Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploring attention on a retailer’s homepage: an eye-tracking & qualitative research study

ABSTRACT This article explores why some areas of a retailer’s homepage receive more attention than others. An eye-tracking study followed by retrospective think-aloud protocols and qualitative semi-structured interviews were conducted with a purposive sample of 52 females (aged 20–70). Findings revealed the visual hierarchy of a retail homepage: 1. Rotating Banner, 2. Main Menu Bar, 3. Left drop-down menu, 4. Static images below banner, 5. Search bar. Qualitative data revealed that some features attracted attention due to them being useful, serving a functional purpose (menu bars, search bar), or due to them being interesting (static banner images) but others did so inadvertently because they were distracting and irritating (rotating banner). This shows that attention can be due to both positive and negative factors. This article contributes to knowledge by providing a rich interpretation of eye-tracking data and attention on a retail homepage, showing the interplay between top-down and bottom-up attention on a user’s shopping journey. This is valuable for future academic research as well as practitioners. This study also highlights the importance of using live websites for research to increase ecological validity.
Synthesis of the Novel Nanocatalyst of Pt3Mo Nanoalloys on Ti0.8W0.2O2 via Hydrothermal and Microwave-Assisted Polyol Process

Direct methanol fuel cell (DMFC) attracts much attention due to its high abundance, environmental friendliness, and convenient transportation and storage. In this study, a novel catalyst of Pt3Mo alloy nanoparticles (NPs) on non-carbon Ti0.8W0. 2O2 support was synthesized by microwave-assisted polyol process. The characteristic of Pt3Mo NPS/Ti0.8W0. 2O2 catalyst was determined by X-ray diffraction (XRD), transmission electron microscopy (TEM), scanning electronic microscopy (SEM), energy-dispersive X-ray (EDX), and Brunauer-Emmett-Teller (BET) method. Pt3Mo NPs had an average diameter of approximate 5.18 nm and were uniformly anchored on Ti0.8W0. 2O2 surface. The ratio of Mo in the Pt3Mo alloy was consistent with the theoretical value, which supported the effectiveness of the synthesis method. In addition, Pt3Mo/Ti0.8W0. 2O2 electrocatalysts exhibited higher CO-like tolerance in methanol oxidation reaction (MOR) than commercial electrocatalysts, excellent catalytic activity, and strong durability after 2000 cycles. The synergistic effect of Pt-Mo alloy, and the strong interaction between the bimetallic Pt-Mo alloy and the mesoporous Ti0.8W0. 2O2 support, could weaken the Pt-CO bond. Besides, the high corrosion resistance and superior electrochemical durability of TiO2-based oxide also contribute to the excellent stability of Pt3Mo/Ti0.8W0. 2O2 electrocatalyst in harsh electrochemical media. These results revealed that this material could be a potential catalyst in DMFC technology.
Analysis of Septuple-Band NGD Circuit Using an E-Shaped Defected Microstrip Structure and Two T-Shaped Open Stubs

In this article, a compact distributed septuple-band negative group delay circuit (NGDC) is proposed and analyzed. It is mainly composed of a high–low–high step-impedance microstrip line with an E-shaped groove and two T-shaped open stubs. This NGDC was first simulated and then fabricated by using a conventional printed circuit board (PCB) process with the substrate of RO4350. To investigate the operational mechanism of the NGDC, an equivalent circuit, consisting of nine transmission lines, four series–parallel LC resonant circuits, and two T-type series LC resonant circuits, has been developed and analyzed. It is found that the theoretical group delay characteristic calculated from the equivalent circuit agrees well both with the simulated data by using ADS as well as HFSS and with the experimental results. The measured seven NGD resonant frequencies occur at 2.03, 2.84, 8.14, 8.74, 13.0, 16.02, and 18.46 GHz, and the corresponding NGD values read −3.65, −3.04, −1.73, −3.23, −1.16, −1.20, and −1.47 ns. The dimensions of the presented passive NGDC are only 25 mm $\times22$ mm without using any lumped components.
Channel-Attention-Enhanced LSTM Neural Network Decoder and Equalizer for RSE-Based Optical Camera Communications

