Miracle-dz/UniFAR-FTUs huggingface dataset:
regulates foxd3 and sox10 expression, affecting neural crest migration and differentiation

This work reports the characterization and functional analysis of disrupted in schizophrenia 1 ( disc1 ), a well-documented schizophrenia-susceptibility gene, in zebrafish cranial neural crest (CNC). Our data demonstrated that disc1 was expressed in zebrafish CNC cells. Loss of Disc1 resulted in persistent CNC cell medial migration, dorsal to the developing neural epithelium, and hindered migration away from the region dorsal to the neural rod. General CNC cell motility was not affected by Disc1 knockdown, however, as the speed of CNC cells was indistinguishable from that of wild-type counterparts. We determined that the failure of CNC cells to migrate away from the neural rod correlated with the enhanced expression of two transcription factors, foxd3 and sox10 . These transcription factors have many functions in CNC cells, including the maintenance of precursor pools, timing of migration onset, and the induction of cell differentiation. Our work, in conjunction with previous studies, suggests that the perpetuation of expression of these factors affects several aspects of CNC cell development, leading to a loss of craniofacial cartilage and an expansion of peripheral cranial glia. Based on our data, we propose a model in which Disc1 functions in the transcriptional repression of foxd3 and sox10 , thus mediating CNC cell migration and differentiation. of pairwise comparisons or a multiple analysis of variance with post-hoc contrasts. Some data sets were log transformed prior to analysis for normalization. Non-parametric data was analyzed using the Wilcoxon/Kruskal-Wallis test for χ 2 approximation.
A systematic mapping on quality attributes and quality models for ambient assisted living systems.

Context: Population ageing is currently taking place across the globe and it is already a reality in many developed countries. In this context, Ambient Assisted Living (AAL) has become an essential, multidisciplinary research topic, aiming at providing software systems and services that assist people (especially elderly or disabled with special needs) in their everyday life activities. Considering the critical nature of AAL systems, several initiatives have already contributed to the improvement of their quality, by mainly focusing on their non-functional requirements. However, despite the importance of quality assurance in AAL systems, there is a lack of a comprehensive analysis on how quality assurance is performed in such systems. This fact might in turn lead to an absence of standardization with regard to the quality assurance process of these systems. Objective: In this report, we provide the planning and conducting phases of a systematic mapping (SM), which aim to offer a broad, detailed panorama about the state of the art on quality models (QMs) and quality attributes (QAs) that are important for the AAL domain. In particular, we aim at identifying which QAs are the most frequently studied, how they have been identified as relevant to AAL, and how their relevance is evaluated. In parallel, we characterize the QAs for each AAL sub-domain and identify the critical QAs for AAL systems. Method: We performed a Systematic Mapping (SM), following well established guidelines for conducting SM in the software engineering area. We used six publication databases to cover all published material pertinent for our SM. We initially obtained 287 studies that were filtered based on a set of well-defined inclusion/exclusion criteria, resulting into a set of 27 studies that were used for exploring QAs for AAL systems.
Evaluationof the Dual-PrecipitationMethodby Comparisonwith the UltracentrifugationMethodfor Measurementof Lipoproteinsin Serum

We evaluated the dual-precipitation method for quantitative measurement of lipoproteins as described by Wilson and Spiger [J. Lab. C/in. Med. 82, 473 (1973)] for norrno- and hyperlipemic sera, by comparison with the results obtained with ultracentrifugation. If serum with an above-normal triglyceride concentration is analyzed, the very-low-density lipoprotein cholesterol value obtained with the precipitation method is usually too low. For measurement of high-den-sity lipoprotein cholesterol the ultracentrifugation and precipitation procedures give comparable results, but the latter method is preferred because sinking pre-/3-lipo-proteins present in the high-density lipoprotein fraction isolated by means of the ultracentrifuge may result in falsely high values for cholesterol in that fraction. Therefore, at least for the determination of very-low-density liproprotein cholesterol in hyperlipemic serum, the use of an ultracentrifuge remains necessary. Because few laboratories have an ultracentrifuge at their disposal, it seemed important to look at the stability of sera in view of the forwarding of samples. Also, a way of increasing the efficiency of the ultracentrifuge was studied. Sera can be stored for a week at 4 #{176}Corfor 54 h at room temperature without noticeable effect on lipoprotein values. Moreover, reliable values can be obtained with an ultracentrifugation time of 8 h (0.8 X 108 g.min). In the
Intelligent Processing of Video Streams for Visual Customer Behavior Analysis

