Miracle-dz/UniFAR-FTUs huggingface dataset:
Eyes-Free Target Acquisition in Interaction Space around the Body for Virtual Reality

Eyes-free target acquisition is a basic and important human ability to interact with the surrounding physical world, relying on the sense of space and proprioception. In this research, we leverage this ability to improve interaction in virtual reality (VR), by allowing users to acquire a virtual object without looking at it. We expect this eyes-free approach can effectively reduce head movements and focus changes, so as to speed up the interaction and alleviate fatigue and VR sickness. We conduct three lab studies to progressively investigate the feasibility and usability of eyes-free target acquisition in VR. Results show that, compared with the eyes-engaged manner, the eyes-free approach is significantly faster, provides satisfying accuracy, and introduces less fatigue and sickness; Most participants (13/16) prefer this approach. We also measure the accuracy of motion control and evaluate subjective experience of users when acquiring targets at different locations around the body. Based on the results, we make suggestions on designing appropriate target layout and discuss several design issues for eyes-free target acquisition in VR.
Isobolographic Analysis of Interaction for Three-Drug Combination of Carbamazepine, Phenobarbital and Topiramate in the Mouse Maximal Electroshock-Induced Seizure Model

Background/Aims: To characterize the anticonvulsant effects of a combination of 3 antiepileptic drugs (AEDs; i.e. carbamazepine (CBZ), phenobarbital (PB) and topiramate (TPM)) at the fixed-ratio of 1:1:1 in the mouse maximal electroshock (MES)-induced seizure model. Methods: Tonic hind limb extension (seizure activity) was evoked in adult male albino Swiss mice by a current (sine-wave, 25 mA, 500 V, 50 Hz, 0.2 s stimulus duration) delivered via auricular electrodes. Type I isobolographic analysis for parallel dose-response relationship curves (DRRCs) was used to analyze the 3-drug combination. Results: In the mouse MES model, all the studied AEDs (i.e. CBZ, PB and TPM) administered singly had their DRRCs parallel to each other. With type I isobolography for parallel DRRCs, a combination of CBZ, PB and TPM at the fixed-ratio of 1:1:1 exerted supra-additive (synergistic) interaction in the mouse MES model. Conclusions: Synergistic interaction among CBZ, PB and TPM at the fixed-ratio of 1:1:1 against MES-induced seizures is worthy of consideration in further clinical settings. All detailed calculations required to perform type I isobolographic analysis for the 3-drug combination were presented.
Implications of Limiting CO2 Concentrations for Land Use and Energy

The Power of Green Carbon dioxide is produced both by fossil fuel burning and by deforestation and other land-use changes. Limiting both sources of CO2 is necessary if we are to curb global warming. Wise et al. (p. 1183) use an integrated assessment model to explore the consequences of limiting atmospheric CO2 concentrations at levels between 450 and 550 parts per million through a combination of fossil-fuel emissions reductions and land-use modification. Land-use modification strategies reduce the cost of limiting atmospheric CO2 concentrations, but can make crop prices rise and transform human diets, for example, when people consume less beef and other carbon-intensive protein sources. The rate at which crop productivity is improved has a strong influence on emissions from land-use change. Thus, the technology used for growing crops is potentially as important for limiting atmospheric CO2 as are approaches like CO2 capture and storage. Technologies for growing crops are potentially as important for limiting the concentration of atmospheric CO2 as are those for capture and storage. Limiting atmospheric carbon dioxide (CO2) concentrations to low levels requires strategies to manage anthropogenic carbon emissions from terrestrial systems as well as fossil fuel and industrial sources. We explore the implications of fully integrating terrestrial systems and the energy system into a comprehensive mitigation regime that limits atmospheric CO2 concentrations. We find that this comprehensive approach lowers the cost of meeting environmental goals but also carries with it profound implications for agriculture: Unmanaged ecosystems and forests expand, and food crop and livestock prices rise. Finally, we find that future improvement in food crop productivity directly affects land-use change emissions, making the technology for growing crops potentially important for limiting atmospheric CO2 concentrations.
Transformation of a closed 3D triangular mesh to a quadrilateral mesh based on feature edges

