Boundary behavior of a given important function or its limit values are essential in the whole spectrum of mathematics and science. We consider some tractable cases of limit values in which either a difference of two ingredients or a difference equation is used coupled with the relevant functional equations to give rise to unexpected results. This involves the expression for the Laurent coefficients including the residue, the Kronecker limit formulas and higher order coefficients as well as the difference formed to cancel the inaccessible part, typically the Clausen functions. We also state Abelian results which yield asymptotic formulas for weighted summatory function from that for the original summatory function

In this work the existence and nonexistence of stationary radial solutions to the elliptic partial differential equation arising in the molecular beam epitaxy are studied. Since we are interested in radial solutions we arrive at the following fourth-order differential equation

Electro-spun ultra-fine fibers exhibit two significant properties: a high surface-to-volume ratio and a relatively defect-free molecular structure. Due to the high surface-to-volume ratio, electro-spun materials are well suited for activities requiring increased physical contact, such as providing a site for a chemical reaction or filtration of small-sized physical materials. However, electrospinning has many shortcomings, including difficulties in producing inorganic nanofibers and a limited number or variety of polymers used in the process. The fabrication of nanofiber bundles via electrospinning is explored in this analytical study, as well as the relationship between extrinsic electrospinning parameters and the relative abundance of various fiber morphologies. Numerous variables could impact the fabrication of nanofibers, resulting in a variety of morphologies; therefore, adequate ambient conditions and selecting the appropriate solvent for achieving a homogenous polymer solution and uniform electro-spun materials are examined. Finally, common polymers suitable for electrospinning and the promising applications of ultra-fine fibers achieved via electrospinning are studied in this paper.

Powder bed fusion (PBF) process is a metal additive manufacturing process which can build parts with any complexity from a wide range of metallic materials. PBF process research has predominantly focused on the impact of only a few parameters on product properties due to the lack of a systematic approach for optimizing a large set of process parameters simultaneously. The pivotal challenges regarding this process require a quantitative approach for mapping the material properties and process parameters onto the ultimate quality; this will then enable the optimization of those parameters. In this study, we propose a two-phase framework for optimizing the process parameters and developing a predictive model for 316L stainless steel material. We also discuss the correlation between process parameters -- i.e., laser specifications -- and mechanical properties and how to achieve parts with high density (> 98%) as well as better ultimate mechanical properties. In this paper, we introduce and test an innovative approach for developing AM predictive models, with a relatively low error percentage of 10.236% that are used to optimize process parameters in accordance with user or manufacturer requirements. These models use support vector regression, random forest regression, and neural network techniques. It is shown that the intelligent selection of process parameters using these models can achieve an optimized density of up to 99.31% with uniform microstructure, which improves hardness, impact strength, and other mechanical properties.

Gelephu, located in the Himalayan region, has experienced one of the strongest development activities due to the suitable topography and geographic location, which has led to rapid urbanization. The main objective of the study is to perform land use land cover (LULC) mapping for Gelephu for 2016 and 2023 by a Random Forest (RF) classifier, using the Semi-automatic Classification Plugin (SCP) in QGIS and identify LULC changes. Furthermore, the study assessed the vegetation change dynamics within the study area by analysing the Normalized Difference Vegetation Index (NDVI) for 2016 and 2023. Additionally, the study characterized the resulting LULC change for Gelephu Thromde, a sub-administrative municipal entity, as a result of the notable intensity of the infrastructure development activities. The current study used a framework to collect Sentiniel-2 satellite data, which was then used for pre- and post-processing to create LULC and NDVI maps. The classification model achieved high accuracy, with an area under the curve (AUC) of up to 0.89. The corresponding LULC and NDVI statistics were analysed to determine the current status of the LULC and vegetation indices, respectively. The LULC change analysis reveals urban growth of 5.65% and 15.05% for Gelephu and Gelephu Thromde, respectively. The NDVI assessment shows significant deterioration in vegetation health with a 75.11% loss of healthy vegetation in Gelephu between 2016 and 2023. This research provides the first version of LULC and NDVI maps of Gelephu. The analysis results indicate possible future implications on sustainable development management in Gelephu Bhutan.

Sorghum is a multipurpose crop, but Cr(VI) toxicity influenced the production of the crop and have established highlighted courtesy, due to robust toxicity and a comparatively less known mode of action. Many reports approve the negative impact of Cr(VI) on plants. Yet, it is not clear that, at what concentrations, Cr(VI) inhibits the growth and nutrient quality of Sorghum. In the present research, toxic effects appeared after 1ppm of Cr treatment. The plant growth decreased 15 – 20% and nutritional quality decreased 30 – 40% significantly with increasing concentration of Cr(VI). Toxic components increased 14 – 16% with increasing concentration of Cr(VI) in both the varieties (HJ 541 and SSG 59-3). Chromium was accumulated more in roots followed by shoots with increasing Cr(VI) treatments (0-4 ppm). Chromium at 4ppm level was becoming lethal to Sorghum. Sorghum cultivar SSG 59-3 was more tolerable to Cr toxicity than HJ 541. Chromium accumulated in Sorghum and increased HCN content and at higher doses adversely affects the nutritive values and growth making it toxic for animal consumption. These findings may be useful for scheming a mitigation strategy for chromium toxicity.

Nanoparticles are widely used in the agricultural sector because of their distinctive properties. Studies have shown the influence of nanoparticles on plant growth and production. Nanoparticles act as effective carriers in the delivery of agrochemicals to plants. They provide site targeted delivery of nutrients and thus, prevents wastage of nutrients applied for plant growth and productivity. Bioremediation of pollutants is an emerging technology that provides bio-nano materials for the protection of agriculture from pollution. The aim of this review is to present and focus on the latest techniques used for the reduction of environmental pollution and improved agricultural production. This review speculates about the biosynthesis of nanomaterials from different sources like plants, fungi, and bacteria along with chemical and organic synthesis from carbon, silver, and gold. The role of nanoscience in detecting plant diseases and the removal of heavy metals. Application of Nanoscience in storing, production, processing, and transport of agricultural materials. It is also emphasized that Nanoscience may transform agriculture through the innovation of new techniques like Precision farming, improvement of plants to engross nutrients, targeted use of inputs, detection and control of diseases and withstand environmental pressures. Further, efforts have been made in describing that nanoparticles may act as a better substitute for agricultural plant growth and nutrition improvement by lowering the content of pollutants and pre-detection of diseases in plants. The biosynthetic route of nanomaterial synthesis could emerge as a better and safer option for environmental pollution reduction. Thus, nanoscience may increase agricultural production to feed a huge population in near future.

Neovascular age-related macular degeneration (nAMD) accounts for one of the leading causes of blindness among the aging population. The current treatment options for nAMD include intravitreal injections of anti-vascular endothelial growth factor (anti-VEGF). However, standardised frequent administration of anti-VEGF injections only improves the vision in approximately 30%-40% of nAMD patients. Current therapies targeting nAMD pose a significant risk of retinal fibrosis and geographic atrophy (GA) development in nAMD patients. A need exists to develop new therapies to treat nAMD with effective and long-term anti-angiogenic effects. Recent research on nAMD has discovered novel therapeutic targets and angiogenic signalling mechanisms involved in its pathogenesis. For example, tissue factor, human intravenous immune globulin, interferon-β signalling, cyclooxygenase-2 (COX-2) and cytochrome P450 monooxygenase lipid metabolites have been identified as key players in the development of angiogenesis in AMD disease models. Furthermore, novel therapies such as NLRP3 inflammasome inhibition, targeted intraceptor nanoparticle therapy, inhibitors of integrins and tissue factor are currently being tested at the level of clinical trials to treat nAMD. The aim of this review is to discuss the scope for alternative therapies proposed to anti-VEGFs for the treatment of nAMD.

Attention mechanisms have become a fundamental component of deep learning, including the field of computer vision. The key idea behind attention in computer vision is to help the model focus on the relevant spatial regions of the input image, rather than treating all regions equally. The traditional approaches to attention mechanisms in computer vision often suffer from distribution inconsistencies in the attention maps, resulting in sharp transitions that negatively affect model’s focus and lead to poor generalization on complex shapes. The problem of spatial incoherence is particularly pronounced in the task of semantic segmentation, where accurate pixel-level predictions require a detailed understanding of the spatial relationships within the image. In this paper, we propose an attention mechanism called Smooth Attention designed for convolutional neural networks to address the problem of spatial inconsistency in attention maps through multidimensional spatial smoothing. We conduct a series of experiments to evaluate the effectiveness of the proposed mechanism and demonstrate its superior performance compared to traditional methods.

This study explores the synthesis and application of BODIPY-functionalized gold nanoparticles (AuNPs) for the sensitive detection of biothiols via an indicator displacement assay coupled with Surface-Enhanced Raman Scattering (SERS) techniques, alongside their efficacy for in vitro cancer cell imaging. Moreover, the assay allowed a visible colorimetric detection of biothiols under normal and ultraviolet light conditions. The BODIPY (boron-dipyrromethene) fluorophores were strategically conjugated to the surface of gold nanoparticles, forming a robust nanohybrid that leverages the plasmonic properties of AuNPs for enhanced spectroscopic sensitivity. The detection mechanism exploits the displacement of the BODIPY indicator upon interaction with biothiols, triggering a measurable change in fluorescence and SERS signals. This dual-mode sensing approach provides high selectivity and sensitivity for biothiol detection, with detection limits reaching nanomolar concentrations using fluorescence and femtomolar concentration for cysteine using SERS. Furthermore, the BODIPY-AuNP complexes demonstrated excellent biocompatibility and photostability, facilitating their use in fluorescence imaging of biothiol distribution within cellular environments and highlighting their potential for diagnostic and therapeutic applications in biomedical research.

Traditional metals such as stainless steel, titanium and cobalt chrome are used in biomedical applications (implants, scaffolds etc.) but suffer from issues such as osseointegration and compatibility with existing bone. One way to improve traditional biomaterials is to incorporate ceramics with these metals so that their mechanical properties can be similar to cortical bones. Tricalcium phosphate is such a ceramic with properties so that it can be used in human body. This research explores the use of binder jetting based additive manufacturing process to create a novel biocomposite made of cobalt chrome and tricalcium phosphate. Experiments were conducted and processing parameters were varied to study their effect on the printing of this biocomposite. Layer thickness, binder saturation and drying time affected the dimensional tolerance and the density of the green samples. This effect is important to understand so that the material can be optimized for use in specific applications.

The integration of diverse distributed generation (DG) units, encompassing both Renewable Energy Sources (RES) and non-RES technologies delves into voltage levels, current distributions, and power flows, aiming to optimize and effectively manage the distribution network. An RES-based DGs such as photovoltaic systems and wind turbines, alongside non-RES units like fuel cells and micro turbines. This study proposes a hybrid approach the Multi-Objective Genetic Algorithm - Grey Wolf Optimizer (MOGA-GWO). By merging the strengths of multi-objective genetic algorithms with the efficiency of the Grey Wolf Optimizer, this advanced algorithm seeks semi-optimal solutions for multi-objective optimization problems. The algorithm aims to improve convergence speed without compromising solution quality, offering a promising solution for optimizing the characteristics of DG and RES integration in distribution networks compared to Cuckoo Search and Simulation Annealing Techniques. Key algorithmic operations include individual representation, initialization, fitness function computation, selection, crossover, mutation, and ending conditions. The DG optimal power flow problem is explored with a focus on minimizing generation costs, improving voltage profiles, minimizing losses, enhancing reliability, integrating renewable energy, reducing environmental impact, managing congestion, and ensuring compliance with operational constraints. Beyond traditional considerations, the study emphasizes neglected objectives and constraints, such as cyber-security concerns, real-time operation, regulatory frameworks, social acceptance, lifecycle environmental impact, grid resilience, data privacy, aging infrastructure compatibility, and economic viability.

Proper and timely segregation of cellular genome is an important and a prime requirement of all cell division programmes. Mis-segregation of chromosomes and resulting aneuploidy leads to several clinical consequences. Over the years, shugoshin emerges as a key protein factor involved in the segregation of genetic material in dividing cells. Deletion or altered level of shugoshin is reported in several human malignancies, as a result, shugoshin now emerges as an important tumour associated gene and a possible target for cancer therapy. Apart from the role in cancer, recent studies also showed the involvement of shugoshin in several other clinical disorders. Through this review, we tried to highlight the clinical relevance of shugoshin.

