Miracle-dz/UniFAR-FTUs huggingface dataset:
Unveiling secrets of successful Chinese software companies

There are secrets and business of successful software companies explained by Hoch in 2000 and Cusumano in 2004, but there existed none cases from China. This occurred maybe the Chinese software companies are in infancy and the survey is challenge in China. However, the software industry plays an important role in innovation and pushing the economical transformation in China economics. So, in this work, we first archived and abstracted the success experiences from the international software companies. Next to setup a criteria to define the successful Chinese software companies (SCSCs) in China and got the materials and data through the telephone survey, interviewing, searching the professional magazines and reviewing the documents of some companies. More, to pigeonholing the data and finding the characteristics that led to success and comparing the characteristics with the international ones. The results showed that SCSCs verified the international characteristics, and displayed some special characteristics that distinguished the SCSC with the international ones. The special characteristics listed as follows. First, the entrepreneurs own the power to find the market space and could provide the high aptness, compact function and high quality product. Second, SCSCs owned the intellectual property rights independently of product, product-type company not service-type company gradually developed into SCSCs. Third the SCSCs usually originated from the middle and low range market, this is representative road that produced SCSCs. Fourth, the founder acts as the leader of the company unremittingly up to now, and control the strategy that decided the fate on the crisis of transformation which make the company stride forward to the Ruritania of the founders. Fifth, make the business on the robust status that to avoid the big variation. Sixth, the core business is prominent and professional.
Behavioral Neuroscience

pathophysiological mechanism for PTSD that surveyed studies of both pharmacological manipulations and non-pharmacological stress challenges concluded that there was insuffi cient evidence to support any of the models advanced so far to implicate HPA axis dysfunction in PTSD (de Kloet et al., 2006). A mechanistic possibility that has received relatively little investigative attention is hyposensitivity to adrenocorticotropin (ACTH) at the level of the adrenal cortex, which could explain both subnormal circulating cortisol concentrations and compensatory upregulation of CNS corticotropin-releasing factor (Kanter et al., 2001). However, Rasmusson et al. (2001) found that patients with PTSD produce more cortisol in response to the standard clinical 250 µg ACTH stimulation test than controls. The supraphysiologi-cal dose of ACTH used in this test, which was designed to be a clinical indicator of adrenal insuffi ciency, provides an index of the adrenal's maximal secretory capability, but is of very limited value in gauging the responsiveness of the adrenal to submaximal, physiological concentrations of ACTH. Therefore, to examine adrenocortical responsiveness to physiological stimulation in PTSD patients, we performed a pilot study to determine doses of ACTH that would stimulate a low to moderate cortisol response and one that would refl ect a high level of stress but remain within the physiological range. On the basis of the pilot study we administered placebo and two doses of ACTH (1.5 and 7.5 ng/kg body weight) to PTSD patients and control participants. We hypothesized that in response to administration of low dose exogenous ACTH, cortisol concentrations of PTSD
Research Note - A Contingency Approach to Investigating the Effects of User-System Interaction Modes of Online Decision Aids

Interactive online decision aids often employ user-decision aid dialogues as forms of user-system interaction to help construct and elicit users’ attribute preferences about a product type. This study extends prior research on online decision aids by investigating the effects of a decision aid’s user-system interaction mode (USIM), which can be either user-guided or system-controlled, on users’ effort-related (number of iterations of using the aid and perceived cognitive effort expended in using it) and quality-related (perceived quality of the aid and acceptance of the product advice it provides) assessments. A contingency approach with two moderating factors is employed. One factor is the decision strategy (additive-compensatory or elimination) employed by the aid, and the other is the users’ product knowledge (high or low). A laboratory experiment was conducted to compare online decision aids with different USIMs. Although the results largely confirm that users assess the user-guided USIM more positively than the system-controlled USIM, the effects of USIM are stronger in two settings: for the elimination-based aid than for the additivecompensatory-based aid and for users with low product knowledge than for those with high product knowledge, especially in terms of effort assessments. This research advances the theoretical understanding of the effects of interaction between two critical components of online decision aids (USIMs and decision strategies) and the moderating role of user characteristics (product knowledge) in affecting users’ evaluations. It also provides practitioners with design advice for developing these aids.
Block compressive channel estimation and feedback for FDD massive MIMO

