Miracle-dz/UniFAR-FTUs huggingface dataset:
Adjuvant Radiotherapy Is Associated With Increased Sexual Dysfunction in Male Patients Undergoing Resection for Rectal Cancer: A Predictive Model

Objectives:The objectives of this study were to evaluate the effect of radiotherapy (RT) on sexual function in patients undergoing oncologic resection for rectal cancer, and to develop a mathematical model for quantifying the risk of sexual dysfunction through time for this group of patients. Methods:Data were prospectively collected on patients undergoing proctosigmoidectomy (group 1: n = 101) or adjuvant radiotherapy (40–50 Gy) and resection (group 2: n = 100) for rectal cancer at a tertiary referral center between December 1998 and July 2004. Study end points were recorded at 7 time intervals (preoperatively, 4 months, 8 months, 1 year, 2 years, 3 years, and 4 years after surgery) and included: 1) ability to have an erection, 2) maintain an erection, 3) attain orgasm, 4) dry orgasm, and 5) whether they were sexually active. Multilevel logistic regression analysis for repeated measures was used to identify factors associated with the sexual dysfunction. A predictive model was developed and internally validated by comparing observed and model-predicted outcomes. Results:Radiotherapy had an adverse effect on the ability to get an erection, maintain an erection, attain orgasm, and being sexually active in comparison with patients undergoing surgery alone (7.4%, 12.6%, 16.2%, and 13.7% reduction 8 months after surgery respectively; P < 0.05). The effect of sexual dysfunction deteriorated with age (odds ratio for erectile function, 0.40 per 10-year increase in age; 95% confidence interval, 0.29–0.49; P < 0.001). A significant variability in sexual function was present among the 7 time points with a maximal deterioration occurring at 8 months after surgery with subsequent slow but not complete recovery (P < 0.001). The predictive model showed adequate discrimination on 4 of the 5 domains of sexual dysfunction (area under the receiver operating characteristic curve >0.70). Conclusions:Radiotherapy has an adverse effect on sexual function, the effect being maximal at 8 months after surgery. The risk of sexual dysfunction can be quantified preoperatively using the proposed index and can assist patients in making better informed choices on the type of treatment they receive.
The Brazilian version of STarT Back Screening Tool - translation, cross-cultural adaptation and reliability *

Background: Psychosocial factors are not routinely identified in physical therapy assessments, although they can influence the prognosis of patients with low back pain. The "STarT Back Screening Tool" (SBST) questionnaire aids in screening such patients for poor prognosis in the primary care setting and classifies them as high, medium, or low risk based on physical and psychosocial factors. Objectives: This study sought to translate and cross-culturally adapt the SBST to the Brazilian Portuguese language and test the reliability of the Brazilian version. Method: The first stage of the study consisted of the translation, synthesis, and back-translation of the original version of the STSB, including revision by the Translation Group, pretest of the translated version, and assessment by an expert panel. The pre-final Brazilian version was applied to 2 samples comprising 52 patients with low back pain; these patients were of both genders and older than 18 years of age. To assess the instrument's reliability, an additional sample comprising 50 patients was subjected to 2 interviews, and the results were assessed using the quadratic weighted kappa value. The instrument's internal consistency was assessed using Cronbach's alpha (n=105), and the standard error of measurement was also calculated (n=50). Results: Translation and back-translation attained consensus, and only item 6 required changes; the reformulated version was applied to an additional sample comprising 52 individuals who did not report any doubts related to this item. The reliability of the SBST-Brazil was 0.79 (95% confidence interval: 0.63-0.95), the internal consistency was 0.74 for the total score and 0.72 for the psychosocial subscale, and the standard error of measurement was 1.9%. Conclusion: The translated and cross-culturally adapted SBST-Brazil proved to be reliable for screening patients according to their risk of poor prognosis and the presence of psychosocial factors.
Timing Predictability on Multi-Processor Systems with Shared Resources

