nils-herrmann/clean_scirepeval huggingface dataset:
Margins of stability of inner-current loop of peak current-mode controlled PWM dc-dc converters

This paper presents expressions for the limiting value of the duty cycle and the minimum value of the slope compensation for marginally stable operation as well as for the normalized crossover frequency, the maximum duty cycle, and the value of the slope compensation at a required phase margin. These quantities describe the performance of the inner-current loop in peak current-mode controlled PWM dc-dc converters. The derivations are based on the Padé approximation of z = exp(sTs). The results of this paper can be used for the design of the inner-current loop with a specified phase margin.
Soccer Event Detection

The research community is interested in developing automatic systems for the detection of events in video. This is particularly important in the field of sports data analytics. This paper presents an approach for identifying major complex events in soccer videos, starting from object detection and spatial relations between objects. The proposed framework, firstly, detects objects from each single video frame providing a set of candidate objects with associated confidence scores. The event detection system, then, detects events by means of rules which are based on temporal and logical combinations of the detected objects and their relative distances. The effectiveness of the framework is preliminary demonstrated over different events like "Ball possession" and "Kicking the ball".
CDMA vs . OFDM-Comparison and Hybrid OFDM-the Solution for the Next Generation

222   This paper investigates the effectiveness of OFDM and proven in other conventional (narrowband) commercial radio technologies (e.g. DS-CDMA in cell phones) (e.g. OFDM in IEEE 802.11a/g).. The main aim was to assess the suitability of OFDM as a modulation technique for a fixed wireless phone system for rural areas. However, its suitability for more general wireless applications is also assessed. Most third generation mobile phone systems are proposing to use Code Division Multiple Access (CDMA) as their modulation technique. For this reason, CDMA is also investigated so that the performance of CDMA could be compared with OFDM on the basis of various wireless parameters. At the end it is concluded that the good features of both the modulation schemes can be combined in an intelligent way to get the best modulation scheme as a solution for wireless communication high speed requirement, channel problems and increased number of users.
Prediction & Evaluation of Online News Popularity Using Machine Intelligence

News popularity is the maximum growth of attention given for particular news article. Social networking websites, news websites are used for reading different news. Online news popularity depends upon various factors such as number of shares on social media, number of comments by visitors, number of likes etc. So it is necessary to build an automated decision support system to predict the popularity of news as it will help in business intelligence too. The work presented in this research intends to find the best model to predict the popularity of online news by using machine learning methods. Initially, LDA is used to reduce the dimension. Then three different learning algorithms such as AdaBoost, LPBoost, and Random Forest are implemented in order to predict the news popularity. The performance of system is tested on the dataset which comes from UCI machine learning repository. The prediction performances of all three methodologies are studied by considering evaluation measures. Adaptive Boosting turns out to be the best model for prediction and it has achieved accuracy of 69%, F-measure of 73%.
Sequential light programs shape kale (Brassica napus) sprout appearance and alter metabolic and nutrient content

Different light wavelengths have specific effects on plant growth and development. Narrow-bandwidth light-emitting diode (LED) lighting may be used to directionally manipulate size, color and metabolites in high-value fruits and vegetables. In this report, Red Russian kale (Brassica napus) seedlings were grown under specific light conditions and analyzed for photomorphogenic responses, pigment accumulation and nutraceutical content. The results showed that this genotype responds predictably to darkness, blue and red light, with suppression of hypocotyl elongation, development of pigments and changes in specific metabolites. However, these seedlings were relatively hypersensitive to far-red light, leading to uncharacteristically short hypocotyls and high pigment accumulation, even after growth under very low fluence rates (<1 μmol m−2 s−1). General antioxidant levels and aliphatic glucosinolates are elevated by far-red light treatments. Sequential treatments of darkness, blue light, red light and far-red light were applied throughout sprout development to alter final product quality. These results indicate that sequential treatment with narrow-bandwidth light may be used to affect key economically important traits in high-value crops.
Cultural Constraints on the Emergence of Women Leaders : How Global Leaders Can Promote Women in Different Cultures

