nils-herrmann/clean_scirepeval huggingface dataset:
A randomized clinical trial of 5% topical minoxidil versus 2% topical minoxidil and placebo in the treatment of androgenetic alopecia in men.

Topical minoxidil solution 2% stimulates new hair growth and helps stop the loss of hair in individuals with androgenetic alopecia (AGA). Results can be variable, and historical experience suggests that higher concentrations of topical minoxidil may enhance efficacy.



The purpose of this 48-week, double-blind, placebo-controlled, randomized, multicenter trial was to compare 5% topical minoxidil with 2% topical minoxidil and placebo in the treatment of men with AGA.



A total of 393 men (18-49 years old) with AGA applied 5% topical minoxidil solution (n = 157), 2% topical minoxidil solution (n = 158), or placebo (vehicle for 5% solution; n = 78) twice daily. Efficacy was evaluated by scalp target area hair counts and patient and investigator assessments of change in scalp coverage and benefit of treatment.



After 48 weeks of therapy, 5% topical minoxidil was significantly superior to 2% topical minoxidil and placebo in terms of change from baseline in nonvellus hair count, patient rating of scalp coverage and treatment benefit, and investigator rating of scalp coverage. Hair count data indicate that response to treatment occurred earlier with 5% compared with 2% topical minoxidil. Additionally, data from a patient questionnaire on quality of life, global benefit, hair growth, and hair styling demonstrated that 5% topical minoxidil helped improve patients' psychosocial perceptions of hair loss. An increased occurrence of pruritus and local irritation was observed with 5% topical minoxidil compared with 2% topical minoxidil.



In men with AGA, 5% topical minoxidil was clearly superior to 2% topical minoxidil and placebo in increasing hair regrowth, and the magnitude of its effect was marked (45% more hair regrowth than 2% topical minoxidil at week 48). Men who used 5% topical minoxidil also had an earlier response to treatment than those who used 2% topical minoxidil. Psychosocial perceptions of hair loss in men with AGA were also improved. Topical minoxidil (5% and 2%) was well tolerated by the men in this trial without evidence of systemic effects.
Humans and Automation : Use , Misuse , Disuse ,

This paper addresses theoretical, empirical, and analytical studies pertaining to human use, misuse, disuse, and abuse of automation technology. Use refers to the voluntary activation or disengagement of automation by human operators. Trust, mental workload, and risk can influence automation use, but interactions between factors and large individual differences make prediction of automation use difficult. Misuse refers to overreliance on automation, which can result in failures of monitoring or decision biases. Factors affecting the monitoring of automation include workload, automation reliability and consistency, and the saliency of automation state indicators. Disuse, or the neglect or underutilization of automation, is commonly caused by alarms that activate falsely. This often occurs because the base rate of the condition to be detected is not considered in setting the trade-off between false alarms and omissions. Automation abuse, or the automation of functions by designers and implementation by managers without due regard for the consequences for human performance, tends to define the operator's roles as by-products of the automation. Automation abuse can also promote misuse and disuse of automation by human operators. Understanding the factors associated with each of these aspects of human use of automation can lead to improved system design, effective training methods, and judicious policies and procedures involving automation use.
Heat-oxidation stability of palm oil blended with extra virgin olive oil.

Rancimat induction time of palm oil (PO), several extra virgin olive oils (EV) and their binary blends have been determined at three different temperatures (120, 130 and 140°C). Analytical composition and oxidation stability of PO/EV blends were found to be a linear combination of the oil partners. Induction time of pure PO was always higher than those of EV oils and blends, in which induction time increased proportionally with the percentage of PO. However, induction time of 80% PO blend was similar to that of pure PO. Fatty acid composition appeared to be the most important factor affecting heat-oxidation stability and a saturated/unsaturated ratio near 1 was the optimally stable composition. Conversely, total phenols had a zero or negative role on the oxidative stability of the blends. Finally, in heat-oxidised oils significant losses of polyunsaturated fatty acids and formation of short-chain fatty acids were recorded.
An asynchronous dataflow FPGA architecture

