nils-herrmann/clean_scirepeval huggingface dataset:
Influence of Resistance Training Frequency on Muscular Adaptations in Well-Trained Men.

The purpose of this study was to investigate the effects of training muscle groups 1 day per week using a split-body routine (SPLIT) vs. 3 days per week using a total-body routine (TOTAL) on muscular adaptations in well-trained men. Subjects were 20 male volunteers (height = 1.76 ± 0.05 m; body mass = 78.0 ± 10.7 kg; age = 23.5 ± 2.9 years) recruited from a university population. Participants were pair matched according to baseline strength and then randomly assigned to 1 of the 2 experimental groups: a SPLIT, where multiple exercises were performed for a specific muscle group in a session with 2-3 muscle groups trained per session (n = 10) or a TOTAL, where 1 exercise was performed per muscle group in a session with all muscle groups trained in each session (n = 10). Subjects were tested pre- and poststudy for 1 repetition maximum strength in the bench press and squat, and muscle thickness (MT) of forearm flexors, forearm extensors, and vastus lateralis. Results showed significantly greater increases in forearm flexor MT for TOTAL compared with SPLIT. No significant differences were noted in maximal strength measures. The findings suggest a potentially superior hypertrophic benefit to higher weekly resistance training frequencies.
Hardening Stratum, the Bitcoin Pool Mining Protocol

Stratum, the de-facto mining communication protocol used by blockchain based cryptocurrency systems, enables miners to reliably and efficiently fetch jobs from mining pool servers. In this paper we exploit Stratum’s lack of encryption to develop passive and active attacks on Bitcoin’s mining protocol, with important implications on the privacy, security and even safety of mining equipment owners. We introduce StraTap and ISP Log attacks, that infer miner earnings if given access to miner communications, or even their logs. We develop BiteCoin, an active attack that hijacks shares submitted by miners, and their associated payouts. We build BiteCoin on WireGhost, a tool we developed to hijack and surreptitiously maintain Stratum connections. Our attacks reveal that securing Stratum through pervasive encryption is not only undesirable (due to large overheads), but also ineffective: an adversary can predict miner earnings even when given access to only packet timestamps. Instead, we devise Bedrock, a minimalistic Stratum extension that protects the privacy and security of mining participants. We introduce and leverage the mining cookie concept, a secret that each miner shares with the pool and includes in its puzzle computations, and that prevents attackers from reconstructing or hijacking the puzzles. We have implemented our attacks and collected 138MB of Stratum protocol traffic from mining equipment in the US and Venezuela. We show that Bedrock is resilient to active attacks even when an adversary breaks the crypto constructs it uses. Bedrock imposes a daily overhead of 12.03s on a single pool server that handles mining traffic from 16,000 miners.
Automatic synchronization of electronic and audio books via TTS alignment and silence filtering

The e-book industry is starting to flourish due, in part, to the availability of affordable and user-friendly e-book readers. As users are increasingly moving from traditional paper books to e-books, there is an opportunity to reinvent and enhance their reading experience, for example, by leveraging the multimedia capabilities of these devices in order to turn the act of reading into a real multimedia experience. In this paper, we focus on the augmentation of the written text with its associated audiobook, so that users can listen to the book they are (currently) reading. We propose an audiobook-to-ebook alignment system by applying a Text-to-Speech (TTS)-based text to audio alignment algorithm, and enhance it with a silence filtering algorithm to cope with the difference on reading style between the TTS output and the speakers in the ebook environment. Experiments done using 12 five-minute excerpts of 6 different audio-books (read by men and women) yield usable word alignment errors below 120ms for 90% of the words. Finally, we also show a user interface implementation in the Ipad for synchronized e-book reading while listening to the associated audiobook.
An Approach to Text Summarization.

