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We present the synthesis, analysis, and utility of polyvinylpyrrolidone (PVP) stabilized monometallic silver nanospheres for liquefied petroleum gas sensing at room temperature. We have synthesised silver nanospheres (Ag-NSs) in the diameter range of 13–21 nm using a microwave assisted method, which is both easy and fast, because microwave irradiation only takes 30 s. A solution of 0.1 M silver nitrate (AgNO3) in an ethanolic medium was microwave-irradiated to produce Ag-NSs. PVP was used as a stabilising agent throughout the process. Spin coating method was used to produce thin films of synthesised monometallic Ag-NSs. X-ray diffraction (XRD), scanning electron microscopy (SEM), acoustic particle sizer (APS), UV–visible absorption (UV–visible) and Fourier Transform Infrared (FT-IR) spectroscopy were used for characterising Ag-NSs. Based on the acoustic attenuation of the prepared sample, the acoustic particle sizer estimated the diameter of Ag-NSs to be around 17 nm. The deposited films were examined for LPG leakage detection at ambient temperature. This is the first report on monometallic Ag-NSs for leakage detection of LPG at room temperature operation below its lower explosive limit (LEL). The significant finding of the developed sensor is that it prompts the quick response (∼16 s) and recovery (∼64 s) as Ag enhances the reaction rate between the sensing film surface and adsorbed LPG, thereby, augments the sensitivity of sensor even below LEL. Moreover, the fabricated LPG sensor shows noteworthy reproducibility (measured up to six cycles) and stability up to 06 months after fabrication.

The correctness and the true validated data in Human Resource Management (HRM) are important for organizations as the data plays an impactful role in recruiting, developing, and retaining a skilled workforce. On one hand, the validated data in an organization helps in recruiting legitimate skillful employees; on the other hand, keeping the employee's data safe and maintaining privacy laws such as compliance with the General Data Protection Regulation (GDPR) is also an organization's responsibility. Besides, transparency in human resource management operations is crucial because it promotes trust and fairness within an organization. The present HRM systems are centralized in nature and their verifiable credential system is ineffective; this leads to the intentions of internal data sabotage or internal threats. Besides, the organizations' biases also become more prominent.In this paper, we address the above-mentioned problems with a blockchain framework for HRM to utilize the privacy of data access through a Privacy Information Retrieval (PIR) process. To be specific, our proposed framework called Blockchained piR of resOurces as humaN (BRON), is the first blockchain framework to show an effective mechanism to access data from organizations globally without hampering privacy. BRON uses a generalized user registration process to use the services of data access and in the background, it uses Zero-Knowledge Proofs (ZKPs) for global verification and PIR for privacy-based data retrieval. More specifically, credential verification and ZKP-based PIR are the highlights of our proposed BRON. Another interesting aspect of BRON is the use of Proof-of-Authority (PoA) to validate the anonymity and unlinkability of any HR operation. Finally, BRON has also contributed with a smart contract to incentivize the employees. BRON is very generic and easily be customizable as per the HR requirements. We run a set of experiments on BRON and observe that it is successful in providing privacy-assured data access and decentralized human resource data management. Overall, BRON provides 30% reduced latency and 35% better throughput as compared to the existing blockchain solutions in the direction of HRM.

Vehicular networks are expanding their applications for future sustainability. The reported increasing rate of data breaches through vehicular networks by Distributed Denial of Service (DDoS) type of intrusion creates concern for such networks. Existing security solutions focus only on intrusion detection. However, prevention solutions are more proactive and provide security by probabilistic analysis. Existing prevention models for vehicular networks have low accuracy and are unable to handle zero-day attacks and advanced persistent threats. In this paper, we solve the problems mentioned above and introduce Predictive Risk Evaluation for Vehicular Infrastructure Resilience (PREVIR), the first amalgamated model of logit method (statistical analysis) and LogitBoost method (machine learning) to prevent DDoS attacks in vehicular networks. In PREVIR, the logit model predicts the packet probabilities for identifying maliciousness. The machine learning method improves PREVIR’s performance through iterative refinement of the model’s periodic updates based on new traffic parameters. We run a set of experiments on PREVIR. We use our NS3-generated dataset, NSL-KDD public dataset, and CIC-DDoS public dataset. PREVIR analyses multiple attack types, including UDP flood, TCP flood, mixed flooding, U2R, Probe, and R2L attacks. The results show that PREVIR classifies packets with accuracy up to 99.99%. Our proposed PREVIR model achieves a True Positive Ratio (TPR) up to 100% and an average False Positive Ratio (FPR) of 35%. The comparative analysis shows that PREVIR’s efficiency is 20% better on average in the prevention of malicious packets as compared to the state-of-the-art models.

Blockchain networks provide a reliable and secure mode of communication due to their decentralized and distributed nature. The emergence of amalgamated blockchain-based internet-of-things (IoT) systems has generated a huge amount of data to be online. Though blockchains show potential for ensuring transparency, traceability, and immutable records, the privacy of online data in blockchains becomes a question. The privacy of blockchain transactions is at stake as various privacy breaching methods are used by attackers such as linking the transactions, deanonymization, etc. However, the benefits of blockchain make the technology a dominator in the present and future technological paradigms. The other side of the coin deals with privacy information retrieval (PIR), which is necessary to retrieve private information from servers without much revealing. However, the conjunction of blockchain privacy and PIR is very critical and an important aspect of blockchain solutions. In this present survey, we pioneer in analyzing the privacy factors of existing blockchain solutions. We discuss the privacy parameters and important privacy enhancement techniques for blockchains comprehensively. We show the applicability of privacy in various domains including e-commerce, supply chain, healthcare, and IoT. We also discuss PIR-related issues and solutions in the existing literature. We highlight open research problems and discuss the benefits of collaborating with PIR and blockchain systems to improve privacy in blockchains. Our survey is beneficial for academia and industries to be aware of the present status of privacy solutions in blockchains and to address the identified loopholes to make the systems better.

المخلص: أهداف البحث: الجرثومة القولونية المسببة لعدوى البول هي العامل المسبب الأكثر شيوعا لإلتهاب المسالك البولية، حيث تشكل أكثر من 80٪ من حالات التهاب المسالك البولية في جميع أنحاء العالم. تقدم هذه الدراسة بيانات حول الأنماط السائدة، ملامح المقاومة، وعوامل شدة الإمراض التي تساعد على التوطين للجرثومة القولونية المسببة لعدوى البول من مناطق جغرافية مختلفة في الهند. طرق البحث: تم تصنيف الأنماط الجرثومية عن طريق التصقل في لوحات القراءة الصغيرة، تم استخدام الأساليب القياسية لكشف عوامل شدة الإمراض المختلفة، أي الأغشية الحية (باستخدام طريقة زراعة الأنسجة)، إفراز الجزيئات الناقلة للحديد (تم الفحص على وسط الكروم أزورول اس وتم تصنيفها وفقا لطرق كساكي وأرنو)، إفراز الكوليسين (باستخدام تقنية تغطية الأغار)، هدم الجيلاتين (على وسط الجيلاتيناز)، التصاق الخلايا السطحي (باستخدام طريقة تجمع الملح) وملامح مقاومة المضادات الحيوية (باستخدام عشرين مضادا حيويا) والبيتا-لاكتاميز ذات الطيف الواسع تم تقييمها وفقا لمعايير معهد الأمراض السريرية والمختبرية. النتائج: أظهرت سلالات الجرثومة القولونية المسببة لعدوى البول معدلات مقاومة عالية جدا لمعظم المضادات الحيوية المستخدمة بشكل شائع مع أعلى معدلات مقاومة للأمبيسيلين (63.4٪)، وحامض الناليديكسيك (63.4٪)، والسيفوتاكسيم (62.1٪). تم الكشف عن معدلات عالية من مقاومة الأدوية المتعددة (63.36٪)، وإنتاج البيتا-لاكتاميز ذات الطيف الواسع (34.1٪)، والجرثومة القولونية المسببة لعدوى البول المقاومة للكاربابينيم (25.0٪) وكانت من جميع المناطق الجغرافية في الهند. التصاق الخلايا السطحي (61.2٪)، إنتاج الأغشية الحية (62.5٪)، وإنتاج الجزيئات الناقلة للحديد (67.7٪) كانت من أكثر خصائص الخبيثة شيوعا في عزلات الإشريكية القولونية المسببة لعدوى الجهاز البولي. كان تعبير مشترك عن عوامل شدة الإمراض شائع جدا (69.8٪) في سلالات الإشريكية القولونية المسببة لعدوى الجهاز البولي. الاستنتاجات: توجد في الهند سلالات من الجرثومة القولونية المسببة لعدوى البول مقاومة للأدوية المضادة للميكروبات بمعدلات عالية جدا، وهي متنوعة من حيث الأنماط الجرثومية وعوامل شدة الإمراض. Abstract: Objectives: Uropathogenic Escherichia coli (UPEC) is the most common causative agent of urinary tract infection, accounting for more than 80% of cases worldwide. This study presents data on prevalent serotypes, resistance profiles, and colonization-aiding virulence characteristics of UPEC from different geographical regions in India. Methods: UPEC were serotyped through microtiter plate agglutination. Standard techniques were used to detect various virulence characteristics, i.e., biofilm formation (tissue culture plate method), siderophore production (screened on Chrome Azurol S agar and categorized with Csaky's and Arnow's methods), colicin release (agar overlay technique), gelatin hydrolysis (on gelatinase agar), and cell surface hydrophobicity (salt aggregation method). Antibiotic resistance profiles (against 20 antimicrobial agents) and extended-spectrum beta-lactamase (ESBL) were evaluated according to Clinical and Laboratory Standards Institute guidelines. Results: UPEC strains exhibited very high drug resistance rates to most of the commonly used antimicrobial agents; the highest resistance rates were observed for ampicillin (63.4%), nalidixic acid (63.4%), and cefotaxime (62.1%). High rates of multi-drug resistance (63.36%), ESBL-production (34.1%), and carbapenem-resistance (25.0%) were detected in UPEC strains from all geographical regions of India. Hydrophobicity (61.2%), biofilm production (62.5%), and siderophore production (67.7%) were the most common virulence characteristics of UPEC isolates. Co-expression of virulence characteristics was common (69.8%) in UPEC strains. Conclusion: UPEC strains with very high antimicrobial-resistance are in circulation in India, and have diverse serotypes and virulence characteristics.

