nils-herrmann/clean_scirepeval huggingface dataset:
Object recognition in rats and mice: a one-trial non-matching-to-sample learning task to study 'recognition memory'

Rats and mice have a tendency to interact more with a novel object than with a familiar object. This tendency has been used by behavioral pharmacologists and neuroscientists to study learning and memory. A popular protocol for such research is the object-recognition task. Animals are first placed in an apparatus and allowed to explore an object. After a prescribed interval, the animal is returned to the apparatus, which now contains the familiar object and a novel object. Object recognition is distinguished by more time spent interacting with the novel object. Although the exact processes that underlie this 'recognition memory' requires further elucidation, this method has been used to study mutant mice, aging deficits, early developmental influences, nootropic manipulations, teratological drug exposure and novelty seeking.
Cartoon image segmentation based on improved SLIC superpixels and adaptive region propagation merging

This paper present a novel algorithm for cartoon image segmentation based on the simple linear iterative clustering (SLIC) superpixels and adaptive region propagation merging. To break the limitation of the original SLIC algorithm in confirming to image boundaries, this paper proposed to improve the quality of the superpixels generation based on the connectivity constraint. To achieve efficient segmentation from the superpixels, this paper employed an adaptive region propagation merging algorithm to obtain independent segmented object. Compared with the pixel-based segmentation algorithms and other superpixel-based segmentation methods, the method proposed in this paper is more effective and more efficient by determining the propagation center adaptively. Experiments on abundant cartoon images showed that our algorithm outperforms classical segmentation algorithms with the boundary-based and region-based criteria. Furthermore, the final cartoon image segmentation results are also well consistent with the human visual perception.
RCLinker: Automated Linking of Issue Reports and Commits Leveraging Rich Contextual Information

Links between issue reports and their corresponding commits in version control systems are often missing. However, these links are important for measuring the quality of a software system, predicting defects, and many other tasks. Several approaches have been designed to solve this problem by automatically linking bug reports to source code commits via comparison of textual information in commit messages and bug reports. Yet, the effectiveness of these techniques is oftentimes suboptimal when commit messages are empty or contain minimum information; this particular problem makes the process of recovering traceability links between commits and bug reports particularly challenging. In this work, we aim at improving the effectiveness of existing bug linking techniques by utilizing rich contextual information. We rely on a recently proposed approach, namely ChangeScribe, which generates commit messages containing rich contextual information by using code summarization techniques. Our approach then extracts features from these automatically generated commit messages and bug reports, and inputs them into a classification technique that creates a discriminative model used to predict if a link exists between a commit message and a bug report. We compared our approach, coined as RCLinker (Rich Context Linker), to MLink, which is an existing state-of-the-art bug linking approach. Our experiment results on bug reports from six software projects show that RCLinker outperforms MLink in terms of F-measure by 138.66%.
A Grey Wolf Optimizer for Modular Granular Neural Networks for Human Recognition

A grey wolf optimizer for modular neural network (MNN) with a granular approach is proposed. The proposed method performs optimal granulation of data and design of modular neural networks architectures to perform human recognition, and to prove its effectiveness benchmark databases of ear, iris, and face biometric measures are used to perform tests and comparisons against other works. The design of a modular granular neural network (MGNN) consists in finding optimal parameters of its architecture; these parameters are the number of subgranules, percentage of data for the training phase, learning algorithm, goal error, number of hidden layers, and their number of neurons. Nowadays, there is a great variety of approaches and new techniques within the evolutionary computing area, and these approaches and techniques have emerged to help find optimal solutions to problems or models and bioinspired algorithms are part of this area. In this work a grey wolf optimizer is proposed for the design of modular granular neural networks, and the results are compared against a genetic algorithm and a firefly algorithm in order to know which of these techniques provides better results when applied to human recognition.
Characterizing and explaining spatio-temporal variation of water quality in a highly disturbed river by multi-statistical techniques

Assessing the spatio-temporal variations of surface water quality is important for water environment management. In this study, surface water samples are collected from 2008 to 2015 at 17 stations in the Ying River basin in China. The two pollutants i.e. chemical oxygen demand (COD) and ammonia nitrogen (NH3-N) are analyzed to characterize the river water quality. Cluster analysis and the seasonal Kendall test are used to detect the seasonal and inter-annual variations in the dataset, while the Moran's index is utilized to understand the spatial autocorrelation of the variables. The influence of natural factors such as hydrological regime, water temperature and etc., and anthropogenic activities with respect to land use and pollutant load are considered as driving factors to understand the water quality evolution. The results of cluster analysis present three groups according to the similarity in seasonal pattern of water quality. The trend analysis indicates an improvement in water quality during the dry seasons at most of the stations. Further, the spatial autocorrelation of water quality shows great difference between the dry and wet seasons due to sluices and dams regulation and local nonpoint source pollution. The seasonal variation in water quality is found associated with the climatic factors (hydrological and biochemical processes) and flow regulation. The analysis of land use indicates a good explanation for spatial distribution and seasonality of COD at the sub-catchment scale. Our results suggest that an integrated water quality measures including city sewage treatment, agricultural diffuse pollution control as well as joint scientific operations of river projects is needed for an effective water quality management in the Ying River basin.
Raji Srinivasan & Christine Moorman Strategic Firm Commitments and Rewards for Customer Relationship Management in Online Retailing

