Miracle-dz/UniFAR-FTUs huggingface dataset:
App development in an urban after-school computing programme: a case study with design implications

ABSTRACT This mixed methods case study presents the experience of a group of middle school students in a year-long, after-school computing programme in a large, inner-city school district in the southeastern United States. The purpose of this research is to explore informal educational strategies that are conducive at giving underrepresented minority youth access to information and communication technology tools and content. Results indicate that hands-on support from mentors, peer collaboration, and options for customising work and creating unique projects contributed positively to the student experience in the programme. This study suggests giving students more creative freedom, adequate scaffolding and the option for peer collaboration when working in informal learning environments. Results are specific to the context of the one school in which this pilot study was conducted, though the findings confirm the research of others in this area. Data sources included a perceptions survey, participant interviews and researcher observations.
What drives firms to invest in training and developing employees? Time-dependent effects of firm internal and external contingencies

Abstract Drawing on the cost–value framework, the present study identifies internal and external firm-specific factors as predictors and firm performance as a contingency to explain the level and temporal growth of firm investment in training and development (T&D) over time. The theoretical propositions are empirically validated by analyzing multisource longitudinal data from 172 firms over a period of three years. The analysis shows that human capital quality and technology change are positive predictors of the level of T&D investment. The growth curve analysis demonstrates that high-performing firms increase T&D investment when they are managed by professional managers and possess high-quality human capital. By contrast, low-performing firms decrease T&D investment when they are controlled by owners, possess low-quality human capital, and operate under low technology change. The current analysis offers intriguing insights into how firms with differing internal and external situations allocate resources to T&D and increase or decrease their T&D investment over time depending on their performance and resulting financial slack. The current investigation on the temporal trajectories of T&D investment under distinct firm-specific situations and contingencies considerably expands the existing literature based on cross-sectional static perspectives.
Ground tire rubber/polyamide 6 thermoplastic elastomers produced by dry blending and compression molding

This study investigates the addition of ground tire rubber (GTR) into virgin polyamide 6 (PA6) to produce thermoplastic elastomer (TPE) blends. In particular, a wide range of GTR concentration (0–100% wt.) was possible by using a simple dry blending technique of the materials in a powder form followed by compression molding. The molded samples were characterized in terms of morphological (scanning electron microscopy), physical (density and hardness) and mechanical (tension, flexion and impact) properties. The results showed a decrease in tensile and flexural moduli and strengths with GTR due to its elastomeric nature. However, significant increases were observed on the tensile elongation at break (up to 167%) and impact strength (up to 131%) compared to the neat PA6 matrix. Based on the results obtained, an optimum GTR content around 75% wt. was observed which represents a balance between high recycled rubber content and a sufficient amount of matrix to recover all the particles. These results represent a first step showing that a simple processing method can be used to produce low cost PA6/GTR compounds with a wide range of physical and mechanical properties.
Quantitative Study on Empirical Strength Parameters of Extremely Fractured Phyllite Based on Fractal Theory

Extremely broken phyllite is widely distributed and is easily seen in engineering construction. Aiming at the problem that the empirical strength parameters of extremely broken surrounding rock have intense subjectivity and significant difference, based on the characteristics of the existence of particle group state in the highly broken surrounding rock, the fractal theory and large-scale direct shear test are used, the fractal description of polar broken phyllite samples with different pile numbers in fault fracture zone of Qinyu Tunnel is carried out, and the fractal dimensions and empirical strength parameters of each sample are determined. Based on a fractal description and large shear test, the functional relationship between fractal dimension and empirical strength parameter of extremely broken phyllite in fault fracture zone is established, and the quantitative value method of empirical strength parameter determined by fractal dimension of extremely broken phyllite is given, which provides ideas for the quantitative value of empirical strength parameter of the similar extremely broken surrounding rock.
Triterpenoids from the Bark of Aglaia glabrata and their In vitro Effects on P-388 Murine Leukemia Cells

Four dammarane-type triterpenoids, dammardienon (1), aglaiabbreviatin E (2), dammar-20,25-dien-3b,24-diol (3) and dammar-24-en-3b,20-diol (4) were isolated from methanolic extract of the bark of Aglaia glabrata. The structures of all triterpenoids were elucidated by 1D-, 2D-NMR, and comparison with previously reported data. All triterpenoids were applied into in vitro bioassay against P-388 murine leukemia cell. Dammar-24-en-3b,20-diol (4) has cytotoxic activity with IC50 value of 9.45 mM towards P-388 murine leukemia cell lines.
Recent advances in black phosphorus-based optical sensors

