Miracle-dz/UniFAR-FTUs huggingface dataset:
Rethinking Postsecondary Remediation: Exploring an Experiential Learning Approach to College Writing

Abstract This article contributes to the national discourse on college readiness and postsecondary remediation reform. It discusses an experiential learning model of writing remediation as an alternative to traditional basic skills instruction. Such a model may be practical to support the degree completion rates of underprepared writers whose sociodemographic characteristics—including age, race, ethnicity, and income—suggest intersecting strands of linguistic disadvantage. The data describe the classroom implementation of an experiential model of writing remediation in the context of a summer bridge program for students who were traditional by the sole criterion of age, but nontraditional on the composite indicators of prior language exposure. Findings from this exploratory study suggest that the failures students experienced within the program provoked a variety of insights on college writing skills and academic behaviors. The article's discussion focuses on implications in the context of developing remediation reforms that benefit students across multiple lines of difference.
Confidence Penalty Threshold Target : Gender Recall For Male Users Variable : Confidence Penalty Threshold Collaborative User Method

This thesis describes the process of conceptualizing and developing a recommender system for a peer-to-peer commerce application. The application in question is called Plick and is a vintage clothes marketplace where private persons and smaller vintage retailers buy and sell secondhand clothes from each other. Recommender systems is a relatively young field of research but has become more popular in recent years with the advent of big data applications such as Netflix and Amazon. Examples of recommender systems being used in e-marketplace applications are however still sparse and the main contribution of this thesis is insight into this sub-problem in recommender system research. The three main families of recommender algorithms are analyzed and two of them are deemed unfitting for the e-marketplace scenario. Out of the third family, collaborative filtering, three algorithms are described, implemented and tested on a large subset of data collected in Plick that consists mainly of clicks made by users on items in the system. By using both traditional and novel evaluation techniques it is further shown that a user-based collaborative filtering algorithm yields the most accurate recommendations when compared to actual user behavior. This represents a divergence from recommender systems commonly used in e-commerce applications. The paper concludes with a discussion on the cause and significance of this difference and the impact of certain data-preprocessing techniques on the results.
Predicting the Risk of Symptomatic Intracerebral Hemorrhage in Ischemic Stroke Treated With Intravenous Alteplase: Safe Implementation of Treatments in Stroke (SITS) Symptomatic Intracerebral Hemorrhage Risk Score

Background and Purpose— Symptomatic intracerebral hemorrhage (SICH) is a serious complication in patients with acute ischemic stroke treated with intravenous thrombolysis. We aimed to develop a clinical score that can easily be applied to predict the risk of SICH. Methods— We analyzed data from 31 627 patients treated with intravenous alteplase enrolled in the Safe Implementation of Treatments in Stroke (SITS) International Stroke Thrombolysis Register. The outcome measure was SICH per the Safe Implementation of Thrombolysis in Stroke-Monitoring Study (SITS-MOST) definition: a Type 2 parenchymal hemorrhage with deterioration in National Institutes of Health Stroke Scale score of ≥4 points or death. Univariate risk factors associated with the outcome were entered into a logistic regression model after stratification of continuous variables. Adjusted ORs for the independent risk factors were converted into points, which were summated to produce a risk score. Results— We identified 9 independent risk factors for SICH: baseline National Institutes of Health Stroke Scale, serum glucose, systolic blood pressure, age, body weight, stroke onset to treatment time, aspirin or combined aspirin and clopidogrel, and history of hypertension. The overall rate of SICH was 1.8%. The risk score ranged from 0 to 12 points and showed a >70-fold graded increase in the rate of SICH for patients with a score ≥10 points (14.3%) compared with a score of 0 point (0.2%). The prognostic discriminating capability by C statistic was 0.70. Conclusions— The SITS SICH risk score predicts large cerebral parenchymal hemorrhages associated with severe clinical deterioration. The score could aid clinicians to identify patients at high as well as low risk of SICH after intravenous alteplase.
Signals, Not Generators!

