Background Telomere shortening is related to aging and unfavourable health outcomes. Obesity and metabolic diseases are important factors for accelerating aging. This study aimed to find out the association between obesity, metabolic disease, and telomere length in metabolically healthy adults. Methods 237 adults were enrolled with written consents at a health promotion centre of a tertiary hospital from February 2014 to March 2015. After excluding 99 subjects who met the exclusion criterion, a total of 130 metabolically healthy subjects were selected for final analysis. The subjects were divided into quartile groups according to the telomere lengths of their oral mucosal cells. Results The subjects consisted of 66 (50.8%) males with a mean age of 58.59 years. The body mass index (BMI, kg/m2) increased significantly along with the quartile groups (Q1, 23.00; Q2, 23.96; Q3, 23.70; Q4, 25.20; P-for trend=0.008). Waist circumference (WC, P-for trend=0.022), waist-to-hip ratio (WHR, P-for trend=0.005), and waist-to-height ratio (WHtR, P=0.001) also increased along with the quartile groups. Obesity prevalence (BMI ≥25 kg/m2), abdominal obesity (WC ≥90 cm for men, ≥85 cm for women), WHR 〉1.0 for men or 〉0.85 for women, and WHtR ≥0.5 increased significantly as the telomere length increased (P-for trend <0.05). After adjusting for covariates, the ORs for each obesity markers increased as the telomere length increased (P-for trend <0.05); and the ORs of WHtR were especially meaningful (Q1, 1.00; Q2, 2.53; Q3, 2.97; Q4, 7.81; P-for trend = 0.001). There were no significant trends for metabolic syndrome and its components along with the prevalence of fatty liver disease. Conclusion Obesity markers and telomere length had significant positive correlation despite the established theory. The obesity paradox may exist in metabolically healthy adults with regard to telomere length, However, further studies with larger sample sizes for the association between obesity and telomere length are needed.

Most people living in Europe's cities are still exposed to levels of air pollution deemed harmful by the World Health Organization. In the modern world, air pollution is the foremost concern because of its impact in human health and economy. This strong connection appears gaining a lot of concern, driven by new installed low-cost electrochemical sensors monitoring systems. Highly accuracy, real-time monitoring, daily and yearly statistics, data access from experts or simple users, low-cost equipment and forecasting needs, enforce the market to develop new air quality monitoring systems using advanced technologies and protocols. In this study, a comparison via low-cost electrochemical sensors and of static, fixed site measurement monitoring station, is taking place in Athens, Greece, along with the data quality and Air Quality Index (AQI) including data accuracy and quality of data concerning adverse health effects due to air pollution. The findings presented in this work, relate to different flexible and affordable alternatives adopted during the evaluation and calibration of low-cost gas sensors for the monitoring. The significance of the positive results is particularly useful, especially considering the founding for interference, environmental conditions affections and air quality information including indexes and health recommendations for a specific location.

Scarification involves the partial removal of the seed coat on the side of the hilum, opposite the radicle, to speed up germination in acorns. The aim of this study was to determine the influence of scarification on the germination capacity of pedunculate oak acorns, selected and prepared for sowing. The diameter, length and mass of acorns were measured before and after scarification in four batches of acorns harvested from uneven-aged trees (76, 91, 131 and 161 years). The measured parameters were used to determine the correlations between acorn dimensions and mass, and to calculate the dimensional scarification index and the mass scarification index in acorns. Scarified and non-scarified acorns from every batch were germinated on sand and peat substrate for 28 days. The analyzed acorns were characterized by average size and mass. Scarification decreased acorn mass by around 22% and acorn length by around 31% on average. Scarification and the elimination of infected acorns increased germination capacity from around 64% to around 81% on average. Acorns can be divided into size groups before scarification to obtain seed material with varied germination capacity. Larger acorns with higher germination capacity can be used for sowing in container nurseries, whereas smaller acorns with lower germination capacity can be sown in open-field nurseries.

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.

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.

Rapid and extensive urbanization has adversely impacted humans and ecological entities in the recent decades through a decrease in surface permeability and the emergence of urban heat islands (UHI). While detailed and continuous assessments of surface permeability and UHI are crucial for urban planning and management of landuse zones, they have mostly involved time consuming and expensive field studies, and single sensor derived large scale aerial and satellite imageries. We demonstrated the advantage of fusing imageries from multiple sensors for landuse and landcover (LULC) change assessments as well as for assessing surface permeability and UHI emergence in Tirunelveli, Tamilnadu, India. Cartosat-2 and Landsat-7 ETM+ imageries from 2007 and 2017 were fused and classified using a Rotation Forest (RF), while surface permeability and temperature were quantified using Soil-Adjusted Vegetation Index (SAVI) and Land Surface Temperature (LST) index, respectively. Fused images exhibited higher classification accuracies than non-fused images, i.e. overall kappa coefficient values 0.83 and 0.75, respectively. We observed an overall increase of 20 km2 (45%) in the coverage of urban (dry, real estate plots and built-up) areas, while a decrease of 27 km2 (37%) for vegetated (cropland and forest) areas in Tirunelveli between 2007 and 2017. The SAVI values indicated an extensive decrease in surface permeability for Tirunelveli overall (0.4) and also for almost all LULC zones. The LST values exhibited an associated overall increase (1.30C) of surface temperature in Tirunelveli with the highest increase (2.40C) for urban built-up areas between 2007 and 2017. The SAVI-LST combined metric depicted the Southeastern built-up areas in Tirunelveli as a potential UHI hotspot, while a caution for the Western riparian zone for UHI emergence in 2017. Our results provide important metrics for surface permeability and UHI monitoring, and inform urban and zonal planning authorities about the advantages of satellite image fusion.

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.

To address three important issues related to extraction of water features from Landsat imagery, i.e., selection of water indexes and classification algorithms for image classification, collection of ground truth data for accuracy assessment, this study applied four sets (ultra-blue, blue, green, and red light based) of water indexes (NWDI, MNDWI, MNDWI2, AWEI_ns, and AWEI_s) combined with three types of image classification methods (zero-water index threshold, Otsu, and kNN) to 24 selected lakes across the globe to extract water features from Landsat-8 OLI imagery. 1440 (4x5x3x24) image classification results were compared with the extracted water features from high resolution Google Earth images with the same (or ±1 day) acquisition dates through computing the Kappa coefficients. Results show the kNN method is better than the Otsu method, and the Otsu method is better than the zero-water index threshold method. If the computational cost is not an issue, the kNN method combined with the ultra-blue light based AWEI_ns is the best method for extracting water features from Landsat imagery because it produced the highest Kappa coefficients. If the computational cost is taken into account, the Otsu method is a good choice. AWEI_ns and AWEI_s are better than NDWI, MNDWI and MNDWI2. AWEI_ns works better than AWEI_s under the Otsu method, and the average rank of the image classification accuracy from high to low is the ultra-blue, blue, green, and red light-based AWEI_ns.

Clustering algorithms for multi-database mining (MDM) rely on computing $(n^2-n)/2$ pairwise similarities between $n$ multiple databases to generate and evaluate $m\in[1, (n^2-n)/2]$ candidate clusterings in order to select the ideal partitioning which optimizes a predefined goodness measure. However, when these pairwise similarities are distributed around the mean value, the clustering algorithm becomes indecisive when choosing what database pairs are considered eligible to be grouped together. Consequently, a trivial result is produced by putting all the $n$ databases in one cluster or by returning $n$ singleton clusters. To tackle the latter problem, we propose a learning algorithm to reduce the fuzziness in the similarity matrix by minimizing a weighted binary entropy loss function via gradient descent and back-propagation. As a result, the learned model will improve the certainty of the clustering algorithm by correctly identifying the optimal database clusters. Additionally, in contrast to gradient-based clustering algorithms which are sensitive to the choice of the learning rate and require more iterations to converge, we propose a learning-rate-free algorithm to assess the candidate clusterings generated on the fly in a fewer upper-bounded iterations. Through a series of experiments on multiple database samples, we show that our algorithm outperforms the existing clustering algorithms for MDM.

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.

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.

The spatiotemporal variability of vegetation in the Middle East was investigated for the period 2001–2019 using the Moderate Resolution Imaging Spectroradiometer (MODIS) 16-day/500 m composites of the Normalized Difference Vegetation Index (NDVI; MOD13A1). The results reveal a strong increase in the NDVI coverage in the Middle East during the study period (R = 0.75, p-value = 0.05). In Egypt, the annual coverage exhibits the strongest positive trend (R = 0.99, p-value = 0.05). In Turkey, both the vegetation coverage and density increased from 2001 to 2019, which can be attributed to the construction of some of the biggest dams in the Middle East, such as the Atatürk and Ilisu dams. Significant increases in the annual coverage and maximum and average NDVI in Saudi Arabia are due to farming in the northern part of the country for which groundwater and desalinated seawater are used. The results of this study suggest that the main factors affecting the vegetation coverage in the Middle East are governmental policies. These policies can have a positive effect on the vegetation coverage in some countries such as Egypt, Saudi Arabia, Qatar, Kuwait, Iran, and Turkey.

Health of migrant is a widely studied topic. It has been argued that migrant health may deteriorate over time. Though migrants are ‘a hard to reach’ population in survey data, this paper builds on a unique dataset provided by Médecins du Monde from five countries. We study self perceived health (SPH) in connection with socio-economic and demographic factors and length of stay. Results show different results for men and women. Asylum seekers compared to other documented migrants have a worse health. Migrants with better living conditions tend to be in better health. Employment and stable accommodation has a positive effect on SPH. Women from poorer countries have a better physical SPH after 3 months of residing in the host country. This paper contributes widely to knowledge of health of migrants. Contrarily to other evidence, health of migrants tends to improve for some migrants.

In the study of QSAR/QSPR, due to high degree of predictability of pharmaceutical properties, the eccentric-connectivity index has very important place among the other topological descriptors, In this paper, we compute the exact formulas of eccentric-connectivity index and its corresponding polynomial, total eccentric-connectivity index and its corresponding polynomial, first Zagreb eccentricity index, augmented eccentric-connectivity index, modified eccentric-connectivity index and its corresponding polynomial for a class of phosphorus containing dendrimers.

Whenever vegetated areas are monitored over time, phenological changes in land cover should be decoupled from changes in acquisition conditions, like atmospheric components, sun and satellite heights, and imaging instrument. This especially holds when the multispectral (MS) bands are sharpened for spatial resolution enhancement by means of a panchromatic (Pan) image of higher resolution, a process referred to as pansharpening. In this paper, we provide evidence that pansharpening of visible/near-infrared (VNIR) bands takes advantage from a correction of the path radiance term introduced by the atmosphere, during the fusion process. This holds whenever the fusion mechanism emulates the radiative transfer model ruling the acquisition of the Earth’s surface from space, that is, for methods exploiting a multiplicative, or contrast-based, injection model of spatial details extracted from the panchromatic (Pan) image into the interpolated multispectral (MS) bands. The path radiance should be estimated and subtracted from each band before the product by Pan is accomplished. Both empirical and model-based estimation techniques of MS path radiances are compared within the framework of optimized algorithms. Simulations carried out on two GeoEye-1 observations of the same agricultural landscape at different dates highlight that the de-hazing of MS before fusion is beneficial for an accurate detection of seasonal changes in the scene, as measured by the normalized differential vegetation index (NDVI).

