A semi-structured interview (SSI) is one of the essential tools in conduction qualitative research. This essay draws upon the pros and cons of applying semi-structured interviews (SSI) in the qualitative research method. Moreover, the challenges of SSI during the coronavirus pandemic are critically discussed to provide plausible recommendations.

Objectives: This study aimed to analyze the awareness of local residents regarding healthcare projects and to suggest some ideas for the revision of local ones. Methods: To delve into the opinions of local residents, the author of this study created a questionnaire composed of eight questions on the general characteristics of the respondents, eight questions on satisfaction with health centers, 16 questions on the awareness of healthcare projects, and 22 questions on local healthcare. The survey was conducted for 409 residents who visited public centers in Gimcheon from 15 March to 14 April 2021. Results: Data analysis revealed the following: The proportion of local residents who use health centers was 39.1%, and those users visit health centers, on average, 3.92 times a year. Among healthcare projects, the project known by the highest proportion of people was vaccinations (84.5%), which was also the project that was most used (38.1%). Among healthcare projects needed in the with-COVID-19 age, respondents awarded the highest score to vaccinations (4.15 points on a five-point Likert scale) and the second highest score to infectious disease management (4.12). Conclusions: For healthcare projects, central and local governments should focus on activating vaccinations, solving the problem of medical accessibility through untact remote treatment and establishing national infectious disease-specializing hospitals and local infectious disease management based on such national hospitals.

Mobile devices have become tools we spend our free time where we carry them with us every moment, they allow us to interact with the environment, we immortalize the moment when necessary. These devices which we spend most of our daily life become very common in recent years and even there are unique business areas emerged. It was announced that the number of people using smartphones is over than 2.5 billion in the first quarter of 2016. As people become more addicted to mobile technology, they become the target of malevolent people. A huge increase in the number of mobile malware is observed as the number of the users increase. Billions of users at risk day by day due to the development of the methods. We have addressed the recent methods used and the types of malware that target mobile devices in our study. We have mentioned the proxy server and reverse proxy server operation logic. We discuss the method of turning mobile devices into reverse proxy servers, risks involved and protection methods.

The microbial contamination in food packaging have been a major concern that paved the way for the search for natural based new anti-microbial agents, such as modified α-mangostin. In the present work, twelve synthetic analogs were obtained via semi-synthetic modification of α-mangostin by Ritter reaction, reduction by palladium-carbon (Pd-C), alkylation, and acetylation. The evaluation of the anti-microbial potential of the synthetic analogs showed higher therapeutic value than the parent molecule. The anti-microbial studies proved that I E showed higher antibacterial activity whereas I I showed most significant antifungal activity. Due to their microbial properties, modified α-mangostin can be utilized as active anti-microbial agents in food packaging.

The concept of economic self-reliance, widely known by Thai people as the philosophy of sufficiency economy, has been widely promoted in rural Thai societies. By practicing this philosophy, it is expected that the citizens’ quality of life and local environments could be sustainably improved. This study aims to explore the contribution of the community practices of the sufficiency economy philosophy to rural villagers’ quality of life improvement, and to investigate potential factors that determine the trust of villagers in the philosophy. With the purpose to propose strategies which could enhance trust and promote villagers’ practices of the philosophy, the study investigated influences of three relevant factors on trust towards the philosophy. Those factors included factors related to cognitive-based trust, factors related to emotional-based trust, and factors related to demographic characteristics. Questionnaire surveys and in-depth interviews with community leaders and local villagers were conducted in the Ban Jamrung community, in Thailand’s Rayong province. The results of the statistical analysis revealed that the residents who applied the sufficiency economy philosophy in their daily lives experienced a relatively better quality of life. Additionally, it was found that trust in the philosophy could be predicted more by rational factors than by emotional factors. These findings could be utilized to develop strategies to maintain and enhance the trust of the people in the philosophy of sufficiency economy.

Local polynomial smoother (LPS) is a weighted local least-squares nonparametric method. It provides a local Taylor series fit of the data at any location and can be directly used in a differential equation to provide a numerical scheme. In this article, we introduce this new nonparametric idea based on local polynomial smoother, for acquiring the numerical solution of the Bagley-Torvik fractional-order differential equations. Furthermore, this paper will present a numerical comparison with some methods, such as legendre operational matrix and pseudo-spectral method. The efficiency and accuracy of the LPS method are demonstrated by two numerical examples.

This article investigates a proposed new mathematical model that considers the infected individuals using various rate coefficients such as transmission, progression, recovery and vaccination. The fact that the dynamic analysis is completely determined by the basic reproduction number is established. More specifically, local and global stabilities of the disease-free equilibrium and the endemic equilibrium are proved under certain parameter conditions when the basic reproduction number is below or above unity. A realistic computer simulation is performed for better understanding of the variations in trends of different compartments after the outbreak of the disease.

The main contribution of this paper is to develop a graphical tool to evaluate the suitability of a candidate parametric model to fit a data set. The practical motivation is to check the adequacy of the so called SAINT model proposed in Jarner and Kryger (2011). This model has been implemented in practice by an important European pension fund concerned with setting annuity reserves for all current or former employees of Denmark. So, one particular relevant question is whether this mortality model is actually fitting old-age. Our graphical test can be described as follows. First we transform the data by means of the parametric model which is being evaluated. Should the model be correct, the transformed data will be in accordance with an Exponential distribution with rate 1. Then we construct a family of local linear hazard estimates based on the data on the transformed scale. Finally we use the statistical tool SiZer to assess the goodness-of-fit of the Exponential distribution to the data on the transformed scale. If the model is correct the SiZer map should not reveal any significant feature in the family of kernel estimates. Our method allow us to establish a diagnostic regarding the validity of the SAINT model when describing mortality patterns in four different countries.

Biocultural heritage-based products, including regional specialty foods, are increasingly part of sustainable rural development strategies. While export-oriented biocultural products are often the most visible, we examine the role of campesino gastronomic heritage in the Central Valley of Tarija, Bolivia, as a case study of a local market-centered biocultural resource-based development strategy reflected in an alternative agri-food network. We develop a biocultural sustainability framework to examine this network from ecological, economic and sociocultural perspectives. Data are drawn from interviews (n=77), surveys (n=89) and participant observation, with primary and secondary producers of traditional and new products, as well as restaurant owners, market vendors and local consumers. We find that campesino biocultural heritage and the alternative agri-food network surrounding it represent an influential territorial project that underpins many household economies, particularly for women. We conclude that the relatively small investments by local governments to promote campesino gastronomic heritage are having positive ripple effects on small-scale producer livelihoods and on biocultural sustainability. We suggest that further support to increase market access and reduce other barriers to participation in alternative food networks will likely increase the options and benefits available to small-scale producers mobilising campesino gastronomic heritage within the local economy.

The features of a class of cubic curves with a shape factor are analyzed by means of the theory of envelope and topological mapping. The effects of the shape factor on the cubic curves are made clear. Necessary and sufficient conditions are derived for the curve to have one or two inflection points, a loop or a cusp, or to be locally or globally convex. Those conditions are completely characterized by the relative position of the edge vectors of the control polygon and the shape factor. The results are summarized in a shape diagram, which is useful when the cubic parametric curves are used for geometric modeling. Furthermore we discussed the influences of the shape factor on the shape diagram and the ability for adjusting the shape of the curve.

Relying on Random Utility Theory (RUT) as the guiding mechanism for the Data Generating Process (DGP), this paper uses households consumption choices on cooking fuel, drinking water, and sanitation from the 2014 United States Agency for International Development's (USAID) Demographic and Health Survey (DHS) data on Burkina Faso, to characterize and investigate the inter-linkages between health consciousness and environmental consciousness, and their relationship with wealth in a low income country context. We achieve this by specifying sequentially three econometric modeling frameworks: the first one being independent binary probit (IBP) models to describe each choice process, followed by a fully parametric trivariate probit (FPTP) model to account for choice dependency, and finally by a semi-parametric trivariate probit (SPTP) model to further relax the linearity assumption. Based on the Akaike Information criteria (AIC) and the estimated Trivariate model correlation coefficients, the SPTP framework is found to be the best specification for describing the observed consumption behaviors. The results show that increased wealth level raises households health and environmental consciousness, while leaving the relative preference ordering over the elements in the household consumption basket unchanged.

Face verification for unrestricted faces in the wild is a challenging task. This paper proposes a method based on two deep convolutional neural networks(CNN) for face verification. In this work, we explore to use identification signal to supervise one CNN and the combination of semi-verification and identification to train the other one. In order to estimate semi-verification loss at a low computation cost, a circle, which is composed of all faces, is used for selecting face pairs from pairwise samples. In the process of face normalization, we propose to use different landmarks of faces to solve the problems caused by poses. And the final face representation is formed by the concatenating feature of each deep CNN after PCA reduction. What's more, each feature is a combination of multi-scale representations through making use of auxiliary classifiers. For the final verification, we only adopt the face representation of one region and one resolution of a face jointing Joint Bayesian classifier. Experiments show that our method can extract effective face representation with a small training dataset and our algorithm achieves 99.71% verification accuracy on LFW dataset.

Local anaesthetic agents suppress action potentials in excitable tissues by blocking voltage-gated sodium channels. In doing so they inhibit the depolarisation of nociceptive nerve fibres and so prevent the transmission of pain impulses. UK legislation allows HCPC-registered Podiatrists with POM-A annotation access to six local anaesthetic drugs and two of these with the addition of adrenaline. The use of local anaesthetia has transformed the treatment of nail pathology by Podiatrists. In the UK, the drug of choice in podiatric practice is 3% mepivacaine hydrochloride: it is a good choice of drug for digital anaesthesia. This paper will review the chemistry, pharmacology and dose calculation of mepivacaine, and challenge some of the orthodoxy over the rigid calculation of maximum safe dosages.

This article develops duality principles and related convex dual formulations suitable for the local optimization of non-convex primal formulations for a large class of models in physics and engineering. The results are based on standard tools of functional analysis, calculus of variations and duality theory. In particular, we develop applications to a Ginzburg-Landau type equation.

Skin cancer is an exquisite disease globally nowadays. Because of the poor contrast and apparent resemblance between skin and lesions, automatic identification of skin cancer is complicated. The rate of human death can be massively reduced if melanoma skin cancer can be detected quickly using dermoscopy images. In this research, an anisotropic diffusion filtering method is used on dermoscopy images to remove multiplicative speckle noise and the fast-bounding box (FBB) method is applied to segment the skin cancer region. Furthermore, the paper consists of two feature extractor parts. One of the two features extractor parts is the hybrid feature extractor (HFE) part and another is the convolutional neural network VGG19 based CNN feature extractor part. The HFE portion combines three feature extraction approaches into a single fused feature vector: Histogram-Oriented Gradient (HOG), Local Binary Pattern (LBP), and Speed Up Robust Feature (SURF). The CNN method also is used to extract additional features from test and training datasets. This two-feature vector is fused to design the classification model. This classifier performs the classification of dermoscopy images whether it is melanoma or non-melanoma skin cancer. The proposed methodology is performed on two ordinary datasets and achieved the accuracy 99.85%, sensitivity 91.65%, and specificity 95.70%, which makes it more successful than previous machine learning algorithms.

We show that the respective oversights in the von Neumann's general theorem against all hidden variable theories and Bell's theorem against their local-realistic counterparts are homologous. Both theorems unjustifiably assume the additivity of expectation values within hidden variable theories to derive their respective conclusions. However, for non-commuting observables, the equivalence of a sum of expectation values and the expectation value of the sum of measurement results, although respected within quantum mechanics, need not hold for hidden variable theories, regardless of specific characteristics such as local realism they may respect. Once this oversight is ameliorated from Bell's argument and local realism is implemented correctly, the bounds on the CHSH correlator work out to be +/-2\/2 instead of +/-2, thereby mitigating the conclusion of Bell's theorem. Consequently, what is ruled out by the Bell-test experiments is not local realism but the additivity of expectation values.