- In today’s society purchasing goods through web shops has become habitual. Some years ago only a few products like books, computer games and music CDs were intensely sold by online retailers. Today’s internet shops are offering almost every imaginable product and service. This also leads to an increasing competition for traditional retailers offering products in stationary retail stores. Losing more and more customers stationary retailers need to think of new approaches for customer retention. Since customer retention is based on knowledge about the customers and their behavior store managers have to come up with new concepts for gaining and using customer knowledge to compete with bargain prices and 24/7 availability. In order to gain this knowledge without using vague customer surveys or short-time observations an automated solution is desirable. In this paper an approach is introduced, which allows to track and analyze customer movements through the store. Person tracking is accomplished by using aerial mounted cameras and a set of computer vision algorithms. Based on the captured movement data customer behavior analysis is performed by applying the dbscan algorithm and Markov models. The approach is illustrated by a test environment showing considerable differences in customer behavior for two settings.
Using Context Awareness to Improve Domain-Specific Named Entity Disambiguation

In this project we designed and implemented a system based on the Learning To Rank framework to perform Named Entity Disambiguation (NED) of ancient author names and work titles being parts of canonical bibliographic citations. The data is made of abstracts extracted from modern publications in the context of Classical Studies. We had to deal with domain specific challenges like the small set of available annotated data, the high level of ambiguity of the citations and a specific knowledge base which does not include the common properties of the knowledge bases usually used in state-of-the-art NED systems like Wikipedia. Finally our system improved the already implemented baseline system and reached a F1 score of 77.62% (+7.1%) and 71.88% accuracy (+10.2%). We also demonstrated how we can further improve the disambiguation by exploiting the co-occurrence probability of entities extracted from the corpus. With this method we improved our system by 6.8% in terms of accuracy on a sub-set of 59 documents.
Hessian matrix-free lagrange-newton-krylov-schur-schwarz methods for elliptic inverse problems

This study focuses on the solution of inverse problems for elliptic systems. The inverse problem is constructed as a PDE-constrained optimization, where the cost function is the L2 norm of the difference between the measured data and the predicted state variable, and the constraint is an elliptic PDE. Particular examples of the system considered in this stud, are groundwater flow and radiation transport. The inverse problems are typically ill-posed due to error in measurements of the data. Regularization methods are employed to partially alleviate this problem. The PDE-constrained optimization is formulated as the minimization of a Lagrangian functional, formed from the regularized cost function and the discretized PDE, with respect to the parameters, the state variables, and the Lagrange multipliers. Our approach is known as an "all at once method. " An algorithm is proposed for an inverse problem that is capable of being extended to large scales. To overcome storage limitations, we develop a parallel preconditioned Newton-Krylov method employed in a Hessian-free manner. The preconditioners have an inner-outer structure, taking the form of a Schur complement (block factorization) at the outer level and Schwarz projections at the inner level. However, building an exact Schur complement is prohibitively expensive. Thus, we use Schur complement approximations, including the identity, probing, the Laplacian, the J operator, and a BFGS operator. For exact data the exact Schur complements are superior to the inexact approximations. However, for data with noise the inexact methods are competitive to or even better than the exact in every computational aspect. We also find that nousymmetric forms of the Karush-Kuhn-Tucker matrices and preconditioners are competitive to or better than the symmetric forms that are commonly used in the optimization community. In this study, iterative Tikhonov and Total Variation regularizations are proposed and compared to the standard regularizations and each other. For exact data with jump discontinuities the standard and iterative Total Variation regulations are superior to the standard and iterative Tikhonov regularizations. However, in the case of noisy data the proposed iterative Tikhonov regularizations are superior to the standard and iterative Total Variation methods. We also show that in some cases the iterative regularizations are better than the noniterative. To demonstrate the performance of the algorithm, including the effectiveness of the preconditioners and regularizations, synthetic one- and two-dimensional elliptic inverse problems are solved, and we also compare with other methodologies that are available in the literature. The proposed algorithm performs well with regard to robustness, reconstructs the parameter models effectively, and is easily implemented in the framework of the available parallel PDE software PETSc and the automatic differentiation software ADIC. The algorithm is also extendable to three-dimensional problems.
Detection of Brain Tumor Using Different Edge Detection Algorithm

