Miracle-dz/UniFAR-FTUs huggingface dataset:
Bioconcentration and Metabolism of Emodin in Zebrafish Eleutheroembryos

Emodin is a major active anthraquinone of various herbal laxatives, which can exert many pharmacological effects. However, chronic use of anthranoid laxatives, even at low dosages, may cause melanosis coli (MC). It has been suggested that the accumulation of anthraquinones is a risk factor in the MC process. To investigate the accumulation of emodin, we conducted a bioconcentration study of emodin in zebrafish eleutheroembryos. Based on the economic cooperation and development (OECD) 305 test, zebrafish eleutheroembryos were exposed to emodin at a constant concentration for 48 h, before the test media were replaced by the blank medium for 24 h of depuration. To eliminate the effect of metabolism of emodin for assessment of the bioconcentration factor (BCF), we also conducted a modified test for which zebrafish eleutheroembryos were exposed to the non-renewed test media, whose emodin concentration decreased with time. At different exposure time points, zebrafish eleutheroembryos and exposure media were sampled for analysis of emodin concentration using HPLC-MS/MS. The results showed rapid accumulation of emodin in zebrafish eleutheroembryos to reach a steady-state concentration within 24 h. Meanwhile, emodin was actively metabolized by zebrafish eleutheroembryos to result in 29.5–40.7% of its elimination. In the groups with high or low concentrations of emodin, the standardized BCF (sBCF) values in the standard test were 24.0 and 20.0, while those in the modified test were 50.4 and 52.0. These results showed that emodin could accumulate in zebrafish eleutheroembryos when used for 48 h and beyond, suggesting that the accumulation of anthraquinones may be a risk factor in the MC process. Accordingly, emodin should be unsuitable for long-term use due to its accumulation.
Compressed Sensing Based Image Restoration Algorithm with Prior Information: Software and Hardware Implementations for Image Guided Therapy

Based on the compressed sensing theorem, we present the integrated software and hardware platform for developing a total-variation based image restoration algorithm by applying prior image information and free-form deformation fields for image guided therapy. The core algorithm we developed solves the image restoration problem for handling missing structures in one image set with prior information, and it enhances the quality of the image and the anatomical information of the volume of the on-board computed tomographic (CT) with limited-angle projections. Through the use of the algorithm, prior anatomical CT scans were used to provide additional information to help reduce radiation doses associated with the improved quality of the image volume produced by on-board Cone-Beam CT, thus reducing the total radiation doses that patients receive and removing distortion artifacts in 3D Digital Tomosynthesis (DTS) and 4D-DTS. The proposed restoration algorithm enables the enhanced resolution of temporal image and provides more anatomical information than conventional reconstructed images. The performance of the algorithm was determined and evaluated by two built-in parameters in the algorithm, i.e., B-spline resolution and the regularization factor. These parameters can be adjusted to meet different requirements in different imaging applications. Adjustments also can determine the flexibility and accuracy during the restoration of images. Preliminary results have been generated to evaluate the image similarity and deformation effect for phantoms and real patient's case using shifting deformation window. We incorporated a graphics processing unit (GPU) and visualization interface into the calculation platform, as the acceleration tools for medical image processing and analysis. By combining the imaging algorithm with a GPU implementation, we can make the restoration calculation within a reasonable time to enable real-time on-board visualization, and the platform potentially can be applied to solve complicated, clinical-imaging algorithms.
systematic review and meta-analysis of tertiary interventions in clinical burnout

Clinical burnout is one of the leading causes of work absenteeism in highand middle-income countries. There is hence a great need for the identification of effective intervention strategies to increase return-to-work (RTW) in this population. This review aimed to assess the effectiveness of tertiary interventions for individuals with clinically significant burnout on RTW and psychological symptoms of exhaustion, depression and anxiety. Four electronic databases (Ovid MEDLINE, PsychINFO, PubMed and CINAHL Plus) were searched in April 2016 for randomized and non-randomized controlled trials of tertiary interventions in clinical burnout. Article screening and data extraction were conducted independently by two reviewers. Pooled odds ratios (ORs) and hazard ratios (HRs) were estimated with random-effects meta-analyses. Eight articles met the inclusion criteria. There was some evidence of publication bias. Included trials were of variable methodological quality. A significant effect of tertiary interventions compared with treatment as usual or wait-list controls on time until RTW was found, HR = 4.5, 95% confidence interval (CI) = 2.15–9.45; however, considerable heterogeneity was detected. The effect of tertiary interventions on full RTW was not significant, OR = 1.33, 95% CI = 0.59–2.98. No significant effects on psychological symptoms of exhaustion, depression or anxiety were observed. In conclusion, tertiary interventions for individuals with clinically significant burnout may be effective in facilitating RTW. Successful interventions incorporated advice from labor experts and enabled patients to initiate a workplace dialogue with their employers.
Distance between extremum graphs