Functional Reactive Programming (FRP) uses signals to describe temporal behavior. Push-based FRP implementations avoid recomputation of signal values in certain cases by taking data dependencies into account. However, they typically do not provide signals directly. Instead, signals are produced by signal generators. Using the same generator multiple times leads to repeated computation and dependence on generation time. This reduces scalability and complicates semantics. This paper presents a push-based implementation approach which does not have these problems. Its keys to success are lazy evaluation, rank-2 polymorphism, and impredicative polymorphism. Our work results in a scalable FRP system which gives the user direct access to the key concept of FRP: the signal.
Media Valuations of Health Journalism and Health Dynamics in Brazilian Printed Media

The objective of this study was to understand the opinions of journalists and health managers regarding the dynamics of health news dissemination in printed newspapers from the state of Espirito Santo, Brazil. Semi-structured interviews were conducted with three journalists from the A Tribuna newspaper, three journalists from the A Gazeta newspaper, two editors from these newspapers, two press officers from the Department of Health of Espirito Santo, Brazil and five health managers. The interviews were analysed using content analysis, with Social Representation Theory as a reference. The data analysis revealed that the newspapers tend to value the negative, the quantitative, the novel, and the aesthetic. Similarly, evidence was found for the factors that determine which health issues/diseases will be addressed by the printed media. The respondents’ answers also emphasised the main difficulties of health journalism, which mainly concern journalists’ relationship with their sources. It was concluded that harmony between these actors is rare, which can lead to a decrease in the quality of health news.
Reaching Citizens' Engagement by Services: Swiss Use Case

Collaboration with citizens and users plays an increasing role in the transformation of public services towards new forms of production and delivery. Thus there is a need to modernize the civil service to accelerate innovation in governments, as civil servants will also have an important role to play. Digital civic engagement platforms can provide a more attractive and accessible means for participation. We believe that neither an exclusive top-down approach nor a bottom-up approach can address the current needs. Instead a hybrid approach should be designed. This paper presents a novel approach to address the issue of current civic disengagement. This approach is illustrated through four different use cases in the Swiss context.
Predicting preschooler obesity at birth: the role of maternal obesity in early pregnancy.

OBJECTIVE Knowing risk factors at birth for the development of childhood obesity could help to identify children who are in need of early obesity prevention efforts. The objective of this study was to determine whether children whose mothers were obese in early pregnancy were more likely to be obese at 2 to 4 years of age. METHODS A retrospective cohort study was conducted of 8494 low-income children who were enrolled in the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) in Ohio and were followed from the first trimester of gestation until 24 to 59 months of age. Measured height and weight data from WIC were linked to birth certificate records for children who were born in the years 1992-1996. Obesity among 2- to 4-year-olds was defined as a body mass index (BMI) > or =95th percentile for age and gender. Mothers were classified as obese (BMI > or =30 kg/m2) or nonobese (BMI <30 kg/m2) on the basis of BMI measured in the first trimester of the child's gestation. RESULTS The prevalence of childhood obesity was 9.5%, 12.5%, and 14.8% at 2, 3, and 4 years of age, respectively, and 30.3% of the children had obese mothers. By 4 years of age, 24.1% of children were obese if their mothers had been obese in the first trimester of pregnancy compared with 9.0% of children whose mothers had been of normal weight (BMI 18.5 and <25 kg/m2). After controlling for the birth weight, birth year, and gender of the children plus the mothers' age, race/ethnicity, education level, marital status, parity, weight gain, and smoking during pregnancy, the relative risk of childhood obesity associated with maternal obesity in the first trimester of pregnancy was 2.0 (95% confidence interval [CI]: 1.7-2.3) at 2 years of age, 2.3 (95% CI: 2.0-2.6) at 3 years of age, and 2.3 (95% CI: 2.0-2.6) at 4 years of age. CONCLUSION Among low-income children, maternal obesity in early pregnancy more than doubles the risk of obesity at 2 to 4 years of age. In developing strategies to prevent obesity in preschoolers, special attention should be given to newborns with obese mothers.
A model of a finite buffer shared by queues with batched poisson arrivals

We study a model of a finite buffer shared by M[x]/ M/1 queues. Customer arrivals in each queue are modeled as a batched Poisson process with an arbitrary batch size distribution. The model is a generalization of the Kamoun and Kleinrock model of a packet switch buffer memory shared by M/M/1 queues. A sufficient condition is found, involving quite general buffer sharing policies, for equilibrium state probability distribution to have the product form. For the special case of the geometrically distributed batches and complete sharing buffer policy, we obtain closed form solutions for the normalization constant. The solutions emerge from a few system load configurations and lead to efficient computational procedures for the performance characteristics.
Development of Capitalism in Agriculture-I