The introduction of the Internet of Things (IoT), i.e. the interconnection of embedded devices over the Internet, has changed the world we live in from the way we measure, make calls, print information and even the way we get energy in our offices or homes. The convenience of IoT products, like CCTV cameras, IP phones, and oscilloscopes, is overwhelming for end-users. In parallel, however, security issues have emerged and it is essential for infrastructure providers to assess the associated security risks. In this paper, we propose a novel method to detect IoT devices and identify the manufacturer, device model, and the firmware version currently running on the device using the page source from the web user interface. We performed automatic scans of the large-scale network at the European Organization for Nuclear Research (CERN) to evaluate our approach. Our tools identified 233 IoT devices that fell into eleven distinct device categories and included 49 device models manufactured by 26 vendors from across the world.

To establish simulated micro-gravity conditions, biological organisms are placed on a simulated microgravity system, which primarily rotate in two or three dimensions and rely on slow sedimentation with latency to detect gravity. Fluid dynamics arise as a consequence of rotation of the chambers with in which the cells are filled. To minimize the effects of centrifugal forces, it is necessary to position the samples as close to the center of rotation as possible. Strong shear forces and velocities within the vessel can have an adverse impact on cells, making this a critical topic in cell biology. During experimental investigation, this specific phenomenon is not apparent, but numerical modelling readily illustrates and is not widely analyzed in literature's. Furthermore, bulk flask are frequently employed on random positioning machines (RPM), not merely because they demand a substantial quantity of reagents. The flask presented in the study can be easily developed and fitted in conventional cell culture plates containing medium and reagents similar to those used in ground experiments, thus allowing it to remain close to the center of rotation. In the present study, a series of fluid dynamics simulations are performed to examine the impact of shear forces within the microvessel presented under varying conditions using a foreign medium condition, and these results are compared with existing vessels by observing the effects of shear forces and maximum velocity zones.

This paper presents a multi-year research study conducted at the University of Toledo, aimed at improving human-machine teaming (HMT) methods and technologies. With the incorporation of artificial intelligence (AI) into 21st-century machines, collaboration between humans and machines has become highly complicated for real-time applications. The penetration of intelligent and synthetic assistants (IA/SA) in virtually every field has opened a path for the new area of HMT. When it comes to crucial tasks such as patient treatment and care, defense, and industrial production, the use of non-standardized HMT technologies may pose a risk to human lives as well as up to billions of taxpayer dollars. A thorough literature survey revealed that there are not many established standards or benchmarks for HMT. In this paper, we aim to address the lack of HMT design and development standards. We propose a method to design an HMT based on a generalized architecture. This design includes the development of an intelligent collaborative system and human team. Followed by processes and metrics to test and validate the proposed model, we present a novel human-in-the-loop (HIL) simulation method using two controlled HMT scenarios; first, emergency care provider (ECP) training, and second, patient treatment by an experienced medic. Both scenarios include humans processing visual data and performing actions that represent real-world applications while responding to a Voice-Based Synthetic Assistant (VBSA) as a collaborator that keeps track of actions. As part of these HMT simulation studies, the impact of each parameter related to machines, humans, and HMT (such as errors made by humans and by the VBSA) is presented from the perspective of performance, rules, roles, and operation limitations. In addition, based on the analysis of results from two case studies, we presented guidelines for designing future HMT. Our conclusions indicate that the proposed HIL can be used to perform standardization studies in the pursuit of developing techniques for benchmarking HMT that can be used in critical situations.

Wood and plants are made of fibers which contain, in addition to cellulose, lignin and hemicelluloses. Xylan and galactoglucomannan are the dominant secondary cell wall hemicelluloses. Besides fibers’ traditional use in textile and paper industries, the fibers are important materials for the biorefinery industry and for developing biocomposites. In the former context, renewable lignocellulosic biomass is used as feedstock to sustainably produce fuels, chemicals, and polymers. On the other hand, in relation to composites, cellulose fibers which are anisotropic play an important reinforcing role in fiber-matrix interactions. However, for these and other applications, structural analysis of the fibers is important and among many analytical techniques used, Raman spectroscopy is one of the methods. However, given the structural similarity between hemicelluloses and cellulose, many of their Raman contributions overlap. While the wavenumber positions corresponding to the Raman contributions of cellulose, hemicelluloses, and lignin are known, extent to which overlapping features of hemicellulose modify the spectrum of cellulose is not yet fully understood. The present investigation focuses on this aspect by using xylan as one of the hemicelluloses. As a model system, samples with various mass ratios of microcrystalline cellulose (cotton) and xylan (birch wood) were prepared and analyzed by FT-Raman spectroscopy. The findings were then applied to interpret Raman spectra of selected xylan containing delignified plant fibers. It is hoped that insights gained would lead to better interpretation of the spectra of natural and treated plant materials.

Pantoea stewartii subsp. indologenes (Psi) is a causative agent of leafspot of foxtail millet and pearl millet; however, novel strains were recently identified that are pathogenic on onion. Our recent host range evaluation study identified two pathovars; P. stewartii subsp. indologenes pv. cepacicola pv. nov. and P. stewartii subsp. indologenes pv. setariae pv. nov. that are pathogenic on onion and millets or on millets only, respectively. In the current study we developed a pan-genome using the whole genome sequencing of newly identified/classified Psi strains from both pathovars [pv. cepacicola (n= 4) and pv. setariae (n=13)]. The full spectrum of the pan-genome contained 7,030 genes. Among these, 3,546 (present in genomes of all 17 strains) were the core genes that were a subset of 3,682 soft-core genes (present in ≥16 strains). The accessory genome included 1,308 shell genes and 2,040 cloud genes (present in ≤ 2 strains). The pan-genome showed a clear liner progression with >6,000 genes, suggesting the pan-genome of Psi is open. Comparative phylogenetic analysis showed differences in phylogenetic clustering of Pantoea spp. using PAVs/wgMLST approach in comparison to core genome SNP-based phylogeny. Further, we conducted a horizontal gene transfer (HGT) study including four other Pantoea species namely, P. stewartii subsp. stewartii LMG 2715T, P. ananatis LMG 2665T, P. agglomerans LMG L15, and P. allii LMG 24248T. A total of 317 HGT events among four Pantoea species were identified with most gene transfers observed between Psi pv. cepacicola and Psi pv. setariae. Pan-GWAS analysis predicted a total of 154 genes including seven cluster of genes associated with the pathogenicity phenotype on onion. One of the clusters contain 11 genes with known functions and are found to be chromosomally located.

This paper describes a novel concept of producing energy efficient ”Maroon enriched natural gas “ and then Pink hydrogen” from any hydrocarbon base. The key idea is the extraction of hydrogen from water in addition to that from the hydrocarbon in an optimal fashion. This has the benefit of higher water vapor to CO2 exhaust ratio than conventional carbonaceous fuels when generating energy via combustion, a prudent step in achieving Netzero goals in a shorter time, and creating energy independence in most places.. The process of production makes concentrated CO₂ available for use and or sequestration. The process also maximizes use of renewable electricity in hydrogen generation, and maximizes use of existing infrastructure, with a minimum capital cost by energy recycle in the process. The process design applies sound thermodynamic principles which evolved during the nineteenth century, and mimics the geochemical processes going on in some of the natural 'colorless hydrogen'.

Nanoindentation load-depth (P-h) plots is the basis for determination of mechanical properties of the samples and is especially vital for thin coatings deposited on substrates of various mechanical makeup from amorphous-brittle (borosilicate glass) to Silicon (having different crystallographic texture) to ductile substrates like stainless steel as well other aspects like indenter tip shape. The elastic-plastic response by simulated P-h plots as per modified empirical relations have been presented. The outcomes of this computational studies enlighten the database on the P-h plots for various coating/substrate systems and shall aid in the analysis of experimental P-h plots obtained,

In mitosis, faithful chromosome segregation is orchestrated by the dynamic interactions between the spindle microtubules (MTs) emanating from the opposite poles and the kinetochores of chromosomes. However, the precise mechanism that coordinates the coupling of kinetochore components to dynamic MTs has been a long-standing question. Microtubule (MT) associated proteins (MAPs) regulate MT nucleation, dynamics, MT-mediated transport and MT cross-linking in cells. Especially during mitosis, MAPs play an essential role not only in determining the spindle length, position and orientation but also in facilitating robust kinetochore-microtubule (kMT) attachments by linking the kinetochores to spindle MTs efficiently. MT-stability imparted by the MAPs is critical to ensure accurate chromosome segregation. This review primarily focuses on the specific function of non-motor kinetochore MAPs, their recruitment to kinetochores and their MT-binding properties. We also attempt to synthesize and strengthen our understanding of how these MAPs work in coordination with the kinetochore-bound Ndc80 complex (the key component of the MT-binding interface in metaphase and anaphase) to establish stable kMT attachments and control accurate chromosome segregation during mitosis.

MicroRNAs (miRNAs) are single-stranded, noncoding RNA molecules that regulate gene expression post-transcriptionally by binding to messenger RNAs. miRNAs are important regulators of gene expression, and their dysregulation is implicated in many human and dog diseases. Most cancers tested, to date, have been shown to express altered miRNA levels, which indicates their potential importance in the oncogenic process. Based on this evidence, numerous miRNAs have been suggested as potential cancer biomarkers for both diagnosis and prognosis. miRNA-based therapies have also been tested in different cancers and have provided measurable clinical benefits to patients. In addition, understanding miRNA biogenesis and regulatory mechanisms in cancer can provide important knowledge about resistance to chemotherapies, leading to more personalized cancer treatment. In this review, we have comprehensively summarized the importance of miRNA in human and dog cancer research. We have discussed the current state of development and potential for miRNA as both a diagnostic marker and a therapeutic target.

The main goal of the paper is to use a generalized proportional Riemann-Liouville fractional derivative (GPRLFD) to model BAM neural networks and to study some stability properties of the equilibrium. Initially, several properties of the GPRLFD are proved such as the fractional derivative of a squared function. Also some comparison results for GPRLFD are provided. Two types of equilibrium of the BAM model with GPRLFD are defined. In connection with the applied fractional derivative and its singularity at the initial time the Mittag-Leffler exponential stability in time of the equilibrium is introduced and studied. An example is given illustrating the meaning of the equilibrium as well as its stability properties.

In this paper, we study the third order semilocal convergence of the Newton-like method for finding the approximate solution of nonlinear operator equations in the setting of Banach spaces. First, we discuss the convergence analysis under ω-continuity condition, which is weaker than the Lipschitz and Hölder continuity conditions. Second, we apply our approach to solve Fredholm integral equations, where the first derivative of involved operator not necessarily satisfy the Hölder and Lipschitz continuity conditions. Finally, we also prove that the R-order of the method is 2p + 1 for any p $\in$ (0,1].

During the most recent years, a lot of research has been done in creating robots with more self-governance so that they can overcome the challenges that real world environments present. The robot's limited versatility in real world applications can be overcome by the development of Legged robots. Also, as they permit movement in unavailable territory to robots with wheels, Legged Robots are more advantageous. But the potency of the legged robots explicitly its energy usage among alternate points of view really fall behind robots that use wheels. So, the present status of development, there are as yet a few perspectives that need to be analysed, optimized and enhanced. This paper presents review of literature of various biologically inspired legged robots, various techniques adopted for their analysis and optimization and the analysis and optimization of the ones that are not biologically inspired

Oxygen is a pulmonary vasodilator and plays an important role in mediating circulatory transition from fetal and postnatal period. Alveolar oxygen tension (PAO2) and pulmonary arterial PO2 are the main factors that influence hypoxic pulmonary vasoconstriction (HPV). Inability to achieve adequate pulmonary vasodilation at birth leads to persistent pulmonary hypertension of the newborn (PPHN). Supplemental oxygen is the mainstay of PPHN management. However, optimal monitoring of oxygenation to achieve low pulmonary vascular resistance (PVR) and optimize oxygen delivery to vital organs is not known. Noninvasive pulse oximetry measures peripheral saturations (SpO2) and ranges 91-95% are recommended during acute PPHN management. However, for a given SpO2, there is wide variability in arterial oxygen tension, especially with variations in hemoglobin type (transfusions), pH and body temperature. This review evaluates the role of alveolar, preductal, postductal, and mixed venous oxygen tension and SpO2 in the management of PPHN. Translation and clinical studies suggest maintaining an arterial oxygen tension of 50-80 mmHg to help decrease PVR and optimize pulmonary vasodilator management. Nevertheless, there are no randomized clinical trials evaluating outcomes in PPHN based on targeting SpO2 or PO2. However, most critically ill patients have umbilical arterial catheters and postductal arterial oxygenation may not be an accurate assessment of oxygen delivery to vital organs or factors influencing HPV. The mixed venous oxygen tension from umbilical venous catheter blood gas may assess pulmonary arterial PO2 and potentially predict HPV. It is crucial to conduct randomized controlled studies with different PO2/SpO2 ranges and compare outcomes in PPHN.