Academic studies offer a generally positive portrait of the effect of customer relationship management (CRM) on firm performance, but practitioners question its value. The authors argue that a firm’s strategic commitments may be an overlooked organizational factor that influences the rewards for a firm’s investments in CRM. Using the context of online retailing, the authors consider the effects of two key strategic commitments of online retailers on the performance effect of CRM: their bricks-and-mortar experience and their online entry timing. They test the proposed model with a multimethod approach that uses manager ratings of firm CRM and strategic commitments and third-party customers’ ratings of satisfaction from 106 online retailers. The findings indicate that firms with moderate bricks-and-mortar experience are better able to leverage CRM for superior customer satisfaction outcomes than firms with either low or high bricks-and-mortar experience. Likewise, firms with moderate online experience are better able to leverage CRM into superior customer satisfaction outcomes than firms with either low or high online experience. These findings help resolve disparate results about the value of CRM, and they establish the importance of examining CRM within the strategic context of the firm.
When Is a Sprint a Sprint? A Review of the Analysis of Team-Sport Athlete Activity Profile

The external load of a team-sport athlete can be measured by tracking technologies, including global positioning systems (GPS), local positioning systems (LPS), and vision-based systems. These technologies allow for the calculation of displacement, velocity and acceleration during a match or training session. The accurate quantification of these variables is critical so that meaningful changes in team-sport athlete external load can be detected. High-velocity running, including sprinting, may be important for specific team-sport match activities, including evading an opponent or creating a shot on goal. Maximal accelerations are energetically demanding and frequently occur from a low velocity during team-sport matches. Despite extensive research, conjecture exists regarding the thresholds by which to classify the high velocity and acceleration activity of a team-sport athlete. There is currently no consensus on the definition of a sprint or acceleration effort, even within a single sport. The aim of this narrative review was to examine the varying velocity and acceleration thresholds reported in athlete activity profiling. The purposes of this review were therefore to (1) identify the various thresholds used to classify high-velocity or -intensity running plus accelerations; (2) examine the impact of individualized thresholds on reported team-sport activity profile; (3) evaluate the use of thresholds for court-based team-sports and; (4) discuss potential areas for future research. The presentation of velocity thresholds as a single value, with equivocal qualitative descriptors, is confusing when data lies between two thresholds. In Australian football, sprint efforts have been defined as activity >4.00 or >4.17 m·s-1. Acceleration thresholds differ across the literature, with >1.11, 2.78, 3.00, and 4.00 m·s-2 utilized across a number of sports. It is difficult to compare literature on field-based sports due to inconsistencies in velocity and acceleration thresholds, even within a single sport. Velocity and acceleration thresholds have been determined from physical capacity tests. Limited research exists on the classification of velocity and acceleration data by female team-sport athletes. Alternatively, data mining techniques may be used to report team-sport athlete external load, without the requirement of arbitrary or physiologically defined thresholds.
UAV exploitation: A new domain for cyber power

The risks of military unmanned aerial vehicles (UAVs) being subjected to electronic attack are well recognised, especially following high-profile incidents such as the interception of unencrypted video feeds from UAVs in Iraq and Israel, or the diversion and downing of a UAV in Iran. Protection of military UAV assets rightly focuses on defence against sophisticated cyber penetration or electronic attack, including data link intercepts and navigational spoofing. Offensive activity to counter adversary drone operations presumes a requirement for high-end electronic attack systems. However, combat operations in eastern Ukraine in 2014-16 have introduced an entirely new dimension to UAV and counter-UAV operations. In addition to drones with military-grade standards of electronic defence and encryption, a large number of civilian or amateur UAVs are in operation in the conflict. This presents both opportunities and challenges to future operations combating hybrid threats. Actual operations in eastern Ukraine, in combination with studies of potential criminal or terrorist use of UAV technologies, provide indicators for a range of aspects of UAV use in future conflict. However, apart from the direct link to military usage, UAVs are rapidly approaching ubiquity with a wide range of applications reaching from entertainment purposes to border patrol, surveillance, and research, which imposes an indirect security and safety threat. Issues associated with the unguarded use of drones by the general public range from potentially highly dangerous situations such as failing to avoid controlled airspace, to privacy violations. Specific questions include attribution of UAV activities to the individuals actually directing the drone; technical countermeasures against hacking, interception or electronic attack; and options for controlling and directing adversary UAVs. Lack of attribution and security measures protecting civilian UAVs against electronic attack, hacking or hijacking, with the consequent likelihood of unauthorised use or interception, greatly increases the complication of each of these concerns.
Identity-Based Data Outsourcing With Comprehensive Auditing in Clouds