We propose an efficient text summarization technique that involves two basic operations. The first operation involves finding coherent chunks in the document and the second operation involves ranking the text in the individual coherent chunks and picking the sentences that rank above a given threshold. The coherent chunks are formed by exploiting the lexical relationship between adjacent sentences in the document. Occurrence of words through repetition or relatedness by sense relation plays a major role in forming a cohesive tie. The proposed text ranking approach is based on a graph theoretic ranking model applied to text summarization task.
Channel Estimation and Data Detection Using Machine Learning for MIMO 5G Communication Systems in Fading Channel

In multiple-input multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) systems, multi-user detection (MUD) algorithms play an important role in reducing the effect of multi-access interference (MAI). A combination of the estimation of channel and multi-user detection is proposed for eliminating various interferences and reduce the bit error rate (BER). First, a novel sparse based k-nearest neighbor classifier is proposed to estimate the unknown activity factor at a high data rate. The active users are continuously detected and their data are decoded at the base station (BS) receiver. The activity detection considers both the pilot and data symbols. Second, an optimal pilot allocation method is suggested to select the minimum mutual coherence in the measurement matrix for optimal pilot placement. The suggested algorithm for designing pilot patterns significantly improves the results in terms of mean square error (MSE), symbol error rate (SER) and bit error rate for channel detection. An optimal pilot placement reduces the computational complexity and maximizes the accuracy of the system. The performance of the channel estimation (CE) and MUD for the proposed scheme was good as it provided significant results, which were validated through simulations.
Sexual Harassment as a Gendered Expression of Power Author ( s ) :

Harassment of Working Women, Catharine MacKinnon notes that men’s victimization of women “is sufficiently pervasive in American society as to be nearly invisible” (1979:1). Since the publication of her book, sexual harassment has become increasingly visible, and variants of MacKinnon’s broad sociocultural explanation have gained broad acceptance (Schultz 2001; MacKinnon 2002; Tangri, Burt, and Johnson 1982; Welsh 1999). In reaction to evidence that at least some male and adolescent workers are targets of sexual harassment (Kalof et al. 2001; Talbot 2002; Thacker 1996), critics have begun to challenge feminist views of sexual harassment as an act committed by powerful adult males against “powerless females” (Patai 1998:170) as founded on “unexamined notions of male ‘power’ and predatoriness” (Patai 1998:59; see also Francke 1997; Schultz 1998:95). Nevertheless, a systematic examination of the theory’s basic propositions about gender and power has yet to emerge in the social science literature. No empirical study of sexual harassment has appeared in the prominent general interest sociology journals American Journal of Sociology, American Sociological Review, or Social Forces (Sever 1996). In light of the impressive body of sociological theory around the phenomenon, a burgeoning research literature in the top specialty journals, and the strong public interest it has generated, this void is surprising. The neglect of sexual harassment in mainstream sociology also forestalls research that could have broad implications. In this paper we Sexual Harassment as a Gendered Expression of Power
Improving WalkSAT By Effective Tie-Breaking and Efficient Implementation

Stochastic local search (SLS) algorithms are well known for their ability to efficiently find models of random instances of the Boolean satisfiability (SAT) problem. One of the most famous SLS algorithms for SAT is WalkSAT, which is an initial algorithm that has wide influence and performs very well on random 3-SAT instances. However, the performance of WalkSAT on random k-SAT instances with k > 3 lags far behind. Indeed, there are limited works on improving SLS algorithms for such instances. This work takes a good step toward this direction. We propose a novel concept namely multilevel make. Based on this concept, we design a scoring function called linear make, which is utilized to break ties in WalkSAT, leading to a new algorithm called WalkSATlm. Our experimental results show that WalkSATlm improves WalkSAT by orders of magnitude on random k-SAT instances with k > 3 near the phase transition. Additionally, we propose an efficient implementation for WalkSATlm, which leads to a speedup of 100%. We also give some insights on different forms of linear make functions, and show the limitation of the linear make function on random 3-SAT through theoretical analysis.
Routing, ship size, and sailing frequency decision-making for a maritime hub-and-spoke container network