Groundwater is an important role of the environment in natural resources. The major sources of groundwater contamination in this study were open discharges of domestic sewage, inadequate sewerage system, open defecation, septic tanks, soak pits, contaminated water pools, unorganized solid waste dumping and use of fertilizers, pesticides for agriculture deteriorated the condition. In this present study revealed that the physical and chemical characteristics of ground water in different areas of Kannur district in Kerala have been determined different seasons with respect to its suitability for drinking and agricultural purposes. For this study the groundwater samples were collected during pre-monsoon and post-monsoon seasons from 70 wells representing the entire the study area. The groundwater samples were analyzed for Physico-chemical characteristics using standard techniques in laboratory and compared with standards. The samples were analyzed with reference to the WHO and BIS standards. The groundwater quality information of the entire study area have been prepared using statistical and GIS technique for all the parameters. This paper proved in GIS will be helpful for measuring, monitoring and managing the groundwater pollution in the study area and suggested to protect groundwater resources in the environment.

This case report describes a 71-year-old female with multiple comorbidities who presented with symptoms suggestive of stroke and was subsequently found to have severe acute kidney injury (AKI) due to acute interstitial nephritis (AIN). The patient has normal kidney function at baseline. She has been on hydrochlorothiazide and metoprolol succinate for hypertension for several years. Due to severe acute kidney injury, a kidney biopsy was performed, revealing severe Acute Interstitial Nephritis secondary and multiple intratubular oxalate crystals. The patient's renal function improved after withdrawing HCTZ, volume repletion and initiating prolonged prednisone taper. We attempt to provide some insights through our paper into the mechanism of acute renal failure from crystal nephropathy and its management.

The open source CFD code OpenFOAM has emerged as one of the most popular alternative to commercial CFD solvers. The recent version of OpenFOAM supports overlapping grids, so called Overset mesh. In this type of mesh, one or more sub-collection of control volumes (or cells) are allowed to overlap with other set of cells. This allows for great flexibility in modelling Fluid Structure Interaction (FSI) problems. Fluid mesh can be standard structured mesh of a rectangular/cuboidal/or cylindrical domain. The structure mesh can be generated separately by creating multiple layers around a given body. The overset mesh functionality allows for overlapping or immersing this structured mesh inside the fluid mesh and a relevant FSI or moving dynamics problems can be solved. The idea of overset mesh has been around since eighties but its support in OpenFOAM is very recent. Most CFD codes which support overset mesh have either been in-house or commercial CFD codes. OpenFOAM's support for overset is the first major open source code resource available for CFD problems. The aim of this research is to solve a classical benchmark airfoil problem using OpenFOAM overset mesh and compare the numerical results with experimental result. We report here flow simulations results around NACA 0018. The result obtained from overset mesh compares convincingly well with experimental results. Computations have been carried out for Reynolds numbers in the range of 10⁵ with angle of attack ranging from α= 5 degree to α= 30 degree with an interval of 5 degree. Turbulence is incorporated using k - ε turbulence model. This study helps developing confidence in using OpenFOAM overset support for more complicated flows and moving dynamics. This report is complemented with a brief description of finite volume discretization using overset mesh.

Direct imaging systems that create an image of an object directly on the sensor in a single step are prone to many constraints as a perfect image is required to be recorded within this step. In designing high resolution direct imaging systems with a diffractive lens, the outermost zone width either reaches the lithography limit or the diffraction limit itself imposing challenges in fabrication. However, if the imaging mode is switched to an indirect one consisting of multiple steps to complete imaging, then different possibilities open up. One such methods is the widely used indirect imaging method with Golay configuration telescopes. In this study, a Golay-like configuration has been adapted to realize a large area diffractive lens with three sub-aperture diffractive lenses. The sub-aperture diffractive lenses are not required to collect light and focus them to a single point as in a direct imaging system but to focus independently on different points within the sensor area. This approach of Large Area Diffractive lens with Integrated Sub-Apertures (LADISA) relaxes the fabrication constraints and allows the sub-aperture diffractive elements to have a larger outermost zone width and smaller area. The diffractive sub-apertures were manufactured using photolithography. The fabricated diffractive element has been implemented in indirect imaging mode using non-linear reconstruction and Lucy-Richardson-Rosen algorithm with synthesized point spread functions. The computational optical experiments revealed an improved optical and computational imaging resolutions compared to previous studies.

In this paper, we introduced a generalized ∆-implicit locally contractive condition and give some examples to support it and to show its significance in fixed point theory. We prove that the mappings satisfying generalized ∆-implicit locally contractive condition admits a common fixed point, where, the ordered multiplicative GM−metric space is chosen as underlying space. The obtained fixed point theorems generalize many earlier fixed point theorems on implicit locally contractive mappings. In addition, some nontrivial and interesting examples are provided to support our findings. To demonstrate the originality of our new main result, we apply it to show existence of solutions to a system of nonlinear -Volterra type- integral equations.

UEDVT still remains an underdiagnosed entity due to a significant percentage of patients who remain asymptomatic. The etiology of UEDVT is overwhelmingly attributed to secondary causes including but not limited to central venous access devices and malignancy. Treatment modalities include anticoagulation, catheter directed thrombolysis, percutaneous mechanical thrombectomy or a multimodality approach along with the management of underlying etiology. We describe a case of a female with breast cancer, who came with left UEDVT and CVC malfunction and was successfully treated using the ClotTriever system to maintain continuous intravenous access.

Artificial Intelligence (AI) models are expected to have a great impact in the manufacturing industry, optimizing time and resource cost by enabling applications such as predictive maintenance (PM) of production machines. A necessary condition for this is the availability of high quality data collected as close as possible to the process in question. With the advent of 5G equipped multi sensor platforms (MSPs), high sampling rate data can be collected and transmitted for processing in real time. This poses a data security challenge, since this data may give valuable insight into confidential business information of companies. Federated learning (FL) enables the training of AI models with data from multiple sources without it leaving the shop floor, by utilizing distributed computing resources available on premise. This paper introduces an architecture of FL based on data collected from 5G MSPs for enabling PM in industrial environments and discusses its potential benefits and challenges.

MiRNAs are 20-22 nucleotide long single-stranded non-coding RNA sequences, which can regulate post transcriptional activity of mRNA by binding with it at 3’UTR region (untranslated region). Thus deregulation of miRNA expression is responsible for dysregulating mRNA function which contributes in developing various diseases as well as cancerous phenotypes. Alteration of single nucleotide in miRNA sequence is one of the reasons behind deregulation of miRNA expression. The most frequent carcinoma in current day is breast cancer which causes a high mortality among women around the world as well as India. Despite of the advancement of diagnostic tools, strategies and treatment, the cases of breast cancer is increasing every year. There are plenty of biomarkers like ER, PR, Her2, Ki-67, etc available which are frequently used in diagnosis and treatment of breast cancer. After the discovery of MiRNA in 1993 in Caenorhabiditis elegans, it is attracting all the limelight in diagnosis and treatment of different carcinomas as well as breast cancer. In this review we will discuss on involvement of different types of MiRNAs and miR SNPs in breast cancer occurrence and susceptibility in a detailed manner.

Distal Sensory Peripheral Neuropathy (DSP) is a common complication in HIV-infected individ-uals, leading to chronic pain and reduced quality of life. Despite antiretroviral therapy (ART), DSP persists, often prompting the use of opioid analgesics, which can paradoxically worsen symptoms through opioid-induced microbial dysbiosis. This study employs the HIV Tg26 mouse model to investigate HIV-DSP development and assess gut microbiome changes in response to chronic morphine treatment and ART using 16s rRNA sequencing. Our results reveal that chronic morphine and ART exacerbate HIV-DSP in Tg26 mice, primarily through mechanical pain path-ways. As the gut microbiome may be involved in chronic pain persistence, microbiome analysis indicated distinct bacterial community changes between WT and Tg26 mice as well as morphine and ART-induced microbial changes in the Tg26 mice. This study reveals the Tg26 mice model to be a relevant system that can help elucidate the pathogenic mechanisms of opioid and ART-induced exacerbation of HIV-associated pain. Our results shed light on the intricate inter-play between HIV infection, ART, opioid use, and the gut microbiome in chronic pain development. They hold implications for understanding the mechanisms underlying HIV-associated pain and microbial dysbiosis, with potential for future research focused on prevention and treatment strategies.

Several recent surges in COVID-19 cases due to newly emerging variant strains of SARS-CoV-2 with greater transmissibility have highlighted the virus’s capability to directly modulate spike-ACE2 interactions and promote immune evasion by sterically masking the immunogenic epitopes. Recently, there have also been reports of the bidirectional transfer of coronavirus between different animal species and humans. The ability of coronavirus to infect and adapt to a wide range of hosts can be attributed to new variants that modify the molecular recognition profile of the spike protein (S protein). The receptor-binding domain of the spike protein specifically interacts with key host receptor molecules present on the host cell membranes to gain entry into the host and begin the infection cycle. In this review, we discuss the molecular, structural, and functional diversity associated with the coronavirus receptors across their different phylogenetic lineages and its relevance to various symptomatology in the rapid human-to-human infection in COVID-19 patients, tropism, and zoonosis. Despite this seeming diversity of host receptors, there may be some common underlying mechanisms that influence the host range, virus transmissibility, and pathogenicity. Understanding these mechanisms may be crucial in not only controlling the ongoing pandemic but also help in stopping the resurgence of such virus threats in the future.

The Coronavirus Disease 2019 (COVID-19) pandemic has resulted in a significant surge of critically ill patients and an unprecedented demand on intensive care services. The rapidly evolving understanding of pathogenesis, limited disease specific evidence and demand-resource imbalances have posed significant challenges for intensive care clinicians. COVID-19 is a complex multisystem inflammatory vasculopathy with a significant mortality implication for those admitted to intensive care. Institutional strategic preparation and meticulous intensive care support are essential to maximising outcomes during the pandemic. The significant mortality variation observed between institutions and internationally, despite a single aetiology and uniform presentation, highlights the potential influence of management strategies on outcome. Given that optimal organ support and adjunctive therapies for COVID-19 have not yet been well defined by trial-based outcomes, strategies are predicated on existing literature and experiential learning. This review outlines the relevant pathophysiology and management strategies for critically ill patients with COVID-19, and shares some of the collective learning accumulated in a high volume Severe Respiratory Failure centre in London.

Salinity is a significant abiotic stress factor for ornamental plants cultivated in greenhouses, as they are supplied with fertilizers over a long period of time. It causes drastic yield losses in com-mercially important ornamentals such as Gerbera jamesonii, whose cut flowers rank fifth in the global flower trade. In the current study, pretreatment of G. jamesonii plants (white and yellow flowering varieties) with optimum concentrations of thiourea (1.0 mM, 5.0 mM & 10.0 mM) in-duced plant salt-tolerance. Gerberas pretreated with thiourea (5.0 mM), when exposed to NaCl (200mM), showed no signs of plant stress or phenotypic abnormalities, as seen in gerberas ex-posed to NaCl without thiourea pretreatment. Moreover, thiourea application significantly pro-moted plant growth as evidenced by increases in fresh and dry leaf weight, relative water con-tent, total protein content, free proline content, and chlorophyll. A decrease in H2O2 and MDA content and an increase in antioxidant enzymes superoxide dismutase, catalase, ascorbate perox-idase, glutathione reductase, and peroxidase activity indicate minimal cellular damage in gerberas treated with thiourea. Thus, spraying leaves with thiourea (5.0 mM) could help gerbera plants overcome the deleterious effects of salt stress during repeated fertilization in nethouses. In addi-tion to alleviating salt stress, thiourea can also be used as a biofertilizer. This could also be ex-tended to other ornamental species to promote sustainable development of the floriculture indus-try.

