nils-herrmann/clean_scirepeval huggingface dataset:
An efficient gene selection algorithm based on mutual information

Gene selection, a significant preprocessing of the discriminant analysis of microarray data, is to select the most informative genes from the whole gene set. In this paper, an efficient mutual informationbased gene selection algorithm (MIGS) is proposed, in which genes are sequentially forward selected according to an approximate measure of the mutual information between the class and the selected selection procedure as well as the employment of Parzen window density estimation technique. Extensive experiments are conducted on three public gene expression datasets and the experimental results confirm the efficiency and effectiveness of the algorithm. Though the computational cost of MIGS-Pruning increases with the number of selected genes, it still has good performance applied in the microarray problems. & 2008 Elsevier B.V. All rights reserved.
A Review on User Interface Design Principles to Increase Software Usability for Users with Less Computer Literacy

This article presents a review on how software usab ility could be increased for users with less comput er literacy. The literature was reviewed to extract us er interface design principles by identifying the s imilar problems of this group of users. There are differen t groups of users with less computer literacy. Howe ver, based on the literature three groups of them need s p cial attention from software designers. The first group is elderly users, as users with lack of computer ba ckground. The second group is children, as novice u sers and the third group is users with mental or physica l disorders. Therefore, this study intends to focus on the mentioned groups, followed by a comparison between pr vious researches in the field, which reveals tha t some commonalities exist between the needs of these users. These commonalities were used to extract us er interface design principles such as (a) reducing th e number of features available at any given time, ( b) avoiding using computer terms, (c) putting customiz ation ability for font, color, size and (d) using appropriate graphical objects such as avatar or ico n. Taking these principles into account can solve s oftware usability problems and increase satisfaction of use rs with less computer literacy.
BPMN Miner 2.0: Discovering Hierarchical and Block-Structured BPMN Process Models

We present BPMN Miner 2.0: a tool that extracts hierarchical and block-structured BPMN process models from event logs. Given an event log in XES format, the tool partitions it into sub-logs (one per subprocess) and discovers a BPMN process model from each sub-log using existing techniques for discovering BPMN process models via heuristics nets or Petri nets. A drawback of these techniques is that they often produce spaghetti-like models and in some cases unsound models. Accordingly, BPMN Miner 2.0 applies post-processing steps to remove unsound constructions as well as a technique to block-structrure the resulting process models in a behavior-preserving manner. The tool is available as a standalone Java tool as well as a ProM and an Apromore plugin. The target audience of this demonstration includes process mining researchers as well as practitioners interested in exploring the potential of process mining using BPMN.
An SVM Based Speaker Independent Isolated Malayalam Word Recognition System

As technology advances man-machine interaction is becoming an unavoidable activity. So an effective method of communication with machines enhances the quality of life. If it is able to operate a system by simply commanding, then it will be a great blessing to the users. Speech is the most effective mode of communication used by humans. So by introducing voice user interfaces the interaction with the machines can be made more user friendly. This paper implements a speaker independent speech recognition system for limited vocabulary Malayalam Words in Raspberry Pi. Mel Frequency Cepstral Coefficients (MFCC) are the features for classification and this paper proposes Radial Basis Function (RBF) kernel in Support Vector Machine (SVM) classifier gives better accuracy in speech recognition than linear kernel. An overall accuracy of 91.8% is obtained with this work.
Quantifying tissue loads and spine stability while performing commonly prescribed low back stabilization exercises.

A quantitative biomechanical comparison of seven different lumbar spine "stabilization exercises."



The purpose of this research was to quantify lumbar spine stability resulting from the muscle activation patterns measured when performing selected stabilization exercises.



Many exercises are termed "stabilization exercises" for the low back; however, limited attempts have been made to quantify spine stability and the resultant tissue loading. Ranking resultant stability together with spinal load is very helpful for guiding clinical decision-making and therapeutic exercise design.



Eight stabilization exercises were quantified in this study. Spine kinematics, external forces, and 14 channels of torso EMG were recorded for each exercise. These data were input into a modified version of a lumbar spine model described by Cholewicki and McGill (1996) to quantify stability and L4-L5 compression.



A rank order of the various exercises was produced based on stability, muscle activation levels, and lumbar compression.



