Miracle-dz/UniFAR-FTUs huggingface dataset:
Personality Assessment Methods and Practices

Part 1 Foundations of personality assessment: history and theories historical foundations theories of personality psychometrics I - statistical methods and test construction measurements and statistics constructing and item-analyzing assessment instruments sources and standards for personality assessment instruments psychometrics II - standardization, reliability and validity standardizing and equating tests reliability validity administration, interpretation and reporting instrument selection and administration interpreting assessment findings psychological assessment reports. Part 2 Observing, interviewing and rating: observations and interviews observations psychometric procedures and instruments for behaviour analysis interviews application blanks and biographical inventories checklists, rating scales and attitude measurement checklists rating scales attitude measurement. Part 3 Personality inventories: rational-theoretical and factor-analyzed inventories psychometric characteristics early personality inventories contemporary rational-theoretical inventories single-construct inventories health-related inventories factor-analyzed inventories perspective on factor analysis in personality assessment criterion-keyed inventories Minnesota multiphase personality inventory the CPI and other MMPI-related inventories the MCMI and other Millon inventories inventories based on combined strategies measuring interests and values interests and personality criterion- and content-validated interest inventories values and personal orientations. Part 4 Projective techniques: associations, completions and drawings concepts and examples association techniques completion techniques projective drawings the Rorschach and other inkblot techniques format and foundations five major systems and alternative approaches Exner's comprehensive system computer-based scoring and interpretation psychometric issues and future prospects the TAT and other apperception techniques administering the TAT an illustration - testing juvenile delinquents scoring and intepreting TAT stories psychometric issues and research TAT modification and other apperception tests. Part 5 Other personality measures, applications and issues: physiological, perceptual and cognitive measures physiological measures perceptual measures cognitive measures issues and prospects in personality assessment older issues in personality assessment continuing controversies newer methods, measures and areas of assessment prospects for the future of pesonality assessment.
Adaptive multi-task compressive sensing for localisation in wireless local area networks

The spatially distributed sparsity of the mobile devices (MDs) in indoor wireless local area networks (WLANs) makes compressive sensing (CS) based localisation algorithms feasible and desirable. In this Letter, the authors exploit the most recent developments in CS to efficiently perform localisation in WLANs and design an accurate indoor localisation scheme by taking advantage of the theory of multi-task Bayesian CS (MBCS). The proposed scheme assembles the strength measurements of signals from the MDs to distinct access points (APs) and jointly utilises them at a central unit or a specific AP to achieve localisation, thus being able to alleviate the burden of MDs while simultaneously giving a precise estimation of the locations. Afterwards, they give a deeper insight into the localisation problem in more practical scenarios with varying number of MDs and investigate two different adaptive algorithms to meet the satisfactory localisation error requirement. Compared with the conventional MBCS algorithms, simulation results validate that both adaptive algorithms could provide superior localisation accuracy and exhibit stronger resilience to the changes in the number of MDs.
On the accumulation of solid bodies in global turbulent protoplanetary disc models

We study the migration of solid bodies in turbulent protoplanetary accretion discs by means of global magnetohydrodynamic simulations. The bodies range in size from 5 cm up to 1 m, and so include objects whose migration is expected to be the most rapid due to gas drag interaction with the disc. As they drift inward through the disc, some of them are trapped in regions where gas pressure maxima are created by long-lived anticyclonic vortices. This accumulation is very efficient, locally increasing the dust-to-gas ratio by a factor >100 in some cases. We discuss the possible implications of this result for theories of planet formation.
Constructive multi-phase test point insertion for scan-based BIST

This paper presents a novel test point insertion technique which, unlike the previous ones, is based on a constructive methodology. A divide and conquer approach is used to partition the entire test into multiple phases. In each phase a group of test points targeting a specific set of faults is selected. Control points within a particular phase are enabled by fixed values, resulting in a simple and natural sharing of the logic driving them. Experimental results demonstrate that complete or near-complete stuck-at fault coverage can be achieved by the proposed technique with the insertion of a few test points and a minimum number of phases.
Activating Transcription Factor 3, a Useful Marker for Regenerative Response after Nerve Root Injury

