nils-herrmann/clean_scirepeval huggingface dataset:
Trial Sequential Analysis in systematic reviews with meta-analysis

Most meta-analyses in systematic reviews, including Cochrane ones, do not have sufficient statistical power to detect or refute even large intervention effects. This is why a meta-analysis ought to be regarded as an interim analysis on its way towards a required information size. The results of the meta-analyses should relate the total number of randomised participants to the estimated required meta-analytic information size accounting for statistical diversity. When the number of participants and the corresponding number of trials in a meta-analysis are insufficient, the use of the traditional 95% confidence interval or the 5% statistical significance threshold will lead to too many false positive conclusions (type I errors) and too many false negative conclusions (type II errors).



We developed a methodology for interpreting meta-analysis results, using generally accepted, valid evidence on how to adjust thresholds for significance in randomised clinical trials when the required sample size has not been reached.



The Lan-DeMets trial sequential monitoring boundaries in Trial Sequential Analysis offer adjusted confidence intervals and restricted thresholds for statistical significance when the diversity-adjusted required information size and the corresponding number of required trials for the meta-analysis have not been reached.  We define the required information size and the corresponding number of required trials in a meta-analysis and the diversity (D2) measure of heterogeneity. We explain the reasons for using Trial Sequential Analysis of meta-analysis when the actual information size fails to reach the required information size. We present examples drawn from traditional meta-analyses using unadjusted naïve 95% confidence intervals and 5% thresholds for statistical significance. Spurious conclusions in systematic reviews with traditional meta-analyses can be reduced using Trial Sequential Analysis. Several empirical studies have demonstrated that the Trial Sequential Analysis provides better control of type I errors and of type II errors than the traditional naïve meta-analysis.



Trial Sequential Analysis represents analysis of meta-analytic data, with transparent assumptions, and better control of type I and type II errors than the traditional meta-analysis using naïve unadjusted confidence intervals.
Exploit the Unknown Gradually: One-Shot Video-Based Person Re-identification by Stepwise Learning

We focus on the one-shot learning for video-based person re-Identification (re-ID). Unlabeled tracklets for the person re-ID tasks can be easily obtained by preprocessing, such as pedestrian detection and tracking. In this paper, we propose an approach to exploiting unlabeled tracklets by gradually but steadily improving the discriminative capability of the Convolutional Neural Network (CNN) feature representation via stepwise learning. We first initialize a CNN model using one labeled tracklet for each identity. Then we update the CNN model by the following two steps iteratively: 1. sample a few candidates with most reliable pseudo labels from unlabeled tracklets; 2. update the CNN model according to the selected data. Instead of the static sampling strategy applied in existing works, we propose a progressive sampling method to increase the number of the selected pseudo-labeled candidates step by step. We systematically investigate the way how we should select pseudo-labeled tracklets into the training set to make the best use of them. Notably, the rank-1 accuracy of our method outperforms the state-of-the-art method by 21.46 points (absolute, i.e., 62.67% vs. 41.21%) on the MARS dataset, and 16.53 points on the DukeMTMC-VideoReID dataset1.
A Compact Dual-Band Dielectric Resonator Antenna Using a Parasitic Slot

A compact dual-band dielectric resonator antenna (DRA) using a parasitic c-slot fed by a microstrip line is proposed. In this configuration, the DR performs the functions of an effective radiator and the feeding structure of the parasitic c-slot in the ground plane. By optimizing the proposed structure parameters, the structure resonates at two different frequencies. One is from the DRA with the broadside patterns and the other from the c-slot with the dipole-like patterns. In order to determine the performance of varying design parameters on bandwidth and resonance frequency, the parametric study is carried out using simulation software High-Frequency Structure Simulator and experimental results. The measured and simulated results show excellent agreement.
a.SCAtch - A Sketch-Based Retrieval for Architectural Floor Plans

Architects’ daily routine means working with drawings. They use either a pen or a computer sketching their ideas or drawing to scale. When beginning a new project they often have to search for similar projects in the past. In this paper a sketch-based approach is proposed to query the floor plan repository. The user searches for semantically similar floor plans just by drawing the new plan. An algorithm extracts the semantic structure sketched by the architect on DFKI’s Touch & Write table and compares the structure of the sketch with the ones from the floor plan repository. The a SCatch system enables the user to easily access knowledge from past projects. While in the current prototype only sketches with a predefined structure are recognized, we will extend the system to work with normal floor plans.
Lateral flow assay with near-infrared dye for multiplex detection.

Lateral flow assays (LFAs) are popular point-of-care diagnostic tools because they are rapid and easy to use. Nevertheless, they often lack analytical sensitivity and quantitative output and may be difficult to multiplex, limiting their usefulness in biomarker measurement. As a proof-of-concept study, we detail the design of a quantitative, multiplex LFA with readily available near-infrared (NIR) detection to improve analytical sensitivity.