Quantification of the calibrated muscle activation levels together with low back compression and resultant stability assists clinical decisions regarding the most appropriate exercise for specific patients and specific objectives.
High Sensitivity and Wide Dynamic Range Analog Front-End Circuits for Pulsed TOF 4-D Imaging LADAR Receiver

Analog front-end (AFE) circuits, which mainly consist of a transimpedance amplifier (TIA) with wide dynamic range and a timing discriminator with double threshold voltage, were designed and implemented for a pulsed time-of-fight 4-D imaging LADAR receiver. The preamplifier of the proposed TIA adopts a shunt-feedback topology to amplify weak echo signal, and a current-mirror topology to amplify strong one, respectively. The proposed AFE can capture directly the pulsed echo amplitude with wide dynamic range through programmable gain control switches. The proposed AFE circuits, which achieve a high gain of 106 dB<inline-formula> <tex-math notation="LaTeX">$\Omega $ </tex-math></inline-formula>, a linear dynamic range of 80 dB, an averaged input-referred noise density of 0.89 pA/Hz<sup>0.5</sup> and a minimum detectable signal of <inline-formula> <tex-math notation="LaTeX">$0.36~\mu \text{A}$ </tex-math></inline-formula> at SNR = 5, and a sensitivity of 8 nW with APD of 45 A/W, were designed with 3.3 V devices and fabricated in a 0.18-<inline-formula> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula> standard CMOS process. The total area of AFE, which includes the circuit core, bandgap and bias circuits, and I/O PAD, is approximately equal to <inline-formula> <tex-math notation="LaTeX">$1.20\times 1.13$ </tex-math></inline-formula> mm<sup>2</sup>.
Towards model-predictive control for aerial pick-and-place

This paper considers pick-and-place tasks using aerial vehicles equipped with manipulators. The main focus is on the development and experimental validation of a nonlinear model-predictive control methodology to exploit the multi-body system dynamics and achieve optimized performance. At the core of the approach lies a sequential Newton method for unconstrained optimal control and a high-frequency low-level controller tracking the generated optimal reference trajectories. A low cost quadrotor prototype with a simple manipulator extending more than twice the radius of the vehicle is designed and integrated with an on-board vision system for object tracking. Experimental results show the effectiveness of model-predictive control to motivate the future use of real-time optimal control in place of standard ad-hoc gain scheduling techniques.
Improving self-regulated learning with a retrieval practice intervention.

Repeated retrieval practice is a powerful learning tool for promoting long-term retention, but students use this tool ineffectively when regulating their learning. The current experiments evaluated the efficacy of a minimal intervention aimed at improving students' self-regulated use of repeated retrieval practice. Across 2 experiments, students made decisions about when to study, engage in retrieval practice, or stop learning a set of foreign language word pairs. Some students received direct instruction about how to use repeated retrieval practice. These instructions emphasized the mnemonic benefits of retrieval practice over a less effective strategy (restudying) and told students how to use repeated retrieval practice to maximize their performance-specifically, that they should recall a translation correctly 3 times during learning. This minimal intervention promoted more effective self-regulated use of retrieval practice and better retention of the translations compared to a control group that received no instruction. Students who experienced this intervention also showed potential for long-term changes in self-regulated learning: They spontaneously used repeated retrieval practice 1 week later to learn new materials. These results provide a promising first step for developing guidelines for teaching students how to regulate their learning more effectively using repeated retrieval practice.
Amorphous metal-organic frameworks.

Crystalline metal-organic frameworks (MOFs) are porous frameworks comprising an infinite array of metal nodes connected by organic linkers. The number of novel MOF structures reported per year is now in excess of 6000, despite significant increases in the complexity of both component units and molecular networks. Their regularly repeating structures give rise to chemically variable porous architectures, which have been studied extensively due to their sorption and separation potential. More recently, catalytic applications have been proposed that make use of their chemical tunability, while reports of negative linear compressibility and negative thermal expansion have further expanded interest in the field. Amorphous metal-organic frameworks (aMOFs) retain the basic building blocks and connectivity of their crystalline counterparts, though they lack any long-range periodic order. Aperiodic arrangements of atoms result in their X-ray diffraction patterns being dominated by broad "humps" caused by diffuse scattering and thus they are largely indistinguishable from one another. Amorphous MOFs offer many exciting opportunities for practical application, either as novel functional materials themselves or facilitating other processes, though the domain is largely unexplored (total aMOF reported structures amounting to under 30). Specifically, the use of crystalline MOFs to detect harmful guest species before subsequent stress-induced collapse and guest immobilization is of considerable interest, while functional luminescent and optically active glass-like materials may also be prepared in this manner. The ion transporting capacity of crystalline MOFs might be improved during partial structural collapse, while there are possibilities of preparing superstrong glasses and hybrid liquids during thermal amorphization. The tuning of release times of MOF drug delivery vehicles by partial structural collapse may be possible, and aMOFs are often more mechanically robust than crystalline materials, which is of importance for industrial applications. In this Account, we describe the preparation of aMOFs by introduction of disorder into their parent crystalline frameworks through heating, pressure (both hydrostatic and nonhydrostatic), and ball-milling. The main method of characterizing these amorphous materials (analysis of the pair distribution function) is summarized, alongside complementary techniques such as Raman spectroscopy. Detailed investigations into their properties (both chemical and mechanical) are compiled and compared with those of crystalline MOFs, while the impact of the field on the processing techniques used for crystalline MOF powders is also assessed. Crucially, the benefits amorphization may bring to existing proposed MOF applications are detailed, alongside the possibilities and research directions afforded by the combination of the unique properties of the amorphous domain with the versatility of MOF chemistry.
Human brain tractography: A DTI vs DKI comparison analysis