In this paper, a semi-empirical model of air waves induced by falling rock is described. The model is composed of a uniform motion phase (velocity close to 0 m·s^-1) and an acceleration movement phase. The uniform motion phase was determined based on experimentally and the acceleration movement phase was derived by theoretical analysis. A series of experiments were performed to verify the semi-empirical model and elucidated the law of the uniform motion phase. The acceleration movement phase accounted for a larger portion with a greater height of the falling rock. Experimental results of different falling heights of the goaf showed close agreement with theoretical analysis values. The semi-empirical model could accurately and conveniently estimate the velocity of air wave induced by falling rock. Thus, the semi-empirical model can provide a reference and basis for estimating the speed of air waves and designing protective measures in mines.

In this paper, we relate Poisson’s summation formula to Heisenberg’s uncertainty principle. They both express Fourier dualities within the space of tempered distributions and these dualities are furthermore the inverses of one another. While Poisson’s summation formula expresses a duality between discretization and periodization, Heisenberg’s uncertainty principle expresses a duality between regularization and localization. We define regularization and localization on generalized functions and show that the Fourier transform of regular functions are local functions and, vice versa, the Fourier transform of local functions are regular functions.

Nowadays, the transparency of governments with respect to the sustainability of public services is a very interesting issue for stakeholders and academics. It has led to previous research and international organisations (EU, IMF, OECD, United Nations, IFAC, G-20, World Bank) to recommend promotion of the online dissemination of economic, social and environmental information. Based on previous studies about e-government and the influence of administrative cultures on governmental accountability, this paper seeks to identify political actions useful to improve the practices of transparency on economic, social and environmental sustainability in European local governments. We perform a comparative analysis of sustainability information published on the websites of 72 local governments in 10 European countries grouped into main three cultural contexts (Anglo-Saxon, Southern European and Nordic). Using international sustainability reporting guidelines, our results reveal significant differences in local government transparency in each context. The most transparent local governments are the Anglo-Saxon ones, followed by Southern European and Nordic governments. Based on individualized empirical results for each administrative style, our conclusions propose useful policy interventions to enhance sustainability transparency within each cultural tradition, such as development of legal rules on transparency and sustainability, tools to motivate local managers for online diffusion of sustainability information and analysis of information needs of stakeholders.

Indoor positioning based on the received signal strength (RSS) of the WiFi signal has become the most popular solution for indoor localization. In order to realize the rapid deployment of indoor localization systems, solutions based on crowdsourcing have been proposed. However, compared to conventional methods, crowdsourced RSS values are more erroneous and can result in large localization errors. To mitigate the negative effect of the erroneous measurements, a graph-based semi-supervised learning (G-SSL) method is used to exploit the correlation between the RSS values at nearby locations to estimate an optimal RSS value at each location. Before using the G-SSL method, the Linear Regression (LR) algorithm is proposed to solve the device diversity problem in crowdsourcing system. Since the spatial distribution of the APs is sparse, the Compressed Sensing (CS) method is applied to precisely estimate the location of the APs. Based on the location of the APs and a simple signal propagation model, the RSS difference between different locations is calculated and used as an additional constraint to improve the performance of G-SSL. Furthermore, to exploit the sparsity of the weights used in the G-SSL, we use the CS method to reconstruct these weights more accurately and make a further improvement on the performance of the G-SSL. Experimental results show improved results in terms of the smoothness of the radio map and the localization accuracy.

Understanding the vulnerability of areas and the likelihood of specific disasters, particularly earthquakes, is one of the most important issues in Iran. One of the major concerns in Iran is the resilience of rural communities. The present study is devoted to spatial analysis of risk in rural areas and the evaluation of preparedness in the rural districts of the city of Abhar. In particular, this study evaluates the resilience to earthquakes. The research was conducted in two parts in which the first part has used the VIKOR Multiple criteria decision making model as well as the employment of this model in the ArcGis. The second part of the study used field studies, in the form of questionnaires, to evaluate the readiness of the local population against the risks of earthquakes. Four indicators, individual, physical, economic abilities and access, were assessed. The population included rural districts, where statistical samples were villagers. Results of the spatial analysis indicated that 15 villages are in the high-risk areas, 24 villages were in the medium-risk areas and all other villages were in low-risk areas. In terms of readiness of the locals, the results indicated a lack of planning with regards to the four mentioned indicators.

This study presents a vibration control using actively tunable vibration absorbers (ATVA) to suppress vibration of a thin plate. The ATVA’s is made of a sandwich hollow structure embedded with the electrorheological fluid (ERF). ERF is considered to be one of the most important smart fluids and it is suitable to be embedded in a smart structure due to its controllable viscosity property. ERF’s apparent viscosity can be controlled in response to the electric field and the change is reversible in 10 microseconds. Therefore, the physical properties of the ERF-embedded smart structure, such as the stiffness and damping coefficients, can be changed in response to the applied electric field. A mathematical model is difficult to be obtained to describe the exact characteristics of the ERF embedded ATVA because of the nonlinearity of ERF’s viscosity. Therefore, a fuzzy modeling and experimental validations of ERF-based ATVA from stationary random vibrations of thin plates are presented in this study. Because Type-2 fuzzy sets generalize Type-1 fuzzy sets so that more modelling uncertainties can be handled, a semi-active vibration controller is proposed based on Type-2 fuzzy sets. To investigate the different performances by using different types of fuzzy controllers, the experimental measurements employing type-1 fuzzy and interval type-2 fuzzy controllers are implemented by the Compact RIO embedded system. The fuzzy modeling framework and solution methods presented in this work can be used for design, performance analysis, and optimization of ATVA from stationary random vibration of thin plates.

In this study a new approach for planning Micro-Catchment Water Harvesting (M.C.W.H.) systems for irrigation in semi-arid regions such as the Aegean islands, is presented. M.C.W.H. is a cheap solution for constructing irrigation infrastructure with zero energy cost in regions where water is scarce. The proposed approach introduces simple linear relationships for estimating the annual volume of water V_s collected mainly from the CA (Contributing Area), stored in the root zone (Infiltration Basin, IB), according to the annual rainfall and runoff depths, after having determined the ratio of areas of micro-catchment (MC) components i.e. λ= Α_CA/Α_ΙΒ and its whole area A_MC This procedure was applied in Paros island of the Cyclades complex in the middle of the Aegean sea in east Mediterranean. Besides, income-cost analysis was performed via NPV method for almond, peach and apricot trees. The new approach was proved versatile and easy to use. Besides, the investment turned out to be advantageous two years after the MCs construction.

Forest community connections are crucial to ensure forest stewardship and sustainability. We set to explore the potential of mushrooming to enable such connections in contexts were these were historically broken, alienating local people from forests. Taking the case of the recent devolution of a community forest in central Portugal (baldios) to the local population, the authors present a five-year pilot project to rework mycology from a mushroom-centered approach to a mushroom-in-baldios approach. Mushrooms were used as an entry-point to connect the forest ecology with the challenges of governance and community building. The devised activities provided an opportunity for people inside and outside the local community to adventure into the woods, find about their socio-ecological history, develop communal and convivial relationships and engage in the responsible gathering of wild mushrooms. However, the hosting of mushroomers to know, value and engage with the community forest recovery is constantly worked against the enclosure of mushrooms to provide marketable forms of leisure. The outcome will depend on the relationships established between mushrooms, mycologists, local administrators, commoners and poachers, operating within a framework that favors the eradication of resources instead of the long-term relationships that sustain places.

The burdens of malnutrition, protein and micronutrient deficiency, and obesity cause enormous costs to society. Crop nutritional quality has been compromised by the emphasis on edible yield and through the loss of biodiversity due to the introduction of high-yielding uniform cultivars. Heirloom crop cultivars are traditional cultivars grown for a long time (> 50 years), and whose heritage has been preserved by regional, ethnic or family groups. Heirlooms are recognized for their unique appearance, names, uses and historical significance. They are gaining in popularity because of their unique flavors and cultural significance to local cuisine, and their role in sustainable food production for small-scale farmers. As a contrast to modern cultivars, heirlooms may offer a welcome alternative in certain markets. Recently, market channels have emerged for heirloom cultivars in the form of farmer-breeder-chef collaborations and seed savers organizations. There is therefore urgent need to know more about the traits available in heirloom cultivars, particularly for productivity, stress tolerance, proximate composition, sensory quality and flavor. This information is scattered and the intention of this review is to document some of the unique characteristics of heirloom cultivars that may be channeled into breeding programs for developing locally adapted high value cultivars.

Risk-averse areas such as the medical, aerospace and energy sectors have been somewhat slow towards accepting and applying Additive Manufacturing (AM) in many of their value chains. This is partly because there are still signicant uncertainties concerning the quality of AM builds. This paper introduces a machine learning algorithm for the automatic detection of faults in AM products. The approach is semi-supervised in that, during training, it is able to use data from both builds where the resulting components were certied and builds where the quality of the resulting components is unknown. This makes the approach cost ecient, particularly in scenarios where part certication is costly and time consuming. The study specically analyses Selective Laser Melting (SLM) builds. Key features are extracted from large sets of photodiode data, obtained during the building of 49 tensile test bars. Ultimate tensile strength (UTS) tests were then used to categorise each bar as `faulty' or `acceptable'. A fully supervised approach identied faulty specimens with a 77% success rate while the semi-supervised approach was able to consistently achieve similar results, despite being trained on a fraction of the available certication data. The results show that semi-supervised learning is a promising approach for the automatic certication of AM builds that can be implemented at a fraction of the cost currently required.

Local air quality is a major concern for the population regularly exposed to high levels of air pollution. The airport, mainly due to its aircraft engines activities during taxiing and take off, is often submitted to heterogeneous but important concentrations of NOx and PM. The study suggests an innovative approach to determine the air traffic impact on air quality at the scale of the airport, its runways and terminals, in order to be able to locate the persistent high concentrations spots. The pollutants concentrations at 10 m resolution and 1 s time step are calculated in order to identify the most affected areas of an airport platform. A real day of air traffic on a regional airport is simulated, using real data as aircraft trajectories (from radar streams). In order to estimate the aircraft emissions, the Air Transport Systems Evaluation Infrastructure (IESTA) is used. Regarding local air quality, IESTA relies on the non-hydrostatic meso-scale atmospheric model Meso-NH using grid-nesting capabilities with 3 domains, for this study. The detailed cartography of the airport distinguishes between grassland, parking and terminals, allowing to compute exchanges of heat, water and momentum between the different types of surfaces and the atmosphere as well as the interactions with the building using a drag force. The dynamic parameters like wind, temperature, turbulent kinetic energy and pollutants concentration are computed at 10 m resolution over the 2 × 4 km airport domain. The pollutants are considered in this preliminary study as passive tracers, without chemical reactions. This preliminary study aims at proving the feasibility of high scale modelling over an airport with state of the art physical models.

This paper considers a two-way relay network, where two source nodes exchange messages through several relays in the presence of an eavesdropper, and the channel state information (CSI) of the eavesdropper is imperfectly known. The amplify-and-forward relay protocol is used and the relay beamforming weights are designed. The model is built up to minimize the total relay transmit power while guaranteeing the quality of service at users and preventing the eavesdropper from decoding the signals. Due to the imperfect CSI, a semi-infinite programming problem is obtained. An algorithm is proposed to solve the problem, and the iterative points are updated through the linesearch technique, where the feasibility are preserved during iterations. The optimality property is analyzed. The obtained subproblems are quadratic constrained quadratic programming problems, either with less than $4$ constraints or with only one variable, which are solved optimally. Simulation results demonstrate the importance of the proposed model, and imply that the proposed algorithm is efficient and converges very fast, where more than 85% of the problems are solved optimally.

