nils-herrmann/clean_scirepeval huggingface dataset:
Primary-Side Power Flow Control of Wireless Power Transfer for Electric Vehicle Charging

Various noncontacting methods of plug-in electric vehicle charging are either under development or now deployed as aftermarket options in the light-duty automotive market. Wireless power transfer (WPT) is now the accepted term for wireless charging and is used synonymously for inductive power transfer and magnetic resonance coupling. WPT technology is in its infancy; standardization is lacking, especially on interoperability, center frequency selection, magnetic fringe field suppression, and the methods employed for power flow regulation. This paper proposes a new analysis concept for power flow in WPT in which the primary provides frequency selection and the tuned secondary, with its resemblance to a power transmission network having a reactive power voltage control, is analyzed as a transmission network. Analysis is supported with experimental data taken from Oak Ridge National Laboratory's WPT apparatus. This paper also provides an experimental evidence for frequency selection, fringe field assessment, and the need for low-latency communications in the feedback path.
Overcurrent protection design, failure mode and effect analysis of an electric vehicle inverter

In the light of rapid developments in electric vehicles, it has raised a concern on the functional safety of inverters. Overcurrent is a common fault in the inverter, which could not only damage the inverter but also be hazardous to drivers and passengers due to unintended motive power loss on the road. Hence, an overcurrent protection design in an inverter is highly needed. In this study, the failure mode and effect analysis on the stated problem is systematically analyzed based on the functional safety standard, ISO26262. A two-level overcurrent protection mechanism with modulation limiter and current limiter strategy is proposed and implemented on a 50kW inverter system. Experimental results show the three-phase current amplitude is regulated within the designated current limit effectively during fault injection, which verifies the validity of the proposed strategies for the electric vehicle application.
No Training Required: Exploring Random Encoders for Sentence Classification

We explore various methods for computing sentence representations from pretrained word embeddings without any training, i.e., using nothing but random parameterizations. Our aim is to put sentence embeddings on more solid footing by 1) looking at how much modern sentence embeddings gain over random methods—as it turns out, surprisingly little; and by 2) providing the field with more appropriate baselines going forward—which are, as it turns out, quite strong. We also make important observations about proper experimental protocol for sentence classification evaluation, together with recommendations for future research.
Complete mesocolic excision with central vascular ligation produces an oncologically superior specimen compared with standard surgery for carcinoma of the colon.

The plane of surgery in colonic cancer has been linked to patient outcome although the optimal extent of mesenteric resection is still unclear. Surgeons in Erlangen, Germany, routinely perform complete mesocolic excision (CME) with central vascular ligation (CVL) and report 5-year survivals of higher than 89%. We aimed to further investigate the importance of CME and CVL surgery for colonic cancer by comparison with a series of standard specimens.



The fresh photographs of 49 CME and CVL specimens from Erlangen and 40 standard specimens from Leeds, United Kingdom, for primary colonic adenocarcinoma were collected. Precise tissue morphometry and grading of the plane of surgery were performed before comparison to histopathologic variables.



CME and CVL surgery removed more tissue compared with standard surgery in terms of the distance between the tumor and the high vascular tie (median, 131 v 90 mm; P < .0001), the length of large bowel (median, 314 v 206 mm; P < .0001), and ileum removed (median, 83 v 63 mm; P = .003), and the area of mesentery (19,657 v 11,829 mm(2); P < .0001). In addition, CME and CVL surgery was associated with more mesocolic plane resections (92% v 40%; P < .0001) and a greater lymph node yield (median, 30 v 18; P < .0001).



