Miracle-dz/UniFAR-FTUs huggingface dataset:
The Investigation and Application of SVC and SVR in Handling Missing Values

The great achievements have been approached in the development of support vector machine (SVM). It has been successfully used for solving classification and regression problems. This paper aims at proposing two algorithms based on SVC and SVR which are two applications of SVM in the fields of classification and regression, to handle both nominal and numerical missing values. Two experiments are conducted. The results indicate that our algorithms provide a high accuracy when compared with some other commonly used algorithms.
Aflatoxin-producing potential of communities of Aspergillus section Flavi from cotton producing areas in the United States

Communities of Aspergillus section Flavi resident in soils planted with cotton were compared among several areas in the southern United States. Incidence of A. flavus and A. tamarii differed among areas. A. flavus incidence increased with temperature and decreased with latitude. Less than 1% of isolates were A. nomius or A. parasiticus. A. flavus isolates were assigned to either the S or L strains on the basis of sclerotial morphology. S strain isolates produced numerous small ( A. flavus was found in all areas. Aflatoxin-producing potential of A. flavus differed among areas and was correlated with S strain incidence. L strain isolates produced only 33% as much aflatoxin B 1 as S strain isolates. No S strain isolate produced both aflatoxin B 1 and aflatoxin G 1 . Correlations indicated that L strain toxigenicity but not S strain toxigenicity varied geographically. While toxigenicities of most isolates were stable through single conidial transfer, 28% of isolates expressed altered levels of toxigenicity after transfer. The observed differences among communities may reflect geographic isolation and/or adaptation, and may cause different vulnerabilities to aflatoxin contamination among crops planted in diverse locations.
Interactive comment on “ Statistical exploration of gaseous elemental mercury ( GEM ) measured at Cape Point from 2007 to 2011 ” by A . D

Venter and co-authors present a statistical exploration of a 4-year record (2007-2011) of gaseous elemental mercury (GEM) concentrations measured at Cape Point, South Africa. Firstly, this paper aims at identifying the origin of high and low mercury concentrations events using a dataset already presented and discussed elsewhere (e.g., Slemr et al., 2013; Slemr et al., 2015) and based on back-trajectories and cluster analysis. Secondly, multi-linear regression analysis was used to predict GEM concentrations from other atmospheric parameters measured at the station. The paper is clearly organized, easy to follow and well written but overall lacks robust statistics. I recommend major revisions.
Relations between Recent Past Leisure Activities with Risks of Dementia and Cognitive Functions after Stroke

Background Leisure activity participation has been shown to lower risks of cognitive decline in non-stroke populations. However, effects of leisure activities participation upon cognitive functions and risk of dementia after stroke are unclear. The purpose of this study is to examine the effects of recent past leisure activities participation upon cognitive functions and risk of incident dementia after stroke. Methods Hospital-based, retrospective cohort study. 88 of 1,013 patients with stroke or TIA having no prestroke dementia were diagnosed to have incident poststroke dementia (PSD) 3–6 months after stroke. Regular participation (≥3 times per week) in intellectual, recreational, social and physical activities over the year before the index stroke was retrospectively recorded at 3–6 months after stroke. Results Logistic regression analyses showed that regular participation in intellectual (RR 0.36, 95%CI 0.20–0.63) and stretching & toning physical exercise (0.37, 0.21–0.64) was significantly associated with a reduced risk of PSD after controlling for age, education, prestroke cognitive decline, stroke subtype, prior strokes and chronic brain changes including white matter changes, old infarcts and global atrophy. Results were similar in patients with past strokes in unadjusted models. Participation in increased number of activities in general (r = 0.41, p<0.01) and in intellectual (r = 0.40, p<0.01), recreational (r = 0.24, p<0.01), strenuous aerobic (r = 0.23, p<0.01) and mind-body (r = 0.10, p<0.01) activities was associated with higher poststroke Mini-mental State Examination scores in models adjusted for prestroke cognitive decline. Conclusions Regular participation in intellectual activities and stretching & toning exercise was associated with a significantly reduced short-term risk of PSD in patients with and without recurrent strokes. Participation in greater number of recent past leisure activities was associated with better poststroke cognitive performance. Findings of this retrospective cohort study call for studies of activity intervention for prevention of cognitive decline in individuals at elevated risk of stroke.
Streaming Graphics

Streaming graphics, a cross between streaming video and dynamic graphics, is a new approach to visualizing data. The goal is to integrate and synchronize multiple streams of data in real time and display them at rates of up to 20 frames per second. This article describes the design of a system, called Dancer, that implements these ideas in Java.
Opportunity Cost Algorithms for Combinatorial Auctions

