Miracle-dz/UniFAR-FTUs huggingface dataset:
Handbook of Psychology, Volume 5: Personality and Social Psychology

Psychology is of interest to academics from many fields, as well as to the thousands of academic and clinical psychologists and general public who can't help but be interested in learning more about why humans think and behave as they do. This award-winning twelve-volume reference covers every aspect of the ever-fascinating discipline of psychology and represents the most current knowledge in the field. This ten-year revision now covers discoveries based in neuroscience, clinical psychology's new interest in evidence-based practice and mindfulness, and new findings in social, developmental, and forensic psychology.
Design and analysis of switched-capacitor-based step-up resonant converters

A switched-capacitor-based step-up resonant converter is proposed. The voltage conversion of the converters is in step-up mode. By adding a different number of switched-capacitor cells, different output voltage conversion ratios can be obtained. The voltage conversion ratio from 2 to any whole number can therefore be generated by these switching-capacitor techniques. A resonant tank is used to assist in zero-current switching hence the current spike, which usually exists for classical switched-capacitor can be eliminated. Both high-frequency operations and high efficiency are possible. Generalized analysis and design method of the converters are also presented. Experimental results verified the theoretical analysis.
Multi-View Constraint Propagation with Consensus Prior Knowledge

In many applications, the pairwise constraint is a kind of weaker supervisory information which can be collected easily. The constraint propagation has been proved to be a success of exploiting such side-information. In recent years, some methods of multi-view constraint propagation have been proposed. However, the problem of reasonably fusing different views remains unaddressed. In this paper, we present a method dubbed Consensus Prior Constraint Propagation (CPCP), which can provide the prior knowledge of the robustness of each data instance and its neighborhood. With the robustness generated from the consensus information of each view, we build a unified affinity matrix as a result of the propagation. Specifically, we fuse the affinity of different views at a data instance level instead of a view level. This paper also introduces an approach to deal with the imbalance between the positive and negative constraints. The proposed method has been tested in clustering tasks on two publicly available multi-view data sets to show the superior performance.
Self-similar correlation function in brain resting-state functional magnetic resonance imaging

Adaptive behaviour, cognition and emotion are the result of a bewildering variety of brain spatio-temporal activity patterns. An important problem in neuroscience is to understand the mechanism by which the human brain's 100 billion neurons and 100 trillion synapses manage to produce this large repertoire of cortical configurations in a flexible manner. In addition, it is recognized that temporal correlations across such configurations cannot be arbitrary, but they need to meet two conflicting demands: while diverse cortical areas should remain functionally segregated from each other, they must still perform as a collective, i.e. they are functionally integrated. Here, we investigate these large-scale dynamical properties by inspecting the character of the spatio-temporal correlations of brain resting-state activity. In physical systems, these correlations in space and time are captured by measuring the correlation coefficient between a signal recorded at two different points in space at two different times. We show that this two-point correlation function extracted from resting-state functional magnetic resonance imaging data exhibits self-similarity in space and time. In space, self-similarity is revealed by considering three successive spatial coarse-graining steps while in time it is revealed by the 1/f frequency behaviour of the power spectrum. The uncovered dynamical self-similarity implies that the brain is spontaneously at a continuously changing (in space and time) intermediate state between two extremes, one of excessive cortical integration and the other of complete segregation. This dynamical property may be seen as an important marker of brain well-being in both health and disease.
Multicenter evaluation of an automated assay for troponin I.

BACKGROUND Cardiac troponin I (cTnI) is a powerful tool to aid in the diagnosis of myocardial infarction and cardiac muscle damage. We describe an assay that overcomes problems of early assays that were often affected by cTnI degradation, assay interference, poor sensitivity, and imprecision. METHODS The analytical performance of the Access AccuTnI assay (Beckman Coulter) was evaluated at five institutions. Controls, zero calibrator, and diluted patient samples were used to determine precision, detection limit, functional sensitivity, and linearity. The 97.5 and 99 percentiles of a reference population were determined. Common interferents and heterophilic patient samples were tested. Equimolarity was determined by assaying samples with various ratios of free and complexed cTnI. Matched samples drawn into serum, EDTA, lithium heparin, and sodium heparin sample tubes were compared. RESULTS Total imprecision (CVs) was 4.0-8.8% between 0.40 and 31 microg/L cTnI. The detection limit was <0.01 microg/L. The 97.5 percentile upper reference limit (URL) was 0.03 microg/L (CV = 20%), and the 99 percentile URL was 0.04 microg/L (CV = 14%). Total CVs of 10% and 20% were seen at and above 0.06 and 0.03 microg/L, respectively. The assay was linear to >60 microg/L and not affected by common assay interferents. An equimolar response was observed with free, complexed, phosphorylated, and dephosphorylated forms of cTnI. Results were 4% lower in serum and 14% lower in EDTA plasma than in lithium heparin plasma (P <0.01), independent of cTnI concentration. CONCLUSION AccuTnI is a sensitive and precise assay for the measurement of cTnI.
Virtual Reality Model of Koumokuten Generated from Measurement