Object. Utilization of pedicle screws (PS) for spine stabilization is common in spinal surgery. With reliance on visual inspection of anatomical landmarks prior to screw placement, the free-hand technique requires a high level of surgeon skill and precision. Three-dimensional (3D) computer-assisted virtual neuronavigation improves the precision of PS placement and minimize steps. Methods. Twenty-three patients with degenerative, traumatic, or neoplastic pathologies received treatment via a novel three-step PS technique that utilizes a navigated power driver in combination with virtual screw technology. 1) Following visualization of neuroanatomy using intraoperative CT, a navigated 3-mm match stick drill bit was inserted at anatomical entry point with screen projection showing virtual screw. 2) Navigated Stryker Cordless Driver with appropriate tap was used to access vertebral body through pedicle with screen projection again showing virtual screw. 3) Navigated Stryker Cordless Driver with actual screw was used with screen projection showing the same virtual screw. One hundred and forty-four consecutive screws were inserted using this three-step, navigated driver, virtual screw technique. Results. Only 1 screw needed intraoperative revision after insertion using the three-step, navigated driver, virtual PS technique. This amounts to a 0.69% revision rate. One hundred percent of patients had intraoperative CT reconstructed images to confirm hardware placement. Conclusions. Pedicle screw placement utilizing the Stryker-Ziehm neuronavigation virtual screw technology with a three step, navigated power drill technique is safe and effective.

This document outlines best practice recommendations for an acute care physiotherapy for patients with COVID-19, with an emphasis on critical care rehabilitation including the patients in extra corporeal membrane Oxygenation (ECMO) support, developed for practice in Qatar but adaptable within any settings. This recommendation is the result of a combination of systematic evidence search, subsequent critical evaluation of retrieved evidence and consensus process. The agreed recommendations were integrated into a physiotherapy clinical reasoning algorithm. It includes recommendations on physiotherapy referral, screening, management categories and best practice recommendations. It is intended for use by physiotherapists and other relevant stakeholders in the acute care setting caring for adult patients with suspected and/or confirmed COVID-19.

The Upper Hunter Valley is a major coal mining area in New South Wales (NSW), Australia. Due to the ongoing increase of mining activities, PM10 (air-borne particle with an aerodynamic diameter less than 10 micrometres) pollution has become a major air quality concern in local communities. The early part of this study identified two air quality subregions in the valley. This paper aims to provide a holistic summarisation of the relationships between elevated PM10 pollution in two subregions and the local- and synoptic-scale meteorological conditions for spring and summer, when PM10 pollution is relatively high. A catalogue of twelve synoptic types and a set of six local meteorological patterns have been quantitatively derived and linked to each other using the self-organising map (SOM) technique. The complex meteorology-air pollution relationships have been visualised/interpretated on the SOM planes for two representative locations. It was found that the influence of local meteorological patterns differed significantly for mean PM10 levels vs the occurrence of elevated pollution events and between air quality subregions. In contrast, synoptic types showed generally similar relationships with mean vs elevated PM10 pollution in the valley. Two local meteorological patterns, the hot-dry-northwesterly wind conditions and the hot-dry-calm conditions, were found most PM10 pollution conducive in the valley when combined with a set of synoptic counterparts. These synoptic types are featured with the influence of eastward migrating continental high pressure system and westerly troughs, or a ridge extending northwest towards coastal northern NSW or southern Queensland from the Tasman Sea. The method and results can be used in air quality research for other locations of NSW, or similar regions elsewhere.

Observations of ocean surface winds from Indian scatterometer SCATSAT-1 have been combined with background wind field from a numerical weather prediction (NWP) model available at National Centre for Medium Range Weather Prediction (NCMRWF) to generate a 6-hourly gridded hybrid wind product. A distinctive feature of the study is to produce a global gridded wind field from SCATSAT-1 scatterometer passes with spatio-temporal data gaps at regular synoptic hours relevant for forcing models and other NWP studies. This is done by making use of concepts from the modern particle filter technique, which does not represent the model probability density function (PDF) following the Gaussian technique. The 6 hourly hybrid wind is generated for the entire year of 2018 and is validated using the wind speed from daily gridded level-4 SCATSAT-1 winds (L4AW), Cross Calibrated Multi-Platform dataset (CCMP) and global buoy data from National Data Buoy Centre (NDBC). The results indicate potential of the technique to produce scatterometer winds at the desired temporal frequency with significantly less noise and along swath biases. The study shows the generated hybrid winds have very high quality with respect to the already existing daily product available from ISRO.

The Upper Hunter Valley is a major coal mining area containing approximately 40% of the currently identified total coal reserves in New South Wales (NSW), Australia. Due to the ongoing increase of mining activities, PM10 (air-borne particle with an aerodynamic diameter less than 10 micrometres) pollution has become a major air quality concern in local communities. This paper summarises the spatial and temporal variability modes of PM10 pollution in the region, based on long-term multi-site monitoring data and the application of the rotated principal component analysis (RPCA) and wavelet analysis techniques. RPCA identified two distinct air quality clusters/subregions in the valley, one in the west/northwest, the other in the southeast. Wavelet analysis revealed the annual cycle to be most persistent temporal mode of PM10 variability in both subregions, with intermittent signals observed at time scales of around 120, 30~90 and under 30 days. How these variation modes are related to the effects of local PM10 emissions and the influence of meteorology at different time scales deserves further attention in future work. The findings will be used in air quality reporting and forecasting in NSW. The methodology and results can also be useful for air quality research in similar regions elsewhere.

Corona virus disease (COVID-19) has infected over more than 10 million people around the globe and killed at least 500K worldwide by the end of June 2020. As this disease continues to evolve and scientists and researchers around the world now trying to find out the way to combat this disease in most effective way. Chest X-rays are widely available modality for immediate care in diagnosing COVID-19. Precise detection and diagnosis of COVID-19 from these chest X-rays would be practical for the current situation. This paper proposes one shot cluster based approach for the accurate detection of COVID-19 chest x-rays. The main objective of one shot learning (OSL) is to mimic the way humans learn in order to make classification or prediction on a wide range of similar but novel problems. The core constraint of this type of task is that the algorithm should decide on the class of a test instance after seeing just one test example. For this purpose we have experimented with widely known Generalized Regression and Probabilistic Neural Networks. Experiments conducted with publicly available chest x-ray images demonstrate that the method can detect COVID-19 accurately with high precision. The obtained results have outperformed many of the convolutional neural network based existing methods proposed in the literature.

Black Knot (BK) is a deadly disease of European (Prunus domestica) and Japanese (Prunus salicina) plums caused by the hemibiotrophic fungus Apiosporina morbosa. Generally, phytopathogens hamper the balance of primary defense phytohormones such as salicylic acid (SA)-jasmonic acid (JA) balance for disease progression. Thus, we quantified the important phytohormones titers in tissues of susceptible and resistant genotypes belonging to European and Japanese plums at five different time points. The results suggested auxin-cytokinins interplay driven by A. morbosa appeared to be vital in disease progression by hampering the plant defense system via perturbance in SA, JA, and gibberellic acid. The results further point out that SA and JA in plant defense are not necessarily antagonistic always, especially in woody perennials. Results also suggest that the changes in SA and JA content following BK disease infection and progression in plums could be utilized as phytohormonal markers in the identification of BK-resistant cultivars.

Black Knot (BK) is a deadly disease of European (Prunus domestics) and Japanese (Prunus salicina) plums caused by the hemibiotrophic fungus Apiosporina morbosa. After infection, the appearance of warty black knots indicates a phytohormonal imbalance in infected tissues. Based on this hypothesis, we quantified phytohormones such as indole-3-acetic acid, tryptophan, indoleamines (N-acetylserotonin, serotonin, and melatonin), and cytokinins (zeatin, 6-benzyladenine, and 2-isopentenyladenine) in temporally collected tissues of susceptible and resistant genotypes belonging to European and Japanese plums during of BK progression. The results suggested auxin-cytokinins interplay driven by A. morbosa appears to be vital in disease progression by hampering the plant defense system. Taken together, our results indicate the possibility of using the phytohormone profile as a biomarker for BK resistance in plums.

Background: The fascial system provides an environment that enables all body systems to operate in an integrated manner and is capable of modifying its tensional state in response to the stress applied to it. Recent in vitro, animal and cadaveric studies have shown that “myofascial force transfer” (MFT) has the potential to play a major role in musculoskeletal function and dysfunction.Objective: Human evidence for the existence of invivo MFT is scarce. This scoping review attempts to gather and analyse the available evidence of the in-vivo human MFT studies in order to sustain and facilitate further research and evidence based practice in this field.Methods: A search of most major databases was conducted with relevant keywords that yielded 238 articles as of August 2020. A qualitative analysis of the studies was conducted after rating it with Oxford’s Center for Evidence –based Medicine (CEBM) scale.Result: Nineteen studies ranging from randomized controlled trials to case studies covering 540 patients were included in this review. The analysed studies were highly heterogeneous and of lower methodological quality meddling with the quantitative analysis. Ten studies are confirming a ‘most likely’ existence of MFT, eight studies confirming it as ‘likely’ and one study couldn’t confirm any MFT existence in this review.Conclusion: Findings from in vivo human studies supports the animal and cadaveric studies claiming the existence of MFT which need to be corroborated by the future high quality studies. Forthcoming studies on MFT may give answers and solutions to many of the human musculoskeletal mysteries or dysfunctions.

This study presents an extensive collection of data on the aerodynamic behavior at a low Reynolds number and geometric coefficients for 2900 airfoils obtained through the class shape transformation (CST) method. By employing a verified OpenFOAM-based CFD simulation framework, lift and drag coefficients were determined at a Reynolds number of 10^5. Considering the limited availability of data on low Reynolds number airfoils, this dataset is invaluable for a wide range of applications, including unmanned aerial vehicles (UAVs) and wind turbines. Additionally, the study offers a method for automating CFD simulations that could be applied to obtain aerodynamic coefficients at higher Reynolds numbers. The breadth of this dataset also supports the enhancement and creation of machine learning (ML) models, further advancing research into the aerodynamics of airfoils and lifting surfaces.

Unwanted proteins and metabolic waste in cerebral spinal fluid are cleared from the brain by meningeal and nasal lymphatics, and perineural sheath of cranial nerves; however, the distribution and clearance of CSF along the subarachnoid space of the entire spinal cord is not fully understood. It was hypothesized that the anatomical resolution of Cryo-Fluorescence Tomography (CFT) could provide the visual evidence of clearance across the spinal cord at each level of the vertebral column. To that end, isoflurane anesthetized mice were infused into the lateral cerebroventricle with 5.0 µl of quantum dots [QdotR 605 ITKTM amino (PEG)] over two mins. Mice were allowed to recover (ca 2-3 min) and remained awake and ambulatory for 5, 15, 30, 60 and 120 minutes after which they were euthanized, and the entire intact body frozen at -800. The entire mouse was sectioned and imaged to produce an isotropic voxel resolution of 35 µm. Both white light and fluorescent images were captured after each slice to produce high resolution three-dimensional volumes for each mouse. CFT highlighted the circulation of tracer throughout the ventricular system and central canal of the spinal cord and the entire subarachnoid space of the CNS. Signal could be visualized in the nasal cavity, deep cervical lymph nodes, thoracic lymph nodes and more superficial submandibular lymph nodes as early as 15 min post infusion. Fluorescent signal could be visualized along the dorsal root ganglia and down the proximal extension of the spinal nerves of the thoracic and lumbar segments at 30 min. There was significant accumulation of tracer in the lumbar and sacral lymph nodes between 15- 60 min. The dense fluorescent signal in the thoracic vertebrae noted at 5- and 15-mins post infusion was significantly reduced by 30 min. Indeed, all signal in the spinal cord was ostensibly absent by 120 min except for trace amounts in the coccyx. The brain still had some residual signal at 120 min. These data show that Qdots with a hydrodynamic diameter of 16-20 nm rapidly clear from the brain of awake mice. These data also clearly demonstrate the rapid distribution and efflux of trace along a major length of the vertebral column and the potential contribution of the spinal cord in the clearance of brain waste.

