Miracle-dz/UniFAR-FTUs huggingface dataset:
Language Education for Sustainable Development: Mother Tongue and Foreign Language in Croatian Primary Education

Education for sustainable development (ESD) is defined as education that changes skills, knowledge, values and attitudes to build more sustainable and just societies for all (UN 2015; UNESCO, 2017). Its importance is recognized and implemented into Croatian educational system at the policy level (National Implementation Report, 2014). However, there is still little research on specific aspects of ESD in Croatia. ESD envisions education that is set on three pillars: economic, environmental and socio-cultural, the latter given the least attention (Gregers Eriksen, 2013; Zygmunt 2016). Being holistic and transformational in its nature (Engdahl, 2015; OMEP, 2017; UNICEF, 2019), ESD concerns learning content, outcomes, pedagogy and learning environment, therefore it should be the main aim of education in general, including language education. Zygmunt (2016) argues that language as a medium of obtaining and transmitting knowledge has immense importance for sustainable development. Bahtic and Visnjic Jevtic (2020) proved that even children at age 3 to 7 understand the concept of diversity, especially linguistic diversity, and its positive value. Also, Otieno (2008) emphasizes that culture underlines the EDS, because culture influences our behavior, communication and learning. Therefore, language education should be one of the main areas to implement EDS (Zygmunt, 2016). This paper deals with Croatian mother tongue (L1) and English foreign language (FL) learning within the scope of ESD. More precisely, it investigates whether the curricula for learning Croatian as L1 and English as FL in primary education (grades 1-4) support education for sustainable development. For the purpose of this paper two curricula will be analyzed: Curriculum for subject Croatian language in the primary and secondary school (MZO, 2019a) and Curriculum for subject English language in the primary and secondary school (MZO, 2019b). Based on the qualitative analysis of the curricula for primary level (grades 1 to 4), it will be discussed how language learning outcomes specified by the two curricula are related and might contribute to the development of ESD key competencies: system thinking competency, anticipatory competency, normative competency, strategic competency, collaborative competency, critical thinking competency, self-awareness competency and integrated problem solving competency. The study has shown that both L1 and FL curricula support the development of ESD key competencies. The most supported competency by both curricula is system thinking competency, followed by self-awareness and collaboration competency. However, in both curricula there is a relatively large number of outcomes that can not be directly related to ESD key competencies. Still, they could be also used to foster the competencies providing ESD pedagogical approaches and methods are applied.
Design, Control, and Analysis of a Novel Grid-Interfaced Switched-Boost Dual T-Type Five-Level Inverter With Common-Ground Concept

Multilevel inverters with a common-ground structure and voltage step-up feature are beneficial for transformerless grid-connected photovoltaic applications. In this article, a novel topology of such converters with a five-level output voltage generation is presented. The proposed topology comprises of an integrated switched-boost (SB) module and a dual T-type (D2T) cell constructed with 10 power switches (six unidirectional and two bidirectional). An inductor in the integrated SB module is used to boost the voltage across two involved capacitors of the D2T cell. Therefore, a desirable ac voltage magnitude for the grid-connected application can be achieved over a wide range of input voltage changes. Current stress is also kept within a permissible input current range by the soft-charging operation of the involved capacitors through the inductor. A corresponding dead-beat continuous-current-control-set controller with a sinusoidal PWM modulator is implemented for controlling the real and reactive powers. The controller has an added benefit of achieving constant switching frequency for power switches. Circuit description, theoretical analyses, and comparative study are discussed. Simulation and experimental results are also presented to confirm the feasibility and correctness of the proposed topology.
Detection of Avian Bornavirus in Wild and Captive Passeriformes in Brazil

