Miracle-dz/UniFAR-FTUs huggingface dataset:
The Psychometrics of the Children’s Depression Inventory When Used With Children Who Are Chronically Ill and Matched Community Comparison Peers

The Children’s Depression Inventory (CDI) is used to screen for depression in children aged 7 years to 16 years. The purpose of this study is to examine the psychometrics of the CDI in a sample of children who are chronically ill (N = 350) and in a sample of matched community comparison peers (N = 357), and determine if the psychometrics of the scale are similar in both groups. Data were aggregated from previous reports examining social and emotional functioning of children with six chronic diseases and matched comparisons. The CDI was completed in the homes of all participants. No significant differences between groups on CDI scores, distributions, reliability, or validity were observed. Findings suggest that the psychometrics of the CDI are similar for children with chronic diseases compared with typically developing children. The CDI may be an effective screening tool for use with children who have chronic health conditions.
Fusion of likelihood ratio classifier with ICP-based matcher for 3D face recognition

Three-dimensional (3D) face recognition systems have started to become popular in biometric systems recently. This is due to several factors: i) facial shape characteristics contain discriminative information, ii) availability of practical 3D acquisition devices, and iii) invariance of 3D facial information to several factors such as illumination and pose changes. It has been shown that classical texture-based 2D face classifiers have difficulties in identifying faces under such conditions. Therefore, taking advantage of 3D facial shape information either alone or together with 2D modality is considered to be a viable solution under such circumstances. In this work, we propose a novel 3D face recognition system using the combination of different individual 3D face classifiers; namely Linear Discriminant-based (LDA) Likelihood Ratio classifier with the Iterative Closest Point-based (ICP) matching algorithm. Both systems operate on aligned and normalized 3D facial surfaces. Alignment phase of the proposed system carries out absolute alignment such that all faces are in a specific position and direction, with non-facial parts removed. LDA-based system uses absolutely aligned faces and produce similarity scores using Likelihood ratio-based classifier. However, the ICP-based classifier performs additional surface matching between absolutely aligned faces, which can be considered as relative alignment. After pair-wise alignment of gallery and probe faces, the ICP algorithm produces dissimilarity scores, by measuring the quality of surface registration. With the use of different matching algorithms and different alignment methods, our approach tries to minimize the shortcomings of each individual method. Finally, the scores obtained by 3D face recognizers are fused to improve the verification accuracy. Our preliminary experiments conducted on the subset of FRGC v2 3D face database show promising performance improvement in verification simulations.
Potřeba poznávání: Studie psychometrických charakteristik zkrácené české verze Škály potřeby poznávání

Need for cognition refers to tendency to engage in and enjoy effortful cognitive activities. As conceptualized by Cacioppo and Petty (1982) need for cognition is a cognitive disposition, relatively stable in time and only slightly related to intellectual capacity and performance in terms of IQ. Need for Cognition Scale (NFCS) by Cacioppo and Petty is considered the most prevalent self report method for assessing need of cognition. Validity study of short Czech version of the questionnaire was performed on a sample of 679 participants (62% men, age 16 to 43, Me = 23). Results show good factor validity and high internal consistency – a two-factor congeneric model (factors based on item wording) showed the best fit among all four tested models and is in accordance with recent research. Construct validity was assessed using need for cognitive closure and right wing authoritarianism questionnaires; in accordance with theoretical assumptions, NFCS correlates negatively with both measures. The specificity of the sample might pose some limitations, however, the translation can be considered validated for research purposes.
Annotation and Analysis of Discourse Relations, Temporal Relations and Multi-Layered Situational Relations in Japanese Texts

This paper proposes a methodology for building a specialized Japanese data set for recognizing temporal relations and discourse relations. In addition to temporal and discourse relations, multi-layered situational relations that distinguish generic and specific states belonging to different layers in a discourse are annotated. Our methodology has been applied to 170 text fragments taken from Wikinews articles in Japanese. The validity of our methodology is evaluated and analyzed in terms of degree of annotator agreement and frequency of errors.
An ES Process Framework for Understanding the Strategic Decision Making Process of ES Implementations

