Miracle-dz/UniFAR-FTUs huggingface dataset:
Ecological capability assessment for afforestation using GIS- based multiple criteria decision making approach (Case study; Mehran County, Iran)

Due to the process of deforestation and Increasing human population and growing demands for forests, afforestation and the development of forest is and will be of paramount importance. The objective of this research is to identify suitable lands for afforestation and forest development in Mehran County on the western of Iran by using multi criteria evaluation making. Site selection analysis was carried out to find the best suitable lands for forest development and afforestation in an example of promising southern Ilam province, Iran. The GIS models were developed to represent a scenario of land use suitability in the study area using GIS Multi Criteria Analysis Modeling. The factors contributed in the analysis are the Topography, Land cover, Climate, Soil, and Geology. Land suitability maps for afforestation have been extracted using weighted overlay techniques. The total resulting areas for afforestation reveal the importance of forest development in Mehran County, and the suitability of the terrain. The suitable map for afforestation shows that 35.88% of the investigated area is highly suitable, 28.64% is moderately suitable and 35.46% is lowly suitable. According to autochthonous species and adaptive exotic species and their ecological demand suggest species for afforestation in suitable places that ecological demand of the suggested species is similar to ecology specifications of this suitable land that have capability for afforestation. Several species suggested for afforestation in suitable lands such as Amygdalus arabica, Prosopis juliflora, Pistasia atlantica, Eucaliptus camaldulensis, Ziziphus spinachristi, Ziziphus numularia, and Myrtus communis. © 2015 Elixir All rights reserved
6 A Framework for Research and Prototyping in Robotics: From Ideas to Software and Hardware Development

Development and prototyping of robotic systems requires the involvement of many people and many hours of design, development, and cooperation; signiﬁcant time and effort overhead is required for evaluating conceptual ideas in design, control and technology, and for bringing them fast into reality for testing. Based on the important advances of the last decade in hardware and software, a simple and low-cost framework and its underlying ideas are presented, with steps that aim at accelerating robotics research work in academia and industry. The framework’s functionality is validated and illustrated by two application examples concerning the control systems of a single-legged hopping robot and an instrumented treadmill. The software required to conduct the same experiments is provided, with the intention to help the reader reuse it in similar applications.
Correlation effects in sequential energy branching: an exact model of the Fano statistics

Correlation effects in the fluctuation of the number of particles in the process of energy branching by sequential impact ionizations are studied using an exactly soluble model of random parking on a line. The Fano factor F calculated in an uncorrelated final-state “shot-glass” model does not give an accurate answer even with the exact gap-distribution statistics. Allowing for the nearest-neighbor correlation effects gives a correction to F that brings F very close to its exact value. We discuss the implications of our results for energy resolution of semiconductor gamma detectors, where the value of F is of the essence. We argue that F is controlled by correlations in the cascade energy branching process and hence the widely used final-state model estimates are not reliable — especially in the practically relevant cases when the energy branching is terminated by competition between impact ionization and phonon emission.
PCR based screening for srfAA ORF1 from local Bacillus species

Cyclic lipopeptides including surfactin, iturin and fengycin families are important metabolites produced by Bacillus having significant role in disease control, agriculture, medicine, cosmetics, pharmaceuticals, food and petroleum industry. Some of these lipopeptides have been reported to show biosurfactant activities with surfactin being the most studied biosurfactant possessing growth inhibition activity for phytopathogenic bacteria, fungi, virus or mycoplasma. srfA operon of surfactin is essential for competence development and the presence of this operon is confined to Bacillus subtilis, B. amyloliquefaciens and B. circulans only. In the present project, three different Bacillus species i.e. Bacillus subtilis, Bacillus thuringiensis and Bacillus sphaericus were screened for the presence of srfAA ORF1 of surfactin synthetase using PCR. Specific primers were designed against this ORF1 region for PCR amplification with the help of online bioinformatics tools and by using already reported GenBank data. Genetic variability in the size of the ORF1 region was observed in the two isolates of Bacillus subtilis (∼500 bp for MBL-A and ∼700 bp for MBL-B) as compared to the reported size. Some nonspecific amplifications of approximately 300 bp size were also seen in Bacillus thuringiensis and Bacillus sphaericus and may represent some part of surfactin synthetase ORF1. Precise knowledge requires further studies of gene characterization, genetic variations and phylogeny.
Transient phase change in two phase reaction between LiFePO4 and FePO4 under battery operation

