Miracle-dz/UniFAR-FTUs huggingface dataset:
A Blended Learning Model of Peer Support Training Program for Women with Breast Cancer

Objectives: Peer support is an important social support for cancer patients. A blended learning model of peer support training program in breast cancer was tested for feasibility . Methods: We developed a peer support training program for women with breast cancer with a blended learning approach combining face-to-face methods with e-learning. After face-to-face orientation, a 20-session e-learning program was provided on the Web followed by a one-day workshop including role playing. Log-files were recorded to assess the pattern of use in the e-learning program. The usability and acceptability were assessed by an evaluation questionnaire with a 5-point Likert scale. Psychosocial outcomes were assessed over time (baseline, post-program, and 3-month follow-up) using repeated measured one-way analysis of variance. Results: Twenty-eight women with breast cancer experience were recruited to the study. The rates of retention and assessment completion were high (92.9% and 89.3%, respectively). Participants favorably rated on the usability of the program. The mean time taken to complete the total of 20 sessions in the e-learning program was 18.69 days. There were no adverse psychosocial effects on the participants. Conclusions: The blended learning model of the breast cancer peer support training program was feasible and well accepted by the peer support volunteers .
Survey for ovine and caprine chlamydiosis by ELISA in AL-Fallujah city/Iraq

Our study was aimed to detect the prevalence of ovine and caprine chlamydiosis in Al-Fallujah city-Iraq by using ELISA, samples were randomly collected from sheep and goats in herds with a history of abortion during the period between October 2016 to March 2017, from out of 184 serum samples only 21 (11.41%) serum showed positive result to ELISA test, these positivity results are 12/124 (9.67%) ewes, 1/30(33.33%) rams, 6/21(28.57%) does and 2/9(22.22%) bucks. The highest prevalence of chlamydiosis in ovine and caprine was in Albu thaher (%16) while the lowest prevalence was in Alshehaa and Alsecher (%0). The age group (1-3 years) was recorded the highest prevalence of chlamydiosis (%17.54) in sheep, and (%13.88) in goat. For sheep the highest prevalence of chlamydiosis was recorded in December (20%), and lowest prevalence was recorded in October (%0), while in goats, the highest prevalence of chlamydiosis was recorded in January (20%), and the lowest prevalence was recorded in October and March (%0) with a significant difference (P<0.05). The study concluded that Chlamydiosis is endemic and a serious cause of abortion in sheep and goat.
Differential expression of antioxidant proteins in the drought-tolerant cyanobacterium Nostoc flagelliforme under desiccation.

Nostoc flagelliforme is a terrestrial nitrogen-fixing cyanobacterium that is distributed in arid or semi-arid steppes in Western and North-western of China. This species shows a strong ecological adaptability to xeric drought environments. 2DE coupled with MALDI-TOF-TOF/MS was used to analyze the differentially expressed antioxidant proteins in N. flagelliforme under desiccation. A total of five antioxidant proteins (eight protein spots) were successfully identified, including peroxiredoxin (Prx), Mn-containing catalase (Mn-CAT), iron superoxide dismutase (Fe-SOD), superoxide dismutase (SOD) and ferritin. These proteins were all significantly down-regulated except for Prx that was up-regulated, when N. flagelliforme was subjected to 24-h desiccation. The colonies maintained very limited amounts of water (15%) and very low physiological activity to resist severe drought. These proteins may serve as biochemical markers for N. flagelliforme colonies under desiccation because of their significant changes in expression level. In assition, the content of superoxide anions increased when the colonies were exposed to desiccating conditions for 6 hours. However, the content dropped when the desiccation treatment lasted for 24 hours.
ERP and Application Status: A Review of Vietnam’s SMEs

This article was studied due to the necessity of applying ERP systems in small and medium-sized enterprises (SMEs). By researching, this study analyzes the evident problem in applying ERP systems in SMEs in Vietnam. It presents a review of ERP systems and states the operational definition as well as the reason of the low rate of ERP application in SMEs in Vietnam. The implications will be consistent with the Vietnamese SMEs to deploy ERP into effect.
A high-bandwidth electromagnetic MEMS motion stage for scanning applications

