Miracle-dz/UniFAR-FTUs huggingface dataset:
Developmental Origins of Health Inequality

Building on early animal studies, 20th-century researchers increasingly explored the fact that early events—ranging from conception to childhood—affect a child’s health trajectory in the long-term. By the 21st century, a wide body of research had emerged, incorporating the original fetal origins hypothesis into the developmental origins of health and disease. Evidence from Organization for Economic Cooperation and Development (OECD) countries suggests that health inequalities are strongly correlated with many dimensions of socioeconomic status, such as educational attainment, and that they tend to increase with age and carry stark intergenerational implications. Different economic theories have been developed to rationalize this evidence, with an overarching comprehensive framework still lacking. Existing models widely rely on human capital theory, which has given rise to separate dynamic models of adult and child health capital within a production function framework. A large body of empirical evidence has also found support for the developmental origins of inequalities in health. On the one hand, studies exploiting quasi-random exposure to adverse events have shown long-term physical and mental health impacts of exposure to early shocks, including pandemics or maternal illness, famine, malnutrition, stress, vitamin deficiencies, maltreatment, pollution, and economic recessions. On the other hand, studies from the 20th century have shown that early interventions of various content and delivery formats improve life course health. Further, given that the most socioeconomically disadvantaged groups show the greatest gains, such measures can potentially reduce health inequalities. However, studies of long-term impacts as well as the mechanisms via which shocks or policies affect health, and the dynamic interaction among them, are still lacking. Mapping the complexities of those early event dynamics is an important avenue for future research.
A State Of The Art Survey On DVFS Techniques In Cloud Computing Environment

Distributed systems comprise miscellaneously heterogeneous computing resources such as high performance computing (HPC), grid computing and cloud computing in which these provision computing resources to their subscribers as a utility. Total cost of ownership (TCO) is the concept helping system owners to reconfigure their human and IT assets to reduce their costs rather that boosting their utilities tariff. Reduction of the vast volume electricity consumption as a big portion of operational expenditure (OPEX) in such large datacenters including hundred even thousands physical machines is first class concern both in economic and green goals viewpoint. Different methods have been done in literature to cope with power management such as virtual machine (VM) migration, server consolidation in virtualized datacenter environment, but aggressive VM migration and server consolidation executions deteriorate the situation in terms of power consumption and performance degradation. So, the dynamic voltage frequency scaling (DVFS) technique in infrastructure level can adjust server’s operational voltage and frequency based on current workload to lower down power wastage and untimely server consolidation schemes. This paper presents a state of the art survey study on DVFS technique to lower down not only on processor chip but also on other peripherals such as cash memory and hard disks. Then it classifies the presented methods based on our thematic taxonomy and metrics derived from literature. It pave the way for other researchers to improve the current schemes. Keywords-HPC, TCO, Cloud Computing, VM migration, Server Consolidation, DVFS
On the comparison of Hungarian and English in an International Computational Linguistics Project

The goal of this paper is to offer an overview of a recently launched computational linguistic project at the Department of English Linguistics at the University of Debrecen. The project aims at developing a syntactic and morphological analysis of the Hungarian language within the basic linguistic framework of Lexical-Functional Grammar (LFG), with special emphasis laid on a comparative English vs. Hungarian aspect. This initiative is a contribution to a large-scale LFG-based international computational linguistic collaboration: Parallel Grammars (PargGram), which is coordinated by Palo Alto Research Center (PARC) in California. In this paper, we discuss the most crucial features of LFG and the computational linguistic apparatus developed by ParGram (in a framework called XLE), and we illustrate them by the help of a sample analysis of some fundamental properties of English and Hungarian noun phrases. The structure of the paper is as follows. In Section 2, we briefly outline and illustrate the design principles of the LFG framework. In Section 3, we provide an overview of the history of the ParGram project, and introduce the key features of the XLE grammar writing apparatus. In Section 4, we discuss the history and the main objectives of the HungGram project, and demonstrate the capabilities of our system by an analysis of a special type of Hungarian noun phrases and their English counterparts. In Section 5, we round up with an outlook on problems and challenges in the domain of natural language processing that we aim to address in our project. Section 6 contains our concluding remarks.
Clustering Lines in High Dimensional Space : Classification of Incomplete Data

