Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessment of hypoxia and perfusion in human brain tumors using PET with 18F-fluoromisonidazole and 15O-H2O.

UNLABELLED Hypoxia predicts poor treatment response of malignant tumors. We used PET with (18)F-fluoromisonidazole ((18)F-FMISO) and (15)O-H(2)O to measure in vivo hypoxia and perfusion in patients with brain tumors. METHODS Eleven patients with various brain tumors were investigated. We performed dynamic (18)F-FMISO PET, including arterial blood sampling and the determination of (18)F-FMISO stability in plasma with high-performance liquid chromatography (HPLC). The (18)F-FMISO kinetics in normal brain and tumor were assessed quantitatively using standard 2- and 3-compartment models. Tumor perfusion ((15)O-H(2)O) was measured immediately before (18)F-FMISO PET in 10 of the 11 patients. RESULTS PET images acquired 150-170 min after injection revealed increased (18)F-FMISO tumor uptake in all glioblastomas. This increased uptake was reflected by (18)F-FMISO distribution volumes >1, compared with (18)F-FMISO distribution volumes <1 in normal brain. The (18)F-FMISO uptake rate K(1) was also higher in all glioblastomas than in normal brain. In meningioma, which lacks the blood-brain barrier (BBB), a higher K(1) was observed than in glioblastoma, whereas the (18)F-FMISO distribution volume in meningioma was <1. Pixel-by-pixel image analysis generally showed a positive correlation between (18)F-FMISO tumor uptake at 0-5 min after injection and perfusion ((15)O-H(2)O) with r values between 0.42 and 0.86, whereas late (18)F-FMISO images (150-170 min after injection) were (with a single exception) independent of perfusion. Spatial comparison of (18)F-FMISO with (15)O-H(2)O PET images in glioblastomas showed hypoxia both in hypo- and hyperperfused tumor areas. HPLC analysis showed that most of the (18)F-FMISO in plasma was still intact 90 min after injection, accounting for 92%-96% of plasma radioactivity. CONCLUSION Our data suggest that late (18)F-FMISO PET images provide a spatial description of hypoxia in brain tumors that is independent of BBB disruption and tumor perfusion. The distribution volume is an appropriate measure to quantify (18)F-FMISO uptake. The perfusion-hypoxia patterns described in glioblastoma suggest that hypoxia in these tumors may develop irrespective of the magnitude of perfusion.
Frequency, antimicrobial susceptibility and plasmid profiles of Escherichia coli pathotypes obtained from children with acute diarrhea

Introduction and objective: Escherichia coli is an important group of pathogens associated with diarrhea among children. The objective of this study was to determine the frequency, antimicrobial susceptibility and plasmid profiles of E. coli pathotypes obtained from children with acute diarrhea. Materials and methods: In a prospective study during 2008, 466 rectal swabs of inpatient children were examined for the presence of E. coli strains. Results: Of the total number of specimens examined, 99 (21.2%) were positive for E. coli. The highest number of isolates, 37(37.4%), was recovered from the 13-24 month age group. Of the 466 children, 191(41%) were girls and 275(59%) were boys. Based on the serological tests, 59(59.6%) of the E. coli strains were identified as enteropathogenic E. coli (EPEC) and 22 (22.2%) were identified as enteroinvasive E. coli (EIEC). The in vitro antibiotic susceptibility pattern of E. coli strains showed that 89.9 %, 88.9%, 79.8%, and 75% of isolates were found to be resistant to tetracycline, chloramphenicol, ampicillin and cefixime respectively. In plasmid profiling, out of the 99 E. coli pathotypes, 35 (35.4%) were found to possess plasmids, which ranged in sizes from 1.7kb to 4.5kb. These plasmids were seen in 33% of EPEC. Only two pathotypes possessed single size plasmid in EIEC.
Time in Perspective