Abstract Black phosphorus (BP), one of new ultrathin two-dimensional (2D) materials, has drawn considerable attention in various applications such as in gas sensing, photoelectric devices, cancer therapy, drug deliver and so on. Owing to its unique structure, excellent optical and electronic properties and good biocompatibility, BP in the field of optical sensors is a rising star and has been intensively investigated in the recent years. In this mini-review, we aim to describe recent development of BP-based optical sensors including colorimetric, fluorescent, electrogenerated chemiluminescent and chemiluminescent sensors.
Urban transport and wellbeing: a critical analysis

The creation of sustainable and human-scale cities for all will be easier if researchers, planners and other stakeholders make room for multiple imaginings of what wellbeing is, how it can be achieved, and what role transport plays in this. Hedonic and eudaimonic conceptions of subjectively experienced wellbeing cannot be taken as universally applicable or always the best ways to think about wellbeing in connection with transport and travel behaviour. Those conceptions have a role to play in research and policy, but the effects generated by the pursuit of those versions of wellbeing should be critically considered. This is particularly important when that pursuit encourages selfish behaviour or research considers people and communities whose beliefs and worldviews are incommensurate with the assumptions of universal emotions, a priori and innate needs, or the individual as fully detached from their social and cultural context. Transport research and planning can benefit significantly from greater engagement with relational and process-oriented understandings of wellbeing and its association with human actions, including different ways of moving around the city. The contours of one such approach, which revolves around a reworked notion of capabilities, are sketched, but experimentation with alternatives is much desired.
Assessment of Meat Quality and Shelf Life from Broilers Fed with Different Sources and Concentrations of Methionine

A trial with different concentrations of DL-methionine (DLM) and DL-2-hydroxy-4-methylthiobutanoic acid (DL-HMTBA) in broiler feed was performed to investigate their effect on the meat quality parameters and the shelf life of breast fillet. In total, fillets from 210 male broiler chickens (Ross 308) were tested in seven groups with 30 animals each. Three different concentrations (0.04, 0.12, and 0.32%; on an equimolar basis) of either DLM or DL-HMTBA were added to a basal diet, summing up to seven treatment groups. After slaughter, fillets were packed aerobically and stored at 4°C. The investigated parameters comprised measurements of microbial as well as physicochemical parameters, such as pH, drip loss, cooking loss, and color measurements. Additionally, sensory investigations were conducted and shelf life was calculated. Mean pH values were between 6.1 and 6.4. Drip loss values were low, with mean values below 0.4%. The cooking loss ranged between 22% and 28% on average. The fillets showed a normal initial microbial quality (2.5 log10 cfu/g) and spoilage process with microbial counts of 8.5 log10 cfu/g at the end of storage. The study revealed a significant influence of methionine supplementation on the quality of broiler breast meat in comparison with the basal group. Methionine supplementation led to higher pH values and a higher water binding. Higher concentrations of methionine had a positive influence on the water-holding capacity by lowering the cooking loss. The L∗ value showed a significant negative correlation to the methionine concentration supplemented. No differences in physicochemical as well as sensory parameters could be detected between both methionine sources. The fillets showed a normal sensory spoilage process and a shelf life of 6 d. White striping was positively correlated to fillet weight as well as color values and significantly affected the Purchase Decision, the sensory investigation, and thus the shelf life of the samples.
Python‐based scikit‐learn machine learning models for thermal and electrical performance prediction of high‐capacity lithium‐ion battery

With the increasing popularity of electric vehicles (EVs), the demands for rechargeable and high‐performance batteries like lithium‐ion (Li‐ion) batteries have soared. Li‐ion battery systems require the use of a battery management system (BMS) to perform safely and efficiently. Accurate and reliable battery modeling is important for the BMS to function properly. Currently, many BMS applications use the equivalent circuit model due to its simplicity. However, with the development of a cloud BMS, machine learning battery models can be utilized, which can potentially improve the accuracy and reliability of the BMS. This work investigates the performance of four different machine learning models used to predict the thermal (temperature) and electrical (voltage) behaviors of Li‐ion battery cells. A prismatic Li‐ion battery cell with a capacity of 25 Ah was cycled under a constant current profile at three different ambient temperatures, and the surface temperature and voltage of the battery were measured. The four machine learning regression models—linear regression, k‐nearest neighbors, random forest, and decision tree—were developed using the scikit‐learn library in Python and validated with experimental data. The results of their performance were reported and compared using the R2 metric. The decision tree‐based model, with an R2 score of 0.99, was determined to be the best model in this case study.
Synchronizability analysis of three kinds of dynamical weighted fractal networks

