Miracle-dz/UniFAR-FTUs huggingface dataset:
Progressive Pseudolithiasis Associated with the Intravenous Administration of Ceftriaxone in Patients with Central Nervous System Infections

We report four adult cases of ceftriaxone (CTRX)-induced pseudolithiasis and nephrolithiasis. With the exception of case 1, none of our cases showed abdominal symptoms. Our patients, who had central nervous system (CNS) infections, had been treated with CTRX (4 g/day) for 35-69 days. CTRX-induced pseudolithiasis and nephrolithiasis can appear depending on the total dose of CTRX and the duration for which it is administered. Patients with bacterial CNS infections who are treated with CTRX are typically treated with higher doses for longer periods. It should be recognized that these patients are at higher risk of developing CTRX-induced pseudolithiasis and nephrolithiasis.
GAMALATE B6▪ Review of a GABAergic Product

To determine the LD50 of Gamalate B6 syrup, the experimentation animal chosen was the albino rat (Wistar), weighing between 180 and 200g. A group of 10 animals received the normal diet established in our laboratory. The administration of the active components of the specialty Gamalate B6 syrup was made through a gastric tube in a dilution at 12% in distilled water. With a dose of 6g/Kg of the active components, only one death occurred in 24h. This has been the highest dose administered, corresponding to 100cc/kg of the specialty Gamalate B6. Therefore, the LD50 of Gamalate B6 syrup by oral route in albino rat can be considered indeterminable.
Annotated catalog and bibliography of the cyclocephaline scarab beetles (Coleoptera, Scarabaeidae, Dynastinae, Cyclocephalini)

Abstract Cyclocephaline scarab beetles represent the second largest tribe of the subfamily Dynastinae, and the group includes the most speciose genus of dynastines, Cyclocephala. The period following publication of Sebő Endrődi’s The Dynastinae of the World has seen a huge increase in research interest on cyclocephalines, and much of this research has not been synthesized. The objective of this catalog and bibliography is to compile an exhaustive list of taxa in Cyclocephalini. This paper provides an updated foundation for understanding the taxonomy and classification of 14 genera and over 500 species in the tribe. It discusses the history of cataloging dynastine species, clarifies issues surrounding the neotype designations in Endrődi’s revision of Cyclocephalini, synthesizes all published distribution data for cyclocephaline species, and increases accessibility to the voluminous literature on the group by providing an easily searchable bibliography for each species. We propose the nomen novum Cyclocephala rogerpauli, new replacement name, for C. nigra Dechambre.
AGD-Library: A Library of Algorithms for Graph Drawing

A graph drawing algorithm produces a layout of a graph in twoor three-dimensional space that should be readable and easy to understand. Since the aesthetic criteria di er from one application area to another, it is unlikely that a de nition of the \optimal drawing" of a graph in a strict mathematical sense exists. A large number of graph drawing algorithms taking different aesthetic criteria into account have already been proposed. In this paper we describe the design and implementation of the AGD{Library, a library of Algorithms for Graph Drawing. The library o ers a broad range of existing algorithms for two-dimensional graph drawing and tools for implementing new algorithms. The library is written in C ++ using the LEDA platform for combinatorial and geometric computing ([16, 17]). The algorithms are implemented independently of the underlying visualization or graphics system by using a generic layout interface. Most graph drawing algorithms place a set of restrictions on the input graphs like planarity or biconnectivity. We provide a mechanism for declaring this precondition for a particular algorithm and checking it for potential input graphs. A drawing model can be characterized by a set of properties of the drawing. We call these properties the postcondition of the algorithm. There is support for maintaining and retrieving the postcondition of an algorithm.
Large-Area Synthesis and Growth Mechanism of Graphene by Chemical Vapor Deposition

