Miracle-dz/UniFAR-FTUs huggingface dataset:
Poverty and prosperity among Britain’s ethnic minorities

Recent research provides evidence of continuing economic disadvantage among minority groups. But the wide variation between specific groups contradicts the notion that being a member of a minority group is, in itself, associated with financial hardship. This article summarises some of the quantitative evidence about ethnic minority incomes. Chinese and Indian households are characterised by a wide range of inequality within each group, with many prosperous families as well as some poor ones. Caribbean and African households are often poorer than white households, but Pakistanis and Bangladeshis are easily the poorest groups in Britain, and depend very heavily on means-tested benefits.
MWI-Sum: A Multilingual Summarizer Based on Frequent Weighted Itemsets

Multidocument summarization addresses the selection of a compact subset of highly informative sentences, i.e., the summary, from a collection of textual documents. To perform sentence selection, two parallel strategies have been proposed: (a) apply general-purpose techniques relying on data mining or information retrieval techniques, and/or (b) perform advanced linguistic analysis relying on semantics-based models (e.g., ontologies) to capture the actual sentence meaning. Since there is an increasing need for processing documents written in different languages, the attention of the research community has recently focused on summarizers based on strategy (a). This article presents a novel multilingual summarizer, namely MWI-Sum (Multilingual Weighted Itemset-based Summarizer), that exploits an itemset-based model to summarize collections of documents ranging over the same topic. Unlike previous approaches, it extracts frequent weighted itemsets tailored to the analyzed collection and uses them to drive the sentence selection process. Weighted itemsets represent correlations among multiple highly relevant terms that are neglected by previous approaches. The proposed approach makes minimal use of language-dependent analyses. Thus, it is easily applicable to document collections written in different languages. Experiments performed on benchmark and real-life collections, English-written and not, demonstrate that the proposed approach performs better than state-of-the-art multilingual document summarizers.
Performance Evaluation of Different Neural Networks Used for Seizure Detection

Brain is one of the most important and complicated organs of humans. It is also susceptible to degenerative disorder, such as epilepsy. A disease caused due to temporary alternation in brain function due to abnormal electrical activity of a group of brain cells and is termed as epileptic seizure. It is a common chronic neurological disorder characterized by seizures. In epilepsy, the normal pattern of neuronal activity becomes disturbed, causing strange sensations, emotions, and behavior or sometimes convulsions, muscle spasms, and loss of consciousness. The term ‘Epilepsy’ is derived from the Greek word epilambanein or epilepsía which means ‘to seize or attack’. Anything that disturbs the normal pattern of brain cells (neuron) activity from illness to brain damage to abnormal brain development can lead to seizures. Epilepsy may develop because of an abnormality in brain wiring, an imbalance of nerve signaling chemicals called neurotransmitters, or some combination of these factors. Having a seizure does not necessarily mean that a person has epilepsy. Only when a person has two or more seizures is he or she considered to have epilepsy. The seizure occurs at random to impair the normal function of the brain. Seizures can be classified into two main categories depending on the extent of involvement of various brain regions focal (or partial) and generalized. Generalized seizures involve from a circumscribed region of the brain, often called epileptic foci. EEGs and brain scans are most common and cost effective diagnostic test for epilepsy. Worldwide, epilepsy affects 50 million people. In this paper different neural networks are studied and compared, for the detection of seizure. Keywords— Support Vector machine (SVM), Elman network (EN), probabilistic Neural Network (PNN), Generalized Feed Forward (GFFNN), Back Propagation Neural Network (BPNN) and Multilayer perceptron (MLP).
Public-private settlement and hospital mortality per sources of payment

