nils-herrmann/clean_scirepeval huggingface dataset:
Pramipexole. A review of its use in the management of early and advanced Parkinson's disease.

Pramipexole is an orally active non-ergoline dopamine agonist with selective activity at dopamine receptors belonging to the D2 receptor subfamily (D2, D3, D4 receptor subtypes) and with preferential affinity for the D3 receptor subtype. It is approved as monotherapy in early Parkinson's disease and as adjunctive therapy to levodopa in patients with advanced disease experiencing motor effects because of diminished response to levodopa. The potential neuroprotective effects of pramipexole have been shown in animal and in vitro studies. Data from relatively long term (10- or 31-week) studies suggest that pramipexole monotherapy (0.375 to 6.0 mg/day) can improve activities of daily living and motor symptoms in patients with early Parkinson's disease. Pramipexole (0.375 to 4.5 mg/day for 31 or 36 weeks), as an adjunct to levodopa in advanced disease, improved activities of daily living and motor symptoms, reduced the duration and severity of 'off' periods and allowed a reduction in levodopa dosage. Mentation, behaviour and mood [Unified Parkinson's Disease Rating Scale (UPDRS) part I], and timed walking test were not significantly improved. The extent of disability improved according to the UPDRS parts II and III but, when assessed by secondary efficacy parameters, it is unclear whether disability or the severity of disease improved. No significant differences were observed in patients randomised to pramipexole or bromocriptine according to a secondary hypothesis in a prospective study in which both drugs were better than placebo. Some quality-of-life measures improved with active treatment relative to placebo. Further studies comparing pramipexole with other dopamine agonists and levodopa in patients with early and advanced Parkinson's disease would be useful. In pramipexole recipients with early disease, the most commonly experienced adverse events were nausea, dizziness, somnolence, insomnia, constipation, asthenia and hallucinations. The most commonly reported adverse events in pramipexole recipients with advanced disease were orthostatic hypotension, dyskinesias, extrapyramidal syndrome (defined as a worsening of the Parkinson's disease), dizziness, hallucinations, accidental injury, dream abnormalities, confusion, constipation, asthenia, somnolence, dystonia, gait abnormality, hypertonia, dry mouth, amnesia and urinary frequency. The incidence of some adverse events did not greatly differ between pramipexole and placebo recipients.



Pramipexole is effective as adjunctive therapy to levodopa in patients with advanced Parkinson's disease. However, the potential beneficial effects of pramipexole on disease progression need to be confirmed in clinical studies. The efficacy of pramipexole monotherapy in patients with early disease has also been demonstrated, although the use of dopamine agonists in early Parkinson's disease remains controversial.
The Emergence of Canalization and Evolvability in an Open-Ended, Interactive Evolutionary System

Many believe that an essential component for the discovery of the tremendous diversity in natural organisms was the evolution of evolvability, whereby evolution speeds up its ability to innovate by generating a more adaptive pool of offspring. One hypothesized mechanism for evolvability is developmental canalization, wherein certain dimensions of variation become more likely to be traversed and others are prevented from being explored (e.g., offspring tend to have similar-size legs, and mutations affect the length of both legs, not each leg individually). While ubiquitous in nature, canalization is rarely reported in computational simulations of evolution, which deprives us of in silico examples of canalization to study and raises the question of which conditions give rise to this form of evolvability. Answering this question would shed light on why such evolvability emerged naturally, and it could accelerate engineering efforts to harness evolution to solve important engineering challenges. In this article, we reveal a unique system in which canalization did emerge in computational evolution. We document that genomes entrench certain dimensions of variation that were frequently explored during their evolutionary history. The genetic representation of these organisms also evolved to be more modular and hierarchical than expected by chance, and we show that these organizational properties correlate with increased fitness. Interestingly, the type of computational evolutionary experiment that produced this evolvability was very different from traditional digital evolution in that there was no objective, suggesting that open-ended, divergent evolutionary processes may be necessary for the evolution of evolvability.
Straylight in the human eye: testing objectivity and optical character of the psychophysical measurement.

The point spread function or PSF of the human eye encompasses hugely different domains: a small-angle, high-intensity domain, called the 'PSF core', and a large-angle, low-intensity domain, usually referred to as 'straylight'. The first domain can be assessed by available double-pass or other optical techniques. For the second domain psychophysical techniques have been developed, in particular the Compensation Comparison or CC technique, recently made available for clinical application in the C-Quant instrument. We address the question of whether the psychophysical technique gives measures of straylight that are compatible with those made by optical methods. With a small adaptation the CC method can be used to assess straylight from physical light scattering samples, instead of straylight in the eye, using the same psychophysics, but without interference from the ocular straylight. The light scattered by each of seven light-scattering samples, encompassing the range of straylight values observed in human eyes, was measured by two optical methods and by the psychophysical technique. The results showed that the optical and psychophysical measurements for the seven samples were almost identical.
Omni-directional steer-by-wire interface for four wheel independent steering vehicle

