Miracle-dz/UniFAR-FTUs huggingface dataset:
Investigation of the Microwave Absorption Properties of Fe Based Nanocomposites

The objective of this work was to provide information about the behaviour of Fe-based nanocomposites when exposed to microwaves. It is about rectangular bulk samples of epoxy resin reinforced by nanocrystalline Fe powders and shaped in accordance to the internal section of the R100 metallic waveguide (8.2 to 12.4 GHz) at a fixed thickness of 7 mm. The nanocrystalline Fe powders were obtained by high-energy mechanical milling process using a planetary Retsch PM 400-ball mill. The milling speed was fixed at 200 rpm for three durations and the milling process were performed under Argon atmosphere. The bulk nanocomposites were obtained by dispersion of 30% vol. of the nanocrystalline Fe powders in the resin matrix. Electromagnetic parameters as complex relative dielectric permittivity and magnetic permeability, electric and magnetic loss tangent and reflection loss were calculated using reordered S parameters. The scattering parameters were characterized using a measure cell made off two metallic R100 wave-guides associated to an Agilent 8719 network analyser according to the reflection-transmission technique. The obtained spectra inform on the new electromagnetic properties as well as the absorption characteristic acquired by the bulk nanocomposites due to the presence of the nanocrystalline Fe powders.
Influence of Substrate Rotational Speed on the Structural and Optical Properties of Sputtered Gd-Doped ZnO Thin Films

Rare-earth element of gadolinium (Gd) were successfully doped into zinc oxide (ZnO) using dual sputter source of DC and RF sputtering. The substrate rotation speed was controlled from 1 rpm to 9 rpm to investigate their effects on the properties of the films in order to achieve a great feature of thin film. XRD profiles confirmed the c-axis orientation with structure of ZnO hexagonal wurtzite. No peaks related to secondary phases were observed. The intensity of dominant peak showed increment upon improvement of substrate rotation speed. The incorporation of Gd into ZnO structure was further confirmed by composition element form EDX with average atomic percentage of 3 at. % for all the films. Surface topology from AFM images showed the grain size has increased with the higher speed of substrate rotation. Gd-doped ZnO thin films indicated good transparency with an average transmittance above 90 % regardless of substrate rotation speed. The bandgap has a slight decrease from 3.06 eV to 3.03 eV with an increment speed of rotational substrate. These findings further imply that the substrate rotation speed has a significant influence on the structural and optical properties of the sputtered thin films.
Green Synthesis of Nanoscale Zero-Valent Iron/Activated Carbon Composites and their Application for Copper and Chromium Removal from Aqueous Solutions

In this study, nanoscale zero-valent iron (nZVI) particles and their composites with powdered activated carbon (nZVI-PAC) and granular activated carbon (nZVI-GAC) were successfully synthesized via a low-cost green approach with the use of green tea extract. The adsorbents were then used to remove Cr and Cu from aqueous solutions, and their adsorption results were fitted with the Freundlich and Langmuir models. The synthesized adsorbents were characterized using XRD, FTIR, and FESEM techniques. The typical peak of Fe0 was detected in the XRD patterns of prepared samples, but the presence of organic compounds in green tea extract weakened related peak. The FESEM characterization demonstrated that the nZVI spherical particles had a chain-like structure and ranging in size from 10 to 50nm. The presence of polyphenols peak in the FTIR spectra revealed that the green tea extract was responsible for the reduction of the Fe2+ to Fe0. The maximum adsorbed amount of Cr and Cu was found to be 5.68 and 6.48 mg/g, which was achieved by nZVI-PAC and nZVI, respectively. The nZVI-PAC and nZVI also showed a higher removal efficiency for Cu and Cr by 62% and 94% for an initial concentration of 100 mg/L, respectively. The results showed that nZVI, nZVI-PAC, and nZVI-GAC could be promising and eco-friendly adsorbents for Cr and Cu removal from aqueous solutions.
Low power general purpose loop acceleration for NDP applications

Modern processor architectures face a throughput scaling problem as the performance bottleneck shifts from the core pipeline to the data transfer operations between the dynamic random access memory (DRAM) and the processor chip. To address such issue researchers have proposed the near-data processing (NDP) paradigm in which the instruction execution is moved to the DRAM die thus, lowering the data movement between the processor and the DRAM. Previous NDP works focus on specific application types and thus the general purpose application execution paradigm is neglected. In this work we propose an NDP methodology for low power general purpose loop acceleration. For this reason we design and implement a hardware loop accelerator from the ground up to improve the throughput and lower the power consumption of general purpose loops. We adopt a novel loop scheduling approach which enables the loop accelerator to take advantage of the dataflow parallelism of the executing loop and we implement our design on the logic layer of a hybrid memory cube (HMC) DRAM. Post-layout simulations demonstrate an average speedup factor of 20.5x when executing kernels from various scientific fields while the energy consumption is reduced by a factor of 9.3x over the host CPU execution.
Including the Quadtree index in SpatialHadoop

