nils-herrmann/clean_scirepeval huggingface dataset:
Mechanisms of Neuropathic Pain

Neuropathic pain refers to pain that originates from pathology of the nervous system. Diabetes, infection (herpes zoster), nerve compression, nerve trauma, "channelopathies," and autoimmune disease are examples of diseases that may cause neuropathic pain. The development of both animal models and newer pharmacological strategies has led to an explosion of interest in the underlying mechanisms. Neuropathic pain reflects both peripheral and central sensitization mechanisms. Abnormal signals arise not only from injured axons but also from the intact nociceptors that share the innervation territory of the injured nerve. This review focuses on how both human studies and animal models are helping to elucidate the mechanisms underlying these surprisingly common disorders. The rapid gain in knowledge about abnormal signaling promises breakthroughs in the treatment of these often debilitating disorders.
Interviewing intoxicated witnesses: Memory performance in theory and practice.

Memory encoding and recall involving complex, effortful cognitive processes are impaired by alcohol primarily due to impairment of a select few, but crucial, cortical areas. This review shows how alcohol affects some, but not all, aspects of eyewitnesses' oral free recall performance. The principal results, so far, are that: a) free recall reports by intoxicated witnesses (at the investigated BAC-levels) may contain less, but as accurate, information as reports by sober witnesses; b) immediate reports given by intoxicated witnesses may yield more information compared to reports by sober witnesses given after a one week delay; c) an immediate interview may enhance both intoxicated and sober witnesses' ability to report information in a later interview; and d) reminiscence seems to occur over repeated interviews and the new information seems to be as accurate as the previously reported information. Based on this, recommendations are given for future research to enhance understanding of the multifaceted impact of alcohol on witnesses' oral free recall of violent crimes.
A Novel Computational Model Predicts Key Regulators of Chemokine Gradient Formation in Lymph Nodes and Site-Specific Roles for CCL19 and ACKR4

The chemokine receptor CCR7 drives leukocyte migration into and within lymph nodes (LNs). It is activated by chemokines CCL19 and CCL21, which are scavenged by the atypical chemokine receptor ACKR4. CCR7-dependent navigation is determined by the distribution of extracellular CCL19 and CCL21, which form concentration gradients at specific microanatomical locations. The mechanisms underpinning the establishment and regulation of these gradients are poorly understood. In this article, we have incorporated multiple biochemical processes describing the CCL19-CCL21-CCR7-ACKR4 network into our model of LN fluid flow to establish a computational model to investigate intranodal chemokine gradients. Importantly, the model recapitulates CCL21 gradients observed experimentally in B cell follicles and interfollicular regions, building confidence in its ability to accurately predict intranodal chemokine distribution. Parameter variation analysis indicates that the directionality of these gradients is robust, but their magnitude is sensitive to these key parameters: chemokine production, diffusivity, matrix binding site availability, and CCR7 abundance. The model indicates that lymph flow shapes intranodal CCL21 gradients, and that CCL19 is functionally important at the boundary between B cell follicles and the T cell area. It also predicts that ACKR4 in LNs prevents CCL19/CCL21 accumulation in efferent lymph, but does not control intranodal gradients. Instead, it attributes the disrupted interfollicular CCL21 gradients observed in Ackr4-deficient LNs to ACKR4 loss upstream. Our novel approach has therefore generated new testable hypotheses and alternative interpretations of experimental data. Moreover, it acts as a framework to investigate gradients at other locations, including those that cannot be visualized experimentally or involve other chemokines.
BenchNN: On the broad potential application scope of hardware neural network accelerators

Recent technology trends have indicated that, although device sizes will continue to scale as they have in the past, supply voltage scaling has ended. As a result, future chips can no longer rely on simply increasing the operational core count to improve performance without surpassing a reasonable power budget. Alternatively, allocating die area towards accelerators targeting an application, or an application domain, appears quite promising, and this paper makes an argument for a neural network hardware accelerator. After being hyped in the 1990s, then fading away for almost two decades, there is a surge of interest in hardware neural networks because of their energy and fault-tolerance properties. At the same time, the emergence of high-performance applications like Recognition, Mining, and Synthesis (RMS) suggest that the potential application scope of a hardware neural network accelerator would be broad. In this paper, we want to highlight that a hardware neural network accelerator is indeed compatible with many of the emerging high-performance workloads, currently accepted as benchmarks for high-performance micro-architectures. For that purpose, we develop and evaluate software neural network implementations of 5 (out of 12) RMS applications from the PARSEC Benchmark Suite. Our results show that neural network implementations can achieve competitive results, with respect to application-specific quality metrics, on these 5 RMS applications.
A synchronous DRAM controller for an H.264/AVC encoder

In order to use a synchronous dynamic RAM (SDRAM) as the off-chip memory of an H.264/AVC encoder, this paper proposes an efficient SDRAM memory controller with an asynchronous bridge. With the proposed architecture, the SDRAM bandwidth is increased by making the operation frequency of an external SDRAM higher than that of the hardware accelerators of an H.264/AVC encoder. Experimental results show that the encoding speed is increased by 30.5% when the SDRAM clock frequency is increased from 100 MHz to 200 MHz while the H.264/AVC hardware accelerators operate at 100 MHz.
Midface rejuvenation: a critical evaluation of a 7-year experience.

