Miracle-dz/UniFAR-FTUs huggingface dataset:
Interference Management Techniques in Small Cells Overlaid Heterogeneous Cellular Networks

Now-a-days because of the rapid increase in mobile users mobile data has also raised. Due to the heavy demand of data rates for advanced applications service providers are forced to adopt different technological advancements in conventional networks. Looking toward this context heterogeneous networks (HetNets) play a vital role in future 5G wireless cellular network deployment. In Heterogeneous Cellular Networks (HCNs) low power small cells are overlaid with the existing macro-only cell which increases the complexity of the network. Some of the emerging network technologies for this cellular evolution are the Femtocell, Picocell and Metrocell networks. Due to the deployment of these small cells in HCNs there are wide varieties of network structures and different transmitting powers which lead to interference in the cellular network. In addition to this, due to the spatiotemporal distribution of the mobile users and their mobility, hotspots also lead to increase of the possibilities of interference generation in wireless cellular network systems. The major technical issues associated with the mass deployment of smaller cells are related to the interference management between smallcells i.e. Femtocells and other serving cells in the same spectrum. Since Femtocells and Macrocells share the same frequency bands, it is necessary to develop efﬁcient interference management techniques to increase the capacity and throughput of HCNs. So in order to meet the user demands in an efﬁcient way
Forecasting Recessions Using Financial Variables Euroindicators working papers

In this paper, we focus on the ability of two financial variables – the yield curve spread and the EUR/USD exchange rate – to predict French recessions over the period 1979-2009. First, we propose a turning point chronology for the French business cycle based on a classical conception of economic cycles and a nonparametric dating algorithm applied to the real GDP series. Second, static and dynamic probit models are developed and estimated to produce the recession probabilities. In-sample results reveal both a strong predictive content of the two financial variables and the superiority of the dynamic specification in forecasting whether or not the French economy will be in recession. Out-of-sample results finally show the performance of the dynamic model in predicting the latest recession occurred in 2008.
Nickel – Toxicity and Immunization of Oral Environment in Orthodontic Patients

Plumbism and cadmium poisoning are a combination of a symptom complex responsible for metal-intoxications. The express of allergy during treatment with fixed appliances usually results from nickel influence. symptoms of nickel allergy, visible on oral mucosa, follow nickel-release during orthodontic treatment. Furthermore, additional factors, such as diet, nicotine, and individual sensibility may intensively promote contribution of heavy metals in the etiology of serious illness. Cadmium and lead intoxication symptoms are widely discussed in the literature. Cadmium and lead also influence the prevalence of caries and periodontal diseases. The aim of the study was to present the literature review concerning either oral environment (accumulated cadmium and lead reservoirs influencing health status of oral cavity) or expression of hypersensivity to nickel as the factors potentially endangering orthodontic patients treated with fixed appliances. Heavy metals such as cadmium, lead and nickel take part in chemical reactions simultaneously damaging functions of the organism. subsequently, designation of accumulation of cadmium and lead in the oral cavity as well as observation symptoms of hypersensitivity to nickel may play a significant role in marking the level of environment contamination by heavy metals. Although individuals particularly endangered are those working with alloys and battery production, permanently increasing interest towards treatment of malocclusion makes orthodontic patients jeopardized as well, especially these surrounded by environment polluted with either lead or cadmium (Dent. Med. Probl. 2010, 47, 4, 465–471).
The MLLP-UPV Spanish-Portuguese and Portuguese-Spanish Machine Translation Systems for WMT19 Similar Language Translation Task

This paper describes the participation of the MLLP research group of the Universitat Politècnica de València in the WMT 2019 Similar Language Translation Shared Task. We have submitted systems for the Portuguese ↔ Spanish language pair, in both directions. We have submitted systems based on the Transformer architecture as well as an in development novel architecture which we have called 2D alternating RNN. We have carried out domain adaptation through fine-tuning.
Generalization of Maximizing Deviation and TOPSIS Method for MADM in Simplified Neutrosophic Hesitant Fuzzy Environment