Scientific phenomena are often studied through collections of related scalar fields generated from different observations of the same phenomenon. Exploration of such data requires a robust distance measure to compare scalar fields for tasks such as identifying key events and establishing correspondence between features in the data. Towards this goal, we propose a topological data structure called the complete extremum graph and define a distance measure on it for comparing scalar fields in a feature-aware manner. We design an algorithm for computing the distance and show its applications in analysing time varying data.
High altitude aero-optic imaging deviation prediction for a hypersonic flying vehicle

Aero-optic imaging deviation characterizes the image position displacement on an imaging plane induced by the nonuniform flow field surrounding a high-speed flying vehicle. It is a kind of aero-optic effect that all the airborne imaging systems will encounter. This paper studies the imaging deviation at high altitudes from 40 to 60 km, with a step length of 5 km. CFD computations are completed by the Reynolds-averaged Navier-Stokes method. Optics calculations are performed by solving a ray equation using the Runge-Kutta algorithm. The dependence of imaging deviation on altitude in 40–60 km is given. The imaging deviation slopes are also calculated and analyzed. The results show that as altitude increases from 40 to 60 km, the imaging deviations decrease. At smaller altitudes, the imaging deviation is relatively sensitive; whereas, at larger altitudes, the imaging deviation slopes approach zero from a negative value.
Advanced cryogenic aerosol cleaning: application to damagefree cleaning of sensitive structured wafers

Cryogenic aerosols formed from either argon and nitrogen or nitrogen gas only have proven successful for high particulate removal without material loss or modification and damage free cleaning of poly silicon line structures. Particle removal efficiency is reported on particulate contamination down to 65 nm. Results on 60 nm poly silicon structures have shown no damage and a particle removal efficiency greater than 92%. Further reducing the poly line critical dimension to 40 nm resulted in particle removal efficiency greater than 71% and has no damage
ERK and cell death: ERK1/2 in neuronal death

Extracellular signal‐regulated kinase (ERK) is a versatile protein kinase that regulates many cellular functions. Growing evidence suggests that ERK1/2 plays a crucial role in promoting cell death in a variety of neuronal systems, including neurodegenerative diseases. It is believed that the magnitude and the duration of ERK1/2 activity determine its cellular function. In this review, we summarize recent evidence for a role of ERK1/2 in neuronal death. Furthermore, we discuss the mechanisms involved in ERK1/2 mediating neuronal death.
The influence of different contraceptive methods on vaginal microbiota: Clinical study

Objective: The aim of this work was to evaluate the vaginal content of women attending family planning controls and its relationship with the contraceptive practice used (oral contraceptive pills, intrauterine device, condoms, or rhythm method) as well as its relationship with the lack of regular contraception. Design: Observational, descriptive study. Setting: Servicio de Atencion Medica—Ministerio de Salud—Sa Pereira—Santa Fe.Argentina. Population: A total of 250 women were studied following the BAVACO (balance of the vaginal content). Methods: Standard method, which included the wet mount test, and Giemsa and Gram stain under the Nugent score. Results: Obtained from the vaginal microbiota, the vaginal inflammatory response, presence of yeast and Trichomonas allowed defining five basic vaginal microbial states which were statistically related to contraceptive methods. Main Outcome Measures: The association of each of the five vaginal states with the different contraceptive practices was determined by X2 test, considering p : a) the positive association of combined oral contraceptives with a normal microbiota indicates a positive trend of protection, b) intrauterine devices increase whereas oral contraceptives decrease the risk for bacterial vaginosis, while oral contraceptives reduce the frequency.
Consensus ranking from a utility view

Consensus ranking problems have attracted much attention in the management science and data mining, where a group of k decision makers (DMs) is asked to rank n alternatives. Several different approaches have been suggested to combine the responses of DMs into a compromise or consensus ranking from a diverse perspective. However, they failed to work out in all situations. In this paper, we propose a new framework for consensus ranking from a utility view. Under this framework, we convert it to an optimization problem, which is proved to be NP-hard. To handle this challenging problem, three algorithms are put forward. Experiments show that Graph-based Ranking (GR) not only has the advantage of stability and validity on data of different scales, but also takes less time, which is quite suitable for the large scale consensus ranking.
Le cadre de vie des hommes du Paléolithique moyen (stades isotopiques 6 et 5) dans le site de Payre (Rompon, Ardèche) : d'une grotte à un abri sous roche effondré