SpatialHadoop is a full-fledged MapReduce framework with native support for spatial data. It uses a two-level (global and local) index structure to store the spatial data in a distributed cluster. The global index partitions data across computing nodes, while the local index organizes data inside each computing node. SpatialHadoop supports R-tree as a local index on the contents of each physical partition. The Quadtree is one of the most used hierarchical access methods to index spatial data because of its property to partition the embedding space into regular cells, regardless of the data distribution. Top-k queries, e.g., k Nearest Neighbors Query (kNNQ) and k Closest Pairs Query (kCPQ), are common operations used in spatial applications. In this paper, the Quadtree is included as a local index in SpatialHadoop and, the design of kNNQ and kCPQ MapReduce algorithms, using this spatial index, is also presented. The experiments have demonstrated the efficiency and scalability of the Quadtree in comparison with the R-tree for distributed kNNQ and kCPQ in SpatialHadoop.
Prepartitioning in MapReduce Processing of Group Nearest-Neighbor Query

Given two datasets of points (called Query and Training), the Group (K) Nearest-Neighbor (GKNN) query retrieves (K) points of the Training with the smallest sum of distances to every point of the Query. This spatial query has been studied during the recent years and several performance improving techniques and pruning heuristics have been proposed. In a previous work, we presented the first MapReduce algorithm, consisting of alternating local and parallel phases, which can be used to effectively process the GKNN query when the Query fits in memory, while the Training one belongs to the Big Data category. In subsequent works, we presented several improvements on the first version of the algorithm. In this paper we present yet another improvement, which consists in the prepartitioning of the Training dataset. As shown in the experimentation section, this technique significantly reduces data transfer and total running time of the algorithm. Furthermore, the prepartitioning of the Training dataset is performed only once and can be reused with multiple Query datasets, leading to faster response times.
Smart Retail: Efficient in-store localization using ensemble classifiers

Smart retail is an important concept in smart cities, due to its potential to deliver competitive advantage to companies. As the retail sector is moving beyond locating products, in-store tracking technologies are used to deliver better services to consumers and acquire insights regarding their behavioral patterns. Retail stores are challenging environments with multiple sources of noise (e.g., shoppers’ moving) that impede indoor localization and there are settings with new requirements that should be further examined. This paper has developed and deployed a low-energy Bluetooth Low Energy (BLE) beacon-based indoor positioning system that utilizes machine learning to improve its accuracy, enabling retailers to offer more effective customer location-based services and improve decision making in retailing.
Online federated learning with imbalanced class distribution

The federated learning paradigm can be a viable solution for handling huge datasets, and for taking advantage of powerful processing nodes on the edge. The process of online federated learning can be employed in order to maximise the potential of federated learning by re-training a shared model on the edge nodes and merging the updated models centrally. This approach allows edge nodes to exchange knowledge without exchanging their own training data, thus preserving their privacy. In this work, we examine the online federated learning approach in an extreme case of imbalanced class distribution between the central and the edge nodes. We examine the effects of different parameters of the online federated learning process and propose a technique that boosts the classification performance above that of the baseline centralised learning approach.
Quantifying the Difficulty of Academic Course Modules

When analysing academic course module grades data, the focus usually alternates between the student’s performance in course modules and the way a typical course module’s assessment procedure profile evolves from one academic year to the next. Exploratory data analysis makes possible the extraction of information in the direction of predicting student performance in course modules remaining to be taken along one’s study path, causal associations between course modules taken by the same students on the basis of the performance of the latter, etc. In the present study, emphasis is given to the data preparation stage of the academic course data analysis process. A framework is proposed for calculating the degree of difficulty of a (any) course module for a specific term examinations period. The quantification of the degree of difficulty of a course module makes possible the calculation of pertinent student grade equivalent ranks. The use of the latter in place of student grades! is expected to facilitate and improve the effectiveness of the data mining process. The proposed framework is expected to be of value to the Departmental Internal Evaluation Committee (DIEC) the needs of which have initiated and motivated this study.
Culture-Sensitive Communication in Applied Developmental Research

Communication about child development between persons with different cultural preoccupations requires that author and audience agree without coercion on how to connect their perspectives. Western cultural hegemony persists in many international fora under the guise of “globalization,” giving rise to systematically distorted communication in ways that do epistemological violence to indigenous cultural models in Africa. The dominant paradigm of public basic schooling is sustained by institutionalized path dependency and construes educational success as extracting the learner from her community of origin. Consensus-building within a framework of mutually respectful communication involves bridging, coordination or fusion. Societal progress is a different kind of “development” than ontogenesis. A given cultural group’s developmental niche for its children is part of a chronosystem that changes over the course of history. An individual’s transactions with significant others are embedded in a complex and dynamic sociocultural system, to which programming of early childhood education should respond.
SAYCam: A Large, Longitudinal Audiovisual Dataset Recorded From the Infant’s Perspective

