nils-herrmann/clean_scirepeval huggingface dataset:
Efficacy of artemether–lumefantrine therapy for the treatment of uncomplicated Plasmodium falciparum malaria in Southwestern Ethiopia

The development and spread of chloroquine-resistant Plasmodium falciparum threatens the health of millions of people and poses a major challenge to the control of malaria. Monitoring drug efficacy in 2-year intervals is an important tool for establishing rational anti-malarial drug policies. This study addresses the therapeutic efficacy of artemether-lumefantrine (AL) for the treatment of Plasmodium falciparum in southwestern Ethiopia. A 28-day in vivo therapeutic efficacy study was conducted from September to December, 2011, in southwestern Ethiopia. Participants were selected for the study if they were older than 6 months, weighed more than 5 kg, symptomatic, and had microscopically confirmed, uncomplicated P. falciparum. All 93 eligible patients were treated with AL and followed for 28 days. For each patient, recurrence of parasitaemia, the clinical condition, and the presence of gametoytes were assessed on each visit during the follow-up period. PCR was conducted to differentiate re-infection from recrudescence. Seventy-four (83.1 %) of the study subjects cleared fever by day 1, but five (5.6 %) had fever at day 2. All study subjects cleared fever by day 3. Seventy-nine (88.8 %) of the study subjects cleared the parasite by day 1, seven (7.9 %) were blood-smear positive by day 1, and three (3.4 %) were positive by day 2. In five patients (5.6 %), parasitaemia reappeared during the 28-day follow-up period. From these five, one (1.1 %) was a late clinical failure, and four (4.5 %) were a late parasitological failure. On the day of recurrent parasitaemia, the level of chloroquine/desethylchloroquine (CQ-DCQ) was above the minimum effective concentration (>100 ng/ml) in one patient. There were 84 (94.4 %) adequate clinical and parasitological responses. The 28-day, PCR-uncorrected (unadjusted by genotyping) cure rate was 84 (94.4 %), whereas the 28-day, PCR-corrected cure rate was 87 (97.8 %). Of the three re-infections, two (2.2 %) were due to P. falciparum and one (1.1 %) was due to P. vivax. From 89 study subjects, 12 (13.5 %) carried P. falciparum gametocytes at day 0, whereas the 28-day gametocyte carriage rate was 2 (2.2 %). Years after the introduction of AL in Ethiopia, the finding of this study is that AL has been highly effective in the treatment of uncomplicated P. falciparum malaria and reducing gametocyte carriage in southwestern Ethiopia.
MobileAppScrutinator: A Simple yet Efficient Dynamic Analysis Approach for Detecting Privacy Leaks across Mobile OSs

Smartphones, the devices we carry everywhere with us, are being heavily tracked and have undoubtedly become a major threat to our privacy. As “Tracking the trackers” has become a necessity, various static and dynamic analysis tools have been developed in the past. However, today, we still lack suitable tools to detect, measure and compare the ongoing tracking across mobile OSs. To this end, we propose MobileAppScrutinator, based on a simple yet efficient dynamic analysis approach, that works on both Android and iOS (the two most popular OSs today). To demonstrate the current trend in tracking, we select 140 most representative Apps available on both Android and iOS AppStores and test them with MobileAppScrutinator. In fact, choosing the same set of apps on both Android and iOS also enables us to compare the ongoing tracking on these two OSs. Finally, we also discuss the effectiveness of privacy safeguards available on Android and iOS. We show that neither Android nor iOS privacy safeguards in their present state are completely satisfying.
Molecular detection of Dirofilaria immitis, Dirofilaria repens and Setaria tundra in mosquitoes from Germany

