nils-herrmann/clean_scirepeval huggingface dataset:
The crying shame of robot nannies : an ethical appraisal

Childcare robots are being manufactured and developed with the long term aim of creating surrogate carers. While total child-care is not yet being promoted, there are indications that it is „on the cards‟. We examine recent research and developments in childcare robots and speculate on progress over the coming years by extrapolating from other ongoing robotics work. Our main aim is to raise ethical questions about the part or full-time replacement of primary carers. The questions are about human rights, privacy, robot use of restraint, deception of children and accountability. But the most pressing ethical issues throughout the paper concern the consequences for the psychological and emotional wellbeing of children. We set these in the context of the child development literature on the pathology and causes of attachment disorders. We then consider the adequacy of current legislation and international ethical guidelines on the protection of children from the overuse of robot care.
Optic disc and cup segmentation by automatic thresholding with morphological operation for glaucoma evaluation

This research proposes a robust method for disc localization and cup segmentation that incorporates masking to avoid misclassifying areas as well as forming the structure of the cup based on edge detection. Our method has been evaluated using two fundus image datasets, namely: D-I and D-II comprising of 60 and 38 images, respectively. The proposed method of disc localization achieves an average Fscore of 0.96 and average boundary distance of 7.7 for D-I, and 0.96 and 9.1, respectively, for D-II. The cup segmentation method attains an average Fscore of 0.88 and average boundary distance of 13.8 for D-I, and 0.85 and 18.0, respectively, for D-II. The estimation errors (mean ± standard deviation) of our method for the value of vertical cup-to-disc diameter ratio against the result of the boundary by the expert of DI and D-II have similar value, namely 0.04 ± 0.04. Overall, the result of ourmethod indicates its robustness for glaucoma evaluation. B Anindita Septiarini anindita.septiarini@gmail.com Agus Harjoko aharjoko@ugm.ac.id Reza Pulungan pulungan@ugm.ac.id Retno Ekantini rekantini@ugm.ac.id 1 Department of Computer Science and Electronics, Faculty of Mathematics and Natural Sciences, Universitas Gadjah Mada, Yogyakarta 55281, Indonesia 2 Faculty of Medicine, Universitas Gadjah Mada, Yogyakarta 55281, Indonesia 3 Department of Computer Science, Mulawarman University, Samarinda 75123, Indonesia
Low-DC Voltage-Controlled Steering-Antenna Radome Utilizing Tunable Active Metamaterial

In this paper, we experimentally realized a steering antenna using a type of active metamaterial with tunable refractive index. The metamaterial is realized by periodically printed subwavelength metallic resonant patterns with embedded microwave varactors. The effective refractive index can be controlled by low direct-current (dc) bias voltage applied to the varactors. In-phase electromagnetic waves transmitting in different zones of such metamaterial slab experience different phase delays, and, consequently, the output direction of the transmitted wave can be steered with progressive phase shift along the interface. This antenna has a simple structure, is very easy to configure the beam direction, and has a low cost. Compared with conventional phased-array antennas, the radome approach has more flexibility to operate with different feeding antennas for various applications.
Brain–Computer Interface Technologies in the Coming Decades

As the proliferation of technology dramatically infiltrates all aspects of modern life, in many ways the world is becoming so dynamic and complex that technological capabilities are overwhelming human capabilities to optimally interact with and leverage those technologies. Fortunately, these technological advancements have also driven an explosion of neuroscience research over the past several decades, presenting engineers with a remarkable opportunity to design and develop flexible and adaptive brain-based neurotechnologies that integrate with and capitalize on human capabilities and limitations to improve human-system interactions. Major forerunners of this conception are brain-computer interfaces (BCIs), which to this point have been largely focused on improving the quality of life for particular clinical populations and include, for example, applications for advanced communications with paralyzed or “locked in” patients as well as the direct control of prostheses and wheelchairs. Near-term applications are envisioned that are primarily task oriented and are targeted to avoid the most difficult obstacles to development. In the farther term, a holistic approach to BCIs will enable a broad range of task-oriented and opportunistic applications by leveraging pervasive technologies and advanced analytical approaches to sense and merge critical brain, behavioral, task, and environmental information. Communications and other applications that are envisioned to be broadly impacted by BCIs are highlighted; however, these represent just a small sample of the potential of these technologies.
STMC: Semantic Tag Medical Concept Using Word2Vec Representation