With the development of the social economy and enlarged volume of information, the application of multiple-attribute decision-making (MADM) has become increasingly complex, uncertain, and obscure. As a further generalization of hesitant fuzzy set (HFS), simplified neutrosophic hesitant fuzzy set (SNHFS) is an efficient tool to process the vague information and contains the ideas of a single-valued neutrosophic hesitant fuzzy set (SVNHFS) and an interval neutrosophic hesitant fuzzy set (INHFS). In this paper, we propose a decision-making approach based on the maximizing deviation method and TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) to solve the MADM problems, in which the attribute weight information is incomplete, and the decision information is expressed in simplified neutrosophic hesitant fuzzy elements. Firstly, we inaugurate an optimization model on the basis of maximizing deviation method, which is useful to determine the attribute weights. Secondly, using the idea of the TOPSIS, we determine the relative closeness coefficient of each alternative and based on which we rank the considered alternatives to select the optimal one(s). Finally, we use a numerical example to show the detailed implementation procedure and effectiveness of our method in solving MADM problems under simplified neutrosophic hesitant fuzzy environment.
Variational Bayesian Context-aware Representation for Grocery Recommendation

Grocery recommendation is an important recommendation use-case, which aims to predict which items a user might choose to buy in the future, based on their shopping history. However, existing methods only represent each user and item by single deterministic points in a low-dimensional continuous space. In addition, most of these methods are trained by maximizing the co-occurrence likelihood with a simple Skip-gram-based formulation, which limits the expressive ability of their embeddings and the resulting recommendation performance. In this paper, we propose the Variational Bayesian Context-Aware Representation (VBCAR) model for grocery recommendation, which is a novel variational Bayesian model that learns the user and item latent vectors by leveraging basket context information from past user-item interactions. We train our VBCAR model based on the Bayesian Skip-gram framework coupled with the amortized variational inference so that it can learn more expressive latent representations that integrate both the non-linearity and Bayesian behaviour. Experiments conducted on a large real-world grocery recommendation dataset show that our proposed VBCAR model can significantly outperform existing state-of-the-art grocery recommendation methods.
THE EFFECTS OF SECOND-LANGUAGE STUDY ON THE COGNITIVE FLEXIBILITY OF FRESHMAN UNIVERSITY STUDENTS

3. When a map, drawing or chart, etc., is part of the material being photo­ graphed the photographer has followed a definite method in “sectioning” the material. It is customary to begin filming at the upper left hand comer of a large sheet and to continue from left to right in equal sections with small overlaps. If necessary, sectioning is continued again—beginning below the first row and continuing on until complete.
MODELLING THE DISTRIBUTION OF PHOTOSYNTHETIC TYPES OF GRASSES IN SAHELIAN BURKINA FASO WITH HIGH-RESOLUTION SATELLITE DATA

We combined grass (Poaceae) occurrence data from the Sahelian parts of Burkina Faso, West Africa, with data on the photosynthetic type of these species. Occurrence data were compiled from relevés and collections of the Herbarium Senckenbergianum, and the assignment of photosynthetic types was taken from the literature and completed by leaf anatomical observations of our own. We used the occurrence data to model species distributions using GARP (Genetic algorithm of rule-set production) and high-resolution satellite data (Landsat ETM+) as environmental predictors. In a subsequent step we summarized the distributions of single species for each photosynthetic type. The resulting distribution patterns reflect the ecological preferences connected with photosynthetic pathways. The only C3 species is strictly bound to watercourses and temporary lakes, C4 MS species mainly occur on the dunes, C4 PS-PCK species are mainly from dunes and watercourses, C4 PS-NAD type species dominate the drier peneplains. Accepted 11 January 2011.
4 . 1 VALIDATIONS OF THE NCEP MSM COUPLED WITH THE NOAH LSM OVER THE HAWAIIAN ISLANDS