Channel state information (CSI) at the base station (BS) is required to fully exploit the advantages of massive MIMO. However, due to massive BS antennas, the estimation and feedback of downlink CSI are very challenging in frequency division duplexing (FDD) massive MIMO. This paper proposes a block compressive channel estimation and feedback scheme for FDD massive MIMO, which can reduce the overhead for CSI acquisition substantially. Specifically, we first propose the non-orthogonal pilots, which is essentially different from conventional orthogonal pilots. Then, a block orthogonal matching pursuit (BOMP) algorithm is proposed to estimate CSI according to the feedback signal from users, where the analog channel feedback is adopted, and the spatial common sparsity of time-domain massive MIMO channels is exploited to reduce the overhead for CSI acquisition. Moreover, we exploit the temporal common sparsity of channels to estimate channels with reduced complexity. Simulation results demonstrate that the proposed scheme with significantly reduced CSI acquisition overhead can approach the performance bound.
Slow oscillating transcranial direct current stimulation during sleep has a sleep‐stabilizing effect in chronic insomnia: a pilot study

Recent evidence suggests that lack of slow‐wave activity may play a fundamental role in the pathogenesis of insomnia. Pharmacological approaches and brain stimulation techniques have recently offered solutions for increasing slow‐wave activity during sleep. We used slow (0.75 Hz) oscillatory transcranial direct current stimulation during stage 2 of non‐rapid eye movement sleeping insomnia patients for resonating their brain waves to the frequency of sleep slow‐wave. Six patients diagnosed with either sleep maintenance or non‐restorative sleep insomnia entered the study. After 1 night of adaptation and 1 night of baseline polysomnography, patients randomly received sham or real stimulation on the third and fourth night of the experiment. Our preliminary results show that after termination of stimulations (sham or real), slow oscillatory transcranial direct current stimulation increased the duration of stage 3 of non‐rapid eye movement sleep by 33 ± 26 min (P = 0.026), and decreased stage 1 of non‐rapid eye movement sleep duration by 22 ± 17.7 min (P = 0.028), compared with sham. Slow oscillatory transcranial direct current stimulation decreased stage 1 of non‐rapid eye movement sleep and wake time after sleep‐onset durations, together, by 55.4 ± 51 min (P = 0.045). Slow oscillatory transcranial direct current stimulation also increased sleep efficiency by 9 ± 7% (P = 0.026), and probability of transition from stage 2 to stage 3 of non‐rapid eye movement sleep by 20 ± 17.8% (P = 0.04). Meanwhile, slow oscillatory transcranial direct current stimulation decreased transitions from stage 2 of non‐rapid eye movement sleep to wake by 12 ± 6.7% (P = 0.007). Our preliminary results suggest a sleep‐stabilizing role for the intervention, which may mimic the effect of sleep slow‐wave‐enhancing drugs.
Variants of Courcelle ’ s Theorem for Complexity Classes inside

Monadic Second-Order Logic (MSO) expresses many natural NP Complete problems as well as problems complete for all levels of the Polynomial-Time Hierarchy. Thus, it was surprising when Bruno Courcelle proved that for inputs of any fixed tree width, all MSO properties are checkable in linear time [Courcelle 1990]. Recently, Michael Elberfeld and his coauthors have refined Courcelle’s Theorem in several striking ways. In particular, they have characterized the complexity of the relevant decision, optimization and counting problems, for structures of bounded tree width as well as for more restricted inputs. All of these problems are inside deterministic logspace, L. Some of them are complete for L, and others live in a variety of smaller classes inside L. Elberfeld explains these ground-breaking results in the following clear and highlevel exposition.
Role of the avian retrovirus mRNA leader in expression: evidence for novel translational control

