Patients with cancer experience insomnia or sleep disturbances. This study aimed to explore whether the discrepancy between a patient's desired time in bed and total sleep time (DBST) index is a measurement tool for insomnia severity or sleep onset latency [SOL] in patients with cancer. This retrospective medical records review study gathered clinical information and rating scale scores including Insomnia Severity Scale (ISI), Cancer-related Dysfunctional Beliefs about Sleep scale (C-DBS), Patient Health Questionnaire-9 items (PHQ-9), State subcategory of State and Trait Anxiety Inventory, and Short form of Fear of Progression Questionnaire. Sleep indices of time variables (bedtime, sleep onset time, and wake-up time), duration variables [SOL, time in bed (TIB), time in bed for 24 hours (TIB/d), and duration from wake-up time to bedtime (WTB)], and the DBST index were calculated. The ISI score was predicted by PHQ-9 (β=0.34, P<0.001), C-DBS (β=0.17, P=0.034), and DBST index (β=0.22, P=0.004) with a significant correlation with the DBST index (r=0.19, p=0.020). The DBST index was significantly correlated with long SOL (r=0.23, P=0.005). Long SOL was predicted by early bedtime (β=0.18, P=0.045), short WTB (β=-0.26, P=0.004), and high DBST index (β=0.19, P=0.013). The DBST index was significantly correlated with a predicting variable each for insomnia severity and SOL in patients with cancer.

Bonchev and Trinajstic defined two distance based entropy measures to measure the molecular branching of molecular graphs in 1977 [Information theory, distance matrix, and molecular branching, J. Chem. Phys., 38 (1977), 4517–4533]. In this paper we use these entropy measures which are based on distance matrices of graphs. The first one is based on distribution of distances in distance matrix and the second one is based on distribution of distances in upper triangular submatrix. We obtain the two entropy measures of paths, stars, complete graphs, cycles and complete bipartite graphs. Finally we obtain the minimal trees with respect to these entropy measures with fixed diameter.

MIGAL – Galilee Research Institute is a regional R&D center in the northeast peripheral region of Israel. An internationally recognized applied research institute, MIGAL specializes in biotechnology and computational sciences, plant sciences, precision agriculture and environmental sciences, as well as food, nutrition and health. Most of MIGAL’s researchers serve as the core faculty at Tel Hai Academic College (TH). Despite the country’s small surface area, socioeconomic inequality in Israel is high by OECD standards, with wage differences between rich and poor regions reaching up to 400%. The aims of this study are to identify possible socioeconomic impacts of MIGAL–TH on the peripheral northeast’s development. We discuss the effects of academic research and institutions of higher education on mitigating differences between the center and periphery of the country. Data for MIGAL, TH and the northeastern peripheral region were collected from the yearly reports of the two institutions and the Israel Central Bureau of Statistics. MIGAL was found to serve as a link between research, academic teaching and socioeconomic development in the northeast periphery. Several variables related to this link and describing MIGAL–TH and northeastern periphery development were analyzed over time: MIGAL’s budget, total number of employees and number of employees with PhDs; number of TH graduate students; socioeconomic index (SEI) of the northeastern periphery and its position on the Israeli list of regional SEIs. The signs and significance levels of their trends indicate a potential socioeconomic impact of academic research and higher education on peripheral development in the northeast of the country. Research budgets and the creation of jobs for academics living in the region are just a few examples of this impact.

The genetic development of commercial broiler led to body misconfiguration and consequent walking disabilities, mainly at the slaughter age. The present study aimed to identify broiler locomotion ability using image analysis automatically. A total of 40 broiler 40 d-old were placed to walk on a specially built runway, and their locomotion was recorded. An image segmentation algorithm was developed, and the coordinates of the bird's center of mass were extracted from the segmented images for each frame analyzed, and the Unrest Index (UI) was applied. We calculated the center of mass's movement of the broiler walking's lateral images, therefore, capturing the bird's displacement speed in the onward direction. Results indicated that broiler speed on the runway tends to decrease with the increase of the gait score. The locomotion did not differ between males or females. The proposed algorithm was efficient if predicting the broiler gait score based on their displacement speed.

Two well-known drawbacks in fuzzy clustering are the requirement of assign in advance the number of clusters and random initialization of cluster centers.; the quality of the final fuzzy clusters depends heavily on the initial choice of the number of clusters and the initialization of the clusters, then it is necessary to apply a validity index to measure the compactness and the separability of the final clusters and run the clustering algorithm several times. We propose a new fuzzy C-means algorithm in which a validity index based on the concepts of maximum fuzzy energy and minimum fuzzy entropy is applied to initialize the cluster centers and to find the optimal number of clusters and initial cluster centers in order to obtain a good clustering quality, without increasing time consumption. We test our algorithm on UCI machine learning classification datasets comparing the results with the ones obtained by using well-known validity indices and variations of FCM using optimization algorithms in the initialization phase. The comparison results show that our algorithm represents an optimal trade-off between the quality of clustering and the time consumption.

Online social networking techniques and large-scale multimedia retrieval are developing rapidly, which not only has brought great convenience to our daily life, but generated, collected, and stored large-scale multimedia data as well. This trend has put forward higher requirements and greater challenges on massive multimedia retrieval. In this paper, we investigate the problem of image similarity measurement, which is one of the key problems of multimedia retrieval. Firstly, the definition of similarity measurement of images and the related notions are proposed. Then, an efficient similarity measurement framework is proposed. Besides, we present a novel basic method of similarity measurement named SMIN. To improve the performance of similarity measurement, we carefully design a novel indexing structure called SMI Temp Index (SMII for short). Moreover, we establish an index of potential similar visual words off-line to solve to problem that the index cannot be reused. Experimental evaluations on two real image datasets demonstrate that the proposed approach outperforms state-of-the-arts.

The application of graph theory in chemical and molecular structure research far exceeds people's expectations, and it has recently grown exponentially. In the molecular graph, atoms are represented by vertices and bonded by edges. Closed forms of multiplicative degree-based topological indices which are numerical parameters of the structure and determine physico-chemical properties of the concerned molecular compound. In this article, we compute and analyze many multiplicative degree-based topological indices of silicon-carbon Si₂C₃-I[p,q] and Si₂C₃-II[p,q].

The objective of this study was to investigate the relationship between coffee consumption and obesity in Korean women. We included 5,995 women who participated in a health screening examination at the Korean National Cancer Center between 2007 and 2016. Daily coffee consumption was evaluated using the food frequency questionnaire. Obesity was assessed by body mass index (BMI), and abdominal obesity was assessed by waist circumference (WC). A multiple logistic regression model was used to calculate the odds ratio (OR) of obesity according to coffee consumption. After multivariate adjustment, high coffee consumption was positively associated with obesity measured by BMI (≥ 3 cups vs. no drinks, OR = 2.52; 95% confidence interval (CI) = 1.91-3.34; P for the trend < 0.001) and abdominal obesity measured by WC (≥ 3 cups vs. no drinks, OR = 2.11; 95% CI = 1.59-2.79; P for the trend < 0.001). The positive association between daily coffee consumption and obesity prevalence was not altered by menopause. The amount of coffee consumed per day by Korean women was positively correlated with the prevalence of obesity, but the mechanism underlying this phenomenon remains to be elucidated.

Deep eutectic solvents (DESs) are known as tunable solvents. It is possible to prepare ternary deep eutectic solvent (TDES) are used for desired purpose by selecting the suitable molar ratio and components of mixture. Therefore, four DESs and two TDESs were prepared in this work. DESs and TDESs were prepared with potassium carbonate (PC) as a hydrogen bond acceptor (HBA) and three hydrogen bond donors (HBDs) such as glycerol (GL), ethylene glycol (EG) and 2-amino-2methyl-1-3-propanediol (AMPD) known as a hindered amine (HA). Binary DESs were PC-GL with molar ratios 1:10 and 1:16 and PC-EG with the same molar ratios. TDES were prepared by adding AMPD in binary DESs such as PC-GL-AMPD 1:16:1 and PC-EG-AMPD 1:10:1. The experimental density and refractive index of all DESs and TDESs were measured at the temperature of 293.15 to 343.15 K with an interval of 5 K. The effect of temperature, molar ratio and alkyl chain length on the properties was investigated. The molar volumes and isobaric thermal expansion were calculated using experimental density data. The experimental refractive index data was used to derive the specific refraction, molar refraction, free molar volume, electronic polarization, polarizability constant and internal pressure at several temperatures.

M-polynomial of different molecular structures helps to calculate many topological indices. A topological index of graph G is a numerical parameter related to G which characterizes its molecular topology and is usually graph invariant. In the field of quantitative structure-activity (QSAR) quantitative structure-activity structure-property (QSPR) research, theoretical properties of the chemical compounds and their molecular topological indices such as the Zagreb indices, Randic index, Symmetric division index, Harmonic index, Inverse sum index, Augmented Zagreb index, multiple Zagreb indices etc. are correlated. In this report, we compute closed forms of M-polynomial, first Zagreb polynomial and second Zagreb polynomial of Octagonal network. From the M-polynomial we recover some degree-based topological indices for Octagonal network. Moreover, we give a graphical representation of our results.

Recent discovery of triangular boron Nanotubes makes it a competitor of carbon in many respects. Closed forms of M-polynomial of nanotubes produce closed forms of many degree-based topological indices which are numerical parameters of the structure and, in combination, determine properties of the concerned nanotubes. In this report, we give M-polynomials of triangular boron nanotubes and recover many important topological degree-based indices of these nanotubes. We also plot surfaces associated to these nanotubes.

This paper proposes an active-reactive power collaborative scheduling model with cluster division for the flexible distributed energy resources (DERs) of smart building system to resolve the high complexity of centralized optimal scheduling of massive dispersed DERs in the distribution network. Specifically, the optimization objective of each cluster is to minimize the operational cost, the power loss cost, and penalty cost for the flexibility deficiency, and the second-order cone-based branch flow method is utilized to convert the power flow equations into the linearized cone constraints, reducing the nonlinearity and heavy computation burden of the scheduling model. Customized virtual battery models for the building-integrated flexible DERs are developed to aggregate the power characteristics of flexible resources while quantifying their regulation capacities with time-shifting power and energy boundaries. Moreover, a cluster division algorithm considering the module degree index based on the electrical distance and flexible balance contribution index is formulated for cluster division to achieve the information exchange and energy interaction in the distribution network with high proportion of building-integrated flexible DERs. Comparative studies have demonstrated the superior performance of the proposed methodology on the economic merits and voltage regulation.

Lung transplantation offers patients with end stage lung disease an opportunity for a better quality of life, but with limited organ availability it is paramount that selected patients have the best opportunity for successful outcomes. Nutrition plays a central role in post-surgical outcomes and historically, body mass index (BMI) has been used as the de facto method of assessing a lung transplant candidate’s nutritional status. Here we review the historical origins of BMI in lung transplantation, summarize the current BMI literature, and review studies of alternative/complementary body composition assessment tools, including lean psoas area, creatinine-height index, leptin, and dual x-ray absorptometry. These body composition measures quantify lean body mass versus fat mass and may provide a more comprehensive analysis of a patient’s nutritional state than BMI alone.

In estimating the maximum and minimum index void ratios for mixtures of sand and silt, the values of several empirical constants must be determined based on the type of sand and silt involved. These empirical constants are the filling coefficient, a, and embedment coefficient, b, both of which can be determined either through lab testing or correlations. These constants are then used in equations to predict the maximum and minimum index void ratios of the sand-silt mixtures. The study reported here developed simple correlations for estimating the filling and embedment coefficients using readily obtained laboratory data. These models were found to be excellent in developing filling and embedment coefficients that accurately (R2 values typically of 0.94 or greater.) predicted values of the index void ratios for sand and silt mixtures.

The focus of recent research shifts towards complex ‘whole organism’ responses (i.e., in multiple functional traits) in adaptation to or to defend against stressors under complex environmental conditions. This increasing complexity is challenging to analyse and demands sophisticated tools to drive meaningful conclusions from those data. Trait-based regression models, multivariate analyses, like principal component analyses, and plasticity indices can be used to tackle challenges with those complex investigations. But those methods have substantial limitations, like the need for high sample size, multi-dimensionality of results or the need for trait coordination in high-dimensional space, or the calculation on the population level, which might buffer or cover the de facto occurring individual effects. To improve and simplify studies on ‘whole organism’ responses, analyses, and their interpretation, we developed the Index for Adaptive Responses. This straightforward framework can unite all traits of an organism in one number. A newly developed transformation method, included in this framework, comprises a normalisation and standardisation to a baseline or control without changing the data or variance structure of the original data. We assessed the performance and accuracy of the framework with an application in an extensive predator-prey case study, with simulations and application examples using literature data. We show that the Index for Adaptive Responses respects adaptations as well as maladaptations and outperforms established approaches. The framework is robust against outliers and non-gaussian distribution. We further show that the qualitative prediction of the adaptiveness of included traits is highly accurate, even under challenging conditions, e.g., low replicate numbers. Functions and algorithms of the framework are provided with an R package but can easily be translated into other programming languages. The Index for Adaptive Responses will simplify future research on complex adaptive responses and improves our understanding of these responses’ ecological as well as evolutionary implications.

