Miracle-dz/UniFAR-FTUs huggingface dataset:
Steerable Filters for Rotation Invariant Salient Feature Points Applied to Monocular SLAM

In this paper, we propose a new detector descriptor for the visual salient points and use it for a monocular visual Simultaneous Localization and Mapping (visualSLAM) application. Because in SLAM, the landmarks should be indexed with distinctive features, we aim to build a detector descriptor insuring the invariance to the rotation and the scale. First, the detector starts filtering an image with a steerable filter set, extracts Harris corners from the convolved image, next it clusters these corners, then it calculates a resulting set of feature points. We show that the repeatability of the detector is higher that other detectors like SIFT, SURF, CENSURE and BRISC. In addition, we implement the descriptor using color attributes. We represent the color at the location of each feature point with a pyramid characterized with many levels of quantization, and we calculate the entropy at each level. We make a simulation of Visual SLAM with known correspondences using these features to prove their efficiency in the localization and the map management of the robot.
Plant defense responses against viral and bacterial pathogen infections. Focus on RNA-binding proteins (RBPs)

Summary Plants have developed intricate defense mechanisms against pathogen infections. Immune system of medicinal plants is well developed. The molecular mechanisms of their ability to protect themselves are not fully understood. Little is known about RNA-binding proteins (RBPs) present in medicinal plants. However, CmGRP1 is an RBP found in the milky sap of medicinal plant Chelidonium majus L. what implies possible importance of RBPs in plant immunity. In this review recent insights into the role of plant RBPs in antiviral and antibacterial defense responses are discussed.
Extraction of severity information from clinical narratives using statistical natural language processing

Natural language processing methods adapted to the medical domain are quickly becoming important tools in the analysis of large amounts of clinical narratives. One important application is in the field of drug safety, where the investigation of suspected adverse drug reactions is based on millions of individual case safety reports from such incidents, and where much of the relevant information is only available in free-text form. In this thesis, a method for automatically extracting information about the severity of adverse reactions from such reports is developed and tested. A set of 1579 reports, pre-annotated for reactions, are manually annotated for severity information and two support vector machine (SVM) classifiers are then trained and tested on this data. The first SVM performs binary classification of tokens to identify severity descriptors using a large number of token and contextual features, while the second classifies the grade of the severity as mild, moderate or severe and uses as input a bag-of-words of severity descriptors associated with a particular reaction. Running the two SVMs in a pipeline gives an overall precision of 0.837 and a recall of 0.887, resulting in an F1-score of 0.861. This performance is considered good enough for the extracted severity information to be potentially useful in the discovery of new adverse drug reactions.
Measurement of the physical properties of the snowpack

This paper reviews measurement techniques and corresponding devices used to determine the physical properties of the seasonal snowpack from distances close to the ground surface. The review is placed in the context of the need for scientific observations of snowpack variables that provide inputs for predictive hydrological models that help to advance scientific understanding of geophysical processes related to snow in the near‐surface cryosphere. Many of these devices used to measure snow are invasive and require the snowpack to be disrupted, thereby precluding the possibility for multiple measurements to be made at the same sampling location. Moreover, many devices rely on the use of empirical calibration equations that may not be valid at all geographic locations. The spatial density of observations with most snow measurement devices is often inadequate. There is a need for improved automation of snowpack measurement instrumentation with an emphasis on field‐based feedback of measurement validity in lieu of postprocessing of samples or data at a lab or office location. The scientific future of snow measurement instrumentation thereby requires a synthesis between science and engineering principles that takes into consideration geophysics and the physics of device operation.
Organic matter partitioning and stoichiometry in response to rising water temperature and copepod grazing