The importance of measuring sustainability in tourism has been significantly advancing in recent years, following the need to manage the impact of tourism on territories and hosting communities. It was further boosted by the pandemic, where sustainability has been defined as one of the central elements to restart global tourism. The ETIS model, developed by the European Commission, is a point of reference based on self-assessment, data collection and analysis by the destinations themselves. The application of ETIS toolkit has faced many challenges, especially at sub-national level, mostly related to the lack of available and updated data to feed the model. The hypothesis explored by the authors is to solve the implementation issues, developing an indicator based on the use of the Sentiment Analysis to frame e-reputation and tourism satisfaction, and further combining it with other open data sources. The Tourism Sustainability Index (TSI) can provide a scalable and geo-referenced evaluation of tourism sustainability, measuring the four pillars and sub-components referenced to ETIS criteria, applicable to any tourism destination. Results show that the TSI can be seen as a consistent and valid tool for destinations to analyze sustainability, monitor its evolution through time periods and sub-areas, and compare it to other benchmark or competitive areas.

Seaweeds are regarded as one of the valuable coastal resources because of their usage in human food, cosmetics, and other industrial items. They also play a significant role in providing nourishment, shelter, and breeding grounds for fish and many other sea species. This study introduces a newly developed seaweed enhancing index (SEI) using spectral bands of near-infrared (NIR) and shortwave infrared (SWIR) of Landsat 8 satellite data. The seaweed patches in the coastal waters of Karachi, Pakistan were mapped using SEI, and its performance was compared with other commonly used indices - Normalized Difference Vegetation Index (NDVI) and Floating Algae Index (FAI). The accuracy of the mapping results obtained from SEI, NDVI, and FAI was checked with field verified seaweed locations. The purpose of the field surveys was to validate the results of this study and to evaluate the performance of SEI with NDVI and FAI. The performance of SEI was found better than NDVI and FAI in enhancing submerged patches of the seaweed pixels what other indices failed to do.

The bulk backscattering ratio ($\tilde{b_{bp}}$) is commonly used as a descriptor of the bulk real refractive index of the particulate assemblage in natural waters. Based on numerical simulations, we analyze the impact of heterogeneity of phytoplankton cells on $\tilde{b_{bp}}$. $\tilde{b_{bp}}$ is modeled considering viruses, heterotrophic bacteria, phytoplankton, detritus, and minerals. Three study cases are defined according to the relative abundance of these different components. Two study cases represent typical situations in open ocean, outside (No-B/No-M) and inside bloom (B/No-M). The third study case is typical of coastal waters with the presence of minerals. Phytoplankton cells are modeled by a two-layered spherical geometry representing a chloroplast surrounding the cytoplasm. The $\tilde{b_{bp}}$ values are higher when heterogeneity is considered because the contribution of coated spheres to backscattering is higher than homogeneous spheres. The impact of heterogeneity is however strongly conditioned by the hyperbolic slope $\xi$ of the particle size distribution. Even if the relative concentration of phytoplankton is small (<1%), $\tilde{b_{bp}}$ increases by about 60% (for $\xi=4.3$ and for the No-B/No-M water body), when the heterogeneity is taken into account, in comparison with a particulate population only composed by homogeneous spheres. As expected, heterogeneity has a much smaller impact (about 5$\%$ for $\xi=4.3$) on $\tilde{b_{bp}}$ when minerals are added.

We have studied Juniperus oxycedrus subsp. badia in the central and southern Iberian Peninsula. Here, the macrobioclimate ranges from Mediterranean-pluviseasonal-oceanic and Mediterranean-pluviseasonal-continental, thermotype from thermomediterranean and supramediterranean. The relevés were taken following the Braun-Blanquet phytosociological methodology. A statistical treatment was applied to establish a separation among Juniperus communities. To understand the presence of Juniperus communities in territories dominated by species of the genus Quercus, we applied the formula of Thornthwaite to calculate potential evapotranspiration. The general cluster analysis clearly separates two groups of plant communities and separates the different associations in each group. All plant communities growing on rocky crests and in steeply extreme sloping areas are significantly influenced by the soil. The Ombroclimatic Index does not explain the presence of plant communities influenced by substrate: so, we propose a new Ombroedaphoxeric Index which explains the presence of the Juniperus communities in territories with a thermotype ranging from the thermo to the supramediterranean belt. The areas of distribution of Juniperus species are expanding due to the spread of rocky areas: this phenomenon causes a rise in edaphoxerophilous areas and a decrease in climatophilous one. We propose four new plant associations and with this update on their structures and floristic compositions, it is possible to make an efficient form of conservation in both territories studied (Spain and Portugal) with specific cross-border-cooperation projects.

In March 2020, several mass gathering events were related to the Falles festival in Borriana (Spain), resulting in a 536 laboratory-confirmed COVID-19 cases outbreak among participants. Our objective was to estimate anti-SARS-CoV-2 antibodies persistence six months after and factors associated with antibody response. A prospective population-based cohort study was carried out by the Public Health Center of Castellon and the Emergency and Clinical Analysis and Microbiology Services of Hospital de la Plana in Vila-real. In October 2020, sero-epidemiologic study to estimate the persistence of anti-SARS-CoV-2 antibodies by a electrochemiluminescence immunoassay (ECLIA) was implemented. We enrolled 484 (90.2%) of the 536 members of the initial outbreak cohort and detected persistent antibodies in 479 (99%) without re-infection episodes. Five participants had a negative antibody test. Factors associated with a negative result were a lower body mass index (BMI), and less contact with other COVID-19 cases. Among the 469 participants with two ECLIA tests, 96 (20.5%) had an increase of antibodies and 373 (79.5%) a decline. Increased antibodies were associated with older age, higher BMI, more severe illness, and low current smokers. After a COVID-19 infection, a high proportion of cases maintained detectable anti-SARS-CoV-2 antibodies.

Chinese investors are easily affected by hot topics on the media and Internet and likely take irrational behavior. They tend to consume rationally and invest emotionally. This research aims to analyze the Baidu index’s effect on share price of solar power industry in China. Three main models are established to identify the correlation between Baidu index and stock price of solar industry. The media index and searching index of Baidu are chosen as an independent variable to measure the influence from media and Internet, and stock price as the dependent variable. To improve and complete the analysis, Hexun index is taken into consideration as mediator variable. This study applied Multiple Linear Regression Model and VAR (Vector auto-regression) Model. The research mainly uses the tools of SPSS, Eviews and Excel to conduct data analysis. The test is based on the theories of Granger Causality, unit root test, F-test, and t-test. The research proves the relationship between the close price of stock and Baidu index, and it also created a model for further forecasting.

In 2019, the Global Burden of Disease (GBD) estimated that prostate cancer (PC) was the 16th cause of death globally in males. In Mexico, PC epidemiology has been reported for a selected number of metrics and years, although without including the most up-to-date estimates. Herein, we describe and compare the burden and trends of PC in Mexico and its 32 states from 2000 to 2019. For this, we extracted online available data from the GBD 2019 to estimate the crude and age-standardized rate (ASR per 100,000 people) of incidence, mortality, and disability-adjusted life years (DALYs). In Mexico, PC caused 27.1 thousand (95% uncertainty intervals, 20.6-36.0 thousand) incident cases, 9.2 thousand (7.7-12.7 thousand) deaths, and 161.5 thousand (122.7-219.5 thousand) DALYs in males of all ages in 2019. Among states, Sinaloa had the greatest ASR of incidence and Guerrero the highest values of deaths and DALYs. The burden of PC showed an increasing trend, although the magnitude of change differed between metrics and locations. We found both an increasing national trend and subnational variation in the burden of PC. Our results confirm the need for updated and timely estimates to design effective diagnostic and treatment campaigns in locations where the burden of PC is the highest.

We introduce a total energy and environmental evaluation method in the manufacturing industry. The method gives us a series of descriptive indexes to assess the overall environmental effect level on materials, energy, wastes and products in the life cycle process. Meanwhile, the method uses partial indexes, environmental effect factors, and correction offsets into the quantitative model to analyze the learning process and rebound effect on the energy and environment at each procedure. In this work, we choose S-shaped learning curves to describe how to decrease energy consumption and improve the technical learning by doing for recent 30 years. Also, we draw the different rebound effect curves of the total energy-environmental evaluation with technical learning method, which use the annual industrial production growth rate to show that it's significant to estimate its effect on technology changes. The ideas about the interaction of energy and production environment from material flows to energy consumption, direct us to build an example to estimate quantitatively the results with different condition factors, and realize the process improvement and develop new products.

Estimating the vehicle crashworthiness parameters experimentally is expensive and time consuming. For these reasons different modelling approaches are utilized to predict the vehicle behaviour and reduce the need for full-scale crash testing. The earlier numerical methods used for vehicle crashworthiness analysis were based on the use of lumped parameters models (LPM), a combination of masses and nonlinear springs interconnected in various configurations. Nowadays, the explicit nonlinear finite element analysis (FEA) is probably the most widely recognized modelling technique. Although informative, finite element models (FEM) of vehicle crash are expensive both in terms of man-hours put into assembling the model and related computational costs. A simpler analytical tool for early analysis of vehicle crashworthiness could greatly assist the modelling and save time. In this paper a simple piecewise LPM composed of a mass-spring-damper system, is used to estimate the vehicle crashworthiness parameters, focusing on the dynamic crush and the acceleration severity index (ASI). The model is first calibrated against a full-scale crash test and a FEM, post-processed with the LS-DYNA software, at an impact velocity of 56 km/h. The genetic algorithm is used to calibrate the model by estimating the piecewise lumped parameters (stiffness and damping of the front structure of the vehicle). After calibration, the LPM is applied to a range of velocities (40, 48, 64 and 72 km/h). The predictions for crashworthiness parameters from the LPM were compared with the predictions from the FEA and the results are much similar. It is shown that the LPM can assist in crash analysis, since LPM has some predictive capabilities and requires less computation time in comparison with the explicit nonlinear FEA.

The reconstruction of land use practices in hyper arid Saharan Africa is often hampered by the accuracy of the available tools and by unconscious biases that see these areas as marginal and inhospitable. Considered for a long time the living space of pastoral mobile communities, new research is showing of agriculture might have been more important in these areas than previously thought. In this paper, after a review of present-day land use strategies in Saharan Africa, we show how ethnographic and ethnoarchaeological data can offer us a different point of view and help in better defining land use and food production strategies in this area. Ultimately, these insights can be integrated into the ongoing effort of reconstructing past land use globally.

Individuals residing in more deprived areas have a lower diet quality. While several studies have shown that individuals with a lower diet quality have a higher mortality risk, a low quality diet might also lead to poor health in highly deprived areas. We aimed to examine the association between deprivation within an area and all-cause mortality risk according to diet quality. Methods: We conducted a population-based prospective study on 27994 men and 33273 women aged 45–75 years. Neighborhood deprivation was assessed using the Japanese areal deprivation index (ADI). Dietary intakes were assessed using a validated 147-item food frequency questionnaire. Subsequently, Japanese Food Guide Spinning Top scores were calculated. Hazard ratios (HR) and 95% confidence intervals (CI) of mortality were calculated according to tertiles of ADI by diet quality score. Results: Individuals residing in the most deprived area had the lowest dietary scores. During the 16.7-year follow-up, compared to individuals with a high quality diet residing in the least deprived area, individuals with a low quality diet had a higher risk of mortality according to increment of ADI (P trend = 0.02); the multivariate adjusted HR (95% CI) was 1.07 (1.00-1.15), 1.15 (1.07-1.24), and 1.18 (1.08-1.29) in those residing in the lowest through the highest third of ADI, respectively. However, individuals with a high quality diet had no significant association between ADI and mortality (P trend =0.87). Conclusion: A well-balanced diet may prevent early death associated with neighborhood socioeconomic status among those residing in highly deprived areas.