Water diffusion can be measured using Diffusion Tensor Imaging (DTI). This technique estimates molecular diffusion using a Gaussian model which can account for anisotropy arising, for example, from the presence of myelin sheath. The main direction of diffusion can also be estimated from DTI and used to compute diffusion tracts (tractography), a good tool to analyse the structure of white matter brain pathways. Nevertheless, DTI has limitations, such as ignoring the non-Gaussian properties of biological tissues and the inability to resolve intra-voxel fibre crossings that may lead to the reconstruction of anatomically inaccurate tracts. Diffusion Kurtosis Imaging (DKI) was introduced to ameliorate these problems. By abandoning the Gaussian model, DKI acts as an extension of DTI, allowing the computation of the same scalar parameters as DTI as well as providing measures of tissue heterogeneity and resolving multiple tracts within each voxel[1]. The purpose of this study is to analyse the DKI performance in tractography comparing to the DTI approach. DKI data was acquired from 3 subjects (1 male, mean age: 39±14 years) using Philips Achieva® 3.0T including diffusion weighted (DW) Single Shot Echo Planar images using 64 directions with b-values 0, 1000 and 2000 s/mm2, reconstruction matrix 256×256, slice thickness 1.5 mm, TE/TR 64/7703 ms, FOV 240×240 mm2, 60 slices. DTI data was extracted from DKI considering only b-values 0 and 1000. All DTI and DKI based tracts were computed using DKIu, a Matlab toolbox created by Neto-Henriques et. al., using three different tractography approaches: DTI, Laz-DKI[2] and KT-DKI[1]. The structures considered were the Internal Capsule (IC) and the Corpus Callosum (CC). Using TrackVis for visualisation, DKI tractography was shown to enable improved fibre crossing resolutio n , consistent in all three subjects. The number of streamlines computed in the CC was higher with the DKI approach than with DTI, but lower in the IC. DKI-based tractography appears to successfully address some of the limitations of DTI, as it resolves crossing fibres, providing more useful information regarding the brain's microstructure. This is particularly important in pre-surgical planning and in identifying brain lesions and pathologies.
Separation of Craniopagus Twins over the Past 20 Years: A Systematic Review of the Variables That Lead to Successful Separation.

Attempted separation of craniopagus twins has continued to be associated with devastating results since the first partially successful separation with one surviving twin in 1952. To understand the factors that contribute to successful separation in the modern era of neuroimaging and modern surgical techniques, the authors reviewed and analyzed cases reported since 1995.



All reported cases of craniopagus twin separation attempts from 1995 to 2015 were identified using PubMed (n = 19). In addition, the Internet was searched for additional unreported separation attempts (n = 5). The peer-reviewed cases were used to build a categorical database containing information on each twin pair, including sex; date of birth; date of surgery; multiple- versus single-stage surgery; angular versus vertical conjoining; nature of shared cerebral venous system; and the presence of other comorbidities identified as cardiovascular, genitourinary, and craniofacial. The data were analyzed to find factors associated with successful separation (survival of both twins at postoperative day 30).



Vertical craniopagus is associated with successful separation (p < 0.001). No statistical significance was attributed to the nature of the shared cerebral venous drainage or the other variables examined. Multiple-stage operations and surgery before 12 months of age are associated with a trend toward statistical significance for successful separation.



The authors' analysis indicates that vertical craniopagus twins have the highest likelihood of successful separation. Additional factors possibly associated with successful separation include the nature of the shared sinus system, surgery at a young age, and the use of staged separations.



Therapeutic, V.
A Wideband Differential-Fed Dual-Polarized Microstrip Antenna Under Radiation of Dual Improved Odd-Order Resonant Modes

A low profile differential-fed dual-polarized microstrip patch antenna (MPA) with bandwidth enhancement is proposed under radiation of the first and second odd-order resonant modes. First, all of even-order modes are fully suppressed by using a differentially feeding scheme instead of the single probe feed. Next, the radiation pattern of a square MPA is theoretically analyzed. It is demonstrated that the traditional monopole-like radiation of the second odd-order mode in the H-plane, i.e., TM21 mode, can be transformed into the broadside radiation by etching out a narrow slot at the center of the radiating patch. After that, an array of shorting pins is symmetrically embedded underneath the radiating patch so as to progressively push up the resonant frequency of the TM01 mode (or TM10 mode), while almost maintaining that of TM21 mode (or TM12 mode) to be unchanged. With these arrangements, a wide impedance bandwidth with stable radiation peak in the broadside direction is achieved for the MPA under this dual modes operation. Finally, the dual-polarized MPA is fabricated and measured. The measured results are found in good agreement with the simulated ones in terms of the reflection coefficient, radiation pattern, and realized gain, demonstrating that the MPA’s impedance bandwidth ( $\vert S_{\mathrm { {dd11}}}\vert <-10$  dB) is tremendously increased up to about 8% with a high differential port-to-port isolation of better than 22.6 dB. In particular, a low profile property of about 0.024 free-space wavelength and the stable radiation pattern are also achieved.
MapReduce is Good Enough? If All You Have is a Hammer, Throw Away Everything That's Not a Nail!

