nils-herrmann/clean_scirepeval huggingface dataset:
Robotic Arm Based 3D Reconstruction Test Automation

The 3-D reconstruction involves the construction of a 3-D model from a set of images. The 3-D reconstruction has varied uses that include 3-D printing, the generation of 3-D models that can be shared through social media, and more. The 3-D reconstruction involves complex computations in mobile phones that must determine the pose estimation. The pose estimation involves the process of transforming a 2-D object into 3-D space. Once the pose estimation is done, then the mesh generation is performed using the graphics processing unit. This helps render the 3-D object. The competitive advantages of using hardware processors are to accelerate the intensive computation using graphics processors and digital signal processors. The stated problem that this technical paper addresses is the need for a reliable automated test for the 3-D reconstruction feature. The solution to this problem involved the design and development of an automated test system using a programmable robotic arm and rotor for precisely testing the quality of 3-D reconstruction features. The 3-D reconstruction testing involves using a robotic arm lab to accurately test the algorithmic integrity and end-to-end validation of the generated 3-D models. The robotic arm can move the hardware at different panning speeds, specific angles, fixed distances from the object, and more. The ability to reproduce the scanning at a fixed distance and the same panning speed helps to generate test results that can be benchmarked by different software builds. The 3-D reconstruction also requires a depth sensor to be mounted onto the device under examination. We use this robotic arm lab for functional, high performance, and stable validation of the 3-D reconstruction feature. This paper addresses the computer vision use case testing for 3-D reconstruction features and how we have used the robotic arm lab for automating these use cases.
An exceptional case of bilateral gestational gigantomastia with multiple breast lumps

Bilateral gigantomastia is a rare condition, often associated with pregnancy that is characterized by a diffuse enlargement of both breasts. Here we present a case of a late 20s woman in her seven months pregnancy with a bilateral gestational gigantomastia associated with multiple breast lumps. Histological analysis revealed a fibroadenoma. Her prolactin level after caesarean delivery was found particularly high. A significant decrease in breast size was achieved with bromocriptine treatment in conjunction with a bilateral lumpectomy. This case report highlights the diversity of gigantomastia and emphasizes the importance of a tailored, multidisciplinary approach to the diagnosis and treatment of this condition.
Learning Explanatory Rules from Noisy Data

Artificial Neural Networks are powerful function approximators capable of modelling solutions to a wide variety of problems, both supervised and unsupervised. As their size and expressivity increases, so too does the variance of the model, yielding a nearly ubiquitous overfitting problem. Although mitigated by a variety of model regularisation methods, the common cure is to seek large amounts of training data—which is not necessarily easily obtained—that sufficiently approximates the data distribution of the domain we wish to test on. In contrast, logic programming methods such as Inductive Logic Programming offer an extremely data-efficient process by which models can be trained to reason on symbolic domains. However, these methods are unable to deal with the variety of domains neural networks can be applied to: they are not robust to noise in or mislabelling of inputs, and perhaps more importantly, cannot be applied to non-symbolic domains where the data is ambiguous, such as operating on raw pixels. In this paper, we propose a Differentiable Inductive Logic framework, which can not only solve tasks which traditional ILP systems are suited for, but shows a robustness to noise and error in the training data which ILP cannot cope with. Furthermore, as it is trained by backpropagation against a likelihood objective, it can be hybridised by connecting it with neural networks over ambiguous data in order to be applied to domains which ILP cannot address, while providing data efficiency and generalisation beyond what neural networks on their own can achieve.
VARIATION OF INDIVIDUALISM AND COLLECTIVISM WITHIN AND BETWEEN 20 COUNTRIES A Typological Analysis

With data from a 20-nation study (N = 2,533), the authors investigated how individual patterns of endorsement of individualist and collectivist attitudes are distributed within and across national contexts. A cluster analysis performed on individual scores of self-reliance (individualist dimension), group-oriented interdependence (collectivist dimension), and competitiveness (individualist or collectivist dimension) yielded a typology of four constrained combinations of these dimensions. Despite the prevalence of a typology group within a given country, variability was observed in all countries. Self-reliant non-competitors and interdependent non-competitors were prevalent among participants from Western nations, whereas self-reliant competitors and interdependent competitors were more common in non-Western countries. These findings emphasize the benefits for cross-cultural research of a typological approach based on combinations of individualist and collectivist dimensions.
Design and Analysis of Swapped Port Coupler and Its Application in a Miniaturized Butler Matrix

This paper presents a novel size reduction technique for designing a Butler matrix using a new type of coupler. This coupler is half the length of a conventional coupler and has a swapped port characteristic wherein the locations of the isolation and coupled ports are switched. These features make the new coupler, called the "swapped port coupler," effective for reducing the size of the Butler matrix. The behavior of the swapped port coupler was mathematically analyzed, and its design equation was derived. Furthermore, the proposed coupler was employed to design a miniaturized Butler matrix. The area of this Butler matrix was 70 × 70 mm2, and its operating frequency was 1 GHz. When the area was normalized to the frequency, the area of the proposed Butler matrix was 10% of a conventional Butler matrix.
Non-pharmacological interventions and neuroplasticity in early stage Alzheimer's disease.

