Miracle-dz/UniFAR-FTUs huggingface dataset:
The effect of intravenous low dose ketamine for reducing postoperative sore throat

Background This study was performed to evaluate the effectiveness of intravenous low dose ketamine for reducing the incidence and severity of postoperative sore throat (POST). Methods This was a prospective, randomized, double-blind clinical trial. The study population consisted of 70 patients between 20 and 70 years old who were classified as American Society of Anesthesiologists I-II and were scheduled for elective laparoscopic cholecystectomy. The patients were divided randomly into two groups. Patients in the ketamine group received an intravenous injection of 0.5 mg/kg of ketamine just before induction, followed by 10 µg/kg/min throughout the operation. Patients in the control group received intravenous saline instead of ketamine. The patients were interviewed 1, 6, and 24 h after the operation. The incidence and severity of POST were recorded. Results No significant differences in the incidence and severity of POST during the 24 h after the operation were found between the two groups (21/31 in the ketamine group vs. 26/34 in the control group, P = 0.398). Conclusions Intravenous injection of low dose ketamine was not effective for reducing POST.
The novel frequency control method for PV-diesel hybrid system

A novel frequency coordination control method is proposed for a PV-diesel isolated hybrid system. In the proposed coordination control strategy, the photovoltaic system (PV) are controlled by using maximum power point tracking (MPPT) method, and the sliding mode control(SMC) is designed for the output power tuning of the diesel generator system to reduce the frequency deviation. In the simulation results, the proposed frequency control method can not only reduce the frequency deviation induced by the load changes and the hybrid renewable energy fluctuation, but also assure make full use of the renewable energy. Moreover, the frequency deviation suppress effect is better than through adding battery storage installation, so the energy storage device hardware investment are reduced and environmental pollution is avoided in the process of large-scale hybrid system construction.
A Positive Theory of Insider-Privatization

We consider the decision of a self-interested government to privatize a . rm to an insider manager whose productivity is private information. Privatization can improve the incentives of managers, but it comes also at the cost of softer budget constraints, in case the government has injected funds for the restructuring of the . rm. Moreover, e¢ciency gains due to privatization may not materialize when managers have an interest to preserve high employment. The predictions of our model are in line with the experience in transition economies and have moreover some interesting implications for the theory of property rights. JEL Classi.cation: D23, L33, P31
GTP Hydrolysis Is Not Important for Ypt1 GTPase Function in Vesicular Transport

ABSTRACT GTPases of the Ypt/Rab family play a key role in the regulation of vesicular transport. Their ability to cycle between the GTP- and the GDP-bound forms is thought to be crucial for their function. Conversion from the GTP- to the GDP-bound form is achieved by a weak endogenous GTPase activity, which can be stimulated by a GTPase-activating protein (GAP). Current models suggest that GTP hydrolysis and GAP activity are essential for vesicle fusion with the acceptor compartment or for timing membrane fusion. To test this idea, we inactivated the GTPase activity of Ypt1p by using the Q67L mutation, which targets a conserved residue that helps catalyze GTP hydrolysis in Ras. We demonstrate that the mutant Ypt1-Q67L protein is severely impaired in its ability to hydrolyze GTP both in the absence and in the presence of GAP and consequently is restricted mostly to the GTP-bound form. Surprisingly, a strain with ypt1-Q67L as the only YPT1 gene in the cell has no observable growth phenotypes at temperatures ranging from 14 to 37°C. In addition, these mutant cells exhibit normal rates of secretion and normal membrane morphology as determined by electron microscopy. Furthermore, the ypt1-Q67L allele does not exhibit dominant phenotypes in cell growth and secretion when overexpressed. Together, these results lead us to suggest that, contrary to current models for Ypt/Rab function, GTP hydrolysis is not essential either for Ypt1p-mediated vesicular transport or as a timer to turn off Ypt1p-mediated membrane fusion but only for recycling of Ypt1p between compartments. Finally, the ypt1-Q67L allele, like the wild type, is inhibited by dominant nucleotide-freeYPT1 mutations. Such mutations are thought to exert their dominant phenotype by sequestration of the guanine nucleotide exchange factor (GNEF). These results suggest that the function of Ypt1p in vesicular transport requires not only the GTP-bound form of the protein but also the interaction of Ypt1p with its GNEF.
Managing the screen-viewing behaviours of children aged 5–6 years: a qualitative analysis of parental strategies