This paper presents the design, fabrication methods and experimental results for a MEMS-based out-of-plane electromagnetic motion stage for scanning applications. The combination of electromagnetic actuation and a flexure-supported platform provides linear bidirectional motion with high precision. A planar microcoil and a permanent magnet are used to generate a Lorentz force, which drives the flexure-supported platform. The copper microcoil is electroplated on a silicon substrate and the platform is fabricated through silicon bulk micromachining of a silicon-on-insulator wafer. The resonant frequency of the fabricated motion stage is approximately 2.0 kHz, which results in an open-loop control bandwidth greater than 500 Hz. Experimental results verify that the stage has highly linear bidirectional motion with negligible hysteresis and nonlinearity over a ± 2.7 µm range. Additionally, excellent high-frequency tracking performance is demonstrated using open-loop control, with a tracking error below 6.5 nm RMS for scan rates up to 200 Hz.
Assessing a Clarinet Player's Performer Gestures in Relation to Locally Intended Musical Targets

Abstract Musicianship is known to display high-level skills, which involve different aspects of mental processing and corporeal control. Of particular interest is the match between the musician's mental focus on musical targets (the so-called musical intentions) and the expressive (or so-called auxiliary) body movements. To what extent are these related to each other? And what does this relationship reveal about mind–body connections? To approach these questions, a case study was set up around a clarinet solo performance played from score, covering a style of music unfamiliar to the player. The clarinetist's movements were recorded with an optical movement tracking system. A statistical analysis method was developed, to account for movement data in relation to the potential musical intentions and targets. The bottom-up movement analysis method was validated with the performer's annotations of targets in the musical score and the performer's annotations of communicative/sound facilitating gestures in the performance video. The results reveal that the mental focus on musical targets is related to bodily expression. This finding supports the idea of an embodied model of musical syntax processing, which is strongly related to corporeal gestures.
On a diffuse interface model for a two-phase flow of compressible viscous fluids

We consider a model of a binary mixture of compressible, viscous, and macroscopically immiscible fluids based on the diffuse interface approximation, where the difference in concentrations of the two fluids plays the role of the order parameter. The resulting system consists of the compressible Navier-Stokes equations governing the motion of the mixture coupled with the Cahn-Hilliard equation for the order parameter. We prove existence of global-in-time weak (distributional) solutions of the problem without any restriction on the size of initial data.
STRUCTURAL OPTIMISATION AS A MOVING BOUNDARY PROBLEM USING LEVEL SET FUNCTIONS

Abstract. This extended abstract presents topology optimisation which uses level set functions representing the moving boundaries. The level set function based approach to topology optimisation has gained much popularity in the recent years due to its numerical stabilities and clear boundary representation of the solution. One advantage of the level set representation is its inherent capability to handle topological changes such as merging and splitting boundaries. We have developed a stable hole nucleation algorithm which makes the level set formulation completely suitable for topology optimisation. We demonstrate that our level set topology optimisation, both in 2D and 3D, have good convergence properties and less dependency on the initial design. We apply this to typical structural optimisation problems as well as coupled aero-structural problems. As coupled multidisciplinary optimisation problems have multiple optima, we find that the solutions 3D level set topology optimisation produce can be quite different from the solutions from the previous elementbased approaches and simplified 2D solutions, suggesting potential alternatives.
Boosting Algorithms as Gradient Descent in Function Space

