Miracle-dz/UniFAR-FTUs huggingface dataset:
The effect of human adipose-derived stem cells on lipopolysaccharide-induced acute respiratory distress syndrome in mice.

Background Acute respiratory distress syndrome (ARDS) is a type of acute respiratory failure in critically ill patients. Recently, several treatment modalities have been proposed for ARDS, but it still has a high mortality rate. In general, the role of mesenchymal stem cells (MSCs) in controlling inflammatory responses has been studied in various immune-associated diseases in humans and animals. However, only a few studies reported adipose-derived stem cells (ASCs), which are easier to isolate, are currently emerging as an attractive treatment option in ARDS. Therefore, in this study, we investigated the therapeutic effects of human ASCs and the regulation of inflammatory responses in an ARDS mouse model. Methods In the ARDS model, lipopolysaccharide (LPS) (5 mg/kg) was administered via the intra tracheal injection method. The mice were divided into the following four groups: (I) saline + medium; (II) saline + ASCs (2×105); (III) LPS + medium; (IV) LPS + ASCs. The ARDS observation time was divided into short and long term. LPS administration increased the concentration of proinflammatory cytokines, which was a consistent systemic inflammatory response. Results LPS/ASC group showed less neutrophil infiltration and less alveolar hemorrhage or congestion than did the LPS group. The lung injury scores of the LPS/ASC group were lower than those of the LPS group (3.8±0.9 vs. 6.8±1.1; P=0.03) at day 2. Compared to the LPS group, LPS/ASC group showed reduced collagen deposition around the vessels and fibrosis accompanied by alveolar septal or interstitial thickening and lower MPO levels than did the LPS group (453.2±26.2 vs. 670.2±65.9 pg/mL; P<0.01) at day 7. Conclusions ASC therapy can inhibit neutrophil recruitment, which shows trend of reducing short term lung injury (day 2) and affecting fibrosis in long term (day 7). Further studies are warranted to understand the mechanism and improve the therapeutic effect of ASCs.
Objective reduction in many-objective optimization problems

Many-objective optimization problems (MaOPs) are multi-objective optimization problems which have more than three objectives. MaOPs face significant challenges because of search efficiency, computational cost, decision making, and visualization. Many well-known multi-objective evolutionary algorithms do not scale well with an increasing number of objectives. The objective reduction can alleviate such difficulties — however, most research in objective reduction use non-dominated sorting or Pareto ranking. However, Pareto is effective in problems having less than four objectives. In this research, we use two approaches to objective reduction: random-based and linear coefficient-based. We use the sum of ranks instead of Pareto Ranking. When applied to many-objective problems, the sum of ranks has outperformed many other optimization approaches. We also use the age layered population structure (ALPS). We use ALPS in our approach to remove premature convergence and improve results. The performance of the proposed methods has been studied extensively on the famous benchmark problem DTLZ. The original GA and ALPS outperform the objective reduction algorithms in many test cases of DTLZ. Among all reduction algorithms, a linear coefficient based reduction algorithm provides better performance for some problems in this test suite. Random based reduction is not an appropriate strategy for reducing objectives.
Incremental Learning Techniques for Part-Based Semantic Segmentation

Semantic Image Segmentation is a computer vision task in which we label each single pixel in an image according to the semantic content. This task is of essential importance for a wide range of applications as: autonomous vehicles, robot perception, human-machine interaction, medical image segmentation, image editing tools, image search engines and augmented reality to name a few. However some application tasks need more accurate scene understanding, for robot perception a human body part segmentation can be a very valuable tool in order to identify parts such as hands and interact with them, in this case it is possible to talk of Part-Based Semantic Segmentation. Although many works have studied this topic and the Pascal-Part dataset has been created specifically for this scope, most of these works concern only parts of few classes as human, animals, cars. One of the biggest problems is to find a more general model capable of learning at the same time a huge number of parts from different classes. In this work we use an Incremental Learning approach to try to develop such model. Our framework uses two networks where the second one is fed with the output of the first. The first network performs the Semantic Segmentation task with 21 classes from the Pascal-VOC dataset, while the second one performs the Part-Based Semantic Segmentation task with 108 classes\parts on the Pascal-Part dataset. We achieve this goal using the features extracted by a custom CNN from the softmax (or argmax) output of the first network to constraint and condition the prediction of the parts. Additionally, we have studied a new loss, with the aim of relating different parts of the same class throught an Adjcency-matrix. Then, a distance function is applied to minimize discrepancies between the predicted matrix and the ground-truth one, this should teach to the network to penalize parts that should not be close. Comparing our model results with a simple network for Semantic Segmentation adapted for our task, we were able to increase the Mean Intersection over Union from 29.9% to 35.1%.
Embryogenic potential of the callus of gabirobeira, Campomanesia adamantium (Cambess) O. Berg