Bamboo agroforestry is currently being promoted as a viable land use option to reduce dependence on natural forest for wood fuels in Ghana. To align the design and introduction of bamboo agroforestry in conformity with farmers’ needs, perceptions, skills and local cultural practices, information on its acceptability and adoption potential among farmers is necessary. It is therefore the objective of this study to (1) describe bamboo ethnobotany and (2) assess socioeconomic factors that affect the acceptability and adoption of bamboo and its integration into farming practices. Accordingly, information has been collected from 200 farmers in the dry semi-deciduous forest zone of Ghana. The study identified the socioeconomic risks and uncertainties as well as biophysical factors that are likely to influence the potential adoption of bamboo agroforestry in the study region. Gender, age, farmers’ known uses of bamboo, the practice of leaving trees on farmlands, farmers’ networking and access to extension services, land availability and ownership by farmers were identified as suitable predictor variables for the adoption of bamboo agroforestry. It is envisaged that bamboo agroforestry is a good bet in the DSFZ though there is the need to explore domestic energy (fuelwood) provision and substitution potential in order to have a broader picture of the technology.

Soil salinity, whether natural or human induced, is a major geo-hazard in arid and semi-arid landscapes. In agricultural lands, it negatively affects plant growth, crop yields, whereas in semi-arid and arid non-agricultural areas it affects urban structures due to subsidence, corrosion and ground water quality, leading to further soil erosion and land degradation Accurately mapping soil salinity through remote sensing techniques has been an active area of research in the past few decades particularly for agricultural lands. Most of this research has focused on the utilization and development of salinity indices for properly mapping and identifying saline agricultural soils. This research study develops a soil salinity index and model using Landsat 8 OLI image data from the near infra-red and shortwave infra-red spectral information with emphasis on soil salinity mapping and assessment in non-agricultural desert arid and semi-arid surfaces. The developed index when integrated into a semi-empirical model outperformed in its soil salinity mapping overall accuracy (60%) in comparison to other salinity indices (~50%). The newly developed index further outperformed other indices in its accuracy in mapping and identifying high saline soils (67%) and excessively high saline soils (90%).

The objective is to study the local perceptions on the conservation of wild chimpanzees (Pan troglodytes verus) in the Réserve Naturelle Communautaire de Dindéfélo (RNCD), southeast of Senegal, to design specific actions to improve conservation management. We conducted 338 semi-structured interviews in three main villages of RNCD. Three-fourths of the population were farmers. Of those interviewed, 29% received elementary education. Two of the three villages participated in a project to plant trees as fences. On average, 66% of the respondents were animists. Of the respondents who were afraid to see a chimpanzee, 68% answered because they attack. Seventy-seven percent washed their clothes in the forest river because there was more water than in the village wells. Of the interviewees who threw the old clothes into the forest, 50% did it due to tradition. Ninety-six percent of respondents stated that chimpanzees do not feed from their crops. The main problems of the locals with the Reserve were lack of water and basic resources and not been allow to cut trees in protected areas. There were significant relationships between education (1 relationship), environmental project (4 relationships) and animism (11 relationships) with local perceptions. The 93% of the respondents who had the traditional belief that “if the old clothes were burnt, children would become sick” feel fear of chimpanzees, while those who did not have this animistic belief the 6% are afraid (χ² = 1.57, P < 0.02). These local perceptions allow us to design specific course of action to improve chimpanzee conservation and sustainable coexistence in this complex period of the Anthropocene.

Both climate change and anthropogenic activities contribute to the deterioration of terrestrial water resources and ecosystems worldwide. Central Asian endorheic basins are among the most affected regions through both climate and human impacts. Here, we used a digital elevation model, digitized bathymetry maps and Landsat images to estimate the areal water cover extent and volumetric storage changes in small terminal lakes in Burabay National Nature Park (BNNP), located in Northern Central Asia (CA), for the period of 1986 to 2016. Based on the analysis of long-term climatic data from meteorological stations, short-term hydrometeorological network observations, gridded climate datasets (CRU) and global atmospheric reanalysis (ERA Interim), we have evaluated the impacts of historical climatic conditions on the water balance of BNNP lake catchments. We also discuss the future based on regional climate model projections. We attribute the overall decline of BNNP lakes to long-term deficit of water balance with lake evaporation loss exceeding precipitation inputs. Direct anthropogenic water abstraction has a minor importance in water balance. However, the changes in watersheds caused by the expansion of human settlements and roads disrupting water drainage may play a more significant role in lake water storage decline. More precise water resources assessment at the local scale will be facilitated by further development of freely available higher spatial resolution remote sensing products. In addition, the results of this work can be used for the development of lake/reservoir evaporation models driven by remote sensing and atmospheric reanalysis data without the direct use of ground observations.

The role of public-sector organizations (PSOs) for promoting the agenda of sustainability accounting and accountability is often not adequately considered [1]. In the public sector universe, Local Governments are close to their communities and thus have a particularly important role to play in the pursuit of sustainability goals [2,3]. Hence, further research is still needed to understand if Local Governments Organizations (LGOs) are still using reporting tools to promote sustainable development. The empirical data show that the Sustainability Report (SR) is not having the spread assumed in the past years; over time, the great majority of Italian Municipalities does not continue or embark on a path of sustainability reporting. The findings suggest the fashion of SR in Italy is falling and it seems that the SR tool is a “mere trend reporting based on descriptive indicators leads to decreasing interest from internal and external audiences” [4]. The carrot is unsuccessful; maybe the mandatory requirements could be a stick?

Semi-solid feedstock of AZ80 magnesium alloy modified by minor rare-earth Y element (0, 0.2, 0.4, 0.8 wt.%) were fabricated by strain induces melting activated (SIMA) in the form of extrusion and partial remelting. The effect of Y addition on the microstructure evolution of extruded and isothermal treated alloy was observed by optical microscope (OM), scanning electron microscope (SEM), X-ray diffraction (XRD) and quantitative analysis. The results show that the Y addition can refine the microstructure and make the β-Mg17Al12 phases agglomerating. During the subsequent isothermal treatment at 570℃, the average solid grain size, shape factor and liquid fractions increased with prolonged soaking time. Smaller spheroidal solid grains and the larger shape factor were obtained due to Y addition. The coalescence and Ostwald ripening of solid grains operated the coarsening process simultaneously. The coarsening rate constants of AZ80M1 (0.2 wt.% Y addition) of 164.22 μm3s-1 was approximately four times less than the un-modified AZ80 alloy of 689.44 μm3s-1. In contrast, the desirable semi-solid structure featured by fine, well globular solid grains and appropriate liquid fractions and shape factor was achieved in AZ80M1 alloy treated at 570℃ for 20-30 min.

In this paper, a local meshless method (LMM) based on radial basis functions (RBFs) is utilized for the numerical solution of various types of PDEs, due to the flexibility with respect to geometry and high order of convergence rate. In case of global meshless methods, the two major deficiencies are the computational cost and the optimum value of shape parameter. Therefore, research is currently focus towards localized radial basis function approximations, as the local meshless method is proposed here. The local meshless procedures is used for spatial discretization whereas for temporal discretization different time integrators are employed. The proposed local meshless method is testified in terms of efficiency, accuracy and ease of implementation using regular and irregular domains.

This article presents the study of religious pluralism and decolonization of Indian mind in Russia. The paper analyzes the investigation results concerning psychological features of modern Indian students from universities in Russia and India. For measuring of connection between religious pluralism and decolonization of Indian mind we made socio-psychological investigation of Indian students. We made 254 semi-structured interview with Indian students who are studying in Russia and India. According to the result of investigation that decolonization of Indian mind is connected with the level of religious pluralism. Among the values principles of religious pluralism get more significance and importance in decolonizing mind of Indian students.

The issue of measurement reliability is certainly undervalued in the local agricultural marketplace organization. Besides, there was nothing identified concerning the extent of cereal commodity trade measurement cost. Hence, this paper aimed to estimate the magnitude of cereals trade quantity measurement cost caused by instrument error and unreliability; mainly by targeting the local marketplace in Ethiopia. The survey was conducted in six different districts’ marketplaces (n = 602) of Oromia region by employing administered structured questionnaires and site mass measurement calibration. The gathered data were analyzed using independent samples t-test, one sample t-test, and analysis of variance. According to the findings, the actual value measurement means of the quantity of most local units of the farmers were greater than small traders. The independent t-test result indicated that the average values of the quantity of the majority of units of measurement between farmers and small traders were varied significantly. Estimated measuring instruments’ error and unreliability associated average measurement cost of one-day market transaction over total cereals marketed amount were higher comparatively for a sack, bowl, and glass units. This study demonstrates that homogeneity in measurement, policy, and institutions that aid cereals trade would have an indispensable role to reduce measurement costs and ensure equitable exchange.

This study assesses attitudes of young adults' (18-30 years old) consumption on local and traditional products in7 European countries. A clustered sample (n=836) from natives of Greece, Bulgaria, Romania, Slovenia, Croatia, Denmark and France was collected, by distributing questionnaires through social media and university mail services. Sample was examined by implementing Principal Component Analysis (PCA) in three different samples; overall and two subgroups, Eastern and Western European countries. Six major factors revealed: consumer behavior, health issues, cost, influence from media and close environment and availability on store. As a result, young adults have a positive attitude to local and traditional food products but they express insecurity for health issues. Cost factor influences less people from Eastern European countries than those from the overall sample (3rd and 5th factor accordingly). Influence of close environment is a different factor in Eastern countries comparing to Western ones that it common with influence from media. Females and older people (25-30 years old) doubt less about TFPs, while media have high influence on consumers’ decisions. Aim of this survey is to create consumer profiles of young adults and create different promotion strategies of local and traditional products among the two groups of countries.

Land degradation monitoring and assessment in the Sahel zone has relied substantially on temporal trends of remote sensing-based vegetation indices, which are proxies for the bioproductivity of the land. However, prior studies have shown that negative or positive trends in bioproductivity are not necessarily associated with degradation or improvement of land condition. In this short communication, while acknowledging the contributions of remote sensing-based indices and global-scale datasets to dismantling an outdated desertification narrative, we argue that local land users have much to contribute to our understanding of land degradation, and particularly to ensuring that scientific assessments of degradation capture variables relevant to them. We used the participatory photo elicitation method in three sites in the Senegalese Ferlo in order to elicit local pastoralists’ perspectives on land degradation and identify the indicators that they use to characterize pasture quality, while empowering them to lead the discussion. The discussion revealed indicators far beyond bioproductivity, including livestock performance as well as composition and quality of the herbaceous and woody vegetative cover, invasive species, soil quality and water availability. We found that the pastoralists’ knowledge and interest in the issue could potentially be harnessed more systematically, and at larger scales, in order to build a spatially explicit field-based knowledge base of land degradation complementary to remote sensing-based maps of trends in bioproductivity. Such a dataset could serve as a standalone product or as a reference dataset for development and validation of remote sensing-based indicators.

: On earth, plants play the most important part. Every organ of a plant plays a vital role in the ecological field as well as the medicinal field. But on the whole earth there are several species of plants are available. Different plants have different diseases. Therefore it is needed to identify the plants and their diseases to prevent loss. Now to identify the plants and their diseases manually is very time consuming. In this research an automatic plant and their disease detection system is proposed. For experimental purposes, high-quality leaf images are accepted for training and testing. For detecting the healthy and diseased area in a leaf, region-based and color-based region thresholding techniques were used. For feature selection Histogram Oriented Gradient (HOG) and Local Binary Pattern (LBP) method were applied. Finally for classification two-class and multi-class Support Vector Machine (SVM) was used. It is observed that both feature selection processes with SVM give 99% accuracy. Finally to understand the automated system a graphical user interface was created for all users.

This paper presents novel feature descriptors and classification algorithms for automated scoring of HER2 in Whole Slide Images (WSI) of breast cancer histology slides. Since a large amount of processing is involved in analyzing WSI images, the primary design goal has been to keep the computational complexity to the minimum possible level and to use simple, yet robust feature descriptors that can provide accurate classification of the slides. We propose two types of feature descriptors that encode important information about staining patterns and the percentage of staining present in ImmunoHistoChemistry (IHC) stained slides. The first descriptor is called a characteristic curve which is a smooth non-increasing curve that represents the variation of percentage of staining with saturation levels. The second new descriptor introduced in this paper is an LBP feature curve which is also a non-increasing smooth curve that represents the local texture of the staining patterns. Both descriptors show excellent interclass variance and intraclass correlation, and are suitable for the design of automatic HER2 classification algorithms. This paper gives the detailed theoretical aspects of the feature descriptors and also provides experimental results and comparative analysis.

