Miracle-dz/UniFAR-FTUs huggingface dataset:
Protective effect of fasudil, a Rho‐kinase inhibitor, on chemokine expression, leukocyte recruitment, and hepatocellular apoptosis in septic liver injury

Rho‐kinase signaling regulates important features of inflammatory reactions. Herein, we investigated the effect and mechanisms of action of the Rho‐kinase inhibitor fasudil in endotoxemic liver injury. C57/BL/6 mice were challenged with lipopolysaccharide (LPS) and D‐galactosamine, with or without pretreatment with the Rho‐kinase inhibitor fasudil. Six hours after endotoxin challenge, leukocyte‐endothelium interactions in the hepatic microvasculature were studied by use of intravital fluorescence microscopy and tumor necrosis factor α (TNF‐α); CXC chemokines as well as liver enzymes and apoptosis were determined. Administration of fasudil reduced LPS‐induced leukocyte adhesion in postsinusoidal venules and sequestration in sinusoids. Moreover, we found that fasudil abolished extravascular infiltration of leukocytes as well as production of TNF‐α and CXC chemokines in the liver of endotoxemic mice. Liver enzymes and hepatocellular apoptosis were markedly reduced, and sinusoidal perfusion was improved significantly in endotoxemic mice pretreated with fasudil. Our novel data document that fasudil is a potent inhibitor of endotoxin‐induced expression of TNF‐α and CXC chemokines as well as leukocyte infiltration and hepatocellular apoptosis in the liver. Based on the present findings, it is suggested that inhibition of the Rho‐kinase signaling pathway may be a useful target in the treatment of septic liver injury.
Empowering Conservation through Deep Convolutional Neural Networks and Unmanned Aerial Systems

Author(s): Epperson, Matthew | Advisor(s): Atanasov, Nikolay | Abstract: Tropical rainforests worldwide are negatively impacted from a variety of human-caused threats. Unfortunately, our ability to study these rainforests is impeded by logistical problems such as their physical inaccessibility, expensive aerial imagery, and/or coarse satellite data. One solution is the use of low-cost, Unmanned Aerial Vehicles (UAV), commonly referred to as drones. Drones are now widely recognized as a tool for ecology, environmental science, and conservation, collecting imagery that is superior to satellite data in resolution. We asked: Can we take advantage of the sub-meter, high-resolution imagery to detect specific tree species or groups, and use these data as indicators of rainforest functional traits and characteristics? We demonstrate a low-cost method for obtaining high-resolution aerial imagery in a rainforest of Belize using a drone over three sites in two rainforest protected areas. We built a workflow that uses Structure from Motion (SfM) on the drone images to create a large orthomosaic and a Deep Convolutional Neural Network (CNN) to classify indicator tree species. We selected: 1) Cohune Palm (Attalea cohune) as they are indicative of past disturbance and current soil condition; and, 2) the dry-season deciduous tree group since deciduousness is an important ecological factor of rainforest structure and function. This framework serves as a guide for tackling difficult ecological challenges and we show two additionally examples of how a similar architecture can help count wildlife populations in the Arctic.
Energy-optimized Data Serialization For Heterogeneous WSNs Using Middleware Synthesis

Developing applications for resourceconstrained devices is an intricate task in itself and additionally requires in-depth domain expertise to optimize aspects such as communication overhead, resource usage and energy consumption. Frequently, these refinements are omitted because they are time-consuming, laborious and error-prone. Hence, automating these aspects lets developers and applications intrinsically benefit from the wisdom of experts. In this paper we propose a combined approach to WSN development that is comprised of our novel data type serialization scheme microFibre and our previously published work FABRIC to generate custom tailored, lean code for heterogeneous devices. We present measurements showing that microFibre clearly outperforms existing well-known solutions in encoding quality while only moderately increasing the application’s footprint.
CHARACTERIZATION OF PHARMACEUTICAL BILAYER TABLETS: A FRACTURE MECHANICS APPROACH

