LLukas22/scidocs huggingface dataset:
Closed-Form Inverse Kinematics Solver for Reconfigurable Robots

|A closed-form inverse kinematics solver for non-redundant recon gurable robots is developed based on the Product-of-Exponentials (POE) formula. Its novelty lies in the use of POE reduction techniques and subproblems to obtain inverse kinematics solutions of a large number of possible con gurations in a systematic and convenient way. Three reduction techniques are introduced to simplify the POE equations. Eleven types of subproblems containing geometric solutions of those simpli ed equations are identi ed and solved. Based on the sequence and types of robot joints, the solved subproblems can be re-used for inverse kinematics of different robot con gurations. This solver can cope with closed-form inverse kinematics of all robots with DOFs of 4 or less, 90 percent of the 5-DOF robots and 50 percent of the 6-DOF robots, as well as frequently used industrial robots with both prismatic and revolute joints. The solver is implemented as a C++ software package and is demonstrated through an example.
Low-Voltage DC Distribution—Utilization Potential in a Large Distribution Network Company

Low-voltage direct-current (LVDC) distribution is a promising solution whose benefits are large power transfer capacity with low voltage, high cost savings potential, and improvements to reliability and voltage quality. Tests by the pilot implementation in the distribution system operator (DSO) Elenia Oy have given promising results. The power transfer capacity of the system has been calculated in this paper using voltage drop and maximum load of cable as boundaries. The branches of the medium-voltage network that can be replaced by LVDC distribution are determined based on the calculations and mass computation of the entire distribution area of Elenia Oy. Based on the electrotechnical and customer outage costs (COC) analyses made, it can be inferred that LVDC distribution has good utilization potential. Based on the power transfer capacity calculations, it is technically possible to replace branch lines up to 8 km long by LVDC distribution which means about 20% of the total medium-voltage network length in the distribution area of Elenia Oy. This means also huge potential in improving the overall reliability of electricity supply and in reducing outage costs of customers which are these days taken into account in the regulation of network business.
MetaExp: Interactive Explanation and Exploration of Large Knowledge Graphs

We present MetaExp, a system that assists the user during the exploration of large knowledge graphs, given two sets of initial nodes. At its core,MetaExp presents a small set of meta-paths to the user, which are sequences of relationships among node types. Such meta-paths do not overwhelm the user with complex structures, yet they preserve semantically-rich relationships in a graph. MetaExp engages the user in an interactive procedure, which involves simple meta-paths evaluations to infer a user-specific similarity measure. This similarity measure incorporates the domain knowledge and the preferences of the user, overcoming the fundamental limitations of previous methods based on local node neighborhoods or statically determined similarity scores. Our system provides a userfriendly interface for searching initial nodes and guides the user towards progressive refinements of the meta-paths. The system is demonstrated on three datasets, Freebase, a movie database, and a biological network. ACM Reference Format: Freya Behrens, Sebastian Bischoff, Pius Ladenburger, Julius Rückin, Laurenz Seidel, Fabian Stolp, Michael Vaichenker, Adrian Ziegler, Davide Mottin, Fatemeh Aghaei, Emmanuel Müller, Martin Preusse, Nikola Müller, Michael Hunger. 2018.MetaExp: Interactive Explanation and Exploration of Large Knowledge Graphs. InWWW ’18 Companion: The 2018 Web Conference Companion, April 23–27, 2018, Lyon, France. ACM, New York, NY, USA, 4 pages. https://doi.org/10.1145/3184558.3186978
Predicting antimicrobial peptides from eukaryotic genomes: In silico strategies to develop antibiotics

A remarkable and intriguing challenge for the modern medicine consists in the development of alternative therapies to avoid the problem of microbial resistance. The cationic antimicrobial peptides present a promise to be used to develop more efficient drugs applied to human health. The in silico analysis of genomic databases is a strategy utilized to predict peptides of therapeutic interest. Once the main antimicrobial peptides' physical-chemical properties are already known, the correlation of those features to search on these databases is a tool to shorten identifying new antibiotics. This study reports the identification of antimicrobial peptides by theoretical analyses by scanning the Paracoccidioides brasiliensis transcriptome and the human genome databases. The identified sequences were synthesized and investigated for hemocompatibility and also antimicrobial activity. Two peptides presented antifungal activity against Candida albicans. Furthermore, three peptides exhibited antibacterial effects against Staphylococcus aureus and Escherichia coli; finally one of them presented high potential to kill both pathogens with superior activity in comparison to chloramphenicol. None of them showed toxicity to mammalian cells. In silico structural analyses were performed in order to better understand function-structure relation, clearly demonstrating the necessity of cationic peptide surfaces and the exposition of hydrophobic amino acid residues. In summary, our results suggest that the use of computational programs in order to identify and evaluate antimicrobial peptides from genomic databases is a remarkable tool that could be used to abbreviate the search of peptides with biotechnological potential from natural resources.
Towards an Empirically Grounded Theory of Action for Improving the Quality of Mathematics Teaching at Scale