Antimicrobial resistance (AMR) has been a serious threat to human health, and combination therapy is proved to be an economic and effective strategy to fight the resistance. However, the abuse of drug combinations would conversely accelerate the spread of AMR. In our previous work, it had been concluded that the mutant selection indexes (SIs) of one agent against a specific bacterial strain are closely related to the proportions of two agents in a drug combination. To discover probable correlations, predictors and laws for further proposing feasible principles and schemes guiding the AMR-preventing practice, here three aspects were further explored. First, the power function (y=ax^b, a > 0) correlation between the SI (y) of one agent and the ratio value (x) of two agents in a drug combination was further established based on the mathematical and statistical analyses for those experimental data, and two rules a₁ × MIC₁ = a₂ × MIC₂ and b₁ + b₂ = -1 were discovered from both equations of y=a₁x^b1 and y=a₂x^b2 respectively for two agents in drug combinations. Simultaneously, it was found that one agent with larger MPC alone for drug combinations show greater potency for narrowing itself MSW and preventing the resistance. Second, a new concept as mutation-preventing selection index (MPSI) was proposed and used for evaluating the mutation-preventing potency difference of two agents in drug combinations, and the positive correlation between the MPSI and the mutant prevention concentration (MPC) or minimal inhibitory concentration (MIC) was subsequently established. Inspired by this, the significantly positive correlation, contrary to previous reports, between the MIC and the corresponding MPC of antimicrobial agents against pathogenic bacteria was established using one hundred and eighty-one of data pairs reported. These results together of above three aspects indicate that the MPCs in alone and combination are very important indexes for drug combinations to predict the mutation-preventing effects and the trajectories of collateral sensitivity, and while the MPC of an agent can be roughly calculated from its corresponding MIC. Subsequently, the former conclusion was further verified and improved by the antibiotic exposure to forty-three groups designed as different drug concentrations and various proportions. The results further proposed that the C/MPC for the agent with larger proportion in drug combinations can be considered as a predictor and is the key to judge whether the resistance and the collateral sensitivity occur to two agents. Based on these above correlations, laws, and their verification experiments, some principles were proposed, and a diagram of the mutation-preventing effects and the resistant trajectories for drug combinations with different concentrations and ratios of two agents was presented. Simultaneously, the reciprocal of MPC alone (1/MPC), proposed as the stress factors of two agents in drug combinations, together with their SI in combination, is the key to predict the mutation-preventing potency and control the trajectories of collateral sensitivity. Finally, a preliminary scheme for antimicrobial combinations preventing the AMR was further proposed for subsequent improvement research and clinic popularization, based on the above analyses and discussion. Moreover, some similar conclusions were speculated for triple or multiple drug combinations.

The importance of this study may be defined by using the smart techniques to earned value indicators of residential buildings projects in Republic of Iraq, only one development intelligent forecasting model was presented to predict Schedule Performance Index (SPI), Cost Performance Index (CPI), and To Complete Cost Performance Indicator (TCPI) are defined as the dependent. The approach is principally influenced by the determining numerous factors which effect on the earned value management, that involves Iraqi historical data. In addition, six independent variables (F1: BAC, Budget at Completion., F2: AC, Actual Cost., F3, A%, Actual Percentage., F4: EV, Earned Value. F5: P%, Planning Percentage., and F6: PV, Planning Value) were arbitrarily designated and satisfactorily described for per construction project. It was found that ANN has the capability to envisage the dust storm with a great accuracy. The correlation coefficient (R) has been 90.00%, and typical accuracy percentage has been 89.00%.

In this study, we present comprehensive climatologies of effective ultraviolet (UV) quantities and photosynthetically active radiation (PAR) over Cyprus for the period 2004 to 2023, leveraging the synergy of earth observation (EO) data and radiative transfer model simulations. The EO dataset, encompassing satellite and re-analysis data for aerosols, total ozone column, and water vapor, alongside cloud modification factors, to capture the nuanced dynamics of Cyprus's atmospheric conditions. With a temporal resolution of 15 minutes and a spatial of 0.05°x0.05°, these climatologies undergo rigorous validation against established satellite datasets and are further evaluated through comparisons with ground-based global horizontal irradiance measurements provided by the Meteorological Office of Cyprus. This dual-method validation approach not only underscores the models' accuracy but also highlights their proficiency in capturing intra-daily cloud coverage variations. Our analysis extends to investigating the long-term trends of these solar radiation quantities, examining their interplay with changes in cloud attenuation, aerosol optical depth (AOD), and total ozone column (TOC). Significant decreasing trends in the noon ultraviolet index (UVI), of -2 to -4% per decade have been found in Autumn, especially marked on the island’s Northeastern part, mainly originating from the (significant) positive trends in TOC. The significant decreasing trends in TOC, of -2 to -3% per decade that were found in Spring do not result in correspondingly significant positive trends in the noon UVI since variations in cloudiness and aerosols also have a strong impact on the UVI in this season. The seasonal trends in the Daylight Integral (DLI) were generally not significant. These insights provide a valuable foundation for further studies aimed at developing public health strategies and enhancing agricultural productivity, highlighting the critical importance of accurate and high-resolution climatological data.

Taiwan’s auditors have suffered from processing excessive audit data, including drawing audit evidence. This study advances sampling techniques by integrating machine learning with sampling. This machine learning integration helps avoid sampling bias, keep randomness and variability, and target the risker samples. We first apply a Naive Bayes classifier to classify data into some classes. Next, a user-based, item-based, or hybrid approach is employed to draw audit evidence. The representativeness index is the primary metric for measuring the representativeness of audit evidence. The user-based approach denotes the selection of samples between two percentiles in a class as audit evidence. It may be equivalent to a combination of monetary and variable sampling methods. The item-based approach represents the choice of risky samples as audit evidence. It may be identical to a combination of non-statistical and monetary sampling methods. Auditors can hybridize those user-based and item-based approaches to balance representativeness and riskiness in selecting audit evidence. Three experiments show that sampling using machine learning integration has the benefits of drawing unbiased samples, handling complex patterns, correlations, and unstructured data, and improving efficiency in sampling big data. However, the limitations are the classification accuracy output by machine learning algorithms and the range of prior probabilities.

Information is uploaded and downloaded through the Internet day in and day out ever since we immersed ourselves in the Internet. Data security becomes an area demanding high attention and one of the efficient techniques to protect data is data hiding. Among various data hiding schemes, more applications prefer the schemes with reversibility. In recent reversible data hiding studies, the indices of a codebook can be reordered to hide secret bits. The hiding capacity of the codeword index reordering scheme increases when the size of the codebook gets larger. Since the codewords in the codebook are not modified, the visual performance of compressed images is retained. We propose a novel scheme making use of the fundamental principle of codeword index reordering technique to hide secret data in encrypted images. By observing our experimental results, the embedding capacity is significantly larger. Secret data can be extracted when a receiver owns a data hiding key and image can be recovered when a receiver owns an encryption key.

Peach (L.) is a kind of fruit tree with considerable economic and nutritional significance. However, it shows a high sensitivity to drought stress, which has a profound impact on its growth. L-methionine (MET) and L-proline (PRO) are two amino acids synthesized by plants, which play an important role in abiotic stress response. However, their exact mechanism of action remains elusive. Through physiological analysis, MET (500ppm) and PRO (500ppm) treatments can effectively reduce the adverse effects of drought stress on the growth of peach seedlings. The results show that MET and PRO can effectively inhibit the stomatal opening of plant leaves under drought conditions and reduce the water evaporation of leaves under drought conditions. In addition, the application of MET or PRO promoted the accumulation of carbohydrates in the leaf tissues of peach seedlings under drought conditions, increased the intracellular relative water content (24%, 24%), decreased the leaf electrical conductivity (21%, 24%), and alleviated the membrane damage caused by drought. Experimental studies have confirmed that the alleviation of drought stress is due to the removal of reactive oxygen species (ROS) in vivo, that is, the downregulation of malondialdehyde (18%, 19%)，peroxidase (50%, 5%) and superoxide dismutase (12%, 14%) activities. In addition, the application of exogenous amino acids also improved the root morphological structure and root vitality of peach seedlings，which was conducive to absorbing external buffer substances and alleviating drought stress. In summary, the application of exogenous amino acids can effectively alleviate the effects of drought stress on plants and reduce the harm.

Studies suggest that chronic psychological stress can lead to oral health deterioration, alter the immune response, and possibly contribute to increased inflammation, which can impact the physiological healing of periodontal tissues. This cross-sectional study seeks to assess and improve clinical understanding regarding the relationship between perceived stress, mindfulness, and periodontal health. A total of 203 people were analysed from December 2022 to June 2023. The Periodontal Screening and Recording (PSR), score and Bleeding Index (GBI), and Plaque Control Record (PCR) of every patient were registered. Subsequently, participants completed the Sheldon Cohen Perceived Stress Scale (PSS) and the Mind-fulness Awareness Attention Scale (MAAS) questionnaires. The collected data was analysed statistically, and correlations and dependencies were evaluated. The p-value was 0.004265 in Welch's t-test to assess the relationship between MAAS and the variable's presence or absence of periodontitis, highlighting that patients with periodontitis have significantly different MAAS scores compared to patients unaffected by periodontitis. The Pearson correlations between GBI and perceived stress, PCR and perceived stress, and PCR and MAAS resulted in p-values of 2.2-16, 3.925-8, and 2.468-8, respectively, indicating a statistically significant correlation in this case. Despite the limitations, the findings of this study suggest a significant relationship between psychological stress, mindfulness and periodontal tissue health. Clinical trials are necessary to incorporate the assessment of a patient’s psychological status as a new valuable tool in the management of periodontal health.

Suboptimal micronutrient intake in children remains a public health concern around the world. This study examined the relationship between a previously defined dietary carbohydrate quality index (CQI) and the risk of micronutrient intake inadequacy in a pediatric cohort of Spanish preschoolers. Children aged 4-5 years old were recruited at their medical center or at school, and information on sociodemographic, dietary, and life-style variables were collected through a self-administered online questionnaire. Dietary information was obtained from a validated 147-item semi-quantitative food frequency questionnaire. We calculated the CQI and categorized participants in quartiles according to their score. We assessed the intakes of 20 micronutrients and evaluated the probability of intake inadequacy using the Estimated Average Requirement cut-off point. Generalized estimating equations were used to adjust for potential confounders and account for the intra-cluster correlations between siblings. The adjusted proportions of children with inadequate intake of ≥3 micronutrients were 23%, 12%, 11% and 9% in the first, second, third and fourth quartiles of the CQI, respectively. Children in the highest quartile of CQI had 0.22-fold lower odds (95%CI 0.10-0.48) of having ≥3 inadequate micronutrient intakes than their peers in the lowest quartile. These findings reinforce the relevance of carbohydrate quality in children’s diets.

The Dst index is the geomagnetic storm index used to measure the energy level of geomagnetic storms, and the prediction of this index is of great significance for the geomagnetic storm study and the solar activity. In contrast to traditional numerical modelling techniques, machine learning, which has emerged in decades ago based on rapidly developing computer hardware and software and artificial intelligence methods, has been unprecedentedly developed in geophysics, especially solar-terrestrial space physics. This study chooses two machine learning models, the LSTM (Long-Short Time Memory, LSTM) and EMD-LSTM model (Empirical Mode Decomposition, EMD), to model and predict the Dst index. By building the Dst index data series from 2018-2023, two models were built to fit and predict the data. Firstly, we evaluated the influences of the learning rate and the amount of training data on the prediction accuracy of the LSTM model, and finally, 10-3 was thought as the optimal learning rate; secondly, the two models were used to predict the Dst index in the solar active and quiet periods, respectively, and the RMSE (Root Mean Square Error) of the LSTM model in the active period is 7.34 nT, the CC (correlation coefficient) is 0.96, those of the quiet period are 2.64nT and 0.97; the RMSE and r of EMD-LSTM model are 8.87nT and 0.93 in active time and 3.29nT and 0.95 in the quiet time. Finally, the prediction accuracy of the LSTM model in short time period is slightly better than the EMD-LSTM model. However, there will be a problem of prediction lag, which the EMD-LSTM model can then solve, and can better predict the geomagnetic storm.

Estuaries are excellent environments of identifying pollution episodes that have affected river basins, as their sediments are the final destination of some of the pollutants. This paper studies the geochemical evolution of five elements (As, Co, Cu, Pb, Zn) in a core extracted from the middle estuary of the Tinto River (SW Spain). Results are based on facies interpretation, ICP Atomic Emission Spectrometry analysis, the application of a regional background to obtain the geoaccumulation index and dating. Four pollution episodes have been detected at ~5.8 cal. kyr BP (acid mine drainage?), 4.7-4.5 kyr BP (first mining activities), the 1850-1960 interval (intensive mining) and the second half of the 20th century (intensive mining and industrial inputs). All episodes show an increase in one or more of these elements, as well as changes in their geochemical classes deduced from the geoaccumulation index.

To supply stable and high-quality power according to the advancement of industrial growth, electric power companies have performed maintenance of power facilities using various meth-ods. In the case of domestic power distribution facilities, there are limitations in performing di-agnostic management on all facilities owing to the large number of facilities; therefore, old fa-cilities are managed by the health index assessment method. The health index assessment com-prises only facility operation data and external environmental data and is managed only for four types of distribution facilities, including overhead/underground transformers and switchgear. In the case of extra high–voltage overhead wires, there is no standard for old replacement, despite the large number of wires, such as transformers and switchgear, and the large ripple effect of power failure in the event of a power outage. Therefore, in this paper, a health index assessment methodology for extra-high voltage overhead cables was developed. In this paper, we devel-oped an economic health index assessment methodology that additionally considers risk cost, which is different from the existing health index assessment method that uses only operational data and external environmental data to determine facility performance evaluation and aging replacement criteria. Using the health index assessment methodology developed in this paper, it is possible to expect a reduction in facility operating costs and investment costs from the per-spective of electric power companies through the replacement of old extra-high voltage over-head cables. In addition, from the perspective of consumers, it is expected to increase power re-liability and reduce the ripple effect of failure by preferentially replacing equipment with a high probability of failure.