As a result of globalization and climate change, Dirofilaria immitis and Dirofilaria repens, the causative agents of dirofilariosis in Europe, continue to spread from endemic areas in the Mediterranean to northern and northeastern regions of Europe where autochthonous cases of dirofilarial infections have increasingly been observed in dogs and humans. Whilst D. repens was recently reported from mosquitoes in putatively non-endemic areas, D. immitis has never been demonstrated in mosquitoes from Europe outside the Mediterranean. From 2011 to 2013, mosquitoes collected within the framework of a German national mosquito monitoring programme were screened for filarial nematodes using a newly designed filarioid-specific real-time PCR assay. Positive samples were further processed by conventional PCR amplification of the cytochrome c oxidase subunit I (COI) gene, amplicons were sequenced and sequences blasted against GenBank. Approximately 17,000 female mosquitoes were subjected to filarial screening. Out of 955 pools examined, nine tested positive for filariae. Two of the COI sequences indicated D. immitis, one D. repens and four Setaria tundra. Two sequences could not be assigned to a known species due to a lack of similar GenBank entries. Whilst D. immitis and the unknown parasites were detected in Culex pipiens/torrentium, D. repens was found in a single Anopheles daciae and all S. tundra were demonstrated in Aedes vexans. All positive mosquitoes were collected between mid-June and early September. The finding of dirofilariae in German mosquitoes implies the possibility of a local natural transmission cycle. While the routes of introduction to Germany and the origin of the filariae cannot be determined retrospectively, potential culicid vectors and reservoir hosts must prospectively be identified and awareness among physicians, veterinarians and public health personnel be created. The health impact of S. tundra on the indigenous cervid fauna needs further investigation.
Rotman lens design and simulation in software [Application Notes]

Since its invention in the early 1960s (Rotman and Turner, 1963), the Rotman Lens has proven itself to be a useful beamformer for designers of electronically scanned arrays. Inherent in its design is a true time delay phase shift capability that is independent of frequency and removes the need for costly phase shifters to steer a beam over wide angles. The Rotman Lens has a long history in military radar, but it has also been used in communication systems. This article uses the developed software to design and analyze a microstrip Rotman Lens for the Ku band. The initial lens design will come from a tool based on geometrical optics (GO). A second stage of analysis will be performed using a full wave finite difference time domain (FDTD) solver. The results between the first-cut design tool and the comprehensive FDTD solver will be compared, and some of the design trades will be explored to gauge their impact on the performance of the lens.
Epigenetic regulation of cardiac fibrosis.

Cardiac fibrosis is characterized by excessive extracellular matrix accumulation that ultimately destroys tissue architecture and eventually abolishes normal function. In recent years, despite the underlying mechanisms of cardiac fibrosis are still unknown, numerous studies suggest that epigenetic modifications impact on the development of cardiac fibrosis. Epigenetic modifications control cell proliferation, differentiation, migration, and so on. Epigenetic modifications contain three main processes: DNA methylation, histone modifications, and silencing by microRNAs. We here outline the recent work pertaining to epigenetic changes in cardiac fibrosis. This review focuses on the epigenetic regulation of cardiac fibrosis.
Nonlinear time-series analysis revisited.

In 1980 and 1981, two pioneering papers laid the foundation for what became known as nonlinear time-series analysis: the analysis of observed data-typically univariate-via dynamical systems theory. Based on the concept of state-space reconstruction, this set of methods allows us to compute characteristic quantities such as Lyapunov exponents and fractal dimensions, to predict the future course of the time series, and even to reconstruct the equations of motion in some cases. In practice, however, there are a number of issues that restrict the power of this approach: whether the signal accurately and thoroughly samples the dynamics, for instance, and whether it contains noise. Moreover, the numerical algorithms that we use to instantiate these ideas are not perfect; they involve approximations, scale parameters, and finite-precision arithmetic, among other things. Even so, nonlinear time-series analysis has been used to great advantage on thousands of real and synthetic data sets from a wide variety of systems ranging from roulette wheels to lasers to the human heart. Even in cases where the data do not meet the mathematical or algorithmic requirements to assure full topological conjugacy, the results of nonlinear time-series analysis can be helpful in understanding, characterizing, and predicting dynamical systems.
Donor evaluation in heart transplantation: The end of the beginning.