Summary In this paper, we propose a method of applying the Q-Morph to the closed three-dimensional triangular mesh. The Q-Morph is the method in order to transform the triangular mesh to the quadrilateral mesh. The Q-morph begins quadrilateral transformation from the initial front edges which are usually the boundary of the 2D domain. Also, the Q-Morph can be applied to the 3D domain. But, the closed 3D triangular mesh does not contain any boundary edges which can be the initial front edges. Because of this reason, the Q-Morph cannot be applied directly to the closed 3D triangular mesh. The initial front edges must be the path of the line segments of which each line segment appears as the edge of the mesh. Furthermore, the shape of converted quadrilateral heavily depends on the initial front edges. So, the initial front edge should be generated by taking the change of the shape into account for effective quadrilateral transformation. Our proposal is to extract feature edges from input triangular mesh based on the semantic mesh partitioning. And, we modify extracted feature edges so that the extracted edges may adapt to the initial front. We use existing mesh partitioning algorithm for feature edge extraction. In general, extracted feature edges may be jaggy. We smooth extracted jaggy feature edges and modify the triangular mesh so that the smoothed feature edges may appear as the mesh edge in order to create the initial front of the Q-Morph.
Petabyte-scale innovations at the European Nucleotide Archive

Dramatic increases in the throughput of nucleotide sequencing machines, and the promise of ever greater performance, have thrust bioinformatics into the era of petabyte-scale data sets. Sequence repositories, which provide the feed for these data sets into the worldwide computational infrastructure, are challenged by the impact of these data volumes. The European Nucleotide Archive (ENA; http://www.ebi.ac.uk/embl), comprising the EMBL Nucleotide Sequence Database and the Ensembl Trace Archive, has identified challenges in the storage, movement, analysis, interpretation and visualization of petabyte-scale data sets. We present here our new repository for next generation sequence data, a brief summary of contents of the ENA and provide details of major developments to submission pipelines, high-throughput rule-based validation infrastructure and data integration approaches.
Hybrid recommendation based on implicative rating measures

This paper proposes the implicative rating measures and the hybrid recommendation model based on those measures to suggest a list of top N items to an active user. The proposed recommendation model is the combination of the user-based collaborative filtering approach and the association rule based approach. This hybrid model are compared to some existing models such as the popular model, the item based collaborative filtering using the Jaccard measure, the user based collaborative filtering using the Jaccard measure, the latent factor model, and the association rule based model using the Confidence measure on two datasets CourseRegistration and MSWeb. The experimental results show that the performance of the proposed model is better than that of the compared models.
Virtual environment for developing real-time image processing for vehicle control

Virtual prototyping is an alternative way to simulate the real product without the physical object. The product is created in simulator before making a physical prototype. In this research, a vehicle controller is the target system for prototyping. The vehicle navigation system is the target program to execute in a vehicle controller system. One of critical factors in a vehicle controller is response time. Thus, this paper aims to create the virtual prototype with real response time for a vehicle controller. The hardware accelerators are used to improve system performance. The hardware accelerators are implemented into two bases, which are GPU and programmable logic (PL). In addition, the overclocking method is applied to increase the operating speed in GPU hardware accelerator. The result from improvement is evaluated in terms of execution time per frame, which is the metric for measurement of the ability of real-time response. To achieve real-time response, the execution time per frame must be below 33.33 ms. The GPU based version achieves run-time response by running at 14.43 ms per frame. The PL based version runs at 16.332 ms per frame, which achieves run-time response.
Molecular diagnosis of Borrelia bacteria for the diagnosis of Lyme disease.