PDEF is expressed in luminal epithelial cells of the prostate gland and associates with luminal phenotype. Hippo pathway regulates cell growth/proliferation, cellular homeostasis, and organ development by modulating phosphorylation of its downstream effectors. In previous studies, we observed decreased levels of PDEF during prostate cancer progression. In the present studies, we evaluated the effects of PDEF on total and phospho (Ser-127)YAP1 protein(a downstream effector of the Hippo pathway) levels in PC3 cells, a line of castrate resistant prostate cancer. We observed that the expression of PDEF in PC3 cells resulted in increased increased phospho(Ser127) -YAP1 protein levels. Our immunofluorescence analysis for YAP1 revealed an increased cytoplasmic/nuclear ratio of YAP1 in PDEF-PC3 cells as compared to VC-PC3 cells, suggesting PDEF may play a critical role in modulating YAP1 phosphorylation, and by extension in the regulation of the Hippo pathway. We also observed a decrease in YAP1 protein levels in prostate cancer tissues as compared to normal prostate tissues. Our analysis of multiple publicly available clinical cohorts revealed a gradual decrease in YAP1 mRNA expression during prostate cancer progression and metastasis. This decrease was similar to the decrease in PDEF levels which we reported earlier. In addition we observed further decreased in PDEF and YAP1 expression in Neuro-Endocrine Prostate Cancer (NEPC), and a direct correlation between PDEF and YAP1 expression. To the best of our knowledge, these results provide the first demonstration of modulation of YAP1 by PDEF in any system and suggest a cross-talk between PDEF and the Hippo pathway.

Cut flowers of Gerbera jamesonii, renowned globally for their vibrant colors and extended shelf life, play a pivotal role in the flourishing floriculture industry. However, repeated fertigation in nethouses/polyhouses poses a significant challenge leading to production losses. In response to this challenge, we hypothesized that the application of Ascorbic acid (AsA), an antioxidant, in optimal concentrations could alleviate the detrimental effects of salt toxicity and enhance Gerbera production. Our objective was to investigate the impact of exogenous AsA (1.0 mM, 2.0 mM, and 4.0 mM) as a foliar spray, followed by NaCl (200 mM) treatment, across two cultivars of Gerbera: white-flowered (salt sensitive) and yellow flowered (salt tolerant) cultivars. The research employed a comprehensive approach, applying AsA and NaCl treatment to evaluate their effects on chlorophyll, proline, and total soluble protein content, MDA, H2O2, and antioxidant enzyme activities (SOD, CAT, APX, GR, and POD). Following exposure to 2.0 mM AsA, treated plants displayed a notable increase in chlorophyll, Proline, and soluble protein content. Concurrently, MDA and H2O2 levels, indicator of intracellular damage, exhibited a decrement, suggesting AsA's protective role against salt stress. Moreover, enhanced antioxidant Enzyme activities were observed. The application of AsA (2.0 mM) not only induced salt tolerance in Gerbera but also showed potential benefits for its overall growth and development. This study underscores the promising role of AsA in mitigating salt-induced challenges in Gerbera cultivation.

The South African government introduced a nationwide lockdown in March 2020 to mitigate the spread of Covid-19. Among other restrictions, the government banned the sale of tobacco products, which lasted for nearly five months. We performed a Google search using the keywords smok*, puff*, lockdown, tobacco, and cigarette*, for articles published in English from 23 March 2020to 18 December 2020 and analysed 441 online media articles. We identified the main arguments made by proponents and opponents of the tobacco sales ban, which were categorised into themes. Three themes were prominent: medical, legal, and economic/financial. Legal aspects were covered in 48% of articles, followed by economic (34%), and medical aspects (18%). The media was generally ambivalent about the tobacco sales ban during the first five weeks of lockdown. Sentiment then turned against the ban. because the medical rationale was not well communicated by the government, there was limited empirical evidence of a link between smoking and contracting Covid-19, and the sales ban was ineffective, since most smokers still purchased cigarettes. Policy framing in the media plays an important role in how the public receives the policy. Any future tobacco control policy intervention should be well-considered and appropriate cessation support services offered.

The production and quality of Phaseolus vulgaris (snap bean) have been negatively impacted by leaf crumple disease caused by two whitefly-transmitted begomoviruses; cucurbit leaf crumple virus (CuLCrV) and sida golden mosaic Florida virus (SiGMFV), which often appear as a mixed infection in Georgia. Host resistance is the most economical management strategy against whitefly-transmitted viruses. Currently, information is not available with respect to resistance to these two viruses in commercial cultivars. In two field seasons (2018 and 2019), we screened Phaseolus sp. genotypes (n = 84 in 2018; n = 80 in 2019; most of the genotypes were common in both years with a few exceptions) for resistance against CuLCrV and/or SiGMFV. Twenty genotypes with high- to moderate-levels of resistance (disease severity ranging from 5-50%) to CuLCrV and/or SiGMFV were identified. Twenty-one genotypes were found to be highly susceptible with a disease severity of ≥66%. Adult whitefly counts differed significantly among snap bean genotypes for both years. The whole genome of these Phaseolus sp. (n=82) genotypes was sequenced and genetic variability among them was identified. Over 900 giga-base (Gb) of filtered data were generated and >88% of the resulting data were mapped to the reference genome, and SNP and Indel variants in Phaseolus genotypes were obtained. A total of 645,729 SNPs and 68,713 Indels including 30,169 insertions and 38,543 deletions were identified, which were distributed in 11 chromosomes with chromosome 02 harboring the maximum number of variants. These phenotypic and genotypic information will be helpful in genome-wide association studies that will aid in identifying genetic basis of resistance to these begomoviruses in Phaseolus sp.

Oral diseases remain a major health problem worldwide, with the World Health Organisation reporting that oral health neglect affects almost half of the world’s population. Quorum sensing molecules (QSMs) influence oral biofilms in various ways with knowledge of direct oral QSM-host interaction being limited, and such studies could provide more insight into the cross-kingdom communication occurring during oral disease development. This review aims to explore the literature on oral QSM-host interaction and to highlight areas of advancement in this field. QSM CSP-1 produced by Gram-positive oral bacteria was found to interact with T2R receptors, activating NF-kB signalling and leading to remodeling of the cytoskeleton. AI-2 in the oral cavity was found in various studies to elicit an inflammatory response in specific oral cells. Overall AHL detection methods remain an area for development, through which greater understanding of oral QSMs’ influence on host cells can be achieved. In conclusion, from the current literature it can be inferred that that QSMs are utilised by host cells to detect bacterial presence and in the majority of cases elicit an immune response towards the environmental QSMs. This may provide a base to target QSMs as novel treatment of oral diseases.

Alzheimer’s disease (AD) is an age-related neuropsychiatric disorder and a common cause of progressive dementia. Diltiazem (DTZ), the non-dihydropyridine benzothiazepine class of calcium channel blocker (CCB), used clinically in angina and other cardiovascular disorders have proven neurological benefits. In the present study, the neuroprotective anti-dementia effects of DTZ against intra-cerebroventricular-streptozotocin (ICV-STZ)-induced sporadic AD (SAD)-type rat model was investigated. ICV-STZ-induced cognitive impairments were measured by passive avoidance and Morris water maze tasks. Anti-oxidative enzyme status, pro-inflammatory markers, and amyloid-beta (Aβ) protein expression in rat brain tissues were measured by ELISA kits, Western blotting, and immunostaining techniques. Data revealed that ICV-STZ injection in rats significantly induced cognitive deficits and altered the levels of oxidative and pro-inflammatory markers (p < 0.05 ~ p < 0.001). Treatment with DTZ (10 mg/kg, 20 mg/kg, and 40 mg/kg. p.o.) daily for twenty-one days, 1 h before a single ICV-STZ (3 mg/kg) injection, significantly improved cognitive impairments, ameliorated the ICV-STZ-induced altered nitrite, pro-inflammatory cytokines (TNF-α, and IL-1β) and anti-oxidative enzyme levels (superoxide dismutase, lipid peroxidation, and glutathione). Further, DTZ restored the increased Aβ protein expression in ICV-STZ-induced brain tissue Considering the data obtained, DTZ exhibited a potential neuroprotective anti-dementia role in ICV-STZ-induced SAD-type conditions in rats and might be repurposed as a potential therapeutic agent in the treatment and management of AD and related dementia pathologies.

Environmental interventions and ecological adaptations harbor millions of valued substances and metabolites in plants which can be employed and commercialized for human benefits. Present study encompasses the untapped potential of pine needles of Indo-Himalayan region for the production of different metabolites and their pharmacological significance in terms of antioxidant and antimicrobial activity. Total phenolic and flavonoid content from the needles of ten pine species was quantified using three different solvent systems. Results revealed that out of 10 different selected Pinus species, Pinus taeda showed highest concentration of total phenolics, soluble-F phenolics and flavonoids content (approx.147.02 mg/g, 141.08 mg/g and 21.91mg/g respectively) as compared to other species. On the other hand P. greggii showed highest Bound-W phenolic content (approx.3.62mg/g). Among all the selected plant species, the needles of P.echinata exhibited the highest and P.thunbergii had the lowest ratio of total flavonoids to total phenolics. Most of these compounds were found to have effective antioxidant activities as well as antimicrobial activity, as estimated by oxygen radical absorbance capacity (ORAC) and disk diffusion test respectively.

Importance: p53 is an unequivocal tumor suppressor altered in half cancers. The immune system produces systemic p53 autoantibodies (p53 Abs) in many cancer patients. Objective: The focus of this systemic review and meta-analysis is on the prognostic value of p53 Abs expressed in the serum of patients with solid tumors. Data Sources: All the clinical investigations were searched on PubMed, MBase and Cochrane from 1993 reporting the first study until May 2021. Study Selection: Studies were included that met the following criteria: 1) participants with cancer; 2) outcome results expressed in relation to the presence of a p53 antibody; 3) a primary outcome (disease free survival, overall survival or progression free survival) expressed as hazard ratio (HR). The following exclusion criteria were used: 1) insufficient data available to evaluate outcomes; 2) animal studies; 3) studies with less than 10 participants. 1333 potentially relevant articles; studies as duplicates, non-patients studies or reviews were excluded. After viewing the titles and abstracts of the 52 remaining studies, the full texts of 34 studies were retrieved and 12 studies were included in the analysis. Data Extraction and Synthesis: PRISMA guidelines were used for abstracting and assessing data quality and validity by three independent observers. The summary estimates were generated using a fixed-effect model (Mantel–Haenszel method) or a random-effect model (DerSimonian–Laird-method) depending on the absence or presence of heterogeneity (I2). Main Outcome(s) and Measure(s): The primary study outcome was to determine the prognostic value of p53 Abs from a large population size of patients with solid tumors, as determined before data collection. Results: In total 12 clinical studies and of which 2094 patients were included and it was determined that p53-wt Abs expression in the serum significantly correlated with a worse survival of cancer patients (95% CI 1.48 [1.24, 1.77]; p<0.00001). On the contrary, data from literature indicated that there was a potential association between p53-mut Abs antibodies with better survival. Conclusions and Relevance: This is the first meta-analysis proving the diagnostic utility of p53-Abs for cancer patients, predicting a worse outcome. The serum-p53 value (s-p53-value) could be useful for future theranostics.