This work introduces an approach to investigate the existence of zeros for holomorphic complex functions, defined on open and simply connected subdomains of C, in a systematic and direct way. This is achieved by means of the theory of dynamical systems (Poincar\'e index) and the perception that a zero of a specific complex function is an equilibtium for the associated dynamical system. The logical basis of proof is to find the mathematical expression for the Poincaré index of the vector field associated to the function under study, assuming the existence of a zero, and investigating the consequences. Depending on the value of the index, an inconsistency may occur, establishing a contradiction.

Antioxidants reduce arterial stiffness but the effects previously reported are weak. The present study evaluated the effects of 2 weeks of therapy with a combination of antioxidants (l-cysteine, thiamine, pyridoxine and ascorbic acid) compared to placebo on stiffness index (SI) a measure of arterial stiffness that is strongly correlated with central pulse wave velocity (PWV), using a Pulse Trace recorder in a diverse group of 78 volunteers. SI fell by 1.7 m/sec relative to placebo (95% confidence intervals 0.6 to 2.7 m/sec), a reduction of 19% (95% confidence intervals 9% to 31%). The Glass effect size was 1.4, indicating a very strong treatment effect which was substantially greater than found in previous studies of the effects of antioxidant therapy on arterial stiffness. The magnitude of reduction in SI was positively correlated with increasing age (r = 0.362 P = 0.02). The change in RI, a measure of compliance of small to medium size arteries, did not differ between the antioxidant and placebo groups The combination of antioxidants studied reduced PWV to a much greater extent than reported for other antioxidants. This combination may be of value in the treatment of cardiovascular disease.

The Harmonic Graphs Conjecture states that there exists an asymptotic relation involving the Harmonic Index and the natural logarithm as the order of the graph increases. This conjecture, grounded in the novel context of Prime Graphs, draws upon the Prime Number Theorem and the sum of divisors function to unveil a compelling asymptotic connection. By carefully expanding the definitions of the harmonic index and the sum of divisors function, and leveraging the prime number theorem's approximations, we establish a formula that captures this intricate relationship. This work is an effort to contribute to the advancement of graph theory, introducing a fresh lens through which graph connectivity can be explored. The synthesis of prime numbers and graph properties not only deepens our understanding of structural complexity but also paves the way for innovative research directions.

The objective of this study was to evaluate the glycemic index and the satiety response of three Mexican kinds of honey. The values of fructose ranged from 272.40-395.10 g/kg, while the glucose value ringed 232.20-355.50 g/kg. The ratio F/G of sample honey was 1.45, 1.00, and 1.17 for Highland, Multifloral, and Avocado honey, respectively. Twenty-six participants completed this study, which was previously approved by the ethics committee of the Facultad de Salud Pública y Nutrición (CE 2/2018-19). Highland and Avocado honey is classified as medium-GI (69.204.07 and 66.365.74, respectively), while Multifloral honey is classified as high-GI (74.245.98). The Highland honey presented the best satiety response. The difference in IG values and the effect of the satiety response of Highland honey could be explained by the different fractions of carbohydrates in samples and other components such as phytochemicals.

BACKGROUND: It has been known for decades that breastfeeding leads to a lower risk of asthma, respiratory infections, or metabolic syndrome at school age. In addition, evidence is now accumulating on the influence of breast milk on the shape, volume, or function of the heart and lungs. Within this field of research into the effects of breast milk on the structure of the heart and lungs, we have set out to analyze the differential electrocardiographic characteristics of schoolchildren who were once breastfed. METHOD: Observational cross-sectional study including 138 children aged 6 or 12 consecutively presenting to a well-child clinic between May and December 2022. Inclusion criteria: the ability to perform reproducible ECG records, the feasibility of weighing and measuring patient, and breastfeeding data collected from birth. RESULTS: Using the 40º cut-off value for the mean P-wave axis among schoolchildren, 76% of never breastfed children in our sample have a P-wave axis in a more vertical position than the mean as compared to 58% of ever-breastfed children (OR:2.25;95%CI:3.13-1.36); there was no other significant difference between infant feeding groups in somatometric characteristics or ECG parameters, CONCLUSION: We found a significant difference of the mean values of the P-wave axis between never and ever breastfed children. Although this report should be approached cautiously, these findings add to the renewed interest in discerning developmental interventions to improve cardiovascular health.

Climate change (CC) poses severe consequences, particularly in sub-Saharan Africa, where poverty rates may escalate by 2050 without significant climate and development action. The health impacts are diverse, encompassing communicable and non-communicable diseases. Mozambique, a climate-vulnerable nation, has experienced significant natural disasters in the past 42 years, impacting its health system. This study aims to assess Mozambique’s health sector vulnerability and adaptation needs to climate change. Following a methodology proposed by the World Health Organization and Intergovernmental Panel for Climate Change, a six-step vulnerability and adaptation assessment was conducted. The Health Vulnerability Index (HVI), integrating historical climate, epidemiological, and socio-economic data at the district level (n=162), was computed using exposure, sensitivity, and adaptive capacity dimensions. The Results revealed spatial patterns in exposure to climate variables, extreme weather events, and variations in sensitivity and adaptive capacity across the country. The HVI mirrored the exposure findings. Notably, high vulnerability was observed in several districts, while major urban centers displayed lower vulnerability. These findings highlight the country’s vulnerability to climate change and underscore the potential for adverse impacts on livelihoods, the economy, and human health. The study provides a foundation for developing strategies and adaptation actions.

Hessenberg differential algebraic equations (Hessenberg-DAEs) with high index play a critical role in the modeling of mechanical systems and multibody dynamics. Motivated by the widely used Lie Group Differential Algebraic Equation (LGDAE) method which only handles index 2 systems, we propose a Modified Extended Lie Group Differential Algebraic Equation (MELGDAE) method for solving index 3 Hessenberg-DAEs, and provide theoretical analysis to deepen the foundation of the MELGDAE method.The performance of the MELGDAE method is compared with the standard methods RADAU and MEBDF on index 2 and 3 DAE systems, and it is demonstrated that the MELGDAE integrator exhibits competitive performance in terms of high accuracy and the preservation of algebraic constraints. In particular, all differential variables in index 3 Hessenberg DAEs achieve second-order convergence using the MELGDAE method, which suggests potential for extension to Hessenberg-DAEs with an index of 4 or higher.

This paper outlines the detection procedure of intrusion as provided by Tripwire tool along-with the enhancement to be made in design and implementation to achieve the optimum performance level of Tripwire. It operates on effective and swift performance mechanism in order to report the system admin about the possible intrusion detected in the system with security assurance in cutting edge computer structures, which is very important in order to provide the integrity and reliability of information. In order to deal with this emerging issue in the historical research, the basic level of security is provided in the system by making enhancement in the existing tripwire tool for UNIX file system. The proposed methodological working of tripwire makes it more effective by adopting reliable and instantaneous mechanism to deal with specifically anomalies and unwanted access in the UNIX file system.

The bond index is an indicator of the grindability of the material and is widely used in the preparation of mineral raw materials and the cement industry. Paper offers new, abbreviated and simplified procedure to determine Bond work index that relies on first-order kinetics law and can be performed with any number of grinding cycles, depending on the desired accuracy of the required data. The parameters G and P80 of each grinding cycle are multiplied by the newly founded coefficients giDT and piDT to obtain values approximately equal to these parameters of the last grinding cycle when the equilibrium state is reached in the standard test. The paper presents comparative results obtained by standard Bond and new shortened procedure on individual samples of andesite, limestone, copper-ore and smelter slag and on composite samples of andesite from limestone and copper-ore with smelter slag in different mass ratios. As the number of grinding cycles increases, the precision of the shortened procedure increases, and the mean square error decrease 3.59%, 2.61% and 1.74% for two, three and four grinding cycles.

Reptile behaviour and welfare are understudied in comparison with mammals. In this study, behavioural data on three species of tortoises were recorded before and after an environmental change which was anticipated to be positive in nature. The environmental changes differed for each population, but included a substantial increase in enclosure size, the addition of substrate material, and a change in handling procedure. A tortoise-specific ethogram was created to standardise data collection. Focal behaviour sampling was used to collect behavioural data. Changes in the duration of performance of co-occupant interaction and object interaction in the leopard (Stigmochelys pardalis) and Aldabra (Aldabrachelys gigantea) tortoises were observed following the environmental changes. The Shannon-Weiner’s diversity index did not yield a significant increase after the changes but had a numerical increase which was relatively greater for the leopard tortoise group, which had experienced the greatest environmental change. The leopard tortoises also demonstrated changes in a greater number of behaviours compared to the other species, and this was sustained over the study period. However, this included a behaviour indicative of negative affect; aggression. Whilst we are unable to conclude that welfare was improved by the management changes, there are suggestions that behavioural diversity increased, and some promotion of positive social behaviours occurred.

In geotechnical engineering applications, it is very important to obtain the undrained shear strength of remolded soils accurately and reliably. This study aims to obtain a trustworthy solution to determine the undrained shear strength of remolded clay mixtures using Atterberg limit test results in various states of consistency. An experimental study was carried out involving a wide range of clay mixtures of varying plasticity and geological origin. In the analyses, the variation of the remolded undrained shear strength depending on the cone penetration depth, water content, flow index, liquidity index and log liquidity index were investigated. In the study, the highest undrained shear strength of 100% Na-montmorillonite (NaM) was obtained at 171.89 kPa at 56.60% water content, while the lowest undrained shear strength was obtained for 100% Sepiolite (S), 9.28 kPa at 31.65% water content. The results of this study revealed that the shear strength is significantly affected by soil conditions, rather than dominant clay mineral. Besides, it was observed that the undrained shear strength at the plastic limit was approximately 30-35 times greater than that at liquid limit. The equations of liquid limit-flow index and plasticity index- flow index were proposed. It was concluded that the interdependence between undrained shear strength, liquidity index, log liquidity index, and flow index is not unique due to the different physical and chemical properties of clays.

A field experiment was conducted at farmer field of Sundarbazar, Lamjung during rainy season of 2020 with an objective to determine the dynamics of weed with respect different planting methods and varieties. The experiment was laid out in split plot design with three replications where five Varieties (KabreKodo 1, KabreKodo 2, Dalle 1, Okhale 1 and local) were used as the main plot factor and three planting methods (Direct sowing;10*10cm, Conventional transplanting;10*10 cm with 15 days old seedlings and System of Crop Intensification;25*25 cm with 30 days old seedlings) as sub plot factor. Result showed that among 5 genotypes of weeds based on Importance value index, Cyperusrotundus was the most dominant during the initial stage but after the first weeding, Aegeratumhaustinianum dominated the field. Weed biomass and density was recorded highest in directly sown field than that in transplanted field. Among the transplanted crop, weed infestation was seen higher in SCI than in conventionally transplanted finger millet due to wider spacing. But after the first hand weeding, due to profuse root growth and tillering in SCI, weeds were suppressed and thus weed biomass was observed higher in CT. After one hand weeding, SCI showed higher weed control index, crop resistance index and planting method efficiency index in terms of yield. Weed infestation was observed higher in Dalle 1 among varieties.

Overweight/obesity is one of the most important health problem worldwide. Birth by cesarean section has been shown to influence long-term health outcome including obesity. The aim of this systematic review-meta-analysis is to examine whether cesarean section increases the risk of offspring’ s overweight/obesity. The study follows the PRISMA and MOOSE guidelines. A systematic literature search was con-ducted on Scopus, PubMed, and WoS until December 2020. For inclusion, studies must have re-ported either (I) both Birth by cesarean section and adult (≥ 18 years) offspring BMI, (II) cohort or case–control study design and (III) a risk estimate. Heterogeneity testing was performed using Cochran's Q and I2 statistics. Publication bias was assessed by Egger’s test and Begg’s test. Me-ta-analysis was performed through a random effect model. Eleven studies with a combined population of 180.408 subjects were included in the meta-analysis. The overall analysis (n = 18) yielded a combined risk estimate for overweight/obesity of 1.19 (95% CI 1.08-1.31) and the test of heterogeneity resulted Q=53,37 (I2 = 70,37 %, P≤0•0001). The risk of offspring obesity is 1.23 (95% CI 1.09-1.39) and the test of heterogeneity resulted Q=39.50 (I2= 72,15%, P≤0•0001). Children born by cesarean section have an increased risk of developing obesity in adulthood

Pollination is the process by which pollen grains are exchanged in plant flowers to allow for fertilisation and production to take place. However, challenges occur when crops are grown under protected structures where there are minimal activities of natural pollination agents such as wind and animals which are responsible for transferring pollen grains from the anther to the stigma. Therefore, the study objective was to determine the effect on hand pollination on the yield of African horned cucumber grown under greenhouse and shade net environment. A factorial experiment with two factors (hand pollinated and non-hand pollinated/control) was conducted under two different growing environments (greenhouse and shade net). African horned cucumber plants were hand self-pollinated in the morning. Pollen were manually transferred with a hand using the new earbud from the male to the female flowers on the same plant (selfing). Results showed that hand pollinated African horned cucumber plants increased total biomass from 0.93 to 2.23 kg under greenhouse environment. Hand pollinated plants increased harvest index from 0.07 to 0.35 under shade net environment. It can thus, be deduced that hand pollination increases African horned cucumber yield in the greenhouse and shade net environments.