Campomanesia adamantium is a native plant species of Brazilian Cerrado with diverse economic potential and great medicinal importance. Its sexual propagation is impaired by the recalcitrance of its seeds, which prevents effective and profitable propagation. With the purpose of establishing commercial crops and minimizing the extractive use of vegetal resources, the aim of the present study was to induce embryogenic calli in nodal segments of gabirobeira, and to determine and characterize their embryogenic phase through the establishment of a growth curve based on cellular characteristics. Calli were induced using nodal segments inoculated in WPM culture medium without the addition of hormones (control) and with different concentrations of 2,4-D, IAA, IBA, NAA or picloram. Cytochemical and SEM analyses revealed cellular characteristics of the formation of meristematic centers that indicated 4.14 μM of picloram to be the best treatment for induction of embryogenic calli, and demonstrating their embryogenic potential. The treatment was used to establish a callus growth curve, from which it was inferred that calli should be transferred to new culture media on the 28 day to maintain cell viability.
DRAGON FRUIT COUNTRY REPORT FROM INDIA

Dragon fruit (Hylocereus spp.), a herbaceous perennial climbing cactus, widely known as Red Pitaya, has recently drawn much attention among the Indian growers, not only because of its attractive red or pink color and economic value as fruit, but also valued for its high antioxidant potential, vitamins and minerals content. Being a native of Southern Mexico, Guatemala and Costa Rica, dragon fruit was introduced in India during the late `90s and still the area under its cultivation is gradually increasing. Farmers in the Indian states of Karnataka, Kerala, Tamil Nadu, Maharashtra, Gujarat, Orissa, West Bengal, Andhra Pradesh and Andaman & Nicobar Islands have already taken up its cultivation, and the estimated total area under Dragon fruit cultivation in these regions may be less than 400 ha. Majority of the dragon fruits presently available in Indian markets are imported from Vietnam, Thailand, Malaysia and Sri Lanka. Being a cactus family and requires long day for flowering, dragon fruit cultivation is well suited in the agro-climatic regions of Southern, Western and North Eastern India that are dry and frost-free. Due to high demand both in domestic and international markets, dragon fruit production could be an economical avocation to both backyard growers as well as entrepreneurs of medium and large scale plantations. Cultivation of dragon fruit already started in different parts of India with many success stories of farmer from different regions. Many nursery men started propagation for raising planting material of dragon fruit. One of the widely grown cultivars and most commonly available dragon fruit is the red color epicarp with white and pink pulped sub-sweet juicy pulp matrix. It is a fast return perennial fruit crop with economic production in the first year after planting, and full production within three to five years. It was also noted to initially produce in its first years on wards provided desirable cultural management practices are applied. Although the initial investment is relatively high, profit is substantial within 4-5 years. The red flesh species i.e H. costaricensis are additionally rich in betalains, meeting the increasing trade interest for antioxidant products and natural food colorant. Fruits are easy to keep fresh under room condition. The crop is hardy and can survive in any type of climatic condition favorable for flowering and fruiting and soil condition provided with good drainage.
Basic theory of educational neuroscience for mathematics teachers – a review

kakoma Luneta university of johannesburg kluneta@uj.ac. za ABSTRACT – This paper is a review of how the knowledge of educational neuroscience by teachers of mathematics and its inclusion in mathematics teacher education curricula can enhance our understanding of how students learn mathematics. It is premised on studies that point to two of the obstacles that teachers of mathematics face, that is we know almost nothing about how people do mathematics and we almost know nothing about how people learn how to do mathematics. Teachers’ understanding and knowledge of what goes on in the brain and mind as learners grapple with mathematical concepts and facts could enhance the way we teach and disseminate mathematical information. Teachers’ knowledge of educational neuroscience will also dispel neuromyths a presentation of facts with little or no scientific bases about the science of the brain, memory and learning
Spectral Diversity Successfully Estimates the α-Diversity of Biocrust-Forming Lichens

