Miracle-dz/UniFAR-FTUs huggingface dataset:
The knowledge value chain as an SME innovation policy instrument framework: an analytical exploration of SMEs public innovation support in OECD countries

Innovation policy instruments in OECD countries are developed from different streams of policies related to the suppliers and the users of knowledge. They are also integrated into different levels of implementation (supranational, national, regional and local). Such complexity leads policy actors and stakeholders to experience a lack of coordination in their innovation efforts. This paper, based on a broad cross-country analysis of 844 innovation policy instruments implemented in 27 OECD countries, aims to contribute to the advancement of knowledge on this issue by: 1 validating a conceptual framework as a tool of policy instrument coordination 2 conducting an innovation policy instrument framework based both on the conceptual framework and a on diversity of instruments. The innovation policy instrument framework has been devised to be used as a roadmap to link innovation policy instruments and innovation functions.
An Adaptive Sequence Approach for OOS Test Case Prioritization

Test case prioritization (TCP) attempts to improve fault detection effectiveness by scheduling important test cases earlier, where important is determined by some criteria and strategy. Adaptive random sequences (ARSs) may be applied to improve the effectiveness of TCP in black-box testing. In this paper, to improve the effectiveness of TCP for object-oriented software, we present an ARS approach based on clustering techniques. In the proposed approach, test cases are clustered according to the number of objects and methods, using two clustering algorithms – K-means and K-medoids. Our proposed sampling strategy can construct ARSs within the clustering framework, constructing two ARS sequences based on the two clustering algorithms, which results in generated test cases with different execution sequences. We also report on experimental studies to verify the proposed approach, with the results showing that our approach can enhance the probability of earlier fault detection, and deliver higher effectiveness than random prioritization.
The Correlation between Age, Body Weight and Testicular Parameters in Murrah Buffalo Bulls Raised in Brazil

Abstract Buffalo are an economically important source for meat and milk production, especially in Brazil. However, important aspects of their biology remain unknown thus far. Herein, we describe the reproductive characteristics of male Murrah buffalo (Bubalus bubalis) raised under extensive management conditions by applying biometrics associated with testicular weight. We analyzed seven males, divided into two groups: G1, which consisted of four 18-month-old animals, and G2, which consisted of three 24-month-old animals. Testicular development occurs slowly in Murrah buffalo, suggesting a delay of sexual maturity. The biometric testicular parameters analyzed were scrotal circumference, testicular weight, testicular length, testicular width, testicular thickness and testicular circumference. Our data indicate strong correlations between SC, age and body weight, and additional significant relationships were identified between body weight, age and other testicular parameters. Thus, these parameters are suitable indicators when selecting bulls for breeding purposes.
Culture and Development of Self-Regulation

In the present paper, I aim to both contribute to a culture based theory of self regulation and clarify some mutually constitutive functions of psychological and sociocultural phenomena. I examine the relations between self and culture and the role of these relations in the develop ment of self regulation. Self regulation is based on the intention to modify internal processes and behavior to reach one’s goals. Because the development of self regulation is embedded in a cultural context that gives priority to a specific model of agency, processes of self regulation are assumed to differ cross culturally. First, I give a brief overview on self regulation research. Fur ther, I discuss the contribution of a culture informed perspective to the study of self regulation and its development, taking into account interpersonal self regulation. Finally, I present a ‘Cul tural Model of Agency and Self Regulation,’ which suggests how to link culture and individual agency. Self regulation has recently become a debated topic in other disciplines such as behavior economics and sociology. In behavior economics, researchers have regarded delay of gratification or the regulation of risk taking behavior as preconditions for rational behav ior. In psychology, self regulation is usually conceived of as a complex, universal human ability that structures goal directed behavior and increases the likelihood of fulfilling a variety of individual needs. This and individual differences in self regulation underline the necessity to investigate its components, its developmental conditions, and its activa tion in different contexts. Although investigators have long noted that standards for self regulation and related strategies differ for people from different cultural backgrounds (e.g., Eisenberg & Zhou, 2000), researchers have neglected the role of culture in most studies on self regulation. In only a few studies have researchers investigated the relations between the individual person (self system) and culture (sociocultural system), and how these relations become effective in the development of self regulation. In line with culture psychological studies on socialization, I assume here that the dominant cultural values and goals and the related cultural model of agency affect socialization conditions for the child and the respective developmental outcomes for self regulation. The trans mission and development of self regulation in the socialization of children is fostered by internalization processes (Tomasello, Carpenter, Call, Behne, & Moll, 2005). According to Grusec and Goodnow (1994), the internalization process is based on a positive parent–child relationship. The expectations of significant others become part of the child’s own personal value system, especially when the other persons belong to the child’s in group (Trommsdorff, 2009). The child’s internalization of social norms and of perceived expectations of others who are close develops into a self regulatory system fostering cultural fit.
Secret Image Sharing Based on Error-Correcting Codes

