nils-herrmann/clean_scirepeval huggingface dataset:
In-Database Learning with Sparse Tensors

In-database analytics is of great practical importance as it avoids the costly repeated loop data scientists have to deal with on a daily basis: select features, export the data, convert data format, train models using an external tool, reimport the parameters. It is also a fertile ground of theoretically fundamental and challenging problems at the intersection of relational and statistical data models. This paper introduces a unified framework for training and evaluating a class of statistical learning models inside a relational database. This class includes ridge linear regression, polynomial regression, factorization machines, and principal component analysis. We show that, by synergizing key tools from relational database theory such as schema information, query structure, recent advances in query evaluation algorithms, and from linear algebra such as various tensor and matrix operations, one can formulate in-database learning problems and design efficient algorithms to solve them. The algorithms and models proposed in the paper have already been implemented and deployed in retail-planning and forecasting applications, with significant performance benefits over out-of-database solutions that require the costly data-export loop.
Robust high-speed low input impedance CMOS current comparator

In this paper, a robust high speed low input impedance CMOS current comparator is proposed. The circuit uses modified Wilson current-mirror to perform a current subtraction. Negative feedback is employed to reduce input impedances of the circuit. The diode connected transistors of the same type (NMOS) are used at the output making the circuit immune to the process variation. HSPICE is used to verify the circuit performance and the results show the propagation delay of 1.67 nsec with an average power dissipation of 0.63 mW using a standard 0.5 /spl mu/m CMOS technology for an input current of /spl plusmn/0.1 /spl mu/A at the supply voltage of 3 V. The input impedances of the proposed current comparator are 123 /spl Omega/ and 126 /spl Omega/ while the maximum output voltage variation is only 1.9%.
S2R(Pgrmc1): the cytochrome-related sigma-2 receptor that regulates lipid and drug metabolism and hormone signaling.

S2R (sigma-2 receptor)/Pgrmc1 (progesterone receptor membrane component 1) is a cytochrome-related protein that binds directly to heme and various pharmacological compounds. S2R(Pgrmc1) also associates with cytochrome P450 proteins, the EGFR receptor tyrosine kinase and the RNA-binding protein PAIR-BP1. S2R(Pgrmc1) is induced in multiple types of cancer, where it regulates tumor growth and is implicated in progesterone signaling. S2R(Pgrmc1) also increases cholesterol synthesis in non-cancerous cells and may have a role in modulating drug metabolizing P450 proteins.



This review covers the independent identification of S2R and Pgrmc1 and their induction in cancers, as well as the role of S2R(Pgrmc1) in increasing cholesterol metabolism and P450 activity. This article was formed through a PubMed literature search using, but not limited to, the terms sigma-2 receptor, Pgrmc1, Dap1, cholesterol and aromatase.



Multiple laboratories have shown that S2R(Pgrmc1) associates with various P450 proteins and increases cholesterol synthesis via Cyp51. However, the lipogenic role of S2R(Pgrmc1) is tissue-specific. Furthermore, the role of S2R(Pgrmc1) in regulating P450 proteins other than Cyp51 appears to be highly selective, with modest inhibitory activity for Cyp3A4 in vitro and a complex regulatory pattern for Cyp21. Cyp19/aromatase is a therapeutic target in breast cancer, and S2R(Pgrmc1) activated Cyp19 significantly in vitro but modestly in biochemical assays. In summary, S2R(Pgrmc1) is a promising therapeutic target for cancer and possibly cholesterol synthesis but research to date has not identified a major role in P450-mediated drug metabolism.
Skeletal Animation Based on BVH Motion Data

skeletal animation model is widely used in character animation. But bounded actions lead to the complexity of making animation data and lower reuse. BVH file, as a universal human feature animation file formats, is popular because of its wide source and making-easy. This paper presented a method by using BVH file as the animation data, to drive the skeletal animation. Based on the analysis of BVH file structure, this paper establishes data structure to parse the BVH file, and also designs a recursive parsing algorithm. At last, we implement the diversification of skeletal animation model of mesh by accessing BVH motion data to drive the skeletal animation The experimental results show that our method is accuracy and efficient.
How a diverse research ecosystem has generated new rehabilitation technologies: Review of NIDILRR’s Rehabilitation Engineering Research Centers