We discuss the design of a high-performance field programmable gate array (FPGA) architecture that efficiently prototypes asynchronous (clockless) logic. In this FPGA architecture, low-level application logic is described using asynchronous dataflow functions that obey a token-based compute model. We implement these dataflow functions using finely pipelined asynchronous circuits that achieve high computation rates. This asynchronous dataflow FPGA architecture maintains most of the performance benefits of a custom asynchronous design, while also providing postfabrication logic reconfigurability. We report results for two asynchronous dataflow FPGA designs that operate at up to 400 MHz in a typical TSMC 0.25 /spl mu/m CMOS process.
A Low-Loss 50–70 GHz SPDT Switch in 90 nm CMOS

This paper presents an ultra-low-loss 50-70 GHz single-pole double-throw (SPDT) switch built using a standard 90 nm CMOS process. The switch is based on λ/4 transmission lines with shunt inductors at the output matching network. The SPDT switch results in a measured insertion loss of 1.5-1.6 dB at 53-60 GHz and <; 2.0 dB at 50-70 GHz. The measured isolation is >25 dB, and the output port-to-port isolation is > 27 dB at 50-70 GHz. The measured P1dB is 13.5 dBm with a corresponding IIP3 of 22.5 dBm at 60 GHz. The return loss is better than -8 dB at 50-70 GHz. The active chip area is 0.5 × 0.55 mm2 and can be reduced in future designs by folding the on λ/4 transmission lines. To our knowledge, this paper presents the lowest insertion loss 60 GHz SPDT in any CMOS technology.
A Low Power Array Multiplier Design using Modified Gate Diffusion Input ( GDI )

This paper proposes a new low power and low area 4x4 array multiplier designed using modified Gate diffusion Input (GDI) technique. By using GDI cell, the transistor count is greatly reduced. Basic GDI technique shows a drawback of low voltage swing at output which prevents it for use in multiple stage circuits efficiently. We have used modified GDI technique which shows full swing output and hence can be used in multistage circuits. The whole design is made and simulated in 180nm UMC technology at a supply voltage of 1.8V using Cadence Virtuoso Environment.
Self-presentation and emotional contagion on Facebook: new experimental measures of profiles' emotional coherence

Social Networks allow users to self-present by sharing personal contents with others which may add comments. Recent studies highlighted how the emotions expressed in a post affect others’ posts, eliciting a congruent emotion. So far, no studies have yet investigated the emotional coherence between wall posts and its comments. This research evaluated posts and comments mood of Facebook profiles, analyzing their linguistic features, and a measure to assess an excessive self-presentation was introduced. Two new experimental measures were built, describing the emotional loading (positive and negative) of posts and comments, and the mood correspondence between them was evaluated. The profiles ”empathy”, the mood coherence between post and comments, was used to investigate the relation between an excessive self-presentation and the emotional coherence of a profile. Participants publish a higher average number of posts with positive mood. To publish an emotional post corresponds to get more likes, comments and receive a coherent mood of comments, confirming the emotional contagion effect reported in literature. Finally, the more empathetic profiles are characterized by an excessive self-presentation, having more posts, and receiving more comments and likes. To publish emotional contents appears to be functional to receive more comments and likes, fulfilling needs of attention-seeking.
A Novel Microstrip Meander-Line Antenna With A Very High Relative Permittivity Substrate For 315-MHz Band Applications

This paper presents a design, simulation, implementation and measurement of a novel microstrip meander patch antenna for the application of sensor networks. The dimension of the microstrip chip antenna is 15 mm times 15 mm times 2 mm. The meander-type radiating patch is constructed on the upper layer of the 2 mm height substrate with 0.0 5 mm height metallic conduct lines. Because of using the very high relative permittivity substrate ( epsivr=90), the proposed antenna achieves 315 MHz band operations.
Design of Frequency Invariant Beamformers for Broadband Arrays