Rising ocean temperature is expected to change the balance between production and degradation of organic matter due to different temperature sensitivities of auto- and heterotrophic processes. Copepods are the most prominent zooplankton group, and elevated temperature increases their growth and grazing rates. So far, it is unknown to what extent copepods affect the partitioning and stoichiometry of organic matter in a warmer surface ocean. We therefore conducted a mesocosm experiment with 3 copepod densities and 2 temperature scenarios to determine effects on the pools of dissolved and particulate organic matter and their C:N:P ratios. Here we show that particulate organic C (POC) concentrations decreased with increasing copepod abundance. This effect was more pronounced at elevated temperature, yielding a decrease in the POC to particulate nitrogen ratio (POC:PN) from 26 to 13 and in the POC:particulate organic phosphorus (POP) ratio from 567 to 257, from low to high copepod density. Dissolved organic carbon (DOC) accumulation was positively affected by temperature. However, increasing copepod abundance decreased the accumulation of DOC at elevated temperature. Copepod grazing and egestion enhanced the recycling of N and P, thereby increasing the availability of these nutrients for autotrophs. In concert with temperature-induced shifts in the phytoplankton community composition and size, changes in copepod abundance may therefore have contributed to altering the elemental composition of seston. Our findings suggest combined effects of zooplankton grazing and temperature on the composition and recycling of organic matter that should be taken into account when simulating biogeochemical cycles in a future ocean.
Identification of new susceptible genes associated with familial carotid body tumor of Chinese pedigree by high-throughput genome sequencing

Hereditary carotid body tumoris a rare disease which is related to the gene mutation. A majority of tumors are inherited in an autosomal dominant pattern. In addition, high-throughput DNA-sequencing technologies are widely applied to detect disease-associated genes. The Chinese pedigree is examined in this study by using highthroughput genome sequencing and gene mutations were confirmed by peripheral blood of the patients. We finally discovered new 57 genes with SNP and 9 genes with InDel in all patients. Based on the hazardous filter of the results, we found the M1I mutation of the exon1 in the succinate dehydrogenase D (SDHD) gene in all subjects.The new susceptible genesmight regulate the development of carotid body tumor and the result suggests SDHD M1I mutation might play a founder mutation in the Chinese HNPGL patients.
HOMOZYGOSITY MAPPING IN SHEEP AFFECTED BY CERVICOTHORACIC VERTEBRAL SUBLUXATION : CANDIDATE GENE IDENTIFICATION AND NOVEL MUTATION INVESTIGATION

Cervicothoracic vertebral subluxation (CVS) is an inherited disorder affecting Merino sheep. Affected animals exhibit sudden onset of ataxia in sheep from 9 months to 3 years of age, the disorder is of an economic and welfare concern to the industry. The prevalence of this disorder both nationally and internationally is unknown due to its ambiguous phenotype. This is the first study to map investigate genetic variations as a likely cause of CVS in Merino sheep. Twelve clinically affected animals from two separate Australian properties (Riverina, NSW, and Central West, NSW) were sampled and genotyped using the Illumina® OvineSNP50 BeadChip. The PDS5 homologue B gene was identified as a positional candidate gene using a homozygosity mapping approach. Sanger sequencing of RT-PCR products was utilised to sequence cDNA of the candidate gene in an affected animal. DNA sequencing revealed four variants within the candidate gene when compared to a reference sequence (GenBank® XM_015098134), a 6pb insertion (3619_3620insGTAAGG), two possible missense mutations (3412_C>A; 4342A>T) and an exon deletion (4066del-exon33). The 6bp insertion has been previously catalogued in other reference genomes, the two missense mutations appear to be a novel identification and the exon 33 deletion may represent a splice variant. Further analysis is required to confirm if any variant is pathogenic. A diagnostic test may be developed using information about associated SNP or after confirmation of a disease casing variant in the PDS5B gene.
Electronic System Fault Diagnosis with Optimized Multi-kernel SVM by Improved CPSO

