Miracle-dz/UniFAR-FTUs huggingface dataset:
BIJECTIVE PARAMETERIZATION WITH FREE BOUNDARIES A Dissertation by JASON DEAN SMITH Submitted to the Office of Graduate and Professional Studies of Texas A&M University in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY

When displaying 3D surfaces onto computer screens, additional information is often mapped onto the surface to enhance the quality of the rendering. Surface parameterization generates a correspondence, or mapping, between the 3D surface and 2D parameterization space. This mapping has many applications in computer graphics, but in most cases cannot be performed without introducing large distortions in the 2D parameterization. Along with problems of distortion, the mapping of the 2D space to 3D for many applications can be invalidated if the property of bijectivity is violated. While there is previous research guaranteeing bijectivity, these methods must constrain or modify the boundary of the 2D parameterization. This dissertation, describes a fully automatic method for generating guaranteed bijective surface parameterizations from triangulated 3D surfaces. In particular, a new isometric distortion energy metric is introduced preventing local folds of triangles in the parameterization as well as a barrier function that prevents intersection of the 2D boundaries. By using a computationally efficient isometric metric energy, the dissertation achieves fast and comparable optimization times to previous methods. The boundary of the parameterization is free to change shape during the optimization to minimize distortion. A new optimization approach is introduced called singularity aware optimization and in conjunction with an interior point approach and barrier energy functions guarantee bijectivity. This optimization framework is then modified to allow for an importance weighting allowing for customizable and more efficient texel usage.
Automatic real-time fault detection for industrial assets using

Large-scale industrial plants require physical sensors to continuously measure quantities such as temperatures or pressures. A large number of sensors is required to accurately describe the operating state of the plant, which unfortunately makes it very difficult for them to be effectively monitored by human operators. In this work we present a method to construct so-called metasensors, virtual sensors that compress the information from several sensors in an optimal manner. These metasensors are used as inputs to a novel anomaly detection system that automatically alerts operators to abnormal operation behaviour.
Blockchain Protocols : The Adversary is in the Details

Blockchain-like protocols are flourishing. Maybe not surprisingly, the differences among these protocols are often subtle and difficult to understand. More importantly, it is often unclear what the weaknesses of each of these protocols are and how easily they can be attacked. The goal of this paper is to shed light on the important differences between blockchain protocols and the impact these differences can have in terms of their vulnerabilities. We cover well-studied protocols ranging from those inspired from the distributed systems literature (e.g., PBFT), to recent research prototypes (e.g., ByzCoin or Algorand), including the popular Bitcoin protocol. Towards reaching our goal, we first precisely define the problem that these protocols seek to solve. Then we propose a unifying scheme that captures, at a high level, the behavior of any blockchain protocol. Interestingly, this scheme is also sufficiently low level to highlight the important differences between these protocols. We show that blockchain-like protocols can be differentiated according to their degree of indulgence— i.e., tolerance towards node misbehavior or towards network asynchrony—which translates into the different vulnerabilities of each of these protocols.
Structural Basis for Ca2+-induced Activation and Dimerization of Estrogen Receptor α by Calmodulin*♦

Background: Estrogen receptor α (ER-α) function is controlled by calmodulin (CaM). Results: Both lobes of CaM interact structurally with the same site on ER-α (Trp292 and Lys299). Conclusion: CaM stabilizes dimerization of ER-α and activates transcription. Significance: CaM prevents ubiquitination of ER-α implicated in breast cancer. The estrogen receptor α (ER-α) regulates expression of target genes implicated in development, metabolism, and breast cancer. Calcium-dependent regulation of ER-α is critical for activating gene expression and is controlled by calmodulin (CaM). Here, we present the NMR structures for the two lobes of CaM each bound to a localized region of ER-α (residues 287–305). A model of the complete CaM·ER-α complex was constructed by combining these two structures with additional data. The two lobes of CaM both compete for binding at the same site on ER-α (residues 292, 296, 299, 302, and 303), which explains why full-length CaM binds two molecules of ER-α in a 1:2 complex and stabilizes ER-α dimerization. Exposed glutamate residues in CaM (Glu11, Glu14, Glu84, and Glu87) form salt bridges with key lysine residues in ER-α (Lys299, Lys302, and Lys303), which are likely to prevent ubiquitination at these sites and inhibit degradation of ER-α. Mutants of ER-α at the CaM-binding site (W292A and K299A) weaken binding to CaM, and I298E/K299D disrupts estrogen-induced transcription. CaM facilitates dimerization of ER-α in the absence of estrogen, and stimulation of ER-α by either Ca2+ and/or estrogen may serve to regulate transcription in a combinatorial fashion.
Duplex Real-Time SYBR Green PCR Assays for Detection of 17 Species of Food- or Waterborne Pathogens in Stools