Surgeons in Erlangen routinely practicing CME and CVL surgery remove more mesocolon and are more likely to resect in the mesocolic plane when compared with standard excisions. This, along with the associated greater lymph node yield, may partially explain the high 5-year survival rates reported in Erlangen.
Integration Trends in Monolithic Power ICs: Application and Technology Challenges

This paper highlights the general trend towards further monolithic integration in power applications by enabling power management and interfacing solutions in advanced CMOS nodes. The need to combine high-density digital circuits, power-management circuits, and robust interfaces in a single technology platform requires the development of additional process options on top of baseline CMOS. Examples include high-voltage devices, devices to enable area-efficient ESD protection, and integrated capacitors and inductors with high quality factors. The use of bipolar devices in these technologies for protection and control purposes in power applications is also addressed.
RFID-based real-time smart waste management system

In an environmental context, the use of RFID (radio frequency identification) and load cell sensor technology can be employed for not only bringing down waste management costs, but also to facilitate automating and streamlining waste (e.g., garbage, recycling, and green) identification and weight measurement processes for designing smart waste management systems. In this paper, we outline a RFID and sensor model for designing a system in real-time waste management. An application of the architecture is described in the area of RFID and sensor based automatic waste identity, weight, and stolen bins identification system (WIWSBIS).
Human luminance pattern-vision mechanisms: masking experiments require a new model.

A widely used model of simultaneous luminance pattern masking is based on mechanisms that sum inputs linearly and produce a response that is an S-shaped function of that sum. This model makes two predictions about masking: (1) Changing the masker spatial waveform will shift the threshold-versus-masker contrast function horizontally by a multiplicative constant. (2) Adding a second fixed-contrast masker will shift this function horizontally by an additive constant. Experimental tests do not support these predictions. The results can be explained by a new model that incorporates broadband divisive inhibition, consistent with physiology.
Fingerprinting Electronic Control Units for Vehicle Intrusion Detection

As more software modules and external interfaces are getting added on vehicles, new attacks and vulnerabilities are emerging. Researchers have demonstrated how to compromise in-vehicle Electronic Control Units (ECUs) and control the vehicle maneuver. To counter these vulnerabilities, various types of defense mechanisms have been proposed, but they have not been able to meet the need of strong protection for safety-critical ECUs against in-vehicle network attacks. To mitigate this deficiency, we propose an anomaly-based intrusion detection system (IDS), called Clock-based IDS (CIDS). It measures and then exploits the intervals of periodic in-vehicle messages for fingerprinting ECUs. The thusderived fingerprints are then used for constructing a baseline of ECUs’ clock behaviors with the Recursive Least Squares (RLS) algorithm. Based on this baseline, CIDS uses Cumulative Sum (CUSUM) to detect any abnormal shifts in the identification errors — a clear sign of intrusion. This allows quick identification of in-vehicle network intrusions with a low false-positive rate of 0.055%. Unlike state-of-the-art IDSs, if an attack is detected, CIDS’s fingerprinting of ECUs also facilitates a rootcause analysis; identifying which ECU mounted the attack. Our experiments on a CAN bus prototype and on real vehicles have shown CIDS to be able to detect a wide range of in-vehicle network attacks.
Zero-Knowledge Proofs of Knowledge Without Interaction (Extended Abstract)

A zero-knowledge proof system of knowledge is a protocol between two parties called the prover and the verifier. The prover wants to convince the verifier that he “knows” the proof of a given theorem without revealing any additional information. This is different from a zero-knowledge proof system of membership where the prover convinces the verifier only of the veridicity of the statement. Zero-knowledge proofs of knowledge are very useful tools in the design of secure protocols. Though, the concept of a proof of knowledge is a very subtle one and great care is needed to obtain a satisfying formalization. In this paper, we investigate the concept of a zero-knowledge proof of knowledge in the noninteractive model of [5, 61. Here, the prover and the verifier share a short random string and the only communication allowed is from the prover to the verifier. Although this is a simpler model than the interactive one, still formalizing zeroknowledge proofs of knowledge is a delicate task. The main results of the paper are the following e We present formal definitions for the concept of non-interactive zero-knowledge proofs ‘Dipartimento di Informatica ed Applicazioni, Universiti di Salerno, 84081 Baronissi (SA), Italy. Partially supported by Italian Ministry of Universit.y and Research (M.U.R.S.T.) and by National Council for Research (C.N.R.) under grant 91.02326.CT12.  ads@udsab.dia.unisa.it ‘Aiken Computation Laboratory, Harvard University, Cambridge, MA 02138, USA and Dipart,imento di Informatica, Universiti di Salerno. Supported at Harvard by NSF Grant # NSF-CCR-90-07677.  persiano@endor.harvard.edu GIUSEPPE PERSIANO+
3D Soft Tissue Analysis – Part 1: Sagittal Parameters