Contents generation from measurement is an effective approach to automatic modeling of real world objects. In this paper, we present a system to create virtual reality model automatically from measurement of real object and present a virtual reality model of Koumokuten clay figure, which is a great treasure at Nara Toudaiji Temple, generated from the system. 3D geometric model of Koumokuten is generated from range image measured by range sensor and color images of it are acquired by digital camera. In the measurement digital camera is mounted on the range sensor and camera parameters between range image and color images are estimated from calibration techniques utilizing calibration box before data acquisition. We get textured model by mapping the images onto the 3D geometric model using the camera parameters estimated from the calibration. And we show several example applications of the virtual reality model of Koumokuten. By utilizing the virtual reality model we get different appearance of Koumokuten.
DCA as Context (Environment) Sensitive System

Existing immune-inspired techniques have not performed as well as expected when applied to the detection of intruders in computer systems. In nature, dendritic cells function as natural anomaly detection agents, instructing the immune system to respond if stress or damage is detected, it is also a crucial cell in the detection and combination of „signals‟ which provide the immune system with a sense of context. General Terms Dendritic Cell Algorithm (DCA), Security
Image Authentication Method by Combining Digital Signature and Watermarking

An image authentication method combining digital signature and watermarking is proposed in this paper. The proposed method not only can resist Holliman-Memon attack, but also can accurately detect the tampered location of an image. First, a watermark is created from a protected image by using an edge detection technique. Second, the created watermark is divided into blocks and embedded into the 2-LSB (top layer) of the protected image. Third, all block signatures are calculated and embedded into the 1-LSB (low layer) of the protected image. At the low layer, the calculated signatures can resist HollimanMemon attack. At the top layer, the created watermark can accurately detect the tampered location of an image. Experimental results show that the proposed method has good performance in tamper detection compared with the Celik et al.’s method.
Working as a self-employed professional, freelancer, contractor, consultant … issues, questions … and solutions?

This special issue ‘Working as a self-employed professional, freelancer, contractor, consultant . issues, questions . and solutions? ’ covers such a broad range and depth of topics that capturing the essence seems almost impossible. We, therefore, open this special edition with a snapshot from thought leaders from around the world. These snapshots cover a world view, presented by renowned British organisational theorist, consultant, and London Business School Professor Lynda Gratton, an Australian perspective from Australian Small Business and Family Enterprise Ombudsman, Kate Carnell to a UK view from Cambridge University’s renowned Labour Law Professor, Simon Deakin and a EU perceptive from esteemed European Policy Centre Advisor, Hans Martens. As you will see, while they are united by being well informed of the issue, they all come to the topic from different (sometime very) perspectives. All of our contributors have written on the subject, including for policy development and have an ‘expert eye’ on the topic.
A Novel Cysteine-Sparing NOTCH3 Mutation in a Chinese Family with CADASIL

Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) is an adult onset cerebral small vessel disorder caused by the mutations of the neurogenic locus notch homolog protein 3 (NOTCH3) gene. The extracellular part of NOTCH3 is composed of 34 epidermal growth factor-like (EGF-like) repeat domains. Each EGF-like domain is rich of cysteine and glycine to produce three loops that are essential for high-affinity binding to its ligand. Nearly all reported CADASIL-associated mutations result in gain or loss of a cysteine residue within the EGF-like domains. Only a few cysteine-sparing NOTCH3 mutations have been documented in the patients with CADASIL to date. Here, we reported a Chinese CADASIL family with a cysteine-sparing NOTCH3 mutation. In this family, affected patients had dizziness, memory loss, gait instability, or hemiplegia. Brain magnetic resonance imaging (MRI) showed diffuse leukoencephalopathy with confluent signal abnormalities in the periventricular white matter, basal ganglia, and centrum semiovale bilaterally. By screening the entire coding region of NOTCH3, a novel missense mutation p.G149V (c.446G>T) was found. This mutation was not detected in 400 normal controls. Considering the critical position of glycine within the C-loop of EGF-like domain and its high conservation through evolution, p.G149V mutation could be a potential pathogenic cause for CADASIL.
Posttraumatic cerebral venous sinus thrombosis as a complication of basilar skull fracture