Enterprise systems (ES) implementations are regarded costly, time and resource consuming and have a great impact on the organization in terms of the risks they involve and the opportunities they provide. The steering committee (SC) represents the group of individuals who is responsible for making strategic decisions throughout the ES implementation lifecycle. It is evident from recent studies that there is a relationship between the decision making process and ES implementation success. One of the key elements that contribute to the success of ES implementations is a quick decision making process (Brown and Vessey, 1999; Gupta, 2000; Parr, et al., 1999). This study addresses the strategic decision-making process by SC through its focus on four research questions (1) How can the strategic decision-making process in the implementation of ES be better understood, during each phase of the ES implementation lifecycle? (2) What is the process by which the SC makes strategic decisions? (3) How are fast decisions made? and (4) How does decision speed link to the success of ES implementation? Process models of ES implementation will provide a framework to investigate the strategic decision making process during each phases of the ES implementation lifecycle. Patterns in the decision making process will be explored using strategic choice models. This study develops a research model that focuses on the decision making process by steering committee to explore research questions. It concludes with identifying contributions to both IS research and business practitioners.
The Syntax of Preverbal Particles and Adjunction in Irish

It is shown that five apparently irreconcilable claims about the clausal syntax of Irish can be reconciled in a natural, base-generated LFG analysis that builds on the standard LFG theory of endocentricity and coheads/extended heads, the LFG projection architecture, and Toivonen’s (2001)’s work on nonprojecting categories and c-structure adjunction. The analysis also builds on McCloskey’s (1996) analysis of Irish adjunction, but does not posit complementizer lowering. The principal theoretical consequences of the analysis are 1) the reconciliation of the five claims, in particular a synthesis of McCloskey’s position that the Irish preverbal particles are complementizers and Sells’s (1984) position that they are head-adjoined to the verb, 2) the elaboration of Toivonen’s (2001) theory of c-structure adjunction, 3) correct predictions about not only adjunction to matrix and subordinate clauses, but also adjunction to appositives.
MICROCONTROLLER BASED METHODOLOGY FOR PART TRACKING IN INDUSTRIAL AUTOMATION

The goal of this work was to design a microcontroller based sorting system. Besides solving the particular problem, a new methodology has also been devised, which simplifies automation tasks. This methodology requires a separate algorithm thread for each station. Subsequent threads are tied to each other through a FIFO. As a byproduct, a generic class library have been developed.
Image feature extraction by sparse coding and independent component analysis

Sparse coding is a method for finding a representation of data in which each of the components of the representation is only rarely significantly active. Such a representation is closely related to the techniques of independent component analysis and blind source separation. In this paper, we investigate the application of sparse coding for image feature extraction. We show how sparse coding can be used to extract wavelet-like features from natural image data. As an application of such a feature extraction scheme, we show how to apply a soft-thresholding operator on the components of sparse coding in order to reduce Gaussian noise. Methods based on sparse coding have the important benefit over wavelet methods that the features are determined solely by the statistical properties of the data, while the wavelet transformation relies heavily on certain abstract mathematical properties that may be only weakly related to the properties of the natural data.
Patient participatory behaviours in healthcare service delivery

Purpose The purpose of this paper is to deepen the understanding on patient participatory behaviours in co-creation of value drawing from the perspective of self-determination theory (SDT) focussing on motivation in particular. Design/methodology/approach A model is proposed to suggest the influence of the various motivation types on a patient’s participatory behaviours drawing from SDT. Following survey design approach, data collected from 345 outpatients from a quasi-government health facility in Accra, Ghana are examined through structural equation modelling using SmartPLS (v. 3.2.3). Findings The findings reveal that patient participatory behaviours are influenced by both controlled and autonomous regulations leading to value attainment. External regulation (a more controlled form of extrinsic motivation) and patient participation in clinical encounters have no significant relationship with a patient’s commitment to compliance with medical instructions. The results reveal patient compliance is largely driven by autonomous regulation as proposed by SDT. However, active patient participation in clinical encounters and commitment to compliance with medical instructions positively and significantly influences perceived value outcomes. Research limitations/implications This research provides empirical evidence in support of understanding patient participatory behaviours in healthcare service delivery by testing theoretically grounded hypotheses developed from SDT perspective. The study focussed on outpatients from one quasi-government health facility, which could limit the generalisation of the findings reported. Practical implications This study illustrates the need for service providers to understand participant’s needs and motivation during the service encounter. This is essential as the various types of motivation influence the nature of the participation throughout the process, which could help improve on the value outcomes from the service. Originality/value This study makes a significant contribution to service literature through the application of SDT to explain patient participatory behaviours in healthcare service delivery, production and value outcomes. From a theoretical perspective, the developed model integrates multiple research disciplines (e.g. SDT, participatory behaviours, and value co-creation) and extends research on patient integration, participation, and compliance.
Manganese exposure among smelting workers: blood manganese–iron ratio as a novel tool for manganese exposure assessment

