Miracle-dz/UniFAR-FTUs huggingface dataset:
Design of a broadband diplexer based on substrate integrated plasmonic waveguide

In this article, a new wideband diplexer for microwave frequencies is proposed. This diplexer is designed based on the combination of spoof surface plasmon polariton structures with substrate integrated waveguide (SIW) structures. In the proposed diplexer, bandpass filters were designed within a frequency range of 6–9.2 GHz (bandwidth of 40%) and 11.7–16.2 Hz (bandwidth of 29%) by creating rectangular grooves on the top and bottom of the metallic layers of the SIW. These grooves generate surface plasmon waves in the SIW structure that limit the dispersion curve to an asymptotic frequency and cause a high cut‐off frequency. The low cut‐off frequency of the filters is determined by the SIW dimensions. Moreover, the two filters were fed using a microstrip T‐junction with stepped impedance transformation. By optimizing the feed lines, the electromagnetic waves in each working band are directed to the filter of that band, and finally, the filters create a proper attenuation outside the band. A sample of the diplexer is fabricated and tested to verify the design. The simulation results are in good agreement with the experimental results. This diplexer can be a good candidate in microwave frequencies for telecommunication systems.
TDG interacts with DNMT3A to inhibit the migration and invasion of human colon cancer cells

Background Colorectal cancer (CRC) is one of the most common malignant tumors with high recurrence and mortality. Thymine DNA glycosylase (TDG) is one of the key molecules involved in base excision repair pathway. Recently, more and more attentions have been paid to the role of TDG on tumor development. However, the specific functions of TDG in CRC remain unclear. Methods The biological functions of TDG and DNA methyltransferase 3 alpha (DNMT3A) in CRC were evaluated using migration and invasion assay. Tumor metastasis assay was performed in nude mice to detect the role of TDG in vivo. The interaction of TDG with DNMT3A was determined by co-immunoprecipitation (Co-IP). Chromatin immunoprecipitation analysis (CHIP) was applied to predict the DNA binding site of DNMT3A. We also performed methylation-specific PCR (MSP) to detect the changes in TIMP2 methylation levels. Results We found that TDG could inhibit the migration and invasion of human colon cancer cells in vitro and in vivo. TDG promoted the ubiquitination and degradation of DNMT3A by binding with it. Interference with siDNMT3A also inhibited the migration and invasion of human colon cancer cells. Further ChIP, MSP, and rescue experiments data confirmed that TDG accelerated the degradation of DNMT3A, and then significantly regulated the transcription and expression of TIMP2, thereby affecting the migration and invasion of human colon cancer cells. Conclusion Our findings reveal that TDG inhibit the migration and invasion of human colon cancer cells through DNMT3A-TIMP2 axis which may be potential therapeutic strategies in the development and treatment of CRC.
Context-aware assistive driving: an overview of techniques for mitigating the risks of driver in real-time driving environment

Purpose This study aims to analyze driver risks in the driving environment. A complete analysis of context aware assistive driving techniques. Context awareness in assistive driving by probabilistic modeling techniques. Advanced techniques using Spatio-temporal techniques, computer vision and deep learning techniques. Design/methodology/approach Autonomous vehicles have been aimed to increase driver safety by introducing vehicle control from the driver to Advanced Driver Assistance Systems (ADAS). The core objective of these systems is to cut down on road accidents by helping the user in various ways. Early anticipation of a particular action would give a prior benefit to the driver to successfully handle the dangers on the road. In this paper, the advancements that have taken place in the use of multi-modal machine learning for assistive driving systems are surveyed. The aim is to help elucidate the recent progress and techniques in the field while also identifying the scope for further research and improvement. The authors take an overview of context-aware driver assistance systems that alert drivers in case of maneuvers by taking advantage of multi-modal human processing to better safety and drivability. Findings There has been a huge improvement and investment in ADAS being a key concept for road safety. In such applications, data is processed and information is extracted from multiple data sources, thus requiring training of machine learning algorithms in a multi-modal style. The domain is fast gaining traction owing to its applications across multiple disciplines with crucial gains. Research limitations/implications The research is focused on deep learning and computer vision-based techniques to generate a context for assistive driving and it would definitely adopt by the ADAS manufacturers. Social implications As context-aware assistive driving would work in real-time and it would save the lives of many drivers, pedestrians. Originality/value This paper provides an understanding of context-aware deep learning frameworks for assistive driving. The research is mainly focused on deep learning and computer vision-based techniques to generate a context for assistive driving. It incorporates the latest state-of-the-art techniques using suitable driving context and the driver is alerted. Many automobile manufacturing companies and researchers would refer to this study for their enhancements.
Geotourism Destinations Online Branding Co-Creation

