Ni1-xGdxFe2O4 (x=0.02, 0.04, 0.06 & 0.08) (NGF) nanoparticles were synthesized via hydrothermal method. The X-ray diffraction study confirmed the single-phase cubic spinel structure. The morphology indicated the stones (approximately nanocubes) like structures in the FESEM images. The mass loss, and thermal transition temperatures were evaluated as a function of Gd-content using TG-DTG, and TG-DSC measurements. The M-H loops evidenced the high magnetization values for NGFO as compared to pure nickel ferrite. Cation distribution showed the preferred occupancy of cations in the magnetic spinel system. Frequency dependence of dielectric, conductivity, and impedance parameters was elucidated with increase in Gd-content.

The invention of nanoscience not only brings a revolutionary change in the field of science but also changed the direction of research. Today the whole world is under the trigger of nano and nanoparticles have multidimensional applications in every aspect of life including environmental point of view. Till today a plethora of nanoparticles have been synthesized and have also been applied for multiple purposes and hence grabbed the attention of researchers all over the world. Among the bunch of NPs discovered to date, we have a particular interest in silver nanoparticles (AgNPs) because of their cost-effectiveness and huge abundance in the earth’s crust. With respect to every passing day, due to various kinds of anthropological activities, the quality of the environment such as air, water and soil is depleting which ultimately hampers the human civilization. To encompass the growing environmental issues, many techniques have been adopted. Among the many strategies, tackling the current issues regarding environment through nanoscience is highly worthy as because of its cost-effectiveness, less time consuming and easy handling process. This article reviews the potential of nanoparticles, particularly silver nanoparticles, for a wide range of environmental applications, such as soil, air, and water remediation.

Recent data suggest that K-Ras4B (hereafter K-Ras) can drive cancer cell stemness via calmodulin (CaM)-dependent, non-canonical Wnt-signalling. Here we examined whether another Ca2+-binding protein, the CaM-related centrin1, binds to K-Ras and could mediate some K-Ras functions that were previously ascribed to CaM. While CaM and centrin1 appear to distinguish between peptides that were derived from their classical targets, they both bind to K-Ras in cells. Cellular BRET-data suggest that CaM engages more with K-Ras than centrin1 and that the interaction with the C-terminal membrane anchor of K-Ras is sufficient for this. Surprisingly, binding of neither K-Ras nor its membrane anchor alone to CaM or centrin1 is sensitive to inhibition of prenylation. In support of an involvement of the G-domain of K-Ras in cellular complexes with these Ca2+-binding proteins, we find that oncogenic K-RasG12V displays increased engagement with both CaM and centrin1. This is abrogated by addition of the D38A effector-site mutation, suggesting that K-RasG12V is held together with CaM or centrin1 in complexes with effectors. When treated with CaM-inhibitors the BRET-interaction of K-RasG12V with centrin1 was also disrupted in the low micromolar range, comparable to that with CaM. While CaM predominates in regulating functional membrane anchorage of K-Ras, it has a very similar co-distribution with centrin1 on mitotic organelles. Given these results, a significant overlap of the CaM- and centrin1-dependent functions of K-Ras is suggested.

This paper reveals the physical properties of Jeffery nanofluid flow past a moving plate embedded in porous medium under the existence of radiation and thermal diffusion. The analysis is carried out in three cases of moving plate, namely stationary plate λ = 0, forth-moving plate λ = 1, back-moving plate λ = −1. Finite difference method is applied to solve the governing equations of the flow and pointed out the variations in velocity, temperature and concentration with the use of graphical presentations. The impact of several parameters on local skin friction, Nusselt number and Sherwood number is also noticed and discussed. Enhancement of velocity is observed under the impact of Jeffery parameter for the cases of stationary plate and back-moving plate, whereas reverse nature is found in the case of forth-moving plate. The velocity enhances as the values of porosity parameter increases for the case of stationary plate and forth-moving plate but a reverse nature is noticed in the case of back-moving plate.

The role of human resource management practices and organizational loyalty dealing with employee retention has been widely explored and examined in the existing literature. The majority of human resource management researchers have focused on the role of policies and practices in different sectors related to employee retention. However, less attention has been given to identifying the practices and procedures common across all industries and sectors. The present study attempts to determine and examine the most important constructs like HR practices and organizational loyalty of employee retention management and proposes a comprehensive structural equation model to measure the impact of these constructs on employee retention. After an extensive review of the literature, organizational loyalty, and human resources management practices like recruitment and selection, compensation and benefit, training and development, supervision and evaluation have been identified as four essential practices dealing with employee retention and are common across all industries. These practices constitute the component factors of an employee retention management predicting employee’s turnover intentions. The survey method was adopted, and the original data obtained through the self-administered questionnaire. The valid one hundred and eighty-nine (189) respondents analyzed by using Lisrel 8.7, Structural equation model (SEM) analysis results shows that human resource management practices and organizational loyalty have strong positive impact on employee retention. This study tends to assist human resource managers and decision makers in selecting the appropriate motivating factors to retain and satisfy their employees

UPF3B is a constituent of the classical nonsense-mediated mRNA decay (NMD) pathway that degrades both the aberrant transcripts and a set of physiological transcripts. In higher eukaryotes, UPF3B have significant biochemical functions in diverse cellular processes including NMD and translation. UPF3B plays a crucial role in neuronal development and differentiation. Next-generation sequencing technologies identified several loss-of-function mutations in the UPF3B gene that results in neuro-developmental disorders in humans. To uncover the mechanistic role of UPF3B in neuronal functions, we have generated the UPF3B-knockout mammalian cell line model system using CRISPR-Cas9 gene editing method. RNA-Sequencing Analysis of cellular transcriptome from UPF3B-KO cells identified specific genes involved in cell growth and neuronal functions. Altered expression of genes related to the axon guidance pathway delineated the UPF3B function to regulate the neuron-specific genes. Functional enrichment analysis identified the genes involved in the disorders related to mental health and intellectual disability. Our study has the potential to identify the direct players of intellectual disability and will have broader implications.

Pharmaceutical packaging is very crucial in as much as it plays the role of enhancing the stability, efficacy as well as safety of the produced medicine through the material used in packaging. It is important to note that cGMP Chapters 661 and 671 are focused on explaining how one should assess the quality of container materials in the sphere of pharmaceuticals. These chapters encompass a number ofmatters among them being Plastic and glass containers and performance testing; they serve as a resource that aids in assuring all standards are met with profound proficiency. Following this, the performance of two core chapters of USP known as Chapter 661 on “Containers—Glass” and Chapter 671 on “Containers—Performance Testing” will be dealt with in a step-by-step manner in the following paper while providing a comprehensive review of both at the same time. Understanding and legal obedience to these rules, as stipulated in the above-mentioned chapter, are indispensable for almost all the parties involved in the production of the drugs, together with the policies and legislation on the same. Thus, the purpose of this paper is to describe and discuss the major aspects of the understanding, application, requirements and evaluation procedures depending on the USP Chapters 661 and 671 in the sphere of the pharmaceutical market.

In this paper, we present sums and partial sums of Horadam sequences via generating functions which extends a recent result of Prodinger.

Conservation history of D614 residue is valuable in predicting the consequences of D614G mutation in the SARS-CoV-2 spike glycoprotein (SGP). We report here that the D614 belonged to an extraordinarily conserved, densely hydrophobic eleven amino acid peptide-motif vavlyqdvnct (11-aa), in the Sarbecovirus group and the variant carrying vavlyqdvnct had appeared in Chinese samples and became predominant in several geographical hotspots in late March, 2020. Interestingly a 2009 annotation of SARS-CoV contained the same mutation.

Recent years have seen a massive increase in research on mindfulness as both a therapeutic practice as well as a protective health factor. While many associations have been made between mindfulness and clinical outcomes, understanding of the underlying mechanistic processes is still in its infancy. In this review, associations between mindfulness and other established frameworks in cognitive control are explored—in particular the dual modes of control framework in cognitive control theory. Studies in mindfulness providing evidence towards a dual-mode mindfulness model are reviewed and compared with the proactive and reactive modes of cognitive control to identify common underlying principles. Studies involving cognitive testing, advanced neuroimaging, and neurotransmitter levels and their associations with proactive and reactive control are reviewed in the context of the dual modes of mindfulness. While evidence supporting relationships between proactive and reactive modes of mindfulness and cognitive control are preliminary, existing literature on mindfulness already supports the notion of two components of mindfulness and is in line with the hypothesis that cognitive control and mindfulness are closely related. Since preliminary evidence suggests that proactive forms of mindfulness are more associated with improvement in clinical outcomes, mindfulness programs could be modified to target proactive mindfulness practices to maximize outcomes. The implications of proactive and reactive mindfulness on therapy, limitations of the framework, and necessity of studies providing direct evidence are further discussed.

In this paper, closed forms of the sum formulas $\sum_{k=0}^{n}x^{k}W_{k}^{3}$ and $\sum_{k=1}^{n}x^{k}W_{-k}^{3}$ for the cubes of generalized Fibonacci numbers are presented. As special cases, we give sum formulas of Fibonacci, Lucas, Pell, Pell-Lucas, Jacobsthal, Jacobsthal-Lucas numbers.

The Hunga Tonga-Hunga Ha’apai underwater volcano (20.57°S, 175.38°W) violently erupted on 15 January 2022. The volcanic plume evolution during its initial stages is delineated by using Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC)-2 radio occultation (RO) measurements. The bending angle (BA) anomaly over the Tonga volcanic plume (within 200 km from the eruption center) at 5:17 UTC on 15 January shows a prominent peak at higher stratospheric heights. The top of the BA anomaly revealed that negative to positive change occurred at ~38 km indicating the first height where the RO line-of-sight encounters the volcanic plume. The BA anomaly further revealed an increase of ~50% at ~36 km and confirms the volcanic plume reached above ~36 km. Further, the evolution of BA perturbations within 24 hours after the initial explosion is also discussed. From collocated RO profiles with the volcanic plume, we find a clear descending of the peak altitude of the BA perturbation from ~36 km to ~30 km within 24 hours after the initial eruption. The results from the study will provide some insights into advancing our understanding of volcanic cloud dynamics and their implementation in volcanic plume modeling.

Thermoelectrics, in particular solid-state conversion of heat to electricity and vice versa, is expected to be a key energy harvesting and temperature management solution in coming years. There has been a resurgence in the search for new materials for advanced thermoelectric energy conversion applications and to enhance the properties of existing materials. In this paper, we review recent efforts on improving figure-of-merit (ZT) through alloying and nano structuring. As heatsink characteristics dictate the performance of thermoelectric modules, various types of heatsink designs has been investigated. Several reported strategies for improving ZT are critically assessed. A notable increase in figure-of-merit of thermoelectric materials (TE) has opened up new areas of applications especially in the medical field. Peltier cooling devices are widely employed for patient core temperature control, skin cooling, medical device and laboratory equipment cooling. Application of these devices in the medical field both in temperature control and power generation has been studied in detail. It is envisioned that this study will provide profound knowledge on the thermoelectric based materials and its role in medical applications.

Frontal Temporal Dementia (FTD) is a neurological disorder known to have less therapeutic options. So far only a few biomarkers are available for FTD that can be used as potential comorbidity targets. To this end, in the present study we aim to identify potential biomarkers or susceptible genes for FTD that show comorbidities with diseases such as COVID-19 and Breast Cancer. Gene expression Omnibus datasets containing FTD expression profiles from African American and white ethnicity background were included in our study. In FTD samples of GSE193391 dataset, we identified 305 DEGs with 168 genes being up-regulated and 137 genes being down-regulated. We conducted comorbidity analysis for COVID-19 and Breast cancer followed by analysis of potential drug interactions, pathogenicity, analysis of genetic variants and functional enrichment analysis. Resulting genes AKT3, GFAP, ADCYAP1R1, VDAC1, and C4A showed significant transcriptomic alterations in FTD and significant comorbidity status with COVID-19 and Breast cancer. Functional pathway analysis revealed that these comorbid genes were significantly enriched in the pathways such as glioma, JAK/STAT signaling, systematic lupus erythematosus, neurodegeneration-multiple diseases and neuroactive ligand-receptor interaction. Overall, from these results, we concluded that these genes could be recommended as potential therapeutic targets for the treatment of comorbidities in FTD.

Bone is a dynamic organ maintained by tightly regulated mechanisms. With old age, bone homeostasis which is maintained by an intricate balance between bone formation and bone resorption, undergoes deregulation. Oxidative stress-induced DNA damage, cellular apoptosis, and cellular senescence are all responsible for this tissue dysfunction and the imbalance in bone homeostasis. These cellular mechanisms have become a target for therapeutics to treat age-related osteoporosis. Pharmacological and genetic mouse models have shown the importance of senescent cell clearance in alleviating age-related osteoporosis. Senescent cells have an altered secretome, which may have an autocrine, paracrine, or endocrine function. The current review discusses the current and potential pathways which lead to a senescence profile in an aged skeleton. The review was written following an extensive literature survey of published studies, mostly excluding articles published on pre-print servers. The review discusses potential therapeutics targeting cellular senescence and the senescent secretome as underlying pathogenesis of an aging bone.

