Miracle-dz/UniFAR-FTUs huggingface dataset:
The repurposing of Tebipenem pivoxil as alternative therapy for severe gastrointestinal 1 infections caused by extensively drug resistant Shigella spp . 2 3

infections caused by extensively drug resistant Shigella spp. 2 3 Elena Fernández Alvaro , Phat Voong Vinh , Cristina de Cozar , David Wille , Beatriz Urones , 4 Alvaro Cortés , Alan Price , Nhu Tran Do Hoang , Tuyen Ha Thanh , Molly McCloskey , Shareef Shaheen , 5 Denise Dayao , Jaime de Mercado , Pablo Castañeda , Adolfo García-Perez , Benson Singa , Patricia 6 Pavlinac , Judd Walson, Maria Santos Martínez-Martínez , Samuel L.M. Arnold , Tzipori Saul , 7 Lluis Ballell , and Stephen Baker 7,8* 8 9 1 GSK Global Health, Tres Cantos, Madrid, Spain 10 2 The Hospital for Tropical Diseases, Wellcome Trust Major Overseas Programme, Oxford University Clinical 11
A Concept of an In-Memory Database for IoT Sensor Data

In the context of digital transformation and use of Industry 4.0 technology in companies, machines and other objects are increasingly being equipped with sensors. Normally, these machines are monitored 24/7, so that data streams are continuously generated by sensors. These data has to be stored in a database. In order to facilitate a fast data mining process and the use of machine learning algorithms, a performant and robust data store for the vast amount of sensor data is necessary. These raw time series sensor data has typical structures that are difficult to model with traditional database management systems. Here, column-oriented In-Memory databases like SAP HANA or Gorilla are better suited. However, SAP HANA have not been developed to store relational data, so that it contains components like transaction and concurrency control, which are unnecessary for the named range of application, because machine learning algorithms only need reading access. By reducing this concept to the essentials, a specialized, lightweight In-Memory database management system can be developed, which perfectly fits to the characteristics of time series sensor data. For that concept the benefits of the In-Memory data structure of SAP HANA and Facebook Gorilla are merged and combined with additional meta information like limits for minimum and maximum warning for each sensor, special user specified column fields or rules for sampling and replenishment values. The evaluation of the implemented prototype shows on the one hand that the time series sensor data can be stored efficiently using a new table structure and an intelligent combination of the ZFP compression method with a block orientated data structure, which results in a good insert performance. On the other hand, this storage logic leads to an efficient data access of the compressed in-memory data structure, thus every reporting or analyzing tasks access the data efficiently and fast.
Farming in the Langkloof : coping with and adapting to environmental shock and social stress

During the period 2006-2012, the Langkloof area, situated in the Eden District Municipality, suffered severely from environmental shocks and social stress including drought, flooding, hail, wildfire, heatwaves and reduced labour demand. These events negatively impacted many farmers and their livelihoods. In response to these external shocks and stressors, large-, mediumand small-scale farmers adopted numerous coping and adaptive strategies. This study performed a comprehensive livelihoods analysis of large-, mediumand small-scale farmers in the Langkloof area, using the widely recognized sustainable livelihoods framework developed by the United Kingdom’s Department for International Development, with a particular focus on coping and adaptive strategies against severe environmental shock and social stress. Variables used in the analysis were the vulnerability context in which farmers pursue a livelihood; livelihood assets (social, human, financial, natural and physical); the policies, institutions and processes in the external environment that influence the degree of ownership and access to assets; livelihood strategies pursued; and the various livelihood outcomes ultimately produced. The analysis of coping and adaptive strategies employed by farmers during these periods formed an integral part of this study. Sixteen livelihood asset indicators were identified to determine the total assets (human, social, physical, financial and natural) of the farmers. After scaling the indicators, a Principal Component Analysis (PCA) was used to assign weights to each indicator and to subsequently calculate the total assets of each household. Regarding the coping and adaptive strategies employed by farmers against environmental shock and social stress, the average number of strategies was calculated for each household. Spearman’s rank correlations were calculated for total assets achieved (capacity) and the number of strategies employed against environmental shock and social stress.
An Empirical Study on Principal Component Analysis for Clustering Gene Expression Data an Empirical Study on Principal Component Analysis for Clustering Gene Expression Data