The application of brand theory to destinations has grown in the last few decades, with the destination brand personality being a viable metaphor for creating and positioning destination brands. An often-overlooked tourism typology is geotourism; more specifically, volcanic tourism, since it can be a passive element of any tourism form or active nature tourism. However, its potential is relatively unexplored in terms of online branding. For this reason, the present study analyzes online brand image co-creation, using 300 websites related to three unique volcanic tourism destinations—Iceland, the Azores, and the Canary Islands. Three different types of sources (destination marketing organizations, commercial, and editorial websites) created these contents. The results demonstrate significant differences between the communication of the three destinations, with Iceland, where there is less aligned communication, most valuing geo elements in their communication, and the Azores, where all stakeholders communicate similar brand personality traits, displaying more aligned communication regarding brand personality. In the Canary Islands geotourism is less explored as a destination offer and is consequently less communicated. Acknowledging the different brand positioning and the parity and differentiation points among destinations with the same baseline offer—volcanic tourism—can be helpful for destination brand managers to reignite tourism and promote a unique tourism experience.
ESTUDO SOBRE AS RESPOSTAS INTRACELULARES AO ESTRESSE ETANÓLICO EM KLUYVEROMYCES MARXIANUS CCT7735

A producao do etanol como combustivel e uma alternativa promissora a utilizacao dos combustiveis fosseis. Nesse contexto, os residuos agroindustriais tem despontado como materias-primas capazes de aumentar a producao de etanol sem competir com a producao de alimentos. Assim, tanto o soro de queijo, quanto subprodutos lignocelulosicos podem ser utilizados como substratos para a producao de etanol. No entanto, a levedura Saccharomyces cerevisiae e incapaz de metabolizar a lactose presente no soro de queijo e de crescer nas elevadas temperaturas requeridas no processo de Sacarificacao e Fermentacao Simultâneas (SSF) de biomassa lignocelulosica. Por outro lado, Kluyveromyces marxianus CCT 7735 fermenta lactose e cresce em altas temperaturas. Todavia, esta levedura tem o seu crescimento inibido em altas concentracoes de etanol. Em S. cerevisiae as respostas adaptativas ao etanol envolvem varias proteinas e metabolitos, porem em K. marxianus CCT7735 elas sao desconhecidas. Contudo, a analise dos mecanismos envolvidos na tolerância ao etanol descritos na literatura tem contribuido para o entendimento das respostas moleculares ao estresse etanolico em K. marxianus CCT 7735 .
The effects of dispersal on spatial synchrony in metapopulations differ by timescale

Understanding the processes that stabilize species populations is a fundamental question in ecology and central to conservation biology. In metapopulations, dispersal can act as a ‘double edged’ sword for species stability by simultaneously decreasing local population variability (thereby decreasing local extinction risk) while increasing spatial synchrony (thereby increasing landscape-level extinction risk). These dynamics may operate at different timescales, complicating efforts to assess their relative importance for long-term stability. Here, we use a simple metapopulation model to understand how dispersal affects population variability and spatial synchrony across timescales. Our model shows that dispersal has contrasting effects at short versus long timescales on the variability and synchrony of populations. For populations that exhibit slow recovery when perturbed (i.e. under-compensatory growth), dispersal decreases local population variability while increasing spatial synchrony at long timescales. In contrast, at short timescales dispersal increases local population variability while decreasing spatial synchrony. For populations that recover via damped oscillation when perturbed (i.e. over-compensatory growth), the effects of dispersal are all opposite to those for populations with under-compensatory growth, at both short and long timescales. The timescale-dependent effect of dispersal has important implications for empirical studies. Specifically, studies conducted over short periods may only observe population variability increasing and spatial synchrony decreasing with dispersal, whereas the opposite patterns may predominate over longer periods. Our results provide novel insights on the dynamics underlying the role of dispersal and highlight the importance of time series length in empirical studies of metapopulations.
Nanoscale Positioning Approaches for Integrating Single Solid‐State Quantum Emitters with Photonic Nanostructures

Deterministically integrating single solid‐state quantum emitters with photonic nanostructures serves as a key enabling resource in the context of photonic quantum technology. Due to the random spatial location of many widely‐used solid‐state quantum emitters, a number of positioning approaches for locating the quantum emitters before nanofabrication have been explored in the last decade. Here, the working principles of several nanoscale positioning methods and the most recent progress in this field, covering techniques including atomic force microscopy, scanning electron microscopy, confocal microscopy with in situ lithography, and wide‐field fluorescence imaging are reviewed. A selection of representative device demonstrations with high‐performance is presented, including high‐quality single‐photon sources, bright entangled‐photon pairs, strongly‐coupled cavity QED systems, and other emerging applications. The challenges in applying positioning techniques to different material systems and opportunities for using these approaches for realizing large‐scale quantum photonic devices are discussed.
Theoretical contributions to the investigation of educational effectiveness: towards a dilemmatic approach

