nils-herrmann/clean_scirepeval huggingface dataset:
Dynamic Modeling and Simulation of Compliant Legged Quadruped Robot

Quadruped robot has many advantages over wheeled mobile robots, but it is a discrete system in which joints of each leg has to operate in particular fashion to get the desired locomotion. So, dynamics plays an important role in the operation and control of quadruped robot. Proper conception of the dynamic formulation is must for the complex system like quadruped robot. Here, an attempt is made to generate three dimensional model of a quadruped using the bond graph technique. Bond graph is an efficient tool for system modeling from the physical model itself and various control strategies can be developed very efficiently. A quadruped robot configuration used for analysis is two links legged robot in which upper link is rigid and lower link is compliant. In a lower link, piston and piston rod is sliding inside the cylinder and movement is restricted by the internal hydraulic pressure of the cylinder which will generate compliance in the leg. Simulation of the various gait performed by the quadruped is carried out, which proves the versatility of the three dimensional model generated. The generated model can be used in research of various aspects pertaining to quadruped, the same thing is demonstrated by doing performance evaluation between compliant and rigid legged robot and also between two different gaits like trot gait and amble gait. Quadruped robot, Bond graph, Dynamic model
Narcolepsy-like sleep disturbance in orexin knockout mice are normalized by the 5-HT1A receptor agonist 8-OH-DPAT

Orexin knockout (KO) mice exhibit a phenotype that is similar to human narcolepsy, and monoamine-related compounds, such as psychostimulants and 5-HT uptake inhibitors, have been used for the treatment of narcoleptic disorders. However, little information is available regarding the pathophysiological features of orexin KO mice, particularly with respect to their narcoleptic-like disorder and how it is affected by monoamine-related compounds. The present study was designed to investigate both the nature of the neuronal changes in orexin KO mice and the therapeutic effects of monoamine-related compounds on the sleep disorder in orexin KO mice. A decrease in locomotor activity in the dark phase was observed in orexin KO mice, and psychostimulants and 5-HT-related compounds, such as 8-OH-DPAT (5-HT1A receptor agonist) and DOI (5-HT2 receptor agonist), inhibited this hypolocomotion. We also found that 5-HT1A receptor mRNA levels, but not those for 5-HT2 or dopamine receptors, were significantly decreased in the prefrontal cortex of orexin KO mice in the dark period and were accompanied by compromising the increase in 5-HT metabolite levels. In addition, the sleep disorder in orexin KO mice, as analyzed by a polysomnography during the dark period, was completely normalized by 8-OH-DPAT. These results suggest that a dysfunction of 5-HT1A receptors is involved in the narcoleptic-like sleep dysfunction in orexin KO mice, and such dysfunction may participate in orexin deficiency-induced sleep disorders. Further, the use of 5-HT1A receptor agonist could be useful for treating the sleep disorder under a deficiency of orexin.
Full-bridge single-stage PFC with reduced DC bus capacitor and improved light load operation as a solution for modern SMPS

Modern Single-Stage Switch Mode Power Supplies (namely Full-Bridge topologies for high power applications >500W), allows to regulate the output voltage and the input current, achieving a sinusoidal waveform by using only the four bridge transistors. However, these solutions still need to be optimized in order to become an interesting and attractive solution for modern Switch Mode Power Supplies with PFC function. One of the most important improvements needed is the downsizing and the cost reduction associated to the DC bus capacitor (CF - filtering capacitor). Nevertheless, this action introduces several complex issues in the regulation of the input current and also high output voltage ripple. The proposed paper describes a new process to reduce the CF value solving the identified issues. Firstly it is proved that it is possible to use a reduced capacitance/watt ratio, lower than the one that is typically used in commercial applications 0.5μF/W, while maintaining the accurate regulation of the input current. The output voltage ripple issues are solved using a modified One Cycle Control, OCC circuit. The concepts and solutions developed will be proved based on experimental results in an optimized FBSS topology that uses a Free Wheeling Capacitor, FWC, circuit in order to improve the low power operation.
Digital Advertising Traffic Operation: Machine Learning for Process Discovery

In a Web Advertising Traffic Operation it’s necessary to manage the day-to-day trafficking, pacing and optimization of digital and paid social campaigns. The data analyst on Traffic Operation can not only quickly provide answers but also speaks the language of the Process Manager and visually displays the discovered process problems. In order to solve a growing number of complaints in the customer service process, the weaknesses in the process itself must be identified and communicated to the department. With the help of Process Mining for the CRM data it is possible to identify unwanted loops and delays in the process. With this paper we propose a process discovery based on Machine Learning technique to automatically discover variations and detect at first glance what the problem is, and undertake corrective measures.
From Trailers to Storylines: An Efficient Way to Learn from Movies

