nils-herrmann/clean_scirepeval huggingface dataset:
[Rhinoplasty: morphodynamic anatomy of rhinoplasty. Interest of conservative rhinoplasty].

To highlight the morphodynamic anatomical mechanisms that influence the results of rhinoplasty. To present the technical modalities of nasal dorsum preservation rhinoplasties. To determine the optimized respective surgical indications of the two main techniques of rhinoplasty: interruption rhinoplasty versus conservative rhinoplasty.



Based on anatomical dissections and initial morphodynamic studies carried out on 100 anatomical specimens, a prospective study of a continuous series of 400 patients operated of primary reduction rhinoplasty or septo-rhinoplasty by one of authors (YS) has been undertaken over a period of ten years (1995-2005) in order to optimize the surgical management of the nasal hump. The studied parameters were: (1) surgical safety, (2) quality of early and late aesthetic result, (3) quality of the functional result, (4) ease of the technical realization of a possible secondary rhinoplasty. The other selected criteria were function of the different nasal hump morphotypes and the expressed wishes of the patients.



The anatomical and morphodynamic studies made it possible to better understand the role of the "M" double-arch shape of the nose and the role of the cartilaginous buttresses not only as a function but also the anatomy and the aesthetics of the nose. It is necessary to preserve or repair the arche structures of the septo-triangular and alo-columellar sub-units. The conservative technique, whose results appear much more natural aesthetically, functionally satisfactory and durable over the long term, must be favoured in particular in man and in cases presenting a risk of collapse of the nasal valve.



The rhinoplastician must be able to propose, according to the patient's wishes and in view of the results of the morphological analysis, the most adapted procedure according to his own surgical training but by supporting conservation of the osteo-cartilaginous vault whenever possible.
Thompson Sampling for Complex Online Problems

We consider stochastic multi-armed bandit problems with complex actions over a set of basic arms, where the decision maker plays a complex action rather than a basic arm in each round. The reward of the complex action is some function of the basic arms’ rewards, and the feedback observed may not necessarily be the reward per-arm. For instance, when the complex actions are subsets of the arms, we may only observe the maximum reward over the chosen subset. Thus, feedback across complex actions may be coupled due to the nature of the reward function. We prove a frequentist regret bound for Thompson sampling in a very general setting involving parameter, action and observation spaces and a likelihood function over them. The bound holds for discretely-supported priors over the parameter space without additional structural properties such as closed-form posteriors, conjugate prior structure or independence across arms. The regret bound scales logarithmically with time but, more importantly, with an improved constant that non-trivially captures the coupling across complex actions due to the structure of the rewards. As applications, we derive improved regret bounds for classes of complex bandit problems involving selecting subsets of arms, including the first nontrivial regret bounds for nonlinear MAX reward feedback from subsets.
Synthetic Aperture Radar (SAR) Interferometry for Assessing Wenchuan Earthquake (2008) Deforestation in the Sichuan Giant Panda Site

Synthetic aperture radar (SAR) has been an unparalleled tool in cloudy and rainy regions as it allows observations throughout the year because of its all-weather, all-day operation capability. In this paper, the influence of Wenchuan Earthquake on the Sichuan Giant Panda habitats was evaluated for the first time using SAR interferometry and combining data from C-band Envisat ASAR and L-band ALOS PALSAR data. Coherence analysis based on the zero-point shifting indicated that the deforestation process was significant, particularly in habitats along the Min River approaching the epicenter after the natural disaster, and as interpreted by the vegetation deterioration from landslides, avalanches and debris flows. Experiments demonstrated that C-band Envisat ASAR data were sensitive to vegetation, resulting in an underestimation of deforestation; in contrast, L-band PALSAR data were capable of evaluating the deforestation process owing to a better penetration and the significant coherence gain on damaged forest areas. The percentage of damaged forest estimated by PALSAR decreased from 20.66% to 17.34% during 2009–2010, implying an approximate 3% recovery rate of forests in the earthquake OPEN ACCESS Remote Sens. 2014, 6 6284 impacted areas. This study proves that long-wavelength SAR interferometry is promising for rapid assessment of disaster-induced deforestation, particularly in regions where the optical acquisition is constrained.
Efficient Lipschitz Extensions for High-Dimensional Graph Statistics and Node Private Degree Distributions