SUMMARY. Avian bornaviruses (ABVs) are the causative agents of proventricular dilatation disease (PDD), a fatal neurologic disease considered to be a major threat to psittacine bird populations. We performed a reverse transcription PCR survey to detect the presence of canary avian bornavirus (CnBV) in birds of order Passeriformes related to different clinical manifestations, such as sudden death, neurologic signs, apathy, anorexia, excessive beak growth, and PDD. A total of 227 samples from captive and wild canaries were included, of which 80 samples were captive birds, comprising saffron finches (n = 71) and common canary (n = 9), and 147 samples were wild birds distributed among a variety of several species. Two samples from captive birds (2/80) were positive for ABV, and in wild birds, only one sample was positive for ABV. The positive samples were subjected to DNA sequencing, and only the CnBV-1 serotype was found, which was the first time it was detected outside of Germany (Austria/Hungary), where it was first detected in 2009. Phylogenetic analysis confirmed that avian bornavirus serotype CnBV-1 is present in order Passeriformes in Brazil.
Compilation-assisted performance acceleration for data analytics

Fundamental data analytics tasks are often simple – many useful and actionable insights can be garnered by simply filtering, grouping, and summarizing data. However the sheer volume of data to be analyzed, demands of a multi-user operating environment, and limitations of general purpose processors make it challenging to perform these operations efficiently at scale. This thesis presents two techniques that address these challenges to improve the response time of data analytics tasks: (1) Newly emerging programmable network processors can perform data analytics tasks at terabits per second. However, existing data analytics systems, like Apache Spark, cannot readily use network processors because network processors are very limited and cannot execute the tasks generated by existing analytics systems. Using network processors for analytics requires re-designing how existing systems compile and execute data processing tasks. This thesis introduces Jumpgate, a system that enables existing data processing systems to execute relational queries using network processors. Jumpgate compiles client requests to a novel execution model that coordinates execution on heterogeneous network processors. Jumpgate can already improve performance by 1.12-3× on industry standard benchmarks, and paves the way for adopting network processors for data analytics tasks. (2) Analytics systems often process similar queries, either submitted by the same or different users. Cross program memoization (CPM) is a technique to re-use results of prior computations across programs and users. However, CPM is often not enabled because prior implementations have high overhead and are unable to reuse the output of user-defined functions (UDFs). This thesis presents KeyChain, a CPM implementation that identifies equivalent UDFs and has low overhead so CPM can be always be enabled.
Managing Organizational Explosions During Digital Business Transformations

The digital transformation imperative is real. Yet while digital transformation is now a top management priority at most companies, the vast majority of executives consider their company’s digital maturity as early stage.3 Particularly challenging is that this transformation is not primarily about technology; it requires a business transformation that leverages digital capabilities to implement a step-change in delighting customers (i.e., improving the customer experience), while simultaneously reducing costs (i.e., improving operational efficiency). Companies that successfully transform both dimensions are able to outperform their peers by an average of 16 percentage points above industry-adjusted net margins.4 Digital business transformation is hard work: large companies have typically developed a wide range of products and services over many years, supported by an ingrained and nondigital culture. These products and services are often organized in silos that are interconnected by a complex web of processes, practices, systems and data. This complexity (often described as “spaghetti”) makes it hard for employees to deliver value, resulting in a fragmented and frustrating experience for customers.
Semantic Probing: Feasibility of using sequential probes to decode what is on a user’s mind

In this paper, we investigate the feasibility of using multiple sequential probe words to decode their relatedness to an active semantic concept on a user’s mind from the respective electrophysiological brain responses. If feasible, this relatedness information could be used by a Brain Computer Interface to infer that semantic concept, by integrating the knowledge of the relationship between the multiple probe words and the ‘unknown’ target. Such a BCI can take advantage of the N400: an event related potential that is sensitive to semantic content of a stimulus in relation to an established semantic context. However, it is unknown whether the N400 is suited for the multiple probing paradigm we propose, as other intervening words might distract from the established context (i.e., the target word). We perform an experiment in which we present up to ten words after an initial target word, and find no attenuation of the strength of the N400 in grand average ERPs and no decrease in classification accuracy for probes occurring later in the sequences. These results lay the groundwork for the development of a BCI that infers the concept on a user’s mind through repeated probing.
Aspergillus oryzae reduces IgE binding ability of allergenic egg white proteins