Transient states of phase transition in LiFePO4/FePO4 for lithium ion battery positive electrodes are investigated by time-resolved measurements. To directly detect changes in electronic and crystal structures under battery operation, in situ time-resolved X-ray absorption and diffraction measurements are performed, respectively. The phase fraction change estimated by the iron valence change is similar to the electrochemically expected change. The transient change of lattice constant during two phase reaction is clearly observed by the time-resolved X-ray diffraction measurement. The nonequilibrium lithium extraction behavior deviates from the thermodynamic diagram of the two phase system, resulting in continuous phase transition during electrochemical reactions.
An Enhanced Faster-RCNN Based Deep Learning Model for Crop Diseases Detection and Classification

Recently Plant phenotyping has gained the attention of many researchers such that it plays a vital role in the context of enhancing agricultural productivity. Indian economy highly depends on agriculture and this factor elevates the importance of early disease detection of the crops within the agricultural fields. Addressing this problem several researchers have proposed Computer Vision and Pattern recognition based mechanisms through which they have attempted to identify the infected crops in the early stages.in this scenario, CNN convolution neural network-based architecture has demonstrated exceptional performance when compared with state-of-art mechanisms. This paper introduces an enhanced RCNN recurrent convolution neural network-based architecture that enhances the prediction accuracy while detecting the crop diseases in early stages. Based on the simulative studies is observed that the proposed model outperforms when compared with CNN and other state-of-art mechanisms.
YOGA POSTURE RECOGNITION ACCORDING TO IMAGES CAPTURED BY RGB CAMERA

Muscle conditions are more common in human as a result of injuries or aging, which is a significant concern for the future. Physical activity may help to get rid of this disease. The most effective form of physical activity is yoga. To have proper yoga posture, it is important to have a correct center of gravity for that pose of yoga. The COG for each yoga asana is different. In yoga asana, COG refers to a hypothetical point on the body where weight has accumulated. Sometimes it’s even located outside of the body. The hypothetical point in the body where the body is concentrated can reduce body pain or weight of that location. This study identifies the COG of these seven asana: Pranamasana,
The Rise of American Corporate Science

Corporate science in America emerged in the interwar period, as some companies set up state-ofthe-art corporate laboratories, employed highly-skilled scientists, and conducted basic research of the kind we would associate today with academic institutions. Using a newly-assembled data set on both publicly-traded and private US companies between 1926 and 1940 with information on corporate ownership, corporate organization (diversification and business group affiliation) and corporate research (publications, patents and their citations and market values), we attempt to explain the historical rise of corporate quasi-academic research. We argue that this phenomenon was driven by companies trying to make up for institutional voids, in this case, the weakness of academic research, which made access to science in certain fields costly for US firms. Measuring institutional voids, or field-specific scientific backwardness, in two different ways, we find that large and diversified corporations, especially those relatively close to the technological frontier, were the ones prone to internalize the provision of basic research, a classic public good. We also find that corporate research was positively correlated with innovative and valuable patents (inventions) and with stock market valuation, suggesting that investment in corporate research paid off. The results shed light on the link between corporate organization and corporate science and, in particular, on the possible role of large firms and diversified business groups in advancing science in less-than-fully-developed economies. ∗Duke University, Fuqua School of Business and NBER (ashish.arora@duke.edu) †Duke University, Fuqua School of Business and NBER (sharon.belenzon@duke.edu) ‡Bank of Israel (konstantin.kosenko@boi.org.il) §Duke University, Fuqua School of Business (jungkyu.suh@duke.edu) ¶Hebrew University of Jerusalem, Jerusalem School of Business Administration, CEPR and ECGI (yishay.yafeh@huji.ac.il) ‖We thank seminar participants at Boston University and the ASSA 2021 annual meeting, as well Tim Simcoe and Bhaven Sampat for helpful comments and suggestions. All remaining errors are our own.
Managing Collaborative Governance Dynamics in Agropolitan Development to Face the New Normal Era