The millions of movies produced in the human history are valuable resources for computer vision research. However, learning a vision model from movie data would meet with serious difficulties. A major obstacle is the computational cost – the length of a movie is often over one hour, which is substantially longer than the short video clips that previous study mostly focuses on. In this paper, we explore an alternative approach to learning vision models from movies. Specifically, we consider a framework comprised of a visual module and a temporal analysis module. Unlike conventional learning methods, the proposed approach learns these modules from different sets of data – the former from trailers while the latter from movies. This allows distinctive visual features to be learned within a reasonable budget while still preserving long-term temporal structures across an entire movie. We construct a large-scale dataset for this study and define a series of tasks on top. Experiments on this dataset showed that the proposed method can substantially reduce the training time while obtaining highly effective features and coherent temporal structures.
A Review of Various Character Segmentation Techniques for Cursive Handwritten Words Recognition

Cursive handwriting recognition is a challenging task for many real world applications such as document authentication, form processing, postal address recognition, reading machines for the blind, bank cheque recognition and interpretation of historical documents. Therefore, in the last few decades the researchers have put enormous effort to develop various techniques for handwriting segmentation and recognition. This review presents the segmentation strategies for automated recognition of off-line unconstrained cursive handwriting from static surfaces. This paper reviews many basic and advanced techniques and also compares the research results of various researchers in the domain of handwritten words segmentation.
iDental: A Haptic-Based Dental Simulator and Its Preliminary User Evaluation

Performance evaluation is indispensable for a surgical simulator to become acceptable. A haptics-based dental simulator (iDental) has been developed and preliminary user evaluation on its first-generation prototype has been carried out to gain the knowledge. Based on detailed requirement analysis of Periodontics procedures, a combined evaluation method including qualitative and quantitative analysis was designed. Construct validity was used to compare the performance difference between two groups of participants (faculty members and dental graduate students). These participants were required to perform three periodontal examination and treatment procedures including periodontal pocket probing, calculus detection, and removal. From the evaluation results, we found that penetration between tool and teeth or cheek will greatly decrease the fidelity of the simulation, therefore, it is necessary to utilize 6-DOF haptic device with both force and torque feedback in dental simulator, and accordingly it is needed to extend point-based rendering to 6-DOF haptic rendering of multiregion contacts. Furthermore, several other key research topics that will enable haptic technology to be effective in a practical dental simulator were identified, including simulation of deformable body such as tongue and gingival, and simulation of occlusion of tongue and cheek on teeth, etc.
Bridging the Gap Between 2D and 3D Organ Segmentation

There has been a debate on whether to use 2D or 3D deep neural networks for volumetric organ segmentation. Both 2D and 3D models have their advantages and disadvantages. In this paper, we present an alternative framework, which trains 2D networks on different viewpoints for segmentation, and builds a 3D Volumetric Fusion Net (VFN) to fuse the 2D segmentation results. VFN is relatively shallow and contains much fewer parameters than most 3D networks, making our framework more efficient at integrating 3D information for segmentation. We train and test the segmentation and fusion modules individually, and propose a novel strategy, named cross-cross-augmentation, to make full use of the limited training data. We evaluate our framework on several challenging abdominal organs, and verify its superiority in segmentation accuracy and stability over existing 2D and 3D approaches.
Biosorption of heavy metals.

Only within the past decade has the potential of metal biosorption by biomass materials been well established. For economic reasons, of particular interest are abundant biomass types generated as a waste byproduct of large-scale industrial fermentations or certain metal-binding algae found in large quantities in the sea. These biomass types serve as a basis for newly developed metal biosorption processes foreseen particularly as a very competitive means for the detoxification of metal-bearing industrial effluents. The assessment of the metal-binding capacity of some new biosorbents is discussed. Lead and cadmium, for instance, have been effectively removed from very dilute solutions by the dried biomass of some ubiquitous species of brown marine algae such as Ascophyllum and Sargassum, which accumulate more than 30% of biomass dry weight in the metal. Mycelia of the industrial steroid-transforming fungi Rhizopus and Absidia are excellent biosorbents for lead, cadmium, copper, zinc, and uranium and also bind other heavy metals up to 25% of the biomass dry weight. Biosorption isotherm curves, derived from equilibrium batch sorption experiments, are used in the evaluation of metal uptake by different biosorbents. Further studies are focusing on the assessment of biosorbent performance in dynamic continuous-flow sorption systems. In the course of this work, new methodologies are being developed that are aimed at mathematical modeling of biosorption systems and their effective optimization. Elucidation of mechanisms active in metal biosorption is essential for successful exploitation of the phenomenon and for regeneration of biosorbent materials in multiple reuse cycles. The complex nature of biosorbent materials makes this task particularly challenging. Discussion focuses on the composition of marine algae polysaccharide structures, which seem instrumental in metal uptake and binding. The state of the art in the field of biosorption is reviewed in this article, with many references to recent reviews and key individual contributions.
Electrophysiological evidence for a neurohormonal dependence in the changes of the late glabellar response in man.

