Miracle-dz/UniFAR-FTUs huggingface dataset:
A REINFORCEMENT LEARNING BASED UAVS AIR COLLISION AVOIDANCE

In this paper, we propose to deal with the UAV airspace conflict resolution problem. We propose to search near optimal conflict free policies in virtue of the model-based reinforcement learning. We first analyze the UAV airspace conflict problem and the basic conditions in ensuring collision-free planning, and then discuss the features that effect the optimal action. We then propose the reinforcement learning based conflict resolution algorithm. In the model-based learning structure, we consider the simplified dynamics of the UAVS in the model, and employ the heuristic method to estimate the state-action value. In the multi-dimension, continuous space, the optimal policy search method is utilized to find the near optimal policy. The experience from the real environment is used to criticize the model-based learning policy. In the end, we apply simulation experiments to demonstrate the proposed algorithm.
Automatic inheritance hierarchy restructuring and method refactoring

Most, object-oriented programs have imperfectly designed inheritance hierarchies and imperfectly factored methods, and these imperfections tend to increase with maintenance. Hence, even object-oriented programs are more expensive to maintain, harder to understand and larger than necessary. Automatic restructuring of inheritance hierarchies and refactoring of methods can improve the design of inheritance hierarchies, and the factoring of methods. This results in programs being smaller, having better code re-use and being more consistent. This paper describes Guru, a prototype tool for automatic inheritance hierarchy restructuring and method refactoring of Self programs. Results from realistic applications of the tool are presented.
IDE Gene Polymorphism Influences on BPSD in Mild Dementia of Alzheimer's Type

Insulin degrading enzyme (IDE) degrades amyloid β (Aβ), which may inhibit the accumulation of Aβ in a brain affected with dementia of Alzheimer's type (DAT). A decrease in the activity of IDE results in changes in glucose utilization in the brain, which could affect the cognitive and psychiatric symptoms of DAT. We investigated a possible association of IDE gene polymorphism and the behavioral and psychological symptoms of dementia (BPSD) in mild DAT. The genotyping for IDE and apolipoprotein E (ApoE) was determined in 207 patients with mild DAT and 215 controls. The occurrence of BPSD was demonstrated using the Behavioral Pathology in Alzheimer's Disease Rating Scale (BEHAVE-AD). IDE gene polymorphism is unlikely to play a substantial role in conferring susceptibility to DAT, but it may be involved in the development of affective disturbance through the course of mild DAT, regardless of the presence of an ApoE ε4 allele. The present data could be the result of a small sample size. Further investigations using larger samples are thus required to clarify the correlation between IDE gene polymorphism, susceptibility to DAT, and emergence of BPSD.
Mixed-Effects Modelling of Scale Growth Profiles Predicts the Occurrence of Early and Late Fish Migrants

Fish growth is commonly used as a proxy for fitness but this is only valid if individual growth variation can be interpreted in relation to conspecifics' performance. Unfortunately, assessing individual variation in growth rates is problematic under natural conditions because subjects typically need to be marked, repeated measurements of body size are difficult to obtain in the field, and recaptures may be limited to a few time events which will generally vary among individuals. The analysis of consecutive growth rings (circuli) found on scales and other hard structures offers an alternative to mark and recapture for examining individual growth variation in fish and other aquatic vertebrates where growth rings can be visualized, but accounting for autocorrelations and seasonal growth stanzas has proved challenging. Here we show how mixed-effects modelling of scale growth increments (inter-circuli spacing) can be used to reconstruct the growth trajectories of sea trout (Salmo trutta) and correctly classify 89% of individuals into early or late seaward migrants (smolts). Early migrants grew faster than late migrants during their first year of life in freshwater in two natural populations, suggesting that migration into the sea was triggered by ontogenetic (intrinsic) drivers, rather than by competition with conspecifics. Our study highlights the profound effects that early growth can have on age at migration of a paradigmatic fish migrant and illustrates how the analysis of inter-circuli spacing can be used to reconstruct the detailed growth of individuals when these cannot be marked or are only caught once.
Optimization and Estimation of Complex-Valued Signals: Theory and applications in filtering and blind source separation

Complex-valued signals occur in many areas of science and engineering and are thus of fundamental interest. When developing signal processing methods in the complex domain, there are two key issues: making use of the full statistical information and optimization. In this article, we review the necessary tools to address these two key issues and provide examples in filtering and blind source separation (BSS) that utilize these tools.
A new method of three-dimensional visualization of satellite cloud image

To solve the problems on 3D visualization of satellite data, such as the inaccuracy of cloud mask, ignorance of visual affect of gray, transparency and orientation, this paper brings forward a series of methods. Through radiation background to detect cloud mask and cloud top inversion etc, can obtain high precision application data, moreover, advances the revised model on aspects of gray, transparency and orientation. modeling by the methods advanced above, 3D satellite data could gain a better effect.
Do arbitrary function approximators make sense as software prediction models?

