Miracle-dz/UniFAR-FTUs huggingface dataset:
Economic growth and Energy consumption nexus in Developing World : The case of China and India

The global energy demand is continuing to grow unabated and all eyes are on the two most developing nations India and China. Here an attempt is made to study the causal relationship between energy consumption (electricity, coal and petroleum) and economic growth for India and China in a VECM framework. Findings suggest the existence of the long run relationship amongst the various forms of energy consumption and economic growth in both the countries. In case of India a bidirectional causality running between coal consumption and economic growth is observed not only in the short run but also in the long run. A unidirectional causality is observed from petroleum consumption to economic growth both in short run and long run in case of India. However for China, unidirectional causality is observed from economic growth to coal consumption and from petroleum consumption to economic growth in both short run and long run. Jel code: O10, Q4, Q43 Copyright © 2014 JAEBR
Parallel Segregation-Integration Networks for Shared-account Cross-domain Sequential Recommendations

Sequential Recommendation (SR) has been attracting a growing attention for the superiority in modeling sequential information of user behaviors. We study SR in a particularly challenging context, in which multiple individual users share a single account (shared-account) and in which user behaviors are available in multiple domains (cross-domain). These characteristics bring new challenges on top of those of the traditional SR task. On the one hand, we need to identify the behaviors by different user roles under the same account in order to recommend the right item to the right user role at the right time. On the other hand, we need to discriminate the behaviors from one domain that might be helpful to improve recommendations in the other domains. In this work, we formulate Shared-account Cross-domain Sequential Recommendation (SCSR) and propose a parallel modeling network to address the two challenges above, namely Parallel Segregation-Integration Network ({\psi}-Net). {\psi}-Net-I is a "Segregation-by-Integration" framework where it segregates to get role-specific representations and integrates to get cross-domain representations at each timestamp simultaneously. {\psi}Net-II is a "Segregation-and-Integration" framework where it first segregates role-specific representations at each timestamp, and then the representations from all timestamps and all roles are integrated to get crossdomain representations. We use two datasets to assess the effectiveness of {\psi}-Net. The first dataset is a simulated SCSR dataset obtained by randomly merging the Amazon logs from different users in movie and book domains. The second dataset is a real-world SCSR dataset built from smart TV watching logs of a commercial company. Our experimental results demonstrate that {\psi}-Net outperforms state-of-the-art baselines in terms of MRR and Recall.
Influence of flavonoids’ lipophilicity on platelet aggregation

Abstract Flavonoids are natural polyphenolic compounds present in a wide spectrum of plants that have a beneficial effect on human health. In the context of cardiovascular diseases related to plaque and thrombus formation, flavonoids exhibit an anti-aggregatory effect. Previously, it has been reported that all tested flavonoids exhibit an antiaggregatory effect on platelet aggregation when measured by impedance aggregometry on whole blood, in the test of aggregation induced by adenosine diphosphate (ADP). As not all flavonoids have the same targets within signaling pathways, an assumption of a common non-specific mechanism related to lipophilicity is to be considered. To test this hypothesis, reverse-phase thin layer chromatography was used to assess the lipophilicity of flavonoids; impedance aggregometry was used for testing of platelet aggregation and flow cytometry to monitor the influence of flavonoids on platelet activation. Lipophilicity analysis showed a highly negative correlation of logP and MINaAC for groups of flavones and flavanones. As determined by flow cytometry, the exposition of receptors necessary for the promotion of platelet activation and primary clot formation was diminished, i.e., lowered expression of the activated form of integrin αIIbβ3 was observed in the presence of flavanone. Platelet membrane stabilization by flavonoids as a mechanism of antiaggregatory effect has been supported by impedance aggregometry experiments when specific inhibitors of platelet aggregation signaling pathways (U73122, indomethacin, verapamil) were used in the presence of a weak (ADP) and a strong (TRAP-6) agonist of aggregation. While individual flavonoids can have specific targets within aggregation signaling pathways, all flavonoids share a common non-specific mechanism of platelet aggregation inhibition related to their lipophilicity and membrane stabilization that, to some extent, contributes to their antiaggregatory effect.
MwSandbox : On Improving the Efficiency of Automated Coarse-grained Dynamic Malware Analysis