A new class of broadband arrays with frequency invariant beam pattern is proposed. By suitable substitutions, the beam pattern of a continuous sensor array can be regarded as the Fourier transform of its spatial and temporal parameters. For the design of practical discrete sensor arrays, it can be regarded as an approximation to the continuous sensor case and a simple design method is provided, which can be applied to linear, rectangular and cubic broadband arrays.
Distilling the neural correlates of consciousness

Solving the problem of consciousness remains one of the biggest challenges in modern science. One key step towards understanding consciousness is to empirically narrow down neural processes associated with the subjective experience of a particular content. To unravel these neural correlates of consciousness (NCC) a common scientific strategy is to compare perceptual conditions in which consciousness of a particular content is present with those in which it is absent, and to determine differences in measures of brain activity (the so called "contrastive analysis"). However, this comparison appears not to reveal exclusively the NCC, as the NCC proper can be confounded with prerequisites for and consequences of conscious processing of the particular content. This implies that previous results cannot be unequivocally interpreted as reflecting the neural correlates of conscious experience. Here we review evidence supporting this conjecture and suggest experimental strategies to untangle the NCC from the prerequisites and consequences of conscious experience in order to further develop the otherwise valid and valuable contrastive methodology.
An Analysis of BitTorrent’s Two Kademlia-Based DHTs

Despite interest in structured peer-to-peer overlays and t heir scalability to millions of nodes, few, if any, overlays operate at that scale. T his paper considers the distributed hash table extensions supported by modern BitT orrent clients, which implement a Kademlia-style structured overlay network amo ng millions of BitTorrent users. As there are two disjoint Kademlia-based DHTs in use, we collected two weeks of traces from each DHT. We examine churn, reachabi lity, latency, and liveness of nodes in these overlays, and identify a variety o f problems, such as median lookup times of over a minute. We show that Kademlia’s ch oi e of iterative routing and its lack of a preferential refresh of its local ne ighborhood cause correctness problems and poor performance. We also identify im ple entation bugs, design issues, and security concerns that limit the effecti v ness of these DHTs and we offer possible solutions for their improvement.
BPMN 2.0: The state of support and implementation

The Business Process Model and Notation 2.0 (BPMN) standard has been hailed as a major step in business process modeling and automation. Recently, it has also been accepted as an ISO standard. The expectation is that vendors of business process management systems (BPMS) will switch to the new standard and natively support its execution in process engines. This paper presents an analysis of the current state and evolution of BPMN 2.0 support and implementation. We investigate how BPMN 2.0 implementers deal with the standard, showing that native BPMN 2.0 execution is an exception. Only three out of 47 BPMS considered support the execution format defined in the standard, although all of them claim to comply to the BPMN 2.0 standard. Furthermore, we evaluate three process engines that do provide native BPMN support, namely camunda BPM, jBPM and activiti, and examine the evolution of their degree of support over a period of more than three years. This lets us delimit the areas of the standard that are considered important by the implementers. Since there is only a limited increase in supported features over the past years, it seems that the implementation of the standard is more or less concluded from the perspective of the implementers. Hence, it is unlikely that features which are not available by now will be implemented in the future.
TREC 2018 News Track

While more and more people are relying on social media for news feeds, serious news consumers still resort to well-established news outlets for more accurate and in-depth reporting and analyses. They may also look for reports on related events that have happened before and other background information in order to better understand the event being reported. Many news outlets already create sidebars and embed hyperlinks to help news readers, often with manual efforts. Technologies in IR and NLP already exist to support those features, but standard test collections do not address the tasks of modern news consumption. To help advance such technologies and transfer them to news reporting, NIST, in partnership with the Washington Post, is starting a new TREC track in 2018 known as the News Track.
Ultrasound-Guided Prolotherapy for Acromial Enthesopathy and Acromioclavicular Joint Arthropathy: A Single-Arm Prospective Study.