A set of k balls B1, . , Bk in a Euclidean space is said to cover a collection of lines if every line intersects some ball. We consider the k-center problem for lines in high dimensional space: Given a set of n lines L = {l1, . , ln} in R, find k balls of minimum radius which cover L. We present a 2-approximation algorithm for the cases k = 2, 3 of this problem, having running time quasi-linear in the number of lines and the dimension of the ambient space. Our result for 3-clustering is strongly based on a new result in discrete geometry which may be of independent interest: a Helly-type theorem for collections of axis-parallel “crosses” in the plane. The family of crosses does not have finite Helly number in the usual sense. Our Helly theorem is of a new type: it depends on ε-contracting the sets. In statistical practice, data is often incompletely specified; we consider lines as the most elementary case of incompletely specified data points. Clustering of data is a key primitive in nonparametric statistics. Our results provide a way of performing this primitive on incomplete data, as well as imputing the missing values.
Crustal Velocity Structure of the Western Part of the Narmada-Son Lineament-A Case Study using DSS Data

A five-layered crustal model with 5.9-6.2, 6.0, 6.3, 6.6 and 7.0 kms velocities is derived with seismic refraction / wide-angle reflection data along the Thuadara-Sendhwa-Sindad profile in central India. The profile traverses across the western part of the Narmada-Son lineament in the N-S direction. The data is subjected to 2-D forward modelling using both travel times and amplitudes. Refracted waves (P n ) from the Moho observed as first arrivals at a distance of about 200 km are used to derive the upper mantle velocity of 8.1 kms. The Moho is well constrained both from the P n and wide-angle reflections from four shot points. The main features of the velocity structure is the delineation of a low velocity layer (6.0 kms) in the upper crust and a 12-16 km thick high velocity (7.0 kms) layer at the base of the crust. The high velocity lower crustal layer, representing the magmatic under plating in the region, may be related to the formation of the Narmada basin and the Deccan volcanic episode. The Deccan Volcanism may be a consequence of Reunion mantle plume activity. The crustal thickness varies between 37 and 43 km along the profile and the thickest crust is found between the Narmada and Tapti rivers. Deep-seated faults responsible for the evolution of Narmada basin are inferred from the present study.
Early Breast Feeding , Healthy Baby . . . Factors Influencing the Breast Feeding in a Tertiary Care Hospital

Original Research Article Exclusive breastfeeding up to six months is considered to be beneficial for the health and wellbeing of infants and mothers. It is believed that breast-feeding is universally and traditionally practiced in India. The best gift a mother can give to infant is breastfeeding. This descriptive study was conducted at a tertiary hospital in Warangal, Telangana state, India. Every third trimester mothers admitted in the maternity ward with a minimum of three antenatal visits were included in the study. These 200 mothers were administered a pre-tested semi structured questionnaire on breastfeeding in the local language, Telugu, within 24 hours of giving birth, 3months and 6 months. The mean age of the mothers was 24.7 ±5.62 years. The age group less than 20 years consist of about 22%. About one third of mothers did not have any formal education (35%), and first-time mothers were (34%), one third of mothers did not have any formal education (35%), and first-time mothers were (34%) and 52% were from low socio-economic status. About 85% lived in nuclear families, 42% had normal delivery and 95% delivered in health institutions. Only 28.5 % newborns were breast fed within 1 hr of birth. 67.5% of newborns were put on breast milk in later hrs of the same day and 4% were fed after one day. Here 56% of newborns received prelacteal feed. Exclusive breast feeding up to six months were noticed in 24.5%, 52.5% up to 4 months, 33% up to 3 months respectively. Majority of mothers (46%) felt that milk is not sufficient enough to satisfy their child. About 7% mothers were found who has delivered twins, in which 4% exclusively breastfed onlyup to 4 month and other 3% breast-fed only up to 1 month. Total 34% mothers were found working out of which 11% mothers did exclusive breastfeeding up to 6 months. Most of mothers were not followed proper birth spacing. About 62% mothers were conceived within one year, in which 35% breast-fed up to 6 months. Breast feeding techniques were shown to 61% of mothers in hospitals and 34% of mothers was told about the benefit and management of breast feeding. The key to successful breastfeeding is Information, Education and Communication strategies aimed at behaviour change in Indian women.
Exploring the Impact of Node Cooperation Level on Routing in Cognitive Radio Networks