Hadoop is currently the large-scale data analysis "hammer" of choice, but there exist classes of algorithms that aren't "nails" in the sense that they are not particularly amenable to the MapReduce programming model. To address this, researchers have proposed MapReduce extensions or alternative programming models in which these algorithms can be elegantly expressed. This article espouses a very different position: that MapReduce is "good enough," and that instead of trying to invent screwdrivers, we should simply get rid of everything that's not a nail. To be more specific, much discussion in the literature surrounds the fact that iterative algorithms are a poor fit for MapReduce. The simple solution is to find alternative, noniterative algorithms that solve the same problem. This article captures my personal experiences as an academic researcher as well as a software engineer in a "real-world" production analytics environment. From this combined perspective, I reflect on the current state and future of "big data" research.
Allergic contact cheilitis in children and improvement with patch testing

ACC: allergic contact cheilitis Bronopol: 2-Bromo-2-nitropropane-1,3-diol MI: methylisothiazolinone MCI: methylchloroisothiazolinone INTRODUCTION Pediatric cheilitis can be a debilitating condition for the child and parents. Patch testing can help isolate allergens to avoid. Here we describe a 2-yearold boy with allergic contact cheilitis improving remarkably after prudent avoidance of contactants and food avoidance.
High Dimensional Cluster Analysis Using Path Lengths

A hierarchical scheme for clustering data is presented which applies to spaces with a high number of dimensions ( 3 D N > ). The data set is first reduced to a smaller set of partitions (multi-dimensional bins). Multiple clustering techniques are used, including spectral clustering; however, new techniques are also introduced based on the path length between partitions that are connected to one another. A Line-of-Sight algorithm is also developed for clustering. A test bank of 12 data sets with varying properties is used to expose the strengths and weaknesses of each technique. Finally, a robust clustering technique is discussed based on reaching a consensus among the multiple approaches, overcoming the weaknesses found individually.
Distributed Fiber-Optic Sensors for Vibration Detection

Distributed fiber-optic vibration sensors receive extensive investigation and play a significant role in the sensor panorama. Optical parameters such as light intensity, phase, polarization state, or light frequency will change when external vibration is applied on the sensing fiber. In this paper, various technologies of distributed fiber-optic vibration sensing are reviewed, from interferometric sensing technology, such as Sagnac, Mach-Zehnder, and Michelson, to backscattering-based sensing technology, such as phase-sensitive optical time domain reflectometer, polarization-optical time domain reflectometer, optical frequency domain reflectometer, as well as some combinations of interferometric and backscattering-based techniques. Their operation principles are presented and recent research efforts are also included. Finally, the applications of distributed fiber-optic vibration sensors are summarized, which mainly include structural health monitoring and perimeter security, etc. Overall, distributed fiber-optic vibration sensors possess the advantages of large-scale monitoring, good concealment, excellent flexibility, and immunity to electromagnetic interference, and thus show considerable potential for a variety of practical applications.
Misdiagnosis of fetus-in-fetu as meconium peritonitis

Fetus-in-fetu (FIF) is a rare congenital condition in which a fetiform mass is detected in the host abdomen and also in other sites such as the intracranium, thorax, head, and neck. This condition has been rarely reported in the literature. Herein, we report the case of a fetus presenting with abdominal cystic mass and ascites and prenatally diagnosed as meconium pseudocyst. Explorative laparotomy revealed an irregular fetiform mass in the retroperitoneum within a fluid-filled cyst. The mass contained intestinal tract, liver, pancreas, and finger. Fetal abdominal cystic mass has been identified in a broad spectrum of diseases. However, as in our case, FIF is often overlooked during differential diagnosis. FIF should also be differentiated from other conditions associated with fetal abdominal masses.
Overlapping Community Detection in Social Network Using Disjoint Community Detection

With increasing popularity and complexity of social networks, community detection in these networks has become an important research area. Several algorithms are available to detect overlapping community structures based on different approaches. Here we propose a two step genetic algorithm to detect overlapping communities based on node representation. First, we find disjoint communities and these disjoint communities are used to find overlapping communities. We use modularity as our optimization function. Experiments are performed on both artificial and real networks to verify efficiency and scalability of our algorithm.