Two general algorithms based on opportunity costs are given for approximating a revenuemaximizing set of bids an auctioneer should accept, in a combinatorial auction in which each bidder offers a price for some subset of the available goods and the auctioneer can only accept nonintersecting bids. Since this problem is difficult even to approximate in general, the algorithms are most useful when the bids are restricted to be connected node subsets of an underlying object graph that represents which objects are relevant to each other. The approximation ratios of the algorithms depend on structural properties of this graph and are small constants for many interesting families of object graphs. The running times of the algorithms are linear in the size of the bid graph, which describes the conflicts between bids. Extensions of the algorithms allow for efficient processing of additional constraints, such as budget constraints that associate bids with particular bidders and limit how many bids from a particular bidder can be accepted.
Determining an Efficient Frontier in a Stochastic Moment Setting

We analyze the problem of portfolio optimization under uncertainty in the assets return distribution. After characterizing the problem using a general formulation involving the product space of the return distribution with the parameter distribution, we propose the use of penalty functions to solve the resulting program. The connection to some important existing approaches is shown, and we then focus on two specific proposals with an important practical feature: the stability of the resulting portfolio composition under changing input variables. With high transaction costs and missing liquidity in some Brazilian markets, this stability feature is of great practical relevance. Finally, we show with an example from the Brazilian market that the penalty function approach does indeed increase stability, and seems to be a promising alternative whose long-range performance should be analyzed.
Common Components, Networks, and Pathways of Cross-Tolerance to Stress. The Central Role of “Redox” and Abscisic Acid-Mediated Controls1

The vigor and responsiveness of plants to environmental stress result from the constant re-adjustment of physiology and metabolism throughout the life cycle within the framework of the genetic background. Plants have developed unique strategies for responding to ever-changing environmental conditions, exhaustively monitoring their surroundings and adjusting their metabolic systems to maintain homeostasis. The severity of stress, the genetic background of the plant, and its individual history determine everyday survival or death. These factors dictate the destiny of any individual. The genomeenvironment interaction is, therefore, an essential focus for the elucidation of the nature of the phenotypic variation leading to the successful response of plants to environmental cues. Plants acclimate to biotic and abiotic stresses by triggering a cascade or network of events that starts with stress perception and ends with the expression of a battery of target genes. The key components of the stress-response relationship are illustrated in Fig. 1. These are stress stimulus, signals, transducers, transcription regulators, target genes, and stress responses, including morphological, biochemical, and physiological changes. In evolutionary terms, components that are near to the end of the stressresponse cascade are not predicted to be the ones whose actions significantly affect the operation of other genes. However, factors that act at early stages are critical for other cell functions. Plants make use of common pathways and components in the stressresponse relationship. This phenomenon, which is known as cross-tolerance, allows plants to adapt/ acclimate to a range of different stresses after exposure to one specific stress. The major focus of this review, therefore, concerns the basic features of signaling that underpin cross-tolerance and result from the action of common elements, which are likely to occur early in the stress response cascade. First, using drought and chilling as examples, we explore the evidence for common signals and elements that confer cross-tolerance. Second, we highlight the importance of “redox signals” in such networks and discuss the evidence to date for the existence of such pathways in plants. The elucidation of common components has enormous potential and has, therefore, become a priority in research and breeding programs aimed at improving plant stress tolerance.
Partitioning Decision Process for Embedded Hardware and Software Deployment

Many types of embedded systems applications are implemented as a combination of software and hardware. For such systems the mapping of the application units into hardware and software, i.e. the partitioning process, is a key phase of the design. Although there exist techniques for partitioning, the entire process, in particular in relation to different application requirements and project constraints, is not properly supported. This leads to several unplanned iterations, redesigns and interruptions due to uncontrolled dependencies between hardware and software parts. In order to overcome these problems, we provide a design process that enables the partitioning based on a multiple criteria decision analysis in a late design phase. We illustrate the proposed approach and provide a proof-of concept on an industrial case study to validate the approach applicability.
Physical interfaces for tabletop games

IncreTable is a mixed-reality tabletop game inspired by The Incredible Machine. Users can combine real and virtual game pieces in order to solve puzzles in the game. Game actions include placing virtual domino blocks with digital pens, controlling a virtual car by modifying the virtual terrain through a depth camera interface, and controlling real robots to topple over real and virtual dominoes.
A framework for detection and classification of plant leaf and stem diseases

We propose and evaluate a framework for detection of plant leaf/stem diseases. Studies show that relying on pure naked-eye observation of experts to detect such diseases can be prohibitively expensive, especially in developing countries. Providing fast, automatic, cheap and accurate image-processing-based solutions for that task can be of great realistic significance. The proposed framework is image-processing-based and is composed of the following main steps; in the first step the images at hand are segmented using the K-Means technique, in the second step the segmented images are passed through a pre-trained neural network. As a testbed, we use a set of leaf images taken from Al-Ghor area in Jordan. Our experimental results indicate that the proposed approach can significantly support accurate and automatic detection of leaf diseases. The developed Neural Network classifier that is based on statistical classification perform well and could successfully detect and classify the tested diseases with a precision of around 93%.
A Simple Calibration Approach to Single View Height Estimation

