nils-herrmann/clean_scirepeval huggingface dataset:
Modeling human disease using organotypic cultures.
Venue: Current opinion in cell biology

Reliable disease models are needed in order to improve quality of healthcare. This includes gaining better understanding of disease mechanisms, developing new therapeutic interventions and personalizing treatment. Up to date, the majority of our knowledge about disease states comes from in vivo animal models and in vitro cell culture systems. However, it has been exceedingly difficult to model disease at the tissue level. Since recently, the gap between cell line studies and in vivo modeling has been narrowing thanks to progress in biomaterials and stem cell research. Development of reliable 3D culture systems has enabled a rapid expansion of sophisticated in vitro models. Here we focus on some of the latest advances and future perspectives in 3D organoids for human disease modeling.
Human physical activity recognition based on computer vision with deep learning model
Venue: 2016 IEEE International Instrumentation and Measurement Technology Conference Proceedings

Human activity recognition is an active research area in the computer science because it is widely used in the fields of the security monitoring, health assessment, human machine interaction and other human related content searching. In this paper, a computer vision model based on the deep learning algorithm is proposed, which can recognize the human physical activity based on the skeleton data of the human body from the sensor of Microsoft Kinect. This model uses the human skeletons data from the CAD 60 dataset to recognize the human physical activity without using any prior knowledge. It can reduce the works on the stage of data preprocessing and feature extraction. It can also improve the generalization performance and robustness of the model, and give a better understanding of the human physical activity. Different tricks which can improve the performance of the neural networks, such as some regularization methods and other activation functions are tested. Finally, a convolutional neural network is used for the feature extraction, and a multilayer perceptron is used as the following classifier. The model can recognize twelve types of activities and the accuracy rate is 81.8% It demonstrates that it is very effective to use the convolutional neural network to supervised learning and this model applies to human physical activity recognition.
A Critical Review on the Major Conceptual Strands/debates on the Reduced Emission from Deforestation and Forest Degradation (REDD+ and Improved Social Livelihoods

The problem of climate change has attracted different approaches on how best to tackle it. Equally, at the level of theorization and conceptualization, it has attracted a fierce debate on how to interpret, analyze, and suggest the best approach which seems to improve the social livelihoods of the main actors who directly depends on forest resources. This paper intends albeit in a brief manner to synthesis various theoretical and conceptual issues which explicitly or implicitly inform REDD+ as a new sustainable intervention in conserving forest and improving people's social livelihoods. At the same time, each approach is critically analyzed to see its strength and weakness in addressing the key issue of improving social livelihood taking into account power dynamics. And lastly, it points out the conceptual framework which at least illuminates the manner in which to apprehend the power dynamics and agency play out in REDD+ interventions.
Visual inertial direct SLAM
Venue: 2016 IEEE International Conference on Robotics and Automation (ICRA)

The so called direct visual SLAM methods have shown a great potential in estimating a semidense or fully dense reconstruction of the scene, in contrast to the sparse reconstructions of the traditional feature based algorithms. In this paper, we propose for the first time a direct, tightly coupled formulation for the combination of visual and inertial data. Our algorithm runs in real time on a standard CPU. The processing is split in three threads. The first thread runs at frame rate and estimates the camera motion by a joint non linear optimization from visual and inertial data given a semidense map. The second one creates a semidense map of high gradient areas only for camera tracking purposes. Finally, the third thread estimates a fully dense reconstruction of the scene at a lower frame rate. We have evaluated our algorithm in several real sequences with ground truth trajectory data, showing a state of the art performance.
Multi objective parametric query optimization
Venue: SGMD

Classical query optimization compares query plans according to one cost metric and associates each plan with a constant cost value. In this paper, we introduce the multi objective parametric query optimization (MPQO) problem where query plans are compared according to multiple cost metrics and the cost of a given plan according to a given metric is modeled as a function that depends on multiple parameters. The cost metrics may, for instance, include execution time or monetary fees; a parameter may represent the selectivity of a query predicate that is unspecified at optimization time. MPQO generalizes parametric query optimization (which allows multiple parameters but only one cost metric) and multi objective query optimization (which allows multiple cost metrics but no parameters) We formally analyze the novel MPQO problem and show why existing algorithms are inapplicable. We present a generic algorithm for MPQO and a specialized version for MPQO with piecewise linear plan cost functions. We prove that both algorithms find all relevant query plans and experimentally evaluate the performance of our second algorithm in multiple scenarios.
Statistical analysis and improvement of coherent to diffuse power ratio estimators for dereverberation
Venue: 2016 IEEE International Workshop on Acoustic Signal Enhancement (IWAENC)

