Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessing how tourism revenues reach the poor-ODI Briefing Papers 21-Briefing papers

Tourism, like any other productive activity, has the potential to improve the livelihoods of poor people. To realise this potential requires an understanding of the volume of tourism benefits that reach the poor and ways to enhance the access of the poor to the tourism value chain. This understanding has, however, been difficult to gain from much previous analysis: • Conventional tourist data and policy analysis focused on macro-variables (tourist arrivals, foreign exchange receipts and investments), with little on measuring benefits to the poor. • As a reaction to this, much pro-poor tourism analysis adopted a micro-level approach – focusing on the livelihood impacts on poor people of specific niche tourism enterprises. A limited geographical scale, descriptive nature and niche focus meant these microstudies failed to generate recommendations for boosting pro-poor tourism benefits in most mainstream tourist destinations. By adapting existing diagnostic tools and applying them in new contexts to map revenue streams and policy frameworks, a handful of development practitioners are starting to close this information gap. Using value chain analysis, they aim to map the tourism economy, its revenue streams, and beneficiaries. They can use this to address a range of questions for developing country policy makers seeking to improve the pro-poor impact of tourism. The Masai people assess their returns from tourist excursions using Value Chain Analysis.
COMPACT TRI-BAND PATCH ANTENNA FOR KU BAND APPLICATIONS

A compact tri-band antenna is designed and analyzed to achieve both transmission and reception of direct broadcast service (DBS) and fixed satellite service (FSS) in Ku band. The proposed antenna design consists of a truncated E-shaped slot, eight rectangular slots, two C-shaped slots in the patch and eight defected ground structure (DGS) slots. The three frequency bands of 11.40–12.91 GHz, 13.86–14.53 GHz, and 17.20–17.86 GHz are achieved with impedance bandwidths of 12.32%, 4.73%, and 3.77%, respectively. Conversely, the measured frequency bands of 11.40–12.98 GHz, 14.21–14.86 GHz, and 17.41–18.98 GHz with the impedance bandwidth of 12.70%, 4.48%, and 8.63%, respectively, are obtained. The simulated results of the proposed antenna are compared with the results of fabricated antenna and are found to be satisfactory for reflection coefficient, impedance bandwidth, polarization, efficiency, gain, and radiation pattern. Moreover, the proposed antenna design can be used as an element in an array configuration to achieve high gain in both transmission and reception modes of FSS and DBS.
Algorithm Implementation for Product Recommendation System Using Collaborative Filtering and Deep Learning

-- Collaborative Filtering (CF) and Deep Learning is one of the most successful recommendation approaches to cope with information overload in the real world. However, typical CF methods equally treat every user and item, and cannot distinguish the variation of user’s interests across different domains. This violates the reality that user’s interests always center on some specific domains, and the users having similar tastes on one domain may have totally different tastes on another domain. Different CF techniques can be classified into two classes: memory-based methods and model based methods. , we studied a novel Domain-sensitive Recommendation (DsRec) algorithm, to make the rating prediction by exploring the user-item subgroup analysis simultaneously.
Email based Real Time Cardio Telemetry System of Patient Monitoring through Internet

— In this study we developed a email based system for remote real-time tele-monitoring of patient with abnormal heart activity that helps doctors for detecting potential problems earlier, providing emergency health care, improving the quality of patient health and minimizing healthcare costs by reducing number of hospitalizations of patients. This paper initiates to develop a system for facilitating the accessibility of information about the patient’s health both in hospital and home by reducing the physical movement of clinical staff to each patient. The study focuses on the key issues and challenges regarding the design and implementation of cost effective remote patient monitoring system and introduces the integration of pulse oximetry transducer based cardio-telemetry system with windows based software interface for real time data acquisition, risk calculation, and finally wireless transmission using the Internet as communication platform for implementation of an email based patient records management system. Using this system a specialist doctor can telematically ‘move’ to the patient site and instruct the patient depending on their vital signs. This cardio-telemetry system is equipped by two types of data base like local data base that is maintained by zonal or remote hospital and master data base that is maintained by administrative hospital, allowing the system to store and manage the data simultaneously.
In a Representative Sample Grit Has a Negligible Effect on Educational and Economic Success Compared to Intelligence