Although edge information is the main clue in image segmentation, it can’t get a better result in analysis the content of images without combining other information. The segmentation of brain tissue in the magnetic resonance imaging (MRI) is very important for detecting the existence and outlines of tumors. In the paper, an algorithm about segmentation based on the symmetry character of brain MRI image is presented. Our goal is to detect the position and boundary of tumors automatically. Experiments were conducted on real pictures, and the results show that the algorithm is flexible and convenient.
Classification of Clothing Attributes Across Domains

Classifying clothing attributes in surveillance images can be useful in the forensic field, making it easier to, for example, find suspects based on eyewitness accounts. Deep Neural Networks are often used successfully in image classification, but require a large amount of annotated data. Since labeling data can be time consuming or difficult, and it is easier to get hold of labeled fashion images, this thesis investigates how the domain shift from a fashion domain to a surveillance domain, with little or no annotated data, affects a classifier. In the experiments, two deep networks of different depth are used as a base and trained on only fashion images as well as both labeled and unlabeled surveillance images, with and without domain adaptation regularizers. The surveillance dataset is new and consists of images that were collected from different surveillance cameras and annotated during this thesis work. The results show that there is a degradation in performance for a classifier trained on the fashion domain when tested on the surveillance domain, compared to when tested on the fashion domain. The results also show that if no labeled data in the surveillance domain is used for these experiments, it is more effective to use the deeper network and train it on only fashion data, rather than to use the more complicated unsupervised domain adaptation method.
The QuIC: Quantitative Intellectual Capital- based methodology for Firm Valuation

The paper proposes a new methodology for evaluating the market value of firms (QuIC – Quantitative Intellectual Capital-based methodology for Firm Valuation) that considers Intellectual Capital (IC) as an important factor that can influence the overall value. Findings show that this approach gives a more fair evaluation able of taking account of the “hidden” value that could remain unconsidered when applying “traditional” valuation approaches. In fact, findings demonstrated that, from a financial standpoint, the difference between DCF and QuIC evaluation can be recognised as the worth of intellectual capital assets.
Tobacco endgame intervention impacts on health gains and Māori:non-Māori health inequity: a simulation study of the Aotearoa/New Zealand Tobacco Action Plan

Background The Aotearoa/New Zealand Government is aiming to end the tobacco epidemic and markedly reduce Māori:non-Māori health inequalities by legislating: (1) denicotinisation of retail tobacco, (2) 95% reduction in retail outlets and (c) a tobacco free-generation whereby people born after 2005 are unable to legally purchase tobacco. This paper estimates future smoking prevalence, mortality inequality and health-adjusted life year (HALY) impacts of these strategies. Methods We used a Markov model to estimate future yearly smoking and vaping prevalence, linked to a proportional multistate life table model to estimate future mortality and HALYs. Results The combined package of strategies (plus media promotion) reduced adult smoking prevalence from 31.8% in 2022 to 7.3% in 2025 for Māori, and 11.8% to 2.7% for non-Māori. The 5% smoking prevalence target was forecast to be achieved in 2026 and 2027 for Māori males and females, respectively. The HALY gains for the combined package over the population’s remaining lifespan were estimated to be 594 000 (95% uncertainty interval (UI): 443 000 to 738 000; 3% discount rate). Denicotinisation alone achieved 97% of these HALYs, the retail strategy 19% and tobacco-free generation 12%. By 2040, the combined package was forcat to reduce the gap in Māori:non-Māori all-cause mortality rates for people 45+ years old by 22.9% (95% UI: 19.9% to 26.2%) for females and 9.6% (8.4% to 11.0%) for males. Conclusion A tobacco endgame strategy, especially denicotinisation, could deliver large health benefits and dramatically reduce health inequities between Māori and non-Māori in Aotearoa/New Zealand.
Determination of the excess noise of avalanche photodiodes integrated in 0.35-μm CMOS technologies

