Miracle-dz/UniFAR-FTUs huggingface dataset:
The Bern Psychopathology Scale for the Assessment of System-Specific Psychotic Symptoms

The translation from psychiatric core symptoms to brain functions and vice versa is a largely unresolved issue. In particular, the search for disorders of single brain regions explaining classical symptoms has not yielded the expected results. Based on the assumption that the psychopathology of psychosis is related to a functional imbalance of higher-order brain systems, the authors focused on three specific candidate brain circuitries, namely the language, and limbic and motor systems. These domains are of particular interest for understanding the disastrous communication breakdown during psychotic disorders. Core symptoms of psychosis were mapped on these domains by shaping their definitions in order to match the related brain functions. The resulting psychopathological assessment scale was tested for interrater reliability and internal consistency in a group of 168 psychotic patients. The items of the scale were reliable and a principal component analysis (PCA) was best explained by a solution resembling the three candidate systems. Based on the results, the scale was optimized as an instrument to identify patient subgroups characterized by a prevailing dysfunction of one or more of these systems. In conclusion, the scale is apt to distinguish symptom domains related to the activity of defined brain systems. PCA showed a certain degree of independence of the system-specific symptom clusters within the patient group, indicating relative subgroups of psychosis. The scale is understood as a research instrument to investigate psychoses based on a system-oriented approach. Possible immediate advantages in the clinical application of the understanding of psychoses related to system-specific symptom domains are also discussed.
Detection of conflicting functional requirements in a use case-driven approach: a static analysis technique based on graph transformation

In object-oriented software development, requirements of different stakeholders are often manifested in use case models which complement the static domain model by dynamic and functional requirements. In the course of development, these requirements are analyzed and integrated to produce a consistent overall requirements specification. Iterations of the model may be triggered by conflicts between requirements of different parties.However, due to the diversity, incompleteness, and informal nature, in particular of functional and dynamic requirements, such conflicts are difficult to find. Formal approaches to requirements engineering, often based on logic, attack these problems, but require highly specialized experts to write and reason about such specifications.In this paper, we propose a formal interpretation of use case models consisting of UML use case, activity, and collaboration diagrams. The formalization, which is based on concepts from the theory of graph transformation, allows to make precise the notions of conflict and dependency between functional requirements expressed by different use cases. Then, use case models can be statically analyzed, and conflicts or dependencies detected by the analysis can be communicated to the modeler by annotating the model.An implementation of the static analysis within a graph transformation tool is presented.
Combined Linkage and Association Studies Show that HLA Class II Variants Control Levels of Antibodies against Epstein-Barr Virus Antigens

Over 95% of the adult population worldwide is infected with Epstein-Barr virus (EBV). EBV infection is associated with the development of several cancers, including Hodgkin lymphoma (HL). Elevated levels of anti-EBV antibodies have been associated with increased risk of HL. There is growing evidence that genetic factors control the levels of antibodies against EBV antigens. Here, we conducted linkage and association studies to search for genetic factors influencing either anti-viral capsid antigen (VCA) or anti-Epstein Barr nuclear antigen-1 (EBNA-1) IgG levels in a unique cohort of 424 individuals of European origin from 119 French families recruited through a Hodgkin lymphoma (HL) patient. No major locus controlling anti-VCA antibody levels was identified. However, we found that the HLA region influenced anti-EBNA-1 IgG titers. Refined association studies in this region identified a cluster of HLA class II variants associated with anti-EBNA-1 IgG titers (e.g. p = 5×10–5 for rs9268403). The major allele of rs9268403 conferring a predisposition to high anti-EBNA-1 antibody levels was also associated with an increased risk of HL (p = 0.02). In summary, this study shows that HLA class II variants influenced anti-EBNA-1 IgG titers in a European population. It further shows the role of the same variants in the risk of HL.
Blind tests of RNA nearest-neighbor energy prediction