Multi-processor systems are becoming increasingly important in consumer electronics as well as in industrial applications, such as automotive software. Tasks need to share data across processing unit boundaries, e.g., local variables, triggering the need for a communication fabric. Therefore, multi-processor systems are constituted not only by a mere set of processing units, but also by communication and memory peripherals. These peripherals are shared resources, i.e., multiple independently executing tasks on multiple processing units compete for accessing them. Real-time tasks execute periodically on a processing element and are constituted by sequential superblocks. In this paper, we consider several models to schedule the superblocks and organize accesses to the shared resources within the superblocks. First, superblocks can be executed sequentially, i.e., a superblock is activated as soon as its preceding superblock has finished, or they can be executed according to a static schedule (preassigned time slots). Second, we consider three models to access shared resources: (1) dedicated access model, in which accesses happen only at the beginning and the end of a superblock, (2) general access model, in which accesses could happen anytime during the execution of a superblock, and (3) hybrid access model, which combines the dedicated and general access models. We show the relation between these models with respect to schedulability and provide experimental results that show that the dedicated phases model with sequential superblocks performs best.
THE IMPACT OF ACCULTURATION, TRAUMA, AND POST-MIGRATION STRESSORS ON THE MENTAL HEALTH OF AFRICAN IMMIGRANTS AND REFUGEES IN SWEDEN

Mental health promotion is an important public health issue which warrants increased and immediate attention due to the significant impact that mental health can have on physical health,quality of life, and functioning. Immigrants and refugees often have unique and increased mental health needs secondary to their migration to a new country and the acculturative stressors and living difficulties that often accompany resettlement, as well as prior experiences of trauma. However, little to no prior research has been conducted regarding the mental health of African immigrants and refugees living in Sweden. This thesis describes data from a study which was conducted in Stockholm, Sweden from 2002 to 2005 that investigated African immigrant and refugee health and quality of life. Stratified quota sampling based on the 2001 Swedish census was used to recruit a representative sample of participants by gender and country of origin. Four hundred and twenty participants completed semi-structured interviews that utilized cross culturally validated survey instruments to measure depression, anxiety, post-traumatic stress disorder (PTSD), acculturation, traumatic events, and post-migration living difficulties. Twenty percent of participants met symptom criteria indicative of depression, and 18.5% met criteria indicative of anxiety. Eighty-ninepercent of participants reported experiencing at least one traumatic event prior to immigration,and 47% met DSM-IV symptomology and functional impairment criteria for PTSD. Mental health outcomes were found to be significantly associated with pre-migration trauma, acculturation level and type, and post-migration stressors. Recommendations for future research, mental health service provision, and integration policies are provided.
Building Efficient Intrusion Detection Model Based on Principal Component Analysis and C4.5

An appropriate feature set helps to build efficient decision model as well as reduced feature set lights up the training and testing process considerably. In this paper, we propose a new approach to build efficient Intrusion detection system (IDS) based on principal component analysis and C4.5. Our method is able to significantly decrease training and testing times while retaining high detection rates with low false positives rates as well as stable feature selection results. We have examined the feasibility of our approach by conducting several experiments using KDD 1999 CUP intrusion dataset. The experimental results show the feasibility of our approach to enable one to building efficient IDS.
An Overlay Multicast that Supports a Distinguished QoS Based on Service Levels and User Environments in the Next Generation Network

Next Generation Network (NGN) is a broadband network that guarantees the quality of data transfers, independent of the lower transfer media, as real-time broadcasting services that are featured as a key service of the NGN require the multicast technique. Nevertheless, the existing IP multicast contains many limitations of application. Overlay multicast IP, an alternative to IP multicast, is a network studied widely for its ability to offer effective multimedia multicast transfers through flexibility and scalability. In this paper, we designed an agent for the destination network of each receiver and a manager that manages the entire overlay multicast topology for the source network where the media server is located. The manager and agent communicate with each other to assume the role of providing services based on network resource status. In this way, we can create a multicast environment that guarantees QoS in the NGN environment, which will be based on RACF (Resource and Admission Control Functions).
Evolving behavioral choice: An investigation of Herrnstein's matching law