Cloud storage system provides facilitative file storage and sharing services for distributed clients. To address integrity, controllable outsourcing, and origin auditing concerns on outsourced files, we propose an identity-based data outsourcing (IBDO) scheme equipped with desirable features advantageous over existing proposals in securing outsourced data. First, our IBDO scheme allows a user to authorize dedicated proxies to upload data to the cloud storage server on her behalf, e.g., a company may authorize some employees to upload files to the company’s cloud account in a controlled way. The proxies are identified and authorized with their recognizable identities, which eliminates complicated certificate management in usual secure distributed computing systems. Second, our IBDO scheme facilitates comprehensive auditing, i.e., our scheme not only permits regular integrity auditing as in existing schemes for securing outsourced data, but also allows to audit the information on data origin, type, and consistence of outsourced files. Security analysis and experimental evaluation indicate that our IBDO scheme provides strong security with desirable efficiency.
Terrain RL Simulator

We provide 89 challenging simulation environments that range in difficulty. The difficulty of solving a task is linked not only to the number of dimensions in the action space but also to the size and shape of the distribution of configurations the agent experiences. Therefore, we are releasing a number of simulation environments that include randomly generated terrain. The library also provides simple mechanisms to create new environments with different agent morphologies and the option to modify the distribution of generated terrain. We believe using these and other more complex simulations will help push the field closer to creating human-level intelligence.
An Accelerometer-Based Device for Sleep Apnea Screening

This paper presents a body-fixed-sensor-based approach to assess potential sleep apnea patients. A trial involving 15 patients at a sleep unit was undertaken. Vibration sounds were acquired from an accelerometer sensor fixed with a noninvasive mounting on the suprasternal notch of subjects resting in supine position. Respiratory, cardiac, and snoring components were extracted by means of digital signal processing techniques. Mainly, the following biomedical parameters used in new sleep apnea diagnosis strategies were calculated: heart rate, heart rate variability, sympathetic and parasympathetic activity, respiratory rate, snoring rate, pitch associated with snores, and airflow indirect quantification. These parameters were compared to those obtained by means of polysomnography and an accurate microphone. Results demonstrated the feasibility of implementing an accelerometry-based portable device as a simple and cost-effective solution for contributing to the screening of sleep apnea-hypopnea syndrome and other breathing disorders.
Magnetism and microfluidics.

Magnetic forces are now being utilised in an amazing variety of microfluidic applications. Magnetohydrodynamic flow has been applied to the pumping of fluids through microchannels. Magnetic materials such as ferrofluids or magnetically doped PDMS have been used as valves. Magnetic microparticles have been employed for mixing of fluid streams. Magnetic particles have also been used as solid supports for bioreactions in microchannels. Trapping and transport of single cells are being investigated and recently, advances have been made towards the detection of magnetic material on-chip. The aim of this review is to introduce and discuss the various developments within the field of magnetism and microfluidics.
Understanding technology choices and values through social class

This ethnographic study of 22 diverse families in the San Francisco Bay Area provides a holistic account of parents' attitudes about their children's use of technology. We found that parents from different socioeconomic classes have different values and practices around technology use, and that those values and practices reflect structural differences in their everyday lives. Calling attention to class differences in technology use challenges the prevailing practice in human-computer interaction of designing for those similar to oneself, which often privileges middle-class values and practices. By discussing the differences between these two groups and the advantages of researching both, this research highlights the benefits of explicitly engaging with socioeconomic status as a category of analysis in design.
A 3D facial expression database for facial behavior research

Traditionally, human facial expressions have been studied using either 2D static images or 2D video sequences. The 2D-based analysis is incapable of handing large pose variations. Although 3D modeling techniques have been extensively used for 3D face recognition and 3D face animation, barely any research on 3D facial expression recognition using 3D range data has been reported. A primary factor for preventing such research is the lack of a publicly available 3D facial expression database. In this paper, we present a newly developed 3D facial expression database, which includes both prototypical 3D facial expression shapes and 2D facial textures of 2,500 models from 100 subjects. This is the first attempt at making a 3D facial expression database available for the research community, with the ultimate goal of fostering the research on affective computing and increasing the general understanding of facial behavior and the fine 3D structure inherent in human facial expressions. The new database can be a valuable resource for algorithm assessment, comparison and evaluation
Breast reduction in gigantomastia using the posterosuperior pedicle: an alternative technique, based on preservation of the anterior intercostal artery perforators.