Dereverberation methods based on coherent to diffuse power ratio (CDR) estimates exploit the spatial properties of signals to suppress late reverberation components. Naturally, the quality of the CDR estimate has a major effect on the quality of the dereverberated signals. This paper presents a statistical study of the performance of state of the art CDR estimators under a Gaussian signal model. The study reveals that the variance of the magnitude of the spatial coherence estimate is the major cause for the degradation of known CDR estimators, while the variance of the phase has only limited impact. Moreover, the variance has more impact on direction of arrival (DOA) independent CDR estimators than on DOA dependent estimators. Accordingly, we propose a cepstrum thresholding technique to reduce the variance of the spatial coherence estimate. Experimental results show that better performance can be achieved for dereverberation when the proposed spatial coherence method is applied to CDR estimators, especially for the DOA independent estimators.
Weaving the Fabric of Public Policies: Comparing and Integrating Contemporary Frameworks for the Study of Policy Processes

For close to three decades multiple frameworks of policy making have served as competitive characterizations of policy processes. All claim to provide accounts that capture diverse factors such as changing governance norms, actors and ideas which drive programme interventions and policy outputs. Paradoxically, the resilience of different models such as the policy cycle framework and the multiple streams framework has been accompanied by numerous critiques that they are "incomplete" and even divorced from the real world. This article presents an effort to synthesize and reconcile these frameworks in which the appeal and strengths of each can be retained while going some way to overcoming their weaknesses and limitations. It does so through the introduction of an integrative metaphor for policy making what Wayne Parsons termed "weaving" which can be applied to all stages of public policy, and is flexible enough to cope with issues such as power, complexity and critical junctures while reconciling different groupings and sets of actors highlighted as significant policy players in earlier models. It elaborates this framework before applying it by way of illustration to one of the most controversial policy initiatives in modern British history: the 1989 93 poll tax. The article and case study highlight the potential for its general application in policy studies.
Investigation of electronic structure, magnetic properties and thermal properties of the new half metallic ferromagnetic full Heusler alloys Cr2GdSi1 xGex: An ab initio study

We have studied the structural, electronic, elastic, magnetic, thermal and thermodynamic properties of the quaternary Heusler alloys Cr2GdSi1 xGex (x 0, 0.25, 0.5, 0.75, 1) with the linearized augmented plane wave method based on density functional theory and implemented in WIEN2K code. For exchange correlation potential, we have used the generalized gradient approximation (GGA) within the Perdew Burke Ernzerhof (PBE 96) parameterization. Our results provide a theoretical study for the mixed Heusler Cr2GdSi1 xGex (0
Modeling Autobiographical Memory in Human Like Autonomous Agents
Venue: AAMAS

Although autobiographical memory is an important part of the human mind, there has been little effort on modeling autobiographical memory in autonomous agents. With the motivation of developing human like intelligence, in this paper, we delineate our approach to enable an agent to maintain memories of its own and to wander in mind. Our model, named Autobiographical Memory Adaptive Resonance Theory network (AM ART) is designed to capture autobiographical memories, comprising pictorial snapshots of one's life experiences together with the associated context, namely time, location, people, activity, and emotion. In terms of both network structure and dynamics, AM ART coincides with the autobiographical memory model established by the psychologists, which has been supported by neural imaging evidence. Specifically, the bottom up memory search and the top down memory readout operations of AM ART replicate how the brain encodes and retrieves autobiographical memories. Furthermore, the wandering in reminiscence function of AM ART mimics how human wanders in mind. For evaluations, we conducted experiments on a data set collected from the public domain to test the performance of AM ART in response to exact, partial, and noisy memory retrieval cues. Moreover, our statistical analysis shows that AM ART can simulate the phenomenon of wandering in reminiscence.
High efficiency integrated readout circuit for single photon avalanche diode arrays in fluorescence lifetime imaging.
Venue: The Review of scientific instruments

