Model predictive control (MPC) is a multi-objective control technique that can handle 2 system constraints. However, the performance of an MPC controller highly relies on a proper 3 prioritization weight for each objective, which highlights the need for a precise weight tuning 4 technique. In this paper, we propose an analytical tuning technique by matching the MPC 5 controller performance with the performance of a linear quadratic regulator (LQR) controller. The 6 proposedmethodology derives the transformation of LQRweightingmatrixwith a fixedweighting 7 factor using discrete algebraic Riccati equation (DARE) and designs MPC controller using the 8 idea of discrete time linear quadratic tracking problem (LQT) in the presence of constraints. 9 The proposed methodology ensures the optimal performance between unconstrained MPC and 10 LQR controller and provides a sub-optimal solution while the constraints are active during 11 transient operations. The resultingMPC behaves as the discrete time LQR by selecting appropriate 12 weighting matrix in the MPC control problem and ensures the asymptotic stability of the system. 13 In this paper, the effectiveness of the proposed technique is investigated in the application of 14 a novel vehicle collision avoidance system which is designed in the form of linear inequality 15 constraints within MPC. The simulation results confirm the potency of the proposed MPC control 16 technique in performing a safe, feasible and collision free path while respecting the inputs, states 17 and collision avoidance constraints.

This article reveals a best possible design for hybrid dispersion compensating fiber (HyDCF) with high birefringence established on modified broadband compensating structure through S, C and L telecommunication bands. The simulation outcome exhibits relatively higher birefringence of 3.76×10-2 at wavelength of 1550 nm. The suggested fiber also has dispersion compensation characteristics in an inclusive series of wavelengths which covers 1400-1625 nm. The reported design can achieve dispersion quantity of – 606 ps/ (nm.km) at 1550 nm effective wavelength. The reported fiber design matches the relative dispersion slope (RDS) 0.003694 nm-1 similar to single mode fiber at 1550 nm operating wavelength. This fiber demonstrates negatively flattened effective dispersion of – 2.703 ± 0.734 ps/ (nm.km) within 180 nm flat band ranging from 1460-1640 nm wavelength. It is also convenient to optical high bit rate communication systems. The low confinement loss is found 3.756×10-10 dB/m at the operating wavelength. This design also achieves highly nonlinear coefficient of 50.34 W-1km-1. In some cases, it can also be used in sensing applications.

Eggplant is a fruit vegetable of family Solanaceae, and eggplant fruits are of different shape and sizes that render them as an ideal system for metabolic engineering. Here, we have developed an agroinfiltration protocol for the transient expression of a gene in the eggplant fruit using GUS bearing; pCAMBIA1304 vector. Thereafter, to prove the effectiveness of the developed protocol, we have used the eggplant hydroxycinnamoyl CoA-quinate transferase (SmHQT), which is the central enzyme studied to increase the chlorogenic acid content, in a gene construct with the specific promoter in a plant transformation vector (pBIN19). Also, in our cassette, we also co-expressed the P19 protein of Tomato bushy stunt virus (native promoter) to overexpress the protein. Overall, using the protocol, the chlorogenic content was increased by more than two folds in the transgenic tissues.

In this work, we firstly explored a mild, clean, and highly efficient approach for the synthesis of graphene quantum dots (GQDs). GQDs with carboxyl groups or amino groups, were prepared from one-pot environmentally friendly method assisted by hydrogen peroxide, respectively. It was proved that carboxyl groups played an important role in the fluorescence quenching. Based on these findings, we developed a novel fluorescent nanosensor by combining molecularly imprinted polymers (MIPs) with carboxyl functionalized GQDs for the determination of tetracycline (TC) in aqueous samples. The nanocomposite was prepared using a sol-gel process. GQDs-MIPs showed strong fluorescent emission at 410 nm when excited at 360 nm, which was subsequently quenched in the presence of TC. Under optimum conditions, the fluorescence intensity of GQDs-MIPs decreased in response to the increase of TC concentration with good linearity rage of 1.0-104 µg L-1. The limit of detection was determined to be 1 µg L-1. The fluorescence intensity of GQDs-MIPs was more strongly quenched by TC compared to the corresponding non-imprinted polymers, GQDs-NIPs. With the high sensitivity, the material was also successfully worked for the detection of TC in real spiked milk samples.

Radish is an annual herbaceous root crop, fruit, and oil crop plant belonging to the Cruciferae family. The important traits for radish breeding include high yield, early maturity, late bolting, pungency, cold-hardiness, drought resistance, heat tolerance, and soil adaptability. For successful radish production, need to the understand nature and behavior of the flower, and very important to identify the S haplotypes of parental lines to produce F₁ hybrids based on self-incompatibility to get rid of laborious hand emasculation in radish. In radish some desirable genes are not present within varieties. Therefore, further breeding programmes depend on inter-specific and intra-specific hybridization, which has a vital role in genomic studies and crop improvement by introducing desirable agronomic characters. It is essential to acquire detailed genetic information on chromosomes and information on inheritance. Genomics is now at the core of crop improvement, and radish crop is exploited to study the underlying differences in genotypes. But some monogenic characters are improved by genetic engineering. A three-decade span following the first documented instance of genetic engineering has witnessed its application's unprecedented growth. Researchers have successfully produced transgenic radishes with various agronomic characteristics over the last decade.

An astonishing increase in temperature is posing several harmful impacts on crop plants. Heat stress is an abiotic environmental phenomenon that causes limits, inhibits plant growth, metabolism, and productivity worldwide, resulting in losses in production yields. Heat stress is caused by human activities and global warming,s such as greenhouse gases, carbon dioxide, methane, nitrous oxide, and water vapour. There are many pieces of evidence to support that heat stress reduces the crop plants yield worldwide, and the effects of heat stress are challenging to meet nutritional security and global food security for human beings. Heat stress has negative impacts on each developmental stage, including from germination to harvesting. Prevalent approaches for heat adaption is inadequate management that is unable either to increase the crop productivity or sustain ld. Several responses to dissect the relevant knowledge about heat stress mechanism involving morphological phenomena, physiological phenomena, reproductive replies, and molecular responses such as heat shock proteins act as mRNA synthesis, mRNA control (effects of genes during heat stress), the translation process, heat response element. There are such phenomena involving disseminating the knowledge concerning heat stress. In this review, we summarise the effect of heat stress on plant mechanisms, including morphological, biochemical and molecular responses.

Eggplant is a functional food owing to its anti-diabetic, anti-inflammatory, and cardio-protective properties. Root-knot nematodes (RKN) are a threat to the successful production of eggplant. RKN infestation manifests as root damage, stunted development, and structural deformations of the plant. RKN infestation can be managed using a variety of management techniques like soil amendments and chemical treatments. Breeding for nematode tolerance is critical for high yields and stable results. As a result, breeding approaches are the most efficient and cost-effective nematode management methods. Furthermore, with advances in breeding technology and genomics assistance, it is becoming more feasible and straightforward. As a result, we've compiled a list of the most recent breeding developments for Meloidogyne spp. resistance in eggplant. We hope this information will serve as an important resource for the eggplant breeders.

Garlic and onion are either cooked like a vegetable because of their green leaves or are also used as a condiment. Many scientific studies affirm the positives of both for their anti-inflammatory, antioxidant, and antimicrobial potential. Moreover, garlic and onion are regularly employed to treat cardiovascular illnesses, strokes, atherosclerosis, hypertension, hyperlipidemias, and thrombosis, and are also proved effective against Alzheimer's, diabetes, and cancers. Here we have compiled a piece of information regarding the compounds present in garlic and onion along with their pharmacological properties. Although much more studies are required to refine the utilization and enhance garlic and medicine's effectiveness. We hope this work will provide helpful information regarding their pharmacological aspects.

Aquatic animals have unique physiological mechanisms to absorb and retain minerals from their diets and water. Research and development in the area of mineral nutrition of farmed fish and crustaceans have been relatively slow and major gaps exist in the knowledge of trace element requirements, physiological functions and bioavailability from feed ingredients. Quantitative dietary requirements have been reported for three macroelements (calcium, phosphorus and magnesium) and six trace minerals (zinc, iron, copper, manganese, iodine and selenium) for selected fish species. Mineral deficiency signs in fish include reduced bone mineralization, anorexia, lens cataracts (zinc), skeletal deformities (phosphorus, magnesium, zinc), fin erosion (copper, zinc), nephrocalcinosis (magnesium deficiency, selenium toxicity), thyroid hyperplasia (iodine), muscular dystrophy (selenium) and hypochromic microcytic anaemia (iron). An excessive intake of minerals from either diet or gill uptake causes toxicity and therefore a fine balance between mineral deficiency and toxicity is vital for aquatic organisms to maintain their homeostasis either through increased absorption or excretion. Release of minerals from uneaten or undigested feed and from urinary excretion can cause eutrophication of natural waters, which requires additional consideration in feed formulation. The current knowledge in mineral nutrition of fish is briefly reviewed.

The scope of a lucrative career promoted by Google through its video distribution platform YouTube 1 has attracted a large number of users to become content creators. An important aspect of this line of work is the feedback received in the form of comments which show how well the content is being received by the audience. However, volume of comments coupled with spam and limited tools for comment classification makes it virtually impossible for a creator to go through each and every comment and gather constructive feedback. Automatic classification of comments is a challenge even for established classification models, since comments are often of variable lengths riddled with slang, symbols and abbreviations. This is a greater challenge where comments are multilingual as the messages are often rife with the respective vernacular. In this work, we have evaluated top-performing classification models and four different vectorizers, for classifying comments which are a mix of different combinations of English and Malayalam (only English, only Malayalam and Mix of English and Malayalam). The statistical analysis of results indicates that Multinomial Naïve Bayes, K-Nearest Neighbors (KNN), Support Vector Machine (SVM), Random Forest and Decision Trees offer similar level of accuracy in comment classification. Further, we have also evaluated 3 multilingual sub-types of the novel NLP language model, BERT and compared its’ performance to the conventional machine learning classification techniques. XLM was the top-performing BERT model with an accuracy of 67.31%. Random Forest with Term Frequency Vectorizer was the best the top-performing model out of all the traditional classification models with an accuracy of 63.59%.

Conventional phenotyping breeding approaches for vegetable crops like Solanaceae, Bulb, Root crops, have made a significant contribution by developing many varieties. Despite this, conventional phenotyping approaches are not sufficient due to the longer time taken to develop a variety, low genetic gain, environmental factors and some other externalities that affect the phenotype-based selection. To address the challenges of conventional phenotype, a new recent method of high throughput phenotyping (HTP) is considered a promising tool. The development of high-throughput phenotyping technology began in the preceding decade as advancements in sensor, computer vision, automation, and advanced machine learning technologies. HTP platforms are being utilized to undertake non-destructive assessments of the complete plant system in a range of crops. HTP provides the precise measurements and suggests the collection of high-quality and accurate data which is necessary for standardizing phenotyping for the collection of genetic dissection and genomic assisted breeding such as genome-wide association studies (GWAS), linkage mapping, marker-assisted selection (MAS), genomic selection (GS). The remainder of this chapter discusses how high-throughput phenotyping technologies can be used in genomic-assisted breeding for vegetable crops

Sweet potatoes are a crucial crop for Asian and African countries. Its nutritional content and capacity to keep you healthy have increased in recent years. Moreover, sweet potatoes' fibre also keeps your gut happy. Most sweet potato varieties don't bloom. Due to pollination issues, sweet potatoes are also incompatible with each other. Sweet potato blooms are self-sterile, so they don't mix well in breeding programmes. Traditional and modern breeding procedures didn't always work with sweet potatoes, but some did. Using molecular biology methods, some individuals become more resistant to illnesses by eliminating particular genes. The crop's nature and growth should be improved. All of this should be done to acquire new characteristics in sweet potatoes by crossing them. Sweet potatoes are a superb tuberous crop, but they have issues with pollination and adjusting to new breeding procedures. Modern breeding and biotechnology methods can be used to get the most out of this crop. These are "chronological" ways to get the most out of farming.

Melon (Cucumis melo L.) a member of family Cucurbitaceae is extensively cultivated for its fleshy fruits. Based on the specific agro-climatic zones of cultivation as well as concerning the regional preferences, melon displays significant variability phenotypic and biochemical attributes. Below, an effort is put forth to considerably evaluate the scope of achievements while in the growth as well as the enactment of melon breeding programs by employing the newest solutions. Melon breeding has achieved critical milestones throughout the previous century, and we hope this trend will go on to persist down the road. However, studies have to determine new genetic information for genes associated with the challenges imposed by climate change. The identification of valuable hereditary and also metabolic variability in the form of landraces and melon wild relatives will be useful for harvest diversification and also for the broadening of the cultivated melon genetic base. Whereas, considerable information on genomics, and melon metabolomics, is beneficial for dissecting the basis of the inheritance of important traits and their impact on the former characteristics. Overall, we hope the manuscript is going to serve as a crucial resource for the melon breeders.

Bitter gourd is an important vegetable of the family Cucurbitaceae, cultivated mainly in humid and subtropical Asia. Bitter gourd is vegetable with immense health benefits due to the presence of medicinal compounds such as charatin, vicine, and polypeptide-p, which play an essential role in lessening the blood glucose levels. Moreover, bitter gourd fruits are particularly rich in vitamin C, minerals, and carotenes. Here, an effort has been made to critically evaluate the extent of achievements during the enhancement and enactment of bitter gourd breeding programs with the use of latest technologies. Broadening of the genetic base of cultivated bitter groud varieties as a result of enrichment of the existing resources by using the wild species in the breeding programs. Practical seed production technological know-how along with the use of the MS system (male sterility)/chemical-induced sterility procedure is nonetheless vital to cope up with the market demands. Superior yielding bitter gourd hybrids combining early maturity and resistance to biotic and abiotic stresses are regularly needed to cope up with the challenge of bitter gourd production.