There has been continuous progress in the development of different synthesis methods to readily produce graphene at a lower cost. Compared with the other methods, chemical vapor deposition (CVD) is an effective and powerful method of producing graphene and has attracted increased attention during the last decade. In this way, we can obtain good uniformity with a multitude of domains, excellent quality, and large scale of the pro - duced graphene. Meanwhile, it is also helping for large-area synthesis of single-crystal graphene. In the CVD method, precursors are typically absorbed on the surface followed by pyrolytic decomposition, which leads to the generation of absorption sites on the sur face and promotes the growth of continuous thin films.
A computationally efficient QRS detection algorithm for wearable ECG sensors

In this paper we present a novel Dual-Slope QRS detection algorithm with low computational complexity, suitable for wearable ECG devices. The Dual-Slope algorithm calculates the slopes on both sides of a peak in the ECG signal; And based on these slopes, three criterions are developed for simultaneously checking 1)Steepness 2)Shape and 3)Height of the signal, to locate the QRS complex. The algorithm, evaluated against MIT/BIH Arrhythmia Database, achieves a very high detection rate of 99.45%, a sensitivity of 99.82% and a positive prediction of 99.63%.
The complement system: an evolution in progress

The complement system, which consists of three independent but interacting pathways, constitutes a powerful arm of innate immunity. Its major function is to recognize and destroy pathogenic microorganisms as well as eliminate modified self-antigens. Although it is a fine-tuned system with innate capacity to discriminate self from non-self as well as danger from non-danger signals, an unwarranted activation can nonetheless occur and cause tissue destruction. To prevent such activation, specific regulators present both in plasma and on the cell surface tightly control it. Data accumulated over the past four decades have also shown that the complement system is capable of not only cross-talk with the activation cascades of plasma––i.e. blood coagulation, contact activation, and the kinin/kallikrein system––but also serving as a bridge between innate and adaptive immunity. It is for these reasons that the various activation steps of the complement system have been recently targeted for therapy to treat diseases in which the role of complement is beyond doubt. This trend will certainly continue for years to come, especially as novel concepts guiding the field into areas never contemplated before are continuing to be discovered.
SEEC: A General and Extensible Framework for Self-Aware Computing

Modern systems require applications to balance competing goals, e.g. achieving high performance and low power. Achieving this balance places an unrealistic burden on application programmers who must understand the power and performance implications of a variety of application and system actions (e.g. changing algorithms or allocating cores). To address this problem, we propose the Self-aware Computing framework, or SEEC. SEEC automatically and dynamically schedules actions to meet application specified goals. While other self-aware implementations have been proposed, SEEC is uniquely distinguished by its decoupled approach, which allows application and systems programmers to separately specify observations and actions, according to their expertise. SEEC’s runtime decision engine observes the system and schedules actions automatically, reducing programmer burden. This general and extensible decision engine employs both control theory and machine learning to reason about previously unseen applications and actions while automatically adapting to changes in both application and system models. This paper describes the SEEC framework and evaluates it in several case studies. SEEC is used to build an adaptive system that optimizes performance per Watt for the PARSEC benchmarks on multiple machines, achieving results as least 1.65× better than a classical control system. Additional studies show how SEEC can learn optimal resource allocation online and respond to fluctuations in the underlying hardware while managing multiple applications.
Nested Circular Array and Its Concentric Extension for Underdetermined Direction of Arrival Estimation

SUMMARY In this paper, a new array geometry is proposed which is capable of performing underdetermined Direction-Of-Arrival (DOA) estimation for the circular array conﬁguration. DOA estimation is a classical (cid:96) 1 -based optimization approach is extended to estimate DOAs us- ing NSCA. Simulations show that better performance for underdetermined DOA estimation is achieved using the proposed array geometry.
Digital image processing for visual prosthesis: Filtering implications