Introduction: Lyme borreliosis is the most common vector-borne disease in the temperate climate zone of Europe and the US, and its frequency is increasing. Serology is often negative in the early stage of Lyme borreliosis and cannot distinguish between active and past infection. Culture is cumbersome and not very sensitive, and polymerase chain reaction (PCR) for the diagnosis of Lyme borreliosis has been described over the last 20 years, with varying results. Areas covered: In this article, all of the major studies in which PCR has been used to diagnose Lyme borreliosis in humans are critically reviewed. However, this article does not include studies that consisted of fewer than 10 patients, nor does it include studies that have inadequate descriptions of the patient population. Expert opinion: There is a lack of standardized protocols, and preamplification procedures have not been standardized. Nested PCRs seem to perform best, but are prone to contamination. PCR on skin biopsies can be used to diagnose.
Regulation of Polysaccharide Utilization Contributes to the Persistence of Group A Streptococcus in the Oropharynx

ABSTRACT Group A Streptococcus (GAS) genes that encode proteins putatively involved in polysaccharide utilization show growth phase-dependent expression in human saliva. We sought to determine whether the putative polysaccharide transcriptional regulator MalR influences the expression of such genes and whether MalR helps GAS infect the oropharynx. Analysis of 32 strains of 17 distinct M protein serotypes revealed that MalR is highly conserved across GAS strains. malR transcripts were detectable in patients with GAS pharyngitis, and the levels increased significantly during growth in human saliva compared to the levels during growth in glucose-containing or nutrient-rich media. To determine if MalR influenced the expression of polysaccharide utilization genes, we compared the transcript levels of eight genes encoding putative polysaccharide utilization proteins in the parental serotype M1 strain MGAS5005 and its ΔmalR isogenic mutant derivative. The transcript levels of all eight genes were significantly increased in the ΔmalR strain compared to the parental strain, especially during growth in human saliva. Following experimental infection, the ΔmalR strain persistently colonized the oropharynx in significantly fewer mice than the parental strain colonized, and the numbers of ΔmalR strain CFU recovered were significantly lower than the numbers of the parental strain CFU recovered. These data led us to conclude that MalR influences the expression of genes putatively involved in polysaccharide utilization and that MalR contributes to the persistence of GAS in the oropharynx.
Efficient Low-Redundancy Codes for Correcting Multiple Deletions

We consider the problem of constructing binary codes to recover from <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula>–bit deletions with efficient encoding/decoding, for a fixed <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula>. The single deletion case is well understood, with the Varshamov–Tenengolts–Levenshtein code from 1965 giving an asymptotically optimal construction with <inline-formula> <tex-math notation="LaTeX">$\approx ~2^{n}/n$ </tex-math></inline-formula> codewords of length <inline-formula> <tex-math notation="LaTeX">$n$ </tex-math></inline-formula>, i.e., at most <inline-formula> <tex-math notation="LaTeX">$\log n$ </tex-math></inline-formula> bits of redundancy. However, even for the case of two deletions, there was no known explicit construction with redundancy less than <inline-formula> <tex-math notation="LaTeX">$n^{\Omega (1)}$ </tex-math></inline-formula>. For any fixed <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula>, we construct a binary code with <inline-formula> <tex-math notation="LaTeX">$c_{k} \log n$ </tex-math></inline-formula> redundancy that can be decoded from <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula> deletions in <inline-formula> <tex-math notation="LaTeX">$O_{k}(n \log ^{4} n)$ </tex-math></inline-formula> time. The coefficient <inline-formula> <tex-math notation="LaTeX">$c_{k}$ </tex-math></inline-formula> can be taken to be <inline-formula> <tex-math notation="LaTeX">$O(k^{2} \log k)$ </tex-math></inline-formula>, which is only quadratically worse than the optimal, non-constructive bound of <inline-formula> <tex-math notation="LaTeX">$O(k)$ </tex-math></inline-formula>. We also indicate how to modify this code to allow for a combination of up to <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula> insertions and deletions. We also note that among <italic>linear</italic> codes capable of correcting <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula> deletions, the <inline-formula> <tex-math notation="LaTeX">$(k+1)$ </tex-math></inline-formula>-fold repetition code is essentially the best possible.
Significant factors for detecting malicious redirections