Significance Understanding RNA machines and how their behavior can be modulated by chemical modification is increasingly recognized as an important biological and bioengineering problem, with continuing discoveries of riboswitches, mRNA regulons, CRISPR-guided editing complexes, and RNA enzymes. Computational strategies for understanding RNA energetics are being proposed, but have not yet faced rigorous tests. We describe a modeling strategy called RECCES–Rosetta (reweighting of energy-function collection with conformational ensemble sampling in Rosetta) that models the full ensemble of motions of RNA in single-stranded form and in helices, including nonstandard nucleotides, such as 2,6-diaminopurine, a variant of adenosine. When compared with experiments, including blind tests, the energetic accuracies of RECCES–Rosetta calculations are at levels close to experimental error, suggesting that computation can now be used to predict and design basic RNA energetics. The predictive modeling and design of biologically active RNA molecules requires understanding the energetic balance among their basic components. Rapid developments in computer simulation promise increasingly accurate recovery of RNA’s nearest-neighbor (NN) free-energy parameters, but these methods have not been tested in predictive trials or on nonstandard nucleotides. Here, we present, to our knowledge, the first such tests through a RECCES–Rosetta (reweighting of energy-function collection with conformational ensemble sampling in Rosetta) framework that rigorously models conformational entropy, predicts previously unmeasured NN parameters, and estimates these values’ systematic uncertainties. RECCES–Rosetta recovers the 10 NN parameters for Watson–Crick stacked base pairs and 32 single-nucleotide dangling-end parameters with unprecedented accuracies: rmsd of 0.28 kcal/mol and 0.41 kcal/mol, respectively. For set-aside test sets, RECCES–Rosetta gives rmsd values of 0.32 kcal/mol on eight stacked pairs involving G–U wobble pairs and 0.99 kcal/mol on seven stacked pairs involving nonstandard isocytidine–isoguanosine pairs. To more rigorously assess RECCES–Rosetta, we carried out four blind predictions for stacked pairs involving 2,6-diaminopurine–U pairs, which achieved 0.64 kcal/mol rmsd accuracy when tested by subsequent experiments. Overall, these results establish that computational methods can now blindly predict energetics of basic RNA motifs, including chemically modified variants, with consistently better than 1 kcal/mol accuracy. Systematic tests indicate that resolving the remaining discrepancies will require energy function improvements beyond simply reweighting component terms, and we propose further blind trials to test such efforts.
Mersenne twister: a 623-dimensionally equidistributed uniform pseudo-random number generator

A new algorithm called Mersenne Twister (MT) is proposed for generating uniform pseudorandom numbers. For a particular choice of parameters, the algorithm provides a super astronomical period of 2<supscrpt>19937</supscrpt> −1 and 623-dimensional equidistribution up to 32-bit accuracy, while using a working area of only 624 words. This is a new variant of the previously proposed generators, TGFSR, modified so as to admit a Mersenne-prime period. The characteristic polynomial has many terms. The distribution up to <italic>v</italic> bits accuracy for 1 ≤ <italic>v</italic> ≤ 32 is also shown to be good. An algorithm is also given that checks the primitivity of the characteristic polynomial of MT with computational complexity <italic>O(p<supscrpt>2</supscrpt>)</italic> where <italic>p</italic> is the degree of the polynomial. We implemented this generator in portable C-code. It passed several stringent statistical tests, including diehard. Its speed is comparable to other modern generators. Its merits are due to the efficient algorithms that are unique to polynomial calculations over the two-element field.
SAP HANA database: data management for modern business applications

The SAP HANA database is positioned as the core of the SAP HANA Appliance to support complex business analytical processes in combination with transactionally consistent operational workloads. Within this paper, we outline the basic characteristics of the SAP HANA database, emphasizing the distinctive features that differentiate the SAP HANA database from other classical relational database management systems. On the technical side, the SAP HANA database consists of multiple data processing engines with a distributed query processing environment to provide the full spectrum of data processing -- from classical relational data supporting both row- and column-oriented physical representations in a hybrid engine, to graph and text processing for semi- and unstructured data management within the same system. From a more application-oriented perspective, we outline the specific support provided by the SAP HANA database of multiple domain-specific languages with a built-in set of natively implemented business functions. SQL -- as the lingua franca for relational database systems -- can no longer be considered to meet all requirements of modern applications, which demand the tight interaction with the data management layer. Therefore, the SAP HANA database permits the exchange of application semantics with the underlying data management platform that can be exploited to increase query expressiveness and to reduce the number of individual application-to-database round trips.
Enlarging just noticeable differences of visual-proprioceptive conflict in VR using haptic feedback

Wearable finger-based haptics with cutaneous feedback is promising, as it allows us to duplicate many real-world rich/important tasks that are relying on the dexterity of fingers and hands in the virtual-world. For this system, one of the key challenges is the finger-tracking, which can of course never be perfect, yet, if used in VR (e.g., with HMD), would still be adequate as long as its tracking error is under a certain detection threshold. In this paper, for such wearable finger-based haptics in VR with HMD, via some suitably-designed human subject studies, we aim to quantitatively answer the following questions: 1) what is the detection threshold (i.e., just noticeable difference (JND)) of visual-proprioceptive conflict (i.e., error tolerance of the finger-tracking system in VR); and 2) is it possible to further reduce this visual-proprioceptive conflict by utilizing cutaneous haptic feedback. We believe these results would be useful to determine the design specification of finger-tracking systems for haptic and general VR applications alike.
Web-based knowledge exchange through social links in the workplace