Much recent attention, both experimental and theoretical, has been focussed on classii-cation algorithms which produce voted combinations of classiiers. Recent theoretical work has shown that the impressive generalization performance of algorithms like AdaBoost can be attributed to the classiier having large margins on the training data. We present abstract algorithms for nding linear and convex combinations of functions that minimize arbitrary cost functionals (i.e functionals that do not necessarily depend on the margin). Many existing voting methods can be shown to be special cases of these abstract algorithms. Then, following previous theoretical results bounding the generalization performance of convex combinations of classiiers in terms of general cost functions of the margin, we present a new algorithm (DOOM II) for performing a gradient descent optimization of such cost functions. Experiments on several data sets from the UC Irvine repository demonstrate that DOOM II generally outperforms AdaBoost, especially in high noise situations. Margin distribution plots verify that DOOM II is willing tògive up' on examples that are too hard in order to avoid overrtting. We also show that the overrtting behavior exhibited by AdaBoost can be quantiied in terms of our proposed cost function.
DISTINGUISHABILITY BASED WEIGHTED FEATURE SELECTION USING COLUMN WISE K NEIGHBORHOOD FOR THE CLASSIFICATION OF GENE MICROARRAY DATASET

In data mining, much research is being carried out to discover the previously unknown, valid, novel, useful and understandable patterns in large databases. The patterns must be actionable so that they might be used for decision making to a variety of applications in healthcare. In this study, feature subset selection is an important area, where many approaches have been proposed. Hence, the authors chosen three existing feature selection algorithms analyzed their performance using the publicly available standard colon tumor dataset. The performance of the existing three methods evaluated and compared each method with DWFS-CKN under study.
Allozyme variation and differentiation in Chionomys nivalis (Martins, 1842)

Allozyme variation and divergence were investigated by electrophoretic analysis of 34 gene loci in eight populations of Chionomys nivalis from Northern Italy (Ch. n. nivalis, Ch. n. leucurus), Yugoslavia (Ch. n. malyi), and Israel (Ch. n. hermonis).
Présentation et évaluation d'une méthode de mesure morphométrique en 3 dimensions

Cette these porte sur une nouvelle methode de quantification de la conformation du cheval (morphometrie). La premiere partie, bibliographique, presente les methodes utilisees jusqu’a present. Mesurer la conformation d’un grand effectif de chevaux de maniere quantitative n’etait possible jusqu’ici qu’avec des methodes photometriques, qui ne peuvent fournir que des mesures en 2D et imposent l’utilisation de marqueurs cutanes. La nouvelle methode de mesure morphometrique 3-D dont la presentation et l’evaluation font l’objet de cette these, consiste a filmer les chevaux au pas, sans marqueurs, a l’aide de quatre cameras video. Les films sont ensuite numerises et synchronises. Une serie de quatre images est selectionnee pour chacune des deux positions de reference (anterieure et posterieure). Vingt-huit reperes anatomiques sont ensuite releves, c'est-a-dire localises sur au moins deux des quatre images de chaque serie. La calibration des images permet d’obtenir les coordonnees 3-D de ces reperes, a partir desquelles 400 parametres morphometriques sont calcules de facon automatique. La derniere partie de cette these presente une evaluation de cette methode, en particulier sous l’angle de la repetabilite des mesures.
The accrual anomaly in the Greek stock market

The authors examine the negative relation of traditional accruals and % accruals with future returns in the Greek stock market. Positive abnormal returns from hedge portfolios on both accrual measures summarize the economic significance of this negative relation. The magnitude of returns obtained from traditional accruals is higher than that obtained from % accruals, contrary to existing evidence from the U.S. capital market. The analysis suggests that the accrual anomaly appears to be present in the Greek stock market: this has macroeconomic implications because firms with low reported accruals may exhibit higher stock returns and at this time, during the ongoing Greek capital market crisis, investors are more likely to gain substantial abnormal returns in the future – if and when the Greek economy returns to positive growth.
Effect of dietary Salvia officinalis essential oil and sodium selenite supplementation on antioxidative status and blood phagocytic activity in broiler chickens