NIR dye was conjugated to selected antibodies and incorporated into LFAs. We used singleplex, optimized NIR-LFAs to measure interleukin (IL)-6 from 0 to 200 pg/mL and developed duplex assays to simultaneously measure IL-6 from 0 to 100 pg/mL (0 to 4.5 pmol/L) and C-reactive protein (CRP) from 50 to 2500 ng/mL (0.4 to 20 nmol/L) on a single test strip. Assays were tested on 60 different spiked samples and compared to ELISA results.



NIR-LFAs detected IL-6 in a 10% plasma matrix with a limit of detection of 4 pg/mL (182 fmol/L) and a CV <7%. Duplex NIR-LFAs quantitatively measured IL-6 and CRP concentrations simultaneously. Values strongly correlated to ELISA measurements, with R(2) values of 0.9825 and 0.9711 for IL-6 and CRP, respectively.



NIR-LFAs exhibit quantitative measurement at pg/mL concentrations owing to a high signal-to-background ratio and robust detection antibody clearance through the test strip. Moreover, NIR-LFAs are able to detect molecules present at vastly different concentrations in multiplex format and compare favorably to ELISAs. LFAs with direct NIR detection may be a valuable tool for biomarker evaluation in the point-of-care setting.
Managing diversity through human resource management : an international perspective and conceptual framework

This paper critically reviews the literature on managing diversity through human resource management (HRM). We discuss the major issues and objectives of managing diversity and examine the state of human resource diversity management practices in organizations. Our review shows that inequality and discrimination still widely exist and HRM has focused mainly on compliance with equal employment opportunity (EEO) and affirmative action (AA) legislation. Less attention has been paid to valuing, developing and making use of diversity. Our review reveals limited literature examining how diversity is managed in organizations through effective human resource management. We develop a framework that presents strategies for HR diversity management at the strategic, tactical and operational levels. Our review also discusses the implications for practice and further research.
Single axis solar tracker actuator location analysis

Current trends in energy power generation are leading efforts related to the development of more reliable, sustainable sources and technologies for energy harvesting. Solar energy is one of these renewable energy resources, widely available in nature. Most of the solar panels used today to convert solar energy into chemical energy, and then to electrical energy, are stationary. Energy efficiency studies have shown that more electrical energy can be retrieved from solar panels if they are organized in arrays and then placed on a solar tracker that can then follow the sun as it moves during the day from east to west, and as it moves from north to south during the year, as seasons change. Adding more solar panels to solar tracker structures will improve its yield. It would also add more challenges when it comes to managing the overall weight of such structures, and their strength and reliability under different weather conditions, such as wind, changes in temperature, and atmospheric conditions. Hence, careful structural design and simulation is needed to establish the most optimal parameters in order for solar trackers to withstand all environmental conditions and to function with a high reliability for long periods of time.
Honeybees - bioindicators for environmental quality

ZhelyaZkova, I., 2012. honeybees – bioindicators for environmental quality. Bulg.  The objective of the study is to use honeybees (Apis mellifera l.) as bioindicators for environmental status in the region of Sarnena Sredna gora, county of Stara Zagora. The study comprises six villages (yagoda, Borilovo, Novo selo, Sulitsa, ostra mogila, kanchevo), located on the territory of Sarnena Sredna gora close to the military range of Zmeyovo. In each village, bee samples were taken and 56 samples of whole bees and fecal mass were prepared during the bee season of 2010. The content of copper, zinc, lead, cadmium, cobalt, nickel, manganese and iron was traced in the bee body and in excrements. The analysis was carried out in the scientific laboratory of Trakia University – Stara Zagora through atomic absorption spectrometry according to ISo 11047. The results have been statistically processed (excel software). Maximum or relatively high values for content of the studied heavy metals and metalloids in the body and fecal mass of bees from the villages included in the study have been found, which makes it possible to comment a possible anthropogenic effect in the area of Sarnena Sredna gora, Zmeyovo military range. higher content of the studied heavy metals and metalloids in excrements compared to the body of bees has been found, which accounts for the biobarrier function of the bee organism. The elements nickel, cadmium, cobalt and lead are accumulated at the highest degree in the bee fecal mass. The results obtained make it possible to assume that honeybees (Apis mellifera L.) respond to changes in their environment and in particular to increased quantities of heavy metals in soil, air, plants. That makes them a reliable indicator and allows their use in biomonitoring of the environment.
Flexible spiral antenna with microstrip tapered infinite balun for wearable applications