Abstract The cloning and characterization of the complete coding sequence of the Clarias magur SRD5A1 (CmSRD5A1) gene, which encodes an enzyme responsible for regulating steroid levels by converting testosterone into 5α-dihydrotestosterone (DHT), have been successfully achieved. DHT plays a vital role in enabling the complete expression of testosterone's actions in neuroendocrine tissues. The ORF of the full-length cDNA sequence of SRD5A1 was 795 bp, translating into 265 amino acids, with a total length of 836 bp including UTRs. Like other vertebrates, the signal peptide analysis revealed that SRD5A1 is a non-secretory protein, and hydropathy profiles indicated that it is hydrophobic in nature. The 3D structure of CmSRD5A1 sequence generated above was predicted using highly accurate AlphaFold 2 in Google Colab online platform. CmSRD5A1 contains seven transmembrane helices connected by six loops, with the N-termini located on the periplasmic side and C-termini on the cytosolic side. Structural superimposition with known bacterial and human SRD5As showed very high structural similarity. The electrostatic potential calculation and surface analysis of CmSRD5A1 revealed the presence of a large cavity with two openings one highly electropositive towards the cytosolic side and another relatively neutral towards the transmembrane region. The structural comparison revealed that the electropositive side of the cavity should bind to NADPH and the steroid hormone in the hydrophobic environment. Polar residues binding to NADPH are highly conserved and the same as known strictures. The conserved residues involved in hydrogen bonding with the ketone group at C-3 in the steroids hence fevering Δ4 double-bond reduction are identified as E66 and Y101. Our findings showed that SRD5A1 expression was lower during the spawning phase than the preparatory phase in female fish, while the administration of Ovatide (a GnRH analogue) resulted in up-regulation of expression after 6 h of injection in the ovary. In males, the lowest expression was observed during the preparatory phase and peaked at 16 h post- Ovatide injection in the testis. The expression of SRD5A1 in the brain of female fish was slightly higher during the Ovatide stimulation phase than the spawning phase. This study represents the first report on the cloning and characterization of the full-length cDNA of SRD5A1 in Indian catfish.

Introduction: The frequency of lymphoma is progressively rising. A key clinical feature of lymphoid malignancies is anaemia. The impact of anaemia goes beyond physical symptoms and can negatively affect functional capacity and Quality of Life (QoL). The presence of anaemia has been identified as a predictive factor for event-free and disease-free survival in patients diagnosed with lymphoma and is regarded as a significant unfavourable predictor for treatment results. Aim: To investigate the prevalence and impact of anaemia in naive lymphoma patients. Materials and Methods: This hospital-based, cross-sectional study was conducted in the Department of Pathology at Geetanjali Medical College and Hospital, Udaipur, Rajasthan, India, from January 2019 to December 2022. A total of 66 patients diagnosed with lymphoid malignancies were included in the study. Various parameters of lymphoma cases were assessed to determine the presence of anaemia and its association with demographic features, disease stage, and haematological indices. Statistical analysis was carried out using Statistical Package for Social Sciences (SPSS) version 20.0 The Pearson's Chi-square test was used to analyse the difference in the prevalence of anaemia in different groups. Results: The mean age of the study patients was 47.35±20.60 years .The present study included 66 patients with lymphoid malignancies and revealed a high incidence of anaemia among them, with 38 (57.58%) cases presenting with anaemia. There was a male predominance, with 52 (78.79%) out of 66 patients male. Out of the total number of patients, 36 (54.55%) were classified as having stage I and stage II disease, while 30 (45.45%) had stage III and stage IV based on age, Ann Arbor staging, extranodal involvement, Lactate Dehydrogenase (LDH) level, and lymphoma prognostic score. Differentiation between anaemic and non anaemic patients was made by statistical analysis. Based on the findings from the complete blood count, the patients were categorised according to the severity and type of anaemia. It was determined that 38 out of 66 patients, accounting for 57.58%, had anaemia. Conclusion: Anaemia was more prevalent in younger patients and females. Microcytic hypochromic anaemia and Anaemia of Chronic Disease (ACD) were the most common types observed. Anaemia was associated with bone marrow infiltration and advanced disease stages. The present study emphasised the importance of early diagnosis and appropriate management of anaemia in lymphoma patients, as it can negatively impact treatment outcomes and reduce QoL.

Malabar spinach (Basella alba) is an underexploited tropical leafy vegetable with high nutritional value and therapeutic properties. The leaves are rich in polyphenols, flavonoids, and antioxidants. Identifying appropriate drying methods and conditions for B. alba leaf production and storage can stimulate large-scale manufacture while preserving its intrinsic bioactive components. In this study, an investigation has been carried out to study the impact of thin-layer drying conditions on the retention of bioactive components in B. alba leaves. Drying tests were performed in a hot air oven (50, 60, 70 °C), microwave (600, 650, 700, 750,800 W), and freeze dryer (freezing temperature: -35 °C and vacuum pressure:150 mbar). The drying characteristics of the leaves were investigated. Semi-empirical thin-layer drying models were fitted to the obtained data with the intent to predict the drying behaviour of leaves. Amongst the fitted models, Page and Aghbashlo models showed the best performance with a high R2 value (0.98 – 0.99). The total drying time taken for microwave drying was 98.25% less than the hot air oven drying and 99.19% less than freeze drying. Maximum retention of total phenolic (4.80 ± 0.12 mg GAE g−1) and total flavonoid (5.95 ± 0.02 mg GAE g−1) compounds was observed in freeze-dried samples. Microwave dried samples showed high antioxidant activity than other samples due to less processing time. Results also revealed a less activation energy of 2.22 kJ mol−1 for microwave drying with high moisture diffusivity (1.54 × 10–9 to 4.09 × 10–9 m2s−1).