Knowledge exchange between employees is an essential feature of recent commercial organisations on the competitive market. Based on the data gathered by various information technology (IT) systems, social links can be extracted and exploited in knowledge exchange systems of a new kind. Users of such a system ask their queries and the system recommends known and unknown experts selected out of user's friends. The friends either provide the solution or forward the query to their friends. By means of the established social paths to experts, the system facilitates informal learning and exchange of latent knowledge between organisation members in their workplace. The overall concept, limitations and detailed features of this novel knowledge exchange system are discussed in the article.
A Computationally Simple Procedure for Imagery Data Compression by the Karhunen-Loeve Method

Of the several methods that have been proposed for imagery data compression, the Karhunen-Loeve procedure minimizes the meansquare error between the original and reconstructed imagery data. In spite of its optimality property, the Karhunen-Loeve procedure has not been widely used because of its computational complexity. The main difficulty is in the computation of the eigenvectors and the eigenvalues of the covariance matrix of the imagery data since the dimension of the covariance matrix is usually large. A computationally short procedure for calculating the eigenvalues and eigenvectors of the covariance matrix is presented. We show that the eigenvalues and eigenvectors of the N × N bisymmetric covariance matrix can be obtained from the eigenvalues and eigenvectors of two N/2 × N/2 submatrices. Since the eigenvector calculations are proportional to the third power of the matrix dimension, the proposed procedure reduces the computations by a factor of four.
Carbon Cost of Rice on State-Operated Farm in Northeast China Plain

Cropping systems in the future will need to increase grain yield while reducing greenhouse gas emission per unit of production. Based on the investigation data of the farmers production, applying carbon cost model, we conducted the carbon cost of rice on state-operated farm (13 production teams) in Northeast China Plain. The results were as follows: the carbon cost of rice on Shuanghe Farm was 221.62±26.32 gCO2e kg-1, in which irrigation accounted for 40.68%, chemical fertilizer accounted for 24.55%, mechanical operation accounted for 24.35%, seed accounted for 9.21%, and pesticides accounted for 1.20%, respectively. The carbon cost of rice in different production teams were significantly different (P<0.01), and 20th production teams was the highest (249.56±26.68 gCO2e kg-1) while 10th team was the lowest (190.87±17.09 gCO2e kg-1). The differences of the carbon cost of rice among production teams almost was resulted from irrigation, and it had the potentiality of emission reduction in the production teams with higher carbon cost.
The Effects of Amino Acid Composition of Glutamine-Rich Domains on Amyloid Formation and Fragmentation

Fragmentation of amyloid polymers by the chaperone Hsp104 allows them to propagate as prions in yeast. The factors which determine the frequency of fragmentation are unclear, though it is often presumed to depend on the physical strength of prion polymers. Proteins with long polyglutamine stretches represent a tractable model for revealing sequence elements required for polymer fragmentation in yeast, since they form poorly fragmented amyloids. Here we show that interspersion of polyglutamine stretches with various amino acid residues differentially affects the in vivo formation and fragmentation of the respective amyloids. Aromatic residues tyrosine, tryptophan and phenylalanine strongly stimulated polymer fragmentation, leading to the appearance of oligomers as small as dimers. Alanine, methionine, cysteine, serine, threonine and histidine also enhanced fragmentation, while charged residues, proline, glycine and leucine inhibited polymerization. Our data indicate that fragmentation frequency primarily depends on the recognition of fragmentation-promoting residues by Hsp104 and/or its co-chaperones, rather than on the physical stability of polymers. This suggests that differential exposure of such residues to chaperones defines prion variant-specific differences in polymer fragmentation efficiency.
Chairman Characteristics and Earnings Management: Evidence from Chinese Listed Firms

Using a large sample of Chinese listed companies during period from 2005 to 2014, this paper investigates whether the managerial characteristics of Chairman affect earnings management. Using McNichols [1] accrual-based and Roychowdhury [2] real earning management, we find that companies with female, long-tenured, older and more educated Chairman have lower absolute discretionary accruals and lower real earnings management after controlling other factors that prior research has shown to be associated with earnings management. The results suggest that Chinese listed companies can improve earning quality by appointing more female, experienced, and educated chairmen, as well as increasing the tenure of Chairman.
EvoGraphDice: Interactive evolution for visual analytics