Over 50 million United States citizens (1 in 6 people in the US) have a developmental, acquired, or degenerative disability. The average US citizen can expect to live 20% of his or her life with a disability. Rehabilitation technologies play a major role in improving the quality of life for people with a disability, yet widespread and highly challenging needs remain. Within the US, a major effort aimed at the creation and evaluation of rehabilitation technology has been the Rehabilitation Engineering Research Centers (RERCs) sponsored by the National Institute on Disability, Independent Living, and Rehabilitation Research. As envisioned at their conception by a panel of the National Academy of Science in 1970, these centers were intended to take a “total approach to rehabilitation”, combining medicine, engineering, and related science, to improve the quality of life of individuals with a disability. Here, we review the scope, achievements, and ongoing projects of an unbiased sample of 19 currently active or recently terminated RERCs. Specifically, for each center, we briefly explain the needs it targets, summarize key historical advances, identify emerging innovations, and consider future directions. Our assessment from this review is that the RERC program indeed involves a multidisciplinary approach, with 36 professional fields involved, although 70% of research and development staff are in engineering fields, 23% in clinical fields, and only 7% in basic science fields; significantly, 11% of the professional staff have a disability related to their research. We observe that the RERC program has substantially diversified the scope of its work since the 1970’s, addressing more types of disabilities using more technologies, and, in particular, often now focusing on information technologies. RERC work also now often views users as integrated into an interdependent society through technologies that both people with and without disabilities co-use (such as the internet, wireless communication, and architecture). In addition, RERC research has evolved to view users as able at improving outcomes through learning, exercise, and plasticity (rather than being static), which can be optimally timed. We provide examples of rehabilitation technology innovation produced by the RERCs that illustrate this increasingly diversifying scope and evolving perspective. We conclude by discussing growth opportunities and possible future directions of the RERC program.
The p-median problem: A survey of metaheuristic approaches

The p-median problem is one of the basic models in discrete location theory. As with most location problems, it is classified as NP-hard, and so, heuristic methods are usually used to solve it. Metaheuristics are frameworks for building heuristics. In this survey, we examine the p-median, with the aim of providing an overview on advances in solving it using recent procedures based on metaheuristic rules.
Automated Diagnosis of Glaucoma Using Texture and Higher Order Spectra Features

Glaucoma is the second leading cause of blindness worldwide. It is a disease in which fluid pressure in the eye increases continuously, damaging the optic nerve and causing vision loss. Computational decision support systems for the early detection of glaucoma can help prevent this complication. The retinal optic nerve fiber layer can be assessed using optical coherence tomography, scanning laser polarimetry, and Heidelberg retina tomography scanning methods. In this paper, we present a novel method for glaucoma detection using a combination of texture and higher order spectra (HOS) features from digital fundus images. Support vector machine, sequential minimal optimization, naive Bayesian, and random-forest classifiers are used to perform supervised classification. Our results demonstrate that the texture and HOS features after z-score normalization and feature selection, and when combined with a random-forest classifier, performs better than the other classifiers and correctly identifies the glaucoma images with an accuracy of more than 91%. The impact of feature ranking and normalization is also studied to improve results. Our proposed novel features are clinically significant and can be used to detect glaucoma accurately.
Threat sensitivity in bipolar disorder.

Life stress is a major predictor of the course of bipolar disorder. Few studies have used laboratory paradigms to examine stress reactivity in bipolar disorder, and none have assessed autonomic reactivity to laboratory stressors. In the present investigation we sought to address this gap in the literature. Participants, 27 diagnosed with bipolar I disorder and 24 controls with no history of mood disorder, were asked to complete a complex working memory task presented as "a test of general intelligence." Self-reported emotions were assessed at baseline and after participants were given task instructions; autonomic physiology was assessed at baseline and continuously during the stressor task. Compared to controls, individuals with bipolar disorder reported greater increases in pretask anxiety from baseline and showed greater cardiovascular threat reactivity during the task. Group differences in cardiovascular threat reactivity were significantly correlated with comorbid anxiety in the bipolar group. Our results suggest that a multimethod approach to assessing stress reactivity-including the use of physiological parameters that differentiate between maladaptive and adaptive profiles of stress responding-can yield valuable information regarding stress sensitivity and its associations with negative affectivity in bipolar disorder.
Role of insulin, insulin-like growth factor-1, hyperglycaemic food and milk consumption in the pathogenesis of acne vulgaris.