OF THE DISSERTATION . ii Acknowledgements . iv Dedication . v List of Tables . viii List of Figures . ix Chapter 1: Introduction . 1 1.1 Motivation . 1 1.2 Characterization of Bilayer Tablets . 5 1.2.1 Mechanical Strength . 5 1.2.2 Characterization of Bilayer Interface . 8 1.3 Figures for Chapter 1 . 11 1.4 Tables for Chapter 1 . 13 Chapter 2: Influence of compaction properties and interfacial topography on the performance of bilayer tablets . 14 2.1 Background . 14 2.2 Materials and Methods . 17 2.2.1 Materials . 17 2.2.2 Bilayer Tablet Preparation . 17 2.2.3 Bilayer Tablet Testing . 18 2.2.4 Surface Roughness . 18 2.3 Results and Discussion . 20 2.3.1 Effect of Layer Forces on the Interfacial Strength of Bilayer Tablets made of Plastic Material . 20 2.3.2 Effect of Layer Forces on the Strength of Bilayer Tablets made of Brittle Material . 23 2.3.3 Effect of Layer Sequence on the Strength of Bilayer Tablets . 24 2.3.4 Effect of Lubricants on the Strength of Bilayer Tablets . 26 2.4 Conclusions . 26 2.5 Figures for Chapter 2 . 29 2.6 Tables for Chapter 2 . 42 Chapter 3: Application of Fracture Mechanics for the Characterization of Bilayer Tablets . 43 3.1 Background . 43 3.2 Materials and Methods . 46 3.2.1 Theory: Fracture Mechanics . 46 3.2.2 Estimation of Interfacial Stress Intensity Factor (KI) . 47 3.2.3 Materials . 49 3.2.4 Bilayer Tablet Testing . 49 3.3 Results and Discussion . 50 3.3.1 Effect of Layer Forces on Stress Intensity Factor (KI) . 51 3.3.2 Effect of Materials and First Layer Force on SIF (KI) . 53 3.3.3 Effect of Layer Sequence and Second Layer Force on SIF . 54 3.3.4 Effect of Interfacial Surface Roughness and Radius of Curvature on SIF . 55 3.4 Conclusions . 58 3.5 Figures for Chapter 3 . 60 Chapter 4: Impact of Bilayer Compression Process Parameters and Material Properties on the Mechanical Strength of Bilayer Tablets . 73 4.1 Background . 73 4.2 Factors for Design of Experiments (DOE) . 74 4.2.1 Materials: . 74 4.2.2 First Layer Force . 75 4.2.3 Second Layer Force . 76 4.2.4 Compaction Speed . 76 4.2.5 Layer Weight Ratio . 77 4.2.6 Lubricant Level . 77 4.3 Statistical Design of Experiments (DOE) . 77
Mining the stock market (extended abstract): which measure is best?

In recent years, there has been a lot of interest in the database community in mining time series data. Surprisingly, little work has been done on verifying which measures are most suitable for mining of a given class of data sets. Such work is of crucial importance, since it enables us to identify similarity measures which are useful in a given context and therefore for which efficient algorithms should be further investigated. Moreover, an accurate evaluation of the performance of even existing algorithms is not possible without a good understanding of the data sets occurring in practice. In this work we attempt to fill this gap by studying similarity measures for clustering of similar stocks (which, of course, is an interesting problem on its own). Our approach is to cluster the stocks according to various measures (including several novel ones) and compare the results to the ”groundtruth” clustering based on the Standard and Poor 500 Index. Our experiments reveal several interesting facts about the similarity measures used for stock-market data.
CLUSTERING USING COSINE AND BINARY MATCHING SIMILARITY MEASURE

Clustering is the process of grouping a set of physical objects into classes of similar object. Objects in real world consist of both numerical and categorical data. Categorical data are not analyzed as numerical data because of the absence of inherit ordering. This paper describes about occurrence based categorical data clustering (OBCDC) technique based on cosine similarity measure and simple binary matching similarity measure. The OBCDC system consists of four modules, such as data pre-processing, similarity matrix generation, cluster formation and validation. Similarity matrix generation uses three functions, namely FrequencyComputation, OccurranceBasedCosine and OccurranceBasedSBMS. The time complexity of various algorithms are discussed and its performance on real world data are measured using accuracy and error rate
Degeneracy and additional alloreactivity of drug-specific human alpha beta(+) T cell clones.