In this paper, an omni-directional steer-by-wire interface for four wheel independent steering vehicle is presented. The proposed steering interface is an extension of a traditional steering interface that provides three steering inputs. By combination of which, driver can control the vehicle in traditional way or omni-directionally without any mode switching operation. The reservation of the conventional steering behavior makes driver easy to adapt the novel steering interface. The force feedback controller is designed to synchronize the extended steering interface and the orientations of wheels so as to improve vehicle handling. Hardware-in-the-loop simulations are conducted to verify the hardware prototype and examine the proposed algorithms.
Generative adversarial networks as integrated forward and inverse model for motor control

Internal models are believed to be crucial components in human motor control. It has been suggested that the central nervous system (CNS) uses forward and inverse models as internal representations of the motor systems. However, it is still unclear how the CNS implements the high-dimensional control of our movements. In this project, generative adversarial networks (GAN) are studied as a generative model of movement data. It is shown that, for a relatively small number of effectors, it is possible to train a GAN which produces new movement samples that are plausible given a simulator environment. It is believed that these models can be extended to generate high-dimensional movement data. Furthermore, this project investigates the possibility to use a trained GAN as an integrated forward and inverse model for motor control.
Malaria in pregnancy in the Asia-Pacific region.

Most pregnant women at risk of for infection with Plasmodium vivax live in the Asia-Pacific region. However, malaria in pregnancy is not recognised as a priority by many governments, policy makers, and donors in this region. Robust data for the true burden of malaria throughout pregnancy are scarce. Nevertheless, when women have little immunity, each infection is potentially fatal to the mother, fetus, or both. WHO recommendations for the control of malaria in pregnancy are largely based on the situation in Africa, but strategies in the Asia-Pacific region are complicated by heterogeneous transmission settings, coexistence of multidrug-resistant Plasmodium falciparum and Plasmodium vivax parasites, and different vectors. Most knowledge of the epidemiology, effect, treatment, and prevention of malaria in pregnancy in the Asia-Pacific region comes from India, Papua New Guinea, and Thailand. Improved estimates of the morbidity and mortality of malaria in pregnancy are urgently needed. When malaria in pregnancy cannot be prevented, accurate diagnosis and prompt treatment are needed to avert dangerous symptomatic disease and to reduce effects on fetuses.
Extended Abstract: Mimicry Resilient Program Behavior Modeling with LSTM based Branch Models

In the software design, protecting a computer system from a plethora of software attacks or malware in the wild has been increasingly important. One branch of research to detect the existence of attacks or malware, there has been much work focused on modeling the runtime behavior of a program. Stemming from the seminal work of Forrest et al., one of the main tools to model program behavior is system call sequences. Unfortunately, however, since mimicry attacks were proposed, program behavior models based solely on system call sequences could no longer ensure the security of systems and require additional information that comes with its own drawbacks. In this paper, we report our preliminary findings in our research to build a mimicry resilient program behavior model that has lesser drawbacks. We employ branch sequences to harden our program behavior model against mimicry attacks while employing hardware features for efficient extraction of such branch information during program runtime. In order to handle the large scale of branch sequences, we also employ LSTM, the de facto standard in deep learning based sequence modeling and report our preliminary experiments on its interaction with program branch sequences.
A miniature home-based sleep monitoring device

Dynamics of sleep, vitally important but commonly overlooked, have been associated with various aspects of physical and mental health. Sleep deprivation not only affects daily activities, causing fatigue, impaired memory, and cognitive dysfunction, but also increases the risk of heart disease, diabetes, and obesity. Sleep disruptions generally present as sleep disorders; apnea, insomnia, snoring, sleep walking, and restless legs syndrome are common examples. Diagnosis as well as treatment require one or more sleep studies: polysomnography (PSG), a multiple sleep latency test (MSLT), a maintenance of wakefulness test (MWT), or actigraphy. Considered the gold standard, PSG is commonly administered at a specialized sleep laboratory, which usually has a long waiting list due to an increasingly overwhelming demand. PSG is expensive and time consuming, requiring an overnight stay. To make it more practically accessible, an augmented home-based PSG would be of great benefit. We propose a sleep monitoring device to be used at the comfort of home. Setting it apart from commercially available products, this is a miniature unit. It is affordable, highly customizable, and user-friendly. Patients can view their results in real-time on a graphical display that is easy to read and understand. Physicians can utilize an interactive user interface for ease of data access during medical evaluation. Furthermore, the device features an integrated web application, enabling suitable and attractive data visualization.
An 84.7% Efficiency 100-MHz Package Bondwire-Based Fully Integrated Buck Converter With Precise DCM Operation and Enhanced Light-Load Efficiency