Avian retroviral mRNAs contain a long 5' untranslated leader of approximately 380 nucleotides. The leader includes sequences required for viral replication and three AUG codons which precede the AUG codon used for translational initiation of the gag and env genes. We have used sensitive, quantitative assays of viral gene transcription and translation to analyze the role of this mRNA leader in viral gene expression. By substituting segments from related viruses, we had previously shown that the endogenous avian provirus ev-1 contained a defective leader segment (B. R. Cullen, A. M. Skalka, and G. Ju, Proc. Natl. Acad. Sci. USA 80:2946-2950, 1983). The sequence analysis presented here, followed by comparison with the nondefective ev-2 endogenous provirus segment, identified the critical changes at nucleotides 4 and 7 upstream of the initiator AUG. These differences do not alter the most conserved nucleotides within the consensus sequence which precedes eucaryotic initiation codons, but lie within a nine-nucleotide region that is otherwise highly conserved among avian retrovirus strains. Analysis of a series of deletion mutants indicated that other sequences within the leader are also required for efficient expression. Characterization of the altered transcripts demonstrated that the presence of the defective ev-1 segment or the deletion of a ca. 200-nucleotide leader segment did not affect the steady-state level or splicing efficiency of these mRNAs. Thus, we conclude that the reduced expression of these mRNAs is due to a translational deficiency. These results indicate that specific leader sequences, other than the previously identified consensus nucleotides which precede eucaryotic AUG initiator codons, can influence eucaryotic gene translation.
Bayesian optimization for conditional hyperparameter spaces

Hyperparameter optimization is now widely applied to tune the hyperparameters of learning algorithms. The hyperparameters can have structure, resulting in hyperparameters depending on conditions, or on the values of other hyperparameters. We target the problem of combined algorithm selection and hyperparameter optimization, which includes at least one conditional hyperparameter: the choice of the learning algorithm. In this work, we show that Bayesian optimization with Gaussian processes can be used for the optimization of conditional spaces with the injection of knowledge concerning conditions in the kernel. We propose and examine the behavior of two kernels, a conditional kernel which forces the similarity of two samples from different condition branches to be zero, and the Laplace kernel, based on similarities with Mondrian processes and random forests. We show the benefit of using such kernels, as well as proper imputation of inactive hyperparameters, on a benchmark of scikit-learn models.
Defective smooth muscle development in qkI‐deficient mice

The qkI gene encodes an RNA binding protein which was identified as a candidate for the classical neurologic mutation, qkv. Although qkI is involved in glial cell differentiation in mice, qkI homologues in other species play important roles in various developmental processes. Here, we show a novel function of qkI in smooth muscle cell differentiation during embryonic blood vessel formation. qkI null embryos died between embryonic day 9.5 and 10.5. Embryonic day 9.5 qkI null embryos showed a lack of large vitelline vessels in the yolk sacs, kinky neural tubes, pericardial effusion, open neural tubes and incomplete embryonic turning. Using X‐gal and immunohistochemical staining, qkI is first shown to be expressed in endothelial cells and smooth muscle cells. Analyses of qkI null embryos in vivo and in vitro revealed that the vitelline artery was too thin to connect properly to the yolk sac, thereby preventing remodeling of the yolk sac vasculature, and that the vitelline vessel was deficient in smooth muscle cells. Addition of QKI and platelet‐endothelial cell adhesion molecule‐1 positive cells to an in vitro para‐aortic splanchnopleural culture of qkI null embryos rescued the vascular remodeling deficit. These data suggest that QKI protein has a critical regulatory role in smooth muscle cell development, and that smooth muscle cells play an important role in inducing vascular remodeling.
The Theory of Intervention Games for Resource Sharing in Wireless Communications