Malware is a major threat to the cyber world and the number of unique malware samples captured by antivirus software venders is making an explosive growth in recent years. To improve the malware analysis efficiency, researchers have developed several automated coarse-grained dynamic malware analysis systems, including Norman Sandbox, CWSandbox and TTAnalyze, etc. However, these systems' analysis capabilities still cannot compare with the growth of malware, because they rely on heavy virtual machines to build malware execution environments. To further improve the efficiency, this paper analyzes the bottlenecks in these systems and proposes two mechanisms, flash revert and VM fork to reduce the found overheads. Experiments on an OS-level VMM based prototype implementation (MwSandbox) show that the efficiency is improved at least an order of magnitude without losing analysis quality.
Role of gene Xpert in diagnosis of tuberculous pleural effusion: Comparison with pleural biopsy

Introduction: Pakistan is an endemic country for Tuberculosis. Gene Xpert is a recent acquired test for the rapid diagnosis of pulmonary tuberculosis. However, its role in the diagnosis of tuberculous pleural effusion has not been studied. Our aim was to find out whether Gene Xpert could be used for the rapid diagnosis of tuberculous pleural effusion and its comparison with Abram's needle pleural biopsy. Objective : To determine the role of Gene Xpert in diagnosis of Tuberculous Pleural effusion and its comparison with Abram's Needle pleural biopsy. Material and Methods : This cross sectional study comprising 25 patients of lymphocytic exudative pleural effusion having strong susceptibility of tuberculosis on clinical grounds, was conducted in the department of Pulmonology, Nishtar Medical Institution Multan. They underwent closed pleural biopsy with Abram's needle in standard way. Specimens were examined histopathologically, and their pleural fluid was also sent for Gene Xpert. Analysis of both reports was carried out for comparison. Results: Among 25 patients Gene Xpert was only positive in 2(8%) and Pleural Biopsy showed definitive caseating granuloma in 14(56%), Malignancy in 6(24%), Acute Inflammation in 1(4%), Pleuritis in 1(4%) and inconclusive report in 3(12%) patients. Conclusion: Pleural Biopsy is a diagnostic tool in diagnosing tuberculosis. Gene Expert has a limited role in diagnosing tuberculous pleural effusion. Key Words : Pleural Biopsy, Abram needle, Gene Xpert, Lymphocytic Exudative Pleural Effusion.
Ethnomedicinal Plants Used in the Healthcare Systems of Tribes of Dantewada, Chhattisgarh India

The tribal people depend on forests for their livelihood and most of the rural people still depend on traditional medicine as a primary healthcare source. The paper highlights the rich plant resources and the vast wealth of ethnobotanical information available with the various tribes of the region. In this paper, some new and less known ethno medicinal uses of 104 plants of tribes of Dantewada, Dakshin Bastar C.G. in different ailments have been reported. The main objective of present work is to give the information and documentation of medicinal plant used by tribal of the study sites. The ethnomedicinal information was gathered from interviews with living elders belonging to Madiya, Muriya, Gond and Bhatra tribes of the study area. The present work on ethnomedicinal plants, used in the healthcare systems of tribes in 15 villages, was carried out from Geedam block of Dantewada, Dakshin Bastar C.G.
Elevated Body Mass Index and Serum Resistin are Associated with Severity of Allergic Rhinitis