A 100-MHz PWM fully integrated buck converter utilizing standard package bondwire as power inductor with enhanced light-load efficiency which occupies 2.25 mm2 in 0.13-μm CMOS is presented. Standard package bondwire instead of on-chip spiral metal or special spiral bondwire is implemented as power inductor to minimize the cost and the conduction loss of an integrated inductor. The accuracy requirement of bondwire inductance is relaxed by an extra discontinuous-conduction-mode (DCM) calibration loop, which solves the precise DCM operation issue of fully integrated converters and eliminates the reverse current-related loss, thus enabling the use of standard package bondwire inductor with various packaging techniques. Optimizations of the power transistors, the input decoupling capacitor (CI), and the controller are also presented to achieve an efficient and robust high-frequency design. With all three major power losses, conduction loss, switching loss, and reverse current related loss, optimized or eliminated, the efficiency is significantly improved. An efficiency of 74.8% is maintained at 10 mA, and a peak efficiency of 84.7% is measured at nominal operating conditions with a voltage conversion of 1.2 to 0.9 V. Converters with various bondwire inductances from 3 to 8.5 nH are measured to verify the reliability and compatibility of different packaging techniques.
Modeling latching fluidic circuits to determine clocking limits for a refreshable braille display

Fluidic circuits made up of tiny chambers, conduits, and membranes can be fabricated in soft substrates to realize pressure-based sequential logic functions. Additional chambers in the same substrate covered with thin membranes can function as bubble-like tactile features. Sequential addressing of bubbles with fluidic logic enables just two external electronic valves to control of any number of tactile features by "clocking in" pressure states one at a time. But every additional actuator added to a shift register requires an additional clock pulse to address, so that the display refresh rate scales inversely with the number of actuators in an array. In this paper, we build a model of a fluidic logic circuit that can be used for sequential addressing of bubble actuators. The model takes the form of a hybrid automaton combining the discrete dynamics of valve switching and the continuous dynamics of compressible fluid flow through fluidic resistors (conduits) and capacitors (chambers). When parameters are set according to the results of system identification experiments on a physical prototype, pressure trajectories and propagation delays predicted by simulation of the hybrid automaton compare favorably to experiment. The propagation delay in turn determines the maximum clock rate and associated refresh rate for a refreshable braille display intended for rendering a full page of braille text or tactile graphics.
Focus : Metabolism Brain metabolism in health , aging , and neurodegeneration

Brain cells normally respond adaptively to bioenergetic challenges resulting from ongoing activity in neuronal circuits, and from environmental energetic stressors such as food deprivation and physical exertion. At the cellular level, such adaptive responses include the “strengthening” of existing synapses, the formation of new synapses, and the production of new neurons from stem cells. At the molecular level, bioenergetic challenges result in the activation of transcription factors that induce the expression of proteins that bolster the resistance of neurons to the kinds of metabolic, oxidative, excitotoxic, and proteotoxic stresses involved in the pathogenesis of brain disorders including stroke, and Alzheimer’s and Parkinson’s diseases. Emerging findings suggest that lifestyles that include intermittent bioenergetic challenges, most notably exercise and dietary energy restriction, can increase the likelihood that the brain will function optimally and in the absence of disease throughout life. Here, we provide an overview of cellular and molecular mechanisms that regulate brain energy metabolism, how such mechanisms are altered during aging and in neurodegenerative disorders, and the potential applications to brain health and disease of interventions that engage pathways involved in neuronal adaptations to metabolic stress.
The incommensurability of nursing as a practice and the customer service model: an evolutionary threat to the discipline.

Corporate and commercial values are inducing some healthcare organizations to prescribe a customer service model that reframes the provision of nursing care. In this paper it is argued that such a model is incommensurable with nursing conceived as a moral practice and ultimately places nurses at risk. Based upon understanding from ongoing research on compassion fatigue, it is proposed that compassion fatigue as currently experienced by nurses may not arise predominantly from too great a demand for compassion, but rather from barriers to enacting compassionate care. These barriers are often systemic. The paradigm shift in which healthcare environments are viewed as marketplaces rather than moral communities has the potential to radically affect the evolution of nursing as a discipline.
Improved performance of microstrip antenna arrays through electromagnetic coupling at Ka-band

A comparison between corporate fed microstrip antenna array (MSAA) and an electromagnetically coupled microstrip antenna array (EMCP-MSAA) at Ka-band is presented. A low loss feed network is proposed based on the analysis of different line widths used in the feed network. Gain improvement of 25% (1.5 dB) is achieved using the proposed feed network in 2×2 EMCP-MSAA. A 8×8 MSAA has been designed and fabricated at Ka-band. The measured bandwidth is 4.3% with gain of 24dB. Bandwidth enhancement is done by designing and fabricating EMCP-MSAA to give bandwidth of 17% for 8×8 array.
Feature-Based Facial Expression Recognition: Sensitivity Analysis and Experiments with A Multilayer Perceptron