Biocrusts, topsoil communities formed by mosses, lichens, liverworts, algae, and cyanobacteria, are a key biotic component of dryland ecosystems worldwide. Experiments carried out with lichen- and moss-dominated biocrusts indicate that climate change may dramatically reduce their cover and diversity. Therefore, the development of reproducible methods to monitor changes in biocrust diversity and abundance across multiple spatio-temporal scales is key for evaluating how climate change may impact biocrust communities and the myriad of ecosystem functions and services that rely on them. In this study, we collected lichen-dominated biocrust samples from a semi-arid ecosystem in central Spain. Their α-diversity was then evaluated using very high spatial resolution hyperspectral images (pixel size of 0.091 mm) measured in laboratory under controlled conditions. Support vector machines were used to map the biocrust composition. Traditional α-diversity metrics (i.e., species richness, Shannon’s, Simpson’s, and Pielou’s indices) were calculated using lichen fractional cover data derived from their classifications in the hyperspectral imagery. Spectral diversity was calculated at different wavelength ranges as the coefficient of variation of different regions of the reflectance spectra of lichens and as the standard deviation of the continuum removal algorithm (SD_CR). The accuracy of the classifications of the images obtained was close to 100%. The results showed the best coefficient of determination (r2 = 0.47) between SD_CR calculated at 680 nm and the α-diversity calculated as the Simpson’s index, which includes species richness and their evenness. These findings indicate that this spectral diversity index could be used to track spatio-temporal changes in lichen-dominated biocrust communities. Thus, they are the first step to monitor α-diversity of biocrust-forming lichens at the ecosystem and regional levels, a key task for any program aiming to evaluate changes in biodiversity and associated ecosystem services in drylands.
Peculiarities of Use of Bentonite Clay at Solid-Phase Purification of Anthocyanins and Flavonoids from Leaves of Plants

Anthocyanins of red colored leaves of Cercis canadensis L. were found to be 3-glucosides of five common anthocyanidins of delphinidin, cyaniding, petunidin, peonidin and malvidin with overall accumulation more than 350 mg per 100 g of FW in early summer. The content of anthocyanins gradually drops to total disappearance at the late September. Extract of anthocyanins may content a large amount of flavonoids that are not separated during solid phase extraction (SPE) on C18-silica syringe cartridges. In the paper, the ability of bentonite clay as a sorbent for SPE of anthocyanins was investigated. Non-charged flavonoids were shown to compete with anthocyanins during sorption. Meanwhile sorption ability of anthocyanins markedly exceeds that of non-charged flavonoids. The method for anthocyanins and non-charged flavonoids is proposed. Keywords—anthocyanins, Cercis canadensis L. , leaves, SPE, flavonoids, clay
Managing time in a changing world: Timing of avian annual cycle stages under climate change