Objectives The present study used qualitative methods to: (1) examine the strategies that were used by parents of children aged 5–6 years to manage screen viewing; (2) identify key factors that affect the implementation of the strategies and (3) develop suggestions for future intervention content. Design Telephone interviews were conducted with parents of children aged 5–6 years participating in a larger study. Interviews were transcribed verbatim and analysed using an inductive and deductive content analysis. Coding and theme generation was iterative and refined throughout. Setting Parents were recruited through 57 primary schools located in the greater Bristol area (UK). Participants 53 parents of children aged 5–6 years. Results Parents reported that for many children, screen viewing was a highly desirable behaviour that was difficult to manage, and that parents used the provision of screen viewing as a tool for reward and/or punishment. Parents managed screen viewing by setting limits in relation to daily events such as meals, before and after school, and bedtime. Screen-viewing rules were often altered depending on parental preferences and tasks. Inconsistent messaging within and between parents represented a source of conflict at times. Potential strategies to facilitate reducing screen viewing were identified, including setting screen-viewing limits in relation to specific events, collaborative rule setting, monitoring that involves mothers, fathers and the child, developing a family-specific set of alternative activities to screen viewing and developing a child's ability to self-monitor their own screen viewing. Conclusions Managing screen viewing is a challenge for many parents and can often cause tension in the home. The data presented in this paper provide key suggestions of new approaches that could be incorporated into behaviour change programmes to reduce child screen viewing.
An Efficient Approach for Cost Optimization of the Movement of Big Data

With the emergence of cloud computing, Big Data has caught the attention of many researchers in the area of cloud computing. As the Volume, Velocity and Variety (3 Vs) of big data are growing exponentially, dealing with them is a big challenge, especially in the cloud environment. Looking at the current trend of the IT sector, cloud computing is mainly used by the service providers to host their applications. A lot of research has been done to improve the network utilization of WAN (Wide Area Network) and it has achieved considerable success over the traditional LAN (Local Area Network) techniques. While dealing with this issue, the major questions of data movement such as from where to where this big data will be moved and also how the data will be moved, have been overlooked. As various applications generating the big data are hosted in geographically distributed data centers, they individually collect large volume of data in the form of application data as well as the logs. This paper mainly focuses on the challenge of moving big data from one data center to other. We provide an efficient algorithm for the optimization of cost in the movement of the big data from one data center to another for offline environment. This approach uses the graph model for data centers in the cloud and results show that the adopted mechanism provides a better solution to minimize the cost for data movement.
Using Typed Dependencies to Study and Recognise Conceptualisation Zones in Biomedical Literature

In the biomedical domain, authors publish their experiments and findings using a quasi-standard coarse-grained discourse structure, which starts with an introduction that sets up the motivation, continues with a description of the materials and methods, and concludes with results and discussions. Over the course of the years, there has been a fair amount of research done in the area of scientific discourse analysis, with a focus on performing automatic recognition of scientific artefacts/conceptualisation zones from the raw content of scientific publications. Most of the existing approaches use Machine Learning techniques to perform classification based on features that rely on the shallow structure of the sentence tokens, or sentences as a whole, in addition to corpus-driven statistics. In this article, we investigate the role carried by the deep (dependency) structure of the sentences in describing their rhetorical nature. Using association rule mining techniques, we study the presence of dependency structure patterns in the context of a given rhetorical type, the use of these patterns in exploring differences in structure between the rhetorical types, and their ability to discriminate between the different rhetorical types. Our final goal is to provide a series of insights that can be used to complement existing classification approaches. Experimental results show that, in particular in the context of a fine-grained multi-class classification context, the association rules emerged from the dependency structure are not able to produce uniform classification results. However, they can be used to derive discriminative pair-wise classification mechanisms, in particular for some of the most ambiguous types.
Application of a Specific and Sensitive Radiometric Assay for Microbial Lipase Activities in Marine Water Samples from the Lagoon of Nouméa