In this paper we propose a recognition system of medical concepts from free text clinical reports. Our approach tries to recognize also concepts which are named with local terminology, with medical writing scripts, short words, abbreviations and even spelling mistakes. We consider a clinical terminology ontology (Snomed-CT), as a dictionary of concepts. In a first step we obtain an embedding model using word2vec methodology from a big corpus database of clinical reports. Word vectors are positioned in the vector space such that words that share common contexts in the corpus are located in close proximity to one another in the space, and so the geometrical similarity can be considered a measure of semantic relation. We have considered 615513 emergency clinical reports from the Hospital "Rafael Méndez" in Lorca, Murcia. In these reports there are a lot of local language of the emergency domain, medical writing scripts, short words, abbreviations and even spelling mistakes. With the model obtained we represent the words and sentences as vectors, and by applying cosine similarity we identify which concepts of the ontology are named in the text. Finally, we represent the clinical reports (EHR) like a bag of concepts, and use this representation to search similar documents. The paper illustrates 1) how we build the word2vec model from the free text clinical reports, 2) How we extend the embedding from words to sentences, and 3) how we use the cosine similarity to identify concepts. The experimentation, and expert human validation, shows that: a) the concepts named in the text with the ontology terminology are well recognized, and b) others concepts that are not named with the ontology terminology are also recognized, obtaining a high precision and recall measures.
Bee-MMT: A load balancing method for power consumption management in cloud computing

Energy consumption management has become an essential concept in cloud computing. In this paper, we propose a new power aware load balancing, named Bee-MMT (artificial bee colony algorithm-Minimal migration time), to decline power consumption in cloud computing; as a result of this decline, CO2 production and operational cost will be decreased. According to this purpose, an algorithm based on artificial bee colony algorithm (ABC) has been proposed to detect over utilized hosts and then migrate one or more VMs from them to reduce their utilization; following that we detect underutilized hosts and, if it is possible, migrate all VMs which have been allocated to these hosts and then switch them to the sleep mode. However, there is a trade-off between energy consumption and providing high quality of service to the customers. Consequently, we consider SLA Violation as a metric to qualify the QOS that require to satisfy the customers. The results show that the proposed method can achieve greater power consumption saving than other methods like LR-MMT (local regression-Minimal migration time), DVFS (Dynamic Voltage Frequency Scaling), IQR-MMT (Interquartile Range-MMT), MAD-MMT (Median Absolute Deviation) and non-power aware.
A Comparison of Class Imbalance Techniques for Real-World Landslide Predictions

Landslides cause lots of damage to life and property world over. There has been research in machine-learning that aims to predict landslides based on the statistical analysis of historical landslide events and its triggering factors. However, prediction of landslides suffers from a class-imbalance problem as landslides and land-movement are very rare events. In this paper, we apply state-of-the-art techniques to correct the class imbalance in landslide datasets. More specifically, to overcome the class-imbalance problem, we use different synthetic and oversampling techniques to a real-world landslide data collected from the Chandigarh - Manali highway. Also, we apply several machine-learning algorithms to the landslide data set for predicting landslides and evaluating our algorithms. Different algorithms have been assessed using techniques like the area under the ROC curve (AUC) and sensitivity index (d'). Results suggested that random forest algorithm performed better compared to other classification techniques like neural networks, logistic regression, support vector machines, and decision trees. Furthermore, among class-imbalance methods, the Synthetic Minority Oversampling Technique with iterative partitioning filter (SMOTE-IPF) performed better than other techniques. We highlight the implications of our results and methods for predicting landslides in the real world.
Psoas hitch and Boari flap ureteroneocystostomy.

