The Vaal Dam catchment, which is the source of potable water for Gauteng province, holds various human activities including mining, urbanization, agricultural and industrial activities coupled with high fluxes of nutrients from different areas within the catchment. This situation led to an enhancement of Harmful Algal Blooms (HABs) in the dam reservoir. Phosphorus and Nitrogen are the limiting nutrients for HABs in many eutrophic aquatic systems when their concentrations are raised in such waters. In this study, multi-time-series plot types and scutter plots were analysed to reveal the relationship between HABs proxy chlorophyll-a (Chl-a) and the potential nutrients. Also (Chl-a) data extracted from landsat-8 satellite images were visualised to show the spatial distribution of HABs in the reservoir. The results showed that the Vaal Dam HABs productivity is a function of the total phosphorus (TP) and the organic nitrogen (KJEL_N) levels, which were positively correlated with chlorophyll-a (Chl-a) concentration. The long-term analysis of Chl-a in-situ data (1986 – 2022) measured at one point within the reservoir showed an average of 11.25μg/l but at some stochastic dates, the Chl-a concentration jumped to very high values reaching the maximum value of 452.8μg/l. Such high values are associated with high records of TP and KJEL_N concentrations at the same dates which clearly reveals their effect on the productivity levels. The decadal time series and its trend analysis showed that the average productivity level of Chl-a increased during the studded period from 4.75μg/l in the first decade (1990 – 2000) to 10.51μg/l in the second decade (2000 – 2010) reaching 16.7 during the last decade (2010 – 2020). The increasing averages of the decadal values are associated with the increasing decadal average of its driving factors, TP from 0.1043 to 0.1096 to 0.1119mg/l for the three decades, respectively and KJEL_N from 0.80mg/l in the first decade to 1.14mg/l in the last decade. The decadal average of temperature showed no significant increase, 17.9 °C in the first decade and 18 °C in the last decade which suggests that temperature is not the only enhancing factor of the HABs productivity in the Vaal Dam. The satellite data analysis during the last decade revealed that the HABs spatial dynamics is a function of the dam geometry and the levels of the discharges from its two feeding rivers. Higher concentrations were observed where the reservoir is meandering and within the areas of restricted water circulation.

In this study, we present the concept of interval-valued fuzzy soft point and then introduce the notions of neighborhood and quasi-neighbourhood of it in interval-valued fuzzy soft topological spaces. Separation axioms in interval-valued fuzzy soft topology, so-called $q$-$T_{i}$ for $ i=0,1,2,3,4 ,$ is introduced and some of its basic properties are also studied.

Accurate rainfall measurement is vital when investigating spatial and temporal precipitation variability at different scales. However, there are many regions around the world, such as North Darfur State in Sudan, where ground-based observations are few. Satellite-based precipitation products can fill such regions' spatial and temporal rainfall data gaps. Six satellite rainfall prod-ucts, namely the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA), African Rainfall Climatology Version 2 (ARC2.0), Climate Hazards Group In-frared Precipitation with Station Data (CHIRPS2.0), the Integrated Multi-satellitE Retrievals for Global Precipitation Measurements (GPM) Final Run v 6 (GPM IMERG6), Precipitation Estima-tion from Remote Sensing Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR), and the Tropical Applications of Meteorology using SATellite and ground-based observations (TAMSAT) v3.1 were evaluated to assess their accuracy in estimating rainfall amounts variability trends in the study area. The global-based satellite rainfall products were assessed at monthly and annual time scales by applying a point-to-pixel comparison with ground-based rain gauge data for the period 2000–2019. Based on the overall statistical results at monthly and temporal yearly scales, five satellite precipitation products (TMPA, CHIRPS, GPM IMERG6, PERSIANN-CDR, and TAMSATv3.1) overestimated rainfall amounts by values ranging from 1.49% to 82.69%. In contrast, the ARC2 product underestimated rainfall amounts by values ranging from-16.9% to-20.25%. The TAMSATv3.1, CHIRPS, and TMPA performed relatively better, showing stronger correlations and higher values of Nash-Sutcliffe efficiency. This study showed that the TAMSATv3.1 and CHIRPS products could reasonably estimate rainfall amounts in the North Darfur State.

Abstract: The empirical soil loss model, RUSLE, was used with a conjunction of remotely sensed data and geographic information system technology to delineate the soil erosion and watershed priorities in terms of conservation practices at seven boundary sub-watersheds (labeled as SW-00, SW-01, …, SW-06) between Iraq and Iran at Ali Al-Gharbi area, southern Iraq. The six factors of the RUSLE model, ie. the rainfall erosivity, the soil erodibility, the slope steepness length, the crop management, and management practice, were calculated or estimated using information from different data sources such as remotely sensed data and previous studies. The finding showed that the annual soil erosion loss ranges from 0 - 1890 (tons h-1 y-1) with an average of 0.66 (tons h-1 y-1). Values of soil erosion were classified into five classes: very low, low, moderate, high, and very high. The potential soil loss in the high and very high classes ranges from 14.84 to 1890 (tons h-1 y-1), and these classes occupy only 27 km2 of the study area, indicating that the soil loss is very low in the area being examined. In terms of the spatial distribution of soil loss, the northern and northeastern parts (mountains and hills) of the sub-watersheds where the slope is steeper are more likely to erode than the plain area in the southern and southeastern portions, indicating that slope, in addition to rainfall erosivity, has a dominant effect on the soil erosion rate. The study of soil erosion in the watersheds under consideration reveals that only the northern portions of the SW-00, SW-02, and SW-04 watersheds require high priority conservation plans; however, these portions are primarily located in mountain regions, making conservation plans implementation in these areas impractical. Due to low soil loss, other sub-watersheds, particularly SW-01, SW-03, SW-05, and SW-06, are given low priority.

Autonomous aircraft are the key enablers of future urban services, such as postal and transportation systems. Digital Twins (DT) are promising cutting-edge technologies that can transform the future transport ecosystem into an autonomous and resilient system. However, since DT is a data-driven solution based on AI, proper data management is essential in implementing DT as a Service (DTaaS). One of the challenges in DT development is the availability of real-life data, particularly for training algorithms and verifying the functionality of DT. The current article focuses on data augmentation through synthetic data generation. This approach can facilitate the development of DT in case the developers do not have enough data to train the Machine Learning (ML) algorithm. The current twinning approach provides a prospective ideal state of the engine used for proactive monitoring of the engine’s health as an anomaly detection service. In line with the track of Unmanned Aircraft Vehicles (UAV) for Urban Air Mobility in Smart Cities applications, this paper focuses specifically on the common Hybrid turbo-shaft in drones/helicopters. However, there is a significant gap in real-life similar synthetic data generation in the UAV domain literature. Therefore, Rolling Linear Regression and Kalman Filter algorithms were implemented on noise-added data, which simulate the data measured from the engine in a real-life operational lifecycle. For both thermal and hybrid models, the corresponding DT model has shown high efficiency in noise filtration and a certain amount of predictions with a lower error rate on all engine parameters, except the engine torque.