Perceptions of time and space are subject to strong contextual effects. Like their physical counterparts, they appear to be bound together. The perceived spatial extent of a constant retinal extent increases with its perceived distance from the observer. The perceived duration of a moving object increases with its covered angular trajectory. It follows that the perceived duration of moving objects covering identical angular trajectories should also increase with distance. Using three-dimensionally rendered balls rolling for 600 ms, 900 ms, and 1,200 ms and covering 5.5°, 11°, and 22° trajectories in fronto-parallel planes of a linear-perspective scene, we showed that perceived duration dilates by up to 50% as the fronto-parallel plane of the rolling ball recedes from the observer. Such time dilation is mostly contributed to by the smaller size of the distant ball. As in a three-dimensional world, objects’ sizes and their covered trajectories per time unit decrease with distance, and as the two factors lead to opposite perceived-duration effects, the results suggest a form of time constancy in a three-dimensional world.
A Personality Model Based on NEO PI-R for Emotion Simulation

SUMMARY The last decade has witnessed an explosion of interest in research on human emotion modeling for generating intelligent virtual agents. This paper proposes a novel personality model based on the Revised NEO Personality Inventory (NEO PI-R). Compared to the popular Big-Five-Personality Factors (Big5) model, our proposed model is more capable than Big5 on describing a variety of personalities. Combining with emotion models it helps to produce more reasonable emotional reactions to external stimuli. A novel Resistant formulation is also proposed to effectively simulate the complicated negative emotions. Emotional reactions towards multiple stimuli are also effectively simulated with the proposed personality model.
Crystal Structure of Binary and Ternary Complexes of Archaeal UDP-galactose 4-Epimerase-like l-Threonine Dehydrogenase from Thermoplasma volcanium*

Background: The catalytic mechanism of UDP-galactose 4-epimerase-like l-threonine dehydrogenase (GalE-like l-ThrDH) is unknown. Results: Four crystal structures of archaeal GalE-like l-ThrDH in the presence of NAD+, an inhibitor, and two substrates were determined. Conclusion: Tyr137 is essential for substrate binding and catalysis by the enzyme. Significance: This study provides new insight into substrate recognition by GalE-like l-ThrDH. A gene from the thermophilic archaeon Thermoplasma volcanium encoding an l-threonine dehydrogenase (l-ThrDH) with a predicted amino acid sequence that was remarkably similar to the sequence of UDP-galactose 4-epimerase (GalE) was overexpressed in Escherichia coli, and its product was purified and characterized. The expressed enzyme was moderately thermostable, retaining more than 90% of its activity after incubation for 10 min at up to 70 °C. The catalytic residue was assessed using site-directed mutagenesis, and Tyr137 was found to be essential for catalysis. To clarify the structural basis of the catalytic mechanism, four different crystal structures were determined using the molecular replacement method: l-ThrDH-NAD+, l-ThrDH in complex with NAD+ and pyruvate, Y137F mutant in complex with NAD+ and l-threonine, and Y137F in complex with NAD+ and l-3-hydroxynorvaline. Each monomer consisted of a Rossmann-fold domain and a C-terminal catalytic domain, and the fold of the catalytic domain showed notable similarity to that of the GalE-like l-ThrDH from the psychrophilic bacterium Flavobacterium frigidimaris KUC-1. The substrate binding model suggests that the reaction proceeds through abstraction of the β-hydroxyl hydrogen of l-threonine via direct proton transfer driven by Tyr137. The factors contributing to the thermostability of T. volcanium l-ThrDH were analyzed by comparing its structure to that of F. frigidimaris l-ThrDH. This comparison showed that the presence of extensive inter- and intrasubunit ion pair networks are likely responsible for the thermostability of T. volcanium l-ThrDH. This is the first description of the molecular basis for the substrate recognition and thermostability of a GalE-like l-ThrDH.
Phosphoryl Transfer Reaction Snapshots in Crystals