ABSTRACT OBJECTIVE To analyze if the adjusted hospital mortality varies according to source of payment of hospital admissions, legal nature, and financing settlement of hospitals. METHODS Cros-ssectional study with information source in administrative databases. Specific hospital admission reasons were selected considering the volume of hospital admissions and the list of quality indicators proposed by the North-American Agency for Healthcare Research and Quality (AHRQ). Were analyzed 852,864 hospital admissions of adults, occurred in 789 hospitals between 2008 and 2010, in Sao Paulo and Rio Grande do Sul, applying multilevel logistic regression. RESULTS At hospital admission level, showed higher chances of death male patients in more advanced age groups, with comorbidity, who used intensive care unit, and had the Brazilian Unified Health System as source of payment. At the level of hospitals, in those located in the mean of the distribution, the adjusted probability of death in hospital admissions financed by plan or private was 5.0%, against 9.0% when reimbursed by the Brazilian Unified Health System. This probability increased in hospital admissions financed by the Brazilian Unified Health System in hospitals to two standard deviations above the mean, reaching 29.0%. CONCLUSIONS In addition to structural characteristics of the hospitals and the profile of the patients, interventions aimed at improving care should also consider the coverage of the population by health plans, the network shared between beneficiaries of plans and users of the Brazilian Unified Health System, the standard of care to the various sources of payment by hospitals and, most importantly, how these factors influence the clinical performance.
A Sub-constant Error-probability Pcp Characterization of Np Part I: the Main Proof

This paper establishes a new characterization of NP in terms of PCP, being the rst such exact characterization to exhibit a sub-constant error-probability with constant number of accesses. Speciically, our theorems state the following: For any < 1=4, membership in any NP language can be veriied with a constant number of accesses, each reading O(log n) bits, and such that the error-probability is at most exponentially small in the number of bits read, i.e., 2 ? log n. For any < 1, membership in any NP language can be veriied with a constant number of accesses, each reading log n log log c n bits (for some xed constant c), and such that the error-probability is at most 2 ? log n. This new characterization of NP, almost immediately implies approximating set-cover to within logarithmic factors to be NP-hard. The main technical lemma utilized for that purpose presents a new consistency-test, implying a new low-degree-test, which is the rst to exhibit sub-constant error-probability with constant number of accesses. Part II of this work describes that consistency-test.
A method for physically based model analysis of conjunctive use in response to potential climate changes

Potential climate change effects on aspects of conjunctive management of water resources can be evaluated by linking climate models with fully integrated groundwater–surface water models. The objective of this study is to develop a modeling system that links global climate models with regional hydrologic models, using the California Central Valley as a case study. The new method is a supply and demand modeling framework that can be used to simulate and analyze potential climate change and conjunctive use. Supply‐constrained and demand‐driven linkages in the water system in the Central Valley are represented with the linked climate models, precipitation‐runoff models, agricultural and native vegetation water use, and hydrologic flow models to demonstrate the feasibility of this method. Simulated precipitation and temperature were used from the GFDL‐A2 climate change scenario through the 21st century to drive a regional water balance mountain hydrologic watershed model (MHWM) for the surrounding watersheds in combination with a regional integrated hydrologic model of the Central Valley (CVHM). Application of this method demonstrates the potential transition from predominantly surface water to groundwater supply for agriculture with secondary effects that may limit this transition of conjunctive use. The particular scenario considered includes intermittent climatic droughts in the first half of the 21st century followed by severe persistent droughts in the second half of the 21st century. These climatic droughts do not yield a valley‐wide operational drought but do cause reduced surface water deliveries and increased groundwater abstractions that may cause additional land subsidence, reduced water for riparian habitat, or changes in flows at the Sacramento–San Joaquin River Delta. The method developed here can be used to explore conjunctive use adaptation options and hydrologic risk assessments in regional hydrologic systems throughout the world.
Equivalence, query-reachability and satisfiability in Datalog extensions

