nils-herrmann/clean_scirepeval huggingface dataset:
An Efficient, Electrically Small Antenna Designed for VHF and UHF Applications

An electrically small electric-based metamaterial-in- spired antenna that is designed for narrow bandwidth operations in the VHF and UHF bands is presented. It is demonstrated that the idealized lossless versions have overall efficiencies at 100% without any external matching circuits and quality factors approaching the Chu limit. When conductor losses are introduced, the overall efficiencies remain high.
Product allocation to different types of distribution center in retail logistics networks

We consider the problem of assigning stockkeeping units to distribution centers (DCs) belonging to different DC types of a retail network, e.g., central, regional, and local DCs. The problem is motivated by the real situation of a retail company and solved by an MIP solution approach. The MIP model reflects the interdependencies between inbound transportation, outbound transportation and instore logistics as well as capital tied up in inventories and differences in picking costs between the warehouses. A novel solution approach is developed and applied to a real-life case of a leading European grocery retail chain. The application of the new approach results in cost savings of 6% of total operational costs compared to the present assignment. These savings amount to several million euros per year. In-depth analyses of the results and sensitivity analyses provide insights into the solution structure and the major related issues.
What do childhood anxiety disorders predict?

Few longitudinal studies of child and adolescent psychopathology have examined the links between specific childhood anxiety disorders and adolescent psychiatric disorder. In this paper we test the predictive specificity of separation anxiety disorder (SAD), overanxious disorder (OAD), generalized anxiety disorder (GAD), and social phobia.



Data come from the Great Smoky Mountains Study (GSMS). A representative population sample of children--ages 9, 11, and 13 years at intake--was followed to age 19. Diagnoses of both childhood (before age 13 years) and adolescent psychiatric disorders (age 13 to 19 years) were available from 906 participants.



Childhood SAD predicted adolescent SAD, whereas OAD was associated with later OAD, panic attacks, depression and conduct disorder (CD). GAD was related only to CD. Social phobia in childhood was associated with adolescent OAD, social phobia, and attention-deficit/hyperactivity disorder (ADHD).



Anxiety disorders in childhood are predictors of a range of psychiatric disorders in adolescence. It appears that children meriting a well-defined diagnosis are missed by the current rules for the diagnosis of GAD. Future studies should examine whether OAD deserves reconsideration as a nosological entity.
Semi-supervised model personalization for improved detection of learner's emotional engagement

Affective states play a crucial role in learning. Existing Intelligent Tutoring Systems (ITSs) fail to track affective states of learners accurately. Without an accurate detection of such states, ITSs are limited in providing truly personalized learning experience. In our longitudinal research, we have been working towards developing an empathic autonomous 'tutor' closely monitoring students in real-time using multiple sources of data to understand their affective states corresponding to emotional engagement. We focus on detecting learning related states (i.e., 'Satisfied', 'Bored', and 'Confused'). We have collected 210 hours of data through authentic classroom pilots of 17 sessions. We collected information from two modalities: (1) appearance, which is collected from the camera, and (2) context-performance, that is derived from the content platform. The learning content of the content platform consists of two section types: (1) instructional where students watch instructional videos and (2) assessment where students solve exercise questions. Since there are individual differences in expressing affective states, the detection of emotional engagement needs to be customized for each individual. In this paper, we propose a hierarchical semi-supervised model adaptation method to achieve highly accurate emotional engagement detectors. In the initial calibration phase, a personalized context-performance classifier is obtained. In the online usage phase, the appearance classifier is automatically personalized using the labels generated by the context-performance model. The experimental results show that personalization enables performance improvement of our generic emotional engagement detectors. The proposed semi-supervised hierarchical personalization method result in 89.23% and 75.20% F1 measures for the instructional and assessment sections respectively.
Reduced duty-cycle loss and output inductor current ripple in a ZVS switched three-phase isolated PWM rectifier

In this paper a PWM method for zero voltage switched three-phase isolated rectifier is presented. The presented PWM scheme features lower maximum output inductor current ripple and lower duty-cycle loss by more than half. Therefore, a smaller output inductor can be used and the ZVS operation can be extended at wider load range for MOSFET devices by increasing the leakage inductance of the transformer. The steady state analysis of duty-cycle loss and inductor current ripple are addressed and verified by the simulation and experimental results for two different PWM schemes.
BIOMASS ETHANOL : Technical Progress , Opportunities , and Commercial Challenges