We compare the relative contribution of grit and intelligence to educational and job-market success in a representative sample of the American population. We find that, in terms of ΔR 2, intelligence contributes 48–90 times more than grit to educational success and 13 times more to job-market success. Conscientiousness also contributes to success more than grit but only twice as much. We show that the reason our results differ from those of previous studies which showed that grit has a stronger effect on success is that these previous studies used nonrepresentative samples that were range restricted on intelligence. Our findings suggest that although grit has some effect on success, it is negligible compared to intelligence and perhaps also to other traditional predictors of success.
: THE CREATION AND DATA MINING OF 3D VISUAL DATABASES

Visualization, perception and the cognitive process are inexorably linked. While many visualization techniques and strategies greatly enhance our mental abilities, others can be more confusing than they are useful. Since our eyes and brain are the main organs involved in the process of visualization and cognition, an understanding of their function should help develop more effective ways of enhancing our cognitive capabilities. While many of us would like to believe that we see a complete and detailed picture of the world, this notion is completely incorrect (O’Regan 1992). For example, our eyes collect image information via a non-uniform distribution of about 100 million receptors. Since the optic nerve linking the eyes to the brain, has about 1 million fibers, only a small fraction of this information becomes available for cognitive processes. The act of perception follows both bottom-up and top-down processes occurring simultaneously in different parts of the brain (Ware, 2008). Bottom-up processing is information driven, searching visual input progressively for features, patterns and objects. Top-down processing is more focused on a specific goal. While the brain is a massive parallel processing system creating complex patterns from features, only a few objects can be worked with at any one time. This very limited visual working memory is the main limitation that visualization techniques are developed to help overcome. Both top-down and bottom-up processing can be very powerful but tend to ignore most of the available information along with any significant information that this information may contain. Moreover, developing a perception of reality based on top-down processing can be very biased towards the goals we are trying to achieve.
A Collaborative Filtering Approach for Big Data Application Based on Clustering

: In the recent days the web domain is augmented with new types of services, with the increase in service and cloud computing. As a result, new forms of web content collecting /designing is done based on the numerous openly available web services online. These services are utilized in many ways by different domains and with the exponential growth of these web services users are experiencing difficulties in finding and utilizing a best matching service for their mash up. A collaborative filtering approach is going to filter and recognize the similar services under same cluster and followed by those evaluations recommendations are made Recommender systems are now popular both commercially and in the research community, where many approaches have been suggested for providing recommendations. In many cases a system designer that wishes to employ a recommendation system must choose between a set of candidate approaches. A first step towards selecting an appropriate algorithm is to decide which properties of the application to focus upon when making this choice. Indeed, recommendation systems have a variety of properties that may affect user experience, such as accuracy, robustness, scalability, and so forth. In this paper the system discusses how to compare recommenders based on a set of properties that are relevant for the application. Recommender systems can now be found in many modern applications that expose the user to huge collections of items. Such systems typically provide the user with a list of recommended items they might prefer, or predict how much they might prefer each item. These systems help users to decide on appropriate items, and ease the task of finding preferred items in the collection.
Genetics of the immune response to ferredoxin : assessment of control at the determinant level