Lipschitz extensions were recently proposed as a tool for designing node differentially private algorithms. However, efficiently computable Lipschitz extensions were known only for 1-dimensional functions (that is, functions that output a single real value). In this paper, we study efficiently computable Lipschitz extensions for multi-dimensional (that is, vector-valued) functions on graphs. We show that, unlike for 1-dimensional functions, Lipschitz extensions of higher-dimensional functions on graphs do not always exist, even with a non-unit stretch. We design Lipschitz extensions with small stretch for the sorted degree list and for the degree distribution of a graph. Crucially, our extensions are efficiently computable. We also develop new tools for employing Lipschitz extensions in the design of differentially private algorithms. Specifically, we generalize the exponential mechanism, a widely used tool in data privacy. The exponential mechanism is given a collection of score functions that map datasets to real values. It attempts to return the name of the function with nearly minimum value on the data set. Our generalized exponential mechanism provides better accuracy when the sensitivity of an optimal score function is much smaller than the maximum sensitivity of score functions. We use our Lipschitz extension and the generalized exponential mechanism to design a nodedifferentially private algorithm for releasing an approximation to the degree distribution of a graph. Our algorithm is much more accurate than algorithms from previous work. ∗Computer Science and Engineering Department, Pennsylvania State University.
Analysis of Thrust Characteristics Considering Step-Skew and Overhang Effects in Permanent Magnet Linear Synchronous Motor

This paper analyzed thrust characteristics by considering the step-skew method and permanent magnet (PM) overhang in a linear synchronous motor. Although the PM overhang increases the thrust, it also influences the air-gap flux density distribution in the stacking direction, and thus, each step length should be adjusted according to the existence and length of the PM overhang. 3-D finite element analysis is used to calculate the magnetic field and the thrust characteristics are compared each other. The analysis results show that the stacking length of both ends of the step should be reduced to get lower detent force and thrust ripples, and higher generated thrust as the PM overhang is increased.
Next Generation Benchmark Control Problem for Seismically Excited Buildings

This paper presents the problem definition and guidelines of the next generation stru control benchmark problem for seismically excited buildings. Focusing on a 20-story steel s ture representing a typical midto high-rise building designed for the Los Angeles, Califo region, the goal of this study is to provide a clear basis to evaluate the efficacy of various tural control strategies. An evaluationmodel has been developed that portrays the salient feat of the structural system. Control constraints and evaluation criteria are presented for the problem. The task of each participant in this benchmark study is to define (including devices sors and control algorithms), evaluate and report on their proposed control strategies. Thes egies may be either passive, active, semi-active or a combination thereof. A simulation pro has been developed and made available to facilitate direct comparison of the efficiency and of the various control strategies. To illustrate some of the design challenges a sample contr tem design is presented, although this sample is not intended to be viewed as a comp design.  The protection of civil structures, including material content and human occupants, is out a doubt a world-wide priority. The extent of protection may range from reliable operation occupant comfort to human and structural survivability. Civil structures, including existing future buildings, towers and bridges, must be adequately protected from a variety of e including earthquakes, winds, waves and traffic. The protection of structures is now moving relying entirely on the inelastic deformation of the structure to dissipate the energy of s dynamic loadings, to the application of passive, active and semi-active structural control de to mitigate undesired responses to dynamic loads. In the last two decades, many control algorithms and devices have been proposed fo engineering applications (Soong 1990; Housner, et al. 1994; Soong and Constantinou 199 Fujino,et al. 1996; Spencer and Sain 1997), each of which has certain advantages, depend the specific application and the desired objectives. At the present time, structural control res is greatly diversified with regard to these specific applications and desired objectives. A com basis for comparison of the various algorithms and devices does not currently exist. Deter 1. Prof., Dept. of Civil Engrg. and Geo Dept. of Civil Engrg.,  St. Louis, MO 63130-4899. March 22, 1999 1 Spencer, et al.
Forecasting daily lake levels using artificial intelligence approaches