Unexposed control subjects (n = 106), power distributing and office workers (n = 122), and manganese (Mn)-exposed ferroalloy smelter workers (n = 95) were recruited to the control, low and high groups, respectively. Mn concentrations in saliva, plasma, erythrocytes, urine and hair were significantly higher in both exposure groups than in the controls. The Fe concentration in plasma and erythrocytes, however, was significantly lower in Mn-exposed workers than in controls. The airborne Mn levels were significantly associated with Mn/Fe ratio (MIR) of erythrocytes (eMIR) (r = 0.77, p < 0.01) and plasma (pMIR) (r = 0.70, p < 0.01). The results suggest that the MIR may serve as a useful biomarker to distinguish Mn-exposed workers from the unexposed, control population.
A noise-immune sub-threshold circuit design based on selective use of Schmitt-trigger logic

Nanoscale circuits operating at sub-threshold voltages are affected by growing impact of random telegraph signal (RTS) and thermal noise. Given the low operational voltages and subsequently lower noise margins, these noise phenomena are capable of changing the value of some of the nodes in the circuit, compromising the reliability of the computation. We propose a method for improving noise-tolerance by selectively applying feed-forward reinforcement to circuits based on use of existing invariant relationships. As reinforcement mechanism, we used a modification of the standard CMOS gates based on the Schmitt trigger circuit. SPICE simulations show our solution offers better noise immunity than both standard CMOS and fully reinforced circuits, with limited area and power overhead.
BUILDING CAD PROTOTYPING TOOL FOR EMERGING NANOSCALE FABRICS

The design of CAD tools for nanofabrics involves new challenges not encountered with conventional CMOS technology. In this paper, we describe the design of a prototyping CAD tool targeting design automation of applications on a wide range of nanofabrics. Our proposal is based on a variety of models that capture as well as isolate the differences between the fabrics. This tool supports the design flow from behavioral description to final layout. It integrates fault-tolerant techniques and fabric-related density transformations with more conventional design automation techniques. After an overview of common requirements, physical models, and associated techniques, a case study in the context of NASIC fabrics is used to illustrate some of the concepts.
The moderating effect of web service on the relationship between business analytics and supply chain performance

In recent years, supply chain performance measurement has received much attention from researchers and practitioners. Effective supply chain performance through supply chain antecedents such as business analytics has become a potentially valuable way of securing competitive advantage and improving supply chain performance. Many organizations have begun to recognize that supply chain management is the key to building a sustainable competitive advantage for their products or services in an increasingly crowded marketplace. Despite the fact that, determining supply chain performance through its antecedents is considered as a unique methodology, theoretical and comprehensive studies on supply chain performance through the methodology is few and far between. This study addressed the lack of the empirical studies by developing a comprehensive model to examine the effect of plan analyse, source analyse, make analyse and delivery analyse on supply chain performance considering moderating effect of WS on the relationships. A quantitative methodology using a cross-sectional survey method was used to investigate the relationship between variables. Data were collected from automotive companies in Iran. The overall response rate was 86.72%. The relationships between variables were examined using structural equation modelling (SEM) technique and partial least squares (PLS) software was used to examine the proposed hypotheses. The results revealed there is a significant and positive relationship between four areas of business analytics namely plan analyse, source analyse, make analyse and delivery analyse and supply chain performance. Moreover, the results indicated that the aforementioned relationship is moderated by WS. The study combined resource- based theory, resource dependence theories to develop a new theoretical framework to demonstrate the importance of the four areas of SCOR approach businesses analytic; in improving supply chain performance. Moreover, the study has provided a new platform to effectively improve supply chain performance.
Belief Propagation on Uncertain Schema Mappings in Peer Data Management Systems

Until recently, most data integration techniques involved central components, e.g., global schemas, to enable transparent access to heterogeneous databases. Today, however, with the democratization of tools facilitating knowledge elicitation in machine-processable formats, one cannot rely on global, centralized schemas anymore as knowledge creation and consumption are getting more and more dynamic and decentralized. Peer Data Management Systems (PDMS) provide an answer to this problem by eliminating the central semantic component and considering instead compositions of local, pair-wise mappings to propagate queries from one database to the others. In the following, we give an overview of various PDMS approaches; all the approaches proposed so far make the implicit assumption that all schema mappings used to reformulate a query are correct. This obviously cannot be taken as granted in typical PDMS settings where mappings can be created (semi) automatically by independent parties. Thus, we propose a totally decentralized, efficient message passing scheme to automatically detect erroneous schema mappings in a PDMS. Our scheme is based on a probabilistic model where we take advantage of transitive closures of mapping operations to confront local belief on the correctness of a mapping against evidences gathered around the network. We show that our scheme can be efficiently embedded in any PDMS and provide an evaluation of our techniques on large sets of automatically-generated schemas.
Variants in the ASB10 Gene Are Associated with Primary Open Angle Glaucoma