The coronavirus COVID-19 epidemic has wreaked havoc on inhabitants of earth killing thousands of humans from more than 150 countries. The epidemic has put a number of countries under complete lockdown and the deadly situation is still prevailing around the globe. Vaccines have been long known as the most effective means of preventing viral infections. However, the lack of vaccines against COVID-19 has further worsened the situation. In this time of health crisis, it is the duty of scientific research community to provide alternative, effective and affordable strategies to vaccinate human bodies against viral infections-COVID-19 based on focused experimental approaches. Growing evidence suggests that certain natural foods and lifestyle changes have potential to optimize immune functions against viral infections including improving defense function, resistance towards invading pathogens, while maintaining self-tolerance. Boosting immune system gives an edge in fending off viruses and staying healthy. This review presents the six smart steps to add to your to-do list which let the inner work of immunity take place against viral infections-COVID-19 by dissolving the powers of disease and illness. Many of these factors are associated in their functions to improve or properly maintain the immune function such as promoting anti-inflammatory functions, inhibiting pro-inflammatory mediators, modulating cell-mediated immunity, altering the antigen-presenting cellular functions as well as promoting communication between the innate and adaptive immune responses. Thus, a scientific illustration of boosting the immune system by proper sleep, moderate exercise, avoiding stress, utilizing vitamins enriched foods, intake of more water and use of fruits and vegetables will hopefully help the community to deal with the coronavirus by vaccinating the human systems naturally.

COVID-19, a rapidly spreading new strain of coronavirus, has affected more than 150 countries and received worldwide attention. The lack of efficacious drugs or vaccines against SARS-CoV-2 has further worsened the situation. Thus, there is an urgent need to boost up research for the development of effective therapeutics and affordable diagnostic against COVID-19. The crystallized form of SARS-CoV-2 main protease (Mpro) was demonstrated by a Chinese researcher Liu et al. (2020) which is a novel therapeutic drug target. This study was conducted to evaluate the efficacy of medicinal plant-based bioactive compounds against COVID-19 Mpro by molecular docking study. Molecular docking investigations were performed by using Molegro Virtual Docker 7 to analyze the inhibition probability of these compounds against COVID-19. COVID-19 Mpro was docked with 80 flavonoid compounds and the binding energies were obtained from the docking of (PDB ID: 6LU7: Resolution 2.16 Å) with the native ligand. According to obtained results, hesperidin, rutin, diosmin, apiin, diacetylcurcumin, (E)-1-(2-Hydroxy-4-methoxyphenyl)-3-[3-[(E)-3-(2-hydroxy-4- methoxyphenyl)-3-oxoprop-1-enyl]phenyl]prop-2-en-1-one, and beta,beta'-(4-Methoxy-1,3- phenylene)bis(2'-hydroxy-4',6'-dimethoxyacrylophenone have been found as more effective on COVID-19 than nelfinavir. So, this study will pave a way for doing advanced experimental research to evaluate the real medicinal potential of these compounds to cure COVID-19.

Finding sustainable renewable energy sources for energy conversion and management is still an obscure topic. This paper presents a model-based simulation for an energy conversion system using piezoelectric energy harvester (PEH) technology. A dynamic mathematical model of a PEH device consists of a piezoelectric transducer, a controlled PWM rectifier, and a closed-loop buck boost converter is developed. A piezoelectric transducer converts mechanical vibrations from a wind force into an oscillating train of electrical charges. The sinewave peak-to-peak level relationship describes the changeable values of these charges, which depend on the severity of the wind vibration. The controlled PWM rectifier, in conjunction with a closed-loop buck-boost converter, converts this train of sinewave cycles into DC voltages. The control blocks of the closed-loop buck-boost converter use the perturbation and observation (P&O) algorithm based on maximum power point tracking (MPPT), which adapts the operational voltage of the piezoelectric source to deliver the maximum power to load and improves the PEHS output voltage stability. A simulation program is employed to perform mathematical analysis on various wind vibration scenarios, piezoelectric sources without PWM converters, and piezoelectric vibration sources connected to a closed-loop P&O converter. The crucial results of this paper demonstrate that the proposed dynamic PEHS model effectively feeds low-power electronic loads by directly adjusting the output voltage level to the set voltage, even under different vibration severity levels. As a result, the proposed PEHS dynamic model serves as a guideline for researchers in the development of self-powered sensors, which contributes to understanding sustainable energy alternatives.

This study assessed the impact of climate change on water availability and variability in two subbasins in the Upper Blue Nile Basin of Ethiopia. Downscaled future climate data from HadCM3 of A2 (medium-high) and B2 (medium-low) emission scenarios were compared to the observed climate data for a baseline period (1961 to 1990). The emission scenario representing the baseline period was used to predict future climate and as input to a hydrologic model to estimate the impact of future climate on the streamflow at three future time horizons 2020 - 2045, 2045 - 2070 and 2070 - 2100. Results suggest that medium-high emission scenario best represents the local rainfall and temperature pattern. With A2 scenario, daily maximum/minimum temperature will increase throughout the future time horizons. The minimum and maximum temperature will increase by 3.6^oC and 2.4^oC, respectively, towards the end of the 21st century. Consequently, potential evapotranspiration is expected to increase by 7.8%, though trends in annual rainfall do not show statistically meaningful trends between years. A notable seasonality was found in the rainfall pattern such that dry season rainfall amounts are likely to increase and wet season rainfall to decrease. The hydrological model indicated that the local hydrology of the study watersheds will be significantly influenced by climate change. Overall, at the end of the century, streamflow will increase in both rivers by up to 64% in dry seasons and decrease by 19% in wet seasons.

In this article, the effect of substitution of Zr and Ga in Dy2Fe17 prepared by arc melting technique are studied. The substitution of Zr and Ga in Dy2Fe17 was found to have an important effect on their structure and magnetic properties. The Rietveld analysis conformed that the crystalline system wereTh2Ni17 structure. Lattice parameters a (Å) and c (Å), unit cell volume (Å3), bonding distance (Å) were calculated by using Rietveld analysis. The unit cell volume of Dy2Fe17-xZrx and Dy2Fe16Ga1-xZrx increase linearly with the Zr and Ga substitution. The substitution of Zr and Ga are limited up to x=1 in order to avoid the decrease in saturation magnetization. The Curie temperature (Tc) of Dy2Fe17-xZrx and Dy2Fe16Ga1-xZrx are found to be Zr content dependent. The Curie temperature is found to be increasing first and then decrease for higher Zr content. The maximum curie temperature was observed 510K at x = 0.75 for Dy2Fe17-xZrx and 505.1 K at x = 0.5 for Dy2Fe17-xZrx which are102 K and 97 K higher than Dy2Fe17. The room temperature Mössbauer analysis shows the decrease in average hyperfine field and increase in isomer shift with Zr doping.

This study focuses on a new class of functions called sub-b-s-preinvex, that is a generalization of sub-b-s-convex and preinvex functions, and discusses some of their properties. A new sub-b-s-preinvex programming is introduced and the sufficient conditions of optimality under this type of function is established.

In this paper, a new identity for the generalized fractional integral is defined, through which new integral inequality for functions whose first derivatives in absolute value are convex. The new generalized Hermite-Hadamard inequality for generalized convex function on fractal sets involving Katugampola type fractional integral is established. We derive trapezoid and mid-point type inequalities connected to these generalized Hermite-Hadamard inequality.

Rough volatility models are popularized by \cite{gatheral2018volatility}, where they have shown that the empirical volatility in the financial market is extremely consistent with rough volatility. Fractional Riccati equation as a part of computation for the characteristic function of rough Heston model is not known in explicit form as of now and therefore, we must rely on numerical methods to obtain a solution. In this paper, we give a short introduction to option pricing theory and an overview of the current advancements on the rough Heston model.

In this paper, some characterizations of fuzzifying strong compactness are given, including characterizations in terms of nets and pre -subbases. Several characterizations of locally strong compactness in the framework of fuzzifying topology are introduced and the mapping theorems are obtained.

Sumudu transform of the Dixon elliptic function with non zero modulus a ≠ 0 for arbitrary powers sm^N(x,a) ; N ≥ 1 ; sm^N(x,a)cm(x,a) ; N ≥ 0 and sm^N(x,a)cm²(x,a) ; N ≥ 0 is given by product of Quasi C fractions. Next by assuming denominators of Quasi C fraction to 1 and hence applying Heliermann correspondance relating formal power series (Maclaurin series of Dixon elliptic functions) and regular C fraction, Hankel determinants are calculated and showed by taking a = 0 gives the Hankel determinants of regular C fraction. The derived results were back tracked to the Laplace transform of sm(x,a) ; cm(x,a) and sm(x,a)cm(x,a).