The problem of fluid dynamics can be greatly simplified if, for every point in space, the strain-rate tensor is diagonalized. This tensor is introduced into the Navier-Stokes equations via material law and divergence of the stress tensor. This article shows that local SO(3)xU(1) gauge fields can be used to locally diagonalize the diffusion components of the strain-rate tensor. The gauge fields resulting from the connection can be interpreted as convection components of the flow, they show properties of quasiparticles and can be interpreted as elementary vortices. Thus, the proposed approach not only offers new insights for the solution and situative simplification of the Navier-Stokes equations, it also uncovers hidden symmetries within the flow convection, allowing - depending on boundary conditions - further interpretation.

Since the public inauguration of the URP (Urban and Regional Planning) Bill in 2009, which is now law (The Urban and Regional Planning Act No. 3 of 2015), urban planning in Zambia has undergone changes. In partnership with the Volunteer Service Overseas (VSO) Federation, the Zambian parliament put into effect pilot urban planning assistance programs to assist districts around the country, including Chipata District in 2011, transition to a more decentralized, integrated and locally-defined approach to urban planning. However, the presence of discrimination, corruption, and negative attitudes towards urban planning engagement, social maladies prominently displayed in Zambian society, pose challenges to implementing the ideal goals of the 2009 URP Bill. The extreme, widespread poverty in Zambia merely exacerbates the propensity towards corrupt and discriminatory behavior, and influences poor attitudes toward urban planning engagement. This paper describes the projects undertaken by the VSO volunteer from the USA between 2011 and 2012 in the light of the specific urban problems facing Chipata District, and discusses the ways the social maladies play out in Zambian society to pose challenges to implementing the recommended changes to the planning system scribed in the 2009 URP Bill.

External impact on the development of fluvial systems is generally exerted by changes in sea level, climate and tectonic movements. In this study it is shown that regional to local differentiation of fluvial response may be caused by semi-direct effects of climate change and tectonic movement, as for instance vegetation cover, frozen soil, snow cover and longitudinal gradient. Such semi-direct effects may be responsible for specific fluvial activity resulting in proper drainage patterns, sedimentation series and erosion-accumulation rates. These conclusions are exemplified by the study of the Tis(z)a catchment in the Pannonian Basin in Hungary and Serbia from the middle of the last glacial to the Pleistocene-Holocene transition. Previous investigations in that catchment are supplemented here by new geomorphological-sedimentological data and OSL-dating. Specific characteristics of this catchment in comparison with other regions are the preponderance of meandering systems during the last glacial and the presence of very large meanders in given time intervals.

Speckle noise reduction is an important area of research in the field of ultrasound image processing. Several algorithms for speckle noise characterization and analysis have been recently proposed in the area. Synthetic ultrasound images can play a key role in noise evaluation methods as they can be used to generate a variety of speckle noise models under different interpolation and sampling schemes, and can also provide valuable ground truth data for estimating the accuracy of the chosen methods. However, not much work has been done in the area of modelling synthetic ultrasound images, and in simulating speckle noise generation to get images that are as close as possible to real ultrasound images. An important aspect of simulated synthetic ultrasound images is the requirement for extensive quality assessment for ensuring that they have the texture characteristics and gray-tone features of real images. This paper presents texture feature analysis of synthetic ultrasound images using local binary patterns (LBP) and demonstrates the usefulness of a set of LBP features for image quality assessment. Experimental results presented in the paper clearly show how these features could provide an accurate quality metric that correlates very well with subjective evaluations performed by clinical experts.

The disruption of conventional manufacturing, supply, and distribution channels for medical supplies during the COVID-19 pandemic has caused widespread shortages and catalyzed local efforts to use nontraditional, rapid manufacturing to meet urgent healthcare needs. Here we present a crisis-responsive design framework designed to assist with product development under pandemic conditions. The framework utilizes extensive stakeholder engagement, comprehensive and dynamic needs assessment, local manufacturing, and product testing for the accelerated development of healthcare products. We contrast this framework with traditional medical device manufacturing and discuss relevant regulatory policies. We highlight the applicability of the crisis-responsive framework to a successful local program that designed and supplied face shields for a large US academic hospital. Finally, we make recommendations aimed at improving future resilience to healthcare emergencies. These include continued development of open source designs suitable for rapid manufacturing and changes in regulatory policy that strike a balance between rigidity and uncontrolled innovation.

Women have been leading organizations and communities for centuries, but their journeys in leadership have sometimes been challenging. This paper aims to reflect on women's positive and negative experiences in leadership roles and understand the factors contributing to their successes and challenges.To explore these issues, we will draw on various academic literature, including studies on gender and leadership and case studies of women in leadership positions. We will also examine the cultural and social factors that affect women's experiences in leadership, including bias and discrimination, societal expectations, and work-life balance challenges.One key theme from this analysis is the importance of role models and support networks in helping women succeed in leadership roles. Women with access to mentorship, sponsorship, and peer networks are more likely to thrive in their roles and overcome the challenges they may face. However, lacking female role models and mentors can make it difficult for women to advance in their careers and contribute to feelings of isolation and imposter syndrome.Another important theme is the need for organizations and society to address systemic biases and discrimination that prevent women from reaching their full potential. This can include initiatives such as unconscious bias training, flexible work arrangements, and policies that support gender diversity and inclusion.In conclusion, this paper highlights women's positive and negative experiences in leadership roles and emphasizes the need for ongoing efforts to support and empower women in leadership. By addressing the challenges women face and building a culture of inclusion and support, organizations and society can help unlock the full potential of women leaders and create a more equitable and just world.

In order to coordinate the damping performance and energy regenerative performance of energy regenerative suspension, this paper proposes a structure of vehicle semi-active energy regenerative suspension with electro-hydraulic actuator (EHA). In light of the proposed concept, a specific energy regenerative scheme is designed and the mechanical properties test is carried out. Based on the test results, the parameter identification for the system model is conducted using recursive least squares algorithm. On the basis of system principle, the nonlinear model of the semi-active energy regenerative suspension with EHA is built. Meanwhile, LQG control strategy of the system is designed. And then the influence of the main parameters of EHA on the damping performance and energy regenerative performance of suspension is analyzed. Finally, the main parameters of EHA actuator are optimized via genetic algorithm. The test results show that when sinusoidal is input at the frequency of 2Hz and the amplitude of 30mm, the spring mass acceleration RMS value of optimized EHA semi-active energy regenerative suspension is reduced by 22.23% and energy regenerative power RMS value is increased by 40.51%, which means while meeting the requirements of certain vehicle ride comfort and driving safety, energy regenerative performance is improved significantly.

We mainly describe the influence factors of captured power by huge wave energy harvesters, which the vertical motion of buoy can transform ocean’s potential energy into piezoelectric energy power by waves. By means of semi-analytical solutions and theoretical analysis, related environmental coefficients are analyzed firstly and find the most appropriate wave frequency and geometric structure as reference. Secondly, the numerical results also discuss the impact trend of hydrodynamic parameters and geometric volume on motion, voltage and power with qualitative agreement. The simulation data confirm that structure parameters of the modified model could markedly deliver sufficient power to ocean high electrical equipment with long-time stability.

To determine the photon emission or absorption probability for a diatomic system in the context of the semiclassical approximation it is necessary to calculate the characteristic canonical oscillatory integral which has one or more saddle points. Integrals like that appear in a whole range of physical problems, e.g. the atom-atom and atom-surface scattering and various optical phenomena. A uniform approximation of the integral, based on the stationary phase method is proposed, where the integral with several saddle points is replaced by a sum of integrals each having only one or at most two real saddle points and is easily soluble. In this way we formally reduce the codimension in canonical integrals of "elementary catastrophes" with codimensions greater than 1. The validity of the proposed method was tested on examples of integrals with three saddle points ("cusp" catastrophe) and four saddle points ("swallow-tail" catastrophe).

The impact of an unlicensed low-cost taxi in Bangladesh is very severe, especially in municipal cities. Day by day the numbers of unlicensed low-cost taxi are increasing by jumping up and creating pressure on traffic and transportation system. The aim of this study is to find out the causes of increasing illegal taxi and the extent of this vehicle in the municipalities of Bangladesh. Pabna municipality is used as a case study due to the more activeness of illegal taxi then the other municipalities. To achieve the objectives, the researcher used a qualitative approach to acquire more depth about the problems. Besides a direct observation of the study area, an open-ended questionnaire survey and HIS survey were conducted. The illegal low-cost taxi is very active it was analyzed through the field survey. A statistical model was developed to understand the actual causes of increasing illegal low-cost taxi, where ten predicted hypotheses (age, education level, marital status and family member support of illegal drivers, and the variable of commuter satisfaction e.g. safety, comfort, continuous service, affordability of service, reliability of service and driver behavior) were tested. The model was run through the multiple regression analyses technique in SPSS and the result proved that education level of illegal low-cost taxi drivers, and the commuter satisfaction variable (safety and comfort) had a positive and significant effect of increasing illegal low-cost taxi in the study area. However other variable had no significant effect in case of increasing illegal low-cost taxi. Besides the safety and comfort, steady job for the operators, provision of continuous, individual and door to door service system are the main reasons for increasing the illegal low-cost taxi in the study area. Finally, the researcher concludes with the requirement of some necessary action from the responsible authority on vehicular regulation for the improvement of the local public transport system in Bangladesh.

: Mistrust, amplified by numerous artificial intelligence (AI) related incidents, has caused the energy and industrial sectors to be amongst the slowest adopter of AI methods. Central to this issue is the black-box problem of AI, which impedes investments and fast becoming a legal hazard for users. Explainable AI (XAI) is a recent paradigm to tackle this challenge. Being the backbone of the industry, the prognostic and health management (PHM) domain has recently been introduced to XAI. However, many deficiencies, particularly lack of explanation assessment methods and uncertainty quantification, plague this young field. In this paper, we elaborate a framework on explainable anomaly detection and failure prognostic employing a Bayesian deep learning model to generate local and global explanations from the PHM tasks. An uncertainty measure of the Bayesian model is utilized as marker for anomalies expanding the prognostic explanation scope to include model’s confidence. Also, the global explanation is used to improve prognostic performance, an aspect neglected from the handful of PHM-XAI publications. The quality of the explanation is finally examined employing local accuracy and consistency properties. The method is tested on real-world gas turbine anomalies and synthetic turbofan data failure prediction. Seven out of eight of the tested anomalies were successfully identified. Additionally, the prognostic outcome showed 19% improvement in statistical terms and achieved the highest prognostic score amongst best published results on the topic.

This paper is devoted to the study of reproducing kernels on 2-inner product Hilbert spaces. We focus on a new structure to produce reproducing kernel Hilbert and Banach spaces. According to multi-variable computing, this structures can be useful in electrocardiographs, machine learning and economy

Regional product labeling can help develop regional business activities, especially with traditional regional products. Their general popularity is a significant source of income for the less developed regions. The Gemer-Malohont region belongs to economically underdeveloped areas with high unemployment rate. The subject of the survey was regional food products, which are made by small farmer. The analysis was carried out on a questionnaire survey in the period April-July 2017 in each of the region's districts. The results obtained by questionnaire survey have been statistically processed using the statistical method (two-step cluster analysis, radar chart, box-plots, regression analysis) using Microsoft Excel and IBM SPSS Statistics 23 software. Through cluster analysis and based on the preference of regional food, we divided consumers into two groups - knowledgeable regional food purchasers and priced oriented consumers. We have shown that the more developed regions (Rimavská Sobota, Rožňava) show a higher rate of purchase of regional foods. Less developed regions (Poltár, Revúca) are represented by lower-income consumers for whose the food price is the decisive criterion. Local residents of backward regions should pay attention to domestic food and local small farmers, who are the way to create local capital and local development.