Ferredoxin (Fd), a f i f t y f i v e amino acid electron transport protein of the anaerobe Clostridium pasteurianum, has been chosen as the ideal probe for immunoregulation studies. Its c r i t i c a l feature is that i t contains two antigenic determinants satisfying the hypothetical minimum requirement for immunogenicity. It was found that both the antibody (as measured by ELISA) and the lympho-proliferative responses to Fd are linked exclusively to the MHC of mice, mapping to K/I-A. Analysis of the response was undertaken at the determinant level with selective enzyme cleavage products of trypsin and carboxypeptidase A which yield respectively a 52 residue C-determinant peptide (devoid of a functional N-determinant), "C", and a 53 residue N-determinant peptide (devoid of a functional C-determinant peptide), "N",. Through the use of these two molecules ("N" and "C") and a doubly digested molecule, "M", the immune response to Fd was dissected. It At f i r s t , anti-Fd antibody from high responder, H-2 , mice was shown to be 10-20% "N" specific with the balance of the response "C" b s directed, while intermediate responder haplotypes, H-2 and H-2 , d . demonstrate equal specificity for the two determinants. H-2 mice were uniformly non-responsive. Fd immune T-cells demonstrated l y m p h o p r o l i f e r a t i v e c a p a c i t y m i r r o r i n g the antibody response of B10.BR (H-2 ) mice: "C" induced p r o l i f e r a t i o n comparable to that w i t h the na t i v e molecule, "N" inducing a much lower response, one matched by the
DISCRETE MESH OPTIMIZATION ON SURFACE AND VOLUME MESHES

State of the art algorithms in surface mesh smoothing rely on computing new vertex positions on approximated shapes and re-projecting the results back onto the real surface or having no internal surface representation at all, which leads inevitably to suboptimal results. Discrete Mesh Optimization (DMO) is a greedy approach to topology-consistent mesh quality improvement, which was initially designed to smooth triangle and quadrilateral meshes in two dimensions and tetrahedral meshes in three dimensions. We present a generalization of DMO which allows optimization on discretized surfaces, or more general d-dimensional manifolds. As the method is not bound to search directions, it is capable of ﬁnding the optimal vertex positions directly on a surface without any re-projection. Therefore, the proposed technique preserves the underlying surface or volume. We present examples for surface and volume meshes, showing the improvement-potential of considering boundary vertices in the smoothing process.
CRISPR/Cas9-Mediated Targeted Mutagenesis of Wild Soybean (Glycine soja) Hairy Roots Altered the Transcription Profile of the Mutant

Clustered Regularly Interspaced Short Palindromic Repeat/CRISPR-associated protein 9 (CRISPR/Cas9) system has been regularly applied for genome editing and gene function identification in wild soybean (Glycine max) cultivars. However, till date no studies have demonstrated successful mutagenesis in wild soybean (Glycine soja) which is the ancestor of Glycine max and rich in stress tolerance genes. In the current study, we report the successful creation of mutations in the loci encoding plasma membrane Na+/H+ antiporter (SOS1) and nonselective cation channels (NSCC) in wild soybean hairy roots using the CRISPR/Cas9 system. Two genes, GsSOS1 and GsNSCC, were mutagenized with frequencies of 28.5% and 39.9%, respectively. Biallelic mutations in GsSOS1 were detected in transgenic hairy roots. GsSOS1 mutants exhibited altered Na+/K+ ratios in the roots under both control and salt-treated conditions. However, no significant effects of GsNSCC mutation on Na+/K+ ratios were observed. RNA-Seq analysis revealed that both GsSOS1 and GsNSCC mutation altered the transcription profiles in mutant roots. Many differentially expressed gene sets that are associated with various cellular functions were identified. Our results demonstrated that CRISPR/Cas9 systems as powerful tools for wild soybean genome editing and would significantly advance the gene mining and functional identification in wild soybean.
CLASSICAL AND NON-LINEAR PREDICTIVE CONTROL APPLIED TO A NON-LINEAR SYSTEM OF COUPLED TANKS

This document presents the design, implementation and comparison of algorithms to control the liquid level in a non-linear system of two coupled tanks. First, a Proportional-Integral (PI) controller was designed; then, a Model-based Predictive Controller (MPC) using the Non-linear Extended Prediction Self-Adaptive Control (NEPSAC) algorithm was designed. The performance of the controllers was evaluated in two scenarios: Setpoint Tracking and Disturbance Rejection. It is concluded that the NEPSAC algorithm presents better performance with respect to the PI, since the PI works correctly in regions very close to the setpoint while the NEPSAC, not requiring linearization of the system, has a performance that does not depend on the setpoint, presenting excellent characteristics at any reference point. To validate the results obtained, the Root Mean Square Error (RMSE) was used, which resulted in better values for the NEPSAC than for the PI.
A Decentralized Platform for Secure, Autonomous and Digital Labor Search and Workflow