Activating transcription factor 3 (ATF3) is induced in various tissues in response to stress. In this experiment, ATF3 expression was studied in adult rats subjected either to a dorsal or ventral root avulsion (VRA; L4-6), or sciatic nerve transection (SNT). Post-operative survival times varied between 1.5 h and 3 weeks. In additional experiments an avulsed ventral root was directly replanted to the spinal cord. Dorsal root ganglias (DRGs) from humans exposed to traumatic dorsal root avulsions were also examined. After SNT ATF3 immunoreactivity (ATF3 IR) was detected in a few DRG neurons already 6 h after the lesion. After 24 h the number had clearly increased and still at 3 weeks DRG neurons remained labeled. In the ventral horn, ATF3 IR in motoneurons (MN) was first detected 24 h after the SNT, and still 3 weeks post-operatively lesioned MN showed ATF3 labeling. After a VRA many spinal MN showed ATF3 IR already after 3 h, and after 6 h all MN were labeled. At 3 weeks a majority of the lesioned MN had died, but all the remaining ones were labeled. When an avulsed ventral root was directly replanted, MN survived and were still labeled at 5 weeks. In DRG, a few neurons were labeled already at 1.5 h after a dorsal root avulsion. At 24 h the number had increased but still only a minority of the neurons were labeled. At 3 days the number of labeled neurons was reduced, and a further reduction was at hand at 7 days and 3 weeks. In parallel, in humans, 3 days after a traumatic dorsal root avulsion, only a few DRG neurons showed ATF3 IR. At 6 weeks no labeled neurons could be detected. These facts imply that ATF3 response to axotomy involves a distance-dependent mechanism. ATF3 also appears to be a useful and reliable neuronal marker of nerve lesions even in humans. In addition, ATF3 up-regulation in both motor and sensory neurons seems to be linked to regenerative competence.
Towards planet-scale localization on smartphones with a partial radiomap

The majority of smartphone localization systems use Assisted-GPS for fine-grained localization in outdoor spaces or WiFi-based RSS (Received Signal Strength) technologies for coarse-grain positioning in indoor and outdoor spaces. The former consumes precious energy from mobile devices, is strictly affected by the environment (e.g., cloudy day, forests, etc.) and does not work in indoor spaces. The latter collects RSS from WiFi beams within a user's vicinity and transfers an RSS vector to the server for localization, in which the position of the user is disclosed possibly violating users' privacy. In this paper, we present BloomMap, an innovative and efficient algorithm that conducts a localization process without unveiling the user's location to the localization service, minimizing the energy consumption of the mobile unit and also minimizing the network traffic by not transferring large positioning structures to the client (i.e., known as radiomap). Our framework is designed for planet-scale RSS localization scenarios, which are expected to emerge in the near-future. In particular, a user may localize itself using a subset of a vast data repository of RSS signals that is updated in real time by smartphone wardrivers. Our preliminary evaluation shows that our propositions can localize a device without unveiling its location in approximately 80% less time, energy and network resources than competitive approaches. We also describe our WiFi-based prototype system developed on the Android OS.
Psychiatric and neuropsychological characterization of Pallister‐Hall syndrome

Pallister‐Hall syndrome (PHS) is a rare, single‐gene, malformation syndrome that includes central polydactyly, hypothalamic hamartoma, bifid epiglottis, endocrine dysfunction, and other anomalies. The syndrome has variable clinical manifestations and is inherited in an autosomal dominant pattern. We sought to determine whether psychiatric disorders and/or neuropsychological impairment were characteristic of PHS. We prospectively conducted systematic neuropsychiatric evaluations with 19 PHS subjects ranging in age from 7 to 75 years. The evaluation included detailed clinical interviews, clinician‐rated and self‐report instruments, and a battery of neuropsychological tests. Seven of 14 adult PHS subjects met diagnostic criteria for at least one DSM‐IV Axis I disorder. Three additional subjects demonstrated developmental delays and/or neuropsychological deficits on formal neuropsychological testing. However, we found no characteristic psychiatric phenotype associated with PHS, and the frequency of each of the diagnoses observed in these subjects was not different from that expected in this size sample. The overall frequency of psychiatric findings among all patients with PHS cannot be compared to point prevalence estimates of psychiatric disease in the general population because of biased ascertainment. This limitation is inherent to the study of behavioral phenotypes in rare disorders. The general issue of psychiatric evaluation of rare genetic syndromes is discussed in light of this negative result.
Opinion classification using Maximum Entropy and K-Means Clustering

responds from academic questionnaire generally contains many comments, advice and suggestions. This responds is not processed systematically due to lack of method to process. whereas such information might be very useful as additional source in decision making. Opinion mining is well suited to address the issue. The objective of this study is to develop opinion classification system using Maximum entropy (ME)) and K-Means Clustering (KMC). Opinion to be classified was Indonesian textual comments from academic questionnaire. Classification was conducted into two classes, i.e. negative opinion and positive opinion. Data contained of 2000 comments that was sampled as multi domain opinion, represented many objects such as lecturer, class room, etc. Features used for classification was selected from word in the opinion text. The weighting scheme that we used for clustering was TF/IDF. The results show that K-Means Clustering gives better performance as compared with ME in averages about 3% precision. KMC also perform faster than ME about 25 msec using 2000 text opinion.
A methodological inquiry into predictors of consumer satisfaction