The evaluation of organ donors is of critical importance in all areas of solid organ transplantation. Donor characteristics have been shown to have robust effects on heart transplant recipient outcomes, and evaluation of the donor for suitability for heart transplantation is therefore very comprehensive. The donor evaluation process is composed of several steps, beginning with the identification of a potential organ donor and ending with the transplantation of a donor heart. The purpose of this review is to dissect the complex process of donor evaluation into its component steps and to highlight the diverse approaches used by transplant clinicians around the world to optimize outcomes at each step. We provide a summary of donor characteristics that have been associated with increased recipient mortality and discuss areas of uncertainty. Recent additions to the literature present novel insights and solutions to vexing problems in donor evaluation, such as how to make a more accurate assessment of allograft quality. Continued advancement in the evaluation of donors is essential to maintain heart transplantation as a viable therapy that provides excellent long-term survival for patients with end-stage heart failure.
An Introduction to Physiological Player Metrics for Evaluating Games

Do you remember insult sword fi ghting in Monkey Island? The moment when you got off the elevator in the fourth mission of Call of Duty: Modern Warfare 2? Your romantic love affair with Leliana or Alistair in Dragon Age? Dancing as Madison for Paco in his nightclub in Heavy Rain? Climbing and fi ghting Cronos in God of War 3? Some of the most memorable moments from successful video games, have a strong emotional impact on us. It is only natural that game designers and user researchers are seeking methods to better understand the positive and negative emotions that we feel when we are playing games. While game metrics provide excellent methods and techniques to infer behavior from the interaction of the player in the virtual game world, they cannot infer or see emotional signals of a player. Emotional signals are observable changes in the state of the human player, such as facial expressions, body posture, or physiological changes in the player’s body. The human eye can observe facial expression, gestures or human sounds that could tell us how a player is feeling, but covert physiological changes are only revealed to us when using sensor equipment, such as
Sentiment analysis and visualisation in a backchannel system

Digital backchannel systems have been proven useful to help a lecturer gather real-time online feedback from students in a lecture environment. However, the large number of posts made during a lecture creates a major hurdle for the lecturer to promptly analyse them and take actions accordingly in time. To tackle this problem, we propose a solution that analyses the sentiment of students' feedback and visualises the morale trend of the student population to the lecturer in real time. In this paper, we present the user interface for morale visualisation and playback of ranked posts as well as the techniques for sentiment analysis and morale computation.
Conduction loss reduction technique with small resonant capacitor for a phase shift full bridge converter

Conduction loss reduction technique using a small resonant capacitor for a phase shift full bridge converter with clamp diodes is proposed in this paper. The proposed technique can be implemented simply by adding a small resonant capacitor beside the leakage inductor of transformer. Since the voltage across the small resonant capacitor is applied to the small leakage inductor of transformer during freewheeling period, the primary current can be decreased rapidly. This results in the reduced conduction loss on the secondary side of transformer while the proposed technique can still guarantee the wide ZVS ranges. The operational principles and analysis are presented. Experimental results show that the proposed reduction technique of conduction loss can be operated properly.
WebVision Database: Visual Learning and Understanding from Web Data

In this paper, we present a study on learning visual recognition models from large scale noisy web data. We build a new database called WebVision, which contains more than 2.4 million web images crawled from the Internet by using queries generated from the 1, 000 semantic concepts of the ILSVRC 2012 benchmark. Meta information along with those web images (e.g., title, description, tags, etc.) are also crawled. A validation set and test set containing human annotated images are also provided to facilitate algorithmic development. Based on our new database, we obtain a few interesting observations: 1) the noisy web images are sufficient for training a good deep CNN model for visual recognition; 2) the model learnt from our WebVision database exhibits comparable or even better generalization ability than the one trained from the ILSVRC 2012 dataset when being transferred to new datasets and tasks; 3) a domain adaptation issue (a.k.a., dataset bias) is observed, which means the dataset can be used as the largest benchmark dataset for visual domain adaptation. Our new WebVision database and relevant studies in this work would benefit the advance of learning state-of-the-art visual models with minimum supervision based on web data.
Third-party inspection as an alternative to command and control regulation.