This paper mainly focuses on the construction of a household welfare index to examine the welfare impact of international remittances in rural Bangladesh. This paper, in achieving this objective, uses primary data and several methods. This paper constructs a household welfare index newly to measure the level of household welfare. Besides, a linear regression and Chi-square test is used to examine the welfare and poverty impact of international remittances, respectively. Remittance receiving households enjoy the higher level of welfare more than non-recipient households in the study area. Household welfare is augmented by 0.116 if the household is under the shade of international remittances. A significant impact of international remittances on the reduction of household poverty is also found in this study. Therefore, this paper suggests policymakers for utilizing international remittances as a significant tool to enhance household welfare and to reduce household poverty.

Background: Overweight and obesity are becoming serious public health menace in the world today. Weight gain is skyrocketing across the globe due to growing economy, fast food expansion and a shift towards more sedentary living. However, most people lack knowledge regarding risks associated with overweight and obesity. Aim: The study aimed to explore the knowledge level of bankers in the Ho Municipality on the health risks associated with overweight and obesity. Methodology: A cross-sectional study design with quantitative method was employed. The study spanned from September 7, 2018 to April 25, 2019. A self-administered questionnaire and convenience sampling technique were used to obtain data. Data were analysed using IBM SPSS Statistics 21 Developer and the results presented in statistical tables and graphs. Results: Of 136 participants investigated, 67 (49.3%) were between 31 - 40 years. 2 participants (1.5%) were underweight, 49(36.0%) had normal weight, 43(31.6%) were overweight while 42 (30.9%) were obese. The study revealed that female bankers were prone to overweight (37.78%) while the males were prone to obesity (56.52%). Participants generally had low knowledge and awareness on health risks of overweight and obesity. Conclusion: Most bankers in the Ho Municipality were overweight and obese due to insufficient knowledge and low awareness on the risks associated with overweight and obesity. Public education and awareness creation are urgently needed to stem the tide.

The present study is aimed at designing anti-reflective (AR) engraving on the Input-Output surfaces of a rectangular light-guide. We estimate AR efficiency, by the transmittance level in the angular range, determined by the light-guide. Using nano-engraving, we achieve a uniform high transmission over a wide range of wavelengths. In the past, we used smoothed conical pins or indentations on the faces of light-guide crystal as the engraved structure. Here, we widen the class of pins under consideration, following the physical model developed in the previous paper. We analyze the smoothed pyramidal pins with different base shapes. The possible effect of randomization of the pins parameters is also examined. The results obtained demonstrate optimized engraved structure with parameters depending on the required spectral range and facet format. The predicted level of transmittance is close to 99\%, and its flatness (estimated by the standard deviation) in the required wavelength range is 0.2\%. The theoretical analysis and numerical calculations indicate that the obtained results demonstrate the best transmission (reflection) we can expect for a facet with the given shape and size for the required spectral band. The approach is equally useful for any other form and of the facet. We also discuss a simple way of comparing experimental and theoretical results for a light-guide with the designed input and output features. In this study, as well as in our previous work, we restrict ourselves to rectangular facets. We also consider the limitations on maximal transmission produced by the size and shape of the light-guide facets. The theoretical analysis is performed for an infinite structure and serves as an upper bound on the transmittance for smaller-size apertures.

A new generation of universal tools and languages for modeling and simulation multi-physical domain applications emerged and became widely accepted, which generate large-scale systems of differential algebraic equations (DAEs) automatically. Motivated by the characteristics of DAEs systems with large dimension, high index or block structures, we first propose a modified Pantelides’ algorithm (MPA) for any high order DAEs based on its Σ matrix, which is similar to Pryce’s Σ method. By introducing a vital parameter vector, a modified Pantelides’ algorithm with parameter has been presented.It leads to a block Pantelides’ algorithm (BPA) naturally which can immediately compute the crucial canonical offsets for whole (coupled) systems with block-triangular form. We illustrate these algorithms by some examples. And numerical experiments show that the time complexity of BPA can be reduced by at least O(ℓ) compared to the MPA, which is mainly consistent with the results of our analysis.

Image fusion is a useful tool for producing a high-resolution multispectral image to be used for land use and land cover mapping. In this study, we use nine pansharpening algorithms namely Color Normalized (CN), Gram-Schmidt (GS), Hyperspherical Color Space (HCS), High Pass Filter (HPF), Nearest-Neighbor Diffusion (NND), Principal Component Analysis (PCA), Resolution Merge (RM), Stationary Wavelet Transform (SWT), and Wavelet Resolution Merge (WRM) to fusion Worldview-3 multispectral Bands and panchromatic band. In spectral and spatial fidelity, several image quality metrics are used to evaluate the performance of pansharpening algorithms. The SWT and PCA algorithms showed better results compared to other pansharpening algorithms while GS and CN algorithms showed the worst results for the original image fusion. The effect of fusion on each band was separately investigated and according to the calculations, we found that the CoastalBlue band and the Blue band showed the best result and the NIR-1 band and NIR-2 band show the worst result for the original image fusion. In the end, we conclude that the choice of fusion method depends on the requirement of remote sensing application.

We review extrapolation methods for calculation of critical points and indices from the perturbative expansions by means of Pad\'{e}-based techniques and their various post-Pad\'{e} extensions by means of root and factor approximants. Factor approximants are applied to finding critical points. Roots are employed within the context of finding critical index. Additive self-similar approximants are discussed and $DLog$ additive recursive approximants are introduced as their generalization. They are applied to the problem of interpolation.

Studies on the gait's parameters have been identified on the patients population. Most researchers confirm that the patients walk differently than normal people and they may have a risk for falls. Consistent finding and description of gender, age, and body mass index differences in gait studies is rare in healthy subjects. A cross-sectional study with forty-five young adult (F = 20, M = 25) was conducted. Stadiometer and Physilog 4 inertial sensors were used for data collection. A gait analyser 5.2 software (GaitUp, S.A. Lausanne, Switzerland) was used to determine spatiotemporal parameters. No statistically significant differences were found in any bilateral foot gait parameters with respect to gender, age, and body mass index. Females are found with higher total double support and cadence than males. Cadence also increases with age. Obese people showed lower gait speed, cadence, and total double support. These findings may be beneficial to those who have abnormal gait pattern due to age, body mass index differences, decreased muscle strength, spasticity, and joint mobility. This important informations should be considered to rehabilitate patients with abnormal gait patterns to controlling dynamic balance and riks to falling.

This study used the National Demographic and Health Survey 2013 data to provide empirical answer the question of the relevance of western education in Nigeria relative to ethnic-regional practices of almajiri in the light of women’s educational attainment and wealth index in Nigeria. Women are the most vulnerable in the cultural practices in Nigeria as women’s education in Sub-Saharan Africa is far below the world average. Nigeria was recently proclaimed the world capital of poverty because it is among one of the countries with the highest number of people living below poverty line in the world with a larger proportion of poor being women. Ordinary Least Square (OLS) and Ordered Probit Model were employed to analyse the data. The results revealed a significant effect of western education on women asset accumulation and the precaurious position of women resulting from lack of western education. This implies that higher attainment of western education increases the likelihood of being wealthy. The counterfactual effect of ethnic-regional practices of almajiri confirmed the disadvantage and backwardness of women staying in the region or coming from the ethnicity. This partly explains the likelihood of the differences in the level of development across the geopolitical zones and women welfare. Based on the findings the study recommends that policy maker should provide easy access to quality education, especially at both pre-primary and primary levels for all especially women. Also issues of graduate unemployment should be addressed as it reduces return from education.

Achieving devices to be transparent is the task considered in the last time in many aspects and for different purposes. One issue of these problems is making anti-reflective surfaces in a wide wavelength range and keeping it flat enough. The authors of the previous publication showed that one could enhance a flat facet's transmission efficiency by suitable engraving. They used smoothed conical fingers and holes. Here, we widen the class of anti-reflective metasurfaces under consideration, following the requirements of the model developed in the previous paper. We involve also smoothed pyramidal fingers. The obtained results provide the improved engraved structure, with parameters dependent on the required spectral range, and the facet format. The predicted level of transmittance is close to 99\%, and the flatness(estimated by the standard deviation) as 0.2\%. This improvement is significant enough for high and broadband transmittance. In this work, we show that the randomization of the engraving parameters does not provide any significant effect for small facets. We also discuss a simple way of comparing experimental and theoretical results for a waveguide with the considered input and output features. In this study, as well as in our previous work, we restrict ourselves by rectangular facets. We also discuss the limitations that originated from the size and shape of the waveguide facets.

The classic Body Mass Index, (BMI), developed in the 19^th century by the Belgian mathematician Adolphe Quetelet [1] is an important indicator of the risk of death, of obesity, of negative health consequences, body fat percentage and of the shape of the body. While he BMI is assumed to indicate obesity in sedentary people and in people who do not practice sports, it is undisputed and a consensus among researchers [2][3][4][5][9][25] that Body Mass Index (BMI) is not a good indicator for obesity in people who developed their body through heavy physical work or sport but also in other segments of population such as those who appear to have a normal weight but in fact have a high body fat percentage and obese methabolism. The BMI also does not include all the variables essential for a health predictor. The BMI is not always a good predictor of metabolic disease, people who appear of healthy weight according to BMI have in some cases an obese metabolic syndrome. The BMI was developed as a law of natural sciences and “social physics” [1], as it was called then, before the middle of the 19^th century, and it had been used from the 70s for medical purposes, to detect obesity and the risk of mortality [6][7]. The BMI has a huge importance for modern society, affected by an obesity epidemic [8]. BMI has applications in medicine, sport medicine, sport, fitness, bodybuilding, insurance, nutrition, pharmacology. The main limitation of the BMI is that it does not account for body composition including non fat body mass such as muscles, joints, body frame and makes no difference between fat and non fat components of the body weight. The body composition and the proportion of fat and muscles make a difference in health outcomes [12][13][14][25][26][27][35][36][37] [38][39][40][41][42][43][44]…[100]. Body composition makes a difference also in the level of sport performance for athletes of every level. In nearly two centuries since the Body Mass Index was developed, no formula had been successfully developed to account for body composition and make the difference between muscle and fat in a consistent way. This can be considered a longstanding open problem of major importance for society. The objective of this analysis is to develop new formulae taking into account the health implication of body composition measured through indirect, simple indicators and making the difference between muscles and fat, healthy and non healthy metabolism. The formulae developed in this article are the only formula to successfully generalize BMI and make this difference. I develop a direct generalization of BMI, in the mathematical and physiological sense to account for fat and fat free mass and muscles, small and large body frames. It is the first such generalization because the classic BMI can be determined as a particular case of my formulae in the strict mathematical and practical physiologic sense. No other formula generalized the BMI to make the difference between fat and a large frame and muscles has ever been published in nearly two centuries since the BMI formula had been developed. The formulae I developed explain and generalize the conclusions of a large number of highly cited empirical experiments cited in the reference section. [35][36][37][38][38][39] [40][42][43][44]..[100] Most of the experimental proof I bring in support of my formulae and bodyweight quantification theory comes from many highly cited experimental research publications in medicine, sports medicine, sport science and physiology. My formulae explain also performance in decades of competitive sports and athletics

The ionospheric scintillation is a rapid phase and amplitude fluctuation of satellite signals due to the small-scale irregularity of electron density in the ionosphere. The characterization of the scintillation index in a proper way is a crucial aspect of the Global Positioning System (GPS) satellite signals for the purpose of space-based navigation, satellite communication, space weather as well as earth observation applications. In the current study, we analyzed the ionospheric scintillation index during the year of 2018 to 2019 over the Nepal region which locates itself almost being sandwiched between India and China and in the vicinity of low latitudes. The characteristic variations of scintillation occurrence are studied during the several geomagnetic storm and quiet days. The results show that the S4 indexes are varying from the 0.05 to 0.45 during the whole year. The S4 indexes behave higher variations during the whole day in the starting of the year and start to decrease at end of the day as well as at the ending months of the year 2019. The S4 values become completely less during the sunset time, while they have higher values during the sunrise. Especially, the S4 index during the storm days are larger than during the quiet days. It is worthy to note that the variations of S4 index studied in this current study do not follow the sunset property during the year of 2019. Consequently, the causes should be discovered and discussed additionally in the next research paper.

This study reports on the assessment of the growth potential of five edible vegetables which were grown in Cr (VI) spiked soils. The vegetable plants that were used in this study were Vigna angularis, Cicer arietinum, Spinacia oleracea, Amaranthus dubius Thell and Phaseolus vulgaris. Dried ground samples from roots, stems and leaves were analysed for various oxidation states of Cr. The daily intake of chromium (DIC), hazard quotient (HQ) and hazard index (HI) methods were employed to assess the potential human health risks posed by these Cr oxidation states through vegetable consumption. The results showed that Vigna angularis was the only vegetable that germinated in highly concentrated Cr (VI) in the simulated soil (456 mg/kg). The highest bioaccumulation factor of CrT in the roots was found in Cicer arietinum at 3.5 ± 0.51 mg/kg DW. The highest translocation factor in stem was that of Cicer arietinum and Vigna angularis at 1.0 ± 0.00, while Cicer arietinum and Spinacia oleracea translocated highest Cr to the leaf at 2.1 ± 0.21. A child or an adult consuming such contaminated Cicer arietinum were likely to take in between 508 -785 mg/kg/day of total Cr which were above the World Health Organisation guidelines of 220 and 340 mg/kg/day, respectively. The highest HQ was found in Cicer arietinum at 8.7 and 13.4 for adults and children, respectively. The same species of plants had also high HI at 17.4 and 27.2 for adults and children respectively. This indicated that consumers of the edible vegetables grown in Cr (VI) rich soil may be exposed to health risks and the children were more likely to be vulnerable to these adverse effects than the adult.

