Miracle-dz/UniFAR-FTUs huggingface dataset:
Roots of Yoga

Yoga is hugely popular around the world today, yet until now little has been known of its roots. This book collects, for the first time, core teachings of yoga in their original form, translated and edited by two of the world's foremost scholars of the subject. It includes a wide range of texts from different schools of yoga, languages and eras: among others, key passages from the early Upanisads and the Mahabharata, and from the Tantric, Buddhist and Jaina traditions, with many pieces in scholarly translation for the first time. Covering yoga's varying definitions across systems, models of the esoteric and physical bodies, and its most important practices, such as posture, breath control, sensory withdrawal and meditation, Roots of Yoga is a unique and essential source of knowledge.
Size-dependent Failure Strength of Silicon Nanofilms

Cracked silicon nanofilms under pure mode I loading are simulated to investigate the dependence of their failure strength on film thickness. Cracked silicon nanofilms exhibit strong nonlinear response when their thickness is smaller than about 14 nm and the applied strain is large. In comparison with the ideal strength of silicon the failure strength of cracked silicon films is much lower. The flaw tolerance mechanism is not observed in silicon nanofilms due to their vanishing flaw tolerance range. For silicon films thinner than about 14 nm, the failure strength increases with the decrease of film thickness because of the combining effects of lattice trapping and nonlinear response. The failure strength converges to the predicted value based on Griffith criterion when film thickness is large. Key-Words: Size-dependence, Silicon nanofilm, Failure strength, Flaw tolerance, Griffith criterion.
Variable Natural Killer Cell Activity in Hematological Malignancies at Diagnosis

eISSN 2093-6338 toxic activity via perforin and granzyme, or by induction of death receptor-mediated apoptosis. Furthermore, they secrete a variety of cytokines and chemokines that promote the adaptive immune system to activate macrophages and lymphocytes [1, 2]. The percentage and/or absolute count of NK cells increase with age, whereas NK cell cytotoxicity decreases with age [3, 4]. NK cells are an important component in the early stages of anticancer defense. The high cytotoxic activity of NK cells is associated with reduced cancer risk [5]. However, tumors can escape immune surveillance by various mechanisms, which induces reduced immunogenicity and leads to upregulation of inhibitory receptors on NK cells or downregulation of the ligands on tumor cells for NK cell activating receptors [1, 2]. Previously, increased expression of the inhibitory NKG2A receptor was observed in patients with renal cell carcinoma, resulting in decreased NK cell activity (NKA) [6]. Patients with prostate, gastrointestinal, or colon cancer showed reduced NK cell numbers and activity, with a high level of T-regulatory cells [7]. In hematological malignancies, de혈액종양 진단 시에 관찰되는 자연살해세포활성의 다양성 Variable Natural Killer Cell Activity in Hematological Malignancies at Diagnosis
Credit Card Fraud Detection using Logistic Regression and Bayesian Network

: The primary target of this plan is to perform prescient investigation on credit cards fraud detection dataset utilizing AI procedures and distinguish the deceitful exchanges from the given dataset. The center is to distinguish if an exchange goes under ordinary class or fake class utilizing prescient models. Diverse examining methods will be executed to handle the class irregularity/deceitful exchange issue and arrangement of AI calculations like Logistic Regression and Bayesian Network will be actualized on the dataset, and the outcomes will be accounted for with estimating the information credited utilizing proposed calculations with more exactness and adequacy.
Real Time Video Segmentation in Cluttered Environment using Graph Cut Approach

: In this paper we extend the work done in [1] in which graph based approach is described. The algorithm defines a predicate used for segmenting images. In this paper we show the analysis of the defined predicate and vary the threshold K of the predicate and examine the regions generated and determine the best predicate for segmenting images and we further extend this work by implementing segmentation in a video on cluttered environment on 3 different categories of video such as entertainment, sports and nature. For a real life application, video sequence can be of much longer duration. In order to handle the seamless video sequence efficiently, we have proposed one of the ways of handling the memory. Multithreading and Process Concurrency is the underlying principle employed in the model
NESTING HABITAT CHARACTERISTICS AND FOOD HABITS OF MALAYAN GIANT SQUIRREL RATUFA BICOLOR (SPARRMANN, 1778) IN GIBBON WILDLIFE SANCTUARY, JORHAT, ASSAM, INDIA

The Malayan giant squirrel, Ratufa bicolor has an extensive mainland distribution, occurring from Singapore to southern China and northeastern India in a variety of tropical and sub-tropical forests as well as on Sumatra and Java. Species was common amongst most deciduous, evergreen and semi-evergreen forests all over Assam, from plains to hills. It was rare but common in some pockets within the protected area and reserved forests. Fewer studies have been conducted on this species in India. The present study provides a brief account of its nesting habitat characteristics in the Gibbon Wildlife Sanctuary, Assam to initiates conservation implications. A total of 50 nests of Malayan giant squirrels were located from February 2010 to February 2011 in the study area. Habitat characteristics along with food habits and food types were observed and analyzed its proportional use. The implications of the results for the conservation and management of the squirrel habitats in this sanctuary have been discussed.
A Review on Malware Detection on Android Smartphones Using Keywords Vector and SVM