Although "traditional" face-lifting techniques can achieve excellent improvement along the jawline and neck, they often have little impact on the midface area. Thus, many different types of procedures have been developed to provide rejuvenation in this region, usually contemplating various dissection planes, incisions, and suspension vectors.



A 7-year observational study of 350 patients undergoing midface lift was analyzed. The authors suspended the midface flap, anchoring to the deep temporal aponeurosis with a suspender-like suture (superolateral vector), or directly to the lower orbital rim with a belt-like suture (superomedial vector). Subjective and objective methods were used to evaluate the results. The subjective methods included a questionnaire completed by the patients. The objective method involved the evaluation of preoperative and postoperative photographs by a three-member jury instructed to compare the "critical" anatomical areas of the midface region: malar eminence, nasojugal groove, nasolabial fold, and jowls in the lower portion of the cheeks. The average follow-up period was 24 months.



High satisfaction was noticeable from the perceptions of both the jury and the patients. Objective evaluation evidenced that midface lift with temporal anchoring was more efficient for the treatment of malar eminence, whereas midface lift with transosseous periorbital anchoring was more efficient for the treatment of nasojugal groove.



The most satisfying aspect of the adopted techniques is a dramatic facial rejuvenation and preservation of the patient's original youthful identity. Furthermore, choosing the most suitable technique respects the patient's needs and enables correction of the specific defects.



Therapeutic, IV.
Analysis of Noise Signal Cancellation using Adaptive Algorithms

Noise is an indispensable part in signal processing that we encounter every day. The study of reducing noise arises from the need to achieve stronger signal to noise ratios. It is any unwanted disturbance that hampers the desired response while keeping the source sound. The different sources may include speech, music played through a device such as a mobile, IPod, computer, or no sound at all. Active noise cancellation involves creating a supplementary signal that DE constructively interferes with the output ambient noise. The cancellation of noise can be efficiently accomplished by using adaptive algorithms. An adaptive filter is one that self-adjusts the coefficients of transfer function according to an algorithm driven by an error signal. The adaptive filter uses feedback in the form of an error signal to define its transfer function to match changing parameters. The adaptive filtering techniques can be used for a wide range of applications, including echo cancellation, adaptive channel equalization, adaptive line enhancer, and adaptive beam forming. In last few years, a lot of algorithms have been developed for eradicating the distortion from the signals. This paper presents analysis of two algorithms namely, Least Mean Square (LMS), Normalized Least Mean Square (NLMS) and gives comparative study on various governing factors such as stability, computational complexity, filter order, robustness and rate of convergence. It further represents the effect of error with alteration in amplitude of noise signal fixating reference signal and desired signal. The algorithms are developed in MATLAB Keywords– Anti noise, Adaptive filter, LMS, NLMS, Rate of convergence, Noise cancellation, Filter
A Lightweight RFID Security Protocol Based on Elliptic Curve Crytography

Radio Frequency Identification (RFID) is a promising new technology that is widely deployed for object tracking and monitoring, ticketing, supply-chain management, contactless payment, etc. However, RFID related security problems attract more and more attentions. This paper has studied a novel elliptic curve cryptography (ECC) based RFID security protocol and it shows some great features. Firstly, the high strength of ECC encryption provides convincing security for communication and tag memory data access. Secondly, the public-key cryptography used in the protocol reduces the key storage requirement and the backend system just store the private key. Thirdly, the new protocol just depends on simple calculations, such as XOR, bitwise AND, and so forth, which reduce the tag computation. Finally, the computational performance, security features, and the formal proof based on BAN logic are also discussed in detail in the paper.
Scene Text Detection in Video by Learning Locally and Globally

There are a variety of grand challenges for text extraction in scene videos by robots and users, e.g., heterogeneous background, varied text, nonuniform illumination, arbitrary motion and poor contrast. Most previous video text detection methods are investigated with local information, i.e., within individual frames, with limited performance. In this paper, we propose a unified tracking based text detection system by learning locally and globally, which uniformly integrates detection, tracking, recognition and their interactions. In this system, scene text is first detected locally in individual frames. Second, an optimal tracking trajectory is learned and linked globally with all detection, recognition and prediction information by dynamic programming. With the tracking trajectory, final detection and tracking results are simultaneously and immediately obtained. Moreover, our proposed techniques are extensively evaluated on several public scene video text databases, and are much better than the state-of-the-art methods.
Radar plots: a useful way for presenting multivariate health care data.