Our purpose in this article is to propose a comprehensive, empirically grounded theory of action for improving the quality of mathematics teaching at scale. In doing so, we summarise current research findings that can inform efforts to improve the quality of mathematics instruction on a large scale, and identify questions that are yet to be addressed. We draw on an ongoing collaboration with mathematics teachers, school leaders, and district leaders in four urban school districts in the US. The provisional theory of action that we report encompasses a coherent system of supports for ambitious instruction that includes both formal and job-embedded teacher professional development, teacher networks, mathematics coaches’ practices in providing job-embedded support for teachers’ learning, school leaders’ practices as instructional leaders in mathematics, and district leaders’ practices in supporting the development of school-level capacity for instructional improvement.
Collaborative personalized tweet recommendation

Twitter has rapidly grown to a popular social network in recent years and provides a large number of real-time messages for users. Tweets are presented in chronological order and users scan the followees' timelines to find what they are interested in. However, an information overload problem has troubled many users, especially those with many followees and thousands of tweets arriving every day. In this paper, we focus on recommending useful tweets that users are really interested in personally to reduce the users' effort to find useful information. Many kinds of information on Twitter are available for helping recommendation, including the user's own tweet history, retweet history and social relations between users. We propose a method of making tweet recommendations based on collaborative ranking to capture personal interests. It can also conveniently integrate the other useful contextual information. Our final method considers three major elements on Twitter: tweet topic level factors, user social relation factors and explicit features such as authority of the publisher and quality of the tweet. The experiments show that all the proposed elements are important and our method greatly outperforms several baseline methods.
Things Fall Apart: Topology Change From Winding Tachyons

We argue that closed string tachyons drive two spacetime topology changing transitions – loss of genus in a Riemann surface and separation of a Riemann surface into two components. The tachyons of interest are localized versions of Scherk-Schwarz winding string tachyons arising on Riemann surfaces in regions of moduli space where string-scale tubes develop. Spacetime and world-sheet renormalization group analyses provide strong evidence that the decay of these tachyons removes a portion of the spacetime, splitting the tube into two pieces. We address the fate of the gauge fields and charges lost in the process, generalize it to situations with weak flux backgrounds, and use this process to study the type 0 tachyon, providing further evidence that its decay drives the theory sub-critical. Finally, we discuss the time-dependent dynamics of this topology-changing transition and find that it can occur more efficiently than analogous transitions on extended supersymmetric moduli spaces, which are limited by moduli trapping.
Plasma Cathepsin S and Cystatin C Levels and Risk of Abdominal Aortic Aneurysm: A Randomized Population–Based Study

BACKGROUND
Human abdominal aortic aneurysm (AAA) lesions contain high levels of cathepsin S (CatS), but are deficient in its inhibitor, cystatin C. Whether plasma CatS and cystatin C levels are also altered in AAA patients remains unknown.


METHODS AND RESULTS
Plasma samples were collected from 476 male AAA patients and 200 age-matched male controls to determine CatS and cystatin C levels by ELISA. Student's t test demonstrated higher plasma levels of total, active, and pro-CatS in AAA patients than in controls (P<0.001). ROC curve analysis confirmed higher plasma total, active, and pro-CatS levels in AAA patients than in controls (P<0.001). Logistic regression suggested that plasma total (odds ratio [OR] = 1.332), active (OR = 1.21), and pro-CatS (OR = 1.25) levels were independent AAA risk factors that associated positively with AAA (P<0.001). Plasma cystatin C levels associated significantly, but negatively, with AAA (OR = 0.356, P<0.001). Univariate correlation demonstrated that plasma total and active CatS levels correlated positively with body-mass index, diastolic blood pressure, and aortic diameter, but negatively with the lowest ankle-brachial index (ABI). Plasma cystatin C levels also correlated negatively with the lowest ABI. Multivariate linear regression showed that plasma total, active, and pro-CatS levels correlated positively with aortic diameter and negatively with the lowest ABI, whereas plasma cystatin C levels correlated negatively with aortic diameter and the lowest ABI, after adjusting for common AAA risk factors.