Le gisement paleolithique moyen de Payre est situe dans le sud-est de la France, dans la moyenne vallee du Rhone. Les fouilles, qui s 'y deroulent depuis 1990, livrent une sequence datee des stades isotopiques 7 a 5, 6 a 5 pour les occupations humaines. Les observations a la fouille permettent de visualiser les limites d'une cavite aujourd'hui effondree. Les hommes seraient venus a plusieurs reprises dans cette cavite et auraient occupe en dernier lieu un abri sous roche. Les donnees du remplissage, associees a celles livrees par l'assemblage osseux, aboutissent a proposer aujourd'hui une reconstitution de la morphologie du site aux differents moments des occupations humaines et a donner une idee du cadre de vie choisi par les hommes, en particulier pour des occupations sans doute de courte duree.
PARAMETRIZED DEEP Q-NETWORKS LEARNING: PLAYING ONLINE BATTLE ARENA WITH DISCRETE-CONTINUOUS HYBRID ACTION SPACE

Most existing deep reinforcement learning (DRL) frameworks consider action spaces that are either discrete or continuous space. Motivated by the project of design Game AI for King of Glory (KOG), one the world’s most popular mobile game, we consider the scenario with the discrete-continuous hybrid action space. To directly apply existing DLR frameworks, existing approaches either approximate the hybrid space by a discrete set or relaxing it into a continuous set, which is usually less efficient and robust. In this paper, we propose a parametrized deep Q-network (P-DQN) farmework for the hybrid action space without approximation or relaxation. Our algorithm combines DQN and DDPG and can be viewed as an extension of the DQN to hybrid actions. The empirical study on the game KOG validates the efficiency and effectiveness of our method.
From situation awareness to smart city planning and decision making

Urban planning under the current rapidly changing conditions requires holistic understanding of the planning ecosystem. Sustainable communities cannot be planned in silos, but ask for systems thinking, collaborative methods, and knowledge management. Smart city planning, or “expanded urban planning”, practices are developed for framing cities from a holistic and integrative perspective as a multi-scalar and multi-dimensional endeavor. The aim of this article is to describe and discuss knowledge creation and situation awareness in collaborative urban planning practice, and the question of how digitalization changes it. These subjects are approached through a case study on an urban planning process in the metropolitan area of Helsinki, Finland. Through empirical findings, this article argues that smart city planning is not only a data-driven superlinear scaling practice, but an integrative and collaborative learning process facilitated by face-to-face interaction and advanced analyses and visualizations of available data, ongoing processes, and local history and stories. ______________________________________________________ S. Eräranta (Corresponding author) • A. Staffans YTK Land Use Planning and Urban Studies Group, Department of Real Estate, Planning and Geoinformatics, P.O. Box 11000, FI-00076 Aalto, Finland Email: susa.eraranta@aalto.fi A. Staffans Email: aija.staffans@aalto.fi CUPUM 2015 197-Paper
Advantages and Disadvantages of Molecular Phylogenetics : A Case Study of Ascaridoid Nematodes 1

The advantages of nucleotide sequence data for studying phylogeny have been shown to include number of potential characters available for comparison, rate independence between molecular and morphological evolution, and utility of molecular data for modeling patterns of nudeotide substitution. Potential pitfalls have also been revealed and include difficulties of inferr ing positional homology, incongruence between organismal and gene genealogies, and low likelihood of recovering the correct phylogeny given certain patterns in the timing of speciation events. Statistical methods for comparing phylogenetic hypotheses have been used to assess the reliability of alternative trees for ascaridoid nematodes. Based on partial ribosomal RNA sequences, tree topologies inconsistent with monophyly of the Ascaridinae were significantly worse by maximum likelihood inference. The topology of the maximum parsimony tree based on full-length sequences of 18S rRNA and 300 nucleotides of Cytochrome oxidase II for 13 ascaridoid species was generally consistent with traditional taxonomic expectations at lower ranks, but inconsistent with most proposed arrangements at higher taxonomic levels.
[Association studies of G352A polymorphism of dopamine transporter gene in Han Chinese attention deficit hyperactivity disorder patients].

OBJECTIVE To investigate association of the new polymorphism G352A in the dopamine transporter gene (DAT1) exon 15 with attention deficit hyperactivity disorder (ADHD) in Han Chinese children. METHODS The new mutant polymorphism G352A in the dopamine transporter gene (DAT1) exon 15 was found by the fluorescently-labeled dye-terminators assay. The study samples were comprised of 337 ADHD children, 207 unrelated controls and 201 integrated ADHD trios (included proband and biological parents). Associations of polymorphisms with ADHD and its subtypes were examined by: (i) comparing cases and controls; and (ii) using family-based association study in transmission-disequilibrium test (TDT). RESULTS The allele frequencies at the DAT1 G352A locus in the control samples were 79.5% for 352G and 20.5% for 352A respectively. Association studies revealed no association between G352A in exon 15 of DAT1 and ADHD. But after a stratification by gender, there was possible association between G352A and ADHD girls: the 352G allele had a tendency to be preferentially transmitted to ADHD girls. CONCLUSION There is no association between G352A, the new polymorphism, in exon 15 of DAT1 and ADHD. The 352G allele has a tendency to be preferentially transmitted to ADHD girls, but the findings require replication before drawing a definitive conclusion.
Parallel iterative search methods for vehicle routing problems