Health care researchers have not taken full advantage of the potential to effectively convey meaning in their multivariate data through graphical presentation. The aim of this paper is to translate knowledge from the fields of analytical chemistry, toxicology, and marketing research to the field of medicine by introducing the radar plot, a useful graphical display method for multivariate data.



Descriptive study based on literature review.



The radar plotting technique is described, and examples are used to illustrate not only its programming language, but also the differences in tabular and bar chart approaches compared to radar-graphed data displays.



Radar graphing, a form of radial graphing, could have great utility in the presentation of health-related research, especially in situations in which there are large numbers of independent variables, possibly with different measurement scales. This technique has particular relevance for researchers who wish to illustrate the degree of multiple-group similarity/consensus, or group differences on multiple variables in a single graphical display.
AES algorithm for Smartphone to vehicle communication

Vehicle theft has become a pervasive problem in metropolitan cities. The aim of our work is to reduce the vehicle and fuel theft with an alert given by commonly used smart phones. The modern vehicles are interconnected with computer systems so that the information can be obtained from vehicular sources and Internet services. This provides space for tracking the vehicle through smart phones. In our work, an Advanced Encryption Standard (AES) algorithm is implemented which integrates a smart phone with classical embedded systems to avoid vehicle theft.
Prediction, Expectation, and Surprise: Methods, Designs, and Study of a Deployed Traffic Forecasting Service

We present research on developing models that forecast traffic flow and congestion in the Greater Seattle area. The research has led to the deployment of a service named JamBayes, that is being actively used by over 2,500 users via smartphones and desktop versions of the system. We review the modeling effort and describe experiments probing the predictive accuracy of the models. Finally, we present research on building models that can identify current and future surprises, via efforts on modeling and forecasting unexpected situations.
A Novel Design of Broadband Terahertz Metamaterial Absorber Based on Nested Circle Rings

A terahertz metamaterial absorber (MA) with properties of broadband width, polarization-insensitive, wide angle incidence is presented. Different from the previous methods to broaden the absorption width, this letter proposes a novel combinatorial way which units a nested structure with multiple metal-dielectric layers. We numerically investigate the proposed MA, and the simulation results show that the absorber achieves a broadband absorption over a frequency range of 0.896 THz with the absorptivity greater than 90%. Moreover, the full-width at half maximum of the absorber is up to 1.224 THz which is 61.2% with respect to the central frequency. The mechanism for the broadband absorption originates from the overlapping of longitudinal coupling between layers and coupling of the nested structure. Importantly, the nested structure makes a great contribution to broaden the absorption width. Thus, constructing a nested structure in a multi-layer absorber may be considered as an effective way to design broadband MAs.
Non-Invasive Blood Glucose Measurement

Diabetes has emerged as a major healthcare problem in India. Today Approximately 8.3 % of global adult population is suffering from Diabetes. India is one of the most diabetic populated country in the world. Today the technologies available in the market are invasive methods. Since invasive methods cause pain, time consuming, expensive and there is a potential risk of infectious diseases like Hepatitis & HIV spreading and continuous monitoring is therefore not possible. Now a days there is a tremendous increase in the use of electrical and electronic equipment in the medical field for clinical and research purposes. Thus biomedical equipment’s have a greater role in solving medical problems and enhance quality of life. Hence there is a great demand to have a reliable, instantaneous, cost effective and comfortable measurement system for the detection of blood glucose concentration. Non-invasive blood glucose measurement device is one such which can be used for continuous monitoring of glucose levels in human body.
Experimental Analysis of BRDF Models

The Bidirectional Reflectance Distribution Function (BRDF) describes the appearance of a material by its interaction with light at a surface point. A variety of analytical models have been proposed to represent BRDFs. However, analysis of these models has been scarce due to the lack of high-resolution measured data. In this work we evaluate several well-known analytical models in terms of their ability to fit measured BRDFs. We use an existing high-resolution data set of a hundred isotropic materials and compute the best approximation for each analytical model. Furthermore, we have built a new setup for efficient acquisition of anisotropic BRDFs, which allows us to acquire anisotropic materials at high resolution. We have measured four samples of anisotropic materials (brushed aluminum, velvet, and two satins). Based on the numerical errors, function plots, and rendered images we provide insights into the performance of the various models. We conclude that for most isotropic materials physically-based analytic reflectance models can represent their appearance quite well. We illustrate the important difference between the two common ways of defining the specular lobe: around the mirror direction and with respect to the half-vector. Our evaluation shows that the latter gives a more accurate shape for the reflection lobe. Our analysis of anisotropic materials indicates current parametric reflectance models cannot represent their appearances faithfully in many cases. We show that using a sampled microfacet distribution computed from measurements improves the fit and qualitatively reproduces the measurements.
Employee Turnover : A Novel Prediction Solution with Effective Feature Selection