The key goal of the current study was to determine suitable areas of water pumping for drinking and agricultural harvest in Tabriz aquifer, located in East Azerbaijan province, northwest Iran. In the study area, groundwater is the key foundation of water for drinking and farming requirements. Groundwater compatibility study was conducted by analyzing Electrical conductivity (EC), Total dissolved solids (TDS), Chloride (Cl), Calcium (Ca), Magnesium (Mg), Sodium (Na), Potassium (K), Sulfate (SO4), Total hardness (TH), Bicarbonate (HCO3), pH, carbonate (CO3) and Sodium Adsorption Ratio (SAR) obtained from 39 wells in the period of 2003 to 2014. For this purpose, the Water Quality Index (WQI) and irrigation water quality (IWQ) index were utilized. The WQI index zoning exposed that the groundwater of the study area for drinking purposes is categorized as excellent, good and poor water. Most drinking water harvested for urban and rural areas are in the class of 'excellent water'. The results revealed that about 37 percent (296 km2) of groundwater has high compatibility, and 63 percent of the study area (495 km2) has average compatibility for agricultural purposes. The trend of IWQ and WQI indexes demonstrates that the groundwater is getting worse over the time.

Background Diabetic patients have an increased risk of infections; however, the association between type 2 diabetes and hospital outcomes of sepsis remains controversial when the diabetes severity is not considered. We examined this association using nationwide and hospital-based databases concomitantly. Methods The first part of this study was conducted using 2 nationwide databases: the Longitudinal Cohort of Diabetes Patients and the Longitudinal Health Insurance Database 2000. The diabetic complication burden was evaluated using the adapted Diabetes Complications Severity Index score (aDCSI score). In the second part, we used the hospital-based database with laboratory data, such as initial blood glucose and HbA1c levels, to make comparisons between surviving and dead patients with type 2 diabetes and sepsis. Results The nationwide study included 19,719 type 2 diabetic sepsis patients and an equal number of non-diabetic patients. The diabetic sepsis patients had an increased odds ratio (OR) of 1.14 (95% CI 1.1-1.19) for hospital mortality. The OR for mortality increased as the complication burden increased (diabetic sepsis patients with aDCSI scores of 0, 1, 2, 3, 4, and ≥5 had ORs of 0.91, 0.87, 1.14, 1.25, 1.56, and 1.77 for mortality, respectively (all P<0.001 and P for trend <0.001)). A total of 1,054 diabetic sepsis patients were included from the hospital-based database. Initial blood glucose levels in the surviving and dead diabetic sepsis patients did not differ significantly: 273.9 ± 180.3 versus 266.1 ± 200.2 (mg/dL) (P=0.095). Moreover, the surviving diabetic sepsis patients did not have a lower HbA1c (%): 8.4 ± 2.6 versus 8.0 ± 2.5 (P=0.078). Conclusions In the case of type 2 diabetic sepsis patients, the diabetes-related complication burden is the major determinant of hospital mortality rather than the diabetes itself. Contrary to popular belief, initial blood glucose and HbA1c levels may not be as important as previously thought.

Psychological wellbeing can be impacted substantially by changes in body image during youth, which can be a predictive factor for positive or negative attitudes, such as for self-esteem and satisfaction. In this study, adherence to the thinness model and to healthy behaviours were analysed in terms of the emotional patterns and body management of the young female Italian population (N = 2287). Skinny girls fitting better with the thinness model tended to develop higher positive emotional patterns, but their body management was low. Findings suggest the urgent need for preventive programmes to enhance awareness of healthy behaviours against appearance models.

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

Horizontal gene transfer (HGT) is the transmission of genes between organisms by other means than parental to offspring inheritance. While it is prevalent in prokaryotes, HGT is less frequent in eukaryotes and particularly in metazoan. Here, we propose Alienness, a taxonomy-aware web application that parses BLAST results against public libraries to rapidly identify candidate HGT in any genome of interest. Alienness takes as input the result of a BLAST of a whole proteome of interest against any NCBI protein library. The user defines recipient (e.g. metazoan) and donor (e.g. bacteria, fungi) branches of interest in the NCBI taxonomy. Based on the best BLAST E-values of candidate donor and recipient taxa, Alienness calculates an Alien Index (AI) for each query protein. An AI >0 indicates a better hit to candidate donor than recipient taxa and a possible HGT. Higher AI represent higher gap of E-values between candidate donor and recipient and a more likely HGT. We confirmed the accuracy of Alienness on phylogenetically confirmed HGT of non-metazoan origin in plant-parasitic nematodes. Alienness scans whole proteomes to rapidly identify possible HGT in any species of interest and thus fosters exploration of HGT more easily and largely across the tree of life.

Primary energy consumption is one of the key drivers of global CO₂ emissions that, in turn, heavily depend on the efficiency of involved technologies. Either the improvement in technology efficiency or the expansion of non-fossil fuel consumption require large investments. The planning and financing of such investments, by policy makers or global energy firms, require, in turn, reliable measures of associated global spreads and their evolution in time. In this paper, our main contribution is the introduction of index measures for accessing global spreads (that is, measures of inequality or inhomogeneity in the statistical distribution of a related quantity of interest) of technology efficiency and CO₂ emission in primary energy consumption. These indexes are based on the Gini index, as used in economical sciences, and generalised entropy measures. Regarding primary energy sources, we consider petroleum, coal, natural gas and non-fossil fuels. Between our findings, we attest some stable relations in the evolution of global spreads of technology efficiency and CO₂ emission, and a positive relation between changes in global spreads of technology efficiency and use of non-fossil fuel.

Accurate measurement of systemic financial risk is critical to maintaining the stability of financial markets. Taking China as the subject of investigation, the Chinese Financial Stress Index (CFSI) indicator system was con-structed by integrating six dimensions and employing Gray Relation Analysis (GRA) for dimensionality reduction of the indicators. The CFSI was derived using the Attribute Hierarchy Model (AHM) method with the Criteria Importance Through the Intercriteria Correlation (CRITIC) method, and an Improved Gravitational Search Algorithm (IGSA) optimized Radial Basis Function Neural Network (RBFNN) was proposed for out-of-sample prediction of CFSI trends from 2024 to 2026. By analyzing the trend of financial pressure indicators, the relationship between financial pressure and economic activity can be effectively identified. The research findings indicate that: (1) The CFSI is capable of accurately reflecting the current financial stress situation in China; (2) The IGSA-RBFNN demonstrates good robustness and generalization capabilities, predicting that the CFSI index will reach a peak value of 0.543 by the end of 2024, and there exists a regular pattern of stress rebound towards the end of each year. The novel methodology benefits policymakers and regulatory authorities to formulate preventive measures and risk management by identifying potential risks and vulnerabilities in advance.

Managing a portfolio whose value closely tracks an index by trading only in a subset of the index constituents involves an NP-hard optimisation problem. In the prior literature, it has been suggested to solve this problem using sequential Monte Carlo (SMC, a.k.a. particle filter) methods. However, this literature does not take transaction costs into account, although transaction costs are the primary motivation for attempting to replicate the index by trading in a subset, rather than the full set of index constituents. This paper extends the SMC approach to index tracking to allow for proportional transaction costs and implements this extended method on empirical data for a variety stock indices. In addition to providing a more practically useful tracking strategy by allowing for transaction costs, we find that including a penalty for transaction costs in the optimisation objective can actually lead to better tracking performance.

This paper presents the results of quantitative research examining the impacts of demographic and socioeconomic factors on community resilience to disasters. The survey was carried out utilising a questionnaire distributed and subsequently collected online from 321 participants during January 2024. The study employed an adapted version of the '5S' social resilience framework, encompassing five sub-dimensions – social structure (10 variables), social capital (9 variables), social mechanisms (17 variables), social equity and diversity (13 variables), and social belief (13 variables). This customized framework includes 62 indicators, providing a thorough assessment of community (social) disaster resilience in the research context. To explore the relationship between predictors and community (social) disaster resilience in Serbia, their attitudes towards the mentioned five sub-dimensions, as well as their engagement in preventive measures and their perception of resilience to various disasters with a particular focus on demographic and socio-economic impacts, statistical methods including t-tests, one-way ANOVA, Pearson’s correlation, and multivariate linear regression were employed. The results of the multivariate regressions across various community disaster resilience subscales indicate that age emerged as the most significant predictor for the social structure subscale. At the same time, education stood out as the primary predictor for the social capital subscale. Additionally, employment status proved to be the most influential predictor for both social mechanisms and social equity-diversity subscales, with property ownership being the key predictor for the social beliefs sub-scale. Despite being considered in the analyses, gender, marital status, income level, and number of household members did not emerge as the most significant predictors across the investigated community (social) disaster resilience subscales. The determined mean value of the community (social) disaster resilience index is M = 2.62, and the findings reveal that participants assigned the highest ratings to the social beliefs subscale (M = 2.76), while the lowest values were observed in the social structure subscale (M = 2.46). Findings can be used to create strategies and interventions aimed at enhancing the resilience of communities in Serbia by addressing the intricate interplay between demographic characteristics, socio-economic factors, and their ability to withstand, adapt to, and recover from different disasters.

The refractive index of seawater is one of the essential parameters in ocean observation, so it is necessary to achieve high precision seawater refractive index measurement. In this paper, we propose a method for measuring the refractive index of seawater based on a Position Sensitive Detector (PSD). Theoretical model is established to depict the correlation between laser spot displacement and refractive index change, utilizing a combination of position sensitive detector and laser beam deflection principle. Based on this optical measurement method, a seawater refractive index measurement system was established. To effectively enhance the sensitivity of refractive index detection, a focusing lens was incorporated into the optical path of the measuring system, and simulations were conducted to investigate the impact of focal length on refractive index sensitivity. The calibration experiment of the measuring system was performed based on the relationship between refractive index of seawater and underwater pressure (depth). By measuring laser spot displacement at different depths, changes in displacement with respect to both refractive index and depth were determined. Experimental results demonstrate that the system exhibits a sensitivity of 9.9277×10−9RIU (refractive index unit), the refractive index deviation due to stability is calculated as ±7.545×10−9RIU. Thereby the feasibility of highly sensitive measurement of seawater refractive index is verified.

This study sought to spatially characterise and explain the differences of peoples’ perceptions on the impact of COVID-19 based on the socio-economic disparities in Gauteng, using choropleth mapping and Geographically Weighted Regression (GWR). Results indicate that respondents from relatively vulnerable municipalities like Merafong, Mogale City and Lesedi reported life being worse, information scant, and overall despondency being high since COVID-19. These are areas that fall under the High to Very High categories in terms of the Socio-economic Risk Index. GWR results, however, did not show a high explanatory power on the COVID-19 variables se-lected for the research, based on R2 values. For instance, the residual in overall satisfaction with life after COVID-19 was the lowest (-0.5 to 0.5) in the less affluent districts of the Rand West City and Sedibeng. Residual variables on life changes after COVID-19 were also the lowest in the southern parts of the same districts, with other low values almost evenly distributed throughout the province for the variable ‘Government information on COVID-19 was scant’. Although overestimation and underestimation existed, most were relatively low falling between -1.5 to -0.5 and distributed evenly across the province. In sum, however, the findings point to the complexity of socio-economic factors in spatially characterising social risk and vulnerability. Additionally, the negative sentiments expressed by people from the more vulnerable locations in the province emphasise the need for more targeted interventions by government to cushion the residents of the province to the continued negative impacts of COVID-19.

Insurance serves as a mechanism to effectively manage and transfer revenue-related risks. We conducted a study to explore the potential financial advantages of index insurance, which protects agricultural producers, specifically sugarcane, against excessive rainfall. Creation of the index involved utilizing generalized additive regression models, allowing for consideration of non-linear effects and quantile generalized additive regression to evaluate relationships with lower quantiles, such as low yield events. To quantify the financial benefits for farmers, should they opt for excessive rainfall index insurance, we employed efficiency analysis based on metrics such as Conditional Tail Expectation, Certainty Equivalence of Revenue, and Mean Root Square Loss. The results of the regression model demonstrate its accuracy in predicting sugar cane yields, with a split testing R2 of 0.691. Additionally, our study suggests that this type of insurance could also apply to sugarcane farmers and other crop producers in regions where extreme rainfall threatens the financial sustainability of agricultural production.

