Miracle-dz/UniFAR-FTUs huggingface dataset:
Grand Policy Narratives: The Effect of Culture and Institutions on Policy Narratives – the Case of Swiss Child and Adult Protection

This paper contributes to completing the Narrative Policy Framework (NPF) by opening a track to explore ‘grand narratives’ on the policy macro-level and conducting a comparative analysis. A systematic inclusion of cultural and institutional features in the NPF is proposed to investigate the effects of these macro-level elements on meso-level policy narratives. The study benefits from the Swiss diverging cultural and institutional settings, which bring the country relatively close to a most-similar systems design. It compares the public controversy on a new child and adult protection policy in the two largest language parts by conducting a quantitative media analysis and semi-structured expert interviews. Findings confirm that cultural and institutional settings, and resulting macro-level narratives, influence meso-level policy narratives. In the German-speaking region, characterised by a more direct democratic political culture, the policy investigated led to a major institutional change, which in turn led to an atmosphere of scepticism and scrutiny towards the new public agency. Grand narratives identified focused on federalism (and cantonal and municipal autonomy) as one of the key features of Swiss democracy, and on rooted institutional traditions in order to argue against the new policy. This could hardly be observed in the French-speaking region. There the culture is characterised by a more representative democratic culture where trust in the state is more inherent. In addition, the new policy only led to a minor institutional change due to different institutional preconditions, which in turn led to a more balanced public perception of the new agency. These effects proved to be stable, even a focusing event could not over-ride them.
Technical Efficiency and Productivity of Private Commercial Banks in Bangladesh through DEA Approach

: The present study examines the efficiency and productivity of 18 private commercial banks in Bangladesh by using a Malmquist Productivity Index (an extension of Data Envelopment Analysis) with a balanced panel data over the years 2013 to 2017. The empirical findings suggest that Bangladeshi private commercial banks have decreased their average annual productivity by 3.0% mainly owing to technical efficiency and technological change. However, technical efficiency decline is due to lack of management effectiveness rather than scale efficiency of the sample banks. The results of the study also indicate that only Eastern Bank Ltd. and Al-Arafah Islami Bank Ltd are found technically efficient during the study period, while remaining sample banks are categorized as inefficient. In the course of examining the productivity changes of the sample banks, this study found only 3 among the 19 banks used in this paper showed total progress in productivity, whereas sixteen banks displayed total decrease in productivity. The major policy implications are further discussed.
VIBRATION-BASED DAMAGE LOCALIZATION USING THE DENSITY RATIO ESTIMATION METHOD

A machine learning technique, the Density Ratio Estimation method is applied for the ﬁrst time to detect structural damage, using test data from a scale model of a three-storey building structure under random excitation as a case study. The method detects damage by comparing the Probability Density Functions (PDFs) of measured vibration signals from an undamaged state and a potentially damaged state. Since the vibration signals from one sensor are not independent over time, instead of applying the vibration signals directly, the sequences of signals are used to train the model in order to account for the signal dependence, leading to multi-dimensional PDFs. To enhance model robustness, non-parametric models are applied for structural health monitoring problems. One limited way to detect damage is to estimate the nonparametric PDFs under the undamaged state and potentially damaged state separately, and then compare them. However, this method is very difﬁcult to apply when the dataset has many dimensions, and can often be intractable. The method applied in the current study estimates the PDF change directly, without estimating individual PDFs. Moreover, the damage indices in conventional methods are generally heuristic. In contrast, the damage index in the current study is Kullback–Leibler divergence, which has a clear statistical meaning; a measure of difference between two PDFs. To demonstrate the capability of the method, it is applied to data from a laboratory test which was previously conducted by Los Alamos National Lab. It is shown that the method can detect damage locations successfully.
NDT_A_305331 2333..2345