It is the purpose of this viewpoint article to delineate the regulatory network of growth hormone (GH), insulin, and insulin-like growth factor-1 (IGF-1) signalling during puberty, associated hormonal changes in adrenal and gonadal androgen metabolism, and the impact of dietary factors and smoking involved in the pathogenesis of acne. The key regulator IGF-1 rises during puberty by the action of increased GH secretion and correlates well with the clinical course of acne. In acne patients, associations between serum levels of IGF-1, dehydroepiandrosterone sulphate, dihydrotestosterone, acne lesion counts and facial sebum secretion rate have been reported. IGF-1 stimulates 5alpha-reductase, adrenal and gonadal androgen synthesis, androgen receptor signal transduction, sebocyte proliferation and lipogenesis. Milk consumption results in a significant increase in insulin and IGF-1 serum levels comparable with high glycaemic food. Insulin induces hepatic IGF-1 secretion, and both hormones amplify the stimulatory effect of GH on sebocytes and augment mitogenic downstream signalling pathways of insulin receptors, IGF-1 receptor and fibroblast growth factor receptor-2b. Acne is proposed to be an IGF-1-mediated disease, modified by diets and smoking increasing insulin/IGF1-signalling. Metformin treatment, and diets low in milk protein content and glycaemic index reduce increased IGF-1 signalling. Persistent acne in adulthood with high IGF-1 levels may be considered as an indicator for increased risk of cancer, which may require appropriate dietary intervention as well as treatment with insulin-sensitizing agents.
Parameters identification of thrust generation subsystem for small unmanned aerial vehicles

This article is concerned with parameters identification problems and computer modeling of thrust generation subsystem for small unmanned aerial vehicles (UAV) quadrotor type. In this paper approach for computer model generation of dynamic process of thrust generation subsystem that consists of fixed pitch propeller, EC motor and power amplifier, is considered. Due to the fact that obtainment of aerodynamic characteristics of propeller via analytical approach is quite time-consuming, and taking into account that subsystem consists of as well as propeller, motor and power converter with microcontroller control system, which operating algorithm is not always available from manufacturer, receiving trusted computer model of thrust generation subsystem via analytical approach is impossible. Identification of the system under investigation is performed from the perspective of “black box” with the known qualitative description of proceeded there dynamic processes. For parameters identification of subsystem special laboratory rig that described in this paper was designed.
Concentric Tube Robot Design and Optimization Based on Task and Anatomical Constraints

Concentric tube robots are catheter-sized continuum robots that are well suited for minimally invasive surgery inside confined body cavities. These robots are constructed from sets of precurved superelastic tubes and are capable of assuming complex 3-D curves. The family of 3-D curves that the robot can assume depends on the number, curvatures, lengths, and stiffnesses of the tubes in its tube set. The robot design problem involves solving for a tube set that will produce the family of curves necessary to perform a surgical procedure. At a minimum, these curves must enable the robot to smoothly extend into the body and to manipulate tools over the desired surgical workspace while respecting anatomical constraints. This paper introduces an optimization framework that utilizes procedure- or patient-specific image-based anatomical models along with surgical workspace requirements to generate robot tube set designs. The algorithm searches for designs that minimize robot length and curvature and for which all paths required for the procedure consist of stable robot configurations. Two mechanics-based kinematic models are used. Initial designs are sought using a model assuming torsional rigidity. These designs are then refined using a torsionally compliant model. The approach is illustrated with clinically relevant examples from neurosurgery and intracardiac surgery.
A Nonlinear Control Law for Hover to Level Flight for the Quad Tiltrotor UAV

This paper presents recent advances in the project: development of a convertible unmanned aerial vehicle (UAV). This aircraft is able to change its flight configuration from hover to level flight and vice versa by means of a transition maneuver, while maintaining the aircraft in flight. For this purpose a nonlinear control strategy based on Lyapunov design is given. Numerical results are presented showing the effectiveness of the proposed approach.
Miniaturization of BranchLine Coupler Using Composite Right / Left-Handed Transmission Lines with Novel Meander-shaped-slots CSSRR

A novel compact-size branch-line coupler using composite right/left-handed transmission lines is proposed in this paper. In order to obtain miniaturization, composite right/left-handed transmission lines with novel complementary split single ring resonators which are realized by loading a pair of meander-shaped-slots in the split of the ring are designed. This novel coupler occupies only 22.8% of the area of the conventional approach at 0.7 GHz. The proposed coupler can be implemented by using the standard printed-circuit-board etching processes without any implementation of lumped elements and via-holes, making it very useful for wireless communication systems. The agreement between measured and stimulated results validates the feasible configuration of the proposed coupler.
Allocation of Splitting Nodes in All-Optical Wavelength-Routed Networks