Several theories of consumer satisfaction, e.g., Contrast [6]; Expectation Disconfirmation [13], report that satisfaction is predicted by the discrepancy between pre-purchase expectations, and actual product performance. Whereas, satisfaction can be indexed using emotion-based measures [13] - Product performance, on the other hand, has been evaluated using a variety of indices (e.g., direct evaluation, brand norm). In the current investigation, we were interested in evaluating product performance using a less conventional methodological approach in order to explore specific product attributes and their predictive influence on satisfaction in the communications market. Customers completed an online survey regarding their experience with the iPad, and then provided emotion-based satisfaction ratings, as well as open- and closed-ended performance feedback. Several converging analyses reveal that negative product feedback predicted lower satisfaction scores, and furthermore, only the product attributes of reliability and navigation negatively predicted satisfaction.
Caring to Know or Knowing to Care? The Relationship between Knowledge Creation and Caring in the Theological Education of Christian Social Work Professionals

Abstract The aim of this article is to investigate the relationship between knowledge creation and caring in the education of one of the Scandinavian churches' care professions: deacons. Care professionals are knowledge workers in the sense that their knowledge and skills influence quality of care. They not only need to have a certain knowledge base, but they also need to handle knowledge development in the context of complex practice. This means that learning how to create knowledge with participants and professionals is necessary to professional caring education. Further, knowledge creation depends on the provision of care in these contexts. Therefore, 1) knowledge creation is important in providing quality care, and 2) care itself may speed up the knowledge creation processes. In this article, we investigate how the relationship between care and knowledge creation is understood in key educational texts, namely education, curriculum documents. Findings indicate that care is understood as the purpose of the education, but less as a condition for the creation of knowledge. Also, the curricula prepare students for knowledge creation and care with participants, but not with other professionals.
Filter Flow : Supplemental Material

In Figure 1 we include a larger version of our linear depth-from-defocus results (Figure 4 in [5]), along with the corresponding result from [6] and from [2]. In Figure 2 we include similar results on another dataset from [6], along with corresponding result from [6] ([2] does not include results on this sequence.) In Figure 3 we include a larger version of our depth-from-defocus and motion results (Figure 5 in [5]). In Figure 4 we include results to illustrate robustness in the presence of blur.
Investigations on features for log-linear acoustic models in continuous speech recognition

Hidden Markov Models with Gaussian Mixture Models as emission probabilities (GHMMs) are the underlying structure of all state-of-the-art speech recognition systems. Using Gaussian mixture distributions follows the generative approach where the class-conditional probability is modeled, although for classification only the posterior probability is needed. Though being very successful in related tasks like Natural Language Processing (NLP), in speech recognition direct modeling of posterior probabilities with log-linear models has rarely been used and has not been applied successfully to continuous speech recognition. In this paper we report competitive results for a speech recognizer with a log-linear acoustic model on the Wall Street Journal corpus, a Large Vocabulary Continuous Speech Recognition (LVCSR) task. We trained this model from scratch, i.e. without relying on an existing GHMM system. Previously the use of data dependent sparse features for log-linear models has been proposed. We compare them with polynomial features and show that the combination of polynomial and data dependent sparse features leads to better results.
Multi-class classification in the presence of labelling errors

Learning a classifier from a training set that contains labelling errors is a difficult, yet not very well studied problem. Here we present a model-based approach that extends multi-class quadratic normal discrim- inant analysis with a model of the mislabelling process. We demonstrate the benefits of this approach in terms of parameter recovery as well as im- proved classification performance, on both synthetic and real-world multi- class problems. We also obtain enhanced accuracy in comparison with a previous model-free approach.
Enterprise E-Learning Success Factors: An Analysis of Practitioners' Perspective (with a Downturn Addendum)

This study proposes nine success factors for enterprise-wide e-learning. These factors were derived from the literature, interviews with e-learning project leaders, and analysis. Twelve semistructured interviews were conducted and analyzed in order to find out the best success factors to implement e-learning. These factors are divided into two categories: “must-have” factors and “nice-to-have” factors. The must-have factors include: useful and easy to use e-learning tools, marketing, management support, the right organizational culture, and the existence of a real need for the organization. The “nice to have” factors include: time to learn, support, mandatory learning, and incentives. Based on the research conclusions, a checklist of e-learning success factors is provided. A special addendum includes looking at the factors in downturn times, their relative importance and nature.
Using tagflake for condensing navigable tag hierarchies from tag clouds

We present the tagFlake system, which supports semantically informed navigation within a tag cloud. tagFlake relies on TMine for organizing tags extracted from textual content in hierarchical organizations, suitable for navigation, visualization, classification, and tracking. TMine extracts the most significant tag/terms from text documents and maps them onto a hierarchy in such a way that descendant terms are contextually dependent on their ancestors within the given corpus of documents. This provides tagFlake with a mechanism for enabling navigation within the tag space and for classification of the text documents based on the contextual structure captured by the created hierarchy. tagFlake is language neutral, since it does not rely on any natural language processing technique and is unsupervised.
Electronic Reprint Biological Crystallography the Protein Data Bank Biological Crystallography the Protein Data Bank