In traditional (k, n) threshold secret image sharing (SIS), a secret image is encrypted into n shadow images (also called shares) distributed to n associated participants. The secret image can be recovered by collecting any k or more shadow images, i.e., SIS is loss-tolerant. In SIS research domain, visual cryptography scheme (VCS) also called visual secret sharing (VSS) and Shamir's polynomial-based SIS scheme are the primary branches. Whereas, VCS mainly focuses on lossy recovery for binary secret image with pixel expansion, and most Shamir's polynomial-based SIS is not directly lossless. In this paper, we propose a SIS scheme based on error-correcting codes. Error-correcting code has the features of loss-tolerant and lossless recovery due to it has the strict mathematical relations of information values and check values, which has been widely used in signal communications. The loss-tolerant and lossless recovery features of error-correcting codes are utilized in the proposed scheme to achieve (k, n) threshold SIS with really lossless recovery. In addition, in the proposed scheme the size of each shadow image is smaller than the size of the original secret image. Experiments are conducted to evaluate the efficiency of the proposed scheme.
Dancelets Mining for Video Recommendation Based on Dance Styles

Dance is a unique and meaningful type of human expression, composed of abundant and various action elements. However, existing methods based on associated texts and spatial visual features have difficulty capturing the highly articulated motion patterns. To overcome this limitation, we propose to take advantage of the intrinsic motion information in dance videos to solve the video recommendation problem. We present a novel system that recommends dance videos based on a mid-level action representation, termed Dancelets. The Dancelets are used to bridge the semantic gap between video content and high-level concept, dance style, which plays a significant role in characterizing different types of dances. The proposed method executes automatic mining of dancelets with a concatenation of normalized cut clustering and linear discriminant analysis. This ensures that the discovered dancelets are both representative and discriminative. Additionally, to exploit the motion cues in videos, we employ motion boundaries as saliency priors to generate volumes of interest and extract C3D features to capture spatiotemporal information from the mid-level patches. Extensive experiments validated on our proposed large dance dataset, HIT Dances dataset, demonstrate the effectiveness of the proposed methods for dance style-based video recommendation.
Intracellular delivery of siRNA by cell-penetrating peptides modified with cationic oligopeptides

To achieve the effective intracellular delivery of siRNA and silence specific genes, various types of conjugates between cell-penetrating peptides (CPPs; Transportan, Penetratin, Tat) and cationic peptides were developed. Uptake, intracellular localization, cytotoxicity, and biological activity of siRNA were significantly dependent on the kind of CPP used and the length of the cationic peptides in the conjugate. Transportan-based conjugates yielded both high internalization of siRNA and strong gene silencing activity, while Penetratin- and Tat-based conjugates did not. These different properties of CPPs emphasize the importance of careful peptide selection and design when attempting the application of CPP technology.
A Framework for Multi-Core Implementations of Divide and Conquer Algorithms and its Application to the Convex Hull Problem