Electronic systems’ safety operation has become a key issue to complex and high reliability systems. Now more emphasis has been laid on the accuracy of electronic system fault diagnosis. Based on the characteristics of the electronic system fault diagnosis, we design a multi-classification SVMs model to attain better fault diagnosis accuracy, which utilizes multi-kernel function consisting of several basis kernel functions to enhance the interpretability of the classification model. In order to optimize the performance of multi-classification SVMs with multi-kernel, we improve the Chaos Particles swarm Optimization (CPSO) algorithm to achieve the optimum parameters of SVMs and the multi-kernel function. For the improved CPSO algorithm, a modified Tent Map chaotic sequence is used to strengthen the search diversity, and an effective method is embedded to the stander PSO algorithm which can ensure to avoid premature stagnation and obtain the global optimization values. The fault diagnosis simulation results of an electronic system show the proposed optimization scheme is a feasible and effective method and it can significantly improve the fault diagnosis accuracy of the multi-kernel SVM.
Forest floor temperature and greenness link significantly to canopy attributes in South Africa’s fragmented coastal forests

Tropical landscapes are changing rapidly due to changes in land use and land management. Being able to predict and monitor land use change impacts on species for conservation or food security concerns requires the use of habitat quality metrics, that are consistent, can be mapped using above-ground sensor data and are relevant for species performance. Here, we focus on ground surface temperature (Thermalground) and ground vegetation greenness (NDVIdown) as potentially suitable metrics of habitat quality. Both have been linked to species demography and community structure in the literature. We test whether they can be measured consistently from the ground and whether they can be up-scaled indirectly using canopy structure maps (Leaf Area Index, LAI, and Fractional vegetation cover, FCover) developed from Landsat remote sensing data. We measured Thermalground and NDVIdown across habitats differing in tree cover (natural grassland to forest edges to forests and tree plantations) in the human-modified coastal forested landscapes of Kwa-Zulua Natal, South Africa. We show that both metrics decline significantly with increasing canopy closure and leaf area, implying a potential pathway for upscaling both metrics using canopy structure maps derived using earth observation. Specifically, our findings suggest that opening forest canopies by 20% or decreasing forest canopy LAI by one unit would result in increases of Thermalground by 1.2 °C across the range of observations studied. NDVIdown appears to decline by 0.1 in response to an increase in canopy LAI by 1 unit and declines nonlinearly with canopy closure. Accounting for micro-scale variation in temperature and resources is seen as essential to improve biodiversity impact predictions. Our study suggests that mapping ground surface temperature and ground vegetation greenness utilising remotely sensed canopy cover maps could provide a useful tool for mapping habitat quality metrics that matter to species. However, this approach will be constrained by the predictive capacity of models used to map field-derived forest canopy attributes. Furthermore, sampling efforts are needed to capture spatial and temporal variation in Thermalground within and across days and seasons to validate the transferability of our findings. Finally, whilst our approach shows that surface temperature and ground vegetation greenness might be suitable habitat quality metric used in biodiversity monitoring, the next step requires that we map demographic traits of species of different threat status onto maps of these metrics in landscapes differing in disturbance and management histories. The derived understanding could then be exploited for targeted landscape restoration that benefits biodiversity conservation at the landscape scale.
Beautiful People Are Better, At Least Online: Associations Between Photo Attractiveness and Text Attractiveness in Women's Online Dating Profiles

Do physically attractive individuals truly possess a multitude of better characteristics? The current study aimed to answer the age old question, “Do looks matter? ” within the context of online dating and framed itself using cursory research performed by Brand and colleagues (2012). Good Genes Theory, Halo Effect, Physical Attractiveness Stereotype, and Social Information Procession theory were also used to explore what function appearance truly plays in online dating and how it influences a user’s written text. 83 men were surveyed and asked to rate 84 women’s online dating profiles (photos and texts) independently of one another to determine if those who were perceived as physically attractive also wrote more attractive texts as well. Results indicated that physical attractiveness was correlated with text attractiveness but not with text confidence. Findings also indicated the more attractive a woman’s photo, the less discrepancy there was between her photo attractiveness and text attractiveness scores. Finally, photo attractiveness did not differ significantly for men’s ratings of women in this study and women’s ratings of men in the Brand et al. (2012) study.
Effects of dietary synbiotics from anaerobic microflora on growth performance, noxious gas emission and fecal pathogenic bacteria population in weaning pigs.