1Department of Psychiatry, Texas Tech University Health Science Center, Midland, TX, USA; 2Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, USA; 3Professor Emeritus, DukeNational University of Singapore, Singapore; 4Department of Statistical Science, Southern Methodist University, Dallas, TX, USA; 5Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA Objective: To develop clinically meaningful improvement thresholds in both the 17-item and the 6-item Hamilton Rating Scale for Depression (HRSD) total scores in depressed outpatients. Methods: The post-hoc analysis included all adult outpatients with non-psychotic major depressive disorder in the STAR*D trial who entered and exited the first treatment step (up to 14 weeks of citalopram) with a complete set of study measures at baseline and exit and at least one post-baseline measure. Within-patient change and linear regression anchor-based analyses were conducted to define meaningful and substantial changes in the HRSD17 and HRSD6 using three patient-reported outcomes [Work and Social Adjustment Scale (WSAS), Quality of Life Enjoyment and Satisfaction-Short Form (Q-LES-Q-SF); Mini-Q-LES-Q] obtained at baseline and exit from the first treatment step in STAR*D. Results: Linear regression analyses identified a meaningful change threshold for the HRSD17 as 3.9 [3.7–4.1] [lower, upper 95% CI] and a substantial change as 7.8 [7.4–8.3] with the WSAS. Analogous thresholds based on the Q-LES-Q-SF were 5.8 [5.5–6.1] and 11.6 [11.0–12.2], respectively, and 4.9 [4.7–5.2] and 9.9 [9.3–10.4] for the Mini-QLES-Q, respectively. For the HRSD6, linear regression analyses with the WSAS identified a meaningful change as 2.2 [2.1–2.4], while a substantial change was 4.5 [4.2–4.7]. Analogous figures based on the Q-LES-Q-SF were 3.2 [3.0–3.4] and 6.4 [6.1–6.8]. Similarly, based on the Mini-QLESQ, results were 2.8 [2.6–2.9] and 5.6 [5.3–5.9]. For both the HRSD17 and the HRSD6, within-patient analyses produced less precise estimates of the same change thresholds with substantial overlap between groups. Based on the WSAS, a clinically meaningful change in the HRSD17 total score was 9.6 (SD = 6.5), while a substantial change was 15.0 (SD = 6.7). Analogous change thresholds based on the Q-LESQ-SF were 12.9 (SD = 6.2) and 16.8 (SD = 6.4), respectively. For the Mini-Q-LESQ, thresholds were 10.9 (SD = 6.5) and 16.1 (SD = 6.2). Conclusion: A 4–6 point change in the HRSD17 is clinically meaningful; a 7–12 point change is clinically substantial. For the HRSD6, analogous estimates were 2–3 and 4–7 point changes, respectively.
Reprint of: Healthy Weight and Obesity Prevention

Overweight and obesity have reached epidemic levels in the United States and worldwide, and this has contributed to substantial cardiovascular and other health risks. However, controversy exists concerning the causes of obesity and effective modalities for its prevention and treatment. There is also controversy related to the concept of metabolically healthy obesity phenotype, the “ obesity paradox, ” and on the importance of ﬁ tness to protect individuals who are overweight or obese from cardiovascular diseases. In this state-of-the-art review, the authors focus on “ healthy weight ” with the emphasis on the pathophysiologic effects of weight gain on the cardiovascular system; mechanistic/triggering factors; and the role of preventive actions through personal, education/environment, and societal/authoritative factors, as well as factors to provide guidance for caregivers of health promotion. Additionally, the authors brie ﬂ y review metabolically healthy obesity, the obesity paradox, and issues beyond lifestyle consideration for weight loss with medications and bariatric surgery. (J Am Coll Cardiol 2018;72:3027 – 52) © 2018 by the American College of Cardiology Foundation.
A Cost-Benefit Method for Business Rules Normalization