Investigators around the world are working on retinal neurostimulation as it may restore functional vision to the blind. The image is captured by a camera and after being processed, a series of electrical stimuli are applied to the surviving ganglion cells of the retina. This visual perception is expected to have low resolution. Therefore, there is a need of new algorithms that present the information contained in a visual scene understandable to humans. This study presents a novel multi-resolution algorithm based on wavelet analysis to extract the useful features of an image. Participants in this experiment were able to configure a filter bank to complete a set of everyday tasks. This study shows that wavelet-based algorithms may facilitate improved functional performance in prosthetic vision.
fraud in canadian nonprofit organizations as seen through the eyes of canadian newspapers , 1998 – 2008

chen, salterio, & murphy / Fraud in Canadian Nonprofit Organizations abstract Canada has one of the largest and most vibrant nonprofit and voluntary sectors in the world. It accounts for 6.8 percent of the nation’s gross domestic product (GDP) and employs 12 percent of Canada’s economically active population. With the significant role nonprofit organizations play in Canadian life and the increasing demand for accountability in nonprofit organizations, more attention is being drawn to nonprofit organizational fraud. Media coverage on fraud in nonprofit organizations is news that catches the public’s eye and can lead to a reduction in trust in those organizations over time. This study searched Canadian national and leading regional newspapers between 1998 and 2008 for reports about frauds committed on Canadian nonprofit organizations. The goal of the research was to better understand the nature of the frauds, the nonprofit organizations defrauded and the characteristics of the perpetrators, with the hope of alerting the nonprofit community to common trends.
Time- and space-optimal algorithms for the many-visits TSP

The many-visits traveling salesperson problem (MV-TSP) asks for an optimal tour of $n$ cities that visits each city $c$ a prescribed number $k_c$ of times. Travel costs may not be symmetric, and visiting a city twice in a row may incur a non-zero cost. The MV-TSP problem finds applications in scheduling, geometric approximation, and Hamiltonicity of certain graph families. The fastest known algorithm for MV-TSP is due to Cosmadakis and Papadimitriou (SICOMP, 1984). It runs in time $n^{O(n)} + O(n^3 \log \sum_c k_c )$ and requires $n^{\Omega(n)}$ space. The interesting feature of the Cosmadakis-Papadimitriou algorithm is its \emph{logarithmic} dependence on the total length $\sum_c k_c$ of the tour, allowing the algorithm to handle instances with very long tours, beyond what is tractable in the standard TSP setting. However, the \emph{superexponential} dependence on the number of cities in both its time and space complexity renders the algorithm impractical for all but the narrowest range of this parameter. In this paper we significantly improve on the Cosmadakis-Papadimitriou algorithm, giving an MV-TSP algorithm that runs in \emph{single-exponential} time with \emph{polynomial} space. More precisely, we obtain the running time $2^{O(n)} + O(n^3 \log{\sum_c k_c})$, with $O(n^2 \log{\sum_c k_c})$ space. Assuming the Exponential-time Hypothesis (ETH), both the time and space requirements of our algorithm are optimal. Our algorithm is deterministic, and arguably both simpler and easier to analyse than the original approach of Cosmadakis and Papadimitriou. It involves an optimization over oriented spanning trees of a graph and employs a recursive, centroid-based decomposition of trees.
Mitochondrial Genome Mutations Associated with Myocardial Infarction

Myocardial infarction is one of the clinical manifestations of coronary heart disease. In some cases, the cause of myocardial infarction may be atherosclerotic plaques which occurred in the human aorta. The association of mtDNA mutations with atherosclerotic lesions in human arteries was previously detected by our research group. In this study, we used samples of white blood cells collected from 225 patients with myocardial infarction and 239 control persons with no health complaints. DNA was isolated from the blood leukocyte samples. Then, PCR fragments of DNA were obtained. They contained the investigated regions of 11 mitochondrial genome mutations (m.5178C>A, m.3336T>C, m.652delG, m.12315G>A, m.14459G>A, m.652insG, m.14846G>A, m.13513G>A, m.1555A>G, m.15059G>A, m.3256C>T). According to the obtained results, three mutations of the human mitochondrial genome correlated with myocardial infarction. A positive correlation was observed for mutation m.5178C>A. At the same time, a highly significant negative correlation with myocardial infarction was observed for mutation m.14846G>A. One single-nucleotide substitution of m.12315G>A had a trend towards negative correlation. These mutations can potentially be useful for creating molecular/cellular models for studying the mechanisms of myocardial infarction and designing novel therapies. Moreover, these mutations can possibly be used for diagnostic purposes.
Real-time retrieval of similar videos with application to computer-aided retinal surgery