: Using line × tester analysis, the current research analyses parental genotypes and their combinations in normal conditions and identifies the genes influencing yield characteristics. In the present study, 15 diverse genotypes, including 10 lines, 5 testers, and 50 F1s hybrids, were evaluated for 13 morphological and 2 biochemical traits. A suitable location was taken to study the effect of 15 characters. The results exposed that ability mean squares were significant for all studied additive and non-additive components. In this direction, the general combining ability of PBW-343, DBW-39, K-402, K-1317, KRL-210, and K-68 were higher than the remaining parents. For morphological traits like yield, the top five crosses were described based on SCA effects, namely, HD-3086 × HD-3171, K-402 × K-9107, K-1317 × K-9107, HD-2967 × K-0307 and K-402 × K-68 in F1 generation. In addition, the high value of heritability was estimated for plant height (77.32%), spike length (32.26%), biological yield/plant (59.52%), and grain yield/plant (68.76%). However, the moderate values of heritability were estimated for days to maturity (22.78%) and phenol color reaction (18.00%). The higher genetic advance was not found for recorded characters; however, a moderate genetic advance was recorded for grain yield per plant (13.15%) and harvest index (11.72%). High heritability coupled with moderate genetic advance was recorded for two characters grain yield per plant and harvest index in F1 and F2 generations.

This paper investigates a novel concept of using cycloidal propellers to augment the maneuverability of unmanned underwater vehicles. Cycloidal propellers are cross-flow propellers that utilize 360$^{\circ}$ thrust vectoring to provide agile maneuvering to surface vessels like yachts, tug boats, buoy tenders and double ended ferries, but have yet to be utilized on present-day unmanned and autonomous marine vehicles. Through 360$^{\circ}$ thrust vectoring, cycloidal propellers enable surface vessels to execute spot turns, and surge in forward and backward directions with equal ease. Such compact maneuvers are difficult to execute with the conventional screw propeller-rudder setup found on marine vehicles today. On unmanned and autonomous marine vehicles, cycloidal propellers can potentially enable controlled and decoupled maneuvering in all six degrees-of-freedom while overcoming disturbances like waves and currents, and extreme flow conditions like cavitation and ventilation. This is critical for marine vehicles operating at low speeds and in restricted waters. Therefore, the objective of this paper is to study the maneuvering characteristics of a UUV driven by a screw propeller and control fins only, and compare it to that of the UUV augmented with retractable cycloidal propellers. The cases considered are a turning circle maneuver, a low-speed 180$^{\circ}$ turn and a low-speed heave maneuver. A six degrees-of-freedom motion prediction model that accounts for the non-linear and coupled loads on an underwater vehicle is developed and validated. Simulation results showed that compared to conventional propulsion systems, cycloidal propellers could potentially enable more swift, compact and decoupled maneuvers in unmanned marine vehicles. Integrated with robust control systems, cycloidal propellers can be explored for use in dynamic positioning, ocean exploration, station-keeping, seakeeping and teaming of unmanned and autonomous marine vehicles.

An increase in the use of smartphones has laid to the use of the internet and social media platforms. The most commonly used social media platforms are Twitter, Facebook, WhatsApp and Instagram. People are sharing their personal experiences, reviews, feedbacks on the web. The information which is available on the web is unstructured and enormous. Hence, there is a huge scope of research on understanding the sentiment of the data available on the web. Sentiment Analysis (SA) can be carried out on the reviews, feedbacks, discussions available on the web. There has been extensive research carried out on SA in the English language, but data on the web also contains different other languages which should be analyzed. This paper aims to analyze, review and discuss the approaches, algorithms, challenges faced by the researchers while carrying out the SA on Indigenous languages.

Contact-based co-culture of fibroblasts and keratinocytes is important to study the structure and functions of the wound bed. Co-culture of these two cell types in direct contact with each other has been challenging, requiring high serum concentrations (up to 10%), feeder systems and a range of supplemental factors. These approaches are not only technically demanding, but also present scientific, cost and ethical limitations associated with high-serum concentrations. We have developed two reduced-serum approaches (1-2%) to support contact-based co-culture of human dermal fibroblasts (HDFa) and human epidermal keratinocytes (HaCaT). The two approaches include (1) Specialized cell culture media for each cell type mixed in a 1:1 ratio (KGM+FGM), and (2) Minimal media supplemented with cell-specific growth factors (MEM+GF). Co-culture could be successfully achieved by co-seeding (two cell types were introduced simultaneously), or in a layered fashion (keratinocytes seeded on top of confluent fibroblasts). With wound scratch assays, the co-cultured platforms could demonstrate cell proliferation, migration and wound closure. The reduced-serum conditions developed are simple, easy to formulate and adopt, and based on commonly-available media components. These contact-based co-culture approaches can be leveraged for wound and skin studies, and tissue bioengineering applications, potentially reducing concerns with high-serum formulations.

French bean (Phaseolus vulgaris L.) a member of family Leguminosae is a useful source of protein (∼22%), minerals (folate), vitamins and fibre. Abiotic and biotic stresses are the constraints to high yield and production of French bean. Varieties reluctant to diseases as well as abiotic stresses is among the top breeding objectives for the French bean. Mendelian ratios could know the genetically reliable forms of resistance, whereas it's more robust to understand the intricate kinds, often referred to as quantitative trait loci (QTL). Here, we review and compile the information from the studies related to the identification of QTLs for critical biofortification traits, biotic and abiotic stresses in French bean. Successful map-based cloning requires QTLs represent single genes which could be isolated in near-isogenic lines, and also the genotypes could be unambiguously inferred by progeny testing. Overall, this information will be useful for directing the French bean breeders to select a suitable method for the inheritance evaluation of quantitative traits and determining the novel genes in germplasm resources to ensure that much more potential of genetic information may be uncovered.

Pedestrian trajectories are crucial for self-driving cars to plan their paths effectively. The sensors implanted in these self-driving vehicles, despite being state-of-the-art ones, often face inaccuracies in the perception of surrounding environments due to technical challenges for adverse weather conditions, interference from other vehicles sensors and electronic devices, and signal reception failure, leading to incompleteness in trajectory data. But for real-time decision making for autonomous driving, the trajectory imputation is no less crucial. Previous attempts to address this issue such as statistical inference and machine learning approaches have shown promise. Yet, the landscape of deep learning is rapidly evolving with new and more robust models emerging. In this research, we have proposed an encoder-decoder architecture, Human Trajectory Imputation Model, coined as HTIM, to tackle these challenges. This architecture aims to fill in the missing parts of pedestrian trajectories. The model has been evaluated using the Intersection drone inD dataset, containing trajectory data at suitable altitudes preserving naturalistic pedestrian behavior with varied dataset sizes. To assess the effectiveness of our model, we have utilized L1, MSE, Quantile and ADE loss. Our experiments have demonstrated that HTIM outperforms the majority of the state-of-the-art methods in this field, thus indicating its superior performance in imputing pedestrian trajectories.

Agriculture is one of the indispensable fields for the survival of mankind. Potatoes also have a significant role in the field of agriculture. The quality and quantity of potatoes are significantly impacted by several diseases, such as early blight and late blight, and manual interpretation of these leaf diseases is time-consuming and inconvenient. Fortunately, leaf appearance is used to detect diseases in potato plants. Productivity will considerably rise if the infections are detected early. Different types of image processing methods and machine learning methods are used for early recognition of those diseases from leaf images so that the product losses are decreased significantly. For the incredible and marvelous performance of CNN, it is the most popular deep learning method that is used immensely for the recognition of leaf diseases from images. Several pretrained deep learning models, such as VGG16, ResNet50, InceptionV3, MobileNetV2, Xception, and a deep learning model developed using CNN, are employed for potato leaf disease classification and recognition on the same dataset. The transfer learning technique is applied to the pretrained model and the data augmentation technique is applied to the Proposed CNN model for potato disease classification from leaf samples. Compared to pretrained models, the proposed CNN model offers the lowest loss and highest accuracy for potato leaf disease detection while using fewer parameters and layers. It achieves the best performance with a test accuracy of 99.33% compared to other Pretrained models used in the diagnosis of potato leaf disease.

Carbon farming is a capable strategy for more sustainable production of food and other related products. It seeks to produce the diverse array of natural farming methods and marketable products simultaneously. In agroforestry system, carbon sequestration is done by incorporating carbon dioxide (CO2) into plant biomass via photosynthesis. Carbon is, thus, stored in reserves of above-ground biomass, such as timber or branches, and below-ground biomass such as roots, or organic carbon in the soil. In addition to the significance of carbon sequestration in climate change mitigation, soil organic carbon (SOC) is an imperative indicator for the soil health as well as fertility. The change in SOC can explain whether the land use pattern degrades or improves the soil fertility. SOC, found in the soil in the form of soil organic matter (SOM), helps to improve soil health either directly or indirectly. Its direct consequence is related to the process of mineralization. Further, agroforestry is highly capable of generating huge amounts of bio-mass. In fact, agroforestry is believed to be particularly suitable for replenishment of SOC. Therefore, efforts should be made to convince farmers for their resource-use efficiency and soil conserving ability in order to get maximum benefits out of agriculture. According to food and agriculture organization (FAO,) agriculture, forestry, and other land use practices account for 24% of global greenhouse gas (GHG) emissions, and total global livestock emissions of 7.1 gigatons of CO2-equivalent per year, representing 14.5% of total anthropogenic GHG emissions. Agroforestry system that deliberately integrates trees and crops with livestock in the agricultural production could potentially increase carbon sequestration and decrease GHG emission from the terrestrial ecosystems, thus, helping in global climatic change mitigation. This study, therefore, aimed at clarification about carbon farming, modifications in carbon cycle and carbon sequestration during agricultural development in addition to benefits of agroforestry.

Species of Acacia have been extensively entrenched in the tropical, and semi-arid regions as well as in the southern hemisphere. Acacia species have been bounteous faces the pest and pathogenic pressure. Integrated Pest Management (IPM) is an immensely important aspect of producing a healthy Acacia plantation without harmful impacts on the environment. Here an attempt was made to determine the possibilities of integrated pest management for Acacia. Overall, this information will be helpful to increase awareness about the integrated pest management of the members of the genus Acacia.

HIV-1 assembly is a complex mechanism taking place at the plasma membrane of the host cell. It requires nice spatial and temporal coordination to end up with a full immature virus. Researchers have extensively studied HIV-1 assembly molecular mechanism during the past decades, in order to dissect the respective roles of viral proteins, viral genome and host cell factors. Nevertheless, the time course of the process has been observed in living cells only a decade ago. The very recent revolution of optical microscopy, combining high speed and high spatial resolution now permit to study assemblies and their consequences at the single molecule level within (living) cells. In this review, after a short description of these new approaches, we will show how HIV-1 assembly in cells has been revisited using these advanced super resolution microscopy techniques and how much it could make a bridge in studying assembly from the single molecule to the host cell.

Nigella sativa's thymoquinone (TQM), a water-insoluble phytonutrient exhibits nephroprotective effects. This study intends to develop a self-micellizing solid dispersion (SMSD) of TQM for better biopharmaceutical and nephroprotective performance. Soluplus®-based SMSD of TQM was created and tested for physicochemical properties, solubility, and pharmacokinetics in rats. Plasma creatinine, blood urea nitrogen (BUN), nephrotoxic indicators, and oxidative stress biomarkers were also tested. During SMSD preparation, TQM was found amorphous, boosting solubility. Minimal band changes between TQM and Soluplus® indicate insignificant drug-carrier interactions. SMSD-TQM generated fine micelles in water, improving TQM's solubility by 97.8% in 60 min. SMSD-TQM was 4.9 times more bioavailable orally in rats than crystalline TQM. In a rat model of acute renal damage by cisplatin (6 mg/kg, i.p.), SMSD-TQM (10 mg-TQM/kg, p.o.) reduced blood creatinine and BUN by 56% and 63.2%, respectively. These findings imply that SMSD-TQM may be a potent dosage option for enhancing TQM's nutrient value.

Mycotoxins are deleterious fungal secondary metabolites that contaminate food and feed, thereby creating concerns regarding food safety. Common fungal genera can easily proliferate in Indian tropical and sub-tropical conditions, and scientific attention is warranted to curb its growth. To address this, two nodal governmental agencies, namely the Agricultural and Processed Food Products Export Development Authority (APEDA) and Food Safety and Standards Authority of India (FSSAI), have developed and implemented analytical methods and quality control procedures to monitor mycotoxin levels in a range of food matrices and assess risks to human health over the past two decades. However, comprehensive information on such advancements in mycotoxin testing and issues in implementing these regulations is inadequately covered in recent literature. The aim of this review is thus to uphold a systematic picture of the role played by the FSSAI and APEDA for mycotoxin control at the domestic level and for the promotion of international trade along with certain challenges in dealing with mycotoxin monitoring. Additionally, it unfolds various regulatory concerns regarding mycotoxin mitigation in India. Overall, it provides valuable insights to the Indian farming community, food supply chain stakeholders, and researchers about India’s success story in arresting mycotoxins throughout the food supply chain.

Deepfakes are manipulated or altered images, or video, that are created using deep learning models with high levels of photorealism. The two popular methods of producing a deepfake are based on either convolutional neural networks (CNN), or autoencoders. Deepfakes created using CNN comparatively show higher qualities of realism, yet oftentimes leave artifacts and distortions in the generated media that can be detected using machine learning and deep learning algorithms. In recent years, there has been an influx of periocular image and video data because of the increase usage of face masks. By wearing masks, much of what is used for facial recognition is hidden, leaving only the periocular region visible to an observer. This loss of vital information leads to easier misidentification of media, allowing deepfakes to less likely be identified as fake. In this work, feature extraction methods, such as Scale-Invariant Feature Transform (SIFT), Histogram of Oriented Gradients (HOG), and CNN, are used to train an ensemble deep learning model to detect deepfakes in videos on a frame-by-frame level based on the periocular region. Our proposed model is able to distinguish original and manipulated images with accuracies around 98.9 percent, which is an improvement to previous works by combining SIFT and HOG for deepfake detection in convolutional neural networks.