A study of the water quality of the Adolfo López Mateos Reservoir (ALMD) was developed through different indicators from a spatial and seasonal perspective. Variables related to the general characteristics of water quality, trophic level and ecological risk were assessed through the water Quality Index (WQI_NSF-BROWN), Trophic State Index (TSI_CARLSON) and the Ecological Risk Index (RI_HAKANSON). Using data from physical, chemical and biological parameters obtained from four sampling points in the ALMD, the water quality was assessed in each model used. The results indicated that the reservoir presents a water quality classified as “medium” (WQI_NSF-BROWN = 70), where significant variations in the concentrations of some parameters are observed. The reservoir showed a general trophic state classified as “Mesotrophic” (TSI_{GENERAL-AVERAGE} = 43.04). The ecological risk analysis achieved the best classification of the methodology, discarding contamination by heavy metals in surface waters. Through this type of applied methodologies will help as decision making tools in the dam, as well as for application in other dams in the region.

This paper focuses on the physical attributes of land that intrinsically limit land use and possibly affect land values. In particular, we investigate if the slope of a land does decrease its price and investigate the role of land slope in forming more reliable constant-quality land price indices and aggregate house price indices. We find that, while land slopes do decrease the land price per unit, they have a small effect on the quality-adjusted land price indices in selected neighborhoods in Auckland, New Zealand, where sloped terrain is common.

This study will investigate different signals and events/news that determined the stock market's movements. As we know, many factors affect the stock market on a daily, weekly, and monthly basis, e.g., rate of interest, exchange rate, and oil prices, etc. Our research will investigate the impact of daily events/news in the KSE-100 index due to several policies announced and events/news in the country because the daily movements in the stock market can be determined only by different signals and events/news. Time series data is collected daily for particular reasons from "The News" (Daily Newspaper, Sunday edition) from 2010 to 2019. The results of this study show that political and global news affects the stock market index ferociously. For investors, the investment in blue chips is not less than a safe haven. When day-to-day transactions are concerned, there is always a higher panic attack than the herd behaviour in the stock exchange. Investors tend to make prompt responses to negative rather than positive news, which makes them risk averters. Our finding also confirmed that the ARCH/GARCH model is better than the simple OLS method concerning stock market upheaval.

Remote sensing and Geographical Information System (GIS) have played an important role in exploration and management of groundwater resources. In this study, we present modeling of groundwater potential zone in Khoyrasol block in Birbhum district, West Bengal by using remote sensing and GIS techniques. The objective of the study is to explore groundwater as well as surface water availability in different geomorphic units. Different thematic maps of geology, hydro-geomorphology, lineament, slope, land use/land cover (LULC), depth to water level and soil maps are prepared and groundwater potential zones are obtained by overlaying all thematic maps in terms of Weightage Index Overlay (WIO) method. All the thematic map classes have been assigned weightage according to their role in groundwater occurrence. Finally, groundwater potential zones are classified into four categories viz., excellent, good to medium, medium to poor and poor. The outcome of the present research work will help the local farmers, decision-maker, researchers and planners for exploration, monitoring, and management of groundwater resources for this study area.

In manual maintenance inspections of large-scaled photovoltaic (PV) or rooftop PV systems, several days are required to survey the entire PV field. To improve reliability and shorten the amount of time involved, this study proposes an electrical examination based method for locating multiple faults in the PV array. The maximum power point tracking (MPPT) algorithm is used to estimate the maximum power of each PV panel; this is then compared with metering the output power of PV array. Power degradation indexes are parameterized to quantify the degradation between maximum power and metered output power. Bidirectional hetero-associative memory (BHAM) networks are then used to locate multiple faults within the entire PV field. For a rooftop PV system with two strings, as seen in Figure 1, experimental results demonstrate that the proposed model has computational efficiency for real-time applications and that its algorithm is easily implemented in a mobile intelligent vehicle.

The Geostationary Ocean Color Imager (GOCI) of the Communication, Ocean, and Meteorological Satellite (COMS) increases the chance of acquiring images with greater clarity at eight times a day and is equipped with spectral bands suitable for monitoring crop yield with a moderate spatial resolution. The objectives of this study were to classify nationwide paddy fields and to project rice (Oryza sativa) yield and production using the grid-based GRAMI-rice model and GOCI satellite products over South Korea from 2011 to 2014. Solar insolation and temperatures were obtained from COMS and the Korea local analysis and prediction system for model inputs, respectively. The paddy fields and transplanting dates were estimated using Moderate Resolution Imaging Spectroradiometer (MODIS) reflectance and land cover products. The crop model was calibrated using observed yield data in 11 counties and was applied to 62 counties in South Korea. The overall accuracies of the detected paddy fields ranged from 89.5 to 90.2%. The simulated rice yields statistically agreed with observed yields, with root-mean-square errors of 0.219 to 0.451 ton ha-1 and Nash–Sutcliffe efficiencies of 0.241 to 0.733 in four years, respectively. According to paired t-tests (α = 0.05), the simulated and observed rice yields were not significantly different. These results demonstrate the possible development of a crop information delivery system that can classify land cover, simulate crop yield, and monitor regional crop production on a national scale.

Silicon-based photonic integrated circuit (PIC) is a research focus in producing high-density photonics. One of the potential applications of silicon PIC is the sensing and measurement system. In this work, we use the one-dimensional photonic crystal (1D-PhC) cavity design which and utilize it at the PIC level design. The 1D PhC design used as the compact model has the same characteristics as experimentally demonstrated in previous works. The compact model is made from the S-parameter extraction of the 1D-PhC device which is done by using Lumerical FDTD software. The PIC design integrates the 1D-PhC device as a sensing component with a PN-phase shifter (PN-PS) to function as a refractive index (RI) sensor calibration or tuning circuit. A custom design of PN-PS device is used by simulating and extracting the bias voltage-effective index (bias-Neff) data by using Lumerical DEVICE and MODE into the circuit simulator. The circuit-level simulation is done by using Lumerical Interconnect software. Finally, we show the GDSII layout design of the 1D-PhC based photonic sensor calibration circuit with an analysis of generic silicon PIC design rules. The designed PIC is applicable for the bio-sensing applications and photonic SOC component. This work also shows the promise of PIC design approach for further PIC development.

The current study investigated the use of two-dimensional spatial distribution mapping representing the chlorophyll-a level in a river generated via an unmanned aerial vehicle (UAV) and an unmanned surface vehicle (USV). A domestically developed UAV (Remo-M, Uconsystem Inc., Korea) and a USV developed by our research team were used to collect data from the Nae Seong stream in Korea. An adaptation of the “Data Cleaner” tool was developed and used for USV data processing and analysis. The operation of the autonomous USV was successful. Four previously described indices for quantifying algal blooms in rivers were utilized to create chlorophyll-a images, the normalized difference vegetation index (NDVI), the normalized green red difference index, the green normalized difference vegetation index (GNDVI), and the normalized difference red edge index. The suitability of the linear regression analysis of the correlation between the spectral indices obtained using the UAV and the in situ chlorophyll-a data obtained using the USV was evaluated with the coefficient of determination (R2) at a significance level of p &lt; 0.001. In field application and correlational analysis the NDVI was strongly correlated with chlorophyll-a (R2 = 0.88, p < 0.001), and the GNDVI was moderately correlated with chlorophyll-a (R2 = 0.74, p < 0.001). The map of chlorophyll-a was successfully quantified using the UAV and USV hybrid platforms.

Globally, saline lakes occupying 23% by area 44% by volume among all the lakes might desiccate by 2025 due to agricultural diversion, illegal encroachment, pollution, and invasive species. India’s largest saline lake, Sambhar is currently shrinking at the rate of 4.23% due to illegal saltpan en-croachment. This research article aims to identify the trend of migratory birds and monthly wetland status. Birds survey was conducted for 2019, 2020 and 2021 and combined with literature data of 1994, 2003, and 2013 for visiting trend, feeding habit, migratory and resident ratio, and ecological diversity index analysis. Normalized Difference Water Index was scripted in Google Earth Engine. Results state that it has been suitable for 97 species. Highest NDWI values for the was whole study period was 0.71 in 2021 and lowest 0.008 in 2019 which is highly fluctuating. The decreasing trend of migratory birds coupled with decreasing water level indicates the dubious status for its existence. If the causal factors are not checked, it might completely desiccate by 2059 as per its future prediction. Certain steps are suggested that might help conservation. Least, the cost of restoration might exceed the revenue generation.

The gravel road pavement has a lower construction cost but poorer performance than the asphalt surface. It also emits dust and deforms under the impact of vehicle loads and ambient air factors. The resulting ripples and ruts are constantly deepening, increasing vehicle vibrations and fuel consumption, reducing safe driving speed and comfort. In this article, existing pavement quality evaluation indexes are analysed, and a methodology for their adaptation for roads with gravel pavement is proposed. This article reports the measured wave depth and length of the gravel pavement profile by the straightedge method of a 160 m long road section in three road exploitation stages. The measured pavement elevation was processed according to ISO 8608, and vehicle frequency response has been investigated using simulations in MATLAB/Simulink. The applied International Roughness Index (IRI) analysis showed that a speed of 30-45 km/h instead of 80 km/h provides the objective results of IRI calculation on the flexible pavement due to a decreasing velocity of vehicle's unsprung mass on a more deteriorated road pavement state. The influence of the corrugation phenomenon of gravel pavement has been explored, identifying specific driving safety and comfort cases. Finally, an increase in the Dynamic Load Coefficient (DLC) at a low speed of 30 km/h on the most deteriorated pavement and a high speed of 90 km/h on the middle-quality pavement demonstrates the demand for timely gravel pavement maintenance and the complicated prediction of a safe driving speed for drivers.

With the development of general anesthesia techniques and anesthetic substances, brought new horizons for the expansion and improvement of surgical techniques. Nevertheless, more complex surgical procedures brought a higher complexity and longer duration for general anesthesia that led to a series of adverse events such as hemodynamic instability, under- or overdosage of anesthetic drugs, as well as an increased number of post-anesthetic events. In order to adapt the anesthesia according to the particularities of each patient, the multimodal monitoring of these patients is highly recommended. Classically, general anesthesia monitoring consists of the analysis of vital functions and gas exchange. Multimodal monitoring refers to the concomitant monitoring of the degree of hypnosis and the nociceptive-antinociceptive balance. By titrating anesthetic drugs according to these parameters, clinical benefits can be obtained, such as hemodynamic stabilization, reduction of awakening times, and the reduction of post-operative complications. Another important aspect is the impact on the status of inflammation and the redox balance. By minimizing inflammatory and oxidative impact one can achieve a faster recovery that will lead to both increased patient satisfaction and an increase in patient safety. The purpose of this literature review is to present the most modern multimodal monitoring techniques, respectively to discuss the particularities of each technique.