The aim of this study was to develop a reliable threedimensional (3D) analysis of facial soft tissues. We determined the mean sagittal 3D values and relationships between sagittal skeletal parameters, and digitally recorded 3D soft tissue parameters. A total of 100 adult patients (nª = 53, nº = 47) of Caucasian ethnic origin were included in this study. Patients with syndromes, cleft lip and palate, noticeable asymmetry or anomalies in the number of teeth were excluded. Arithmetic means for seven sagittal 3D soft tissue parameters were calculated. The parameters were analyzed biometrically in terms of their reliability and gender-specific differences. The 3D soft tissue values were further analyzed for any correlations with sagittal cephalometric values. Reproducible 3D mean values were defined for 3D soft tissue parameters. We detected gender-specific differences among the parameters. Correlations between the sagittal 3D soft tissue and cephalometric measurements were statistically significant. 3D soft tissue analysis provides additional information on the sagittal position of the jaw bases and on intermaxillary sagittal relations. Further studies are needed to integrate 3D soft tissue analysis in future treatment planning and assessment as a supportive diagnostic tool. Ziel dieser Untersuchung war die Entwicklung einer reliablen dreidimensionalen (3D) Analyse der Gesichtsweichteile. Es sollten sagittale 3D-Durchschnittswerte bestimmt werden und Beziehungen zwischen sagittalen skelettalen Parametern und digital erfassten 3D-Weichteilparametern dargestellt werden. In die Studie eingeschlossen wurden 100 erwachsene Patienten (nª = 53, nº = 47) kaukasischer Herkunft. Ausgeschlossen wurden Patienten mit Syndromen, LKGSSpalten, auffälligen Asymmetrien oder Anomalien der Zahnzahl. Es wurden arithmetische Mittelwerte für sieben sagittale 3DWeichteilparameter ermittelt. Die Parameter wurden biometrisch hinsichtlich ihrer Reliabilität und geschlechtsspezifischer Unterschiede analysiert.  Weiteren wurden die 3D-Weichteilwerte bezüglich bestehender Korrelationen zu sagittalen kephalometrischen Werten untersucht. Für die 3D-Weichteilparameter konnten reproduzierbare 3D-Durchschnittswerte definiert werden. Innerhalb der Parameter ließen sich geschlechtsspezifische Unterschiede feststellen. Die Korrelationen zwischen den sagittalen 3D-Weichteilmessungen und den kephalometrischen Messungen waren statistisch signifikant. Die 3D-Weichteilanalyse lässt Aussagen sowohl über den sagittalen Einbau der Kieferbasen als auch über die sagittalen intermaxillären Beziehungen zu. Weitere Untersuchungen sind wünschenswert, um die 3D-Weichteildiagnostik zukünftig als unterstützendes diagnostisches Instrument in die Behandlungsplanung und -bewertung integrieren zu können.
In vivo 3-dimensional analysis of scapular kinematics: comparison of dominant and nondominant shoulders.

Alterations in scapular motion frequently are seen in association with various shoulder disorders. It is common clinically to compare the pathological shoulder with the contralateral shoulder, in spite of arm dominance, to characterize the disorder. However, there have been few articles that test the underlying assumption that dominant and nondominant shoulders exhibit comparable dynamic kinematics. The purpose of this study was to compare the 3-dimensional (3-D) scapular kinematics of dominant and nondominant shoulders during dynamic scapular plane elevation using 3-D-2-D (2-dimensional) registration techniques.