This paper presents two partition methods that speed up iterative search methods applied to vehicle routing problems including a large number of vehicles. Indeed, using a simple implementation of taboo search as an iterative search method, every best-known solution to classical problems was found. The first partition method (based on a partition into polar regions) is appropriate for Euclidean problems whose cities are regularly distributed around a central depot. The second partition method is suitable for any problem and is based on the arborescence built from the shortest paths from any city to the depot. Finally, solutions that are believed to be optimum are given for problems generated on a grid. © 1993 by John Wiley & Sons, Inc.
Rough set-based concept mining from social networks

Motivated by successful applications of rough set theory to symbolic knowledge discovery from data tables, we would like to extend the approach to description logic (DL)-based mining of social networks. Unlike classical rough set theory, in which the attribute values of objects fully determine the indiscernibility relation, the rough set analysis of social networks must account for the social relationships between objects as well as their attributes. In this paper, the indiscernibility relation is defined by using the notions of positional equivalences in social network analysis. The indiscernibility relation can partition the universe of a social network into elementary sets which are used to define the lower and upper approximations of an arbitrary concept as in classical rough set theory. To induce concept definitions from such approximations, we use DL to represent knowledge discovered from social networks and present a constructive procedure to find a characterizing DL concept terms for each elementary set. Because the lower and upper approximations of a target concept are unions of elementary sets, we can use the disjunction of such characterizing concept terms to describe the definition of the target concept. This leads to a complete process of DL-based concept mining from social networks.
Perceptual compensation for effects of reverberation in speech identification: a computer model based on auditory efferent processing

Human speech perception is remarkably robust to the effects of reverberation, due in part to mechanisms of perceptual constancy that compensate for the characteristics of the acoustic environment. A computer model of this phenomenon is described, which shows compensation for the effects of reverberation in a word identiﬁcation task. The presence of reverberation is detected as a change in the mean-to-peak ratio of the simulated auditory nerve response. In turn, this leads to attenuation of peripheral auditory activity, which is achieved through an efferent feedback loop. The computer model provides a qualitative match to a range of perceptual data, suggesting that auditory mechanisms under efferent control might contribute to compensation for reverberation in particular speech identiﬁcation tasks.
A GPS-BASED ENHANCED APPROACH FOR TRAFFIC INCIDENT AND CONGESTION DETECTION

Evaluating traffic networks is crucial for administration of roadway systems, to better address congestion, safety, and air quality issues around the globe, however, challenges in implementation abound, including huge investment, big data mazes and obtaining timely and accurate feedback. Recently developed low-cost Global Positioning System (GPS) data loggers are a promising tool for traffic monitoring, thanks to their low cost, ready availability on smartphones
A Statistical Analysis of RF-Energy Harvesting in Wireless Networks

The ability of wireless terminals to harvest energy from Radio Frequency (RF) signals is gaining tremendous momentum as a mean to prolong the lifetime of these terminals and to recycle the radiated energy. This article gives a much needed statistical analysis for the amount of harvested energy over a period of time T. By studying the input/output characteristics of a typical harvesting circuit, we show that i) the amount of harvested energy over a period of T seconds, denoted by ψ<sub>out</sub>, is a stochastic process, and ii) that it can be written as a scaled version of the amount of incoming energy, ψ<sub>in</sub>, over the same period of time, i.e., ψ<sub>out</sub> = ε̂ψ<sub>in</sub>, where ε̂ ∈ [0, 1] is the harvesting efficiency. We also unveil the dependence of ψ<sub>out</sub> on the sensitivity of the harvesting circuit which is captured using a Signal to Noise Ratio (SNR) threshold, γ<sub>th</sub>.
Relationship Mapping for Proactive Growth of Knowledge Networks

Interactions between colleagues in the modern workplace are becoming increasingly complex. Collaboration occurs through informal networks of employees as well as formal reporting structures. However, these informal networks can be unreliable, and are hidden from those outside the network. The Instant knowledge project will improve the handheld information devices used by many in today's workplace to make informal networks more effective. By extracting useful information from mobile communications and using social network analysis techniques, information about communicants' relationships can be inferred. Quantifying properties of these relations enables a social network map to be built. This social map will be used as a basis for developing technologies which enable the exchange of contact information among users, providing them with a communications architecture which better supports work through informal networks than existing infrastructure