Miracle-dz/UniFAR-FTUs huggingface dataset:
Characterization of the universal stress protein F from atypical enteropathogenic Escherichia coli and its prevalence in Enterobacteriaceae

Atypical enteropathogenic Escherichia coli (aEPEC) are heterogeneous strains in terms of serotypes, adherence patterns and the presence of novel virulence factors. This heterogeneity is intriguing, promoting studies trying to characterize these novel proteins and to better comprehend this pathotype group. In a previous study analyzing low‐molecular mass proteomes of four representative aEPEC strains of three different adhesion phenotypes, we classified proteins according to their annotated function, with most of them being involved in metabolism and transport; while some of them were classified as hypothetical proteins. The majority of the hypothetical proteins were homologue products of genes identified in the genome of enterohemorrhagic E. coli. One of the hypothetical proteins was annotated as Z2335, with orthologue in EPEC, and by bioinformatics analysis, this protein was revealed to be the universal stress protein F (UspF). Thus, herein we successfully obtained a recombinant UspF protein from aEPEC, which is a α/β, ATP‐binding protein involved in stress response, with comparable protein production among the four studied strains, but showing noteworthy differences when cultivated in different stress conditions, also present in other enterobacterial species, such as Shigella sonnei and Citrobacter freundii. Furthermore, our results confirm that the Usp protein superfamily encompasses a conserved group of proteins involved in stress resistance in aEPEC and other Enterobacteriaceae.
Chemical Variations in Peridotite Xenoliths from Vitim, Siberia: Inferences for REE and Hf Behaviour in the Garnet-Facies Upper Mantle

Peridotite xenoliths in a Miocene picrite tuff from the Vitim volcanic province east of Lake Baikal, Siberia, are samples of the off-craton lithospheric mantle that span a depth range from the spinel to garnet facies in a mainly fertile domain. Their major and trace element compositions show some scatter (unrelated to sampling or analytical problems), which is not consistent with different degrees of partial melting or metasomatism. Some spinel peridotites and, to a lesser degree, garnet-bearing peridotites are depleted in heavy rare earth elements (HREE) relative to middle REE (MREE), whereas some garnet peridotites are enriched in HREE relative to MREE, with Lu abundances much higher than in primitive mantle estimates. Clinopyroxenes from several spinel peridotites have HREE-depleted patterns, which are normally seen only in clinopyroxenes coexisting with garnet. Garnets in peridotites with similar modal and major element compositions have a broad range of Lu and Yb abundances. Overall, HREE are decoupled from MREE and Hf and are poorly correlated with partial melting indices. It appears that elements with high affinity to garnet were partially redistributed in the Vitim peridotite series following partial melting, with few effects for other elements. The Lu---Hf decoupling may disturb Hf-isotope depletion ages and their correlations with melting indices.
Immigration, Ancestry and Residence in Sydney

The paper examines the ancestry of Europeans in Sydney and that of the two largest non European groups. Spatial divergence occurs between the English, Scottish and Irish, and divergence from those of Australian ancestry. Residential persistence across generations occurs with persons of Greek, Italian, Maltese and Dutch origins, but not spatial segmentation. While there is greater language persistence in Greek and Italian second and third settlement concentrations, few third generation persons speak their ancestral language at home. The Chinese and Lebanese are compared with Greek and Italian ancestry in their areas of strongest representation. First generation Chinese are evident in areas of both low and high socioeconomic status, but without third generation language persistence. An evolving ethnic mix in Sydney is indicated.
Attentive Interactive Neural Networks for Answer Selection in Community Question Answering

Answer selection plays a key role in community question answering (CQA). Previous research on answer selection usually ignores the problems of redundancy and noise prevalent in CQA. In this paper, we propose to treat different text segments differently and design a novel attentive interactive neural network (AI-NN) to focus on those text segments useful to answer selection. The representations of question and answer are first learned by convolutional neural networks (CNNs) or other neural network architectures. Then AI-NN learns interactions of each paired segments of two texts. Row-wise and column-wise pooling are used afterwards to collect the interactions. We adopt attention mechanism to measure the importance of each segment and combine the interactions to obtain fixed-length representations for question and answer. Experimental results on CQA dataset in SemEval-2016 demonstrate that AI-NN outperforms state-of-the-art method.
Deep Transfer Learning Technique for Potato Leaf Diseases Classification