Background: PKAc (catalytic subunit) catalyzes phosphorylation of protein substrates thereby regulating a myriad of cellular processes. Results: X-ray structures of PKAc complexes along the phosphoryl transfer reaction have been obtained. Conclusion: The phosphotransfer follows a multistep mechanism, including conformational changes of the substrate and product groups, a loose transition state, and metal movement. Significance: Mechanistic knowledge about the phosphorylation by PKAc will contribute to understanding of the kinase function and regulation. To study the catalytic mechanism of phosphorylation catalyzed by cAMP-dependent protein kinase (PKA) a structure of the enzyme-substrate complex representing the Michaelis complex is of specific interest as it can shed light on the structure of the transition state. However, all previous crystal structures of the Michaelis complex mimics of the PKA catalytic subunit (PKAc) were obtained with either peptide inhibitors or ATP analogs. Here we utilized Ca2+ ions and sulfur in place of the nucleophilic oxygen in a 20-residue pseudo-substrate peptide (CP20) and ATP to produce a close mimic of the Michaelis complex. In the ternary reactant complex, the thiol group of Cys-21 of the peptide is facing Asp-166 and the sulfur atom is positioned for an in-line phosphoryl transfer. Replacement of Ca2+ cations with Mg2+ ions resulted in a complex with trapped products of ATP hydrolysis: phosphate ion and ADP. The present structural results in combination with the previously reported structures of the transition state mimic and phosphorylated product complexes complete the snapshots of the phosphoryl transfer reaction by PKAc, providing us with the most thorough picture of the catalytic mechanism to date.
Cerebrospinal fluid features in SARS-CoV-2 RT-PCR positive patients

Abstract This study analyzed the cerebrospinal fluid features of 31 COVID-19 patients with neurological complications. We observed neither SARS-CoV-2 RNA in the cerebrospinal fluid, nor intrathecal IgG synthesis, but did observe signs of blood-brain barrier disruption. These results might serve as a basis for a better understanding of SARS-CoV-2 related neuropathogenesis.
Geographies of wellbeing and development: Empirical analyses on the relationship between objective and subjective measures of wellbeing in Europe

This thesis investigates the cross-sectional association between different quantifiable societal dimensions that indicate spatially varying levels of wellbeing and development. The analysis is grounded in human geography but applies an explicitly interdisciplinary focus, combining theories and measures from economic geography, cultural studies, spatial economics, sociology and social psychology. In the empirical analyses, geographically referenced European Social Survey (ESS) data containing measures of subjective wellbeing (SWB) and human values were analysed together with objective indicators of economic performance on national and subnational scales. This dissertation suggests that multivariate models of SWB data can focus on three different areas of geographical heterogeneity. First, intercept heterogeneity, which is built on a constructivist and container-based view of geography, as it focuses on spatially varying levels (intercepts) of SWB aggregated from survey data. Second, slope heterogeneity, which suggests that different geographical contexts affect the relationship between individual level SWB and its predictors. Third, scale heterogeneity, which involves the spatial rescaling of the analysis while interpreting the relief map of SWB. This thesis studied these areas in four different empirical analyses. First, Paper I demonstrated that levels of ‘social trust’ and ‘social contact and support’, which indicate social wellbeing, and a sense of ‘competence and meaning’, which denotes personal wellbeing, are significant positive correlates with regional GDP after controlling for regional economic indicators and the spatial effects embedded in the data. Second, Paper II utilized the Human Values Scale in the ESS and studied the association between certain values and the level of economic performance. The paper demonstrated that the aggregate level of the value ‘self-direction’, which indicates independent thought, action and creativity, is a strong predictor of regional GDP. Paper II also addressed the question of rescaling and used welfare regimes as a relevant socio-historic framework of analysis. Paper III focused on the contextual effects of living in ‘Metropolitan Finland’. The results showed that the negative effect on life satisfaction of residing in the capital region of Finland is first compositional, as the population in ‘Metropolitan Finland’ is composed of individuals who appreciate the values of ‘power’ and ‘achievement’, which are themselves associated with lower life satisfaction. However, it is also contextual, as residing in the capital region moderates the positive wellbeing effect of socially focused values such as ‘benevolence’ and ‘conformity’. Finally, Paper IV added vertical detail to the intercept heterogeneity approach and asked whether changes in macroeconomic conditions, in the context of Ireland and its recent economic recession, are experienced differently in different socio-economic categories, i.e. classes. The results show that the
Robust pseudo-random fiducial marker for indoor localization