Non-pharmacological interventions have the potential to reduce cognitive decline and to improve psychosocial aspects in mild cognitive impairment and Alzheimer's dementia, and the absence of side effects makes them a favorable option also for preventive strategies. We provide an overview on recent studies involving cognitive training and reminiscence, stimulating and challenging experiences such as visual art and music, physical activities, and electromagnetic stimulation. We review findings on neuroplasticity in the aging brain and their relevance for cognitive improvement in patients with neurodegenerative diseases. We discuss cognitive reserve and possible mechanisms that drive neuroplasticity and new learning. Finally, we identify promising avenues for future intervention strategies and research, such as combinations of cognitive and pharmaceutical interventions, and individual strategies adapted to the disease stage and tailored to the needs, predispositions and preferences of patients.
Bulk current injection test modeling using an equivalent circuit for 1.8V mobile ICs

This paper shows a novel simulation method for bulk current injection (BCI) tests of I/O buffer circuits of mobile system memory. The simulation model consists of BCI probe, directional coupler, PCB, PKG, and IC. The proposed method is based on a behavioural I/O buffer model using a pulse generator as an input. A detailed simulation flow is introduced and validated through simulations performed on several injection probe loading conditions using a power decoupling capacitor and an on-chip decoupling capacitor.
PATDroid: permission-aware GUI testing of Android

Recent introduction of a dynamic permission system in Android, allowing the users to grant and revoke permissions after the installation of an app, has made it harder to properly test apps. Since an app's behavior may change depending on the granted permissions, it needs to be tested under a wide range of permission combinations. At the state-of-the-art, in the absence of any automated tool support, a developer needs to either manually determine the interaction of tests and app permissions, or exhaustively re-execute tests for all possible permission combinations, thereby increasing the time and resources required to test apps. This paper presents an automated approach, called PATDroid, for efficiently testing an Android app while taking the impact of permissions on its behavior into account. PATDroid performs a hybrid program analysis on both an app under test and its test suite to determine which tests should be executed on what permission combinations. Our experimental results show that PATDroid significantly reduces the testing effort, yet achieves comparable code coverage and fault detection capability as exhaustively testing an app under all permission combinations.
Direct Reprogramming of Fibroblasts into Functional Cardiomyocytes by Defined Factors

Masaki Ieda,1,2,3,6,* Ji-Dong Fu,1,2,3 Paul Delgado-Olguin,1,2,4 Vasanth Vedantham,1,5 Yohei Hayashi,1 Benoit G. Bruneau,1,2,4 and Deepak Srivastava1,2,3,* 1Gladstone Institute of Cardiovascular Disease 2Department of Pediatrics 3Department of Biochemistry and Biophysics 4Cardiovascular Research Institute 5Department of Medicine University of California, San Francisco, San Francisco, CA 94158, USA 6Present address: Departments of Cardiology and of Clinical and Molecular Cardiovascular Research, Keio University School of Medicine, Shinanomachi 35, Shinjuku-ku, Tokyo 160-8582, Japan *Correspondence: ieda@cpnet.med.keio.ac.jp (M.I.), dsrivastava@gladstone.ucsf.edu (D.S.) DOI 10.1016/j.cell.2010.07.002
A Comparative Analysis of Personality-Based Music Recommender Systems

This article describes a preliminary study on considering information about the target user’s personality in music recommender systems (MRSs). For this purpose, we devised and implemented four MRSs and evaluated them on a sample of real users and real-world datasets. Experimental results show that MRSs that rely on purely users’ personality information are able to provide performance comparable with those of a state-of-the-art MRS, even better in terms of the diversity of the suggested items.
Power-Efficient Resource Allocation for MC-NOMA with Statistical Channel State Information

In this paper, we study the power-efficient resource allocation for multicarrier non-orthogonal multiple access (MC-NOMA) systems. The resource allocation algorithm design is formulated as a non-convex optimization problem which takes into account the statistical channel state information at transmitter and quality of service (QoS) constraints. To strike a balance between system performance and computational complexity, we propose a suboptimal power allocation and user scheduling with low computational complexity to minimize the total power consumption. The proposed design exploits the heterogeneity of QoS requirement to determine the successive interference cancellation decoding order. Simulation results demonstrate that the proposed scheme achieves a close-to-optimal performance and significantly outperforms a conventional orthogonal multiple access (OMA) scheme.
Design of compact microstrip diplexer with high selectivity