In 1961, Herrnstein famously observed that many animals match the frequency of their response to different stimuli in proportion to the reinforcement obtained from each stimulus type. Since then, a great deal of research has attempted to elucidate the mechanisms underlying this ``matching law'', so far without a clear consensus emerging. Here, we take the view that ``choice behaviour'' is a product of agent, environment, and observer, and that ``mechanisms of choice'' are therefore not to be located solely within the chooser. A simple model, employing the novel methodology of evolving choice behaviour in a multi-agent system, is used to demonstrate that matching behaviour can occur (in stable environments) without any dedicated choice mechanism.
Optimal control of parallel hybrid electric vehicles

In this paper, a model-based strategy for the real-time load control of parallel hybrid vehicles is presented. The aim is to develop a fuel-optimal control which is not relying on the a priori knowledge of the future driving conditions (global optimal control), but only upon the current system operation. The methodology developed is valid for those problem that are characterized by hard constraints on the state-battery state-of-charge (SOC) in this application-and by an arc cost-fuel consumption rate-which is not an explicit function of the state. A suboptimal control is found with a proper definition of a cost function to be minimized at each time instant. The "instantaneous" cost function includes the fuel energy and the electrical energy, the latter related to the state constraints. In order to weight the two forms of energy, a new definition of the equivalence factors has been derived. The strategy has been applied to the "Hyper" prototype of DaimlerChrysler, obtained from the hybridization of the Mercedes A-Class. Simulation results illustrate the potential of the proposed control in terms of fuel economy and in keeping the deviations of SOC at a low level.
Using Queuing Theory and Simulation Modelling to Reduce Waiting Times in An Iranian Emergency Department

Background: Hospital emergencies have an essential role in health care systems. In the last decade, developed countries have paid great attention to overcrowding crisis in emergency departments. Simulation analysis of complex models for which conditions will change over time is much more effective than analytical solutions and emergency department (ED) is one of the most complex models for analysis. This study aimed to determine the number of patients who are waiting and waiting time in emergency department services in an Iranian hospital ED and to propose scenarios to reduce its queue and waiting time. Methods: This is a cross-sectional study in which simulation software (Arena, version 14) was used. The input information was extracted from the hospital database as well as through sampling. The objective was to evaluate the response variables of waiting time, number waiting and utilization of each server and test the three scenarios to improve them. Results: Running the models for 30 days revealed that a total of 4088 patients left the ED after being served and 1238 patients waited in the queue for admission in the ED bed area at end of the run (actually these patients received services out of their defined capacity). The first scenario result in the number of beds had to be increased from 81 to179 in order that the number waiting of the “bed area” server become almost zero. The second scenario which attempted to limit hospitalization time in the ED bed area to the third quartile of the serving time distribution could decrease the number waiting to 586 patients. Conclusion: Doubling the bed capacity in the emergency department and consequently other resources and capacity appropriately can solve the problem. This includes bed capacity requirement for both critically ill and less critically ill patients. Classification of ED internal sections based on severity of illness instead of medical specialty is another solution.
Crowding out Both Sides of the Philanthropy Market: Evidence from a Panel of Charities