— This paper presents a cost/benefit analysis method for the normalization of business rules. To determine the economic benefit of business rules normalization three variables are addressed: 1) the number of anomalies a rule set endures, 2) the storage space a rule set requires and the 3) deterioration of rules in response time. The approach is evaluated by means of an experiment, based on mortgage data of an international bank. Results show that the method is useful for determining when to normalize business rule sets; the method enables business rules analysts to produce more cost-effective business rules architectures. In this paper, we re-address and - present our earlier work [1], yet we extended the previous research with more detailed descriptions of the related literature, findings, and results, which provides a grounded basis from which further research on business rules normalization can be conducted.
The Predictive Ability of Cognitive Motivation, Optimism and Pessimism of Academic Procrastination

The study aimed for revealing the cognitive motivation, and where the study sample leads to optimism and pessimism, and it aimed for showing the female students’, at Prince Sattam Bin Abdul-Aziz University, ability of cognitive motivation, optimism, and pessimism of academic procrastination. The study sample consisted of 421 students from the faculty of education, who had been chosen by the available way. For achieving the study goals, the two researchers improved the scales of the cognitive motivation and the academic procrastination; they also extracted their sincerity and constancy indications. In addition, the study results indicated that the cognitive motivation level was high, and that sample’s individuals tended to be more optimistic than pessimistic. Also, it showed that the cognitive motivation is more influential in predicting the academic procrastination. Hence, the regression coefficient reached (0.240), which is a statistical function. On the other hand, optimism’s and pessimism’s ability of predicting the academic procrastination took the second position with a regression coefficient of (0.135). Accordingly, the study recommended to study the academic procrastination and its relation to other variables, and to study it in different environment rather than the university one. Moreover, the study recommended to create awareness programs and guidance publications in order to reduce the phenomenon of the academic procrastination as much as possible. And, for optimism and pessimism, the study recommended to construct educational centers for the youth, males and female, that improves their skills and abilities, and that connect them to the society to communicate with it in order to break their solitude, which causes pessimism.
Molecular characterization and phylogenetic analysis of betasatellite molecules associated with okra yellow vein mosaic disease in Sri Lanka and phylogenetic analysis of betasatellite molecules associated with yellow vein

In the years, okra growth and yield has been greatly affected in Sri Lanka by a 21 disease called okra yellow vein mosaic (OYVM). The disease is caused by begomovirus and 22 associated beta-satellites. The associated beta-satellite molecule determines the development 23 and severity of the disease. Therefore, knowledge of the sequence and diversity of the beta- 24 satellite molecules associated with OYVM disease would assist choice of virus isolates or 25 trial locations to use when selecting resistant varieties of okra. The present study aimed to 26 characterize the beta-satellite DNA sequences associated with OYVM disease in Sri Lanka 27 and determine their phylogenetic relationships. Beta-satellite DNA of six virus isolates from 28 widely separated geographical locations were sequenced and compared with already reported 29 begomovirus beta-satellites. The beta-satellite molecules have features common to 30 begomovirus beta-satellite DNAs: a conserved nonanucleotide TAATATTAC, a coding 31 sequence for the protein βC1, an adenine rich region and a satellite conserved region. er 32 Nucleotide diversity among the isolates was relatively low (  = 0.027). Recombination events 33 were detected at a specific region in the genome of all the isolates. The isolates shared 34 sequence identity >96 % with bhendi yellow vein beta-satellites reported from India. This is 35 further supported by phylogenetic analysis.
A Comparative analysis of machine learning algorithms applied to multi lingual texts summarization

Over the scarce period the World Wide Web (WWW) takes prolonged extremely and huge volumes of information in the form of news articles is available online. Many a times individuals don’t take the spell besides tolerance towards recite whole news divisions or ample long articles. At this time ascends the essential of computerized texts summarization. Uncertainty an instant of the real fillings of the broadcast object is obtainable formerly it will convert calmer for the handler to get a gist of the article as well as it would save a lot of his time. Nearby, numerous methods towards texts summarization which could be off the record on the root of numerous factors such as level of processing, kind of information being processed, etc. The work proposed in this paper tries to integrate these approaches with modern computational linguistics, semantic technologies and machine learning algorithms to devise a novel technique for multi lingual text summarization which could produce summaries aimed at sole too as group of forms. The anticipated method specifically addresses two major languages for the study, one is English being the language used worldwide and second Hindi being the national language of India. The machine learning techniques used for extraction are neural networks and fuzzy logic systems. Finally, a comparison of these techniques is done to show that fuzzy logic systems give better precision as compared to neural networks for summarization in both the languages. The average difference in precision is around 8-10% for Hindi and around 45-50% for English text documents.
New Tools for Investigating the Comparative Biology of C. briggsae and C. elegans