Malicious redirections refer to a technique where a genuine search user is befooled and made to pass through a chain of redirections and ultimately presented with a compromised web page that may be an adware or an irrelevant content for the user. As a consequence the search engines earn a bad name in quality information retrieval and moreover the users are too dissatisfied. Also, there is sever wastage of expensive network resources like bandwidth. Detecting these malicious redirections is important for quality information retrieval from web. But detecting such redirections is a very tedious task due to the genuine usage of redirections. Also, the conventional methods of spam detection such as blacklists, whitelists are not very successful as they need to be updated every time. This paper explores various reasons behind redirections and presents the redirection attack scenario. To design a more robust and reliable approach, we present some new factors that facilitate redirection spam detection. We also explored the operational profile of each identified factor along with the criteria for its selection.
Creation of computer animation from story descriptions

This thesis describes a computer system that creates simple computer animation in response to high-level, vague, and incomplete descriptions of films. It makes its films by collecting and evaluating suggestions from several different bodies of knowledge. The order in which it makes its choices is influenced by the focus of the film. Difficult choices are postponed to be resumed when more of the film has been dete.rmined. The system was implemented in an object-oriented language based upon computational entities called "actors". The goal behind the construction of the system is that, whenever faced with a choice, it sensibly choose between alternatives. based upon the description of the film and as much general knowledge as possible. The system is ·presented as a computational model of creativily and aesthetics. Name and Title of Thesis Supervisor: Carl Hewitt, Associate Professor of Computer Science
Root Ideotype Influences Nitrogen Transport and Assimilation in Maize

Maize (Zea mays, L.) yield is strongly influenced by external nitrogen inputs and their availability in the soil solution. Overuse of nitrogen-fertilizers can have detrimental ecological consequences through increased nitrogen pollution of water and the release of the potent greenhouse gas, nitrous oxide. To improve yield and overall nitrogen use efficiency (NUE), a deeper understanding of nitrogen uptake and utilization is required. This study examines the performance of two contrasting maize inbred lines, B73 and F44. F44 was selected in Florida on predominantly sandy acidic soils subject to nitrate leaching while B73 was selected in Iowa on rich mollisol soils. Transcriptional, enzymatic and nitrogen transport analytical tools were used to identify differences in their N absorption and utilization capabilities. Our results show that B73 and F44 differ significantly in their genetic, enzymatic, and biochemical root nitrogen transport and assimilatory pathways. The phenotypes show a strong genetic relationship linked to nitrogen form, where B73 showed a greater capacity for ammonium transport and assimilation whereas F44 preferred nitrate. The contrasting phenotypes are typified by differences in root system architecture (RSA) developed in the presence of both nitrate and ammonium. F44 crown roots were longer, had a higher surface area and volume with a greater lateral root number and density than B73. In contrast, B73 roots (primary, seminal, and crown) were more abundant but lacked the defining features of the F44 crown roots. An F1 hybrid between B73 and F44 mirrored the B73 nitrogen specificity and root architecture phenotypes, indicating complete dominance of the B73 inbred. This study highlights the important link between RSA and nitrogen management and why both variables need to be tested together when defining NUE improvements in any selection program.
Detection of the Airway Obstruction Stage in Asthma Using Impulse Oscillometry System