This paper presents a simple calibration approach to height estimation based on single view metrology. Instead of calibrating intrinsic or extrinsic parameters, our approach aims to estimate the vanishing points of a stationary camera. The calibration process is formulated as an optimization problem with a novel objective function, in which twelve parameters for estimating vanishing points are defined. The genetic algorithm with Cauchy mutation operator is further used for obtaining robust results. The major advantages of the proposed approach are: 1) it is easy to setup since only a cubic box and some optional line segments are required, and 2) it works without camera's intrinsic parameters. Experimental results show the effectiveness of the proposed approach with digital and analog video cameras.
How to Rapidly Prototype a Real-Time Scheduler

Implementing a new scheduling algorithm in an OS kernel is often an important step in scheduling research because it permits evaluation of the algorithm’s performance on real workloads. However, developing a new scheduler is not a trivial task because it requires sophisticated programming skills and a deep knowledge of kernel internals. In this paper we show how to use the HLS scheduling framework to develop new schedulers in a user-level simulator, where advanced debugging tools can be used to achieve a high level of robustness before the scheduler is converted to a loadable kernel module simply by recompiling it. Besides facilitating debugging and porting, the HLS abstraction has the benefit of bringing the programming model very close to what, in our experience, scheduler developers want.
Prediction of Plant Height in Arabidopsis thaliana Using DNA Methylation Data

Prediction of complex traits using molecular genetic information is an active area in quantitative genetics research. In the postgenomic era, many types of -omic (e.g., transcriptomic, epigenomic, methylomic, and proteomic) data are becoming increasingly available. Therefore, evaluating the utility of this massive amount of information in prediction of complex traits is of interest. DNA methylation, the covalent change of a DNA molecule without affecting its underlying sequence, is one quantifiable form of epigenetic modification. We used methylation information for predicting plant height (PH) in Arabidopsis thaliana nonparametrically, using reproducing kernel Hilbert spaces (RKHS) regression. Also, we used different criteria for selecting smaller sets of probes, to assess how representative probes could be used in prediction instead of using all probes, which may lessen computational burden and lower experimental costs. Methylation information was used for describing epigenetic similarities between individuals through a kernel matrix, and the performance of predicting PH using this similarity matrix was reasonably good. The predictive correlation reached 0.53 and the same value was attained when only preselected probes were used for prediction. We created a kernel that mimics the genomic relationship matrix in genomic best linear unbiased prediction (G-BLUP) and estimated that, in this particular data set, epigenetic variation accounted for 65% of the phenotypic variance. Our results suggest that methylation information can be useful in whole-genome prediction of complex traits and that it may help to enhance understanding of complex traits when epigenetics is under examination.
Connexin 26 hemichannels with a mutation that causes KID syndrome in humans lack 1 sensitivity to CO 2 2 3

Connexin26 hemichannels with a mutation that causes KID syndrome in humans lack 1 sensitivity to CO2 2 3 Louise Meigh 4 School of Life Sciences, University of Warwick, Coventry, CV4 7AL, UK 5 6 Naveed Hussain 7 Division of Neonatal Pediatrics, Connecticut Children's Medical Center’s NICU at University of 8 Connecticut Health Center, Farmington, CT 06030, USA 9 10 Daniel K. Mulkey 11 Dept. Physiology and Neurobiology, University of Connecticut, Storrs, CT 06268, USA 12 13 Nicholas Dale 14 School of Life Sciences, University of Warwick, Coventry, CV4 7AL, UK 15 16
Knowledge about HIV in a Community Sample of Urban African Americans in the South

Purpose Race and HIV are intertwined in complex ways. African Americans, particularly those residing in the southern United States, are at great risk for contracting and subsequently transmitting HIV. Research on the extent to which members of this population understand the risks associated with engaging in specific behaviors is limited. This paper examines HIV knowledge among at-risk adult African American men and women and the factors associated with levels of HIV knowledge. Methods Based on a conceptual model derived from Social Disorganization Theory and Syndemics Theory, interviews were conducted between 2009 and 2011. Questionnaire-based interviews were conducted with 1,864 respondents from 80 strategically-chosen census block groups in Atlanta, Georgia. An innovative approach to assessing amount of HIV knowledge was implemented, to derive better estimates of the extent of knowledge. Results Overall, HIV knowledge was low (average=43.5% correct answers). Seven factors were identified as contributing uniquely to having higher levels of knowledge about HIV transmission: (1) younger age, (2) being educated beyond the high school level, (3) being gay, lesbian or bisexual, (4) experiencing sexual abuse during childhood and/or adolescence, (5) drinking alcohol less frequently, (6) knowing a larger number of HIV-infected persons and (7) knowing anyone currently living with “full blown” AIDS. Conclusion HIV educational and intervention programs targeting at-risk African American adults need to develop effective ways of bolstering a solid understanding of how HIV is/not transmitted. In particular, efforts need to be targeted toward older adults, those with lower levels of educational attainment and persons who are not acquainted with anyone who is HIV-infected.
Real-time PCR detection of fraudulent addition of bovine milk to caprine and ovine milk.