The purpose of this study was to describe and evaluate the outcomes of breast reduction in cases of gigantomastia using a posterosuperior pedicle.



Four hundred thirty-one breast reductions were performed between 2004 and 2007. Fifty patients of 431 (11.6 percent) responded to the inclusion criteria (>1000 g of tissue removed per breast (100 breasts). The mean age was 33.2 years (range, 17 to 58 years). The average notch-to-nipple distance was 37.9 cm (range, 35 to 46 cm). The mean body mass index was 27 (range, 22 to 35 cm). The technique of the posterosuperior pedicle was used, in which the perforators from fourth anterior intercostal arteries are preserved (posterior pedicle). Results were evaluated by means of self-evaluation at 1 year postoperatively.



The average weight resected was 1231 g (range, 1000 to 2500 g). The length of hospital stay was 2.3 days (range 2 to 4 days). Thirty seven patients evaluated their results as "very good" (74 percent), nine as "good" (18 percent), and four as "acceptable" (8 percent). There were no "poor" results. The chief complaint was insufficient breast reduction (four patients), despite the considerable improvement in their daily life (8 percent). Back pain totally resolved in 46 percent and partially (with significant improvement) in 54 percent of cases. One major and seven minor complications were recorded.



The posterosuperior pedicle for breast reduction is a reproducible and versatile technique. The preservation of the anterior intercostal artery perforators enhances the reliability of the vascular supply to the superior pedicle.
NDDR-CNN: Layer-wise Feature Fusing in Multi-Task CNN by Neural Discriminative Dimensionality Reduction

In this paper, we propose a novel Convolutional Neural Network (CNN) structure for general-purpose multi-task learning (MTL), which enables automatic feature fusing at every layer from different tasks. This is in contrast with the most widely used MTL CNN structures which empirically or heuristically share features on some specific layers (e.g., share all the features except the last convolutional layer). The proposed layerwise feature fusing scheme is formulated by combining existing CNN components in a novel way, with clear mathematical interpretability as discriminative dimensionality reduction, which is referred to as Neural Discriminative Dimensionality Reduction (NDDR). Specifically, we first concatenate features with the same spatial resolution from different tasks according to their channel dimension. Then, we show that the discriminative dimensionality reduction can be fulfilled by 1 × 1 Convolution, Batch Normalization, and Weight Decay in one CNN. The use of existing CNN components ensures the end-to-end training and the extensibility of the proposed NDDR layer to various state-of-the-art CNN architectures in a “plug-andplay” manner. The detailed ablation analysis shows that the proposed NDDR layer is easy to train and also robust to different hyperparameters. Experiments on different task sets with various base network architectures demonstrate the promising performance and desirable generalizability of our proposed method.
Triquetrohamate Impaction Syndrome: An Unrecognized Cause of Ulnar-Sided Wrist Pain; Its Presentation Further Defined.

The aim of this review was to further define the clinical condition triquetrohamate (TH) impaction syndrome (THIS), an entity underreported and missed often. Its presentation, physical findings, and treatment are presented.



Between 2009 and 2014, 18 patients were diagnosed with THIS. The age, sex, hand involved, activity responsible for symptoms, and defining characteristics were recorded. The physical findings, along with ancillary studies, were reviewed. Delay in diagnosis and misdiagnoses were assessed. Treatment, either conservative or surgical, is presented. Follow-up outcomes are presented.



There were 15 male and 3 females, average age of 42 years. Two-handed sports such as golf and baseball accounted for more than 60% of the cases, and these cases were the only ones that involved the lead nondominant hand, pain predominantly at impact. Delay in diagnosis averaged greater than 7 months, with triangular fibrocartilage (TFCC) and extensor carpi ulnaris (ECU) accounting for more than 50% of misdiagnoses. Physical findings of note included pain over the TH joint, worse with passive dorsiflexion and ulnar deviation. Radiographic findings are described. Instillation of lidocaine with the wrist in radial deviation under fluoroscopic imaging with relief of pain helped to confirm the diagnosis. Conservative treatment was successful in 9 of 18 patients (50%), whereas in the remaining, surgical intervention allowed approximately 80% return to full activities without limitation.



Triquetrohamate impaction syndrome remains an underreported and often unrecognized cause of ulnar-sided wrist pain. In this report, the largest series to date, its presentation, defining characteristics, and treatment options are further elucidated.