Each year, the global population and agriculture suffer critical agricultural output losses as a result of severe drought devastation. Physiological drought occurs when plants are unable to extract water from the soil, even though it is available in the root zone. Apart from having a significant effect on plant physiology, drought stress has the effect of reducing crop yield. Drought stress influences plant metabolism both directly and indirectly. Drought stress alters the morpho-anatomical, physiological, and biochemical composition of plants, thereby decreasing transpiration water loss and increasing the efficiency with which plants use their water. Constant water loss through transpiration, combined with previously lost water, results in leaf water deficits. Nonetheless, drought stress has a wide variety of effects, ranging from lesions to confusion. Plant health is harmed when their ability to absorb water and nutrients, interact with their environment, and breathe is harmed. Apart from oxidative damage to plants, it may also result in cell death, which can occur under certain conditions when cells are exposed to their environment. Drought induces a plethora of physiological and molecular changes in plants, the majority of which assist them in adapting to the harsh environment. To mitigate drought's adverse effects, we must first gain a better understanding of how drought affects plant physiology. The purpose of this research is to better understand how drought affects plant development by examining the causes and effects of drought stress.

Chilli leaf curl virus (ChiLCV) is a severe threat to the successful cultivation of the chilli peppers. Besides, the genetics and heterosis for important traits under the influence of ChiLCV infestation is not well studied. Therefore here, were crossed seven genotypes (lines) with high yield and quality attributes with four highly resistant genotypes (testers) in a line (L) × tester (T) mating design to produce 28 F1 hybrids. Parents and their hybrids were evaluated for yield attributes and ChiLCV resistance. All the four testers were symptomless and among seven lines, two were moderately resistant and five were moderately susceptible to the ChiLCV. Among 28 F1 hybrids, 12 showed a moderate resistant reaction, 11 were moderately susceptible and five susceptible to the ChiLCV disease. Based on per se performance, most promising hybrid combinations were L3 × T2, L6 × T1, and L3 × T1 for yield attributes. Whereas the superior crosses for ChiLCV resistance based on heterobeltosis, standard heterosis and specific combining ability test (SCA) effects were L6 × T1 and L7 × T3. Lines and testers showed significant differences for all the characters except for the plant height. The general combining ability (GCA) effects for testers were significant for all the traits except for days to first harvest. The ratio of σ2GCA/σ2SCA indicated the predominance of non-additive gene effects in the inheritance of traits studied in this experiment. The contribution of lines was more compared to testers for all the characters except for primary branches plant-1. Overall, this study provides valuable information regarding the genetics and heterosis in chilli with respect to ChiLCV infestation

Quantification of bone loss for follow-up comparisons has not been routinely performed in patients with parietal thinning so far. This study compares different methodological approaches including both 2- and 3-dimensional methods in computerized tomographies of a single patient. The 2-dimensional method provides accurate measurements of bone thickness, while the 3-dimensional method allows for a more comprehensive view of the bone's structure, including parameters like shape, size, and thickness. The techniques provided valuable data for the treating physician and suggest a possible effect of corticosteroids in this individual patient. The study concludes that 3-dimensional reconstruction of computerized tomographies with subsequent 2-dimensional analyses appears justified for routine radiological practice to increase clinical awareness of the size of the parietal bone defects and allow for quantification of bone loss during long-term follow-ups. Further validation of the proposed analytical approaches is warranted in larger studies to investigate patterns of bone thinning across the skull and changes in bone volumes over time, with specialized software to be approved for such analyses.

Climate variation and change are an unavoidable phenomenon faced by the natural habitat of this planet. For getting potential yield from vegetable crops under the changing climate conditions, the practical strategies at field level can serve as a guideline for the farmers. Moreover, there are several strategies available for mitigating the harmful effects of climate change. In this manuscript, efforts have been made for reviewing the mitigating strategies against the impact of climate change in vegetable crops via conventional approaches. Considering the situation, the information reviewed revealed that significant result of conventional approaches with climate-smart adoptions strategies has a direct bearing on vegetable production for the increasing population in frenziedly changing climate scenario.

Wheat is the essential constituent of cereal-based diets and one of the most significant sources of calories. However, there is an inherently low bioavailability of proteins, mineral, and vitamins in modern wheat grains. Biofortification has earned recognition as an outstanding approach, at the same time as a cure for world hunger. The developments in the identifications of quantitative trait loci (QTL) analysis and understanding of the physiological and molecular basis of QTLs controlling the biofortification traits in wheat has revealed new horizons for the improvement of modern wheat varieties. Within this review, we have compiled the information from the studies carried out in wheat using QTL mapping methodologies that is among the best methods for biofortification traits. We hope this review will serve as an essential reference for the QTLs identified for the several important biofortification traits in wheat.

The present study was designed to develop a self-micellizing solid dispersion (SMSD) containing Thymoquinone (TQM), a phytonutrient obtained from Nigella sativa seeds, aiming to improve its biopharmaceutical and nephroprotective functions. The apparent solubility of TQM in polymer solutions was used to choose an appropriate amphiphilic polymer that could be used to make an SMSD system. Based on the apparent solubility, Soluplus® was chosen as an appropriate carrier, and mixing with TQM, SMSD-TQM with different loadings of TQM (5–15%) was made by solvent evaporation and freeze-drying techniques, respectively, and the formulations were optimized. The optimized SMSD-TQM was evaluated in terms of particle size distribution, morphology, release characteristics, pharmacokinetic behavior, and nephroprotective effects in a rat model of acute kidney injury. SMSD-TQM significantly improved the dissolution characteristics (97.8%) of TQM in water within 60 min. Oral administration of SMSD-TQM in rats exhibited a 4.9-fold higher systemic exposure than crystalline TQM. In a cisplatin-induced (6 mg/kg, i.p.) acute kidney-damaged rat model, oral SMSD-TQM (10 mg/kg) improved the nephroprotective effects of TQM based on the results of kidney biomarkers and histological abnormalities. These findings suggest that SMSD-TQM might be efficacious in enhancing the nephroprotective effect of TQM by overcoming biopharmaceutical limitations.

Increased nutrient withdrawal by rapidly expanding intensive cropping systems, in combination with imbalanced fertilization, is leading to potassium (K) depletion from agricultural soils in Asia. There is an urgent need to better understand the soil K-supplying capacity and K-use efficiency of crops to address this issue. Maize is increasingly being grown in rice-based systems in South Asia, particularly in Bangladesh and North East India. The high nutrient extraction, especially K, however, causes concerns for the sustainability of maize production systems in the region. The present study was designed to estimate, through a plant-based method, the magnitude, and variation in K-supplying capacity of a range of soils from the maize-growing areas and the K-use efficiency of maize in Bangladesh. Eighteen diverse soils were collected from several upazillas (or sub-districts) under 11 agro-ecological zones to examine their K-supplying capacity from the soil reserves and from K fertilization (@ 100 mg K kg-1 soil) for successive seven maize crops grown up to V10-V12 in pots inside a net house. A validation field experiment was conducted with five levels of K (0, 40, 80, 120 and 160 kg ha-1) and two fertilizer recommendations based on “Nutrient Expert for Maize-NEM” and “Maize Crop Manager-MCM” decision support tools (DSSs) in 12 farmers’ fields in Rangpur, Rajshahi and Comilla districts in Bangladesh. Grain yield and yield attributes of maize responded significantly (P < 0.001) to K fertilizer, with grain yield increase from 18 to 79% over control in all locations. Total K uptake by plants not receiving K fertilizer, considered as potential K-supplying capacity of the soil in the pot experiment, followed the order: Modhukhali >Mithapukur >Rangpur Sadar >Dinajpur Sadar >Jhinaidah Sadar >Gangachara >Binerpota >Tarash >Gopalpur >Daudkandi >Paba >Modhupur >Nawabganj Sadar >Shibganj >Birganj >Godagari >Barura >Durgapur. Likewise in the validation field experiment, the K-supplying capacity of soils was 83.5, 60.5 and 57.2 kg ha-1 in Rangpur, Rajshahi, and Comilla, respectively. Further, the order of K-supplying capacity for three sites was similar to the results from pot study confirming the applicability of results to other soils and maize-growing areas in Bangladesh and similar soils and areas across South Asia. Based on the results from pot and field experiments, we conclude that the site-specific K management using the fertilizer DSSs can be the better and more efficient K management strategy for maize.

Tree members of the genus Acacia have benefits that are obvious for enhancing soil fertility in farming, forestry and agroforestry in regions with nutrient-poor soils, and for restoring degraded ecosystems and lands. Nevertheless, the species of the genus Acacia have got the potential to bring about significant adverse impacts on biodiversity or ecosystem functioning when it gets invasive. The ecology of the species in nearly all areas of its created range remains poorly understood. Here we have compiled the information regarding the importance, cultivation and the production of important species of genus Acacia. We hope this information will be useful to get awareness about the crucial trees in the genus Acacia.

Germplasm is a valuable natural resource in plant diversity that is crucial for its potential use. It provides knowledge about a species genetic composition. Germplasm protection strategies are not just planting hope threatened with extinction, they preserve medicinal and other essential plants on which survival rests. The successful use of genetic plant resources necessitates diligent collection, storage, analysis, documentation, and germplasm exchange. Slow growth cultures, cryopreservation, pollen and DNA banks, botanic gardens, genetic reserves and farmer’s fields are few conservation techniques. However, usage of an in vitro procedure with any chance of genetic instability leads to the destruction of the entire substance. Improved understanding of basic regeneration biology would, in turn, undoubtedly increase the capacity to regenerate plants from in vitro harvested explants, thus expanding selection possibilities. Germplasm conservation seeks to conserve endangered and vulnerable plant species worldwide for future proliferation and development; it is also the bedrock of agricultural production.

Rice (Oryza sativa L.) supplies nourishment to about half of the population of the world's inhabitants. Of them, more than 2 billion people suffer from "hidden hunger" in which they are unable to meet the recommended nutrients or micronutrients from their daily dietary intake. Bio-fortification refers to developing micronutrient-rich diet foods using traditional breeding methods and modern biotechnology, a promising approach to nutrition enrichment as part of an integrated strategy for food systems. To improve the profile of rice grain for the biofortification related traits, understanding the genetics of important biofortification traits is required. Moreover, these attributes are quantitative in nature and are influenced by several genes and environmental variables. In the course of past decades, several endeavours such, as finding the important quantitative trait loci (QTLs) for improving the nutrient profile of rice seeds were successfully undertaken. In this review, we have presented the information regarding the QTLs identified for the biofortification traits in the rice.

The precise information regarding the date of sowing, seed rate and row spacing is critical for achieving yield targets and better economic returns of barley. Therefore here, we determined the information regarding the optimum date of sowing, seed rate, spacing and economic aspects for barley production. This study was conducted for three years, in north Indian plains. Early sowing date of barley (last week of October) recorded higher yield in comparison to late sown crop (3^rd week of November). Moreover, the higher barley production proved more remunerative when sown early in the last week of October to the first week of November as compared to late sown the late sown crop. Furthermore, the enhanced seed rate of 10% then recommended did not affect the grain yield of barley. But, the closer spacing of 20 cm (row to row) produced higher grain yield (5.45 Mg ha^-1 ) than the recommended spacing of 22.5 cm (5.30 Mg ha^-1). Likewise, the economical parameters (net returns) were higher with 20 cm row spacing. Overall, this study determines the optimum date of sowing, seed rate and spacing for scoring better returns of barley crop under north Indian conditions.

This paper proposes a mathematical model to simulate Day-ahead markets of large-scale multi-energy systems with high share of renewable energy. Furthermore, it analyses the importance of including unit commitment when performing such analysis. The results of the case study, which is performed for the North Sea region, show the influence of massive renewable penetration in the energy sector and increasing electrification of the district heating sector towards 2050, and how this impacts the role of other energy sources such as thermal and hydro. The penetration of wind and solar is likely to challenge the need for balancing in the system as well as the profitability of thermal units. The degree of influence of the unit commitment approach is found to be dependent on the configuration of the energy system. Overall, including unit commitment constraints with integer variables leads to more realistic behaviour of the units, at the cost of increasing considerably the computational time. Relaxing integer variables reduces significantly the computational time, without highly compromising the accuracy of the results. The proposed model, together with the insights from the study case, can be specially useful for system operators for optimal operational planning.

Plant-microbial interactions are very crucial for the terrestrial ecosystem. At the rhizospheric, phyllospheric and endospheric regions, these interactions occur through different signalling pathways and play a pivotal role as they strengthen the plant defence mechanism against pathogen attacks and other stresses. A better knowledge of these relationships will help to develop novel solutions for sustainable agriculture and safeguarding the global food supply in the context of climate change and mounting environmental concerns. This chapter emphasises the role of the microbiome in providing resistance to plants against various environmental stresses and aiding in their improved adaption. This chapter also underscores the impact of the microbiome in providing resilience to plants under changing climatic scenarios.

Climate change has had a significant impact on many ecosystems worldwide, prompting native population species to adapt to the current weather patterns eventually. Pre-existing genetic variation in populations explains part of this adaptation. Still, recent studies have shown that new stable phenotypes can be generated through epigenetic modifications in just a few generations, thereby contributing to the stability and survival of plants in their natural habitat as they eventually adjust to the surrounding impacts. The state of chromatin inside plant cells varies, allowing cells to fine-tune their transcriptional profiles to better adapt to stimuli from the external environment. Within a cell, chromatin state changes such as post-transcriptional histone modifications and variations, DNA methylation, and non-coding RNA activity are all examples of chromatin state alterations that may epigenetically dictate certain transcriptional outputs. Recent advances in the field of ‘Omics’ in major crops has made it easier to identify epigenetic changes and their impact on plant responses to environmental stresses. These epigenetic mechanisms thus play an important role in improving crop adaptation and resilience to changing environments. This variation that has emerged can thus be exploited in crop breeding, ultimately leading to the generation of stable climate-resilient genotypes.