In the middle of the last century, Dolff , Paquin [2] and Zimmermann et al.  developed principles for ureteroneocystostomy after gynaecological ureter injuries. Turner-Warwick and Worth  adopted these techniques, named it the ‘Psoas Bladder-Hitch Procedure’ and applied this technique of ureteroneocystostomy for the treatment of distal ureteric obstruction, ureteric fistulas and ‘distended duplication’ of the upper urinary tract.
SOAP2: an improved ultrafast tool for short read alignment

SOAP2 is a significantly improved version of the short oligonucleotide alignment program that both reduces computer memory usage and increases alignment speed at an unprecedented rate. We used a Burrows Wheeler Transformation (BWT) compression index to substitute the seed strategy for indexing the reference sequence in the main memory. We tested it on the whole human genome and found that this new algorithm reduced memory usage from 14.7 to 5.4 GB and improved alignment speed by 20-30 times. SOAP2 is compatible with both single- and paired-end reads. Additionally, this tool now supports multiple text and compressed file formats. A consensus builder has also been developed for consensus assembly and SNP detection from alignment of short reads on a reference genome.



http://soap.genomics.org.cn.
Randomized control trial to assess the efficacy of metacognitive training compared with a psycho-educational group in people with a recent-onset psychosis.

Aims were to assess the efficacy of metacognitive training (MCT) in people with a recent onset of psychosis in terms of symptoms as a primary outcome and metacognitive variables as a secondary outcome.



A multicenter, randomized, controlled clinical trial was performed. A total of 126 patients were randomized to an MCT or a psycho-educational intervention with cognitive-behavioral elements. The sample was composed of people with a recent onset of psychosis, recruited from nine public centers in Spain. The treatment consisted of eight weekly sessions for both groups. Patients were assessed at three time-points: baseline, post-treatment, and at 6 months follow-up. The evaluator was blinded to the condition of the patient. Symptoms were assessed with the PANSS and metacognition was assessed with a battery of questionnaires of cognitive biases and social cognition.



Both MCT and psycho-educational groups had improved symptoms post-treatment and at follow-up, with greater improvements in the MCT group. The MCT group was superior to the psycho-educational group on the Beck Cognitive Insight Scale (BCIS) total (p = 0.026) and self-certainty (p = 0.035) and dependence self-subscale of irrational beliefs, comparing baseline and post-treatment. Moreover, comparing baseline and follow-up, the MCT group was better than the psycho-educational group in self-reflectiveness on the BCIS (p = 0.047), total BCIS (p = 0.045), and intolerance to frustration (p = 0.014). Jumping to Conclusions (JTC) improved more in the MCT group than the psycho-educational group (p = 0.021). Regarding the comparison within each group, Theory of Mind (ToM), Personalizing Bias, and other subscales of irrational beliefs improved in the MCT group but not the psycho-educational group (p < 0.001-0.032).



MCT could be an effective psychological intervention for people with recent onset of psychosis in order to improve cognitive insight, JTC, and tolerance to frustration. It seems that MCT could be useful to improve symptoms, ToM, and personalizing bias.
Prevalence of Parent-Reported ADHD Diagnosis and Associated Treatment Among U.S. Children and Adolescents, 2016.