It has been well established that T cells can recognize small mol. wt compounds such as drugs. Results from previous studies revealing a high heterogeneity and cross-reactivity of drug-specific T cell clones (TCC) in individual patients prompted us to analyze the degeneracy of drug-reactive TCR in detail. Hence, we analyzed the MHC restriction pattern of a panel of 100 drug-specific TCC isolated from different drug-allergic donors. We found that 28 of the tested clones showed an MHC allele-unrestricted drug recognition. Most of these clones were at the same time highly drug specific, i.e. they could only be stimulated by the original drug and not by any drug derivatives. In contrast, TCC with the ability to interact with different drug derivatives displayed a clearly MHC allele-restricted drug recognition. Therefore, we concluded that the TCR of these clones is mainly interacting with side chains of the appropriate drug molecules and hence able to tolerate alterations in the MHC molecule. Moreover, we tested all clones for additional alloreactivity and found that 27 clones could be stimulated by a self-MHC--peptide--drug complex as well as by a non-self-MHC--peptide complex. This cross-reactivity with allogeneic MHC molecules was substantially higher in drug-specific TCC compared to tetanus toxoid-specific clones from the same donors. This suggests that from the point of view of drug-specific TCR, non-self-MHC--peptide complexes have a higher incidence to mimic the 'original' self-MHC--peptide-drug complex and this may occur for TCR recognizing self-MHC--pathogen-derived peptide complexes. Finally, the biological functions of bispecific TCC were not influenced by the nature of the stimulating ligand. Both drug as well as allogeneic stimulation led to similar reaction patterns in the analyzed TCC.
Theoretical Biology and Medical Modelling Models of Epidemics: When Contact Repetition and Clustering Should Be Included

Background: The spread of infectious disease is determined by biological factors, e.g. the duration of the infectious period, and social factors, e.g. the arrangement of potentially contagious contacts. Repetitiveness and clustering of contacts are known to be relevant factors influencing the transmission of droplet or contact transmitted diseases. However, we do not yet completely know under what conditions repetitiveness and clustering should be included for realistically modelling disease spread.
Honey and Radiation-Induced Stomatitis in Patients With Head and Neck Cancer

Background: Stomatitis is a common oral complication which affects 100% of patients undergoing head and neck radiotherapy. Acute stomatitis might cause failure and delay radiotherapy. Attention to mouth hygiene, particularly using mouthwash, has a fundamental importance for these patients. Objectives: The current study came to addresses the effects of pure natural honey on radiation-induced stomatitis in patients with a variety of head and neck cancers. Patients and Methods: The present single-blinded nonrandomized controlled trial was conducted on 105 patients undergoing radiotherapy due to head and neck cancer at the radiation unit of Shafa hospital in Kerman, Iran, from October 2012 to March 2012. The research groups were selected by writing the names of the protocols (the mouthwashes of chamomile, honey and the common caring protocol at ward which uses water) on three cubes. The first extracted cube was related to the chamomile mouthwash (Matrica), the second to the honey mouthwash and the last cube to the water mouthwash. The first experimental group (n = 35) gurgled a solution containing 20 mL diluted honey, the second group gurgled a solution containing German chamomile, and the 35 patients in the control group were advised to gurgle 20 mL water (the ward routine). Results: The results showed that severe stomatitis in groups of honey, chamomile and control was 0, 5.7%, and 17.6%, respectively. On the 14th day, it was 0, 0, and 17.6%, respectively. There were significant differences between the three groups regarding the severity of stomatitis in the 14th day (P < 0.001). Conclusions: The application of natural honey is effective in managing and preventing radiation-induced stomatitis in patients with head and neck cancers.
Bandit Algorithms boost motor-task selection for Brain Computer Interfaces

Brain-computer interfaces (BCI) allow users to “communicate” with a computer without using their muscles. BCI based on sensori-motor rhythms use imaginary motor tasks, such as moving the right or left hand, to send control signals. The performances of a BCI can vary greatly across users but also depend on the tasks used, making the problem of appropriate task selection an important issue. This study presents a new procedure to automatically select as fast as possible a discriminant motor task for a brain-controlled button. We develop for this purpose an adaptive algorithm, UCB-classif , based on the stochastic bandit theory. This shortens the training stage, thereby allowing the exploration of a greater variety of tasks. By not wasting time on inefficient tasks, and focusing on the most promising ones, this algorithm results in a faster task selection and a more efficient use of the BCI training session. Comparing the proposed method to the standard practice in task selection, for a fixed time budget, UCB-classif leads to an improved classification rate, and for a fixed classification rate, to a reduction of the time spent in training by 50%.
Inducing Gazetteers for Named Entity Recognition by Large-Scale Clustering of Dependency Relations