Dieren moeten seizoensstadia, zoals broeden en migratie, dusdanig timen dat deze plaatsvinden op het juiste moment. Ze gebruiken omgevingssignalen om veranderingen te voorspellen en deze stadia daardoor goed te plannen. Maar wat gebeurt er wanneer klimaatverandering de mogelijkheid tot het maken van deze voorspellingen beinvloed? Door klimaatverandering moeten vogels de stadia van hun jaarlijkse cyclus vervroegen, maar elk stadium kan anders verschuiven. Hierdoor verandert de tijd die beschikbaar is tussen de stadia, bijvoorbeeld de tijd tussen broeden en ruien, waardoor dieren het moeilijk kunnen krijgen om hun jaarlijkse cyclus als geheel te organiseren. We hebben de oorzaken en de consequenties van ongelijke verschuivingen in de timing van stadia in de jaarlijkse cyclus onderzocht in de Bonte Vliegenvanger (Ficedula hypoleuca). Deze vogels migreren elk voorjaar van hun overwinteringsgebieden in westelijk Afrika naar hun broedgebieden in Europa, waar ze minder dan 5 maanden per jaar verblijven. In dit korte interval moeten ze de belangrijke broed- en ruistadia passen, maar ook de overgang van aankomst naar broeden en de voorbereiding op de herfstmigratie. Als reactie op klimaatverandering zijn de timing van aankomst, broeden en rui verschoven met verschillende snelheden, wat resulteert in een korter tijdsinterval tussen aankomst en broeden en tussen broeden en rui. Klimaatopwarming leidt dus zowel tot het verhogen als het verlagen van de tijdsdruk, afhankelijk van het stadium. De kosten van deze verschuivingen varieren tussen geslachten en leeftijden van de vogels. Voor een breder begrip van de ecologische consequenties van klimaatverandering moeten verschillende stadia van de jaarlijkse cyclus worden onderzocht, vooral voor dieren met complexe jaarcycli.
University of Southern Denmark Examining the heterogeneity and cost effectiveness of a complex intervention by segmentation of patients with chronic obstructive pulmonary disease

Objectives: To examine the heterogeneity in cost-effectiveness analyses of patient-tailored complex interventions. Methods: Latent class analysis (LCA) was performed on data from a randomized controlled trial evaluating a patient-tailored case management strategy for patients suffering from chronic obstructive pulmonary disease (COPD). LCA was conducted on detailed process variables representing service variation in the intervention group. Features of the identified latent classes were compared for consistency with baseline demographic, clinical, and economic characteristics for each class. Classes for the control group, corresponding to the identified latent classes for the intervention group, were identified using multinomial logistic regression. Cost-utility analyses were then conducted at the class level, and uncertainty surrounding the point estimates was assessed by probabilistic sensitivity analysis. Results: The LCA identified three distinct classes: the psychologically care class, the extensive COPD care class, and the limited COPD care class. Patient baseline characteristics were in line with the features identified in the LCA. Evaluation of cost-effectiveness revealed highly disparate results, and case ee front matter Copyright & 2018, International S r Inc. This is an open access article under the CC ons.org/licenses/by-nc-nd/4.0/). 1016/j.jval. 2017.08. 001 ondence to: Sabrina Storgaard Sørensen, Departm org University, Fibigerstræde 11, Aalborg 9220, D torgaardsoerensen@gmail.com. management for only the extensive COPD care class appeared costeffective with an incremental cost-effectiveness ratio of £26,986 per quality-adjusted life-year gained using the threshold value set by the National Institute of Health and Care Excellence. Conclusions: Findings indicate that researchers evaluating patient-tailored complex interventions need to address both supply-side variation and demand-side heterogeneity to link findings with outcome. The article specifically proposes the use of LCA because it is believed to have the potential to enable more appropriate targeting of complex care strategies.
ANALISIS DAN IMPLEMENTASI ALGORITMA AGGLOMERATIVE HIERARCHICAL CLUSTERING UNTUK DETEKSI KOMUNITAS PADA MEDIA

Community detection is the process of finding and identifying a community within a network, one of them on social networks. There are two characteristics of data in detecting the community that is the relationship between individuals and similarity between individuals. The community detection algorithm usually focuses on only one of its characteristics. In this research the author discusses the identify of the community using the algorithm Agglomerative Hierarchical Clustering (AHC) based on enhanced similarity on the Facebook data, which is an algorithm that sequentially modeling the grouping using the threshold value as a grouping tool, two nodes that have similarity value greater than threshold value then it will be made into a community by taking into account the relationship of the node. In the evaluation, the authors use modularity as a cluster quality measure, in which the quality of the cluster is said to be good if it has more solid relationship inside the community than the relationship outside the community. The results of Algortima AHC are able to show that AHC can detect community with cluster quality (modularity) reach 0.4453 in real network.
European Journal of Alternative Education Studies-ISSN 2501-5915