In this paper, we report our experiments on feature-based facial expression recognition within an architecture based on a two-layer perceptron. We investigate the use of two types of features extracted from face images: the geometric positions of a set of fiducial points on a face, and a set of multi-scale and multi-orientation Gabor wavelet coefficients at these points. They can be used either independently or jointly. The recognition performance with different types of features has been compared, which shows that Gabor wavelet coefficients are much more powerful than geometric positions. Furthermore, since the first layer of the perceptron actually performs a nonlinear reduction of the dimensionality of the feature space, we have also studied the desired number of hidden units, i.e., the appropriate dimension to represent a facial expression in order to achieve a good recognition rate. It turns out that five to seven hidden units are probably enough to represent the space of feature expressions. Then, we have investigated the importance of each individual fiducial point to facial expression recognition. Sensitivity analysis reveals that points on cheeks and on forehead carry little useful information. After discarding them, not only the computational efficiency increases, but also the generalization performance slightly improves. Finally, we have studied the significance of image scales. Experiments show that facial expression recognition is mainly a low frequency process, and a spatial resolution of 64 pixels 64 pixels is probably enough.
This technology allows stacked silicon chips to interconnect through direct contact to provide high-speed signal processing and improved photo detection for image sensing.

| Recently, the development of three-dimensional large-scale integration (3D-LSI) has been accelerated. Its stage has changed from the research level or limited production level to the investigation level with a view to mass production [1]–[10]. The 3D-LSI using through-silicon via (TSV) has the simplest structure and is expected to realize a high-performance, highfunctionality, and high-density LSI cube. This paper describes the current and future 3D-LSI technologies with TSV.
Early Oral Versus “Traditional” Postoperative Feeding in Gynecologic Oncology Patients Undergoing Intestinal Resection: a Randomized Controlled Trial

A randomized controlled trial was performed to assess the outcome of early oral postoperative feeding (EOF) compared with traditional oral feeding (TOF) in gynecologic oncology patients undergoing laparotomy with associated intestinal resection. Patients aged 18–75 years, undergoing elective laparotomy, and with preoperative diagnosis of gynecologic malignancy, were eligible. Exclusion criteria included infectious conditions, intestinal obstruction, severe malnutrition, American Society of Anesthesiologists (ASA) score ≥4, and postoperative stay in the intensive care unit lasting >24 h. Patients allocated to EOF received liquid diet in the first postoperative day and then regular diet. Patients received traditional feeding scheme until resolution of postoperative ileus to start liquid diet. The primary end-point of the trial was length of hospital stay. Between January 1st, 2007 and March 15th, 2008, 40 patients were randomized to receive either EOF or TOF. Hospital stay in patients who received EOF (n = 18) was 6.9 days versus 9.1 days in the TOF group (n = 22) (P = 0.022). Requirements for analgesic and antiemetic drugs, intensity of pain, intestinal function recovery, mean levels of postoperative satisfaction, postoperative complications, and quality-of-life scores did not differ between the two groups. Early resumption of oral intake is feasible and safe in gynecologic oncology patients undergoing intestinal resection as part of a planned surgical procedure. Moreover, significant reduction in length of hospital stay was demonstrated.
Whale Optimization Algorithm and Moth-Flame Optimization for multilevel thresholding image segmentation

Determining the optimal thresholding for image segmentation has got more attention in recent years since it has many applications. There are several methods used to find the optimal thresholding values such as Otsu and Kapur based methods. These methods are suitable for bi-level thresholding case and they can be easily extended to the multilevel case, however, the process of determining the optimal thresholds in the case of multilevel thresholding is time-consuming. To avoid this problem, this paper examines the ability of two nature inspired algorithms namely: Whale Optimization Algorithm (WOA) and Moth-Flame Optimization (MFO) to determine the optimal multilevel thresholding for image segmentation. The MFO algorithm is inspired from the natural behavior of moths which have a special navigation style at night since they fly using the moonlight, whereas, the WOA algorithm emulates the natural cooperative behaviors of whales. The candidate solutions in the adapted algorithms were created using the image histogram, and then they were updated based on the characteristics of each algorithm. The solutions are assessed using the Otsu’s fitness function during the optimization operation. The performance of the proposed algorithms has been evaluated using several of benchmark images and has been compared with five different swarm algorithms. The results have been analyzed based on the best fitness values, PSNR, and SSIM measures, as well as time complexity and the ANOVA test. The experimental results showed that the proposed methods outperformed the other swarm algorithms; in addition, the MFO showed better results than WOA, as well as provided a good balance between exploration and exploitation in all images at small and high threshold numbers.