The excessive intake of sodium (Na) and insufficient intake of potassium (K) are major concerns to prevent hypertension. Using low-Na/K seasonings (reducing 25% of the NaCl and adding K salt) may improve the dietary Na/K ratio and help prevent hypertension. To devise an intervention study using low-Na/K seasonings at a company cafeteria, we calculated the Na and K contents of the meals served at the cafeteria and estimated changes in the intakes when suitable low-Na/K seasonings were used. We also considered using milk as a good source of K. We used an ingredient list of a company cafeteria and calculated Na and K contents in each dish. The average amounts of NaCl and K per use were 5.04 g and 718 mg, respectively. Seasonings contributed 70.9% of the NaCl. With the use of low-Na/K seasonings, an estimated reduction in NaCl of 0.8 g/day and an estimated increase in K of 308 mg/day was achieved. An additional serving (200 mL) of milk, NaCl was reduced by 0.57 g/day and K was increased by 610 mg/day, with an overall decrease in the dietary Na/K ratio from 3.20 to 2.40. The use of low-Na/K seasonings and dairy may improve the dietary Na/K ratio among cafeteria users and help prevent hypertension.

A field experiment was conducted during Kharif 2018, laid out in Randomized Block Design with three replications having seven treatments viz. N omission (T1), N applied as basal and AT (T2), N as basal, AT and PI (T3), N as basal and top dressing at NDVI threshold of 0.75 (T4), at NDVI threshold of 0.8 (T5), at SPAD threshold of 35.0 (T6) and SPAD threshold of 37.5 (T7) with Rice variety Sahabhagidhan.The study revealed that application of 30 kg N/ha as basal dose and top dressing of 20 kg N/ha twice at 35 and 63 DAS guided by NDVI threshold value of 0.8 (T5) was found to be superior over other treatments with respect to productivity. T5 recorded highest grain yield of 4438 kg/ha which was 17.0% higher than that top dressed at NDVI threshold of 0.75 (T4) and 7.1% higher than that top dressed at SPAD threshold value of 37.5 (T7). In case of SPAD meter, nitrogen top dressed at threshold value of 37.5 (T7) produced grain yield of 4143 kg/ha which was 15.0% higher than T6. T5 produced maximum dry matter of 8678 kg/ha with highest grain yield (4438 kg/ha), straw yield (5092 kg/ha) and harvest index 46.0%.

As reported by us and others previously (1, 2), the D614G mutation appeared in the spike glycoprotein (SPG) of the SARS-CoV-2 (the pathogen behind COVID-19) at the early stages of the pandemic and then G614 containing variant of SARS-CoV-2 became the predominant strain in most human populations across the world. However, one of the most recent reports from India (3) stated the incidence of G614 to be only 26% in the Indian population. This report is contradictory to the information available through the GenBank (4) SARS-CoV-2 sequence deposits made by various laboratories from India. The above stated report currently circulating in the Indian media is likely to create a public perception that the Indian strain is less contagious and such a notion could be harmful to people’s welfare. In view of this concern we have re-evaluated, updated and recalculated the incidence of the G614 variant in the Indian population by analyzing 395 Indian SARS-CoV-2 genomic sequences available in the GenBank as of June 26, 2020. In our analysis we have categorized the samples by the month in which the samples were collected. We have used an alignment-free software tool named Compare (5, 6), and the Basic Local Alignment Search Tool (BLAST) (7) in the present analysis. We finally inspected each of the 395 sequences physically for the presence of aspartic acid (D) or glycine (G) at the 614^th position of the spike glycoprotein. We analyzed an Australian cohort in parallel for comparison. We have found that the prevalence of G614 variant in the Indian samples for the month of June 2020 is 90.6%. The trends are similar with the Australian samples.

Telehealth has been playing a progressively major role in the management of the NCOVID-19 crisis. The enforcement of social distancing measures has had the consequence of reduced technology distance in almost every walk of life. In this paper, based primarily on the still unfolding experiences of deploying it during the current situation, we argue that telehealth has finally come of age and that it is time to move it from the peripheries to the center of the 21st century healthcare. To provide a live context to the discussion, several instances of how telehealth strengthened our healthcare systems during the NCOVID-19 crisis are presented.

Artificial General Intelligence (AGI) represents a pivotal advancement in AI with far- reaching implications across technological, ethical, and societal domains. This paper addresses the following: (1) an in-depth assessment of AGI’s transformative potential across different sectors and its multifaceted implications, including significant financial impacts like workforce disruption, income inequality, productivity gains, and potential systemic risks; (2) an examination of critical ethical considerations, including transparency and accountability, complex ethical dilemmas and societal impact; (3) a detailed analysis of privacy, legal and policy implications, particularly in intellectual property and liability, and (4) a proposed governance framework to ensure responsible AGI development and deployment. Additionally, the paper explores and addresses AGI's political implications, including national security and potential misuse. By analyzing and considering computer science, philosophy, economics, and policy perspectives, we offer a multidisciplinary view of AGI’s challenges and opportunities, advocating for proactive measures to align AGI development with human values and societal interests.

To enable purposeful design and implementation of automated concrete technologies, precise assessment and prediction of the complex material flow at various stages of the process chain are necessary. This paper investigates the intermediate stage of the extrusion and deposition processes in extrusion-based 3D-concrete-printing, using a numerical model based on the Particle Finite Element Method (PFEM). In PFEM, due to the Lagrangian description of motion, remeshing algorithms and the alpha shape method are used to track the free surface during large deformation scenarios. The Bingham constitutive model was used for describing the rheological behaviour of fresh concrete. This model is validated by comparing the numerically predicted layer geometries with those obtained from laboratory 3D printing experiments. Extensive parametric studies were then conducted using the numerical simulation, delineating the influence of process and material parameters on the layer geometries, the dynamic surface forces generated under the extrusion nozzle and the inter-layer interactions.

Interfaces between layers in 3D-printed elements produced by extrusion-based material deposition were investigated on both macro- and micro-scales. On the macro-scale, compression and bend tests were performed on two 3D-printable cement-based compositions (3PCs), namely C1 and C2. The influences of binder composition and time interval between layers on layer-interface strength were critically analyzed. In the context of additive manufacturing, the optimized composition C2, containing pozzolanic additives, exhibited mechanical performance superior to that of the mixture with Portland cement as the sole binder. In particular, Mixture C2 showed a less pronounced decrease in interface tensile strength. Even for time intervals between depositions of two layers as long as 1 day the loss in corresponding flexural strength was below 25%, as compared with C2 specimens tested in the perpendicular direction. In contrast, the decrease in flexural strength measured for C1 specimens amounted to over 90% for the same set of parameters. Higher porosity at the interfaces of the printed concrete layers was identified as the cause for the lower interface strengths of C1. Microscopic observations supported the findings of the macroscopic investigations. While a pronounced recovery (“self-healing”) of the porous, discontinuous interlayers was observed with increasing age for Mixture C2, in case of C1 the filling products grown in the porous interlayer were found to be non-strengthening.

Buildability, i.e. the ability of a deposited material bulk to retain its dimmensions under increasing load, is an inherent prerequisite for formwork-free digital construction (DC). Since DC processes are relatively new, no standard methods of characterization are available yet. The paper at hand presents practice-oriented buildabilty criteria by taking various process parameters and construction costs into consideration. In doing so, direct links between laboratory buildability tests and target applications are established. A systematic basis for calculating the time interval (TI) to be followed during laboratory testing is proposed for the full-width printing (FWP) and filament printing (FP) processes. The proposed approach is validated by applying it to a high-strength, printable, fine-grained concrete. Comparative analyses of FWP and FP revealed that to test the buildability of a material for FP processes, higher velocities of the printhead should be established for laboratory tests in comparison to those needed for FWP process, providing for equal construction rates.

The process model is very essential for the model based control design. The model of the process can be identified using system identification algorithm. The system identification is done through the open loop and closed loop approaches. In this work, the lab scale conical tank setup configured as a non square MIMO system. The conical tank system is identified through the both appraoches, the effectiveness and need of the both approaces are discussed. Based on the open loop identified model the controller designed and the controller implemented in the real time the to record the process data. From this data the closed loop identification are conducted uisng N4SID algorithm. The controller seetings are obtained using the smith predcitor based IMC based PI controller for the obtained model. The proposed identification algorithm and controller tuning show the better reults over the conventional method. Moreover, this method is applicable for all the non square MIMO system.

Polyketides are large group of secondary metabolites that have notable variety in their structure and function. Polyketides exhibit a wide range of bioactivities such as antibacterial, antifungal, anticancer, antiviral, immune-suppressing, anti-cholesterol and anti-inflammatory activity. Naturally, they are found in bacteria, fungi, plants, protists, insects, mollusks and sponges. Streptomyces is a genus of Gram-positive bacteria that has a filamentous form like fungi. This genus is best known as one of polyketides producers. Some examples of polyketides produced by Streptomyces are rapamycin, oleandomycin, actinorhodin, daunorubicin and caprazamycin. Biosynthesis of polyketides involves a group of enzyme activities called polyketide synthases (PKSs). There are three types of PKSs (type I, type II, and type III) in Streptomyces that responsible for producing polyketides. This paper focuses on biosynthesis of polyketides in Streptomyces with three structurally different types of PKSs.

Forest fire is a major ecological disaster, which has economic, social and environmental impacts on humans and also causes the loss of biodiversity. Forest officials issue the warnings to the public on the basis of fire danger index classes. There is no fire danger index for the country India due to the sparsely distributed meteorological stations. Previous studies suggest that Static Fire Danger Index (SFDI) as well as Dynamic Fire Danger Index (DFDI) have been derived from the satellite datasets. In this study, we have made an attempt to integrate both the Static and Dynamic fire danger indices and also used the Near Real Time (NRT) data sets that can be available for download through NASA FTP server after one hour of the satellite overpass. In this study, DFDI has been calculated from the MODIS Terra NRT Land Surface Temperature (MOD11_L2) and MODIS TERRA NRT surface reflectance MOD09. Finally, The Forest Fire Danger Index (FFDI) has been developed from the static and dynamic fire danger indices by the additive model and the overall accuracy was around 81.27%. Thus, the FFDI has been useful to predict the fire danger accurately and can be useful anywhere, where the meteorological stations are un-available.

Time is a component quantity of various measurements and is also used on its own to sequence events, to compare the duration of events or the intervals between them, and to quantify rates of change of quantities in material reality or in the conscious experience [1]. The measuring equipment well might happen to be a clock. By making a presupposition that clock is Time, it is perceived experimentally that “Time exhibits wave-like properties”

The study, conducted at the Department of Medicine, Maulana Azad Medical College and associated Lok Nayak Hospital, aimed to investigate the prevalence of iron deficiency anaemia among anaemic overweight and obese individuals. Fifty participants were included after screening and consent, undergoing socio-demographic assessment, clinical evaluation, and laboratory investigations. Middle to old-aged individuals predominated (Mean ± SD: 54.54 ± 11.32 years), with females comprising 62%. All subjects were obese (mean BMI: 37.27 ± 5.71 kg/m²), with common comorbidities including hypertension (68%), diabetes (36%), and obstructive sleep apnea-hypopnea syndrome (32%). Nutritional deficiencies, particularly iron deficiency, were prevalent, affecting 62% of subjects, with 48% having iron deficiency alone. Anemia of chronic illness was observed in 38%. Laboratory parameters showed low hemoglobin (8.53 ± 1.23 g/dL), MCV (78.75 ± 10.13 fL), and elevated ESR (20.56 ± 21.47 mm/hour) and CRP levels (4.71 ± 3.32 mg/dL), indicating inflammation. Correlation analyses revealed negative associations between BMI and serum iron/ferritin and positive associations with serum hepcidin. The study underscores the significance of addressing nutritional deficiencies and monitoring iron status in obese populations, suggesting potential associations between obesity and iron metabolism. Further research is needed to explore these relationships for clinical management implications.

A global event such as the COVID-19 crisis presents new, often unexpected responses that are fascinating to investigate from both, scientific and social standpoints. Despite several documented similarities, the Coronavirus pandemic is clearly distinct from the 1918 flu pandemic in terms of our exponentially increased, almost instantaneous ability to access/share information, offering an unprecedented opportunity to visualise rippling effects of global events across space and time. Personal devices provide “big data” on people’s movement, the environment and economic trends, while access to the unprecedented flurry in scientific publications and media posts provides a measure of the response of the educated world to the crisis. Most bibliometric (co-authorship, co-citation, or bibliographic coupling) analyses ignore the time dimension, but COVID-19 has made it possible to perform a detailed temporal investigation into the pandemic. Here, we report a comprehensive network analysis based on more than 20000 published documents on viral epidemics, authored by over 75,000 individuals from 140 nations in the past one year of the crisis. In contrast to the 1918 flu pandemic, access to published data over the past two decades enabled a comparison of publishing trends between the ongoing COVID-19 pandemic and those of the 2003 SARS epidemic, to study changes in thematic foci and societal pressures dictating research over the course of a crisis.