Selected indicators of the antioxidant status and blood phagocytic activity were investigated in broiler chickens fed diets enriched with essential oil from Salvia officinalis and/or sodium selenite for 5 weeks. Twenty four one-day-old Ross 308 hybrid broilers were randomly divided into four groups according to dietary treatments. The control group was fed unsupplemented basal diet, whereas the feeds of three treatment groups were supplemented with essential oil (0.05%), sodium selenite (0.4 mg Se/kg dry matter) or their combination, respectively. The intake of diets containing essential oil alone or together with Se significantly elevated (P < 0.05) the total antioxidant status in plasma. The combination of essential oil and sodium selenite added to the basal diet resulted in significant reduction (P < 0.05) of superoxide dismutase activity in erythrocytes, increased activities of glutathione peroxidase in liver (P < 0.001) and duodenal mucosa (P < 0.05) compared to the control. Higher malondialdehyde concentrations in kidney tissues (P < 0.01) of chickens supplemented with sodium selenite were reduced by addition of essential oil to their diet. Blood phagocytic activity was significantly (P < 0.001) increased in both groups supplemented with selenium. The presented results demonstrate that Salvia officinalis essential oil and sodium selenite jointly added to diets had a more positive effect on the antioxidant status of broilers than when both additives were administered separately. Sage, selenium, antioxidant enzymes, poultry
Discourses of Race & Racism Within Environmental Justice Studies: An Eco-racial Intervention

The social force of racism in relation to natural resources plays a prominent role in the development of environmental justice (EJ) studies within the United States. I contend that the dominant paradigm of environmental racism (ER) may encourage superficial applications of race and racism and colorblind approaches to EJ. I argue that race and racism are at times essentialized, which has in part to do with essentialized notions of the environment. The goal of this eco-racial intervention is to encourage more explicit engagement with the dynamic ways that society creates meaning around and makes use of race and natural resources in relation to each other, processes that may include and operate beyond conventional and critical approaches to ER. Spirited by critical ER and racial formation theory, I propose the construct ‘eco-racial justice project’ as part of an alternative framework for evaluating racialization within efforts to achieve environmental justice.
Vehicle data analysis using cloud-based stream processing

In the automotive industry, maintenance planning can be seen as a set of strategies that aims to increase the uptime of vehicles. Unexpected events such as if a vehicle suddenly stops due to internal component failures or due to a flat tire are in the context of maintenance planning referred to as unplanned stops. For transport vehicles, unplanned stops are critical and will in most cases lead to late deliveries and possibly damaged goods and can in the worst case imply dangerous consequences for the driver of the vehicle. As data become more and more available and the connectivity in vehicles get better, more advanced techniques can be applied when it comes to maintenance planning. The demand of creating self-learning or automated systems that can predict unplanned stops is increasing due to the big amounts of data that are generated by today’s systems. Manually analyzing vehicle data is becoming an unsustainable approach and it is hard for humans to keep up with the digitised systems due to increased complexity and big data amounts in the vehicles. In this thesis, we propose a concept that enables stream processing on vehicle data on a remote machine. The implementation of the proposed concept is built using state-of-the-art streaming components, namely Apache Spark Streaming and Apache Kafka. This thesis focuses more on the design of the system architecture and the components of the concept. The results show that it is possible to create machine learning models that continuously evolves and learns from data streams. Implementations of the proposed concept can for example be used to detect anomalies in vehicle components remotely without re-configuring any software inside the vehicles. The machine learning models that were trained with a Volvo data set did not deliver the desired prediction accuracy for the area of maintenance planning. Future work in this area would require further research in which online machine learning algorithms that best fits this vehicle data and also how features should be chosen to be able to predict anomalies in vehicle data.
Probabilistic Outputs for Support vector Machines and Comparisons to Regularized Likelihood Methods

The output of a lassi(cid:12)er should be a alibrated posterior probability to enable post-pro essing. Standard SVMs do not provide su h probabilities. One method to reate probabilities is to di-re tly train a kernel lassi(cid:12)er with a logit link fun tion and a regularized maximum likelihood s ore. However, training with a maximum likelihood s ore will produ e non-sparse kernel ma-hines. Instead
The Impact of the 1998 Forest Fire on Ectomycorrhizae of Dipterocarp Trees and their Recovery in Tropical Rain Forests of East Kalimantan, Indonesia