In this paper, we analyze the effect of different degrees of node cooperation on the performance of routing protocols for cognitive radio networks. We first present an analytical model of the routing performance in terms of expected end-to-end packet delivery ratio (PDR) for cognitive radio networks with uncooperative node behaviors. We also performed extensive simulations to evaluate the analytical model. The simulation results show that Optimal PrimaryAware Route Quality Protocol (OPERA) could provide better PDR performance under higher degrees of network cooperation and Shortest Path First routing protocol (SPF) works better under lower cooperation degrees. Finally, our results suggest that even a modest level of node cooperation is sufficient to achieve significant performance improvement with respect to the fully non-cooperative network in which all secondary users are selfish. Keywordsnode selfishness; cognitive radio; routing.
A Comparative Review of Data Modeling in UML and ORM

Since its adoption by Object Management Group (OMG) in 1997, the Unified Modeling Language (UML) has become the de facto standard language for object-oriented analysis and design. Several minor and major revisions have led to UML version 2.5, in beta form (OMG, 2012a) at the time of writing, and the language is still being refined. Although suitable for object-oriented code design, UML is less suitable for information analysis, since its graphical language for data modeling provides only weak support for the kinds of business rules found in data-intensive applications, and its textual Object Constraint Language (OCL) is arguably too technical for most business people to understand in spite of claims to the contrary (OMG, 2012b). Moreover, UML’s graphical language does not lend itself readily to verbalization and multiple instantiation for validating data models with domain experts. These problems can be remedied by using a factoriented approach for information analysis, where communication takes place in simple sentences, each sentence type is easily populated with multiple instances, and attributes are avoided in the base model. At design time, a fact-oriented model can be used to derive a UML class model or a logical database model. Object Role Modeling (ORM), the main exemplar of the fact-oriented approach, originated in Europe in the mid-1970s (Falkenberg, 1976), and has been extensively revised and extended since, resulting in (ORM 2) a second generation ORM (Halpin, 2005) along with tool support (e.g., Curland & Halpin, 2010). This article provides a concise comparison of the data modeling features within UML and ORM. The next section provides background on both approaches. The following section summarizes the main structural differences between the two approaches, and outlines some benefits of ORM’s fact-oriented approach. Simple examples are then used to illustrate the richness of ORM’s graphical constraint notation compared with UML’s class modeling notation. Future trends are then briefly outlined, and the conclusion motivates the use of both approaches in concert to provide a richer data modeling experience. Finally, references are provided for further reading, and key terms are listed along with their definitions.
Laboratory Phonology 7

This collection of recent papers in Laboratory Phonology approaches phonological theory from several different empirical directions. Psycholinguistic research into the perception and production of speech has produced results that challenge current conceptions about phonological structure. Field work studies provide fresh insights into the structure of phonological features, and the phonology-phonetics interface is investigated in phonetic research involving both segments and prosody, while the role of underspecification is put to the test in automatic speech recognition.
Growth of Textured CoFe 2 O 4 Thin Films on Platinized Silicon Prepared by a Sol-Gel Method