In this paper we introduce a flexible, side-fed, ultra-wideband, spiral antenna with an integrated microstrip tapered infinite balun operating from 1-5GHz. It was fabricated using Rogers 5880 subtrate and specially coated to prevent oxidization. The simulation and measurements match quite well with S11 below -10dB throughout the frequency range and gain of close to 5dB and average efficiency of 65%. Most importantly, this antenna does not have an obtrusive center feed, and instead has a side feed, is flexible, compact, rendering many possible wearable antenna applications.
Control for Robotic Manipulators with Proportional Integral Derivative & Computed Torque Control

Inspite of long years of research, problem of manipulator path tracking control is the thrust area for researchers to work upon. Non-linear systems like manipulator are multi-input-multi-output, non-linear and time variant complex problem. A number of different approaches presently followed for the control of manipulator vary from classical PID (Proportional Integral Derivative) to CTC (Computed Torque Control) control techniques. This paper presents design and implementation of PID and CTC controller for robotic manipulator. Comparative study of simulated results of conventional controllers, like PID and CTC are also shown. Tracking performance and error comparison graphs are presented to show the performance of the proposed controllers.
Interpolation for Polygon Texture Mapping and Shading

A simple, fast method is presented for the interpolation of texture coordinates and shading parameters for polygons viewed in perspective. The method has application in scan conversion algorithms like z-bu er and painter's algorithms that perform screen space interpolation of shading parameters such as texture coordinates, colors, and normal vectors. Some previous methods perform linear interpolation in screen space, but this is rotationally variant, and in the case of texture mapping, causes a disturbing \rubber sheet" e ect. To correctly compute the nonlinear, projective transformation between screen space and parameter space, we use rational linear interpolation across the polygon, performing several divisions at each pixel. We present simpler formulas for setting up these interpolation computations, reducing the setup cost per polygon to nil and reducing the cost per vertex to a handful of divisions.  incremental, perspective, projective, a ne.
Two Phases of V1 Activity for Visual Recognition of Natural Images

Present theories of visual recognition emphasize the role of interactive processing across populations of neurons within a given network, but the nature of these interactions remains unresolved. In particular, data describing the sufficiency of feedforward algorithms for conscious vision and studies revealing the functional relevance of feedback connections to the striate cortex seem to offer contradictory accounts of visual information processing. TMS is a good method to experimentally address this issue, given its excellent temporal resolution and its capacity to establish causal relations between brain function and behavior. We studied 20 healthy volunteers in a visual recognition task. Subjects were briefly presented with images of animals (birds or mammals) in natural scenes and were asked to indicate the animal category. MRI-guided stereotaxic single TMS pulses were used to transiently disrupt striate cortex function at different times after image onset (SOA). Visual recognition was significantly impaired when TMS was applied over the occipital pole at SOAs of 100 and 220 msec. The first interval has consistently been described in previous TMS studies and is explained as the interruption of the feedforward volley of activity. Given the late latency and discrete nature of the second peak, we hypothesize that it represents the disruption of a feedback projection to V1, probably from other areas in the visual network. These results provide causal evidence for the necessity of recurrent interactive processing, through feedforward and feedback connections, in visual recognition of natural complex images.
Neural-network approximation of piecewise continuous functions: application to friction compensation

One of the most important properties of neural nets (NNs) for control purposes is the universal approximation property. Unfortunately,, this property is generally proven for continuous functions. In most real industrial control systems there are nonsmooth functions (e.g., piecewise continuous) for which approximation results in the literature are sparse. Examples include friction, deadzone, backlash, and so on. It is found that attempts to approximate piecewise continuous functions using smooth activation functions require many NN nodes and many training iterations, and still do not yield very good results. Therefore, a novel neural-network structure is given for approximation of piecewise continuous functions of the sort that appear in friction, deadzone, backlash, and other motion control actuator nonlinearities. The novel NN consists of neurons having standard sigmoid activation functions, plus some additional neurons having a special class of nonsmooth activation functions termed "jump approximation basis function." Two types of nonsmooth jump approximation basis functions are determined- a polynomial-like basis and a sigmoid-like basis. This modified NN with additional neurons having "jump approximation" activation functions can approximate any piecewise continuous function with discontinuities at a finite number of known points. Applications of the new NN structure are made to rigid-link robotic systems with friction nonlinearities. Friction is a nonlinear effect that can limit the performance of industrial control systems; it occurs in all mechanical systems and therefore is unavoidable in control systems. It can cause tracking errors, limit cycles, and other undesirable effects. Often, inexact friction compensation is used with standard adaptive techniques that require models that are linear in the unknown parameters. It is shown here how a certain class of augmented NN, capable of approximating piecewise continuous functions, can be used for friction compensation.
A real-time logo detection system using data offloading on mobile devices

