nils-herrmann/clean_scirepeval huggingface dataset:
Increased expression of arginase II in human diabetic corpus cavernosum: in diabetic-associated erectile dysfunction

Nitric oxide (NO) is the principal mediator of penile erection. NO is synthesized by nitric oxide synthase (NOS). It has been well documented that the major causative factor contributing to erectile dysfunction in diabetic patients is the reduction in the amount of NO synthesis in the corpora cavernosa of the penis resulting in alterations of normal penile homeostasis. Arginase is an enzyme that shares a common substrate with NOS, thus arginase may downregulate NO production by competing with NOS for this substrate, l-arginine. The purpose of the present study was to compare arginase gene expression, protein levels, and enzyme activity in diabetic human cavernosal tissue. When compared to normal human cavernosal tissue, diabetic corpus cavernosum from humans with erectile dysfunction had higher levels of arginase II protein, gene expression, and enzyme activity. In contrast, gene expression and protein levels of arginase I were not significantly different in diabetic cavernosal tissue when compared to control tissue. The reduced ability of diabetic tissue to convert l-arginine to l-citrulline via nitric oxide synthase was reversed by the selective inhibition of arginase by 2(S)-amino-6-boronohexanoic acid (ABH). These data suggest that the increased expression of arginase II in diabetic cavernosal tissue may contribute to the erectile dysfunction associated with this common disease process and may play a role in other manifestations of diabetic disease in which nitric oxide production is decreased.
Development of automatic vehicle plate detection system

This paper presents the development of automatic vehicle plate detection system using image processing technique. The famous name for this system is Automatic Number Plate Recognition (ANPR). Automatic vehicle plate detection system is commonly used in field of safety and security systems especially in car parking area. Beside the safety aspect, this system is applied to monitor road traffic such as the speed of vehicle and identification of the vehicle's owner. This system is designed to assist the authorities in identifying the stolen vehicle not only for car but motorcycle as well. In this system, the Optical Character Recognition (OCR) technique was the prominent technique employed by researchers to analyse image of vehicle plate. The limitation of this technique was the incapability of the technique to convert text or data accurately. Besides, the characters, the background and the size of the vehicle plate are varied from one country to other country. Hence, this project proposes a combination of image processing technique and OCR to obtain the accurate vehicle plate recognition for vehicle in Malaysia. The outcome of this study is the system capable to detect characters and numbers of vehicle plate in different backgrounds (black and white) accurately. This study also involves the development of Graphical User Interface (GUI) to ease user in recognizing the characters and numbers in the vehicle or license plates.
Copy-move forgery detection based on deep learning

Copy-move forgery detection (CMFD) is probably one of the most active research areas within the blind image forensics field. Among existing algorithms, most of them are based on block and key-point methods, or combination of them. Recently, some deep convolutional neural networks methods have been applied in the image classification, image forensic, image hashing retrieval, and so on, which have shown better performance than the traditional method. In the work, a novel copy-move forgery detection method based on convolutional neural network is proposed. The proposed method uses existing trained model from large database as ImageNet, and then adjusts slightly the net structure using small training samples. Experimental results show that the method we proposed obtains satisfactory performance to the forgery image generated automatically by computer with simple image copy-move operation
Switched state-space model for a switched-capacitor power amplifier

This paper presents a switched state-space modeling approach for a switched-capacitor power amplifier. In contrast to state of the art behavioral models for nonlinear devices like power amplifiers, the state-space representation allows a straightforward inclusion of the nonidealities of the applied input sources. Hence, adding noise on a power supply or phase distortions on the carrier signal do not require a redesign of the mathematical model. The derived state-space model (SSM), which can be efficiently implemented in any numerical simulation tool, allows a significant reduction of the required simulation run-time (14x speedup factor) with respect to standard Cadence Spectre simulations. The derived state-space model (SSM) has been implemented in MATLAB/Simulink and its results have been verified by comparison with Cadence Spectre simulations.
The iliac crest in forensic age diagnostics: evaluation of the apophyseal ossification in conventional radiography