This paper investigates the efficacy of YOLOv8 variants for vehicle detection and license plate detection within smart parking applications, emphasizing performance under varying ambient lighting conditions. The proposed system is to seize full video frames, extracts regions of interest containing vehicles, and feeds them into separate, pre-trained YOLOv8 models – one dedicated to vehicle detection and another for license plate detection. Four YOLOv8 variants, nano, small, medium, and large, are evaluated. As a pre-processing step, the images are processed with the help of OpenCV and Pillow libraries to adjust the luminosity and increase the images’ DPI so that they would be easy to perceive by the Tesseract OCR engine. Sixteen potential combinations arise from pairing the four YOLOv8 models for vehicle and license plate detection tasks. To identify the most suitable combinations, we employ the Multi-Criteria Decision-Making method, specifically Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) analysis. This analysis considers 4 critical metrics: Precision, mean average precision at 95% Intersection of Union threshold, Recall and Total Inference Time. The objective is to achieve an optimal balance between high accuracy and real-time processing. Following the selection of optimal YOLOv8 combinations through TOPSIS analysis, we assess their performance under varying ambient light intensity (measured in lux). This evaluation aims to identify the most robust model combinations that ensure accurate vehicle and license plate recognition across the diverse lighting conditions encountered in real-world environment.

We report the growth of graphene at a low temperature using the cold wall chemical vapor deposition technique (CWCVD). Few layered (~6-8 layers) graphene were grown on nickel-coated silicon with acetylene as the precursor gas. The advantage of the combination of the acetylene (as a carbon feedstock) and the nickel catalyst was the lowering of the graphene growth temperature. Nickel coated silicon samples were pre-treated (heat treatment in inert atmosphere) before the growth and the effect of the pre-treatment on the catalyst as well as on the grown film was studied. The final samples were characterized with scanning electron microscopy and Raman spectroscopy. In CWCVD route, the heating of only the substrate holder enabled high heating and cooling rates, which, along with the control over partial pressure of the precursor gas had profound effect on the formation of graphene. In the best sample we have achieved almost equal intensity of the G and 2D peaks in Raman spectrum, which implied about ~6-8 layers of Graphene. The defect peak (the D band) was extremely small in the sample and it was attributed to the ripples and the underlying roughness of the nickel film. We analyzed that a proper choice of the thickness of catalyst layer and a higher cooling rate after graphene growth it would be possible to obtain monolayered graphene. Similar samples grown in a normal atmospheric CVD (with some engineered design to promote fast cooling) were also compared with the cold wall CVD grown samples and plasma assisted CWCVD, and cold-wall CVD demonstrated a better control over the quality of graphene film through the fast cooling and a controlled partial pressure of the precursor gas.

miRNAs are major regulators of eukaryotic gene expression, host immunity, and play an important role in the inflammation-mediated pathways in periodontal disease (PD) pathogenesis. Expanding our previous observation with the global miRNA profiling using partial human mouth microbes and lack of in vivo studies involving oral spirochete Treponema denticola induced miRNAs, this study was designed to delineate the global miRNA expression kinetics during progression of periodontitis in mice infected with T. denticola by using NanoString nCounter® miRNA panels. All the T. denticola-infected male and female mice at 8- and 16 weeks demonstrated bacterial colonization (100%) on the gingival surface, and an increase in alveolar bone resorption (p &lt; 0.0001). A total of 70 miRNAs with at least 1.0-fold differential expression/regulation (DE) miRNAs (26 upregulated and 44 downregulated) were identified. nCounter miRNA expression profiling identified 13 upregulated miRNAs (e.g. miR-133a, miR-378) and 25 downregulated miRNAs (e.g. miR-375, miR-34b-5p) in T. denticola-infected mice mandibles during 8-weeks infection whereas 13 upregulated miRNAs (e.g. miR-486, miR-126-5p) and 19 downregulated miRNAs (miR-2135, miR-142-3p) were observed during 16- weeks of infection. One miRNA (miR-126-5p) showed significant difference between 8-and 16-weeks of infection. Interestingly, miR-126-5p has been presented as a potential biomarker in patients with periodontitis and coronary artery disease. Among the 13 upregulated miRNAs, miR-486, miR-126-3p, miR-126-5p were reported in human gingival plaques samples with periodontitis. KEGG analysis revealed various functional pathways of DE miRNAs such as bacterial invasion of epithelial cells, Ras signaling, Fc gamma R- mediated phagocytosis, osteoclast differentiation, adherens signaling and ubiquitin mediated proteolysis. This is the first study of DE miRNAs in mice mandibles at different time-points of T. denticola infection and the combination of three specific miRNAs miR-486, miR-126-3p, miR-126-5p may serve as an invasive biomarker of T. denticola in PD. These miRNAs may have significant role in PD pathogenesis and establishes a link between miRNA, periodontitis, and systemic diseases.

Falls, especially those left unattended, are fatal for the elderly. Several efforts have been made to use the Internet of Things and Machine Learning algorithms to detect falls. All such systems have issues such as (a) sensor placement on the torso and thigh which will be uncomfortable for the elderly. (b) Predictions made on the cloud- the result of the prediction is then sent back to the end device to raise an alert. This is prone to network connectivity and latency issues. We have built an end/device that is wrist-worn and has multiple Inertial Measurement Unit sensors and a heart sensor. We have developed three novel ensemble algorithms (a)Stack(A) (b) Variable weighted Ensemble Voting algorithm-B(VWE(B)), and (c) Variable weighted Ensemble Voting algorithm-C (VWE(C)). Since the ensemble algorithm is run on the end-device built around Qualcomm Snapdragons 820c, we do both feature extraction and selection to reduce data dimensionality. We have used multiple methods such as (a) Identifying features that have maximum impact (b) Principal Component Analysis (PCA) (c) Shapley’s values (d) Cross-Correlation combined with relliefF. We got an accuracy of 97% and specificity of 99%. In this paper, we present the analysis of the system with and without pruning.

Tissue programmed death ligand-1 (PD-L1) protein expression is predictive of immune checkpoint inhibitor (ICI) benefit. However, tissue PD-L1 can be fraught with tissue acquisition and heterogeneity limitations. Plasma testing can overcome these limitations. However, the overall survival (OS) predictive benefit of plasma PD-L1 assays have not been well characterized. Patients with stage IV non-small cell lung cancer (NSCLC) and plasma cfRNA PD-L1 by PCR expression were identified and assessed for OS. 16 patients treated with front-line ICI-based regimens were assessed and represented a real-world patient population with over half with a performance status of 2 or greater. 10 contemporaneous patients at the same institution treated with chemotherapy alone were also identified and assessed. With a median follow-up of 33 months, median OS was 13 months with a 30% 3-year OS for the ICI treated patients compared to a median OS of 3 months and a 10% 3-year OS for those treated with chemotherapy alone. Comparative log-rank test p-value = 0.014 and a hazard ratio 0.376 (95%-CI 0.134-1.057). Plasma cfRNA PD-L1 was associated with a statistically significant survival benefit from ICI-based treatment compared to chemotherapy in the first line treatment of a real-world patient population of advanced NSCLC.

Pattern recognition techniques form the heart of most, if not all, incoherent linear shift-invariant systems. When an object is recorded using a camera, the object information gets sampled by the point spread function (PSF) of the system, replacing every object point with the PSF in the sensor. The PSF is a sharp Kronecker Delta-like function when the numerical aperture (NA) is large with no aberrations. When the NA is small, and the system has aberrations, the PSF appears blurred. In the above case, if the PSF is known, then the object information can be obtained by scanning the PSF over the recorded object intensity pattern and looking for pattern matching conditions through a mathematical process called correlation. In this study, a recently developed deconvolution method, the Lucy-Richardson-Rosen algorithm (LR2A), has been implemented to computationally refocus images recorded in the presence of spatio-spectral aberrations. The performance of LR2A was compared against the Lucy-Richardson algorithm and non-linear reconstruction. LR2A exhibits a superior deconvolution capability even in extreme cases of spatio-spectral aberrations and blur. Experimental results of deblurring a picture captured using high-resolution smartphone cameras are presented. LR2A was implemented to significantly improve the performances of the widely used deep convolutional neural networks for image classification.

Potentilla nepalensis belongs to the Rosaceae family, and has numerous therapeutic applications as potent plant-based medicine. Forty phytoconstituents (PCs) from the root and stem through n-hexane (NR and NS) and methanolic (MR and MS) extracts were identified in our earlier studies. However, the PCs affecting human genes and their roles in the body are not disclosed till now. In this study, we employed network pharmacology, molecular docking, molecular dynamics simulations (MDS), and MMGBSA methodologies. SMILES format of PCs from the PubChem used as input to DIGEP-Pred, 764 identified as the inducing genes. Their enrichment studies have shown inducing genes gene ontology descriptions, involved pathways, associated diseases, and drugs. PPI networks constructed in String DB and network topological analysing parameters done in Cytoscape v3.10 revealed three biomarkers, TP53 from MS, NR, and NS induced genes; HSPCB and Nf-kB1 from MR induced genes. From 40 PCs, two PCs 1b (MR) and 2a (MS), showed better binding scores (kcal/mol) with p53 protein of -8.6, and -8.0; three PCs 3a, (NR) 4a and 4c (NS) with HSP protein of -9.6, -8.7, and -8.2. MDS and MMGBSA revealed these complexes are stable without higher deviations with better free energy values. Biomarkers identified in this study, have a prominent role in numerous cancers. Thus, further investigations such as in-vivo and in-vitro should be done to find the molecular functions and interlaying mechanism of the identified biomarkers on numerous cancer cell lines in considering the PCs of P.nepalensis.

We successfully created a composite photonic structure out of porous silicon (PSi) microcavities doped by the photochromic protein, photoactive yellow protein (PYP). Massive incorporation of the protein molecules into the pores was substantiated by a 30-nm shift of the resonance dip upon functionalization, and light-induced reflectance changes of the device due to the protein photocycle were recorded. Model calculations for the photonic properties of the device were consistent with earlier results on the nonlinear optical properties of the protein, whose degree of incorporation into the PSi structure was also estimated. The successful proof-of-concept results are discussed in light of possible practical applications in the future.

Analysing and understanding donor behaviour in Non-profit Organisations (NPOs) is challenging due to the lack of human and technical resources. Machine learning (ML) techniques can analyse and understand donor behaviour at a certain level; however, it remains to be seen how to build and design an Artificial Intelligence enabled Decision Support System (AI-enabled DSS) to analyse donor behaviour. Thus, this paper proposes an AI-enabled DSS conceptual design to analyse donor behaviour in NPOs. A conceptual design is created following a Design Science Research approach to evaluate an AI-enabled DSS's initial DPs and features to analyse donor behaviour in NPOs. The evaluation process of the conceptual design applied formative assessment through conducting interviews with stakeholders from NPOs. The interviews were conducted using the Appreciative Inquiry framework to facilitate the process of interviews. The results of analysis based on the interviews provide insightful information not only about the proposed conceptual design for an AI-enabled DSS, but also about what is required to analyse donor behaviour NPOs using DSS. Evaluating the conceptual design results recommend efficiency, effectiveness, flexibility, and useability in the requirements of the AI-enabled DSS. This research contributes to the design knowledge base of AI-enabled DSS for analysing donor behaviour in NPOs. Future research will combine theoretical components to introduce a practical AI-enabled DSS for analysing donor behaviour in NPOs. This research is limited to such analysis on donors who donate money or volunteer time for NPOs.

The rescue, digitisation, quality control, preservation and utilization of long and high quality meteorological and climate records, particularly related to historical marine data, are crucial for advancing our understanding of the Earth's climate system. In combination with land and air measurements, the historical marine records serve as foundational pillars in linking present and past weather and climate information, offering essential insights into natural climate variability, extreme events in marine areas, baseline data for assessing current changes, and inputs for en-hancing predictive climate models and reanalyses. This paper provides an overview of marine data rescue activities covering the past centuries, presents and highlights several ongoing projects across the world and how the data are used in an integrative and international framework. Current and future continuous efforts in data rescue, digitisation, quality control and the de-velopment of temporally high resolution meteorological and climatological observations from the Sea, will greatly help to further complete our understanding and knowledge of the Earth system including extremes, as well as improving the quality of reanalysis.