In the past few years, mobile augmented reality (AR) has attracted a great deal of attention. It presents us a live, direct or indirect view of a real-world environment whose elements are augmented (or supplemented) by computer-generated sensory inputs such as sound, video, graphics or GPS data. Also, deep learning has the potential to improve the performance of current AR systems. In this paper, we propose a distributed mobile logo detection framework. Our system consists of mobile AR devices and a back-end server. Mobile AR devices can capture real-time videos and locally decide which frame should be sent to the back-end server for logo detection. The server schedules all detection jobs to minimise the maximum latency. We implement our system on the Google Nexus 5 and a desktop with a wireless network interface. Evaluation results show that our system can detect the view change activity with an accuracy of 95:7% and successfully process 40 image processing jobs before deadline. ARTICLE HISTORY Received 6 June 2018  June 2018
Conceptual Partitioning: An Efficient Method for Continuous Nearest Neighbor Monitoring

Given a set of objects P and a query point q, a k nearest neighbor (k-NN) query retrieves the k objects in P that lie closest to q. Even though the problem is well-studied for static datasets, the traditional methods do not extend to highly dynamic environments where multiple continuous queries require real-time results, and both objects and queries receive frequent location updates. In this paper we propose conceptual partitioning (CPM), a comprehensive technique for the efficient monitoring of continuous NN queries. CPM achieves low running time by handling location updates only from objects that fall in the vicinity of some query (and ignoring the rest). It can be used with multiple, static or moving queries, and it does not make any assumptions about the object moving patterns. We analyze the performance of CPM and show that it outperforms the current state-of-the-art algorithms for all problem settings. Finally, we extend our framework to aggregate NN (ANN) queries, which monitor the data objects that minimize the aggregate distance with respect to a set of query points (e.g., the objects with the minimum sum of distances to all query points).
Maxillary molar and premolar indices in North Indians: A Dimorphic Study

Tooth morphometry is known to be influenced by cultural, environmental and racial factors. Tooth size standards can be used in age and sex determination. One hundred models (50 males & 50 females) of normal occlusion were evaluated and significant correlations (p<0.001) were found to exist between the combined maxillary incisor widths and the maxillary intermolar and interpremolar arch widths. The study establishes the morphometric criterion for premolar and molar indices and quantifies the existence of a statistically significant sexual dimorphism in arch widths (p<0.02).  Teeth are an excellent material in living and non-living populations for anthropological, genetic, odontologic and forensic investigations 1 .Their morphometry is known to be influenced by cultural, environmental and racial factors. The variations in tooth form are a common occurrence & these can be studied by measurements. Out of the two proportionswidth and length, the former is considered to be more important 2 . Tooth size standards can be used in age and sex determination 3 . Whenever it is possible to predict the sex, identification is simplified because then only missing persons of one sex need to be considered. In this sense identification of sex takes precedence over age 4 . Various features like tooth morphology and crown size are characteristic for males and females 5 .The present study on the maxillary arch takes into account the premolar arch width, molar arch width and the combined width of the maxillary central incisors in both the sexes. Pont's established constant ratio's between tooth sizes and arch widths in French population which came to be known as premolar and molar indices 6 .In the ideal dental arch he concluded that the ratio of combined incisor width to transverse arch width was .80 in the premolar area and .64 in the molar area. There has been a recent resurgence of interest in the clinical use of premolar and molar indices for establishing dental arch development objectives 7 . The present study was conducted to ascertain whether or not Pont's Index can be used reliably on north Indians and to establish the norms for the same.  One hundred subjects, fifty males and fifty females in the age group of 17-21 years were selected for the study as attrition is considered to be minimal for this age group. The study was conducted on the students of Sudha Rustagi College of Dental Sciences & Research, Faridabad, Haryana.  Healthy state of gingival and peridontium.
On the Complexity of Value Iteration

Value iteration is a fundamental algorithm for solving Markov Decision Processes (MDPs). It computes the maximal n-step payoff by iterating n times a recurrence equation which is naturally associated to the MDP. At the same time, value iteration provides a policy for the MDP that is optimal on a given finite horizon n. In this paper, we settle the computational complexity of value iteration. We show that, given a horizon n in binary and an MDP, computing an optimal policy is EXPTIME-complete, thus resolving an open problem that goes back to the seminal 1987 paper on the complexity of MDPs by Papadimitriou and Tsitsiklis. As a stepping stone, we show that it is EXPTIME-complete to compute the n-fold iteration (with n in binary) of a function given by a straight-line program over the integers with max and + as operators.
Capital Flows and the Risk-Taking Channel of Monetary Policy

This paper examines the relationship between low interests maintained by advanced economy central banks and credit booms in emerging economies. In a model with crossborder banking, low funding rates increase credit supply, but the initial shock is amplified through the “risk-taking channel” of monetary policy where greater risk-taking interact with dampened measured risks that are driven by currency appreciation to create a feedback loop. In an empirical investigation using VAR analysis, we find that expectations of lower short-term rates dampens measured risks and stimulate cross-border banking sector capital flows.