DEVELOPMENTS in the Indian Agrarian scene in recent years have provoked rather diverse assesments by academic economists-as diverse indeed as their political viewpointsregarding their implications for the future development of the Indian economy. Broadly speaking, three distinct types of analyses have emerged. Firstly, there are those technocrats who are fairly optimistic about the spread of new cultivation techniques and use of new inputs, and assume that India's food problem can be solved in the foreseeable future provided progress continues in the technical field. They regard the poor harvest years from 1965 to 1967 as exceptional, and deny that there has occurred any deceleration in the growth rate of agricultural output in the 1960's as compared to the 1950's. They appear to envisage a generalisation to the mass of the peasantry of the use of new purchased inputs, at present confined to a small section of it : this at any rate is the only premise on which their optimistic view is tenable.1 This view is challenged by the second group of cautious empiricists,2 who point to the technical limitations upon the rapid spread of the new techniques (principally the difficulties of expanding the area under assured irrigation) as well
Whole-genome sequencing of a Plasmodium vivax isolate from the China-Myanmar border area

Currently, there is a trend of an increasing number of Plasmodium vivaxmalaria cases in China that are imported across its Southeast Asia border, especially in the China-Myanmar border area (CMB). To date, little is known about the genetic diversity of P. vivax in this region. In this paper, we report the first genome sequencing of a P. vivaxisolate (CMB-1) from a vivax malaria patient in CMB. The sequencing data were aligned onto 96.43% of the P. vivax Salvador I reference strain (Sal I) genome with 7.84-fold coverage as well as onto 98.32% of 14 Sal I chromosomes. Using the de novo assembly approach, we generated 8,541 scaffolds and assembled a total of 27.1 Mb of sequence into CMB-1 scaffolds. Furthermore, we identified all 295 known virgenes, which is the largest subtelomeric multigene family in malaria parasites. These results provide an important foundation for further research onP. vivax population genetics.
A gesture based kinect for quadrotor control

This paper presents a novel approach to control or navigate mobile platforms in a GPS denied environment, using natural human gestures. Gesture based interfaces and visual computing techniques are used to develop systems that can be used in Unmanned Aerial Vehicle (UAV) navigation using body postures. This approach will easily marginalize the complexity in Human-Computer interaction (HCI), making it more intuitive and repetitive.
Steam temperature control for steam distillation pot using model predictive control

This paper present a model predictive control (MPC) that was proposed to implement at plant steam distillation pot with induction heating system. By using the ARX model structure, the model predictive control was design to control of steam temperature. Since the steam temperature play important role during the extraction of essential oil, important to researcher to find the control technique to optimize the product yield and quality. The development and implementation of an ARX (Auto-Regressive exogenous) process model that will be used to design a Model Predictive Control (MPC) for steam distillation extraction system. MPC has been proposed as a controller to regulate the system that can preserve the optimum operation temperature besides minimizing the energy that is used to power up the plant. MPC tuning was examined with several values of prediction horizon with the similar default parameter to achieve the optimal setting for better controller's performance. Simulation results show that MPC is able to control the steam temperature in more efficient way using a first order ARX model.
Effect of group cognitive-behavioral therapy on the quality of life and social functioning of patients with mild depression

Background Several studies of moderate-to-severe depression have shown that combined treatment with individual cognitive behavioral therapy (CBT) and antidepressant medication is better than either CBT or antidepressants alone. Less research has focused on the outcomes of group-CBT and antidepressants in persons with mild depression. Aim Evaluate the effects of group-CBT in combination with antidepressants on the quality of life and social functioning of outpatients with mild depression. Methods We randomized 62 outpatients with mild depression into a control group (n=30) that received antidepressant medication for 12 weeks and an intervention group (n=32) that received antidepressants and group-CBT for 12 weeks; both groups were then continued on antidepressants alone for one year. Blinded evaluators used Chinese versions of the Hamilton Depression Rating Scale, Hamilton Anxiety Rating Scale, Social Disability Screening Schedule, Life Satisfaction Rating, Multidimensional Scale of Perceived Social Support, and Short Form Health Survey to assess participants after 12 weeks of treatment and at the end of one year of follow-up. Results Repeated measures analysis of variance showed that the depressive and anxiety symptoms of both groups improved significantly during treatment and that the improvement was greater in the CBT+antidepressant experimental group. Almost all of the social functioning, social support, and quality of life measures also showed significantly greater improvement in the CBT+antidepressant group than in the antidepressant-only group. Moreover, even after adjusting for differences in baseline demographic and clinical characteristics and for changes in the severity of depression and anxiety over time using an analysis of covariance, the greater improvement in the CBT+antidepressant group remained statistically significant both after the 12 weeks of group-CBT treatment and one year after the group CBT had ended. Conclusion Antidepressants alone or combined treatment with antidepressants and group-CBT can effectively improve the social function, quality of life, and healthy functioning of individuals with mild depression. However, combined treatment with both antidepressants and group CBT is better than treatment with antidepressants alone, and these benefits persist for up to one year after the CBT sessions have ended.
The Heterogeneous Systems Integration Design and Implementation for Lane Keeping on a Vehicle