Objective: Non-typhoidal Salmonellae (NTS) are a neglected group of enteric pathogens whose prevalence is increasing at alarming rates across India. The disease burden is being underestimated because of a lack of effective surveillance of NTS infections in the Indian population. This study depicts the acquisition of NTS infection, and its persistence and spread through a diverse range of hosts, including humans and animals, and food and environmental sources. Methods: During the study period from 2016 to 2018, a total of 999 suspected NTS isolates were received from across India and were phenotypically and serologically characterized for the presence of NTS. Results: Of the 999 isolates, 539 (53.95%) were confirmed as NTS, consisting of 17 different NTS serovars. The majority were isolated from human samples (n = 319, 59.18%), followed by food products (n = 99, 18.37%), animals (n = 83, 15.4%) and the environment (n = 38, 7.05%). Some predominant serovars obtained included S. Typhimurium (n = 167, 30.98%), S. Lindenberg (n = 135, 25.05%), S. Enteritidis (n = 56, 10.39%), S. Weltevreden (n = 44, 8.16%), S. Choleraesuis (n = 41, 7.61%) and S. Mathura (n = 33, 6.12%). Conclusion: This study depicts the NTS disease burden across India, on the basis of the isolation of NTS serovars across diverse geographic locations. The emergence of newer or less common NTS serovars implicated in human infection poses a potential challenge to the healthcare system in India. Therefore, national and regional level surveillance is needed to implement effective control strategies and safeguard community health in India.

The semiconductor industry is actively looking for an all-encompassing memory solution that incorporates the advantageous aspects of current technology. This features non-volatility, like that of Flash memory, high scalability, like that of both Dynamic Random Access Memory (DRAM) and Flash, quick operation, like that of Static RAM (SRAM), and durability, like that of both DRAM and SRAM. Ferroelectric thin films, which have electrically switchable bi-stable polarization, are one prospective technology that has the potential to revolutionize memory storage. However, due to difficulties with scalability and dependable industrial manufacturing, Ferro-Electric (FE) memory technology has not been able to effectively compete with DRAM and Flash. Research in this area has accelerated after the recent discovery of resistive switching in ferroelectric tunnel junctions (FTJs). For FTJs to be successful, it is important to overcome some obstacles, such as preserving bi-stability in ferroelectric thin films over the critical thickness. Additionally, the existence of interfacial layers, sometimes known as a “dead layer”, between the electrode and the film can affect its characteristics. The article gives an overview of semiconductor memories with an emphasis on emerging technologies having the potential for future applications. It then goes into detail on the benefits of FTJ and its non-destructive reading capacity. The article also discusses the potential uses for FTJs in resistive switching while acknowledging their drawbacks and constraints.

The development of sequencing methods has resulted in the investigation of many unexplored research areas. Among the different sequencing methods, single-cell transcriptomics is versatile and has completely changed the researchers' perception of biological processes from tissue to single-cell. Single-cell transcriptomic is applied in various fields to reveal cell-cell interaction, phytopathogenic interactions, cell-specific genetic expression, regulatory pathways, and the effects of drugs on cells. Single-cell transcriptomics was initially applied to the model organisms, such as mice and Arabidopsis thaliana, and then later expanded to other non-model species. Recently, single-cell transcriptomics is revolutionizing plant and animal research. The direct application of single-cell transcriptomics has become simple with advanced sequencing methods and data analysis tools available. This review summarizes the latest knowledge on single-cell transcriptomics in plant and animal research. We emphasize various sequencing methods, bioinformatics software development, comparison between plant and animal single-cell transcriptomics studies, and the limitations and future prospectus.

Abstract Aim This study was designed to evaluate the frequency of developing second and subsequent primary cancers among cancer survivors. Methods We have retrospectively analyzed 121 multiple primary cancer patients treated at Bhagwan Mahavir Cancer Hospital and Research Centre, Jaipur, Rajasthan, India from the last 20 years. The survival analysis was performed by Kaplan-Meier methodology. Results The prevalence of multiple primary malignant tumors (MPMTs) was 1.51% (121/8000), with a male to female ratio of 1:1.42. In males most of the reported MPMTs were synchronous and most common first primary cancer cases were head & neck and lung whereas, in females most of the reported MPMTs were metachronous and most common first primary cancer cases were breast and gynaecological malignancies. Family history was reported in 15 cases. Maximum 33.05% patients received combined treatment of chemotherapy, radiotherapy and 91.73% (111/121) of patients with MPMTs were effectively followed up, 35 (28.92%) patients died and 5-year survival rate of the remaining 86 patients was 68.46%. Conclusions In the present observational study the most frequent sites of MPMTs in men were head & neck and lung whereas, in women breast and gynaecological sites were common. Therefore, careful monitoring and follow up are required for these patients.

IntroductionMango (Mangifera indica L.), acclaimed as the ‘king of fruits’ in the tropical world, has historical, religious, and economic values. It is grown commercially in more than 100 countries, and fresh mango world trade accounts for ~3,200 million US dollars for the year 2020. Mango is widely cultivated in sub-tropical and tropical regions of the world, with India, China, and Thailand being the top three producers. Mango fruit is adored for its taste, color, flavor, and aroma. Fruit color and firmness are important fruit quality traits for consumer acceptance, but their genetics is poorly understood.MethodsFor mapping of fruit color and firmness, mango varieties Amrapali and Sensation, having contrasting fruit quality traits, were crossed for the development of a mapping population. Ninety-two bi-parental progenies obtained from this cross were used for the construction of a high-density linkage map and identification of QTLs. Genotyping was carried out using an 80K SNP chip array.Results and discussionInitially, we constructed two high-density linkage maps based on the segregation of female and male parents. A female map with 3,213 SNPs and male map with 1,781 SNPs were distributed on 20 linkages groups covering map lengths of 2,844.39 and 2,684.22cM, respectively. Finally, the integrated map was constructed comprised of 4,361 SNP markers distributed on 20 linkage groups, which consisted of the chromosome haploid number in Mangifera indica (n =20). The integrated genetic map covered the entire genome of Mangifera indica cv. Dashehari, with a total genetic distance of 2,982.75 cM and an average distance between markers of 0.68 cM. The length of LGs varied from 85.78 to 218.28 cM, with a mean size of 149.14 cM. Phenotyping for fruit color and firmness traits was done for two consecutive seasons. We identified important consistent QTLs for 12 out of 20 traits, with integrated genetic linkages having significant LOD scores in at least one season. Important consistent QTLs for fruit peel color are located at Chr 3 and 18, and firmness on Chr 11 and 20. The QTLs mapped in this study would be useful in the marker-assisted breeding of mango for improved efficiency.

The increasing number of connected devices in the era of Internet of Thing (IoT) has also increased the number intrusions. Intrusion Detection System (IDS) is a secondary intelligent system to monitor, detect, and alert about malicious activities; an Intrusion Prevention System (IPS) is an extension of a detection system that triggers relevant action when an attack is suspected in a futuristic aspect. Both IDS and IPS systems are significant and useful for developing a security model. Several studies exist to review the detection and prevention models; however, the coherence in the opportunistic or advancements in the models is missing. Besides, the existing models also have some limitations, which need to be surveyed to develop new security models. Our survey is the first one to present a study of risk factor analysis using mapping technique, and provide a proposal for hybrid framework for an efficient security model for intrusion detection and/or prevention. We explore the importance of various Artificial Intelligence (AI)-based techniques, tools, and methods used for the detection and/or prevention systems in IoTs. More specifically, we emphasize on Machine Learning (ML) and Deep Learning (DL) techniques for intrusion detection-prevention systems and provide a comparative analysis focusing on the feasibility, compatibility, challenges, and real-time issues. This present survey is beneficial for industry and academia to categorize the challenges and issues in the current security models and generate the new dimensions of developments of security frameworks with efficient ML or DL methods.

Some prognostic markers have been shown to determine the course and survival of Urothelial Cancer. A cross-sectional retrospective study, specifically looking at the role that various indices related to platelets—namely Mean Platelet Volume (MPV), platelet count and MPV/Platelet ratio—play in the diagnosis and prognosis of urinary bladder cancer, was conducted at the Department of Pathology, Geetanjali Medical College and Hospital, Udaipur, Rajasthan (India) between January 2016 and August 2021 and included 76 patients who underwent multicore TURBT biopsy. Complete Blood Count (CBC) was used to determine platelet count, MPV and MPV/Platelet ratio. Platelet count was found to be more elevated in patients with high grade urothelial carcinoma and muscle invasive urothelial carcinoma as compared to patients with low grade urothelial carcinoma and non-muscle invasive urothelial carcinoma (p < 0.05). The median MPV and MPV/PLT ratio was found to be significantly lower in patients with high grade urothelial carcinoma and muscle invasive urothelial carcinoma as compared to patients with low grade urothelial carcinoma and non-muscle invasive urothelial carcinoma (p < 0.05). Thus, platelet indices can be useful supportive prognostic and diagnostic indicators in the determination of the clinical outcome of urothelial carcinoma.