The purpose of this study is to estimate the national prevalence of parent-reported attention deficit/hyperactivity disorder (ADHD) diagnosis and treatment among U.S. children 2-17 years of age using the 2016 National Survey of Children's Health (NSCH). The NSCH is a nationally representative, cross-sectional survey of parents regarding their children's health that underwent a redesign before the 2016 data collection. It included indicators of lifetime receipt of an ADHD diagnosis by a health care provider, whether the child currently had ADHD, and receipt of medication and behavioral treatment for ADHD. Weighted prevalence estimates were calculated overall and by demographic and clinical subgroups (n = 45,736). In 2016, an estimated 6.1 million U.S. children 2-17 years of age (9.4%) had ever received an ADHD diagnosis. Of these, 5.4 million currently had ADHD, which was 89.4% of children ever diagnosed with ADHD and 8.4% of all U.S. children 2-17 years of age. Of children with current ADHD, almost two thirds (62.0%) were taking medication and slightly less than half (46.7%) had received behavioral treatment for ADHD in the past year; nearly one fourth (23.0%) had received neither treatment. Similar to estimates from previous surveys, there is a large population of U.S. children and adolescents who have been diagnosed with ADHD by a health care provider. Many, but not all, of these children received treatment that appears to be consistent with professional guidelines, though the survey questions are limited in detail about specific treatment types received. The redesigned NSCH can be used to annually monitor diagnosis and treatment patterns for this highly prevalent and high-impact neurodevelopmental disorder.
Reinforcement Learning for Pivoting Task

In this work we propose an approach to learn a robust policy for solving the pivoting task. Recently, several model-free continuous control algorithms were shown to learn successful policies without prior knowledge of the dynamics of the task. However, obtaining successful policies required thousands to millions of training episodes, limiting the applicability of these approaches to real hardware. We developed a training procedure that allows us to use a simple custom simulator to learn policies robust to the mismatch of simulation vs robot. In our experiments, we demonstrate that the policy learned in the simulator is able to pivot the object to the desired target angle on the real robot. We also show generalization to an object with different inertia, shape, mass and friction properties than those used during training. This result is a step towards making model-free reinforcement learning available for solving robotics tasks via pre-training in simulators that offer only an imprecise match to the real-world dynamics.
SEC-TOE Framework: Exploring Security Determinants in Big Data Solutions Adoption

As in any new technology adoption in organizations, big data solutions (BDS) also presents some security threat and challenges, especially due to the characteristics of big data itself the volume, velocity and variety of data. Even though many security considerations associated to the adoption of BDS have been publicized, it remains unclear whether these publicized facts have any actual impact on the adoption of the solutions. Hence, it is the intent of this research-in-progress to examine the security determinants by focusing on the influence that various technological factors in security, organizational security view and security related environmental factors have on BDS adoption. One technology adoption framework, the TOE (technological-organizational-environmental) framework is adopted as the main conceptual research framework. This research will be conducted using a Sequential Explanatory Mixed Method approach. Quantitative method will be used for the first part of the research, specifically using an online questionnaire survey. The result of this first quantitative process will then be further explored and complemented with a case study. Results generated from both quantitative and qualitative phases will then be triangulated and a cross-study synthesis will be conducted to form the final result and discussion.
Dual-feed circularly polarized microstrip antenna for S-Band transmitter of Synthetic Aperture Radar (SAR) system

In this research, a single patch microstrip antenna has been made, using dual-feed line technique to produce a circular polarization. A rectangular slot has been used in order to reduce antenna dimension and increase the bandwidth. To increase the gain, front-end parasitic elements has been used. The antenna has a circular polarization with unidirectional radiation pattern. The center frequency is 2.35 GHz. The obtained value of VSWR is less than 1.5 with the bandwidth of 165.9 MHz, and the gain is 6.36 dBic.
An Effective Voltage Controller for Quasi-Z-Source Inverter-Based STATCOM With Constant DC-Link Voltage

A quasi-Z-source inverter (qZSI) could achieve buck/boost conversion as well as dc to ac inversion in a single-stage topology, which reduces the structure cost when compared to a traditional two-stage inverter. Specifically, the buck/boost conversion was accomplished via shoot-through state which took place across all phase legs of the inverter. In this paper, instead of using traditional dual-loop-based proportional integral (PI)-P controller, a type 2 based closed-loop voltage controller with novel dc-link voltage reference algorithm was proposed to fulfill the dc-link voltage tracking control of a single-phase qZSI regardless of any loading conditions, without the need of inner inductor current loop. A dc–ac boost inverter with similar circuit parameters as a qZSI was used to verify the flexibility of the proposed controller. The dynamic and transient performances of the proposed controller were investigated to evaluate its superiority against the aforementioned conventional controller. The integrated proposed controller and qZSI topology was then employed in static synchronous compensator application to perform reactive power compensation at the point of common coupling. The effectiveness of the proposed approach was verified through both simulation and experimental studies.
Ultralow-Loss CMOS Copper Plasmonic Waveguides.