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.

The topological index is a numerical quantity based on the characteristics of various invariants or molecular graph. For ease of discussion, these indices are classified according to their logical derivation from topological invariants rather than their temporal development. Degree based topological indices depends upon the degree of vertices. This paper computes Zagreb polynomials and redefined first, second and third Zagrebindices of Bismuth Tri-Iodide chains and sheets.

This paper deals with the study of the existence and non existence of solutions of a three parameter's family of nonlinear fractional differential equation with mixed-integral boundary value conditions. We consider the $\alpha$-Riemann-Liouville fractional derivative, with $\alpha \in (1,2]$. In order to deduce the existence and non existence results, we first study the linear equation, by deducing the main properties of the related Green's functions. We obtain the optimal set of parameters where the Green's function has constant sign. After that, by means of the index theory, the nonlinear boundary value problem is studied. Some examples, at the end of the paper, are showed to illustrate the applicability of the obtained results.

This article investigates if public investments in rural basic infrastructure represent the best strategy for boosting the local economy of rural communities from Romania. The article focuses on one specific program implemented under the Cohesion policy in the framework of the National Plan for Rural Development called Measure 322. Geographically, the research included a sample of rural communes from the North-Western Region of Romania. Moreover, the study also looks at other determinants of local economic development (LED) than infrastructure investments, with a focus on certain feature characterizing Romanian rural communities such as population size, isolation from urban centers, connection with European and national roads networks, educational stock, etc. The research included three steps, namely the construction of the LED Index, a cvasi-experimental research, and a regression model. Our main findings seem to suggest that while investments in infrastructure help the development gap between beneficiaries and non-beneficiaries remains relatively the same. In terms of determinants of LED, percentage of population with a university degree and connection to a European road are the most significant in the Romanian rural context.

Maize (Zea mays subsp. mays) is the staple food crop in the world. In this study, multi-layer perceptron (MLP), support vector machine (SVM), genetic algorithm-based multi-layer perceptron (MLP-GA), and genetic algorithm-based support vector machine (SVM-GA) hybrid artificial intelligence algorithms were used for the prediction of drought tolerance and stress tolerance indices in teosinte maize lines. Correspondingly, the gamma test technique was applied to determine efficient input and output vectors. The potential of developed models was evaluated based on statistical indices and graphical representation. Results of gamma test based on the least value of gamma and standard error indices show that day of anthesis (DOA), day of silking (DOS), yield index (YI), and gross yield per plant (GYP) information vector arrangements were determined as efficient information vector combination for drought-tolerant index (DTI) as well as the stress-tolerant index (STI). The results of MLP, SVM, MLP-GA, and SVM-GA algorithms were compared based on statistical indices and visual interpretation that have satisfactory for prediction of the drought-tolerant index and stress-tolerant index in maize crop. It has also seemed that genetic algorithm-based hybrid models (MLP-GA and SVM-GA) were found a better prediction of the drought-tolerant index and stress-tolerant index in maize crop. Similarly, the SVM-GA model has the highest potential to forecast the DTI and STI in maize crops as compared to MLP, SVM, MLP-GA models.

Topological indices are numerical parameters of a graph which characterize its topology and are usually graph invariant. In this paper, bounds for the Randić, general Randić, sum-connectivity, the general sum-connectivity and harmonic indices for tensor product of graphs are determined by using the combinatorial inequalities and combinatorial computing.

Cost estimating based on building cost index plays an important role in project planning and management by providing accurate cost information. Recently, tremendous advances in cost estimating has been made but serious inaccuracies in it are still too frequently witnessed. This study aims to improve estimating accuracy for residential building costs in New Zealand. In this study, the New Zealand house prices index is involved in the transfer function models to produce forecasts of building costs for one-storey house, two-storey house, and town house in New Zealand. To demonstrate the effectiveness of the proposed models, this study compares the estimate results of the transfer function models with the univariate ARIMA models. The results indicate that the proposed transfer function models can achieve better outcomes than ARIMA models by considering the causality between building costs and New Zealand house prices. During the modelling process, the better cost estimation approach can be identified, and the movements of building costs are shown.

Temperature-index modeling is used to determine the magnitude of temperature depression in the northern Sawatch Range required to maintain steady-state mass balances of six reconstructed glaciers at their extent during the local Last Glacial Maximum (LLGM), dated at ~21 ka. Assuming no significant differences in precipitation compared to modern values, mean annual temperatures in the region were on average 8.8 +0.5/–0.8 °C cooler than they are today. Allowing for modest increases or decreases in precipitation, required temperature depressions only differ by ± 0.2 °C. Temperature depression in the northern Sawatch Range are consistent, although slightly greater, with those determined in other ranges in Colorado using similar approaches. The estimates presented here are, however, substantially less than those suggested by several downscaled simulations of global LGM climate, that might be due to the need for improved calibration of such downscalings, or the models from which they are derived. Our estimates of LGM temperature depression are considerably greater than that previously determined in the study area and those in two other ranges in Colorado derived using different methodologies, the latter being most likely responsible for the discrepancies.

Let G[F,Vk, Huv] be the graph with k pockets, where F is a simple graph of order n ≥ 1,Vk= {v1,v2,··· ,vk} is a subset of the vertex set of F and Hvis a simple graph of order m ≥ 2,v is a specified vertex of Hv. Also let G[F,Ek, Huv] be the graph with k edge pockets, where F is a simple graph of order n ≥ 2, Ek= {e1,e2,···ek} is a subset of the edge set of F and Huvis a simple graph of order m ≥ 3, uv is a specified edge of Huvsuch that Huv− u is isomorphic to Huv− v. In this paper, we derive closed-form formulas for resistance distance and Kirchhoff index of G[F,Vk, Hv] and G[F,Ek, Huv] in terms of the resistance distance and Kirchhoff index F, Hv and F, Huv, respectively.

This paper proposes a method for monitoring the structural health of concrete bridges in Iran. In this method, the bridge condition index (BCI) of bridges is determined by the analytical hierarchy process. BCI constitutes eight indices that are scored based on the experts' views, including structural, hydrology and climate, safety, load impact, geotechnical and seismicity, strategic importance, facilities, and traffic and pavement. Experts' views were analyzed by Expert Choice software, and the relative importance (weight) of indices were determined using the analytical hierarchy process (AHP). Then, the gave scores of experts were assigned to indices for various conditions. Bridge inspectors can examine the bridge, determine the scores of indices, and compute BCI. Higher values of BCI ​​indicate better conditions. Therefore, bridges with lower BCI take priority in maintenance activities. Five bridges in Iran, Semnan province, were selected as the case studies, and BCI calculation of these bridges was conducted.

Fire-tolerant eucalypt forests of south eastern Australia are assumed to fully recover from even the most intense fires but surprisingly very few studies have quantitatively assessed that recovery. Accurate assessment of horizontal and vertical attributes of tree crowns after fire is essential to understand the fire’s legacy effects on tree growth and on forest structure. In this study, we quantitatively assessed individual tree crowns 8.5 years after a 2009 wildfire that burnt extensive areas of eucalypt forest in temperate Australia. We used airborne lidar data validated with field measurements to estimate multiple metrics that quantified the cover, density, and vertical distribution of individual-tree crowns in 51 plots of 0.05 ha in fire-tolerant eucalypt forest across four wildfire severity types (unburnt, low, moderate, high). Significant differences in the field-assessed mean height of fire scarring as a proportion of tree height, and in the proportions of trees with epicormic (stem) resprouts were consistent with the gradation in fire severity. Linear mixed-effects models indicated persistent effects of both moderate- and high-severity wildfire on tree crown architecture. Trees at high-severity sites had significantly less crown projection area and live crown width as a proportion of total crown width than those at unburnt and low-severity sites. Significant differences in lidar-based metrics (crown cover, evenness, leaf area density profiles) indicated that tree crowns at moderate- and high-severity sites were comparatively narrow and more evenly distributed down the tree stem. These conical-shaped crowns contrasted sharply with the rounded crowns of trees at unburnt and low-severity sites, and likely influenced both tree productivity and the accuracy of biomass allometric equations for nearly a decade after the fire. Our data provide a clear example of the utility of airborne lidar data for quantifying the impacts of disturbances at the scale of individual trees. Quantified effects of contrasting fire severities on the structure of resprouter tree crowns provide a strong basis for interpreting post-fire patterns in forest canopies and vegetation profiles in lidar and other remotely-sensed data at larger scales.

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.

Temperature-index modeling is used to determine the magnitude of temperature depression on the Blanca Massif, Colorado, required to maintain steady-state mass balances of nine reconstructed glaciers at their extent during the Last Glacial Maximum (LGM). The mean temperature depression thus determined is ~8.6 +0.7/–0.9 °C where the uncertainties account for those inherent in the glacier reconstructions, in model parameters (e.g. melt factors), and possible modest changes in LGM precipitation. Associated equilibrium-line altitudes (ELAs) exhibit a statistically significant directional dependency being lower toward the north and east. Under the assumption that regional temperature change was uniform, required changes in precipitation vary systematically – also exhibiting a directional dependency coinciding with that in ELAs – and indicate increases (over modern) occurred on the eastern side of the massif while decreases occurred on the western side. This disparity represents a strengthening of a precipitation asymmetry, particularly winter precipitation, that exists today. The modern precipitation asymmetry may be a consequence of snow being blown over to the eastern side of the massif (advective transport) by southwesterly flow. Intensification of this flow during the LGM would have enhanced advection, and augmented snow accumulation on glaciers, thus explaining the lower ELAs and increased precipitation on that side of the massif.

Considering increasingly ambitious pledges by countries, pressure from society, investors, and clients further up the supply chain, the question for companies is not so much whether to take decarbonisation action, but what action and by when. However, determining an ideal mix of measures to apply ‘decarbonisation efficiency’ requires more than knowledge of technically feasible measures and how to combine them to achieve the most economic outcome: In this paper, the author describes seven aspects which heavily influence the composition of an ‘ideal mix’ that executive leadership needs to take a (strategic) position on. These aspects consider underlying motivations and span across (socio-)economic, technical, regulatory, strategic, corporate culture and environmental factors and further underline the necessity of clarity of definitions. How these decisions influence the determination of the decarbonisation-efficient ideal mix of measures, both in principle but also in terms of specific impact is further explored by providing examples. What choices are taken by German manufacturers in several of the aspects is disclosed by insights from about 850 responses to the ‘Energy Efficiency Index of German Industry’. Knowledge of the status quo, and clarity in definitions, objectives, time frames and scope are key.

Ensuring equal access to affordable higher education for women and men has become a crucial target of UNESCO’s SDG4-Education 2030. Currently, about one-third of the world's college-age population participates in higher education, while the gender disparity persists in various systems. This study employed GDP per capita, gross enrollment ratio (GER), and the gender parity index (GPI) to demonstrate how the education systems have expanded resulting in the transformation of gender parity. We selected Japan, Korea, Taiwan, and the UK as research targets using a cross-correlation function and trend analysis to detect concurrent relationships and future trends with GDP per capita, GER, and GPI. The findings suggest Japan, Korea, and the UK continue to show gender disparity and need to respond to this issue in their policy intervention for SDG4-Education 2030. The results reveal a potential problem in the UK when GPI growth might become unlimited with females dominated. This study suggests the higher education expansion phenomenon and gender diversity in mass and universal systems can be detected by the trend analysis with GDP per capita, GER, and GPI in different settings. The design of the study provides an example to explore the gender diversity patterns in higher education systems for sustainable development.