Potato, a globally significant food crop ranking as the fourth largest by production, is cultivated in various regions worldwide. However, potato crops are notably susceptible to fungal infections, leading to the occurrence of early blight and late blight diseases. Timely disease control and management measures are pivotal in augmenting crop yields and mitigating agricultural losses for farmers. The capacity to automatically discern diseased crops holds substantial promise for farmers. Consequently, this research endeavors to present the power of transfer learning in SoTA Convolutional Neural Network (CNN) architecture ResNet-50v2 and DenseNet-201 which are finetuned to the task of potato disease detection. In our experimental endeavors, we employed three distinct datasets, and in each instance, we attained state-of-the-art results.
Globally Consistent Multi-People Tracking using Motion Patterns

Many state-of-the-art approaches to people tracking rely on detecting them in each frame independently, grouping detections into short but reliable trajectory segments, and then further grouping them into full trajectories. This grouping typically relies on imposing local smoothness constraints but almost never on enforcing more global constraints on the trajectories. In this paper, we propose an approach to imposing global consistency by first inferring behavioral patterns from the ground truth and then using them to guide the tracking algorithm. When used in conjunction with several state-of-the-art algorithms, this further increases their already good performance. Furthermore, we propose an unsupervised scheme that yields almost similar improvements without the need for ground truth.
Intraretinal Layer Segmentation of Macular Optical Coherence Tomography Images Using Optimal 3-D Graph Search

Current techniques for segmenting macular optical coherence tomography (OCT) images have been 2-D in nature. Furthermore, commercially available OCT systems have only focused on segmenting a single layer of the retina, even though each intraretinal layer may be affected differently by disease. We report an automated approach for segmenting (anisotropic) 3-D macular OCT scans into five layers. Each macular OCT dataset consisted of six linear radial scans centered at the fovea. The six surfaces defining the five layers were identified on each 3-D composite image by transforming the segmentation task into that of finding a minimum-cost closed set in a geometric graph constructed from edge/regional information and a priori determined surface smoothness and interaction constraints. The method was applied to the macular OCT scans of 12 patients (24 3-D composite image datasets) with unilateral anterior ischemic optic neuropathy (AION). Using the average of three experts' tracings as a reference standard resulted in an overall mean unsigned border positioning error of 6.1 plusmn 2.9 mum, a result comparable to the interobserver variability (6.9 plusmn 3.3 mum). Our quantitative analysis of the automated segmentation results from AION subject data revealed that the inner retinal layer thickness for the affected eye was 24.1 mum (21%) smaller on average than for the unaffected eye (p < 0.001), supporting the need for segmenting the layers separately.
Correction to “Oceanic uptake and the global atmospheric acetone budget”

] In the paper ‘‘Oceanic uptake and the global atmo-spheric acetone budget’’ by C. A. Marandino et al. (Geo-phys. Res. Lett., 32, L15806, doi:10.1029/2005GL023285)it was recently determined that a calculation error was madeduring flux data processing. The flux data has been reproc-essed and all the values in both the text and figures havebeen recomputed. The qualitative discussion and conclu-sions remain the same. After the data was reprocessed, itwas determined that the low frequency correction could bemodified. Instead of eliminating the power at frequencieslower than 5E-3 Hz in all of the records, a low frequencydiagnostic was created to assess whether the record shouldbe retained at all. This diagnostic was the ratio between theflux at the 5E-3 Hz cutoff and the full flux (i.e. no cutoff). Ifthe ratio indicated a difference greater than 30%, the recordwas not included in the final dataset. The entire dataprocessing procedure will be published in the Journal ofGeophysical Research [Marandino et al., 2006]. A secondcalculationerrorwasfoundintheuncertaintyanalysisfortheglobal acetone sink budget. Corrected versions of Table 1and Figures 1–3 from the original paper are given. Anadditional table (Table 2) has been included listing therecomputed values of several quantities discussed in theoriginal paper.
A Novel Testis-Enriched Gene Spata33 Is Expressed during Spermatogenesis

