Miracle-dz/UniFAR-FTUs huggingface dataset:
Assignments as Influential Factor to Improve the Prediction of Student Performance in Online Courses

Studies on the prediction of student success in distance learning have explored mainly demographics factors and student interactions with the virtual learning environments. However, it is remarkable that a very limited number of studies use information about the assignments submitted by students as influential factor to predict their academic achievement. This paper aims to explore the real importance of assignment information for solving students’ performance prediction in distance learning and evaluate the beneficial effect of including this information. We investigate and compare this factor and its potential from two information representation approaches: the traditional representation based on single instances and a more flexible representation based on Multiple Instance Learning (MIL), focus on handle weakly labeled data. A comparative study is carried out using the Open University Learning Analytics dataset, one of the most important public datasets in education provided by one of the greatest online universities of United Kingdom. The study includes a wide set of different types of machine learning algorithms addressed from the two data representation commented, showing that algorithms using only information about assignments with a representation based on MIL can outperform more than 20% the accuracy with respect to a representation based on single instance learning. Thus, it is concluded that applying an appropriate representation that eliminates the sparseness of data allows to show the relevance of a factor, such as the assignments submitted, not widely used to date to predict students’ academic performance. Moreover, a comparison with previous works on the same dataset and problem shows that predictive models based on MIL using only assignments information obtain competitive results compared to previous studies that include other factors to predict students performance.
Effectively Managing Classroom: A Case Study of Four Novice Elementary Teachers in Private Schools

This study explored the lived experiences of novice elementary school teachers with respect to classroom management. This study used a phenomenological case study research design. Four novice elementary school teachers struggling with classroom management were selected from private elementary schools in Lahore. Semi-structured interviews were conducted to elicit the lived experiences of the participants. All interviews were audio-recorded and later transcribed for conducting a qualitative content analysis of the data. The analysis revealed that novice teachers faced various challenges in managing their class�and used multiple pedagogical techniques to handle day-to-day classroom issues. Usually, a new teacher is highly dependent on the support and help from the school management; irony, however, is that they seldom receive any. This study contributes to contextual knowledge related to the issues and needs of novice private elementary school teachers at the start of their careers.
Modelo estructural de las competencias de innovación en Latinoamérica. Evidencia en México, Colombia y Bolivia

El objetivo de la presente investigación es determinar cómo influyen las competencias de innovación individual e interpersonal sobre la creación de redes dentro del contexto latinoamericano. Se llevó a cabo una investigación cuantitativa y correlacional y, además, se elaboró un modelo estructural a través del programa SmartPLS. Aquí, mediante una muestra conformada por 153 participantes de México (n = 40), Bolivia (n = 85) y Colombia (n = 28), se encontró que sólo la competencia de innovación interpersonal tiene un impacto positivo y significativo sobre la creación de redes. En conclusión, la aportación del presente documento muestra que el desarrollo de la innovación en una región colectivista como latinoamericana, requiere de una interpretación cultural.
Gait Data Generation Method for Humanoid Robot Training

This paper presents an approach to generate the human gait data applied in the articulated humanoid robot training. Usually, the human body of gait sequence is expressed by a dynamical skeleton that are used to train humanoid robots by a tenacity machine intelligence algorithm. Such a machine intelligence algorithm needs massive data for training. To solve this issue, we formulate the skeletons' shapes as trajectories on the shape space of skeletons. Furthermore, we construct a trajectory manifold with stretching channels, where the gait data generation is formulated as an issue of elements interpolation. Several experiments demonstrate the performance of our method in gait data generation.
Development of optimisation model for black soldier fly-based aquaculture feed supply chains in Malaysia

Aquaculture is identified as one of the critical food supplies in Malaysia. Due to the increasing demand for aquaculture products, the demand for protein sources for fish feed is also increased accordingly. Black soldier fly larvae is identified as one of the main protein sources that can be used in fish feed. Such larvae can be grown using different types of organic materials, such as food waste, agriculture waste, etc. As Malaysia is the second-largest palm oil producer in the world, therefore, a large number of agricultural wastes, also known as palm-based biomass (e.g., empty fruit bunches, mesocarp fibre, decanter cake, etc.) are generated annually. Based on the current industry practise, palm-based biomass can be converted into value-added products. However, using palm-based biomass as feedback to grow black soldier fly larvae is a relatively recent discovery. Thus, a viable supply chain model has yet to be established. In this work, a mathematical optimisation model is developed via commercial optimisation software (Lingo v. 16) to synthesise an optimum black soldier fly-based aquaculture feed supply chain that utilised palm–based biomass as the feedstock. Based on the optimised result, the annual operating cost of the aquaculture feed supply chain is estimated as RM 5.2 million.
Metal-Organic Frameworks Characterization via Inverse Pulse Gas Chromatography