We present a framework for multi-core implementations of divide and conquer algorithms and show its efficiency and ease of use by applying it to the fundamental geometric problem of computing the convex hull of a point set. We concentrate on the Quickhull algorithm introduced in [2]. In general the framework can easily be used for any D&C-algorithm. It is only required that the algorithm is implemented by a C++ class implementing the job-interface introduced in section 3 of this paper.
DC bus voltage control in four-wire Shunt Active Power Filters with split capacitor

This paper shows an algorithm to control the DC bus voltage of a Shunt Active Power Filter (SAPF), based on the performance of the Proportional Integral (PI) controller. The power converter topology corresponds to a four-wire three-leg Voltage Source Inverter (VSI) with split capacitor. The algorithm is focused on the voltage control for each capacitor, such that the dc-voltages follow a reference level in order to guarantee both the active filter controllability and the balance in the distribution of the DC bus voltage. The algorithm performance is evaluated through some simulations in ATP. Finally, the algorithm effectiveness is shown when it is used to control a SAPF that compensates distorted and unbalanced currents.
Knowledge Representation, Reasoning and Declarative Problem Solving

Knowledge management and knowledge-based intelligence are areas of importance in today's economy and society, and their exploitation requires representation via the development of a declarative interface whose input language is based on logic. Chitta Baral demonstrates how to write programs that behave intelligently by giving them the ability to express knowledge and reason about it. He presents a language, AnsProlog, for both knowledge representation and reasoning, and declarative problem solving. Many of the results have never appeared before in book form but are organized here for those wishing to learn more about the subject, either in courses or through self-study.
Empowering Device-to-Device Networks with Cross-Link Interference Management

Device-to-device (D2D) communications is an emerging service model that is currently under standardization by 3GPP. While D2D offloading has a great potential to relieve increasingly congested cellular networks, its benefits, however, come at a cost, namely interference. Most of the prevailing D2D designs conservatively avoid interference via either spectrum resource allocation or power control. These designs, however, do not exploit spatial degrees of freedom (DoF), which are inherently supported by multi-antenna devices. In this work, we present <inline-formula> <tex-math notation="LaTeX">$\sf {MD2D}$</tex-math><alternatives><inline-graphic xlink:href="lin-ieq1-2582169.gif"/> </alternatives></inline-formula>, a multiuser D2D system that embraces concurrent D2D transmissions, while leveraging MIMO techniques to actively eliminate interference across D2D pairs. <inline-formula><tex-math notation="LaTeX"> $\sf{MD2D}$</tex-math><alternatives><inline-graphic xlink:href="lin-ieq2-2582169.gif"/></alternatives></inline-formula> has a systematic methodology that checks whether the antenna combination in a D2D network is capable of eliminating cross-pair interference and, thereby, ensuring interference-free concurrent transmissions. If the interference can be eliminated, then <inline-formula><tex-math notation="LaTeX">$\sf{MD2D}$</tex-math><alternatives> <inline-graphic xlink:href="lin-ieq3-2582169.gif"/></alternatives></inline-formula> applies a <italic>bucket-based DoF assignment algorithm</italic> to determine an effective antenna usage configuration that handles the interference. We evaluate our design via testbed experiments and large-scale simulations. The results show that, as compared to the traditional interference avoidance scheme, <inline-formula><tex-math notation="LaTeX">$\sf{MD2D}$</tex-math> <alternatives><inline-graphic xlink:href="lin-ieq4-2582169.gif"/></alternatives></inline-formula> improves the throughput by 87.39 and 218.84 percent in a three-pair testbed and in large-scale simulations, respectively.
Immunoradiometric Assay (IRMA) for Human Follicle Stimulating Hormone (FSH) and Luteinizing Hormone (LH) Using Common Avidin Solid Phase