We consider the problems of equivalence, satisfiability and query-reachability for datalog programs with negation and dense-order constraints. These problems are important for optimizing datalog programs. We show that both query-reachability and satisfiability are decidable for programs with stratified negation provided that negation is applied only to EDB predicates or that all EDB predicates are unary. In the latter case, we show that equivalence is also decidable. The algorithms we present are also used to push constraints from a given query to the EDB predicates. Finally, we show that satisfiability is undecidable for datalog programs with unary IDB predicates, stratified negation and the interpreted predicate ≠
Bilingual Corpora Segmentation Using Bilingual Recursive Alignments

A bilingual recursive alignment is a set of nested phrase-based alignments. This set is represented through a binary tree where the inner nodes can model a direct or an inverse translation. In this work, we compute recursive alignments using a greedy algorithm based on a statistical translation dictionary. Different bilingual segmentations can be obtained from a bilingual recursive alignment of a pair of sentences, depending on the degree of granularity to be achieved. Bilingual segmentation results are reported for a Spanish-English task and a Spanish-Basque task.
View indexing in relational databases

The design and maintenance of a useful database system require efficient optimization of the logical access paths which demonstrate repetitive usage patterns. Views (classes of queries given by a query model) are an appropriate intermediate logical representation for database. Frequently accessed views of databases need to be supported by indexing to enhance retrieval. This paper investigates the problem of selecting an optimal index set of views and describes an efficient algorithm for this selection.
Duet: exploring joint interactions on a smart phone and a smart watch

The emergence of smart devices (e.g., smart watches and smart eyewear) is redefining mobile interaction from the solo performance of a smart phone, to a symphony of multiple devices. In this paper, we present Duet -- an interactive system that explores a design space of interactions between a smart phone and a smart watch. Based on the devices' spatial configurations, Duet coordinates their motion and touch input, and extends their visual and tactile output to one another. This transforms the watch into an active element that enhances a wide range of phone-based interactive tasks, and enables a new class of multi-device gestures and sensing techniques. A technical evaluation shows the accuracy of these gestures and sensing techniques, and a subjective study on Duet provides insights, observations, and guidance for future work.
Age and the Trying Out of New Ideas

The aging of the scientific workforce and graying of grant recipients are central concerns in science policy. These trends are potentially important because older scientists are often seen as less open to new ideas than younger scientists. Here we put this hypothesis to an empirical test. A text analysis of 20 million biomedical research articles shows that papers published by younger researchers are more likely to build on new ideas. Collaboration with an experienced researcher also matters. Papers with a young first author and a more experienced last author are more likely to try out newer ideas than papers published by other team configurations. Our results buttress the case for funding young researchers but also provide a caution against unconditional idolatry of youth over experience.
Arbuscular Mycorrhizal Fungi Alleviate the Negative Effects of Iron Oxide Nanoparticles on Bacterial Community in Rhizospheric Soils

As a crucial reciprocal partner, arbuscular mycorrhizal fungi (AMF) can alleviate the negative effects of a variety of pollutants on their hosts and soil microbes. In our previous studies, such characteristics of AMF on plant growth were documented in response to metal engineered nanoparticle (ENP) treatments. However, the role of AMF in influencing ENP effects on soil microbes is still under debate. To address this, we investigated the responses of soil microorganisms to iron oxide nanoparticles (FeONPs) along a concentration gradient (0.1, 1.0 and 10.0 mg kg-1) in maize plants inoculated with or without AMF. The results showed that a high concentration of FeONPs significantly decreased the soil bacterial abundance and shifted the community composition, and these negative responses were associated with decreased DOC contents. However, in the presence of AMF, no significant changes in soil biota and DOC contents were observed under FeONPs treatment. These results indicate that AMF alter the effects of FeONPs on soil microorganisms, possibly by influencing plant growth and organic matter released from plant roots, as DOC contents were impacted by AMF. Our findings suggest that AMF can influence FeONP-plant-microbe interactions; therefore, more attention should be focused on plant-associated microbes when evaluating the biological effects of nanoparticles.
Learning-based aspect identification in customer review products