ABSTRACT A duplex real-time SYBR Green LightCycler PCR (LC-PCR) assay with DNA extraction using the QIAamp DNA Stool Mini kit was evaluated with regard to detection of 8 of 17 species of food- or waterborne pathogens in five stool specimens in 2 h or less. The protocol used the same LC-PCR with 20 pairs of specific primers. The products formed were identified based on a melting point temperature (Tm) curve analysis. The 17 species of food- or waterborne pathogens examined were enteroinvasive Escherichia coli, enteropathogenic E. coli, enterohemorrhagic E. coli, enterotoxigenic E. coli, enteroaggregative E. coli, Salmonella spp. , Shigella spp. , Yersinia enterocolitica, Yersinia pseudotuberculosis, Campylobacter jejuni, Vibrio cholerae, Vibrio parahaemolyticus, Vibrio vulnificus, Aeromonas spp. , Staphylococcus aureus, Clostridium perfringens, and Bacillus cereus. No interference with the LC-PCR assay was observed when stool specimens were artificially inoculated with each bacterial species. The detection levels were approximately 105 food- or waterborne pathogenic bacteria per g of stool. The protocol for processing stool specimens for less than 104 food- or waterborne pathogenic bacteria per g of stool requires an overnight enrichment step to achieve adequate sensitivity. However, the rapid amplification and reliable detection of specific genes of greater than 105 food- or waterborne pathogenic bacteria per g in samples should facilitate the diagnosis and management of food- or waterborne outbreaks.
Relations among psychopathology, substance use, and physical pain experiences in methadone-maintained patients.

OBJECTIVE Differences in psychiatric distress and substance use (licit and illicit) were examined in methadone maintenance treatment (MMT) patients with a variety of pain experiences. METHOD Parametric and nonparametric statistical tests were performed on data obtained from 150 patients currently enrolled in MMT. Assessments were carried out at the 3 opioid agonist treatment programs operated by the APT Foundation, New Haven, Connecticut. Participants were recruited between March 2007 and March 2008. RESULTS In comparison to MMT patients reporting no pain in the previous week, those with chronic severe pain (CSP) (ie, pain lasting at least 6 months with moderate to severe pain intensity or significant pain interference) exhibited significantly higher (P < .01) levels of depression, anxiety, somatization, overall psychiatric distress, and personality disorder criteria but reported comparable rates of substance use. A third group, ie, non-CSP MMT patients reporting some pain in the past week, differed significantly (P < .05) from the other 2 pain groups on somatization and global psychiatric distress but reported comparable rates of substance use. CONCLUSIONS Pain-related differences in psychiatric problems exist in MMT patients and may have implications for program planning and outreach efforts.
Utilization of d-Ribitol by Lactobacillus casei BL23 Requires a Mannose-Type Phosphotransferase System and Three Catabolic Enzymes