We fabricated textured polycrystalline CoFe2O4 thin films on Pt(111)/TiO2/SiO2/Si substrate through a sol-gel method. We varied the thickness of the films, by using precursor solutions with different concentrations of 0.1, 0.2, and 0.3 M, and by depositing 5, 8, or 10 layers on the substrate by spin-coating. X-ray diffraction spectra indicated that when the precursor concentration of the solution was higher than 0.1 M, the spin-coated films were preferentially oriented in the direction. Inspection of the surface morphology by scanning electron microscopy revealed that CoFe2O4 thin films prepared with 0.2 M solution and 5-time spin-coatings had smoother surface, as compared to the other conditions. Each coating had an average thickness of about 50 nm. The magnetic properties measured by vibrating sample magnetometer showed magnetic anisotropy, as evidenced from the difference in the in-plane and out-of-plane hysteresis loops, which we attributed to the textured orientation of the CoFe2O4 thin films.
Induced Seismicity Around Masjed Soleyman Dam , South West of Iran

During impounding of the Masjed Soleyman reservoir regards to national and international catalogues such as International Institute of Earthquake Engineering and Seismology (IIEES) and EHB catalog, an increasement in seismic rate have been observed in the dam region, and 90 days after completing the impounding, an earthquake with moment magnitude of Mw=5.6 was occurred in the close vicinity of Masjed Soleyman reservoir. We installed a local seismic network of 5 seismological stations in the area since June 2006 for 15 months. The largest recorded earthquakes during the monitoring of Masjed Soleyman reservoir have magnitudes of ML=3.9 and ML=3.6. Statistical methods such as study of water level changes with variation of regional seismicity, foreshocks and aftershocks pattern, and correlation between the fractal dimension and the b-value used to identifying induced earthquakes occurred in the dam region.
Analysis of 24-hour ambulatory blood pressure in prehypertensive subjects

AIM: To explore the characteristics of ambulatory blood pressure monitoring(ABPM) in prehypertensive subjects.METHODS: According to resting blood pressure levels,392 subjects were divided into three groups: normotensive group(n=82),prehypertensive group(n=183) and essential hypertensive group(n=127). A 24-h ABPM was performed in all patients.RESULTS: The 24-h BP variation coefficient of SBP(24-h SSD) in normotensive,prehypertensive and hypertensive subjects were,respectively,(14.0±2.1)%,(17.2±3.2)% and(20.5±4.6)%. The 24-h BP variation coefficient of DBP(24-h DSD) was(10.4±1.9)%,(13.1±1.9)% and(16.3±2.1)%,and the proportion of non-dipper blood pressure was 7%,25% and 39%. SBP load(SBP-L) was(35±20)% and DBP load was(33±20)%(P0.05,P0.01). The rate of decrease of SBP at night(SBPF) was 13% and the rate of decrease of DBP at night(DBPF) was 11%,lower than that of the normotensive group but higher than that of the hypertensive group(P0.01). CONCLUSION: The circadian pattern of BP significantly changed in the prehypertensive group.BP level,BP variability rate,BP load rate,and the proportion of non-dipper BP all increased,whereas SBPF and DBPF decreased.
Automatic Intrusion Detection System Using Deep Recurrent Neural Network Paradigm

Network security field had gained research community attention in the last decade due to its growing importance. This paper addresses directly one vital problem in that field is “Intrusion Detection System” (IDS). As much as many researchers tackle this problem, many challenges arise while converting this research to reliable automatic system. The biggest challenge is to make the system works with low false alarm with new unseen threats. In this paper, we address this challenge by building a descriptive model using different models of deep Recurrent Neural Network (RNNs). (RNN) models has the ability to generalize the knowledge that can be used to identify seen and unseen threats. This generalization comes from RNN capabilities to define in its terms the normal behavior and the deviation accepted to be normal. Four different models of RNN were tested on a benchmark dataset, NSL-KDD, which is a standard test dataset for network intrusion. The proposed system showed superiority over other previously developed systems according to the standard measurements: accuracy, recall, precision and f-measure.
Vision-based people detection using depth information for social robots