In this paper, the new optical wave solutions of truncated M-fractional perturbed Kundu-Eckhaus model with full non-linearity are obtained by utilizing the expa function technique and modified extended tanh expansion function technique. The solutions are in the form of dark soliton, bright soliton, singular solitons and other form of solutions. The gained solutions are helpful for the further development of concerned model. The obtained results have also been presented graphically in both two-dimensional and three-dimensional formats to discuss the dynamical features as well as the parametric dependence of the constructed solutions. The study offers a highly spectacular and acceptable techniques to combine various intriguing wave demonstrations for more sophisticated models of the modern day.

The Ali-Cesaro Stolz theorem, introduced in this paper, extends the classical Cesaro-Stolz theorem by addressing cases where the latter does not yield results or provides a "Does Not Existe (DNE) form. This novel theorem leverages the properties of limits and Z-transforms, offering a robust framework for analyzing sequences and series. The theorem is particularly effective in scenarios where traditional approaches fail, providing new insights and tools for mathematical analysis. This paper presents a detailed formulation of the Ali-Cesaro Stolz theorem, including proofs, applications, and a discussion on its implications and advantages over existing methods.

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

Doxorubicin (DOX) is an incessantly used chemotherapeutic drug that can cause detrimental dose-dependent effects such as cardiotoxicity and congestive heart failure. Hence, there is a need to discover innovative therapeutic approaches to counteract DOX-induced cardiotoxicity (DIC). MSC-Exos have shown to reduce apoptosis and cardiac fibrosis and promote cardiomyocyte proliferation in myocardial infracted mice. However, the effect of MSC-Exos on ameliorating DOX-induced pyroptosis has not been investigated. In this current study H9c2 were first exposed to DOX to stimulate pyroptosis, followed by subsequent treatment with MSC-Exos, with further analysis performed through immunocytochemistry, western blotting, and RT-PCR. Our data depicted that post-treatment with MSC-Exos significantly (p<0.05) reduced the HMGB1/TLR4 axis, inflammasome formation (NLRP3), pyroptotic markers (caspase-1, IL-1β, and IL-18), and the pyroptotic executioner (GSDMD) in DOX-treated H9c2 cells. In conclusion, our data shows that MSC-Exos attenuates inflammation-induced pyroptosis in our in vitro DIC model. Our findings indicate that MSC-Exos may serve as a promising therapeutic intervention for mitigating DIC, as they maintain the therapeutic capabilities of MSCs while circumventing the drawbacks associated with traditional stem cell therapy.

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

The prim objective of commenced article is to determine q-sumudu transforms of a product of unified family of q-polynomials with basic (or q-) analogue of fox’s H-function and q-analog of I-functions. Specialized cases of the leading outcome are further evaluated as q-sumudu transform of general class of q-polynomials and q-sumudu transforms of the basic analogues of Fox’s H-function and I-functions.

In this study, we define new classes of convexity called of h-Godunova-Levin and h-Godunova-Levin preinvexity, through which some new inequalities of Hermite-Hadamard type were established. These new classes are the generalisation of several known convexity including the s-convex, P-function, Godunova-Levin. Further, the properties of h-Godunova-Levin function were also discussed. Meanwhile, the applications of h-Godunova-Levin Preinvex function are given

In this article, the new Hermite–Hadamard type inequalities are studied via generalized s-convexity on fractal sets. These inequalities derived on fractal sets are shown to be the generalized s-convexity on fractal sets. We proved that the absolute values of the first and second derivatives for the new inequalities are the generalization of s-convexity on fractal sets.

In the present work we study the properties of geodesic sub-$ (\alpha,b,s) $-preinvex functions on Hadamard manifolds and establish some basic properties in both general and differential cases. Further, we study sufficient conditions of optimality and proved some new inequalities under geodesic sub-($ \alpha,b,s $)-preinvexity.

In this article, the new Hermite–Hadamard type inequalities are studied via generalized s-convexity on fractal sets. These inequalities derived on fractal sets are shown to be the generalized s-convexity on fractal sets. We proved that the absolute values of the first and second derivatives for the new inequalities are the generalization of s-convexity on fractal sets.

The generalized Kuramoto–Sivashinsky equation is investigated using the modified Kudrayshov method for the exact analytical solution. The modified Kudrayshov method converts the nonlinear partial differential equation to algebraic equations, as a result of various steps, which on solving the so obtained equation systems yields the analytical solution. By this way various exact solutions including complex structures are found and drawn their behaviour in complex plane by Maple to compare the uniqueness of solutions.

This article deals with the conformable double Laplace transforms and their some properties with examples and also the existence Condition for the conformable double Laplace transform is studied. Finally, in order to obtain the solution of nonlinear fractional problems, we present a modified conformable double Laplace that we call conformable double Laplace decomposition methods (CDLDM). Then, we apply it to solve, Regular and singular conformable fractional coupled burgers equation illustrate the effectiveness of our method some examples are given.

Climate change is a major development challenge to Ethiopia. Unless adaptation measures are widely implemented, climate change can set back development efforts and achievements by years. Recognizing this, the Government of Ethiopia (GoE) and civil society organizations have since recently been making considerable efforts to tackle the climate change problem. This paper documents the experience of CARE International in Ethiopia in facilitating bottom-up approaches to promote community-led disaster risk management and climate change adaptation planning through a participator scenario planning (PSP) methodology. PSP is a coordinated approach which leverages a variety of stakeholders' skills and mandates to explore potential climate change risks and their impacts, and then develop locally relevant and shared adaptation action plans that support livelihoods, social capital and ecosystem resilience. The approach has facilitated timely access to and communication of seasonal climate advisories which in turn is empowering communities to take advantage of opportunities that climate presents, which is a key part of adapting to climate change. The institutionalization of the approach by district and regional disaster prevention and food security coordination offices in the southern pastoral regions of Ethiopia encouraged integration of PSP into community livelihood adaptation and local government development planning, hence continuity of the process. Sustainability is expected to be fully achieved when local government planning processes recognize the importance of and provides resources for the participation of meteorological services and community forecasting experts to help refine plans on a seasonal basis, and for systems for dissemination of advisories. Key words: Climate Change, Disaster Risk Reduction, Adaptation, Pastoralism, Ethiopia,

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

Researches are moving to iron and ammonia elimination from ground water. Here, we are using poly acrylic–poly acrylamide hydrogel which grafted with 3-chloroaniline. This copolymer was synthesized by addition polymerization. Effect of agitation time, dosage and adsorbents temperature on the removal process sensitivity has been investigated. The copolymer was described experientially and theoretically. Isothermal, kinetic adsorption models and were discussed. This hydrogel could be regenerated efficiently (98.3%removal of iron and 100% removal of ammonia). Density functional theory DFT method using B3LYP/6-311G(d,p),LANL2DZ level of the theory were managed to investigate stationary states of grafted co-polymer and the complexation energy of the hydrogel with the studied cations. NBO analysis is using DFT to investigate the negative centers on the hydrogel. The complexation energy showed selectively of hydrogel to studied cations.

In this study, we first present a time-fractional L$\hat{e}$vy diffusion equation of the exponential option pricing models of European option pricing and the risk-neutral parameter. Then, we modify a particular L$\hat{e}$vy-time fractional diffusion equation of European-style options. Introduce a more general model from the models based on the L$\hat{e}$vy-time fractional diffusion equation and review some recent findings regarding of the Europe option pricing of risk-neutral free.