Cerebral venous thrombosis (CVT), also known as a venous stroke, is relatively rare, more common in young people, and about 3/4 of patients are women. This disease may contribute to focal brain damage. The paper presents a case of a young man after a fall from a height with associated polytrauma (including basilar skull fracture), in which on the basis of magnetic resonance imaging transverse and sigmoid sinus thrombosis of the right side was diagnosed. Despite long-term anticoagulation, complete regression of thrombotic lesions has not been achieved. The clinical course of the described case raises a number of doubts about how to proceed in this group of patients, especially in the case of possible complications. Because so far clear standards of behavior therapy in venous thrombosis and cerebral sinus have not been established, it is still an important diagnostic and therapeutic problem.
The Flypaper Effect Unstuck: Evidence on Endogenous Grants from the Federal Highway Aid Program

Contrary to simple theoretical predictions, previous empirical research has found that state government public spending is increased far more, often dollar-for-dollar, by federal grant receipts than by equivalent increases in constituent private income. This anomaly has come to be known as the flypaper effect. First, a legislative bargaining model developed in this paper provides a critique of this empirical finding. The model demonstrates a positive correlation between constituent preferences for public goods and intergovernmental grant receipts, and this correlation has likely biased the existing literature towards finding a flypaper effect. The model also motivates using measures of the political power of state congressional delegations as an instrument for grant receipts. Second, after correcting for the endogeneity of grant receipts, the results demonstrate that constituent private income and grants have similar effects on public spending.
Verifying the long-range dependency of RNN language models

It has been argued that recurrent neural network language models are better in capturing long-range dependency than n-gram language models. In this paper, we attempt to verify this claim by investigating the prediction accuracy and the perplexity of these language models as a function of word position, i.e., the position of a word in a sentence. It is expected that as word position increases, the advantage of using recurrent neural network language models over n-gram language models will become more and more evident. On the text corpus of Penn Tree Bank (PTB), a recurrent neural network language model outperforms a trigram language model in both perplexity and word prediction. However, on the AMI meeting corpus, a trigram outperforms a recurrent neural network language model.
Universal quantum simulation with prethreshold superconducting qubits: Single-excitation subspace method

Current quantum computing architectures lack the size and fidelity required for universal fault-tolerant operation, limiting the practical implementation of key quantum algorithms to all but the smallest problem sizes. In this work we propose an alternative method for general-purpose quantum computation that is ideally suited for such "prethreshold" superconducting hardware. Computations are performed in the n-dimensional single-excitation subspace (SES) of a system of n tunably coupled superconducting qubits. The approach is not scalable, but allows many operations in the unitary group SU(n) to be implemented by a single application of the Hamiltonian, bypassing the need to decompose a desired unitary into elementary gates. This feature makes large, nontrivial quantum computations possible within the available coherence time. We show how to use a programmable SES chip to perform fast amplitude amplification and phase estimation, two versatile quantum subalgorithms. We also show that an SES processor is well suited for Hamiltonian simulation, specifically simulation of the Schrodinger equation with a real but otherwise arbitrary nxn Hamiltonian matrix. We discuss the utility and practicality of such a universal quantum simulator, and propose its application to the study of realistic atomic and molecular collisions.
Geometry, Drawings, Visual Thinking and Imagery: Towards a Visual Turing Test of Machine Intelligence

Psychometrics is the science of measurement of human intelligence, knowledge, aptitude and personality. By analogy, we need a science of computational psychometrics for measuring the intelligence and knowledge of intelligent machines. In psychometrics, the most common and reliable test of human intelligence is the Raven's Progressive Matrices Test that relies solely on a set of visual analogy problems. By analogy, we propose understanding visual drawings as a test of machine intelligence. Understanding drawings requires background knowledge, commonsense reasoning, as well as mental imagery, all of which appear central to human-level intelligence. Background, Motivations and Goals: Any behavioral
The Complete Chloroplast Genome of 17 Individuals of Pest Species Jacobaea vulgaris: SNPs, Microsatellites and Barcoding Markers for Population and Phylogenetic Studies

Invasive individuals from the pest species Jacobaea vulgaris show different allocation patterns in defence and growth compared with native individuals. To examine if these changes are caused by fast evolution, it is necessary to identify native source populations and compare these with invasive populations. For this purpose, we are in need of intraspecific polymorphic markers. We therefore sequenced the complete chloroplast genomes of 12 native and 5 invasive individuals of J. vulgaris with next generation sequencing and discovered single-nucleotide polymorphisms (SNPs) and microsatellites. This is the first study in which the chloroplast genome of that many individuals within a single species was sequenced. Thirty-two SNPs and 34 microsatellite regions were found. For none of the individuals, differences were found between the inverted repeats. Furthermore, being the first chloroplast genome sequenced in the Senecioneae clade, we compared it with four other members of the Asteraceae family to identify new regions for phylogentic inference within this clade and also within the Asteraceae family. Five markers (ndhC-trnV, ndhC-atpE, rps18-rpl20, clpP and psbM-trnD) contained parsimony-informative characters higher than 2%. Finally, we compared two procedures of preparing chloroplast DNA for next generation sequencing.
Offline recognition of handwritten Chinese characters using Gabor features, CDHMM modeling and MCE training