Aspect extraction is an important step in opinion mining to identify aspect in customer review products. Most existing works defines the pattern set manually or using heuristic approach. In this paper, we propose learning-based approach using decision tree and rule learning to generate pattern set based on sequence labelling. The patterns will be used to identify and extract aspect in customer product review combined with opinion lexicon. We use ID3, J48, RandomTree, Part and Prism to generate pattern that identifies aspect, based on sequence labelling. Our experiment results based on some generated pattern using Decision Tree and Rule Learning, show that the generated pattern can produced better performance than baseline model. However, there is significant increase in the number of patterns generated from learning-based aspect extraction compared with previous pattern.
3D Spheroid Culture Enhances the Expression of Antifibrotic Factors in Human Adipose-Derived MSCs and Improves Their Therapeutic Effects on Hepatic Fibrosis

Three-dimensional (3D) cell culture has been reported to increase the therapeutic potentials of mesenchymal stem cells (MSCs). However, the action mechanisms of 3D MSCs vary greatly and are far from being thoroughly investigated. In this study, we aimed to investigate the therapeutic effects of 3D spheroids of human adipose-derived MSCs for hepatic fibrosis. Our results showed that 3D culture enhanced the expression of antifibrotic factors by MSCs, including insulin growth factor 1 (IGF-1), interleukin-6 (IL-6), and hepatocyte growth factor (HGF). In vitro studies indicated conditioned medium of 3D cultured MSCs protected hepatocytes from cell injury and apoptosis more effectively compared with 2D cultured cells. More importantly, when transplanted into model mice with hepatic fibrosis, 3D spheroids of MSCs were more beneficial in ameliorating hepatic fibrosis and improving liver function than 2D cultured cells. Therefore, the 3D culture strategy improved the therapeutic effects of MSCs and might be promising for treatment of hepatic fibrosis.
The Estimation Of Intercensal Migration From Birth-Residence Statistics: A Study Of Data For The United States, 1950 And 1960

One of the principal objections to the use of census survival ratios for estimating net migration is the error that must arise from geographic variations in enumeration error and in mortality rates around the national averages. The possibility of reducing this type of error emerged with the tabulation, in two successive censuses, of birth-residence statistics for the native population of the United States by age, sex and color. By treating each group of persons having a common area of birth as a closed population, one can derive census survival ratios for the decade 1950-1960 that are specific for area of birth as well as for age, sex and color. Disciplines Demography, Population, and Ecology | Sociology Comments PSC Analytical and Technical Reports Number 7 This technical report is available at ScholarlyCommons: http://repository.upenn. edu/psc_penn_papers/3 THE EST:IMATION OF.INTERCENSALMIGRATION FRpM BIRTH-RESIDENCE STATISTICS: ••. ' . •. •••••. •. •. _: . :'. c. c· . •. •. _. _ . _. -. , A S.rUDYOF ]). t\TAFOR THE UNITED STATES, 1950 AND 1960 ~~. -~~ . "~ -~ by Hope T. Eldridge and Yun Kim GEOGRAPHIC DIVISIONS OF CONTERMINOUS UNITED STATES Adapted from U.S. Bureau of the Census, U.S. Census of Population: 1960, Volume l, Part l, Figure 2. 1
Rate-dependent Thermo-mechanical Modelling of Superelastic Shape-memory Alloys for Seismic Applications

Experimental tests performed on superelastic shape-memory alloys (SMAs) show a significant dependence of the stress—strain relationship on the loading—unloading rate, coupled with a not negligible oscillation of the material temperature. This feature is of particular importance in view of the use of such materials in earthquake engineering, where the loading rate affects the structural response. Motivated by this observation and by the limited number of available works on the modelling of SMAs for seismic applications, the present article addresses a uniaxial constitutive model for representing the system rate-dependent thermo-mechanical behavior of superelastic SMAs. The model is based on a single internal scalar variable, the martensite fraction, for which different rate-independent evolutionary equations in rate form are proposed. Moreover, it takes into account the different elastic properties between austenite and martensite. The whole model is then thermo-mechanically coupled with a thermal balance equation. Hence, it considers mechanical dissipation as well as latent heat and includes temperature as a primary independent variable, which is responsible for the dynamic effects. The article also provides a description for the integration, in time, of the constitutive equation and presents the solution algorithm of the corresponding time-discrete problem. Finally, results from numerical analyses are reported and the ability of the model to simulate experimental data obtained from uniaxial tests performed on superelastic SMA wires and bars at frequency levels of excitation typical of earthquake engineering is assessed.
Clustering algorithms for face recognition based on client-server architecture