With an increasing incidence of male idiopathic infertility, identification of novel genes involved in spermatogenesis is an important aspect for the understanding of human testicular failure. In the present study, we have identified a novel gene Spata33, also called as 4732415M23Rik or C16orf55, which is conserved in mammalian species. Spata33 was predominantly expressed in the postpartum and adult mouse testes at mRNA and protein levels. Its expression was increased during the first wave of the spermatogenesis, indicating that Spata33 may be associated with the meiotic process. Further immunohistochemistry analysis revealed that Spata33 was mainly expressed in the spermatocytes, spermatogonia and round spermatids. Its expression was uniformly distributed in the nucleus and cytosol in these germ cells, which was further confirmed by Spata33-tagged with GFP staining in the GC-1 and TM4 cells. These results indicated that Spata33 was predominantly expressed in the mouse testis and associated with spermatogenesis. Identification and characterization of the novel testis-enriched gene Spata33 may provide a new route for understanding of spermatogenesis failure.
Components of Exercise Prescription and Pregnancy

Physicians should discuss decreasing sedentary time and behavior with their pregnant patients to assist sedentary women to become more active using light activities. Medical screening before engaging or continuing in a moderate aerobic exercise program is vital to ensure a low-risk pregnancy. The FITT principle is important to use in prescription that suggests: Frequency (3 to 4 times per week), Intensity (appropriate target heart rate zone, rating of perceived exertion scale, or the talk test), Time (start at 15 min progressing to 30 min), and Type (moving large muscles groups such as walking, swimming, and cycling) of physical activity.
RSS-based node localization in the presence of attenuating objects

Node localization is an important task in the context of wireless sensor networks. Although algorithms already exist to carry out localization using measurements of received signal strength (RSS), none of these methods take into account the attenuating and scattering effects of objects which lie within or around the network and which therefore affect the obtained RSS measurements. In this paper, we use a map of the attenuations seen over a given area in order to reinterpret the measured RSS values, thereby refining RSS-based node localization and providing significant improvements over existing algorithms. Simulation results are presented to demonstrate the performance gains which can be achieved using our method.
DEFORMATION AND STRESS-CHANGE MODELING AT SIERRA NEGRA VOLCANO, GALÁPAGOS, FROM ENVISAT INSAR AND GPS OBSERVATIONS

We use radar interferograms and GPS observations to constrain models of magma accumulation and faulting at Sierra Negra volcano, Galapagos, during the years before its 2005 eruption. The data have shown ~5 m of pre-eruption uplift and multiple trapdoor faulting events on an intra-caldera fault system. We find the pattern of uplift to be consistent with an inflating sill at 2.2 km depth under the caldera. Our deformation modeling and stress-change calculations suggest that the inflating sill triggered faulting on an inwarddipping thrust fault and that the faulting in turn relieved the pressure within the sill. This sill-fault interaction tends to thicken the sill and limit its lateral extent within the area bounded by the fault.
Scalable supervised dimensionality reduction using clustering

The automated targeting of online display ads at scale requires the simultaneous evaluation of a single prospect against many independent models. When deciding which ad to show to a user, one must calculate likelihood-to-convert scores for that user across all potential advertisers in the system. For modern machine-learning-based targeting, as conducted by Media6Degrees (M6D), this can mean scoring against thousands of models in a large, sparse feature space. Dimensionality reduction within this space is useful, as it decreases scoring time and model storage requirements. To meet this need, we develop a novel algorithm for scalable supervised dimensionality reduction across hundreds of simultaneous classification tasks. The algorithm performs hierarchical clustering in the space of model parameters from historical models in order to collapse related features into a single dimension. This allows us to implicitly incorporate feature and label data across all tasks without operating directly in a massive space. We present experimental results showing that for this task our algorithm outperforms other popular dimensionality-reduction algorithms across a wide variety of ad campaigns, as well as production results that showcase its performance in practice.
Assessment of Bone Quality within the Tuberosities of the Osteoporotic Humeral Head