Surface plasmon polaritons can give a unique opportunity to manipulate light at a scale well below the diffraction limit reducing the size of optical components down to that of nanoelectronic circuits. At the same time, plasmonics is mostly based on noble metals, which are not compatible with microelectronics manufacturing technologies. This prevents plasmonic components from integration with both silicon photonics and silicon microelectronics. Here, we demonstrate ultralow-loss copper plasmonic waveguides fabricated in a simple complementary metal-oxide semiconductor (CMOS) compatible process, which can outperform gold plasmonic waveguides simultaneously providing long (>40 μm) propagation length and deep subwavelength (∼λ(2)/50, where λ is the free-space wavelength) mode confinement in the telecommunication spectral range. These results create the backbone for the development of a CMOS plasmonic platform and its integration in future electronic chips.
PRECAST CONCRETE WALL PANELS WITH GLASS CONCRETE

NOTICE This report was prepared by Columbia University in the course of performing work contracted for and sponsored by the New York State Energy Research and Development Authority (hereafter " NYSERDA "). The opinions expressed in this report do not necessarily reflect those of NYSERDA or the State of New York, and reference to any specific product, service, process, or method does not constitute an implied or expressed recommendation or endorsement of it. Further, NYSERDA, the State of New York, and the contractor make no warranties or representations, expressed or implied, as to the fitness for particular purpose or merchantability of any product, apparatus, or service, or the usefulness, completeness, or accuracy of any processes, methods, or other information contained, described, disclosed, or referred to in this report. NYSERDA, the State of New York, and the contractor make no representation that the use of any product, apparatus, process, method, or other information will not infringe privately owned rights and will assume no liability for any loss, injury, or damage resulting from, or occurring in connection with, the use of information contained, described, disclosed, or referred to in this report.  A research project was conducted to develop a concrete material that contains recycled waste glass and reprocessed carpet fibers and would be suitable for precast concrete wall panels. Post-consumer glass and used carpets constitute major solid waste components. Therefore their beneficial use will reduce the pressure on scarce landfills and the associated costs to taxpayers. By identifying and utilizing the special properties of these recycled materials, it is also possible to produce concrete elements with improved esthetic and thermal insulation properties. Using recycled waste glass as substitute for natural aggregate in commodity products such as precast basement wall panels brings only modest economic benefits at best, because sand, gravel, and crushed stone are fairly inexpensive. However, if the esthetic properties of the glass are properly exploited, such as in building façade elements with architectural finishes, the resulting concrete panels can compete very effectively with other building materials such as natural stone. As for recycled carpet fibers, the intent of this project was to exploit their thermal properties in order to increase the thermal insulation of concrete wall panels. In this regard, only partial success was achieved, because commercially reprocessed carpet fibers improve the thermal properties of concrete only marginally, as compared with other methods, such as the use of …
An ultra low power UHF RFID tag front-end for EPCglobal Gen2 with novel clock-free decoder

In this paper, an ultra low power front-end circuit for an UHF RFID tag is presented. In order to minimize the power consumption, a novel data decoder is proposed, which removes the need for high frequency oscillator. In addition, a dual voltage multiplier scheme is employed, which increases the power efficiency. Simulation results shows that the proposed circuit reduces the power consumption by an order magnitude compared to conventional RFID front-end circuits that use high frequency oscillators and single voltage multiplier.