‘‘This is really still a nightmare — a German nightmare,’’ asserted Mechtilde Maier, Deutsche Telekom’s head of diversity. A multinational company with offices in about 50 countries, Deutsche Telekom is struggling at German headquarters to bring women into its leadership ranks. It is a startling result; at headquarters, one might expect the greatest degree of compliance to commands on high. With only 13% of its leadership positions represented by women, the headquarters is lagging far behind its offices outside Germany, which average 24%. Even progress has been glacial, with an improvement of a mere 0.5% since 2010 versus a 4% increase among its foreign subsidiaries. The phenomenon at Deutsche Telekom reflects a broader pattern, one that manifests in other organizations, in other nations, and in the highest reaches of leadership, including the boardroom. According to the Deloitte Global Centre for Corporate Governance, only about 12% of boardroom seats in the United States are held by women and less than 10% in the United Kingdom (9%), China (8.5%), and India (5%). In stark contrast, these rates are 2—3 times higher in Bulgaria (30%) and Norway (approximately 40%). Organizations are clearly successful in some nations more than others in promoting women to leadership ranks, but why? Instead of a culture’s wealth, values, or practices, our own research concludes that the emergence of women as leaders can be explained in part by a culture’s tightness. Cultural tightness refers to the degree to which a culture has strong norms and low tolerance for deviance. In a tight culture, people might be arrested for spitting, chewing gum, or jaywalking. In loose cultures, although the same behaviors may be met with disapproving glances or fines, they are not sanctioned to the same degree nor are they necessarily seen as taboo. We discovered that women are more likely to emerge as leaders in loose than tight cultures, but with an important exception. Women can emerge as leaders in tight cultures too. Our discoveries highlight that, to promote women to leadership positions, global leaders need to employ strategies that are compatible with the culture’s tightness. Before presenting our findings and their implications, we first discuss the process by which leaders tend to emerge.
Multitask learning for neural generative question answering

Neural generative model in question answering (QA) usually employs sequence-to-sequence (Seq2Seq) learning to generate answers based on the user’s questions as opposed to the retrieval-based model selecting the best matched answer from a repository of pre-defined QA pairs. One key challenge of neural generative model in QA lies in generating high-frequency and generic answers regardless of the questions, partially due to optimizing log-likelihood objective function. In this paper, we investigate multitask learning (MTL) in neural network-based method under a QA scenario. We define our main task as agenerative QA via Seq2Seq learning. And we define our auxiliary task as a discriminative QA via binary QAclassification. Both main task and auxiliary task are learned jointly with shared representations, allowing to obtain improved generalization and transferring classification labels as extra evidences to guide the word sequence generation of the answers. Experimental results on both automatic evaluations and human annotations demonstrate the superiorities of our proposed method over baselines.
Using a novel computational drug-repositioning approach (DrugPredict) to rapidly identify potent drug candidates for cancer treatment

Computation-based drug-repurposing/repositioning approaches can greatly speed up the traditional drug discovery process. To date, systematic and comprehensive computation-based approaches to identify and validate drug-repositioning candidates for epithelial ovarian cancer (EOC) have not been undertaken. Here, we present a novel drug discovery strategy that combines a computational drug-repositioning system (DrugPredict) with biological testing in cell lines in order to rapidly identify novel drug candidates for EOC. DrugPredict exploited unique repositioning opportunities rendered by a vast amount of disease genomics, phenomics, drug treatment, and genetic pathway and uniquely revealed that non-steroidal anti-inflammatories (NSAIDs) rank just as high as currently used ovarian cancer drugs. As epidemiological studies have reported decreased incidence of ovarian cancer associated with regular intake of NSAIDs, we assessed whether NSAIDs could have chemoadjuvant applications in EOC and found that (i) NSAID Indomethacin induces robust cell death in primary patient-derived platinum-sensitive and platinum- resistant ovarian cancer cells and ovarian cancer stem cells and (ii) downregulation of β-catenin is partially driving effects of Indomethacin in cisplatin-resistant cells. In summary, we demonstrate that DrugPredict represents an innovative computational drug- discovery strategy to uncover drugs that are routinely used for other indications that could be effective in treating various cancers, thus introducing a potentially rapid and cost-effective translational opportunity. As NSAIDs are already in routine use in gynecological treatment regimens and have acceptable safety profile, our results will provide with a rationale for testing NSAIDs as potential chemoadjuvants in EOC patient trials.
A 1.24  $\mu$ A Quiescent Current NMOS Low Dropout Regulator With Integrated Low-Power Oscillator-Driven Charge-Pump and Switched-Capacitor Pole Tracking Compensation

Supply regulation using low quiescent current linear regulators helps in extending the battery life of power aware applications with very long standby time. A 1.24 <inline-formula> <tex-math notation="LaTeX">$\mu \text{A}$ </tex-math></inline-formula> quiescent current NMOS low dropout (LDO) that uses a hybrid bias current generator (HBCG) which boosts the bias current dynamically and adaptively to improve the transient response is presented in this paper. A bias-current scalable error amplifier with an on-demand pull-up/pull-down buffer drives the NMOS pass device. The error amplifier is powered with an integrated dynamic frequency charge pump to ensure low dropout voltage. A low-power relaxation oscillator (LPRO) generates the charge pump clocks. A novel switched-capacitor pole tracking (SCPT) compensation scheme is proposed to ensure stability up to maximum load current of 150 mA with a low-ESR 1 <inline-formula> <tex-math notation="LaTeX">$\mu \text{F}$ </tex-math></inline-formula> output capacitor. Designed in a 0.25 <inline-formula> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula> CMOS process, the LDO has an output voltage range of 1–3 V, a dropout voltage of 240 mV, and a core area of 0.11 mm<sup>2</sup>.
A comparative study on RPL attacks and security solutions