In recent years, lifetime measurements by means of the Time Correlated Single Photon Counting (TCSPC) technique have led to a significant breakthrough in medical and biological fields. Unfortunately, the many advantages of TCSPC based approaches come along with the major drawback of a relatively long acquisition time. The exploitation of multiple channels in parallel could in principle mitigate this issue, and at the same time it opens the way to a multi parameter analysis of the optical signals, e.g. as a function of wavelength or spatial coordinates. The TCSPC multichannel solutions proposed so far, though, suffer from a tradeoff between number of channels and performance, and the overall measurement speed has not been increased according to the number of channels, thus reducing the advantages of having a multichannel system. In this paper, we present a novel readout architecture for bi dimensional, high density Single Photon Avalanche Diode (SPAD) arrays, specifically designed to maximize the throughput of the whole system and able to guarantee an efficient use of resources. The core of the system is a routing logic that can provide a dynamic connection between a large number of SPAD detectors and a much lower number of high performance acquisition channels. A key feature of our smart router is its ability to guarantee high efficiency under any operating condition.
Latent heat storage in building elements: A systematic review on properties and contextual performance factors

A systematic review of latent heat storage in building elements was conducted to establish the current knowledge base and reveal key design and performance factors that could be used to define technologies available for immediate implementation and for specific applications. All relevant literature published by April 2014 was critically evaluated and a data extraction procedure was used to organise, analyse and report design and performance parameters of Phase Change Material (PCM) elements. The review of a total of 120 papers revealed that published information on these aspects is diverse and in many cases insufficient. The diversity of test conditions and variety of reported values indicate that physical properties and performance data concerning materials and complete PCM elements are not directly comparable. Therefore matching technologies and applications for specific climates and building typologies is not possible solely through published information. However evidence was collected which shows that, with appropriate design, PCM elements can contribute to reducing loads and achieving energy savings in buildings, while securing a comfortable indoor environment. Key design factors to this end were found to be the climate and target season, the design of appropriate controls for active and passive systems used in combination with the PCM elements and cost related factors. The review also mapped the research foci to date, revealing the range of variations previously examined and potential research gaps worth pursuing in the future.
Research on simulation system of welding robot in Unity3d
Venue: VRCAI

In industrial application and teaching training, robot simulation plays an important role. In this paper, the method of system development is discussed. First the robot model and simulation scene model are built. And the kinematics model is established including positive and inverse kinematics. Then two kinds of path, line and circle, are planned about positon and orientation as well. And the pose of torch is discussed for welding. With the help of Unity3d's powerful engine, simulation effects are implemented. Finally, a welding robot simulation system is set up in Unity3d based on Virtual Reality technology. The simulation results show that the system is well applied in engineering and training.
Development of puzzle game about children's etiquette based on Unity3D
Venue: 2016 17th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)

Because of the development of the technology, people's material and cultural conditions is developing faster and faster, life conditions is getting better and better living conditions. However, the improvement of inherent virtue of people has failed to match the growing material and cultural criteria. Many parents are busy in work, leading to many children cannot obtain a culture etiquette and upbringing at an early age, children cannot treat people how to do things correctly, this is more harm than good for children's emotional intelligence development and future life. But the growing material conditions has created a possibility for the popularity of computer games, children can come into contact with computers and other modern electronic products when they are very small, which also getting children premature contact with, even hooked on computer games. So game developers can combine computer games with children etiquette education, let the children play games, but also by the influence of culture and etiquette. This game is arranged two scenes which are sitting room scene and bus scene, the player can choose a scene casually. After entering the game scenes, there will be a plot unfolds, players need to react differently and politely according to different scenarios before clearance. Meanwhile, the game also leave interface for future game developers, the child's answer can be speech recognized in the future.
Designing of a study game of the mathematics probability in middle school based on Unity3D

The emergence of educational games has greatly changed the students' learning style, so that students can combine learning and entertainment, so as to improve the learning interest and efficiency. The article uses 3ds Max as the model design tool to build three dimensional game scene and props, takes Unity3D as the development platform, uses JavaScript to program, designs the three dimensional study game of the mathematics probability in middle school.
Design and Implementation of 3D Virtual Digital Campus Based on Unity3D
Venue: 2016 Eighth International Conference on Measuring Technology and Mechatronics Automation (ICMTMA)

Based on the Unity3D multi platform to establish a three dimensional virtual digital campus system, has a strong practical. Using the Unity3D engine to realize the virtual digital campus scene design, access and interactive roaming and other functions, the need to achieve a combination of various simulation effects. The 3D Virtual Digital Campus Based on Unity3D development system has high efficiency and low maintenance cost, which has obvious advantages. This paper will mainly elaborate the principle of system design, design of virtual scene and the practice of the system.
Epidemiological pathology of Tau in the ageing brain: application of staging for neuropil threads (BrainNet Europe protocol) to the MRC cognitive function and ageing brain study
Venue: Acta neuropathologica communications