This study formulates a two-objective model to determine the optimal liner routing, ship size, and sailing frequency for container carriers by minimizing shipping costs and inventory costs. First, shipping and inventory cost functions are formulated using an analytical method. Then, based on a trade-off between shipping costs and inventory costs, Pareto optimal solutions of the twoobjective model are determined. Not only can the optimal ship size and sailing frequency be determined for any route, but also the routing decision on whether to route containers through a hub or directly to their destination can be made in objective value space. Finally, the theoretical findings are applied to a case study, with highly reasonable results. The results show that the optimal routing, ship size, and sailing frequency with respect to each level of inventory costs and shipping costs can be determined using the proposed model. The optimal routing decision tends to be shipping the cargo through a hub as the hub charge is decreased or its efficiency improved. In addition, the proposed model not only provides a tool to analyze the trade-off between shipping costs and inventory costs, but it also provides flexibility on the decision-making for container carriers.
Synchronous Rectification LLC Series-Resonant Converter

The primary goals in use of half-bridge LLC series-resonant converter (LLC-SRC) are high efficiency, low noise, and wide-range regulation. A voltage-clamped drive circuit for simultaneously driving both primary and secondary switches is proposed to achieve synchronous rectification (SR) at switching frequency higher than the dominant resonant frequency. No high/low-side driver circuit for half-bridge switches of LLC-SRC is required and less circuit complexity is achieved. The SR mode LLC-SRC developed for reducing output rectification losses is described along with steady-state analysis, gate drive strategy, and its experiments. Design consideration is described thoroughly so as to build up a reference for design and realization. A design example of 240W SR LLC-SRC is examined and an average efficiency as high as 95% at full load is achieved. All performances verified by simulation and experiment are close to the theoretical predictions.
Time-Frequency Training OFDM with High Spectral Efficiency and Improved Performance over Fast Fading Channels

Time domain synchronous OFDM (TDS-OFDM) has higher spectral efficiency than cyclic prefix OFDM (CP-OFDM), but suffers from severe performance loss over fast fading channels. In this paper, a novel transmission scheme called time-frequency training OFDM (TFT-OFDM) is proposed. The time-frequency joint channel estimation for TFT-OFDM utilizes the time-domain training sequence without interference cancellation to merely acquire the time delay profile of the channel, while the path coefficients are estimated by using the frequency-domain group pilots. The redundant group pilots only occupy about 1% of the useful subcarriers, thus TFT-OFDM still has much higher spectral efficiency than CP-OFDM by about 10%. Simulation results also demonstrate that TFT-OFDM outperforms CP-OFDM and TDS-OFDM over time-varying channels.
An Algorithm Faster than NegaScout and SSS * in Practice

In this paper we introduce a framework for best first search of minimax trees. Existing best first algorithms like SSS* and DUAL* are formulated as instances of this framework. The framework is built around the Alpha-Beta procedure. Its instances are highly practical, and readily implementable. Our reformulations of SSS* and DUAL* solve the perceived drawbacks of these algorithms. We prove their suitability for practical use by presenting test results with a tournament level chess program. In addition to reformulating old best first algorithms, we introduce an improved instance of the framework: MTD(ƒ). This new algorithm outperforms NegaScout, the current algorithm of choice of most chess programs. Again, these are not simulation results, but results of tests with an actual chess program, Phoenix.
Metadata-Assisted Global Motion Estimation for Medium-Altitude Unmanned Aerial Vehicle Video Applications