Soil Organic Carbon (SOC) is a crucial indicator of ecosystem health and soil quality. Machine learning (ML) models that predict soil quality based on environmental parameters are becoming more prevalent. However, studies have yet to examine how well each ML technique performs when predicting and mapping SOC, particularly at high spatial resolutions. Model predictors include topographic variables generated from SRTM DEM; vegetation and soil indices derived from Landsat satellite images predict SOC for the Lakhimpur district of the upper Brahmaputra Valley of Assam, India. Four ML models, Random Forest (RF), Cubist, Extreme Gradient Boosting (XGBoost), and Support Vector Machine (SVM), were utilized to predict SOC for the top layer of soil (0–15 cm) at a 30 m resolution. The results showed that the descriptive statistics of the calibration and validation sets were close enough to the total set data and calibration dataset, representing the complete samples. The measured SOC content varied from 0.10 to 1.85%. The RF model’s performance was optimal in the calibration and validation sets (R2c = 0.966, RMSEc = 0.159%, R2v = 0.418, RMSEv = 0.377%). The SVM model, on the other hand, had the next-lowest accuracy, explaining 47% of the variation (R2c = 0.471, RMSEc = 0.293, R2v = 0.081, RMSEv = 0.452), while the Cubist model fared the poorest in both the calibration and validation sets. The most-critical variable in the RF model for predicting SOC was elevation, followed by MAT and MRVBF. The essential variables for the Cubist model were slope, TRI, MAT, and Band4. AP and LS were the most-essential factors in the XGBoost and SVM models. The predicted OC ranged from 0.44 to 1.35%, 0.031 to 1.61%, 0.035 to 1.71%, and 0.47 to 1.36% in the RF, Cubist, XGBoost, and SVM models, respectively. Compared with different ML models, RF was optimal (high accuracy and low uncertainty) for predicting SOC in the investigated region. According to the present modeling results, SOC may be determined simply and accurately. In general, the high-resolution maps might be helpful for decision-makers, stakeholders, and applicants in sericultural management practices towards precision sericulture.

Composites of banana fiber were prepared using polyester resin/natural latex (Euphorbia coagulum) blend as matrix and evaluated for various physicomechanical properties. The best physicomechanical properties have been obtained by replacing 40% of polyester resin with coagulum. The morphology and biodegradability of the controlled and optimum composition of the composite, i.e., composite containing banana fiber, Euphorbia coagulum, and polyester resin in the ratio 40: 24: 36, were carried out. Morphology study shows that incorporation of Euphorbia coagulum in polyester–banana fiber composites improves the compatibility between the fiber and matrix. Biodegradability study shows that the composite containing polyester resin/Euphorbia coagulum blend as matrix exhibited a high degree of biodegradation compared to the composite containing polyester resin as the matrix. The use of developed green composites may help in reducing the generation of nonbiodegradable polymeric wastes.

Numerous applications in agriculture, climate, ecology, hydrology, and the environment are severely constrained by the lack of detailed information on soil texture. The purpose of this study was to predict soil particle-size fractions (PSF) in the Ri-Bhoi district of Meghalaya state, India, using a random forest model (RF). For the modeling of soil particle-size fractions, we employed 95 soil profiles (456 depth-wise layers) gathered from a recent national land resource inventory as well as currently accessible environmental variables. Sand, silt, and clay content were predicted using the Random Forest model at varied depths of 0–5, 5–15, 30–60, 60–100, and 100–200 cm. Our results showed the R2 for sand was found to be 0.30 (0–5 cm), 0.28 (5–15 cm), and 0.21 (15–30 cm). For the sand, silt, and clay fractions, respectively, the concordance correlation coefficient (CCC) was found to be greater in the 0–30 cm, 0–60 cm, and 0–15 cm depths. When there is a reasonably close monitoring of the coverage probability with a confidence level along the 1:1 line, prediction interval coverage probability (PICP) gives a decent indicator of what to anticipate. The most crucial variables for the prediction of sand and silt were channel network base level (CNBL) and LS-Factor, whereas Min Temperature of Coldest Month (°C) (BIO6) was discovered for clay prediction. For all three soil texture fractions, the range between the 5% lower and 95% higher prediction bounds was large, indicating that the existing spatial predictions may be improved. The maps of soil texture were significantly more precise, and they accurately depicted the spatial variations of particle-size fractions. Additionally, there is still a need to investigate novel methodologies for extensive digital soil mapping, which will be very advantageous for many international initiatives.

Background: Primary cardiac sarcomas (PCS) are extremely rare malignant tumors involving the heart. Only isolated case reports have been described in the literature over different periods of time. This pathology has been associated with a dismal prognosis and given its rarity; treatment options are very limited. Furthermore, there are contrasting data about the effectiveness of current treatment modalities in improving the survival of patients with PCS, including surgical resection which is the mainstay of therapy. There is a paucity of data on the epidemiological characteristics of PCS. This study has the objective of investigating the epidemiologic characteristics, survival outcomes, and independent prognostic factors of PCS. Methods: A total of 362 patients were ultimately registered in our study from the Surveillance, Epidemiology, and End Results (SEER) database. The study period was from 2000 to 2017. Demographics such as clinical characteristics, overall mortality (OM), and PCS-specific mortality (CSM) were taken into account. A p value of p < 0.001), followed by age 60–79 (HR = 1.429, 95% CI 1.028–1.986, p = 0.033); and PCS with distant metastases (HR = 1.888, 95% CI 1.389–2.566, p < 0.001). Patients that underwent surgical resection of the primary tumor and patients with malignant fibrous histiocytomas (HR = 0.657, 95% CI 0.455–0.95, p = 0.025) had a better OM (HR = 0.606, 95% CI 0.465–0.791, p < 0.001). The highest cancer-specific mortality was observed in age 80+ (HR = 5.037, 95% CI 2.606–9.736, p < 0.001) and patients with distant metastases (HR = 1.953, 95% CI 1.396–2.733, p < 0.001). Patients with malignant fibrous histiocytomas (HR = 0.572, 95% CI 0.378–0.865, p = 0.008) and those who underwent surgery (HR = 0.581, 95% CI 0.436–0.774, p < 0.001) had a lower CSM. Patients in the age range 80+ (HR = 13.261, 95% CI 5.839–30.119, p < 0.001) and advanced disease with distant metastases (HR = 2.013, 95% CI 1.355–2.99, p = 0.001) were found to have a higher OM in the multivariate analyses adjusting for covariates). Lower OM was found in patients with rhabdomyosarcoma (HR = 0.364, 95% CI 0.154–0.86, p = 0.021) and widowed patients (HR = 0.506, 95% CI 0.263–0.977, p = 0.042). Multivariate cox proportional hazard regression analyses of CSM also revealed higher mortality of the same groups, and lower mortality in patients with Rhabdomyosarcoma. Conclusion: In this United States population-based retrospective cohort study using the SEER database, we found that cardiac rhabdomyosarcoma was associated with the lowest CSM and OM. Furthermore, as expected, age and advanced disease at diagnosis were independent factors predicting poor prognosis. Surgical resection of the primary tumor showed lower CSM and OM in the crude analysis but when adjusted for covariates in the multivariate analysis, it did not significantly impact the overall mortality or the cancer-specific mortality. These findings allow for treating clinicians to recognize patients that should be referred to palliative/hospice care at the time of diagnosis and avoid any surgical interventions as they did not show any differences in mortality. Surgical resection, adjuvant chemotherapy, and/or radiation in patients with poor prognoses should be reserved as palliative measures rather than an attempt to cure the disease.