Non-Vitamin K Oral Anticoagulants (NOACs) have revolutionized anticoagulant therapy, offering improved safety and efficacy over traditional agents like warfarin. This review comprehensively examines the dual roles of NOACs—Apixaban, Rivaroxaban, Edoxaban, and Dabigatran—not only as anticoagulants but also as modulators of inflammation via Protease-Activated Receptor (PAR) signaling. We highlight the unique pharmacotherapeutic properties of each NOAC, supported by key clinical trials demonstrating their effectiveness in preventing thromboembolic events. Beyond their established anticoagulant roles, emerging research suggests that NOACs influence inflammation through PAR signaling pathways, implicating factors such as FXa and Thrombin in the modulation of inflammatory responses. This review synthesizes current evidence on the anti-inflammatory potential of NOACs, exploring their impact on inflammatory markers and conditions like atherosclerosis and diabetes. By delineating the mechanisms by which NOACs mediate anti-inflammatory effects, this work aims to expand their therapeutic utility, offering new perspectives for managing inflammatory diseases. Our findings underscore the broader clinical implications of NOACs, advocating for their consideration in therapeutic strategies aimed at addressing inflammation-related pathologies. This comprehensive synthesis not only enhances understanding of NOACs' multifaceted roles but also paves the way for future research and clinical applications in inflammation and cardiovascular health

The Photovoltaic modules are usually installed on the ground which exposes it to surface deposition of foreign particles. In the Middle East and North Africa region, the primary culprit is dust and sand. They form an insulating and opaque layer on the surface of the glass, which obstructs its heat transfer and optical properties, thereby reducing the overall yield efficiency of the solar panel. Cleaning of this layer is critical to the operation of the solar panel and often requires great effort and energy on a large-scale solar array. In this paper, we propose a novel self-cleaning mechanism for solar panels, with an understanding of the structural integrity of the Photovoltaic laminate and application of external mechanical vibration. By applying an external source of vibration, the solar panels vibrate, excites its fundamental frequencies and cleans by its own. The method is analyzed using finite element analysis method and tested using experiments. Our simulation results based on IEC 61215 show that the maximum principal stress and deformation in the critical layers is within limits. Our experimental results prove the proposed theory is feasible and can be extended to large scale solar arrays. Our proposed method is retrofittable and could save money, energy and effort in cleaning the solar arrays, which can replace current techniques.

3D-printing with foam concrete, which is known for its distinct physical and mechanical properties, has not yet been purposefully investigated. The article at hand presents a methodological approach for the mixture design of 3D-printable foam concretes and a systematic investigation of the potential application of this type of material in digital construction. Three different foam concrete compositions with water-to-binder ratios between 0.33 and 0.36 and having densities of 1100 to 1580 kg/m³ in the fresh state were produced with a pre-foaming technique using a protein-based foaming agent. Based on the fresh-state tests, including 3D-printing as such, an optimum composition was identified and its compressive and flexural strengths were characterised. The printable foam concrete showed compressive strength above 10 MPa and low thermal conductivity, which make it suitable for 3D-printing applications, while fulfilling both load-carrying and insulating functions.

One of the major limitations of the current 3D-concrete-printing technology is incorporation of reinforcement. Furthermore, there is a need to decrease the ecological footprint of printable concrete. As a possible solution for these challenges, this paper presents a 3D-printable strain-hardening geopolymer composite (3DP-SHGC) that shows pseudo-ductile behaviour under direct tension. The developed 3DP-SHGC is composed of one-part (just-add-water) geopolymer binder made of slag (GGBFS), fly ash (FA) and solid activator. The one-part geopolymer binder eliminates the need for elevated temperature curing and handling of corrosive alkaline liquids. At first, an optimum matrix was identified by studying the effects of FA to GGBFS ratio on the rheological properties and compressive strength. Subsequently the optimum matrix was reinforced by PVA fibres to make the 3DP-SHGC, which printing performance and rheological properties were evaluated. In addition, the influences of curing temperature on the compressive, flexural and tensile performances of the printed specimens were also investigated. The results were compared with those obtained for the mould-cast specimens. The 3DP-SHGC exhibited superior flexural performance, higher tensile strength, and comparable tensile strain capacity to the mould-cast counterpart. Further, the curing temperature had influence on the mechanical properties of both 3D-printed and mould-cast SHGCs. The underlying reasons for the differences are discussed.

The world has been evolving with new technologies and advances day-by-day. With the advent of various learning technologies in every field, the research community is able to provide solution in every aspect of life with the applications of Artificial Intelligence, Machine Learning, Deep Learning, Computer Vision, etc. However, with such high achievements, it is found to lag behind the ability to provide explanation against its prediction. The current situation is such that these modern technologies are able to predict and decide upon various cases more accurately and speedily than a human, but failed to provide an answer when the question of why to trust its prediction is put forward. In order to attain a deeper understanding into this rising trend, we explore a very recent and talked-about novel contribution which provides rich insight on a prediction being made -- ``Explainability.'' The main premise of this survey is to provide an overview for researches explored in the domain and obtain an idea of the current scenario along with the advancements published to-date in this field. This survey is intended to provide a comprehensive background of the broad spectrum of Explainability.

Chaotic switching is a newly evolve randomization method which can suppress conducted electromagnetic interference generated within the DC-DC converter. It can suppress the spectral peaks present in the frequency band effectively by spread spectrum technique and can spread it over the wide range of frequency band implying EMI suppression. In this paper, a chaotic PWM technique based on RCFMFD scheme is generated through Field programmable gate array (FPGA) for suppressing the conducted electromagnetic interference (EMI) generated within the Luo converter. A hardware prototype of Luo converter was developed in order to analyze EMI reduction through FFT analysis by comparing both traditional periodic PWM switching and chaotic PWM switching. The results obtained from the hardware setup shows significant reduction of EMI with Chaotic switching as compared to traditional PWM switching for both boost and buck operation of Luo converter.

The effect of climate change plays a significant role on groundwater level variations and crop yield. The change in climate leading to increased temperatures, decreased rainfalls and extreme drought conditions ultimately cause low groundwater level and crop yield. Judicious groundwater management technology viz., water recharge options, need based irrigation, crop selection, must be adapted for further increasing the water table level in soil ecosystem. Additionally, climate change impacts combined with changes in agricultural water use can affect groundwater dynamics. Increased irrigation demand and decreased summer precipitation can lower groundwater levels, impacting crop production. Overall, climate change affects both groundwater resources and crop yield highlighting the need for sustainable water management practices and consideration of soil properties in agricultural modelling. The authors carefully selected relevant research articles addressing the impact of climate change on ground water level in Asian countries. The review highlights the use of machine learning method to ground water level and crop yield modelling. According to the study, machine learning techniques have made significant contributions to predicting groundwater level changes and crop yield with higher accuracies, high performance and less running time.

It has been suggested that primordial planets could have formed in the early Universe and the missing baryons in the Universe could be explained by primordial free-floating planets of solid hydrogen. Many such planets were recently discovered around the old and metal poor stars and such planets could have formed at early epochs. Another possibility for missing baryons in the Universe could be that these baryons are admixed with DM particles inside the primordial planets. Here we discuss the possibility of admixture of baryons to the DM primordial planets discussed earlier. We consider gravitationally bound DM objects with the DM particles constituting them varying in mass from 20 to100GeV. Different fractions of DM particles mixed with baryonic matter in forming the primordial planets are discussed. For the different mass range of DM particles forming DM planets, we have estimated the radius and density of these planets with different fractions of DM and baryonic particles. It is found that for heavier mass DM particles with the admixture of certain fractions of baryonic particles, the mass of the planet increases and can reach or even substantially exceed Jupiter-mass. The energy released during the process of merger of such primordial planets is discussed. Also the energy required for the tidal breakup of such an object in the vicinity of a black hole is also discussed.

We interviewed 48 people including local communities, ex hunters and protected area management professionals. The purpose of the interviews was to understand the motivations for, and the nature of, illegal hunting of prey species of iconic predators - tigers and leopards - in the northern section of Bardia National Park. Participants reported that hunting of prey species occurs mostly in spring and autumn and is less common during the summer. In the past, hunting was primarily for the purposes of obtaining meat for household consumption. Since the introduction of a road network in the region, opportunities to sell wild meat at ad-hoc ‘highway markets’ have developed. The purported medicinal properties of wild meat was also cited as a driver for illegal hunting. Mostly, locally hand-made guns are used for hunting and the use of dogs in hunting was often reported. Protected area managers informed that illegal hunting problems in the study area are associated with a lack of presence of park authorities, remoteness and underdevelopment and poverty of the community. Our study suggested that skills development training for local community members might reduce dependency on wild meat for household consumption and earning thereby reducing illegal hunting.

In the paper, the authors generalize the notion "k-Mittag-Leffler function'', establish some integral transforms of the generalized k-Mittag-Leffler function, and derive several special and known conclusions in terms of the generalized Wright function and the generalized k-Wright function.

Lack of reliable information on PTC industry in Sri Lanka is hampering the advancement of the technology. Hence, this study attempted to assess the current status of PTC industry in Sri Lanka in order to ascertain the type and the level of interventions needed to broaden the horizons of the industry. Data of last 05 years were collected through qualitative research methods including a questionnaire-based survey, personal interviews, etc. and personal interviews to identify product diversity, R&D, available facilities, production capacity, and markets. Information was analyzed qualitatively using descriptive statistical software to assess the current status, and identify gaps, challenges and opportunities. COVID pandemic and the economic crisis had a heavy toll on the PTC industry. Six major challenges experienced by business owners were identified as increasing capacity, opportunities to build market linkages, demand fluctuations, issues relating to awareness and insufficient support given by the government. Proper identification and screening of mother plants, determining the production capacities and marketing, knowledgeable and skilled human resources, were identified as important contributory factors for success. Development strategies identified mainly include instinctive decision making and government support. Embracing the significant trade achievements through resource reallocation, prioritization and improvisation processes at individual, family group, inter-organizational levels and across these levels need to be regulated through a responsible authority. These interpretations and recommendations of this research can be utilized both by the policy makers and public and private sector organizations for decision making purposes targeting commercial scale advancements.

Diabetes mellitus, a metabolic disorder that is persistent in nature, is identified by an elevated concentration of glucose in the bloodstream. The disease has become a major public health problem, affecting millions of people globally, and is associated with significant morbidity and mortality. The increasing prevalence of diabetes and the lack of effective therapeutic interventions have led to the exploration of alternative and complementary forms of therapy, including ethnomedicine. Ethnomedicine is the study of traditional medical systems and the medicinal plants used by Indigenous communities. In other words, Ethnomedicine refers to the traditional medical practices and beliefs of a particular cultural or ethnic group. The most popular example of traditional medicine is the use of Aloe vera for the treatment of various diseases such as sunburn, cuts, burns, hypertension, diabetes, and jaundice for thousands of years [1]. In recent years, there has been increasing interest in the potential role of ethnomedicine in the management of diabetes, given its widespread use in many communities and its potential to offer cost-effective and culturally acceptable treatment options. It encompasses a range of traditional healing practices, including herbalism, acupuncture, and massage therapy. Despite the inconsistencies, there is growing evidence to suggest that certain ethnomedical practices may be effective in the management of diabetes [2,3]. For example, several studies have shown that certain herbal remedies, such as cinnamon, ginseng, and bitter melon, may have potential benefits in terms of improving glucose control and reducing the risk of complications associated with diabetes. Evidence-based ethnomedicine is an approach that applies scientific principles and methods to evaluate the efficacy and safety of traditional medical practices. This approach is crucial in the development of effective and safe ways to treat diabetes. To date, there have been numerous studies conducted to examine the efficacy and safety of various ethnomedical interventions for diabetes, including herbal remedies, dietary changes, and physical activity [4]. However, it is important to note that not all ethnomedical interventions for diabetes have been thoroughly evaluated, and many remain unproven. Furthermore, some interventions may be associated with significant risks, particularly in terms of drug interactions and adverse effects. As such, it is crucial that any ethnomedical interventions for diabetes be carefully evaluated using rigorous scientific methods and that patients be advised to consult with their healthcare provider before using any such interventions. It is important to note that the results of these studies have been mixed, with some showing promising results, while others have failed to demonstrate significant benefits. In this chapter, the evidence-based current state of ethnomedicine for diabetes was reviewed. We first provide an overview of diabetes and its pathophysiology, followed by a discussion of traditional medicinal practices used to treat the disease. We then present a systematic review of the scientific literature on the use of ethnomedicine for diabetes, focusing on herbal remedies and dietary interventions. Our review found that several medicinal plants offered promising results to treat all types of diabetes. For example, Gymnema sylvestre, a traditional Indian herb, has been shown to reduce blood glucose levels and improve insulin sensitivity [5]. Additionally, the use of bitter melon (Momordica charantia) has been shown to reduce fasting blood glucose levels and improve glucose tolerance in individuals with type 2 diabetes [6]. Another important aspect of ethnomedicine for diabetes is the use of dietary interventions [7]. Traditional diets, such as the Mediterranean diet, have been shown to have beneficial particularly in terms of improving glycaemic control, reducing the risk of cardiovascular disease, and insulin sensitivity [8]. Additionally, the use of low-carbohydrate diets, such as the ketogenic diet, has been shown to improve glycaemic control in individuals with type 2 diabetes [9]. Traditional medicine has a long history of treating the symptoms and managing the condition. However, the efficacy and safety of these traditional practices have not always been scientifically tested, and there is a lack of standardization and regulation in the production and use of traditional remedies for diabetes. This creates a challenge for healthcare providers and patients, who need to ensure that the treatments they use are safe and effective. Additionally, there is a need for further research to understand the mechanisms by which traditional remedies may be effective in managing diabetes and to determine the optimal dosage and administration methods [9]. Finally, it is also important to understand that the use of traditional remedies may interact with conventional medications, leading to adverse effects; for example, the use of Chinese traditional medicine, known as “herb ginseng,” for the treatment of various health conditions, including diabetes sometimes cause the side effect such as dizziness, confusion, and fainting while interacting with the anti-diabetic medications [10]. Therefore, it is important to approach the use of ethnomedicine for diabetes with caution and under the guidance of a qualified healthcare professional. In conclusion, evidence-based ethnomedicine offers a promising approach to the treatment of diabetes. While further research is needed to fully understand the mechanisms and safety of these interventions, the results to date suggest that traditional remedies and dietary interventions have the potential to be effective in the management of this disease. However, it is important to approach the use of ethnomedicine for diabetes with caution and under the guidance of a qualified healthcare professional and to continue to conduct rigorous scientific research to fully understand the benefits and risks associated with these interventions.