Background Tears of the rotator cuff are highly prevalent in patients older than 60 years, thereby presenting a population also suffering from osteopenia or osteoporosis. Suture fixation in the bone depends on the holding strength of the anchoring technique, whether a bone tunnel or suture anchor is selected. Because of osteopenic or osteoporotic bone changes, suture anchors in the older patient might pull out, resulting in failure of repair. Hypothesis The aim of our study was to analyze the bone quality within the tuberosities of the osteoporotic humeral head using high-resolution quantitative computed tomography (HR-pQCT). Study Design Descriptive laboratory study. Methods Thirty-six human cadaveric shoulders were analyzed using HR-pQCT. The mean bone volume to total volume (BV/TV) as well as trabecular bone mineral densities (trabBMDs) of the greater tuberosity (GT) and the lesser tuberosity (LT) were determined. Within the GT, 6 volumes of interest (VOIs) within the LT, and 2 VOIs and 1 control volume within the subchondral area beyond the articular surface were set. Results Comparing BV/TV of the medial and the lateral row, significantly higher values were found medially (P < .001). The highest BV/TV, 0.030% ± 0.027%, was found in the posteromedial portion of the GT (P < .05). Regarding the analysis of the LT, no difference was found comparing the superior (BV/TV: 0.024% ± 0.022%) and the inferior (BV/TV: 0.019% ± 0.016%) portion. Analyzing trabBMD, equal proportions were found. An inverse correlation with a correlation coefficient of —0.68 was found regarding BV/TV of the posterior portion of the GT and age (P < .05). Conclusion Significant regional differences of trabecular microarchitecture were found in our HR-pQCT study. The volume of highest bone quality resulted for the posteromedial aspect of the GT. Moreover, a significant correlation of bone quality within the GT and age was found, while the bone quality within the LT seems to be independent from it. Clinical Relevance The shape of the rotator cuff tear largely determines the bony site of tendon reattachment, although the surgeon has distinct options to modify anchor positioning. According to our results, placement of suture anchors in a medialized way at the border to the articular surface might guarantee a better structural bone stock.
Declarative definition of group indexed data structures and approximation of their domains

We introduce a new high-level programming abstraction which extends the concept of data collection. The new construct, called GBF (for Group Based Data-Field), is based on an algebra of index sets, called a shape, and a functional extension of the array type, the field type. Shape constructions are based on group theory and put the emphasis on the logical neighborhood of the data structure elements. A field is a function from a shape to some set of values. In this study, we focus on regular neigh borhood structures and we show that arrays of any dimensions, cyclic array and trees are special kind of GBF.The recursive definitions of a GBF are then studied and we provide some elements for an implementation and some computability results in the case of recursive definition.
ANALISIS WILAYAH KOMODITAS KOPI DI INDONESIA

This research was intended (1) to map areas of coffee production and land base in Indonesia, (2) to identify the characteristics of the coffee commodity distribution in Indonesia, (3) to identify the roles of coffee in supporting plantation sector in Indonesia. The research area was determined by using purposive method, research was conducted in Indonesia. The method used in this research was descriptive and analytical method. The data used were secondary data in the periods of 2009-2018. Methods of data analysis used were analysis (LQ), analysis of localization and specialization, analysis of Basic Service Ratio (BSR) and Regional Multiplier (RM). The research results showed that: (1) Areas of coffee production bases consisted of: Nanggroe Aceh Darussalam, South Sumatra, Bengkulu, Lampung, East Java, Bali, West Nusa Tenggara East Nusa Tenggara and South Sulawesi. Areas of coffee commodity bases based on indicators such as land size were Nanggroe Aceh Darussalam, West Sumatera, South Sumatera, Bengkulu, Lampung, East Java, Bali, East Nusa Tenggara and South Sulawesi; (2) Characteristics of the spread of coffee did not lead to the principles of localization and specialization; (3) Coffee commodity was capable of supporting the activities of plantations in Indonesia. Keyword: Areas of coffee production and land bases, localization and specialization, Basic Service Ratio, Regional Multiplier
A robust partitioning scheme for ad-hoc query workloads