In an RGB-LED-based optical camera communication system, it is an essential goal to have better performance in the data rate and BER. However, in a higher symbol rate, due to the conventional sampling algorithm, the deterioration of transmission performance brought by the inter-symbol interference and inter-channel interference is significant. Innovatively, in this paper, the sub-image obtained by a captured frame of received video is encoded by a channel-attention-Net-based encoder to generate a descriptor without existing sampling methods. Moreover, we propose an LSTM-based equalizer to decode the descriptor and mitigate transmission performance deterioration. Utilizing the long-short-term memory of an LSTM unit, an equalizer not only can reduce bit error rates but also increase the data rate. The experimental results show that at a symbol rate of 46 kbaud/s, a record-high data rate at 44.03 kbit/s is achieved under random data transmission while still meeting the pre-forward error correction requirement.
Digital watermarking method for image feature point extraction and analysis

Multimedia information (e.g., photos) is subject to numerous attacks when extensively dispersed, excellent stealth and robustness play a critical role in information concealment. Next, to further improve the imperceptibility of the generated images, we introduce an information embedding based on feature extraction, since the feature points themselves are robust as strong corner points in the images. We will perform specific practical applications in information‐hiding scenarios, such as ticket anticounterfeiting, copyright protection, tampering hints, and covert marking. As a result, while assuring the accuracy of hidden data, assault resistance must also be addressed. In this paper, a strategy for watermark embedding utilizing image feature points is proposed. In principle, the embedding and extraction of digital watermarks are achieved in the transform domain by discrete wavelet transform processing to make digital images more robust than before. The effectiveness of the algorithm is analyzed by experimental data, in which different wavelet bases are used. To check the robustness of the watermarking algorithm, various attacks are performed on watermarked images.
The Prevalence of Cardiometabolic Health Risk Factors among Airline Pilots: A Systematic Review

Background: The occupational demands of professional airline pilots such as shift work, work schedule irregularities, sleep disruption, fatigue, physical inactivity, and psychological stress may promote adverse outcomes to cardiometabolic health. This review investigates the prevalence of cardiometabolic health risk factors for airline pilots. Methods: An electronic search was conducted utilizing PubMed, MEDLINE (via OvidSP), CINAHL, PsycINFO, SPORTDiscus, CENTRAL, and Web of Science for publications between 1990 and February 2022. The methodological quality of included studies was assessed using two quality assessment tools for cross-sectional and clinical trial studies. The prevalence of physiological, behavioral, and psychological risk factors was reported using descriptive analysis. Results: A total of 48 studies derived from 20 different countries, reviewing a total pooled sample of 36,958 airline pilots. Compared with general population estimates, pilots had a similar prevalence for health risk factors, yet higher sleep duration, lower smoking and obesity rates, less physical activity, and a higher overall rate of body mass index >25. Conclusions: The research reported substantial prevalence >50% for overweight and obesity, insufficient physical activity, elevated fatigue, and regular alcohol intake among pilots. However, the heterogeneity in methodology and the lack of quality and quantity in the current literature limit the strength of conclusions that can be established. Enhanced monitoring and future research are essential to inform aviation health practices and policies (Systematic Review Registration: PROSPERO CRD42022308287).
Systematic realisation of inductorless and resistorless Chua’s chaotic oscillator using VDGA