Robots are starting to be applied in areas which involve sharing space with humans. In particular, social robots and people will coexist closely because the former are intended to interact with the latter. In this context, it is crucial that robots are aware of the presence of people around them. Traditionally, people detection has been performed using a flow of two-dimensional images. However, in nature, animals’ sight perceives their surroundings using color and depth information. In this work, we present new people detectors that make use of the data provided by depth sensors and red-green-blue images to deal with the characteristics of human–robot interaction scenarios. These people detectors are based on previous works using two-dimensional images and existing people detectors from different areas. The disparity of the input and output data used by these types of algorithms usually complicates their integration into robot control architectures. We propose a common interface that can be used by any people detector, resulting in numerous advantages. Several people detectors using depth information and the common interface have been implemented and evaluated. The results show a great diversity among the different algorithms. Each one has a particular domain of use, which is reflected in the results. A clever combination of several algorithms appears as a promising solution to achieve a flexible, reliable people detector.
Fault Diagnosis Basing on the Information of the Interval Delays of Symptoms

The paper presents the formal conditions for fault isolability in the case of reasoning based on binary diagnostics matrix and the intervals of delays for each fault-symptom pair. It is shown that the higher fault isolability can be achieved while taking into account the knowledge about the symptoms delays. Finally, the new isolation algorithm utilising such knowledge is proposed. The presented approaches are illustrated with the example of fault isolability analysis for three tank system.
CROSS-FERTILISATION BETWEEN COMPUTER ARCHITECTURE AND OTHER COMPUTER SCIENCE FIELDS

The main aim of this paper is to prove that using new scientific tools in Computer Architecture research could be quite efficient and useful. We exemplified this idea during the paper, by analysing some innovative proposals in branch prediction research field. It’s necessary that computer architects to be more opened at other Computer Science areas and research methods, in order to enlarge their view and to improve their results. Cross-fertilisation is seen as essential if microprocessors are to continue their exponential growth. In conclusion we consider that using some more mature theoretical research tools, belonging to different science fields, could be an excellent alternative approach in the present-day Computer Architecture research method.
EFFECT OF AGROCHEMICALS ON THE GROWTH OF DIFFERENT TRICHODERMA ISOLATES

Biological control of plant pathogens through antagonists involves the use of beneficial microorganisms to attack and control plant pathogens, and the diseases they cause. It is an ecofriendly and potential approach under sustainable agriculture, apart them being a promising alternative to the use of chemicals (Patel et.al., 2014). Biocontrol fungi (BCF) are beneficial organisms that reduce the negative effects of plant pathogens and promote positive responses in the plant. In agriculture, these fungi, improves plant growth and development, has biological control activity against other fungi and nematodes (brunner et al., 2005, Hanson and Howell, 2004, Hoyos et al., 2009). Application of Trichoderma spp. is such an example of biocontrol agent with plant growth promoting ability coupled with antagonistic effect in phytopathogens (Kumar et al., 2012). It has been found that the persistent use of fungicides could weak the natural antagonistic activity (Lenteren and Woets, 1988). There are Trichoderma tolerant strains that can survive field concentrations of chemical fungicides. Now we have several approaches that can be used to obtain Trichoderma strains resistant to chemical fungicides.
Behavioral Economic , Rationality and Islamic Ethics

This work consists essentially of a comparative approach between behaviors and manners recommended by Islam and methods derived from Western experiences likely to avoid these biases (nudges). Moreover, in each case, this study tried to do corollary with Quranic verses and hadith to show that the life style recognized by Islamic healthy enough and far away from the negative image conveyed by extremists. The conclusion of this study is the habits and behavior preached by Islam, it doesn’t aim to make the man slave of a rigid doctrine of the Middle Ages, but instead, it’s healthy, peaceful and civilized behavior demonstrated by the experiences of behaviorists and aimed mainly to prevent the individual and society the misdeeds of a materialistic and selfish society. This work will be an invitation to Muslim scholars in the social sciences and economics in particular to be more interested in experimental and behavioral economics.