The study examines differences in students’ academic achievement in conventional and alternative schools (aka speed schools) in Tigrai, Ethiopia. Students in speed schools attended the three-year program of the conventional curriculum in ten months. A total of 372 students from conventional and speed schools were involved in the study. Ten speed school facilitators and eight conventional school teachers responded to questionnaires. Literacy and numeracy tests as well as teacher made tests were used to compare differences. Students in the speed school classes have statistically significantly higher scores on the outcome measures both in numeracy and literacy than those in conventional schools. The same students also scored higher in the teacher made tests. Furthermore, a similar comparison in grade four revealed that students from alternative schools performed relatively higher scores. Policy makers need to critically look into the experiences of speed schools and identify important lessons to apply to conventional schools.
Union Strategy and Optimal

Union Strategy and Optimal Income Taxation Restrictions on work hours are more important in countries with a large welfare state. We show that this empirical observation is consistent with the strategic effects of such restrictions in a welfare state in the context of optimal direct taxation in the tradition of Mirrlees (1971). Our results also apply to non-welfarist states which have income redistribution, but not in purely extortionary states. JEL Classification: H21, H23
What works in school-based alcohol education: A systematic review

Background: Considerable attention has been focused on the impact of young people’s alcohol use. To address this, schools often implement alcohol and drug education and there are many potential programmes to choose from. Objective: The aim of this study was to identify evidence-based alcohol education programmes for schools. Methods: A systematic review was undertaken of school-based programmes that targeted alcohol within a school setting and included at least one alcohol behaviour or knowledge change outcome. Six-hundred seventy-five abstracts were screened resulting in 454 studies assessed for eligibility, with 70 studies, evaluating 40 individual programmes, included in the final review. Results: Of the 40 programmes, 3 had good evidence of a positive effect. They included CLIMATE Schools (Australia), Project ALERT (USA) and All Stars (USA). Of the others, 4 showed some evidence of positive effect, 1 had no evidence of effect, 29 were inconclusive and 2 showed negative outcomes, such as increases in alcohol use. Although many programmes were evaluated, very few had sufficient evidence to be able to endorse their widespread implementation in schools. Conclusion: Three programmes included in the review had sufficient positive outcomes to be recommended for implementation, and four showed good outcomes in some areas. Schools should consider these results when deciding on introducing alcohol education. Overall, the evidence base is broad but relatively weak and further research is required, focusing on programmes identified as having good or potentially good outcomes.
INVERSE AND FORWARD HYDROGEOCHEMICAL MODELING OF ACID MINE DRAINAGE

In almost all environmental problems, there is a need for knowledge or predictions of the solute concentrations in space and time. Through the whole cycle of a mining project, from the exploration and feasibility studies, permitting, active mining, to remediation, reclamation and closure of a mining site, there is a wide spectrum of environmental issues in which geochemical modeling can play a significant role. For example accurate prediction of acidic drainage from proposed mines is recognized by both industry and government as a critical requirement of mine permitting and long term operation. This paper demonstrates the practical application of geochemical speciationsolubility, inverse mass balance and reaction path models to describe water chemistry in abandoned Ala ehir (Manisa-Turkey) Hg mine.
Phonological and perceptual factor symbiosis in loanword adaptation

This paper examines the two-way interaction of perceptual and production factors in the light of resolving French and English loan structures in Kirundi. The investigation is framed within the view that loanword adaptation results from attempts to match the non-native perception of the L2 input within the confines of the L1 grammar. Neither a purely perceptual nor a purely grammatical account can explain the facts. Based on a collection of 239 French loans and 44 English corpora of loans, this study examines loanword adaptation at both the phonemic and the phonotactic levels. We prove how the constraint-ranking Optimality Theory (OT) can account for the phonological adaptations of loans, but with limitations. The adaptation cannot be fully understood unless perceptual similarity and auditory factors are integrated in the grammar. This study enriches our understanding of the role of perceptual similarity and perceptual salience in phonology and their relationship to constraint ranking.