Egg white proteins are one of the major allergens. The objective of this study was to investigate the effect of Aspergillus oryzae cultivation on IgE binding ability of egg white proteins. Effect of A. oryzae on egg white proteins was determined using ninhydrin method, SDS-PAGE, ELISA, fluorescence FITC labeling, MALDITOF-MS and LC-MS/MS analysis. Adding mycelium of A. oryzae ATCC 1011 and 16868 substantially reduced the IgE binding ability of acidified egg white after 24 h incubation. The binding capacity of egg white proteins to IgE in plasma from four egg allergy patients was almost completely lost after incubation with mycelium of ATCC 16868. Results from SDS-PAGE, free amino acid analysis, MALDI-TOF-MS and LC-MS/MS indicated that there was no substantial protein degradation during incubation. Therefore, the reduction of IgE binding ability of egg white proteins during A. oryzae treatment was probably due to a loss of ~1700 Da mass including a fragment of the ovomucoid N terminus.
Smoke compounds aggravate stress inflicted on Brassica seedlings by unfavourable soil conditions

The aim of the study was to assess the physiological status of Brassica seedlings grown in two types of soils following a single application of smoke water (SW). One soil was contaminated with heavy metals from a local smelter, and another was sandy and poor in nutrients. Three-week monitoring indicated that soil composition was the primary factor affecting chlorophyll fluorescence (CF) parameters, growth, and development of seedlings, and the contaminants affected the plants more than the lack of nutrients. SW aggravated the negative impact of heavy metals, which became visible when the plants transiently suffered from the heavy metal exposure. Most of CF parameters changed suddenly but then the trend reversed indicating that plants gradually adapted to the specific conditions. However, this was not reflected in the final biomass of the seedlings. This might be due to redirection of photosynthates towards protective mechanisms against toxic effects of metals.
Response of Riparian Vegetation, Instream Habitat, and Aquatic Biota to Riparian Grazing Exclosures

Improper riparian grazing can alter riparian vegetation and reduce streambank stability, negatively impacting aquatic habitat and biota. We evaluated differences in riparian and instream habitat, benthic macroinvertebrates, and fish inside versus outside seven riparian exclosures constructed from 1982 to 2005 in Idaho. The normalized difference vegetation index from Landsat imagery (1985 to 2015) showed significant increases in riparian vegetation productivity after some but not all exclosures were constructed. Field data collected in 2015 showed woody riparian vegetation to be more abundant, streambanks less altered, and stream channels narrower inside versus outside exclosures, as we expected. However, instream habitat, a benthic macroinvertebrate index, fish species richness, and adult salmonid density showed no response. Higher age-0 salmonid densities were the only aquatic organism response observed. Broader watershed-scale factors likely limited strong and consistent responses by aquatic biota to exclosures. We conclude that riparian exclosures have localized effects on stream systems, such as increased riparian vegetation, reduced streambank alteration, and improved channel stability, but may not always influence aquatic biota that commonly reflect larger watershed-scale processes and conditions. Therefore, well-maintained riparian exclosures should be used to eliminate livestock use in localized areas of stream corridors that are sensitive to disturbance. To improve stream health at the larger watershed scale that is relevant to most aquatic biota, exclosures should only be one of several grazing management tools implemented simultaneously to reduce the impacts of improper livestock grazing. Livestock grazing is a predominant land use in North America, and increasing demand for livestock products associated with human population growth will increase grazing needs and competition for natural resources in the future (Thornton 2010). This is especially true in the western United States, where grazing is widespread, and when done improperly can impact biodiversity and ecosystem function (Fleischner 1994). Livestock often concentrate in riparian areas due to water and forage availability, and this concentration can impact aquatic ecosystems (Kauffman and Krueger 1984). Improper riparian grazing has been shown to reduce riparian vegetation and destabilize streambanks, leading to wide, shallow, and incised stream channels with low physical habitat complexity and *Corresponding author: ddauwalter@tu.org. Received June 13, 2018; accepted August 23, 2018 North American Journal of Fisheries Management 38:1187–1200, 2018 © 2018 American Fisheries Society ISSN: 0275-5947 print / 1548-8675 online DOI: 10.1002/nafm.10224
SDAC: A Slow-Aging Solution for Android Malware Detection Using Semantic Distance Based API Clustering