There are many medicinal plants that have various medicinal properties in their different parts. The medicinal plants are major backbone of pharmaceutical industries. In this article we compare the antioxidants properties from various plants parts (root, stem, leaf, flower and bark) of the most important medicinal plant, Justicia adhatoda L. Various plant parts showed the good amount of antioxidant properties. These results enhance the medicinal properties of this plant due to the presence of good amount of antioxidants; among all the plant parts leaves and flowers showed maximum natural antioxidants, hence the study could be saying that this plant has good efficacy of antioxidants.

MicroRNAs are used as biomarkers for classification of cancer subtypes since certain miRNAs are differentially expressed in normal and patient samples. Moreover, miRNAs target mRNAs and can heavily influence Gene Expressions. Thus, deregulation of miRNAs is linked to various disorders. Thus, miRNAs can be used for prognosis and developing personalized health solutions for patients. Given the importance of miRNAs, there has been substantial work done in the field. In this paper, recent works in the field of using miRNAs expressions of patients were considered. A total of 20 papers were surveyed which utilized feature selection ensembles, fuzzy logic as well as deep learning. 10 papers have been reported which offer insight into how miRNAs can be utilized for subtype-specific or generalized cancer diagnosis.

Globally, open-pit coal mining is associated with severe land use impact and contamination of soil and water resources with heavy metals. Thus, in growing economies like India, where coal is a significant energy source, the heavy metals contamination of soil and water become ubiquitous. Remediation of such a large stretch of mined-out land is a major challenge and a costly process for the mining industry. In recent years, the application of biochar for the remediation of such heavy metals-contaminated soil has been widely practiced. However, applying biochar and cultivating plants in field conditions becomes challenging. This study uses a unique remediation approach by developing biochar-bentonite-based seed balls encapsulating Shorgham grass seeds at their core for application in the contaminated soil. The seed ball was developed by using the bentonite biochar composite in varying weight fractions of 0.5 – 5 % with respect to the kaolinite, whose fractions in the seed ball also varied at one, three, and five parts. The seed balls were applied to the pots containing 3 kg of heavy metals contaminated soil for a pot-culture study in a polyhouse for a period of four months. Initial soil analysis results indicated that the mine soil samples showed poor nutrient and organic matter content and were contaminated with heavy metals such as Ni, Zn, Cr, and Cd. Post-pot-culture soil analysis results indicated that the application of seed balls containing five fractions of biochar composite with its combination with three and five-weight fractions of kaolinite showed substantial improvement in the pH, available nutrients, organic matter content, soil enzymes, and overall soil fertility index compared to the controlled study and other cases. The same combination of seed balls also significantly reduced the plant-available fractions of Ni, Zn, Cr, and Cd in the soil and the translocation of these heavy metals from the rhizosphere zone to the grass’s aerial parts, indicating stabilization of heavy metals within the soil matrix. Moreover, the application of seed balls also substantially improved the plant physiology and reduced the release of stress hormones such as proline and glutathione within the plant cells indicating improvement in the plant’s biotic and abiotic stress factors. Thus, the application of seed balls in heavy metals contaminated soils, particularly over a large stretch of land, could be a low-cost and viable remediation technique.

This paper will explore analogs of groups formed by the transformations of two ropes as presented by Minh-Tam Quang Trinh.1 The two operations acting on these ropes are T and S, defined as twists and clockwise turns, respectively. These actions intertwine the ropes, creating tangles. T and S also have the ability to untangle the rope when used in certain combinations. In the two-rope case, these actions expressed as a group presentation were shown to be isomorphic to SL₂(Z). We explored the analog of these opera- tions, T and S, and conjectured the corresponding group to which they are isomorphic. Partial proofs for this conjecture are included and future work would include proving our conjecture as well as generalizing results to k ropes.

Unlike animals, persistent dynamic environmental perturbations threaten plants, as they are sessile. Plants keep an inbuilt database of all epigenetic episodes during their lifetime. Present knowledge for exploiting information about how the gene network of plants contributes to epigenetic memory needs to be improved, and extensive in-depth studies are needed. Data from epigenetic memories imparts intelligent behaviour to plants, and these memories can be decoded further to investigate how these plants respond when the same abiotic stress recurs. The epigenetic phenomenon refers to gene expression patterns, including vital factors such as nucleic acids (small ribonucleic acids), histones modelling and methylation of DNA. These changes are cell cycle-associated events that may be transmitted to successive generations. Epigenetic memories due to abiotic stress are necessary for maintaining healthy ecophysiological behaviour of plants and impart the tendency to resist and adapt to challenging environmental conditions. These intelligent memories can be stored and interpreted to prepare for future challenges.

In the last few decades, the dynamics of tumor cells and their growths are presented via clinical, experimental, and theoretical approaches, which leads to the development of the new idea of multiple cancer therapies to control and reduce the death rate for earlier detection. In this paper, we discussed the dynamics of tumor cell growth and its treatment process. We analyzed some simple mathematical models and generalized the study to understand the growth of tumor cells. The main proposed model is a system of ordinary differential equations which combines interactions among natural killer cells, dendritic cells and cytotoxic CD8+ T cells. The model is solved numerically to explain how the tumor cells spread and become more dangerous as well as the treatment process of cancer. It is also studied that how the cell behaves in the presence of different therapy and drugs. The optimal control of chemotherapy has been discussed. It has also been explained how much the model is effective in reducing tumor cells over time. Finally, a couple of spatially distributed models are discussed for tumor cell growth.

Severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2/2019-nCoV) infection is an emerging pandemic. The virus binds to angiotensin converting enzyme 2 (ACE2) and TMPRSS2 which are abundantly expressed on various human cells including lung epithelial cells and intestinal cells and the virus can infect these cells. Currently no specific treatments or vaccines are available for this disease. A per oral live attenuated vaccine can be beneficial in SARS-Cov-2 infection because the attenuated virus initially infects the gut, stimulates the mucosa associated immune system sparing the respiratory system during the initial immune response. The live virus can also spread in the community boosting herd immunity.

This study empirically investigates the complex interplay between the severity of the coronavirus pandemic, mobility changes in retail and recreation, transit stations, workplaces, and residential areas, and lockdown measures in 88 countries of the word. To conduct the study, data on mobility patterns, socioeconomic and demographic characteristics of people, lockdown measures, and coronavirus pandemic were collected from multiple sources (e.g., Google, UNDP, UN, BBC, Oxford University, Worldometer). A Structural Equation Modeling (SEM) technique is used to investigate the direct and indirect effects of independent variables on dependent variables considering the intervening effects of mediators. Results show that lockdown measures have significant effects to encourage people to maintain social distancing. However, pandemic severity and socioeconomic and institutional factors have limited effects to sustain social distancing practice. The results also explain that socioeconomic and institutional factors of urbanity and modernity have significant effects on pandemic severity. Countries with a higher number of elderly people, employment in the service sector, and higher globalization trend are the worst victims of the coronavirus pandemic (e.g., USA, UK, Italy, and Spain). Social distancing measures are reasonably effective at tempering the severity of the pandemic.

:Peat substrate is made from peat from drained peatlands, which is a limited resource. A realistic estimate is that 50% of the world’s wetlands have been lost. Peat is used in horticulture, especially for the cultivation of vegetables in greenhouses. The consequences of peatland exploitation are an in-crease in the greenhouse effect and a decrease in carbon stocks. Wood fiber can be used as an al-ternative to peat. The chemical properties of the growing media interact and change continuously due to the small volume of the growing media, which is limited by the growing container. This study aims to gain new knowledge on the impact of nutrient changes in the microbial degradation of carbon compounds in wood fiber and mixtures with peat substrate on the content and uptake of nutrients required by plants. Cucumbers (Cucumis sativus L.) variety “Dirigent H” developed in the Netherlands, were cultivated in growing media of peat substrate and wood fiber: (1) peat substrate (PS); (2) wood fiber (WF); (3) wood fiber and peat substrate 50/50 v/v (WF/PS 50/50); (4) wood fiber and peat substrate 25/75 v/v (WF/PS 25/75). The rates of fertilization were the following: (1) con-ventional fertilization (CF); (2) N13; (3) N23; (4) N30. The experiment was carried out in three repli-cations. As the amount of wood fiber increased, the humidity and pH of the growing medium in-creased. Fertilization of cucumbers with different rates of nitrogen influenced the nutrient uptake. Plants grown in 50/50 and 25/75 growing media had the best Cu uptake when fertilized with N23. When the plants grown in the wood fiber media and the 50/50 media were fertilized with N13, N23, and N30, the Mn content in the growing media at the end of the growing season was significantly lower than the Mn content in the media with conventional fertilization. Thus, nitrogen improved the uptake of Mn by plants grown not only in the wood fiber but also in combinations with peat sub-strate. Growing plants in wood fiber and fertilizing them with N13 can result in optimum uptake of micronutrients. The number and mass of cucumber fruits per plant were influenced by the amount of wood fiber in the growing media and the application of nitrogen fertilizer. The highest number of fruits and mass of fruits per plant was obtained significantly higher when cucumbers were grown on WF/PS 50/50 growing media with additional N13 fertilization.

: Greenhouse plants are usually grown in containers filled with growing media. Peat is the main component of the growing media used in greenhouses. However, peat substrate is made from peat from drained peatlands, which is a limited resource. Wood fiber can be an alternative to use as a growing media for controlled-climate crops. The chemical properties of the growing media interact and change continuously due to the small volume of the growing media, which is limited by the vegetative container. Therefore, this study aims to gain new knowledge on the impact of nutrient changes in the microbial degradation of carbon compounds in wood fiber and mixtures with peat substrate on the content and uptake of nutrients required by plants. Cucumbers (Cucumis sativus L.) were cultivated in growing media of peat substrate and wood fiber: (1) peat substrate (PS); (2) wood fiber (WF); (3) wood fiber and peat substrate 50/50 v/v (WF/PS 50/50); (4) wood fiber and peat substrate 25/75 v/v (WF/PS 25/75). The rates of fertilization were the following: (1) conventional fertilization (CF); (2) N13; (3) N23; (4) N30. Fertilization of cucumbers with different rates of nitrogen influenced the nutrient uptake. Plants grown in WF/PS 50/50 and WF/PS 25/75 growing media had the best Cu uptake when fertilized with N23. When the plants grown in the wood fiber media and the 50/50 media were fertilized with N13, N23, and N30, the Mn content in the growing media at the end of the growing season was significantly lower than the Mn content in the media with conventional fertilization. Thus, nitrogen improved the uptake of Mn by plants grown not only in the wood fiber but also in combinations with peat substrate. Growing plants in wood fiber and fertilizing them with N13 can result in optimum uptake of micronutrients. The number and mass of cucumber fruits per plant were influenced by the amount of wood fiber in the growing media and the application of nitrogen fertilizer. The highest number of fruits and mass of fruits per plant was obtained significantly higher when cucumbers were grown on WF/PS 50/50 growing media with additional N13 fertilization.

The KcsA is a prokaryotic potassium-oriented channel, which is sourced from the Streptomyces lividans soil bacteria. From extensive studies that have been carried over the KcsA potassium channel, it has been proved that various factors enable the gating and shuttling of the potassium ions into and out of the cells. Some of the factors include the different concentration of protons in the inside and outside membrane. The other factor is the existence of the selectivity filter equipped in the exit of channel pore, which enables the movement of the K⁺ ions. Not only are potassium ions present in the channel but also sodium ions. Potassium and sodium ions are the ions that are essential in the conductivity of a cell because of their charge. An intuitive idea about why K⁺ ions are at least 10,000 times more permeant than Na⁺ ions is presented in various entities. The hypothesis is that the selectivity ratio is probably related to the successive entry of Na⁺ ions, based on the premise that the ratio seems to be relevant to unpredictable quantities caused by Brownian corrosion of ions.