SARS-CoV-2 is a newly emerging, highly transmissible, and pathogenic coronavirus in humans, which has caused global public health emergency and economic crisis. To date, millions of infections and thousands of deaths have been reported worldwide, and the numbers continue to rise. Currently, there is no specific drug or vaccine against this deadly virus; therefore, there is a pressing need to understand the mechanism through which this virus enters the host cell. Viral entry into the host cell is a multistep process in which SARS-CoV-2 utilizes the receptor binding domain of the spike glycoprotein (S) to recognize ACE2 receptors on the human cells; this initiates host cell entry by promoting viral-host cell membrane fusion through large scale conformational changes in the S protein. Receptor recognition and fusion are critical and essential steps of viral infections and are key determinants of the viral host range and cross-species transmission. In this review, we summarize the current knowledge on the origin and evolution of SARS-CoV-2 and the roles of key viral factors. We discuss the RNA dependent RNA polymerase structure of SARS-CoV-2, its significance in drug discovery, and explain the receptor recognition mechanisms of coronaviruses. We provide a comparative analysis of the SARS-CoV and SARS-CoV-2 S proteins, receptor-binding specificity, and discuss the differences in their antigenicity based on biophysical and structural characteristics.

Aflatoxins (AFs) contamination of cereals is considered one of the greatest food safety concerns worldwide. Occurrence of AFs in maize, wheat, rice and sorghum is highly prevalent with each commodity accounting for more than 10% of world’s AF exposure. Their occurrence as food contaminants is also associated with huge economic losses. AFs are highly stable compounds that cannot be eliminated by regular processing of grains. Hence, prevention of AFs in food and feed is now considered more important than the subsequent interventions to mitigate the deleterious health effects of AFs in human and animals. However, the development of an effective preventive strategy hinges on a clear understanding of the underlying factors influencing AFs production. Therefore, the present review aims to highlight the most significant factors influencing AFs contamination of cereals at pre-and post-harvest stages. This is crucial for effective monitoring of critical control points and optimisation of preventive strategies in food and feed supply chains. Several intrinsic and extrinsic factors have been reported of which nutritional composition, environmental factors (temperature, water activity and relative humidity) and climate change have been identified as primary factors, while pH of the substrate, carbon dioxide (CO2) levels in the gaseous environment, and agronomic and socioeconomic status are the main secondary factors promoting AFs biosynthesis in cereals. Additionally, an overview of global occurrence of AFs in cereals, with their health impacts and various preventive measures have also been highlighted.

Urinary peptides are the products of systemic protein turn over which are excreted out of the body and hence can serve as an important biomarker for various pathophysiology. These peptides in other species of bovine have been reported to possess several bioactive properties. To investigate the potential of urinary peptides we generated a peptidome profile from the urine of Murrah Buffaloes (n=10). Urine samples were processed using &lt;10 kDa MWCO filter, filtrate obtained was used for peptide extraction using Solid Phase Extraction (SPE). Eluate, obtained after SPE was extracted using ethyl acetate and the peptide-containing aqueous phase was collected. We extensively assessed the antimicrobial properties of the urinary aqueous phase. The nLC-MS/MS of the aqueous phase from 10 animals resulted in the identification of 8165 peptides originating from 6041 parent proteins. 76 Proteases responsible for the release of these sequences from precursor proteins were also identified. We further analyzed these peptide sequences to identify bioactive peptides and classify them into anti-cancerous, anti-hypertensive, anti-microbial, and anti-inflammatory groups with a special emphasis on antimicrobial properties. With this in mind, we simultaneously conducted experiments to evaluate antimicrobial properties of urinary aqueous extract on three pathogenic bacterial strains S. aureus, E. coli, &amp; S. agalactiae.

Light-gated ion channel and ion pump rhodopsins are widely used as optogenetic tools and these can control the electrically excitable cells as: (1) they are a single-component system i.e., their sensor and effector functions are encoded by the 7-transmembrane domains and (2) they show fast kinetics with small dark-thermal recovery time. In cellular signaling, a signal receptor, modulator and effector components are involved for attaining synchronous multicomponent regulation. Optical modulation of this network requires either receptor to effector encoded in a single ORF or direct modulation of the effector domain through bypassing all upstream players. Recently discovered modular rhodopsins like rhodopsin guanine cyclase (RhoGC) and rhodopsin phosphodiesterase (RhoPDE) paves the way to establish proof of concept. Light sensor coupled modular system could be expressed in a precise cell type and which holds great potential in the advancement of optogenetics 2.0. It would enable manipulating entire relevant cell signaling system. Here, we had identified 50 novels modular rhodopsins with variant rhodopsins domain and its diverse cognate signaling cascades encoded in a single ORF, which are associated with specialized functions in the cells. These novel modular algal rhodopsins have been characterized functionality based on their sequence and structural homology with previously characterized rhodopsins. Presented novel modular rhodopsins with various effector domains hold potential to expand optogenetics tool kit to regulate various cellular signaling pathways across the diverse biological model systems.

Trans fatty acids (TFA) are a concern for public health due to their negative impact on cardiovascular health. This study aimed to assess the levels of TFA and other fatty acids in popular edible oils and fried foods commonly consumed in Tanzania. A total of 57 samples from 38 brands of edible oils and 20 samples of fried street foods and fast foods were collected in Dar es Salaam, Tanzania. Capillary gas chromatography was used to determine TFA levels, while nutritional labeling and other fatty acid classes were also evaluated. Among the analyzed edible oils, 21% exceeded the recommended TFA levels, primarily found in popular brands of margarine, industrially refined sunflower oils, animal butter, and peanut butter. Only two food items surpassed the 2% TFA limit, but a majority of the foods had high levels of saturated fatty acids and a fatty acid profile similar to palm oil. Additionally, only 22% of the edible oils provided TFA content information. These findings indicate the persistence of TFA levels beyond recommended limits and inadequate TFA nutritional labeling in Tanzanian food products. Urgent interventions are necessary to reduce TFA levels and improve nutritional labeling practices to safeguard public health.

For a significant period, conventional breeding and genetic modification were the key techniques that were effective in managing biotic and abiotic stresses in crops and adding desirable traits. However, the recent appearance of novel diseases and unexpected climatic changes that have substantial implications for agriculture worldwide have urged scientists to look for alternative methods to quickly manage seasonal crises. The primary emphasis of this chapter is on the obstacles and diverse biotechnological methods employed to enhance crop resilience against a range of biotic and abiotic stressors in plants. Furthermore, we consider gene transformation, omics techniques, genome editing, and other sophisticated biotechnological tools that utilize transcriptomic, proteomic, metabolomic, phenomics, RNA interference, and epigenome modifications for enhancing plant resilience. Lastly, we examine the potential of merging these eco-friendly and innovative methods with conventional breeding to promote modern agriculture and aid in enhancing tolerance to different biotic, abiotic stresses and growth promotion.

Cancer is a catchall term that refers to a collection of more than one chronic disease that can adversely affect the body, including the organs of the body. These diseases can be grouped together under the umbrella term "cancer." Cancer is a catch-all term that is used to refer to a number of different diseases. During the process of looking for new chemical entities, it was found that certain compounds with a basic nucleus of benzoic acid (BA) exhibit a remarkable anticancer potential. This was discovered while the researchers were looking for new chemical entities. In the sixteenth century, the aromatic chemical known as BA, which is also known as an aromatic carboxylic acid, was discovered. BA is also referred to as an aromatic carboxylic acid. When it comes to the chemical synthesis of a wide range of different active molecules, the utilization of a sizeable quantity of BA as a raw material is absolutely necessary. In addition to being present in a variety of other naturally occurring compounds, the BA moiety is the component that is responsible for the activity of the naturally occurring compounds vanillin, gallic acid, and syringic acid. In the synthesis of a wide variety of synthetic bioactive molecules, the BA scaffold is utilized as a building block. The drugs furosemide, bumetanide, benzocaine, tetracaine, and bexarotene are all examples of molecules that fall into this category. The scope of this review article allows for the discussion of a number of noteworthy and recent achievements of BA derivatives in terms of their effectiveness against cancer.

We propose an $E_8 \otimes E_8$ unification of the standard model with pre-gravitation, on an exceptional Lie algebra-valued space . Each of the $E_8$ has in its branching an $SU(3)$ for space-time and an $SU(3)$ for three fermion generations. The first $E_8$ further branches to the standard model $SU(3)_c \otimes SU(2)_L \otimes U(1)_Y$ and describes the gauge bosons, Higgs and the left chiral fermions of the standard model. The second $E_8$ further branches into a right-handed counterpart (pre-gravitation) $SU(3)_{grav}\otimes SU(2)_R \otimes U(1)_g$ of the standard model, and describes right chiral fermions, a Higgs, and twelve gauge bosons associated with pre-gravitation, from which general relativity is emergent. We account for 208 out of the 496 degrees of freedom of $E_8 \otimes E_8$ and propose an interpretation for the remaining 288, motivated by the trace dynamics Lagrangian of our theory. We explain how the two copies of $SU(3)_{spacetime}$ together give rise to a 6D spacetime with signature $(3,3)$ which upon symmetry breaking gives rise to our 4D spacetime and to a second 4D anti-spacetime with flipped signature.

The COVID-19 pandemic has presented an unprecedented challenge to the healthcare system. Identifying the genomics and clinical biomarkers for effective patient stratification and management is critical to controlling the spread of the disease. Omics datasets provide a wealth of information that can aid in understanding the underlying molecular mechanisms of COVID-19 and identifying potential biomarkers for patient stratification. Artificial intelligence (AI) and machine learning (ML) algorithms have been increasingly used to analyze large-scale omics and clinical datasets for patient stratification. In this manuscript, we demonstrate the recent advances and predictive accuracies in AI and ML-based patient stratification modeling linking omics and clinical biomarker datasets, focusing on COVID-19 patients. Our ML model not only demonstrates that clinical features are enough an indicator of COVID-19 severity and survival but also infers what clinical features are more impactful, which makes our approach a useful guide for clinicians for prioritization of best-fit therapeutics for a given cohort of patients. Moreover, with weighted gene network analysis, we are able to provide insights into gene networks that have a significant association with COVID-19 severity and clinical features. Finally, we have demonstrated the importance of clinical biomarkers in identifying high-risk patients and predicting disease progression.

The ongoing evolution of severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) has resulted in the recent emergence of a highly divergent variant of concern (VOC) defined as Omicron or B.1.1.529. This VOC is of particular concern because it has the potential to evade most therapeutic antibodies and has undergone a sustained genetic evolution, resulting in the emergence of five distinct sub-lineages. However, the evolutionary dynamics of initially identified Omicron BA.1 and BA.2 sub-lineages remain poorly understood. Herein, we combined Bayesian phylogenetic analysis, mutational profiling, and selection pressure analysis to track virus genetic changes that drive the early evolutionary dynamics of the Omicron. Based on the Omicron dataset chosen for the improved temporal signals and sampled globally between November 2021 and January 2022, most recent common ancestor (tMRCA) and substitution rates for BA.1 were estimated to be 18 September 2021 (95% highest posterior density (HPD) 04 August – 22 October 2021) and 1.435×10-3 (95% HPD = 1.021×10-3 – 1.869×10-3) substitution/site/year, respectively, whereas 03 November 2021 (95% highest posterior density (HPD) 26 September – 28 November 2021) and 1.074×10-3 (95% HPD = 6.444×10-4 – 1.586×10-3) substitution/site/year for BA.2 sub-lineage. The findings of this study suggest that the Omicron BA.1 and BA.2 sub-lineages originated independently and evolved over time. Furthermore, we identified multiple sites in spike protein undergoing continued diversifying selection that may alter the neutralization profile of BA.1. This study shed light on the ongoing global genomic surveillance and Bayesian molecular dating analyses to better understand the evolutionary dynamics the virus and, as a result, mitigate the impact of emerging variants on public health.

G protein-coupled receptor 15 (GPR15, also known as BOB) is an extensively studied orphan GPCR involving HIV infection, colonic inflammation and smoking-related diseases. Recently, GPR15 was deorphanized and its corresponding natural ligand demonstrated an ability of inhibiting cancer cell growth. However, no study reported the potential role of GPR15 in a pan-cancer manner. Using large-scale publicly available data from the Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) databases, we found that GPR15 expression is significantly lower in colon adenocarcinoma (COAD) than in normal tissues. And among 33 cancer types, GPR15 expression is significantly correlated with the prognoses of COAD, neck squamous carcinoma (HNSC), lung adenocarcinoma (LUAD) positively and stomach adenocarcinoma (STAD) negatively. This study also revealed that commonly upregulated gene set in the high GPR15 expression group (stratified via median) of COAD, HNSC, LUAD and STAD are enriched in immune systems, indicating that GPR15 might be considered as a potential target for cancer immunotherapy. Furthermore, we modelled the 3D structure of GPR15 and conducted the structure-based virtual screening. The top 8 hits compounds were screened and then subjected to molecular dynamics (MD) simulation for stability analysis. Our study provided novel insights into the role of GPR15 in a pan-cancer manner and discovered a potential hit compound for GPR15 antagonists.

Offshore grids can have a key role in the transition of the energy system to sustainability. Although they require extensive infrastructure investments, they open up for the exploitation of additional resources and may be important to provide for part of the increasing electricity demand driven by sector coupling. This paper quantifies the socio-economic value of offshore grids and identifies their major drivers, performing energy system optimization in a model application of the Northern-central European energy system and the North Sea offshore grid towards 2050. The increasing wake loss with the size of hub-connected wind farms is integrated in the modelling. We find that without sector coupling no offshore grid may develop, and that the higher the level of sector coupling, the higher the value of offshore grids. Therefore, it can be strongly stated that offshore grid infrastructure development should not be discussed as a separate political topic, but seen in connection to sector coupling.