There is a great need to develop analytical methodology to analyze and to exploit the information contained in gene expression data. Because of the large number of genes and the complexity of biological networks, clustering is a useful exploratory technique for analysis of gene expression data. Other classical techniques, such as principal component analysis (PCA), have also been applied to analyze gene expression data. Using different data analysis techniques and different clustering algorithms to analyze the same data set can lead to very different conclusions. Our goal is to study the effectiveness of principal components (PC's) in capturing cluster structure. In other words, we empirically compared the quality of clusters obtained from the original data set to the quality of clusters obtained from clustering the PC's using both real gene expression data sets and synthetic data sets. Our empirical study showed that clustering with the PC's instead of the original variables does not necessarily improve cluster quality. In particular, the first few PC's (which contain most of the variation in the data) do not necessarily capture most of the cluster structure. We also showed that clustering with PC's has different impact on different algorithms and different similarity metrics.
An empirical study on Principal Component Analysis for clustering gene expression data

There is a great need to develop analytical methodology to analyze and to exploit the information contained in gene expression data. Because of the large number of genes and the complexity of biological networks, clustering is a useful exploratory technique for analysis of gene expression data. Other classical techniques, such as principal component analysis (PCA), have also been applied to analyze gene expression data. Using different data analysis techniques and different clustering algorithms to analyze the same data set can lead to very different conclusions. Our goal is to study the effectiveness of principal components (PC's) in capturing cluster structure. In other words, we empirically compared the quality of clusters obtained from the original data set to the quality of clusters obtained from clustering the PC's using both real gene expression data sets and synthetic data sets. Our empirical study showed that clustering with the PC's instead of the original variables does not necessarily improve cluster quality. In particular, the first few PC's (which contain most of the variation in the data) do not necessarily capture most of the cluster structure. We also showed that clustering with PC's has different impact on different algorithms and different similarity metrics.
Extrapolation of bidirectional texture functions using texture synthesis guided by photometric normals

Numerous applications in computer graphics and beyond benefit from accurate models for the visual appearance of real-world materials. Data-driven models like photographically acquired bidirectional texture functions (BTFs) suffer from limited sample sizes enforced by the common assumption of far-field illumination. Several materials like leather, structured wallpapers or wood contain structural elements on scales not captured by typical BTF measurements. We propose a method extending recent research by Steinhausen et al. to extrapolate BTFs for large-scale material samples from a measured and compressed BTF for a small fraction of the material sample, guided by a set of constraints. We propose combining color constraints with surface descriptors similar to normal maps as part of the constraints guiding the extrapolation process. This helps narrowing down the search space for suitable ABRDFs per texel to a large extent. To acquire surface descriptors for nearly at materials, we build upon the idea of photometrically estimating normals. Inspired by recent work by Pan and Skala, we obtain images of the sample in four different rotations with an off-the-shelf flatbed scanner and derive surface curvature information from these. Furthermore, we simplify the extrapolation process by using a pixel-based texture synthesis scheme, reaching computational efficiency similar to texture optimization.
ACCELERATED TEMPLATE MATCHING USING LOCAL STATISTICS AND FOURIER TRANSFORMS

This paper presents a method to accelerate correlation-based image template matching using local statistics that are computed by Fourier transform cross correlation. This approach is applicable to several different metrics. The concept is based upon equivalent spatial and frequency domain principles. Each metric is computed completely in the frequency domain using Discrete Fourier Transforms. Timing results are shown to be independent of the size of the smaller template image.
Review on raindrop detection and removal in weather degraded images

Bad weather conditions lead the robustness of most surveillance and driver assistance system. Therefore this paper attempts to review the type of bad weather in a perspective of computer vision and image processing and some recent effort on raindrop detection and removal techniques which has been successfully designed and developed to enhance the image degraded by the bad weather.
Acta Tropica Trypanosoma Cruzi Nucleoside Triphosphate Diphosphohydrolase 1 (tcntpdase-1) Biochemical Characterization, Immunolocalization and Possible Role in Host Cell Adhesion