When the government gives a grant to a private charitable organization, do the donors to that organization give less? If they do, is it because the grants crowd out donors who feel they gave through taxes (classic crowd out), or is it because the grant crowds out the fund-raising of the charities who, after getting the grant, reduce efforts of fund-raising (fund-raising crowd out)? This is the first paper to separate these two effects. Using a panel of almost 3100 charities, we find that crowding out is significant, at about 56 percent. Most of this crowding out is due to reduced fund-raising. We estimate that 68 percent of crowd out is from reduced fund-raising, and only 32 percent from the classic crowd out. Such a finding could have important consequences for how governments structure grants to non-profits. Our results indicate, for example, that requirements that charities match a fraction of government grants with increases in private donations might be a feasible policy that could reduce the detrimental effects of crowding out. JEL Classification: H00, H32, H50 * Andreoni: Department of Economics, University of California, San Diego (email: andreoni@ucsd.edu); Payne: Department of Economics, McMaster University, KTH 426, Hamilton, ON L8S 4M4 Canada (email: paynea@mcmaster.ca). This research was supported by grants from the National Science Foundation, from the Social Sciences and Humanities Research Council of Canada, the Canada Foundation for Innovation, and the Ontario Innovation Trust. We would also like to thank the Urban Institute for providing us with access to the IRS 990 data set. We’re grateful to Justin Rao for helpful comments.
Antibacterial Action of a Condensed Tannin Extracted from Astringent Persimmon as a Component of Food Addictive Pancil PS-M on Oral Polymicrobial Biofilms

The purpose of this study was to evaluate the antibacterial activity against polymicrobial (PM) biofilms of a condensed tannin extracted from astringent persimmon (PS-M), which is contained in refreshing beverages commercially available in Japan. Salivary PM biofilms were formed anaerobically on glass coverslips for 24 and 72 h and were treated for 5 min with sterilized deionized water (DW), 0.05 and 0.2 wt% chlorhexidine digluconate (CHX), and 0.5–4.0 wt% PS-M solution. The colony forming units (CFU/mL) were determined and morphological changes of the biofilms were observed by scanning electron microscopy (SEM). The CFUs were lower in all PS-M and CHX groups compared to the DW group. PS-M exerted a dose-dependent effect. PS-M (1.53 × 107) at a dose of 4.0 wt% had the same effect as 0.2 wt% CHX (2.03 × 107), regardless of the culture period. SEM revealed the biofilm structures were considerably destroyed in the 4.0 wt% PS-M and 0.2 wt% CHX. These findings indicate that the antibacterial effects of PS-M, a naturally derived substance, are comparable to those of CHX. PS-M may keep the oral cavity clean and prevent dental caries and periodontal disease related to dental plaque, as well as systemic disease such as aspiration pneumonitis.
RI-Small : Statistical Relational Models for Semantic Robot Mapping 1

In the last decade, the mobile robotics community has made tremendous progress in the development of efficient yet robust techniques for dealing with noisy sensor data. A major reason for this progress is a better understanding of probabilistic algorithms, which have become the most successful and most widely applied tools for dealing with uncertainty in mobile robotics [11, 23, 144]. The key idea of these techniques is to represent uncertainty using probability distributions and to make use of structural independences to make inference tractable. Bayesian filtering techniques, for example, have been applied with great success to state estimation problems ranging from robot localization [26, 65, 40, 8, 124] to map building [31, 142, 102, 113, 56, 147] to people and object tracking [103, 37, 129, 74]. However, current robot systems are still very limited in their capabilities to reason about environments in high-level concepts such as places and objects. Such concepts are extremely important especially for applications that require robots to interact and collaborate with humans, such as health care [34, 151, 99, 150], personal assistants for the elderly [10, 101], or search and rescue [72, 91]. For instance, in search and rescue tasks, a mobile robot that can reason about objects such as doors, and places such as rooms is able to coordinate with first responders in a much more natural way, being able to accept commands such as “Search the room behind the third door on the right of this hallway”, and conveying information such as “There is a wounded person behind the desk in that room”. As another example, consider autonomous vehicles navigating in urban areas. While the recent success of the DARPA Urban Challenge [21, 146] demonstrates that it is possible to develop autonomous vehicles that can navigate safely in constraint settings, the successful application of such systems in more realistic, populated urban areas requires the ability to distinguish between objects such as cars, people, buildings, trees, and traffic lights. The goal of this project is to develop a reasoning and learning framework that enables robots to build rich, semantic maps of their environments. Semantic maps describe environments in terms of places, such as rooms, hallways, streets, or parking lots, and objects, such as doors, walls, cars, people, or trees. Current mapping techniques lack the expressive power necessary to generate such representations. Our framework, called Relational Semantic Maps (RS-Maps), overcomes limitations of existing mapping techniques by building on recent advances in statistical relational learning [52]. Relational models extend (propositional) probabilistic models such as Bayesian networks [114, 29, 53, 106], Markov Random Fields [49, 7, 155], or Conditional Random Fields [79, 138] to (first-order) relational domains. By using first-order logical languages to specify the structures of the underlying probabilistic models, relational techniques are extremely expressive and flexible. However, building semantic maps still requires us to address various research challenges:
Friends, not foes