Background: Allergic rhinitis is a prevalent chronic respiratory problem that can impair quality of life, sleep and work. The increase in the prevalence of allergic rhinitis among the general population appears to have an association with weight. Obese individuals are more vulnerable to allergy. Resistin, a recently discovered adipokine, has been shown to have pro-inflammatory properties in humans. This study was designed to evaluate the body mass index of patients with allergic rhinitis and their serum resistin levels and to investigate their association with clinical disease severity. Methods: A case-controlled study was performed on 34 with persistent allergic rhinitis and 20 healthy controls with similar age and sex. Anterior rhinoscopy was done for all patients. Blood samples were collected from the patients for analysis including: total serum immunoglobulin E (IgE) cortisol and resistin. Each patient completed a questionnaire assessment to evaluate the severity of allergic symptoms including nasal obstruction, sneezing, rhinorrhea, and itchy nose. Height and weight were measured by a trained researcher. Results: Body mass index and serum levels of resistin were significantly increased in patients with allergic rhinitis compared with controls, and both correlated positively with disease severity. In addition, they correlated positively with nasal symptom scores. A significant positive correlation was observed between serum levels of resistin with both IgE and body mass index. Conclusions: Patients with allergic rhinitis persistent were found to have higher body mass index and serum levels of resistin, and their levels increased with the progress of disease severity. Resistin may represent a novel link between inflammation and allergic rhinitis . Weight control should be considered as a potential strategy to improve the health status of patients with allergic rhinitis, through the control of symptoms and the improvement of general health.
The First Experiment Use of Some Mineral Nutrients to Reduce Cracking of " Wonderful " Pomegranates Thirty standard "

Pomegranates fruit cracking and poor coloration of peel and aril are the main problems facing the expansion of its cultivation especially under arid condition in the desert. This study was conducted during the two successive seasons 2014 and 2015 on "Wonderful" pomegranates (Punica granatum L.). The trees were grown under drip irrigation system in a private orchard at Nubaria region, Beheira Governorate, Egypt. The trees were treated twice at weekly interval by using a hand sprayer to the run off point at the marble size with some mineral nutrients to reduce fruit cracking. The treatments included: water spray (as the control), calcium borate at 100 ppm, calcium borate at 200 ppm, zinc chelated with EDTA at 100 ppm, zinc chelated with EDTA at 200 ppm and finally calcium nitrate at 1% (W/V). Moreover, to enhance coloration of pomegranates peel and aril, at maturity the trees were treated with the control (water spray), ProTone (ABA 1%) at 100 ppm, ProTone at 100 ppm plus glycerol at 1% (V/V), ProTone at 100 ppm plus potassium sulphate at 1% (W/V), ProTone at 100 ppm plus potassium sulphate at 1% and glycerol at 1% (V/V), glycerol at 1% (V/V) and finally potassium sulphate at 1% (W/V). The non-ionic surfactant Top film at 0.05% (V/V) was added to all treatments. The results proved that calcium borate at 200 ppm treatment was more effective on reducing cracking and sun scald of pomegranate fruits. In addition, the results revealed that the formulation containing ProTone plus potassium sulphate and glycerol had a consistent effect on increasing anthocyanin content in the peel, when compared with the control or with ProTone alone. Moreover, anthocyanin content of the arils was significantly increased by application ProTone along with glycerol or ProTone plus potassium sulphate and glycerol in both seasons. Meanwhile, electrolyte leakage of the aril was similar for most applications. There was also a significant increase in total sugars by various ProTone-containing formulations relative to the control in the juice. Thus, this study recommended applying ProTone in a formulation containing potassium sulphate and glycerol in order to enhance coloration and quality of "Wonderful" pomegranates in a consistent manner under field conditions.
Pedestrian Action Anticipation using Contextual Feature Fusion in Stacked RNNs

One of the major challenges for autonomous vehicles in urban environments is to understand and predict other road users' actions, in particular, pedestrians at the point of crossing. The common approach to solving this problem is to use the motion history of the agents to predict their future trajectories. However, pedestrians exhibit highly variable actions most of which cannot be understood without visual observation of the pedestrians themselves and their surroundings. To this end, we propose a solution for the problem of pedestrian action anticipation at the point of crossing. Our approach uses a novel stacked RNN architecture in which information collected from various sources, both scene dynamics and visual features, is gradually fused into the network at different levels of processing. We show, via extensive empirical evaluations, that the proposed algorithm achieves a higher prediction accuracy compared to alternative recurrent network architectures. We conduct experiments to investigate the impact of the length of observation, time to event and types of features on the performance of the proposed method. Finally, we demonstrate how different data fusion strategies impact prediction accuracy.
Evolution of Turbulence Through Terrestrial Bow Shock and its Changes in the Foreshock