Keywords: Recombinant protein Trypanosoma cruzi Nucleoside triphosphate diphosphohydrolase Immunolocalization Adhesion a b s t r a c t Previous work has suggested that Trypanosoma cruzi diphosphohydrolase 1 (TcNTPDase-1) may be involved in the infection of mammalian cells and serve as a potential target for rational drug design. In this work, we produced recombinant TcNTPDase-1 and evaluated its nucleotidase activity, cellular localiza-tion and role in parasite adhesion to mammalian host cells. TcNTPDase-1 was able to utilize a broad range of triphosphate and diphosphate nucleosides. The enzyme's K m for ATP (0.096 mM) suggested a capability to influence the host's ATP-dependent purinergic signaling. The use of specific polyclonal antibodies allowed us to confirm the presence of TcNTPDase-1 at the surface of parasites by confocal and electron microscopy. In addition, electron microscopy revealed that TcNTPDase-1 was also found in the flagellum, flagellum insertion region, kinetoplast, nucleus and intracellular vesicles. The presence of this enzyme in the flagellum insertion region and vesicles suggests that it may have a role in nutrient acquisition, and the widespread distribution of TcNTPDase-1 within the parasite suggests that it may be involved in other biological process. Adhesion assays using anti-TcNTPDase-1 polyclonal antibodies as a blocker or purified recombinant TcNTPDase-1 as a competitor revealed that the enzyme has a role in parasite–host cell adhesion. These data open new frontiers to future studies on this specific parasite–host interaction and other unknown functions of TcNTPDase-1 related to its ubiquitous localization. Open access under CC BY-NC-ND license. Open access under CC BY-NC-ND license.
Higher Energy Does Not Mean Better Outcome Following Endovenous Laser Ablation of Great Saphenous Vein

Background: Endovenous laser ablation is a relatively newer alternative to treat great saphenous vein insufficiency. We evaluated the efficiency and safety of treatment endovenous laser procedures on the different saphenous vein diameters with different energy levels. Methods: Data regarding endovenous laser ablation of symptomatic chronic great saphenous venous insufficiency in 209 patients were prospectively recorded. Patients were grouped into two main groups based on their diameters as 5 to 7 millimeters (Group A) or more than 7 millimeters (Group B). Patients in each group was randomized into two groups as >90 J/cm (A1 and B1) or 80-90 J/cm (A2 and B2). Postoperative outcome and complications were recorded during follow-ups at 1st week; 1st, 3rd and 6th months to examine the venous reflux and recanalization. Results: Perioperative complaints as pain, cramps and ankle swelling were more commonly observed in A1 group. Fatigue was more common in A2 and B2 groups. No major complications as deep vein thrombosis or skin burns were observed. Conclusions: Endovenous laser ablation is a safe and effective procedure with a high satisfaction rate shortening hospitalization durations and early ambulant activity. Pain, ankle swelling and fatigue are the most common minor complaints in the early postoperative period.
Dealing with uncertain feature assessments in interactive object recognition

Object recognition is a typical task of aerial reconnaissance and especially in military applications, to determine the class of an unknown object on the battlefield can give valuable information on its capabilities and its threat. RecceMan® (Reconnaissance Manual) is a decision support system for object recognition developed by the Fraunhofer IOSB. It supports object recognition by automating the tedious task of matching the object features with the set of possible object classes, while leaving the assessment of features to the trained human interpreter. The quality of the features assessed by the user is influenced by several factors such as the quality of the image of the object. These factors are potential sources of error, which can lead to an incorrect classification and therefore have to be considered by the system. To address this issue, two methods for consideration of uncertainty in human feature assessment - a probabilistic and a heuristic approach - are presented and compared based on an experiment in the exemplary domain of flower recognition.
Genetic diversity in section Rhizomatosae of the genus Arachis (Fabaceae) based on microsatellite markers