In 19 normal adults reserpine administration induced significant changes in the parameters of the second glabellar response (R2): shortening of the latency and duration; decrease of the excitability threshold and complete blockade of the physiological habituation of R2 to the electrical and mechanical stimulation. No changes in the first response (R1) were observed. All the R2 changes disappeared within about 3 days of drug administration. The Parkinson-like effect of reserpine on the glabellar reflex is discussed in the light of a neurohormonal hypothesis in the control of the polysynaptic pathways biasing R2.
Performance Comparison between Sliding Mode Control (SMC) and PD-PID Controllers for a Nonlinear Inverted Pendulum System

The objective of this paper is to compare the time specification performance between conventional controller PID and modern controller SMC for an inverted pendulum system. The goal is to determine which control strategy delivers better performance with respect to pendulum’s angle and cart’s position. The inverted pendulum represents a challenging control problem, which continually moves toward an uncontrolled state. Two controllers are presented such as Sliding Mode Control (SMC) and ProportionalIntegral-Derivatives (PID) controllers for controlling the highly nonlinear system of inverted pendulum model. Simulation study has been done in Matlab Mfile and simulink environment shows that both controllers are capable to control multi output inverted pendulum system successfully. The result shows that Sliding Mode Control (SMC) produced better response compared to PID control strategies and the responses are presented in time domain with the details analysis. SMC, PID, Inverted Pendulum System.
Ubiquinol: an endogenous antioxidant in aerobic organisms

Ubiquinone (coenzyme Q), in addition to its function as an electron and proton carrier in mitochondrial and bacterial electron transport linked to ATP synthesis, acts in its reduced form (ubiquinol) as an antioxidant, preventing the initiation and/or propagation of lipid peroxidation in biological membranes and in serum low-density lipoprotein. The antioxidant activity of ubiquinol is independent of the effect of vitamin E, which acts as a chain-breaking antioxidant inhibiting the propagation of lipid peroxidation. In addition, ubiquinol can efficiently sustain the effect of vitamin E by regenerating the vitamin from the tocopheroxyl radical, which otherwise must rely on water-soluble agents such as ascorbate (vitamin C). Ubiquinol is the only known lipid-soluble antioxidant that animal cells can synthesize de novo, and for which there exist enzymic mechanisms that can regenerate the antioxidant from its oxidized form resulting from its inhibitory effect of lipid peroxidation. These features, together with its high degree of hydrophobicity and its widespread occurrence in biological membranes and in low-density lipoprotein, suggest an important role of ubiquinol in cellular defense against oxidative damage. Degenerative diseases and aging may bc 1 manifestations of a decreased capacity to maintain adequate ubiquinol levels.
Optimal design of an EV fast charging station coupled with storage in Stockholm

Is battery energy storage a feasible solution for lowering the operational costs of electric vehicle fast charging and reducing its impact on local grids? The thesis project aims at answering this question for the Swedish scenario. The proposed solution (fast charging station coupled with storage) is modelled in MATLAB, and its performance is tested in the framework provided by Swedish regulation and electricity tariff structure. The analysis is centred on the economic performance of the system. Its cost-effectiveness is assessed by means of an optimisation algorithm, designed for delivering the optimal control strategy and the required equipment sizing. A mixed-integer linear programming (MILP) formulation is utilised. The configuration and operative costs of conventional fast charging stations are used as a benchmark for the output of the optimisation. Sensitivity analysis is conducted on most relevant parameters: charging load, battery price and tariff structure. The modelling of the charging demand is based on statistics from currently implemented 50 kW DC chargers in Sweden. Overall, results show that with current figures the system may be an economically viable solution for both reducing costs and lowering the impact on the local distribution grid, at least during peak-period pricing. However, sensitivity analysis illustrates how system design and performance are highly dependent on input parameters. Among these, electricity tariff was identified as the most important. Consequently, detailed discussion on the influence of this parameter is conducted. Finally, the study shows how the system is in line with most recent directives proposed by the European Commission.
OPTIMIZING UNSUPERVISED LEARNING OF OPINION TARGETS FROM UNSTRUCTURED REVIEWS USING WORDNET BASED SEMANTIC ORIENTATION

Target identification is an important task of opinion mining problem. Several approaches have been employed for this task which can be broadly divided into two major categories: supervised and unsupervised. The supervised approaches require training data which need manual work and are mostly domain dependent. Unsupervised technique is most popularly used due to its two main advantages: domain independent and no need of training data. This paper presents optimization of an unsupervised approach for opinion target identification from unstructured reviews. The unsupervised approaches basically extract frequently observed features in text hence the infrequently occurred features are ignored. This paper utilizes lexical resources to identify infrequent features. Empirical results shows direct impact on the performance of the frequency based features extraction
Prosthetic hand with a linkage finger mechanism for power grasping applications