Synbiotics is the term used for a mixture of probiotics (live microbial feed additives that beneficially affects the host animal) and prebiotics (non-digestible food ingredients that beneficially affect the organism). This study investigated the effect of probiotics from anaerobic microflora with prebiotics on growth performance, nutrient digestibility, noxious gas emission and fecal microbial population in weaning pigs. 150 pigs with an initial BW of 6.80±0.32 kg (20 d of age) were randomly assigned to 5 dietary treatments as follows: i) US, basal diet+0.15% antibiotics (0.05% oxytetracycline 200 and 0.10% tiamulin 38 g), ii) BS, basal diet+0.2% synbiotics (probiotics from bacteria), iii) YS, basal diet+0.2% synbiotics (probiotics from yeast), iv) MS, basal diet+0.2% synbiotics (probiotics from mold), v) CS, basal diet+0.2% synbiotics (from compounds of bacteria, yeast and mold). The probiotics were contained in 10 9 cfu/ml, 10 5 cfu/ml and 10 3 tfu/ml of bacteria, yeast and molds, respectively. The same prebiotics (mannan oligosaccharide, lactose, sodium acetate and ammonium citrate) was used for all the synbiotics. Pigs were housed individually for a 16-day experimental period. Growth performance showed no significant difference between antibiotic treatments and synbiotics-added treatments. The BS treatment showed higher (p<0.05) dry matter (DM) and nitrogen digestibility while ether extract and crude fiber digestibility were not affected by the dietary treatment. Also, the BS treatment decreased (p<0.05) fecal ammonia and amine gas emissions. Hydrogen sulfide concentration was also decreased (p<0.05) in BS, YS and MS treatments compared to other treatments. Moreover, all the synbiotics-added treatments increased fecal acetic acid concentration while the CS treatment had lower propionic acid concentration than the US treatment (p<0.05) gas emissions but decreased in fecal propionate gas emissions. Total fecal bacteria and Escherichia coli populations did not differ significantly among the treatments, while the Shigella counts were decreased (p<0.05) in synbiotics-included treatment. Fecal bacteria population was higher in the YS treatment than other treatments (p<0.05). The BS treatment had higher yeast concentration than YS, MS and CS treatments, while US treatment had higher mold concentrations than MS treatment (p<0.05). Therefore, the results of the present study suggest that synbiotics are as effective as antibiotics on growth performance, nutrient digestibility and fecal microflora composition in weaning pigs. Additionally, synbiotics from anaerobic microflora can decrease fecal noxious gas emission and synbiotics can substitute for antibiotics in weaning pigs.
Chapter 2 Formal Design Flows for Embedded IoT Hardware

Embedded systems are usually relatively small/medium computing platforms that are self-sufficient. Such systems consist of all the software and hardware components which are “embedded” inside the system so that complete applications can be implemented and run without the aid of other external components or resources. Usually, embedded systems are found in portable computing products such as PDAs, mobile, and smart phones as well as GPS receivers. Nevertheless, larger systems such as microwave ovens and vehicle electronics contain embedded systems. Nevertheless, here embedded systems are considered that can communicate with each other by means of a wired or wireless communication protocol, such as Zigbee, IEEE.802. 11 standard, or any of its derivatives. Therefore, special attention is paid here to embedded Internet-of-Things (IoT) hardware, its design methodology, and implementation requirements. An embedded platform with such communication features can be thought of as a system that contains one or more general-purpose microprocessor or microprocessor core, a number of standard peripherals, along with a number of customized, special function co-processors, accelerators or special function engines on the same electronic board or integrated inside the same system-on-chip (SoC). Already a number of IoT manufacturers include hardware encryption and cryptography blocks in order to increase the security capability of their devices. Normally, specific blocks such as encryption/decryption and video processing engines can be attached on the embedded system’s bus and offer hardware accelerated functionality to the IoT module. An embedded and portable system that includes all of the above hardware/software modules can be thought of as a complete, standalone IoT node.
Impact of particle size, thermal processing, fat inclusion, and moisture addition on starch gelatinization of broiler feeds