The genus Arachis (Fabaceae) native to South America, contains 80 species divided into nine sections, three of which contain species of special economic importance such as the cultivated peanut (Arachis hypogaea), belonging to the section Arachis, and some perennial forage species from sections Caulorrhizae and Rhizomatosae. We used microsatellite markers to assay genetic variability among 77 accessions of four species from section Rhizomatosae, the diploid Arachis burkartii (2n = 2x = 20) and the tetraploid Arachis glabrata, Arachis pseudovillosa and Arachis nitida (2n = 4x = 40). A total of 249 alleles were found in the fifteen loci analyzed and a high degree of intra and interspecific polymorphism was detected. The lowest intraspecific variation occurred in Arachis burkartii, while the smallest estimated interspecific value was between A. nitida and A. pseudovillosa and the largest was between A. burkartii and A. nitida. High observed heterozygosity was detected in A. glabrata. The diploid accessions grouped in one cluster and the tetraploid accessions in another. It was possible to distinguish all 77 accessions and the genetic distance between accessions could not be correlated with geographic origin.
EGF stimulates proliferation of mouse embryonic stem cells: involvement of Ca 2 (cid:1) inﬂux and p44/42 MAPKs

EGF stimulates proliferation of mouse embryonic cells: involvement of Ca (cid:1) inﬂux and p44/42 MAPKs. 290: C123–C133, 2006. We examined the effect of EGF on the proliferation of mouse embryonic stem (ES) cells and their related signal pathways. EGF increased [ 3 H]thymidine and 5-bromo-2 (cid:2) -deoxyuridine incorporation in a time-and dose-dependent manner. EGF stimulated the phosphorylation of EGF receptor (EGFR). Inhibition of EGFR tyrosine kinase with AG-1478 or herbimycin A, inhibition of PLC with neomycin or U-73122, inhibition of PKC with bisindolylmaleimide I or staurosporine, and inhibition of L-type Ca 2 (cid:1) channels with nifedipine or methoxyverapamil prevented EGF-induced [ 3 H]thymidine incorporation. PKC- (cid:3) , - (cid:4) I , - (cid:5) , - (cid:6) , and - (cid:7) were translocated to the membrane and intracellular Ca 2 (cid:1) concentration ([Ca 2 (cid:1) ] i ) was increased in response to EGF. Moreover, inhibition of EGFR tyrosine kinase, PLC, and PKC completely prevented EGF-induced increases in [Ca 2 (cid:1) ] i . EGF also increased inositol phosphate levels, which were blocked by EGFR tyrosine kinase inhibitors. Furthermore, EGF rapidly increased formation of H 2 O 2 , and pretreatment with antioxidant ( N -acetyl- L - cysteine) inhibited EGF-induced increase of [Ca 2 (cid:1) ] i . In addition, we observed that p44/42 MAPK phosphorylation by EGF and inhibition of EGFR tyrosine kinase, PLC, PKC, or Ca 2 (cid:1) channels blocked EGF-induced phosphorylation of p44/42 MAPKs. Inhibition of p44/42 MAPKs with PD-98059 (MEK inhibitor) attenuated EGF-induced increase of [ 3 H]thymidine incorporation. Finally, inhibition of EGFR tyrosine kinase, PKC, Ca 2 (cid:1) channels, or p44/42 MAPKs attenuated EGF-stimulated cyclin D1, cyclin E, cyclin-dependent kinase (CDK)2, and CDK4, respectively. In conclusion, EGF partially stimulates proliferation of mouse ES cells via PLC/PKC, Ca 2 (cid:1) inﬂux, and p44/42 MAPK signal pathways through EGFR tyrosine kinase phosphorylation.
Dielectric Properties of Composites Based on Nanocrystalline Cellulose and Triglycine Sulfate

This paper is devoted to studies of properties of composites based on nanocrystalline cellulose and triglycine sulfate. The presence of one or two peaks in the temperature dependence of dielectric permittivity was revealed and their shift to higher temperatures as compared with the bulk TGS to 54°C and 100°C was detected, respectively. An explanation of the results is related to the appearance of internal bias fields in the nanocomposites.
Hadoop Fair Sojourn Protocol Based Job Scheduling On Hadoop