Due to the increasing significance of forensic age estimations in the age of globalisation, novel radiographic criteria besides clavicles and hand bones may provide additional certainty for forensic age expertises. The present study analyses the suitability of the iliac crest apophysis by means of 643 pelvic radiographs of patients between 10 and 30 years of age. Retrospective assessments were carried out according to the forensically established classification and sub-classification systems modified after Kreitner et al. (Rofo 166(6):481–486, 1997) and Kellinghaus et al. ( 2010). The basic ossification stages range from 1 to 4, and the sub-stages of stage 2 and 3 range from a to c. While stage 3c was first achieved at the age of 15 by both sexes, stage 4 was first observed in females at the age of 16 and in males at the age of 17. This indicates the possibility of a valid diagnosis of both the age of 14 and the age of 16 years which represent legally relevant age thresholds in numerous countries. Applied as targeted radiography on the iliac crest, the exposure to radiation would range between other radiographic techniques recently applied. Therefore, the iliac crest apophysis appears principally suitable as novel possible criterion for forensic age estimation in the living. However, for the establishment of the iliac crest apophysis in routine diagnostics, further studies are needed focussing on the comparison of different grading systems and different radiological techniques.
Fuzzy Clustered Probabilistic and Multi Layered Feed Forward Neural Networks for Electrocardiogram Arrhythmia Classification

The role of electrocardiogram (ECG) as a noninvasive technique for detecting and diagnosing cardiac problems cannot be overemphasized. This paper introduces a fuzzy C-mean (FCM) clustered probabilistic neural network (PNN) for the discrimination of eight types of ECG beats. The performance has been compared with FCM clustered multi layered feed forward network (MLFFN) trained with back propagation algorithm. Important parameters are extracted from each ECG beat and feature reduction has been carried out using FCM clustering. The cluster centers form the input of neural network classifiers. The extensive analysis using the MIT-BIH arrhythmia database has shown an average classification accuracy of 97.54% with FCM clustered MLFFN and 99.58% with FCM clustered PNN. Fuzzy clustering improves the classification speed as well. The result reveals the capability of the FCM clustered PNN in the computer-aided diagnosis of ECG abnormalities.
WIRELESS POWER TRANSMISSION OF SPACE BASED SOLAR

The aim of this paper is to analyze advanced solar dynamic space power systems for electrical space power generation. Space-based solar power [1] (SBSP) is a system for the collection of solar power in space, to meet the ever increasing demand for energy on Earth. SBSP differs from the usual method of solar power collection in the Earth. At the earth based solar power collection, array of panels are placed in the ground facing the sun, which collects sun’s energy during the day-time alone. In SBSP huge solar panels are fitted in the large satellite which collects the entire solar energy present in orbit and beams it down to Earth. In space, the collection of Sun’s energy is unaffected by the day/night cycle, weather, seasonal changes and the filtering effect of Earth’s atmospheric gases. A major interest in SBSP stems from the fact that solar collection panels can consistently be exposed to a high amount of solar radiation. SBSP offers a complete displacement of fossil fuel, nuclear and biological sources of energy. It is the only energy technology that is clean, renewable, constant and capable of providing power to virtually any location on Earth. KeywordsSpace-based solar power (SBSP), Solar power satellite (SPS), Rectifying Antenna (Rectanna)
Aalborg Universitet A Survey on Control of Electric Power Distributed Generation Systems for Microgrid Applications