Abstract. The excess noise of avalanche photodiodes (APDs) integrated in a high-voltage (HV) CMOS process and in a pin-photodiode CMOS process, both with 0.35-μm structure sizes, is described. A precise excess noise measurement technique is applied using a laser source, a spectrum analyzer, a voltage source, a current meter, a cheap transimpedance amplifier, and a personal computer with a MATLAB program. In addition, usage for on-wafer measurements is demonstrated. The measurement technique is verified with a low excess noise APD as a reference device with known ratio k = 0.01 of the impact ionization coefficients. The k-factor of an APD developed in HV CMOS is determined more accurately than known before. In addition, it is shown that the excess noise of the pin-photodiode CMOS APD depends on the optical power for avalanche gains above 35 and that modulation doping can suppress this power dependence. Modulation doping, however, increases the excess noise.
MODELLING LONG-TERM OUTCOMES AND RISK OF DEATH FOR PATIENTS WITH POST-STROKE SPASTICITY RECEIVING ABOBOTULINUMTOXINA TREATMENT AND REHABILITATION THERAPY

Objective Stroke is associated with a high risk of death and cardiovascular events. Rehabilitation therapy is critical for functional recovery, to reduce hospital readmissions, all-cause and cardiovascular mortality, and stroke recurrence (long-term outcomes). Post-stroke spasticity may prevent effective recovery by restricting mobility. AbobotulinumtoxinA is an adjunctive therapy to physical therapy for post-stroke spasticity, but its long-term effects are unknown. The objective was to model the long-term clinical and economic outcomes of abobotulinumtoxinA for post-stroke spasticity. Methods Effects of abobotulinumtoxinA on treating post-stroke spasticity and evidence linking functional outcomes with long-term outcomes were collected in a focused literature review. A model was developed to estimate health benefits on long-term outcomes, direct medical costs, life- and quality-adjusted life-years for abobotulinumtoxinA injections plus rehabilitation therapy compared with rehabilitation therapy alone, from a UK perspective over a 10-year time-period. Results AbobotulinumtoxinA + rehabilitation therapy led to a risk reduction of 8.8% for all-cause mortality, and an increase of 13% in life-years and 59% in quality-adjusted life-years compared with rehabilitation therapy alone. AbobotulinumtoxinA + rehabilitation therapy was considered cost-effective compared with rehabilitation therapy alone (incremental cost-effectiveness ratio: £24,602). Conclusion AbobotulinumtoxinA + rehabilitation therapy may improve long-term outcomes, including post-stroke survival, while being cost-effective for the treatment of post-stroke spasticity. LAY ABSTRACT Here we developed a model to explore and compare the long-term benefits and overall costs of two interventions for the treatment of post-stroke spasticity (PSS): abobotulinumtoxinA injections plus rehabilitation therapy (aboBoNT-A+RT) vs. RT alone. Stroke survivors are known to be at a higher risk of recurrent stroke and death, and more than 25% are affected by spasticity. PSS significantly reduces patients’ mobility, physical functioning, and subsequently their ability to recover after a stroke. AboBoNT-A+RT is an effective treatment for spasticity. This model is the first to highlight that combining aboBoNT-A injections with RT could improve the overall survival of stroke survivors with spasticity by 8.8% and their overall quality of life, while being considered good value for money by UK payers.
Chemically synthesised flavone and coumarin based isoxazole derivatives as broad spectrum inhibitors of serine β-lactamases and metallo-β-lactamases: a computational, biophysical and biochemical study