A novel design of compact microstrip diplexer, using coupled dual-mode open-loop resonators, is proposed. The main advantage in using dual-mode open-loop resonators is that a compact narrowband bandpass filter with high selective asymmetrical frequency response is easily realized. This property is explored to design diplexer for a system with two extremely close bands. A prototype diplexer operating in the 2.07/2.3 GHz band, having compact size (44 mm × 11 mm) and high isolation (>;-40 dB), is designed for demonstration.
The effects of perceived risk and technology type on users' acceptance of technologies

Previous studies on technology adoption disagree regarding the relative magnitude of the effects of perceived usefulness and perceived ease of use. However these studies did not consider moderating variables. We investigated four potential moderating variables – perceived risk, technology type, user experience, and gender – in users’ technology adoption. Their moderating effects were tested in an empirical study of 161 subjects. Results showed that perceived risk, technology type, and gender were significant moderating variables. However the effects of user experience were marginal after the variance of errors was removed.
Encoding Specificity and Retrieval Processes in Episodic Memory

Recent changes in prctheorclical orientation toward problems of human memory have brought with them a concern with retrieval processes, and a number of early versions of theories of retrieval have been constructed. This paper describes and evaluates explanations offered by these theories to account for the effect of extralist cuing, facilitation of recall of list items by nonlist items. Experiments designed to test the currently most popular theory of retrieval, the generation-recognition theory, yielded results incompatible not only with generation-recognition models, but most other theories as well: under certain conditions subjects consistently failed to recognize many recallable list words. Several tentative explanations of this phenomenon of recognition failure were subsumed under the encoding specificity principle according to which the memory trace of an event and hence the properties of effective retrieval cue are determined by the specific encoding operations performed by the system on the input stimuli.
A model of design decision making based on empirical results of interviews with software designers

Despite the impact of design decisions on software design, we have little understanding about how design decisions are made. This hinders our ability to provide design metrics, processes and training that support inherent design work. By interviewing 25 software designers and using content analysis and explanation building as our analysis technique, we provide qualitative and quantitative results that highlight aspects of rational and naturalistic decision making in software design. Our qualitative multi-case study results in a model of design decision making to answer the question: how do software designers make design decisions? We find the structure of the design problem determines the aspects of rational and naturalistic decision making used. The more structured the design decision, the less a designer considers options.
Remediating organizational functioning in children with ADHD: immediate and long-term effects from a randomized controlled trial.

The study compared the efficacy of 2 behavioral interventions to ameliorate organization, time management, and planning (OTMP) difficulties in 3rd- to 5th-grade children with attention-deficit/hyperactivity disorder (ADHD).



In a dual-site randomized controlled trial, 158 children were assigned to organizational skills training (OST; N = 64); PATHKO, a performance-based intervention that precluded skills training (N = 61); or a wait-list control (WL, N = 33). Treatments were 20 individual clinic-based sessions over 10-12 weeks. OST involved skills building provided primarily to the child. PATHKO trained parents and teachers to reinforce children contingently for meeting end-point target goals. Primary outcomes were the Children's Organizational Skills Scales (COSS-Parent, COSS-Teacher). Other relevant functional outcomes were assessed. Percentage of participants no longer meeting inclusion criteria for OTMP impairments informed on clinical significance. Assessments occurred at post-treatment, 1-month post-treatment, and twice in the following school year.



OST was superior to WL on the COSS-P (Cohen's d = 2.77; p < .0001), COSS-T (d = 1.18; p < .0001), children's COSS self-ratings, academic performance and proficiency, homework, and family functioning. OST was significantly better than PATHKO only on the COSS-P (d = 0.63; p < .005). PATHKO was superior to WL on most outcomes but not on academic proficiency. Sixty percent of OST and PATHKO participants versus 3% of controls no longer met OTMP inclusion criteria. Significant maintenance effects were found for both treatments.



Two distinct treatments targeting OTMP problems in children with ADHD generated robust, sustained functional improvements. The interventions show promise of clinical utility in children with ADHD and organizational deficits.
Supply Chain Inventory Management and the Value of Shared Information

In traditional supply chain inventory management, orders are the only information firms exchange, but information technology now allows firms to share demand and inventory data quickly and inexpensively. We study the value of sharing these data in a model with one supplier, N identical retailers, and stationary stochastic consumer demand. There are inventory holding costs and back-order penalty costs. We compare a traditional information policy that does not use shared information with a full information policy that does exploit shared information. In a numerical study we find that supply chain costs are 2.2% lower on average with the full information policy than with the traditional information policy, and the maximum difference is 12.1%. We also develop a simulation-based lower bound over all feasible policies. The cost difference between the traditional information policy and the lower bound is an upper bound on the value of information sharing: In the same study, that difference is 3.4% on average, and no more than 13.8%. We contrast the value of information sharing with two other benefits of information technology, faster and cheaper order processing, which lead to shorter lead times and smaller batch sizes, respectively. In our sample, cutting lead times nearly in half reduces costs by 21% on average, and cutting batches in half reduces costs by 22% on average. For the settings we study, we conclude that implementing information technology to accelerate and smooth the physical flow of goods through a supply chain is significantly more valuable than using information technology to expand the flow of information.
Compiler-Directed Lightweight Checkpointing for Fine-Grained Guaranteed Soft Error Recovery