We investigate the evolution of solar wind turbulence in the terrestrial foreshock and magnetosheath with a focus on the foreshock region. We analyzed plasma measurements by BMSW instrument on board Spektr-R satellite that has a unique 31 ms time resolution of the ion flux, ion density, solar wind and thermal speeds. We have found that the spectral power within the fluctuations on all spatial scales increases when we compare the foreshock with solar wind power spectra. In the MHD region, the increase of the foreshock density fluctuations compared to those in the solar wind is more prominent, roughly tenfold, whereas in the kinetic region, the increase is in the order of units. In the MHD region, the slopes of the power spectra change dramatically, while in the kinetic region, they remain the same.
The Design of Bilateral Routing Algorithm given the Utility Parameter from the Road User View

In this study, a new approach in the design of routing algorithm to start from the origin and destination and its situation is designed. In this algorithm utility parameter from the road user view that the path as possible is short and straight is considered. One of the outputs of this algorithm is provide the balance curve of path costs. using the balance curve of path costs will be design based on the available budget and available funds, the optimal path.
The Role of E-Intermediaries in Local Retail Hyperlink Networks : A Hyperlink Network Analysis

Local Owner Operated Retail Outlets (LOOROs) are threatened by the digitalization pressure from offline and online competitors on the one hand and by changing shopping habits of customers on the other. The involvement of e-intermediaries like e-marketplaces could help LOOROs to regain competitive power – not only in terms of additional online sales channels, but also with regard to professional online behavior and e.g. online visibility in terms of SEO. However, little is known about LOOROs online networking patterns, linkbuilding strategies and the specific role of e-intermediaries in this matter. To investigate the raised questions, this study analyzes hyperlink networks of local retailers in three German cities. We explored 14.780 websites and identified 12 categories of important stakeholders for local retail hyperlink networks. Our results reveal that LOOROs neglect the opportunities of local online cooperation. E-Intermediaries act as link hubs for local retailers, but local retailers follow passive link-building strategies and hesitate to link to e-
LAGGED MULTI-OBJECTIVE JUMPING PARTICLE SWARM OPTIMIZATION FOR WIRELESS SENSOR NETWORK DEPLOYMENT

Studies pertaining to wireless sensor network deployment (WSND) have escalated in recent years due to its exceptional function in planning configurations for sensor networks in order to attain maximum coverage and lifetime in a cost-effective manner. Although the approach of meta-heuristic searching optimization has been commonly applied, it has failed in addressing several issues related to multiple objectives and intricate optimization surface. As such, this work developed a novel multi-objective optimization (MOO) called the lagged multi-objective jumping particle swarm optimization (LMOJPSO) in order to overcome the drawbacks of WSND. It aims at finding the best locations and configuration of sensors in 2D environment in order to prolong the life time of the network with obtaining the best coverage and other performance measures. Three types of Pareto front, which were global, iteration (including lag), and local, had been incorporated for optimization search. Upon application to WSND, the proposed algorithm appears to ascertain network coverage and connectivity. When the outcomes of LMOJPSO were compared with the state-of-the-art NSGA-II method, the proposed algorithm seemed to display superior outputs for (MOO). Keyword: Multi-Objective, WSND, NSGA-II, Coverage, Connectivity, LMOJPSO, Optimization
Assessment of Genetic Variability on Some Orange Accessions Using RAPD-DNA Markers