A herbarium is a library of preserved dried samples of vascular plants, bryophytes, fungi, algae and/or lichens and is maintained for educational and scientific purposes, and provides detailed information on taxonomy, systematic, biodiversity, ecological and evolutionary research studies. Globally, there are more than 3,000 active public herbaria that preserve around 400 million exsiccates. In Brazil there are 216 active herbaria, of which 162 are indexed in the Index Herbariorum and in the Central region there are 21 herbaria. In this context, the Herbarium of the University of Brasília (international code UB) was founded in 1963 together with the Department of Botany of UnB and is located at the Institute of Biological Sciences of the Campus Darcy Ribeiro, Brasília and it is fifth largest herbarium in Brazil and presents approximately 277 thousand samples. In this study, we present here the bryophytes collection at the UB Herbarium. The collection of bryophytes of UB herbarium has 30,902 samples of all continents and 79 countries and most come from Brazil, Papua New Guinea, Malaysia, United States of America and Argentina.

In preserving genetic diversity among domestic animal breeds, the strategies emphasizing be-tween-breed diversity may be not optimal by neglecting within-breed variation. The present study aimed to assess the extent of the population subdivision of Mangalica pigs and the contri-bution of migration intensity to their substructure. Genealogy analysis was performed for breeding animals born between 1981 and 2023 examining three colour variations (Blonde, Swal-low-Belly, and Red). The fixation index (FST) was calculated and evaluated by Multidimensional Scaling and Clustering to expose the population substructure. The average FST is 0.04 for the Blonde and 0.05 for the Swallow-Belly and the Red while in the active herds, these parameters are smaller being 0.03 and 0.04, respectively. The migration of individuals affected 61.63% of the Blonde, 75.53% of the Swallow-Belly, and 63.64% of the Red breed herds. No population sub-structure was found in any Mangalica breed which can be explained by the extensive within breed migration among the herds.

Underground storage of natural gas has the characteristics of clean and low-carbon, and has the ability to provide sustainable and stable supply. It is a very high-quality green energy that can increase the storage efficiency of gas storage through fracturing, achieving the sustainable development goal of "Carbon Peaking and Carbon Neutrality". The accurate evaluation of the fracability of a reservoir is an important prerequisite for reservoir fracturing design and post fracturing productivity evaluation. At present, research on fracability is mainly based on qualitative characterization or quantitative evaluation based on rock mechanics and fracturing construction parameters, which cannot fully reflect the rock composition and structure of each stage. Firstly, based on logging data, this paper analyzes the evolution laws of strain energy such as elastic properties, pre-peak dissipation energy, and post-peak fracture energy during the transition of rock materials from plastic deformation to brittle fracture in an energy perspective, and determines the key energy that affects the brittle characteristics of rocks. Secondly, a brittleness index evaluation approach has been established that can comprehensively reflect the mechanical properties of rocks during pre-peak deformation and post-peak damage stages. In addition, this article focuses on the impact of reservoir stratigraphic environment by combining the influence of geo-stresses with the rock brittleness index, and proposes a new method for evaluating reservoir fracability. Finally, this paper conducts a study on the fracability evaluation of three wells in a gas storage facility in eastern China. The results indicate that low modulus and fracability coefficient are beneficial for fracturing, thereby improving the gas production and peak shaving ability of gas storage.

Introduction: The coronary flow reserve (CFR) is a sign of early-stage coronary artery disease (CAD). Plasma atherogenic index (PAI) is related to atherosclerosis and cardiovascular mortality. Therefore, our aim was to determine CFR and PAI in patients with primary hyperparathyroidism (PHPT) and investigate whether PAI can be used in the detection of early-stage CAD. Material and Methods: The sample was comprised of 44 patients with PTHT and 33 healthy volunteers. We defined CFR as the ratio of the hyperemic diastolic peak velocity to the baseline diastolic peak velocity. PAI values were calculated with the formula of log 10 triglyceride (TRG) / high-density lipoprotein (HDL). Result: The comparison of the groups for PAI and CFR demonstrated that PAI levels were significantly higher while CFR levels were significantly lower in the PTHT patients (p<0.01, p=0.01, respectively). The correlation analysis revealed that CFR was negatively correlated with PAI and TRG (PAI- p<0.0001 r=-0.537).The multivariate logistic regression analysis showed that only a high PAI level (OR: 151.6, 95% confidence interval (CI): 4.1-5480, p=0.006) was an independent predictor of reduction in CFR in PHPT patients. Conclusion: Overall, we found an independent correlation between PAI and CFR values. Hence, PAI may be useful in identifying PHPT patients facing a high risk of adverse cardiovascular events and may also allow early diagnosis of subclinical atherosclerosis.

The study is devoted to analyzing the economic sustainability of the town of Amherst, MA. The city's top employer and core enterprise is the University of Massachusetts Amherst, with over 32,000 students and almost 2,000 staff members. Based on a literature review, a hypothesis was put forward that a university city should have a high level of economic sustainability. To assess economic sustainability, the USCESI Index was developed. It evaluates sustainability in three groups of parameters: society, economy, and ecology. The first group includes the level of racial diversity, the level of education of the population, and the access to medical services. The second group consists of the Gini coefficient by income level, the median cost of housing, and the unemployment rate. The environmental situation is assessed according to the Air Quality Index developed by the US Environmental Protection Agency. For comparison, the town of Braintree, MA, was taken. The USCESI was calculated for both locations. The analysis showed that both Amherst and Braintree have a high degree of economic sustainability. However, it was revealed that proximity to a significant economic center has a more powerful positive impact on economic sustainability than the location of a large university.

The association between obesity and clinical as well as radiological outcomes in patients suffering non-traumatic intracerebral haemorrhage (ICH) remains unclear. The obesity paradox suggests a protective effect regarding in-hospital mortality. This study evaluates the impact of body mass index (BMI) on functional long-term outcome and bleeding volume in patients with non-traumatic ICH. A retrospective cohort study including all consecutive patients with spontaneous ICH treated at a tertiary referral centre between December 2017 and June 2021, aged 80 years or younger (n = 218), were included. Patients were dichotomized into overweight (OW, BMI ≥ 25 kg/m2) and normal weight (NW, BMI < 25 kg/m2). Functional outcomes were assessed by the modified Rankin scale (mRS), extended Glasgow Outcome Scale (GOS-E) and the National Institutes of Health Stroke Scale score (NIHSS) at 1, 3, 6 and 12-months follow-up. Bleeding volumes were calculated as ABC/2. Univariate and multivariate analysis were performed to assess clinical predictors of favourable outcome in the long-term. Of 218 patients (66.04 ± 15.18 years) suffering non-traumatic ICH, 115 (52.75%) were OW (29.72 ± 3.82). Female sex (p = 0.1), NIHSS (p = 0.69), cardiovascular risk factors (p = 0.55), ICH volume (p = 0.19), and presence of anticoagulation (p = 0.67) did not significantly differ between the OW and NW cohort. At discharge, functional outcome did not significantly differ between both cohorts (NW, mRS 3.92 ± 2.54 vs. OW, mRS 3.21 ± 2.43, (p = 0.28)). Multivariate analysis revealed that haemorrhage volume (p = 0.01) was the only robust risk factor to predict functional outcome after 1 year. Our data suggests that in ICH patients, neither obesity nor patient’s age are negative predictors for functional outcome in the long-term. Instead, bleeding volume is a robust risk factor predicting poor functional status after ICH. Therefore, prospective randomized trials analysing this coherence are highly warranted.

In this study, we presented a simple highly sensitive sensor based on commercially available solid core photonic crystal fiber (PCF) and surface plasmon resonance (SPR) for measuring the refractive index (RI) of analytes. The numerical simulation based on the finite element method (FEM) has been examined to compute the optical properties such as confinement loss, power spectrum, and transmission intensity of the sensor. The most sensitive and inert plasmonic materials (gold and silver) have been assumed to be coated inside the fiber with the range of analytes RI from 1.32 to 1.40. The performance of the proposed sensor has been evaluated by tracing the several optical features like wavelength sensitivity, amplitude sensitivity, resolution of the sensor, and figure of merit. As a result, the comparative study between silver and gold elements has been carried out in which the maximum sensitivity received as 1.15 μm/RIU and 1.10 μm/RIU respectively. Whereas, on the base of power spectrum the obtained sensitivity was 513 μm/RIU for the gold layer. Moreover, the effect of other structural parameters (air holes and plasmonic layers thickness) on the sensing performance has been taken into an account. According to the simulation analysis and results, this sensor would have a great potential in various sensing applications of biomedical and liquid refractive index.

Background: A prognostic index validated for the outcomes of advanced high-grade serous ovarian cancer (HGSOC) patients with neoadjuvant chemotherapy (NACT) is still lacking. We therefore developed an ovarian neoadjuvant chemotherapy prognostic index (ONCPI) to enhance predictive accuracy. Methods: We analyzed clinicopathologic feature of advanced HGSOC patients receiving platinum-based NACT. Blood inflammatory composite markers were calculated and binary-transformed by optimal cutoffs. The omental hematoxylin and eosin (H&E) stained slides were selected for the assessment of chemotherapy response score (CRS). Logistic regression analyses and Cox proportional hazard regression model were utilized to develop a prognostic index. Results: Multivariate analysis showed that CRS and neutrophils-to-lymphocyte ratio (NLR) are independent risk factors for platinum-chemotherapy response. Meanwhile, Kaplan–Meier and Cox regression analysis revealed that CRS score was significantly correlated with PFS and OS, and NLR-high patients was associated with poor OS. We further developed an ONCPI model based on the CRS score and NLR level. Survival analysis suggested that patients with score 0 and 1 of ONCPI were significantly associated with improved PFS and OS. Conclusions: The ONCPI score emerges as a significant prognostic marker for predicting NACT outcomes in advanced HGSOC patients. Its integration into clinical practice and risk-stratified trial design is conceivable.

In the overall context of national eco-conservation civilization development and considering the hills in the Beijing-Tianjin-Hebei-Shanxi region, the local forest coverage rate is gradually on the rise, and so is the risk of forest fire. Every year, satellites can monitor and detect hundreds of fire spots on average. In recent years, serious fire took place for several times, leading to loss of life and personal injury. Then the fire-fighting work consumed huge amount of labor and material resources, exerting negative social impacts in many ways. Thus, the analysis of fire climate background in this region and the forecast based on fire weather indexes constitute an important part in the forest fire risk management. Located in the tropical monsoon climate zone, four provinces and municipalities of Beijing, Tianjin, Hebei and Shanxi are similar in terms of climate characteristics. This study tries to analyze the characteristics about fire spots under satellite monitoring, fire climate and fire weather index. The probability distribution analysis of weather index about fire spots in history and key meteorological observation stations as well as the weather index analysis in the early stage of typical fire indicate that the Fine Fuel Moisture Content (FFMC) and the Initial Spread Index (ISI) in the Fire Weather Index (FWI) system is applicable to the fire risk analysis in the Beijing-Tianjin-Hebei-Shanxi region, which can also effectively indicate the fuel moisture and spread conditions. As regards to the average level in Beijing-Tianjin-Hebei-Shanxi, when the FFMC is smaller than 93.5 and the ISI is also smaller than 5.0, there is a low risk of fire; when the FFMC is above 94 and the ISI is larger than 10.0, there is a high risk of fire; and the fire risk will be extremely high if the FFMC is over 96 and the ISI is above 13.0. In the practical fire-fighting management, the fire danger class can be released in reference to the ISI classes and threshold values of key meteorological observation stations under analysis provided by this study.

Considering the significant interest in the synthesis and various properties of the polymorphs of tin dioxide (SnO2), they are still comparatively rare in modern photovoltaic techniques. The hybrid organic-inorganic lead perovskites have triggered a revolution among solar cell researchers due to their low cost and ultrahigh power conversion efficiency. In this research, the optical properties of seven stable polymorphs (Balakrishnan Kanimozhi et al. ACS omega 7, 12 (2022): 10382-10393) of SnO2 have been investigated using first-principles approaches. The effective mass of stable SnO2 polymorphs has been computed and it is found to vary depending on the specific polymorph and the direction in which it is measured. Moreover, the spectroscopic limited maximum efficiency (SLME) of SnO2 polymorphs was also computed and compared to that of other efficient perovskite solar cells. Both Pnnm and Pbca have equivalent efficiency in comparison to the rutile polymorph. Three of the seven stable polymorphs are effective in solar cell applications. This study is the very first attempt to examine the atomic structure and electronic properties of various SnO2 polymorphs using X-ray absorption near-edge spectroscopy (XANES) at both the Sn-K-edge and O-K-edge wavelengths. Our findings, as mentioned in this paper, may be an important advancement in the understanding of these materials, thereby facilitating the development of more efficient photovoltaic devices.

As an important means of controlling the spread of cities, large-scale urban green belts have been widely used in the planning and construction of green space systems in various mega-size cities around the world. In previous studies, there has been more research on the overall isolation effect of green belts, while there has been less research on changes in their internal structure. There have been more perspectives on the land-use change (LUC) caused by urban expansion, and less systematic research on the dual driving factors of LUC. In this paper, we constructed a multi-dimensional index system to measure the "contraction-expansion" mechanism of land use in the overlapping vegetation areas of large green belts under the dual influence of urban expansion and urban greening, from the perspectives of quantity, space, and connectivity during different construction periods. Taking the boundary of two green belts in Beijing as an example, we hope to provide scientific support for the construction and ecological protection of Beijing's green belts.