Prolotherapy is an injection-based complementary treatment for various musculoskeletal diseases. The aim of this study was to evaluate the therapeutic efficacy of ultrasound-guided prolotherapy in the treatment of acromial enthesopathy and acromioclavicular joint arthropathy.



Thirty-one patients with chronic moderate-to-severe shoulder pain were recruited from September 2015 to September 2017. Ultrasound-guided prolotherapy was performed by injecting 10 mL of a 15% dextrose solution into the acromial enthesis of the deltoid or acromioclavicular joint capsule aseptically. Prolotherapy was given in 2 sessions separated by a 1-month interval. The pretreatment-to-posttreatment change in the pain visual analog scale (VAS) score was recorded as the primary outcome. The mean follow-up duration was 61.8 days. A paired t test was used to assess the difference in pretreatment and posttreatment VAS scores. A univariate logistic regression analysis was conducted to identify the demographic variables associated with substantial pain reduction after the intervention. Substantial pain reduction was defined as a posttreatment VAS score of 3 or less.



Twenty of the 31 patients reported substantial pain reduction without adverse effects after the intervention. The mean VAS score reduction ± SD was 4.3 ± 2.6 (pretreatment, 6.8 ± 1.5; posttreatment, 2.5 ± 2.1; P < .01).



Ultrasound-guided prolotherapy with a 15% dextrose solution is an effective and safe therapeutic option for moderate-to-severe acromial enthesopathy and acromioclavicular joint arthropathy.
The Spatial Dimension of Online Echo Chambers

This study explores the geographic dependencies of echo-chamber communication on Twitter during the Brexit referendum campaign. We review the literature on filter bubbles, echo chambers, and polarization to test five hypotheses positing that echo-chamber communication is associated with homophily in the physical world, chiefly the geographic proximity between users advocating sides of the campaign. The results support the hypothesis that echo chambers in the Leave campaign are associated with geographic propinquity, whereas in the Remain campaign the reverse relationship was found. This study presents evidence that geographically proximate social enclaves interact with polarized political discussion where echo-chamber communication is observed. The article concludes with a discussion of these findings and the contribution to research on filter bubbles and echo chambers.
Unsupervised Feature Selection by Preserving Stochastic Neighbors

Feature selection is an important technique for alleviating the curse of dimensionality. Unsupervised feature selection is more challenging than its supervised counterpart due to the lack of labels. In this paper, we present an effective method, Stochastic Neighborpreserving Feature Selection (SNFS), for selecting discriminative features in unsupervised setting. We employ the concept of stochastic neighbors and select the features that can best preserve such stochastic neighbors by minimizing the KullbackLeibler (KL) Divergence between neighborhood distributions. The proposed approach measures feature utility jointly in a nonlinear way and discriminative features can be selected due to its ’push-pull’ property. We develop an efficient algorithm for optimizing the objective function based on projected quasi-Newton method. Moreover, few existing methods provide ways for determining the optimal number of selected features and this hampers their utility in practice. Our approach is equipped with a guideline for choosing the number of features, which provides nearly optimal performance in our experiments. Experimental results show that the proposed method outperforms state-ofthe-art methods significantly on several realworld datasets.
Factors Influencing the Use of Prenatal Care: A Systematic Review