This paper proposes a reliable fiducial marker system that is based on Pseudo-Random Arrays. The marker system describes a planar surface that specifies multi-bit information, which can be efficiently detected in a color image. It provides excellent robustness to occlusion through the use of two digital encoding techniques, Cyclic Redundancy Check and Reed Solomon Error Correction. In environments where color coding is feasible, an estimate of the camera pose relative to the marker can be obtained in a single image. The System relies on a low resolution camera and thus provides real-time results suitable for indoor localization applications.
M ENTAL MODELS FOR NEURAL MODELS

Neural networks are statistical models that excel at capturing regularities that tend to be true, but are not so good at deducing facts that have to be true logically. An example from Go playing, one of the signature successes of neural networks, illustrates the difference. One of the first patterns taught to a novice human Go player is “two eyes” (Figure 1A), a configuration of stones that cannot be captured: even when surrounded by black stones, the white stones can still “breathe” through at least one of the two central empty spaces. It is clear that models like AlphaGo know about two eyes; they wouldn’t be able to play as well as they do otherwise. But it is equally clear that the way the models learn about the pattern is very different from the way humans do. For models, eyes are simply a pattern observed, over many human lifetimes of play, to be correlated to some extent with game wins. A human player, though, requires essentially no play experience to grasp the special properties of two eyes: if she knows the rules of the game, she can articulate an informal proof showing how the rules entail the invulnerability of stones in eyes.
“I Would Just Ask Someone”: Learning Feature-Rich Design Software in the Modern Workplace

Design professionals increasingly need to learn and use multiple feature-rich software to design complex artifacts in a variety of domains. In this work, we aimed to understand how design professionals learn new software features and seek help in today’s modern workplace of interconnected spaces and increased access to shared online learning resources. We conducted 20 interviews with design professionals working in different disciplines such as architecture and planning, construction, structural design, and broadcast media, who used complex feature-rich applications on a daily basis. We found that despite the wide availability of learning resources on the web and decades of research dedicated to workplace knowledge management tools, design professionals still rely heavily on interpersonal help-seeking. Furthermore, while companies have devised a variety of technological channels to answer employees’ help requests, such intermediate tools were often abandoned, and help-seeking conversations shifted to face-to-face learning episodes. Our findings point to design opportunities and shortcomings in the design of remote communication tools when seeking help for feature-rich software applications.
On the parametrization of optical particle counter response including instrument-induced broadening of size spectra and a self-consistent evaluation of calibration measurements

Optical particle counters (OPCs) are common tools for the in situ measurement of aerosol particle number size distributions. As the actual quantity measured by OPCs is the intensity of light scattered by individual particles, it is necessary to translate the collected distribution of scattering signals into the desired distribution of particle sizes. A crucial part in this challenge is the modeling of OPC response and the calibration of the instrument, i.e. to establish the relation between particle scattering cross-section and measured signal amplitude. To date, existing methods lack a comprehensive parametrization of this instrument response, particularly regarding the instrument-induced broadening of size distribution widths. We introduce an approach overcoming the present shortcomings by implementing a simple parametrization of the broadening effect and a self-consistent way to evaluate calibration measurements using a Markov chain Monte Carlo (MCMC) method. We further outline how to obtain realistic uncertainty estimates for OPC size distributions within this new framework. Measurements of particle standards for two OPCs, the Grimm model 1.129 (SkyOPC) and the DMT Passive Cavity Aerosol Spectrometer Probe (PCASP), show substantial reduction in residuals between measured and modeled response compared to existing methods. For the presented set of measurements only the new approach yields results that are conform with the true size distributions within the range of model uncertainty. The offered approach will help to improve the accuracy of derived size distributions and the assessment of their precision for OPC measurements in general.
Micro Design Approach for Gamifying Students’ Assignments