Routing Protocol for Low Power and Lossy Networks (RPL) is the routing protocol for IoT and Wireless Sensor Networks. RPL is a lightweight protocol, having good routing functionality, but has basic security functionality. This may make RPL vulnerable to various attacks. Providing security to IoT networks is challenging, due to their constrained nature and connectivity to the unsecured internet. This survey presents the elaborated review on the security of Routing Protocol for Low Power and Lossy Networks (RPL). This survey is built upon the previous work on RPL security and adapts to the security issues and constraints specific to Internet of Things. An approach to classifying RPL attacks is made based on Confidentiality, Integrity, and Availability. Along with that, we surveyed existing solutions to attacks which are evaluated and given possible solutions (theoretically, from various literature) to the attacks which are not yet evaluated. We further conclude with open research challenges and future work needs to be done in order to secure RPL for Internet of Things (IoT).
Characterizing Temperature, Power, and Soft-Error Behaviors in Data Center Systems: Insights, Challenges, and Opportunities

GPUs have become part of the mainstream high performance computing facilities that increasingly require more computational power to simulate physical phenomena quickly and accurately. However, GPU nodes also consume significantly more power than traditional CPU nodes, and high power consumption introduces new system operation challenges, including increased temperature, power/cooling cost, and lower system reliability. This paper explores how power consumption and temperature characteristics affect reliability, provides insights into what are the implications of such understanding, and how to exploit these insights toward predicting GPU errors using neural networks.
Female genital injuries resulting from consensual and non-consensual vaginal intercourse.

The purpose of this study was to compare the incidence of genital injury following penile-vaginal penetration with and without consent.



This study compared observations of genital injuries from two cohorts.



Participants were drawn from St. Mary's Sexual Assault Referral Centre and a general practice surgery in Manchester, and a general practice surgery in Buckinghamshire.



Two cohorts were recruited: a retrospective cohort of 500 complainants referred to a specialist Sexual Assault Referral Centre (the Cases) and 68 women recruited at the time of their routine cervical smear test who had recently had sexual intercourse (the Comparison group).



Presence of genital injuries.



22.8% (n=00, 95% CI 19.2-26.7) of adult complainants of penile-vaginal rape by a single assailant sustained an injury to the genitalia that was visible within 48h of the incident. This was approximately three times more than the 5.9% (n=68, 95% CI 1.6-14.4) of women who sustained a genital injury during consensual sex. This was a statistically significant difference (a<0.05, p=0.0007). Factors such as hormonal status, position during intercourse, criminal justice outcome, relationship to assailant, and the locations, sizes and types of injuries were also considered but the only factor associated with injury was the relationship with the complainant, with an increased risk of injury if the assailant was known to the complainant (p=0.019).



Most complainants of rape (n=500, 77%, 95% CI 73-81%) will not sustain any genital injury, although women are three times more likely to sustain a genital injury from an assault than consensual intercourse.
The psychosocial burden of psoriatic arthritis.

To assess the psychosocial impact of psoriatic arthritis (PsA), describe how health-related quality of life (QoL) is affected in patients with PsA, discuss measures used to evaluate the psychosocial impact of PsA, and review studies examining the effect of therapy on QoL.



A targeted review on the impact of PsA on QoL and the role of tailored psychosocial management in reducing the psychosocial burden of the disease was performed. PubMed literature searches were conducted using the terms PsA, psychosocial burden, QoL, and mood/behavioral changes. Articles were deemed relevant if they presented information regarding the psychosocial impact of PsA, methods used to evaluate these impacts, or ways to manage/improve management of PsA and its resulting comorbidities. The findings of this literature search are descriptively reviewed and the authors׳ expert opinion on their interpretation is provided.



The psychosocial burden of PsA negatively affects QoL. Patients suffer from sleep disorders, fatigue, low-level stress, depression and mood/behavioral changes, poor body image, and reduced work productivity. Additionally, each patient responds to pain differently, depending on a variety of psychological factors including personality structure, cognition, and attention to pain. Strategies for evaluating the burdens associated with PsA and the results of properly managing patients with PsA are described.