This paper develops a game-theoretic framework for the design and analysis of a new class of incentive schemes called intervention schemes. We formulate intervention games, propose a solution concept of intervention equilibrium, and prove its existence in a finite intervention game. We apply our framework to resource sharing scenarios in wireless communications, whose non-cooperative outcomes without intervention yield suboptimal performance. We derive analytical results and analyze illustrative examples in the cases of imperfect and perfect monitoring. In the case of imperfect monitoring, intervention schemes can improve the suboptimal performance of non-cooperative equilibrium when the intervention device has a sufficiently accurate monitoring technology, although it may not be possible to achieve the best feasible performance. In the case of perfect monitoring, the best feasible performance can be obtained with an intervention scheme when the intervention device has a sufficiently strong intervention capability.
A Novel Rehabilitation System for Upper Limbs

Rehabilitation system for upper limbs is the device of implementing rehabilitation for patients' wounded limbs instead of therapists. According to review the development of rehabilitation system, we find some deficiencies such as insufficient movement space, few exact evaluations for impairment, and inadequate support for serious hemiplegia. Aiming at these problems, a novel rehabilitation system for upper limbs based on sEMG (surface electromyographic) signal is developed. The proposed system imitates human arm movements and can implement space motion because of its 5 DOF. As a diagnostic tool, the system is introduced sEMG, which is considered as the main basis of evaluation for motor function impairment. Software is developed to analyze sEMG signal during the movements to obtain valid characteristic parameters with time-, frequency-, and time-frequency-domain analytical methods. These parameters are associated with those of other sensor signals such as joint torque, joint angle, and force to quantify motor function injury. As a therapeutic tool, it can provide effective plans based on the parameters mentioned above. During the course of exercises, changes of each sensor signal and their characteristic parameters can be detected and monitored on the intuitive software interface, which can guide the device to carry out trainings. It provides a good platform for researching of sEMG signal and provides a new path for clinic hemiplegia upper limb therapy
Online contact point estimation for uncalibrated tool use

One of the big challenges for robots working outside of traditional industrial settings is the ability to robustly and flexibly grasp and manipulate tools for various tasks. When a tool is interacting with another object during task execution, several problems arise: a tool can be partially or completely occluded from the robot's view, it can slip or shift in the robot's hand - thus, the robot may lose the information about the exact position of the tool in the hand. Thus, there is a need for online calibration and/or recalibration of the tool. In this paper, we present a model-free online tool-tip calibration method that uses force/torque measurements and an adaptive estimation scheme to estimate the point of contact between a tool and the environment. An adaptive force control component guarantees that interaction forces are limited even before the contact point estimate has converged. We also show how to simultaneously estimate the location and normal direction of the surface being touched by the tool-tip as the contact point is estimated. The stability of the the overall scheme and the convergence of the estimated parameters are theoretically proven and the performance is evaluated in experiments on a real robot.
Cluster-based one-class ensemble for classification problems in information retrieval

A number of relevant information retrieval classification problems are one-class classification problems at heart. I.e., labeled data is only available for one class, the so-called target class, and common discrimination-based classification approaches, be them binary or multiclass, are not applicable. Achieving a high effectiveness when solving one-class problems is difficult anyway and it becomes even more challenging when the target class data is multimodal, which is often the case. To address these concerns we propose a cluster-based one-class ensemble that consists of four steps: (1) applying a clustering algorithm to the target class data, (2) training an individual one-class classifier for each of the identified clusters, (3) aggregating the decisions of the individual classifiers, and (4) selecting the best fitting clustering model. We evaluate our approach with four datasets: an artificially generated dataset, a dataset compiled from a known multiclass text corpus, and two datasets related to one-class problems that received much attention recently, namely authorship verification and quality flaw prediction. Our approach outperforms a one-class SVM on all four datasets.
Social immunity in honeybees (Apis mellifera): transcriptome analysis of varroa‐hygienic behaviour