A novel slow-aging solution named SDAC is proposed to address the model aging problem in Android malware detection, which is due to the lack of adapting to the changes in Android specifications during malware detection. Different from periodic retraining of detection models in existing solutions, SDAC evolves effectively by evaluating new APIs’ contributions to malware detection according to existing API’s contributions. In SDAC, the contributions of APIs are evaluated by their contexts in the API call sequences extracted from Android apps. A neural network is applied on the sequences to assign APIs to vectors, among which the differences of API vectors are regarded as the semantic distances. SDAC then clusters all APIs based on their semantic distances to create a feature set in the training phase, and extends the feature set to include all new APIs in the detecting phase. Without being trained by any new set of real-labelled apps, SDAC can adapt to the changes in Android specifications by simply identifying new APIs appearing in the detection phase. In extensive experiments with datasets dated from 2011 to 2016, SDAC achieves a significantly higher accuracy and a significantly slower aging speed compared with MaMaDroid, a state-of-the-art Android malware detection solution which maintains resilience to API changes.
Evolution of Rifampin Resistance in Escherichia coli and Mycobacterium smegmatis Due to Substandard Drugs

Poor-quality medicines undermine the treatment of infectious diseases, such as tuberculosis, which require months of treatment with rifampin and other drugs. Rifampin resistance is a critical concern for tuberculosis treatment. ABSTRACT Poor-quality medicines undermine the treatment of infectious diseases, such as tuberculosis, which require months of treatment with rifampin and other drugs. Rifampin resistance is a critical concern for tuberculosis treatment. While subtherapeutic doses of medicine are known to select for antibiotic resistance, the effect of drug degradation products on the evolution of resistance is unknown. Here, we demonstrate that substandard drugs that contain degraded active pharmaceutical ingredients select for gene alterations that confer resistance to standard drugs. We generated drug-resistant Escherichia coli and Mycobacterium smegmatis strains by serially culturing bacteria in the presence of the rifampin degradation product rifampin quinone. We conducted Sanger sequencing to identify mutations in rifampin-resistant populations. Strains resistant to rifampin quinone developed cross-resistance to the standard drug rifampin, with some populations showing no growth inhibition at maximum concentrations of rifampin. Sequencing of the rifampin quinone-treated strains indicated that they acquired mutations in the DNA-dependent RNA polymerase B subunit. These mutations were localized in the rifampin resistance-determining region (RRDR), consistent with other reports of rifampin-resistant E. coli and mycobacteria. Rifampin quinone-treated mycobacteria also had cross-resistance to other rifamycin class drugs, including rifabutin and rifapentine. Our results strongly suggest that substandard drugs not only hinder individual patient outcomes but also restrict future treatment options by actively contributing to the development of resistance to standard medicines.
The role of African buffalo in the epidemiology of foot-and-mouth disease in sympatric cattle and buffalo populations in Kenya

Transmission of pathogens at wildlife-livestock interfaces poses a substantial challenge to the control of infectious diseases, including for foot-and-mouth disease virus (FMDV) in African buffalo and cattle. The extent to which buffalo play a role in the epidemiology of this virus in livestock populations remains unresolved in East Africa. Here, we show that FMDV occurs at high seroprevalence (~77%) in Kenyan buffalo. In addition, we recovered 80 FMDV VP1 sequences from buffalo, all of which were serotype SAT1 and SAT2, and seventeen FMDV VP1 sequences from cattle, which included serotypes A, O, SAT1 and SAT2. Notably, six individual buffalo were co-infected with both SAT1 and SAT2 serotypes. Our results suggest that transmission of FMDV between sympatric cattle and buffalo is rare. However, viruses from FMDV outbreaks in cattle elsewhere in Kenya were caused by viruses closely related to SAT1 and SAT2 viruses found in buffalo. We also show that the circulation of FMDV in buffalo is influenced by fine-scale geographic features, such as rivers, and that social segregation amongst sympatric herds may limit between-herd transmission. Our results significantly advance knowledge of the ecology and molecular epidemiology of FMDV at wildlife-livestock interfaces in Eastern Africa, and will help to inform the design of control and surveillance strategies for this disease in the region.
The Role of Fatty Acid Signaling in Islet Beta-Cell Adaptation to Normal Pregnancy