: It is estimated over 90% of workers in India work in the informal economy, and are therefore vulnerable to exploitation in an informal and unregulated environment. In spite of the various labor protection acts, there exists no solution which ensures an exploitation free labor task-force and adherence to minimum wages, safety and maximum hour’s regulations. Moreover, employers have to pay more and labors get less due to presence of hierarchal system of bribery and transaction fees. In this paper, we propose an online decentralized job search system based on blockchain for employers and job seekers to interact directly. This complete system would eliminate the exploitation faced by job seekers and the money wasted at various intermediate levels of job search. Also, pursuit of each job would be represented as a smart contract where payment would be deferred and also determined partially by quality of the work. Also, we propose a unique Aadhar based authentication system for ensuring authenticity of the digital identities of the people on the decentralized network. There is also the added benefit of ensuring that the worker is not underage by checking against the Aadhar API and thereby eliminating child labor.
Application of the IIoT to Equipment Maintenance

As an increasing number of plant facilities are aging and with growing demand for environmental protection, condition-based maintenance (CBM) is needed in developed countries. However, identifying and managing the state of facilities depends largely on skilled field workers, and it is difficult to transfer their know-how to the next generation, hindering the widespread use of CBM. Yokogawa Electric Corporation has long been involved in plant operation and equipment maintenance, and is now planning to use the Industrial Internet of Things (IIoT) and artificial intelligence (AI) in these areas in order to promote CBM. Yokogawa’s Sushi Sensor is a product based on this concept. This paper describes the functions and various technologies behind Sushi Sensor.
Alternative splicing of human elastin mRNA demonstrated by sequence analysis of cloned genomic and complementary DNA

Poly A/sup +/ RNA, isolated from a single 7 month human fetal aorta, was used to synthesize cDNA by the RNAse H method, using AMV reverse transcriptase for first strand synthesis and DNA polymerase I for the second strand. Three clones containing inserts of 3.3, 2.8 and 2.5 kb were selected for further analysis. Three overlapping clones containing 18.4 kb of the human elastin gene were also isolated from genomic libraries. Complete sequence analysis of the 6 clones demonstrated that: (1) the largest cDNA encompassed the entire translated portion of the mRNA (2) there was extensive alternative splicing of the mRNA, (3) there were several unusual hydrophilic amino acid sequences not previously identified in pig tropoelastin, (4) exons encoding either hydrophobic or crosslinking domains in the protein alternate in the gene (5) there is a great abundance of Alu repetitive sequences throughout the introns. These results suggest the potential for significant variation in the precise molecular structure and function of the elastic fiber in the human population.
Analysis of Classification Algorithms to find the Key Factors Causing Road Accidents

: Road calamities have become the root cause of increasing fatal death count that hands-on with roads, driver, vehicle-condition and weather. Concerning the safe longevity, it entails the data analytic tool to take the measures for diminishing the death toll. Data mining is one such area that identifies the underlying reason behind every accident. Classification technique is the most likely preferable for the prediction steps. At the same pace, the increases in death count stimulates to discover the very fine methodology to handle the huge amount of accidental data in an effective way. This research led to uncover the fact that serves as the root cause for the road calamities using the Decision tree and K-Nearest Neighbor (KNN) algorithm to prevent the human loss
A Secure Data Sharing in Public Cloud using DES, RC4 and Diffie