The objective of this research is to develop an experimental-theoretical analysis about the influence of the cooling medium and the geometry of the welding bead profile in fatigue life and associated parameters with structural integrity of welded joints. A welded joint with cruciform geometry is considered using SMAW, plates in structural steel ASTM A36 HR of 8 mm of thickness and E6013 electrode input. A three-dimensional computational model of the cruciform joint was created using the finite element method. For this model, the surface undulation of the cord and differentiation in the mechanical properties of the fusion zone were considered, the heat-affected zone (HAZ) and base material, respectively. In addition, an initial residual stress field which was established experimentally was considered. The results were a set of analytical expressions for the weld magnification factor Mk. It was found that values for the latter decrease markedly in function of the intensity of the cooling medium used in the post welding cooling phase, mainly due to the effect of the residual compressive stresses. The obtained models of behavior of the weld magnification factor are compared with the results from other researchers with some small differences, mainly due to the inclusion of the cooling effect of the post weld and the variation of the leg of the weld bead. The obtained analytical equations in the present research for Mk can be used in management models of life and structural integrity for this type of welded joint.

Exercise-based cardiac rehabilitation requires patients to perform a set of certain prescribed exercises a specific number of times. Local muscular endurance (LME) exercises are an important part of the rehabilitation program. Automatic exercise recognition and repetition counting, from wearable sensor data is an important technology to enable patients to perform exercises independently in remote settings, e.g. their own home. In this paper we first report on a comparison of traditional approaches to exercise recognition and repetition counting, corresponding to supervised machine learning and peak detection from inertial sensing signals respectively, with more recent machine learning approaches, specifically Convolutional Neural Networks (CNNs). We investigated two different types of CNN: one using the AlexNet architecture, the other using time-series array. We found that the performance of CNN based approaches were better than the traditional approaches. For exercise recognition task, we found that the AlexNet based single CNN model outperformed other methods with an overall 97.18% F1-score measure. For exercise repetition counting , again the AlexNet architecture based single CNN model outperformed other methods by correctly counting repetitions in 90% of the performed exercise sets within an error of ±1. To the best of our knowledge, our approach of using a single CNN method for both recognition and repetition counting is novel. In addition to reporting our findings, we also make the dataset we created, the INSIGHT-LME dataset, publicly available to encourage further research.

The search for new materials that could improve the energy density of Li-ion batteries (LIB) is one of today’s most challenging issues. Recently, cation-disordered lithium-excess metal oxides have emerged as a promising new class of cathode materials for LIB, due to their high reversible capacities and nice structural stability. However, a full structural model of the Li-transition metal (TM) sharing sublattice and the origin of short range ordering (SRO) of cation ions requires further investigation. In this work, we put forward a Monte Carlo strategy of building a cation-disordered rocksalt material supercell model. The cation ions of Li_1.0Ti_0.5Ni_0.5O₂ (LTNO) are placed at the FCC sublattice sites with the constraint of Pauling’s electroneutrality rule, instead of a random way. This constraint causes the Li-Ti and Ni-Ni clustering (the cation short range ordering). Based on this model, we discussed the relationship between the short range ordering, the local distorting, the theoretic capacity and the order-disorder strengths. A unified understanding of these factors in cation-disordered materials may enable a better design of disordered-electrode materials with high capacity and high energy density.

For voltage-gated Ca2+ channel (VGCC), its α2δ subunits are traditionally considered to be auxiliary subunits that regulates VGCC trafficking to the plasma membrane. The antiepileptic, antinociceptive and anxiolytic gabapentin (GBP) has previously been shown to bind the VGCC α2δ subunits with high affinity to disrupt VGCC trafficking. Yet, the interaction between GBP and α2δ still remains poorly understood from a structural point of view. For instance, it is not clear yet what the structural implication is of α2δ-1-bound GBP against VGCC trafficking. With a set of experimental data-driven structural analysis of the VGCC α2δ-1 and its ligand GBP, this article postulates for the first time that: 1), α2δ-1 bound GBP stabilizes the α2δ-1-GBP complex structure; 2), α2δ-1 bound GBP restrains the conformational flexibility of α2δ-1; 3), α2δ-1-bound GBP establishes an electrostatic axis consisting of Q535 (Gln535)-R241 (Arg241)-GBP (gabapentin)-D452 (Asp452), which constitutes an energetically favourable contribution towards the structural stability of the α2δ-1-GBP complex and helps restrains the conformational flexibility and local structural rigidification of α2δ-1; and 4), GBP-induced local conformational inflexibility and structural rigidification of α2δ-1 is one key step in the pharmacological disruption of VGCC trafficking by GBP.

Despite a global push in the development and implementation of widespread alternative energy use, significant disparities exist across given nation-states. These disparities reflect both technical and economic factors, as well as the social, political, and ecological gaps between how communities see energy development and national/global policy goals. Known as the “local-national gap,” many nations struggle with fostering meaningful conversations about the role of alternative energy technologies within communities. Mitigation of this problem first requires understanding the distribution of existing alternative energy technologies at the local level of policymaking. Using the State of Georgia, U.S.A. as a case study, we present a model for analyzing how existing adoption trends enable/limit conversation at the scale of local governance (i.e., county governments). Leveraging existing work on the Gini Coefficient as a metric for measuring energy inequity, we argue these tools can be applied to analyze where gaps exist in ongoing solar adoption trends. As we demonstrate, communities that adopt solar tend to be concentrated in a few counties, indicating existing conversations are limited to a circumscribed set of social networks. This information and the model we demonstrate can enable focused qualitative analyses of existing solar trends, not only amongst high-adoption areas but within communities where little to no adoption has occurred.

Surface urban heat island (SUHI) depicts the deteriorating thermal environment in high-density cities and local climate zone (LCZ) classification provides a universal protocol for SUHI identification. In this study, taking the central urbanized area of Guangzhou in the humid subtropical region of China as the study area, the maps or images of LCZ, land surface temperature (LST), SUHI and urban design factors were achieved by using Landsat satellite data, GIS database and a series of retrieval and classification algorithms, and the urban design factors influencing SUHI were investigated based on 625 samples of LCZs. The results show that in the summer daytime under the clear sky condition, the LST varied greatly from 26 °C to 40 °C and the SUHI changed in a wide range of -6 °C to 8 °C in the LCZs of the study area. Seven and five urban design factors influencing the summer daytime SUHI were identified for the two dominant LCZ of LCZs 1-5 (LCZ 1 to LCZ 5) and the mixed LCZ (containing at least three types of LCZs), respectively. The summer daytime SUHI prediction models were obtained by using the step-wise multiple linear regression, with the performance of R2 of 0.697, RMSE of 1.21 °C, and the d value of 0.81 for the model of LCZs 1-5, and the values of 0.666, 1.66 °C, and 0.76 for the model of the mixed LCZ, indicating that the models can predict the changes of SUHI with LCZs to a large and satisfactory extent. This study presents a methodology to efficiently achieve a large sample of SUHI and urban design factors of LCZs in the largely urbanized cities, and provides information beneficial to the urban designs and regenerations in the humid subtropical region.

Global environmental and societal changes threaten the cultures of Indigenous Peoples and Local Communities (IPLC). Despite the importance of IPLC worldviews and knowledge systems to human well-being and biodiversity, risks to these cultural resources are commonly simplified or neglected in environmental impact assessments, in part because cultural impacts are often indirect and therefore difficult to demonstrate. Here, we show that dependency of a culture on the environment can be mapped through human connections with biophysical elements in their environment. We illustrate a rich variety of cultural values that connect an indigenous Māori tribe in New Zealand with their local environment, then evaluate the resilience of this socio-environmental value system to environmental changes. Our results detail how loss of access to key environmental elements can have extensive direct and cascading impacts on multiple facets of indigenous cultural heritage. Consequently, considering only direct effects of environmental change on cultural heritage, or treating the richness of IPLC environmental relations simplistically, can severely underestimate the seriousness of environmental impacts on IPLC culture. Thus, protecting Earth’s cultural and biological diversity requires inclusion of human-environment relationships in environmental impact assessments.

I demonstrate that Bell's theorem is based on circular reasoning and thus a fundamentally flawed argument. It unjustifiably assumes the additivity of expectation values for dispersion-free states of contextual hidden variable theories for non-commuting observables involved in Bell-test experiments, which is tautologous to assuming the bounds of ±2 on the Bell-CHSH sum of expectation values. Its premises thus assume in a different guise the bounds of ±2 it sets out to prove. Once this oversight is ameliorated from Bell's argument, the bounds on the Bell-CHSH sum of expectation values work out to be ±2√2 instead of ±2, thereby mitigating the conclusion of Bell's theorem. Consequently, what is ruled out by the Bell-test experiments is not local realism but the additivity of expectation values, which does not hold for non-commuting observables in any hidden variable theories to begin with.

Life on Earth evolved to accommodate the biochemical and biophysical boundary conditions of the planet millions of years ago. The former includes nutrients, water, and ability to synthesize other needed chemicals. The latter include the 1 g gravity of the planet, radiation, and the geomagnetic field (GMF)of the planet. How complex life forms have accommodated the GMF is not known in detail considering that Homo sapiens evolved a neuro system and a cardiovascular system that develops electromagnetic fields as part of their functioning. In addition, many proteins and physiologic processes utilize Fe ions, an ion that exhibits magnetic properties. Thus, complex organisms such as current humans generate magnetic fields, contain significant quantities of the Fe ion, and also respond to exogenous-supplied static and electromagnetic fields. Whether humans can store information in self-generated magnetic fields remains to be determined. Given the current body of literature, it remains somewhat unclear how Homo sapiens use exogenous magnetic fields to regulate function, and what can happen if the boundary condition of the GMF of Earth is no longer exerting an effect. Proposed deep space flights to destinations such as Mars will provide some insights as space flight could not have been anticipated by evolution. The results of such space flight “experiments” will provide new insights in the role of magnetic fields on human functioning. The outcomes may also have implications for those on Earth as magnetic field influences may play a role in developmental conditions such as autism and senescence-associated conditions such as dementia when integration of the biological and biophysical aspects of humans of humans are required for effective functioning. This review will discuss the involvement of magnetic fields on various normal and disturbed processes in humans while on Earth and then further discuss potential outcomes when the GMF is no longer available to impact host systems. Thus, the GMF of the Earth has been present throughout evolution but details of its role in human functions still remain to be elucidated.

Factorization reduces computational complexity and is therefore an important tool in statistical machine learning of high dimensional systems. Conventional molecular modeling, including molecular dynamics and Monte Carlo simulations of molecular systems, is a large research field based on approximate factorization of molecular interactions. Recently, the local distribution theory was proposed to factorize global joint distribution of a given molecular system into trainable local distributions. Belief propagation algorithms are a family of exact factorization algorithms for trees and are extended to approximate loopy belief propagation algorithms for graphs with loops. Despite the fact that factorization of probability distribution is their common foundation, computational research in molecular systems and machine learning studies utilizing belief propagation algorithms have been carried out independently with respective track of algorithm development. The connection and differences among these factorization algorithms are briefly presented in this perspective, with the hope to intrigue further development in factorization algorithms for physical modeling of complex molecular systems.