Dairy cattle predicted by genomic breeding values to be heat tolerant are known to have less milk production decline and lower core body temperature increases in response to elevated temperatures. In a study conducted at the University of Melbourne’s Dookie Robotic Dairy Farm during summer, we identified the most 20 heat-susceptible and 20 heat-tolerant cows in a herd of 150 Holstein Friesian lactating cows based on their phenotypic responses (changes in respiration rate, surface body temperature, panting score, and milk production). Hair samples were collected from the tip of the cows' tail following standard genotyping protocols. The results indicated variation in feed saved and HT genomic estimated breeding values (GEBVs) (P≤0.05) across age, indicating a potential for their selection. As expected, the thermotolerant group had higher GEBVs for HT and feed saved but lower for milk production. In general, younger cows had superior GEBVs for Balanced Performance Index (BPI), Type Weighted Index (TWI) and Australian Selection Index (ASI), whilst older cows were superior in fertility, feed saved (FS) and HT. The study demonstrated highly significant (P≤ 0.001) negative correlations (-0.28 to -0.74) between HT and GEBVs for current Australian Dairy cattle selection indices (BPI, TWI, ASI, HWI) and significant (P≤ 0.05) positive correlations between HT and GEBVs for traits like FS (0.45) and fertility (0.25). Genomic selection for HT will help improve cow efficiency and sustainability of dairy production under hot summer conditions. However, a more extensive study involving more lactating cows across multiple farms is recommended to confirm the associations between the phenotypic predictors of HT and GEBVs.

Trends focused on the Global Innovation Index (GII) as a measure for progress of nanochemistry. This paper provides projections of recent developments in the word in nanochemistry based on the Global Innovation Index as a predictor for certain Arab countries. The GII is an annual ranking of countries by its ability and performance in innovation and is calculated on a basic average from five and two pillars in two sub-indexes, the Innovation Input Index and the Innovation Output Index. Each pillar represents a trait of creativity and consists of up to five measures, with a weighted average formula for measuring their ranking. In 2008, the GII rose to 36.3 in 2016 from 0.5. The GII is smaller than the GII in Arabic countries worldwide. During the years 2013-2016, the worldwide GII was increasing while for the same period, for Arabic countries, this decline could be explained by economic and industrial wars in the Arab region.

Background: This study explored the effects of a virtual reality exercise program on overweight middle-aged women. Methods: This randomized controlled trial included women 4065 years of age with a body mass index (BMI) of 23 kg/m2 or more living in D city. The virtual reality environment was set up by attaching an IoT sensor to an indoor bicycle and linking it with a smartphone, enabling exercise in an immersive virtual reality through a head-mounted display. Results: In the virtual reality exercise group, the BMI was significantly decreased after the 8-week intervention compared with the baseline value (F=100.806, p<.001). The depression scores were significantly different among the three groups, with the intervention effect being more significant in the virtual reality exercise group than in the indoor bicycle exercise and con-trol groups (F=3.462, p<.001). Furthermore, the levels of exercise fun (F=12.373, p<.001) and exer-cise immersion (F=14.629, p<.001) were significantly higher in the virtual reality exercise group than in the indoor bicycle exercise and control groups. Conclusions: The virtual reality exercise program positively affected the BMI and the levels of depression, exercise fun, and exercise im-mersion in overweight middle-aged women. It is an effective home exercise program for obesity management in this population.

Objective. Political instability, corruption, exclusive institutions et al. are some of the hypotheses backed by literature as to why some nations are more developed than others. One hypothesis which has not been intensively studied is the culpability of individual and institutional behavior and its impact on development. To examine the validity of such a hypothesis, a composite index which quantifies such development hindering behavior must be developed. The prelude to developing this index is to investigate whether such a quantitative measure exists to begin with. To achieve this objective, a bibliometric analysis of Scopus and Web of Science databases will be conducted. Method. A bibliometric and content analysis of Scopus and Web of science databases using Excel, VOSviewer, and R software. Results. The findings of the bibliometric analysis indicate the absence of such measure particularly within the scope of ‘bad behavior’, ‘unethical behavior’, and ‘development’. Conclusions. The study findings provide the greenlight to proceed with the construction of the ‘Bad Behavior Index’. Contribution. The practical contribution of this study is that it provides researchers with an improved methodology on how to conduct a bibliometric analysis to identify the absence of knowledge and provide a justification for the creation of such knowledge by integrating and analyzing two journal databases instead of one, using three mediums: Excel, VOSviewer, and R software.

Catalyst with high catalytic activity and good stability are desirable in the electrocatalytic oxidation of glucose. Herein, Pt concave nanocubes with high-index facets (HIFs) supported by carbon black (Pt CNC/CB) are prepared through a hydrothermal method. The experimental results demonstrate that the peak current densities in different potential regions on the Pt CNC/CB anode are 0.22, 0.20, and 0.60 mA cm−2, respectively. The glucose oxidation reaction shows superior performances in basic and neutral conditions than in acid conditions. Better stability is achieved by Pt CNC/CB than Pt concave nanocubes (Pt CNCs). Abundant surface defects with low-coordinated atom numbers, such as the steps, kinks, and edges, are served as active sites in the electrocatalytic oxidation of glucose. With the addition of carbon black, the catalytic activity can be improved by facilitating the full exposure of the active surface defects on the HIFs of Pt CNCs. Moreover, to address the aggregation of Pt CNCs, caused by the high surface energy of HIFs, the introduction of carbon material is an effective way to preserve the HIFs, and thus enhance the stability of the catalyst. Hence, the prepared Pt CNC/CB electrocatalyst has great potential to be applied in the electrooxidation of glucose.

Cities consume over 75% of natural resources, produce over 50% of global waste and emit 60 - 80% of greenhouse gases. The scenario that by 2050 two thirds of the world population will live in cities, highlights how cities are still responsible of the growing consumption characterized by linear economy processes, with the production of various types of waste. In this unsustainable framework, the Circular Economy offers the opportunity to shape the urban system by means of rethinking the possibility to produce and use goods and services exploring new ways to ensure long-term prosperity. The Circular City paradigm contains in fact all the principles of the Circular Economy: recovery, recycling and sharing. In particular, Circular City also introduces actions related to the development of renewable energy communities, use of green materials, CO2 absorption approaches and Proximity Cities. The aim of this work is to develop a methodology to build a composite index (Circular City Index) capable of measuring the degree of implementation of urban policies that enable the territory to initiate an ecological transition of public assets. The city of Cagliari (Sardinia, Italy) represents the case study to apply circular urban policies in public properties, for civil and military use.

There are a number of Anopheles species playing either primary or secondary roles in malaria transmission. Hence, understanding the species composition, their bionomics, and behaviors are all important in designing and implementing vector control intervention tools. Moreover, accurate identification of different species is vital. This study aimed to assess species composition, sporozoite infection rate, and blood meal origins of malaria mosquitoes in two malaria-endemic villages of Boreda district in Gamo zone, southwest Ethiopia. Thirty houses, 20 for Centers for Disease Control and Prevention (CDC) light traps and 10 for Pyrethrum Spray Catches (PSC), were randomly selected for bimonthly mosquito collection from October 2019 to February 2020. Enzyme-linked-immunosorbent assay (ELISA) test was done to detect the blood meal origins and circumsporozoite proteins (CSPs). The entomological inoculation rate (EIR) was calculated by multiplying the sporozoite and human biting rates from PSCs. Anopheles gambiae and An. funestus complexes were further identified into species by polymerase chain reaction (PCR). Anopheles species with some morphological structures confusing with An. gambiae or An. funestus complexes were father confirmed by PCR. A total of 15 Anopheles species were documented, of which An. demeilloni was the dominant one. Only An. arabiensis was positive for P. falciparum CSP. The overall P. falciparum CSP rate of An. arabiensis was 0.54%. The overall estimated P. falciparum EIR of An. arabiensis from PSC was 1.5 infectious bites/person/five months. Of the 145 freshly fed Anopheles mosquitoes tested for blood meal source, 57.9% (84/145) had bovine blood meal, 22 (15.2%) had human blood meal origin alone and 24 (16.5%) had mixed blood meal origins of human and bovine. An. demeilloni mainly fed on bovine blood (102/126 = 80.9%). Among 420 morphologically classified An. demeilloni, 11 (2.6%) were confirmed as An. lessoni (one of the An. funestus complexes) by PCR. A substantial number of morphologically classified An. salbaii, An. maculipalpis and An. fuscivenosus were found to be An. arabiensis by PCR. Regardless of the high diversity of Anopheles mosquitoes, An. arabiensis is playing the primary role in malaria transmission. Morphological misclassification of species could be a challenge in malaria mosquito monitoring and surveillance, and hence it should be supported by more sensitive techniques for confirmation.

This study aims to understand the temporal and spatial characteristics of public concern for "children's mental health" in China in the context of the COVID-19 epidemic. Baidu Index is a research tool to collect and analyze massive data of Chinese netizens' behaviors. Using Baidu Index as the research tool, this paper analyzes the trend and distribution of Chinese netizens' attention to "children's mental health" from December 1st, 2019 to March 20th, 2022 from three aspects of trend research, need map, and crowd portrait. The study found that since the outbreak of COVID-19, the search trend of "children's mental health" has shown a cyclical change, peak in May and valley around the Spring Festival and National Day, and stable in other periods. "Mental health", "handwritten newspaper on mental health" and "youth mental health" are the most popular buzzwords among the public. The groups concerned of "children's mental health" is mainly distributed in Guangdong, Jiangsu, Beijing, and the majority are women between 30 and 39 years old. Meanwhile, search trend for "mental health" are like that for "children's mental health." The factors influencing the search volume change of "children's mental health" include Chinese traditional holidays, Spring Festival, National Day, Chinese Mental Health Day, and policies and instructions on children's mental health issued by the PRC Ministry of Education. The public would like to know about "mental health", "handwritten newspaper on mental health" and "adolescent mental health".

Research have been conducted in many countries around the world to assess air quality during COVID-19 pandemic, especially during lockdown period, some of these studies found an increase or decrease in some pollutants. This paper investigates the impact of COVID-19 on seven air pollutants (i.e., PM_2.5, PM₁₀, NO₂, O₃, SO₂, H₂S, CO) from the period January 2020 to December 2020 in the State of Kuwait. Kuwait is a desert country located in the north-eastern part of the Arabian Peninsula, and the northeast of the Arabian Gulf (Persian as it is sometimes called). Several analytical methods were conducted, such as spatial analysis (spatial interpolation) to study the distribution of the studied variables. The data was also statistically analysed (time series analysis - Kernel density) to study the temporal changes. The analysis also included applying air quality index to the data. We found that concentrations for the pollutants decreased during the pandemic due to the decrease of anthropogenic sources including such as traffic and petroleum activities, but the concentration for PM_2.5 increased, mostly because of the transported dust coming with the northwest winds prevailing in Kuwait from the Arabian deserts and Iraq.

Vegetation status assessment is crucial for agricultural monitoring and management. Vegetation indices derived from high resolution image time series can be used to derive key phenological parameters for annual crops. In this work, we propose a procedure for the estimation of these parameters and their associated uncertainties. The approach uses Bayesian inference through Markov Chain Monte Carlo in order to obtain the full joint posterior distribution of the phenological parameters given the satellite observations. The proposed algorithm is quantitatively validated on synthetic data. Its use on real data is presented together with an application to real-time within season estimation allowing for phenology forecasting.

The use of machine learning techniques to predict yield based on remote sensing is a no-return path and studies conducted on farm aim to help rural producers in decision-making. Thus, commercial fields equipped with technologies in Mato Grosso, Brazil, were monitored by satellite images to predict cotton yield using supervised learning techniques. The objective of this research was to identify how early in the growing season, which vegetation indices and which machine learning algorithms are best to predict cotton yield at the farm level. For that, we went through the following steps: 1) We observed the yield in 398 ha (3 fields) and eight vegetation indices (VI) were calculated on five dates during the growing season. 2) Scenarios were created to facilitate the analysis and interpretation of results: Scenario 1: All Data (8 indices on 5 dates = 40 inputs) and Scenario 2: best variable selected by Stepwise regression (1 input). 3) In the search for the best algorithm, hyperparameter adjustments, calibrations and tests using machine learning were performed to predict yield and performances were evaluated. Scenario 1 had the best metrics in all fields of study, and the Multilayer Perceptron (MLP) and Random Forest (RF) algorithms showed the best performances with adjusted R2 of 47% and RMSE of only 0.24 t ha^-1, however, in this scenario all predictive inputs that were generated throughout the growing season (approx. 180 days) are needed, so we optimized the prediction and tested only the best VI in each field, and found that among the eight VIs, the Simple Ratio (SR), driven by the K-Nearest Neighbor (KNN) algorithm predicts with 0.26 and 0.28 t ha^-1 of RMSE and 5.20% MAPE, anticipating the cotton yield with low error by ±143 days, and with important aspect of requiring less computational demand in the generation of the prediction when compared to MLP and RF, for example, enabling its use as a technique that helps predict cotton yield, resulting in time savings for planning, whether in marketing or in crop management strategies.

This study investigated and classified typical structures in rural village and analyzed the vulnerability of various typical types of structures. Based on the statistics of earthquake damages with magnitudes above 5 from 1996 to 2013 in China, the damage matrixes of different types of structures in rural village are obtained. And The vulnerability index and the vulnerability equation of structure are crucial to assess the earthquake losses of typical structures under different magnitudes earthquakes. According to the seismic loss of different types of structures under different earthquake magnitudes, there are possible to improve the seismic resilience of the buildings in rural village. Moreover, the regional vulnerability is analyzed by β probability distribution function, and the comprehensive seismic performance index of different types of agricultural buildings in the region is obtained. The main research is to predict the loss of different types of structures under different earthquake magnitudes in the future, and to provide technical support for different types of building in rural village reinforcement.