Mapping drought from space using, e.g., surface soil moisture (SSM), has become viable in the last decade. However, state of the art SSM retrieval products suffer from very poor coverage over northern latitudes. In this study, we propose an innovative drought indicator with a wider spatial and temporal coverage than that obtained from satellite SSM retrievals. We evaluate passive microwave brightness temperature observations from the Soil Moisture and Ocean Salinity (SMOS) satellite as a surrogate drought metric, and introduce a Standardized Brightness Temperature Index (STBI). The STBI is validated against drought indices from a land surface data assimilation system (LDAS-Monde), two satellite dervied SSM indices and a standardized precipitation index. Finally, we evaluate the STBI against the before mentioned drought indices in a case study of the 2018 Nordic drought. The STBI is found to be superior to the drought index created from satellite derived SSM in both spatial and temporal coverage over the Nordic region. Our results indicate that when compared to drought indices from precipitation data and a land data assimilation system, the STBI is able to capture the 2018 drought onset, severity and extent. Thus, the STBI index could provide additional information for drought monitoring in regions where the SSM retrieval problem is difficult.

Keywords: flow mediated skin fluorescence; FMSF technique; NADH fluorescence, microcirculation, flowmotion, reactive hyperemia response, RHR, hypoxia sensitivity, HS, normoxia oscillatory index, NOI

Background: Ultrasound measurement of dynamic changes in inferior vena cava (IVC) diameter and collapsibility index (CI) evaluates to estimate the fluid responsiveness and intravascular volume status. We conducted a analysis to quantify the sonographic measurement of IVC diameter changes in adult patients at preoperative and postoperative period. Methods: Ultrasonography was performed on 72 patients scheduled for surgery with American Society of Anesthesiologists physical status I to III. Quantitative assessments of the end-expiration (D_min), end-inspiration (D_max) and CI at preoperative and postoperative period were compared in a prospective, observational study. The patients received intravenous fluid according to standard protocol regimes peroperatively. The cutt-off value of dIVC 40% was accepted as hypovolemia. Results: Ultrasonography of IVC measurement was unsuccessful in 12.5% of patients and 63 patients remained for analyses. The mean age was 43.29 ± 17.22 (range 18 - 86) years. The average diameter of the D_min, D_max and dIVC at preoperative and postoperative were 1.99 ± 0.31 vs. 2.05 ± 0.29 cm, 1.72 ± 0.33 vs. 1.74 ± 0.32 cm, 14.0 ± 9.60 % vs. 15.14 ± 11.18 %, respectively (p<0.05). Using a threshold dIVC of 40%, one patient preoperatively and 5 postoperatively were hypovolemic (p<0.05). CI was also positively associated preoperatively and postoperatively (regression coefficient = 0.438, p<0.01). Conclusion: The diameter of IVC did not change preoperatively and postoperatively in adult patients with standard fluid regimens. The parameters of the IVC diameter increased postoperatively according to preoperative period.

This work has the purpose to demonstrate that if an adequate melt treatment is applied, it is pos-sible to obtain recycled aluminium alloy AlSi10MnMg(Fe) with as good metal cleanliness than primary AlSi10MnMg alloy. The melt quality is assessed by the thermal analysis, density index, macro- and micro-inclusions tests, of one primary and two secondary alloys, before and after the melt treatment. The melt treatment is based on deoxidation, degassing and skimming with de-tailed procedure described in this article. The different analysis are: Thermal analysis to compare the variables of the solidification cooling curve (Al primary temperature and its undercooling; Al-Si eutectic temperature and its recalescence); Density index is used to evaluate the hydrogen gas content in the melt; Macroinclusions level is analysed after solidifying the melt under vacuum of 5 mbar, favouring inclusion floatation to the sample surface; Microinclusion level is evaluate with porous disc filtration apparatus (similar to PoDFA).

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.

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.

Stroke represents one of the most important causes of morbidity ( eighty million patients with disabling of ongoing effects of stroke at a given time, globally) and mortality (the second leading cause of death) worldwide. Innovative systems biology-based approach is likely to increase the understanding of the underpinning of acute stroke promise to enhance stroke prevention, acute treatment, and neurorehabilitation. Recent growing body of evidence with shared pathobiology with COVID-19 and the critically important role of inflammation in the context of stroke points to far-reaching consequences of acute stroke, just as in the case of COVID-19 ( post-acute event issues as well as long term issues ) . So far, stroke typically defined by late-appearing disease manifestation by the range of stroke subtypes as defined by the WHO or American Stroke Association. This definition neglects the underlying pathobiological mechanisms such as low-grade chronic inflammation and already compromised vascular system. Diseases such as stroke is hardly a simple result of a single problem, but rather a complex cascade of pathobiological processes and interactions in a complex biochemical environment. The evidence of changes in innate immunity and adaptive immunity during the index event of acute stroke and recovery over next 3-12 months can be easily elicited with simple bedside blood tests such as neutrophil-lymphocyte ratio (NLR) with well over 300 published papers including several systematic reviews and meta-analyses confirming this. Global standard operating procedures (SOP) of stroke care dictated by the national and international stroke guidelines at present. It is imperative to explore the evidence of systems biology approach in current stroke guidelines. This is likely to be a key turning point in managing stroke across the continuum (prevention, management of acute event and rehabilitation).

This paper proposes a new non-radial biennial Luenberger energy and environmental performance index (EEPI) to measure the EEP change in various Chinese cities. The sources of EEP change, in terms of technical efficiency change and technological change, are examined by Luenberger EEPI. The contributions from specific undesirable outputs and energy inputs to the EEP change are identified by means of the non-radial efficiency measure. The proposed approach is applied to evaluate the EEP of the industrial sector in 283 cities in China over 2010-2014. Factors influencing the emission abatement potential are investigated by employing geographically weighted regression (GWR) model. We find that 1) changes in EEP can be attributed to technological progress but that technological progress slows down across the study period; 2) the soot emission performance experiences a downtrend among four specific sub-performances in line with the truth that severe haze happened frequently in China; 3) the best performers begin to move from the coastal to inland cities with the less resource consumption and higher ecological equality; 4) cities with the strongest positive effect in regards to pollution intensity on emission abatement potential are located in the areas around the Bohai Gulf, where air pollution is particularly severe.

Road networks are monitored to evaluate their decay level and the performances regarding ride comfort, vehicle rolling noise, fuel consumption, etc. In this study, an Inertial Measurement Unit is proposed by using a low-cost three-axis Micro-Electro-Mechanical Systems accelerometer and a GPS instrument, which are connected to a Raspberry Pi Zero W board and embedded inside a vehicle to monitor indirectly the road condition. To assess the level of pavement decay, the comfort index awz defined by the ISO 2631 standard was considered. Considering 21 km of roads, with different levels of pavement decay, validation measures made using the proposed IMU, another pre-assembled IMU, and a Road Surface Profiler were performed. Therefore, comparisons between awz determined with accelerations measured on the two different IMU are made; in addition, also correlations between awz, International Roughness Index (IRI), and Ride Number (RN) were performed. The results were shown very good correlations between the awz calculated with the proposed IMU and ones in the other IMU. In addition, the correlations between awz and IRI and RN were showed promising results, considering the use and the costs of the proposed IMU as a reliable method to assess the pavements decay in road networks where the use of traditional systems is difficult and/or not cheap.

Background: Intelligence quotient (IQ) is a measure of intellectual ability of performing, comprehension, and learning. Previous studies reported that intelligence measures predict various measures of job performance and income. Emotional awareness (EA) is the measure of emotional capacity to recognize and make sense of one’s emotions, as well as those of others. A high level of emotional awareness (EA) indicates one can learn from expressed emotions quickly. Both IQ and EA are important for personal and professional success.Objective: This study tests the hypothesis that the average national income rank is best predicted by the combined effect of the population's average intelligence quotient (one's ability to perform and learn) and emotional awareness (ability to recognize and make sense of emotions).Method: The population’s average intelligence quotient (IQ), emotional awareness (EA), and indices of good governance, which include corruption perception index and educational expenses for each country, were obtained from public data sources. The outcome variable was per capita gross national income. All the variables that are statistically significant in univariate analysis were included in the multivariate regression analyses but excluded from the final model if not statistically significant.Result: The total number of countries included in the final analysis was 81 because of missing values in different variables. Intelligence quotient (IQ) and emotional awareness (EA) were found to be highly correlated, at 0.77 and 0.32 respectively, with the per capita gross national income. The independent effects of intelligence quotient (IQ) and emotional awareness (EA) were found significant in the multivariate model after adjusting for measures of good governance. The R square value for the final multivariate model was 0.82. The corruption perception index (CPI) and educational expenses were strongly correlated with other measures of good governance such as democracy index, functioning of government, electoral process and pluralism, political participation, and civil liberty, but these variables were found not significant in the multivariate model. Conclusion: The study concludes the effect of intelligence quotient (IQ) and emotional awareness (EA) are complementary to each other but intelligence quotient (IQ) is a stronger predictor than emotional awareness (EA) for gross national income or wealth. We also find that indicators of good governance, including corruption perception index and educational expenses, have important associations with per capita gross national income. This study implies a nation may build more wealth if the educational system focuses on developing emotional awareness in addition to intelligence. The study concludes the effect of intelligence quotient (IQ) and emotional awareness (EA) are complementary to each other but intelligence quotient (IQ) is a stronger predictor than emotional awareness (EA) for gross national income or wealth. We also find that indicators of good governance, including corruption perception index and educational expenses, have important associations with per capita gross national income. This study implies a nation may build more wealth if the educational system focuses on developing emotional awareness in addition to intelligence.

Recently, the relationship between emotional arousal and depression has been studied. Focusing on this relationship, we first developed an arousal level voice index (ALVI) to measure arousal levels using the Interactive Emotional Dyadic Motion Capture database. Then, we calculated ALVI from the voices of depressed patients from two hospitals (Ginza Taimei Clinic [GTC] and National Defense Medical College hospital [NDMC]) and compared them with the severity of depression as measured by the Hamilton Rating Scale for Depression (HAM-D). Depending on the HAM-D score, the datasets were classified into a no depression (HAM-D&lt;8) and a depression group (HAM-D≥8) for each hospital. A comparison of the mean ALVI between the groups was performed using the Wilcoxon rank-sum test and a significant difference at the level of 10% (p = 0.094) at GTC and 1% (p = 0.0038) at NDMC was determined. The area under the curve (AUC) of the receiver operating characteristic was 0.66 when categorizing between the two groups for GTC, and the AUC for NDMC was 0.70. The relationship between arousal level and depression severity was indirectly suggested via ALVI.

Management practices must be developed to improve yam production sustainability. Image-based phenotyping techniques could help developing such practices based on non-destructive analyses of important plant traits. Our objective was to determine the potential of image-based phenotyping methods to assess traits relevant for tuber yield formation in yam grown in glasshouse and field. We took plant and leaf pictures with consumer cameras. We used the numbers of image pixels to derive the shoot biomass and the total leaf surface and calculated the ‘triangular greenness index’ (TGI) which is an indicator of the plant nitrogen (N) nutritional status. Under glasshouse conditions, the number of pixels obtained from nadir view (image taken top down) was positively correlated to the shoot biomass, and the total leaf surface, while the TGI was negatively correlated to the N content of diagnostic leaves. Under field conditions, pictures taken from the nadir view showed an increase in soil surface cover and a decrease in TGI with time. TGI was negatively correlated to SPAD measured on specific leaves but was not correlated to the N content of these leaves. In conclusion, these phenotyping techniques deliver relevant results but need to be further developed and validated for application in yam.