Dimapur (Nagaland, India) is dominated by undifferentiated hillside slopes and alluvial plains. The Muga and Eri silk industries are important cultural and economic activities for the inhabitants of Dimapur. Profitable silk production requires adequate quality and quantity of healthy leaves and is highly dependent on the soil fertility of the region. Keeping this in view, the present study was carried out as a first attempt to prepare a geographic information system (GIS) map for Muga and Eri soils in Dimapur, Nagaland. A total 65 surface (0–15 cm) soil samples from Muga farms and 79 surface soil samples from Eri farms were collected and analysed for soil pH, organic carbon content and availability of macro- and micronutrients. Soils of both Muga and Eri farms were found to be extremely (−1) and medium available phosphorus content (2.68–154.6 kg ha−1). The sulphur availability index was 0.26 and 11.81 for Muga and Eri host plant farms, respectively. The multi-macronutrient map revealed that 46.95% of the district’s total geographical area (TGA) showed deficiencies in one or more macronutrients (high priority zone). Thus, these regions need urgent attention in terms of nutrient management decisions in order to reduce the declining trend of soil fertility and achieve sustainable sericulture production.

Industrial Internet of Things (IIoTs) are the extensions of the Internet of Things (IoTs) and have paved the way towards the industry revolution 4.0. IIoT accelerates the industry automation of internal and external working process including transport, manufacturing, and marketing units with a number of connected devices. Being the extension of IoT, it inherits the insecurities of the technology; however, this sensor-configured infrastructure of IIoT needs some extra effort to customize the existing security solutions. In spite of the reconstructions of security models, the scope of improved developments is open to detect unknown attacks. The present study helps the researchers to understand the cause for intrusion by classifying and comparing various attacks of each IIoT layers. The main focus of this survey is to analyze various security issues faced by IIoT and provide a comparative analysis on the available solutions to enhance the industrial IoTs' protection systems. This study also notifies some open research problems for academia, technologists, and researchers to flourish the IIoT domain and its security aspects.

There is an increasing drive to provide improved levels of trust within an Internet-of-Things (IoTs) environments, but the devices and sensors used tend to be limited in their capabilities for dealing with traditional cryptography methods. Resource constraints and security are often the two major concerns of IIoT (Industrial IoT applications and big data generation at the present time. The strict security measures are often not significantly resource-managed and therefore, negotiation normally takes place between these. Following this, various light-weight versions of generic security primitives have been developed for IIoT and other resource-constrained sustainability. In this paper, we address the authentication concerns for resource-constrained environments by designing an efficient authentication protocol. Our authentication scheme is based on LiSP (light-weight Signcryption Protocol); however, some further customization has been performed on it to make it more suitable for IIoT-like resource-constrained environments. We use Keccack as the hash function in the process and Elli for light-weight public-key cryptography. We name our authentication scheme: Extended light-weight Signcryption Protocol with Keccack (LiSP-XK). The paper outlines a comparative analysis on our new design of authentication against a range of state-of-the-art schemes. We find the suitability of LiSP-XK for IIoT like environments due to its lesser complexity and less energy consumption. Moreover, the signcryption process is also beneficial in enhancing security. Overall the paper shows that LiSP-XK is overall 35% better in efficiency as compared to the other signcryption approaches.

Objective: This study aims to address the spatial variation in the availability of public health facilities and utilization of Maternal and Child Health (MCH) services at district level in India. Methods: Two nationally representative secondary data sources such as the National Family Health Survey 2015-16 and Census of India, 2011 were used to identify districts, which are lagging behind in terms of the availability and utilization of MCH services. Mapping and spatial clustering analyses was performed to identify underperforming districts in India. Further, Ordinary least square and spatial autoregressive models were used to determine the predictor for utilization of MCH services at the district level. Results: Significantly, less availability of public health facilities and utilization of MCH services were observed in districts of Jharkhand, Bihar, Uttar Pradesh, Madhya Pradesh, Chhattisgarh, and North-Eastern states as compared to the national average. A shortage of 72,198 (21.9%) doctors and 165,791 (17.5%) paramedical staff found at the country level. After controlling for socio-economic factors, we observed that availability of sub-centre, dispensary, and population hospital bed ratio were significant positive predictors for Antenatal Care (ANC) service utilization whereas, shortage of paramedical staff was a negative predictor for full immunization at district level in India. Conclusions: Adequate availability of health facilities, and human resources are needed in districts, which are underperforming in terms of availability and utilization of MCH services to improve utilization of MCH services.

Objective: The objective of this study is to observe the differences in craniofacial parameters in subjects with cleft lip and palate and compare with normal subjects and also evaluate the association between chin deviation and asymmetry of face. Materials and Methods: Fifty cone-beam computed tomography (CBCT) scans (25 each) of the control group (Group I: normal) and study group (Group II: cleft lip and palate) subjects residing in Uttar Pradesh were obtained using care-stream CS 9300 3D system (care-stream Health, Inc. 2004). The digitizations and measurements were carried out in Dolphin Imaging software (Dolphin imaging version 11.9.07.24 premium). All subjects were within the age group of 15.1–18.9 years. Asymmetry indices (AI%) of the parameters were calculated as proposed by Habets et al. Results: Mean ± standard deviation of the differences in the variables between noncleft side (right side) and the cleft side (left) among the study group showed significant differences for Nasal width (P < 0.001), Ramus length (P < 0.004); mandibular body length (P < 0.021), total mandibular body length (P < 0.023), gonial angle (P < 0.034), nasal height (P < 0.043), maxillary dental width (P < 0.039), and mandibular dental width (P < 0.01). The asymmetric index value was >3% threshold value for nasal width (5.08% ± 5.72%) and for nasal height (−4.80 ± 10.81%) in the study group. Conclusion: From the study, it was observed that asymmetry exists in the region of the defect that lies in the area of the contracture. Mandibular asymmetry has also been expressed with deviation of chin to the cleft side. The asymmetry index (AI%) values were >3% threshold value only in the region of the defect.

Abstract Background As India already missed maternal and child health related millennium development goals, the maternal and child health outcomes are a matter of concern to achieve sustainable development goals (SDGs). This study is focused to assess the gap in coverage and inequality of various reproductive, maternal, neonatal and child health (RMNCH) indicators in 640 districts of India, using data from most recent round of National Family Health Survey. Methods A composite index named Coverage Gap Index (CGI) was calculated, as the weighted average of eight preventive maternal and child care interventions at different administrative levels. Bivariate and spatial analysis were used to understand the geographical diversity and spatial clustering in districts of India. A socio-economic development index (SDI) was also derived and used to assess the interlinkages between CGI and development. The ratio method was used to assess the socio-economic inequality in CGI and its component at the national level. Results The average national CGI was 26.23% with the lowest in Kerala (10.48%) and highest in Nagaland (55.07%). Almost half of the Indian districts had CGI above the national average and mainly concentrated in high focus states and north-eastern part. From the geospatial analysis of CGI, 122 districts formed hotspots and 164 districts were in cold spot. The poorest households had 2.5 times higher CGI in comparison to the richest households and rural households have 1.5 times higher CGI as compared to urban households. Conclusion Evidence from the study suggests that many districts in India are lagging in terms of CGI and prioritize to achieve the desired level of maternal and child health outcomes. Efforts are needed to reduce the CGI among the poorest and rural resident which may curtail the inequality.

In the smart environments several smart devices are continuously working together to make individuals' lives more comfortable. Few of the examples are smart homes, smart buildings, smart airports, etc. These environments consist of many resource constrained heterogeneous entities which are interconnected, controlled, monitored and analyzed through the Internet. One of the most challenging tasks in a distributed smart environment is how to provide robust security to the resource constraint Internet-enabled devices. However, an authentication can play a major role ensuring that only authorized devices are being connected to the distributed smart environment applications. In this paper, we present a robust and lightweight mutual-authentication scheme (RLMA) for protecting distributed smart environments from unauthorized abuses. The proposed scheme uses implicit certificates and enables mutual authentication and key agreement between the smart devices in a smart environment. The RLMA not only resists to various attacks but it also achieves efficiency by reducing the computation and communication complexities. Moreover, both security analysis and performance evaluation prove the effectiveness of RLMA as compared to the state of the art schemes.

Blockchain is a technology used with the series of users in peer-to-peer transactions to utilize the usability properties of the immutable data records. The distributed nature of this technology has given the wide acceptance to its range of applications in various sectors. Seeing the prospect of this new technology, we have chosen the field of human resource management as these data needs to be privacy preserving and confidential along with significant research value. Distributed ledger approach is a novel idea in this field of work specifically for the application of human resource records management. We have used a privacy preserving framework that provides a transparent system for human resource record management. Wallets are generated with organization id and outputting with public-private key pair along with privacy parameter mapping with hash. Keys are used to provide confidentiality, integrity and authentication. Smart contract uses distributed but converged decision with privacy level classification. Performance of the proposed work has been measured based on time, memory consumptions, failure point identification and read-write latencies. The analysis of the results confirms the efficiency of the system.