Aggregating data is the main line of any discipline dealing with fusion of information from the knowledge-based systems to the decision-making. The purpose of aggregation methods is to convert a list of objects, all belonging to a given set, into a single representative object of the same set usually by an n-ary function, so-called aggregation operator. Since the useful aggregation functions for modeling real-life problems are limit, the basic problem is to construct a proper aggregation operator for each situation. During the last decades, a number of construction methods for aggregation functions have been developed to build new classes based on the well-known operators. This paper reviews some of these construction methods where they are based on transformation, composition and weighted rule.

This research aims to analyse the sustainability of retirement system and relevant optimal path to achieve sustainable post-retirement livings in Malaysia context. Focus of this study is put on Employees Provident Fund (EPF) which is mainly constituted by employees from private sector. EPF is a fully funded defined-contribution by both employees and employers. In this research, main variables used are contribution rate and retirement age based on relevant indexation of pension. For a sustainable retirement living, retirement benefits are expected to be in a maximisation function. Attempts to find sustainable retirement fund are via step-by-step mathematical calculation using formulas in Microsoft Excel and verification of the result with Excel Solver via Generalised Reduced Gradient (GRG) algorithm. Eventually, two-third retirement decision model is used to justify the sustainability of retirement fund other than justification using monthly household expenditure.

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

Aim: This study measures and evaluates the socioeconomic burden of people living with keratoconus in Saudi Arabia. Methods: The study employed a cross-sectional design, a Keratoconus Economic Burden Questionnaire, and a convenient sample of 89 keratoconus patients (58.4% male) drawn from multiple regions in Saudi Arabia. It was conducted using online surveys and the data was analysed using appropriate quantitative techniques. Results: The mean age and annual income of participants were 33.24 years and Saudi Riyal (SAR) 33,505.6180 (SD=62,215.29), respectively, with only 37% being employed for wages. Up to 94.4% needed glasses or contact lenses at least once a week and 73.0% received care from optometrists. The condition forced 45.9% of the respondents to change careers or leisure activities, with a further 51.3% having to take time off work. The mean annual out-of-pocket expenses for buying and maintaining glasses or contact lenses as well as traveling and accommodation for keratoconus-related treatment were SAR 8,673.19 (SD=11,307.73), with 48.32 incurring upwards of SAR 12,000 over the period. The treatment costs increased with disease duration, r(89) = .216, p < .05. Regression results show that the existence of comorbid eye disease, changing glasses at least once a year, and wearing either glasses or contact lenses at least once a week individually have statistically significant, negative effects on the total annual keratoconus treatment costs, while disease duration, utilisation of optometrists, and taking time off had a statistically significant increase on the total cost (p<.05). Conclusion: With a prevalence rate of 1 in 375, progressive debilitation, and the lifetime nature of the disease, keratoconus is a critical public health concern in Saudi Arabia. The resulting visual impairment and discomfort as well as both direct and indirect economic burdens have considerable impacts on the patient's quality of life.

Purpose of this article is to introduce a modification of Phillips operators on the interval $\left[ \frac{1}{2},\infty \right) $ via Dunkl generalization. This type of modification enables a better error estimation on the interval $\left[ \frac{1}{2},\infty \right) $ rather than the classical Dunkl Phillips operators on $\left[ 0,\infty \right) $. We discuss the convergence results and obtain the degrees of approximations. Furthermore, we calculate the rate of convergence by means of modulus of continuity, Lipschitz type maximal functions, Peetre's $K$-functional and second order modulus of continuity.

Purpose of this article is to introduce a modification of Phillips operators on the interval $\left[ \frac{1}{2}% ,\infty \right) $ via Dunkl generalization. This type of modification enables a better error estimation on the interval $\left[ \frac{1}{2},\infty \right) $ rather than the classical Dunkl Phillips operators on $\left[ 0,\infty \right) $. We discuss the convergence results and obtain the degrees of approximations. Furthermore, we calculate the rate of convergence by means of modulus of continuity, Lipschitz type maximal functions, Peetre's $K$-functional and second order modulus of continuity.

Recently, the environment is being put under constantly increasing pressure. Globally, water shortage is considered as one of the most serious environmental problems which affect human life and plant wealth. Iraq is highly affected by water deficit in many regions. In particular, Al-Najaf region is selected to be under evaluation for the current and future water resources shortage. This study is based on the collected data for rainfall, evaporation, flow-rate, groundwater, water needed for irrigation, and daily uses for the period between 2000 and 2018. The Artificial Neural Network, normal distribution, and lognormal distribution type III are applied for analyzing the collected data in addition to predict the water shortage for year 2050. Results show a water shortage in years 2002, 2004, 2005, and 2017 only for the selected period. A Simulink model is constructed using Matlab to increase the credibility of the estimated results and gives accurate results for the groundwater and surface water needed. Where in 2050, it is found that it needs to use the groundwater source by 0.024 x 10⁹ m³ to support the surface water source which is represented by the Euphrates River. The study shows the extent of inefficient management of water resources in Al-Najaf region.

We consider a model of predator-prey interaction at fractional-order where the predation obeys the ratio-dependent functional response and the prey is linearly harvested. For the proposed model, we show the existence, uniqueness, non-negativity as well as the boundedness of the solutions. Conditions for the existence of all possible equilibrium points and their stability criteria, both locally and globally, are also investigated. The local stability conditions are derived using the Magtinon's theorem, while the global stability is proven by formulating an appropriate Lyapunov function. The occurance of Hopf bifurcation around the interior point is also shown analytically. At the end, we implement the Predictor-Corrector scheme to perform some numerical simulations.

K-band radar waves have high penetration and low attenuation coefficients. However, the wavelength of this radar wave is relatively short; thus, designing and preparing both broadband and wide-angle radar wave absorbers in this band presents considerable challenges. In this study, a resin-based K-band radar wave absorber with a biomimetic lotus leaf structure was designed and formed by UV curing. Here, microscale lotus leaf papillae and antireflection structures were prepared using a DLP 3D printer, and the contact angle between the material and water droplets was increased from 56° to 130°. In addition, the influence of the geometric parameters of the lotus leaf antireflection structure on the electromagnetic absorption performance and mechanical strength was investigated. After simulation optimization, the maximum electromagnetic loss of the lotus leaf structure 3D printed sample was −32.3 dB, and the electromagnetic loss was below −10 dB in the 20.8–26.5 GHz frequency range. When the radar incidence angle was 60°, the maximum electromagnetic loss was still less than −10 dB. The designed lotus leaf structure has a higher mechanical energy absorption per unit volume (337.22 KJ/m3) and per unit mass (0.55 KJ/Kg) than commonly used honeycomb lightweight structures during the elastic deformation stage, and we expect that the designed structure can be used as an effective lightweight material for K-band radar stealth.

This article aims to discuss, the stability and boundedness character of the solutions of the rational equation of the form \begin{equation}\label{eql21.1} y_{t+1}=\frac{\nu\epsilon^{-y_t}+\delta\epsilon^{-y_{t-1}}}{\mu+\nu y_t+\delta y_{t-1}},\quad t\in N(0). \end{equation} Here, $\epsilon>1, \nu,\delta,\mu\in (0,\infty)$ and $y_0, y_1$ are taken as arbitrary non-negative reals and $N(a)=\{a,a+1,a+2,\cdots \}$. Relevant examples are provided to validate our results. The exactness is tested using MATLAB.