Abstract This paper describes the use of avidin-biotin interaction as an affinity system, wherein avidin immobilized magnetizable particles (cellulose) are used as a common separation system in immunoradiometric assay (IRMA) for hormones of the human reproductive system, human follicle stimulating hormone (FSH), and luteinizing hormone (LH). Biotinylated probe was prepared by biotinylation of specific monoclonal antibody for respective antigen using the caproyl derivative of biotin N-hydroxysuccinimide. The detector antibody for the respective antigen was radiolabelled with 125I by a chloramine-T oxidation method and purified by gel filtration. In the IRMA procedure, standard/sample, respective biotinylated, and radiolabelled antibody as a single reagent, and avidin solid phase were added simultaneously to the assay tubes. After incubation for 3 h with shaking, the bound complex was quantitated for its radioactivity associated with the common avidin solid phase. Results showed that the developed assay protocol is applicable to IRMA of FSH and LH with good precision (intra and inter assay CV less than 8% and 11%, respectively), good assay range (0–200 mIU/mL) and analytical recovery (87–110%). The assay could detect 0.5 mIU/mL and 0.9 mIU/mL of FSH and LH, respectively, and showed good correlation with commercially available kits (FSH y = 0.98x + 0.21 and LH y = 0.99x + 0.18).
Consistent integration between object oriented and coloured petri nets models

Unified Modeling Language (UML) is easier to understand and communicate using graphical notations, but lacks techniques for model validation and verification especially if these diagrams are updated. Formal approaches like Coloured Petri Nets (CPNs) are based on strong mathematical notations and proofs as basis for executable modeling languages. Transforming UML diagrams to executable models that are ready for analysis is significant, and providing an automated technique that can transform these diagrams to a mathematical model such as CPNs avoids the redundancy of writing specifications. The use of UML diagrams in modeling Object Oriented Diagrams (OODs) leads to a large number of interdependent diagrams. It is necessary to preserve the diagrams consistency since they are updated continuously. This research proposes a new structure for the mutual integration between OODs and CPNs modeling languages to support model changes, the proposed integration suggest a new structure (Object Oriented Coloured Petri Nets (OOCPN)) to include set of rules to check and maintain the consistency and integrity of the OOCPN model based on OODs relations.
Compensation and Malingering in Traumatic Brain Injury: A Dose-Response Relationship?

The purpose of this study was to determine if there is a dose-response relationship between potential monetary compensation and failure on psychological indicators of malingering in traumatic brain injury. 332 traumatic brain injury patients were divided into three groups based on incentive to perform poorly on neuropsychological testing: no incentive; limited incentive as provided by State law; high incentive as provided by Federal law. The rate of failure on five well-validated malingering indicators across these groups was examined. Cases handled under Federal workers compensation laws showed considerably higher rates of failure and diagnosable malingering than cases handled under State law. The findings indicate that monetary compensation associated with workers compensation claims is a major motive for exaggeration and malingering of problems attributed to work-related brain injuries. The clinician's index of suspicion regarding exaggeration and malingering of symptoms and deficits should be much higher in the context of Federal workers compensation claims, particularly in patients who have suffered only mild traumatic brain injury.
The effects of continuous positive airway pressure therapy on mean platelet volume in patients with obstructive sleep apnea

Previous studies have reported increased platelet activation and aggregation in patients with obstructive sleep apnea (OSA). Continuous positive airway pressure (CPAP) treatment has been shown to decrease platelet activation. We aimed to study the effects of nasal CPAP therapy has on MPV values in patients with severe OSA. Thirty-one patients (21 men; mean age 53.8 ± 9.2 years) with severe OSA (AHI > 30 events/hour) constituted the study group. An age, gender and body mass index (BMI) matched control group was composed 25 subjects (14 men; mean age 49.6 ± 8.5 years) without OSA (AHI < 5 events/hour). We measured MPV values in patients with severe OSA and control subjects and we measured MPV values after 6 months of CPAP therapy in severe OS patients. The median (IQR) MPV values were significantly higher in patients with severe OSA than in control group (8.5 [8.3–9.1] vs. 8.3 [7.5–8.8] fL; p = 0.03). The platelet counts were significantly lower in patients with severe OSA than in control group (217.8 ± 45.9 vs. 265.4 ± 64.0 × 109/L; p = 0.002). The six months of CPAP therapy caused significant reductions in median (IQR) MPV values in patients with severe OSA (8.5 [8.3–9.1] to 7.9 [7.4–8.2] fL; p < 0.001). Six months of CPAP therapy caused significant increase in platelet counts when compared with baseline values (217.8 ± 45.9 to 233.7 ± 60.6 × 109/L; p < 0.001). We have found that the MPV values of patients with severe OSA were significantly higher than those of the control subjects and 6 months CPAP therapy caused significant reductions in the MPV values in patients with severe OSA.
Structural vulnerability assessment of electric power grids