In this paper, we introduce the splitter placement problem in wavelength-routed networks (SP-WRN). Given a network topology, a set of multicast sessions, and a fixed number of multicast-capable cross-connects, the SP-WRN problem entails the placement of the multicast-capable cross-connects so that the blocking probability is minimized. The SP-WRN problem is NP-complete as it includes as a subproblem the routing and wavelength assignment problem which is NP-complete. To gain a deeper insight into the computational complexity of the SP-WRN problem, we define a graph-theoretic version of the splitter placement problem (SPG), and show that even SPG is NP-complete. We develop three heuristics for the SP-WRN problem with different degrees of trade-off between computation time and quality of solution. The first heuristic uses the CPLEX general solver to solve an integer-linear program (ILP) of the problem. The second heuristic is based on a greedy approach and is called most-saturated node first (MSNF). The third heuristic employs simulated annealing (SA) with route-coordination. Through numerical examples on a wide variety of network topologies we demonstrate that: (1) no more than 50% of the cross-connects need to be multicast-capable, (2) the proposed SA heuristic provides fast near-optimal solutions, and (3) it is not practical to use general solvers such as CPLEX for solving the SP-WRN problem.
Smart: Support: Management Automated Reasoning Technology for Compaq Customer Service

Because of the increasingly competitive nature of the computer manufacturing industry, Compaq Computer Corporation has made some trend-setting changes in the way it does business. One of these changes is the extension of Compaq's call-logging sy ste problem-resolution component that assists customer support personnel in determining the resolution to a customer's questions and problems. Recently, Compaq extended its customer service to provide not only dealer support but also direct end user support; it is also accepting ownership of any Compaq customer's problems in a Banyan, Mi-crosoft, Novell, or SCO UNIX operating environment. One of the tools that makes this feat possible is SMART (support management automated reasoning technology). SMART is part of a Compaq strategy to increase the effectiveness of the customer support staff and reduce overall cost to the organization by retaining problem-solving knowledge and making it available to the entire support staff at the point it is needed.
Semantics-based Access Control Approach for Web Service

Due to the open and distributed characteristics of web service, its access control becomes a challenging problem which has not been addressed properly. In this paper, we show how semantic web technologies can be used to build a flexible access control system for web service. We follow the Role-based Access Control model and extend it with credential attributes. The access control model is represented by a semantic ontology, and specific semantic rules are constructed to implement such as dynamic roles assignment, separation of duty constraints and roles hierarchy reasoning, etc. These semantic rules can be verified and executed automatically by the reasoning engine, which can simplify the definition and enhance the interoperability of the access control policies. The basic access control architecture based on the semantic proposal for web service is presented. Finally, a prototype of the system is implemented to validate the proposal.
Wind Power Prediction by a New Forecast Engine Composed of Modified Hybrid Neural Network and Enhanced Particle Swarm Optimization

Following the growing share of wind energy in electric power systems, several wind power forecasting techniques have been reported in the literature in recent years. In this paper, a wind power forecasting strategy composed of a feature selection component and a forecasting engine is proposed. The feature selection component applies an irrelevancy filter and a redundancy filter to the set of candidate inputs. The forecasting engine includes a new enhanced particle swarm optimization component and a hybrid neural network. The proposed wind power forecasting strategy is applied to real-life data from wind power producers in Alberta, Canada and Oklahoma, U.S. The presented numerical results demonstrate the efficiency of the proposed strategy, compared to some other existing wind power forecasting methods.
Cytokines in the systemic inflammatory response syndrome: a review

Patients subject to major surgery, suffering sepsis, major trauma, or following cardiopulmonary bypass exhibit a systemic inflammatory response. This inflammatory response involves a complex array of inflammatory polypeptide molecules known as cytokines. It is well accepted that the loss of local control of the release of these cytokines leads to systemic inflammation and potentially deleterious consequences including the Systemic Inflammatory Response Syndrome, Multi-Organ Dysfunction Syndrome, shock and death.



The Medline database was searched for literature on mechanisms involved in the development of SIRS and potential targets for modifying the inflammatory response. We focus on the novel therapy of cytokine adsorption as a promising removal technology.



Accumulating data from human studies and experimental animal models suggests that both pro- and anti- inflammatory cytokines are released following a variety of initiating stimuli including endotoxin release, complement activation, ischaemia reperfusion injury and others.



Pro-and anti-inflammatory cytokines interact in a complex and unpredictable manner to influence the immune system and eventually cause multiple end organ effects. Cytokine adsorption therapy provides a potential solution to improving outcomes following Systemic Inflammatory Response Syndrome.