Objective. Although spirometry is the most common method for evaluating the airway obstruction stage in asthma patients, it is difficult to perform in some patients. The aim of this study was to evaluate whether impulse oscillometry, an easy-to-perform technique, can detect asthmatic airway obstruction stage. Methods. A total of 80 subjects, including healthy volunteers and patients with asthma, were enrolled in this study. The asthma patients were classified into three groups according to American Thoracic Society (ATS)/European Respiratory Society (ERS)-2005: the mild group (forced expiratory volume in 1 second (FEV1) ≥ 70% predicted (Pred), n = 20), the moderate group (50% Pred ≤ FEV1 <70% Pred, n = 20), and the severe group (FEV1 < 50% Pred, n = 20). Spirometry and impulse oscillometry (IOS) parameters were obtained from every subject. Correlation analysis was used to compare spirometry measurements and IOS parameters. One-way analysis of variance (ANOVA) was performed to compare IOS parameters among different groups. The potential of using all individual IOS parameters to detect the different stages of asthmatic airway obstruction was evaluated by the receiver operating characteristic (ROC) curve analysis. Results. The correlation analysis showed that IOS parameters, such as respiratory resistance at 5 Hz (R5), respiratory resistance at 10 Hz (R10), respiratory resistance at 20 Hz (R20), difference in resistance between 5 Hz and 20 Hz (R5–20), impedance at 5 Hz (Z5), resonant frequency (Fres), and area of reactance (AX) were negatively correlated with FEV1 and peak expiratory flow (PEF), while reactance at 5 Hz (X5) was positively correlated with FEV1 and PEF. The increase in R5, R10, R20, Z5, R5–20, Fres, (−X5), and AX parameters corresponded significantly with an increase in the airway obstruction stage, as determined by one-way ANOVA . ROC curve analysis revealed that all the IOS parameters studied, except for Fres, were capable of classifying asthmatic airway obstruction. R5, R5–20, and Z5 were the most accurate parameters. Conclusion. IOS provides an accurate, reliable, and patient-friendly technique for classifying asthmatic airway obstruction.
Deep Models Under the GAN: Information Leakage from Collaborative Deep Learning

Deep Learning has recently become hugely popular in machine learning for its ability to solve end-to-end learning systems, in which the features and the classifiers are learned simultaneously, providing significant improvements in classification accuracy in the presence of highly-structured and large databases. Its success is due to a combination of recent algorithmic breakthroughs, increasingly powerful computers, and access to significant amounts of data. Researchers have also considered privacy implications of deep learning. Models are typically trained in a centralized manner with all the data being processed by the same training algorithm. If the data is a collection of users' private data, including habits, personal pictures, geographical positions, interests, and more, the centralized server will have access to sensitive information that could potentially be mishandled. To tackle this problem, collaborative deep learning models have recently been proposed where parties locally train their deep learning structures and only share a subset of the parameters in the attempt to keep their respective training sets private. Parameters can also be obfuscated via differential privacy (DP) to make information extraction even more challenging, as proposed by Shokri and Shmatikov at CCS'15. Unfortunately, we show that any privacy-preserving collaborative deep learning is susceptible to a powerful attack that we devise in this paper. In particular, we show that a distributed, federated, or decentralized deep learning approach is fundamentally broken and does not protect the training sets of honest participants. The attack we developed exploits the real-time nature of the learning process that allows the adversary to train a Generative Adversarial Network (GAN) that generates prototypical samples of the targeted training set that was meant to be private (the samples generated by the GAN are intended to come from the same distribution as the training data). Interestingly, we show that record-level differential privacy applied to the shared parameters of the model, as suggested in previous work, is ineffective (i.e., record-level DP is not designed to address our attack).
SQL to NoSQL transformation system using data adapter and analytics

Popularity of bigdata in cloud computing is growing tremendously nowadays. Data production rate has become explosive. Many existing systems need to enlarge their service to sustenance explosive data generation rate. NoSQL database are suitable to handle large volume of data. This paper focuses on a data adapter which provides support for hybrid database systems, NoSQL as well as relational databases. Also, a seamless mechanism is provided for hybrid database system construction, which enables access to both databases at same time. This paper focuses on the automatic transformation of hybrid systems with multiple structured data. Hybrid database systems provide access to either relational or NoSQL database, per data size. The proposed data adapter supports application queries and database transformation at same time, which in turn speed up the process. Three different approaches are proposed for queries on database. Blocking transformation mode, blocking truncation mode, direct access mode. This paper also discusses the integration of Pentaho business analytics tool with proposed data adapter for big data predictive analytics. This integration focuses on empowering users to prepare, model and visualize and explore data sets stored in NoSQL databases. This paper describes the design of data adapter in detail.