ABSTRACT This paper presents an implementation of inductorless and resistorless Chua’s chaotic oscillator using voltage-differencing gain amplifier (VDGA). The chaotic oscillator circuit is implemented by designing a resistorless Chua’s diode using a single VDGA and a VDGA-based tank oscillator with coupled network circuit. The proposed chaotic oscillator uses two VDGAs and three grounded capacitors only. Although resistors and inductors may also be fabricated, the use of no resistor and inductor makes the circuit suitable for fabrication in terms of cost and area. It offers the advantages of an increased frequency spectrum having a dominant operating frequency of 21.1 MHz. The Chua’s circuit is simulated in Pspice using both macro models of IC MAX435 and 0.18 µm CMOS TSMC Technology parameters. As a result, chaotic waveforms (V1 and V2) and the various attractors (V1 versus V2) are found in the simulation. These results confirm the theoretical predictions of Chua’s chaotic oscillator. Various aspects of the proposed implementation of Chua’s oscillator are compared with the earlier implementations. Finally, the paper concludes with simple remarks on the proposed circuit.
Conceptual evaluation of hybrid energy system comprising wind-biomass-nuclear plants for load balancing and for production of renewable synthetic transport fuels

Future energy systems will increasingly need to integrate variable renewable energy in order to reduce greenhouse gas emissions from power production. Addressing this trend the present paper studies how a hybrid energy systems comprising aggregated wind farms, a biomass processing plant, and a nuclear cogeneration plant could support high renewable energy penetration. The hybrid energy system operates so that its electrical output tends to meet demand. This is achieved mainly through altering the heat-to-power ratio of the nuclear reactor and by using excess electricity for hydrogen production through electrolysis. Hybrid energy systems with biomass treatment processes, i.e. drying, torrefaction, pyrolysis and synthetic fuel production were evaluated. It was shown that the studied hybrid energy system comprising a 1 GWe wind farm and a 347 MWe nuclear reactor could closely follow the power demand profile with a standard deviation of 34 MWe. In addition, on average 600 m 3 of bio-gasoline and 750 m 3 bio-diesel are produced daily. The reduction of greenhouse gas emissions of up to 4.4 MtCO2eq annually compared to power generation and transport using conventional fossil fuel sources.
Um Modelo de Ensino Virtual de Engenharia de Software Orientado por Competências, Times e Projetos

Devido à pandemia COVID-19, muitas disciplinas oferecidas presencialmente em várias instituições educacionais precisaram ser repensadas para uma emergência e oferta virtual. Este trabalho apresenta um relato de experiência na aplicação de um modelo de ensino virtual de Engenharia de Software, envolvendo a seleção das Metodologias Ativas como a Aprendizagem Baseada em Projetos (PjBL), a Aprendizagem Baseada em Equipes (TBL) e a Aprendizagem Baseada em Competências (CBL), com foco em competências, equipes e projeto aplicado na disciplina Fundamentos de Engenharia de Software do Instituto Tecnológico de Aeronáutica (ITA) no segundo semestre de 2020. O modelo apresentado contém um modelo de concepção e um modelo de execução. Também foi realizada uma análise de aderência do modelo de ensino virtual para dois importantes referenciais de ensino em Engenharia de Computação, como o Exame Nacional de Desempenho de Estudantes (ENADE) e a Sociedade Brasileira de Computação (SBC).
A Novel Differential Chaos Shift Keying Scheme With Transmit Diversity

A novel differential chaos shift keying scheme with transmit diversity, referred to as TD-DCSK scheme, is proposed in this letter. The proposed TD-DCSK scheme can achieve full diversity and high data rate by advisably designing the space-time (ST) block of the transmitted signal. With the designed ST block, the transmitter with multiple transmit antennas in the TD-DCSK scheme requires only one radio frequency chain, which is particularly important for keeping low hardware complexity. We derive the theoretical expression of bit-error rate (BER) and diversity order of the TD-DCSK scheme over multipath Rayleigh fading channels, and analyze its hardware complexity. Simulation results illustrate the superiority of the proposed scheme and validate the accuracy of the theoretical derivation. The proposed TD-DCSK scheme stands out as a promising solution for low-power and low-cost short-range wireless communications.
Soluções Para a Logística de Distribuição de Encomendas na Etapa de Última Milha - Um Estudo de Caso na Empresa ALFA