Global motion estimation (GME) is a key technology in unmanned aerial vehicle remote sensing (UAVRS). However, when a UAV’s motion and behavior change significantly or the image information is not rich, traditional image-based methods for GME often perform poorly. Introducing bottom metadata can improve precision in a large-scale motion condition and reduce the dependence on unreliable image information. GME is divided into coarse and residual GME through coordinate transformation and based on the study hypotheses. In coarse GME, an auxiliary image is built to convert image matching from a wide baseline condition to a narrow baseline one. In residual GME, a novel information and contrast feature detection algorithm is proposed for big-block matching to maximize the use of reliable image information and ensure that the contents of interest are well estimated. Additionally, an image motion monitor is designed to select the appropriate processing strategy by monitoring the motion scales of translation, rotation, and zoom. A medium-altitude UAV is employed to collect three types of large-scale motion datasets. Peak signal to noise ratio (PSNR) and motion scale are computed. This study’s result is encouraging and applicable to other mediumor high-altitude UAVs with a similar system structure.
The Rag GTPases bind raptor and mediate amino acid signaling to mTORC1.

The multiprotein mTORC1 protein kinase complex is the central component of a pathway that promotes growth in response to insulin, energy levels, and amino acids and is deregulated in common cancers. We find that the Rag proteins--a family of four related small guanosine triphosphatases (GTPases)--interact with mTORC1 in an amino acid-sensitive manner and are necessary for the activation of the mTORC1 pathway by amino acids. A Rag mutant that is constitutively bound to guanosine triphosphate interacted strongly with mTORC1, and its expression within cells made the mTORC1 pathway resistant to amino acid deprivation. Conversely, expression of a guanosine diphosphate-bound Rag mutant prevented stimulation of mTORC1 by amino acids. The Rag proteins do not directly stimulate the kinase activity of mTORC1, but, like amino acids, promote the intracellular localization of mTOR to a compartment that also contains its activator Rheb.
Comparison of Three High-End Endoscopic Visualization Systems on Telesurgical Performance

Previous studies and surgeon interviews have shown that most surgeons prefer quality standard de nition (SD)TV 2D scopes to rst generation 3D endoscopes. The use of a telesurgical system has eased many of the design constraints on traditional endoscopes, enabling the design of a high quality SDTV 3D endoscope and an HDTV endoscopic system with outstanding resolution. The purpose of this study was to examine surgeon performance and preference given the choice between these. The study involved two perceptual tasks and four visual-motor tasks using a telesurgical system using the 2D HDTV endoscope and the SDTV endoscope in both 2D and 3D mode. The use of a telesurgical system enabled recording of all the subjects motions for later analysis. Contrary to experience with early 3D scopes and SDTV 2D scopes, this study showed that despite the superior resolution of the HDTV system surgeons performed better with and preferred the SDTV 3D scope.
Meta-Unsupervised-Learning: A supervised approach to unsupervised learning

We introduce a new paradigm to investigate unsupervised learning, reducing unsupervised learning to supervised learning. Specifically, we mitigate the subjectivity in unsupervised decision-making by leveraging knowledge acquired from prior, possibly heterogeneous, supervised learning tasks. We demonstrate the versatility of our framework via comprehensive expositions and detailed experiments on several unsupervised problems such as (a) clustering, (b) outlier detection, and (c) similarity prediction under a common umbrella of meta-unsupervised-learning. We also provide rigorous PAC-agnostic bounds to establish the theoretical foundations of our framework, and show that our framing of metaclustering circumvents Kleinberg’s impossibility theorem for clustering.
Stable multi-target tracking in real-time surveillance video

The majority of existing pedestrian trackers concentrate on maintaining the identities of targets, however systems for remote biometric analysis or activity recognition in surveillance video often require stable bounding-boxes around pedestrians rather than approximate locations. We present a multi-target tracking system that is designed specifically for the provision of stable and accurate head location estimates. By performing data association over a sliding window of frames, we are able to correct many data association errors and fill in gaps where observations are missed. The approach is multi-threaded and combines asynchronous HOG detections with simultaneous KLT tracking and Markov-Chain Monte-Carlo Data Association (MCM-CDA) to provide guaranteed real-time tracking in high definition video. Where previous approaches have used ad-hoc models for data association, we use a more principled approach based on a Minimal Description Length (MDL) objective which accurately models the affinity between observations. We demonstrate by qualitative and quantitative evaluation that the system is capable of providing precise location estimates for large crowds of pedestrians in real-time. To facilitate future performance comparisons, we make a new dataset with hand annotated ground truth head locations publicly available.
Shunt compensation of SMIB power system incorporated with highly penetrated photovoltaic generator