This paper introduces ongoing research on computer-aided ophthalmic surgery. In particular, a novel Content-Based Video Retrieval (CBVR) system is presented. Its purpose is the following: given a video stream captured by a digital camera monitoring the surgery, the system should retrieve, in real-time, similar video subsequences in video archives. In order to retrieve semantically-relevant videos, most existing CBVR systems rely on temporally flexible distance measures such as Dynamic Time Warping. These distance measures are slow and therefore do not allow real-time retrieval. In the proposed system, temporal flexibility is introduced in the way video subsequences are characterized, which allows the use of simple and fast distance measures. As a consequence, realtime retrieval of similar video subsequences, among hundreds of thousands of examples, is now possible. Besides, the proposed system is adaptive: a fast training procedure is presented. The system has been successfully applied to automated recognition of retinal surgery steps on a 69-video dataset: areas under the Receiver Operating Characteristic curves range from Az=0.809 to Az=0.989.
A Review on Classification and Comparison of Automatic Logo Based Document Image Retrieval Methods and other Applications

In this paper we provided an effective categorization of vast number of methods, techniques, transforms, algorithms, approaches and schemes available for the purpose of logo detection in various image processing applications like Authenticity of documents, Security for information, Traffic Surveillance (Intelligent Transportation System), Pattern recognition, Marketing, Medical Imaging, Satellite imaging, Drones and Ocean Imaging. We have highlighted the mostly used Scale Invariant Feature Transform (SIFT) and Speed Up Robust Feature (SURF) Algorithms along with the comparison between these two (SIFT and SURF) algorithms.
An Approach for Detecting Malicious Emails Using Runtime Monitoring with Hidden Data

Abstract : Computer systems continue to be at risk of attack by malicious software that are attached to email. Email has been determined to be the cause of 80% of computer virus infections. Millions of dollars are lost yearly due to the damage brought by malicious emails. Popular approaches toward the defense against malicious emails are antivirus scanners and server-based filters. Further, state-of-the-art methods are being employed to enhance security against malicious programs. However, despite efforts being subjected toward the protection of personal information in emails, malicious programs continue to pose a significant threat. This thesis presents the application of a hybrid of Runtime Monitoring and Machine Learning for monitoring patterns of malicious emails. The system is designed in a way that it gathers malicious emails to determine whether they are suspicious, unknown, or benign. The application of runtime monitoring helps reduce the chance that suspicious emails are spread and lowers the likelihood that users will be threatened. Patterns were developed in Rules4business.com to facilitate the detection of threats and apply rules to the identified rules validation, while at the same time tracking them. The runtime monitoring application system entails the detection of the malicious emails by assessing the pattern in which they are sent and qualifying them into different states identified as suspicious, unknown, or benign. Through the application of the system, it would be possible to eliminate threats posed to private individuals and corporations emanating from the malicious emails. We performed deterministic runtime monitoring, built a Hidden Markov Model (HMM), and performed runtime monitoring with hidden data. It is the reasoning about the patterns of malicious emails with hidden artifacts that provides the potential of providing improved classification
MASSAGE COMBINED WITH MUSCLE ENERGY TECHNIQUE COULD IMPROVE HEIGHT OF SEPAKTAKRAW SERVES

Flexibility of hamstring muscles is very important in the height of Sepaktakraw serves. The most beneficial type of stretching of lower limb muscles for this sport has not been verified. This study aimed to evaluate the effects of applied Thai massage combined with muscle energy technique (ATMMET) versus passive static stretching technique (PSST) on hamstring flexibility and the height of a Sepaktakraw serve. One hundred and eight healthy Sepaktakraw amateur athletes were randomly allocated to 3 comparison groups. Subjects in the ATMMET group and the PSST group received a 10 min session of corresponding intervention, whereas the subjects in the control group sat on a chair without intervention for the same period of time. Passive straight leg raise test (PSLR) and the height of Sepaktakraw serves were measured at 3 consecutive periods, consisting of pre-test, post-test, and 24 hours after intervention. An analysis of two-way repeated measures ANOVA found that there was a statistically significant difference in hamstring flexibility and the height of Sepaktakraw serves in both intervention groups but not in the control group. However, no significant differences were found between the three groups (p >0.05). We conclude that both ATMMET and PSST may improve hamstring flexibility and the height of a Sepaktakraw serve immediately.
Conflict-of-Interest Disclosures to The Journal of Bone & Joint Surgery: The Relevance of Industry-Reported Payments