Background Maintenance of a normal fetal nutrient supply requires major adaptations in maternal metabolic physiology, including of the islet beta-cell. The role of lipid signaling processes in the mechanisms of islet beta-cell adaptation to pregnancy has been minimally investigated. Objective To determine the effects of pregnancy on islet fatty acid (FA) metabolic partitioning and FA augmentation of glucose-stimulated insulin secretion (GSIS). Methods Age matched virgin, early pregnant (gestational day-11, G11) and late pregnant (G19) Sprague-Dawley rats were studied. Fasted and fed state biochemistry, oral glucose tolerance tests (OGTT), and fasted and post-OGTT liver glycogen, were determined to assess in vivo metabolic characteristics. In isolated islets, FA (BSA-bound palmitate 0.25 mmol/l) augmentation of GSIS, FA partitioning into esterification and oxidation processes using metabolic tracer techniques, lipolysis by glycerol release, triacylglycerols (TG) content, and the expression of key beta-cell genes were determined. Results Plasma glucose in pregnancy was lower, including during the OGTT (glucose area under the curve 0-120 min (AUC0-120); 655±24 versus 849±13 mmol.l-1.min; G19 vs virgin; P<0.0001), with plasma insulin concentrations equivalent to those of virgin rats (insulin AUC0-120; 97±7 versus 83±7 ng.ml-1.min; G19 vs virgin; not significant). Liver glycogen was depleted in fasted G19 rats with full recovery after oral glucose. Serum TG increased during pregnancy (4.4±0.4, 6.7±0.5; 17.1±1.5 mmol/l; virgin, G11, G19, P<0.0001), and islet TG content decreased (147±42, 172±27, 73±13 ng/µg protein; virgin, G11, G19; P<0.01). GSIS in isolated islets was increased in G19 compared to virgin rats, and this effect was augmented in the presence of FA. FA esterification into phospholipids, monoacylglycerols and TG were increased, whereas FA oxidation was reduced, in islets of pregnant compared to virgin rats, with variable effects on lipolysis dependent on gestational age. Expression of Ppargc1a, a key regulator of mitochondrial metabolism, was reduced by 51% in G11 and 64% in G19 pregnant rat islets compared to virgin rat islets (P<0.001). Conclusion A lowered set-point for islet and hepatic glucose homeostasis in the pregnant rat has been confirmed. Islet adaptation to pregnancy includes increased FA esterification, reduced FA oxidation, and enhanced FA augmentation of glucose-stimulated insulin secretion.
Waterlogging effects upon the phenological phases of common bean cultivar BRSMG-Uai

Common bean (Phaseolus vulgaris L.) is an important source of protein and carbohydrates, besides being rich in several mineral nutrients. In a flooding situation, the low availability of oxygen may result in hypoxia or anoxia condition. Therefore, this study aimed to evaluate the responses of the common bean cultivar BRSMG-Uai subjected to hypoxia in different phenological phases, analyzing its responses in terms of growth, productivity, carbon and nitrogen metabolism. Thus, seeds of common beans were germinated and when the seedling reached growth stage V1, they were transferred to plastic boxes containing 40L of nutritive solution with steady aeration. Distinct series of plants were exposed to air-restriction on their roots for nine days, in three different phenological phases V3/V4, R6 and R7. Samples were collected for biochemical and growth analyses in a completely random design (n=6). The plants subjected to low availability of oxygen presented a reduction in bean number, displaying the greatest loss in productivity in V3/V4, conferring the highest sensitivity to hypoxia in this phase. On the other hand, there was an increase in sugar concentration in leaves, and it was also possible to observe an increase in hydrogen peroxide in leaves and roots, concomitant with a decrease in superoxide dismutase activity in all phenological phases. There was also an increase in ascorbate peroxidase activity in roots in R6, as well as in nitrate reductase activity. We conclude that the cultivar BRSMG-Uai presents sensitivity to low oxygen availability, and the phenological phaseV3/V4 is the most critical for it.