Many students suffer from a lack of motivation and interest in doing their homework. This paper introduced a micro-design approach for implementing gamification of learning assignments, led to the extraction of the procedures for gamifying assignment with the micro-design approach, and a suggested conceptual design model called “Snowflake”. The most interesting finding was that micro-level analysis has a positive impact on a gamified assignment which begins with the identification of raw objects such as quizzes, lessons, learning objects and resources.
Misinformed Speculators and Mispricing in the Housing Market

This paper examines the contribution of out-of-town second-house buyers to mispricing in the housing market. We show that demand from out-of-town second-house buyers during the mid 2000s predicted not only house-price appreciation rates but also implied-to-actual-rent-ratio appreciation rates, a proxy for mispricing. We then apply a novel identification strategy to address the issue of reverse causality. We give supporting evidence that out-of-town second-house buyers behaved like misinformed speculators, earning lower capital gains (misinformed) and consuming smaller dividends (speculators). Received August 4, 2014; accepted August 28, 2015 by Editor Stefan Nagel.
Analysis and Evaluation for Core Competence of Insurance Company Based on SEM

Evaluation the core competence reasonably plays an important role in the insurance company, it is related to whether the insurance can maintain a stable long-term competitive advantage or not, and whether obtain a stable long-term excess profits or not. In this paper, we select 6 first-degree indexes (including the core competence) and 28 second-degree indexes to evaluate the core competence of insurance company by Structural Equation Model (SEM), and analysis the relationships among the first-degree indexes. Besides, we use a new algorithm proposed by us to improve the calculation of SEM.
Drivetrain System Identification in a Multi-Task Learning Strategy using Partial Asynchronous Elastic Averaging Stochastic Gradient Descent

The limited ability of deep learning models to generalize to regions outside of the training data distribution impedes their use for mechatronic applications, with high requirements of safe and robust operation in multiple operating conditions. We draw inspiration from the fields of Multi-Task Learning and distributed computing and propose an adaptation to Elastic Averaging Stochastic Gradient Descent that makes it possible to leverage upon the information of a fleet of systems to extend the generalization capabilities of the individual models, without having access to the full dataset. We demonstrate in simulation that our method enables models to generalize even outside of the joint training data distribution of the fleet. We compare our method to vanilla Elastic Averaging Stochastic Gradient Descent and demonstrate the importance of our adaptation for convergence in the Multi-Task Learning setting. Finally we investigate the interplay between the elastic force and the individual gradients in the update rules as a determining force for its performance.
Cloud Detection of optical remote sensing image time series using Mean Shift algorithm

Cloud detection in multi-temporal optical remote sensing images is a significant task. In this paper, we proposed an efficient method to coarsely detect the cloud via Mean Shift Cloud Detection (MSCD) algorithm, which can work automatically without any reference images. Experimental results on Landsat-8 OLI dataset show the effectiveness of the proposed method.
Optimization and Evaluation of Energy-Efficient Mixed-Signal MFCC Feature Extraction Architecture

Speech feature extraction is an indispensable module in the whole speech recognition process. Especially in the energy-constrained internet of things nodes, low-power feature extraction greatly improves the working time of the system. This paper optimizes a complete energy-efficient speech feature extraction architecture in the mixed-signal domain for speech recognition. The speech feature extraction architecture extracts acoustic features in the mixed-signal domain, which significantly reduces the cost of Analog-to-Digital Converter (ADC) and computational complexity. Moreover, the noise robustness of the mixed-signal MFCC feature has been investigated to adapt to the real scene. In order to evaluate the performance of the proposed optimized architecture, we fabricate a chip about the proposed feature extraction architecture in 180nm CMOS process, the post-simulation results show that the core of mixed-signal MFCC feature extraction achieves 70% power saving and enhanced noise robustness than state of the art.
Does differential predation permit invasive and native mosquito larvae to coexist in Florida?

Abstract. 1. The hypothesis that selective predation on larvae of the invasive Aedes albopictus (Skuse) could account for its stable coexistence with the native mosquito species and inferior competitor Ochlerotatus triseriatus (Say) in Florida treeholes and container systems was tested experimentally.