: We present Hadoop Fair Scheduler Protocol, a scheduler introducing this technique to a real, multi-server, complex and widely used system such as Hadoop. The scheduling discipline is based on the concepts of virtual time and job aging. These techniques are conceived to operate in a multi server system with tolerance to failures, scale-out upgrades, and multi-phase jobs a peculiarity of Map Reduce. The results indicate that size-based scheduling is a realistic option for Hadoop clusters, because HFSP sustains even rough approximations of job sizes. Which are based on realistic workloads generated via a standard benchmarking suite, pinpoint at a significant decrease in system response times with respect to the widely used Hadoop Fair scheduler, without impacting the fairness of the scheduler, and show that HFSP is largely tolerant to job size estimation errors.
Determinants of adoption of mobile phone banking by the base of pyramid (BOP) customers of commercial banks in Kenya

v TABLE OF CONTENTS . vi LIST OF TABLES . vii CHAPTER ONE: INTRODUCTION . 1 1.1 Background to the study . 1 1.1.1 Customers at the Base of Pyramid (BOP) . 2 1.1.2 The Concept of Mobile Phone Banking . 2 1.1.3 Adoption of Innovation . 4 1.1.4 Commercial banks in Kenya . 5 1.2 Research Problem . 6 1.3 Research Objectives . 7 1.4 Value of the study . 7 CHAPTER TWO: LITERATURE REVIEW . 8 2.
Effect of spacing and cutting management on survival, growth and biomass production of Moringa oleifera intercropped with maize on-farm at Gairo inland plateau, Morogoro in Tanzania

A study was carried out at Gairo, Tanzania to determine appropriate planting spacing and cutting management for optimising maize yield without jeorpadising the potential of Moringa oleifera to produce sufficient biomass. Two trials (on-farm spacing-intercropping and on-farm pollarding height-intercropping) were laid out using Randomized Complete Block Design (RCBD). Assessments were done at tree ages of 6, 12, and18 for the spacing trial and at tree ages of 6, 12, 18, 24 and 36 months for the pollarding trial. Grain weights were measured on a yearly basis (seasons). Plot means for all response variables were subjected to standard Analysis Of Variance (ANOVA) and significant means were separated by Duncan’s Multiple Range Test (DMRT). Results for the spacing trial showed that, overall all growth parameters increased significantly with spacing, and tree growth was generally higher in monoculture compared to intercropped plots. During the last assessment, foliar and stem biomass ranged from 571.57 kg/ha for maize+150cm pollarding height to 682.15 kg/ha for maize+50 cm pollarding height and from 181.72 kg/ha for 150 cm pollarding height to 254.29 kg/ha for maize+100 cm pollarding height respectively. Moringa intercropping is recommended to be done only during the first cropping season, due to severe competition thereafter.
DYNAMICS OF MACROINVERTEBRATE DRIFT IN A LOWLAND RIVER

Macroinvertebrate drift in the fourth order section of the lowland Drzewiczka River was investigated in the main types of habitats, over the annual cycle. The percentage of macroinvertebrate biomass in the water column in the total trans- ported organic matter was low. Terrestrial invertebrates, mainly winged insects, varied among seasons and habitats, reaching from 13.1% to 49.8% of total drift biomass. Abundance of aquatic macroinvertebrates was roughly congruent with the ranges of values reported from other rivers and differed from habitat to habitat, season to season and between season x habitat pairs (two-way ANOVA). Among agile swimmers Ephemeroptera, and among the other taxa Orthocladiinae and Tanytarsini (Chironomidae) and Naididae (Oligochaeta) showed the highest propensity to drift.
Quality Perspective on the Dynamic Balance of Cultivated Land in Wenzhou, China

Cultivated land in China has faced severe challenges in recent years due to rapid urbanization. In 1997, the “cultivated land requisition-compensation balance” policy was implemented by the government to maintain the quantity and quality of cultivated land. Previous studies mainly focused on the quantity changes of cultivated land. In this study, from a quality perspective, we characterized the occupation and compensation of cultivated land in Wenzhou City utilizing remote sensing and geographic information systems during 2005–2010 and 2010–2014. Our results indicated that although the quantity balance of cultivated land has been achieved in Wenzhou, there was a trend of consuming prime cultivated land for urbanization while compensating with less productive land. It was also found that topography, water resources, and accessibility play important roles in cultivated land changes, with urbanization occurring on the eastern coastal plain where high quality lands are prevalent. Less than 60% of the gained lands were under cultivation, with the majority of reclaimed land from forests and coastal areas and located in remote regions. Therefore, we suggest that a “cultivated land protection red line” policy should be implemented to protect the best cultivated lands, while preventing random land reclamation to secure agricultural and environmental sustainability.