Data partitioning is crucial to improving query performance several workload-based partitioning techniques have been proposed in database literature. However, many modern analytic applications involve ad-hoc or exploratory analysis where users do not have a representative query workload a priori. Static workload-based data partitioning techniques are therefore not suitable for such settings. In this paper, we propose Amoeba, a distributed storage system that uses adaptive multi-attribute data partitioning to efficiently support ad-hoc as well as recurring queries. Amoeba requires zero set-up and tuning effort, allowing analysts to get the benefits of partitioning without requiring an upfront query workload. The key idea is to build and maintain a partitioning tree on top of the dataset. The partitioning tree allows us to answer queries with predicates by reading a subset of the data. The initial partitioning tree is created without requiring an upfront query workload and Amoeba adapts it over time by incrementally modifying subtrees based on user queries using repartitioning. A prototype of Amoeba running on top of Apache Spark improves query performance by up to 7x over full scans and up to 2x over range-based partitioning techniques on TPC-H as well as a real-world workload.
Stabilization of monocyte chemoattractant protein-1-mRNA by activated protein C

Summary The activated protein C (APC) pathway has been suggested to be a common link between coagulation and inflammation. APC may function to restore hemostasis via modulation of cytokine expression. We investigated the effect of APC on the endothelial expression of monocyte chemoattractant protein-1 (MCP-1), a chemokine that is controlled by the activation of central proinflammatory transcription factors, such as nuclear factor-kappa B (NF-κ B). We found that human APC (2.5-10 μ g/ml) upregulated the amount of MCP-1-mRNA in human umbilical vein endothelial cells (HUVEC) and caused a time- and dose-dependent increase in MCP-1 protein production (p <0.001 for APC 2.5 μg/ ml at 4 up to 24 h). In this cell culture model MCP-1 induced an improvement of cell migration and wound repair after injury to endothelial monolayers. After stimulation of MCP-1-mRNA-transcription with TNF-α (0.1-1 ng/ml), HUVEC’s were washed and an inhibitor of gene transcription, Actinomycin D (1 μg/ml), was added in the presence or absence of APC. HUVEC’s receiving APC contained more MCP-1-mRNA than controls after one hour and up to eight hours suggesting an inhibitory effect of APC on MCP-1-mRNA degradation (with APC: 753 ± 56 atto mol of MCP-1-mRNA per ml of cell lysate vs. 263 ± 60 atto mol/ml without APC at t =4 h; p <0.001). Electrophoretic mobility shift assays revealed that APC attenuated NF- κB DNA-binding capacity implying that NF- B may not be involved in the upregulatory effect of APC on MCP-1 production. The ability of APC to upregulate the production of MCP-1, most likely by increasing the stability of MCP-1-mRNA rather than by transcriptional activation via NF- B, identifies a novel immunomodulatory pathway, by which APC may control the local inflammatory reaction, thereby initiating wound repair and modulating the extent of endothelial injury.
Challenges in Analyzing Software Documentation in Portuguese

Many tools that automatically analyze, summarize, or transform software artifacts rely on natural language processing tooling for the interpretation of natural language text produced by software developers, such as documentation, code comments, commit messages, or bug reports. Processing natural language text produced by software developers is challenging because of unique characteristics not found in other texts, such as the presence of code terms and the systematic use of incomplete sentences. In addition, texts produced by Portuguese-speaking developers mix languages since many keywords and programming concepts are referred to by their English name. In this paper, we provide empirical insights into the challenges of analyzing software artifacts written in Portuguese. We analyzed 100 question titles from the Portuguese version of Stack Overflow with two Portuguese language tools and identified multiple problems which resulted in very few sentences being tagged completely correctly. Based on these results, we propose heuristics to improve the analysis of natural language text produced by software developers in Portuguese.