Schizophrenia is a spectrum of neuropsychiatric deformities, characterized by hallucination, delusion, mood disorders, speech pathology, and neurocognitive deficits. Among various clinical manifestations, hallucination has been recognized as a core psychotic symptom that occurs more frequently in schizophrenia. A significant number of subjects with neurocognitive disorders like Alzheimer’s disease (AD), Parkinson’s disease (PD), Huntington’s disease (HD), and other neurological diseases like stroke and epileptic seizure also experience hallucinations. While aberrant neurotransmission has been linked to the neuropathogenic events of schizophrenia, the specific cellular mechanism contributing to hallucinations remains ambiguous. Neurodegeneration in the hippocampus of the brain has been identified as a predominant pathogenic determinant of dementia. While the scientific proof for the neurodegeneration in schizophrenia is limited, the occurrence of dementia in schizophrenia has become increasingly evident. To note, both neurodegenerative, neurodevelopmental, and neuropsychiatric disorders display impaired neurogenesis in the brain. Impaired neurogenesis in the hippocampus has been linked to dementia and mood disorders. Notably, the early phase of many neurodegenerative disorders has been characterized by reactive neuroblostosis and aberrant cell cycle activation in mature neurons leading to the fluctuation in neurogenic processes leading to abnormal synaptogenesis and neurotransmission in the brain. Thus, this article emphasizes a hypothesis that aberrant neurogenic processes could be an underlying mechanism of hallucination in schizophrenia and other neurological diseases.

Though there have been works highlighting the advantages and disadvantages of online learning, no study focused on university-level economics students. None of the studies explored students' opinions about improving the quality and effectiveness of online classes. Many used questionable samples, closed-ended questions, and all those researches were carried out at the beginning of online classes. In this paper, we overcome these limitations of earlier studies. Using a convenience sampling technique and open-ended questions, we collect data from 154 university-level economics students after being exposed to the online class for a year. Some advantages of online classes are: students can do classes from home without being exposed to health risks, easily accessible, flexible class schedule, students remained connected with the study, it saves costs, reduce the likelihood of semester loss, easy to understand, less stressful, and learning new technologies. Major problems from students' perspectives include network problems, difficulties in understanding the topic, unsuitable for mathematical courses, concentration problem, class not interactive, financial constraint, adverse health impacts, device issues, power outages, unfamiliarity with digital technology, internet problem, and unfixed class-schedule. Disadvantages outnumbered advantages. Students made several suggestions to improve the quality and effectiveness of online classes. Some of the vital suggestions are: using state-of-the-art digital tools, recording and uploading lectures, resolving internet issues, holding classes regularly, higher efforts to make the topics easier, resolving network issues, lowering class duration, institutional support, implementing a fixed class schedule, and introducing online evaluation system.

Abstract The aim of the present review is to discuss the roles of vitamin K and vitamin K-dependent proteins, and the combined action of the vitamins K and D, for maintenance of bone health. The most relevant vitamin K-dependent proteins in this respect are osteocalcin and matrix Gla-protein (MGP). When carboxylated these proteins appear to have the ability to chelate and import calcium from the blood to the bone, thereby reducing the risk of osteoporosis. Carboxylated osteocalcin appears to contribute directly to bone quality and strength. Adequate vitamin K status is required for carboxylation of MGP and osteocalcin. In addition, vitamin K acts on bone metabolism by other mechanism, such as a ligand for the nuclear steroid and xenobiotic receptor (SXR). In this narrative review, we examine the evidence for increased bone mineralization through dietary adequacy of vitamin K (phylloquinone or menaquinone). Summarizing the evidence for a synergistic effect of vitamin K and vitamin D3 we find that an adequate supply of vitamin K on top of an optimal vitamin D status seems to add to the benefit for maintaining bone health. More research related to synergism and possible mechanisms of vitamins D3 and K interaction in bone health is needed.

The harrowing second wave of COVID-19 in India has led to much discussion over the quality and timeliness of reporting of deaths attributed to the pandemic. In this brief report, we aim to present the existing evidence, as well as the broader complexities surrounding the mortality burden of COVID-19 in India. This article sheds light on the following epidemiological issues: (1) general and India-specific challenges to COVID-19 death reporting, (2) latest COVID-19 mortality estimates in India as of May 16, 2021, (3) the apparent scale of uncaptured COVID-19 deaths, and (4) the role of disaggregated historic mortality trends in quantification of excess deaths attributed to COVID-19. We conclude with a set of high-level policy recommendations for improving the vital surveillance system and tracking of causes of death in India. We encourage direct efforts to integrate health data and indirect strategies for cross-validation of registered deaths. Such system-wide advances would drastically aid epidemiological research efforts and strengthen India’s position to overcome future public health crises.

The $k$-means problem is to compute a set of $k$ centers (points) that minimizes the sum of squared distances to a given set of $n$ points in a metric space. Arguably, the most common algorithm to solve it is $k$-means++ which is easy to implement, and provides a provably small approximation factor in time that is linear in $n$. We generalize $k$-means++ to support: (i) non-metric spaces and any pseudo-distance function. In particular, it supports M-estimators functions that handle outliers, e.g. where the distance $\mathrm{dist}(p,x)$ between a pair of points is replaced by $\min {\mathrm{dist}(p,x),1}$. (ii) $k$-means clustering with $m\geq 1$ outliers, i.e., where the $m$ farthest points from the $k$ centers are excluded from the total sum of distances. This is the first algorithm whose running time is linear in $n$ and polynomial in $k$ and $m$.

Sudden cardiac arrest (SAC) is a leading cause of mortality. In recent years, though, many lives have been saved through the use of defibrillators by random bystanders. As a result, defibrillators have been popping up in various locations. In this work we propose a state mandate demanding the presence of a defibrillator at every pharmacy store and argue that it could greatly enhance and augment the impact of the defibrillator network. We support our claim via detailed calculations of the immediate (a defibrillator readily available) and partial (a defibrillator available at a reasonable distance) population coverage achievable by the implementation of our proposal, taking the Argolis area in Peloponnese Greece as a case study. Our findings indicate that, in addition to other benefits, the use of pharmacies to establish a defibrillator network could bring an eight-fold increase in the immediate population coverage of defibrillators and would provide immediate / partial access to a defibrillator to 18 / 24 incidents of SCA per year that would otherwise lead to death, potentially leading to the saving of numerous lives. Alternative scenaria are also discussed.

Due to its high specific surface area and rich porous structure, acacia-derived porous activated carbon is the most potentially effective material for wastewater treatment. This research study aimed to prepare activated carbon using Acacia erioloba seedpods as carbonaceous materials and phosphoric acid as an activating agent. The specific surface area of the prepared activated carbon sample was characterised by Brunauer–Emmett–Teller instrument. The specific surface area value was 387 m²/g. The activated carbon prepared was then sieved into three different particle sizes of 50, 100 and 200 micrometres and characterised using various analytical procedures, including proximate analysis to study moisture content, ash content, volatile matter content and fixed carbon content. The bulk density, SEM, power of hydrogen, iodine number and methylene blue number index were also investigated to determine the adsorption properties of the prepared activated carbon. Batch adsorption dynamics for the removal of organic compounds such as methylene blue and unsaturated character of fatty acid from aqueous solution were also carried out at room temperature to evaluate the prepared activated carbon's applicability in water treatment. The iodine number was 528, 638, and 554 mg/g for the 50, 100, and 200 μm activated carbon particles, respectively. From the results, the adsorption of methylene blue favoured the Freundlich adsorption model, showing higher correlation (R²) values than the Langmuir model. The results indicate that methylene blue particles were adsorbed on heterogeneous surfaces.

Atherosclerosis is a leading cause of cardiovascular disease and mortality worldwide. Alterations in the gut microbiota composition, known as gut dysbiosis, have been shown to contribute to atherosclerotic cardiovascular disease (ACVD) development through several pathways. Disruptions in gut homeostasis are associated with activation of immune processes and systemic inflammation. The gut microbiota produces several metabolic products, namely trimethylamine (TMA), which is used to produce the proatherogenic metabolite trimethylamine-N-oxide (TMAO). Short chain fatty acids (SCFAs), including acetate, butyrate, and propionate, and certain bile acids (BAs) produced by the gut microbiota lead to inflammation resolution and decrease atherogenesis. Chronic low-grade inflammation is associated to common risk factors for atherosclerosis, including metabolic syndrome, type 2 diabetes mellitus (T2DM), and obesity. Novel strategies for reducing ACVD include the use of nutraceuticals such as resveratrol, modification of glucagon-like peptide 1 (GLP-1) levels, supplementation with probiotics, and administration of prebiotic SCFAs and BAs. Investigation into the relationship between the gut microbiota and its metabolites, and the host immune system could reveal promising insight into ACVD development, prognostic factors, and treatments.

Increased severity of droughts, due to anthropogenic activities and global warming has imposed a severe threat on agricultural productivity ever before. This has further advanced the need for some eco-friendly approaches to ensure global food security. In this regard, application of plant growth-promoting rhizobacteria (PGPR) can be beneficial. PGPR through various mechanisms viz. osmotic adjustments, increased antioxidant, phytohormone production, regulating stomatal conductivity, increased nutrient uptake, releasing Volatile organic compounds (VOCs), and Exo-polysaccharide (EPS) production, etc not only ensures the plant’s survival during drought but also augment its growth. This review, extensively discusses the various mechanisms of PGPR in drought stress tolerance. We have also summarized the recent molecular and omics-based approaches for elucidating the role of drought responsive genes. The manuscript presents an in-depth mechanistic approach to combat the drought stress and also deals with designing PGPR based bioinoculants. Lastly, we present a possible sequence of steps for increasing the success rate of bioinoculants.

We review time expansion wave theory and refine our model showing it to accurately match observed cosmological luminosity data. The theory augments general relativity to create a container within which quantum effects can be explained by treating time as an artefact of a fourth spatial dimension that we observe as the expansion of the universe. This leads us to explain mass creation, the speed of light limit, gravity, black holes without singularities and other macroscopic effects. Our model leads to an expansion velocity of 6.87 0.36 × 106 ms-1, which results in a Hubble expansion rate constant of 71.3 3.7 km/s/Mpc. Because of the finite window of time in which we exist, an extra a degree of freedom is available leading to interesting interpretations at the subatomic level. At this size range, then a spin is allowed within the time dimension explaining why wave particle duality occurs and explains the electromagnetic force and other quantum mechanical properties. It provides a solution to the double slit conundrum and can explain how quantum entangled partners can behave in a quantum way and pass seemingly time-defying information. The potential quantitative origin of the fine structure constant which governs the size of the electromagnetic force is also strongly indicated by this theory.

Gilbert Syndrome, is a benign condition characterized by persistent indirect hyperbilirubinemia due to reduced UDP-glucuronyltransferase enzyme activity. Its coexistence with other clinical disorders has important clinical and pharmacological implications. GS is known to coexist with many hemolytic conditions and may lead to diagnostic difficulty and also increased incidence of gallstones. UGT1A1 gene has been shown to be involved in the conjugation of various physiologically important endogenous and exogenous compounds, so individuals with Gilbert mutation (the variant allele UGT1A1*28) have an increased risk of toxicity of various drugs and endogenous compounds like irinotecan, steroid hormones, implicated in various human carcinoma like colorectal and breast carcinoma. Deferiprone (DFP) is an orally available chelator used in the management of iron overload in patients with Transfusion Dependent Thalassemia (TDT). In this study, fifteen out of 275 patients with TDT, had a deferiprone-induced joint deformity. Among these fifteen patients with joint deformity, eleven patients (four patients were homozygous for TA 7 repeats and seven were heterozygous for TA7 repeats) had associated gilbert mutation. Therefore, we hypothesize that patients of TDT who had underlying Gilbert mutation might have decreased enzymatic activity of UGTIA6, which metabolizes the DFP, leading to more prominent adverse effects related to DFP.

Nearest-neighbour clustering is a simple yet powerful machine learning algorithm that finds natural application in the decoding of signals in classical optical-fibre communication systems. Quantum k-means clustering promises a speed-up over the classical k-means algorithm; however, it has been shown to currently not provide this speed-up for decoding optical-fibre signals due to the embedding of classical data, which introduces inaccuracies and slowdowns. Although still not achieving an exponential speed-up for NISQ implementations, this work proposes the generalised inverse stereographic projection as an improved embedding into the Bloch sphere for quantum distance estimation in k-nearest-neighbour clustering, which allows us to get closer to the classical performance. We also use the generalised inverse stereographic projection to develop an analogous classical clustering algorithm and benchmark its accuracy, runtime and convergence for decoding real-world experimental optical-fibre communication data. This proposed `quantum-inspired' algorithm provides an improvement in both the accuracy and convergence rate with respect to the k-means algorithm. Hence, this work presents two main contributions. Firstly, we propose the general inverse stereographic projection into the Bloch sphere as a better embedding for quantum machine learning algorithms; here, we use the problem of clustering quadrature amplitude modulated optical-fibre signals as an example. Secondly, as a purely classical contribution inspired by the first contribution, we propose and benchmark the use of the general inverse stereographic projection and spherical centroid for clustering optical-fibre signals, showing that optimizing the radius yields a consistent improvement in accuracy and convergence rate.