The impact of forest fire in 1997 and 1998 on the mycorrhzae was studied at the dipterocarp forest in East Kalimantan, Indonesia. In unaffected forest more than half of total ectomycorrhizae distributed in the organic layer but in the fire-affected forest one and a half years after the fire, total amount of mycorrhizae was smaller and they were found in deeper soil. The number of morphotypes of mycorrhizae was also smaller in fire-affected forest. An artificial plantation established after clear cut and prescribed burn had the largest amount of ectomycorrhizae, but the diversity was smaller than the unaffected forest. After four years, mycorrhizae had not yet recovered in fire-affected forest although the organic layer had recovered. Pioneer species of mycorrhizal fungi (early-stage fungi) developed sporocarps around the surviving hosts in severely affected forest and this suggests the start of secondary succession of mycorrhizae. In moderately affected forest, the species composition of mycorrhizal fungi which fruited during the study was similar to those of unaffected forest. This fact suggests that such sites may be the refugia of symbionts and be important in reforestation.
TAX COMPETITION OR TAX INNOVATION?: AN EMPIRICAL ANALYSIS OF INTERDEPENDENCE IN TAX AUDITING POLICIES *

Tax interdependence among subcentral governments might not only occur regarding statutory tax parameters, but also in administrative tax parameters. We aim at testing the empirical relevance of this latter kind of interdependence, in particular, focusing on tax auditing policies. We use a publicized database regarding the behaviour of regional tax administrations in Spain (1987-2001), and find empirical evidence of a strong positive interdependence among them. We identify two potential sources of interdependence: tax competition and (diffusion of) tax innovation. Both are certainly at work, although the latter is especially present since 1997, when formal forums of collaboration among tax administrations were created.
How are NH 3 dry deposition estimates affected by combining the LOTOS-EUROS model with IASI-NH 3 satellite observations?

Abstract. Atmospheric levels of reactive nitrogen have substantially increased during the last century resulting in increased nitrogen deposition to ecosystems, causing harmful effects such as soil acidification, reduction in plant biodiversity and eutrophication in lakes and the ocean. Recent developments in the use of atmospheric remote sensing enabled us to resolve concentration fields of NH 3 with larger spatial coverage and these observations may be used to improve the quantification of NH 3 deposition. In this paper we use a relatively simple, data-driven method to derive dry deposition fluxes and surface concentrations of NH 3 for Europe and for the Netherlands. The aim of this paper is to determine for the applicability and the limitations of this method for NH 3 using space-born observations of the Infrared Atmospheric Sounding Interferometer (IASI) and the LOTOS-EUROS atmospheric transport model. The original modelled dry NH 3 deposition flux from LOTOS-EUROS and the flux inferred from IASI are compared to indicate areas with large discrepancies between the two and where potential model improvements are needed. The largest differences in derived dry deposition fluxes occur in large parts of Central Europe, where the satellite-observed NH 3 concentrations are higher than the modelled ones, and in Switzerland, northern Italy (Po Valley) and southern Turkey, where the modelled NH 3 concentrations are higher than the satellite-observed ones. A sensitivity analysis of 8 model input parameters important for NH 3 dry deposition modelling showed that the IASI-derived dry NH 3 deposition fluxes may vary from ~ 20 % up to ~ 50 % throughout Europe. Variations in the dry deposition velocity used for NH 3 led to the largest deviations in the IASI-derived dry NH 3 deposition flux and should be focused on in the future. A comparison of NH 3 surface concentrations with in-situ measurements of several established networks (EMEP, MAN and LML) showed no significant, or consistent improvement in the IASI-derived NH 3 surface concentrations compared to the originally modelled NH 3 surface concentrations from LOTOS-EUROS. It is concluded that the IASI-derived NH 3 deposition fluxes do not show strong improvements compared to modelled NH 3 deposition fluxes and there is future need for better, more robust, methods to derive NH 3 dry deposition fluxes.