Using first-principles molecular dynamics (FPMD), we performed numerical simulations at 300 K to explore the interaction of a 2D MoS2 surface and a platinum atom, calculating the optical properties of the resulting material. The pristine MoS2 is a semiconductor with a gap of around 1.8 eV. The Pt atom is chemisorbed by the surface with an adsorption energy of −1.718 eV. With the adsorption of the Pt atom, the material remains a semiconductor, and its energy band gap reduces to 1.04 eV. But changes in the material's energy band structure imply substantial changes in its optical properties. The energy band structure of the 2D MoS2 with a sulfur vacancy VS shows that the material becomes a conductor, and there are significant changes in its optical properties. We also found that the Pt atom chemisorbs in a sulfur vacancy of the material, with an adsorption energy of −4.1164 eV. After the adsorption of Pt atoms in the sulfur vacancy, the material becomes a semiconductor with a band gap of 1.06 eV, and the changes in the optical absorption and reflectivity are significant.

This paper aims to investigate the criteria of behaviour of certain type of third order neutral generalized difference equations with distributed delay. With the technique of generalized Riccati transformation and Philos-type method, some oscillation criteria are obtained to ensure convergence and oscillatory solution of suitable example is listed to illustrate the main result.

The authors intend to establish new oscillation criteria for a class of generalized third order functional difference equation of the form \begin{equation}{\label{eq01}} \Delta_{\ell}\left(a_2(n)\left[\Delta_{\ell}\left(a_1(n)\left[\Delta_{\ell}z(n)\right]^{\beta_1}\right)\right]^{\beta_2}\right)+q(n)f(x(g(n)))=0, ~~n\geq n_0, \end{equation} where $z(n)=x(n)+p(n)x(\tau(n))$. We also present sufficient conditions for the solutions to converges to zero. Suitable examples are presented to validate our main results.

In the present work we study the existence of solutions for hybrid nonlinear fractional integrodifferential equations. We developed an algorithm by using the operator theoretical techniques in order to obtain the approximate solutions. The main results depend on the Dhage iteration method that were incorporated with the modern hybrid fixed point theorems. The approximate solutions were obtained by using Lipschitz conditions and weaker form of mixed partial continuity. Further, we provide some examples to explain the hypotheses and the related results.

Presently, smartphones support a large range of applications, many of which require high computing power. This presents a problem because smartphones offer limited computing power, storage, and energy. Fortunately, Cloud computing (CC) is rapidly becoming known as the state of the art technology in the computer world. CC allows users to use unlimited dynamic resources when necessary. Mobile Cloud Computing (MCC) is integration into a mobile environment of the concept of cloud computing which eliminates barriers to the performance of mobile devices. The demand for mobile cloud applications and mobile user services is strong. This gives MCC a great opportunity to do business and research. However, security problems are a major obstacle to the adaptability of mobile cloud computing. This study presents the definitions of Cloud Computing, Mobile Computing (MC) and Mobile Cloud Computing including the architecture and applications of MCC. Furthermore, it discusses the challenges and opportunities faced in MCC.

Dielectric spectroscopy (DS) is a promising cell screening method that can be used for diagnostic and drug discovery purposes. The primary challenge of using DS in physiological buffers is the electrode polarization (EP) that overwhelms the impedance signal within a large frequency range. These effects further amplify with miniaturization of the measurement electrodes. In this study, we present a microfluidic system and the associated equivalent circuit models for real-time measurements of cell membrane capacitance and cytoplasm resistance in physiological buffers with 10s increments. The current device captures several hundreds of biological cells in individual microwells through gravitational settling and measures the system’s impedance using microelectrodes covered with dendritic gold nanostructures. Using PC-3 cells (a highly metastatic prostate cancer cell line) suspended in cell growth media (CGM), we demonstrate stable measurements of cell membrane capacitance and cytoplasm resistance in the device for over 15 minutes. We also describe a consistent application of the equivalent circuit model, starting from the reference measurements used to determine the system parameters. The circuit model is tested using devices with varying dimensions, and the obtained cell parameters between different devices are nearly identical. Further analyses of the impedance data have shown that accurate cell membrane capacitance and cytoplasm resistance can be extracted using a limited number of measurements in the 5 MHz to 10 MHz range. This will potentially reduce the timescale required for real-time DS measurements below 1s. Overall the new microfluidic device can be used for dielectric characterization of biological cells in physiological buffers for various cell screening applications.

In this article, we consider the three dimensional $\alpha$-fractional nonlinear delay differential system of the form \begin{align*} D^{\alpha}\left(u(t)\right)&=p(t)g\left(v(\sigma(t))\right),\\D^{\alpha}\left(v(t)\right)&=-q(t)h\left(w(t))\right),\\D^{\alpha}\left(w(t)\right)&=r(t)f\left(u(\tau(t))\right),~ t \geq t_0, \end{align*} where $0 < \alpha \leq 1$, $D^{\alpha}$ denotes the Katugampola fractional derivative of order $\alpha$. We have established some new oscillation criteria of solutions of differential system by using generalized Riccati transformation and inequality technique. The obtained results are illustrated with suitable examples.

The key objective of the present paper is to propose a numerical scheme based on the homotopy analysis transform technique to analyze the time-fractional nonlinear predator-prey population model. The population model is coupled fractional order nonlinear partial differential equations often employed to narrate the dynamics of biological systems in which two species interact, first is a predator and the second is a prey. The proposed scheme provides the series solution with great freedom and flexibility by choosing appropriate parameters. The convergence of results is free from small or large parameters. Three examples are discussed to demonstrate the correctness and efficiency of the used computational approach.

The purpose of this article is to characterize the Caristi type mapping by the absolute derivative. The equivalences of the Caristi mapping with contraction mapping is discussed too. In addition, it was shown that the contraction mapping can be characterized by its absolute derivative.

In this article, we show the existence of fixed point for the derivative of interval-valued functions. Meanwhile, the fixed point inquiry will utilize the common fixed point methods under the condition of compatibility of the hybrid composite mappings in the sense of the Hausdorff metric. Some examples are given to support the usability of the result of this research .

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

In this paper, initially a mathematical model is formulated for transient frequency of power system considering time delays which occur while transmitting the control signals in open communication infrastructure. Time delay negligence in a power system leads to improper measurement of frequency variation in power system. The study of impact of time delays on the stability of power system is performed by estimating the decay rate of frequency wave form using Kalman Filter (KF). In power system, there is a possibility of multiple time delays. This paper also focusses on developing Interacting Multiple Model (IMM) Algorithm with multiple model space using Kalman Filter (KF) as state estimator tool. The multiple time delays in power system is considered as multiple model space. The result shows that KF provides better estimate of correct model for a particular input-set. The qualitative properties of Riccati difference equation (RDE) in terms of state error covariance of IMMKF are also analyzed and presented.

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

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

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

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

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

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

Short Linear Motifs (SLiMs) are short linear sequences that can mediate protein-protein interaction. Mimicking eukaryotic SLiMs to compete with extra or intracellular binding partners or to sequester host proteins is the crucial strategy of viruses to pervert the host system. The evolved proteins in viruses facilitate minimal protein-protein interactions that significantly affect intracellular signaling networks. Unfortunately, very little information about the SARS-CoV-2 SLiMs is known, especially across the SARS-CoV-2 variants. Through ELM database-based sequence analysis of spike protein from all the major SARS-CoV-2 variants, we identified four overriding SLiMs in the SARS-CoV-2 Omicron variant including LIG_TRFH_1, LIG_REV1ctd_RIR_1, LIG_CaM_NSCaTE_8, and MOD_LATS_1. These SLiMs are highly likely to interfere with various immune functions, interact with host intracellular proteins, regulate cellular pathways, and lubricate viral infection and transmission. These cellular interactions possibly serve as potential therapeutic targets for these variants, and this approach can be further exploited to combat emerging SARS-CoV-2 variants.