Abstract The β-lactam antibiotics are the most effective medicines for treating bacterial infections. Resistance to them, particularly through the production of β-lactamases, which can hydrolyse all kinds of β-lactams, poses a threat to their continued use. The synthesised flavone and coumarin based isoxazole derivatives have the potential to be used as broad-spectrum inhibitors of the mechanistically different serine-(SBL) and metallo-β-lactamases (MBL). The synthesised compounds were discovered as potent β-lactamase inhibitors using molecular docking and in silico pharmacokinetic analysis. We studied the binding of chemically synthesised inhibitors to clinically significant β-lactamases of class A, B, and C using biophysical and biochemical approaches, and computational analyses. These molecules follow Lipinski’s rule of five and have acceptable solubility, permeability, and oral bioavailability. These molecules were found to be non-toxic and non-carcinogenic. MIC results suggest that these molecules restore the antibiotic efficacy against class A, B, and C β-lactamases. Kinetics data showed that these molecules reduce the catalytic efficiency of clinically relevant class A, B, and C β-lactamases. Fluorescence study showed significant interaction between these flavone-/coumarin-based isoxazole derivatives and class A/B/ C β-lactamases. This study showed promising effect of these new generation compounds as broad spectrum β-lactamase inhibitors of both SBLs and MBLs. Communicated by Ramaswamy H. Sarma
Melatonin protects gingival mesenchymal stem cells and promotes differentiation into osteoblasts

Melatonin (MEL) has antioxidant properties and participates in osteogenic differentiation. In periodontitis, in which increased oxidative stress and bone resorption are involved, mesenchymal stem cells derived from the gingiva (GMSCs) combined with MEL could be relevant for osteogenic regeneration. In this study, we studied the antioxidant and differentiating effect of MEL on an in vitro system of GMSCs. Primary culture of GMSCs from Wistar rats was developed to evaluate differentiation into osteoblasts with an appropriate medium with or without MEL. Marker genes of mesenchymal stem cells by real time‐polymerase chain reaction, clonogenic capacity, and cell migration after wound assay were used to characterize GMSCs as mesenchymal stem cells. Alkaline phosphatase activity and the alizarin red technique were used to evaluate osteogenic activity and differentiation. MEL increased alkaline phosphatase activity and alizarin red values, promoting osteogenic differentiation. Besides this, MEL protected GMSCs in a model of cellular damage related to oxidative stress, returning viability to baseline. MEL was more effective in promoting and protecting GMSCs by the production of osteogenic cells when oxidative stress is present. This evidence supports the use of MEL as a novel bone‐regenerative therapy in periodontal diseases.
Detection of Wolbachia in Mosquitoes (Diptera: Culicidae) in the State of Maranhão, Brazil

Abstract Recently, the endobacteria Wolbachia has emerged as a biological tool for the control of arboviruses. Thus, we investigated the rate of natural infection by Wolbachia in Culicidae species from Maranhão, Brazil. For this, we amplified the Wolbachia surface protein gene (wsp) from mosquitoes collected in six localities of Maranhão, and positive samples were subjected to new analysis using group-specific primers. In total, 448 specimens comprising 6 genera and 18 species of mosquitoes were analyzed. Wolbachia DNA was PCR-detected in 7 species, three of which are new records: Aedes scapularis (Rondani, 1848), Coquillettidia juxtamansonia (Chagas, 1907) and Cq. venezuelensis (Theobald, 1912), in addition to Ae. albopictus (Skuse, 1894) and Culex quinquefasciatus Say, 1823, which are commonly described as permissive to maintain this bacterium in natural environments, and two species of the subgenera Anopheles (Nyssorhynchus) Blanchard, 1902 and Culex (Melanoconion) Theobald, 1903 which could not be identified at species level. The infection rate of all species ranged from 0 to 80%, and the average value was 16.5%. This study increases the knowledge about the prevalence of Wolbachia in the culicid fauna and may help in selecting strains for biological control purposes.