We propose using large-scale clustering of dependency relations between verbs and multiword nouns (MNs) to construct a gazetteer for named entity recognition (NER). Since dependency relations capture the semantics of MNs well, the MN clusters constructed by using dependency relations should serve as a good gazetteer. However, the high level of computational cost has prevented the use of clustering for constructing gazetteers. We parallelized a clustering algorithm based on expectationmaximization (EM) and thus enabled the construction of large-scale MN clusters. We demonstrated with the IREX dataset for the Japanese NER that using the constructed clusters as a gazetteer (cluster gazetteer) is a effective way of improving the accuracy of NER. Moreover, we demonstrate that the combination of the cluster gazetteer and a gazetteer extracted from Wikipedia, which is also useful for NER, can further improve the accuracy in several cases.
Obstructive Sleep Apnea and Coronary Artery Disease: From Pathophysiology to Clinical Implications

Coronary artery disease (CAD) and obstructive sleep apnea (OSA) are both complex and significant clinical problems. The pathophysiological mechanisms that link OSA with CAD are complex and can influence the broad spectrum of conditions caused by CAD, from subclinical atherosclerosis to myocardial infarction. OSA remains a significant clinical problem among patients with CAD, and evidence suggesting its role as a risk factor for CAD is growing. Furthermore, increasing data support that CAD prognosis may be influenced by OSA and its treatment by continuous positive airway pressure (CPAP) therapy. However, stronger evidence is needed to definitely answer these questions. This paper focuses on the relationship between OSA and CAD from the pathophysiological effects of OSA in CAD, to the clinical implications of OSA and its treatment in CAD patients.
Image Retrieval Based on the Color Textons Descriptor

In perceptually uniform color space, color differences can be measured in a way close to the human perception of two colors. A new feature descriptor, namely the color textons descriptor, is proposed in this paper according to the attribute of perceptually uniform color space. This descriptor can represent features via color differences in textons component images. It converts color image from RGB color space to CIE Lab color space, and then quantized the color images into 64 colors and find out the textons location in Lab color components. Finally, color differences are used to represent features and for image retrieval. Image retrieval experimental results have shown that the color textons descriptor has the discrimination power of color and texture features, and the performance is better than that of the edge histogram descriptor and LBP method significantly.
Redundancy evaluation process of processor components for permanent fault compensation

This paper presents a scalable hardware architecture for permanent fault compensation in arbitrary processor components. The utilization of this architecture is independent from the fault case and is therefore suitable for fault compensation after production as well as in the field. Through the application of this architecture, based on active hardware redundancy, a gain in reliability for a specified mission time is possible, while functionality is not degraded. System modeling in this paper enables efficiency calculations for the presented architecture considering the additional hardware for redundancy and their administrative components. Therefore an efficient selection process for processor components and their amount of redundancy is possible. Consequently, the optimal amount of redundancy for an existing system and an objective in reliability to achieve can be calculated and is furthermore available early in the design process. Beyond describing structure as well as functionality of the architecture this paper shows that the integration in existing design processes with usual methods and tools is possible. The used system model, which realizes the redundancy selection process, is described as well. Finally, an application example is used to exhibit the practicability of the presented approach. The resulting efficiency and the required costs of this approach for the chosen example are discussed.
Intensity drift removal in LC/MS metabolomics by common variance compensation