Abstract We introduce a new resource: the SAYCam corpus. Infants aged 6–32 months wore a head-mounted camera for approximately 2 hr per week, over the course of approximately two-and-a-half years. The result is a large, naturalistic, longitudinal dataset of infant- and child-perspective videos. Over 200,000 words of naturalistic speech have already been transcribed. Similarly, the dataset is searchable using a number of criteria (e.g., age of participant, location, setting, objects present). The resulting dataset will be of broad use to psychologists, linguists, and computer scientists.
Grammar modulates discourse expectations: evidence from causal relations in English and Korean

abstract This paper investigates whether differences in grammar affect the production of discourse relations. We report the results of two story continuation experiments on speakers of two typologically unrelated languages, English and Korean, and in two different discourse genres, monologues (Experiment 1) and conversations (Experiment 2), focusing on the contrast between the explanation discourse relation and the result discourse relation. Since the grammar of clause linkage in Korean, but not English, disfavors a backward causal order (explanation relation), we predicted that Korean speakers are less likely to produce EXPLANATION continuations in MONOLOGUES than English speakers. We also predicted that this difference disappears in conversation, as questions that can be uttered in conversations are not subject to the same constraints on clause linkage in Korean. The results confirmed our predictions. The effect of language on the production of discourse relations in monologue suggests that LINGUISTIC STRUCTURES can affect speakers’ discourse expectation and production, while the absence of language effect in conversation suggests that this language effect is not due to differences in the way speakers causally relate events or to conceptual or cultural differences in preferences for iconic discourse between English and Korean speakers.
Syntheses and applications of conducting polymer polyaniline nanofibers

Abstract Nanofibers with diameters of tens of nanometers appear to be an intrinsic morphological unit that was found to "naturally" form in the early stage of the chemical oxidative polymerization of aniline. In conventional polymerization, nanofibers are subject to secondary growth of irregularly shaped particles, which leads to the final granular agglomerates. The key to producing pure nanofibers is to suppress secondary growth. Based on this, two methods - interfacial polymerization and rapidly mixed reactions - have been developed that can readily produce pure nanofibers by slightly modifying the conventional chemical synthesis of polyaniline without the need for any template or structural directing material. With this nanofiber morphology, the dispersibility and processibility of polyaniline are now much improved. The nanofibers show dramatically enhanced performance over conventional polyaniline applications such as in chemical sensors. They can also serve as a template to grow inorganic/polyaniline nanocomposites that lead to exciting properties such as electrical bistability that can be used for nonvolatile memory devices. Additionally, a novel flash welding technique for the nanofibers has been developed that can be used to make asymmetric polymer membranes, form patterned nanofiber films, and create polymer-based nanocomposites based on an enhanced photothermal effect observed in these highly conjugated polymeric nanofibers.
Efficacy of implementing intermittent STOP THE BLEED® reviews on long term retention of hemorrhage control skills of first year medical students

Abstract Context Some medical schools integrate STOP THE BLEED® training into their curricula to teach students how to identify and stop life threatening bleeds; these classes that are taught as single day didactic and hands-on training sessions without posttraining reviews. To improve retention and confidence in hemorrhage control, additional review opportunities are necessary. Objectives To investigate whether intermittent STOP THE BLEED® reviews were effective for long term retention of hemorrhage control skills and improving perceived confidence. Methods First year osteopathic medical students were asked to complete an eight item survey (five Likert scale and three quiz format questions) before (pretraining) and after (posttraining) completing a STOP THE BLEED® training session. After the surveys were collected, students were randomly assigned to one of two study groups. Over a 12 week intervention period, each group watched a 4 min STOP THE BLEED® review video (intervention group) or a “distractor” video (control group) at 4 week intervals. After the 12 weeks, the students were asked to complete an 11 item survey. Results Scores on the posttraining survey were higher than the pretraining survey. The median score on the five Likert scale items was 23 points for the posttraining survey and 14 points for the pretraining survey. Two of the three knowledge based quiz format questions significantly improved from pretraining to posttraining (both p<0.001). On the 11 item postintervention survey, both groups performed similarly on the three quiz questions (all p>0.18), but the intervention group had much higher scores on the Likert scale items than the control group regarding their confidence in their ability to identify and control bleeding (intervention group median = 21.4 points vs. control group median = 16.8 points). Conclusions Intermittent review videos for STOP THE BLEED® training improved medical students’ confidence in their hemorrhage control skills, but the videos did not improve their ability to correctly answer quiz-format questions compared with the control group.
Crystallization of Amorphous Lactose