The desire to customize the properties of a material through complete control over both its chemical and architectural structure has created a constant and persistent need for efficient and convenient characterization techniques. Inverse gas chromatography (IGC) is considered a useful characterization method for probing the material’s surface properties, like its enthalpies of adsorption, which are the key stimulus components for their adsorption performance. Here, we conclusively review the significance of a less common application of the IGC technique for the physicochemical characterization of metal-organic frameworks (MOFs), which are an innovative subclass of porous materials with matchless properties in terms of structure design and properties. This review focuses on the fundamental theory and instrumentation of IGC as well as its most significant applications in the field of MOF characterization to shed more light on this unique technique.
Borreliae Part 2: Borrelia Relapsing Fever Group and Unclassified Borrelia

Simple Summary Following Borreliae Part 1, this second review describes Borreliae of the relapsing fever group (RFG) and unclassified Borreliae. The RFG is further divided according to vector transmission and geographical distribution in other subgroups, namely the soft-tick-borne relapsing fever (STBRF) group, the hard-tick-borne relapsing fever (HTBRF) one, the louse-borne relapsing fever (LBRF) group, and the Avian relapsing fever group. Where possible, according to the literature description, each sub-group of the RFG Borreliae is organized here in sections explaining the geographical distribution, the vectors, the hosts, the epidemiology, and the microbiology. In case of human infectiveness, clinical aspects are also discussed. Isolation and sequencing of Borrelia species is ongoing, and in addition to the groups mentioned in these reviews, there are Borreliae that at present cannot be cultivated, but according to sequencing data they share some characteristics with one specific group. Nevertheless, they still cannot be classified in one of them. This is the case of Borreliae with not-yet-identified pathogenicity for humans or animals, which are here named “unclassified Borreliae” and described separately, recalling the similarities with Borreliae already classified. In the future, we expect that those Borreliae are going to be characterized, including them in one of the previous groups. Abstract Borreliae of the relapsing fever group (RFG) are heterogenous and can be divided mainly into three groups according to vectors, namely the soft-tick-borne relapsing fever (STBRF) Borreliae, the hard-tick-borne relapsing fever (HTBRF) Borreliae, the louse-borne relapsing fever (LBRF) Borreliae, and the avian relapsing fever ones. With respect to the geographical distribution, the STBRF Borreliae are further subdivided into Old World and New World strains. Except for the Avian relapsing fever group Borreliae, which cause avian spirochetosis, all the others share infectivity in humans. They are indeed the etiological agent of both endemic and epidemic forms of relapsing fever, causing high spirochaetemia and fever. Vectors are primarily soft ticks of Ornithodoros spp. in the STBRF group; hard ticks, notably Ixodes sp. , Amblyomma sp. , Dermacentor sp. , and Rhipicephalus sp. , in the HTBRF group; and the louse pediculus humanus humanus in the TBRF one. A recent hypothesis was supported for a common ancestor of RFG Borreliae, transmitted at the beginning by hard-body ticks. Accordingly, STBRF Borreliae switched to use soft-bodied ticks as a vector, which was followed by the use of lice by Borrelia recurrentis. There are also new candidate species of Borreliae, at present unclassified, which are also described in this review.
Improving Mathematical Models of Cancer through Game-Theoretic Modelling: A Study in Non-Small Cell Lung Cancer

We examined a dataset of 590 Non-Small Cell Lung Cancer patients treated with either chemotherapy or immunotherapy using a game-theoretic model that includes both the evolution of therapy resistance and a cost of resistance. We tested whether the game-theoretic model provides a better fit than classical mathematical models of population growth (exponential, logistic, classic Bertalanffy, general Bertalanffy, Gompertz, general Gompertz). To our knowledge, this is the first time a large clinical patient cohort (as opposed to only in-vitro data) has been used to apply a game-theoretic cancer model. The game-theoretic model provided a better fit to the tumor dynamics of the 590 Non-Small Cell Lung Cancer patients than any of the non-evolutionary population growth models. This was not simply due to having more parameters in the game-theoretic model. The game-theoretic model was seemingly able to fit more accurately patients whose tumor burden exhibit a U-shaped trajectory over time. We explained how this game-theoretic model provides predictions of future tumor growth based on just a few initial measurements. Using the estimates for treatment-specific parameters, we then explored alternative treatment protocols and their expected impact on tumor growth and patient outcome. As such, the model could possibly be used to suggest patient-specific optimal treatment regimens with the goal of minimizing final tumor burden. Therapeutic protocols based on game-theoretic modeling can help to predict tumor growth, and could potentially improve patient outcome in the future. The model invites evolutionary therapies that anticipate and steer the evolution of therapy resistance.
Integrative of Perceived Management Support on Information Technology Innovativeness