(1) Background: Type-2 Diabetes (T2DM) is a long-term medical disorder characterized by Insulin deficiency and high blood glucose levels. Among other medication to cure T2DM, the review of the literature found that various Pyrimidine derivative act as an agonist for G-protein-coupled receptor 119 (GPR119) was proposed to control blood glucose levels by enhancing the function of pancreatic beta-cells and its mechanism of action with fewer adverse effects.; (2) Methods: In the present research work, in-silico investigations were carried out to investigate the potential of Pyrimidine analogue as an agonists to the protein target GPR119 receptor. We performed exhaustive molecular modelling and protein modelling methodologies such as homology mod-elling, molecular docking along with various drug designing tools such as 3D-QSAR and pharmacophore mapping to ascertain the design of better GPR119 agonists.; (3) Results: On the basis of in-depth computa-tional studies, we designed new pyrimidine moiety and analyzed them for GPR-119 receptor agonist and fur-ther explored the ADME properties. Designed compounds found to exhibit better predicted activities as com-pared to reference compound; (4) Conclusions: The current research on pyrimidine derivatives, using molec-ular docking, 3D-QSAR and Pharmacophore mapping demonstrated that the obtained computational model has significant properties and the designed molecules and Dataset from this model, produced antidiabetic compound against the target GPR119 i.e., compound 1S, 1Z and 1D with the docking score of −11.696, -9.314 and -8.721 respectively. The pharmacokinetics and drug-likeness studies revealed that these compounds may be the future candidate for the treatment of diabetes acting via GPR119 agonist mechanism.

Falls are extremely damaging to the elderly. The number of elderly who have experienced falls has increased over the years, several of the elderly stay alone or in in badly maintained elderly homes. This makes a low-cost fall detection system a necessity. There has been huge improvements in terms of IoT systems, ML algorithms. Varied data sets have been collected across the world for fall detection. These data sets have a very little in common among them, in terms of user demographics, sensors used, the ADL and Fall activities Hence in this paper we present a data set that has wide user demographics, we used various sensors – such as accelerometer, gyroscope, magnetometer and hear rate. We used wrist worn sensors to collect data. In this paper we present a detailed analysis of the data set we collected using common ML algorithms such as – Naïve Bayes (NB), K Nearest Neighbor (KNN), Logistic Regression (LR), Random Forest (RF) and Support Vector Machines (SVM). We analyzed the performance of these algorithms for variations in accuracy with respect to age, gender, height, weight and health issues and we have identified outliers by analyzing each incorrect prediction. This paper provides the complete details of the data collection methodology, The methods used for analysis and presents the results of analysis in complete detail.

Silybin is a natural compound extensively studied for its hepatoprotective, neuroprotective and anti-cancer properties. Envisioning the enhancement of silybin potential by suitable modifications in its chemical structure, here, a series of new 7-O alkyl silybins derivatives were synthesized by Mitsunobu reaction starting from the silybins and tyrosol-based phenols, such as tyrosol (TYR, 3), 3-methoxytyrosol (MTYR, 4) and 3-hydroxytyrosol (HTYR, 5). This research sought to explore the antioxidant and anticancer properties of new eighteen derivatives and their mechanisms. In particular, the antioxidant properties of new derivatives outlined by DPPH assay, showed a very pronounced activity depending on the tyrosyl moiety (HTYR&gt;MTYR&gt;&gt;TYR). A significant contribution of the HTYR moiety was observed for silybins and 2,3-dehydro-silybin based derivatives. According to the very potent antioxidant activity, 2,3-dehydro-silybin derivatives 15ab, 15a and 15b exerted the most potent anticancer activity in human prostate cancer PC-3 cells. Furthermore, flow cytometric analysis for cell cycle and apoptosis revealed that 15ab, 15a and 15b induce strong G1 phase arrest and increase late apoptotic population in PC-3 cells. Additionally, western blotting for apoptotic marker cleaved caspase-3 confirmed apoptosis induction by these silybin derivatives in PC-3 cells. These findings hold significant importance in the investigation of anticancer properties of silybin derivatives and strongly encourage swift investigation in pre-clinical models and clinical trials.

A refractive lens is one of the simplest, cost-effective and easily available imaging elements. With a spatially incoherent illumination, a refractive lens can faithfully map every object point to an image point in the sensor plane, when the object and image distances satisfy the imaging conditions. However, static imaging is limited to the depth of focus, beyond which the point-to-point mapping can be only obtained by changing either the location of the lens or the imaging sensor. In this study, the depth of focus of a refractive lens in static mode has been expanded using a recently developed computational reconstruction method, Lucy-Richardson-Rosen algorithm (LRRA). The technique consists of three steps. In this first step, the point spread functions (PSFs) were recorded along different depths and stored in the computer as PSF library. In the next step, the object intensity distribution was recorded. The LRRA was then applied to deconvolve the object information from the recorded intensity distributions in the final step. The results of LRRA were compared against two well-known reconstruction methods namely Lucy-Richardson algorithm and non-linear reconstruction.

In this article, two elliptical-ovel-shaped cylindrical dielectric resonator based wideband Graphene inspired reconfigurable metasurface absorber is designed on diffused quartz substrate having a relative permittivity of 3.75 and conductivity 2200Kg/m3 with height of 25μm. This metasurface having gold plated ground in microstrip with 5μm which is essential by calculating skin depth at 2.0THz frequency. Two elliptical ovel shaped patches with Graphene plated having built in potential varies 0-2.5eV and relaxation time 1.0ps at 290oK. By changing the relaxation time of Graphene 0.1ps-0.3ps its resonance frequency also varies i.e., reconfigurable property they provide without adding any active i.e., PIN diode components. The proposed MS is designed having a dimension of 100×100μm2 is designed on a microstrip. This MS works in the range of 1.6-2.38THz having more than 90% absorbance with two transmission zero at 2.1THz and 2.3THz having high Q ˃ 50 which is used to determine the sensitivity where the proposed MS used as a sensor to determine hemoglobin (Blood Glucose level) and urine (Uric acid) by changing their refractive index from 1.34-1.43. Maximum sensitivity achieved at 2000GHz/RIU and average sensitivity for hemoglobin and urine sensing achieved 833.33GHz/RIU, FOM-8.33 and 4277.7733GHz/RIU, FOM-555.55 respectively.

Background: Metastatic triple-negative breast cancer (TNBC) is aggressive with a poor median overall survival (OS), ranging from 8 to 13 months. There exists considerable heterogeneity in the survival at the individual patient level. To better understand the survival heterogeneity and improve risk stratification, our study aims to identify the factors influencing survival utilizing a large patient sample in the National Cancer Database (NCDB). Methods: Women diagnosed with metastatic TNBC from 2010 to 2020 in the NCDB were included. Demographic, clinic-pathological, treatment data, and overall survival (OS) outcomes were collected. Kaplan-Meier curves were used to estimate OS. The log-rank test was used to identify OS differences between groups for each variable in the univariate analysis. For the multivariate analysis, the Cox proportional hazard model with backward elimination was used to identify factors affecting OS. Adjusted hazard ratios and 95% confidence intervals are presented. Results: 2,273 women had a median overall survival of 13.6 months. Factors associated with statistically significantly worse OS included older age, higher comorbidity scores, specific histologies, higher number of metastatic sites, presence of liver or other site metastases in those with only one metastatic site (excluding brain metastases), presence of cranial and extra-cranial metastases, lack of chemotherapy, lack of immunotherapy, lack of surgery to distant sites, lack of radiation to distant sites, and receipt of palliative treatment to alleviate symptoms. In the multivariate analysis, comorbidity score, histology, number of metastatic sites, immunotherapy, and chemotherapy had a statistically significant effect on the OS. Conclusions: Through NCDB analysis, we have identified prognostic factors for metastatic TNBC. These findings will help improve prognostication at diagnosis, optimize treatment strategies, and facilitate patient stratification in future clinical trials.

Indirect imaging methods involve at least two steps, namely optical recording, and computational reconstruction. The optical recording process uses an optical modulator that transforms the light from the object into a typical intensity distribution. This distribution is numerically processed to reconstruct the object’s image corresponding to different spatial and spectral dimensions. There have been numerous optical modulation functions and reconstruction methods developed in the past years for different applications. In most cases, a compatible pair of optical modulation function and reconstruction method gives optimal performance. A new reconstruction method termed non-linear reconstruction (NLR) was developed in 2017 to reconstruct the object image in the case of optical scattering modulators. During the years, it was revealed that the NLR could reconstruct an object’s image modulated by an axicons, bifocal lenses and even exotic spiral diffractive elements, which generate deterministic optical fields. Apparently, NLR seems to be a universal reconstruction method for indirect imaging. In this review, the performance of NLR has been investigated for many deterministic and stochastic optical fields. Simulation and experimental results for different cases are presented and discussed.

Congenital Pouch Colon (CPC) is a rare anorectal anomaly common to North Western India specifically Rajasthan. Despite efforts to understand the clinical genetic makeup of CPC, no attempt on identifying non-coding RNAs was done. We have earlier reported CPC's rare variants from whole exome sequencing across 18 affected samples in a total of 64 subjects. A Smith-Waterman algorithm was used to infer a couple of lncRNAs from WES samples of CPC with predictions from the Noncode database. Further screening and quantification using PCR, we ascertained interactions using Micro Scale Thermophoresis (MST). We report the role of lnc-EPB41-1-1 shown to be promiscuously interacting with KIF13A substantiating their role in regulation.

The risk of 'zoonotic spillovers,' or the transmission of viruses from animals to humans, has been raised by climate change and the devastation of nature, as infectious disease experts have long warned. Even as the world works to stop the spread of the currently unfolding pandemic of coronavirus disease 2019 (COVID-19) and the breakout of monkeypox virus (MPXV), a new animal virus, the Langya henipavirus (LayV), has been discovered in humans in Eastern China. The scientists say there is little danger of the virus spreading among humans, but it shares genetic material with Hendra virus and Nipah virus, two other henipaviruses that infect humans and cause life-threatening respiratory diseases. Humans infected with LayV can expect to experience high body temperature, cough, weariness, poor appetite, muscle discomfort, myalgia, nausea and vomiting. It is likely that the virus will spread from animals to humans. Currently, the health authorities of Taiwan and other health organizations are tracking the progress of the ailment to ensure it does not reach humans. Researchers have examined 25 species of small wild animals for presence of the virus, and so far, shrews are the only ones that have tested positive for the virus's RNA. Based on these results, shrews are a possible candidate for the virus's natural reservoir. Too far, no therapies or vaccines have been developed and licensed for henipaviruses like the LayV. When other therapies fail to alleviate viral infections, ribavirin may be the next best thing. The need for novel vaccinations against the LayV infection and the timely delivery of these vaccines to areas at high epidemiological risk is real. To lessen the likelihood of a health calamity being caused by this newly developing virus, it is crucial to conduct active surveillance in a transparent and globally collaborative manner. The questions that have not been answered yet require additional study.

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

Systems genetics is key for integrating a large number of variants associated with diseases. Vitamin K (VK) is one of the scarcely studied conditions in lieu of ascertaining either the differentially expressed genes (DEGs) or variants in an individual subpopulation of diseased phenotypes associated with VK, viz. myocardial infarction, renal failure, prostate cancer, thrombosis, thrombocytopenia, coagulation related diseases to name a few. In this work, we have screened characteristic DEGs common to three VK-related diseases, viz. myocardial infarction, renal failure and prostate cancer and asked whether or not any DEGs in addition to pathogenic variants are common to these conditions. We attempt to bridge the gap in finding characteristic biomarkers and discuss the role of long noncoding RNAs (lncRNAs) in the biogenesis of VK deficiencies.

Phase imaging of biochemical samples has been demonstrated for the first time at the Infrared Microspectroscopy (IRM) beamline of the Australian Synchrotron using the usually discarded Near-IR (NIR) region of the synchrotron-IR beam. The synchrotron-IR beam at the Australian Synchrotron IRM beamline has a unique fork shaped intensity distribution as a result of the gold coated extraction mirror shape, which includes a central slit for rejection of the intense X-ray beam. The resulting beam configuration makes any imaging task challenging. For intensity imaging, the fork shaped beam is usually tightly focused to a point on the sample plane followed by a pixel-by-pixel scanning approach to record the image. In this study, a pinhole was aligned with one of the lobes of the fork shaped beam and the Airy diffraction pattern was used to illuminate biochemical samples. The diffracted light from the samples was captured using a NIR sensitive lensless camera. A rapid phase-retrieval algorithm was applied to the recorded intensity distributions to reconstruct the phase information corresponding to different planes. The preliminary results are promising to develop multimodal imaging capabilities at the IRM beamline of the Australian Synchrotron.