This paper presents Bolt, a compiler-directed soft error recovery scheme, that provides fine-grained and guaranteed recovery without excessive performance and hardware overhead. To get rid of expensive hardware support, the compiler protects the architectural inputs during their entire liveness period by safely checkpointing the last updated value in idempotent regions. To minimize the performance overhead, Bolt leverages a novel compiler analysis that eliminates those checkpoints whose value can be reconstructed by other checkpointed values without compromising the recovery guarantee. As a result, Bolt incurs only 4.7% performance overhead on average which is 57% reduction compared to the state-of-the-art scheme that requires expensive hardware support for the same recovery guarantee as Bolt.
Principles of interleukin (IL)-6-type cytokine signalling and its regulation.

The IL (interleukin)-6-type cytokines IL-6, IL-11, LIF (leukaemia inhibitory factor), OSM (oncostatin M), ciliary neurotrophic factor, cardiotrophin-1 and cardiotrophin-like cytokine are an important family of mediators involved in the regulation of the acute-phase response to injury and infection. Besides their functions in inflammation and the immune response, these cytokines play also a crucial role in haematopoiesis, liver and neuronal regeneration, embryonal development and fertility. Dysregulation of IL-6-type cytokine signalling contributes to the onset and maintenance of several diseases, such as rheumatoid arthritis, inflammatory bowel disease, osteoporosis, multiple sclerosis and various types of cancer (e.g. multiple myeloma and prostate cancer). IL-6-type cytokines exert their action via the signal transducers gp (glycoprotein) 130, LIF receptor and OSM receptor leading to the activation of the JAK/STAT (Janus kinase/signal transducer and activator of transcription) and MAPK (mitogen-activated protein kinase) cascades. This review focuses on recent progress in the understanding of the molecular mechanisms of IL-6-type cytokine signal transduction. Emphasis is put on the termination and modulation of the JAK/STAT signalling pathway mediated by tyrosine phosphatases, the SOCS (suppressor of cytokine signalling) feedback inhibitors and PIAS (protein inhibitor of activated STAT) proteins. Also the cross-talk between the JAK/STAT pathway with other signalling cascades is discussed.
A Hybrid Feature Selection Algorithm For Classification Unbalanced Data Processsing

The performance and accuracy of classifier are affected by the result of feature selection directly. Based on the one-class F-Score feature selection and the improved F-Score feature selection and genetic algorithm, combined with machine learning methods like the K nearest neighbor, support vector machine, random forest, naive Bayes, a hybrid feature selection algorithm is proposed to process the two classification unbalanced data problem and multi classification problem. Compared with the traditional machine learning algorithm, it can search in wider feature space and promote classifier to deal with the characteristics of unbalanced data sets according to heuristic rules, which can handle the problem of unbalanced classification better. The experiment results show that the area under receiver operating characteristic curve for two classifications and the accuracy rate for multi classification problem have been improved compared with other models
High speed cascode flyback converter using multilayered coreless printed circuit board (PCB) step-down power transformer

In this paper, design and analysis of the high speed isolated cascode flyback converter using multilayered coreless PCB step down power transformer is presented. The converter is tested for the input voltage variation of 60–120V with a nominal DC input voltage of 90V. The designed converter was simulated and tested successfully up to the output power level of 30W within the switching frequency range of 2.6–3.7MHz. The cascode flyback converter is compared with the single switch flyback converter in terms of operating frequency, gate drive power consumption, conduction losses and stresses on MOSFETs. The maximum energy efficiency of the cascode converter is approximately 81% with a significant improvement of about 3–4% compared to single switch flyback converter. The gate drive power consumption which is more dominant compared to conduction losses of the cascode converter using GaN MOSFET is found to be negligible compared to single switch flyback converter.
Safe collaboration of humans and SCARA robots

This paper presents a method to determine distance between human operator and SCARA robot using computer vision in order to provide a safe workstation for human robot collaboration. Kinect sensor is used as the input device to the system. Kinect has four streams of data among which depth data is effectively used in this approach. The measured distance is used to calculate danger index. Online trajectory generation allows the robot to perform appropriate action. The results of applying this system to FUM SCARA is presented.