Adulteration of caprine (Capra hircus) and ovine (Ovis aries) milk and dairy products by cheaper bovine (Bos taurus) milk is a common fraud attempted with the desire of profit. The intention to shorten and simplify the control of such deceits has encouraged the development of various analytical methods. Detection of bovine DNA from somatic cells using real-time PCR is a promising approach for qualitative and quantitative determination of bovine milk presence in milk and other dairy products. In our study, we evaluated specific real-time PCR with BOS/MAN system to detect bovine and mammalian DNA. First, the most efficient method of DNA extraction was selected followed by optimization of real-time PCR protocol with SybrGreen I and TaqMan chemistry. Then, the standard curves were designed and the area of linearity, efficiency, sensitivity and specificity of the BOS/MAN systems were determined. Sensitivity determined theoretically with standard plasmid DNA was 0.6 pg/μL and practically with standard milk mixtures was 0.5 % of bovine milk in the tested samples. We confirmed that the BOS/MAN system is adequate for qualitative detection of bovine milk in caprine and ovine milk. Although some researchers claim to perform successful quantification using real-time PCR for bovine milk, we could not repeat their results. The main issue in absolute quantification of bovine milk in samples consisted of mixed milk is the variable number of somatic cells in the milk. Information about this is surprisingly limited, what will be the focus discussion.
Nonlinear optimal control of an overhead travelling crane

This paper presents an H2-norm optimal control scheme for the three main axes of an overhead travelling crane, which guarantees both tracking of desired trajectories for the crane load and an active damping of crane load oscillations. For the model-based feedback control design series expansions are utilised to obtain an approximate solution of the corresponding Hamilton-Jacobi-Bellmann-equation. The tracking capabilities concerning desired trajectories for the crane load can be significantly improved by introducing feedforward control based on an inverse system model. The position of the crane load is measured by a CMOS camera using the spatial filtering principle. Desired trajectories for the crane load position in the three-dimensional workspace can be tracked independently with high accuracy. Experimental results from an implementation on a test rig show a high control performance.
Submodular maximization with multi-knapsack constraints and its applications in scientific literature recommendations

Submodular maximization problems belong to the family of combinatorial optimization problems and enjoy wide applications. In this paper, we focus on the problem of maximizing a monotone submodular function subject to a d-knapsack constraint, for which we propose a streaming algorithm that achieves a (1/1+2D − ε)-approximation of the optimal value, while it only needs one single pass through the dataset without storing all the data in the memory. In our experiments, we extensively evaluate the effectiveness of our proposed algorithm via an application in scientific literature recommendation. It is observed that the proposed streaming algorithm achieves both execution speedup and memory saving by several orders of magnitude, compared with existing approaches.
L-2-amino–3-phosphonopropionic Acid Modulates the Release of Glutamate by Blocking Presynaptic Group Ii Mglu Receptors at Neuromuscular Junction in Procambarus Clarkii

The non-selective antagonist DL-AP3, L-2-Amino-3-phosphonopropionic acid, was used to regulate the response of the Group II metabotroic glutamate receptors (mGlurs) on the presynaptic terminal in the common North American crayfish, Procambarus clarkii. The experiment was conducted to better understand the negative feedback mechanism of the Group II mGlurs, thereby furthering current research concerning the adverse effects of amyotrophic lateral sclerosis (ALS) and other degenerative neurological diseases caused by neurotoxicity within the synaptic cleft. Our results confirmed the hypothesis that the addition of the antagonist DL-AP3 to an extracellular fluid containing high concentrations of glutamate precipitated a subsequent increase in the stimulated excitatory postsynaptic potential (EPSP). Likewise, the difference in the addition of DL-AP3 to an extracellular fluid containing a high concentration of glutamate when compared to an extracellular fluid containing a low concentration of glutamate without the addition of DL-AP3 was not statistically significant. The modulation of frequencies between 0.5 Hz and 10 Hz provided further evidence to support our hypothesis by demonstrating that the Group II mGlurs were responsive to increased activity of synaptic transmission.