The primary operational models for the NWSFO-HNL (National Weather Service Forecast Office – Honolulu) are the Aviation (AVN) and the Medium Range Forecast (MRF) runs of the Global Spectral Model (GSM). These model runs are generally able to provide forecast guidance on the synoptic-scale systems that affect the Hawaiian Islands; they are however unable to resolve the mesoscale weather features associated with the local complex terrain due to their coarse resolution. Recently, the NCEP (National Centers for Environmental Predictions) developed the high resolution Regional Spectral Model (RSM) (Juang and Kanamitsu 1994). In a collaborative effort among the University of Hawaii, NCEP and NWSFO-HNL, the hydrostatic version of the RSM with a 10-km resolution was implemented in early 1997 into the operational run stream for the state of Hawaii by NCEP. From preliminary analyses (Wang et al. 1998) and feedback from local forecasters, it is apparent that the RSM forecasts show improvements over the AVN and MRF runs in simulating heavy rainfall and high wind events. Nevertheless, there are still large discrepancies between the RSM simulations and observations because (1) the 10-km RSM grid is inadequate to resolve the local complex terrain, and (2) localized convections, resulting from the effects of topography, are not well represented by a hydrostatic model. More recently, the nonhydrostatic version of the RSM (referred to as the Mesoscale Spectral Model; MSM) has been developed at NCEP (Juang 2000). In this model, both the hydrostatic perturbation in association with the external hydrostatic state and the nonhydrostatic perturbation related to the internally evolved hydrostatic state are introduced. The same model physics implemented in the RSM are used in the MSM without the hydrostatic assumption. It is shown in Juang (2000) that the MSM performs reasonably well in idealized and real case studies and is superior to the RSM with a coarse horizontal resolution of 50 km. ____________________________________________
1 A facile synthesis of ( PIM-polyimide )-2 ( 6 FDA-durene-polyimide ) copolymer as novel 3 polymer membranes for CO 2 separation 4

Random copolymers made of both (PIM-polyimide) and (6FDA-durene-PI) were 13 prepared for the first time by a facile one-step polycondensation reaction. By combining the highly 14 porous and contorted structure of PIM (polymers with intrinsic microporosity) and high 15 thermomechanical properties of PI (polyimide), the membranes obtained from these random 16 copolymers [(PIM-PI)x-(6FDA-durene-PI)y] showed high CO2 permeability (> 1047 Barrer) with 17 moderate CO2/N2 (> 16.5) and CO2/CH4 (> 18) selectivity, together with excellent thermal and 18 mechanical properties. The membranes prepared from three different compositions of two 19 comonomers (1:4, 1:6 and 1:10 of x:y), all showed similar morphological and physical properties, 20 and gas separation performance, indicating ease of synthesis and practicability for large-scale 21 production. The gas separation performance of these membranes at various pressure ranges 22 (100–1500 torr) was also investigated. 23
Handling multimodality and scarce resources in sign language machine translation