To investigate this suitability of Black Mustard (Brassica Nigra L.) and Camelina (Camelina Sativa L.) for pulp manufacturing the nitrate-alkaline method was used. The non-wood plants were characterized by chemical analysis, especially lignin, cellulose, ash, extractives and alpha-, beta-, gamma-cellulose. The pulp was cooked in 6% nitric acid and then underwent the extraction by 5% sodium-hydroxide and neutralized by 1% acetic acid. The cooked pulp was characterized by delignification degree – Kappa number. The laboratory sheets were made from this cooked pulp and they were characterized by tensile index, breaking length, smoothness and compared with commonly available papers.

In France, the regional airport’s demand for services is facing challenges due to the continuous expansion of the high-speed train, high-speed line, and highway networks. This study focuses on the viability of regional airports in France through technical efficiency using data envelopment, principle component analysis, Malmquist productivity index, and regression analysis using bootstrapping. To face the current competitive environment, the regional airports in France adopted strategies, such as the construction of low-cost carrier (LCC) dedicated terminals (LCCTs) with lower expenses to attract more LCCs, increasing non-aeronautical revenue, and hosting regional hubs of LCCs. This is the first study that analyzes all of the French regional airports. The findings indicate that the existence of LCCTs positively affects technical efficiency on the airport’s performance, and share of LCCs at a regional airport leads to neither the efficiency nor the profit level.

Utilization of Bidirectional Reflectance Distribution Function (BRDF) model parameters obtained from the multi-angular remote sensing is one of the approaches for the retrieval of vegetation structural information. In this research, the potential of multi-angular vegetation indices, formulated by the combination of multi-spectral reflectance from different view angles, for the retrieval of forest above ground biomass was assessed. This research was implemented in the New England region with the availability of a high quality forest inventory database. The multi-angular vegetation indices were generated by the simulation of the Moderate Resolution Imaging Spectroradiometer (MODIS) BRDF/Albedo Model Parameters Product (MCD43A1 Version 6) based BRDF parameters. The effects of seasonal (spring, summer, autumn, and winter) composites of the multi-angular vegetation indices on above ground biomass, angular relationship of the spectral reflectance with above ground biomass, and the interrelationships between the multi-angular vegetation indices were analyzed. Among the existing multi-angular vegetation indices, only the Nadir BRDF-adjusted NDVI ( and Hot-spot incorporated NDVI ( showed significant relationship (more than 50%) with the above ground biomass. This research proposed two more sensitive vegetation structural indices, Fore-scattering Back-scattering NDVI and Vegetation Structure Index (VSI). The Fore-scattering Back-scattering NDVI showed higher sensitivity (R² = 0.62, RMSE = 52.46) towards the above ground biomass than existing multi-angular vegetation indices. Furthermore, the VSI performed in the most efficient way explaining 64% variation of the above ground biomass, suggesting that the right choice of the spectral channel and observation geometry should be considered for improving the estimates of the above ground biomass. In addition, the right choice of seasonal data (summer) was found to be important for estimating the forest biomass while other seasonal data were either insensitive or pointless. The promising results shown by the VSI suggest that it could be an appropriate candidate for monitoring vegetation structure from the multi-angular satellite remote sensing.

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].

To understand the physiological basis of tolerance to combined stresses to low phosphorus (P) and drought in mungbean (Vigna radiata (L.) R. Wilczek), a core set of 100 accessions were evaluated in hydroponics at sufficient (250 μM) and low (3 μM) P, and exposed to drought (dehydration) stress. The principal component analysis and ranking of accessions based on relative values revealed that IC280489, EC397142, IC76415, IC333090, IC507340 and IC121316 performed superior while IC119005, IC73401, IC488526 and IC325853 performed poorly in all treatments. Selected accessions were evaluated in soil under control (sufficient P, irrigated), low P (without P, irrigated), drought (sufficient P, withholding irrigation) and combined stress (low P, withholding irrigation). Under combined stress, a significant reduction in gas exchange traits (photosynthesis, stomatal conductance, transpiration, instantaneous water use efficiency), P uptake in seed and shoot was observed under combined stress as compared to individual stresses. Among accessions, IC488526 was most sensitive while IC333090 and IC507340 exhibited tolerance to individual or combined stress. The water balance and low P adaptation traits like membrane stability index, relative water content, specific leaf weight, organic acid exudation, biomass, grain yield and P uptake can be used as physiological markers to evaluate for agronomic performance. Accessions with considerable resilience to low P and drought stress can be either used as ‘donors’ in Vigna breeding program or cultivated in areas with limited P and water availability or both.

The Urban Eco-Sustainable Index for Upscaling Water Security at Catchment Level in Langat River, Malaysia has developed by using the Modified Watershed Sustainability Index or MicroWSI (MWSI), which was based on the Participation, Design and Management Components. The study has successfully applied spatial and social dimensions on ecohydrology of the selected Langat River reach for stormwater management, natural ecosystems health and quality of life. The planning and public participation aspects of the study have evaluated the surrounding neighborhood area of Langat. The conceptual design of rehabilitation works implementation related to Urban Stormwater Management Manual for Malaysia (MSMA) Stormwater Management Ecohydrology (SME) within the study area has been developed with four components of MSMA-SME to be implemented in the study area i.e Bioretention System, Porous Pavement System, Constructed Wetland and Slope Protection Works. These components were proposed to be applied in the development of Langat Riverfront Community Park (LRCP) which has taken into account the components of Design, Management and Participation of Community and Stakeholders in Langat River Basin, Malaysia. This study analyzed the MWSI for the Upscaling of MSMA Ecohydrology at Catchment Level of Langat River and has found the medium level of sustainability for the level of participation, proposed design, and management. Thus, there is a need to increase the level of readiness in the community and stakeholder participation in the Langat River towards sustainability of river conservation and rehabilitation programmes in this basin.

Polycystic ovary syndrome (PCOS) is a complex hormonal disorder which impair ovarian function. The adherence to healthy dietary patterns and physical exercise are the first line of recommended treatment for PCOS patients, but it is no clear what type of diet is more adequate. In this case-control study, we explore the association between the adherence to five dietary quality indices widely used and PCOS. We enrolled 126 cases of PCOS and 159 controls (Murcia, Spain). Diagnostic of PCOS and its phenotypes were established following the Rotterdam criteria [hyperandrogenism (H), oligoanovulation (O), polycystic ovaries morphology (POM)]. We used a validated food frequency questionnaires to calculate the scores for five dietary indices: alternate Healthy Eating index (AHEI), AHEI-2010, relative Mediterranean Dietary Score (rMED), alternate Mediterranean Dietary Score (aMED) and Dietary Approaches to Stop Hypertension (DASH). We used multivariable logistic regression to estimate adjusted odds ratios and confidence intervals. In the multivariable analysis, AHEI-2010 index was inversely associated with “H+O” PCOS’ phenotype (ORQ3 VS Q1= 0.1; 95% CI :(0.0; 0.9); P for trend= 0.02). In conclusion, we did not find any statistical significative association between dietary indices and total, anovulatory and ovulatory PCOS, but it seems interesting explore these association among the diverse phenotypes of PCOS in studies with higher sample size.

Over the last decades, the energy market around the world has reshaped due to accommodating the high penetration of renewable energy resources. Although renewable energy sources have brought various benefits, including low operation cost of wind and solar PV power plants, and reducing the environmental risks associated with the conventional power resources, they have imposed a wide range of difficulties in power system planning and operation. Naturally, classical optimal power flow (OPF) is a nonlinear problem. Integrating renewable energy resources with conventional thermal power generators escalates the difficulty of the OPF problem due to the uncertain and intermittent nature of these resources. To address the complexity associated with the process of the integration of renewable energy resources into the classical electric power systems, two probability distribution functions (Weibull and lognormal) are used to forecast the voltaic power output of wind and solar photovoltaic, respectively. Optimal power flow, including renewable energy, is formulated as a single-objective and multi-objective problem in which many objective functions are considered, such as minimizing the fuel cost, emission, real power loss, and voltage deviation. Real power generation, bus voltage, load tap changers ratios, and shunt compensators values are optimized under various power systems’ constraints. This paper aims to solve the OPF problem and examines the effect of renewable energy resources on the above-mentioned objective functions. A combined model of wind integrated IEEE 30-bus system, solar PV integrated IEEE 30-bus system, and hybrid wind and solar PV integrated IEEE 30-bus system are performed using the equilibrium optimizer technique (EO) and other five heuristic search methods. A comparison of simulation and statistical results of EO with other optimization techniques showed that EO is more effective and superior.

In this paper, a plasmonic refractive index sensor based on metal insulated metal waveguide (MIM) with three rings and a resonant cavity is first proposed and numerically evaluated. Next, we add four teeth to the sensor structure. We study and simulate the resonant wavelengths and refractive index of resonators using the time difference finite difference method. Given that the sensor and the conduction characteristics of plasmonic waves are influenced by the structure parameters,Therefore, by changing the refractive index and changing the dimensions and coordinates of the cavity and rims, we can change the passage coefficient in the resonant modes and measure the sensor performance. As a result, we obtain the sensitivity coefficient, the figure of merit (FOM) and the quality factor Q of the sensor. We modulate the resonance wavelength FWHM using the generated modes and reach a sensitivity of 2166 nm / RIU. These plasmonic sensors with a simple framework and balanced performance and high optical resolution can be used to measure the refractive index in the medical, chemical and food industries.

MIGAL – Galilee Research Institute is a regional R&amp;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.

Abstract: Changes in forest landscapes have been connected with human activity for centuries, which can be considered as one of the main driving forces of change in the global perspective. The spatial distribution of forests changes along with the geopolitical situation, demographic changes, intensification of agriculture, urbanization or changes in the land use policy. However, due to the limited availability of historical data, the driving forces of changes in forest landscapes are most often considered in relation to recent decades, without taking into account long-term analyzes. The aim of this paper is to determine the impact of natural and socio-economic factors on changes in forest landscapes within the protected area – Ślęża Landscape Park and its buffer zone in the aspect of long-term analyzes covering the period of 140 years (1883-2013). The comparison of historical and current maps, demographic data on 4 different periods as well as natural and location factors by using the ArcGIS software allowed analyzing selected driving forces of forest landscape transformations. We took into account natural factors like altitude, slope, exposure of the hillside and socio-economic drivers like population changes, distances to centers of municipalities, main roads and built-up areas.

We have studied the very large amount of literary works written by the Italian mystic Maria Valtorta to assess similarities and differences in her writings because she claims that most of them are due to mystical visions. We have used mathematical and statistical tools developed for specifically studying deep linguistic aspects of texts. The general trend indicates that the literary works explicitly attributable to Maria Valtorta differ significantly from her other literary works, that she claims are attributable to the alleged characters Jesus and Mary. Mathematically, they seem to have been written by different authors. The comparison with the Italian literature is very striking. A single author, namely Maria Valtorta, seems to be able to write texts so diverse to cover the entire mathematical range (suitable defined) of the Italian literature of seven centuries.