Cloud is not a new technology, but a new delivery method in which services are hosted on third party assets. Due to its distributed architecture, security is one of the prime concern in cloud computing. Cloud computing provides the facility of data storage and access for cloud users, Cloud computing is widely used service model for storage. Outsourcing the data to a third party causes safety issue of sensitive data. Shared sensitive data must be strongly secured from unauthorized access over the clouds so data is protected by restricting the data. We proposed two level security mechanism. In our proposed scheme there is a registration for user to use cloud services. The registration of the user also assures security of the data in cloud. Only authorized users can access the cloud data. Data should be encrypted with the help of symmetric algorithms. Two tier authentication scheme provide the integrity, authenticity to the user. In proposed scheme first encryption is user based and the second is cloud based. After successful authentication user can get the data. Aim of this scheme is to combine the best of symmetric and asymmetric mechanisms to provide effective security model on public clouds.
A critical narrative review of medical cannabis in pediatrics beyond epilepsy, part I: background

In the past few decades, the use of marijuana, now commonly referred to as cannabis in the scientific community, has expanded globally to a myriad of medical conditions beyond epilepsy in pediatrics. In this comprehensive review, PubMed, Embase, and Clinicaltrials.gov (1966–May 2020) searches were performed using the key search terms cannabis, medical marijuana, cannabinoids, pediatrics, neuropsychiatric disorders, spasticity, pain, gastrointestinal disorders, and cancer. All article abstracts were evaluated for relevance. Only articles pertaining to cannabis were included. Cannabis has had an extensive history in medicinal therapeutics, dating back to ancient civilizations. With the recent legalization of cannabis that has augmented its use, a critical review of the medicinal properties and clinical use of cannabis is warranted to support pediatric healthcare practitioners in making informed and evidence-based decisions. In this first section of a three-part series, a comprehensive overview of cannabis and conditions surrounding its use was presented, incorporating its historical perspective, chemical constituents and mechanistic properties within the endocannabinoid system, position for its use by regulatory and professional bodies, ethical considerations, and importance of education of healthcare providers. Our current understanding of the medical use of cannabis is limited by lack of optimal dosing, long-term efficacy, safety, and drug interaction data in the pediatric population, prompting the need for additional research.
Molecular systematics of the South African gobiid fishes of the genus glossogobius gill, 1862 (teleostei : gobiidae)

ii ACKNOWLEDGEMENTS v LIST OF CONTENTS vii LIST OF TABLES x LIST OF FIGURES xii CHAPTER 1: GENERAL INTRODUCTION 1 1. LITERATURE REVIEW 1 1.1. South African biogeographic regions and the study areas 5 1.2. Studied taxa 7 1.2.1 Glossogobius callidus 9 1.2.2 Glossogobius giuris 9 1.3. Molecular systematics 10 1.4. Genetic structure and phylogeography 11 1.5. Genetic markers 13 1.5. 1 Animal Mitochondrial DNA marker (mtDNA) 14 1.5. 1.1 Cytochrome b 15 1.5. 2 Nuclear DNA marker 16 2. AIMS AND OBJECTIVES 17 CHAPTER 2: MATERIALS AND METHODS 25 2. OVERVIEW 25 2.1. Sampling procedure and species identification 25 2.2. DNA extractions 26 2.3. Polymerase chain reaction (PCR) 26 -
On-the-fly Targetless Extrinsics Calibration For Multi-Stereo Systems Without Field-of-View Overlap

We propose an on-the-fly extrinsics calibration method for stereo pairs lacking overlapping field of view (FoV) that is robust to visual odometry errors. Multi-stereo systems are becoming increasingly popular because of their large field of view that benefits both state estimation and mapping. A critical challenge in multi-stereo systems is to calibrate the extrinsics among the stereo pairs, which becomes even more difficult when the FoV of different stereo pairs does not overlap. Moreover, due to external forces (e.g., impact or vibration) or changes of the environment (e.g., temperature or pressure), the extrinsics can change over time. As a result, on-the-fly calibration of the extrinsics is necessary. We propose an on-the-fly targetless extrinsic calibration method for a multi-stereo system without FoV overlap. Experimental results with both simulation and real-world data show that the proposed method is successful in estimating and updating the extrinsics on-the-fly and is fairly robust to outliers and degeneracy in the measurements.