Increasing pesticide resistance in plant pathogens is major concern in agriculture production. Research on ecofriendly alternatives of chemical pesticides are more in demand in pesticide industry. In the current study, an ethyl acetate extract from the endophytic fungus Trichoderma sp. EFI 671, isolated from the stem parts of the medicinal plant Laurus sp., was screened for bioactivity against plant pathogens (Fusarium graminearum, Rhizoctonia solani, Sclerotinia sclerotiorum and Botrytis cinerea), insect pests (Spodoptera littoralis, Myzus persicae, Rhopalosiphum padi) and plant parasites (Meloidogyne javanica). The bioactive components have been characterized following a bioassay-guided isolation against M. persicae. The chemical study of this bioactive extract resulted in the isolation of 1-oleoyl-2-linoleoyl-3-palmitoylglycerol (1), eburicol (2), (24R)-stigmast-4-ene-3-one or β-sitostenone (3), ergosterol (4) and ergosterol peroxide (5). The free fatty acids present in compound 1 (oleic, linoleic and palmitic) showed strong dose-dependent aphid antifeedant effects against M. persicae. Liquid (PDB, and SDB) and solid (corn, sorghum, pearl millet and rice) growth media were tested in order to optimize the yield and bioactivity of the fungal extracts. Pearl millet and corn gave the highest extract yields. All the extracts from these solid media had strong effects against M. persicae with sorghum being the most active. Corn increased the content in linolenic, pearl millet the oleic and stearic and sorghum oleic and linolenic acids compared to rice. Their antifeedant effects correlated with linoleic /oleic acids. The phytotoxic effects of these extracts against Lolium perenne and Lactuca sativa varied with culture media, with sorghum being the least toxic.

The use of Retrieval-augmented generation (RAG) using large language models (LLMs) has shown potential for addressing issues such as hallucinations and inadequately contextualized responses. A pivotal stage in the RAG process involves a retriever for retrieving chunks based on semantic similarity with the query. In this study, we advocate for and provide experimental evidence supporting integrating and maintaining questions and answers (QA) formatted databases to improve retrieved-context representations and response quality. Our experiments evaluate our approach on benchmark RAG datasets using standard evaluation metrics and provide comparative analyses against state-of-the-art retrieval methods, showing the potential of our approach.

This research presents a comprehensive bibliometric and sentiment analysis of nanocomposite literature from 1990 to 2024. Employing cutting-edge computational methods, the study delves deep into the progression of microstructural characterization, electrical properties, and mechanical behaviors of nanocomposites. The analysis utilizes advanced Boolean search strategies from the Scopus database, ensuring a thorough extraction of thematic content. The results explore various themes and insights, shedding light on trends evident in the Scopus database, particularly the prominence of research on nanocomposite microstructure, electrical attributes, and mechanical performance. The paper also offers textual analytics and bibliometric data, showcasing critical collaborative efforts and influential studies. Significant discoveries encompass the evolution of research language, shifts in thematic focus, and global contributions, providing a comprehensive perspective on the current landscape of nanocomposite research and its dynamic evolution. Moving forward, the "State-of-the-Art and Gaps Extracted from Results and Discussions" section of the paper delves into the most recent advancements in nanocomposite research. It delves into various types of nanocomposites, with a particular emphasis on their microstructural characteristics, electrical properties, mechanical dynamics, and the application of nanocomposite films. This section identifies key research themes, traces historical progress, and highlights emerging trends while underscoring the significance of collaboration and the influence of pivotal studies that have shaped the field. Lastly, in the "Literature Review Guided by Artificial Intelligence" section, the paper introduces a revised approach for researching nanocomposites through AI-guided techniques. This approach prioritizes articles published in 2023 based on citation frequency. Here, the focus is on exploring the relationship between nanocomposites and their electrical properties, emphasizing their fundamental interactions and impact on electrical characteristics. Various nanocomposite systems are covered, highlighting their composition, structure, and functionality. Findings from recent studies are integrated to provide a comprehensive overview of the current state of knowledge in this area. Notably, the sentiment analysis, anchored by an average sentiment score of 0.638771, underscores a positive trajectory in academic discourse, emphasizing the growing recognition of the potential of nanocomposites. The bibliometric exploration maps the intellectual domain, emphasizing pivotal research themes and the influence of crosslinking time on nanocomposite attributes. While this study is thorough, it acknowledges its limitations and advocates for broader database inclusion in future research endeavors. This work elucidates the prevailing trends in nanocomposite research, emphasizing the indispensable role of computational tools in comprehending this vast wealth of information.

Exudative-pleural-effusion (ePE) is a common presentation in pulmonology clinics. Pleural biopsy is indicated for identifying the aetiology in undiagnosed ePE especially the ones with low adenosine-deaminase levels. The access to rigid and semi-rigid medical thoracoscopy is scarce and heterogeneous in a resource limited country like India. In such circumstances, using flexible bronchoscope via intercostal-chest-tube for visualization of parietal pleura and pleural biopsy offers a way out. Here, in this retrospective study, we have presented our experience of such practice on 25 cases. Mean age was 52.4±1 years. Adhesions were present in 40% of the subjects. Most common finding was presence of nodules. On an average 6.8 passes were taken with maximum of 10. In 32% cases only tiny tissue was obtained, hence requiring multiple passes. Large tissue could be obtained in 44% of the subjects. Mean duration of the procedure was 35.6±9.0 minutes. Tissue diagnosis was established in 80% with most common being malignancy (48%) followed by tuberculosis (20%). In 3 cases, the final diagnosis was made by exclusion. No major complications were recorded. In conclusion, medical thoracoscopy using flexible video bronchoscope via intercostal-chest-tube was a feasible alternative for the diagnosis of ePE effusion in resource limited settings.

Perturbation in the microbial population/colony index has harmful consequences on human health. Both biological and social factors influence the composition of the gut microbiota and promote gastric diseases. Changes in the gut microbiota manifest in disease progression owing to epigenetic modification in host which influences differentiation and function of immune cells adversely. Uncontrolled use of antibiotics; chemotherapeutic drugs and change in the diet pattern usually contribute to the changes in the colony index of sensitive strains known to release microbial content in the tissue micromillieu. Ligands released from dying microbes induce TLR mimicry on interaction with TLR abnormally which skew hypoxia and sterile inflammation contributing to severity of disease like IBD autoimmunity and cancer. Various modalities/interventions practiced across the globe and future strategies for microbiota based therapeutic approaches with special emphasis on tumor and inflammatory diseases are reviewed here. Therefore the major aim and scope of this manuscript is to both discuss various modalities/interventions across the globe and to design future microbiota based therapeutic approaches for mitigating the burden with special emphasis on tumor and Inflammatory diseases.

Patient derived model systems are important tools for studying novel anti-cancer therapies. Patient derived xenografts (PDXs) have gained favor over the last 10 years as newer mouse strains have improved the success rate of establishing PDXs from patient biopsies. PDXs can be engrafted from head and neck cancer (HNC) samples across a wide range of cancer stages, retain the genetic features of their human source, and can be treated with both chemotherapy and radiation, allowing for clinically relevant studies. Not only do PDXs allow for study of patient tissues in an in vivo model, they can also provide a renewable source of cancer cells for organoid cultures. Herein, we review the uses of HNC patient derived models for radiation research including approaches to establishing both orthotopic and heterotopic PDXs, approaches and potential pitfalls to delivering chemotherapy and radiation to these animal models, biological advantages and limitations, and alternatives to animal studies that still use patient-derived tissues.

Chlorella vulgaris has considerable promise as a raw material for biofuel production since it has a high productivity per unit area, has a minimum influence on the environment, and does not significantly affect food security. Nevertheless, the low fatty content of their biomass poses a considerable economic obstacle for commercialization. Increasing the amount of biomass and lipids produced by these algae is essential for improving the economic feasibility of using them as biofuel sources. This review highlights the significance of identifying appropriate algal strains, namely those found in local environments, and utilising mutagenesis and genetic engineering techniques to create 'platform strains'. Prior endeavours have primarily concentrated on altering environmental and dietary parameters to enhance the production of biomass and lipids. Here, we review a scientific literature that examines biotechnological approaches and develops methodologies designed to increase lipid production, emphasising the importance of aligning engineering efforts with breakthroughs in DNA manipulation tools. In addition, the review research evaluates the present economic and commercial situation of algal biorefineries, including any related disadvantages. In summary, this thorough research highlights the importance of using creative methods to tackle the intricacies of lipogenesis and enhance the economic viability of producing biofuels from algae.

Background: Cytokines are multifunctional glycoproteins playing a vital role in the tumor microenvironment and in the progression of breast cancer. The immune responses in the tumors restrained by pro- and anti-inflammatory cytokine expressions could be influenced by genetic polymorphisms. Hence, the present study evaluated the contribution of IL6 (rs1800797, rs1800796, and rs1800795), and IL18 (rs1946518, rs187238, and rs549908) genotypes and its haplotypes with risk and progression of breast cancer in south Indian population. Methods: The polymorphisms of IL6 gene -597G>A, -572G>C, -174G>C and IL18 gene -607C>A, -137G>C, and 105A>T were genotyped through PCR-RFLP and As-PCR assays in blood DNA of 600 subjects. We have performed haplotype, LD, univariate, multivariate logistic regression and Kaplan-Meier analyses for the obtained data. Results: The frequency of AA genotype & A-allele of IL6 -597G>A, and CC genotype & C allele of IL6 -174G>C polymorphism was higher in breast cancer patients and was found to be significantly associated with TNM staging, late (advanced) stage, metastasis, etc. While, CG and GG genotypes of IL6 -572 C>G polymorphism had a protective role against breast cancer. Further, IL18 -607C>A, -137G>C & 105A>T polymorphisms were found to be associated with lobular carcinoma subtype, PR-ve and HER2+ve breast cancer patients. Perfect LD was observed between all SNPs of IL6 & IL18 genes under study; G-C-C, A-G-G and A-C-C haplotype combination of IL6 genes had conferred 2.09, 2.25 and 4.72 folds risk for breast cancer respectively. In survival analysis, we observed that the C allele of rs 1800795 was found to be significantly associated with 5years overall survival in breast cancer subjects. Conclusions: Overall, our results suggest the importance of genotypic and haplotype analysis of IL6, and IL18 gene variants in progression and risk identification of breast cancer.

Aurora kinase A (AURKA) is a normal cell proliferation-inducing enzyme encoded by AURKA gene, with over-expression observed in different types of malignancies. Hence, the goal is to find potential inhibitors against AURKA. In this study, molecular docking, Standard Precision and Extra Precision methods were employed. After the docking study, the ligands showed an extremely low binding score which suggested very high binding affinity of the ligands. Furthermore, Quantum polarized ligand docking (QPLD) was performed to predict the binding status of the molecules. Based on the binding affinity, the top four compounds were chosen for further analysis. The docked complexes were further analyzed in explicit water conditions using 100 ns molecular dynamics simulations and binding free energy calculation. Then, density functional theory (DFT) calculation was used to calculate the molecular properties of the molecules. Finally, systems biology experiments validated the molecular docking and molecular dynamics simulation studies and indicated that quercetin, kaempferol, luteolin and rutin could inhibit the AURKA. The results show that, these four molecules have high binding affinity to the AURKA and significant interactions (LEU139, GLU211and ALA213) were also identified with the hinge region of Aurora kinase A. Thus, LEU139, GLU211, and ALA213 were identified as the crucial protein mechanisms.

Genome-wide sequencing data play an important role in evaluating the genomic level differences between superior and poor-quality crop plants and improving our understanding of molecular association with desired traits. We analyzed the obtained 92,921,066 raw reads from genome-wide resequencing of Cucumis sativus var. hardwickii through in-silico approaches and mapped to the reference genome of Cucumis sativus to identify the genome-wide single nucleotide polymorphisms (SNPs) and Single nucleotide variations (SNV). Here, we report 19, 74,213 candidate SNPs including 1,33,468 insertions and 1,43,237 deletions and 75 Indels genome-wide. A total of 2228224 identified variants were classified into four classes including 0.01% sequence alteration, 5.94% insertion, 6.37% deletion and 87.66% SNV respectively. These variations can be a major source of phenotypic diversity and sequence variation within the species. During the present study these variants were also utilized to resolve orthologous relationships among the genomes of C. melo and C. sativus var. hardwickii. Overall, the discovery of SNPs and genomic variants may help predict the plant response to certain environmental factors and can be utilized to improve crop plants' economically important traits.

This chapter explores the pivotal role of maize (Zea mays L.) in global nutrition, emphasizing its status as a staple food worldwide. It discusses maize's complex nutritional profile, including macronutrients, micronutrients, and dietary fiber. The chapter also covers biofortification efforts to enhance maize with essential nutrients, addresses nutritional concerns related to maize-centric diets, and explores genetic modification and agronomic strategies to boost nutrient-rich maize yields. Additionally, it delves into maize processing traditions, nutrient retention techniques, and the importance of promoting nutrient-rich maize varieties. The chapter outlines post-harvest strategies to combat nutrient loss and prevent contamination while emphasizing the significance of consumer education and diverse diets. Case studies illustrate the impact of improved maize nutrition and provide replicable strategies. The chapter concludes by considering emerging research and technology, identifying challenges, and proposing solutions to enhance maize's nutritional value in the future.

Development of high nutritious bakery products with optimum utilization of food waste is a major challenge for food industries. Food waste is major challenge in an each country. The optimum utilization of food waste for sustainable development goal of country is important ant for growth of the nation. The aim of the present work is to prepare value-added composite flour mixed bread from wastes of fruit and vegetables. The composite flour was prepared in four formulations of Peel and Pomace Wheat Flour (PPWF), as PPWF1, PPWF2, PPWF3 and PPWF4. Compositing flour was blended by a mix of vegetable and fruits pomace powders and whole wheat flour. Indian gooseberry pomace powder, apple pomace powder, bottle gourd peel powder, and potato peel powder were used with whole wheat flour to make pomace and whole wheat flour compositions as PPWF1, PPWF2, PPWF3 and PPWF4. Broadly this work was divided into three phases, first phase has conducted nutritional and functional analysis on peel and pomace powders individually, which shows the significance of using them for our research work. The second phase works in the creation of composite flours with different composition ratios as discussed above as PPWF. This phase shows the nutritional and functional analysis of four composite flours. Out of these four flours, PPWF3 contained a good amount of fiber 8.16%, crude protein 3.18%, total phenolic content 14.48%, moisture 9.5%, vitamin C 13.64mg/100g, and total phenolic compound 14.48(mg/GAE/g) which are maximum and acceptable range values as compared to other three composite flours and the wheat flour-control group flour. Then in the third phase, the PPWF3 is used as a partial replacement ratio of wheat flour in wheat flour due to its high phenolic content, Vitamin C, and the richness of fibers. This composite flour is used to make bread dough, two samples G1 and G2 are made; out of which G2 offers better nutritional, functional, and sensory evaluations in comparison with refined wheat four bread is taken as a control group. Thus, such utilization of food wastes in bread making can generate a value of wastes and can improve nutritional attributes of bread, which may improve an individual’s health.