ABSTRACT Marine microbiologists commonly assay lipase activities by using a synthetic fluorescent analog, 4-methylumbelliferyl (MUF)-oleate. The technique is convenient, but it is considered to be unspecific because of the structure of this analog. This study reports the design of a new specific and sensitive lipase assay based on the use of a radiolabeled triglyceride, [3H]triolein. Free fatty acids (FFA) resulting from its hydrolysis are isolated as a function of time in a one-step liquid-liquid extraction and then radioassayed. MUF-oleate and [3H]triolein techniques were compared by measuring lipase activities at similar substrate concentrations along a trophic gradient in the Southwest Lagoon of New Caledonia, near Nouméa. Hydrolysis rates decreased from the nearshore station to the offshore station and showed similar trends regardless of the technique used. Rates decreased from 5.83 to 0.88 nmol of FFA · liter−1 · h−1 and from 0.76 to 0.23 nmol of3H-FFA · liter−1 · h−1, respectively. These results appeared to be consistent with bacterial production results, which also decreased similarly (from 0.59 to 0.26μ g of C · liter−1 · h−1). However, the ratio of MUF-oleate activities to [3H]triolein activities, which was constant at the offshore stations (3.8 ± 0.1), gradually increased at the nearshore stations (from 4.1 to 7.6). This result shows that the two assays respond in different ways to changes in environmental conditions and validates the need to set up more specific enzymatic assays.
A Mobile Visual Analytics Approach for Law Enforcement Situation Awareness

The advent of modern smart phones and handheld devices has given analysts, decision-makers, and even the general public the ability to rapidly ingest data and translate it into actionable information on-the-go. In this paper, we explore the design and use of a mobile visual analytics toolkit for public safety data that equips law enforcement agencies with effective situation awareness and risk assessment tools. Our system provides users with a suite of interactive tools that allow them to perform analysis and detect trends, patterns and anomalies among criminal, traffic and civil (CTC) incidents. The system also provides interactive risk assessment tools that allow users to identify regions of potential high risk and determine the risk at any user-specified location and time. Our system has been designed for the iPhone/iPad environment and is currently being used and evaluated by a consortium of law enforcement agencies. We report their use of the system and some initial feedback.
Linked data and provenance in biological data webs

The Web is now being used as a platform for publishing and linking life science data. The Web's linking architecture can be exploited to join heterogeneous data from multiple sources. However, as data are frequently being updated in a decentralized environment, provenance information becomes critical to providing reliable and trustworthy services to scientists. This article presents design patterns for representing and querying provenance information relating to mapping links between heterogeneous data from sources in the domain of functional genomics. We illustrate the use of named resource description framework (RDF) graphs at different levels of granularity to make provenance assertions about linked data, and demonstrate that these assertions are sufficient to support requirements including data currency, integrity, evidential support and historical queries.
Ranking of evolving stories through meta-aggregation

In this paper we focus on the problem of ranking news stories within their historical context by exploiting their content similarity. We observe that news stories evolve and thus have to be ranked in a time and query dependent manner. We do this in two steps. First, the mining step discovers metastories, which constitute meaningful groups of similar stories that occur at arbitrary points in time. Second, the ranking step uses well known measures of content similarity to construct implicit links among all metastories, and uses them to rank those metastories that overlap the time interval provided in a user query. We use real data from conventional and social media sources (weblogs) to study the impact of different meta-aggregation techniques and similarity measures in the final ranking. We evaluate the framework using both objective and subjective criteria, and discuss the selection of clustering method and similarity measure that lead to the best ranking results.
Author ' s personal copy Rapid pedestrian detection in unseen scenes

In this paper, a rapid adaptive pedestrian detection method based on cascade classifier with ternary pattern is proposed. The proposed method achieves its goal by employing the following three new strategies: (1) A method for adjusting the key parameters of the trained cascade classifier dynamically for detecting pedestrians in unseen scenes using only a small amount of labeled data from the new scenes. (2) An efficient optimization method is proposed, based on the cross entropy method and a priori knowledge of the scenes, to solve the classifier parameter optimization problem. (3) In order to further speed up pedestrian detection in unseen scenes, each strong classifier in the cascade employs a ternary detection pattern. In our experiments, two significantly different datasets, AHHF and NICTA, were used as the training set and testing set, respectively. The experimental results showed that the proposed method can quickly adapt a previously trained detector for pedestrian detection in various scenes compared with other existing methods. & 2011 Elsevier B.V. All rights reserved.
Empowering leadership and organizational ambidexterity: a moderated mediation model

Purpose The purpose of this paper is to examine the effect of empowering leadership on contextual ambidexterity. To this end, the authors underscore the underlying mechanism of perceived organizational support (POS). Furthermore, to provide more robust insights into this indirect effect, role ambiguity was examined as a moderator. Design/methodology/approach The paper is based on a questionnaire survey. Data collected from 219 employees working in three IT small-and-medium enterprises located in Greece. Findings The findings indicated that empowering leadership is positively related to contextual ambidexterity through POS and, further, this indirect association is contingent on role ambiguity. Originality/value The study provides more insights into the important role of leadership in generating contextual ambidexterity. Thus, moderated mediation framework that has empirically tested considers both how and when empowering leadership affects contextual ambidexterity and provides important implications for both theory and practice.
Study on Pervasive Computing-Based Process Management in Cooperative Design for Architectural Construction Engineering