Twelve healthy males with a mean age of 32 years (range, 27-36) were enrolled in this study. Bilateral fluoroscopic images during scapular plane elevation and lowering were taken, and CT-derived 3-D bone models were matched with the silhouette of the bones in the fluoroscopic images using 3-D-2-D registration techniques. Angular values of the scapula and scapulohumeral rhythm were compared between dominant and nondominant shoulders with statistical analysis.



There was a significant difference in upward rotation angles between paired shoulders (P < .001), while significant differences were not found in the other angular values and scapulohumeral rhythm. The dominant scapulae were 10° more downwardly rotated at rest and 4° more upwardly rotated during elevation compared to the nondominant scapulae.



Scapular motion was not the same between dominant and nondominant arms in healthy subjects. The dominant scapula was rotated further downward at rest and reached greater upward rotation with abduction. These differences should be considered in clinical assessment of shoulder pathology.
A Maturity Model for Green ICT: The Case of the SURF Green ICT Maturity Model

This paper discusses the development and evaluation of a maturity model for Green ICT. We describe how the model was developed with the input of a number of Green ICT experts before it was released to the general public. The model consists of three domains with attributes on Green ICT that encompass both Greening of ICT as well as Greening by ICT. The quality of the model and its accuracy to capture the full scope of Green ICT has been evaluated through an online survey. We evaluated the quality of the model on relevancy of attributes, whether the attributes were well defined and whether the domains were complete. Twenty participants contributed meaningfully. Two attributes were considered to be irrelevant and six new attributes were suggested. With these results the quality of the maturity model can be improved. Our next step is to test the usefulness of the model by seeing how it is used in practice. We hope this paper inspires more work on testing the quality and usefulness of models and frameworks on Green ICT.
Anisotropic diffusion-based detail-preserving smoothing for image restoration

It is important in image restoration to remove noise while preserving meaningful details such as edges and fine features. The existing edge-preserving smoothing methods may inevitably take fine detail as noise or vice versa. In this paper, we propose a new edge-preserving smoothing technique based on a modified anisotropic diffusion. The proposed method can simultaneously preserve edges and fine details while filtering out noise in the diffusion process. Since the fine detail in the neighborhood of a small image window generally have a gray-level variance larger than that of the noisy background, the proposed diffusion model incorporates both local gradient and gray-level variance to preserve edges and fine details while effectively removing noise. Experimental results have shown that the proposed anisotropic diffusion scheme can effectively smooth noisy background, yet well preserve edge and fine details in the restored image. The proposed method has the best restoration result compared with other edge-preserving methods.
In Defense of the Triplet Loss for Person Re-Identification

In the past few years, the field of computer vision has gone through a revolution fueled mainly by the advent of large datasets and the adoption of deep convolutional neural networks for end-to-end learning. The person reidentification subfield is no exception to this, thanks to the notable publication of the Market-1501 and MARS datasets and several strong deep learning approaches. Unfortunately, a prevailing belief in the community seems to be that the triplet loss is inferior to using surrogate losses (classification, verification) followed by a separate metric learning step. We show that, for models trained from scratch as well as pretrained ones, using a variant of the triplet loss to perform end-to-end deep metric learning outperforms any other published method by a large margin.
Understanding vehicular traffic behavior from video: a survey of unsupervised approaches

Recent emerging trends for automatic behavior analysis and understanding from infrastructure video are reviewed. Research has shifted from high-resolution estimation of vehicle state and instead, pushed machine learning approaches to extract meaningful patterns in aggregates in an unsupervised fashion. These patterns represent priors on observable motion, which can be utilized to describe a scene, answer behavior questions such as where is a vehicle going, how many vehicles are performing the same action, and to detect an abnormal event. The review focuses on two main methods for scene description, trajectory clustering and topic modeling. Example applications that utilize the behavioral modeling techniques are also presented. In addition, the most popular public datasets for behavioral analysis are presented. Discussion and comment on future directions in the field are also provided.
"Like-Me" Simulation as an Effective and Cognitively Plausible Basis for Social Robotics