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

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

Recent years have witnessed significant advances in reinforcement learning (RL), which has registered remarkable success in solving various sequential decision-making problems in machine learning. Most of the successful RL applications, e.g., the games of Go and Poker, robotics, and autonomous driving, involve the participation of more than one single agent, which naturally fall into the realm of multi-agent RL (MARL), a domain with a relatively long history, and has recently re-emerged due to advances in single-agent RL techniques. Although, typically, the communication protocol between agents is manually specified and not altered during training, recently, some papers have shown signs of trying to emerge a communication between agents on the one hand and, on the other hand, to understand what is exchanged between agents. So, there is a growing body of literature on this topic which includes qualitative and quantitative studies and the ones that apply mixed methods. This study presents the scoping review of the methodological strategies undertaken in a total of 16 research articles. The results present the critical appraisal of quantitative methods in terms of validity and reliability and for qualitative methods considering four trustworthiness factors. In the end, relevant insights are further explored with implications and reflections on how they can benefit one's research in the field.

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

Background: COVID-19 vaccines have been a game changer in the pandemic, their extensive use was favorable compared to the burden of COVID-19 complications. Despite the low incidence of complications, it was important to analyze them carefully to understand the underlying mechanisms and predisposing factors. For instance, myopericarditis especially from mRNA vaccines, and its relatively higher prevalence in young adults and adolescents has raised a public concern about the use of this vaccine in this group. We aimed through this review to compare the age likelihood of ADEM from COVID-19 vaccines, with that reported in myopericarditis cases; secondary outcome parameters included the gender and number of doses needed to induce COVID-19 vaccines related ADEM. Methodology: A literature search has been conducted on relevant databases to retrieve all case reports/series and systematic reviews describing ADEM with possible linkage to COVID-19. Exclusion criteria included any report not including the desired outcome parameters. Our results were then qualitatively compared with a similar systematic review reporting myopericarditis from COVID-19 vaccines. Results: In 38 cases with ADEM, mean age was 49±16 compared to 25±14 in myopericarditis, females were more likely to be affected, and while most of myopericarditis cases develop after the second dose, most of ADEM cases develop after the first dose (76%). Moreover, age>56 years was more predictive of negative outcome after ADEM in the form of death or permanent vegetative state. Conclusion: The discrepancy in age, gender and number of doses needed to induce complications between ADEM and myopericarditis, signify that the tissue affected is the major orchestrator of the age, gender, and dose characteristics, and not the type of vaccines. A leakier blood brain barrier with aging, might allow easier passage of autoantibodies and cytokines into the brain while lack of inhibitory immune checkpoints in the myocardium in young age might explain the higher prevalence of those cases in young adults and adolescents.

Background and objectives: Chronic Kidney Disease and Mineral Bone Disorders (CKD-MBD) are frequently associated with an increased risk of both Vascular Calcifications (VCs) and bone fractures (BFs). The complex pathogenesis of VCs and BFs involves various factors such as calcium overload, phosphate imbalance, and secondary hyperparathyroidism. Key players, such as the vitamin K-dependent proteins (VKDPs) matrix Gla protein (MGP) and osteocalcin (BGP), have pivotal roles both for VCs and BFs. The Vitamin K Italian (VIKI) dialysis study, highlighted that hemodialysis patients treated with calcimimetics had higher levels of total BGP and MGP as compared to those untreated, suggesting a potential protective effect of these drugs on BFs and VCs, beyond the beneficial effect to reduce PTH levels. Methods: ETERNITY-ITA is a multi-center, comparative effectiveness, observational, longitudinal study that will enroll 160 hemodialysis patients (80 patients treated with Etelcalcetide and 80 age and sex-matched patients treated with Calcitriol or vitamin D analogs). Nephrologists will tailor the target dose of Etelcalcetide on individual level to achieve the KDIGO PTH target. In the Etelcalcetide-treated group, the addition of calcitriol will be allowed when required by clinical practice (for correction of hypocalcemia). Conclusion: The study will evaluate the real-world effect of Etelcalcetide on VKDP levels, such as BGP and MGP, at 3, 9, and 18 months from baseline. The resulting preservation of vascular and bone health will be assessed for the first time by examining aortic and iliac artery calcifications and vertebral fractures, respectively. Keywords: bone fractures; etecalcetide; hemodialysis; vascular calcification; vitamin K

The tumor necrosis factor receptor associated factor 1 (TRAF1) plays a key role in promoting lymphocyte survival, proliferation, and cytokine production. Recent evidence showed that TRAF1 plays opposing roles in monocytes and macrophages where it controls NF-B activation and limits pro-inflammatory cytokine production as well as inflammasome-dependent IL-1 secretion. Importantly, TRAF1 polymorphisms have been strongly linked to an increased risk of rheumatoid arthritis (RA). However, whether and how TRAF1 contributes to RA pathogenesis is not fully understood. Moreover, investigating the role of TRAF1 in driving RA pathogenesis is complicated by its multifaceted and opposing roles in various immune cells. In this study, we show that intraarticular injection of TRAF1 deficient macrophages into knee joints of wildtype (WT) mice subjected to the collagen antibody induced arthritis (CAIA) model of RA significantly exacerbated joint inflammation, immune cell infiltration and tissue damage compared to mice injected with WT macrophages. This study may lay the groundwork for novel therapies for RA that target TRAF1 in macrophages.

Hyperlipidemia is an identified risk factor for metabolic syndrome, obesity and cardiovascular complications characterized by elevated levels of lipids in blood. The present study aimed to inhibit HMG-CoA reductase with 15-oxoursolic acid through in-vivo and in-silico assessments. HFD-induced hyperlipidemia in rats was developed with a marked increase in total cholesterol (58.34 ± 0.21 mg/dl), triglycerides (45.45 ± 0.39 mg/dl), LDL-c (66.12 ± 0.10 mg/dl), VLDL-c (19.34 ± 0.16 mg/dl), and a decrease in HDL-c (10.34 ± 0.18 mg/dl). The oral administration of 15-oxoursolic acid at a concentration of 30 mg/Kg b.w significantly reduced the serum concentration of total cholesterol (42.65 ± 0.54 mg/dl), triglycerides (32.33 ± 0.16 mg/dl), LDL-c (50.34 ± 0.15 mg/dl) and VLDL-c (13.15 ± 0.45 mg/dl) respectively and an increased in the serum HDL-c (18.56 ± 0.34 mg/dl). 15-oxo ursolic acid also caused a decrease in the coronary risk index and atherogenic risk index. In-silico studies of 15-oxoursolic acid with HMG-CoA reductase showed significant interaction capability with binding energy (-9.26805 Kcal/mol). It is concluded that 15-oxoursolic acid could significantly reduce the total cholesterol, triglycerides and LDL levels in HFD-induced hyperlipidemia rats which might lead to new medication with significant hypolipidemic potential.

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

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

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

Sugarcane (Saccharum spp.) is a crop of great industrial and alimentary importance, essential for the production of numerous products. Given its significance, genetic improvement programs exist that involve a rigorous study process, from material selection to the development of new varieties, requiring at least seven selection phases. This study modeled the growth curve of the sucrose percentage (SP) in 33 hybrids and six control varieties (MEX 69-290, ITV 92-1424, CP 72-2086, COLMEX 94-8, COLMEX 95-27, RB 85-5113) during the plant and ratoon periods in the experimental fields of the Melchor Ocampo Sugar Mill, Jalisco, Mexico. For clustering the materials, k-means, k-medoids, and Density-based spatial clustering of applications with noise (DBSCAN) algorithms were used, considering four maturity types among the control varieties. The DBSCAN algorithm proved to be the most effective, as the means between groups were not statistically equal. The hybrids identified as candidates for subsequent phases due to their high SP were COSTA JAL, ATEMEX 99-48, ATEMEX 99-1, ATEMEX 99-61, MEX 70-486, MEX 80-1521, ITSAMEX 07-44814, ITSAMEX 06-6395, and ITSAMEX 07-1903. These results are crucial for improving the productivity and sustainability of the crop, with significant implications for the sugar industry.