ABSTRACT Lactobacillus casei strains 64H and BL23, but not ATCC 334, are able to ferment d-ribitol (also called d-adonitol). However, a BL23-derived ptsI mutant lacking enzyme I of the phosphoenolpyruvate:carbohydrate phosphotransferase system (PTS) was not able to utilize this pentitol, suggesting that strain BL23 transports and phosphorylates d-ribitol via a PTS. We identified an 11-kb region in the genome sequence of L. casei strain BL23 (LCABL_29160 to LCABL_29270) which is absent from strain ATCC 334 and which contains the genes for a GlpR/IolR-like repressor, the four components of a mannose-type PTS, and six metabolic enzymes potentially involved in d-ribitol metabolism. Deletion of the gene encoding the EIIB component of the presumed ribitol PTS indeed prevented d-ribitol fermentation. In addition, we overexpressed the six catabolic genes, purified the encoded enzymes, and determined the activities of four of them. They encode a d-ribitol-5-phosphate (d-ribitol-5-P) 2-dehydrogenase, a d-ribulose-5-P 3-epimerase, a d-ribose-5-P isomerase, and a d-xylulose-5-P phosphoketolase. In the first catabolic step, the protein d-ribitol-5-P 2-dehydrogenase uses NAD+ to oxidize d-ribitol-5-P formed during PTS-catalyzed transport to d-ribulose-5-P, which, in turn, is converted to d-xylulose-5-P by the enzyme d-ribulose-5-P 3-epimerase. Finally, the resulting d-xylulose-5-P is split by d-xylulose-5-P phosphoketolase in an inorganic phosphate-requiring reaction into acetylphosphate and the glycolytic intermediate d-glyceraldehyde-3-P. The three remaining enzymes, one of which was identified as d-ribose-5-P-isomerase, probably catalyze an alternative ribitol degradation pathway, which might be functional in L. casei strain 64H but not in BL23, because one of the BL23 genes carries a frameshift mutation.
Joint Post and Link-level Influence Modeling on Social Media

Microblogging websites, like Twitter and Weibo, are used by billions of people to create and spread information. This activity depends on various factors such as the friendship links between users, their topic interests and social inﬂuence between them. Social inﬂuence can be thought of as a latent factor, that may alter users posting and linking behaviors. Making sense of these behaviors is very important for fully understanding and utilizing these platforms. Most prior work in this space either ignores the eﬀect of social inﬂuence, or considers its eﬀect only on link formation or post generation. In contrast, we propose PoLIM , leveraging simple weak supervision, a novel model which jointly models the eﬀect of inﬂuence on both link and post generation. We also give PoLIM-FIT , an eﬃcient parallel inference algorithm which scales to large datasets. In our experiments on a large tweets corpus, we detect meaningful topical communities, celebrities, as well as the inﬂuence strengths patterns among them. Further, we ﬁnd that there are signiﬁcant portions of posts and links that are caused by inﬂuence, and this portion increases when the data focuses on a speciﬁc event. We also show that diﬀerentiating and identifying these inﬂuenced content beneﬁts other speciﬁc quantitative downstream tasks as well, like predicting future tweets and link formation, where we signiﬁcantly outperform state-of-the-art.
Euclidean-Based Entity Resolution for Evolving Data

With large companies and corporations becoming increasingly responsible for data collection, in recent years, a growing number of scientists have proposed using a variety of algorithms and different theories to solve the database problem. Even though existing solutions are effective in many cases many, problems are left to solve during the integration of database. The entity resolution (ER) is a crucial problem to solve. ER has been used in many applications during the updating and loading process of the big data set, while the evolving data needs most. The evolving data set are currently used in the biology and computer information a lot, which contains microscope observation and biology information. Even though researchers have proposed different ER methods, the cost of ER problems is usually too large to accept. We use the high-dimensional space Euclidean vector to simulate the states of different entities in big data set. We combine this approach with the parallel improved Top-K algorithm, devising a way to more effectively detect the identity of the entity. Theoretical analysis and experimental results show that the proposed method could perform entity resolution on evolving data effectively and efficiently.
Rate-distortion-complexity analysis for prediction unit modes in 3D-HEVC depth coding