Vitamin K occupies a unique and often obscured place among its fellow fat-soluble vitamins. Evidence is mounting however, that vitamin K (VK) may play an important role in the visual system apart from the hepatic carboxylation of hemostatic related proteins. However, to our knowledge, no review covering the topic has appeared in the medical literature. Recent studies have confirmed that matrix Gla protein (MGP), a vitamin K-dependent protein (VKDP), is essential for the regulation of intraocular pressure in the mouse. The PREDIMED (Prevención con Dieta Mediterránea) study, a randomized trial involving 5860 adults at risk for cardiovascular disease, demonstrated a 29% reduction in the risk of cataract surgery in participants with the highest tertile of dietary vitamin K1 (PK) intake compared with the lowest tertile. However, the specific requirements of the eye and visual system (EVS) for VK, and what might constitute an optimized VK status, is currently unknown and largely unexplored. It is the intention therefore of this narrative review to provide an introduction concerning VK and the visual system, review ocular VK biology, and to provide some historical context to recent discoveries. Potential opportunities and gaps in current research efforts will be touched upon, in the hope of raising awareness, and encouraging continued VK related investigations in this important and highly specialized sensory system.

Clustering, or otherwise known as cluster analysis, is a learning problem that takes place without any human supervision. This technique has often been utilized, much efficiently, in data analysis, and serves for observing and identifying interesting, useful, or desired patterns in the said data. The clustering technique functions by performing a structured division of the data involved, in similar objects based on the characteristics that it identifies. This process results in the formation of groups, and each group that is formed, is called a cluster. A single said cluster consists of objects from the data, that have similarities among other objects found in the same cluster, and resemble differences when compared to objects identified from the data that now exist in other clusters. The process of clustering is very significant in various aspects of data analysis, as it determines and presents the intrinsic grouping of objects present in the data, based on their attributes, in a batch of unlabeled raw data. A textbook or otherwise said, good criteria, does not exist in this method of cluster analysis. That is because this process is so different and so customizable for every user, that needs it in his/her various and different needs. There is no outright best clustering algorithm, as it massively depends on the user’s scenario and needs. This paper is intended to compare and study two different clustering algorithms. The algorithms under investigation are k-mean and mean shift. These algorithms are compared according to the following factors: time complexity, training, prediction performance and accuracy of the clustering algorithms.

This study explored the intricate nexus between public service provision and land use planning, with a specific focus on the conservation of local plant species in Tambon Khao Phanom, Amphoe Khao Phanom, Krabi Province. Rooted in commitment. The research framework encompasses three fundamental activities: resource survey and collection, resource conservation and utilization, and resource development planning for public services, emphasizing land use planning for local plant species conservation. This multidisciplinary approach integrates the one-map method and draws data from the Department of Land Development to formulate a comprehensive land utilization plan that optimizes land use for biodiversity conservation. This study underscores the critical synergy between public service delivery and land use planning, highlighting their collective potential to advance community well-being and sustainable development.

Study in black rice has gain prominence in recent times due to its high nutritive value, curative effect, and anti-oxidant properties. However, its poor agronomic traits, including low yield necessitates the incorporation of the colour-grain trait into elite varieties through plant breeding techniques. SSR markers play an important role in plant identification and breeding. Here, the generation of reference-based transcriptome, annotation of transcriptome datasets, and a large set of simple sequence repeat (SSR) markers derived from Black rice have been described. In all 28664 SSRs were predicted in 34978 (48.59%) expressed transcripts. However, 7068 (20.20%) transcripts were found to have more than one SSR. The identified SSRs were dominated by tri-nucleotide and tetra-nucleotide repeats representing about 54.11% and 33.31% respectively, of total SSRs. Validation of selected markers associated with anthocyanin trait performed across different black rice accessions established the reliability of the process used for mining SSR markers. The SSR markers identified in this study could be used to select varieties with desired traits, and to investigate the genetic mechanism underlying anthocyanin accumulation in the pericarps of black rice. Furthermore, the findings from this study may prove beneficial in future genetic diversity studies, primer development, and selective breeding programs.

In the particular configuration of the scalar field K-essence in the Wheeler-DeWitt quantum equation, for some age in the Bianchi type I anisotropic cosmological model, a fractional differential equation for the scalar field arises naturally. The order of the fractional differential equation is $\beta=\frac{2\alpha}{2\alpha - 1}$. This fractional equation belongs to different intervals, depending on the value of the barotropic parameter; when $\omega_{X} \in [0,1]$, the order belongs to the interval $1\leq \beta \leq 2$, and when $\omega_{X}\in[-1,0)$, the order belongs to the interval $0<\beta \leq 1$. In the quantum scheme, we introduce the factor ordering problem in the variables $(\Omega,\phi)$ and its corresponding momenta $(\Pi_\Omega, \Pi_\phi)$, obtaining a linear fractional differential equation with variable coefficients in the scalar field equation, then the solution is found using a fractional power series expansion. The corresponding quantum solutions are also given. We found the classical solution in the usual gauge N obtained in the Hamiltonian formalism and without a gauge. In the last case, the general solution is presented in a transformed time $T(\tau)$, however in the dust era we found a closed solution in the gauge time $\tau$.

The main objective of this paper is to introduce k-fractional derivative operator by using the definition of k-beta function. We establish some results related to the newly defined fractional operator such as Mellin transform and relations to k-hypergeometric and k-Appell's functions. Also, we investigate the k-fractional derivative of k-Mittag-Leffler and Wright hypergeometric functions.

Litchi orchards of 15 year age in Pantnagar were subjected to different fruit bagging treatments in study entitled “Impact of pre-harvest fruit bagging technology on growth and quality traits in litchi cv. Rose Scented under Indian prospective”. The combination includes white and pink polypropylene bags practiced on three dates i.e. 15, 25 and 30 days after fruit set and a control. Hence, study comprised of 7 treatment combination in total. The data of year 2017 and 2018 as well as pooled data revealed that T1 i.e. white polypropylene bags + bagging 15 days after fruit set was found to be promising in attributes such as fruit cracking (%) and Sun burn (%). T3 White Polypropylene bags + bagging 30 days after fruit set was found best for fruit Weight (g) and Acidity (%), T4 Pink Polypropylene bags + bagging 15 days after fruit set was found promising for TSS (0Brix), T6-Polypropylene Pink + 10th May (30 days after fruit set) was observed to be best for most of the desired attributes viz. Fruit breadth (mm), Yield (Kg/tree), Acidity (%), Anthocyanin (mg/100g), Fruit colour (visual), borer infestation (%) and B:C Ratio. However, fruits without bagging i.e. control were found to have inferior appearance and have maximum fruit cracking (%) and sun burn (%). Thus the bagging of litchi fruits with white polypropylene bags 15 days after fruit set resulted in lesser cracking and sunburn incidence. For other attributes, polypropylene pink bagged 30 days after fruit set was found promising. In Litchi under Indian condition, the novel technique of fruit bagging significantly enhance the fruit appearance and quality.

Structural variations (SVs) play a key role in the pathogenicity of hematological malignancies. Optical genome mapping (OGM) is an emerging technology that enables genome-wide detection of all classes of SVs at a high resolution and sensitivity. Identification of cryptic SVs leading to gene disruption or predicted novel gene fusions could be important drivers for cancer development and/or portend a prognostic relevance, which could be used to modify the treatment plan. A cohort of 106 consented cases that had a successful OGM analysis performed were included in the study. Demographic, clinical, laboratory and treatment data were collected. Routine diagnostic and prognostic testing were done on the peripheral blood and bone marrow aspirate as indicated. Additional samples of peripheral blood and/or bone marrow were sent for OGM testing. OGM led to a change in risk stratification in 17/66 (25.75%) of patients with hematological malignancies, the majority of these patients (15/66, 22.72%), having their risk stratification upgraded with a resulting change in treatment of 14 patients. This study highlights the ability of OGM to detect rare, cryptic and clinically relevant variants that potentially impact disease diagnosis, risk stratification and actionable treatment targets.

For marine vessels, a propeller shaft system, also known as a propulsion shaft system, is an essential changer in engine torque and propeller thrust. The propeller shaft system is subjected to transverse, longitudinal, and torsional excitations during operation. These sources of excitations originate from alternating thrust generated by the propeller, operation of a propeller in a stern flow field which is non-uniform in time and space, misalignment of components such as shafts, bearings, and keyholes in the assembly, excitations in the form of rotational motion, and the whirling motion of the shafts. These dynamic excitations posed a challenging issue for the integrity and reliability of a marine vehicle. Thus, it is crucial to analyze the dynamic response of the propulsion shaft system. The dynamic analysis of the propulsion shaft system is typically conducted using numerical /analytical models. At present, Finite Element Model (FEM) as a numerical model plays a vital role in analyzing the dynamic response of the structure. The computed response and the modal parameters from the FE model are reliable only if accurate boundary conditions, such as stiffness, can be imposed on the model. However, the numerical FE model deviates from the experimental results because of uncertainties in the stiffness values of the bearings and other connectors. This paper uses the Response Surface Optimization (RSO) technique to estimate the unknown stiffness of the bearings used in the propulsion shaft system. The experimental model of the propeller shaft system is constructed from the steady-state response of the system using the step sine excitation. The natural frequencies and the amplitude of vibrations in the FE model are updated using the parametric RSO technique. The updated model shows that the difference in natural frequencies and vibration amplitude is less than 10% between the optimized and experimental models. Propeller Shaft, Vibrations, Optimization, Response Surface

Several traps are recommended for monitoring corn earworm, Helicoverpa zea (Boddie), an important pest of field, vegetable and fruit crops in the U.S. These traps, which are meant to capture H. zea in many cases end up capturing other insects. Helicoverpa zea has recently been found feeding on different seeds and dual-type (seed and fiber) hemp, Cannabis sativa L. (Rosales: Cannabaceae) causing serious damage. Limited work has been done on developing integrated pest management (IPM) for H. zea industrial hemp in Missouri. We evaluated the attractiveness of different traps with the aim of developing a monitoring system for the adult male H. zea in industrial hemp fields in two Missouri locations In addition, we recorded other non-target insects in the traps to determine trap selectivity. Commercially available green, clear, tricolor bucket traps Heliothis Scentry and Scentry Delta 1X traps baited with H. zea sex pheromones were evaluated in 2021 and 2022. Tricolor traps captured significantly more adult male H. zea than the other traps in both years. Non-target insects, mainly Xylocopa virginica (L.) (Hymenoptera: Apidae), Bombus spp (Hymenoptera: Apidae), and Apis mellifera L. (Hymenoptera: Apidae) were also captured. The tricolor trap captured the most bees. The presence of non-target species highlights the risk of using tricolor traps as a monitoring tool. This data provides information for planning the monitoring of corn earworm in industrial hemp farms in Missouri.

In this paper, we introduce a new iteration scheme, named as the S**-iteration scheme, for approximation of fixed point of the nonexpansive mappings. This scheme is faster than Picard, Mann, Ishikawa, Noor, Agarwal, Abbas, Thakur, and Ullah iteration schemes. We show the stability of our instigated scheme and give a numerical example to vindicate our claim. We also put forward some weak and strong convergence theorems for Suzuki's generalized nonexpansive mappings in the setting of uniformly convex Banach spaces. Our results comprehend, improve, and consolidate many results in the existing literature.

This study develops a hybrid machine learning (ML) algorithm integrated with IoT technology to improve the accuracy and efficiency of soil monitoring and tomato crop disease prediction in Anakapalle, a south Indian station. An IoT device collected one-minute and critical soil parameters—humidity, temperature, pH values, nitrogen (N), phosphorus (P), and potassium (K)—essential for assessing soil health and optimizing crop growth. Kendall's correlations were computed to rank these parameters for utilization in hybrid ML techniques. Various ML algorithms including K-Nearest Neighbors (KNN), Support Vector Machines (SVM), Decision Tree (DT), Random Forest (RF), and Logistic Regression (LR) were evaluated. A novel hybrid algorithm, 'Bayesian Optimization with KNN', was introduced to combine multiple ML techniques and enhance predictive performance. The hybrid algorithm demonstrated superior results with 95% accuracy, precision, and recall, and an F1 score of 94%, while individual ML algorithms achieved varying results: KNN (80% accuracy), SVM (82%), DT (77%), RF (80%), and LR (81%) with differing precision, recall, and F1 scores. This hybrid ML approach proved highly effective in predicting tomato crop diseases in natural environments, underscoring the synergistic benefits of IoT and advanced ML techniques in optimizing agricultural practices.