Government Information Technology Innovativeness defined as notion of openness to new information technology ideas in the government as an aspect of an organizational culture. In adopting the information technology innovativeness, management support plays a crucial effect. Misunderstood organizational characteristic within information technology innovativeness may generate unrealistic or inaccurate outcomes. Unfortunately, the effect of organizational context is nearly ignored in information technology innovativeness literature. In response, using the Resources based view (RBV) and Diffusion-Innovation-Theory (DIT), this paper argues on the interaction between the influence of organizational characteristic (management support), so as to explain information technology innovativeness. This proposition could improve understanding the information technology innovativeness and help to resolve inconsistency of findings in the literature.
Anti-Inflammatory Activity of Bullfrog Oil Polymeric Nanocapsules: From the Design to Preclinical Trials

Background Although bullfrog oil (BFO) exerts anti-inflammatory effects, it has undesirable properties limiting its use. Methodology BFO nanocapsules (BFONc) were produced through nanoprecipitation, and their physicochemical and morphological properties were characterized. To evaluate the biocompatibility of the formulation, a mitochondrial activity evaluation assay was conducted, and cell uptake was assessed. The in vitro anti-inflammatory activity was evaluated by measuring reactive oxygen species (ROS), nitric oxide (NO), type-6 interleukin (IL-6), and tumor necrosis factor (TNF) levels. The in vivo anti-inflammatory effect was assessed by quantifying myeloperoxidase (MPO) levels using the carrageenan-induced paw edema model. Results BFONc showed a particle size of 233 ± 22 nm, a polydispersity index of 0.17 ± 0.03, and a zeta potential of −34 ± 2.6mV. BFONc revealed remarkable biocompatibility and did not induce changes in cell morphology. Furthermore, BFONc decreased ROS levels by 81 ± 4%; however, NO level increased by 72 ± 18%. TNF and IL-6 levels were reduced by approximately 10% and 90%, respectively. Significant in vivo anti-inflammatory activity was observed compared to dexamethasone. MPO levels were reduced up to 2 MPOs/mg. Conclusion Taken together, the results pointed out the remarkable biocompatibility and anti-inflammatory effects of BFONc.
Fractional Calculus

This paper aims to give the reader a comfortable introduction to Fractional Calculus. Fractional Derivatives and Integrals are defined in multiple ways and then connected to each other in order to give a firm understanding in the subject. The reader is expected to be versed in undergraduate complex analysis, meaning that they should also be familiar with real analysis. In the concluding remarks, the readers familiar with measure theory will find a brief discussion of how to extend the topics discussed in the paper to more general analysis.
English and Spanish Adjectives That Describe the Japanese Concept of Kawaii

The word “kawaii” is ubiquitous in contemporary Japan and has spread to the rest of the world with the dissemination of Japanese pop culture. Although the word is conventionally translated in English as “cute,” its meaning is more nuanced than “cute,” and it is used for a wider variety of objects. The primary aim of this study was to determine if Spanish has an equivalent to the word “kawaii”; additionally, similarities and differences across Japanese, English, and Spanish were explored. An internet survey was conducted in which respondents from Japan (n = 486), the United States (n = 365), and Argentina (n = 303) were presented with various photographic images that were often described as “kawaii” in Japanese and asked to write three adjectives to describe the images. They were also instructed to rate their affective states when looking at each image in the valence and arousal dimensions. The results showed that babyish objects (e.g., human, animal, and toy) were most frequently defined as “kawaii” in Japanese, “cute” in English, and “tierno” in Spanish. The average frequency at which these words were used as primary adjectives was higher for “kawaii” (57.5%) than for “cute” (26.8%) or “tierno” (22.4%). All of these images were associated with positive and moderately-aroused affective states similarly across all three countries. The present study demonstrates that the adjectives “kawaii,” “cute,” and “tierno” can be used almost equivalently for describing babies and pets, but that the Japanese adjective “kawaii” encompasses wider categories than the other two words.
Dietary Fat and Betaine Supplements Offered to Lactating Cows Affect Dry Matter Intake, Milk Production and Body Temperature Responses to an Acute Heat Challenge