In the recent past, there has been a rise in Prostate Cancer (PCa) in Asia, particularly India. Although systematic reviews on PCa have dealt on the genetics, genomics and the environmental influence in causal of PCa, no predictive analytics in comparing the PCa from Caucasian, American to Asian population was attempted. In this review article, we have attempted to elaborate this aspect of PCa and deliberated on challenges related to next generation sequencing methods of PCa’s manifestation when compared to the west.

Certain species of Mucorales have been identified as causative agents of mucormycosis, a rare yet often lethal fungal infection. Notably, these fungi exhibit intrinsic resistance to common azole drugs, which target lipids. Given the pivotal role of lipids in drug resistance and their contribution to the innate resistance to azoles, this study provides a comprehensive overview of key lipid classes, including sphingolipids (SLs), glycerophospholipids(GPLs), and sterols, in Rhizopus delemar 99-880, a well-characterized reference strain among Mucorales. Through high-throughput analysis involving the identification and quantification of intermediates, we have elucidated the biosynthetic pathways of SLs, PGLs, and sterols. Notably, the acidic SLs were not found probably because the acidic branch of the SL biosynthesis pathway terminates at α-hydroxy phytoceramides as evident by their high abundance. Intermediates in the neutral SL pathway incorporated higher levels of 16:0 fatty acid compared to other pathogenic fungi. A strikingly high phosphatidylethanolamine (PE)/phosphatidylcholine (PC) ratio was observed among GPLs. Ergosterol remains the major sterol, similar to other fungi, and our analysis confirms the existence of alternate ergosterol biosynthesis pathways. The total lipidomic profile of R. delemar 99-880 offers insights into its lipid metabolism and potential implications for studying pathogenesis and drug resistance mechanisms.

Bacteria currently included in Rhizobium leguminosarum are too diverse to be considered a single species, so we can refer to this as a species complex (the Rlc). We have found 429 publicly available genome sequences that fall within the Rlc and these show that the Rlc is a distinct entity, well separated from other species in the genus. Its sister taxon is R. anhuiense. We constructed a phylogeny based on concatenated sequences of 120 universal (core) genes, and calculated pairwise average nucleotide identity (ANI) between all genomes. From these analyses, we concluded that the Rlc includes 18 distinct genospecies, plus 7 unique strains that are not placed in these genospecies. Each genospecies is separated by a distinct gap in ANI values, usually at around 96% ANI, implying that it is a 'natural' unit. Five of the genospecies include the type strains of named species: R. laguerreae, R. sophorae, R. ruizarguesonis, "R. indicum" and R. leguminosarum itself. The 16S ribosomal RNA sequence is remarkably diverse within the Rlc, but does not distinguish the genospecies. Partial sequences of housekeeping genes, which have frequently been used to characterise isolate collections, can mostly be assigned unambiguously to a genospecies, but alleles within a genospecies do not always form a clade, so single genes are not a reliable guide to the true phylogeny of the strains. We conclude that access to a large number of genome sequences is a powerful tool for characterising the diversity of bacteria, and that taxonomic conclusions should be based on all available genome sequences, not just those of type strains.

Alginate-silver nanocomposites in the form of spherical beads and films were prepared using a green approach by using the aqueous extract of Ajwa dates seeds. The nanocomposites were fabricated by in situ reduction and gelation method by ionotropic crosslinking using calcium ions in solution. The rich phytochemicals of the dates seeds extract played a dual role as reducing and stabilizing agent in the synthesis of silver nanoparticles. The formation of silver nanoparticles was studied using UV-Vis absorption spectroscopy and a distinct surface plasmon resonance (SPR) peak at 421 nm characteristic of silver nanoparticles confirmed the green synthesis of silver nanoparticles. The morphology of the nanocomposite beads and film was compact with even distribution of silver nanoclusters. The catalytic property of the nanocomposite beads was evaluated for the degradation of 2-nitrophenol in the presence of sodium borohydride. The degradation followed pseudo-first order kinetics with a rate constant of 1.40 ´ 10^-3 s^-1 at 23 °C with an activation energy of 18.45 kJ mol^-1. The thermodynamic parameters such as changes in enthalpy and entropy were evaluated to be 15.22 kJ mol^-1 and -197.50 J mol^-1 K^-1, respectively. The nanocomposite exhibited properties against three clinically important pathogens (Gram-positive and Gram-negative bacteria)

We report the case of a 28-year-old male with uncontrolled human immunodeficiency virus (HIV) infection who presented with extensive ulcerated lesions with dark lamellated crusting on his face, torso, and limbs. The patient had an RPR of 1:512. A skin biopsy revealed granulomata surrounded by lymphocytes, histiocytes, and plasma cells, with spirochetes visible on immunohistochemical staining. This severe form of secondary syphilis has been termed malignant syphilis, lues maligna, ulceronodular syphilis, and rupioid syphilis, among other names. The patient’s rash resolved with hyperpigmented scarring after treatment with penicillin and doxycycline. First, we propose a single descriptive name for this entity, ulceronodular-rupioid syphilis. In 1967, Fisher and coworkers proposed criteria for malignant syphilis based on lesion appearance, RPR values, histopathologic findings, the occurrence of the Jarisch-Herxheimer reaction, and response to treatment. However, the Fisher criteria were found to be imprecise. Thus, we examined the features of an additional 74 cases from the medical literature and propose new diagnostic criteria based on rash appearance, histopathologic characteristics, non-treponemal and treponemal test positivity, and response to therapy. We also found that uncontrolled viremia and not a low CD4 count is a major risk factor for this severe manifestation of secondary syphilis in the HIV population.

SARS-CoV-2, is the cause of the COVID-19 pandemic which has claimed more than six million lives worldwide, devastating the economy and overwhelming healthcare systems globally. The development of new drug molecules and vaccines has played a critical role in managing the pandemic; however, new variants of concern still pose a significant threat as the current vaccines cannot prevent all infections. This situation calls for the collaboration of biomedical scientists and healthcare workers across the world. Repurposing approved drugs is an effective way of fast-tracking new treatments for recently emerged diseases. To this end, we have assembled and curated a database consisting of 7817 compounds from the Compounds Australia Open Drug collection. We developed a set of eight filters based on indicators of efficacy and safety that were applied sequentially to down-select drugs that showed promise for drug repurposing efforts against SARS-CoV-2. Considerable effort was made to evaluate approximately 14000 assay data points for SARS-CoV-2 FDA/TGA-approved drugs and provide an average activity score for 3539 compounds. The filtering process identified 12 FDA approved molecules with established safety profiles that have a plausible mechanism for treating COVID-19 disease. The methodology developed in our study provides a template for prioritising repurposable drug candidates that are safe, efficacious, and cost-effective for the treatment of COVID-19, long COVID, or any other future disease. We present our database in an easy-to-use interactive interface (CoviRx, https://www.covirx.org/) that was also developed to enable scientific community to access to the data of over 7000 potential drugs and to implement alternative prioritisation and down-selection strategies.

Background: Early diagnosis of postoperative complications is an urgent task, allowing timely prescribing of appropriate therapy and reducing the cost of patient treatment. Prognostic models based on various data could help in the early diagnosis of postoperative complications after cardiac surgery. Objectives: The purpose of the study was to determine whether an integrated approach based on clinical data along with metabolites and biomarkers had greater predictive value than the models built on less data. Methods: The study included patients (n=62) admitted for planned cardiac surgery (coronary artery bypass grafting with cardiopulmonary bypass), who were retrospectively divided into two groups depending on the presence (n=26) or absence (n=36) of postoperative complications of all types. Clinical and laboratory data on the first day after surgery were analyzed. Additionally, patients' blood samples were collected before and on the first day after surgery to determine biomarkers (interleukin-6, procalcitonin, NT-proBNP, high-sensitivity troponin T) and metabolites (8 aromatic and 2 dicarboxylic acids were detected using gas chromatography-mass spectrometry). Results: Patients before surgery, compared with healthy donors, differed in the concentration of metabolites (p &lt; 0.05), and had concentrations of a number of biomarkers exceeding the corresponding reference values. Multivariate PLS-DA models, predicting the presence or absence of postoperative complications, were built using clinical data (ROC-AUC=0.71), concentrations of metabolites and biomarkers (ROC-AUC=0.60), and the entire data set (ROC-AUC=0.75). For comparison we built univariate models using the EuroScore2 (ROC-AUC=0.59) and SOFA (ROC-AUC=0.76) scales; concentrations of lactate (ROC-AUC=0.71), the dynamic changes of 4-hydroxyphenyllactic acid (ROC-AUC=0.69), and the sum of three sepsis-associated metabolites (ROC-AUC=0.70). The proposed complex model using entire data set was comparable to the SOFA scale, which confirms the expediency of searching for new predictive models based on a variety of factors.

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

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

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

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

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

In recent years, electroencephalogram (EEG) emotion recognition has emerged as a research hotspot in the field of artificial intelligence (AI). Despite advancements in EEG-based emotion recognition, room for enhancing performance persists due to EEG signal redundancy and limitations in feature extraction, leading to inefficient models and emotional information loss. To fully utilize EEG's emotional information and improve recognition accuracy while reducing computational costs, this paper proposes a Convolutional-Recurrent Hybrid Network with a dual-stream adaptive approach and an attention mechanism (CSA-SA-CRTNN). Firstly, the model utilizes a CSAM module to assign corresponding weights to EEG channels. Then, an adaptive dual-stream convolutional-recurrent network (SA-CRNN and MHSA-CRNN) is applied to extract local spatial-temporal features. After that, the extracted local features are concatenated and fed into a temporal convolutional network with a multi-head self-attention mechanism (MHSA-TCN) to capture global information. Finally, the extracted EEG information is used for emotion classification. We conducted binary and ternary classification experiments on the DEAP dataset, achieving 99.26% and 99.15% accuracy for arousal and valence in binary classification, and 97.69% and 98.05% in ternary classification, surpassing relevant algorithms. Additionally, the model's efficiency is significantly higher than other models, achieving better accuracy with lower resource consumption.

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

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

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

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

Although various vaccines are now commercially available, they have not been able to stop the spread of COVID-19 infection completely. An excellent strategy to quickly get safe, effective, and affordable COVID-19 treatment is to repurpose drugs that are already approved for other diseases as adjuvants along with the ongoing vaccine regime. The process of developing an accurate and standardized drug repurposing dataset requires a considerable level of resources and expertise due to the commercial availability of an extensive array of drugs that could be potentially used to address the SARS-CoV-2 infection. To address this bottleneck, we created the CoviRx platform. CoviRx is a user-friendly interface that provides access to the data, which is manually curated for COVID-19 drug repurposing data. Through CoviRx, the data curated has been made open-source to help advance drug repurposing research. CoviRx also encourages users to submit their findings after thoroughly validating the data, followed by merging it by enforcing uniformity and integ-rity-preserving constraints. This article discusses the various features of CoviRx and its design principles. CoviRx has been designed so that its functionality is independent of the data it dis-plays. Thus, in the future, this platform can be extended to include any other disease X beyond COVID-19. CoviRx can be accessed at www.covirx.org.

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

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

The aim of this retrospective study was to compare the clinical outcomes of treating isolated surgical neck fractures of the humerus using either the intramedullary nail or the MIROS (Minimally Invasive Reduction and Osteosynthesis System®) system. The study included 42 patients who underwent surgical treatment at the Polyclinic from January 2014 to June 2020. The results indicated that both treatments were effective; however, the MIROS system exhibited a higher complication rate. Intramedullary nailing was more reliable, thus recommended as the primary treatment method. This study underscores the importance of selecting the appropriate fixation technique to minimize complications and enhance patient outcomes.