Cascading failures are the typical reasons of blackouts in power grids. The grid topology plays an important role in determining the dynamics of cascading failures in power grids. Measures for vulnerability analysis are crucial to assure a higher level of robustness of power grids. Metrics from Complex Networks are widely used to investigate the grid vulnerability. Yet, these purely topological metrics fail to capture the real behaviour of power grids. This paper proposes a metric, the effective graph resistance, as a vulnerability measure to determine the critical components in a power grid. Differently than the existing purely topological measures, the effective graph resistance accounts for the electrical properties of power grids such as power flow allocation according to Kirchoff laws. To demonstrate the applicability of the effective graph resistance, a quantitative vulnerability assessment of the IEEE 118 buses power system is performed. The simulation results verify the effectiveness of the effective graph resistance to identify the critical transmission lines in a power grid.
Using colour features to block dubious images

This paper describes a vision system that classifies web-images containing people. It works by identifying skin-coloured regions, extracting very simple features from these regions and making a classification decision. A two-stage skin filtering algorithm using likelihood matrices in HSV space followed by some local clustering works well. Our conclusion is that a simple approach using low-level features can work as well as much more complicated methods.
G-OLA: Generalized On-Line Aggregation for Interactive Analysis on Big Data

Nearly 15 years ago, Hellerstein, Haas and Wang proposed online aggregation (OLA), a technique that allows users to (1) observe the progress of a query by showing iteratively refined approximate answers, and (2) stop the query execution once its result achieves the desired accuracy. In this demonstration, we present G-OLA, a novel mini-batch execution model that generalizes OLA to support general OLAP queries with arbitrarily nested aggregates using efficient delta maintenance techniques. We have implemented G-OLA in FluoDB, a parallel online query execution framework that is built on top of the Spark cluster computing framework that can scale to massive data sets. We will demonstrate FluoDB on a cluster of 100 machines processing roughly 10TB of real-world session logs from a video-sharing website. Using an ad optimization and an A/B testing based scenario, we will enable users to perform real-time data analysis via web-based query consoles and dashboards.
Understanding Data Retrieval Practices: A Social Informatics Perspective

Open research data are heralded as having the potential to increase effectiveness, productivity, and reproducibility in science, but little is known about the actual practices involved in data search and retrieval. The socio-technical problem of locating data for (re)use is often reduced to the technological dimension of designing data search systems. In this article, we explore how a social informatics perspective can help to better analyze the current academic discourse about data retrieval as well as to study user practices and behaviors. We employ two methods in our analysis - bibliometrics and interviews with data seekers - and conclude with a discussion of the implications of our findings for designing data discovery systems.
The novel droop control strategy for low voltage microgrid without matching line impedance

In view of the independent operation of the AC low-voltage microgrid, differences can be existed in the state of charge (SOC) of parallel batteries because of the unmatched line impedance, which leads to the over-discharge of energy storage batteries and reduce the energy storage unit life. Therefore, an improved droop control strategy is proposed to consider the energy storage system with unmatched line impedance. Firstly, the dynamic virtual impedance is used to eliminate the influence of the line impedance. At the same time, the SOC index is reduced by the e-index droop, which reduces the impact of the error convergence process on the system. Finally, the control strategy is simulated by Matlab/Simulink, and the correctness and validity of the proposed method are verified.