■ Abstract Ethanol made from lignocellulosic biomass sources, such as agricultural and forestry residues and herbaceous and woody crops, provides unique environmental, economic, and strategic benefits. Through sustained research funding, primarily by the U.S. Department of Energy, the estimated cost of biomass ethanol production has dropped from∼$4.63/gallon in 1980 to∼$1.22/gallon today, and it is now potentially competitive for blending with gasoline. Advances in pretreatment by acid-catalyzed hemicellulose hydrolysis and enzymes for cellulose breakdown coupled with recent development of genetically engineered bacteria that ferment all five sugars in biomass to ethanol at high yields have been the key to reducing costs. However, through continued advances in accessing the cellulose and hemicellulose fractions, the cost of biomass ethanol can be reduced to the point at which it is competitive as a pure fuel without subsidies. A major challenge to realizing the great benefits of biomass ethanol remains to substantially reduce the risk of commercializing first-ofa-kind technology, and greater emphasis on developing a fundamental understanding of the technology for biomass conversion to ethanol would reduce application costs and accelerate commercialization. Teaming of experts to cooperatively research key processing steps would be a particularly powerful and effective approach to meeting these needs.
Economic Perspectives in Test Automation: Balancing Automated and Manual Testing with Opportunity Cost

Testing is a major cost factor in software development. Test automation has been proposed as one solution to reduce these costs. Test automation tools promise to increase the number of tests they run and the frequency at which they run them. So why not automate every test? In this paper we discuss the question "When should a test be automated?" and the trade-off between automated and manual testing. We reveal problems in the overly simplistic cost models commonly used to make decisions about automating testing. We introduce an alternative model based on opportunity cost and present influencing factors on the decision of whether or not to invest in test automation. Our aim is to stimulate discussion about these factors as well as their influence on the benefits and costs of automated testing in order to support researchers and practitioners reflecting on proposed automation approaches.
Revisiting the hallmarks of cancer.

The hallmarks of cancer described by Hanahan and Weinberg have proved seminal in our understanding of cancer's common traits and in rational drug design. Not free of critique and with understanding of different aspects of tumorigenesis coming into clearer focus in the recent years, we attempt to draw a more organized and updated picture of the cancer hallmarks. We define seven hallmarks of cancer: selective growth and proliferative advantage, altered stress response favoring overall survival, vascularization, invasion and metastasis, metabolic rewiring, an abetting microenvironment, and immune modulation, while highlighting some considerations for the future of the field.
A 7.663-TOPS 8.2-W Energy-efficient FPGA Accelerator for Binary Convolutional Neural Networks

FPGA-based hardware accelerator for convolutional neural networks (CNNs) has obtained great attentions due to its higher energy efficiency than GPUs. However, it has been a challenge for FPGA-based solutions to achieve a higher throughput than GPU counterparts. In this paper, we demonstrate that FPGA acceleration can be a superior solution in terms of both throughput and energy efficiency when a CNN is trained with binary constraints on weights and activations. Specifically, we propose an optimized accelerator architecture tailored for bitwise convolution and normalization that features massive spatial parallelism with deep pipeline (temporal parallelism) stages. Experiment results show that the proposed architecture running at 90 MHz on a Xilinx Virtex-7 FPGA achieves a computing throughput of 7.663 TOPS with a power consumption of 8.2 W regardless of the batch size of input data. This is 8.3x faster and 75x more energy-efficient than a Titan X GPU for processing online individual requests (in small batch size). For processing static data (in large batch size), the proposed solution is on a par with a Titan X GPU in terms of throughput while delivering 9.5x higher energy efficiency.
Winding design for pole-phase modulation of induction machines

Induction machines with pole-phase modulation (PPM) can extend speed / torque capabilities for applications in integrated starter/generator and hybrid electric vehicles. In this paper, a general winding design rule for the PPM of induction machines is proposed. A prototype is used to verify the proposed method and the feasibility of the designed pole-changing winding. Besides, the characteristics of three different structure machines — conventional winding machine, toroidal winding machine and dual-rotor torodial winding machine operated in the same mode are compared by using the finite element software JMAG-studio. The results show that both conventional winding machine and dual-rotor torodial winding machine present good performances. Moreover, conventional winding machine has many advantages such as a simple structure, so its experimental prototype is designed and manufactured for next control work.
Bayesian identification of fixations, saccades, and smooth pursuits