Accurate prediction of lake-level variations is important for planning, design, construction, and operation of lakeshore structures and also in the management of freshwater lakes for water supply purposes. In the present paper, three artificial intelligence approaches, namely artificial neural networks (ANNs), adaptive-neuro-fuzzy inference system (ANFIS), and gene expression programming (GEP), were applied to forecast daily lake-level variations up to 3-day ahead time intervals. The measurements at the Lake Iznik in Western Turkey, for the period of January 1961–December 1982, were used for training, testing, and validating the employed models. The results obtained by the GEP approach indicated that it performs better than ANFIS and ANNs in predicting lake-level variations. A comparison was also made between these artificial intelligence approaches and convenient autoregressive moving average (ARMA) models, which demonstrated the superiority of GEP, ANFIS, and ANN models over ARMA models. & 2011 Elsevier Ltd. All rights reserved.
The Construction of Social Reality An Exchange

In his The Construction of Social Reality, Searle presents an account of rights, responsibilities, obligations, duties, and similar entities in terms of the formula X counts as Y in context C, where “X” refers in the simplest case to some physical object or event and “Y ” to the result of imposing upon X some deontic power or function. Smith attempts to show the limitations of this formula, focusing especially on the examples of contested property rights (where C is not uniquely defined), and of money in bank accounts and other phenomena (where no physical X-term is available). Searle responds to these criticisms, above all by pointing to the fact that some of the problems Smith raises are to be addressed not by an ontological analysis of social reality but rather through legal or political means.
Si, SiGe Nanowire Devices by Top–Down Technology and Their Applications

Nanowire (NW) devices, particularly the gate-all-around (GAA) CMOS architecture, have emerged as the front-runner for pushing CMOS scaling beyond the roadmap. These devices offer unique advantages over their planar counterparts which make them feasible as an option for 22 -nm and beyond technology nodes. This paper reviews the current technology status for realizing the GAA NW device structures and their applications in logic circuit and nonvolatile memories. We also take a glimpse into applications of NWs in the ldquomore-than-Moorerdquo regime and briefly discuss the application of NWs as biochemical sensors. Finally, we summarize the status and outline the challenges and opportunities of the NW technology.
On the usability of business process modelling tools - a review and future research directions

The choice of a business process modelling (BPM) tool in combination with the selection of a modelling language is one of the crucial steps in BPM project preparation. Different aspects influence the decision: tool functionality, price, modelling language support, etc. In this paper we discuss the aspect of usability, which has already been recognized as an important topic in software engineering and web design. We conduct a literature review to find out the current state of research on the usability in the BPM field. The results of the literature review show, that although a number of research papers mention the importance of usability for BPM tools, real usability evaluation studies have rarely been undertaken. Based on the results of the literature analysis, the possible research directions in the field of usability of BPM tools are suggested.
VIOLENCE ON THE BRAIN : A CRITIQUE OF NEUROSCIENCE IN CRIMINAL LAW

Current research in law and neuroscience is promising to answer these questions with a "yes." Some legal scholars working in this area claim that we are close to realizing the "early criminologists' dream of identifying the biological roots of criminality." These hopes for a neuroscientific transformation of the criminal law, although based in the newest research, are part of a very old story. Criminal law and neuroscience have been engaged in an ill-fated and sometimes tragic affair for over two hundred years. Three issues have recurred that track those that bedeviled earlier efforts to ground criminal law in brain sciences. First is the claim that the brain is often the most relevant or fundamental level at which to understand criminal conduct. Second is that the various phenomena we call "criminal violence" arise causally from dysfunction within specific locations in the brain ("localization"). Third is the related claim that, because much violent criminality arises from brain dysfunction, people who commit such acts are biologically different from typical people ("alterity" or "otherizing").
Novel hyaluronic acid dermal filler: dermal gel extra physical properties and clinical outcomes.