Seven local orange accessions; Acidless orange (succary), Valencia (summer orange), Common orange (Balady) , Navel orange (Abusoura) and three unknown orange trees (No.1, 2 & 3) were collected from one private farm in kawesna (Monofeia government). They were used for studying fruit characters (physical and chemical) and RAPD-DNA genetic analysis experiments. The unknown orange trees No.3 had higher values of five physical fruit characters; Fruit weight, Fruit volume , Peel weight, Fruit length and Fruit diameter. Also, it had three higher values of chemical fruit characters; ascorbic acid, TSS/acid ratio and Titratable acidity TSS/acid ratio. The specify of the RAPD-PCR was highlighted by distinguishing DNA fingerprints for unknown orange tree No (3). It had one group (cluster A) and the entire rest orange accessions had other group (cluster B) with genetic unsimilarity of approximately 100% between them. In conclusion, the RAPD data supported the results from fruit characters (physical and chemical), the Unknown orange tree No 3 may be consider new variety. It has some economic fruit characters (physical and chemical)
Title Time series classification with Echo Memory Networks

Echo state networks (ESNs) are randomly connected recurrent neural networks (RNNs) that can be used as a temporal kernel for modeling time series data, and have been successfully applied on time series prediction tasks. Recently, ESNs have been applied to time series classification (TSC) tasks. However, previous ESN-based classifiers involve either training the model by predicting the next item of a sequence, or predicting the class label at each time step. The former is essentially a predictive model adapted from time series prediction work, rather than a model designed specifically for the classification task. The latter approach only considers local patterns at each time step and then averages over the classifications. Hence, rather than selecting the most discriminating sections of the time series, this approach will incorporate non-discriminative information into the classification, reducing accuracy. In this paper, we propose a novel end-to-end framework called the Echo Memory Network (EMN) in which the time series dynamics and multi-scale discriminative features are efficiently learned from an unrolled echo memory using multi-scale convolution and max-over-time pooling. First, the time series data are projected into the high dimensional nonlinear space of the reservoir and the echo states are collected into the echo memory matrix, followed by a single multi-scale convolutional layer to extract multi-scale features from the echo memory matrix. Max-over-time pooling is used to maintain temporal invariance and select the most important local patterns. Finally, a fully-connected hidden layer feeds into a softmax layer for classification. This architecture is applied to both time series classification and human action recognition datasets. For the human action recognition datasets, we divide the action data into five different components of the human body, and propose two spatial information fusion strategies to integrate the spatial information over them. With one training-free recurrent layer and only one layer of convolution, the EMN is a very efficient end-to-end model, and ranks first in overall classification ability on 55 TSC benchmark datasets and four 3D skeleton-based human action recognition tasks. © 2019 Elsevier Ltd. All rights reserved.
The French Corporate Venture Network and Business Survival : Is there any relation ?

The goal of this paper is to investigate the relati onship between the survival of the venture and the corporations’ network position in t he French corporate venturing network. Using network analysis, we find that big c orporations are the central actor in these networks. The findings highlight a negativ e relation between centrality metrics and the failure rate (which measures the pr oportion of failed investments). Having many ties can compromise the attention of la rge corporations on the focal young company. The results suggest that when establ ished companies finance many young companies, they may become too busy to partic ipa e effectively to innovative projects.
Design and Construction of Computer Experiments in Fluid Mechanics and Ship Stability

The paper considers a generalized functional and algorithmic construction of direct computational experiments in fluid dynamics. Tensor mathematics naturally embedded in the finiteoperation in the construction of numerical schemes. As an elementary computing object large fluid particle which has a finite size, its own weight, internal displacement and deformation is considered. The proposed approach focuses on the use of explicit numerical schemes. The numerical solution of the problem is divided into several stages that are a combination of Lagrange and Euler methods.
An Introduction to the Kondo Effect

The following paper discusses the resistance minima found at low temperatures in metals doped with magnetic impurities, known today as the Kondo effect[1]. It provides a brief introduction to the history and main principles behind the effect, touches on the theory that gave this effect the Kondo name, presents two experimental examples of the Kondo effect, and succinctly reviews its relevance in the physics world today. Any fault, flaws, or logical fallacies are solely attributable to the authors of this paper (and please do let us know if you find any! ).