: In the recent years smart phones are widely used and with that malwares also come with mobile phones like with the Android phones and that malware cause harm to user information. And the big problem is how to detect new malware and malicious. And by observing that develop the feature extraction method by using binary problem, this paper represent the method for feature extraction of java source code.This method use the Keyword Correlation Distance for computing the correlation between key codes such as APL calls, Android permissions, the common parameters, and also the common keywords in Android malware source code. After that use the SVM (Support Vector Machine) for the system gain to assists the function of new malware software sample, so as to detect new malicious software and existing malwares. This method is different from the conventional methods which are based on the context of the text. This method combines the characteristics of the malicious software categories and operating environment to record the behavior of the malicious software. Experiments show that the method is efficient and effective in detecting malwares on Android platform.
Upregulated NTF4 in colorectal cancer promotes tumor development via regulating autophagy

Autophagy plays a key role in colorectal cancer (CRC) development and reduces the sensitivity of CRC cells to treatment. The present study reported a novel tumor-suppressive role for autophagy, which was demonstrated to be regulated through the novel oncogene neurotrophin-4 (NTF4). NTF4 was significantly overexpressed in tumor tissue compared with non-tumor mucosa, and the upregulation of NTF4 in CRC was associated with poor overall survival and advanced TNM stage. The genetic knockdown of NTF4 using short hairpin RNA in CRC cells prevented epithelial-to-mesenchymal transition and activated autophagy; this was regulated through the interaction between autophagy-associated gene 5 (Atg5) and the mitogen-activated protein kinase pathway. In addition, the knockdown of NTF4 inhibited cell invasion, migration, proliferation and colony formation, and promoted cell cycle arrest. Treatment of the cells with the autophagy inhibitor chloroquine (CQ) rescued these functions and promoted cell invasion, migration, proliferation and colony formation. Finally, the knockdown of NTF4 inhibited the growth of subcutaneous xenografts in Balb/c-nu mice. In conclusion, these findings suggested that NTF4 may be a diagnostic marker associated with the overall survival and progression of patients with CRC. NTF4 was found to promote tumorigenesis and CRC development through autophagy regulation.
Reducing the Cost of Remoteness: Community-Based Health Interventions, Fertility Choices and Child Health Investments♣

Distance to health centers can represent a significant healthcare cost for poor households. Community-based health interventions and community health workers can be an alternative to deficient formal health care provision among remote populations. We analyze the effects on fertility and child health investments of a large-scale community-based health worker program that aims to reach remote areas distant from health facilities in Madagascar. We use a triple-difference model that exploits time and geographic variation in the program rollout and the geocoded household distance to the closest health facility. Our findings indicate that the program decreased the probability of conception among women in treated areas but did not have a differential effect among women living in remote areas. A potential mechanism underlying this fertility reduction is that the program increased women’s modern contraceptive use. Regarding child investments, we find an improvement in vaccination uptake in areas distant from the closest health facility.
Growth of Graphene by Silicon Carbide Sublimation

Graphene has become the material of choice for several investigators because of its desirable properties. This two-dimensional “super” material is hexagonally bonded in an sp2 carbon arrangement. Successful methods for growing graphene include chemical vapor deposition (CVD) on metal surfaces like copper or nickel and by sublimation of silicon carbide (SiC). Graphene on SiC is of particular interest because it does not require transferal onto another substrate like graphene grown on copper does and the process is not as strenuous and damage-prone. This work investigates the conditions necessary for producing graphene on C-terminated 6H-SiC wafers by sublimation. Hydrogen (H2) surface etching was performed at 1200°C, while sublimation was done between 1500°C-1700°C in the presence of argon (Ar) gas, at a pressure of 200 Torr. The growth times were varied from 15-60 minutes. Scanning electron microscopy (SEM) and Raman spectroscopy were used to characterize the results obtained for single and multilayer graphene.
An Improved MPPT of SPV System using PSO

Due to increasing energy demand, depletion of fossil fuel resources, requirement of pollution reduction solar energy is becoming an important alternative solution as non-conventional energy source observing its positive impact on society and nature. The photovoltaic module is an unstable source of energy as the maximum power output from solar module depends on temperature and irradiation for all instances imparting non-linearity in output characteristic. This dependency necessitates the tracking of Maximum Power Point. A comparative study of MPPT method using Particle Swarm Optimization applied to two different Swarms is presented in this paper. “Simulink” facility is used to build MPPT controller for stand-alone Solar Power Generation System.
RESEARCH AND DEVELOPMENT INTENSITY, FIRM PERFORMANCE, AND GREEN PRODUCT INNOVATION