Dermal gel extra (DGE) is a new, tightly cross-linked hyaluronic acid (HA)-based dermal filler containing lidocaine engineered to resist gel deformation and degradation.



To develop a firmer gel product (DGE) and compare the efficacy and safety of DGE with nonanimal stabilized HA (NASHA) for correction of nasolabial folds (NLFs).



DGE physical properties were characterized, and 140 subjects with moderate to deep NLFs were treated with DGE and NASHA in a randomized, multicenter, split-face design study. Efficacy, pain, and satisfaction were measured using appropriate standard instruments. Adverse events were monitored throughout the study.



DGE has a higher modulus and a higher gel:fluid ratio than other HA fillers. Similar optimal correction was observed with DGE and NASHA through 36 weeks (9 months). Study subjects required less volume (p<.001) and fewer touch-ups (p=.005) and reported less injection pain (p<.001) with DGE treatment. Most adverse events were mild to moderate skin reactions.



DGE is a firm HA gel that required significantly less volume and fewer touch-ups to provide equivalent efficacy to NASHA for NLF correction; both dermal gels were well tolerated. DGE will provide a comfortable and cost-effective dermal filler option for clinicians and patients.
Ultrasonic communication in frogs

Among vertebrates, only microchiropteran bats, cetaceans and some rodents are known to produce and detect ultrasounds (frequencies greater than 20 kHz) for the purpose of communication and/or echolocation, suggesting that this capacity might be restricted to mammals. Amphibians, reptiles and most birds generally have limited hearing capacity, with the ability to detect and produce sounds below ∼12 kHz. Here we report evidence of ultrasonic communication in an amphibian, the concave-eared torrent frog (Amolops tormotus) from Huangshan Hot Springs, China. Males of A. tormotus produce diverse bird-like melodic calls with pronounced frequency modulations that often contain spectral energy in the ultrasonic range. To determine whether A. tormotus communicates using ultrasound to avoid masking by the wideband background noise of local fast-flowing streams, or whether the ultrasound is simply a by-product of the sound-production mechanism, we conducted acoustic playback experiments in the frogs' natural habitat. We found that the audible as well as the ultrasonic components of an A. tormotus call can evoke male vocal responses. Electrophysiological recordings from the auditory midbrain confirmed the ultrasonic hearing capacity of these frogs and that of a sympatric species facing similar environmental constraints. This extraordinary upward extension into the ultrasonic range of both the harmonic content of the advertisement calls and the frog's hearing sensitivity is likely to have co-evolved in response to the intense, predominantly low-frequency ambient noise from local streams. Because amphibians are a distinct evolutionary lineage from microchiropterans and cetaceans (which have evolved ultrasonic hearing to minimize congestion in the frequency bands used for sound communication and to increase hunting efficacy in darkness), ultrasonic perception in these animals represents a new example of independent evolution.
Learning of Coordination Policies for Robotic Swarms

Inspired by biological swarms, robotic swarms are envisioned to solve real-world problems that are difficult for individual agents. Biological swarms can achieve collective intelligence based on local interactions and simple rules; however, designing effective distributed policies for large-scale robotic swarms to achieve a global objective can be challenging. Although it is often possible to design an optimal centralized strategy for smaller numbers of agents, those methods can fail as the number of agents increases. Motivated by the growing success of machine learning, we develop a deep learning approach that learns distributed coordination policies from centralized policies. In contrast to traditional distributed control approaches, which are usually based on human-designed policies for relatively simple tasks, this learning-based approach can be adapted to more difficult tasks. We demonstrate the efficacy of our proposed approach on two different tasks, the well-known rendezvous problem and a more difficult particle assignment problem. For the latter, no known distributed policy exists. From extensive simulations, it is shown that the performance of the learned coordination policies is comparable to the centralized policies, surpassing state-of-the-art distributed policies. Thereby, our proposed approach provides a promising alternative for real-world coordination problems that would be otherwise computationally expensive to solve or intangible to explore.
ActNeT: Active Learning for Networked Texts in Microblogging