We present a successful design approach for social robotics based on a computational cognitive architecture and mental simulation. We discuss an approach to a Theory of Mind known as a “like-me” simulation in which the agent uses its own knowledge and capabilities as a model of another agent to predict that agent’s actions. We present three examples of a “like-me” mental simulation in a social context implemented in the embodied version of the Adaptive Control of Thought-Rational (ACT-R) cognitive architecture, ACT-R/E (for ACT-R Embodied). Our examples show the efficacy of a simulation approach in modeling perspective taking (identifying another’s left or right hand), teamwork (simulating a teammate for better team performance), and dominant-submissive social behavior (primate social experiments). We conclude with a discussion of the cognitive plausibility of this approach and our conclusions.
A Machine Learning Approach to Predict Gene Regulatory Networks in Seed Development in Arabidopsis

Gene regulatory networks (GRNs) provide a representation of relationships between regulators and their target genes. Several methods for GRN inference, both unsupervised and supervised, have been developed to date. Because regulatory relationships consistently reprogram in diverse tissues or under different conditions, GRNs inferred without specific biological contexts are of limited applicability. In this report, a machine learning approach is presented to predict GRNs specific to developing Arabidopsis thaliana embryos. We developed the Beacon GRN inference tool to predict GRNs occurring during seed development in Arabidopsis based on a support vector machine (SVM) model. We developed both global and local inference models and compared their performance, demonstrating that local models are generally superior for our application. Using both the expression levels of the genes expressed in developing embryos and prior known regulatory relationships, GRNs were predicted for specific embryonic developmental stages. The targets that are strongly positively correlated with their regulators are mostly expressed at the beginning of seed development. Potential direct targets were identified based on a match between the promoter regions of these inferred targets and the cis elements recognized by specific regulators. Our analysis also provides evidence for previously unknown inhibitory effects of three positive regulators of gene expression. The Beacon GRN inference tool provides a valuable model system for context-specific GRN inference and is freely available at https://github.com/BeaconProjectAtVirginiaTech/beacon_network_inference.git.
The Neural Substrate of Human Empathy: Effects of Perspective-taking and Cognitive Appraisal

Whether observation of distress in others leads to empathic concern and altruistic motivation, or to personal distress and egoistic motivation, seems to depend upon the capacity for self-other differentiation and cognitive appraisal. In this experiment, behavioral measures and event-related functional magnetic resonance imaging were used to investigate the effects of perspective-taking and cognitive appraisal while participants observed the facial expression of pain resulting from medical treatment. Video clips showing the faces of patients were presented either with the instruction to imagine the feelings of the patient (imagine other) or to imagine oneself to be in the patient's situation (imagine self). Cognitive appraisal was manipulated by providing information that the medical treatment had or had not been successful. Behavioral measures demonstrated that perspective-taking and treatment effectiveness instructions affected participants' affective responses to the observed pain. Hemodynamic changes were detected in the insular cortices, anterior medial cingulate cortex (aMCC), amygdala, and in visual areas including the fusiform gyrus. Graded responses related to the perspective-taking instructions were observed in middle insula, aMCC, medial and lateral premotor areas, and selectively in left and right parietal cortices. Treatment effectiveness resulted in signal changes in the perigenual anterior cingulate cortex, in the ventromedial orbito-frontal cortex, in the right lateral middle frontal gyrus, and in the cerebellum. These findings support the view that humans' responses to the pain of others can be modulated by cognitive and motivational processes, which influence whether observing a conspecific in need of help will result in empathic concern, an important instigator for helping behavior.