Crystallization of amorphous lactose was studied at constant water content and at constant relative humidity above glass transition temperature (Tg). The rate of crystallization was followed using differential scanning calorimetry. Crystallization at constant water content increased the amount of water in the remaining amorphous matrix, which decreased Tg and accelerated crystallization. At constant relative humidity crystallization proceeded at a rate determined by T -Tg which increased with crystallinity. Temperature dependence of time to complete crystallization was confirmed to follow Williams-Landel-Ferry (WLF) equation. The results can be used to evaluate diffusion and crystallization kinetics of amorphous carbohydrates.
APPLYING THE LIFESPAN MODEL OF ETHNIC-RACIAL IDENTITY: EXPLORING AFFECT, BEHAVIOR, AND COGNITION TO PROMOTE WELL-BEING

This paper presents an application of the Lifespan Model of Ethnic-Racial Identity (ERI) Development (see Williams, et al., in press). Using a tripartite approach, we present the affective, behavioral, and cognitive aspects of ERI in a framework that can be adapted for group and individual psychosocial interventions across the lifespan. These A-B-C anchors are presented in developmental contexts as well as the larger social contexts of systemic oppression and current and historical sociopolitical climates. It is ultimately the aspiration of this identity work that individuals will engage in ERI meaning-making, drawing from the implicit and explicit aspects of their A-B-Cs, to support a healthy and positive sense of themselves and others as members of ethnic-racial social groups.
Overcoming pandemic social distancing challenges in research in Portugal and England

A dystopian scenario dated 1909: the air on Earth becomes lethal. A mother and her son live apart and isolated. They see each other and communicate through a “Machine”. 2019: the world faces the emergence of a real and highly contagious disease that spreads through air. And throughout 2020, families around the world experience a similar reality, as lockdowns accelerate the mediatization of their lives. This commentary focuses on the impact of COVID-19 on my Families iTec research, which is an ongoing longitudinal study with 18 families with children aged 0–8, living in Portugal (n = 16) and England (n = 2). These families are diverse in terms of family structure, composition, children’s ages, nationality (an effect of globalization), socio-economic status, and patterns of digital media use (Castro & Ponte, forthcoming). The goal of the study is to reach a holistic understanding of how the ecological environment of families lives – that is, the interconnections between settings and events (Bronfenbrenner, 1979) – influence their digital media use and mediation over time. We take a qualitative approach, using ethnographic and participatory strategies. When the realities of the pandemic and lockdowns made it impossible for me to continue to physically visit the families for data collection, I embraced the shift to the digital. Video chatting and phone calls have been paramount to keep closely in touch with them and to continue an investigation that has become increasingly necessary, as family school and work routines, entertainment and emotional ties became massively entangled, mediated and moulded by the internet thorough the pandemic. Parents responded positively to the digitally supported interactions that allowed us to continue this research. They have been sort of field collaborators – sharing videos, pictures, and occurrences of their children’s “new normal”. Nevertheless, parents’ goodwill in this collaboration has seemed to fade over time. After the initial enchantment of seeing the lockdown as an opportunity for enjoying family quality time, parents have become more preoccupied with the confluent crises that threaten their health, wellbeing, finances, emotions, and social ties. In some families, those concerns are heightened further still by social inequalities that have become more visible and challenging in 2020.
Persistent Homology Metrics Reveal Quantum Fluctuations and Reactive Atoms in Path Integral Dynamics

Nuclear quantum effects (NQEs) are known to impact a number of features associated with chemical reactivity and physicochemical properties, particularly for light atoms and at low temperatures. In the imaginary time path integral formalism, each atom is mapped onto a “ring polymer” whose spread is related to the quantum mechanical uncertainty in the particle’s position, i.e., its thermal wavelength. A number of metrics have previously been used to investigate and characterize this spread and explain effects arising from quantum delocalization, zero-point energy, and tunneling. Many of these shape metrics consider just the instantaneous structure of the ring polymers. However, given the significant interest in methods such as centroid molecular dynamics and ring polymer molecular dynamics that link the molecular dynamics of these ring polymers to real time properties, there exists significant opportunity to exploit metrics that also allow for the study of the fluctuations of the atom delocalization in time. Here we consider the ring polymer delocalization from the perspective of computational topology, specifically persistent homology, which describes the 3-dimensional arrangement of point cloud data, (i.e. atomic positions). We employ the Betti sequence probability distribution to define the ensemble of shapes adopted by the ring polymer. The Wasserstein distances of Betti sequences adjacent in time are used to characterize fluctuations in shape, where the Fourier transform and associated principal components provides added information differentiating atoms with different NQEs based on their dynamic properties. We demonstrate this methodology on two representative systems, a glassy system consisting of two atom types with dramatically different de Broglie thermal wavelengths, and ab initio molecular dynamics simulation of an aqueous 4 M HCl solution where the H-atoms are differentiated based on their participation in proton transfer reactions.