3D-HEVC achieves significant compression efficiency thanks to the addition of several tools and features for multiview and 3D video content on top of those already available in HEVC. However, such gains come at the cost of large increases in the encoding computational complexity, which is a problem for computationally and battery-constrained devices. As the use of each tool or feature yields different compression efficiency, those that do not contribute significantly should be the first to be disabled in a complexity-constrained system with limited computational resources. Thus, this paper presents two major analyses on the use of Prediction Unit (PU) modes in 3D-HEVC: a preliminary, statistical study and a Rate-Distortion-Complexity (RDC) analysis. The first study observed the occurrence of asymmetric and rectangular PU modes in depth maps, while the RDC analysis evaluated the impact caused by the deactivation of the least used modes during the encoding of depth maps, based on the results found in the preliminary study. Experimental results have shown that a computational complexity reduction of 9% can be achieved with a negligible rate-distortion penalty (0.1%) if the least used modes are disabled.
Fast Scan Cyclic Voltammetry as a Novel Method for Detection of Real-Time Gonadotropin-Releasing Hormone Release in Mouse Brain Slices

Pulsatile gonadotropin-releasing hormone (GnRH) release is critical for the central regulation of fertility. There is no method allowing real-time GnRH detection in brain slices. We developed fast-scan cyclic voltammetry (FSCV) using carbon-fiber microelectrodes (CFME) to detect GnRH release and validated it using a biologically relevant system. FSCV parameters (holding potential, switching potential, and scan rate) were determined for stable GnRH detection in vitro, then optimized for GnRH detection in mouse brain slices. Placement of CFMEs in the median eminence (ME) near GnRH terminals allowed detection of both KCl-evoked and spontaneous GnRH release. GnRH release was also detected from GnRH fibers passing near GnRH soma and near fiber–fiber appositions in the preoptic area. No GnRH signal was detected from CFMEs in the ME of hpg mice, which lack GnRH, or in regions not containing GnRH neurons in wild-type mice; application of exogenous GnRH produced a signal similar to that observed for spontaneous/evoked endogenous GnRH release. Using an established mouse model that produces diurnal variations in GnRH neuron activity, we demonstrated corresponding changes in spontaneous GnRH release in the median eminence. These results validate FSCV to detect GnRH in brain slices and provide new information on the sites and amounts of GnRH release, providing insight into its neuromodulatory functions.
GPU-Based Rendering for Ray Casting of Multiple Geometric Data

We present a new GPU-based rendering method for ray casting of multiple geometric data. Our approach supports a polygonal data to calculate scattered light. Terrain is represented for the base of scalar perturbation functions. The geometric model is based on non-polygonal representation. We present a new representation scheme for freeform surfaces it is possible to combine basic surface and perturbation functions. To recognize the place it is often sufficient to fill areas with the generalized texture patterns, such as "themes". Themes designed beforehand and consumption of memory for storing them is not huge.
Effects of an osteoarthritis self-management programme.

AIM The aim of this study was to assess the effectiveness of a self-management programme among osteoarthritis knee sufferers. BACKGROUND Osteoarthritis of the knee is a major cause of loss of function and is common in the older people. A self-management programme is an effective way to increase arthritis self-efficacy, and helps with mastering self-management practices. METHOD This study was carried out from January 2008 to December 2008 and included 205 participants, with 114 in the intervention group and 91 in the control group. The 4-week trial was followed by an 8-week follow-up assessment. The outcome measures included assessments of arthritis self-efficacy, pain beliefs, unplanned medical consultations, pain days and disability days using the Mann-Whitney U-test and Friedman test. FINDINGS At post-intervention, significant differences were found in pain beliefs (P<0·001) and pain days (P<0·004). At 8-week follow-up, there was a significant improvement in arthritis self-efficacy: pain and other symptoms subscales (P<0·001 and 0·049, respectively), pain beliefs (P<0·001) and number of unplanned medical consultations (P<0·010). CONCLUSION The study supports the hypothesis that a self-management programme enhances arthritis-related self-efficacy and pain beliefs. A decrease in the number of unplanned medical consultations, pain days and disability days suggests that the programme might help reduce healthcare costs. This programme has introduced a significant result about self-efficacy and self-management to a chronic disease population in Taiwan. In short, there were great beneficial effects on self-management among persons who are affected by knee osteoarthritis.
Oil Price Shocks and Cyclical Dynamics in an Asymmetric Monetary Union # 247