Honeybees have evolved a social immunity consisting of the cooperation of individuals to decrease disease in the hive. We identified a set of genes involved in this social immunity by analysing the brain transcriptome of highly varroa‐hygienic bees, who efficiently detect and remove brood infected with the Varroa destructor mite. The function of these candidate genes does not seem to support a higher olfactory sensitivity in hygienic bees, as previously hypothesized. However, comparing their genomic profile with those from other behaviours suggests a link with brood care and the highly varroa‐hygienic Africanized honeybees. These results represent a first step toward the identification of genes involved in social immunity and thus provide first insights into the evolution of social immunity.
Prevalence and predictors of ventricular remodeling after anterior myocardial infarction in the era of modern medical therapy

Summary Background The consequences of aggressive therapy following a myocardial infarction (MI) on ventricular remodeling are not well established. Thus, the objective of this study was to analyze the prevalence, clinical characteristics, and predictors of left ventricular remodeling in the era of modern medical therapy. Material/Methods Clinical characteristics and echocardiographic data were analyzed in 66 consecutive patients with anterior infarction at admission and at 6-month follow-up. Ventricular remodeling was defined as an increase of 10% in ventricular end-systolic or end-diastolic diameter. Results In our study, 58% of patients presented with ventricular remodeling. Patients with remodeling possessed higher total plasma creatine kinase (CPK), MB-fraction (CPK-MB), heart rate, heart failure, shortness of breath, and reperfusion therapy than patients without remodeling. In contrast, patients with remodeling had a smaller ejection fraction, E-Wave deceleration time (EDT), and early (E′ Wave) and late (A′ Wave) diastolic mitral annulus velocity (average of septal and lateral walls), but a higher E/E′ than patients without remodeling. Patients with remodeling used more diuretics, digoxin, oral anticoagulants and aldosterone antagonists than patients without remodeling. In the multivariate analyses, only E′ Wave was an independent predictor of ventricular remodeling. Each 1 unit increase in the E′ Wave was associated with a 59% increased odds of ventricular remodeling. Conclusions In patients with anterior MI, despite contemporary treatment, ventricular remodeling is still a common event. In addition, diastolic function can have an important role as a predictor of remodeling in this scenario.
Iterative PLDA Adaptation for Speaker Diarization

This paper investigates iterative PLDA adaptation for cross-show speaker diarization applied to small collections of French TV archives based on an i-vector framework. Using the target collection itself for unsupervised adaptation, PLDA parameters are iteratively tuned while score normalization is applied for convergence. Performances are compared, using combinations of target and external data for training and adaptation. The experiments on two distinct target corpora show that the proposed framework can gradually improve an existing system trained on external annotated data. Such results indicate that performing speaker diarization on small collections of unlabeled audio archives should only rely on the availability of a sufficient boot-strap system, which can be incrementally adapted to every target collection. The proposed framework also widens the range of acceptable speaker clustering thresholds for a given performance objective.
Program Transformation Mechanics. A Classification of Mechanisms for Program Transformation with a Survey of Existing Transformation Systems

Transformation techniques are spreading from application in compilers to general use in generative programming and document processing. Since transformation requires operations such as pattern matching, generic structure traversal, and querying, which are not normally provided by general-purpose programming languages, many tools have been developed to provide higher-level support for the implementation of transformations. These tools come in many flavors each with their own merits and based on different paradigms, which makes comparison difficult. In this paper, we consider transformation from the point of view of mechanics and develop a classification of transformation mechanisms that provides a reference for comparing tools developed for different applications, using different implementations, and in different programming paradigms. To do so we distinguish three fundamental aspects of transformation mechanisms: scope, direction, and stages. We apply this classification in a discussion of design patterns for transformation, characterization of several typical transformations, and a systematic comparison of eleven representative transformation tools.