Mobile devices like smartphones and tablets have become an integral part of our everyday life. These devices often store private information, which needs to be protected. To preserve this data we mainly use passwords, codes or SMS confirmation. They are easy to use, however there is always a risk of forgetting the password and also the risk of an impostor. On the other hand, there are other methods to identify a person, which overcome these threats. Biometric methods use the person itself to verify its identity. Many mobile devices like smartphones or tablets already have an implementation of biometric systems, but their usage often caused problems like shorter battery life, because of their computational complexity. Here a client-server architecture can be used, where the recognition process is divided into computational part running on the server and the acquisitional part running on the mobile device. In this paper a client-server face recognition system is presented with several clustering algorithms like k-means, self-organizing map etc. used for automatic training sample selection. The paper provides a comparative study of these algorithms and their impact on the implemented systems success rate.
An Improvement Video Search Method for VP-Tree by using a Trigonometric Inequality

This paper presents an approach for improving the use of VP-tree in video indexing and searching. A vantage-point tree or VP-tree is one of the metric space-based indexing methods used in multimedia database searches and data retrieval. Instead of relying on the Euclidean distance as a measure of search space, the proposed approach focuses on the trigonometric inequality for compressing the search range, which thus, improves the search performance. A test result of using 10,000 video files shows that this method reduced the search time by 5-12%, as compared to the existing method that uses the AESA algorithm
Black is not beautiful: Persistent messages and the globalization of “white” beauty in African women’s magazines

ABSTRACT This study examines the representation of African women in an era of globalization. Using Dyer’s concept of whiteness and a visual content analysis approach, this study focuses on how four influential African magazines portrayed African women from 2010 to 2015. Findings suggest that African magazines’ portrayal of beauty is not representative of diverse body sizes, skin tones, and hair types common among African women. Rather, magazines represent an image of beauty rooted in white/western/Eurocentric beauty standards.
AOP4CSM: An Aspect-Oriented Programming Approach for Cloud Service Monitoring

Monitoring is important for managing a Cloud computing environment. This task should be performed without modifying the implementation of the offered Cloud services. In this paper, a monitoring approach that neither modifies the server implementation nor the client implementation is presented. The proposed approach, called AOP4CSM, is based on aspect-oriented programming and monitors quality-of-service parameters of the Software-as-a-Service layer. The use of AOP4CSM is exemplified in the context of fault tolerance. Experimental results show the efficiency of AOP4CSM (very low overhead) and its advantages when applied to provide fault tolerance (good recovery decision).
Radiolabelling of Antigen and Liposomes for Vaccine Biodistribution Studies

A relatively simple and effective method to follow the movement of pharmaceutical preparations such as vaccines in biodistribution studies is to radiolabel the components. Whilst single radiolabelling is common practice, in vaccine systems containing adjuvants the ability to follow both the adjuvant and the antigen is favourable. To this end, we have devised a dual-radiolabelling method whereby the adjuvant (liposomes) is labelled with 3H and the antigen (a subunit protein) with 125I. This model is stable and reproducible; we have shown release of the radiolabels to be negligible over periods of up to 1 week in foetal calf serum at 37 °C. In this paper we describe the techniques which enable the radiolabelling of various components, assessing stability and processing of samples which all for their application in biodistribution studies. Furthermore we provide examples derived from our studies using this model in tuberculosis vaccine biodistribution studies.