We've been developing a Chinese OCR engine for handwritten Chinese scripts. Currently, our OCR engine supports a vocabulary of 4616 characters which include 4516 simplified Chinese characters in GB2312-80, 62 alphanumeric characters, 38 punctuation marks and symbols. By using 1,384,800 character samples to train our recognizer, an averaged character recognition accuracy of 96.34% is achieved on a testing set of 1,025,535 character samples. An arguably best Chinese OCR product on the market achieves an accuracy of 94.07% for the recognizable Chinese characters in the above testing set. In this paper, we describe key techniques used in our recognizer that contribute to the high recognition accuracy, namely the use of Gabor features and their spatial derivatives as raw features, the use of LDA for feature extraction and dimension reduction, the use of CDHMMs for modeling Chinese characters along both horizontal and vertical directions, and the use of minimum classification error as a criterion for model training.
Biosensors with Built-In Biomolecular Logic Gates for Practical Applications

Molecular logic gates, designs constructed with biological and chemical molecules, have emerged as an alternative computing approach to silicon-based logic operations. These molecular computers are capable of receiving and integrating multiple stimuli of biochemical significance to generate a definitive output, opening a new research avenue to advanced diagnostics and therapeutics which demand handling of complex factors and precise control. In molecularly gated devices, Boolean logic computations can be activated by specific inputs and accurately processed via bio-recognition, bio-catalysis, and selective chemical reactions. In this review, we survey recent advances of the molecular logic approaches to practical applications of biosensors, including designs constructed with proteins, enzymes, nucleic acids, nanomaterials, and organic compounds, as well as the research avenues for future development of digitally operating “sense and act” schemes that logically process biochemical signals through networked circuits to implement intelligent control systems.
Antipattern-Based Problem Injection for Assessing Performance and Reliability Evaluation Techniques

A challenging problem with today's increasingly large and distributed software systems is their performance behavior. To help developers avoid or detect mistakes that lead to performance problems, many researchers in software performance engineering have come up with classifications of such problems, called antipatterns. To test the approaches for antipattern detection, data from running systems is required. However, the usefulness of this data is doubtful as it may or may not include manifestations of performance problems. In this paper, we classify existing performance antipatterns w.r. t. their suitability for being injected and, based on this, introduce an extensible tool that allows to inject instances of these antipatterns into existing applications. The approach can be useful for researchers to test and validate their automated runtime problem evaluation and prevention techniques. Using two exemplary performance antipatterns, it is demonstrated that the injection is easily possible and produces feasible, though currently rather clinical results.
Diabetes Mellitus and Risk of Age-Related Macular Degeneration: A Systematic Review and Meta-Analysis

Age-related macular degeneration (AMD) is a major cause of severe vision loss in elderly people. Diabetes mellitus is a common endocrine disorder with serious consequences, and diabetic retinopathy (DR) is the main ophthalmic complication. DR and AMD are different diseases and we seek to explore the relationship between diabetes and AMD. MEDLINE, EMBASE, and the Cochrane Library were searched for potentially eligible studies. Studies based on longitudinal cohort, cross-sectional, and case-control associations, reporting evaluation data of diabetes as an independent factor for AMD were included. Reports of relative risks (RRs), hazard ratios (HRs), odds ratio (ORs), or evaluation data of diabetes as an independent factor for AMD were included. Review Manager and STATA were used for the meta-analysis. Twenty four articles involving 27 study populations were included for meta-analysis. In 7 cohort studies, diabetes was shown to be a risk factor for AMD (OR, 1.05; 95% CI, 1.00–1.14). Results of 9 cross-sectional studies revealed consistent association of diabetes with AMD (OR, 1.21; 95% CI, 1.00–1.45), especially for late AMD (OR, 1.48; 95% CI, 1.44–1.51). Similar association was also detected for AMD (OR, 1.29; 95% CI, 1.13–1.49) and late AMD (OR, 1.16; 95% CI, 1.11–1.21) in 11 case-control studies. The pooled ORs for risk of neovascular AMD (nAMD) were 1.10 (95% CI, 0.96–1.26), 1.48 (95% CI, 1.44–1.51), and 1.15 (95% CI, 1.11–1.21) from cohort, cross-sectional and case-control studies, respectively. No obvious divergence existed among different ethnic groups. Therefore, we find diabetes a risk factor for AMD, stronger for late AMD than earlier stages. However, most of the included studies only adjusted for age and sex; we thus cannot rule out confounding as a potential explanation for the association. More well-designed prospective cohort studies are still warranted to further examine the association.