This paper analyzes the dynamic eff ects of anticipated and unanticipated oil price increases in a small two-country monetary union, which is simultaneously characterized by asymmetric wage adjustments and asymmetric interest rate sensitivities of private absorption. Common external oil price disturbances lead in this asymmetric macroeconomic setup to temporary divergences in output developments across the monetary union. In the case of anticipated oil price increases the relative cyclical position is reversed in the course of the adjustment process. Complete stabilization of the output variables throughout the overall adjustment process requires a restrictive monetary policy being time inconsistent from a quantitative but time consistent from a qualitative point of view. That means that the central bank credibly announces a future reduction in the growth rate of the nominal money stock but actually implements a reduction, which is less restrictive than the original announcement. JEL Classifi cation: E63, F41
Using Census Data to Predict Solar Panel Deployment

New renewable energy sources require improvements to the current electric grid. The recent surge in the number of intermittent energy generation facilities, such as solar and wind farms, has resulted in a need for improved monitoring and control methods for the electric grid due to increased supply-side uncertainty. Mitigating the uncertainty in the amount of electricity privately produced would greatly increase power generation efficiency, resulting in less waste of fossil-fuel generated electricity. One major component of supply-side uncertainty comes from residential solar panel installations. Today, installing solar panels on residential homes is easy and affordable, and will only become easier and more affordable as time progresses. As a result, it is difficult to know how many solar panels exist and supply power to the grid. If energy companies had more insight into this piece of the supply-side puzzle, they could better model an area’s energy production and balance power plant production accordingly, resulting in lower energy costs and less environmental impact. For this project, we implemented and optimized an artificial neural network (NN) and a support vector regression (SVR) algorithm to predict the number of solar installations in a given tract from census data. The input to the model consists of geographical and demographical characteristics, such as land area, average household income, climate data, number of residents of age 30-39, etc. The model takes these census data and then outputs the number of solar systems in a given tract. The model is trained using supervised learning on a labeled dataset. We also used the models and principal-component-analysis (PCA) to determine which features have the most influence on modeling the number of solar systems (i.e. which features are most strongly correlated with solar deployment density).
Tyrosine hydroxylase isoenzyme I is present in human melanosomes: a possible novel function in pigmentation

Abstract: Both human epidermal melanocytes and keratinocytes have the full capacity for de novo synthesis of 6(R) L‐erythro 5,6,7,8, tetrahydrobiopterin, the essential cofactor for the rate limiting step in catecholamine synthesis, via tyrosine hydroxylase. Catecholamine synthesis has been demonstrated in proliferating keratinocytes of the epidermis in human skin. This study presented herein identified for the first time the expression of tyrosine hydroxylase isozyme I mRNA within the melanocyte. The location of the enzyme was demonstrated in both the cytosol and melanosomes of human epidermal melanocytes, using immunohistochemistry and immunofluorescence double staining as well as immunogold electron microscopy. High‐performance liquid chromatography (HPLC) analysis of pure melanosomal extracts from the human melanoma cell line, FM94, confirmed the production of L‐dopa within these organelles. In addition, enzyme activities for both tyrosine hydroxylase and tyrosinase were measured in the same preparations, by following the catalytic release of tritiated water from L‐[3,5‐3H]tyrosine. The melanosomal membrane location of tyrosine hydroxylase together with tyrosinase implies a coupled interaction, where L‐dopa production facilitates the activation of tyrosinase. Our results support a direct function for tyrosine hydroxylase in the melanosome via a concerted action with tyrosinase to promote pigmentation.
Susceptibility of Urinary Tract Bacteria to Fosfomycin

ABSTRACT We evaluated the in vitro activity of fosfomycin against urinary isolates in a region in Greece that exhibits considerable antimicrobial resistance by evaluating retrospectively relevant susceptibility data retrieved from the microbiological library of the University Hospital of Heraklion, Crete, Greece. We examined 578 urinary isolates. In total, 516 (89.2%) were susceptible to fosfomycin; 415 isolates were gram negative, and 101 isolates were gram positive. Fosfomycin appears to exhibit good levels of in vitro activity against the examined urinary isolates.