Nanoporous membranes promise energy-efficient water desalination. Hexagonal boron nitride (h-BN), like graphene, exhibits outstanding physical and chemical properties, making it a promising candidate for water treatment. We employed Car–Parrinello molecular dynamics simulations to establish accurate modeling of Na+ and Cl- permeation through hydrogen passivated nanopores in graphene and h-BN membranes. In these complex systems the classical potentials cannot properly account for the physics at play. We demonstrate that ion separation works well for the h-BN by imposing a barrier of 0.13 eV and 0.24 eV for Na+ and Cl- permeation respectively, compared to the graphene where the Cl- ion faces a negative barrier of 0.68 eV and is prone toward blockade and Na+ permeation is associated with a slightly negative barrier of 0.03 eV. From the change in the solvation shell, we get the following trend: Na/h-BN > Na/G > Cl/G > Cl/h-BN. We argue that the trend in the permeation barrier changes to Cl-h-BN > Na-h-BN > Na-G > Cl-G due to a combination of several interactions, including the distortion of the water network induced by the ions, the ion-water interaction, and the ion-nanopore interaction. Overall, the desalination performance of h-BN surpasses that of their graphene counterparts.

DNA markers have high occurrence and mutation rates and are generally located around the controlling regions of some tissue-specific genes and housekeeping genes that can change the expression pattern. Microsatellites and CpG islands are stretches of DNA with repeats and are known to influence gene expression. Microsatellites are more prone to mutations than the rest of the genomic DNA which allows the straightforward genomic nucleotide evolutionary transformation rate in different species. In the present study, these DNA markers are mined and an in-silico comparison was carried out to understand their occurrence pattern and distribution frequency in sex chromosomes (X and Y) of 12 different animal species using Perl and R programming pipelines. It was found that female-dominant X chromosomes had higher occurrence and distribution frequencies for these DNA markers than that of male-dominant sex chromosome i.e. Y which means that the former has a higher number of the evolutionary sites. The density of DNA markers however, showed remarkable variation for different animal species The results obtained need validation through wet-lab experimentation. Tri- and hexa-nucleotide repeats are more abundant in exons, whereas other repeats are more abundant in non-coding regions.

This paper presents a new semi-explicit algorithm for parameters estimation in a time-fractional generalization of dual-phase-lag heat conduction model with the Caputo fractional derivatives. It is shown that this model can be derived from a general linear constitutive relation for the heat transfer by conduction when the heat conduction relaxation kernel contains the Mittag-Leffler function. The model can be used to describe heat conduction phenomena in a material with power-law memory. The proposed algorithm of parameters estimation is based on the time integral characteristics method. The explicit representations of the thermal diffusivity and the fractional analogues of the thermal relaxation time and the thermal retardation are obtained via a Laplace transform of the temperature field and utilized in the algorithm. An implicit relation is derived for the order of fractional differentiation. In the algorithm, this relation is resolved numerically. An example illustrates the proposed technique.

Introduction: Endoscopic biliary stenting is a widely utilized procedure in the realm of interventional gastroenterology, primarily employing plastic stents for short-term biliary drainage. This case series endeavours to investigate the occurrence and ensuing clinical ramifications of forgotten or retained biliary stents. Methods: Carried out over an 8-month duration at King George Hospital in Visakhapatnam, this case series encompasses 12 patients diagnosed with forgotten biliary stents. Diagnostic confirmation was established through a combination of X-ray, abdominal ultrasound, and magnetic resonance cholangiopancreatography (MRCP). Four patients experienced complications such as fractured distal pigtails and obstructed stents, thwarting retrieval efforts via endoscopic retrograde cholangiopancreatography (ERCP) and cholangioscopy. Results: This case series featured 12 patients with a median age of 48 years (range: 18-76), comprising 7 females (58.3%) and 5 males (41.7%). The primary indication for initial stent placement was choledocholithiasis in 10 instances (83.3%), while benign biliary strictures accounted for 3 cases (25%). On average, patients presented 31.3 months post-initial stenting, primarily manifesting cholangitis symptoms (83.3%). ERCP succeeded in stent removal in 8 cases (66.6%), while the remaining cases necessitated advanced procedures such as cholangioscopy, with two patients being referred for surgical intervention. It is noteworthy that there were no instances of mortality. Conclusion: This case series, conducted against the backdrop of the COVID-19 pandemic, highlights an increased prevalence of neglected plastic biliary stents. The principal complication encountered was cholangitis, often coexisting with common bile duct (CBD) stones. Standard ERCP techniques demonstrated reduced efficacy in instances characterized by fractured, obstructed, or displaced stents, necessitating the exploration of alternative strategies like cholangioscopy or surgical intervention. This compilation of cases underscores the pressing imperative for prompt stent retrieval and the enhancement of management protocols to proactively mitigate the potential for complications.

The visualization of hyperspectral images in display devices, having RGB colour composition channels is quite difficult due to the high dimensionality of these images. Thus, principal component analysis has been used as a dimensionality reduction algorithm to reduce information loss, by creating uncorrelated features. To classify regions in the hyperspectral images, K-means clustering has been used to form clusters/regions. These two algorithms have been implemented on the three datasets imaged by AVIRIS and ROSIS sensors.

Concept Knowledge (C-K) theory has been used in engineering and science-based research for more than a decade. Design of an Information Technology (IT) artefact is mostly pragmatic in nature. Design Science Research (DSR) methodology applied and studied in many Information Systems (IS) research. Many sub design decisions involved through the design of an IT artefact from a concept (idea) to a working prototype. A DSR artefact is based on a combination of decisions made during several sub-design stages. Artefacts are built based on the selection of elements in each sub-design space. Recording the design decisions on each sub-design space would be beneficial for future researchers. By knowing the design decisions on each sub-design space, researchers would be able to try different combinations of the design. C-K theory provides the ability to capture the design processes’ several sub-design spaces. In this paper, we discuss the DSR research methodology by looking at the stages proposed in the literature, and the application of C-K theory in an IT-based DSR. This paper also proposed a C-K theory-based protocol called Concept Tree for tracking and reporting artefact design steps. The application of C-K theory in DSR is exhibited using the implementation of the Concept Tree for a prototype design IT artefact.

In this paper, some convexity properties and some inequalities for the (p,k)-analogue of the Gamma function, Г_p,k(x) are given. In particular, a (p,k)-analogue of the celebrated Bohr-Mollerup theorem is given. Furthermore, a (p,k)-analogue of the Riemann zeta function, ζ_p,k(x) is introduced and some associated inequalities are derived. The established results provide the (p,k)-generalizations of some known results concerning the classical Gamma function.

Food security is intrinsically related to health and well-being. This paper investigates the status-quo of food insecurity among the population residing close to transit in various parts of the United States of America (USA). The data from the 2020 National Health Interview Survey (NHIS) collected by the National Center for Health Statistics (NCHS) of the USA are analyzed in this research. Logistic regression is carried out by treating food insecurity as the dependent variable and socioeconomic variables such as age, income, education and dependency on the Supplemental Nutrition Assistance Program (SNAP) as independent variables. Food insecurity is assessed with aggregated information on four aspects of inputs from those respondents who live near a transit: 1) worry food would run out, 2) food didn't last, 3) couldn't afford to eat balanced meals, and 4) cut the size of meals or skip meals. Findings suggest that respondents who live close to transit in the USA and are from large central metro counties of the Northeast, Southern and Western states showed an increase in food insecurity if they were below 65 years of age, had income below country’s median income or their educational attainment was below bachelor’s degree. There was a significant association found between food insecurity of respondents living close to transit and subscribed to using food stamps or SNAP. Policies that could alleviate food insecurity by reducing cost of living near transit are recommended.

Virtual Reality(VR) is an emerging technology with a broad range of application in training, entertainment, and business. To maximize the potentials of virtual reality as a medium, the unwelcome feeling of simulation sickness needs to be minimized. Even with advancements in VR, the usability concerns are barriers for a wide-spread acceptance. Several factors (hardware, software, human) play a part towards a pleasant VR experience. The reviewed scientific articles are mostly part of documents indexed in digital libraries. In this paper, we review the potential factors which cause simulation sickness and minimize the usability of virtual reality systems. We review the best practices from a developer’s perspective and some of the safety measures a user must follow while using the VR systems from existing research. Even after following some of the guidelines and best practices VR environments do not guarantee a pleasant experience for users. Limited research in VR environments towards requirement specification, design, and development for maximum usability and adaptability was the main motive for this work.

The COVID-19 pandemic is adversely impacting food and nutrition security and requires urgent attention from policymakers. Sustainable intensification of agriculture is one strategy that attempts to increase food production without adversely impacting the environment, by shifting from water-intensive crops to other climate-resistant and nutritious crops. This paper focuses on the Indian state of Andhra Pradesh by studying the impact of shifting 20% of the area under paddy and cotton cultivation to other crops like millets and pulses. Using FAO’s CROPWAT model, along with monsoon forecasts and detailed agricultural data, we simulate the crop water requirements across the study area. We simulate a business-as-usual base case and compare it to multiple crop diversification strategies using various parameters – food, calories, protein production, as well as groundwater and energy consumption. Results from this study indicate that reduced paddy cultivation decreases groundwater and energy consumption by around 9-10%., and a calorie deficit between 4-8% - making up this calorie deficit requires a 20-30% improvement in the yields of millets and pulses. We also propose policy interventions to incentivize the cultivation of nutritious and climate-resistant crops as a sustainable strategy towards strengthening food and nutrition security while lowering the environmental footprint of food production.

Background: Recent developments in our understanding of the interactions between long non-coding RNA (lncRNA) and cellular components have improved treatment approaches for various human diseases including cancer, vascular diseases, and neurological diseases. Although investigation of specific lncRNAs revealed their role in the metabolism of cellular RNA, our understanding of their contribution to post-transcriptional regulation is relatively limited. In this study, we explore the role of lncRNAs in modulating alternative splicing and their impact on downstream protein-RNA interaction networks. Results: Analysis of alternative splicing events across 39 lncRNA wildtype and knockout RNA-sequencing datasets from three human cell lines: HeLa (Cervical Cancer), K562 (Myeloid Leukemia), and U87 (Glioblastoma), resulted in high confidence (fdr < 0.01) identification of 4432 skipped exon events and 2474 retained intron events, implicating 759 genes to be impacted at post-transcriptional level due to the loss of lncRNAs. We observed that a majority of the alternatively spliced genes in a lncRNA knockout were specific to the cell type, in agreement with the finding that genes affected by alternative splicing also displayed enriched functions in a cell type specific manner. To understand the mechanism behind this cell-type specific alternative splicing patterns, we analyzed RNA binding protein (RBP)-RNA interaction profiles across the spliced regions. Conclusions: Despite limited RBP binding data across cell lines, alternatively spliced events detected in lncRNA perturbation experiments were associated with RBPs binding in proximal intron-exon junctions, in a cell type specific manner. The cellular functions affected by alternative splicing were also affected in a cell type specific manner. Based on the RBP binding profiles in HeLa and K562 cells, we hypothesize that several lncRNAs are likely to exhibit a sponge effect in disease contexts, resulting in the functional disruption of RBPs due to altered titration of the RBPs from their target loci. We propose that such lncRNA sponges can extensively rewire the post-transcriptional gene regulatory networks by altering the protein-RNA interaction landscape in a cell-type specific manner.

Background: Persistent up regulation of NF-κB leads to chronic inflammation and subsequent microglial activation and takes neurons towards death by activating death receptor domains and the p53 pathway. Thus, inhibition of NF-κB may lead to more effective treatment for Parkinson’s disease. Therefore, we have used mangiferin, specific inhibitor of NF-κB in this study. Method: The study utilized male Wistar rats weighing 200-250 gm (n=8 in each group). Stereotactic surgery of rats was done to induce 6-OHDA lesioning in rats. On day 42, rats were subjected to behavioural studies to evaluate effect of mangiferin and their brains were taken out after euthanasia to perform biochemical and molecular studies. Results: Mangiferin significantly increases locomotor parameters in 6-OHDA lesioned rats. It also decreases activity of Cyclooxygenase enzyme which then leads to decrease concentration of inflammatory cytokines. Microglial inflammation was also substantially reduced by reducing MPO concentration. Oxidative stress burden was also reduced after treatment with mangiferin as indicated by increase in Total Antioxidant Capacity, SOD and Catalase and reduction in concentration of MDA. Treatment with mangiferin also reduces burden of oxidative stress by increasing the activity of NRF2/ARE pathway. Activity of Caspase 3 and 9 was also significantly reduced after treatment with mangiferin. Significant decrease in activity of both Cox1 and Cox 2 was also observed. Maximum improvement in all parameters was observed in rats treated with grouping of mangiferin 45mg.kg-1 and levodopa 10mg.kg-1. Treatment with levodopa alone has no significant effect on biochemical and molecular parameters though it significantly improves behavioural parameters. Conclusion and Implications: Results of this study suggest that mangiferin has protective effect in hemi-parkinsonian rats by inhibiting NF-κB. Current treatment of Parkinson’s disease does not target the underlying problem of the disease. Therefore, combination therapy of mangiferin and levodopa can be helpful in better management of Parkison’s.

