number could best analyze the flow conditions, the behavior of the hydrodynamic forces and the Froude number have been the focus of this investigation. From the study of outcomes, an inverse relation of the Froude number with respect to the buoyancy force, along with positive trends relating to drag, frictional, and rolling resistance, were noticed. ABSTRAK: Dari segi kestabilan, tindak balas kereta statik dalam air banjir telah banyak dikaji. Walau bagaimanapun, hidrodinamik kenderaan tidak statik yang terdedah kepada kejadian seperti itu kurang diterokai. Kajian ini menilai daya hidrodinamik kenderaan tidak statik yang cuba melintas jalan raya yang banjir. Sehubungan itu, sebuah Perodua Viva dimodelkan (1:10) dan diuji dalam Makmal Hidraulik di bawah perendaman separa dan didedahkan kepada aliran sub-kritikal, seperti ketika kejadian. Manakala nombor Froude adalah terbaik dalam menganalisa keadaan aliran air. Oleh itu, tindak balas daya hidrodinamik dan nombor Froude menjadi fokus penyelidikan ini. Dapatan kajian menunjukkan kaitan terbalik nombor Froude pada daya apungan, sedangkan tren positif yang berkaitan dengan daya tarik, geseran dan rintangan guling diperhatikan.