The introduction of microgrids in distribution networks based on power electronics facilitates the use of renewable energy resources, distributed generation (DG) and storage systems while improving the quality of electric power and reducing losses thus increasing the performance and reliability of the electrical system, opens new horizons for microgrid applications integrated into electrical power systems. The hierarchical control structure consists of primary, secondary, and tertiary levels for microgrids that mimic the behavior of the mains grid is reviewed. The main objective of this paper is to give a description of state of the art for the distributed power generation systems (DPGS) based on renewable energy and explores the power converter connected in parallel to the grid which are distinguished by their contribution to the formation of the grid voltage and frequency and are accordingly classified in three classes. This analysis is extended focusing mainly on the three classes of configurations grid-forming, grid-feeding, and gridsupporting. The paper ends up with an overview and a discussion of the control structures and strategies to control distribution power generation system (DPGS) units connected to the network.  Distributed power generation system (DPGS); hierarchical control; grid-forming; grid-feeding; grid-supporting. Nomenclature Symbols id − iq Vd − Vq P Q ω E f U
Annotation of Entities and Relations in Spanish Radiology Reports

Radiology reports express the results of a radiology study and contain information about anatomical entities, findings, measures and impressions of the medical doctor. The use of information extraction techniques can help physicians to access this information in order to understand data and to infer further knowledge. Supervised machine learning methods are very popular to address information extraction, but are usually domain and language dependent. To train new classification models, annotated data is required. Moreover, annotated data is also required as an evaluation resource of information extraction algorithms. However, one major drawback of processing clinical data is the low availability of annotated datasets. For this reason we performed a manual annotation of radiology reports written in Spanish. This paper presents the corpus, the annotation schema, the annotation guidelines and further insight of the data.
Lidar-Based Relative Position Estimation and Tracking for Multi-robot Systems

Relative positioning systems play a vital role in current multirobot systems. We present a self-contained detection and tracking approach, where a robot estimates a distance (range) and an angle (bearing) to another robot using measurements extracted from the raw data provided by two laser range finders. We propose a method based on the detection of circular features with least-squares fitting and filtering out outliers using a map-based selection. We improve the estimate of the relative robot position and reduce its uncertainty by feeding measurements into a Kalman filter, resulting in an accurate tracking system. We evaluate the performance of the algorithm in a realistic indoor environment to demonstrate its robustness and reliability.
Osteopathy for primary headache patients: a systematic review

This systematic review aimed to assess the efficacy, effectiveness, safety, and tolerability of osteopathic manipulative treatment (OMT) in patients with headache.



Migraine is one of the most common and disabling medical conditions. It affects more than 15% of the general population, causing high global socioeconomic costs, and the currently available treatment options are inadequate.



We systematically reviewed all available studies investigating the use of OMT in patients with migraine and other forms of headache.



The search of literature produced six studies, five of which were eligible for review. The reviewed papers collectively support the notion that patients with migraine can benefit from OMT. OMT could most likely reduce the number of episodes per month as well as drug use. None of the included studies, however, was classified as low risk of bias according to the Cochrane Collaboration's tool for assessing risk of bias.



The results from this systematic review show a preliminary low level of evidence that OMT is effective in the management of headache. However, studies with more rigorous designs and methodology are needed to strengthen this evidence. Moreover, this review suggests that new manual interventions for the treatment of acute migraine are available and developing.
Grounded Unsupervised Semantic Parsing

We present the first unsupervised approach for semantic parsing that rivals the accuracy of supervised approaches in translating natural-language questions to database queries. Our GUSP system produces a semantic parse by annotating the dependency-tree nodes and edges with latent states, and learns a probabilistic grammar using EM. To compensate for the lack of example annotations or question-answer pairs, GUSP adopts a novel grounded-learning approach to leverage database for indirect supervision. On the challenging ATIS dataset, GUSP attained an accuracy of 84%, effectively tying with the best published results by supervised approaches.
FPGA Implementation of 256-Bit, 64-Point DIT-FFT Using Radix-4 Algorithm