Background: Academic journals such as The Journal of Bone & Joint Surgery (JBJS) require disclosures of financial relationships that authors report as potential conflicts of interest. Because industry payments can take various forms, including food and beverage, consulting, or research payments, the purpose of this study was to determine which categories of industry-reported payments were most frequently considered by authors as irrelevant to their specific publication, and therefore not included in their journal disclosures. Methods: Author disclosures were collected from scientific articles published in JBJS in 2016. Payments reported by authors as relevant to the published article were compared with industry-reported payments from the Centers for Medicare & Medicaid Services Open Payments Database (OPD), which includes all payments to eligible physicians in the United States. The number of authors with payments found in the OPD and appearing in publication-specific disclosures was determined for each payment type. Of note, OPD data are not indicative of relevance to a particular publication; therefore, the accuracy of author disclosures could not be determined in this study. Results: A total of 747 eligible authors were included; 60.5% of authors did not report at least 1 payment from their OPD report in their publication-specific disclosures, most frequently representing industry payments for food and beverage (55.7%), followed by travel and lodging (26.9%). Payments for consulting (16.3%), royalties (8.2%), research (8.4%), and ownership interests (1.5%) were not considered to be relevant disclosures for specific journal articles by authors at lower rates than those for food and beverage and for travel and lodging. Conclusions: Authors publishing in JBJS were more likely to conclude that industry-reported payments in the OPD for food and beverage and for travel and lodging were irrelevant for specific publications (as disclosed to the journal) than payments for consulting, royalties, research, and ownership interests.
Prevalence and Risk Factors for Methicillin-Resistant Staphylococcus aureus (MRSA) Infections in Custodial Populations: A Systematic Review

Methicillin-resistant Staphylococcus aureus (MRSA) in prisons can result in serious morbidity and death. We reviewed rates and risk factors for MRSA infection in custody, searching Medline, EMBASE, and CINAHL databases. Between 1997 and 2015, 17 studies reported MRSA skin and soft tissue infections (SSTIs), with four case reports of MRSA non-SSTI (necrotizing pneumonias, brain abscess, and epiduritis). Significant associations with MRSA SSTI were found: MRSA colonization, previous skin infection, sharing soap or personal items, SSTI presenting as an abscess or furuncle, younger age, non-Caucasian, overweight, communal laundering, infrequent handwashing, lower hygiene score. Recommendations: early identification, isolation, and treatment of skin infections at admission; education on maintaining skin integrity and presenting early with skin infections; increasing hygiene by not sharing items and encouraging handwashing; improved handling and disinfection of communal laundering; influenza vaccination for all prisoners and staff; and population-based longitudinal studies including younger detainees.
Probabilistic MIMO Symbol Detection With Expectation Consistency Approximate Inference

In this paper, we explore low-complexity probabilistic algorithms for soft symbol detection in high-dimensional multiple-input multiple-output (MIMO) systems. We present a novel algorithm based on the expectation consistency (EC) framework, which describes the approximate inference problem as an optimization over a nonconvex function. EC generalizes algorithms such as belief propagation and expectation propagation. For the MIMO symbol detection problem, we discuss feasible methods to find stationary points of the EC function and explore their tradeoffs between accuracy and speed of convergence. The accuracy is studied, first in terms of input–output mutual information and show that the proposed EC MIMO detector greatly improves state-of-the-art methods, with a complexity order cubic in the number of transmitting antennas. Second, these gains are corroborated by combining the probabilistic output of the EC detector with a low-density parity-check channel code.