Tagetes genus of Composite family consider one of the most favorite floriculture plant. Therefore, of particular interest examine the salt tolerance of this bedding and coloring agent plant. In this research, was report the role of glycinebetaine (GB) in attenuating the adverse impacts of salt stress in African marigold plant, along with their anti-oxidative capacities and biochemical attributes. The salt stressed African marigold (100 and 150 mM NaCl) was treated with GB at 200 mM, beside untreated control plants. According to the obtained results, the growth characters were negatively in salt stressed plants but a mitigate impact of GB were observed in this respect. Obviously, the morphological as well as some physiological characters were reduced with salinity treatments while GB treatment reverses these effects. Overall, the alleviate impact of GB on the negative impact of salt stress was enhanced through improving total phenolic and antioxidant enzyme activity. Further, it is concluded that GB concentration induces the activities of antioxidative enzymes which scavenged ROS increased under saline conditions.

The fabrication of thin-film multilayer structures by sputtering technique usually requires multi-cathode deposition machine. This study proposes a simpler approach based on the RF power modulation: silicon nitride (SiN$_x$) thin films were prepared by RF reactive sputtering in (Ar + N$_2$) atmosphere at room temperature. The samples were analyzed to highlight the effects of different deposition conditions on the morphological and optical properties of the films in the visible and near/mid-IR regions. The refractive index of the films was changed in the range of 1.5 - 2.5 (at $\lambda$=800 nm) by tuning the sputtering power. IR reflectance measurements revealed the absence of spurious (oxygen- or hydrogen-based) phases, while atomic force and scanning electron microscopies confirmed the presence of flat and defect-free samples surfaces.

Capability assessment plays a crucial role in the demonstration and construction of equipment. To improve the accuracy and stability of capability assessment, we study the neural network learning algorithms in the field of capability assessment and index sensitivity. Aiming at the problem of over-fitting and parameter optimization in neural network learning, the paper proposes an improved machine learning algorithm—the Ensemble Learning Based on Policy Optimization Neural Networks (ELPONN) algorithm with the policy optimization and ensemble learning. This algorithm presents optimized neural network learning algorithm through different strategies evolution, and builds an ensemble learning model of multi-intelligent algorithms to assessment the capability and analyze the sensitivity of the indexes. Through the assessment of capabilities, the algorithm effectively avoids parameter optimization from entering the minimum point in performance to improve the accuracy of equipment capability assessment, which is significantly better than previous neural network assessment methods. The experimental results show that the mean relative error is 4.10%, which is better than BP, GABP, and early stopping. The ELPONN algorithm has better accuracy and stability performance, and meets the requirements of capability assessment.

Herein, a novel cavity design of racetrack integrated circular cavity established on metal-insulator-metal (MIM) waveguide is suggested for refractive index sensing application. Over the past few years, we have witnessed several unique cavity designs to improve the sensing performance of the plasmonic sensors created on the MIM waveguide. The optimized cavity design can provide the best sensing performance. In this work, we have numerically analyzed the device design by utilizing the finite element method (FEM). The small variations in the geometric parameter of the device can bring a significant shift in the sensitivity and FOM of the device. The best sensitivity and FOM of the anticipated device are 1400 nm/RIU and ~12.01, respectively. We believe that the sensor design analyzed in this work can be utilized in the on-chip detection of biochemical analytes.

Objective: The objective of the present study was to evaluate the activities of daily living using the Barthel Index, before and after the infection by SARS-COV-2 and to see if the results vary according to sex. Methods: The activities of daily living of 68 cohabiting geriatric patients, 34 men and 34 women, in 2 nursing homes were measured before and after SARS-COV-2 infection using the Barthel index. Results: The Covid 19 infection affects the performance of daily life activities in institutionalized elderly in nursing homes, and it does so especially the older the subject, regardless of sex. Conclusions: The Covid 19 pandemic, in addition to having claimed some victims, especially in the elderly population, has reduced the ability of these people to carry out their activities of daily life, considerably worsening their quality of life despite have been able to overcome the disease.

Fitts' law predicts the human movement response time for a specific task by a simple linear formulation, in which the intercept and the slope are estimated from the task's empirical data. This research was motivated by our pilot study, which found that the linear regression's essential assumptions are not satisfied in the literature. Furthermore, the keystone hypothesis in Fitts' law, that the movement time per response will be directly proportional to the minimum average amount of information per response demanded by the particular amplitude and target width, has never been formally tested. Therefore, this study developed an optional formulation derived from fusing the findings in psychology, physics, and physiology for fulfilling the statistical assumptions. An experiment was designed to test the hypothesis in Fitts' law and validate the proposed model. To conclude, our results indicated that movement time could be related to the index of difficulty underlying the same constant amplitude. The optional formulation accompanies the index of difficulty in Shannon form robustly performs the prediction better than the traditional model across studies. Finally, a new approach to modeling movement time prediction is deduced from our research results

The WASP-Index is computed over Iberia for three monthly timescales in 1961-2020, based on an observational gridded precipitation dataset (E-OBS), and in 2021-2070, based on bias-corrected precipitation generated by a six-member climate model ensemble from EURO-CORDEX, under RCP4.5 and RCP8.5. The WASP performance in identifying extremely dry or wet events, reported by the EM-DAT disaster database, is assessed for 1961–2020. An overall good agreement between the WASP spatial patterns and the EM-DAT records is found. The areolar mean values revealed an upward trend in the frequency of occurrence of intermediate-to-severe dry events over Iberia, which will be strengthened in the future, particularly for the 12m-WASP intermediate dry events under RCP8.5. Besides, the number of 3m-WASP intermediate-to-severe wet events is projected to increase, mostly the severest events under RCP4.5, but no evidence was found for an increase in the number of more persistent (12m-WASP) wet events under both RCPs. Despite important spatial heterogeneities, an increase(decrease) of the intensity, duration, and frequency of occurrence of the 12m-WASP intermediate-to-severe dry(wet) events is found under both scenarios, mainly in the southernmost regions of Iberia, thus becoming more exposed to prolonged and severe droughts in the future, corroborating the results from previous studies.

The International Roughness Index (IRI) is the standard scale for evaluating road roughness in many countries in the world. The Taipei City government actively promotes a Road Smoothing Project and plans to complete the rehabilitation of the main and minor roads within its jurisdiction. This study aims to detect the road surface roughness in Taipei City and recommend appropriate IRI thresholds for road rehabilitation. A total of 171 asphalt concrete pavement sections in Taipei City with a total length of 803.49 km were analyzed and compared by IRI. The longitudinal profile of the detected road sections was measured using an inertial profiler. The statistical analysis showed that the IRI value prior to road leveling was mainly distributed between 5 and 8 m/km, while the IRI value after road leveling was mainly distributed between 3 and 4.5 m/km. This confirms that the implementation of the Road Smoothing Project has a significant effect on improving road smoothness. Moreover, based on the analysis results, it is recommended that the IRI threshold value for road rehabilitation in Taipei City be set at 4.50 m/km.

Bio-surfactants are surface-active molecules which are produced by the wide range of microbes including bacteria, fungi, and yeast. This study was conducted to identify bio-surfactants by Bacillus subtilis combined with use of cheap substrates and industrial wastes (Mustard cake, Whey and Soya cake) which are found locally in Nepal. Bacillus subtilis, one of the most potential bio-surfactants producer; was isolated from soil sample of hydrocarbon contaminated site. Isolates were grown in a Minimal Salt Media (MSM) with 10% (v/v) mustard oil cake, whey and soya cake separately. The presence and potential of surfactant was determined by the oil spreading technique, emulsification index (%E24) and surface tension measurement. It was revealed that the surface tensions of cell free extract were 54.41, 60.02 and 56.64 mN/m for from mustard cake, whey and soya cake respectively as compared to distilled water (72.09) at 25oC. The emulsification index values are was found to be highest in engine oil from the bio-surfactant extracted from mustard cake, soya cake and whey respectively. Similarly, mustard oil showed the lowest value of emulsification index. The highest emulsification activity was shown in mustard oil i.e. 1.13 from the cell free extract from mustard oil and lowest in engine oil i.e., 0.07, by the extract from soya cake medium, when measured in spectrophotometer at 540 nm. In conclusion, strain of Bacillus subtilis was found to be the potential surface active agent producers on the mustard oil cake, which can be useful medium for various environmental, food and industrial processes.

The Body Mass Index (BMI) formula has been developed by Belgian mathematician Adolphe Quetelet and published in 1840 [1] as a law of nature and society, based on statistics about the weight and height of the population of that time, the first part of the 19^th century. He called it “social physics”. From then, for nearly two centuries, the BMI had been the most important formula describing the normal relations and ratio of weight to the square of the height for humans. The problem arises if the BMI formula, developed in the first part of the 19^th century is still good today when the type of work people perform is very different? In modern times, most people are less muscular than at the time when the BMI was developed because they do not work physically as heavy as at that time. In many cases, the Body Mass index can predict mortality, morbidity and illness but not always, for example cases such as (a) the obesity paradox for some cardiovascular problems and (b) the U shape mortality paradox as well as (c) false positive obesity diagnostic in regard to people who are strong and muscular, have low body fat percentage but are classified as obese by the BMI and (d) cases where BMI is normal but people have an “obese metabolism” (e) BMI normal but high fat percentage. The objective is to develop a formula good for all body types, a formula that makes the difference between fat and non-fat body weight such as muscle and body frame and quantifies the effect of strength and fitness, which BMI does not. Another objective is to develop a formula to predict the health risks and fitness status of people, better than BMI. The first generalizations of BMI using anthropometric metrics could be found in [2], where I discuss and analyze many formulae, developed, tested, and simulated by me, using similar new methods, accounting for body shape, physical shape and body function, making the difference between muscle mass and fat, fat and non fat body weight. Nearly all formulae and methods developed and proposed in this new model are new, never published before. Many experiments published before, in highly cited papers show that grip strength and muscle strength is a predictor of health, mortality, morbidity, endocrine and metabolic disease outside the BMI and anthropometric measures. The purpose of my formula is to explain the outcome of those experiments and create a formula which predicts these experiments [21-41].

Remote sensing has been used as an important tool for disaster monitoring and disaster scope extraction, especially for the analysis of spatial and temporal disaster patterns of large-scale and long-duration series. Based on the Google Earth Engine cloud platform, this study used MODIS vegetation index products with 250-m spatial resolution synthesized over 16 days from the period 2005–2019 to develop a rapid and effective method for monitoring disasters across a wide spatiotemporal range. Three types of disaster monitoring and scope extraction models are proposed: the normalized difference vegetation index (NDVI) median time standardization model (R_{NDVI_TM(i)}), the NDVI median phenology standardization model (R_{NDVI_AM(i)(j)}), and the NDVI median spatiotemporal standardization model (R_{NDVI_ZM(i)(j)}). The optimal disaster extraction threshold for each model in different time phases was determined using Otsu’s method, and the extraction results were verified by medium-resolution images and ground-measured data of the same or quasi-same period. Finally, the disaster scope of cultivated land in Heilongjiang Province from 2010–2019 was extracted, and the spatial and temporal patterns of the disasters were analyzed based on meteorological data. This analysis revealed that the three aforementioned models exhibited high disaster monitoring and range extraction capabilities, with verification accuracies of 97.46%, 96.90%, and 96.67% for R_{NDVI_TM(i)}, R_{NDVI_AM(i)}, and _(j)R_{NDVI_ZM(i)(j)}, respectively. The spatial and temporal disaster distributions were found to be consistent with the disasters of the insured plots and the meteorological data across the entire province. Moreover, different monitoring and extraction methods were used for different disasters, among which wind hazard and insect disasters often required a delay of 16 days prior to observation. Each model also displayed various sensitivities and were applicable to different disasters. Compared with other techniques, the proposed method is fast and easy to implement. This new approach can be applied to numerous types of disaster monitoring as well as large-scale agricultural disaster monitoring and can easily be applied to other research areas. This study presents a novel method for large-scale agricultural disaster monitoring.

The aim of this study was to introduce a new activity-based balance index by using accelerometer data. Twenty-seven junior soccer players from the Iranian premier league were selected. Four functional tests, consisting of one leg stance, dynamic Y balance, running and dribbling tests, were conducted to assess the players’ balance, activity and skill. During these four tests, besides their relative scores, the acceleration of their body center was also recorded. Activity-based balance index (ABI) was calculated using these acceleration data. The results showed positive correlations between ABI and both static and dynamic balance scores. Additionally, negative correlations were found between ABI and dribbling scores, which demonstrate the agility required for this skill. It seems that this new index achieves the evaluation of both the balance and the skill level of soccer players. Perhaps this is a new way of talent identification and also a re-development of balance tests from traditional to modern.

Recent studies of the difficulties faced by smallholder farmers in many developing countries have echoed their disconnection with formal markets. These limitations have been attributed to a number of factors including stringent quality and volume requirements, among others. While smallholder farmers seek access to formal markets, the existing alternatives through which they sell their produce remain obscure. Using an interview of market outlets and selected smallholder farmers in the area, the study applied a crop marketing index to examine the outlets currently used by farmers and the volume of potatoes sold in each. Findings indicate that smallholder farmers on average sold sixty-eight percent of their produce. The outlet mostly used by farmers was street vendors because the large supermarkets sold potatoes supplied from external sources. It would be helpful for smallholder farmers to aggregate their produce through producer and marketing cooperatives, to better engage with these formal market outlets.