Review article  Prenatal care is a key strategy for achieving public health goals, primary healthcare objectives, and the Millennium Development Goals. The aim of this study was to investigate the factors influencing the use of prenatal care services in order to design suitable interventions and promote the use of these services.  In this systematic quantitative literature review, studies published in years 2010-2014 were evaluated. For this purpose, two international electronic databases, i.e., Scopus and PubMed, were explored to find English-language articles by using relevant keywords; moreover, the reference lists of the articles were hand-searched. We reviewed all cross-sectional and prospective studies, which focused on factors associated with the use of prenatal care services within the specified period of time.  In total, 17 relevant articles were included in our review. The results showed that late initiation and inadequate use of prenatal care services are independently associated with multiple variables, including demographic characteristics, socioeconomic factors, predisposing cultural and religious factors, social support, factors related to healthcare providers, women’s awareness and attitude, unintended pregnancy, high-risk medical or obstetric history, and health behaviors.  Based on the literature review, proper use of prenatal care cannot be achieved merely by establishing healthcare centers. Utilization of maternal health services may be achieved and improved via developing socioeconomic factors and addressing patients' basic needs including education and financial independence.  21-Jul-2015 Accepted: 14-Nov-2015
An Efficient Cross-lingual Model for Sentence Classification Using Convolutional Neural Network

In this paper, we propose a cross-lingual convolutional neural network (CNN) model that is based on word and phrase embeddings learned from unlabeled data in two languages and dependency grammar. Compared to traditional machine translation (MT) based methods for cross lingual sentence modeling, our model is much simpler and does not need parallel corpora or language specific features. We only use a bilingual dictionary and dependency parser. This makes our model particularly appealing for resource poor languages. We evaluate our model using English and Chinese data on several sentence classification tasks. We show that our model achieves a comparable and even better performance than the traditional MT-based method.
Survey on Digital Image Processing in sports.

Digital Image Processing has found to be useful in many domains. In sports, it can either be used as an analytical tool to determine strategic instances in a game or can be used in the broadcast of video to television viewers. Modern day coverage of sports involves multiple cameras and an array of technologies to support it, since manually going through every video coming to a station would be a near-impossible task, a wide range of Digital Image Processing algorithms are applied to do the same. Highlight Generation and Event Detection are the foremost areas in sports where a multitude of DIP algorithms exist. This study provides an insight into the applications of Digital Image Processing in Sports, concentrating on algorithms related to video broadcast while listing their advantages and drawbacks.
New trends in precision agriculture: a novel cloud-based system for enabling data storage and agricultural task planning and automation

It is well-known that information and communication technologies enable many tasks in the context of precision agriculture. In fact, more and more farmers and food and agriculture companies are using precision agriculture-based systems to enhance not only their products themselves, but also their means of production. Consequently, problems arising from large amounts of data management and processing are arising. It would be very useful to have an infrastructure that allows information and agricultural tasks to be efficiently shared and handled. The cloud computing paradigm offers a solution. In this study, a cloud-based software architecture is proposed with the aim of enabling a complete crop management system to be deployed and validated. Such architecture includes modules developed by using Google App Engine, which allows the information to be easily retrieved and processed and agricultural tasks to be properly defined and planned. Additionally, Google’s Datastore (which ensures a high scalability degree), hosts both information that describes such agricultural tasks and agronomic data. The architecture has been validated in a system that comprises a wireless sensor network with fixed nodes and a mobile node on an unmanned aerial vehicle (UAV), deployed in an agricultural farm in the Region of Murcia (Spain). Such a network allows soil water and plant status to be monitored. The UAV (capable of executing missions defined by an administrator) is useful for acquiring visual information in an autonomous manner (under operator supervision, if needed). The system performance has been analysed and results that demonstrate the benefits of using the proposed architecture are detailed.
Self-Test and Diagnosis for Self-Aware Systems

<italic>Editor’s note:</italic> Self-testing hardware has a long tradition as a complement to manufacturing testing based on test stimuli and response analysis. Today, it is a mature field and many complex SoCs have self-testing structures built-in (BIST). For self-aware SoCs this is a key technology, allowing the system to distinguish between correct and erroneous behavior. This survey article reviews the state of the art and shows how these techniques are to be generalized to facilitate self-awareness. —<italic>Axel Jantsch</italic>, <italic>TU Wien</italic> —<italic>Nikil Dutt, University of California at Irvine</italic>