Smooth pursuit eye movements provide meaningful insights and information on subject’s behavior and health and may, in particular situations, disturb the performance of typical fixation/saccade classification algorithms. Thus, an automatic and efficient algorithm to identify these eye movements is paramount for eye-tracking research involving dynamic stimuli. In this paper, we propose the Bayesian Decision Theory Identification (I-BDT) algorithm, a novel algorithm for ternary classification of eye movements that is able to reliably separate fixations, saccades, and smooth pursuits in an online fashion, even for low-resolution eye trackers. The proposed algorithm is evaluated on four datasets with distinct mixtures of eye movements, including fixations, saccades, as well as straight and circular smooth pursuits; data was collected with a sample rate of 30 Hz from six subjects, totaling 24 evaluation datasets. The algorithm exhibits high and consistent performance across all datasets and movements relative to a manual annotation by a domain expert (recall: μ = 91.42%, σ = 9.52%; precision: μ = 95.60%, σ = 5.29%; specificity μ = 95.41%, σ = 7.02%) and displays a significant improvement when compared to I-VDT, an state-of-the-art algorithm (recall: μ = 87.67%, σ = 14.73%; precision: μ = 89.57%, σ = 8.05%; specificity μ = 92.10%, σ = 11.21%). For the algorithm implementation and annotated datasets, please contact the first author.  Pattern Recognition – Models; I.6.4 [Computing Methodologies]: Simulation and Modeling – Model Validation and Analysis; J.7 [Computer Applications]: Computers in Other Systems – Real Time;
Design of a non invasive haptic feedback device for transradial myoelectric upper limb prosthesis

This paper presents the design of a new haptic feedback device for transradial myoelectric upper limb prosthesis that allows the amputee person to perceive the sensation of force-gripping and object-sliding. The system designed has three mechanical-actuator units to convey the sensation of force, and one vibrotactile unit to transmit the sensation of object sliding. The device designed will be placed on the user's amputee forearm. In order to validate the design of the structure, a stress analysis through Finite Element Method (FEM) is conducted.
Earnings Quality and Stock Returns

An exclusive focus on bottom-line income misses important information about the quality of earnings. Accruals (the difference between accounting earnings and cash flow) are reliably, negatively associated with future stock returns. Earnings increases that are accompanied by high accruals, suggesting low-quality earnings, are associated with poor future returns. We explore various hypotheses — earnings manipulation, extrapolative biases about future growth, and under-reaction to changes in business conditions — to explain accruals’ predictive power. Distinctions between the hypotheses are based on evidence from operating performance, the behavior of individual accrual items, discretionary versus nondiscretionary components of accruals, and special items. We check for robustness using within-industry comparisons, and data on U.K.
Going Further with Point Pair Features

Point Pair Features is a widely used method to detect 3D objects in point clouds, however they are prone to fail in presence of sensor noise and background clutter. We introduce novel sampling and voting schemes that significantly reduces the influence of clutter and sensor noise. Our experiments show that with our improvements, PPFs become competitive against state-of-the-art methods as it outperforms them on several objects from challenging benchmarks, at a low computational cost.
Autofocus survey: a comparison of algorithms

There are numerous passive contrast sensing autofocus algorithms that are well documented in literature, but some aspects of their comparative performance have not been widely researched. This study explores the relative merits of a set of autofocus algorithms via examining them against a variety of scene conditions. We create a statistics engine that considers a scene taken through a range of focal values and then computes the best focal position using each autofocus algorithm. The process is repeated across a survey of test scenes containing different representative conditions. The results are assessed against focal positions which are determined by manually focusing the scenes. Through examining these results, we then derive conclusions about the relative merits of each autofocus algorithm with respect to the criteria accuracy and unimodality. Our study concludes that the basic 2D spatial gradient measurement approaches yield the best autofocus results in terms of accuracy and unimodality.
Deep learning based image description generation