In this paper, we study the synchronizability of three kinds of dynamical weighted fractal networks (WFNs). These WFNs are weighted Cantor-dust networks, weighted Sierpinski networks and weighted Koch networks. We calculated some features of these WFNs, including average distance ([Formula: see text]), fractal dimension ([Formula: see text]), information dimension ([Formula: see text]), correlation dimension ([Formula: see text]). We analyze two representative types of synchronizable dynamical networks (the type-I and the type-II). There are two indexes ([Formula: see text] and [Formula: see text]) that can be used to characterize the synchronizability of the two types of dynamical network. Here, [Formula: see text] and [Formula: see text] are the minimum nonzero eigenvalue and the maximum eigenvalue of the Laplacian matrix of the network, respectively. We find that the larger scaling factor [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text] or [Formula: see text] implies stronger synchronizability for the type-I dynamical WFNs.
Biosurfactant Production by a Newly Isolated
Enterobacter cloacae B14 Capable of Utilizing
Spent Engine Oil

This work aims to investigate biosurfactant production by a bacterium capable of utilizing spent engine oil. The effects of pH and temperature on the growth of this bacterium on spent engine oil were determined. The bacterium was isolated from petroleum-contaminated soil. Based on 16S rRNA gene sequence, it was identified as Enterobacter cloacae with 99% identity. Growth of Enterobacter cloacae B14 on mineral medium containing 1% (v/v) spent engine oil was optimum when incubated at 30oC. The bacterium showed the ability to grow under a wide range of pH medium, whereas the highest specific growth rate (0.29 hr-1) was obtained when grown under pH 7. Biosurfactant production by E. cloacae B14 was observed when grown in mineral medium containing 1% (w/v) glucose. Cell-free supernatant showed 42.2% emulsification activity (E24) against spent engine oil. Such activity was higher than some previous works and was obtained from a lower amount of biomass. Positive results from oil displacement, drop collapse and CTAB-methylene blue agar tests strongly indicated that strain B14 is an effective biosurfactant producer. Therefore, Enterobacter cloacae B14 has the potential for applications in bioremediation of oil-contaminated sites due to its biosurfactant production and growth on spent engine oil.
Quantized precoding and companding schemes for PAPR reduction in UFMC‐based massive MIMO downlink systems

Universal‐filtered multi‐carrier (UFMC) is a promising waveform technology, which inherits the robustness of FBMC and simplicity of OFDM. In this article, the UFMC waveform is combined with the massive multi‐user multiple‐input and multiple‐output (MU‐MIMO) technology to meet the desired needs of future wireless networks. In order to eliminate MU interference (MUI), the precoding is essential in massive MU‐MIMO downlink. However, the transmitted signals produced by the precoders have high peak‐to‐average power ratio (PAPR), thus resulting in reduction of power efficiency of the system. Hence, this article proposes the quantized MU precoding and companding schemes to increase the power efficiency of UFMC‐based massive MU‐MIMO downlink systems. A nonlinear quantized precoder called squared‐infinity norm Douglas‐Rachford splitting (SQUID), which generates signals with constant envelope, is proposed. The proposed SQUID precoder reduces the power consumption and MUI of UFMC‐based massive MU‐MIMO systems. Moreover, a piecewise linear companding (PLC) scheme, which further reduces the PAPR by employing two threshold values and one companding parameter, is also proposed. The simulation results confirm that the proposed UFMC‐based massive MU‐MIMO with quantized nonlinear SQUID precoding provides better performance than quantized linear precoders. Besides, the proposed system with the PLC scheme offers better PAPR reduction of 4.5 dB when compared with linear nonsymmetrical transform and μ ‐law schemes.
Mimicking skyglow at ecosystem level in a large-scale lake enclosure facility

Light pollution is an environmental stressor of global extent that is growing exponentially in area and intensity. Artificial skyglow, a form of light pollution with large range, is hypothesized to have environmental impact at ecosystem level. However, testing the impact of skyglow at large scales and in a controlled fashion under in situ conditions has remained elusive so far. Here we present the first experimental setup to mimic skyglow at ecosystem level outdoors in an aquatic environment. Spatially diffuse and homogeneous surface illumination that is adjustable between 10 mlx and 10 lx, resembling rural to urban skyglow levels, was achieved with white light-emitting diodes at a large-scale lake enclosure facility. The illumination system was enabled by optical modeling with Monte-Carlo raytracing and validated by measurements. Our method can be adapted to other outdoor and indoor skyglow experiments, urgently needed to understand the impact of skyglow on ecosystems.
Kaingang indigenous, family farmers and soy in southern Brazil: new old conflicts over land