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

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

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

Automatic and blind parameter estimation based on the inherent features of wireless signals is a major research area due to the fact that these techniques lead to the simplification of receivers, especially in terms of coarse synchronization, more importantly reduce down the signaling load at the control channels. Thus, in the literature many techniques are proposed to estimate a vast set of parameters including modulation types and orders, data and chip rates, phase and frequency offsets and so on. In this paper, a cyclostationary feature detection based method is proposed to estimate the carrier numbers and carrier spacing of carrier-aggregated direct sequence spread spectrum cellular signals blindly. The particular chip rate of the signal is also estimated through the process jointly. In the paper, after the proposed method is formulated, the measurement setup which is developed to collect the data for the validation of the proposed method is introduced. The measurement results are post-processed for performance analysis purposes. To that end, the method is investigated in terms of SNR values, different channel conditions, and measurement durations. Furthermore, the performance of the proposed method is compared with that of energy detection. Measurement results indicate superior performance of the proposed method under significant wireless channel impairments and in low-SNR regions.

Energy storage systems play a crucial role in the overall performance of hybrid electric vehicles. Therefore, the state of the art in energy storage systems for hybrid electric vehicles has been discussed in this paper along with appropriate background information for facilitating future research in this domain. Specifically, we have compared the key parameters such as cost, power density, energy density, cycle life, and response time for various energy storage systems. For the energy storage systems employing ultra capacitors, we have presented the characteristics such as cell voltage, cycle life, power density and energy density. Furthermore, we have discussed and evaluated the interconnection topologies for the existing energy storage systems. We have also discussed the hybrid battery-flywheel energy storage system as well as the mathematical modeling of the battery-ultracapacitor energy storage system. Toward the end, we have discussed energy efficient powertrain for hybrid electric vehicles.

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

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

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

This study aims to conduct a content analysis of the postgraduate theses on the education of the concept of atom in Turkey from 2000 to 2023. The study utilized the document analysis method, a qualitative research design approach. The theses were obtained by conducting a search in the "Thesis Center" of the Council of Higher Education (YÖK). "Thesis Classification Form" and "Thesis Screening Form" were used as data collection tools. Content analysis was performed on 51 theses that were conducted between 2000 and 2023 and whose full versions were accessed. It was observed that the theses were conducted in 25 different universities, using more than one data collection tool and analysis method. It was determined that most of the theses were supervised by academicians having the title of Prof.Dr. It was determined that almost all of the theses were conducted in the form of research-studies, qualitative research approach was mostly used as the research method, quasi-experimental model was mostly used as the research model, and students were generally used as the sample group. The most widely used data collection tools in the theses were interviews and achievement tests, while t-tests and content analysis were used as analysis techniques. In the selection of thesis topics, the studies in which teaching methods were tried the most were conducted. It was determined that students had difficulty in understanding the concept of atom and had misconceptions.

Pakistan relies mostly on fossil fuel for fulfilling its energy demand which is expensive as 11 well as not friendly for the environment. The need of the hour is to shift from fossil fuels to renew-12 able energy resources like geothermal, wind, solar etc. to cater for global warming issues. Pakistan 13 has a lot of potential geothermal sites because of several fault lines and hot springs. A sound 14 knowledge of ground temperature is essential to use geothermal energy, which is obtained by drill-15 ing boreholes and putting sensors making it an expensive procedure. Thus, to avoid huge cost for 16 drilling bore holes, particularly for ground temperature analysis, a numerical approach has been 17 considered for determining ground temperature. Furthermore, correlation charts between air and 18 ground temperatures have been developed as there were no proper studies on the ground temper-19 ature of Pakistan. Then, with the help of a boreholes drilled in National University of Sciences and 20 Technology Islamabad Pakistan, the actual ground and numerically calculated temperatures have 21 been compared which shows an error margin in the range between 0.27% for higher depths to 7.3% 22 near surface. Thus, it is shown that the proposed method is easy to implement and better than large 23 scale testing methods for the depths at which geothermal energy is extracted.

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

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

Beta thalassemia is an inherited blood disorder that results in inefficient erythropoiesis due to genetic mutation that leads to reduction or absence of the hemoglobin beta-globulin protein. Approximately 8.5% of UAE residents suffer from β-thalassemia, a significant health and financial problem. The treatment options available for β-Thalassemia major are limited and associated with a wide range of complications. β-thalassemia gene therapy is emerging as a potential novel treatment option that eliminates the complications caused by the current long-term treatment modalities and the associated economic burden. This paper reviews the scientific literature related to emerging gene-therapy for β-Thalassemia by analyzing all the articles published from January 2010 to December 2023 in the English language on Databases like PubMed, Scopus, ProQuest, and CINAHL. The use of gene therapy has demonstrated promising outcomes for a permanent cure of β-Thalassemia. ZYNTEGLO (Betibeglogene autotemcel) is the only cell-based gene therapy which was approved by the FDA on 19th August, 2018. To conclude, Gene therapy is an innovative solution. It demonstrates a promising future, but does come with its own set-backs and is something that must be tackled in-order to revolutionize it in the medical world. FDA approved ZYNTEGLO is a potentially one-time curative treatment for β-Thalassemia. Although cutting-edge, its use is limited because of the high cost; a price of $2.8million per patient.

We report on the fabrication and electrical characteristics of zinc-oxide (ZnO) based metal-insulator-semiconductor (MIS) type Schottky barrier diodes (SBHs). ZnO thin layer on the p-type silicon substrate was fabricated by atomic layer deposition (ALD). The structure and surface properties of the thin film were characterized by X-ray diffraction (XRD), atomic force microscope (AFM) and secondary ion mass spectrometer (SIMS). The current-voltage (I-V) characteristics of Al/ALD-grown ZnO/p-Si diodes were measured under dark at room temperature. The electrical parameters such as ideality factor (n), series resistance (R_s) and barrier height (ϕ_b) of the diodes were analyzed using standard thermionic emission (TE) theory, Norde and Cheung method. The barrier height value obtained from I-V and Cheung method was found to be 0.73 eV and 0.76 eV, respectively. The interface state density (Dit) of the diodes was determined from the I-V characteristics. The nonideal behavior of measured parameters suggested the presence of interface states. The obtained results showed that the prepared diode can be used for NIR Schottky photodetector applications.

Neuro-rehabilitation services are essential in reducing post-stroke impairments, enhancing independence, and improving recovery in hospital and post-discharge. However these services are therapist-dependent and resource intensive. Patients’ disengagement and boredom in stroke units are common which adversely affect functional and psychological outcomes. Novel techniques such as use of iPads™ are increasingly researched to overcome such challenges. The aim of this review is to determine the feasibility, effectiveness, acceptability, and barriers to the use of iPads™ in stroke neuro-rehabilitation. Four databases and manual literature search were used to identify published studies using the terms “iPad”, “Stroke”, and “neuro-rehabilitation”. Studies were included in accordance with the review selection criteria. A total of 16 articles were included in the review. The majority of the studies focused on iPads use in speech and language therapy. Although of small scale, the studies highlighted that iPads are feasible, have the potential to improve rehabilitation outcomes, and can improve patient’s social isolation. Patients’ stroke severity and financial limitations are some of the barriers highlighted in this review. This review presents preliminary data supportive for the use of iPad technology in stroke neuro-rehabilitation. However, further research is needed to determine impact on rehabilitation goals acquisition, clinical efficacy, and cost-efficiency.