CONCLUSIONS
Correlation of plasma CatS and cystatin C with aortic diameter and the lowest ABI suggest these serological parameters as biomarkers for human peripheral arterial diseases and AAA.
Engaging citizens: The role of power-sharing institutions

Drawing on established theories of comparative political institutions, we argue that democratic institutions carry important messages that influence mass attitudes and behaviors. Power-sharing political institutions signal to citizens that inclusiveness is an important principle of a country’s democracy and can encourage citizens to participate in politics. Applying multilevel modeling to data from the World Values Survey, we test whether democratic institutions influence political engagement in 34 countries. Further, we examine whether underrepresented groups, specifically women, are differentially affected by the use of power-sharing institutions such that they are more engaged in politics than women in countries with power-concentrating institutions. We find that disproportional electoral rules dampen engagement overall and that gender gaps in political engagement tend to be smaller in more proportional electoral systems, even after controlling for a host of other factors. Power-sharing institutions can be critical for explaining gender differences in political engagement.
Differences in human meibum lipid composition with meibomian gland dysfunction using NMR and principal component analysis.

PURPOSE
Nuclear magnetic resonance (NMR) spectroscopy has been used to quantify lipid wax, cholesterol ester terpenoid and glyceride composition, saturation, oxidation, and CH₂ and CH₃ moiety distribution. This tool was used to measure changes in human meibum composition with meibomian gland dysfunction (MGD).


METHODS
(1)H-NMR spectra of meibum from 39 donors with meibomian gland dysfunction (Md) were compared to meibum from 33 normal donors (Mn).


RESULTS
Principal component analysis (PCA) was applied to the CH₂/CH₃ regions of a set of training NMR spectra of human meibum. PCA discriminated between Mn and Md with an accuracy of 86%. There was a bias toward more accurately predicting normal samples (92%) compared with predicting MGD samples (78%). When the NMR spectra of Md were compared with those of Mn, three statistically significant decreases were observed in the relative amounts of CH₃ moieties at 1.26 ppm, the products of lipid oxidation above 7 ppm, and the =CH moieties at 5.2 ppm associated with terpenoids.


CONCLUSIONS
Loss of the terpenoids could be deleterious to meibum since they exhibit a plethora of mostly positive biological functions and could account for the lower level of cholesterol esters observed in Md compared with Mn. All three changes could account for the higher degree of lipid order of Md compared with age-matched Mn. In addition to the power of NMR spectroscopy to detect differences in the composition of meibum, it is promising that NMR can be used as a diagnostic tool.
Smart Homes for Elderly Healthcare—Recent Advances and Research Challenges

Advancements in medical science and technology, medicine and public health coupled with increased consciousness about nutrition and environmental and personal hygiene have paved the way for the dramatic increase in life expectancy globally in the past several decades. However, increased life expectancy has given rise to an increasing aging population, thus jeopardizing the socio-economic structure of many countries in terms of costs associated with elderly healthcare and wellbeing. In order to cope with the growing need for elderly healthcare services, it is essential to develop affordable, unobtrusive and easy-to-use healthcare solutions. Smart homes, which incorporate environmental and wearable medical sensors, actuators, and modern communication and information technologies, can enable continuous and remote monitoring of elderly health and wellbeing at a low cost. Smart homes may allow the elderly to stay in their comfortable home environments instead of expensive and limited healthcare facilities. Healthcare personnel can also keep track of the overall health condition of the elderly in real-time and provide feedback and support from distant facilities. In this paper, we have presented a comprehensive review on the state-of-the-art research and development in smart home based remote healthcare technologies.
A randomized clinical trial of an individualized home-based exercise programme for women with fibromyalgia.

OBJECTIVE
To determine the efficacy of a 12-week individualized home-based exercise programme on physical functioning, pain severity and psychological distress for women with fibromyalgia (FM).


METHODS
Seventy-nine women with a primary diagnosis of FM were randomized to a 12-week individualized home-based moderate-intensity exercise programme or to a usual care control group. Outcomes were functional capacity (Fibromyalgia Impact Questionnaire), pain severity and psychological distress. Outcomes were measured at study entry, at the end of the 12-week intervention, and at 3 and 9 months following completion of the intervention.


RESULTS
On the basis of intention-to-treat analyses, a significant improvement in functional capacity at 3 and 9 months following treatment for participants in the exercise group who were more functionally disabled at study entry was observed. At both 3 and 9 months post-treatment, the mean estimated benefit of the intervention was more than 10 points [-12.3 (95% CI, -21.9 to -2.8); -10.8 (95% CI, -21.5 to -0.2)]. Compared with the control group, statistically significant improvements in upper body pain were evident in the exercise group at post-treatment. These between-group differences in upper body pain were maintained at 3 and 9 months post-treatment. No statistically significant group differences on lower body pain and psychological distress were found.