The present study evaluated the effect of feed particle size, thermal processing different levels of fat inclusion and of moisture addition on the amount of gelatinized starch in a corn-soybean broiler diet. The different processing factors were combined in a 2 x 4 x 4 x 2 factorial arrangement in a three randomized block design consisting of three production series: two particle sizes (coarse: 1041 microns and medium: 743 microns), four fat inclusion levels at the mixer (15, 25, 35, and 45 g/ kg of feed), four moisture addition levels in the conditioner (0, 7, 14, and 21g/kg of feed), and two thermal processing treatments (conditioningpelleting or conditioning-expanding-pelleting) which resulted in 64 different processed feeds. For the determination of the amount of gelatinized starch one feed sample was collected per treatment in each of three production series, totaling three replicates/treatment. Data were transformed using a variation of Box-Cox transformation in order to fit normal distribution (p>0.05). Adding moisture up to 21g/kg of feed in the conditioner linearly increased the amount of gelatinized starch (p<0.05). The conditioner-expander-pelleting treatment of the diets (at 110°C) increased (p<0.05) the degree of starch gelatinization from 32.0 to 35.3 % compared with the conditioner-pelleting treatment (at 8082°C). The gelatinized starch content increased from 30.2 to 37.2% in the feed (p<0.05) as the particle size increased from medium to coarse. Fat inclusion had a quadratic effect (p<0.05) on starch gelatinization. The degree of starch gelatinization was significantly reduced with fat inclusion levels higher than 35 g/kg of diet. The factors evaluated in this study resulted in interactions and significant effects on degree of starch gelatinization.
Rapid accretion of dissolved organic carbon in the Springs of Florida: the most organic-poor natural waters

Abstract. The concentration of dissolved organic carbon (DOC) in groundwater emanating as spring discharge at several locations in Florida, USA and the net increase in DOC in the downstream receiving waters were measured as part of a larger investigation of carbon dynamics in flowing waters. Springs with high discharge (>2.8 m3 s−1) were found to be the most organic-poor natural waters yet reported (13 ± 1.6 μmol C L−1), while springs with lesser discharge exhibited somewhat higher DOC concentrations (values ranging from 30 to 77 μmol C L−1). DOC concentrations increased rapidly downstream from the point of spring discharge, with the calculated net areal input rate of DOC ranging from 0.04 to 1.64 mol C m−2 d−1 across springs. Rates of DOC increase were generally greater in those springs with high discharge rates. These input rates compare favorably with values reported for gross primary production in these macrophyte-dominated spring systems, assuming that 17% of macrophyte primary production is lost, on average, as DOC. The measures reported here are possible only because of the remarkably low DOC levels in the up-surging groundwaters and the short residency times of the water in the spring-runs themselves.
The Role of Immune Response in Optimal HIV Treatment Interventions

A mathematical model for the transmission dynamics of human immunodeficiency virus (HIV) within a host is developed. Our model focuses on the roles of immune response cells or cytotoxic lymphocytes (CTLs). The model includes active and inactive cytotoxic immune cells. The basic reproduction number and the global stability of the virus free equilibrium is carried out. The model is modified to include anti-retroviral treatment interventions and the controlled reproduction number is explored. Their effects on the HIV infection dynamics are investigated. Two different disease stage scenarios are assessed: early-stage and advanced-stage of the disease. Furthermore, optimal control theory is employed to enhance healthy CD4+ T cells, active cytotoxic immune cells and minimize the total cost of anti-retroviral treatment interventions. Two different anti-retroviral treatment interventions (RTI and PI) are incorporated. The results highlight the key roles of cytotoxic immune response in the HIV infection dynamics and corresponding optimal treatment strategies. It turns out that the combined control (both RTI and PI) and stronger immune response is the best intervention to maximize healthy CD4+ T cells at a minimal cost of treatments.