Predicting software development effort with high precision is still a major challenge for the industry and a major research area in software engineering. A significant share of research on software prediction is devoted to research on arbitrary function approximators, such as estimation by analogy, regression trees and artificial neural networks. This paper questions the use of arbitrary function approximators (AFA's) for software prediction by invoking theory of science and appealing to common sense. We argue that arbitrary function approximators may be useful in exploratory data analysis but we question their value for predictive purposes, and especially for software effort prediction
Hand Gesture Recognition Systems: A Survey

Gesture was the first mode of communication for the primitive cave men. Later on human civilization has developed the verbal communication very well. But still nonverbal communication has not lost its weightage. Such non – verbal communication are being used not only for the physically challenged people, but also for different applications in diversified areas, such as aviation, surveying, music direction etc. It is the best method to interact with the computer without using other peripheral devices, such as keyboard, mouse. Researchers around the world are actively engaged in development of robust and efficient gesture recognition system, more specially, hand gesture recognition system for various applications. The major steps associated with the hand gesture recognition system are; data acquisition, gesture modeling, feature extraction and hand gesture recognition. There are several sub-steps and methodologies associated with the above steps. Different researchers have followed different algorithm or sometimes have devised their own algorithm. The current research work reviews the work carried out in last twenty years and a brief comparison has been performed to analyze the difficulties encountered by these systems, as well as the limitation. Finally the desired characteristics of a robust and efficient hand gesture recognition system have been described. General Terms Hand gesture recognition, comparison
The Effectiveness and Safety of Topical Capsaicin in Postherpetic Neuralgia: A Systematic Review and Meta-analysis

In particular, neuropathic pain is a major form of chronic pain. This type of pain results from dysfunction or lesions in the central and peripheral nervous system. Capsaicin has been traditionally utilized as a medicine to remedy pain. However, the effectiveness and safety of this practice is still elusive. Therefore, this systematic review aimed to investigate the effect of topical capsaicin as a pain-relieving agent that is frequently used in pain management. In brief, all the double-blinded, randomized placebo- or vehicle-controlled trials that were published in English addressing postherpetic neuralgia were included. Meta-analysis was performed using Revman® version 5.3. Upon application of the inclusion and exclusion criteria, only six trials fulfilled all the criteria and were included in the review for qualitative analysis. The difference in mean percentage change in numeric pain rating scale score ranges from -31 to -4.3. This demonstrated high efficacy of topical capsaicin application and implies that capsaicin could result in pain reduction. Furthermore, meta-analysis was performed on five of the included studies. All the results of studies are in favor of the treatment using capsaicin. The incidence of side effects from using topical capsaicin is consistently higher in all included studies, but the significance of safety data cannot be quantified due to a lack of p-values in the original studies. Nevertheless, topical capsaicin is a promising treatment option for specific patient groups or certain neuropathic pain conditions such as postherpetic neuralgia.
Semi-automatic determination of allograph duration and position in on-line handwriting words based on the expected number of strokes.

In this paper, a semi-automatic character labeling ('truthing') procedure is presented which uses an initial un-supervised algorithm to estimate the starting stroke and number of strokes per allograph, followed by minimal user interaction to improve the estimates (in this study, a stroke is deened as the trajectory of the pen tip between two consecutive minima in the absolute pen-tip velocity). Such a procedure is very useful since the complete manual labeling of handwriting takes a lot of time from the user, in the order of one hour per 100 written words. Even without making use of detailed shape information the proposed algorithm already yields a usable segmentation which aids the manual labeling process.
An appraisal of how the vitamin A-redox hypothesis can maintain honesty of carotenoid-dependent signals

The vitamin A-redox hypothesis provides an explanation for honest signaling of phenotypic quality by carotenoid-dependent traits. A key aspect of the vitamin A-redox hypothesis, applicable to both yellow and red coloration, is the hypothesized negative feedback of tightly regulated Vitamin A plasma levels on the enzyme responsible for sequestering both Vitamin A and carotenoids from the gut. We performed a meta-analysis and find that vitamin A levels are positively related to carotenoid plasma levels (r = 0.50, P = 0.0002). On the basis of this finding and further theoretical considerations, we propose that the vitamin A-redox hypothesis is unlikely to explain carotenoid-dependent honest signaling.
A Correlation Analysis of English Particle Placement of Three East Asian EFL Learners Writings

This paper examines the English particle placements of EFL learners’ writings in three East Asian countries (Chinese, Japan, and Korea). Three parts of the TOEFL11 corpus were chosen, and all the sentences with particles were extracted. The ICE-GB was chosen as a native speakers’ English. Then, eleven linguistic factors were manually encoded. The collected data were analyzed with R. Correlation tests and a hierarchical clustering analysis was adopted. Through the analysis, the following two facts were observed: (i) each linguistic factor affected differently in four varieties of English and (ii) Japanese English was similar to native speakers’ counterparts whereas Korean and Chinese formed another group.
Systemwide joint position sensor fault tolerance in robot systems using Cartesian accelerometers