Comparative studies of C. briggsae and C. elegans have provided insights into gene function and developmental control in both organisms. C. elegans is a well developed model organism with a variety of molecular and genetic tools to study gene functions. In contrast, there are only very limited tools available for its closest relative, C. briggsae . To take advantage of the full potential of this comparative approach, we have developed several genetic and molecular tools to facilitate functional analysis in C. briggsae . First, we designed and implemented an SNP based oligonucleotide microarray for rapid mapping of genetic mutants in C. briggsae . Second, we generated a mutagenized frozen library to permit the isolation of targeted deletions and used the library to recover a deletion mutant of cbr-unc-119 for use as a transgenic marker. Third, we used the cbr-unc-119 mutant in ballistic transformation and generated fluorescently labeled strains that allow automated lineaging and cellular resolution expression analysis. Finally, we demonstrated the potential of automated lineaging by profiling expression of egl-5 , hlh-1 and pha-4 at cellular resolution and by detailed phenotyping of the perturbations on Wnt signaling pathway. These additions to the experimental toolkit for C. briggsae should greatly increase its utility in comparative studies with C. elegans . With the emerging sequence of nematode species more closely related to C. briggsae , these tools may open novel avenues of experimentation in C. briggsae itself.
Studies of operation modes for the ATHENA WFI detectors

The Wide Field Imager (WFI) is one of two instruments for ESA’s Athena X-ray observatory. It will employ DEPFET (depleted p-channel field effect transistor) active pixel technology to provide unprecedented spectroscopic and imaging capabilities over a broad energy band from 0.2 keV to 15 keV, with a large field of view of 40′ × 40′ . Using prototype detectors of various sizes we have started first tests of window mode operation, where only a subset of the full sensor array is being read out, leading to a higher frame rate for this area. We also investigated the possibility of operation at room temperature for a basic functionality test when cooling is not possible, e.g. on ground after integration on the satellite.
Estimation Problems in Jump Markov Systems

In this work we address estimation problems in linear systems subject to Markovian jumps. We first introduce the class of jump Markov linear systems. These are discrete-time systems jumping in time among a finite set of known linear modes. Each mode is defined by a stochastic difference equation, describing the evolution of a continuous state vector xk, and a static equation modeling noisy measurements yk of xk. The current operating mode is determined by the value of a discrete state qk taking values in a finite set Q. The evolution of qk follows the laws of a discrete-time Markov chain. We illustrate the problem of estimating the values of xk and qk based on the measurements y collected up to time k. The optimal Bayesian solution is presented and is shown to have complexity exponentially increasing in time. An overview of certain finite-complexity approximate estimation algorithms is presented. Open issues in suboptimal estimation and limitations of the discrete-time model are discussed. A similar model is then considered for systems with continuous-time dynamics. In this model, a stochastic differential equation governs the evolution of a continuous state ξ(t). Measurements yk of the state are taken at fixed sample times tk. Switching among different discrete states is determined by the outcome q(t) of a continuous-time Markov chain taking values in Q. We state the problem of estimating ξ(t) and q(t) based on the collection of data y and formulate the optimal solution of the problem. Application of conditioned Kalman filtering and a recursive estimation algorithm are discussed for the case of filtering and prediction. State estimation on single-switch models is studied in depth and is shown to be equivalent to a fault detection problem. Algorithms for fault detection are derived and are evaluated on the basis of numerical simulations. Finally, we focus back on state estimation in discrete time, and consider the problem of detecting the whole sequence of discrete states q0, . qk from the available data y. A sequential testing rule for the selection of a set of most probable sequences is considered. We investigate the connection between the structural properties of the system and the ability of the test to discriminate sequences, and determine the laws that regulate the probability of discarding the true sequence.
Multimodal Biometric System for Voters Verification in an Electioneering Process