Author(s) of this paper may load this reprint on their own web site provided that this cover page is retained. Republication of this article or its storage in electronic databases or the like is not permitted without prior permission in writing from the IUCr. the single worldwide archive of primary structural data of biological macromolecules. Many secondary sources of information are derived from PDB data. It is the starting point for studies in structural bioinformatics. This article describes the goals of the PDB, the systems in place for data deposition and access, how to obtain further information and plans for the future development of the resource. The reader should come away with an understanding of the scope of the PDB and what is provided by the resource.
Comparing Different Term Weighting Schemas for Topic Modeling

Topic Modeling is a type of statistical model that tries to determine the topics present in a corpus of documents. The accuracy measures applied to clustering algorithm can also be used to assess the accuracy of topic modeling algorithms because determining topics for documents is similar with clustering them. This paper presents an experimental validation regarding the accuracy of Latent Dirichlet Allocation in comparison with Non-Negative Matrix Factorization and K-Means. The experiments use different weighting schemas when constructing the document-term matrix to determine if the accuracy of the algorithm improves. Two well known, already labeled text corpora are used for testing. The Purity and Adjusted Rand Index are used to evaluate the accuracy. Also, a time performance comparison regarding the run-time of these algorithms is presented.
Low-power and high-throughput hardware design for the 3D-HEVC depth intra skip

This paper presents a low-power and high-throughput hardware design for the 3D-HEVC (Three Dimensional High Efficiency Video Coding) Depth Intra Skip coding tool. A strategy to reduce the computational effort was employed based on an analysis using the 3D-HEVC reference software. The proposed strategy consists of replacing the SVDC (Synthesized View Distortion Change) for the SAD (Sum of Absolute Differences) as the similarity criterion. This way, the number of arithmetic operations related with the similarity criterion is reduced over 71%, and a rendering process is avoided at the cost of only 0.21% increase in the BD-Rate. The hardware was described in VHDL and synthesized for ASIC technology. The synthesis results for the 45nm Nangate standard cells demonstrate that the architecture can process 60 UHD 2160p frames per second (five views) with a power dissipation of 19.57mW.
Aryl hydrocarbon receptor knock-out exacerbates choroidal neovascularization via multiple pathogenic pathways

The aryl hydrocarbon receptor (AhR) is a heterodimeric transcriptional regulator with pleiotropic functions in xenobiotic metabolism and detoxification, vascular development and cancer. Herein, we report a previously undescribed role for the AhR signalling pathway in the pathogenesis of the wet, neovascular subtype of age‐related macular degeneration (AMD), the leading cause of vision loss in the elderly in the Western world. Comparative analysis of gene expression profiles of aged AhR−/− and wild‐type (wt) mice, using high‐throughput RNA sequencing, revealed differential modulation of genes belonging to several AMD‐related pathogenic pathways, including inflammation, angiogenesis and extracellular matrix regulation. To investigate AhR regulation of these pathways in wet AMD, we experimentally induced choroidal neovascular lesions in AhR−/− mice and found that they measured significantly larger in area and volume compared to age‐matched wt mice. Furthermore, these lesions displayed a higher number of ionized calcium‐binding adaptor molecule 1‐positive (Iba1+) microglial cells and a greater amount of collagen type IV deposition, events also seen in human wet AMD pathology specimens. Consistent with our in vivo observations, AhR knock‐down was sufficient to increase choroidal endothelial cell migration and tube formation in vitro. Moreover, AhR knock‐down caused an increase in collagen type IV production and secretion in both retinal pigment epithelial (RPE) and choroidal endothelial cell cultures, increased expression of angiogenic and inflammatory molecules, including vascular endothelial growth factor A (VEGFA) and chemokine (C–C motif) ligand 2 (CCL2) in RPE cells, and increased expression of secreted phosphoprotein 1 (SPP1) and transforming growth factor‐β1 (TGFβ1) in choroidal endothelial cells. Collectively, our findings identify AhR as a regulator of multiple pathogenic pathways in experimentally induced choroidal neovascularization, findings that are consistent with a possible role of AhR in wet AMD. The data discussed in this paper have been deposited in NCBI's Gene Expression Omnibus; GEO Submission No. GSE56983, NCBI Tracking System No. 17021116. © 2014 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.
A robust recognition system for a drawing superimposed on a map

A robust and efficient drawing recognition system that is based on a representation technique using accurate shape and topological line information for an input drawing image is described. This representation supports primitive decomposition and object extraction that enable accurate automatic interpretation even for low-quality drawings. The system, which is adapted to an underground electric cable diagram, has been implemented on a workstation. <<ETX>>