This article makes the case for relying on decentralized market-based incentive mechanisms to supplement performance-based regulations for promoting industrial safety. In particular, we examine how third-party inspections, coupled with insurance protection, can encourage firms to reduce their risks from accidents and disasters. Our proposal is thus an example of a management-based regulatory strategy where the locus of decision making is shifted from the regulator to firms, which are now required to do their own planning as to how they will meet a set of standards or regulations. The third-party inspections we have in mind would take the form of a voluntary contractual relationship between the firm and the party auditing the facility in place of relying solely on the regulatory agency as enforcer. In undertaking the inspection, the third party can simply play the role of informing the firm that it is in violation of a regulation or, going one step further, it can assist the firm in developing a program for reducing its risks to comply with a particular standard or regulation. The passage of Section 112(r) of the Clean Air Act Amendments (CAAA) of 1990 offers an opportunity to implement such a program. This legislation created two new federal regulatory programs aimed at preventing releases of hazardous chemicals: the Occupational Health and Safety Administration (OSHA) Process Safety Management (PSM) standard and the U.S Environmental Protection Agency (EPA)  The OSHA program was enacted in 1992 and requires facilities containing large quantities of highly hazardous chemicals to implement accident prevention and emergency response measures to protect workers. The EPA Risk Management Program regulation, published in 1996, borrowed the same accident prevention concepts and language from PSM but went beyond the OSHA program. It also required facilities to perform a hazard assessment, estimate consequences from accidents, and submit a summary report, called the Risk Management Plan (RMP), to EPA by June 21, 1999. The challenge is how to encourage compliance with these regulations so that firms will be operating in a safer manner. The article proceeds as follow. In the next section we make the case for well-enforced RMPs and then show in Section 3 why firms may not voluntarily comply with this regulation. Section 4 shows analytically that third-party inspections coupled with insurance provide economic incentives for many firms to undertake RMPs voluntarily and encourages the remaining recalcitrant firms to comply with the regulation. Section 5 illustrates implementation challenges in utilizing third-party inspections while at the same time pointing to their success in a variety of different contexts. The concluding section discusses a set of open issues and questions, the need for future studies, and what analysts and practitioners can learn from this work.
Artificial Intelligence and Machine Learning in Radiology: Opportunities, Challenges, Pitfalls, and Criteria for Success.

Worldwide interest in artificial intelligence (AI) applications, including imaging, is high and growing rapidly, fueled by availability of large datasets ("big data"), substantial advances in computing power, and new deep-learning algorithms. Apart from developing new AI methods per se, there are many opportunities and challenges for the imaging community, including the development of a common nomenclature, better ways to share image data, and standards for validating AI program use across different imaging platforms and patient populations. AI surveillance programs may help radiologists prioritize work lists by identifying suspicious or positive cases for early review. AI programs can be used to extract "radiomic" information from images not discernible by visual inspection, potentially increasing the diagnostic and prognostic value derived from image datasets. Predictions have been made that suggest AI will put radiologists out of business. This issue has been overstated, and it is much more likely that radiologists will beneficially incorporate AI methods into their practices. Current limitations in availability of technical expertise and even computing power will be resolved over time and can also be addressed by remote access solutions. Success for AI in imaging will be measured by value created: increased diagnostic certainty, faster turnaround, better outcomes for patients, and better quality of work life for radiologists. AI offers a new and promising set of methods for analyzing image data. Radiologists will explore these new pathways and are likely to play a leading role in medical applications of AI.
A translational approach to micro-inflammation in end-stage renal disease: molecular effects of low levels of interleukin-6.