This study proposed to address a new method that could select subsets more efficiently. In addition, the reasons why employers voluntarily turnover were also investigated in order to increase the classification accuracy and to help managers to prevent employers’ turnover. The mixed subset selection used in this study combined Taguchi method and Nearest Neighbor Classification Rules to select subset and analyze the factors to find the best predictor of employer turnover. All the samples used in this study were from industry A, in which the employers left their job during 1st of February, 2001 to 31st of December, 2007, compared with those incumbents. The results showed that through the mixed subset selection method, total 18 factors were found that are important to the employers. In addition, the accuracy of correct selection was 87.85% which was higher than before using this subset selection (80.93%). The new subset selection method addressed in this study does not only provide industries to understand the reasons of employers’ turnover, but also could be a long-term classification prediction for industries.  Voluntary Turnover; Subset Selection; Taguchi Methods; Nearest Neighbor Classification Rules; Training pattern
A positive role for patched-smoothened signaling in promoting cell proliferation during normal head development in Drosophila.

The transmembrane receptor Patched regulates several developmental processes in both invertebrates and vertebrates. In vertebrates, Patched also acts as a tumor suppressor. The Patched pathway normally operates by negatively regulating Smoothened, a G-protein-coupled receptor; binding of Hedgehog ligand to Patched relieves this negative interaction and allows signaling by Smoothened. We show that Ptc regulates Drosophila head development by promoting cell proliferation in the eye-antennal disc. During head morphogenesis, Patched positively interacts with Smoothened, which leads to the activation of Activin type I receptor Baboon and stimulation of cell proliferation in the eye-antennal disc. Thus, loss of Ptc or Smoothened activity affects cell proliferation in the eye-antennal disc and results in adult head capsule defects. Similarly, reducing the dose of smoothened in a patched background enhances the head defects. Consistent with these results, gain-of-function Hedgehog interferes with the activation of Baboon by Patched and Smoothened, leading to a similar head capsule defect. Expression of an activated form of Baboon in the patched domain in a patched mutant background completely rescues the head defects. These results provide insight into head morphogenesis, a process we know very little about, and reveal an unexpected non-canonical positive signaling pathway in which Patched and Smoothened function to promote cell proliferation as opposed to repressing it.
Suspended Alexandrium Spp . Hypnozygote Cysts in the Gulf of Maine

The life cycle of dinoflagellates of the genus Alexandrium includes sexual reproduction followed by the formation of a dormant hypnozygote cyst, which serves as a resting stage. Negatively buoyant cysts purportedly fall to the benthos where they undergo a mandatory period of quiescence. Previous reports of cysts in the surficial sediments of the Gulf of Maine, where Alexandrium blooms are well documented, show a broad distribution of cysts, with highest concentrations generally in sediments below 100m depth. We report here an exploration of cysts suspended in the water column, where they would be better positioned to inoculate springtime Alexandrium populations. During cruises in February, April, and June of 2000, water samples were collected at depths just off the bottom (within 5m), at the top of the bottom nepheloid layer, and near the surface (1m) and examined for cyst concentrations. Suspended cysts were found throughout the Gulf of Maine and westernmost Bay of Fundy. Planktonic cyst densities were generally greater in near-bottom and top of the bottom nepheloid layer samples than in near-surface water samples; densities were of the order of 10 cystsm 3 in surface waters, and 10–10 cystsm 3 at near-bottom depths. Temporally, they were most abundant in February and least abundant in April. Reports by earlier workers of cysts in the underlying sediments were on the order of 10 cysts cm . We present calculations that demonstrate the likelihood of cyst resuspension from bottom sediments forced by swell and tidal currents, and propose that such resuspended cysts are important in inoculating the seasonal bloom. We estimate that suspended cysts may contribute significantly to the annual vegetative cell population in the Gulf of Maine.
Design of permanent magnets to chaoize doubly salient permanent magnet motors for electric compaction

This article proposes and implements a class of chaotic motors for electric compaction. The key is to develop a design approach for the permanent magnets PMs of doubly salient PM DSPM motors in such a way that chaotic motion can be naturally produced. The bifurcation diagram is employed to derive the threshold of chaoization in terms of PM flux, while the corresponding phase-plane trajectories are used to characterize the chaotic motion. A practical three-phase 12/8-pole DSPM motor is used for exemplification. The proposed chaotic motor is critically assessed for application to a vibratory soil compactor, which is proven to offer better compaction performance than its counterparts. Both computer simulation and experimental results are given to illustrate the proposed chaotic motor.