The intensification of modern farming methods in developed nations has exacerbated the issue of soil degradation and over-utilization of naturally available resources, hence, tinkering negatively with the health and productive capacity of soil. Chemical fertilizers, while increasing crop yields, have resulted in environmental pollution and health hazards. Green manuring presents a sustainable alternative by enriching soil fertility and reducing reliance on chemical fertilizers. This paper reviews the impact of green manuring on soil properties, crop yield, and farm economies. In-situ green manuring involves growing and incorporating the crops within the field, while ex-situ green manuring incorporates plant material from external sources. Leguminous green manures are particularly effective owing to nitrogen fixation capability and rapid decomposition. The inclusion of green manure improves the availability of nutrients, microbial count and carbon content of the soil, thereby, enhancing the overall health of soil and crop productivity. Additionally, green manures reduce pests and diseases, suppress weeds, and provide supplementary forage. Despite the benefits, challenges such as limited water resources, seed availability, and farmer reluctance hinder widespread adoption. Future research should focus on raising awareness, quantifying benefits, and developing location-specific cropping systems to optimize green manuring practices.

Maize (Zea mays L.) stands as one of the most extensively cultivated crops globally, offering significant contributions to food, animal feed, and biofuel production. Maize yield is significantly impacted by diverse climate and soil variables, yet its productivity faces hindrances due to abiotic stresses, including drought, salinity, extreme temperatures, and cold conditions. In confronting these hurdles, the field of crop breeding has undergone a transformation thanks to high-throughput sequencing technologies (HSTs). These advancements have streamlined the identification of beneficial quantitative trait loci (QTL), associations between markers and traits (MTAs), as well as genes and alleles that contribute to crop improvement. Presently, well-established omics techniques such as genomics, transcriptomics, proteomics, and metabolomics are being amalgamated into maize breeding studies. These approaches have unveiled new biological markers that are being employed to bolster maize's capacity to withstand an array of challenges. In this chapter, we explore the current knowledge regarding the morpho-physiological and molecular mechanisms that underlie the resistance and tolerance of maize to biotic and abiotic stresses. The focus is on utilizing omics techniques to augment maize's ability to withstand these challenges. Moreover, it emphasizes the significant potential of integrating various omics techniques to tackle the challenges presented by biotic and abiotic stress in maize productivity, contrasting with singular approaches.

Severe acute respiratory syndrome novel coronavirus 2 (SARS-CoV-2) has caused the global pandemic as COVID-19, which is the most notorious global public health crisis in the last 100 years. SARS-CoV-2 is composed of four structural proteins and several non-structured proteins. The multi-facet nucleocapsid (N) protein is the major component of structural proteins of CoVs, However, there are no dedicated genomic, sequences and structural analyses focusing on potential roles of N protein. Hence, there is an urgent requirement of a detailed study on N protein of SARS-CoV-2. Herein, we are presenting a comprehensive study on N protein from SARS-CoV-2. We have identified seven motifs conserved in the three major domains namely N-terminal domain, linker regions and the C-terminal domains. Out of seven motifs, six motifs are conserved across different members of coronaviridae, while motif4 is specific for SARS CoVs with potential amyloidogenic properties. Additionally, we report this protein has large patches of disordered regions flanking with these seven motifs. These motifs are hubs of epitopes with 67 experimentally verified epitopes from related viruses. We report the presence of three nuclear localization signals (NLS1-NLS3 mapped to 36-41, 256-26, and 363-389 residues, respectively) and two nuclear export signals (NES1-NLS2 from 151-161 and 217-230 residues, respectively) in the N protein of SARS-CoV-2. These deciphered two Q-patches as Q-patch1 and Q-patch2, mapped in the regions of 266-306, and 361-418 residues, which potentially help in the aggregation of the viral proteins along with ²¹⁹LALLLLDR²²⁶ patch. Additionally, we have identified 14 antiviral drugs potentially binding to seven motifs of N-proteins using docking-based drug discovery methods.

Natural and sustainable plant-based antioxidants and antimicrobials are highly desirable for improving food quality and safety. The present investigation assessed the antimicrobial and antioxidant properties of active components from Alkanna tinctoria (herb) roots, also known as Ratanjot root. Two methods were used to extract active components: microwave-assisted hot water (MAHW) and ethanol and air-dried. MAHW extract yielded 6.29% while the ethanol yielded 18.27%, suggesting superior Ratanjot root extract powder (RRP) solubility in ethanol over water. The ethanol extract showed significantly higher antioxidant activity than the MAHW extract. Gas chromatography and mass-spec analysis revealed three major phenolic compounds: Butanoic acid, 3-hydroxy-3-methyl-; Arnebin 7, and Diisooctylpthalate. The color attributes (L*, a*, b*, hab, C*ab) for the ethanolic and MAHW extracts revealed significant differences (P < 0.05) in all the above parameters for both types of extracts, except for yellowness (b*) and chroma (C*ab) values. The ethanol extract exhibited antimicrobial activity against 14 bacterial species, with a signifi-cantly higher inhibitory effect against Gram-positive bacteria (Listeria monocytogenes and Staphylococcus aureus) than the Gram-negative bacteria (Salmonella enterica serovar Typhimurium and Escherichia coli). The minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) were both 25 mg/ml for the Gram-negative bacteria, while the MIC and MBC concentrations varied for Gram-positive bacteria (0.049 - 0.098 mg/ml and 0.098 - 0.195 mg/ml) and the antimicrobial effect was bactericidal. The antimicrobial activities of RRP extract remained stable under broad temperature (37-100°C) and pH (2-6) conditions, as well as during refrigerated storage for 30 days. Application of RRP at 1% (10 mg/g) and 2.5% (25 mg/g) levels in a cooked chicken meatball model system prevented lipid oxidation and improved sensory attributes and retarded microbial growth during refrigerated (4°C) storage for 20 days. Furthermore, the RRP extract was non-toxic when tested with sheep erythrocytes and did not inhibit the growth of probiotics, Lacticaseibacillus casei, and Lactiplantibacillus plantarum. In conclusion, the study suggests that RRP possesses excellent antimicrobial and antioxidant activities, thus making it suitable for food preservation.

Predicting anomalies in manufacturing assembly lines is crucial for reducing time and labor costs and improving processes. For instance, in rocket assembly, premature part failures can lead to significant financial losses and labor inefficiencies. With the abundance of sensor data in the Industry 4.0 era, machine learning (ML) offers potential for early anomaly detection. However, current ML methods for anomaly prediction have limitations, with F1-measure scores of only 50% and 66% for prediction and detection, respectively. This is due to challenges like the rarity of anomalous events, scarcity of high-fidelity simulation data (actual data is expensive), and the complex relationships between anomalies not easily captured by traditional ML approaches. Specifically, these challenges relate to two dimensions of anomaly prediction: predicting when anomalies will occur and understanding the dependencies between them. This paper introduces a new method called Robust and Interpretable 2D Anomaly Prediction (RI2AP) designed to address both dimensions effectively. RI2AP is demonstrated on a rocket assembly simulation, showing up to a 30-point improvement in F1 measure compared to current ML methods. This highlights its potential to enhance automated anomaly prediction in manufacturing. Additionally, RI2AP includes a novel interpretation mechanism inspired by a causal-influence framework, providing domain experts with valuable insights into sensor readings and their impact on predictions. Finally, the RI2AP model is deployed in a real manufacturing setting for assembling rocket parts. Results and insights from this deployment demonstrate the promise of RI2AP for anomaly prediction in manufacturing assembly pipelines.

Milk serves as a crucial source of natural bioactive compounds essential for human nutrition and health. The gastrointestinal digestion of milk proteins releases various biologically active peptides that positively impact human health and enhance physiological performance. With the growing production of cheese, Greek yogurt, and other dairy products, the volume of unutilized acid whey is significantly increasing. Acid whey, containing almost all whey proteins and approximately one-quarter of casein, presents a valuable raw material for generating peptides with potential health benefits. These peptides exhibit properties such as antioxidant, antimicrobial, anti-inflammatory, anticarcinogenic, antihypertensive, antithrombotic, opioid, mineral-binding, and growth-stimulating activities, contributing to improved human immunity and the treatment of chronic diseases. Enzymatic hydrolysis of milk proteins has been developed as a method to produce these peptides, facilitating their use in food fortification. To incorporate whey into functional beverages, it undergoes fermentation by lactic acid bacteria with proteolytic activity. To specifically enrich these beverages with peptides exhibiting targeted bioactivities, it is essential to select lactic acid bacteria strains possessing the requisite protease profiles. Additionally, the sensory properties of the final product can be enhanced using starter cultures with diverse metabolic capabilities, even in the absence of added flavoring agents. Given the imperative to develop waste-free technologies and enhance the profitability of the dairy industry, there is a growing need to efficiently utilize and transform acid whey into a broad spectrum of valuable products and food additives. This approach is justified not only by the nutritional benefits of the bioactive components in whey but also by the commercial potential of safe and health-enhancing products.

The paper focuses on the application of a multilevel, integrative and territorial approach to the protection of cultural heritage through planning instruments in Serbia. It points out the problems of the sectoral approach and discusses international recommendations that can be integrated into the planning methodology. The case study is the area of Djerdap National Park, which has an already established international and national importance. The research suggests that the cultural heritage in the area, with the exception of the Roman limes, is still recognized at the level of individual localities. The study emphasizes the importance of aligning all levels of governance to safeguard the whole spatial entity rather than focusing solely on its particular areas. The interna-tional and national importance of the planning area contributes to the strengthening of awareness of heritage and its institutional protection. However, the vitality of the area, which is key to its sustainable development, comes from the local level. Planning documents contribute to the inte-gration of local values and local communities into development programs and projects.

In order to shorten the detection time and improve the average precision on embedded devices, A lightweight and high accuracy model is proposed for passion fruit in complex environments (backlight, occlusion, overlap, sunny, cloudy, rainy). Firstly, replacing the backbone network of YOLOv5 with a lightweight GhostNet model reduces the number of parameters and computation while improving detection speed. Secondly, a new feature branch is added to the GhostNet network, and the feature fusion layer in the neck network is reconstructed to effectively combine the lower-level and higher-level features, which not only improves the accuracy of the model but also maintains its lightweight. Finally, the knowledge distillation methods are used to transfer the knowledge from the more capable teacher model to the less capable student model, which significantly improving the detection accuracy. The improved model is denoted as G-YOLO-NK. The average accuracy of the G-YOLO-NK network is 96.00%, which is 1.00% higher than the original YOLOv5s model. Furthermore, the improved model size is 7.14MB, reduced to half of the original model, and the real-time detection frame rate is 11.25 FPS on the Jetson Nano. Compared to the state-of-the-art model, the proposed model outperforms them in terms of average precision and detection performance. The present work provides an effective model for real-time detection of passion fruits in complex orchard scenes, which can provide valuable technical support for the development of orchard picking robots and greatly improve the intelligence level of orchards.

The Simultaneous Localization And Mapping (SLAM) scanner is an easy and portable Light Detection And Ranging (LiDAR) data acquisition device. Its main output is a 3D point cloud covering the scanned scene. Regarding the importance of accuracy in the survey domain, this paper aims to assess the accuracy of two SLAM scanners: the NavVis VLX and the BLK2GO Scanner. This assessment is conducted for both outdoor and indoor environments. In this context, two types of reference data are used: the Total Station (TS) and the static scanner Z+F Imager 5016. To carry out the assessment, four comparisons are tested: cloud to cloud, cloud to mesh, mesh to mesh, and edge detection board assessment. However, the results of the assessments confirm that the accuracy of indoor SLAM scanner measurements (5 mm) is greater than that of outdoor ones (between 10 mm and 60 mm). Moreover, the comparison of cloud to cloud provides the best accuracy regarding direct accuracy measurement without manipulations. Finally, based on the high accuracy, scanning speed, flexibility, and the accuracy differences between tested cases, it is confirmed that SLAM scanners are effective tools for data acquisition.

The impact of interaction SS with MJO on rainfall along Java Island to East Nusa Tenggara has been studied using daily rainfall observation data from 2140 weather observation stations, which are also equipped with GSMaP, OLR, and ERA5 data. There were 61 SS events found, 17 during active MJO and 44 in inactive MJO. Rainfall increases more in the western study area when the active MJO and more in the eastern study area when the inactive MJO is due to SS. SS reduces rainfall in the Jakarta region, regardless of the activity or inactivity of the MJO. SS causes extreme rainfall to only occur in a small part of certain areas, so it tends to significantly reduce the possibility of extreme rainfall. In the southern part of the IMC, SS predominates over MJO in supporting increased water vapor transport. Large-scale synoptic circulations like the monsoon, SS, and MJO can interact with local land-sea wind circulation to produce spatiotemporal variability in rainfall on Java Island. Rainfall mostly increases in the afternoon and decreases in the morning when SS occurs, whether there is MJO or not. Convective instability analysis indicates that SS increases precipitation, most likely by lowering CIN and raising VIMFC.

Glycosidic linkage analysis was conducted on the unfractionated polysaccharides in the alcohol-insoluble residues (AIRs) prepared from six red seaweeds (Gracilariopsis sp., Prionitis sp., Mastocarpus papillatus, Callophyllis sp., Mazzaella splendens, and Palmaria palmata) using GC-MS/FID analysis of partially methylated alditol acetates (PMAAs). The cell walls of P. palmata primarily contained mixed-linkage xylans and small amounts of sulfated galactans and cellulose. In contrast, the unfractionated polysaccharides of the other five species were rich in galactans displaying diverse 3,6-anhydro-galactose and galactose linkages with varied sulfation patterns. Different levels of cellulose were also observed. This glycosidic linkage method offers advantages for cellulose analysis over traditional monosaccharide analysis that is known for underrepresenting glucose in crystalline cellulose. Relative linkage compositions calculated from GC-MS and GC-FID measurements showed that anhydro sugar linkages generated more response in the latter detection method. This improved linkage workflow presents a useful tool for studying polysaccharide structural variations across red seaweed species. Furthermore, for the first time, relative linkage compositions from GC-MS and GC-FID measurements, along with normalized FID and total ion current (TIC) chromatograms without peak assignments, were analyzed using principal component analysis (PCA) as a proof-of-concept demonstration of the technique's potential to differentiate various red seaweed species.