Back pain is a common symptom that affects all age groups across the globe, when left untreated may eventually lead to disability. A convenient sample selection method was used in this study due to the global Covid-19 pandemic lockdown which was effective in Turkey during the investigation period. Thus, virtual data collection and health education including some health risks were employed. A total population of two hundred adult women was involved in the study but one hundred and twenty-one responses were collected. Findings show that, for socio-demographic characteristics, the pain was found highest in women between the ages of 41-50 and obese/overweight individuals. Although, there was no significant difference recorded in the marital status category. Moreover, statistical mean differences were detected between the scales for ODI (4.18) and BPFS (6.09). Also, p<0.05, paired sample t-test was 0.001 ODI and 0.001 BPFS after the training exercise. This suggests that exercise training is inversely correlated with pain severity which implies that training has a significant influence on pain intensity. Thus, it could be concluded that there is a relationship between the training exercise and ODI/BPFS.

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 present study investigated the effect of different ambient temperature and relative humidity (RH) but equal temperature-humidity index (THI) on laying performance, egg quality, heterophil to lymphocyte ratio (H/L ratio), corticosterone (CORT) concentration in blood, yolk and albumen, and plasma biochemical parameters in laying hens. One hundred and twenty commercial hens (Hy-Line Brown) aged 60 weeks were allocated into 2 environmental chambers. Laying hens were subjected to either one of two thermal treatments, i.e., 26ºC and 70% RH (LH75) and 30ºC and 30% RH (HL75) for 28 days. Both thermal treatments had equal THI being 75. Neither LH75 nor HL75 affected (P > 0.05) laying performance including egg production, egg weight, egg mass, feed intake, and feed conversion ratio. Plasma biochemical parameters such as total cholesterol, high-density lipoprotein cholesterol, triglyceride, calcium, magnesium, and phosphorus was not altered (P > 0.05) by thermal treatments. As to the stress indicators, both environment regimes failed (P > 0.05) to affect blood H/L ratio and CORT levels in plasma, yolk and albumen although albumen CORT levels were elevated (P < 0.05) in LH75 vs. HL75 at days 3, 7, and 28. In conclusion, our study suggests that laying hens performed and responded equally when they were exposed to equal THI environment conditioned from either 26ºC and 70% RH or 30ºC and 30% RH. The results of this study will be served as a scientific basis for management decisions and handling under thermally challenging conditions.

This paper proposes a method for determining the bridge condition index (BCI) in concrete bridges, which is based on the views of bridge experts. First, eight indices were defined for a concrete bridge including structure, hydrology, safety, load impact, geotechnical and seismicity, strategic importance, facilities, and finally traffic and pavement. Each index consists of several sub-indices. Next, a series of questionnaires about the relative importance of indices and their sub-indices were prepared and distributed among bridge experts. Experts’ views were analyzed by Expert Choice software and the relative importance (weight) of each index and each sub-index was determined using the analytical hierarchy process (AHP). Then, based on experts’ views, an average score was assigned to each sub-index for any condition. Now the bridge inspectors can examine the bridge and determine the scores of sub-indices. Each index’s score is the sum of the weighted score assigned to its’ sub-indices and BCI is the sum of weighted scores assigned to indices. Higher values of BCI indicate a better condition. Therefore, bridges with lower BCI take priority in maintenance activities. To apply the proposed method, five bridges were selected in Semnan province, Iran, and BCI calculation of these bridges were conducted.

Solar reflective index (SRI) is one of the important parameters in the analysis of a building’s energetic and thermal performance, especially for “cool” reflective paints or coatings. However, there exists less information on the typical performance of the cool materials exposed for long term in the Middle East and more specifically in the United Arab Emirates (UAE). In this study, we determined values of reflectance, emittance, solar reflective index (SRI), and color difference, for three different high SRI white paints exposed naturally on low and high sloped racks for three years. After 3 years, reflectance values of exposed paint panels significantly decreased with an increased color difference in comparison with original unexposed paint surfaces. Emissivity of the paint changed very little for all of the exposed samples, but SRI, determined from both the reflectance and emittance, was reduced from between 95 and 110 to between 60 and 90 after three years. This appeared to be related to exposure to high temperatures, UV radiation, and adhesion of airborne contaminants in conjunction with low precipitation. Macroscopically, panels exposed on a low slope were the most discolored with the greatest presence of dust infusion and reduction in increase in surface temperatures which was demonstrated through thermal imaging. Such natural weathering research study is necessary for the development of standard exposure tests and determination of various control elements to increase the durability of cool materials in hot and arid climatic conditions of UAE.

The COVID-19 pandemic has caused significant medical and psychological challenges worldwide, and not only exceeded the capacity of hospitals and intensive care units but also an individuals’ ability to cope with life. Health-care workers have continued to provide care for patients despite exhaustion, fear of transmission to themselves and their family, illness or death of friends and colleagues, and losing many patients. They have also faced additional stress and anxiety due to long shifts combined with unprecedented population restrictions, including personal isolation. In this study, we study the effect of an app-based Yoga of Immortals (YOI) intervention on mental health of healthcare workers. In this study, the health care workers were digitally recruited, and their psychological parameters were measured using validated questionaries. The participants were randomly grouped into control and test groups. The validated psychological measures were the Patient Health Questionnaire-8 (PHQ-8), Insomnia Severity Index (ISI) and generalized anxiety disorder (GAD-7) scales. The digital YOI intervention significantly reduced the anxiety, depression symptoms, and insomnia in healthcare workers of all age groups. In contrast, there was no improvement in the control group. This study details the effectiveness of an app-based YOI intervention in healthcare workers.

Temporary changes in precipitation may lead to sustained and severe drought or massive floods in different parts of the world. Knowing variation in precipitation can effectively help the water resources decision-makers in water resources management. Large-scale circulation drivers have a considerable impact on precipitation in different parts of the world. In this research, the impact of El Niño-Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), and North Atlantic Oscillation (NAO) on seasonal precipitation over Iran was investigated. For this purpose, 103 synoptic stations with at least 30 years of data were utilized. The Spearman correlation coefficient between the indices in the previous 12 months with seasonal precipitation was calculated, and the meaningful correlations were extracted. Then the month in which each of these indices has the highest correlation with seasonal precipitation was determined. Finally, the overall amount of increase or decrease in seasonal precipitation due to each of these indices was calculated. Results indicate the Southern Oscillation Index (SOI), NAO, and PDO have the most impact on seasonal precipitation, respectively. Also, these indices have the highest impact on the precipitation in winter, autumn, spring, and summer, respectively. SOI has a diverse impact on winter precipitation compared to the PDO and NAO, while in the other seasons, each index has its special impact on seasonal precipitation. Generally, all indices in different phases may decrease the seasonal precipitation up to 100%. However, the seasonal precipitation may increase more than 100% in different seasons due to the impact of these indices. The results of this study can be used effectively in water resources management and especially in dam operation.

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

Heart myocardia are critical to the facilitation of heart pumping and blood circulating around the body. The biaxial mechanical testing of the Left Ventricle (RV) is utilised to build the computa-tional model of the whole heart with little importance given to the unique mechanical properties of Right Ventricle (RV) and Mid-wall (MDW). Most of those studies focussed on the LV of the heart, and then apply the obtained characteristics with a few modifications to the right side of the heart. However, that view has been contested over time with the realisation that the right side of the heart possesses its own unique mechanical properties that are widely distinct from that of the left side of the heart. This paper is aimed at reporting and evaluating the passive mechanical property dif-ferences in the three main walls of the rat heart based on biaxial tensile test data. Fifteen mature Wistar rats weighing 225 ± 25 g were euthanised by inhalation of 5 % halothane. The hearts were excised after which all the top chambers comprising the two atria, pulmonary and vena cava trunks, aorta and valves are all dissected out. Then 5 x 5 mm sections from the middle of each wall were carefully dissected with a surgical knife to avoid over-prestraining the specimens. The specimens were subjected tensile test. The elastic moduli, peak stresses in the toe region and stresses at 40 % strain, anisotropy indices as well as the stored strain energy in the toe and linear region up to 40 % strain are used for statistical significance tests. The following are the main findings of this study: (1) LV and MDW tissues have relatively shorter toe regions of 10 - 15 % strain as compared to RV tissue whose toe region extends up to twice as much as that (2) LV tissues have higher strain energy storage in the linear region despite being lower in stiffness than the RV (3) the MDW has the highest strain energy storage along both directions which might be directly related to its high level of anisotropy. These findings, though for a specific animal species at similar age and around the same body mass, emphasize the importance of application of wall specific material parameters to obtain accurate ventricular hyperelastic models. The findings further enhance our understanding of the desired mechanical behaviour of the different ventricle walls.

Appropriate estimation of soil settlement is of significant importance since it directly influences the performance of building and infrastructures that are built on soil. In particular, the settlement of fine-grained soils is critical because of low permeability and continuous settlement with time. Coefficient of consolidation (C_c) is a key parameter to estimate settlement of fine-grained soil layers. However, estimation of this parameter is time consuming, needs skilled technicians, and specific equipment. In this study, C_c was estimated using several soil parameters such as liquid limit (LL), plastic limit (PL), and initial void ratio (e₀). Estimating such parameters in laboratory is straight forward and needs substantially less time and cost compared to conventional tests to estimate C_c such as oedometer test. This study presents a novel prediction model for C_c of fine-grained soils using gene-expression programming (GEP). GEP is a biologically inspired technique capable of offering closed-form solution for the optimal solution. A database consisted of 108 different data points was used to develop the model. A closed-form equation solution was derived to estimate C_c based on LL, PL, and e₀. The performance of developed GEP-based model was evaluated through coefficient of determination (R²), root mean squared error (RMSE), and mean average error (MAE). High R² and low error values indicated the descent performance of the model. Furthermore, the model was evaluated using the additional performance measures and met all the suggested criteria. Furthermore, the model had a better performance in terms of R², RMSE, and MAE compared to most of existing models. It is expected that the developed model will decrease the time and cost associate with determining C_c of fine-grained soils.Keywords: evolutionary model, gene-expression programming (GEP), prediction, soil compression index, estimation, soil engineering, soil informatics, civil engineering, machine learning, data science, big data, soft computing, deep learning, forecasting, subject classification codes, construction informatics, computational intelligence (CI), artificial intelligence (AI), estimation

Agricultural landscapes are more and more characterized by intensification and habitat losses. Landscape composition and configuration are known to mediate insect abundance and richness. In the context of global insect decline, and despite 75% of crops being under insect’s dependence, there is still a gap of knowledge about the link between pollinators and aromatic crops. Fennel (Foeniculum vulgare) is an aromatic plant cultivated in South of France, for its essential oil which is of great economic interest. Using pan-traps, we investigated the influence of the surrounding habitats at landscape scale (semi-natural habitat proportion and vicinity, landscape configuration) and local scale agricultural practices (insecticides and patch size) on fennel-flower-visitor abundance and richness and their subsequent impact on fennel essential oil yield. We found that fennel may to be a generalist plant species. We did not find any effect of intense local management practices on insect abundance and richness. Landscape configuration and the proximity to semi-natural habitat were the main drivers of flying insect’s family richness. This richness positively influenced fennel essential oil yield. Maintaining a complex configuration of patches at the landscape scale are important to sustain insect diversity and crop yield.