As empresas de logística tem cada vez mais enfrentado os desafios da distribuição na last mile (última milha), sendo expressa como em uma unidade de medida, como a última perna logística, ou seja, os 1,6 kms finais de uma entrega. Diante deste contexto, recai a situação problemática deste estudo: como é possível repensar a distribuição de encomendas de forma a otimizar o processo de entrega externa, considerando a jornada do entregador e a racionalização de recursos organizacionais, para a empresa ALFA? Nesse contexto, traçou-se o objetivo de analisar o processo logístico de entrega de encomendas (cargas fracionadas) da empresa ALFA, visando propor soluções para a racionalização da etapa de última milha, no sentido de obter ganhos para a empresa e para os clientes. A pesquisa possui natureza exploratória e a estratégia utilizada foi o estudo de caso na empresa ALFA. Os principais resultados obtidos residem primeiro na jornada metodológica utilizada, com uma participação ampla (interna e externa), que possibilitou a obtenção de uma visão mais sistêmica sobre o processo como um todo. Um segundo ponto, foi verificar que nem sempre a aparência de um problema inicial, pode ser totalmente correta e soluções pontuais podem ajudar, mas não necessariamente resolver problemas que são sistêmicos. Assim, jornadas mais colaborativas ou metodologias para identificação de problemas podem ser soluções interessantes. Terceiro, a existência de amparo na literatura especializada para as soluções apresentadas e a extensão da participação com atores internos e externos, pode gerar visões mais consistentes sobre problemas organizacionais.
First record of the camphor shot borer, Cnestus mutilatus (Blandford) (Coleoptera: Curculionidae: Scolytinae) in Pennsylvania.

Cnestus mutilatus (Blandford) (Coleoptera: Curculionidae: Scolytinae) is reported from Pennsylvania for the first time, new state record. Specimens were collected using baited Lindgren funnels as early as 2013. Within Pennsylvania, C. mutilatus is now reported from Berks, Bucks, Lehigh, Montgomery, and York Counties.
Identifying Complex Patterns in Online Information Retrieval Processes

We define a computable benchmark framework that replicates the online information retrieval behavior of users as they proceed through the alternatives ranked by a search engine. Through their search processes, decision makers (DMs) must evaluate the characteristics defining the alternatives while aiming to observe a predetermined number satisfying their subjective preferences. A larger number of predetermined alternatives requires more complex information assimilation capacities on the side of DMs. Similarly, the complexity of the algorithms defined to formalize the subsequent retrieval behavior increases in the number of alternatives considered. The set of algorithms delivers two different strings of data, the pages clicked by the DMs and a numerical representation of each evaluation determining their retrieval behavior. We illustrate how, even when providing an Artificial Neural Network with both strings of data, the model faces considerable problems categorizing DMs correctly as their information assimilation capacities are enhanced.
Benchmark Analysis of Semantic Segmentation Algorithms for Safe Planetary Landing Site Selection

This paper presents an in-depth analysis of state-of-the-art semantic segmentation algorithms applied to spacecraft safe planetary landing via hazard detection and avoidance. Several architectures are trained from binary safety maps and the rich dataset of the High-Resolution Imaging Science Experiment (HiRISE) embedded on Mars Reconnaissance Orbiter for realistic purposes. The study incorporates several metrics comparisons such as recognition accuracy, computational complexity, model complexity, and inference time. The proposed performance indices and combinations are analyzed and discussed. The experiments were performed using a Raspberry Pi 4B, which is a relevant commercial-of-the-shelf microcontroller surrogate of NASA’s High-Performance Spaceflight Computer (HPSC) that will thrive within the next decades in space exploration. This paper allows researchers to know what has been tested on the subject and serves as a catalog for users to pick the most relevant architecture for their own application.
In-depth joint supply chain learning: towards a