Joint position sensors are necessary for most robot control systems. A single position sensor failure in a normal robot system can greatly degrade performance. This paper presents a method to obtain position information from Cartesian accelerometers without integration. Depending on the number and location of the accelerometers, the proposed system can tolerate the loss of multiple position sensors. A solution technique suitable for real-time implementation is presented. Simulations were conducted using 5 triaxial accelerometers to recover from the loss of up to 4 joint position sensors on a 7 degree of freedom robot moving in general three dimensional space. The simulations show good estimation performance using non-ideal accelerometer measurements.
Manipulating the Sensitivity of Signal-Induced Repression: Quantification and Consequences of Altered Brinker Gradients

Traditionally, the analysis of gene regulatory regions suffered from the caveat that it was restricted to artificial contexts (e.g. reporter constructs of limited size). With the advent of the BAC recombineering technique, genomic constructs can now be generated to test regulatory elements in their endogenous environment. The expression of the transcriptional repressor brinker (brk) is negatively regulated by Dpp signaling. Repression is mediated by small sequence motifs, the silencer elements (SEs), that are present in multiple copies in the regulatory region of brk. In this work, we manipulated the SEs in the brk locus. We precisely quantified the effects of the individual SEs on the Brk gradient in the wing disc by employing a 1D data extraction method, followed by the quantification of the data with reference to an internal control. We found that mutating the SEs results in an expansion of the brk expression domain. However, even after mutating all predicted SEs, repression could still be observed in regions of maximal Dpp levels. Thus, our data point to the presence of additional, low affinity binding sites in the brk locus.
The ICEA plug-in for virtual reality, immersive creation and edition of animation

This paper reports on ICEA, the Immersive Creation and Edition of Animation platform we developed in order to support easy computer animations. This plug-in allows users to create new animations and to modify existing ones by interacting intuitively within Virtual Environments. The aim of our system is to enable people without computer animation background to design objects' motions and animations through simplified and immersive recording, editing and modification processes. Indeed, ICEA uses the immersive authoring principles, and as such, it offers an alternative to classic 3D animation solutions: users have only to perform actions in the virtual environment using any available interfaces to create animations. ICEA's core is coded in Haskell on top of the FRVR framework. It builds on a functional reactive paradigm, thus allowing easy scaling of the plug-in usage. ICEA is a fully C++ compatible plug-in supporting most Virtual Reality applications. To validate the concept ICEA, we implemented and tested it on a “sale's man-like” problem: users were asked to generate (e.g. create, play, and edit) the movement of a character on what they considered the shortest path linking predetermined points. Our preliminary results show that users familiarize quickly with immersive paths manipulation.
Pan-cancer transcriptome analysis reveals long noncoding RNAs with conserved function

A growing number of gene-centric studies have highlighted the emerging significance of lncRNAs in cancer. However, these studies primarily focus on a single cancer type. Therefore, we conducted a pan-cancer analysis of lncRNAs comparing tumor and matched normal expression levels using RNA-Seq data from ∼ 3,000 patients in 8 solid tumor types. While the majority of differentially expressed lncRNAs display tissue-specific expression we discovered 229 lncRNAs with outlier or differential expression across multiple cancers, which we refer to as 'onco-lncRNAs'. Due to their consistent altered expression, we hypothesize that these onco-lncRNAs may have conserved oncogenic and tumor suppressive functions across cancers. To address this, we associated the onco-lncRNAs in biological processes based on their co-expressed protein coding genes. To validate our predictions, we experimentally confirmed cell growth dependence of 2 novel oncogenic lncRNAs, onco-lncRNA-3 and onco-lncRNA-12, and a previously identified lncRNA CCAT1. Overall, we discovered lncRNAs that may have broad oncogenic and tumor suppressor roles that could significantly advance our understanding of cancer lncRNA biology.
Automatic Detection of Phishing Target from Phishing Webpage

An approach to identification of the phishing target of a given (suspicious) webpage is proposed by clustering the webpage set consisting of its all associated webpages and the given webpage itself. We first find its associated webpages, and then explore their relationships to the given webpage as their features for clustering. Such relationships include link relationship, ranking relationship, text similarity, and webpage layout similarity relationship. A DBSCAN clustering method is employed to find if there is a cluster around the given webpage. If such cluster exists, we claim the given webpage is a phishing webpage and then find its phishing target (i.e., the legitimate webpage it is attacking) from this cluster. Otherwise, we identify it as a legitimate webpage. Our test dataset consists of 8745 phishing pages (targeting at 76 well-known websites) selected from Phish Tank and preliminary experiments show that the approach can successfully identify 91.44% of their phishing targets. Another dataset of 1000 legitimate webpages is collected to test our method’s false alarm rate, which is 3.40%.
Self-Affirmation Reduces Delay Discounting of the Financially Deprived