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

This paper focuses on studying the mapping properties of singular integral operators on product spaces. The boundedness of such operators is established on Triebel-Lizorkin spaces whenever their kernel functions belong to Grafakos and Stefanov class. Our results generalize and improve some previously known results.

The paper addresses the ongoing and continuous interest in photovoltaic energy systems (PESs). In this context, the study focuses on an isolated photovoltaic system with hybrid bat-tery-supercapacitor storage (HBSS). The integration of supercapacitors (SCs) in this system is of particular importance because of their high specific power density. In photovoltaic (PV) systems, multi-storage systems use two or more energy storage technologies to enhance system perfor-mance and flexibility. When batteries and supercapacitors are combined in a PV system, their benefits are maximized and offer a more reliable, efficient, and cost-effective energy storage op-tion. In addition, effective multi-storage power management in a PV system needs a solid grasp of the energy storage technologies, load power demand profiles, and the whole system architecture. In this work, battery-supercapacitor storage system (HBSS) is established by combining batteries and supercapacitors. The primary objective is to devise a novel management algorithm that ef-fectively controls the different power sources. The algorithm's purpose is to regulate the charge and discharge cycles of the HBSS, ensuring that the state of charge (SOC) of both batteries and supercapacitors remains within the desired range. The proposed management algorithm is de-signed to be simple, efficient, and light on computational resources. It efficiently handles the energy flow within the HBSS, optimizing the usage of both batteries and supercapacitors based on real-time conditions and energy demands. By maintaining the SOC of these energy storage components within the specified limits, the proposed method ensures their longevity and max-imizes their performance. Simulation results obtained from applying the management strategy are found to be satisfactory. These results show that the proposed algorithm maintains the SOC of batteries and supercapacitors within the desired range, leading to improved energy management and enhanced system efficiency.

Herbal Coffee is getting more popular due to its unique flavor and higher concentration of bioactive compounds, mainly polyphenols. Rosemary is a unique herb with potent antioxidant properties. A green technique called ultrasound aids in releasing bioactive substances from the plant cell wall. In this context, ultrasound-assisted herbal coffee prepared and their anti-diabetic, anti-Alzheimer, and antioxidant activities were measured while the LC/MS was used to determine the bioactive components from the herbal coffee infusion. A total of 95 secondary metabolites were putatively reported, including alkaloids, phenolic acids, and flavonoids, which we identified in the herbal coffee infusion. The total phenolic content (61.5 ± 5.1 mg GAE/g), total flavonoid content (19.3 ± 0.9 mg QE/g), and total condensed tannin (7.6 ± 0.7 mg CE/g) of herbal coffee infusion were observed to be highest of the two remaining samples. The herbal coffee extracts were used to determine all samples' antioxidant, anti-diabetic, and anti-Alzheimer activities. Using LC-MS/MS, we semi-quantified 19 phenolic metabolites. The results show numerous bioactive components in herbal coffee infusion with more potent antioxidant, antidiabetic, and anti-Alzheimer potential. Moreover, more studies must be conducted to confirm how the metabolomic profile of herbal coffee affects its flavor profile.

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

The primary purpose of this research article is to study the famous K$\ddot{o}$the's Conjecture for the special cases - when a ring $\mathfrak{R}$ is commutative, and when $\mathfrak{R}$ is an Algebra over a field. Furthermore, some open problems involving tensor product of Algebras over a field has also been discussed extensively along with their proofs. Subsequently, an equivelent statement of K$\ddot{o}$the's problem in terms of algebra of matrices has been established.

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

We know that the classical Mittag-Leffler function play an important role as solution of fractional order differential and integral equations. We introduce the j-generalized p - k Mittag-Leffler function. We evaluate the second order differential recurrence relation and four different integral representations and introduce a homogeneous linear differential equation whose one of the solution is the j-generalized p-k Mittag-Leffler function. Also we evaluate the certain relations that exist between j-generalized p - k Mittag-Leffler function and Riemann-Liouville fractional integrals and derivatives. We evaluate Mellin-Barnes integral representation of j-generalized p-k Mittag-Le er Function. The relationship of j-generalized p-k Mittag-Leffler Function with Fox H-Function and Wright hypergeometric function is also establish. we obtained its Euler transform, Laplace Transform and Mellin transform. Finally we derive some particular cases.

This paper explores the application of the generalized double reduction method to the (1+1)-dimensional Kaup-Boussinesq (K-B) system, which models nonlinear wave propagation. Double reduction method is a structured and systematic approach in the analysis of partial differential equations (PDEs). We first identify the Lie point symmetries of the K-B system and construct four non-trivial conservation laws using the multiplier method. The association between the Lie point symmetries and the conservation laws is established, and the generalized double reduction method is then applied to transform the B-K system into second-order differential equations or algebraic equations. The reduction process allowed us to derive two exact solutions for the K-B system, illustrating the method’s effectiveness in handling nonlinear systems. This work highlights the effectiveness of the generalized double reduction method in simplifying and solving nonlinear nonlinear systems of PDEs, contributing to a deeper understanding of the systems.

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

In this paper, several classes of rough Marcinkiewicz integral operators along surfaces of revolution on product spaces are investigated. We prove the Lp boundedness of these operators when their kernels functions belong to a class of functions related to a class of functions introduced by Grafakos-Stefanov. The results in this paper extend and improve several known results on Marcinkiewicz integrals.

Real time condition monitoring and precision health assessment system is a mandatory need for effective maintenance program in industrial sector. Rapid advancement in the information technology and other engineering technologies have invited more proactive attention from research and development in industrial sectors and particularly in condition monitoring of machines and related Industrial processes. In this work, drill bit condition monitoring techniques have been developed based on wavelet analysis and artificial neural networks (ANN) for automatic drill bit fault detection and classification. An experimental work has been conducted to capture the vibration signals for analysis. In this experiment, the CNC drill machine is used with high carbon steel drill bit and mild steel material as work piece. The cutting condition parameters are kept constant and the wear level is varied from 0.2 to 0.6 mm. The Data Acquisition system (DAQ) with Lab VIEW software is used to capture the vibration signals for drill bit with different wear conditions using accelerometer. The captured vibrations data are analyzed using continuous wavelet transform (CWT) with Morlet wavelet and Daubechies wavelet as a prime function. In general, the CWT coefficient is used to generate the inputs features to ANN for automatic tool condition classification, with two outputs (0, 1) for healthy and (1, 0) for faulty. The outcome of ANN showed 98% of accuracy in the wear prediction and this results show the effectiveness of the combed WT and ANN for automatic classification of tool wear conditions with high success rate.

Embracing Fourth Industrial Revolution(4IR) techniques is a need for a long-term sustainability and to do automation in the processes of Industrial and education sector. Rapid advancement in the information technology and other engineering technologies demand more proactive steps in the education institutes. In the post pandemic world, there is an increasing demand of changes in teaching and learning methodologies with the support of modern digital technologies. So, all of the teaching institutes need to have a significant step change in the areas of learning and teaching. The impact of 4 IR is more on the education sectors compared to previous generation’s industrial revolution. Keeping track of key technologies can be quite a challenge as they keep evolving at a very fast pace. Fourth Industrial revolution is the current technological digital revolution in which major focus is on cyber physical and biological systems such as Artificial Intelligence, Robotics, Internet on Things, Virtual Reality etc., The educators and institutions should establish the pedagogies and teaching with the aid of Industry 4.0 techniques to evolve education 4.0. So, it is very important to understand the challenges and competencies required about the implementation of 4IR by the faculty members and students who are currently studying in Higher Education Institutes (HEIs). This paper aim is to do a systematic review about industry 4.0 techniques and its application in relate to the online learning and teaching, change in pedagogies, enhancement of data management in HEIs, digital and virtual laboratories etc.