PsA is associated with a considerable psychosocial burden and new assessment tools, specific to PsA, have been developed to help quantify this burden in patients. Future management algorithms of PsA should incorporate appropriate assessment and management of psychological and physical concerns of patients. Furthermore, patients with PsA should be managed by a multidisciplinary team that works in coordination with the patient and their family or caregivers.
中图法分类号 TP 391 A MultiView Face Detection Based on Real Adaboost Algorithm

In this paper, a multi-view face detection method based on real Adaboost algorithm is presented. Human faces are divided into several viewpoint categories according to their poses in 3D, and for each of these categories we design a form of weak classifiers in look-up-table (LUT) type using Haar-like features that have confidences in real values as their outputs, and correspondingly construct its space of weak classifiers from which the cascade face detector is learnt by using real Adaboost algorithm. For speed up, multi-resolution searching and pose prediction strategies are introduced. For frontal face detection the experiments on CMU+MIT frontal face test set result a 94.5% correct rate with 54 false alarms; for multi-view face detection the experiments on CMU profile face test set result a 89.8% correct with 221 false alarms. The average processing time on a PIV 2.4GHz PC is about 80 ms for a 320×240-pixel image. It can be seen that the proposed method is very efficient and has significant value in application.
Typing on an Invisible Keyboard

A virtual keyboard takes a large portion of precious screen real estate. We have investigated whether an invisible keyboard is a feasible design option, how to support it, and how well it performs. Our study showed users could correctly recall relative key positions even when keys were invisible, although with greater absolute errors and overlaps between neighboring keys. Our research also showed adapting the spatial model in decoding improved the invisible keyboard performance. This method increased the input speed by 11.5% over simply hiding the keyboard and using the default spatial model. Our 3-day multi-session user study showed typing on an invisible keyboard could reach a practical level of performance after only a few sessions of practice: the input speed increased from 31.3 WPM to 37.9 WPM after 20 - 25 minutes practice on each day in 3 days, approaching that of a regular visible keyboard (41.6 WPM). Overall, our investigation shows an invisible keyboard with adapted spatial model is a practical and promising interface option for the mobile text entry systems.
Camel: Content-Aware and Meta-path Augmented Metric Learning for Author Identification

In this paper, we study the problem of author identification in big scholarly data, which is to effectively rank potential authors for each anonymous paper by using historical data. Most of the existing deanonymization approaches predict relevance score of paper-author pair via feature engineering, which is not only time and storage consuming, but also introduces irrelevant and redundant features or miss important attributes. Representation learning can automate the feature generation process by learning node embeddings in academic network to infer the correlation of paper-author pair. However, the learned embeddings are often for general purpose (independent of the specific task), or based on network structure only (without considering the node content). To address these issues and make a further progress in solving the author identification problem, we propose Camel, a content-aware and meta-path augmented metric learning model. Specifically, first, the directly correlated paper-author pairs are modeled based on distance metric learning by introducing a push loss function. Next, the paper content embedding encoded by the gated recurrent neural network is integrated into the distance loss. Moreover, the historical bibliographic data of papers is utilized to construct an academic heterogeneous network, wherein a meta-path guided walk integrative learning module based on the task-dependent and content-aware Skipgram model is designed to formulate the correlations between each paper and its indirect author neighbors, and further augments the model. Extensive experiments demonstrate that Camel outperforms the state-of-the-art baselines. It achieves an average improvement of 6.3% over the best baseline method.
Towards Blending Semantics with an Education Based Ontology Using Protege 5.2.0 A Revisit

In today's world of globalization, there is a serious need of incorporating semantics in Education Domain which is very significant with an ultimate goal of providing an efficient, adaptive and personalized learning environment. An attempt towards this goal has been made to develop an Education based Ontology with some capability to describe a semantic web based sharable knowledge. So as a contribution, this paper presents a revisit towards amalgamating Semantics in Education. In this direction, an effort has been made to construct an Education based Ontology using Protege 5.2.0, where a hierarchy of classes and subclasses have been defined along with their properties, relations, and instances. Finally, at the end of this paper an implementation is also presented involving query retrieval using DLquery illustrations.
On the topology of the Lü attractor and related systems

We use well-established methods of knot theory to study the topological structure of the set of periodic orbits of the Lü attractor. We show that, for a specific set of parameters, the Lü attractor is topologically different from the classical Lorenz attractor, whose dynamics is formed by a double cover of the simple horseshoe. This argues against the ‘similarity’ between the Lü and Lorenz attractors, claimed, for these parameter values, by some authors on the basis of non-topological observations. However, we show that the Lü system belongs to the Lorenz-like family, since by changing the values of the parameters, the behaviour of the system follows the behaviour of all members of this family. An attractor of the Lü kind with higher order symmetry is constructed and some remarks on the Chen attractor are also presented.
Ultra broadband transmission line transformers - planar realization principles

Three Guanella-type transmission line transformers (TLT) are presented: a coiled TLT on a GaAs substrate, a straight ferriteless TLT on a multilayer PCB and a straight hybrid TLT that employs semi-rigid coaxial cables and a ferrite. All three devices have 4:1 impedance transformation ratio, matching 12.5 /spl Omega/ to 50 /spl Omega/. Extremely broadband operation is achieved. A detailed description of the devices and their operational principle is given. General aspects of the design of TLT are discussed.