This paper considers target characterization and recognition in radar images with keypoint-based local descriptor. Most of the preceding works rely on the global features or raw intensity values, and hence produce the limited recognition performance. Moreover, the global features are sensitive to the real-world sources of variability, such as aspect view, configu-ration, and incidence angle changes, clutter, articulation, and occlusion. Keypoint-based local descriptor was developed as a powerful strategy to address invariance to contrast change and geometric distortion. This property inspires us to investigate whether the family of local features are relevant for radar target recognition. Most of the preceding works typically devote to finding the correspondences between a collected image and a reference one. The representative applications include image register and change detection. Little work was pursued to target recognition in SAR images. This is because the huge number of local descriptors resulting from radar images make the computational cost and memory consumption unacceptable. To handle the problems, this paper develops two families of methods. The proposed methods are used to achieve target recognition by means of local descriptors. Our first solver refers to building multiple linear regression models, and addresses the problem by the theory of sparse representation. The second scheme rebuilds a new feature by the feature quantization skill, from which the inference can be drawn. Multiple comparative studies are pursued to verify the performance of detectors and descriptors popularly used. The source code was publicly released on https://ganggangdong.github.io/homepage/.

We review a theory that predicts the onset of thermalization in a quantum mechanical coupled non-linear oscillator system, which models the vibrational degrees of freedom of a molecule. A system of N non-linear oscillators perturbed by cubic anharmonic interactions exhibits a many-body localization (MBL) transition in the vibrational state space (VSS) of the molecule. This transition can occur at rather high energy in a sizable molecule because the density of states coupled by cubic anharmonic terms scales as ~ N3, in marked contrast to the total density of states, which scales as exp(aN), where a is a constant. The emergence of a MBL transition in the VSS is seen by analysis of a random matrix ensemble that captures the locality of coupling in the VSS, referred to as local random matrix theory (LRMT). Upon introducing higher order anharmonicity, the location of the MBL transition of even a sizable molecule, such as an organic molecule with tens of atoms, still lies at an energy that may exceed the energy to surmount a barrier to reaction, such as a barrier to conformational change. Illustrative calculations are provided, and some recent work on the influence of thermalization on thermal conduction in molecular junctions is also discussed.

Sequence analysis program is outlined that analyzes and investigates homology between various nucleic acid or protein sequence. The dot matrix technique compares the sequences and the consensus sequence is obtained by superimposing on each other all the dot matrices. Local Alignment and Global Alignment both sequence from start to end is the best possible alignment over the entire duration between the two sequences. This method is more important to align with two closely related sequences roughly the same length. This method may not able to generate optimal results for divergent sequences and variable length sequence because between the two sequences it does not recognize very similar local region.

Several specific types of generalized compactness of generalized topological spaces have been defined, investigated and related to compactness in ordinary topological spaces from time to time in the literature of topological spaces. Our recent research in the field of a new class of generalized compactness in a generalized topological space is reported herein as a starting point for more generalized classes.

Sustainability, as well as a concept related to a development model, is becoming a real guide to drive the governance choices of value chains. A sustainable policy has the objective of perpetuating production models over time while maintaining the environmental, economic and social dimensions that characterize a given production process. It is therefore important to measure the sustainability of a production system in its environmental, social and economic components and to understand the ongoing trends under the pressure of agricultural policies, market dynamics and innovation pattern introduced along the time in a production system. The purpose of the article is to assess the evolution of the level of sustainability of Parmigiano Reggiano production system under the effect of 20 years of innovation mechanism which impact on product quality, value chain performance and rural development. To this aim the paper discuss a holistic framework that allows the representation of stakeholder’s role considering the value chain and the territorial dimension. The paper discus also the use of dimensional indicators and propose a use of synthetic indexes to provide an overall picture of the evolution of sustainability of specific production system.

Use of local anesthesia at the time of ring castration and tail docking can improve lamb welfare. However, few local anesthetics are registered for sheep, and data on their duration of effect is limited. Three studies were conducted to evaluate the efficacy of procaine (P), lidocaine (L) and bupivacaine (B) in terms of observed alleviation of behavioral responses to castration and/or tail docking in 10-min blocks in the first 60 min post treatment. In each study, comparisons were made between two groups of lambs castrated and/or tail docked with rubber rings and either receiving the agent using the NUMNUTS® instrument (N) or receiving no anesthetic agent (RR). Acute pain behavior was lower in NL (n = 28) than RRL (n = 15) males in the first 10 min post procedure (P &lt; 0.05); lower in NB (n = 16) than RRB (n = 16) males in periods 10-20 min (0.05 &lt; P &lt; 0.01), 20-30 min (P &lt; 0.05) and 40-50 min (0.05 &lt; P &lt; 0.01); lower in NB (n = 16) than RRB (n = 16) females between 20 and 40 min post-procedure (0.05 &lt; P &lt; 0.01); lower in NP (n = 8) than RRP (n = 7) males in period 10-20 min (0.05 &lt; P &lt; 0.01), and lower in NP (n = 9) than RRP (n = 9) females in periods 0-10 min (0.05 &lt; P &lt; 0.01), and 10-40 min (P &lt; 0.05). Analgesic benefits were modest, and the effects of procaine appear to last longer than lidocaine, while bupivacaine is slower to take effect than either procaine or lidocaine but may provide longer lasting analgesia. The duration of action of local anesthetics is short in sheep, and detailed behavioral evaluations are required in the first hour post procedure to establish efficacy.

Molecular modeling is widely utilized in subjects including but not limited to physics, chemistry, biology, materials science and engineering. Impressive progress has been made in development of theories, algorithms and software packages. To divide and conquer, and to cache intermediate results have been long standing principles in development of algorithms. Not surprisingly, Most of important methodological advancements in more than half century of molecule modeling are various implementations of these two fundamental principles. In the mainstream classical computational molecular science based on force fields parameterization by coarse graining, tremendous efforts have been invested on two lines of algorithm development. The first is coarse graining, which is to represent multiple basic particles in higher resolution modeling as a single larger and softer particle in lower resolution counterpart, with resulting force fields of partial transferability at the expense of some information loss. The second is enhanced sampling, which realizes "dividing and conquering" and/or "caching" in configurational space with focus either on reaction coordinates and collective variables as in metadynamics and related algorithms, or on the transition matrix and state discretization as in Markov state models. For this line of algorithms, spatial resolution is maintained but no transferability is available. Deep learning has been utilized to realize more efficient and accurate ways of "dividing and conquering" and "caching" along these two lines of algorithmic research. We proposed and demonstrated the local free energy landscape approach, a new framework for classical computational molecular science and a third class of algorithm that facilitates molecular modeling through partially transferable in resolution "caching" of distributions for local clusters of molecular degrees of freedom. Differences, connections and potential interactions among these three algorithmic directions are discussed, with the hope to stimulate development of more elegant, efficient and reliable formulations and algorithms for "dividing and conquering" and "caching" in complex molecular systems.

To reduce solar power production invariance, it is critical to study varying patterns of power production in the concerned region. Analyzing the patterns of past power production trends can help simulate power production scenarios for future. The current study area is around Amsterdam, located in Netherlands. PVoutput.org website is used to mine 6 months of solar power production data for 120 stations around Amsterdam city. FME Workbench software is used to actively fetch the data from the mentioned website and manage in a MySQL database. Solar attenuation maps created using ArcGIS, helped to graphically visualize the variations in solar power production at different times and locations. Further, spatial autocorrelation is checked between the stations using semi-variograms in geostatistical tool of ArcMap. This feature allows to check whether the stations located close to each other are more correlated to each other rather than stations which are far apart. The statistical data analysis of power production can aid solar power production companies to better interpolate and predict solar power in advance for the concerned study region.

The City of Pasadena is located in southern California; a region which has a Mediterranean climate and where the vast majority of rainfall occurs between October and April with the period between January and March being the most intense. A significant amount of the local water supply comes from regional rainfall, therefore any changes in precipitation patterns in the area has considerable significance. HYPOTHESIS: Local climate change has been occurring in the Pasadena area over the last 100 years resulting in changes in air temperature and rainfall. AIR TEMPERATURES: Between 1886 and 2016 the air temperature in Pasadena, California has increased significantly, from a minimum of 23.8°C in the daytime and 8.1°C at night between 1911 and 1920 to 27.2°C and 13.3°C between 2011 and 2016. The increase in nighttime temperature was uniform throughout the year, however daytime temperatures showed more seasonal variation. There was little change in the daytime temperatures May through July but more change the rest of the year. For example, the median daytime temperature for June between 1911 and 1920 was 27.9°C but was 28.7°C between 2011 and 2016, a difference of 0.8°C. In contrast, for October for the same periods the median daytime temperatures were 25.6°C and 28.9°C, a difference of 3.3°C. RAINFALL: There has been a change in local rainfall pattern over the same period. In comparing rainfall between 1883 – 1949 and 1950 – 2016, there appeared to be less rainfall in the months of October, December, and April while other months seemed to show no change in rainfall. For example, between the two periods mentioned above, the median rainfall in October was 12.4 mm and 8.9 mm respectively while for December they were 68.6 mm and 40.4 mm. There was comparatively a smaller change in the median volume of rainfall in April (18.8 mm vs. 17.5 mm). However, between 1883 and 2016 there were 13 with less than 1 mm of rain, 12 of which occurred after 1961. In the same line of logic, no measureable amount of rain occurred for 23 Octobers, 15 of those occurred after 1961. CONCLUSION: As air temperatures increased over the last 100 years in the Pasadena area, rainfall may have decreased in October, December, and April.

In quantum many-body systems, a Hamiltonian is called an ``extensive entropy generator'' if starting from a random product state the entanglement entropy obeys a volume law at long times with overwhelming probability. We prove that (i) any Hamiltonian whose spectrum has non-degenerate gaps is an extensive entropy generator; (ii) in the space of (geometrically) local Hamiltonians, the non-degenerate gap condition is satisfied almost everywhere. Specializing to many-body localized systems, these results imply the observation stated in the title of Bardarson et al. [PRL 109, 017202 (2012)].

Anomalous waves and rogue events are closely associated with irregularities and unexpected events occurring at various levels of physics, such as in optics, in oceans and in the atmosphere. Mathematical modeling of rogue waves is a highly actual field of research, which has evolved over the last decades into a specialized part of mathematical physics. The applications of the mathematical models for rogue events is directly relevant to technology development for prediction of rogue ocean waves, and for signal processing in quantum units. In this survey, a comprehensive perspective of the most recent developments in methods for representing rogue waves is given, along with discussion of the devised and forms and solutions. The standard nonlinear Schrödinger equation, the Hirota equation, the MMT equation and further to other models are discussed, and their properties highlighted. This survey shows that the most recent advancement in modeling rogue waves give models which can be used to establish methods for prediction of rogue waves at open seas, which is important for the safety and activity of marine vessels and installations. The study further puts emphasis on the difference between the methods, and how the resulting models form a basis for representing rogue waves in various forms, solitary or with a wave-background. This review has also a pedagogic component directed towards students and interested non-experts, and forms a complete survey of the most conventional and emerging methods published until recently

This paper proposes a real-time local positioning system (RT-LPs) utilizing a mobile platform equipped with three anchor nodes placed in a right-angle triangle formation for a real-time locating system (RTLS). After deriving an analytic formula to calculate the target position utilizing the measured distances among anchor nodes and the target node, we find that four parameters have an effect on the position error of the target node. The spacing between anchors is a design parameter that must be large enough to the reduce position error. However, the distance from the anchor node to the target node is an operation parameter that must be small enough to reduce the position error. Additionally, the measured ranges among the anchors and the target node have probabilistic distributions with a mean and variance, which are dominant parameters that have effects on the position error. A comparison study was conducted to determine the effects of the parameters of the target position in both a simulation and an experiment, showing rates of approximately 4% ~ 10%. These findings indicate that our simulation can work properly with the proposed method after assuming that the distance error is a Gaussian model.

Given the cross-scale interactions of agricultural ecosystems, it is important to collect ecosystem service data at the multiple spatial scales they operate at. Mapping of ecosystem services helps to assess their spatial and temporal distribution and is a popular communication tool of their availability and value. For example, maps can be used to quantify distance between areas of available ecosystem services and their beneficiaries and how services fluctuate with changes in land use patterns over time, allowing identification of synergies and trade-offs. However, a lack of local context and too large a resolution can reduce the utility of these maps, whilst masking heterogeneities in access due to equity dynamics. This review identifies and summarizes eight main methods of ESS mapping found in the literature—remote sensing, biophysical modelling, agent based modelling, economic valuation, expert opinion, user preference, participatory mapping, and photo-elicitation. We consider what spatial scales these methods are utilized at and the transferability of data created by each method. The analysis concludes with a methodological framework for mapping ecosystem services, intended to help researchers identify appropriate methods for a multi-scale research design. The framework is exemplified with an overview of a research project in Ethiopia.