Visualization of large and complex datasets is a research challenge, especially in frameworks like industrial design, decision making and visual analytics. Interactive Evolution, used not only as an optimisation tool, but also as an exploration tool may provide some versatile solutions to this challenge. This paper presents an attempt in this direction with the EvoGraphDice prototype, developed on top of GraphDice, a general purpose visualization freeware for multidimensional visualization based on scatterplot matrices. EvoGraphDice interactively evolves compound additional dimensions, that provide new viewpoints on a multidimensional dataset. Compound dimensions are linear combination of terms based on the initial data dimensions, they are initialised with a Principal Component Analysis (PCA), and modified progressively by the interactive evolution process. Various interactions are available to the user, either in a transparent way, via a capture of mouse-clicks, or in a fully controlled manner, where the user has the opportunity to modify or include his own compound dimension in the evolved population, control the search space, or do some interactive queries. EvoGraphDice is tested on a synthetic dataset of dimension 6, where a known dependency is rediscovered via interactive manipulation. A second example is presented, based on a real dataset of dimension 13, provided by an industrial partner. Our experiments prove the potential of this interactive approach, and allow us to sketch future directions of development for the EvoGraphDice prototype.
Motion primitives for human-inspired bipedal robotic locomotion: walking and stair climbing

This paper presents an approach to the development of bipedal robotic control techniques for multiple locomotion behaviors. Insight into the fundamental behaviors of human locomotion is obtained through the examination of experimental human data for walking on flat ground, upstairs and downstairs. Specifically, it is shown that certain outputs of the human, independent of locomotion terrain, can be characterized by a single function, termed the extended canonical human function. Optimized functions of this form are tracked via feedback linearization in simulations of a planar robotic biped walking on flat ground, upstairs and downstairs - these three modes of locomotion are termed “motion primitives. ” A second optimization is presented, which yields controllers that evolve the robot from one motion primitive to another - these modes of locomotion are termed “motion transitions. ” A final simulation is given, which shows the controlled evolution of a robotic biped as it transitions through each mode of locomotion over a pyramidal staircase.
Anti-miR-17 therapy delays tumorigenesis in MYC-driven hepatocellular carcinoma (HCC)

Hepatocellular carcinoma (HCC) remains a significant clinical challenge with few therapeutic options. Genomic amplification and/or overexpression of the MYC oncogene is a common molecular event in HCC, thus making it an attractive target for drug therapy. Unfortunately, currently there are no direct drug therapies against MYC. As an alternative strategy, microRNAs regulated by MYC may be downstream targets for therapeutic blockade. MiR-17 family is a microRNA family transcriptionally regulated by MYC and it is commonly overexpressed in human HCCs. In this study, we performed systemic delivery of a novel lipid nanoparticle (LNP) encapsulating an anti-miR-17 oligonucleotide in a conditional transgenic mouse model of MYC driven HCC. Treatment with anti-miR-17 in vivo, but not with a control anti-miRNA, resulted in significant de-repression of direct targets of miR-17, robust apoptosis, decreased proliferation and led to delayed tumorigenesis in MYC-driven HCCs. Global gene expression profiling revealed engagement of miR-17 target genes and inhibition of key transcriptional programs of MYC, including cell cycle progression and proliferation. Hence, anti-miR-17 is an effective therapy for MYC-driven HCC.
Testing a Model of Physical and Psychological Recovery After a Cardiac Event

Little is known about the specific sources and types of support that assist patients in alleviating stress and achieving positive recovery outcomes after a cardiac event. The purpose of this study is to examine the effects of illness-related stress, emotional and tangible support from a significant other, and informational support from a health care provider on physical and psychological recovery outcomes in cardiac patients 8 weeks after their cardiac event. The sample consists of 220 cardiac patients. Data analysis uses structural equation modeling. Final fit indices were as follows: χ2 (df = 110) = 156.169, comparative fit index = . 963, Tucker—Lewis index = . 949, and root mean square error of approximation = . 044 suggesting an acceptable model. Illness-related stress has direct effects on depression, physical recovery, and activity levels. Partner emotional support has a direct effect on depression. The findings provide direction for developing social support interventions aimed at improving recovery outcomes.
Amplification and Attenuation Across USArray Using Ambient Noise Wavefront Tracking

As seismic traveltime tomography continues to be refined using data from the vast USArray data set, it is advantageous to also exploit the amplitude information carried by seismic waves. We use ambient noise cross correlation to make observations of surface wave amplification and attenuation at shorter periods (8–32 s) than can be observed with only traditional teleseismic earthquake sources. We show that the wavefront tracking approach can be successfully applied to ambient noise correlations, yielding results quite similar to those from earthquake observations at periods of overlap. This consistency indicates that the wavefront tracking approach is viable for use with ambient noise correlations, despite concerns of the inhomogeneous and unknown distribution of noise sources. The resulting amplification and attenuation maps correlate well with known tectonic and crustal structure; at the shortest periods, our amplification and attenuation maps correlate well with surface geology and known sedimentary basins, while our longest period amplitudes are controlled by crustal thickness and begin to probe upper mantle materials. These amplification and attenuation observations are sensitive to crustal materials in different ways than traveltime observations and may be used to better constrain temperature or density variations. We also value them as an independent means of describing the lateral variability of observed Rayleigh wave amplitudes without the need for 3‐D tomographic inversions.