Collaborative dynamics are the main components that determine successful collaborative governance. A progressive collaboration dynamics cycle helps collaborative participants develop collective goals and guides collaborative action. However, because it is interactive, dynamic, depends on prevailing conditions and characteristics, sometimes it is varied, does not always work well, can hinder the effectiveness of collaborative governance. Therefore it is important to manage collaboration dynamics in agropolitan development to be able to realize local economic development and increase the welfare of society in the new normal era. This research used qualitative methods with interactive data analysis and in-depth interviews with 29 key informants who represented local governments, the private sector, communities, farmer groups, media. The result of the study indicates that collaboration dynamics was a formative type of collaboration that starts on its own. The success rate of collective action capacity is highly dependent on the development of facilitative leadership and responsiveness to current situations and conditions, especially in the face of the new normal era. Keywords—collaborative governance, collaboration dynamics, agropolitan development
Motion Planning with Environment Uncertainty

—As robots are becoming more pervasive and are increasingly used in close proximity to humans and other objects in factories, living spaces, elderly care, and robotic surgery, planning for collision free trajectories in real-time is imperative for safe and efﬁcient operation. Yet, in the presence of noisy sensors, both the robot and world state cannot be estimated precisely. In this paper we investigate the problem of motion planning under environment uncertainty. To this end, we ﬁrst incorporate object uncertainties in Belief Space Planning (BSP) and derive the resulting Bayes ﬁlter in terms of the Extended Kalman Filter (EKF) update equations. We further formulate the collision constraint as a quadratic form in random variables, thus computing an exact expression for collision probability. We further validate our approach using numerical integration and provide a comparison to other approaches.
ALCOHOLIC REDUCTION PLATINUM NANOPARTICLES SYNTHESIS BY SONOCHEMICAL METHOD

The studies of alcoholic reduction show that platinum nanoparticles formation is influenced by the type of reducing alcohol and capping polymer. Our study refer to sonochemical synthesis of platinum nanoparticles, obtained by reduction of H2PtCl6 with methanol, ethanol and propanol that work simultaneously as solvents and reducing agents, in the presence of different capping polymers: chitosan, polyethylene glycol and poly(amidehydroxyurethane). The polymer stabilized platinum nanoparticles were characterised by X-ray diffractometry (XRD), atomic force microscopy (AFM), and laser diffraction particle size analysis (DLS). The optical properties were studied in solution by UV-Vis-NIR spectrometry. The dimension of obtained nanoparticles is approximately 3 nm and present an absorption peak at about 200 nm that depend of alcohol and polymer used.
Multiobjective Optimization Using Goal Programming for Industrial Water Network Design

The multiobjective optimization (MOO) of industrial water networks through goal programming is studied using a mixed-integer linear programming (MILP) formulation. First, the efficiency of goal programming for solving MOO problems is demonstrated with an introductive mathematical example and then with industrial water and energy networks design problems, formerly tackled in literature with other MOO methods. The first industrial water network case study is composed of 10 processes, 1 contaminant, and 1 water regeneration unit. The second, a more complex real industrial case study, is made of 12 processes, 1 contaminant, 4 water regeneration units, and the addition of temperature requirements for each process, which implies the introduction of energy networks alongside water networks. For MOO purposes, several antagonist objective functions are considered according to the case, such as total freshwater flow rate, number of connections, and total energy consumption. The MOO methodology proposed is demonstrated to be very reliable as an a priori method, by providing Pareto-optimal compromise solutions in significant less time compared to other traditional methods for MOO.
Optimizing Classification Error in Handwritten Devnagari Text Documents Using GA