Background: Educating college students about the importance of good sleep habits could lead to the adoption of healthier sleep routines, including sufficient sleep duration and sleep quality. The current pre-post study examines the impact of completing a sleep education program called “Sleep 101” on (1) sleep hygiene practices, (2) sleep quality, and (3) weekday and weekend sleep behaviors among college students. “Sleep 101” is an interactive online course developed to educate college students about the importance of sleep by addressing basic sleep physiology, the impact of sleep on mood, academic and physical performance, the interactions between sleep and various substances, and common sleep disorders. Methods: 338 college students were recruited from a midsized public university in the US and invited to participate in “Sleep 101”, of which 25 participants completed the baseline and post-intervention questionnaire. The Sleep Hygiene Index (SHI) was utilized to evaluate sleep hygiene practices, while standard questions were employed to assess weekday and weekend sleep behaviors and overall sleep quality. Results: Those who completed the study demonstrated a significant increase in weekday sleep duration and were less likely to engage in negative prior bedtime activities. In addition, 40% of those who completed baseline and post-intervention assessments noticed improvements in their sleep quality. Conclusion: These findings suggest that a brief online program is beneficial in improving sleep behaviors among college and could be a scalable approach to addressing current sleep issues and preventing future sleep problems in college students.

The profile of secondary metabolites occurring in apple cuticular layer is not only characteristic for particular apple cultivar, but also dynamically reflects various external factors in growing environment. In this study, the possibility to authenticate apple samples based on analysis of their cuticular layer extracts was investigated. Ultra-high-performance liquid chromatography coupled to high resolution tandem mass spectrometry (UHPLC-HRMS/MS) was employed for obtaining metabolomic fingerprints. In total, 274 authentic apple samples, four cultivars harvested within the seasons 2020 to 2022 in the Czech Republic and Poland were analysed. The generated complex data processed by univariate and multivariate statistical methods enabled to build classification models for discrimination of apple cultivars as well as their geographical origin. The models showed very good performance in differentiation of Czech and Polish samples for three of four cultivars: ‘Gala’, ‘Golden Delicious’ and ‘Idared’, moreover, the validity of the models was verified over harvest seasons. The diagnostic markers, besides metabolites of triterpene biosynthetic pathway, mainly represented wax esters. ‘Jonagold’, which is known to be susceptible to mutations, was the only cultivar for which the unambiguous classification of geographical origin was not possible.

Superior fiber quality is one of the most important objectives in cotton breeding. To detect the genetic basis underlying fiber quality, an F2 population containing 413 plants was constructed by crossing Jifeng 914 and Jifeng 173, both of which have superior fiber quality, with Jifeng 173 being better. Five fiber quality traits were investigated in the F2, F2:3, F2:4, and F2:5 populations. Quantitative trait loci (QTL) mapping was conducted based on a high-density genetic map containing 11,488 single nucleotide polymorphisms (SNPs) and spanning 4,202.12 cM in length. Transgressive segregation patterns and complex correlations in the five tested traits were observed. A total of 108 QTLs were found, including 27 for fiber length (FL), 16 for fiber strength (FS), 24 for micronaire (MC), 17 for fiber uniformity (FU), and 24 for fiber elongation rate (FE). Chromosome A7 contained 12 QTL, ranking the first. No QTL was found on chromosome D1 and D11. Each QTL contributed 1.98%–21.45% to the phenotypic variation (PV), including 13 major effect QTLs that contributed more than 10% toward PV. Two QTLs could be repeatedly detected in three populations, including qFL-D3-2 in F2, F2:4, and F2:5 with 9.18%–21.45% of PV, qFS-A11-1 in F2:3, F2:4 and F2:5 with 6.05%–10.41% of PV. Another seven stable QTLs could be detected in two populations, including four major effect QTLs: qFL-A12-3, qFS-D10-2, qMC-D6-2, and qMC-D8-1. Fourteen QTL-overlapping regions were found, which might explain the complex correlations among the five phenotypic traits. Four regions on chromosome A11, D3, D6, and D10 covered by both stable and major effect QTLs are promising for further fine mapping. The genomic regions of the two QTLs detected in three populations and the four major effect QTLs contain 810 genes. Gene functional analysis revealed that the annotated genes are mainly involved in protein binding and metabolic pathways. Fifteen candidate genes in the qFL-D3-2 region are highly expressed in fiber or ovules during fiber initiation, elongation, secondary cell wall thickening, or maturation stages. qRT-PCR revealed that Ghir_D03G005440.1 and Ghir_D03G011310.1 may play a role in promoting fiber initiation, Ghir_D03G006470.1 may be beneficial for promoting fiber elongation. This study provides more information for revealing the molecular genetic basis underlying cotton fiber quality.

Currently there are fewer depth models applied to pepper picking detection, while the existing generalized neural networks have problems such as large model parameters, long training time, and low model accuracy.In order to solve the above problems, this paper proposes a Yolo-chili target detection algorithm for chili pepper detection. First, the classical target detection algorithm yolov5 is used as a benchmark model, and an adaptive spatial feature pyramid structure combining the attention mechanism and the idea of multi-scale prediction is introduced to improve the model's detection effect on occluded peppers and small target peppers. Secondly, a three-channel attention mechanism module is introduced to improve the algorithm's long-distance recognition ability and reduce the interference of redundant testers. Finally, the quantized pruning method is used to reduce the model parameters and realize the lightweight processing of the model. Applying the method to the homemade chili pepper dataset, the AP value of chili pepper reaches 93.11%; the accuracy rate is 93.51% and the recall rate is 92.55%.The experimental results show that yolo-chili is able to achieve accurate and real-time pepper detection under complex orchards.

The temporary immersion system bioreactor named GreenTray®[2], [3]presents advantages over the existing ones. Firstly, there is no need to use forceps to move the shoots or plantlets in or out of the recipient, neither the use of scalpel to divide them. Secondly, the basis of the shoot can remain in the GreenTray® and can sprout again in several cycles of growth. These two characteristics reduce the costs in the process of micropropagation. Besides, shoots or plantlets development is enhanced by the aeration of the recipient, thus enriching with CO2 the recipient atmosphere. The chapter describes and provides images and values of interest in (1) the micropropagation process of some commercial Prunus or Pyrus rootstocks; (2) the plantlet growth under autotrophic conditions; and (2) the inoculation of plants with pathogens that reproduce in vitro the symptoms observed in vivo, using the GreenTray® bioreactor.

Aiming at the problems of inaccurate segmentation of long object and information loss of small object in real-time semantic segmentation algorithm, this paper proposes a lightweight multi-branch real-time semantic segmentation network based on BiseNetV2. The new auxiliary branch makes full use of spatial details and context information to cover the long object in the field of view. Meanwhile, in order to ensure the inference speed of the model, the asymmetric convolution is used in each stage of the auxiliary branch to design a structure with low computational complexity. In the multi-branch fusion stage, the alignment and fusion module is designed to provide guidance information for deep and shallow feature mapping, so as to make up for the problem of feature misalignment in the fusion of information at different scales, and thus reduce the loss of small target information. In order to further improve the model’s awareness of key information, a global context module is designed to capture the most important features in the input data. The proposed network uses NVIDIA GeForce RTX 3080 Laptop GPU experiment, on the road street view data set Cityscapes and CamVid average occurring simultaneously ratio reached 77.1% and 78.4% respectively, with running speed of 127 frames/s respectively and 112 frames/s. The experimental results show that the proposed algorithm can achieve real-time segmentation and improve the accuracy significantly, showing good semantic segmentation performance

In this paper we study a class of impulsive delayed neural networks with parameter uncertainties and reaction-diffusion terms. Using the properties of M-matrices and some inequality techniques, some sufficient conditions are derived to guarantee the global exponential stability of the given system. The results obtained are presented by simple algebraic inequalities, which are certainly more concise than previous methods. Finally, the validity and usefulness of our results are illustrated by arithmetic examples.

Strawberry root rot caused by Neopestalotiopsis clavispora is one of the main diseases of strawberry and significantly impacts the yield and quality of strawberry fruit. There are now no effective control techniques available except for fungicide sprays, which may directly impact consumers. Biological control is becoming an alternative method for the control of plant diseases to replace or decrease the application of traditional synthetic chemical fungicides. Trichoderma is widely used as a biological agent for controlling strawberry root rot. In order to provide resources for screening the highly effective biocontrol fungus for controlling strawberry root rot caused by Neopestalotiopsis clavispora, the biocontrol mechanism,the control effects of Trichoderma asperellum CMT10 against strawberry root rot and growth-promoting effects on strawberry seedlings were investigated by plate culture, microscopy observation and root drenching methods.The results showed that CMT10 had obvious competitive, antibiotic and hyperparasitism effects on Neopestalotiopsis clavispora CMGF3. The CMT10 could quickly occupy nutritional space, and the inhibition rates of CMT10 against CMGF3 in confrontation culture on 7 d was 65.49%. The inhibition rates of volatile metabolite and fermentation metabolite produced by CMT10 against CMGF3 were 79.67% and 69.84%, respectively. The mycelium of strain CMT10 can act as hyperparasites by making contacting, winding and penetrating hyphae of CMGF3. Pot experiment showed that the biocontrol efficacy of CMT10 on strawberry root rot caused by Neopestalotiopsis clavispora was 63.00%. CMT10 had obvious promotion effect on strawberry growth, the plant height, root length, total fresh weight, root fresh weight, stem fresh weight and root dry weight, with the promotion rates were 20.09%, 22.39%, 87.11%, 101.58%, 79.82% and 72.33%, respectively. Overall, this study showed the ability of Trichoderma asperellum CMT10 to control strawberry root rot and their potential to develop as novel biocontrol agents to replace chemical fungicides for eco-friendly, sustainable agriculture.

Pyrops candelaria is one of the common pests of fruit trees, but the research on the pathogenic microorganisms it may carry is very limited. Therefore, it is essential to reveal the pathogenic microbes it carries and their potential hazards. This study found a new virus from the transcriptome of P. candelaria, which was first reported in P. candelaria and named as PyCaV (Pyrops candelaria associated virus). RACE and bioinformatics assay revealed that the full-length of PyCaV is 10855 bp with the polyA tail, containing a single open reading frame (ORF) encoding a polyprotein consisting of 3171 amino acid (aa). The virus has a typical Iflavirus structure, including two rhv domains, a RNA helicase domain (HEL), a 3C cysteine protease domain (Pro), and a RNA-dependent RNA polymerase domain (RdRp). Further phylogenetic analysis revealed that this virus belongs to family Iflaviridae and sequence alignements analysis suggedted PyCaV is new member in unassigned genus of family Iflaviridae. Further in-depth analysis of virus-infection-part showed that PyCaV is distributing in the whole longan lanternfly, including its head, chest, and abdomen, but more PyCaV was identified in the chest. The distribution of PyCaV in different parts of P. candelaria was further explored, which showed that more PyCaV were detected in its piercing-sucking mouthparts and chest viscera. Statistical analysis showed that the PyCaV infection was affected by time and locations.

With the burgeoning growth of online retail, the issue of counterfeit products has become a significant threat to both consumer trust and brand integrity, posing challenges to sustainable market practices. Online retail platforms are promoted to redesign their channel structures and enhance brand traceability to tackle counterfeits using blockchain technology. To investigate the interactions between blockchain technology and the channel structures of online retail platforms, we design a game theory model incorporating a manufacturer with(out) blockchain participation selling products via an online retail platform that operates an agency channel and/or a reselling channel. We show that the critical trade-off of blockchain participation comprises the brand assurance effect of the blockchain, the channel competition intensification effect, and the blockchain adoption cost. The platform is capable of strategically designing the channel structure to encourage (while discouraging) blockchain participation by the manufacturer. Our analysis highlights the complementarity between blockchain participation and the channel structure. Furthermore, the effect of the consumer’s belief in the reselling channel, the commission fee in the agency channel, and the substitutability between channels are investigated in depth. The research provides valuable insights for online retail platforms and policymakers seeking to foster a sustainable and trustworthy e-commerce ecosystem.

Apis mellifera, especially weak ones, are highly vulnerable to Carpoglyphus lactis mites, which can rapidly infest and consume stored pollen, leading to weakened colonies and potentially colony collapse. This study aimed to ascertain and investigate the prevalence of this mite in honeybee colonies across 9 provinces in the Republic of Korea (ROK). A total of 615 honeybee colonies were collected, from 66 apiaries during the spring and 58 apiaries during the summer of 2023. A 1,242 bp segment of the the Cytochrome c oxidase subunit 1 (COI) gene was amplified using the polymerase chain reaction method. The detection levels of C. lactis in the honeybees were compared between winter and summer. Based on the COI sequence analysis, the nucleotide sequence similarity of C. lactis mites isolated in the ROK with those from China (NC048990.1) was found to be 99.5%, and with those from the United Kingdom (KY922482.1) was 99.3%. This study is the first report of C. lactis in Korean apiaries. The findings in this study demonstrate a significantly higher detection rate in winter, which is 4.1 times greater than that in summer (p &lt; 0.001). Furthermore, the results underscore the usefulness of molecular diagnostic techniques for detecting C. lactis mites.