Supervised learning, e.g., classification, plays an important role in processing and organizing microblogging data. In microblogging, it is easy to mass vast quantities of unlabeled data, but would be costly to obtain labels, which are essential for supervised learning algorithms. In order to reduce the labeling cost, active learning is an effective way to select representative and informative instances to query for labels for improving the learned model. Different from traditional data in which the instances are assumed to be independent and identically distributed (i.i.d.), instances in microblogging are networked with each other. This presents both opportunities and challenges for applying active learning to microblogging data. Inspired by social correlation theories, we investigate whether social relations can help perform effective active learning on networked data. In this paper, we propose a novel Active learning framework for the classification of Networked Texts in microblogging (ActNeT). In particular, we study how to incorporate network information into text content modeling, and design strategies to select the most representative and informative instances from microblogging for labeling by taking advantage of social network structure. Experimental results on Twitter datasets show the benefit of incorporating network information in active learning and that the proposed framework outperforms existing state-of-the-art methods.
Scalp Acupuncture Treatment Protocol for Anxiety Disorders: A Case Report

Anxiety disorders are among the most common psychiatric illnesses, and acupuncture treatment is widely accepted in the clinic without the side effects seen from various medications. We designed a scalp acupuncture treatment protocol by locating two new stimulation areas. The area one is between Yintang (M-HN-3) and Shangxing (DU-23) and Shenting (DU-24), and the area two is between Taiyang (M-HN-9) and Tianchong (GB-9) and Shuaigu (GB-8). By stimulating these two areas with high-frequency continuous electric waves, remarkable immediate and long-term effects for anxiety disorders have been observed in our practice. The first case was a 70-year-old male with general anxiety disorder (GAD) and panic attacks at night. The scalp acupuncture treatment protocol was applied with electric stimulation for 45 minutes once every week. After four sessions of acupuncture treatments, the patient reported that he did not have panic attacks at night and he had no feelings of anxiety during the day. Follow-up 4 weeks later confirmed that he did not have any episodes of panic attacks and he had no anxiety during the day since his last acupuncture treatment. The second case was a 35-year-old male who was diagnosed with posttraumatic stress disorder (PTSD) with a history of providing frontline trauma care as a Combat Medics from the Iraq combat field. He also had 21 broken bones and multiple concussions from his time in the battlefield. He had symptoms of severe anxiety, insomnia, nightmares with flashbacks, irritability, and bad temper. He also had chest pain, back pain, and joint pain due to injuries. The above treatment protocol was performed with 30 minutes of electric stimulation each time in combination with body acupuncture for pain management. After weekly acupuncture treatment for the first two visits, the patient reported that he felt less anxious and that his sleep was getting better with fewer nightmares. After six sessions of acupuncture treatments, the patient completely recovered from PTSD, went back to work, and now lives a healthy and happy family life. The above cases and clinical observation show that the scalp acupuncture treatment protocol with electric stimulation has a significant clinic outcome for GAD, panic disorder and PTSD. The possible mechanism of action of scalp acupuncture on anxiety disorder may be related to overlapping modulatory effects on the cortical structures (orbitofrontal cortex [OFC]) and medial prefrontal cortex [mPFC]) and subcortical/limbic regions (amygdala and hippocampus), and biochemical effect of acupuncture through immunohistochemistry (norepinephrine, serotonin) performed directly to the brain tissue for anxiety disorders.