Based on the theory of pervasive computing, and according to the characters of information management in institutes of design, CDPMS (Command-Dispatching and Process Management System) is designed and developed. It is a sub-system of CodeFAR. CDPMS is used to manage and configure the process and the resources in cooperative design by workflow. By the cooperative work platform in CodeFAR, the methods, such as task decomposition tree, project progress rate and performance recording, are adopted to implement the functions of task dispatching, scheduling control, document management, and performance management
The Assignment of Workers to Jobs with Endogenous Information Selection

We present a model where information processing constraints on workers and firms lead to an endogenous matching function. We provide conditions under which the matching process has a unique equilibrium computable in closed-form. The main finding is that equilibrium matching is generally inefficient. This result does not depend on the form of heterogeneity, the distribution of surplus or bargaining rules. It is driven by information processing constraints which weaken the strategic complementarities and enhance the negative externalities in search efforts of workers and firms. A closed-form solution of the model provides a bound on the size of this inefficiency.
Vriendelijke burgemeesters in crisistijd: leiderschap, tijdsdruk en situationele ambiguïteit

Dit artikel gaat in op de relatie tussen de Big Five-persoonlijkheidstrek Vriendelijkheid en het autocratisch en participatief leiderschapsgedrag en de effectiviteit van burgemeesters tijdens crises. Op basis van de trekactivatietheorie werd verwacht dat de relatie tussen de vriendelijkheid van een burgemeester en (de effectiviteit van) diens autocratisch en participatief leiderschapsgedrag afhankelijk is van de mate waarin een crisis gekenmerkt wordt door tijdsdruk en ambiguiteit. Verwachtingen zijn getoetst in 68 openbare-orde- en veiligheidscrises. De mate van vriendelijkheid bleek tijdens crises via autocratisch leiderschapsgedrag negatief gerelateerd aan de leiderschapseffectiviteit van de burgemeester. Onder lage (hoge) tijdsdruk bleek verder dat vriendelijkheid positief (negatief) gerelateerd was aan leiderschapseffectiviteit via participatief leiderschapsgedrag. De mate van ambiguiteit bleek alleen van invloed op de relatie tussen autocratisch leiderschapsgedrag en de effectiviteit van de burgemeester als leider. Autocratisch leiderschapsgedrag van de burgemeester was positief gerelateerd aan diens leiderschapseffectiviteit en deze relatie werd sterker bij toenemende ambiguiteit. We besluiten met implicaties voor leiderschapstheorie en crisisbeheersing.
Community evolution detection in time-evolving information networks

In this paper, we propose a framework for representing, modeling and mining time-evolving information networks. Our framework introduces a graph-based model-theoretic approach to represent such networks and how they change over time. Also, we provide a method for supporting matching-based community evolution detection in time-evolving information networks, by identifying several classes of community transitions, along with algorithms that implement them.
Utilizing Computational Intelligence in Estimating Software Readiness

Defect tracking using computational intelligence methods is used to predict software readiness in this study. By comparing predicted number of faults and number of faults discovered in testing, software managers can decide whether the software are ready to be released or not. Our predictive models can predict: (i) the number of faults (defects), (ii) the amount of code changes required to correct a fault and (iii) the amount of time (in minutes) to make the changes in respective object classes using software metrics as independent variables. The use of neural network model with a genetic training strategy is introduced to improve prediction results for estimating software readiness in this study. Existing object-oriented metrics and complexity software metrics are used in the Business Tier neural network based prediction model. New sets of metrics have been defined for the Presentation Logic Tier and Data Access Tier.
Secure automotive gateway — Secure communication for future cars

The main focus of the paper is to secure the onboard communication of automobiles. The current trend in the automotive domain is to incorporate technologies known from the consumer segment (e.g., WLAN, Ethernet) into the car. This makes it easier for an attacker to attack the on-board networks of the car, even without having physical access. To detect attacks against the automotive networks such as CAN and FlexRay, we introduce the concept of the so called “security gateway” which is part of the automotive architecture and is located on transition points, where different networks connect with each other. A language was created to specify the correct application behavior and to configure the security gateway. Using this representation of the application behavior the security gateway not only detects failures caused by an attacker but also detects failures caused by malfunctions.