IntroductionDeposition of abnormally phosphorylated tau (phospho tau) occurs in Alzheimer'sdisease but also with brain ageing. The Braak staging scheme focused on neurofibrillary tangles, butabundant p tau is also present in neuropil threads, and a recent scheme has been proposed by theBrainNet Europe consortium for staging tau pathology based on neuropil threads. We determined therelationship of threads to tangles, and the value of staging for threads in an unselected population representative ageing brain cohort. We also determined the prevalence of astroglial tau pathologies, and their relationship to neuronal tau. Phospho tau pathology was determined by immunohistochemistry (AT8 antibody) in the MRC CFAS neuropathology cohort. Neuropil threads were staged using the BrainNet Europe protocol for tau pathology, and compared with Braak tangle stages. Astroglial tau pathology was assessed in neo cortical, mesial temporal and subcortical areas.ResultsCases conformed well to the hierarchical neuropil threads staging of the BrainNet Europe protocol and correlated strongly with Braak staging (r=0.84, p 0.001) Based on the areas under the receiver operator curves (AUC) incorporating either threads or tangle staging significantly improved dementia case identification to a similar degree over age alone (Braak stage X2(1)=10.1, p=0.002; BNE stage X2(1)=9.7, p=0.002) Thorn shaped astrocytes, present in 40 of cases, were most common in mesial temporal lobe, then brainstem, and were associated with subpial tau positive neurites (mesial temporal: X2(1)=61.3, p 0.001; brainstem: X2(1)=47.9, p 0.001) Adding thorn astrocytes did not improve dementia prediction (AUC: X2(1)=0.77, p=0.381) but there was a weak relationship between numbers of areas involved and staging for threads or tangles (r=0.17, p=0.023) Neuropil threads develop hierarchically in parallel with neurofibrillary tangles.ConclusionsThe BrainNet Europe staging protocol is straightforward to apply, and offers similar predictive value for dementia to Braak tangle staging. Astroglial tauopathy, particularly thorn shaped astrocyte formation, does not relate to dementia status, but the association with phospho tau neurites may suggest a pathogenic relationship to neuronal tau pathology.
Load frequency controller design of a two area system composing of PV grid and thermal generator via firefly algorithm
Venue: Neural Computing and Applications

In this paper, firefly algorithm (FA) for optimal tuning of PI controllers for load frequency control of hybrid system composing of photovoltaic (PV) system and thermal generator is introduced. Also, maximum power point tracking of PV is considered in the design process. The block diagram of the hybrid system is performed. To robustly tune the parameters of controllers, a time domain based objective function is established which is solved by the FA. Simulation results are presented to show the improved performance of the suggested FA based controllers compared with genetic algorithm (GA) These results show that the proposed controllers present better performance over GA in terms of settling times and different indices.
Development of a competitive and collaborative platform for block diagram and resistive circuit reduction in a basic electrical engineering course
Venue: 2016 IEEE Global Engineering Education Conference (EDUCON)

Competition and collaboration are two universal ingredients in all human cultures. Competition has been observed over time as a phenomenon that has helped people achieve the very best of their potentials in their various fields. Competition has also helped individuals achieve feats they would not have ordinarily achieved as they are pushed beyond their limits. The same can also be said of cooperation and collaboration, which can be used to achieve specific goals or objectives. Hence, both competition and collaboration can be vital in creating a healthy learning process among students. This paper discusses a competitive and collaborative platform on the learning process for two selected online courses in Electrical Engineering. Using a platform developed in LabVIEW programming language, a community of students were encouraged to compete online as they try to reduce block diagrams of subsystems in Control Engineering as well as reduce given Series Parallel Resistor Circuits in the shortest time and amount of steps possible. At the end of each trial, students can view the finish time of other students and can share, online, their individual solutions with the community as well as discuss ideas such as reduction techniques they find most expedient via a public online notepad. This creates a means of learning from the community. The platform helps to passively induce a competitive and collaborative perspective in the learning pathway of students, thereby improving the interest and experience of students in the selected subject areas. The platform uses an online server to maintain communications from all the students in their various locations. Students can view the timed performance of their counterparts on a leadership board thereby engendering induced competition in the learning community. The instructor or administrator can also monitor activities in the community from a server portal.