This study was conducted to determine the effect of research and development intensity (RNDI) on firm performance (FP) with green product innovation (GPI) as an intervening variable. Companies which are always innovative with market developments will get two benefits. First, achieving competitive advantage. Second, obtaining economic benefits, therefore it will increase firm performance. This study uses 170 company observations from listed companies in Indonesia Stock Exchange at 2013-2017 as sample of research. The samples were choosen by purposive sampling method and were analized by path analysis method using STATA software. The result shows that RNDI has an effect on FP, RNDI has an effect on GPI, and GPI has an effect on FP. They indicate that GPI can mediate the effect of RNDI on FP in partial.
Experimental Analysis of Residual Stresses in the Various Zones of Arc Welded EN-8 Steel

Residual stresses are internal stresses locked into a rigid part in the absence of external forces or thermal gradients. Residual stresses present in the material lead cracking in the material. Hence, the estimation of residual stresses becomes essential after fabrication processes like welding, casting, etc. In the present work, residual stress has been measured arc welded EN8 steel using high resolution x-ray diffraction method (HRXRD). EN8 steels are used in many machine parts such as axles, shafts, presses & punches parts, piston rods & gear rods. The base material (EN8 steel) has been joined using arc welding process. The residual stress analysis was carried out in the three zones namely, welded zone, heat affected zone (HAZ) and parent zone. In XRD technique, when the stress is positive then the dspacing increases and when it is negative then the d-spacing decreases. Distributions of residual stresses on the welded zone, heat affected zone and parent zone have been evaluated. The result shows that the residual stress distribution for all the zones is characterized by compressive stresses.
Improving Infrastructure in Informal Settlements: Experimental Evidence from India

The rapid pace of urbanization in most cities of the developing world can create enormous challenges for the quality of life of people living in informal settlements. We focus on understanding the role of supply-side and informational constraints in the quality of urban sanitation. We implement a cluster-randomized experiment in 110 slums in the cities of Lucknow and Kanpur, India. Community Toilets (CTs) and their catchment areas are randomly allocated to either a supply-side intervention on its own or combined with information provision. Data from both slum dwellers and CT caretakers’ behaviour is obtained using a wide range of methods, including surveys, observational data and incentive-compatible behavioural measurements. JEL codes: TBD.
Management of anastomotic leaks after esophagectomy and gastric pull-up

Anastomotic leak is one of the most feared complications of esophagectomy, leading to prolonged hospital stay, increased postoperative mortality, and additional cost both to the patient and the hospital. Historically, anastomotic leaks have been treated with several techniques including conservative measures, percutaneous or operative drainage, primary surgical repair with buttressing, T-tube drainage, or excision of the esophageal replacement conduit with end esophagostomy. With advances in treatment modalities, including endoscopic stenting, clips and suturing, endoluminal vacuum-assisted closure (EVAC), such leaks increasingly are being managed without operative re-intervention and with salvage of the esophageal replacement conduit. For the purposes of this review, we identified studies analyzing the management of postoperative leak after esophagectomy. We then compared the efficacy of the various newer modalities for closure of anastomotic leaks and gastric conduit defects. We found both esophageal stent and EVAC sponges are effective treatments for closure of anastomotic leak. The chosen treatment modality for salvage of the esophageal replacement conduit is entirely dependent on the patient’s clinical status and the surgeon’s preference and experience. Emerging endoscopic and endoluminal therapies have increased the armamentarium of tools the esophageal surgeon has to facilitate successful resolution of anastomotic leaks following esophagectomy with reconstruction. While some literature suggests that EVACs have a slightly superior result in conduit success, we question this endorsement as EVACs mostly are utilized for contained leaks, many of which may have healed with conservative measures. This poses a challenge as there is clearly a bias given patient selection.
Building an Intrusion Detection System Using a Filter-Based Feature Selection Algorithm

: With the development of Internet, there has been a huge increment in the quantity of attacks and in this manner Intrusion detection Systems (IDS's). unessential segments in data have achieved a whole deal issue in framework action gathering. These segments back off the method of course of action and in addition shield a classifier from settling on exact decisions, especially when adjusting to huge data. In this paper, we propose common information based figuring that methodically picks the perfect part for game plan. This mutual information based segment assurance computation can manage straightforwardly and nonlinearly subordinate data features. Its ampleness is surveyed in the cases of framework intrusion disclosure. An Intrusion Detection System (IDS), is manufactured using the components picked by our proposed incorporate assurance estimation. The execution of Intrusion Detection is surveyed using two intrusion recognizable proof evaluation datasets, to be particular KDD Cup 99 and NSL KDD.The evaluation comes to fruition show that our component decision figuring contributes more fundamental components for Intrusion Detection to fulfill better accuracy and lower computational cost differentiated and the best in class methods.
Predicting Depression Level Using Social Media Posts