Inflammation plays a key role in the progression of cardiovascular disease, the leading cause of mortality in ESRD (end-stage renal disease). Over recent years, inflammation has been greatly reduced with treatment, but mortality remains high. The aim of the present study was to assess whether low (<2 pg/ml) circulating levels of IL-6 (interleukin-6) are necessary and sufficient to activate the transcription factor STAT3 (signal transducer and activator of transcription 3) in human hepatocytes, and if this micro-inflammatory state was associated with changes in gene expression of some acute-phase proteins involved in cardiovascular mortality in ESRD. Human hepatocytes were treated for 24 h in the presence and absence of serum fractions from ESRD patients and healthy subjects with different concentrations of IL-6. The specific role of the cytokine was also evaluated by cell experiments with serum containing blocked IL-6. Furthermore, a comparison of the effects of IL-6 from patient serum and rIL-6 (recombinant IL-6) at increasing concentrations was performed. Confocal microscopy and Western blotting demonstrated that STAT3 activation was associated with IL-6 cell-membrane-bound receptor overexpression only in hepatocytes cultured with 1.8 pg/ml serum IL-6. A linear activation of STAT3 and IL-6 receptor expression was also observed after incubation with rIL-6. Treatment of hepatocytes with 1.8 pg/ml serum IL-6 was also associated with a 31.6-fold up-regulation of hepcidin gene expression and a 8.9-fold down-regulation of fetuin-A gene expression. In conclusion, these results demonstrated that low (<2 pg/ml) circulating levels of IL-6, as present in non-inflamed ESRD patients, are sufficient to activate some inflammatory pathways and can differentially regulate hepcidin and fetuin-A gene expression.
How a Cockpit Remembers Its Speeds

Cognitive science normally takes the individual agent as its unit of analysis. In many human endeavors, however, the outcomes of interest are not determined entirely by the information processing properties of individuals. Nor can they be inferred from the properties of the individual agents, alone, no matter how detailed the knowledge of the properties of those individuals may be. In commercial aviation, for example, the successful completion of a flight is produced by a system that typically includes two or more pilots interacting with each other and with a suite of technological devices. This article presents a theoretical framework that tokes a distributed, socio-technical system rather than an individual mind as its primary unit of analysis. This framework is explicitly cognitive in that it is concerned with how information is represented and how representations are transformed and propagated in the performance of tasks. An analysis of a memory task in the cockpit of a commercial airliner shows how the cognitive properties of such distributed systems can differ radically from the cognitive properties of the individuals who inhabit them.
Supporting Trust in Autonomous Driving

Autonomous cars will likely hit the market soon, but trust into such a technology is one of the big discussion points in the public debate. Drivers who have always been in complete control of their car are expected to willingly hand over control and blindly trust a technology that could kill them. We argue that trust in autonomous driving can be increased by means of a driver interface that visualizes the car’s interpretation of the current situation and its corresponding actions. To verify this, we compared different visualizations in a user study, overlaid to a driving scene: (1) a chauffeur avatar, (2) a world in miniature, and (3) a display of the car’s indicators as the baseline. The world in miniature visualization increased trust the most. The human-like chauffeur avatar can also increase trust, however, we did not find a significant difference between the chauffeur and the baseline.
Interpersonal Synchrony: A Survey of Evaluation Methods across Disciplines

Synchrony refers to individuals' temporal coordination during social interactions. The analysis of this phenomenon is complex, requiring the perception and integration of multimodal communicative signals. The evaluation of synchrony has received multidisciplinary attention because of its role in early development, language learning, and social connection. Originally studied by developmental psychologists, synchrony has now captured the interest of researchers in such fields as social signal processing, robotics, and machine learning. This paper emphasizes the current questions asked by synchrony evaluation and the state-of-the-art related methods. First, we present definitions and functions of synchrony in youth and adulthood. Next, we review the noncomputational and computational approaches of annotating, evaluating, and modeling interactional synchrony. Finally, the current limitations and future research directions in the fields of developmental robotics, social robotics, and clinical studies are discussed.