COX II containing a dual core CuA active site is one of the three core subunits of mitochondrial Cco, which plays a significant role in the physiological process. In this report, the full-length cDNA of COXⅡ gene was cloned from Sitophilus zeamais, which had an ORF of 684 bp encoding 227 amino acids residues. The predicted COXⅡ protein had a molecular mass of 26.2 kDa with pI value of 6.37, and multiple sequence alignment and phylogenetic analysis indicated that Sitophilus zeamais COXⅡ had high sequence identity 78.51% with the COXⅡ of other insect species, especially similarity to sitophilus oryzae. This gene was subcloned into the prokaryotic expression vector pET-32a, and induced by IPTG in E.coli Transetta (DE3) expression system. Finally the COXⅡ with 6-His tag was purified using affinity chromatography with Ni²⁺-NTA agarose. WB showed the recombinant COXⅡ was about 44 kD, and the concentration of fusion protein was 50μg/mL. UV-spectrophotometer and infrared spectrometer analysis showed that recombinant COXⅡ could catalyze the oxidation of substrate Cytc, and influenced by AITC. It was found that AITC could form a hydrophobic region with COXⅡ protein via molecular docking, besides, a sulfur atom of AITC structure could form a length of 2.9 Å hydrogen bond with Leu-31. These results will provide valuable information for elucidating the role of COXⅡ in Sitophilus zeamais responses to AITC, meanwhile, it will helpful to carry out a point mutation in AITC binding sites for the future research.

The properties of the annual, semiannual and triennial oscillations (AO, SAO and TO) in the middle atmosphere have been investigated using the TIMED/SABER temperature data. The Lomb-Scargle and wavelet spectra were used to determine the dominant oscillations in the background temperature field. The AO is prominent at the mid-latitudes. The AO amplitudes present an asymmetry between the two Hemispheres, being larger in the mesosphere than in the stratosphere. The SAO dominates the tropical regions, with three amplitude maxima at altitudes of 45, 75, and 85 km. The SAOs in the upper mesosphere (75 km) are out of phase with those in the mesopause (85 km) in the tropical regions, which can generate an enhancement of 11 K at each equinox, contributing to the lower mesospheric inversion layer. The TO is significant in the tropical region, with amplitude being maximum at 35, 45 and 85 km. Result shows that there may be potential interaction by the TO with SAO at 85km at the equator. The relation between ENSO and TO has also been discussed. The ENSO signal may modulate the amplitude of the TO, mainly in the lower stratosphere. The real origin of the TO may lie in the wave-mean-flow interaction.

The paper describes the new method for image compression based on coordinated group signal transformation. The algorithm is a type of difference coding. Coordinated processing significantly simplifies the difference signal conversion scheme using a single group codec for all signals. The described method considers color channels as correlated signals of a multi-channel communication system. The specifics of the processed data required modification of the coordinated group processing algorithm. First, we changed how to calculate the difference signals to prevent data loss. Secondly, the group codec was supplemented with a neural network to improve the quality of reconstructed images. We considered the following types of neural networks: fully connected, recurrent, convolution, and convolution in the Fourier space. Based on the simulation results, it is best to use fully connected neural networks if the goal is to minimize processing delay time. These networks have a response time of 13 ms. On the other hand, if the priority is to improve quality in cases where delays are not critical, then convolution neural networks in the Fourier space should be used. These networks have a response time of 140 ms and are of significant interest.

As the world population grows, fulfilling the need for biomaterials in the healthcare system becomes increasingly important. Biomaterials, which include metals, polymers, ceramics, and composites, play an important role in the creation of medical devices that improve people's lives. The European Society for Biomaterials described biomaterials as non-biological materials used in medical devices to interact with biological systems. This definition has developed to encompass materials that treat, assess, or replace tissues or bodily functions. Biocompatibility, as defined by the FDA, is a key feature of biomaterials, as is the requirement to fulfil design requirements such as mechanical performance, geometry, and electrical control. Over the last decade, advances in regenerative medicine and tissue engineering have boosted biomaterials' usage in medical applications dramatically. Despite its promise, scientists, engineers, and physicians continue to face significant challenges due to the complexity of biomaterials. Biomaterials have various benefits, including biodegradability, non-toxicity, and biocompatibility, making them extremely useful for replacing, sustaining, or improving biological activities in damaged tissues. They are used in a wide range of applications, including tissue engineering implants, human tissue healing and regeneration, medication delivery systems, and biosensors. This study gives insights into the fundamental characteristics, case studies, and ethical issues associated with the usage and use of biomaterials, further examining their potential and significance in healthcare and medicine.

The studied solar pot is a recent invention, which gained a utility model protection in 2021 from the Hungarian Intellectual Property Office under patent number 5489. The device is made for environmentally friendly cooking or heating (by utilizing solar energy) of foods and liquids. Its structure is similar to a double pipe heat exchanger, it has an outer mantle and an inner cooking tank. The goals of the paper are proposing a new physically-based mathematical model describing the solar pot and carrying out computer experiments with it, assembling an experimental system of the pot connected with a solar collector and performing measurements on it. Based on the results, the solar pot can successfully be used for cooking or sterilizing foods or liquids during the studied time period, in Hungary.

The research reported on this paper was aimed at improving the overall efficiency of a PDO certified artisanal cheese production process. Being a PDO certified foodstuff by the EU, it is considered to have properties and qualities determined by the geographical environment in which is made, with its production taking place in a specific and determined geographical location, in this case the Serra da Estrela region. In that sense, the authors conducted a mapping according to a systemic perspective of the processes involved in the context of manufacturing and distribution of certified Serra da Estrela cheese. Numerous methods were used throughout the process, such as a systemic design analysis, and techniques derived from ethnographic methods, which led to the collection of data in the field and consequently provided the immersion of the researcher in genuine work situations. Critical points were identified and emphasized in the systemic map with the purpose of encouraging initiatives to address and overcome the gaps and inefficiencies detected. The systemic design analysis triggered the development of design work. Observations following an ethnographic approach identified ergonomic risks in cheese making during the process of cutting excess chips, fostering the emergence of musculoskeletal disorders at the wrist. A tool that fits best to the task at hand was developed. A prototype of the new tool enabled collecting feedback from use in the work context, in order to inform product development. The domains of agricultural production and microbiology, considering the specific microorganisms developed trough the ripening process of the cheese, turned out to be aspects of high importance for the issue under focus, contributing to a broader understanding of the ripening process and its risks, simultaneously improving the efficiency and success of cheese production. If it were not for the systemic analysis, which served as a link between the boundaries of distinct domains such as the risk of microorganism contamination, ergonomics, energy efficiency, legislation and regulation policies, transportation challenges and economic viability, approached throughout the research. Simultaneously creating bridges between them, the various problems might not have been detected in the first place, as they are usually addressed in specialized disciplines, predetermined by the restrictions of each specific area of knowledge. As a consequence of the development of this research, which was based on an analysis that sought to establish possible connections between various disciplines and tried to constantly maintain a holistic perspective, making new connections and observing the issues from a new angle, apart from the already established methodologies. All this allowed to lay out the seeds for the development of a plan to tackle the critical points identified by the systemic analysis reported in this paper.

This paper is focused on typical rural settlements in the Stara Planina Mountain area in Serbia. They are distinguished by their authenticity, identity and character, and they have still not been destroyed by inappropriate development as is the case in some other mountain areas in Serbia, where the effects of urbanization, globalization and homogenization are obvious. Consequently, there is a need to prevent these effects in mountain areas where there is a threat of disbalance between development and the inherited natural and cultural values. The paper starts from several important concepts that relate contemporary approaches to cultural heritage preservation, place morphology and planning future development. The concept definitions from recent documents from related fields are used. These concepts are then applied to the area of Stara Planina Mountain and its rural settlements. The necessity for an integrative approach to planning this area with significant natural and anthropogenic potential is pointed out, including its integration into international programs of sustainable development.

Abstract: Transcription factors are crucial pre-transcriptional regulatory mechanisms that can modulate the expression of downstream genes by binding to their promoter regions. DOF (DNA binding with One Finger) proteins are a unique class of transcription factors with extensive roles in plant growth and development. Our previous research indicated a decrease in iron content in chlorotic bamboo leaves. However, to our knowledge, genes related to iron metabolism pathways in bamboo species have not yet been studied. Therefore, in the current study, we identified iron metabolism-related (IMR) genes in bamboo and determined the transcription factors that significantly influence them. Among these, DOFs were found to have widespread effects and potentially significant impacts on their expression. We identified specific DOF members in Dendrocalamus latiflorus with binding abilities through homology with Arabidopsis DOF proteins, and established connections between some of these members and IMR genes using RNA-seq data. Additionally, molecular docking confirmed the binding interactions between these DlDOFs and the DOF binding sites in the promoter regions of IMR genes. The co-expression relationship between the two gene sets was further validated using q-PCR experiments. This study paves the way for research into iron metabolism pathways in bamboo and lays the foundation for understanding the role of DOF transcription factors in D. latiflorus.

The technology-driven world of the 21^st century is currently confronted with a major threat to humankind in the form of the coronavirus disease (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). As of April 22, 2020, COVID-19 has claimed 169, 006 human lives and had spread to over 200 countries with more than 2,471,136 confirmed cases. The perpetually increasing figures associated with COVID-19 are disrupting the social and economic systems globally. The losses are unmatched and significantly higher compared to those from previously encountered pathogenic infections. Previously, two CoVs (SARS-CoV and Middle East respiratory syndrome-CoV) affected the human population in 2002 and 2012 in China and Saudi Arabia, respectively. Based on genomic similarities, animal-origin CoVs, primarily those infecting bats, civet cats, and pangolins, were presumed to be the source of emerging human CoVs, including the SARS-CoV-2. The cohesive approach amongst virologists, bioinformaticians, big data analysts, epidemiologists, and public health researchers across the globe has delivered high-end viral diagnostics. Similarly, vaccines and therapeutics against COVID-19 are currently in the pipeline for clinical trials. The rapidly evolving and popular technology of artificial intelligence played a major role in confirming and countering the COVID-19 pandemic using digital technologies and mathematical algorithms. In this review, we discuss the noteworthy advancements in the mitigation of the COVID-19 pandemic, focusing on the etiological viral agent, comparative genomic analysis, population susceptibility, disease epidemiology, animal reservoirs, laboratory animal models, disease transmission, diagnosis using artificial intelligence interventions, therapeutics and vaccines, and disease mitigation measures to combat disease dissemination.

The wetlands in northeastern Bangladesh are home to some of the most prolific and valuable ecosystems on the planet, offering a wide range of benefits to both the local and wider communities. A limited number of research on this topic have been carried out in various wetlands in coastal hilsa, but none have been located in the northeastern region of Bangladesh. Thus, the goal of this study was to better understand the most commercially relevant species (anadromous hilsa) in northeastern Bangladesh as well as to assess the wetland ecosystem services more thoroughly with the contribution of their fish genetic resources. In addition to laboratory studies, fieldwork was done in the fishing settlements along the Surma River, Hakaluki Haor, and Tanguar Haor. The study classified 77 fish species into 21 subcategories of ecosystem services, of which 56% were not threatened, 17% were vulnerable, and 10% were highly endangered. The species Hilsa was found to be the most economically significant, accounting for 1% of the GDP overall. The study determined if the hilsa stock of the examined wetlands maintains a single or several subpopulations in comparison to other parts of the country when they migrate from saline water to northeastern Bangladesh (freshwater). But when compared to other groups, the FST score was between 0.000 to 0.017, indicating that the populations are identical and that there is genetic material sharing between them. Additionally, these statistics imply that the Sylhet haor and adjacent river systems contain a single stock of Hilsa fish. Nevertheless, a number of stresses and risks, including overexploitation, illicit and destructive fishing, siltation, and natural disasters like flash floods, have been linked to changes in the supply of hilsa and other ecosystem services. This study also emphasizes the necessity of policy attention and research to address the concerns.

Severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) continues to be a global threat due to its ability to evolve and generate new subvariants, leading to new waves of infection. Additionally, other coronaviruses like Middle East respiratory syndrome coronavirus (MERS-CoV, formerly known as hCoV-EMC) which first emerged in 2012, persists and continues to present a threat of severe illness to humans. The continued identification of novel coronaviruses, coupled with the potential for genetic recombination between different strains, raises the possibility of new coronavirus clades of global concern emerging. As a result, there is a pressing need for pan-CoV therapeutic drugs and vaccines. After extensive optimization of an HCV protease inhibitor screening hit, a novel 3CLPro inhibitor (MK-7845) was discovered and subsequently profiled. MK-7845 exhibited nanomolar in vitro potency with broad spectrum activity against a panel of clinical SARS-CoV-2 subvariants and MERS-CoV. Furthermore, when administered orally, MK-7845 demonstrated a notable reduction of viral burdens by &gt;6 log orders in the lungs of transgenic mice infected with SARS-CoV-2 (K18-hACE2 mice) and MERS-CoV (K18-hDDP4 mice).

The continuous casting process of helical fiber reinforced metal matrix composites was proposed, and the experimental equipment was designed and manufactured. The relationship model be-tween the process parameters and the helical shape of the fibers in the metal matrix is analyzed by differential geometry. Helical carbon fiber reinforced lead matrix composites were prepared under different conditions. When the melting temperature and cooling intensity were increased, the helical radius of helical carbon fiber in lead matrix was increased. When the fiber rotation speed was increased, the helical radius was decreased, and the helical pitch was de-creased proportionally. The experimental results are consistent with the process model. Carbon fiber rein-forced aluminum composites were prepared. Scanning electron microscopy showed that the infiltration between the aluminum matrix and the carbon fiber was not complete. As the volume fraction of carbon fiber which was added in composites is too small, the mechanical properties of the composites have not been significantly improved.

This article presents an innovative approach to the design of a safe adaptive backstepping control system. Tailored specifically for underactuated marine robots, the system utilizes simple sensors for enhanced practicality and efficiency. Given their operation in diverse oceanic environments fraught with various sources of uncertainties, ensuring the system's safe and robust behavior holds paramount importance in the control literature. To address this concern, this paper introduces a control strategy designed to ensure robustness at both the kinematic and dynamic levels. By emphasizing the compensation for the system uncertainties, the design integrates a straightforward fuzzy system structure. To further ensure the system's safety, a funnel surface is defined, followed by the design of a suitable nonlinear sliding surface as a function of the funnel and tracking error. Specifically leveraging the Lyapunov function, the study formally establishes the Semi-globally Practically Finite-time Stability of the closed-loop system, validated through simulations conducted on underactuated marine robots.