features, CH histogram and finding intersection. The MLP based classifier technique is used and reported the accuracy of recognition as 92.30 %. Sandhya Arora [4], proposed handwritten character recognition approach for the shadow features, CH histrogram, View based features, and longest –run features and support vector machines and artificial neural networks and reported the 93.35 % accuracy for the 7154 data set size. R. J. Ramteke proposed a handwritten devnagari numerals recognition method for moment invariant features with template and elastic matching classifier for the dataset size 1593
Physics-Informed Neural Networks for Non-linear System Identification for Power System Dynamics

Varying power-infeed from converter-based generation units introduces great uncertainty on system parameters such as inertia and damping. As a consequence, system opera-tors face increasing challenges in performing dynamic security assessment and taking real-time control actions. Exploiting the widespread deployment of phasor measurement units (PMUs) and aiming at developing a fast dynamic state and parameter estimation tool, this paper investigates the performance of Physics-Informed Neural Networks (PINN) for discovering the frequency dynamics of future power systems. PINNs have the potential to address challenges such as the stronger non-linearities of low-inertia systems, increased measurement noise, and limited availability of data. The estimator is demonstrated in several test cases using a 4-bus system, and compared with state of the art algorithms, such as the Unscented Kalman Filter (UKF), to assess its performance.
The (In)efficiency of Share-Tenancy Revisited: The Role of Supervision

Sharecropping, particularly its effect on agricultural efficiency, has long fascinated economists. With a couple of notable exceptions, past studies find small or insignificant productivity differentials between sharecropped and owner-cultivated land. This paper provides more conclusive evidence using a large, nationwide, microdata set from rural Pakistan. Our estimates show that the average yield differential between share-tenanted and owner-cultivated plots is highly unlikely to exceed 8 percent. An analysis of tenant labor allocation corroborates this conclusion. To understand why sharecropping does not lead to substantial productivity losses on average, we use unique data on monitoring frequency collected directly from tenants. We find that "unsupervised" tenants are significantly less productive than their "supervised" counterparts. We show that the coexistence of these two types of tenants is consistent with an agency model in which landlords have different costs of supervision. To assess the model, we investigate whether a landlord’s decision about the form of incentive contract and degree of supervision is driven, in part, by variation in supervision costs. ∗Development Research Group, The World Bank. Contact Information: Jacoby: e-mail: hjacoby@worldbank.org; Mansuri: e-mail: gmansuri@worldbank.org.
EC CARDIOLOGY Mini Review Difficulties and Pitfalls in Performing Speckle-Tracking Echocardiography to Assess Left Ventricular Systolic Function

Left ventricle systolic function is one of the most important measurements in cardiac evaluation. Transthoracic echocardiography is the most common and quickest technique to access qualitative and quantitative left ventricle systolic function mainly by the calculation of left ventricular ejection fraction (LVEF). However, despite its overwhelming clinical utility, LVEF has several limitations: it doesn’t detect small changes in the contractile function and it also doesn’t diagnose subclinical myocardial damage which has important implications in the therapeutic choice and in the clinical protocol. In turn, strain imaging provides an accessible, feasible and non-invasive technique to assess cardiac mechanics, and speckle tracking echocardiography (STE) is the primary modality with the utility for detection of subclinical ventricular dysfunction. For this purpose a high-quality images are required. This article describes the main difficulties and pitfalls in the acquisition and analysis of left ventricular systolic function by STE.
Absent Left Anterior Descending Coronary Artery as a Potential Cause of Ischemic Stroke: A Case Report