ABSTRACT Over the past two decades, the expansion of agriculture in Brazil, along with indigenous peoples’ growing claims for land, has increased the tension between indigenous groups and farmers. This paper addresses the dispute for land between Kaingangs and family farmers in southern Brazil, aiming to reveal tensions, disagreements and coalitions – that is, the frictions – demonstrated by these subjects when they narrate their current experiences and practices. Our proposal is to look at these conflicts from a cosmopolitical perspective. The research is inspired by multilocal ethnographies, using open interviews with Kaingangs, farmers and local authorities as its main methodological procedure. We also discuss the main historical-political characteristics of recent decades, situating the action of the State regarding conflicts involving indigenous peoples, as well as how this situation may develop in the current context.
Climate Change Acts in Scotland, Austria, Denmark and Sweden: the role of discourse and deliberation

ABSTRACT Climate Change Acts (CCAs) have become a key legislative tool to mitigate climate change. While various case studies have shown that ambition varies greatly, little is known about why this is the case. This comparative study aims to fill this gap by examining the emergence of six CCAs across four legislatures: Scotland (2009 and 2019), Austria (2011), Denmark (2014 and 2020) and Sweden (2017). We focus on climate change discourse broadly and processes of deliberation within legislatures specifically, to explore how they influenced the ambition of the six CCAs from our analysis. We combine extensive document analysis with 43 semi-structured interviews conducted between June 2018 and May 2019. We show that heightened attention at the discursive level combined with a strong deliberative process within legislatures to underpin all of the more ambitious CCAs. Overall, governments are more likely to adopt strong CCAs when prominent discursive junctures politicize climate policy and when parliamentary deliberation is strong. The overarching climate discourse and parliamentary deliberation had an even greater influence in our case studies than the political orientation of governments. Centre-left governments adopted weak GHG emission reduction targets at times of low political salience for climate but were more ambitious when supportive politicization of climate was present. Key policy insights CCAs have very different levels of ambition. While some are merely symbolic, others set out ambitious climate policy frameworks. Climate policy discourse, in a broad sense, shapes the content of CCAs. Prominent discursive junctures can support ambitious legislation. The level of deliberation in parliaments is another factor that shapes CCAs. More deliberation often helps to raise ambitions, in particular when broader discursive conditions are in favour of climate issues. Supportive climate discourse and opportunities for deliberation had more influence on the ambition of CCAs (in particular on GHG emission reduction targets) than the political orientation of governments.
Effects of Training on Side-Scan Sonar Use as a Fish Survey Tool: a Case Study in Alligator Gar

Consumer-grade side-scan sonar has become a versatile fisheries management tool. First applied to assess habitat, its use has expanded to surveying fishes in recent years. However, an important consideration is the skill and experience of users, which can impact both the accuracy and comparability of surveys. To this end, we characterized the ability of a small sample of novice users (N = 8) to identify alligator gar Atractosteus spatula in imagery, as well as the effect of a two-hour training exercise on user performance. Prior to training, mean accuracy (expressed as the difference between observed and expected counts) among participants ranged from -2.6 to 1.3 fish and precision ranged from ± 1.2 to 2.4 fish, with the majority of participants underestimating the number of alligator gar present in the imagery. False positives (i.e., identifying alligator gar in imagery when none were present) were common among participants. Post-training mean accuracy ranged from -3.1 to 0 among participants and precision ranged from ± 1.6 to 3.2 fish. The frequency of false positives was significantly reduced following training, and participants reported significant increases in confidence associated with image interpretation. The relatively high accuracy and precision we observed prior to training indicated that side-scan sonar can be easily incorporated into large-scale fishery monitoring efforts for alligator gar. However, our results also suggested that a rather minimal investment in training can further improve consistency and reduce uncertainty among novice users.
Effectiveness of the Virtual Learning Environment (VLE) for online teaching, learning, and assessment: Perspectives of Academics and Students of the Royal University of Bhutan

— This study investigated the effectiveness of virtual learning environment features for online Teaching, Learning and Assessment in all colleges of the Royal University of Bhutan. A mixed methods, parallel convergent design was adopted for this study. A total of 155 academics and 650 students participated in online survey questionnaires and 22 academic and 43 students responded to the online semi-structured interview questions. The auto-generated reports of VLE usage of 93 modules across the colleges were analysed to validate the findings on the usage of VLE features by academics from qualitative and quantitative data. The results showed that the academics’ overall experience of using VLE for online teaching was positive whereas the majority of the students found it a challenging learning experience. While the academics were found to be competent in using only basic VLE features for online teaching, the students’ perceptions of their tutors’ competencies in online teaching were diverse ranging from very experienced to a beginner. Both the academics and students found learning through VLE not very effective as assessment and giving feedback online requires previous experience, sound IT knowledge and adequate resources. The results also showed that both academics and students were generally satisfied with the ICT facilities and resources in the colleges. However, students have experienced major constraints such as internet connectivity, financial support, IT facilities, power fluctuation and household chores while learning online from homes. Generally, they have found online learning through VLE as a new enriching opportunity to learn ICT tools, communication skills and social skills for collaborative online learning.