Purpose – The purpose of this paper is to build a conceptual framework for understanding how in-depth joint supply chain learning can be successfully developed. This kind of learning is becoming increasingly important in highly turbulent and uncertain economic environments of new and growing interdependencies and complexities. Design/methodology/approach – Using a “synthesizing” or “bricolage” approach, key insights, now dispersed over a variety of literatures and disciplines, are integrated to develop the framework. Findings – The leading facilitative actor’s orientations, competencies and behavior play a significant role in enhancing the relationships between the supply chain actors shaping in-depth joint learning. Starting with establishing interaction boundary conditions by the leading actor, this process is likely to lead to system-level generative outcomes. These outcomes, in turn, serve the process cycle of in-depth joint learning as inputs for the relationship building process among all the actors. Research limitations/implications – By centering on the actual shaping of in-depth joint learning, and the concrete enactment of roles by protagonists enhancing this process, the paper has opened the black box. Future research should refine the framework. Practical implications – Apart from giving insight into the repertoire of relational competencies and behaviors needed to enhance the relationship building process conducive to in-depth joint learning, the paper addresses how these skills can be developed in practice and education. Originality/value – The paper identifies several implications for research, practice, and education. Instead of focusing predominantly on the content, procedure, levers, or outcomes of learning, the relational construction of the learning process itself is clarified.
A Relief from Mental Overload in a Digitalized World: How Context-Sensitive User Interfaces Can Enhance Cognitive Performance

Abstract Information overload resulting from the ever faster-growing mass of digital data makes knowledge work more and more complex. Being able to not get distracted and focus on what is currently relevant consumes valuable cognitive resources. Support by intelligent assistance software might alleviate this problem. We report two experiments that addressed this challenge by examining how context-based assistance may provide more available cognitive resources. Experiment 1 focused on work within a single context. Results indicate that external relevance classification can improve memory for content classified as currently more relevant. Experiment 2 focused on switching between two different contexts and shows that cognitive performance after context switches can be enhanced by context-specific structuring and saving a previous task status. Taken together, these results clearly demonstrate that automatic external information structuring by intelligent assistance software can protect knowledge workers from information overload by lightening their cognitive load and, thus, help improve cognitive performance.
Role of the Synergistic Interactions of Environmental Pollutants in the Development of Cancer

There is a growing awareness that the large number of environmental pollutants we are exposed to on a daily basis are causing major health problems. Compared to traditional studies that focus on individual pollutants, there are relatively few studies on how pollutants mixtures interact. Several studies have reported a relationship between environmental pollutants and the development of cancer, even when pollutant levels are below toxicity reference values. The possibility of synergistic interactions between different pollutants could explain how even low concentrations can cause major health problems. These intricate that molecular interactions can occur through a wide variety of mechanisms, and our understanding of the physiological effects of mixtures is still limited. The purpose of this paper is to discuss recent reports that address possible synergistic interactions between different types of environmental pollutants that could promote cancer development. Our literature studies suggest that key biological pathways are frequently implicated in such processes. These include increased production of reactive oxygen species, activation by cytochrome P450, and aryl hydrocarbon receptor signaling, among others. We discuss the need to understand individual pathological vulnerability not only in relation to basic genetics and gene expression, but also in terms of measurable exposure to contaminants. We also mention the need for significant improvements in future studies using a multitude of disciplines, such as the development of high‐throughput study models, better tools for quantifying pollutants in cancer patients, innovative pharmacological and toxicological studies, and high‐efficiency computer analysis, which allow us to analyze the molecular mechanisms of mixtures.
Strategies and Considerations for Least-Squares Analysis of Total Scattering Data

The process of least-squares analysis has been applied for decades in the field of crystallography. Here, we discuss the application of this process to total scattering data, primarily in the combination of least-squares Rietveld refinements and fitting of the atomic pair distribution function (PDF). While these two approaches use the same framework, the interpretation of results from least-squares fitting of PDF data should be done with caution through carefully constructed analysis approaches. We provide strategies and considerations for applying least-squares analysis to total scattering data, combining both crystallographic Rietveld and fitting of PDF data, given in context with recent examples from the literature. This perspective is aimed to be an accessible document for those new to the total scattering approach, as well as a reflective framework for the total scattering expert.