Background Recently nonsynonymous coding variants in the ankyrin repeats and suppressor of cytokine signaling box-containing protein 10 (ASB10) gene were found to be associated with primary open angle glaucoma (POAG) in cohorts from Oregon and Germany, but this finding was not confirmed in an independent cohort from Iowa. The aim of the current study was to assess the role of ASB10 gene variants in Pakistani glaucoma patients. Methods Sanger sequencing of the coding exons and splice junctions of the ASB10 gene was performed in 30 probands of multiplex POAG families, 208 sporadic POAG patients and 151 healthy controls from Pakistan. Genotypic associations of individual variants with POAG were analyzed with the Fisher’s exact or Chi-square test. Results In total 24 variants were identified in POAG probands and sporadic patients, including 11 novel variants and 13 known variants. 13 of the variants were nonsynonymous, 6 were synonymous, and 5 were intronic. Three nonsynonymous variants (p.Arg49Cys, p.Arg237Gly, p.Arg453Cys) identified in the probands were not segregating in the respective families. This is not surprising since glaucoma is a multifactorial disease, and multiple factors are likely to be involved in the disease manifestation in these families. However a nonsynonymous variant, p.Arg453Cys (rs3800791), was found in 6 sporadic POAG patients but not in controls, suggesting that it infers increased risk for the disease. In addition, one synonymous variant was found to be associated with sporadic POAG: p.Ala290Ala and the association of the variant with POAG remained significant after correction for multiple testing (uncorrected p-value 0.002, corrected p-value 0.047). The cumulative burden of rare, nonsynonymous variants was significantly higher in sporadic POAG patients compared to control individuals (p-value 0.000006). Conclusions Variants in ASB10 were found to be significantly associated with sporadic POAG in the Pakistani population. This supports previous findings that sequence variants in the ASB10 gene may act as a risk factor for glaucoma.
Climatic Effects on Lake Basins. Part I: Modeling Tropical Lake Levels

The availability ofsatellite estimatesof rainfalland lakelevels offersexciting new opportunities toestimate the hydrologic properties of lake systems. Combined with simple basin models, connections to climatic variations can then be explored with a focus on a future ability to predict changes in storage volume for water resources or natural hazards concerns. This study examines the capability of a simple basin model to estimate variationsin waterlevelfor 12tropicallakesandreservoirsduringa 16-yrremotelysensedobservationperiod (1992‐2007). The model is constructed with two empirical parameters: effective catchment to lake area ratio and time delay between freshwater flux and lake level response. Rainfall datasets, one reanalysis and two satellite-based observational products, and two radar-altimetry-derived lake level datasets are explored and cross checked. Good agreement is observed between the two lake level datasets with the lowest correlations occurring for the two small lakes Kainji and Tana (0.87 and 0.89). Fitting observations to the simple basin model provides a set of delay times between rainfall and level rise ranging up to 105 days and effective catchment to lake ratios ranging between 2 and 27. For 9 of 12 lakes and reservoirs the observational rainfall products provide a better fit to observed lake levels than the reanalysis rainfall product. But for most of the records any of the rainfall products provide reasonable lake level estimates, a result which opens up the possibility of using rainfall to create seasonal forecasts of future lake levels and hindcasts of past lake levels. The limitations of the observation sets and the two-parameter model are discussed.
Essential Faces and Stability Conditions of Multiclass Networks with Priorities

It is now well-known that multiclass networks may be unstable even under the «usual conditions» of stability (when the loads are less than one at all queues), but the proofs of transience (in the Markovian case) generally require a complex work based on the dynamics of an associated «fluid model». Here we develop a sample-path argument introduced in a previous paper, which provides new ergodicity conditions for networks ruled by {\em priorities}; when one of these conditions is violated, the network diverges at linear speed. Our approach is based on the identification of the {\em essential faces}, which are the sets of classes that can be simultaneously occupied in stationary regime. A graph is associated with the network, the existence of unessential faces being equivalent to the presence of {\em cycles} in this graph, in which case the usual conditions are not sufficient conditions of stability. As a by-product of our results, we recover the stability conditions and complete the analysis of two exemplary models, the Rybko-Stolyar network and the Lu-Kumar network.