Many data center transports have been proposed in recent times (e.g., DCTCP, PDQ, pFabric, etc). Contrary to the common perception that they are competitors (i.e., protocol A vs. protocol B), we claim that the underlying strategies used in these protocols are, in fact, complementary. Based on this insight, we design PASE, a transport framework that synthesizes existing transport strategies, namely, self-adjusting endpoints (used in TCP style protocols), innetwork prioritization (used in pFabric), and arbitration (used in PDQ). PASE is deployment friendly: it does not require any changes to the network fabric; yet, its performance is comparable to, or better than, the state-of-the-art protocols that require changes to network elements (e.g., pFabric). We evaluate PASE using simulations and testbed experiments. Our results show that PASE performs well for a wide range of application workloads and network settings.
Pulsed eddy current empirical modeling

The pulsed eddy current responses to varying material thickness and conductivity are modeled using an electrical circuit ideal transformer non-linear model. The Levenberg-Marquardt algorithm is used to curve fit the experimental signal to the model. The resulting synthetic signal is examined for its ability to preserve experimental signal features such as lift-off point of intersection (LOI), a pulsed eddy current signal feature used successfully in NDE of corrosion, cracks, thickness and conductivity measurements. The method is tested on specimens for its ability to reproduce inspection images using synthetic signals in lieu of experimental signals. This procedure conserves data storage space and allows rapid analysis of images using equations.
Educationally enhanced virtual worlds

Virtual worlds continue to attract considerable interest as an innovative means of engaging students through the use of immersive, 3D, collaborative environments. They allow for the dynamic creation of content and for that content to be programmed. Second Life is the dominant virtual world technology in use, and whilst attractive in that it is a ready-made — albeit commercial — service, it was not designed for educational use and has significant social and technical drawbacks when used for that purpose. As such, we have been researching the serious use of OpenSim as an alternative virtual world for Computer Science education. OpenSim is a free, open source software development project which supports self-hosting and maintenance of virtual worlds. This paper explains our rationale for using OpenSim and reports on our experiences to date. It includes a feature comparison between OpenSim and Second Life as an aid for those wishing to exploit virtual worlds in the Computer Science curriculum.
A Valid Candidate Approach to Mining Bi-Directional Traversal Patterns on the WWW

Mining traversal patterns is one of important topics in Web mining. It focuses on how to find the Web page sequences which are frequently browsed by users. In this paper, we propose two algorithms for mining traversal patterns. For the first algorithm, SpeedTracer*-I, it is a revised version of the SpeedTracer algorithm. It directly generates and counts all candidate patterns from user sessions. Moreover, it improves the checking step when candidate patterns are generated. Next, based on the SpeedTracer*-I algorithm, we propose the SpeedTracer*-II algorithm, which improves the performance of the SpeedTracer*-I algorithm by decreasing the times to scan the database. From the simulation results, we show that the SpeedTracer*-I algorithm needs less processing time than the SpeedTracer algorithm. Moreover, the SpeedTracer*-II algorithm needs less processing time than SpeedTracer*-I and Apriori-like algorithms (e.g., FS and FDLP algorithms). (keywords: association rules, data mining, traversal patterns, Web mining, WWW)