UNLABELLED Liquid chromatography coupled to mass spectrometry (LC/MS) has become widely used in Metabolomics. Several artefacts have been identified during the acquisition step in large LC/MS metabolomics experiments, including ion suppression, carryover or changes in the sensitivity and intensity. Several sources have been pointed out as responsible for these effects. In this context, the drift effects of the peak intensity is one of the most frequent and may even constitute the main source of variance in the data, resulting in misleading statistical results when the samples are analysed. In this article, we propose the introduction of a methodology based on a common variance analysis before the data normalization to address this issue. This methodology was tested and compared with four other methods by calculating the Dunn and Silhouette indices of the quality control classes. The results showed that our proposed methodology performed better than any of the other four methods. As far as we know, this is the first time that this kind of approach has been applied in the metabolomics context. AVAILABILITY AND IMPLEMENTATION The source code of the methods is available as the R package intCor at http://b2slab.upc. edu/software-and-downloads/intensity-drift-correction/. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
POTENCIAL PEDOCLIMÁTICO DO ESTADO DA PARAÍBA PARA A CULTURA DA CANA DE AÇÚCAR (SACCHARUM SPP) / PEDOCLIMATIC POTENTIAL OF THE PARAÍBA STATEFOR CULTURE OF THE SUGAR CANE (SACCHARUM SPP)

doi: 10.12957/geouerj.2017. 23167 Este trabalho objetivou avaliar o potencial pedoclimatico do Estado da Paraiba para a cultura agricola da cana de acucar. Na obtencao dos mapas de potencial pedoclimatico, as informacoes do potencial dos solos foram cruzadas com as da aptidao climatica considerando tres cenarios pluviometricos: anos chuvosos, anos regulares e anos secos. O cruzamento das informacoes foi realizado por meio de tecnicas de geoprocessamento utilizando o software SPRING e obtendo-se os mapas do potencial pedoclimatico. O resultado das interpretacoes foi classificado em quatro classes de potencial pedoclimatico: Muito Alto, Alto, Medio, Baixo e Muito Baixo. Com o uso de tecnicas de geoprocessamento foi possivel a espacializacao das areas e definir os ambientes favoraveis de potencial da cultura da cana de acucar. Foram observadas diferencas significativas na extensao territorial das classes e subclasses de potencial pedoclimatico do Estado da Paraiba que apresentou variacoes de ordem pedologica e climatica em seu territorio, influenciando no potencial pedoclimatico para a cultura da cana de acucar. O potencial de cultivo da cana de acucar esta concentrado no Litoral do Estado e em pequena area na regiao do Brejo. O potencial pedoclimatico Muito Alto nao foi representado no mapeamento devido as restricoes pedologicas e climaticas. A exigencia hidrica e pedologica para a cultura da cana de acucar restringiu as areas de plantio no Estado. Nao foi possivel mapear areas menores, devido a escala de trabalho, havendo a possibilidade do cultivo da cultura da cana de acucar em pequenas areas que nao foram identificadas neste trabalho.
Mouth morphometry and body lengths with respect to the feeding habits of Hill stream fishes from Western Himalaya H.P. (INDIA)

The hill stream fishes viz. Barilius bendelisis (Hamliton), Crossocheilus latius latius (Hamliton), Garra gotyla gotyla (Gray), Pethia ticto (Hamliton), Schizothorax richardsonii (Gray) and Mastacembelus armatus (Lecepede) collected from the streams of the Beas Drainage system (Himachal Pradesh) have been selected for the studies. The inter-relationship between mouth dimensions and relationship between mouth size dimensions & different body length i.e. HL and TL have been undertaken. Further, the mouth modification with respect to food and feeding habits has been explored which is helpful in understanding the trophic level of the fishes. During the studies it has been analysed that in case of B. bendelisis VG was almost equal to HG as such belong to the category of surface feeder- omnivore. M. armatus and P. ticto exhibited VG greater than HG and adopted for column-omnivore/carnivore feeding habit whereas in G. gotyla gotyla, S. richardsonii and C. latius latius HG was greater than VG and adopted for bottom- herbivore habit. The analytical techniques of statistics were used to analyse and interpret the results by using SPSS-16.0 software.
Generalized NoGoods in CSPs

Although nogood learning in CSPs and clause learning in SAT are formally equivalent, nogood learning has not been as successful a technique in CSP solvers as clause learning has been for SAT solvers. We show that part of the reason for this discrepancy is that nogoods in CSPs (as standardly defined) are too restrictive. In this paper we demonstrate that these restrictions can be lifted so that a CSP solver can learn more general and powerful nogoods. Nogoods generalized in this manner yield a provably more powerful CSP solver. We also demonstrate how generalized nogoods facilitate learning useful nogoods from global constraints. Finally, we demonstrate empirically that generalized nogoods can yield significant improvements in performance.