Patient: Male, 36-year-old Final Diagnosis: Stroke Symptoms: Dizziness • dysarthria • hemiplegia • seizure Medication: — Clinical Procedure: Coronary angiography • MRI • VSD closure surgery Specialty: Neurology Objective: Congenital defects/diseases Background: Embolic stroke of undetermined source (ESUS) represents 20-30% of ischemic strokes, with a high risk of recurrence. It usually requires an extensive diagnostic evaluation to address the potential etiologies. Coronary artery anomaly (CAA) of the left anterior descending artery (LAD) is uncommon, and it is known to be linked to myocardial complications. The association of this anomaly with ischemic strokes has not been reported yet. Here, we report on a rare case of a young patient with hypoplastic LAD complicated by an impaired ventricular function that resulted in left ventricular (LV) thrombus formation as a source of recurrent ischemic strokes. Case Report: A 36-year-old man had a 4-year history of recurrent strokes despite maintaining antiplatelet treatment. He had no pre-existing vascular risk factors or relevant family history. The initial stroke etiology work-up was inconclusive. A transesophageal echocardiogram showed moderate ventricular hypokinesia. A coronary angiogram was initiated, and a hypoplastic (LAD) artery anomaly was found. At first, the antiplatelet therapy was maintained. Later on, he presented with transient focal neurological symptoms indicative of a transient ischemic attack. Repeated echocardiograms detected left ventricular thrombus. Apixaban was started, with successful thrombus resolution in a one-month follow-up echocardiogram. He has not had a further recurrent ischemic event for 18 months. Conclusions: This case suggests that CAAs might be considered as an associated etiology of ESUS in a young patient with recurrent cerebral events. In a clinical setting, we encourage early use of advanced cerebral and cardiac imaging modalities to accurately determine the stroke etiology, target the appropriate treatment, and prevent a further neurological sequel.
DetectingMycobacterium Tuberculosis through Bacterioferritin Gene Amplification by Real-Time PCR

Tuberculosis is known to be the second most common cause from substantial morbidity and mortality through infectious diseases worldwide following the human HIV Sample selection was performed at the Chest and Respiratory Diseases Institute / Baghdad Medical City in Bagdad. The samples collecting were done from January to October 2019, at which time 90 suspected TB patients were investigated. The results revealed when comparing between RT-PCR test and microbiological test we have calculated sensitivity and specificity for each test. The RT-PCR test showed 100 percent for both sensitivity and specificity while the Microbiological tests showed 0.067 specificity and 0.933 sensitivity. These findings our results showed a high sensitivity and specificity of RT-PCR technique targeting BfrB gene for the detection of MTB by using specific probe.
Momentum in Mature and Emerging Markets under Different Market States: the Case of the Baltic Region

The paper investigates momentum profits in the emerging and unexplored Baltic markets and compares the results to the developed Swedish market. In addition, recent economic turmoil helps the study capture the effect of different market states on momentum returns. We employ the methodology by Jegadeesh and Titman (1993) to construct momentum portfolios and the methodology by Rouwenhorst (1998) to measure the impact of market states on momentum profitability. We uncover that momentum profits tend to be positive, but statistically insignificant in the Baltic States. In comparison, momentum returns in Sweden are found to be positive and statistically significant. The difference is mainly driven by the lower returns of losers in Sweden. Also, we document that momentum returns cannot be fully explained by the Fama and French factors and the liquidity risk factor. In addition, we find that market states can explain momentum returns to a large extent more momentum exists in expansionary periods in both
Piezometric Assessment for Salinity in Multi Aquifer System in Dharoi Command Area, Gujarat

Our earlier study carried out in Dharoi command area in Sabarmati River Basin, in India, defined the sensitive parameters to address the problem of water logging and salinity in the shallow aquifer, contribution of multi-aquifer system in making the scenario complex, was thus evident. Therefore, extension of the study by analyzing the piezometric data of complex lithological setup is attempted in this paper. The present paper establishes and discusses the relationships of various depth wise aquifer zones with the help of the seasonal piezometric heads and TDS values, analyzed as tracers.