For the parentage testing in canine microsatellite length polymorphism markers were used to check the efficacy of the markers. In the current study 5’ fluorescently labeled 12 SSR markers were used to check the use of the markers in popular owned-dog breeds (Labrador, German Shepherd, Pug, Mudhol Hound, Tibetan Mastiff, Gaddi dog, Beagle, Belgian Malinois, Pointer, and Cane Corso) maintained of India (not necessarily indigenous breeds). The number of alleles, heterozygosity, polymorphism information content, and probability of exclusion were determined for all the markers to check the effectiveness of the markers. The mean number of alleles per locus ranged from 5 to 29 and the effective number of alleles ranged from 3.6 to 15.2. The expected heterozygosity was greater than 0.73. The population inbreeding coefficient (FIS) demonstrated that there was no inbreeding in the breeds studied, as the samples were collected from owners and dog breeders belonging to various states, including Punjab, Haryana, Himachal Pradesh, and Karnataka. The polymorphism information content and the probability of the exclusion values were greater than 0.65. the combined probability of exclusion for all the breeds was (2.82E-12) 0.99999995. The results indicated that the selected 12 markers are effective enough to determine the parentage of the dogs.

Vaccination is an important method of immunological preventive care required for health management of all animal including fish. More particularly, immunization is important in in-land fisheries for the management of diseases in fish brood stocks and healthy seed production. According to the latest statistics in 2020, 90.3 million tonnes of captured fish production was achieved from the aquaculture sector. Out of the above, 78.8 million tonnes from marine and 11.5 million tonnes from inland waters aquaculture sectors. About 4% decline in fish production was achieved in 2020 than 2018 from inland fisheries sectors. On the other hand, the digestive protein content, healthy fats and nutritional values of fish products are comparitively more affordable as compared to other meat sources. In 2014, about 10% aquatic cultured animals were lost (costing &gt; 10 billion $ global annual loss) due to infectious diseases. Therefore, vaccination in fish especially in brood stocks is one of the most important approaches to stop such losses in the fisheries sector. Fish vaccines consist of either whole killed pathogens, subunit of a protein, a recombinant protein, DNA vaccines or live attenuated vaccines. Challenges existing are adaption of vaccination in fisheries sector, route of administration, use of effective adjuvants and most importantly lack of effective results. Use of autogenous vaccines, vaccination via intramuscular, intraperitoneal or oral routes, and most importantly adding vaccines in feed using top dressing methods or as a constituent in fish feed are now in emerging. These method shall lower the risk of using antibiotics in cultured water which in turn will reduce the environmental contamination.

Tumor necrosis factor-α (TNFα), one of the major pro-inflammatory cytokines, plays a key role in an effective immune response. However, the chronic presence of TNFα can lead to several inflammatory disorders like rheumatoid arthritis, psoriasis, Crohn’s disease etc. Inhibition of TNFα by pharmacological inhibitors or antibodies has proven to be effective in palliative treatment to some extent. The aim of this study was to develop an anti-TNFα antibody which may be used as a therapeutic option to inhibit TNFα-mediated cytotoxicity. We characterized several hybridoma clones secreting monoclonal antibodies (mAbs) to human-TNFα. Four mAbs rescued L929 fibroblast cells from TNFα-triggered cell death and one of these, namely C8 was found to have the highest affinity. To gain insights into the mechanism by which mAb C8 inhibits human TNFα-mediated toxicity, the epitope corresponding to the mAb was delineated. The antigenic determinant was found to comprise of the stretch of amino acids 99-120, of which, 102-104 (QRE) form the core epitope. The observation was supported by bioinformatics analyses of an antigen-antibody complex model. In addition, the binding affinity of mAb C8 to TNFα was found to be comparable with that of Infliximab which is a commercially available anti TNFα mAb.

The current study aims to produce a material that has a dual effect of healing and anti-inflammatory. For this target k-carrageenan/polyacrylamide hydrogel film loaded with cetrimide (k-CAR/PAAm/CI) was performed by manual casting technique. Definite concentrations of k-CAR and AAm was heated at 80°C for 2 hours, CI and glycerol were added. The solution was cast without using initiator and cross-linker. The reaction of the sulfonic acid group -SO3H of k-CAR with -CONH2 group of PAAm lead to the formation of a sulfonamide (-SO2NH-) linkage. The characteristics of the produced films were investigated by FTIR, TGA, contact angle, and mechanical properties. Improvement in the thermal stability was performed in k-CAR/PAAm/CI2 film containing 1.5% CI compared to the film has 0.5% CI (k-CAR/PAAm/CI1). The contact angle measurement proved the films are hydrophobic that enhanced by increasing CI content. The tensile strength and elongation percent values are considered adequate for materials used in wound care. k-CAR/PAAm/CI2 (1.5% CI) film showed superior antimicrobial activity against P. aeruginosa, moderate activity against S. aureus, and low activity against E. coli. The film k-CAR/PAAm/CI2 was effectively inhibiting the heat-induced hemolysis and may offer a promising approach for the development of effective wound dressings.

Salinity, resulting from climate change and excessive mineral fertilization, burdens farmers and negatively impacts soil and water ecosystems in the Northeastern Nile Delta. Organic and biological approaches are crucial for addressing these issues. This study examined the effects of individual and combined inoculations with cyanobacteria, yeast, and Arbuscular Mycorrhizal Fungi (AMF), with or without K-humate, on enhancing salinity tolerance, increasing yield, and improving crop quality of wheat and faba bean. The aim was to reduce NPK mineral fertilizer application rates to 25% of recommended doses. An economic evaluation was also conducted. In a preliminary laboratory experiment, the interactive effects of these microbiomes on the production of plant antioxidant enzymes and soil enzymes were investigated under salinity stress. Results showed that co-inoculation, especially with K-humate, yielded superior outcomes compared to individual inoculations. The laboratory experiment findings were confirmed by a field trial conducted in saline-alkaline soil in the Northeastern Nile Delta region. The study found that the integrated inoculation of cyanobacteria, yeast, and mycorrhizae with K-humate, along with 25% mineral NPK fertilization enhanced microbial activity, including AMF colonization, spore density, and total bacteria, cyanobacteria, and yeast counts in the plant rhizosphere. It also increased soil enzyme activity, improving soil fertility compared to individual or mineral control treatments. This integration resulted in wheat yields of 2.77 tons/ha and faba bean yields of 4.75 tons/ha. Crop quality improved, with higher levels of nitrogen, potassium, phosphorus, and protein in wheat grains and faba bean seeds. Microbiomes inoculation increased potassium uptake over sodium, enhancing the potassium/sodium ratio and salt stress tolerance. This approach reduces reliance on costly mineral fertilizers by up to 75%, enabling economically viable cultivation in marginal lands. These sustainable practices optimize resource utilization, maximize economic efficiency, and preserve natural resources.

This study delves into the impact of artificial intelligence on students’ learning.The paper pioneers the use of kmeans classification to reduce the dimensionality of features before the classification process, which minimizes redundant information and computational overhead. This step is not commonly found in prior research.Firstly, a random forest model is established with “whether AI assistance was used to complete the paper” as the output, and various features as inputs. The analysis of the predictive accuracy when changing input features reveals the degree of influence of each feature on using AI to complete the paper. After feature selection, the remaining 6 features can still effectively predict the use of AI to complete the paper, indicating the representativeness of the extracted indicators. Subsequently, the PCA-K-means algorithm is employed to classify the use of artificial intelligence. PCA algorithm is used for dimensionality reduction of the extracted features to better characterize students’ use of AI. Three representative variables are selected, and the contribution of each feature is computed based on the factor loading matrix. Finally, the K-means algorithm is used to classify students based on the three dimensional features, showing that students can be effectively classified into 2 categories. The results indicate that the majority of students support the use of AI technology to enhance their abilities, although some students may only intend to use AI to cope with exams and similar tasks.

Ranked Set Sampling (RSS) is a useful technique for improving the estimator of population mean when the sampling units in a study can be easily ranked than the actual measurement. RSS performs better than simple random sampling (SRS) when the mean of units corresponding to each rank is used. The performance of RSS can be increased further by assigning weights to the ranked observations. In this paper, we propose weighted RSS procedures to estimate the population mean of positively skew distributions. It is shown that the gain in the relative precisions of the population mean for chosen distributions are uniformly higher than those based on RSS. The gains in relative precisions are substantially high. Further, the relative precisions of our estimator are slightly higher than the ones based on Neyman’s optimal allocation model for small sample sizes. Moreover, it is shown that, the performance of the proposed estimator increases as the skewness increases by using the example of lognormal family of distributions.

While lidar-based forest inventory methods have been widely demonstrated, prediction of tree diameters with lidar is not well understood. The performance metrics typically used in studies for prediction of diameters can be difficult to interpret and may not support comparative inferences between sampling designs or study areas. We evaluate a variety of lidar and k nearest neighbor (k-NN) strategies for prediction of tree diameter distributions using two indices which are easier to interpret and compare. The indices are based on the coefficient of determination (R²), and root mean square deviation (RMSD). These indices facilitate comparisons with alternative (non-lidar) inventory strategies, and with other project areas. We evaluate k nearest neighbors (k-NN) dbh density (relative frequency by dbh class) prediction strategies with lidar for 190 training plots distribute across the 800 km² Savannah River Site in South Carolina, USA. We evaluate the performance of k-NN with respect to distance metrics, number of neighbors, predictor sets, and response sets. Amongst the examined strategies we found Mahalanobis distance with k = 3 neighbors performed best according to a number of criteria.

There are many modern and traditional methods in valuing the performance of the company among them EVA, CVA are modern methods where as EPS, ROI, ROE etc. are some of the traditional methods. modern and traditional methods are not only used to check the performance of a company but it also used in investment decisions by the investors. Stern Stewart, managing partner of M/s Stern Stewart & Co. introduced a modified concept of economic profit in 1990 in the name of Economic Value Added (EVA) as measure of business performance and CVA is only a cash consideration in EVA. In this paper an attempt is made to study which method is used by the investors while taking the investment decisions i.e. traditional methods are modern methods. 100 respondents (Investors) are questioned and collected their views, we are assuming that there is no impact of traditional or modern methods while taking investment decisions by the investors.

Real time condition monitoring and precision health assessment system is a mandatory need for effective maintenance program in industrial sector. Rapid advancement in the information technology and other engineering technologies have invited more proactive attention from research and development in industrial sectors and particularly in condition monitoring of machines and related Industrial processes. In this work, the drill bit condition monitoring techniques have been developed based on the wavelet analysis and artificial neural network (ANN) as automatic drill bit fault detection and classification. An experimental work has been conducted to capture the vibration signals for analysis. In this experiment, the CNC drill machine is used with high carbon steel drill bit and mild steel material as work piece. The cutting condition parameters are kept constant and the wear level is changed. The Data Acquisition system (DAQ) with Lab VIEW software is used to capture the vibration signals for drill bit with different wear conditions. The captured vibrations data are analyzed using continuous wavelet transform (CWT) with Morlet wavelet and Daubechies wavelet as a prime function. In general, the CWT coefficient is used to generate the inputs features to ANN for automatic tool condition classification, with two outputs (0, 1) for healthy and (1, 0) for faulty. The results show the effectiveness of the combed WT and ANN for automatic classification of tool wear conditions with high success rate.

Background: Hypertension is a condition of a person's blood pressure being at a level above normal, hypertension treatment can be done herbally using avocado leaves. Avocado leaves can lower blood pressure because they contain active substances, namely flavonoids and quercetin. This research was conducted in the working area of the Tilango Health Center. Objective: This study aims to determine the effect of giving boiled water of avocado leaves on reducing blood pressure in the elderly with hypertension. Methods: Design This study used a two-group quasi-experimental pre-test - post-test design. The sample is the elderly who have hypertension, amounting to 125 people with purposive sampling technique. The research instrument used a questionnaire. Results: Statistical test using T-Test on blood pressure before and after the intervention was given a significance value of 0.000 (p-value < 0.05 ). Conclusion : This study concludes that there is a significant effect between giving avocado leaf boiled water on reducing blood pressure in the elderly with hypertension in the working area of the Tilango Health Center.

(1) Background: Vitamin K deficiency is a common feature of chronic kidney disease (CKD), leading to impaired bone quality and increased risk of vascular calcifications. A method to indirectly measure Vitamin K status is measuring the blood level of Vitamin K dependent proteins (VKDP)- osteocalcin (OC) and matrix GLA protein (MGP). The aim of this study is to correlate the level of OC and MGP with markers of CKD mineral bone disorder (CKD-MBD). (2) Methods: We conducted a single-center cross-sectional study that included 45 CKD G5D patients and measured blood biochemistry, complete blood count and intact osteocalcin and matrix GLA protein. (3) Results: We found a strong statistically significant correlation of OC with the markers of CKD-MBD such as: iPTH , serum calcium and serum phosphorus and a strong indirect statistically significant correlation with abdominal circumference. There was also a statistically significant correlation of MGP with markers of inflammation (CRP). Higher levels of MGP were found in patients treated with vitamin K antagonists, non-calcium based phosphate binders and vitamin D receptor activator- paricalcitol. (4) Conclusions: In our study, we found that vitamin K deficiency, measured indirectly using the level of VKDP is associated to CKD-MBD. The use of medication such as phosphate binders, that reduce vitamin K absorbtion, Vitamin D that increases Vitamin K requirements and also vitamin K antagonists, seem to have an influence on the blood level of VKDPs.