Simple Summary Hot weather is associated with reduced milk yield of dairy cows. Supplementing the diet of lactating cows with ingredients that increase dietary energy density or that reduce internal heat production, may reduce some of the negative impacts of hot weather on milk yield. We used controlled-climate chambers to simulate a short hot-weather event and measured changes in milk yield, feed intake, and body temperature of cows fed either a fat supplement, betaine or a combination of both. Feeding cows fat resulted in improved milk production but also increased body temperature and caused a decrease in feed intake. Feeding betaine did not affect milk yield but did reduce cow body temperature at times. Contrary to our expectations, the combination of fat and betaine supplements did not result in a clear benefit in terms of milk production or body temperature. Further work is warranted to understand the interactions between dietary fat type and betaine supplements when offered to cows during periods of hot weather. Abstract Supplementing the diet of lactating cows with ingredients that increase energy density, or reduce internal heat production, may reduce some of the negative impacts of hot weather on milk yield. Thirty-two dairy cows were assigned either: (1) basal diet only, (2) basal diet plus canola oil, (3) basal diet plus betaine, or (4) basal diet plus canola oil and betaine. The basal diet was lucerne hay, pasture silage, and grain. Cows were exposed to a four-day heat challenge (temperature-humidity index 74 to 84) in controlled-environment chambers. Canola oil supplementation increased milk production (22.0 vs. 18.7 kg/d) across all periods of our experiment and increased body temperature (39.6 vs. 39.0 °C) during the heat challenge. Betaine supplementation reduced maximum body temperature during the pre-challenge period (39.2 vs. 39.6 °C) but not during the heat challenge (40.3 °C). Cows fed canola oil had greater declines in dry matter intake (5.4 vs 2.7 kg DM) and energy corrected milk (1.3 vs. 1.0 kg) from the pre-challenge to the heat challenge than other cows. Contrary to our expectations, the combination of fat and betaine supplements did not result in a clear benefit in terms of milk production or body temperature. Further work is warranted to understand the interactions between diet and hot weather.
Impacts on business models resulting from digitalization

The development of the Internet created new technologies that are changing the way of doing business, particularly Industry 4.0 in current days. One challenge of the implementation of new technologies is the change required from companies' business models. However, the literature concerning Industry 4.0 is mainly focused on technological innovations and less in their impact on business models. This paper aims to understand the impacts of the digitalization process inherent to Industry 4.0 on business models. To achieve this purpose, an exploratory multiple-case study based on semi-structured interviews was conducted in two Portuguese medium companies from two different sectors. Findings show that besides companies being able to change to a customer-oriented approach, individualized mass production may not be the only purpose of this transformation. Networking is particularly appealing for small and medium enterprises, once they usually have fewer resources to dedicate to innovation projects. Additionally, in the era of globalization, logistic costs are still an obstacle for serving international markets. Finally, social media are seen as an internal tool of communication for business-to-business companies. Being one of the first empirical studies of the Portuguese context, it aims to diminish the lack of literature concerning this particular topic and enable future researches on the use of business models as a management tool. Secondly, it intends to help managers develop or redesign business models adjusted to a more dynamic and competitive environment.
Neuropsychological differences between treatment-resistant and treatment-responsive schizophrenia: a meta-analysis

Abstract Antipsychotic treatment resistance affects up to a third of individuals with schizophrenia. Of those affected, 70–84% are reported to be treatment resistant from the outset. This raises the possibility that the neurobiological mechanisms of treatment resistance emerge before the onset of psychosis and have a neurodevelopmental origin. Neuropsychological investigations can offer important insights into the nature, origin and pathophysiology of treatment-resistant schizophrenia (TRS), but methodological limitations in a still emergent field of research have obscured the neuropsychological discriminability of TRS. We report on the first systematic review and meta-analysis to investigate neuropsychological differences between TRS patients and treatment-responsive controls across 17 published studies (1864 participants). Five meta-analyses were performed in relation to (1) executive function, (2) general cognitive function, (3) attention, working memory and processing speed, (4) verbal memory and learning, and (5) visual−spatial memory and learning. Small-to-moderate effect sizes emerged for all domains. Similarly to previous comparisons between unselected, drug-naïve and first-episode schizophrenia samples v. healthy controls in the literature, the largest effect size was observed in verbal memory and learning [dl = −0.53; 95% confidence interval (CI) −0.29 to −0.76; z = 4.42; p < 0.001]. A sub-analysis of language-related functions, extracted from across the primary domains, yielded a comparable effect size (dl = −0.53, 95% CI −0.82 to −0.23; z = 3.45; p < 0.001). Manipulating our sampling strategy to include or exclude samples selected for clozapine response did not affect the pattern of findings. Our findings are discussed in relation to possible aetiological contributions to TRS.
Handbook on Alternative Theories of Innovation

It is unwise to judge a book by its cover. Even so, the cover of this handbook is instructive. The image on the front of the hardback edition is an impressionistic depiction of spinning wheels that look rather like cogs. The cogs are only loosely connected and there are bits of unattached material floating between the spaces. The publishers have included an explanation of the cover image (p.x): the spinning wheels symbolize the several theories (of innovation) considered in the handbook. Some dominate, but not completely. They cover a lot, but not everything. Everything is unfinished and the whole system does not work together without some friction. There is debris (unattached stuff) floating around. On the back cover, the publishers have included a promotional statement from Peter Weingart: