nils-herrmann/clean_scirepeval huggingface dataset:
Audio Style Transfer

“Style transfer” among images has recently emerged as a very active research topic, fuelled by the power of convolution neural networks (CNNs), and has become fast a very popular technology in social media. This paper investigates the analogous problem in the audio domain: How to transfer the style of a reference audio signal to a target audio content? We propose a flexible framework for the task, which uses a sound texture model to extract statistics characterizing the reference audio style, followed by an optimization-based audio texture synthesis to modify the target content. In contrast to mainstream optimization-based visual transfer method, the proposed process is initialized by the target content instead of random noise and the optimized loss is only about texture, not structure. These differences proved key for audio style transfer in our experiments. In order to extract features of interest, we investigate different architectures, whether pre-trained on other tasks, as done in image style transfer, or engineered based on the human auditory system. Experimental results on different types of audio signal confirm the potential of the proposed approach.
A Disease-Modifying Approach for Advanced Hidradenitis Suppurativa (Regimen with Metformin, Liraglutide, Dapsone, and Finasteride): A Case Report

Hidradenitis suppurativa (HS) is a challenging skin disease with limited therapeutic options. Obesity and metabolic syndrome are being increasingly implicated and associated with younger ages and greater metabolic severity. A 19-year-old female with an 8-year history of progressively debilitating cicatricial HS disease presented with obesity, profound anemia, leukocytosis, increased platelet count, hypoalbuminemia, and elevated liver enzymes. A combination of metformin, liraglutide, levonorgestrel-ethinyl estradiol, dapsone, and finasteride was initiated. Acute antibiotic use for recurrences and flares could be slowly discontinued. Over the course of 3 years on this regimen, the liver enzymes normalized in 1 year, followed in2 years by complete resolution of the majority of the hematological and metabolic abnormalities. The sedimentation rate reduced from over 120 to 34 mm/h. She required 1 surgical intervention for perianal disease after 9 months on the regimen. Flares greatly diminished in intensity and duration, with none in the past 6 months. Right axillary lesions have completely healed with residual disease greatly reduced. Chiefly abdominal lesions are persistent. She was able to complete high school from home, start a job, and resume a normal life. Initial weight loss of 40 pounds was not maintained. The current regimen is being well tolerated and continued.
Treatment of Pseudomonas aeruginosa biofilm-infected wounds with clinical wound care strategies: a quantitative study using an in vivo rabbit ear model.

Bacterial biofilm is recognized as a major detriment to wound healing. The efficacy of traditional wound care against biofilm has never been studied. The authors evaluated the effect of clinical strategies against biofilm-infected wounds in a quantitative, in vivo model.



Using a rabbit ear biofilm model, wounds were inoculated with Pseudomonas aeruginosa or left as uninfected controls. Inoculated wounds acted as untreated controls or underwent treatment: every-other-day sharp débridement (I), lavage (II), Silvadene (III), or lavage and Silvadene (IV), or initial débridement with daily lavage and Silvadene (V). Wounds were harvested on days 12 and 18. Histological wound healing parameters and viable bacterial counts were measured. Biofilm structure was studied with scanning electron microscopy.



Uninfected controls healed better than P. aeruginosa biofilm-infected wounds across all parameters (p = 0.01). Groups IV and V demonstrated improved healing (p = 0.05) and decreased bacterial count (p = 0.05) compared with untreated P. aeruginosa biofilm, whereas groups I through III showed no differences in either. Scanning electron microscopy following a group V treatment showed temporary disruption of biofilm structure, which reformed in 24 hours.



Pseudomonal biofilm markedly impairs wound healing, shown quantitatively using our in vivo model. Despite common practice, wound care strategies cannot restore biofilm wounds to a healing phenotype when used alone or infrequently. The durability of biofilm extends nonhealing wound chronicity, thus requiring aggressive, multimodal therapy aimed at reducing bacterial burden. The authors' novel, rigorous study validates critical principles applicable to all clinical wound care.
Biometric liveness detection using gaze information

This thesis is concerned with liveness detection for biometric systems and in particular for face recognition systems. Biometric systems are well studied and have the potential to provide satisfactory solutions for a variety of applications. However, presentation attacks (spoofing), where an attempt is made at subverting them system by making a deliberate presentation at the sensor is a serious challenge to their use in unattended applications. Liveness detection techniques can help with protecting biometric systems from attacks made through the presentation of artefacts and recordings at the sensor. In this work novel techniques for liveness detection are presented using gaze information. The notion of natural gaze stability is introduced and used to develop a number of novel features that rely on directing the gaze of the user and establishing its behaviour. These features are then used to develop systems for detecting spoofing attempts. The attack scenarios considered in this work include the use of hand held photos and photo masks as well as video reply to subvert the system. The proposed features and systems based on them were evaluated extensively using data captured from genuine and fake attempts. The results of the evaluations indicate that gaze-based features can be used to discriminate between genuine and imposter. Combining features through feature selection and score fusion substantially improved the performance of the proposed features.
Modelling of bone fracture and strength at different length scales: a review.

In this paper, we review analytical and computational models of bone fracture and strength. Bone fracture is a complex phenomenon due to the composite, inhomogeneous and hierarchical structure of bone. First, we briefly summarize the hierarchical structure of bone, spanning from the nanoscale, sub-microscale, microscale, mesoscale to the macroscale, and discuss experimental observations on failure mechanisms in bone at these scales. Then, we highlight representative analytical and computational models of bone fracture and strength at different length scales and discuss the main findings in the context of experiments. We conclude by summarizing the challenges in modelling of bone fracture and strength and list open topics for scientific exploration. Modelling of bone, accounting for different scales, provides new and needed insights into the fracture and strength of bone, which, in turn, can lead to improved diagnostic tools and treatments of bone diseases such as osteoporosis.
A 28-GHz CMOS Broadband Single-Path Power Amplifier with 17.4-dBm P1dB for 5G Phased-Array

This paper reports a fully integrated broadband and linear power amplifier (PA) for 5G phased-array. Weakly-and strongly-coupled transformers are compared and analyzed in detail. The output strongly-coupled transformer is designed to transfer maximum power. The inter-stage weakly-coupled transformer is optimized to broaden the bandwidth. Besides, linearity is highly improved by operating the PA in deep class AB region. Designed and implemented in 65-nm CMOS process with 1V supply, the two-stage PA delivers a maximum small-signal gain of 19 dB. Maximum 1-dB compressed power (P1dB) of 17.4 dBm and saturated output power (PSAT) of 18 dBm are measured at 28 GHz. The power-added efficiency (PAE) at P1dB is 26.5%. The measured P1dBis above 16 dBm from 23 to 32 GHz, covering potential 5G bands worldwide around 28 GHz.
Optimization of PID Parameter for Position Control of DC-Motor using Multi-Objective Genetic Algorithm

The ambition of this paper is to design a position controller of a DC motor by selection of a PID parameter using genetic algorithm. The Proportional plus Integral plus Derivative (PID), controllers are most widely used in control theory as well as industrial plants due to their ease of execution and robustness performance. The aspiration of this deed representation capable and apace tuning approach using Genetic Algorithm (GA) to obtain the optimized criterion of the PID controller so as to appropriate the essential appearance designation of the technique below consideration. This scheme is a simulation and experimental analysis into the development of PID controller using MATLAB/SIMULINK software. There are several techniques which are used for tuning of PID controller to control the speed control of DC motor. Tuning of PID parameters is considerable because these parameters have a admirable effect on the stability and performance of the control system. Using genetic algorithms to perform the tuning of the controller results in the optimum controller being appraise for the system every time.
Inside the Mind of the Insider: Towards Insider Threat Detection Using Psychophysiological Signals

Insider threat is a great challenge for most organizations in today’s digital world. It has received substantial research attention as a significant source of information security threat that could cause more financial losses and damages than any other threats. However, designing an effective monitoring and detection framework is a very challenging task. In this paper, we examine the use of human bio-signals to detect the malicious activities and show that its applicability for insider threats detection. We employ a combination of the electroencephalography (EEG) and the electrocardiogram (ECG) signals to provide a framework for insider threat monitoring and detection. We empirically tested the framework with ten subjects and used several activities scenarios. We found that our framework able to achieve up to 90% detection accuracy of the malicious activities when using the electroencephalography (EEG) signals alone. We then examined the effectiveness of adding the electrocardiogram (ECG) signals to our framework and results show that by adding the ECG the accuracy of detecting the malicious activity increases by about 5%. Thus, our framework shows that human brain and heart signals can reveal valuable knowledge about the malicious behaviors and could be an effective solution for detecting insider threats.
A multi-touch interface circuit for a large-sized capacitive touch panel

This study presents a multi-touch sensing circuit for large-sized (more than 12 inches) capacitive touch panel. A new AC sensing technique is developed to enable the touch sensing in a large-sized capacitive touch panel. This novel designs of multi-touch sensing circuit lies in the operation principles through a 4×4 ITO film sensor array, a low-disturbance array circuit, a capacitance to voltage converter circuit and the proposed design procedure of chip parameters by circuit simulation. Furthermore, the sequence control for the array is generated by an FPGA module to accomplish the operation of the whole circuit. Some of objectives are to reduce environmental disturbance of the panel and to distinguish multi-touching locations from the panel. The corresponding output voltages of multi-touch sensing circuit are output in proportional to location touched by a human finger. Finally, the whole circuit is implemented by using TSMC 0.35µm 2P4M process. The circuit output voltages are used to distinguish touch locations by a proposed algorithm.
Private Transactions in Public Places: An Exploration of the Impact of the Computer Environment on Public Transactional Web Site Use

Organizations and governments continue to advance toward using electronic means to interact with their customers. However, the use of this medium presents an access-toservice issue for people across the digital divide who do not have private Internet access from their homes. Publicly-available computers connected to the Internet are an important and expanding source of Internet access for consumers. Still, we do not know if people are willing to engage in e-commerce transactions in such environments. We expand the Facilitating Conditions construct of Triandis’ (1980) modified theory of reasoned action to develop a model of transactional Web site use in public environments that incorporates the physical and virtual computer environments associated with publicly accessible computers, moderated by the individual’s need for privacy. The model was tested in public libraries, and the results indicate that the virtual and physical facilitating conditions of a public computer are determinants of e-commerce use in a public environment, and the user’s need for privacy moderates these relationships.
The Role of Pharmacogenomics in Bipolar Disorder: Moving Towards Precision Medicine

Bipolar disorder (BD) is a common and disabling psychiatric condition with a severe socioeconomic impact. BD is treated with mood stabilizers, among which lithium represents the first-line treatment. Lithium alone or in combination is effective in 60% of chronically treated patients, but response remains heterogenous and a large number of patients require a change in therapy after several weeks or months. Many studies have so far tried to identify molecular and genetic markers that could help us to predict response to mood stabilizers or the risk for adverse drug reactions. Pharmacogenetic studies in BD have been for the most part focused on lithium, but the complexity and variability of the response phenotype, together with the unclear mechanism of action of lithium, limited the power of these studies to identify robust biomarkers. Recent pharmacogenomic studies on lithium response have provided promising findings, suggesting that the integration of genome-wide investigations with deep phenotyping, in silico analyses and machine learning could lead us closer to personalized treatments for BD. Nevertheless, to date none of the genes suggested by pharmacogenetic studies on mood stabilizers have been included in any of the genetic tests approved by the Food and Drug Administration (FDA) for drug efficacy. On the other hand, genetic information has been included in drug labels to test for the safety of carbamazepine and valproate. In this review, we will outline available studies investigating the pharmacogenetics and pharmacogenomics of lithium and other mood stabilizers, with a specific focus on the limitations of these studies and potential strategies to overcome them. We will also discuss FDA-approved pharmacogenetic tests for treatments commonly used in the management of BD.
Pharmacotherapy for erectile dysfunction.

Erectile dysfunction (ED) is defined as the consistent inability to obtain or maintain an erection for satisfactory sexual relations. An estimated 20-30 million men suffer from some degree of sexual dysfunction. The past 20 years of research on erectile physiology have increased our understanding of the biochemical factors and intracellular mechanisms responsible for corpus cavernosal smooth muscle contraction and relaxation, and revealed that ED is predominantly a disease of vascular origin. Since the advent of sildenafil (Viagra), there has been a resurgence of interest in ED, and an increase in patients presenting with this disease. A thorough knowledge of the physiology of erection is essential for future pharmacological innovations in the field of male ED.
Tropical Underdevelopment

Most recent cross-country analyses of economic growth have neglected physical geography as a determinant of economic growth. This paper reviews the distinctive development challenges faced by economies situated in tropical climates. Using geographic information system (GIS) mapping, the paper presents evidence that production technology in the tropics has lagged behind temperate zone technology in the two critical areas of agriculture and health, and this in turn opened a substantial income gap between climate zones. The difficulty of mobilizing energy resources in tropical economies is emphasized as another significant contributor to the income gap. These factors have been amplified by geopolitical power imbalances and by the difficulty of applying temperate-zone technological advances in the tropical setting. The income gap has also been amplified because poor public health and weak agricultural technology in the tropics have combined to slow the demographic transition from high fertility and mortality rates to low fertility and mortality rates. The analysis suggests that economic development in tropical ecozones would benefit from a concerted international effort to develop health and agricultural technologies specific to the needs of the tropical economies.
Recognition memory: What are the roles of the perirhinal cortex and hippocampus?

The hallmark of medial temporal lobe amnesia is a loss of episodic memory such that patients fail to remember new events that are set in an autobiographical context (an episode). A further symptom is a loss of recognition memory. The relationship between these two features has recently become contentious. Here, we focus on the central issue in this dispute — the relative contributions of the hippocampus and the perirhinal cortex to recognition memory. A resolution is vital not only for uncovering the neural substrates of these key aspects of memory, but also for understanding the processes disrupted in medial temporal lobe amnesia and the validity of animal models of this syndrome.
Stress, stress hormones, and adult neurogenesis

The dentate gyrus of the hippocampus continues to produce new neurons throughout adulthood. Adult neurogenesis has been linked to hippocampal function, including learning and memory, anxiety regulation and feedback of the stress response. It is thus not surprising that stress, which affects hippocampal function, also alters the production and survival of new neurons. Glucocorticoids, along with other neurochemicals, have been implicated in stress-induced impairment of adult neurogenesis. Paradoxically, increases in corticosterone levels are sometimes associated with enhanced adult neurogenesis in the dentate gyrus. In these circumstances, the factors that buffer against the suppressive influence of elevated glucocorticoids remain unknown; their discovery may provide clues to reversing pathological processes arising from chronic exposure to aversive stress.
Application of Game-based Learning (GBL) on Chinese Language Learning in Elementary School

The purpose of this study is to explore the effect of applying game-based learning (GBL) in Chinese language learning for elementary school students in Taiwan. This study used the "Millionaire Language Game" was the research tool in the team competitions in Chinese language instruction. It then conducted survey on the students' attitudes and feedback regarding their usage experience, and interviews with teachers and students. The main conclusions of this study are: 1) the application of GBL on Chinese language instruction has a positive influence on the learning attitude of learners, 2) the influence of the application of GBL on Chinese language instruction on the learning attitude of learners is not restricted by gender, 3) the application of GBL on Chinese language instruction influences the learning attitude of learners transcending usage experiences, 4) for teachers, GBL is beneficial to Chinese language instruction.
Canting of the occlusal plane: Perceptions of dental professionals and laypersons

To determine if canting of the occlusal plane influences esthetic evaluation of the smile among orthodontists, dentists and laypersons.



A frontal photo of a smile with 0 occlusal plane canting in relation to the bipupillary plane was modified using Adobe Photoshop C3 (Adobe Systems Inc, San José, California) to generate two images with occlusal plane inclinations of 2 and 4 . The three images were evaluated esthetically by orthodontists (n=40) general dentists (n=40) and laypersons (n=40). Each image was awarded a score as follows: 1=esthetically acceptable; 2=moderately acceptable; 3=esthetically unacceptable. Evaluators also placed the three images in order in preference. Data were analyzed using the Kruskal-Wallis (p<0.05) and the Mann-Whitney tests, applying the Bonferroni Correction (p<0.016).



No significant differences (p> 0.05) were found between the three groups for 0 and 2 cants (median for orthodontists=1; general dentists=1; laypersons=1). Orthodontists (median score=3) made evaluations of the image with 4 occlusal plane that were significantly different from general dentists (median=2) and laypersons (median=2). All three groups put the 0 image in first place in order of esthetic acceptability, the 2 image in second place and the 4 image in third place. Orthodontists placed the 0 image in first place with significantly greater frequency (p<0.016) than laypersons.



Occlusal plane canting of 0 and 2 were evaluated as esthetically acceptable by the three groups. The 4 occlusal plane cant was evaluated more negatively by orthodontists than by general dentists and laypersons. All three groups placed the 0 image in first place of esthetic acceptability, 2 in second place and 4 in third. Orthodontists put the 0 image in first place with significantly greater frequency than laypersons.
Declarative Probabilistic Programming with Datalog

Probabilistic programming languages are used for developing statistical models. They typically consist of two components: a specification of a stochastic process (the prior) and a specification of observations that restrict the probability space to a conditional subspace (the posterior). Use cases of such formalisms include the development of algorithms in machine learning and artificial intelligence.
 In this article, we establish a probabilistic-programming extension of Datalog that, on the one hand, allows for defining a rich family of statistical models, and on the other hand retains the fundamental properties of declarativity. Our proposed extension provides mechanisms to include common numerical probability functions; in particular, conclusions of rules may contain values drawn from such functions. The semantics of a program is a probability distribution over the possible outcomes of the input database with respect to the program. Observations are naturally incorporated by means of integrity constraints over the extensional and intensional relations. The resulting semantics is robust under different chases and invariant to rewritings that preserve logical equivalence.
Stock Market Index Prediction via Hybrid Inertia Factor PSO and Constriction Coefficient PSO

Conventional statistical techniques for forecasting are constrained by the underlying seasonality, non-stationary and other factors. Increasingly over the past decade, Artificial intelligence (AI) methods including Artificial Neural network (ANN), Genetic Algorithm (GA), and Particle Swarm Optimization (PSO) etc. have been used successfully to perform predictions in financial markets and other areas. This study presents a hybrid inertia factor and constriction coefficient PSO-based methodology to deal with the Stock market index problem. We will demonstrate the superiority an applicability of the proposed approach by using Tehran Stock Exchange Index (TSEI) data and comparing the outcomes with other PSO methods such as: standard PSO, Inertia Factor PSO and Constriction Coefficient PSO. Experimental results clearly show that a hybrid PSO approach meaningfully outperforms all of the other PSO methods in terms of MAD, MSE, RMSE and MAPE Evaluation statistics also, the proposed approach can be considered as a suitable AI model for stock market index forecasting problem.