In the field of statistical machine translation, the translation of sign languages poses an interesting and challenging problem. Translating from a signed language into a spoken language is usually a two-step process. From the video of a person signing, an automatic sign language recognition system extracts the signs in some form. Since signed languages differ in grammar, vocabulary and expression from spoken languages even within the same country, the recognised sequence of signs has to be translated into a spoken language text. In sign languages, meaning is conveyed simultaneously not only via the two hands, but also by facial expressions, body posture, head movement, and eye gaze. Because of this complex and multimodal nature of sign languages, there is no common writing system, and the scientific question of an annotation scheme suitable for machine translation remains open. Another difficulty when applying statistical methods to sign language translation is the lack of a sufficient amount of training data. This data scarcity often leads to poor translation results. Moreover, the multimodal nature of sign language is not handled by current translation systems, which usually process sequences of words. In this thesis, we approach the above three problems: finding a suitable annotation scheme, dealing with small amounts of annotated data, and handling multimodality in the machine translation process. While we focus on the second step of translating the recognised signs into a spoken language text, we also aim at improving the overall process of recognition and translation by optimising the interface between the two systems. In the course of the EU-project SignSpeak, our research group implemented the whole pipeline of sign language recognition and translation, and we evaluated this pipeline with automatic measures and human evaluators. The annotation scheme of the RWTH-PHOENIX-Weather 2014, a sign language corpus which was created in the course of this thesis, contains not only information on the signs expressed by the hands, but also marks mouthings, locations in the signing space or simultaneous signing of two different signs with both hands. We analyse the importance of this additional information for machine translation and devise an improved way of including it in the process of translation. Since available sign language corpora are rather small when compared to spoken language corpora, the lack of sufficient training data often leads to a poor automatic alignment between the annotated signs and their translations in the spoken language. This issue is aggravated by the fact that sign languages, which are expressed by moving the hands in front of the body, have a morphology which is totally different from spoken languages, which are produced by sequences of sounds. We improve the automatic alignment by applying a morphosyntactic and a semantic analysis and bridging the differences to find corresponding signs and phrases.
MECHANISMS OF ACUPUNCTURE INTERVENTION IN RATS OF POST-STROKE DEPRESSION

Post-stroke depression (PSD) directly affects the rehabilitation of patients who have suffered stroke and increases the morbidity and mortality of stroke. This leaves patients, their families and society with a heavy burden. PSD has an incidence of 20% to 60% among stroke patients, and PSD is divided into mild and severe depression types. Mild depression manifests as sadness, sleep disorders, mental activity decline, inattention, introversion, and decreased interest. In addition to these symptoms, severe depression includes, anxiety, early awakening, weight loss, loss of appetite, slow thinking, delusion and fantasy, despair and suicidal thoughts. PSD with mild to moderate depression is more common than severe PSD). PSD pathogenesis is complex, involving biological mechanisms, Acta Medica Mediterranea, 2018, 34: 507
The Sparse + Low-Rank Trick for Matrix Factorization-Based Graph Algorithms

Matrix factorization is a central block in many graph algorithms for embedding, clustering and a number of other tasks. This block is usually the computational bottleneck of these algorithms and a naive implementation can prevent them from scaling to large datasets. However, the matrices to factorize often have a closedform "sparse + low-rank" structure. In this paper, we show how to adapt state-of-the-art matrix factorization techniques to this class of matrices. We demonstrate that the method is highly competitive with respect to a naive implementation and that it comes at a very small extra cost as compared to the decomposition of the sparse component alone.
A Review on Azelaic Acid Emulgel for Acne and Hyperpigmentation

Acne is a very common inflammatory skin disease also known as Pimples. Pimples are commonly found on face, chest, upper back and neck. Propionibacterium and Staphylococcus aureus (S. aureus) are responsible for acne they are mainly present in Sweat gland. Azelaic acid is anti-keratinizing, antibacterial and anti-inflammatory drug. Azelaic Acid is mainly act on cellular protein synthesis in both aerobic and anaerobic bacteria and it reducing the proliferation of Propionibacterium. Azelaic acid is used to treat acnes as well as Hyperpigmentation and it also reduce inflammation and redness. But Azelaic Acid is Hydrophobic drug low soluble and low permeable so The Aim of present study was to Enhance Permeability and Solubility of Azelaic Acid by Formulating Emulgel For effective treatment of Acne and Hyperpigmentation. Keyword: Acne, Hyperpigmentation, Hydrophobic drug, Azelaic Acid, Emulgel.
INTERVARIETAL VARIATION IN SALT TOLERANCE OF LENTIL ( LENS CULINARIS MEDIK . ) IN POT EXPERIMENTS