The ecological background condition of the semi-arid steppe region (SASR) is extremely fragile. It is recognized that the development of coal and electricity power is a kind of strong human interference behavior for regional landscape ecology. Landscape ecological classification (LEC) is the premise of landscape ecology research of the mining area. The current research on the SASR and grassland LEC of coal-power base is relatively less, but still remains uncertainty concerning how to stratify and classify urban mining landscapes into units of ecological significance at spatial scales appropriate for management. This study is based on hierarchy theory, scale theory, landscape process, the patch-corridor-matrix model, the network, the theory of multiple planning integration and the principle of remote sensing. According to the comprehensive principle, principles of the combining of structure and function, principle of the combining human-ominated and natural landscape, principle of emphasis, and principle of combining qualitative analysis with quantitative research of LEC in large-scale coal-power base(LSCPB). On the basis of occurrence method land classification, fully consider the ecological attributes of the land, integration pattern, processes and function theory of the landscape ecology, the LEC system of the LSCPB in the SASR has been constructed by using top-down decomposition classification method. Empirical research of the Victory and Mindong No.1 mining areas of Shenhua Group shows that the classification system constructed in this paper can meet the requirements of LEC and fully reflect the status of landscape ecology of LSCPB in SASR. This study can provide theoretical guidance for the landscape ecology of LSCPB, while also supporting a theoretical reference for the LEC research.

Bacterial infections are world-wide problem and resistant bacteria is increasing globally that lead to treatments failure. Thus, it is important to find new techniques that are effective for the treatment antibiotic-resistant microorganisms. Green medicine used for the medication of different bacterial infection. Therefore , the study aimed to evaluate the immunomodulatory activity of essential fatty acid semi carbazide (EFASC) compounds extracted from flaxseed to eradicate resistance pathogens . Crud extracts of Linum usitatissimum was extracted by hexane for extraction of EFASC. The results of LD₅₀ appear that a live suspension of E.coli was 0.49×10⁷ ,while HK E.coli was 10⁸ , 125 mg /ml were the optimum dose in stimulate immune response of EFASC which gave maximum dose of total WBC , Neutrophil and Monocyte count. The immunomodulatory activity appear that E.coli + EFASC released moderate levels of IL-4 . HK E.coli release higher IL-4 lead to increase the hypersensitivity and hyper responses of immune system. HK + EFASC immunogen revealed moderate increased in IL-12 mean level 0.99 pg /ml, HK bacteria recorded 1.49 pg/ml, while the mean of EFASC revealed no significant different compare with control. An effective protection was observed in immunized groups with HK E.coli and EFASC challenged with 100 of LD50 of a live E.coli.

Complex modeling has received significant attention in recent years and is increasingly used to explain the statistical phenomenon with increasing and decreasing fluctuations such as the similarity or difference of spike protein charge patterns of coronaviruses. Different from the existing covariance or correlation coefficient methods in traditional integer dimension construction, this study proposes a simplified novel fractional dimension derivation with the exact Excel tool algorithm. It involves the fractional center moment extension to covariance, which ends up a complex covariance coefficient that is better than the Pearson correlation coefficient, in the sense that the nonlinearity relationship can be further depicted. The spike protein sequences of coronaviruses were obtained from the GenBank and GISAID database, including the coronaviruses from pangolin, bat, canine, swine (three variants), feline, tiger, SARS-CoV-1, MERS, and SARS-CoV-2 (including the strains of Wuhan, Beijing, New York, German, and UK variant B.1.1.7) were used as the representative examples in this study. By examining the values above and below the average/mean based on the positive and negative charge patterns of the amino acid residues of the spike proteins from coronaviruses, the proposed algorithm provides deep insights into the nonlinear evolving trends of spike proteins for understanding the viral evolution and identifying the protein characteristics associated with viral fatality. The calculation results demonstrate that the complex covariance coefficient analyzed by this algorithm is capable of distinguishing the subtle nonlinear differences in the spike protein charge patterns with reference to Wuhan strain SARS-CoV-2 for which the Pearson correlation coefficient may overlook. Our analysis reveals the unique convergent (positive correlative) to divergent (negative correlative) domain center positions of each virus. The convergent or conserved region may be critical to the viral stability or viability; while the divergent region is highly variable between coronaviruses suggesting high frequency of mutations in this region. The analyses show that the conserved center region of SARS-CoV-1 spike protein is located at amino acid residues 900, but shifted to the amino acid residues 700 in MERS spike protein, and then to amino acid residues 600 in SARS-COV-2 spike protein, indicating the evolvement of the coronaviruses. Interestingly, the conserved center region of the spike protein in SARS-COV-2 variant B.1.1.7 shifted back to amino acid residues 700, suggesting this variant is more virulent than the original SARS-COV-2 strain. Another important characteristic our study reveals is that the distance between the divergent mean and the maximal divergent point in each of the viruses (MERS>SARS-CoV-1>SARS-CoV-2) is proportional to viral fatality rate. This algorithm may help to understand and analyze the evolving trends and critical characteristics of SARS-COV-2 variants, other coronaviral proteins and viruses.

Environmental accounting should be performed by both private companies and local governments. However, it may be difficult for government agencies to objectively measure their current environmental impact, and there is currently no internationally standardized methodology of environmental accounting for local governments. This study therefore attempts to incorporate life cycle impact assessment (LCIA) into the calculation of environmental loads for administrative divisions. In LCIA, environmental loads for several impact categories, such as “Climate change” and “Land use,” are integrated into a simple indicator expressed in terms of monetary units. This study leverages the LIME-3 assessment theory, one of the endpoint-type and global-scale LCIA methods. Annual environmental loads for administrative divisions in 42 countries were measured in a tentative assessment. Results showed that the annual damages for the 42 countries to be USD 10.5 trillion. Assessment results are shown on the world map to highlight the regionality of the damages in the 42 countries’ administrative divisions. This study seeks to provide new knowledge that local governments around the world can use in environmental accounting.

Currently, the number of approved veterinary medicines are limited, and human medications are used off-label. These approved human medications are of too high potencies for a cat or a small dog breed. Therefore, there is a dire demand for smaller doses of veterinary medicines. This study aims to investigate the use of three semi-solid extrusion 3D printers in a pharmacy or animal clinic setting for extemporaneous manufacturing of prednisolone containing orodispersible films for veterinary use. Orodispersible films with adequate content uniformity and acceptance values defined by the European Pharmacopoeia was produced with one of the studied printers, namely, the Allevi 2 bioprinter. Smooth and flexible films, with high mechanical strength, neutral pH, and low moisture content were produced with high correlation between prepared design and obtained drug amount, indicating that the Allevi 2 printer could successfully be used to extemporaneously manufacture personalized doses for animals at the point-of-care.

Membranes based on sulfonated synditoactic polystyrene were thoroughly characterized by contrast variation SANS over a wide Q-range in dry and hydrated states. The film samples were prepared by solid-state sulfonation that allowed a uniform sulfonation of only the amorphous phase while preserving the crystallinity of the membrane. The samples were loaded with different guest molecules in either the amorphous (fullerenes) or the crystalline (toluene) regions, in order to vary the neutron contrast or to reproduce the conditions enabling an increased resistance of the membranes to chemical decomposition. The use of uni-axially deformed film samples and contrast variation with different H2O/D2O mixtures allowed for the identification and characterization of different structural levels with sizes between nm and μm, which form and evolve in the membrane morphology in dry and hydrated states and produce scattering features on different detection sectors and at different detection distances after the sample, depending on their size and orientation.

Performance appraisal is a fundamental indicator in public accountability to achieve the good governance principles. Hence, this study aims to analyze the performance measurement that can improve performance on government agencies in South Sulawesi, Indonesia. The study was conducted in qualitative approach. The research found that non-integrated models of performance measurement in South Sulawesi are inefficient and ineffective. Inefficiency happens because it uses time and cost resources separately, while being ineffective is because both models focuses on each goal instead on performance goals and the process is not supported by the actual management.

In rural Zimbabwe, selling of cattle has for a long time been one of the most dependable sources of income that has sustained livelihoods for decades. Informal cattle marketing which involves door to door or gate sales has been the most predominant system for the last three decades. However, the outbreak of the global COVID-19 pandemic followed by the imposition of lockdowns has exposed the vulnerability of rural communities that are regressing into poverty due to a lack of alternative sources of income. The aim of this paper is, therefore, to delineate how formal cattle markets could be used as a sustainable source of income for rural communities’ livelihoods during and post the COVID-19 pandemic era. This qualitative research study relied on secondary data from published journal articles, online publications, and reports to understand the COVID-19 pandemic and also understand how it has impacted the livelihoods of people in rural Zimbabwe. The findings show that the current informal cattle marketing system is no longer suitable for rural communities as it exposes them to infections due to the challenges in ensuring compliance with the World Health Organisation (WHO) precautionary measures. It is recommended that formal (public) cattle markets be reintroduced in all rural areas as there is the certainty that WHO health guidelines will be enforced since they are organised by local and central government institutions. Since formal cattle markets offer competitive market-related prices this will then guarantee the flow of regular income thereby reducing the vulnerability of rural communities to poverty and inequalities.

The classical Rotational Isomeric State (RIS) model, originally proposed by Flory, has been used to rationalize a wide range of physicochemical properties of neutral polymers. However, many weak polyelectrolytes of interest are able to regulate their charge depending on the conformational state of the bonds. Recently, it has been shown that the RIS model can be coupled with the Site Binding (SB) model, for which the ionizable sites can adopt two states: protonated or deprotonated. The resulting combined scheme, the SBRIS model, allows to analyse ionization and conformational equilibria on the same foot. In the present work this approach is extended to include pH-dependent electrostatic Long Range (LR) interactions, ubiquitous in weak polyelectrolytes at moderate and low ionic strengths. With this aim the original LR interactions are taken into account by defining effective Short Range (SR) and pH-dependent parameters, such as effective microscopic protonation constants and rotational bond energies. The new parameters are systematically calculated using variational methods. The machinery of statistical mechanics for SR interactions, including the powerful and fast transfer matrix methods, can then be applied. The resulting technique, to which we will refer as Local Effective Interaction Parameters (LEIP) method, is illustrated with a minimal model of a flexible linear polyelectrolyte containing only one type of rotating bonds. LEIP reproduces very well the pH dependence of the degree of protonation and bond probabilities obtained by semi-grand canonical Monte Carlo simulations, where LR interactions are taken explicitly into account. The reduction in the computational time in several orders of magnitude suggests that the LEIP technique could be useful in a range of areas involving linear weak polyelectrolytes, allowing direct fitting of the relevant physical parameters to the experimental quantities.

Fluctuation theorems are a class of equalities each of which links a thermodynamic path functional such as heat and work to a state function such as entropy and free energy. Jinwoo and Tanaka [L. Jinwoo and H. Tanaka, Sci. Rep. 5, 7832 (2015)] have shown that each microstate of a fluctuating system can be regarded as an ensemble (or a 'macrostate') if we consider trajectories that reach each microstate. They have revealed that local forms of entropy and free energy are true thermodynamic potentials of each microstate, encoding heat, and work, respectively, within an ensemble of paths that reach each state. Here we show that information that is characterized by the local form of mutual information between two subsystems in a heat bath is also a true thermodynamic potential of each coupled state and encodes the entropy production of the subsystems and heat bath during a coupling process. To this end, we extend the fluctuation theorem of information exchange [T. Sagawa and M. Ueda, Phys. Rev. Lett. 109, 180602 (2012)] by showing that the fluctuation theorem holds even within an ensemble of paths that reach a coupled state during dynamic co-evolution of two subsystems.