The human hand is an exceptionally significant part of the human body which has a very complex biological system with bones, joints, and muscles. Among all hand functions, power grasping plays a crucial role in the activities of daily living. In this research a prosthetic terminal device is designed to assist the power grasping activities of amputees subjected to wrist disarticulation. The designed terminal device contains four identical fingers made of a novel linkage mechanism, which can accomplish flexion and extension. With the intention of verifying the effectiveness of the mechanism, kinematic analysis has been carried out. Furthermore, the motion simulation has demonstrated that the mechanism is capable of generating the appropriate finger movements to accomplish cylindrical and spherical power grasps. In addition, the work envelop of the proposed prosthetic finger has been determined. The 3D printed prototype of the finger was experimentally tested. The experimental results validate the effectiveness of the proposed mechanism to gain the expected motion patterns.
Brain-Computer Interfaces Using Electrocorticographic Signals

Many studies over the past two decades have shown that people and animals can use brain signals to convey their intent to a computer using brain-computer interfaces (BCIs). BCI systems measure specific features of brain activity and translate them into control signals that drive an output. The sensor modalities that have most commonly been used in BCI studies have been electroencephalographic (EEG) recordings from the scalp and single- neuron recordings from within the cortex. Over the past decade, an increasing number of studies has explored the use of electro-corticographic (ECoG) activity recorded directly from the surface of the brain. ECoG has attracted substantial and increasing interest, because it has been shown to reflect specific details of actual and imagined actions, and because its technical characteristics should readily support robust and chronic implementations of BCI systems in humans. This review provides general perspectives on the ECoG platform; describes the different electrophysiological features that can be detected in ECoG; elaborates on the signal acquisition issues, protocols, and online performance of ECoG- based BCI studies to date; presents important limitations of current ECoG studies; discusses opportunities for further research; and finally presents a vision for eventual clinical implementation. In summary, the studies presented to date strongly encourage further research using the ECoG platform for basic neuroscientific research, as well as for translational neuroprosthetic applications.
Mobile technologies in medical education: AMEE Guide No. 105.

Mobile technologies (including handheld and wearable devices) have the potential to enhance learning activities from basic medical undergraduate education through residency and beyond. In order to use these technologies successfully, medical educators need to be aware of the underpinning socio-theoretical concepts that influence their usage, the pre-clinical and clinical educational environment in which the educational activities occur, and the practical possibilities and limitations of their usage. This Guide builds upon the previous AMEE Guide to e-Learning in medical education by providing medical teachers with conceptual frameworks and practical examples of using mobile technologies in medical education. The goal is to help medical teachers to use these concepts and technologies at all levels of medical education to improve the education of medical and healthcare personnel, and ultimately contribute to improved patient healthcare. This Guide begins by reviewing some of the technological changes that have occurred in recent years, and then examines the theoretical basis (both social and educational) for understanding mobile technology usage. From there, the Guide progresses through a hierarchy of institutional, teacher and learner needs, identifying issues, problems and solutions for the effective use of mobile technology in medical education. This Guide ends with a brief look to the future.
Hybrid fur rendering: combining volumetric fur with explicit hair strands

Hair is typically modeled and rendered using either explicitly defined hair strand geometry or a volume texture of hair densities. Taken each on their own, these two hair representations have difficulties in the case of animal fur as it consists of very dense and thin undercoat hairs in combination with coarse guard hairs. Explicit hair strand geometry is not well-suited for the undercoat hairs, while volume textures are not well-suited for the guard hairs. To efficiently model and render both guard hairs and undercoat hairs, we present a hybrid technique that combines rasterization of explicitly defined guard hairs with ray marching of a prismatic shell volume with dynamic resolution. The latter is the key to practical combination of the two techniques, and it also enables a high degree of detail in the undercoat. We demonstrate that our hybrid technique creates a more detailed and soft fur appearance as compared with renderings that only use explicitly defined hair strands. Finally, our rasterization approach is based on order-independent transparency and renders high-quality fur images in seconds.
STRT-seq-2i: dual-index 5ʹ single cell and nucleus RNA-seq on an addressable microwell array

Single-cell RNA-seq has become routine for discovering cell types and revealing cellular diversity, but archived human brain samples still pose a challenge to current high-throughput platforms. We present STRT-seq-2i, an addressable 9600-microwell array platform, combining sampling by limiting dilution or FACS, with imaging and high throughput at competitive cost. We applied the platform to fresh single mouse cortical cells and to frozen post-mortem human cortical nuclei, matching the performance of a previous lower-throughput platform while retaining a high degree of flexibility, potentially also for other high-throughput applications.