Describing the contents of images is a challenging task for machines to achieve. It requires not only accurate recognition of objects and humans, but also their attributes and relationships as well as scene information. It would be even more challenging to extend this process to identify falls and hazardous objects to aid elderly or users in need of care. This research makes initial attempts to deal with the above challenges to produce multi-sentence natural language description of image contents. It employs a local region based approach to extract regional image details and combines multiple techniques including deep learning and attribute learning through the use of machine learned features to create high level labels that can generate detailed description of real-world images. The system contains the core functions of scene classification, object detection and classification, attribute learning, relationship detection and sentence generation. We have also further extended this process to deal with open-ended fall detection and hazard identification. In comparison to state-of-the-art related research, our system shows superior robustness and flexibility in dealing with test images from new, unrelated domains, which poses great challenges to many existing methods. Our system is evaluated on a subset from Flickr8k and Pascal VOC 2012 and achieves an impressive average BLEU score of 46 and outperforms related research by a significant margin of 10 BLEU score when evaluated with a small dataset of images containing falls and hazardous objects. It also shows impressive performance when evaluated using a subset of IAPR TC-12 dataset.
Pathogenicity of the family Legionellaceae

The Legionellae are Gram-negative bacteria able to survive and replicate in a wide range of protozoan hosts in natural environments, but they also occur in man-made aquatic systems, which are the major source of infection. After transmission to humans via aerosols, Legionella spp. can cause pneumonia (Legionnaires’ disease) or influenza-like respiratory infections (Pontiac fever). In children, Legionnaires’ disease is uncommon and is mainly diagnosed in children with immunosuppression. The clinical picture of Legionella pneumonia does not allow differentiation from pneumonia caused by others pathogens. The key to diagnosis is performing appropriate microbiological testing. The clinical presentation and the natural course of Legionnaires’ disease in children are not clear due to an insufficient number of samples, but morbidity and mortality caused by this infection are extremely high. The mortality rate for legionellosis depends on the promptness of an appropriate antibiotic therapy. Fluoroquinolones are the most efficacious drugs against Legionella. A combination of these drugs with macrolides seems to be promising in the treatment of immunosuppressed patients and individuals with severe legionellosis. Although all Legionella species are considered potentially pathogenic for humans, Legionella pneumophila is the etiological agent responsible for most reported cases of community-acquired and nosocomial legionellosis.
Influence of blue-enriched classroom lighting on students׳ cognitive performance

Light is a powerful zeitgeber that synchronizes our endogenous circadian pacemaker with the environment and has been previously described as an agent in improving cognitive performance. With that in mind, this study was designed to explore the influence of exposure to blue-enriched white light in the morning on the performance of adolescent students. 58 High school students were recruited from four classes in two schools. In each school, one classroom was equipped with blue-enriched white lighting while the classroom next door served as a control setting. The effects of classroom lighting on cognitive performance were assessed using standardized psychological tests. Results show beneficial effects of blue-enriched white light on students' performance. In comparison to standard lighting conditions, students showed faster cognitive processing speed and better concentration. The blue-enriched white lighting seems to influence very basic information processing primarily, as no effects on short-term encoding and retrieval of memories were found. & 2014 Elsevier GmbH. All rights reserved.
Impact of Computed Tomography on Operative Planning for Ankle Fractures Involving the Posterior Malleolus.

The purpose of this study was to (1) Determine the effect of computed tomography (CT) on identification of fractures involving the posterior malleolus, (2) determine its effect on operative indications, and (3) determine its effect on the overall operative plan.



Patients with ankle fractures involving the posterior malleolus were identified. Only injuries with complete preoperative plain radiographs and a CT scan were included. Spiral tibia fractures and pilon variants were excluded. The plain radiographs were deidentified, randomized, and presented to 3 orthopedic surgeons. They were asked 3 questions: (1) Is this fracture simple or complex? (2) Does the injury require direct visualization and reduction? and (3) How would you position the patient and approach the fracture? The same process was repeated for the CT scans. A total of 376 posterior malleolus injuries were identified and 25 met the inclusion criteria.



A complex fracture pattern was identified on 44% of plain radiographs and 56% of CT scans. The surgeons chose to operate in 84% of cases based on plain radiographs and 92% of cases based on CT scan. The observers changed their operative approach or positioning 44% of the time after reviewing CT images. The interobserver and intraobserver correlation coefficients were moderate.



The use of CT scan changed operative positioning and approach in 44% of cases. There was no significant change in characterization or operative indications when comparing plain radiographs to CT scan. CT scan may be a valuable tool in the management of ankle fractures involving the posterior malleolus.