Human needs with technical devices are increasing rapidly. In order to meet their requirements the system should be accurate and fast. The fastness and accuracy of a system depends on its intra and inter peripherals/algorithms. In the view of this, the proposed paper came into existence. It focuses on the development of the Fast Fourier Transform (FFT) algorithm, based on Decimation-InTime (DIT) domain, called Radix-4 DIT-FFT algorithm. VHDL is used as a design entity and for simulation Xilinx ISE. The synthesis results show that the computation for calculating the 256-bit 64-point FFT is efficient in terms of speed and is implemented on FPGA Spartan-3E kit.
Extending App Pre-Launch Service with Emotion Context: Poster Abstract

This paper reports a mobile application pre-launch scheme that is based on user's emotion. Smartphone application's usage and smartwatch's internal sensors are exploited to predict user's intension. User's emotion can be extracted from the PPG sensor in the smartwatch. In this paper, we extend previous App pre-launch service with user's emotion data. Applying machine learning algorithm to the training data, we can predict the application to be executed in near future. With our emotion context, we expect we can predict user's intension more accurately.
Learning Meta-Embeddings by Using Ensembles of Embedding Sets

Word embeddings – distributed representations of words – in deep learning are beneficial for many tasks in natural language processing (NLP). However, different embedding sets vary greatly in quality and characteristics of the captured semantics. Instead of relying on a more advanced algorithm for embedding learning, this paper proposes an ensemble approach of combining different public embedding sets with the aim of learning meta-embeddings. Experiments on word similarity and analogy tasks and on part-of-speech tagging show better performance of metaembeddings compared to individual embedding sets. One advantage of meta-embeddings is the increased vocabulary coverage. We will release our meta-embeddings publicly.
Plasmodium transmission blocking activities of Vernonia amygdalina extracts and isolated compounds

Medicinal plants are a validated source for discovery of new leads and standardized herbal medicines. The aim of this study was to assess the activity of Vernonia amygdalina leaf extracts and isolated compounds against gametocytes and sporogonic stages of Plasmodium berghei and to validate the findings on field isolates of Plasmodium falciparum. Aqueous (Ver-H2O) and ethanolic (Ver-EtOH) leaf extracts were tested in vivo for activity against sexual and asexual blood stage P. berghei parasites. In vivo transmission blocking effects of Ver-EtOH and Ver-H2O were estimated by assessing P. berghei oocyst prevalence and density in Anopheles stephensi mosquitoes. Activity targeting early sporogonic stages (ESS), namely gametes, zygotes and ookinetes was assessed in vitro using P. berghei CTRPp.GFP strain. Bioassay guided fractionation was performed to characterize V. amygdalina fractions and molecules for anti-ESS activity. Fractions active against ESS of the murine parasite were tested for ex vivo transmission blocking activity on P. falciparum field isolates. Cytotoxic effects of extracts and isolated compounds vernolide and vernodalol were evaluated on the human cell lines HCT116 and EA.hy926. Ver-H2O reduced the P. berghei macrogametocyte density in mice by about 50% and Ver-EtOH reduced P. berghei oocyst prevalence and density by 27 and 90%, respectively, in An. stephensi mosquitoes. Ver-EtOH inhibited almost completely (>90%) ESS development in vitro at 50 μg/mL. At this concentration, four fractions obtained from the ethylacetate phase of the methanol extract displayed inhibitory activity >90% against ESS. Three tested fractions were also found active against field isolates of the human parasite P. falciparum, reducing oocyst prevalence in Anopheles coluzzii mosquitoes to one-half and oocyst density to one-fourth of controls. The molecules and fractions displayed considerable cytotoxicity on the two tested cell-lines. Vernonia amygdalina leaves contain molecules affecting multiple stages of Plasmodium, evidencing its potential for drug discovery. Chemical modification of the identified hit molecules, in particular vernodalol, could generate a library of druggable sesquiterpene lactones. The development of a multistage phytomedicine designed as preventive treatment to complement existing malaria control tools appears a challenging but feasible goal.
Feedback Control of Computing Systems