Seven lentil (Lens culinaris Medik.) varieties were grown in pots irrigated with NaCl solution of different concentrations (0, 100, 200 and 300 mM) to assess their salinity tolerance potentials. Data revealed that the highest and the lowest salt tolerance were shown by BARI masur-5 (168.50%) and BARI masur-2 (56.32%), respectively. Cluster analysis based on the salt tolerance indices also showed grouping of the varieties into 4 clusters where BARI masur-5 was found highly salt tolerant, BARI masur-6 was moderately salt tolerant and BARI masur-1 and BARI masur-2 were least tolerant. Although shoot height, fresh weight and water content decreased, root length and root to shoot ratio increased significantly with the increase of salt concentrations in the varieties tested. Introduction Soil salinity is one of the main factors that limit crop production in many parts of the world (Shannon 1986). It is estimated that 6% of the world’s land surface and 20% of irrigated land area of the world are affected by soil salinity (Chinnusamy et al. 2005). It is also reported that the area under salinity is increasing gradually posing threats to agriculture. However, the problem of salinity is more alarming in some countries where food production has to be increased in the limited land area (Ponnamieruma 1984, Yokoi et al. 2002). Given the scenarios of increasing trend of soil salinity worldwide, use of salt tolerant crops could be one of the suitable options to cope with the salinity problems because soil reclamation is expensive and not environment friendly (Kökten et al. 2010). Lentil (Lens culinaris Medik.) is an important crop in many countries including Bangladesh since it provides protein-rich food for humans and animals and acts as soil quality improver by supplying increased nutrients to soil (Thomson and Siddique 1997, Katerji et al. 2001). In Bangladesh, lentil is placed second position among the pulses according to cultivated area and production while first in terms of usage (Afzal et al. 1999). However, cultivation of lentil has been challenged in Bangladesh due to increasing trend of soil salinity (Sikder and Elias 1985, Ashraf and Waheed 1990). Although, several disease-resistant varieties of lentil have been developed and released in Bangladesh over the years, information about the salt tolerance of these varieties is not available (Ashraf and Waheed1990, Hossain et al. 2016). The main objective of the present study, therefore, was to identify salt tolerant lentil varieties released by the Bangladesh Agricultural Research Institute (BARI). Materials and Methods Seeds of seven lentil varieties (BARI masur-1, BARI masur-2, BARI masur-3, BARI masur4, BARI masur-5, BARI masur-6 and BARI masur-7) were collected from the courtesy of the Pulses Research Centre of BARI, *Author for correspondence: .
JFNWAT Web Report: A New Japanese FrameNet Web Application Tool

This paper introduces the JFNWAT Web Report, a web-based tool to display and query annotated data from the Japanese FrameNet database. It is part of the Japanese FrameNet Web Application Tool (JFNWAT), which ultimately aims to replace the existing JFN production and reporting tools. JFNWAT is designed to be language independent, meaning that the Web Report module could be used for nonJapanese FrameNet projects.
Differences in the Responses to Monetary Policy Shocks before and after the EU Membership : Evidence from the Czech Republic

Differences in the Responses to Monetary Policy Shocks before and after the EU Membership: Evidence from the Czech Republic Yongho Park Department of Economics The Graduate School Seoul National University The purpose of this thesis is to investigate differences in the effects before and after joining the European Union(EU) on economy to monetary policy shocks as a small open country. In this paper, the case of the Czech Republic is considered as the representative country. For comparison of the responses of macroeconomic variables for the data before and after the membership of the EU, whole data are divided by two based on the date when the Czech Republic became the member. By employing Structural Vector Autoregression(SVAR) model, this paper is trying to reveal the difference in the responses of major variables to monetary tightening shocks. As a result, significant exchange rate puzzles are found in the both. While the puzzles are robust in the results for pre-membership sample, those are not robust for the later sample. According to additional tests, the intervention of the ce ntral bank of the country in the foreign reserves market may cause the differences in the impacts of foreign reserves before and after the membership. Due to the dissimilarity, co-movement of impulse responses of NEER and FORE is only shown in the results for the earlier sample.