CONCLUSIONS
Home-based exercise, a relatively low-cost treatment modality, has the potential to improve important health outcomes in FM.
Self-Organising management of Grid environments

This paper presents basic concepts, architectural principles and algorithms for efficient resource and security management in cluster computing environments and the Grid. The work presented in this paper is funded by BTExacT and the EPSRC project SO-GRM (GR/S21939).
Golden section search over hyper-rectangle: a direct search method

Abstract: This paper generalises the golden section optimal search method to higher dimensional optimisation problem. The method is applicable to a strict quasi-convex function of N-variables over an N-dimensional hyper rectangle. An algorithm is proposed in N-dimension. The algorithm is illustrated graphically in two dimensions and verified through several test functions in higher dimension using MATLAB.
Dietary intake of pollutant aerosols via vegetables influenced by atmospheric deposition and wastewater irrigation.

Pot culture experiments were conducted to study dietary intake of heavy metals via vegetables, spinach (Spinacia oleracea L.), radish (Raphanus sativus L.) and tomato (Lycopersicon esculentum Mill) grown under the influence of atmospheric deposition and wastewater irrigation. The results indicated substantial accumulation of heavy metals in vegetables, which contribute significantly to dietary intake of total heavy metals ranging from 1.34 to 110.40 μg g⁻¹ through leaves (spinach), 1.04 to 105.86 μg g⁻¹ through root (radish) and 0.608 to 82.19 μg g⁻¹ through fruits (tomato). Concentration of Cd, Ni and Pb in vegetables exceeded the safe limits of Prevention of Food Adulteration Act 1954. Health risk index for Cd and Pb exceeded the safe limits set by the United States Environmental Protection Agency. The study indicated that the atmospheric depositions as well as wastewater irrigation have significantly elevated the levels of heavy metals in dietary vegetables presenting a significant threat for the health of users.
Motivational intervention to enhance post-detoxification 12-Step group affiliation: a randomized controlled trial

AIMS
To compare a motivational intervention (MI) focused on increasing involvement in 12-Step groups (TSGs; e.g. Alcoholics Anonymous) versus brief advice (BA) to attend TSGs.


DESIGN
Patients were assigned randomly to either the MI or BA condition, and followed-up at 6 months after discharge.


SETTING AND PARTICIPANTS
One hundred and forty substance use disorder (SUD) patients undergoing in-patient detoxification (detox) in Norway.


MEASUREMENTS
The primary outcome was TSG affiliation measured with the Alcoholics Anonymous Affiliation Scale (AAAS), which combines meeting attendance and TSG involvement. Substance use and problem severity were also measured.


FINDINGS
At 6 months after treatment, compared with the BA group, the MI group had higher TSG affiliation [0.91 point higher AAAS score; 95% confidence interval (CI) = 0.04 to 1.78; P = 0.041]. The MI group reported 3.5 fewer days of alcohol use (2.1 versus 5.6 days; 95% CI = -6.5 to -0.6; P = 0.020) and 4.0 fewer days of drug use (3.8 versus 7.8 days; 95% CI = -7.5 to -0.4; P = 0.028); however, abstinence rates and severity scores did not differ between conditions. Analyses controlling for duration of in-patient treatment did not alter the results.


CONCLUSIONS
A motivational intervention in an in-patient detox ward was more successful than brief advice in terms of patient engagement in 12-Step groups and reduced substance use at 6 months after discharge. There is a potential benefit of adding a maintenance-focused element to standard detox.
The role of MRI in rheumatoid arthritis: research and clinical issues.

PURPOSE OF REVIEW
This review describes the important role of MRI in rheumatoid arthritis (RA), exploring recent reliability and validity work, as well as the current use of MRI in clinical trials and practice.


RECENT FINDINGS
Both bone oedema and erosions on MRI have been confirmed as representing osteitis and cortical bone defects, respectively, adding to what was already known about the validity of contrast enhanced synovium representing synovitis. An increasing number of studies have used MRI as an outcome measure with interest moving from disease-modifying antirheumatic drugs (DMARDs) to biological therapies and a more technical focus on dynamic imaging. In addition, low-field extremity MRI has been developed as a well tolerated, comfortable and convenient method for imaging assessment in clinical practice.


SUMMARY
This review has highlighted both recent research advances as well as the future potential for MRI in RA, with the aim that MRI will become part of standard measures for RA clinical trials. With respect to extremity imaging, further work is required to provide useful clinical algorithms.
An FEM investigation into the behavior of metal matrix composites: tool-particle interaction during orthogonal cutting

An analytical or experimental method is often unable to explore the behaviour of a metal matrix composite (MMC) during machining due to the complex deformation and interactions among particles, tool and matrix. This paper investigates the matrix deformation and tool-particle interactions during machining using the finite element method. Based on the geometrical orientations, the interaction between tool and particle reinforcements was categorized into three scenarios: particles along, above and below the cutting path. The development of stress and strain fields in the MMC was analyzed and physical phenomena such as tool wear, particle debonding, displacements and inhomogeneous deformation of matrix material were explored. It was found that tool-particle interaction and stress/strain distributions in the particles/matrix are responsible for particle debonding, surface damage and tool wear during machining of MMC.