In this paper, an intelligent automated lane-keeping system is proposed and implemented on our vehicle platform, i.e., TAIWAN i TS-1. This system challenges the online integrating heterogeneous systems such as a real-time vision system, a lateral controller, in-vehicle sensors, and a steering wheel actuating motor. The implemented vision system detects the lane markings ahead of the vehicle, regardless of the varieties in road appearance, and determines the desired trajectory based on the relative positions of the vehicle with respect to the center of the road. To achieve more humanlike driving behavior such as smooth turning, particularly at high levels of speed, a fuzzy gain scheduling (FGS) strategy is introduced to compensate for the feedback controller for appropriately adapting to the SW command. Instead of manual tuning by trial and error, the methodology of FGS is designed to ensure that the closed-loop system can satisfy the crossover model principle. The proposed integrated system is examined on the standard testing road at the Automotive Research and Testing Center (ARTC)1 and extra-urban highways.
Heterogeneous communication architecture for the smart grid

The smart grid concept provides a solution to the growing recognition that current utility grids need an ICT deployment infrastructure based upgrade to allow millions of potential market players to operate and to cope with distributed generation, wide-area situational awareness, demand response, electric storage, and efficient electric transportation. Smart grid deployment is mainly about defining the necessary standards for ICT solutions. The design of the communication network associated with the smart grid involves detailed analysis of its communication requirements, a proposal of the appropriate protocol architecture, the choice of the most suitable technologies for each case study, and a scheme for the resultant heterogeneous network management system. Given the smart grid use cases, this article is focused on proposing a heterogeneous communication paradigm for smart grids based on power line communications and wireless networks. The proposal is related to the framework of the ITU ubiquitous sensor network architecture using the ITU next-generation network model. This architecture allows for better management of the QoS in the smart grid and should facilitate interoperability with other technologies.
Regional Trade Agreements

This paper reviews the theoretical and the empirical literature on regionalism. The formation of regional trade agreements has been, by far, the most popular form of reciprocal trade liberalization in the last fifteen years. The discriminatory character of these agreements has raised three main concerns: that trade diversion would be rampant, because special interest groups would induce governments to form the most distortionary agreements; that broader external trade liberalization would stall or reverse; and that multilateralism could be undermined. Theoretically, all of these concerns are legitimate, although there are also several theoretical arguments that oppose them. Empirically, neither widespread trade diversion nor stalled external liberalization have materialized, while the undermining of multilateralism has not been properly tested. There are also several aspects of regionalism that have received too little attention from researchers, but which are central to understanding its causes and consequences.
The engineering of emergence in complex adaptive systems

Agent-oriented software engineering is a new software engineering paradigm that is ideally suited to the analysis and design of complex systems. The main focus of these methodologies is to engineer a complex system in such a way that the correct emergent behavior results. In a complex adaptive system, however, emergent behavior cannot be predicted during analysis and design as it evolves only after implementation. By restricting emergent behavior as is done in most agent-oriented software engineering approaches, a complex system cannot be fully adaptive as well. We propose the BaBe methodology that will enable a complex system to be adaptive as the system can learn from its environment during run-time and modify its behavior in order to adapt to changes in its environment. This methodology adds a run-time emergence model consisting of distributed Bayesian Behavior Networks to the agent-oriented software engineering lifecycle. These networks are initialized by the human software engineer and deployed by Bayesian Agencies (also complex adaptive systems). The distributed Bayesian Behavior Networks, being specialized Bayesian Networks, will enable the Bayesian Agencies to collectively mine relationships between emergent behaviors and the interactions that caused them to emerge. This technology will further enable the Bayesian Agencies to collectively learn from the emerged behaviors and to modify the behavior of the system in order to adapt to changes in the environment. We describe a prototype implementation of the Bayesian Agencies using Sun’s Enterprise JavaBeansTM component architecture.
Resource manager with multi-core support for parallel desktop

Due to the fall in the price of multicore processors, today's non-dedicated clusters tend to include this kind of hardware in their configurations. However, most current resource managers and job schedulers are optimized with the aim of maximizing the throughput in single-core environments. Additionally, job schedulers balance thread loads without considering such aspects as cache affinity, resource contention or other additional criteria. In the same way, general purpose Operating System schedulers will support requirements like the coexistence of soft-real time, best effort or interactive applications are open questions that need to be addressed carefully. For these reasons, new user interfaces, middlewares, and environments that can fill the gap between the user and the new processor architectures are needed. Our CISNE environment has been extended to take into account issues discussed earlier: the mixture of different types of applications considering the multicore features of current desktop environments.