: Depression is a major issue which is increasing day by day. Worldwide mental illness is primary cause of depression. Millions of people each year suffered from depression and only fraction of them undergoes adequate treatment. It is serious medical illness which corresponds to user’s ability to work, study, participation in social activities and having fun. Depression is serious challenge in personal and public health. One of the major solutions to this problem is detailed study of individual’s behaviour attributes. These attributes are available on various social networking sites such as Facebook ,twitter,instagrametc.Social networking platform is best way to know person behaviour,thinking style,mood,egoistic networks ,opinions etc. The use of social networking sites is increasing especially by young generation.The people on social media express their feelings, daily activities, opinions about various topics etc.So,social networking sites are used as screening tool to predict depression levels. These social networking platforms givesperson’sexperiences,opinions,socialization,personality.People feelings could be positive, negative or neutral. In order to determine depression levels, person’s negative response is important because it tells us about the negativism. Earlier method of diagnosis of patient is not so relevant but by using user generated content on social media such as Facebook definitely helps to predict mental health levels and depression of particular individual. Our project aim is to extract information from social media posts and by having clear understanding of person’s behavioural attributes and attempted questionnaires, depression levels of user is predicted. By using machine learning algorithms such as Naive Bayes, depression level of user is classified into different levels and provides doctor’s location near to user location.
Selected highlights of the 2019 Pulmonary Pathology Society Biennial Meeting: PD-L1 test harmonization studies

Immune checkpoint inhibitors (ICI) including programmed death 1 (PD-1) inhibitors, such as nivolumab and pembrolizumab, or programmed death ligand 1 (PD-L1) inhibitors, such as atezolizumab and durvalumab, have recently emerged in advanced stage lung cancer as new standards of care. They are now indicated in first- line and second- or later-line treatment of metastatic or locally-advanced stage III non-small cell lung cancer (NSCLC), as well as for metastatic small cell lung cancer (SCLC), as single agent immunotherapy or in combination with chemotherapy. Four PD-L1 immunohistochemistry (IHC) assays have been established and validated in randomized trials, each for a specific ICI. They use different primary monoclonal antibodies, platforms and detection systems, as well as different scoring systems to assess PD-L1 expression either by tumor cells (TCs) and/or by infiltrating immune cells (ICs). Most studies have shown a close analytical performance of three of these clinically-validated standardized assays, but their use restricted to dedicated platforms, which are not all available in most laboratories, questions their applicability. In addition, the relative high costs of the assays have led to the development of in-house protocols in many pathology laboratories. Their use in clinical practice to assess the predictive value of PD-L1 expression for prescription of ICI raises the issue of their reliability and their validation as compared to standardized assays. This article discusses the main comparative studies available between LDT and assays, with clear evidence that LDT can reach a performance equivalent to the trial-validated assays. The requirements are an adequate validation as compared to an appropriate standard, and the participation to external quality assurance programs and training programs for PD-L1 IHC assessment for pathologists.
An Innovative Optimized Design for Laminated Composites in terms of a Proposed Bi-Objective Technique

The article proposes a bi-objective optimization approach for layup design of laminates. The optimization method combines the Particle Swarm Optimization (PSO) heuristics and Simulated Annealing (SA) optimization method. The minimum weight optimization is subjected to design constraints such as strength, stiffness, layup blending continuity, and several manufacturing design rules, which are combined as a single function and included within the bi-objective formulation. Several composite materials design problems are included to show the capabilities and usefulness of the proposed method. The optimization analysis has also been connected to the finite element analysis to solve the problem of composite plate optimization with blending constraints. The plate is divided into some regions, and the blending constraints are imposed globally by using the concepts of the greater-than-or-equal-to blending to achieve continuity of laminate layups across the regions. The results generally showed that the proposed method led to excellent results, representing a promising approach for the design of laminated composite materials.
2 emissions from the residential sectors in Europe: drivers and distributive consequences (Preliminary draft)

This paper investigates empirically the causal factors of the 2 emissions from the residential sectors for 14 European countries during the 1990 − 2012 period. We find significant effects of both economic and climatic variables on 2 emissions. We compute the distributional impacts of a European carbon tax (20) and show that it increases the inequalities among countries, in terms of tax revenue-toGDP ratio. We finally simulate the country-specific carbon tax policies that equalize the burden among countries. We define the compensatory transfers that may correct these inequalities, increasing therefore the acceptability of the environmental policy. Basically, these transfers represent (in average) 5% of the cost of the European Union climate and energy package.