One of the most problematic forms of nature protection in Poland relates to landscape parks. On the one hand, they include the most valuable landscapes; on the other hand, the areas within the landscape park still have economic uses. Therefore, the monitoring of landscape changes within landscape parks is necessary in order to properly manage these forms of protection. The main objective of the study was to monitor the scale and nature of landscape transformations within the boundaries of landscape parks in Poland during the period 2000–2018 and to assess the possibility of using the landscape change index (LCI) to monitor the intensity of landscape transformations within this type of protected area. Filling a gap in the research on landscape changes, I developed and verified the possibility of using LCI for monitoring the intensity of landscape changes using the example of 12 landscape parks in the Lower Silesia region. Preliminary analyses of the transformations within all landscape parks in Poland showed an upward trend, both in terms of the number of types of identified landscape changes as well as their area. In spite of the large diversity and degree of transformation in landscape parks, several dominant processes can be observed. The largest number and area of changes during each of the analyzed periods were found in transformations within forest landscapes (temporary and permanent deforestation and forest maturation), which constitute the dominant type of land cover within most of the landscape parks. In open landscapes, changes mainly relate to afforestation and natural succession in meadows, pastures and arable land, as well as the transformation of arable land into mining areas. Twelve case studies, covering all landscape parks of the Lower Silesia, have shown that the LCI is an excellent tool for monitoring the intensity of landscape changes, but it is dependent on the accuracy of the source data. The analyses confirmed that, during the study periods, the changes in all 12 Lower Silesian landscape parks were at a low level, but their particular intensification took place in the years 2012–2018. The highest LCI was found in the area where a natural disaster had occurred (air tornado), which destroyed huge areas of forest in landscape parks. After changes in the forest landscape, the most frequently identified type of change in 2006–2012 is the transformation of non-forest landscapes into forest landscapes. The main reason for such changes was the expansion of forest into abandoned arable land, meadows and pastures. The use of the Corine Land Cover database to calculate LCI and monitor the intensity of landscape change revealed a low usability of the database for the year 2000 and a high usability for data from 2006–2018.

This work uses a new approach to investigate the Riemann hypothesis, drawing conclusions about its trueness. It is based on the more general method presented in a very recent publication, by the same author, showing in detail how to approach that very well-known and interesting problem. This is achieved by means of the theory of dynamical systems (Poincaré index associated to equilibria of 2-dimensional systems) and the study of the zeros of the Dirichlet eta function, defined by a Dirichlet series. By using the well-known fact that the zeros of the eta function include all zeros of the Riemann zeta function in the (open) critical strip, excluded the critical line, ((0,1/2) ∪ (1/2,1)) × (−∞,∞), the development proceeds using only the eta function. In addition, the open and simply connected region (1/2,1) × (0,∞) is used along the text, taking into account the symmetries of zeros of the functions under analysis in the critical strip. The basic line of proof is to find the mathematical expression for the Poincaré index of the vector field associated to the eta function, assuming the existence of a zero of the eta function outside the critical line (in (1/2,1) × (0,∞)), and investigating the resulting unfoldings. Eventually, an inconsistency occurs and the proof ends by contradiction.

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.

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 goal of this study was to analyze the forest degradation in the Reserve for San Rafael National Park, Paraguay, during the period 2005-2019. This Reserve is one of the most important forest remnants of the Upper Paraná Atlantic Forest Ecoregion. A multitemporal analysis of degradation was carried out due to the occurrence of three disturbances: forest fires, a twister and illicit crops, using the Continuous Degradation Detection (CODED) algorithm, for which 3 factors were considered: variations due to pixel in the NDFI index values before, during and after every disturbance registered. In this context, the phenomenon with the greatest impact in terms of magnitude of degradation were the forest fires of 2005, being that year at the same time, the one that reported the highest degradation values. Secondly, there are the illicit crops established until the first semester of 2019, and lastly, the twister that occurred in 2017. Our findings demonstrate that CODED algorithm can detect multi-temporal degradation events in a Subtropical Broadleaf Forest, and the post-disturbance regeneration process after every disturbance tends to occur immediately. The response in terms of degradation-regeneration is highly variable, depending of the nature and severity of each disturbance and the vegetation recovery dynamics.

Target 12.3 of the United Nations Sustainable Development Goals (SDGs) calls for halving per capita global food waste at the retail and consumer levels, by 2030. The Food Waste Index is suggested as a methodology for grasping the situation. This paper focuses on the consumer level (household food waste). We argue that in order for generating useful information for devising and implementing effective measures for reducing food waste, it should be measured at Level 3 of the Food Waste Index, based on sorting analysis of generated waste, making a distinction between avoidable and non-avoidable food waste. Furthermore, a breakdown by sub-categories that reflect the flow of food in the household could help identify target behaviours. We have developed a categorisation scheme that is internationally agreeable and adoptable, and 1) generates useful information for policy-making and for tackling with reduction of food waste, 2) makes clear the concept of avoidable food waste, and 3) is practical and does not overcomplicate the work of grasping the situation of food wastage. Results of workshops regarding this scheme suggest that the scheme satisfies the criteria. This scheme has been applied to a few sorting analyses of household food waste in Japan, and their results are compared.

Using two metal insulated metal waveguides (MIM) and five resonator (a quadrilateral cavity and three rings with different dimensions), we design a plasmonic refractive index sensor. Using the time domain finite difference method, we examine and analyze the sensor performance (numerical analysis) and using the transmission line model method, we theoretically examine the performance of the sensor By summarizing these two methods and calculating the sensitivity coefficient S, quality coefficient Q and figure of merit (FOM), a plasmonic sensor with good performance is obtained. Using the supermods of the resonators, we will achieve a stable wavelength spectrum and a suitable and stable sensitivity coefficient spectrum. Challenges and changes that occur in different modes of this sensor will lead to a balanced and relatively good structure. This designed sensor can be useful in the development of integrated optical circuits.

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.

A quasi-two-dimensional (quasi-2D) modelling approach is introduced to mimic transverse mixing of an inflow into a river from one of its banks, either an industrial outfall or a tributary. The concentrations of determinands in the inflow vary greatly from those in the river, leading to very long mixing lengths in the river downstream of the inflow location. Ideally, a two-dimensional (2D) model would be used on a small scale to capture the mixing of the two flow streams. However, for large-scale applications of several hundreds of kilometres of river length, such an approach demands too many computational resources and too much computational time, especially if the application will at some point require ensemble input from climate-change scenario data. However, a one-dimensional (1D) model with variables varying in the longitudinal flow direction but averaged across the cross-sections is too simple of an approach to capture the lateral mixing between different flow streams within the river. Hence, a quasi-2D method is proposed in which a simplified 1D solver is still applied but the discretisation of the model setup can be carried out in such a way as to enable a 2D representation of the model domain. The quasi-2D model setup also allows secondary channels and side lakes in floodplains to be incorporated into the discretisation. To show proof-of-concept, the approach has been tested on a stretch of the lower Athabasca River in Canada flowing through the oil sands region between Fort McMurray and Fort MacKay. A dye tracer and suspended sediments are the constituents modelled in this test case.

Objectives To examine the comorbidity burden in patients with rheumatoid arthritis (RA) patients using a nationwide population-based cohort by assessing the Charlson Comorbidity Index (CCI), Elixhauser Comorbidity Index (ECI), Multimorbidity Index (MMI), and Rheumatic Disease Comorbidity Index (RDCI) scores and to investigate their predictive ability for all-cause mortality. Methods We identified 24,767 RA patients diagnosed between 1998–2008 in Taiwan and followed up until December 31, 2013. The incidence of comorbidities was estimated in three periods (before, during, and after the diagnostic period). The incidence rate ratios were calculated by comparing during vs. before and after vs. before the diagnostic period. One- and 5-year mortality rates were calculated and discriminated by low and high-score groups and modified models for each index. Results The mean score at diagnosis is 0.8 in CCI, 2.8 in ECI, 0.7 in MMI, and 1.3 in RDCI, and annual percentage changes are 11.0%, 11.3%, 9.7%, and 6.8%, respectively. The incidence of any increase in the comorbidity index is significantly higher in the periods of ‘during’ and ‘after’ the RA diagnosis (incidence rate ratios for different indexes: 1.33-2.77). The mortality rate significantly differs between the high and low-score groups measured by each index (adjusted hazard ratios: 2.5-4.3 for different indexes). CCI is slightly better in the prediction of 1- and 5-year mortality rates. Conclusion Comorbidities are common before and after RA diagnosis, and the rate of accumulation accelerates after RA diagnosis. All four comorbidity indexes are useful to measure the temporal changes and to predict mortality.

During recent years UAVs have been increasingly used in agriculture and forestry research and application. Nevertheless, most of this work has been devoted to improving accuracy and explanatory power, often at the cost of usability and affordability. We tested a low-cost UAV and a simple workflow to apply four different greenness indices to the monitoring of pine (Pinus sylvestris and P. nigra) after-fire regeneration in a Mediterranean forest. We selected two sites and masured all pines within a pre-selected plot. Winter flights were carried out at each of the sites, at two flight altitudes (50 and 100 m). Automatically normalizing images entered an SfM based photogrammetric software for restitution and the obtained point cloud and orthomosaic processed to get a canopy height model and four different greenness indices. Sum of pine DBH was regressed on summary statistics of greenness indices and canopy height model. ExGI and GCC indices outperformed VARI and GRVI in estimating pine DBH, while canopy height model slightly improved the models. Flight altitude did not severely affect model performance. Our results show that low cost UAVs may improve forest monitoring after disturbance, even in those habitats and situations were resource limitation is an issue.

Developed countries have shown a time trend towards a younger age at menarche (AAM), which is associated with increased risk of later obesity and non-communicable diseases. We aimed to assess whether a time trend in AAM with associated disease risk is also present in Mexico. For this, we used data of 30,826 women from the Mexican National Health Survey (2000). Linear and log binomial regression was used for nutritional and disease outcomes, whereas Welch-ANOVA was used to test for a time trend. AAM decreased over time (p < 0.001), with a maximal difference of 0.99 years between the 1920s (13.6 years) and 1980s (12.6 years). AAM (in years) was negatively associated with weight (β = -1.01 kg; 95 % CI -1.006, -1,004) and BMI (β = -1.01 kg/m2; -1.007, -1.006), and positively with height (β = 0.18 cm; 0.112, 0.231). AAM was associated with diabetes (RR = 0.95; 0.93, 0.98) and hypercholesterolemia (RR = 0.93; 0.90, 0.95), but not with hypertension, breast cancer or arthritis. In Mexico, AAM decreased significantly during the 20th century. AAM was inversely associated with adult weight and BMI, and positively with height. Women with a later AAM had a lower risk of diabetes and hypercholesterolemia.

A single paragraph of about 200 words maximum. For research articles, abstracts should give a pertinent overview of the work. We strongly encourage authors to use the following style of structured abstracts, but without headings: (1) Background: Place the question addressed in a broad context and highlight the purpose of the study; (2) Methods: briefly describe the main methods or treatments applied; (3) Results: summarize the article's main findings; (4) Conclu-sions: indicate the main conclusions or interpretations. The abstract should be an objective rep-resentation of the article and it must not contain results that are not presented and substantiated in the main text and should not exaggerate the main conclusions.