The increasing number of devices in the age of Internet-of-Thing (IoT) has arisen a number of problems related to security. Cryptographic processes, more precisely the signatures and the keys, increase and generate an overhead on the network resources with these huge connections. Therefore, in this paper we present a signcryption framework to address the above problems. The solution highlights the use of aggregate signcryption and certificaless approach based on bilinear pairings. The use of signcryption with aggregation and certificateless authentication reduces the time consumption, overhead and complexity. The solution is also able to solve the key staling problems. Experimental results and comparative analysis based on key parameters, memory utilization and bandwidth utilization have been measured. It confirms that the presented work is efficient for IoT infrastructure.

Industry 4.0 has brought solutions for faster data accessibility, fault identification, performance analysis, and control of machines remotely by managers. Though beneficial but dangerous as the IoT (Internet of Things) nodes communicate over the unsecured wireless medium. The communication over unsecured wireless channel opened enormous ways for the illegitimate nodes to access the information and take control over the industrial machines despite being physically away. These threats can be overpowered with secure sessions; however, the exchange of keys to establish a secure session over a vulnerable channel becomes a challenge. Our approach (LKE) intend to solve this problem. LKE provides a lightweight key exchange platform to the legitimate IoT nodes and prohibit the unauthorized abuses. LKE uses lightweight Elliptic Curve Qu-Vanstone (ECQV) based implicit certificates for trust-building and generating keys among entities. All the messages exchanged are secured to prevent unauthorized access to information and preventing against forgery, replay, modification, impersonation and man-in-the-middle attacks, etc. The proposed scheme is tested on the AVISPA tool and results indicate its trustworthiness and strong resistivity against potential attacks. LKE has less computation and communication complexities due to the utilization of limited cryptographic operations which make it superior in comparison to other state-of-the-work.

Ravine and gully formations are both spectacular and also the worst forms of water-induced soil erosion and have in situ and ex situ impact on geomorphology, hydrology, productivity and environmental security, and they are the root causes of degradation of marginal and adjacent land along with reduced production potential. A long-term (2011–2019) study was conducted on marginal land of the Chambal ravine to assess the impact of six land uses, i.e., Agriculture (T1—Rainfed Soybean), Agri-horticulture (T2—Soybean + Manilkara achras), Horti-Pastoral (T3—Emblica officinalis + Cenchurus ciliaris), Pasture (T4—C. ciliaris), Silviculture (T5—Acacia nilotica) and Silvi-pasture (T6—A. nilotica + C. Ciliaris) on soil properties, runoff interception, sediment trapping and soil loss reduction. The lowest average annual soil loss (4.83 ton ha−1 year−1) and runoff (109.52 mm) were recorded under T4, while the highest sediment loss (8.09 ton ha−1 year−1) and runoff (136.07 mm), respectively, were under T5. The runoff coefficient of land uses was in the order of T3 (20.30%) < T4 (20.56%) < T1 (21.95%) < T2 (22.26%) < T6 (22.83%) < T5 (25.54%). The C. ciliaris improved bulk density and recorded lowest in horti-pasture (1.63 ± 0.04 g cm−3) followed by pasture (1.66 ± 0.03 g cm−3) land use system. The active SOC content in pasture, horti-pasture and silvi-pasture was 0.95, 0.87 and 0.64 times higher, respectively, than agriculture land use. Under pure C. ciliaris cover, resistance to penetration varied from 0.68 to 1.97 MPa, while in silviculture land use, it ranges from 1.19 to 2.90 Mpa. Grass cover had substantial impact on soil loss and runoff reduction, SOC content, soil aggregation and resistance to penetration. In degraded ecosystems, Cenchrus ciliaris can be used alone and in combination with plants for protection of natural resources from water-induced soil erosion, runoff conservation, soil quality improvement and maximization of precipitation water use.

Abstract Plants produce diverse secondary metabolites in response to different environmental cues including pathogens. The modification of secondary metabolites, including acylation, modulates their biological activity, stability, transport, and localization. A plant‐specific BAHD‐acyltransferase (BAHD‐AT) gene family members catalyze the acylation of secondary metabolites. Here we characterized the rice (Oryza sativa L.) BAHD‐ATs at the genome‐wide level and endeavor to define their plausible role in the tolerance against Rhizoctonia solani AG1‐IA. We identified a total of 85 rice OsBAHD‐AT genes and classified them into five canonical clades based on their phylogenetic relationship with characterized BAHD‐ATs from other plant species. The time‐course RNA sequencing (RNA‐seq) analysis of OsBAHD‐AT genes and qualitative real‐time polymerase chain reaction (qRT‐PCR) validation showed higher expression in sheath blight susceptible rice genotype. Furthermore, the DNA methylation analysis revealed higher hypomethylation of OsBAHD‐AT genes that corresponds to their higher expression in susceptible rice genotype, indicating epigenetic regulation of OsBAHD‐AT genes in response to R. solani AG1‐IA inoculation. The results shown here indicate that BAHD‐ATs may have a negative role in rice tolerance against R. solani AG1‐IA possibly mediated through the brassinosteroid (BR) signaling pathway. Altogether, the present analysis suggests the putative functions of several OsBAHD‐AT genes, which will provide a blueprint for their functional characterization and to understand the rice–R. solani AG1‐IA interaction.

The present study highlights the significant impact of trace level doping of boron in titanium dioxide (TiO2) nanotubes by investigating the structural, optical and electronic properties of samples, TNT and B-TNT. TEM analysis of boron-doped sample confirms the formation of crystalline nanotube structures and the trace level quantification of boron was confirmed by XPS analysis, where B shows feature of Ti–O–B bonding. Raman analysis revealed that the rutile phase becomes prominent after boron doping and Raman bands shift towards higher wavenumber was observed with increase in the tube diameter. The boron incorporation in TiO2 nanotubes reduces the band gaps from 3.3 eV to 3.1 eV and the mid-gap states were created within the band gap of the B-TNT sample. The change in valance band position from 2.5 eV to 2.9 eV after boron doping significantly changed the Fermi level position in TiO2 nanotubes. The work function of pristine and boron doped TiO2 samples are observed as 4.23 eV and 4.27 eV, respectively, as measured by Kelvin probe force microscopy. Here, we have investigated the band alignment of TNT and B-TNT by using state-of-the-art material characterization surface sensitive techniques. It can also be concluded that the electron affinity of the B-TNT sample is enhanced ∼4.07 eV than that of TNT ∼ 3.43 eV. The type –II band alignment is observed to be in between TNT and B-TNT with a valence band offset (VBO) ∼ 0.4 eV and conduction band offset (CBO) ∼ 0.6 eV. Keywords: Nanotubes, Boron-doping, Surface potential, Fermi level position, Band alignment, Electron affinity

The progress in network technology and hardware in conjunction with the Internet-of-Things (IoTs) has provided the comfortability for an easier human life at present. Apart from the so-called “smart” environments, including smart homes, smart city, smart agriculture, IoTs have been included recently in e-healthcare systems as well for real-time diagnosis and medical consultancy. To enhance the capabilities of IoT-based healthcare systems, fog layers have been employed and that have shown its worth by providing fast response time and low latency. However, such development is posing a severe challenge in preserving the privacy of the users which further addresses the security/privacy issues to some extent. Being in an infant stage, such technology has invariably run into fewer privacy controls. Therefore, our present work is about an e-healthcare framework dealing with electronic medical records (EMRs) which preserves the privacy issues. Moreover, we have experimented the proposed work with respect to response time and delay and have compared with recent works. The results show that the proposed work is efficient in providing privacy along with standard network parameters.

In this research paper, blockchain-based trust management model is proposed to enhance trust relationship among beacon nodes and to eradicate malicious nodes in Wireless Sensor Networks (WSNs). This composite trust evaluation involves behavioral-based trust as well as data-based trust. Various metrics such as closeness, honesty, intimacy and frequency of interaction are taken into account to compute behavioral-based trust of beacon nodes. Further, the composite (behavior and data) trust value of each beacon nodes is broadcast to Base Stations (BS) to generate a blockchain of trust values. Subsequently, the management model discards the beacon node with least trust value and that ensures reliability and consistency of localization in WSNs. The simulated results of the proposed algorithm are compared with the existing ones in terms of detection accuracy, False Positive Rate (FPR) and False Negative Rate (FNR) and Average Energy Consumption (AEC).