Financial deprivation is associated with excessive discounting of delayed rewards. In the present research, we argue that this counterproductive tendency may be driven, at least in part, by the aversive and self-threatening nature of experiencing financial deprivation. Accordingly, we propose that self-affirmation—an intervention known to buffer negative consequences of psychological threats—may reduce delay discounting of the financially deprived. Results of two high-powered, preregistered experiments support this proposition. Specifically, in Study 1 (n = 546), we show that among participants with relatively lower income, self-affirmation effectively reduces delay discounting. In Study 2 (n = 432), we manipulate the feeling of financial deprivation and demonstrate that self-affirmation reduces delay discounting among those who feel financially deprived. We also examine the underlying process of this effect and find that self-affirmation bolsters a sense of personal control among those who feel financially deprived, which in turn reduces their delay discounting (Study 2). Overall, our findings suggest that the relationship between financial deprivation and delay discounting is malleable and psychological interventions that attenuate self-threats and bolster a sense of personal control can be applied to reduce myopic tendencies of the poor.
An energy aware routing design to maximize lifetime of a Wireless Sensor Network with a mobile base station

Due to the nature of many-to-one or many-to-few traffic patterns in Wireless Sensor Networks (WSNs), some critical nodes overload and tend to exhaust their energy at an early age bringing the whole network down. Typically, most routing algorithms employ a reliable cost metric to route the data but are unable to ensure balanced energy consumption from all the nodes in the WSN. In this paper, we have employed an energy aware routing algorithm to route data packets in a network with mobile base station. The routing algorithm balances the energy utilized from the hotspot nodes and ensures proper utilization of the whole network. We have evaluated the performance of our algorithm with other contemporary routing algorithms and the simulation results show a significant improvement in performance in terms of network lifetime.
A colorimetric method for point mutation detection using high-fidelity DNA ligase

The present study reported proof-of-principle for a genotyping assay approach that can detect single nucleotide polymorphisms (SNPs) through the gold nanoparticle assembly and the ligase reaction. By incorporating the high-fidelity DNA ligase (Tth DNA ligase) into the allele-specific ligation-based gold nanoparticle assembly, this assay provided a convenient yet powerful colorimetric detection that enabled a straightforward single-base discrimination without the need of precise temperature control. Additionally, the ligase reaction can be performed at a relatively high temperature, which offers the benefit for mitigating the non-specific assembly of gold nanoparticles induced by interfering DNA strands. The assay could be implemented via three steps: a hybridization reaction that allowed two gold nanoparticle-tagged probes to hybrid with the target DNA strand, a ligase reaction that generates the ligation between perfectly matched probes while no ligation occurred between mismatched ones and a thermal treatment at a relatively high temperature that discriminate the ligation of probes. When the reaction mixture was heated to denature the formed duplex, the purple color of the perfect-match solution would not revert to red, while the mismatch gave a red color as the assembled gold nanoparticles disparted. The present approach has been demonstrated with the identification of a single-base mutation in codon 12 of a K-ras oncogene that is of significant value for colorectal cancers diagnosis, and the wild-type and mutant type were successfully scored. To our knowledge, this was the first report concerning SNP detection based on the ligase reaction and the gold nanoparticle assembly. Owing to its ease of operation and high specificity, it was expected that the proposed procedure might hold great promise in practical clinical diagnosis of gene-mutant diseases.
Construction details of an autoradiographic-based rat brain phantom for emission tomography

A digital brain phantom was created from rat brain autoradiographic (AR) data for use in emission computed tomography studies. The animal tissue was radio-labeled with [/sup 14/C]-2-deoxyglucose, a functional analog of the PET agent [/sup 18/F]-fluro-deoxyglucose. Following sacrifice of the animal, serial tissue sections were cut at 20 /spl mu/m thickness, digitized, and calibrated to represent the ground truth 2D relative spatial distribution of radionuclide within the tissue. A 3D representation was achieved by digital alignment of the serial AR images to corresponding video blockface images acquired at the time of cutting. In addition, a magnetic resonance data set was co-registered to the AR and blockface data using the AIR algorithm. This paper is concerned with outlining the details of construction for this phantom.
The Big and the Small: Challenges of Imaging the Brain’s Circuits

The relation between the structure of the nervous system and its function is more poorly understood than the relation between structure and function in any other organ system. We explore why bridging the structure-function divide is uniquely difficult in the brain. These difficulties also explain the thrust behind the enormous amount of innovation centered on microscopy in neuroscience. We highlight some recent progress and the challenges that remain.