This paper presents the effect of incorporating the Single-Machine-Infinite-Bus (SMIB) power system embraced with highly penetrated Photovoltaic (PV) generator with shunt compensation. The conventional variable shunt capacitor is connected at a common coupling point where the terminals of the two generators are combined. The dynamics of the Automatic Voltage Regulator (AVR) and Turbine Governor (TG) of the synchronous generator and the nonlinearity of the output characteristics of the PV generator are included. The stability of the operating point of the system is firstly studied through the linearized model eigenvalues. Time domain simulations based on the complete nonlinear model in d-q stationary reference frame are then presented after step changes on the values of the shunt compensation. The study is carried out at three realistic solar irradiance levels. It is concluded that shunt compensation of SMIB power system equipped with PV generator can control the total reactive power injected to the grid. During numerical simulations, it has been concluded that to have a stable system operating point, the value of the shunt compensation should be reduced as the solar irradiance level decreases. Additionally, the lower the solar irradiance level, the narrower the range of shunt compensation values which can provide a stable system operating point.
Co-Saliency Detection for RGBD Images Based on Multi-Constraint Feature Matching and Cross Label Propagation

Co-saliency detection aims at extracting the common salient regions from an image group containing two or more relevant images. It is a newly emerging topic in computer vision community. Different from the most existing co-saliency methods focusing on RGB images, this paper proposes a novel co-saliency detection model for RGBD images, which utilizes the depth information to enhance identification of co-saliency. First, the intra saliency map for each image is generated by the single image saliency model, while the inter saliency map is calculated based on the multi-constraint feature matching, which represents the constraint relationship among multiple images. Then, the optimization scheme, namely cross label propagation, is used to refine the intra and inter saliency maps in a cross way. Finally, all the original and optimized saliency maps are integrated to generate the final co-saliency result. The proposed method introduces the depth information and multi-constraint feature matching to improve the performance of co-saliency detection. Moreover, the proposed method can effectively exploit any existing single image saliency model to work well in co-saliency scenarios. Experiments on two RGBD co-saliency datasets demonstrate the effectiveness of our proposed model.
Design of an Active 1-DOF Lower-Limb Exoskeleton with Inertia Compensation

Limited research has been done on exoskeletons to enable faster movements of the lower extremities. An exoskeleton’s mechanism can actually hinder agility by adding weight, inertia and friction to the legs; compensating inertia through control is particularly difficult due to instability issues. The added inertia will reduce the natural frequency of the legs, probably leading to lower step frequency during walking. We present a control method that produces an approximate compensation of an exoskeleton’s inertia. The aim is making the natural frequency of the exoskeleton-assisted leg larger than that of the unaided leg. The method uses admittance control to compensate the weight and friction of the exoskeleton. Inertia compensation is emulated by adding a feedback loop consisting of low-pass filtered acceleration multiplied by a negative gain. This gain simulates negative inertia in the low-frequency range. We tested the controller on a statically supported, single-DOF exoskeleton that assists swing movements of the leg. Subjects performed movement sequences, first unassisted and then using the exoskeleton, in the context of a computer-based task resembling a race. With zero inertia compensation, the steady-state frequency of leg swing was consistently reduced. Adding inertia compensation enabled subjects to recover their normal frequency of swing.
Dental implants in the periodontal patient.

The principal reason for providing periodontal therapy is to achieve periodontal health and retain the dentition. Patients with a history of periodontitis represent a unique group of individuals who previously succumbed to a bacterial challenge. Therefore, it is important to address the management and survival rate of implants in these patients. Systematic reviews often are cited in this article, because they provide a high level of evidence and facilitate reviewing a vast amount of information in a succinct manner.