The Rivest Cipher 4 (RC4) has been one of the most popular stream ciphers for providing symmetric key encryption, and is now proposed as an efficient cipher within light-weight cryptography. As an algorithm it has been considered to be one of the fastest stream ciphers and one of the easiest to implement. Unfortunately, despite its simplicity of usage, a number of attacks on it have been found. Therefore, various improvements of this algorithm exist in cryptography, but none of them use proper randomness. This paper outlines modified version of RC4 and which has the desirable features of an efficient stream cipher algorithm, and which integrates the Symmetric Random Function Generator (SRFG) method. Though RC4 uses pseudorandom features with an initialisation vector and a seed value, the use of true randomness in RC4 is novel in this domain. Therefore, this paper proposes a modified RC4 as MRC4, and which then evaluates the statistical features of MRC4 based upon parameters such as non-linearity, resiliency, balancedness, propagation and immunity. Further, we have compared the security features and confusion-diffusion attributes with some recent variants of RC4 and have found that MRC4 is efficient in withstanding against attacks. The experimental results show that MRC4 supports a 60% better confusion property and 50% better diffusion as compared to the original RC4 method.

Changes in land use have several impacts on soil organic carbon (C) and nitrogen (N) cycling, both of which are important for soil stability and fertility. Initially, the study area was barren uncultivated desert land. During the late 1960s, the introduction of a canal in the arid region converted the barren deserts into cultivated land. The objectives of the present study were to evaluate the effects of various land use systems on temporal changes in soil organic C and N pools, and to evaluate the usefulness of different C and N management indices for suitable and sustainable land use systems under arid conditions. We quantified soil organic C and N pools in five different land uses of the Ghaggar flood plains, in hot, arid Rajasthan, India. The study focused on five land use systems: uncultivated, agroforestry, citrus orchard, rice–wheat, and forage crop. These land use systems are ≥20 years old. Our results showed that total organic carbon (TOC) was highest (7.20 g kg−1) in the forage crop and lowest in uncultivated land (3.10 g kg−1), and it decreased with depth. Across different land uses, the very labile carbon (VLC) fraction varied from 36.11 to 42.74% of TOC. In comparison to the uncultivated system, forage cropping, rice–wheat, citrus orchard, and agroforestry systems increased active carbon by 103%, 68.3%, 42.5%, and 30.6%, respectively. Changes in management and land use are more likely to affect the VLC. In soil under the forage crop, there was a considerable improvement in total N, labile N, and mineral N. Lability index of C (LIC), carbon management index (CMI), and TOC/clay indices were more sensitive to distinguishing land uses. The highest value of CMI was observed in the forage crop system followed by rice–wheat and agroforestry. In the long term, adoption of the forage crop increased soil quality in the hot, arid desert environment by enhancing CMI and VLC, which are the useful parameters for assessing the capacity of land use systems to promote soil quality.

Introduction: In development of cancer chronic inflammation plays a major role. Most established determinants of Prostate Carcinoma (PCa) are modern lifestyle, genetics, and age. In the first prostate biopsy, approximately 1 out of 5 men i.e., 20% with PCa may be misdiagnosed. Therefore, there is clear requirement of novel markers, which can detect both clinically significant PCa, and prevent unnecessary biopsy. Some solid tumours found to have association of Neutrophil to Lymphocyte Ratio (NLR), Platelet to Lymphocyte Ratio (PLR) and Red cell Distribution Width (RDW). Aim: To study the significance of association of Prostate Specific Antigen (PSA), PLR, NLR and RDW with PCa. Materials and Methods: This study was conducted using the cross-sectional method in the Department of Pathology, Geetanjali Medical College and Hospital, Udaipur, Rajasthan between January 2018 to November 2020. In this cross-sectional study, 84 patients who underwent Trans Rectal Ultrasound (TRUS) guided prostate biopsy were included. Complete Blood Count (CBC) was used to determine PLR, NLR and RDW and biochemical test for PSA. Patients were divided into two groups; having benign and malignant pathology. Unpaired t-test, Mannwhitney U test, logistic regression analysis and correlation were performed for statistical analysis. Results: With the use of univariate logistic regression, association between PSA, NLR, PLR, RDW values and PCa detection was determined. Serum PSA was significantly more in the PCa group (as BPH and prostatitis are both benign conditions so are kept in non-PCa group) compared to other two groups (p

IntroductionImproving quality of care (QoC) for childbirth and sick newborns is critical for maternal and neonatal mortality reduction. Information on the process and impact of quality improvement at district and sub-district hospitals in India is limited. This implementation research was prioritized by the Haryana State (India) to improve the QoC for maternal and newborn care at the busy hospitals in districts.MethodsThis study at nine district and sub-district referral hospitals in three districts (Faridabad, Rewari and Jhajjar) during April 2017-March 2019 adopted pre-post, quasi-experimental study design and plan-do-study-act quality improvement method. During the six quarterly plan-do-study-act cycles, the facility and district quality improvement teams led the gap identification, solution planning and implementation with external facilitation. The external facilitators monitored and collected data on indicators related to maternal and newborn service availability, patient satisfaction, case record quality, provider's knowledge and skills during the cycles. These indicators were compared between baseline (pre-intervention) and endline (post-intervention) cycles for documenting impact.ResultsThe interventions closed 50% of gaps identified, increased the number of deliveries (1562 to 1631 monthly), improved care of pregnant women in labour with hypertension (1.2% to 3.9%, pConclusionThis multipronged quality improvement strategy improved the maternal and newborn services, case documentation and patient satisfaction at district and sub-district hospitals. The processes and lessons learned shall be useful for replicating and scaling up.

Defining nutrient management zones (MZs) is crucial for the implementation of site-specific management. The determination of MZs is based on several factors, including crop, soil, climate, and terrain characteristics. This study aims to delineate MZs by means of geostatistical and fuzzy clustering algorithms considering remotely sensed and laboratory data and, subsequently, to compare the zone maps in the north-eastern Himalayan region of India. For this study, 896 grid-wise representative soil samples (0–25 cm depth) were collected from the study area (1615 km2). The soils were analysed for soil reaction (pH), soil organic carbon and available macro (N, P and K) and micronutrients (Fe, Mn, Zn and Cu). The predicted soil maps were developed using regression kriging, where 28 digital elevation model-derived terrain attributes and two vegetation derivatives were used as environmental covariates. The coefficient of determination (R2) and root mean square error were used to evaluate the model’s performance. The predicted soil parameters were accurate, and regression kriging identified the highest variability for the majority of the soil variables. Further, to define the management zones, the geographically weighted principal component analysis and possibilistic fuzzy c-means clustering method were employed, based on which the optimum clusters were identified by employing fuzzy performance index and normalized classification entropy. The management zones were constructed considering the total pixel points of 30 m spatial resolution (17, 86,985 data points). The area was divided into four distinct zones, which could be differently managed. MZ 1 covers the maximum (43.3%), followed by MZ 2 (29.4%), MZ 3 (27.0%) and MZ 4 (0.3%). The MZs map thus would not only serve as a guide for judicious location-specific nutrient management, but would also help the policymakers to bring sustainable changes in the north-eastern Himalayan region of India.

Phycoremediation is a cost effective, environmentally sustainable, safe and alternative technology for remediation of wastewater. The present work was aimed to evaluate the role of inoculated microalgae (Chlorella minutissima) in phycoremediation of sewage wastewater. The selected microalgae removed 94.4% TDS, 88.9% of NO3 -N, 66.3% potassium, 67.4% phosphorus, 48.2% NH4 +, 93% (Biological Oxygen Demand) BOD5 and 80.5% (Chemical Oxygen Demand) COD. The wastewater obtained after phycoremediation have safe limit of nutrients to be used as irrigation water in agricultural fields. The results of this study suggested that growing algae in nutrient-rich sewage wastewater offers a new opportunity to bio-remediate pollution load of wastewater and use it for irrigation purposes.