Despite their Nobel prize-winning empirical verification, the interpretation of the Bell inequality remains controversial. The alleged nonlocal character of quantum mechanics is inextricably related to the formulation of the Bell theorem. However, as is usually presented, the relation disagrees with Bell's approach and is inappropriately posed. The departure from the clear line of reasoning that Bell tried to convey has contributed to a polarization of part of the scientific community. We review part of Bell's work and show how the correct appreciation of Bell's rationale calls for reformulating a widespread argument on quantum nonlocality, yielding a more balanced perspective of the problem. We highlight a more formal proof of quantum mechanics' violation of local causality. For completeness, we mention a few alternatives that may justify considering quantum mechanics as a local theory.

Increased attention has been paid to the influence of coal mining subsidence on ecological environment. Restoration of ecosystem in damaged mining area is critical for restoring disturbed environment. The comparing of plant communities and microbial communities in the artificial restoration and natural restoration areas provides an effective method for evaluating the restoration effects. However, such studies are limited in coal mining subsidence restoration areas. Subsidence area in Shendong mining area, located in the semi-arid region of Western China, was restored from 2003 with 5 ecological restoration plant species. In July 2017, the comparison and analysis of plant and microbial communities were conducted at the artificial restoration areas (AR) and the natural remediation areas (NR). The results showed that the artificial ecological restoration in Shendong mining area has achieved some success, but it has not recovered to a similar ecosystem before the destruction. A higher plant species, coverage and bacterial community diversity were observed in AR. However, these features have lower similarity compared with those in NR sites. Potential soil factors, such as pH, moisture content, total carbon content, organic matter, nitrogen and bulk density, have a greater impact on soil bacterial community structure and diversity. In the ecological restoration of the mining area, attention should be paid to the restoration of soil properties in the mining area. This study can provide theoretical guidance for more scientific ecological restoration in the damaged mining area.

A radical, albeit pragmatic protocol for experimental access to putative String/M-theoretic, Einstein Unified Field Mechanical (UFM) additional dimensionality (XD) of the brane-bouquet bulk is presented. If successful, results demonstrate the existence dimensionality beyond the metric of observed physical reality provided by the Standard Model (SM) of particle physics and Cosmology. Quantum Mechanics (QM), as well-known is incomplete and further, should no longer be considered the basement of reality; meaning, Locality and Unitarity – the fundaments of quantum theory are an insufficient basis for extending the representation of reality. A seminal model of Tight Bound States (TBS) below the lowest Bohr orbit in the hydrogen atom, proposed by Vigier, is extended to a Kaluza-Klein-like (KK) cyclical tier of XD hyperspherical cavities defined within a manifold of uncertainty (MOU) of finite radius up to the semi-quantum limit, predicting, within its domain, new spectral lines in Hydrogen. The proposed protocol for this process, with phase modifications, provides efficacy of large-scale additional dimensionality (LSXD) of the brane bulk; XD-LSXD incursion duality accesses nonlocal Einsteinian UFM phenomena, leading to myriad new classes of technological innovation.

Abstract. The purpose of this review is to investigate the nature of privacy concerns in the context of Smart Local Energy Systems (SLES) to understand how SLES providers can minimize both users’ concern, and cause for concern, around privacy. We conducted a rapid realist review and thematic framework analysis against Bronfrenbrenner’s socio-ecological model to understand privacy concerns in different contexts. A common privacy concern was that sharing detailed energy use data had the potential to reveal information about home life, and to intrude upon people’s sense of autonomy, choice and control. Evidence suggests that people are willing to accept newdata sharing technologies if the benefits of doing so are clear, anticipated, and mutually beneficial. Building trust, through increasing knowledge and understanding was a mechanism for overcoming privacy concerns, but this was mediated by the organization providing the information. Non-profit organizations were more trusted to ensure appropriate safeguards to privacy were in place. One key barrier to participation with good supporting evidence was that people can resist perceived intrusions on their privacy. This could be actively resisted by refusing to install data collection technologies or passively by non-participation in adapting energy use behaviors: both of which are necessary for SLES to achieve their goals of managing energy demand and building resilience in smart grids.

The ability to predict the skin sensitization potential of small organic molecules is of high importance to the development and safe application of cosmetics, drugs and pesticides. One of the most widely accepted methods for predicting this hazard is the rodent local lymph node assay (LLNA). The goal of this work was to develop in silico models for the prediction of the skin sensitization potential of small molecules that go beyond the state of the art, with larger LLNA data sets and, most importantly, a robust and intuitive definition of the applicability domain, paired with additional indicators of the reliability of predictions. We explored a large variety of molecular descriptors and fingerprints in combination with random forest and support vector machine classifiers. The most suitable models were tested on holdout data, on which they yielded competitive performance (Matthews correlation coefficients up to 0.52; accuracies up to 0.76; areas under the receiver operating characteristic curves up to 0.83). The most favorable models are available via a public web service at https://nerdd.zbh.uni-hamburg.de/skinDoctor/ that, in addition to predictions, provides assessments of the applicability domain and indicators of the reliability of the individual predictions.

The conversion of CO2 into more synthetically flexible CO is an effective and potential method for CO2 remediation, utilization and carbon emission reduction. In this paper, the reaction of carbon-carbon dioxide (Boudouard reaction) was performed in a microwave fixed bed reactor using semi-coke (SC) as both the microwave absorber and reactant and was systematically compared with that heated in a conventional thermal field. The effects of the heating source, SC particle size, CO2 flow rate and additives on CO2 conversion and CO output were investigated. By microwave heating (MWH), CO2 conversion reached more than 99 %, while by conventional heating (CH), the maximum conversion of CO2 was approximately 29% at 900 °C. Meanwhile, for the reaction with 5 wt% Barium Carbonate added as a promoter, the reaction temperature was significantly reduced to 750 °C with almost quantitative conversion of CO2. Further kinetic calculations showed that the apparent activation energy of the reaction under microwave heating was 46.3 kJ/mol, which was only one-third of that observed under conventional heating. The microwave-assisted Boudouard reaction with catalytic barium carbonate is a promising method for carbon dioxide utilization.

Recently, there has been renewed interest in the performance, functionality, and sustainability of traditional small-scale storage interventions (check dams, farm bunds and tanks) used across India for the improvement of local water security. The Central Groundwater Board of India is en-couraging the construction of such interventions for the alleviation of water scarcity. It is of critical importance to understand the hydrological effect of these interventions at basin scales to maximise their effectiveness. The quantification of small-scale interventions in hydrological modelling is often neglected, especially in large-scale modelling exercises. A bespoke version of the GWAVA model was developed to assess the impact of interventions on the water balance of the Cauvery Basin and two smaller sub-catchments. Model results demonstrate that farm bunds appear to have a negligible effect on the estimated average annual simulated streamflow at the outlets of the two sub-catchments and the basin whereas tanks and check dams have a more significant effect. In-terventions generally were found to increase evaporation losses across the catchment. The model adaption used in this study provides a step-change in the conceptualisation and quantification of the consequences of small-scale storage interventions in large- or basin-scale hydrological models.

The planning and decision-making for a distributed energy supply concept in complex actor structures like in districts calls for the approach to be highly structured. Here, a strategy with strong use of energetic simulations is developed, the core elements are presented and research gaps are identified. The exemplary implementation is shown using the case study of a new district on the former Oldenburg airbase in northwestern Germany. The process is divided into four consecutive phases, which are carried out with different stakeholder participation and use of different simulation tools. Based on a common objective, a superstructure of the applicable technologies is developed. Detailed planning is then carried out with the help of a multi-objective optimal sizing algorithm and Monte Carlo based risk assessment. The process ends with the operating phase, which is to guarantee a further optimal and dynamic mode of operation. The main objective of this publication is present the core elements of the planning processes and decision-making framework based on the case study and to find and identify research gaps that will have to be addressed in the future.

Depletion of ore deposits, increasing demand for raw materials, the need to process low-grade, complex and finely disseminated ores and the reprocessing of tailings are challenges, especially for froth flotation separation technologies. Even though capable of handling relatively fine grain sizes the flotation separation of very fine and ultrafine particles faces many problems still. Further, the flotation of low-contrast semi-soluble salt-type minerals with very similar surface properties, many complex interactions between minerals, reagents and dissolved species often result in poor selectivity. This study investigates the flotation beneficiation of ultrafine magnesite rich in dolomite from de-sliming, currently reported to the tailings. The paper especially focuses on the impact of the depressant sodium hexametaphosphate (SHMP) on: (i) the froth properties using dynamic froth analysis (DFA), (ii) the separation between magnesite and dolomite/calcite and (iii) its effect on the entrainment. Furthermore, the application of 1-hydroxyethylene-1,1-diphosphonic acid (HEDP) is a more environmentally friendly and low-cost alternative to SHMP is presented and discussed. The paper contributes to understanding on the complexity of depressant responses in froth flotation.

The minimum energy structures of the Si3C5 and Si4C8 clusters are planar and contain planar tetracoordinate carbons (ptCs). These species have been classified, qualitatively, as global () and local () aromatics according to the adaptive natural density partitioning (AdNDP) method, which is an orbital localization method. This work evaluates these species' aromaticity, focusing on confirming and quantifying their global and local aromatic character. For this purpose, we use an orbital localization method based on the partitioning of the molecular space according to the topology of the electronic localization function (LOC-ELF). In addition, the magnetically induced current density is analyzed. The LOC-ELF-based analysis coincides with the AdNDP study (double aromaticity, global and local). Besides, the current density analysis detects global and local ring currents. The strength of the global and local current circuit is significant, involving 4n+2 - and -electrons, respectively. The latter implicates the Si-ptC-Si fragment, which would be related to the 3c-2e -bond detected by the orbital localization methods in this fragment.

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.

Crowd density estimation is an important task for crowd monitoring. Many efforts have been done to automate the process of estimating crowd density from images and videos. Despite series of efforts, it remains a challenging task. In this paper, we proposes a new texture feature-based approach for the estimation of crowd density based on Completed Local Binary Pattern (CLBP). We first divide the image into blocks and then re-divide the blocks into cells. For each cell, we compute CLBP and then concatenate them to describe the texture of the corresponding block. We then train a multi-class Support Vector Machine (SVM) classifier, which classifies each block of image into one of four categories, i.e. Very Low, Low, Medium, and High. We evaluate our technique on the PETS 2009 dataset, and from the experiments, we show to achieve 95% accuracy for the proposed descriptor. We also compare other state-of-the-art texture descriptors and from the experimental results, we show that our proposed method outperforms other state-of-the-art methods.

The aim of the studies was to test the hydraulic pressure losses along the length, local pressure losses, absolute and relative roughness values of the pipeline walls made of modern polymer material. The article presents the results of the experimental studies of hydraulic resistance of pipelines from modern polymer materials, the method of theoretical determination of resistance coefficients in the VALTEC ISO 21003 metal polymer pipeline, the classification and method of determining the values of local hydraulic resistance coefficients of T-Junctions are given, the dependence for determining the Darcy λ hydraulic friction coefficient associated with the value of the equivalent hydraulic roughness coefficient of the inner surface of pipes and the Reynolds number. The experimental data of the hydraulic coefficient of friction Darcy λ was compared with the known theoretical relationships of A.D. Altschul, Colbrooke for smooth pipes, Colbrooke and White, an alternative to the Colbrooke-White, Offengenden equation for low-shear pipes and pipes from polymer materials with Reynolds numbers Re>10^4. Dependence of hydraulic coefficient of friction on relative equivalent roughness of pipeline walls and Reynolds number, specific energy loss per one linear meter on total flow rate in system of hydraulically short pipeline is obtained. The empirical dependence of values of coefficients of local resistance ζ=f(Q2/Q3) from a ratio of the divided expenses of Q2/Q3 of the equal-pass T-Junction α=90 the pipeline to a branch up, on pass in the direct T-Junction and division of streams at various internal pipeline diameters of VALTEC.