— Electioneering process in many developing countries results in election frauds such as double registration, ballot stuffing, under-age voting and other forms of election drawbacks during registration of voters and casting of votes by eligible voters. In some developing countries, electronic biometric registration and verification system have been introduced during the registration and verification of voters. In many cases, some of the genuine registered voters were not recognized by the biometric machine. However, the rules and regulations pertaining to the elections stipulated that a voter would not be allowed to vote until he/she had been registered and verified. This means that before a voter could be allowed to cast his/ her vote, the biometric machine is supposed to recognize him/her first. Furthermore, some citizens that are physically challenged would also be denied the opportunities of exercising their franchise because the system used for the registration made use of fingerprint only. A Multi-modal biometric system is designed to eradicate the problem of eligible registered voters being disenfranchised by the current biometric system. This work presents a multi modal system that allows citizens to use their iris and fingerprint to go through the registration and verification process instead of their fingerprints alone as in the case of Nigeria electioneering process. The introduction of this system for general elections is expected to create room for full participation of all eligible voters, eliminate multiple voting and also increase the confidence of the people in electioneering processes.
Modèle pour les Zp-espaces

Soit x un espace topologique sur lequel agit le groupe z(p) des entiers modulo p (p premier), avec points fixes. Nous etudions ici le z(p) type d'homotopie rationnelle de x a l'aide de la cohomologie de Bredon et des travaux de G. Triantafillou. Nous construisons d'abord un modele algebrique de x. Une equivalence de categories homotopiques permet d'affirmer qu'il contient toute l'information concernant le z(p) type d'homotopie rationnelle. La notion de z(p) formalite est ensuite abordee. Un z(p) espace x est z(p) formel si x et h(x;q) ont le meme z(p) modele. Nous montrons ici que cette propriete equivaut a la formalisabilite de l'inclusion de l'ensemble des points fixes i : x(z)p->x. Des exemples d'espaces z(p) formels et d'espaces non z(p) formels sont egalement donnes
Fructosamlne concentration and serum TRAP capacity of healthy subjects and diabetic patients

Kruskal-Walbs ANOVA was applied to the following sets of data: (A) nondiabetics, type 1, and type 2 or (B) nondlabetics and satisfactorily and poorly controlled. Dunn’s test was used postanalysis to estimate significance between the corresponding pairs of data Significantly different from nondiabetics (P <0.0001). b Significantly dIfferent from nondiabetics (P <0.005) and from satisfactorily controlled (P <0.01).
Technological Innovation in Mobile Payment Solutions

The advent of mobile payment solution has brought a mixed reaction on the mind of potential consumers on whether to adopt or not. Also, the mobile payment has elicited discussion about its future. The major question is on whether the technology will replace traditional banking processes, or if it will act as a compliment. The thesis seeks to promote the adoption of mobile payment by improving available information for stakeholders. The advent of mobile payment technology shows that it has a high number of benefits, but it does not match with the current adoption rate. The statistics show that the majority of users of mobile payment uses it to for smaller transactions such as the purchase of books and food. The slow uptake of mobile payment adoption vis a vis immense benefit of the platform. The disparity motivated the study on factors that influence solution adoptions. The thesis provides a clear linkage of factors such as environmental risk, reputation, trust, perceived usefulness, ease of use and mobility in influencing potential consumer attitude and intention to use a specific payment solution. Keywords— Mobile payment, perceived usefulness, perceived ease of use, attitude, intention to use, environmental risk, reputation and mobility.