Introduction: The kidney is one of the most highly differentiated organs in the body, affected by various disease processes, some resulting in permanent damage leading to surgical removal of the organ i.e., nephrectomy. Patterns of the indications for nephrectomy vary in different age groups, geographical locations and time periods. Nephrectomy is a common procedure in urological practice done for various conditions like calculi, chronic pylelonephritis, malignancy, obstruction, injury etc., with wide range of morbidity and mortality. Aim: The aim of this study was to study the pattern of histopathological lesions in nephrectomy cases in Southern Rajasthan. Materials and Methods: This study was conducted in the Department of Pathology, Geetanjali Medical College and Hospital (GMCH), Udaipur, Rajasthan. It was a cross-sectional study performed on 121 patients, from January 2015 to March 2020 in which patient’s detail such as age, sex, gross and microscopic findings were retrieved and reviewed. Data was tabulated and analysed. Results: A total of 121 specimens of nephrectomy were included in the study. Among 121 nephrectomy cases, higher incidence was observed in 6th and 3rd decade of life with approximately equal preponderance of male and female; 0.98:1. Out of 121 cases 88 (72.7%) were non-neoplastic and 33 (22.27%) were neoplastic. Conclusion: Benign conditions of kidney are the leading cause of End Stage Renal Disease (ESRD) in the developing world. In our country, there are an increased number of ESRD which require dialysis and transplantation. This study has been performed to know the different causes of nephrectomy in a tertiary care center of India.

Microalgae, due to their complex metabolic capacity, are being continuously explored for nutraceuticals, pharmaceuticals, and other industrially important bioactives. However, suboptimal yield and productivity of the bioactive of interest in local and robust wild-type strains are of perennial concerns for their industrial applications. To overcome such limitations, strain improvement through genetic engineering could play a decisive role. Though the advanced tools for genetic engineering have emerged at a greater pace, they still remain underused for microalgae as compared to other microorganisms. Pertaining to this, we reviewed the progress made so far in the development of molecular tools and techniques, and their deployment for microalgae strain improvement through genetic engineering. The recent availability of genome sequences and other omics datasets form diverse microalgae species have remarkable potential to guide strategic momentum in microalgae strain improvement program. This review focuses on the recent and significant improvements in the omics resources, mutant libraries, and high throughput screening methodologies helpful to augment research in the model and non-model microalgae. Authors have also summarized the case studies on genetically engineered microalgae and highlight the opportunities and challenges that are emerging from the current progress in the application of genome-editing to facilitate microalgal strain improvement. Toward the end, the regulatory and biosafety issues in the use of genetically engineered microalgae in commercial applications are described.

Medicinal and aromatic plants (MAPs) are a rich source of bioactive compounds that are immensely important due to their potential use in pharmacological and agricultural applications. Here, we have evaluated the antimicrobial activity of essential oils (EOs) from three different species of Ocimum: O. gratissimum (EO1), O. tenuiflorum (EO2), and O. sanctum (EO3). The EOs were screened for antibacterial activity against pathogenic strains of Escherichia coli, Enterobacter cloacae and methicillin-resistant Staphylococcus aureus (MRSA). The essential oils EO1 and EO3 showed significant growth inhibition of the tested bacteria. Likewise, all EOs exhibited antifungal potential against the broad-spectrum plant fungal pathogen Sclerotinia sclerotiorum that causes white-mould disease in plants. Moreover, the antimicrobial potential of the EOs correlates well with their antioxidant activity determined by DPPH free radical scavenging activity. The biochemical analysis of the EOs employing high-performance thin-layer chromatography, gas chromatography-mass spectrometry, and Fourier transform infrared spectroscopy, revealed the presence of distinct phytoconstituents that might be responsible for their differential bioactivity. Furthermore, an in-silico evaluation of the candidate phytoconstituents using molecular docking analysis suggests their potential for antimicrobial applications. Altogether, our results clearly show that EO1 and EO3 possess promising antimicrobial properties, and therefore could be utilized as a potential antimicrobial agent.

Rice is a staple food crop for almost half of the world’s population, especially in the developing countries of Asia and Africa. It is widely grown in different climatic conditions, depending on the quality of the water, soil, and genetic makeup of the rice cultivar. Many (a)biotic stresses severely curtail rice growth and development, with an eventual reduction in crop yield. However, for molecular functional analysis, the availability of an efficient genetic transformation protocol is essential. To ensure food security and safety for the continuously increasing global population, the development of climate-resilient crops is crucial. Here, in this study, the rice transformation protocol has been effectively optimized for the efficient and rapid generation of rice transgenic plants. We also highlighted the critical steps and precautionary measures to be taken while performing the rice transformation. We further assess the efficacy of this protocol by transforming rice with two different transformation constructs for generating galactinol synthase (GolS) overexpression lines and CRISPR/Cas9-mediated edited lines of lipase (Lip) encoding the OsLip1 gene. The putative transformants were subjected to molecular analysis to confirm gene integration/editing, respectively. Collectively, the easy, efficient, and rapid rice transformation protocol used in this present study can be applied as a potential tool for gene(s) function studies in rice and eventually to the rice crop improvement.

Vehicular ad hoc networks (VANETs) have been considered as one of the most influential applications of mobile ad hoc networks. The VANETs have also become an important part of Internet of Things. Along with the advantages, such networks are facing a number of security issues. A number of research have been done so far to identify the solution of the security problems in the VANETs. But the existing solutions do not confirm the confidentiality-integrity-availability (CIA) triad services simultaneously. Therefore, in this paper, we have provided a solution for the VANETs security using end-to-end authentication to avoid intrusion in the VANETs. After verifying the communicating entities, the data are transmitted in encrypted form thus the proposed approach provides CIA security services to VANETs communication. Along with this, we have used a sandboxing method for in-vehicle communication for prevention of intrusion in form of downloaded information. Moreover, in this paper, the VANETs are considered as a hierarchical model to concentrate on a less number of message exchanges. Furthermore, the simulation results show the efficiency of our proposed solution.

Cryptographic algorithms and functions should possess some of the important functional requirements such as: non-linearity, resiliency, propagation and immunity. Several previous studies were executed to analyze these characteristics of the cryptographic functions specifically for Boolean and symmetric functions. Randomness is a requirement in present cryptographic algorithms and therefore, Symmetric Random Function Generator (SRFG) has been developed. In this paper, we have analysed SRFG based on propagation feature and immunity. Moreover, NIST recommended statistical suite has been tested on SRFG outputs. The test values show that SRFG possess some of the useful randomness properties for cryptographic applications such as individual frequency in a sequence and block-based frequency, long run of sequences, oscillations from 0 to 1 or vice-versa, patterns of bits, gap bits between two patterns, and overlapping block bits. We also analyze the comparison of SRFG and some existing random number generators. We observe that SRFG is efficient for cryptographic operations in terms of propagation and immunity features.

Vehicular networks are the combination of transport systems and the internet systems formed with the main motive to increase the safety of passengers, although non-safety applications are also provided by vehicular networks. Internet of Things (IoT) has a subsection called Mobile Ad hoc Network (MANET)m which in turn has a subsection called Vehicular Ad hoc Network (VANET). Internet of Energy (IoE) is a new domain that is formed using electric vehicles connected with VANETs. As a large number of transport systems are coming into operation and various pervasive applications are designed to handle such networks, the increasing number of attacks in this domain is also creating threats. As IoE is connected to VANETs extension with electric cars, the future of VANETs can be a question if security measures are not significant. The present survey is an attempt to cover various attack types on vehicular networks with existing security solutions available to handle these attacks. This study will help researchers in getting in-depth information about the taxonomy of vehicular network security issues which can be explored further to design innovative solutions. This knowledge will also be helpful for new research directions, which in turn will help in the formulation of new strategies to handle attacks in a much better way.

In the present era, the global need for food is increasing rapidly; nanomaterials are a useful tool for improving crop production and yield. The application of nanomaterials can improve plant growth parameters. Biotic stress is induced by many microbes in crops and causes disease and high yield loss. Every year, approximately 20–40% of crop yield is lost due to plant diseases caused by various pests and pathogens. Current plant disease or biotic stress management mainly relies on toxic fungicides and pesticides that are potentially harmful to the environment. Nanotechnology emerged as an alternative for the sustainable and eco-friendly management of biotic stress induced by pests and pathogens on crops. In this review article, we assess the role and impact of different nanoparticles in plant disease management, and this review explores the direction in which nanoparticles can be utilized for improving plant growth and crop yield.