This book is about feedback control of computing systems. The main idea of feedback control is to use measurements of a system’s outputs, such as response times, throughputs, and utilizations, to achieve externally specified goals. This is done by adjusting the system control inputs, such as parameters that affect buffer sizes, scheduling policies, and concurrency levels. Since the measured outputs are used to determine the control inputs, and the inputs then affect the outputs, the architecture is called feedback or closed loop. Almost any system that is considered automatic has some element of feedback control. In this book we focus on the closed-loop control of computing systems and methods for their analysis and design.
On the Origin of Reverse Transcriptase-Using CRISPR-Cas Systems and Their Hyperdiverse, Enigmatic Spacer Repertoires

Cas1 integrase is the key enzyme of the clustered regularly interspaced short palindromic repeat (CRISPR)-Cas adaptation module that mediates acquisition of spacers derived from foreign DNA by CRISPR arrays. In diverse bacteria, the cas1 gene is fused (or adjacent) to a gene encoding a reverse transcriptase (RT) related to group II intron RTs. An RT-Cas1 fusion protein has been recently shown to enable acquisition of CRISPR spacers from RNA. Phylogenetic analysis of the CRISPR-associated RTs demonstrates monophyly of the RT-Cas1 fusion, and coevolution of the RT and Cas1 domains. Nearly all such RTs are present within type III CRISPR-Cas loci, but their phylogeny does not parallel the CRISPR-Cas type classification, indicating that RT-Cas1 is an autonomous functional module that is disseminated by horizontal gene transfer and can function with diverse type III systems. To compare the sequence pools sampled by RT-Cas1-associated and RT-lacking CRISPR-Cas systems, we obtained samples of a commercially grown cyanobacterium-Arthrospira platensis Sequencing of the CRISPR arrays uncovered a highly diverse population of spacers. Spacer diversity was particularly striking for the RT-Cas1-containing type III-B system, where no saturation was evident even with millions of sequences analyzed. In contrast, analysis of the RT-lacking type III-D system yielded a highly diverse pool but reached a point where fewer novel spacers were recovered as sequencing depth was increased. Matches could be identified for a small fraction of the non-RT-Cas1-associated spacers, and for only a single RT-Cas1-associated spacer. Thus, the principal source(s) of the spacers, particularly the hypervariable spacer repertoire of the RT-associated arrays, remains unknown. While the majority of CRISPR-Cas immune systems adapt to foreign genetic elements by capturing segments of invasive DNA, some systems carry reverse transcriptases (RTs) that enable adaptation to RNA molecules. From analysis of available bacterial sequence data, we find evidence that RT-based RNA adaptation machinery has been able to join with CRISPR-Cas immune systems in many, diverse bacterial species. To investigate whether the abilities to adapt to DNA and RNA molecules are utilized for defense against distinct classes of invaders in nature, we sequenced CRISPR arrays from samples of commercial-scale open-air cultures of Arthrospira platensis, a cyanobacterium that contains both RT-lacking and RT-containing CRISPR-Cas systems. We uncovered a diverse pool of naturally occurring immune memories, with the RT-lacking locus acquiring a number of segments matching known viral or bacterial genes, while the RT-containing locus has acquired spacers from a distinct sequence pool for which the source remains enigmatic.
Early Fusion for Goal Directed Robotic Vision

Increasingly, perceptual systems are being codified as strict pipelines wherein vision is treated as a pre-processing step to provide a dense representation of the scene to planners for high level reasoning downstream. Problematically, this paradigm forces models to represent nearly every aspect of the scene even if it has no bearing on the task at hand. In this work, we flip this paradigm, by introducing vision models whose feature representations are conditioned on embedded representations of the agent’s goal. This allows the model to build scene descriptions that are specifically designed to help achieve that goal. We find this leads to models that learn faster, are substantially more parameter efficient and more robust than existing attention mechanisms in our domain. Our experiments are performed on a simulated robot item retrieval problem and trained in a fully end-to-end manner via imitation learning.