ABSTRACT The study of educational effectiveness has become increasingly complex. Alongside methodological advancements in the investigation and measurement of educational effectiveness, meta-analyses conducted by leading researchers have shown that the field has been suffering from a significant lack of theory or from a weak theoretical basis. The present paper seeks to address this gap by connecting the four models of organisational effectiveness incorporated in Quinn and Rohrbaugh’s framework of competing values to the four dualities of educational design that appear in Wenger’s theory of communities of practice. By doing so, the paper contributes theoretical insights towards the development of a dilemmatic approach to the study of educational effectiveness. Based on the theoretical insights offered here, the paper argues that effective educational organisations are those that are able to address successfully and on an ongoing basis paradoxical tensions and incorporate interrelated and yet contradictory elements of the educational process and school organisation.
Mauritians and Latter-Day Saints: Multicultural Oral Histories of The Church of Jesus Christ of Latter-Day Saints within “The Rainbow Nation”

The Church of Jesus Christ of Latter-day Saints emerged within the Mauritian landscape in the early 1980s after the arrival of foreign missionary work. With a population of Indian, African, Chinese, French heritage, and other mixed ethnicities, Mauritius celebrates multiculturalism, with many calling it the “rainbow nation”. Religiously, Hinduism dominates the scene on the island, followed by Christianity (with Catholicism as the majority); the small remainder of the population observes Islam or Buddhism. Although Mauritian society equally embraces people from these ethnic groups, it also has historically marginalized communities who represent a “hybrid” of the mentioned demographic groups. This article, based on ethnographic research, explores the experiences of Mauritian Latter-day Saints as they navigate the challenges and implications of membership in Mormonism. Specifically, it focuses on how US-based Mormonism has come to embrace the cultural heritage of people from the various diaspora and how Mauritian Latter-day Saints perceive their own belonging and space-making within an American born religion. This case study presents how the local and intersecting adaptations of language, race, and local leadership within a cosmopolitan society such as Mauritius have led to the partial hybridization of the Church into the hegemony of ethnic communities within Mauritian Latter-day Saint practices. These merging of cultures and world views prompts both positive and challenging religious experiences for Mauritian Church members. This article illustrates the implications and pressures of the Church trying to globalize its faith base while adapting its traditionally Anglocentric approaches to religious practices to multiracial, multicultural cosmopolitan communities such as Mauritius.
The moderating role of R&D intensity on the association between external embeddedness and subsidiary product innovation: evidence from Vietnam

ABSTRACT Drawing on the business network theory and the resource-based view, we investigate the moderating role of R&D intensity on the relationship between subsidiaries’ external embeddedness in a host country and the probability of subsidiary product innovation. Using data from 402 subsidiaries located in Vietnam, the Probit regression results revealed that the higher the subsidiary’s embeddedness with local sales and local input suppliers in a transition economy, the higher the probability that it will achieve product innovation. R&D intensity positively moderates such associations. Our finding extends the argument of the business network theory by stressing the need of MNEs to use their foreign subsidiaries in transition economies to gain local knowledge and other resources from local sales agents and local input suppliers; they can do so by embedding themselves into the environment and simultaneously using these sources and internal resources to strengthen their product innovation possibilities.
Choosing the right molecular machine learning potential

Quantum-chemistry simulations based on potential energy surfaces of molecules provide invaluable insight into the physicochemical processes at the atomistic level and yield such important observables as reaction rates and spectra. Machine learning potentials promise to significantly reduce the computational cost and hence enable otherwise unfeasible simulations. However, the surging number of such potentials begs the question of which one to choose or whether we still need to develop yet another one. Here, we address this question by evaluating the performance of popular machine learning potentials in terms of accuracy and computational cost. In addition, we deliver structured information for non-specialists in machine learning to guide them through the maze of acronyms, recognize each potential's main features, and judge what they could expect from each one.
NORA3: A Nonhydrostatic High-Resolution Hindcast of the North Sea, the Norwegian Sea, and the Barents Sea

The 3-km Norwegian Reanalysis (NORA3) is a 15-yr mesoscale-permitting atmospheric hindcast of the North Sea, the Norwegian Sea, and the Barents Sea. With a horizontal resolution of 3 km, the nonhydrostatic numerical weather prediction model HARMONIE–AROME runs explicitly resolved deep convection and yields hindcast fields that realistically downscale the ERA5 reanalysis. The wind field is much improved relative to its host analysis, in particular in mountainous areas and along the improved grid-resolving coastlines. NORA3 also performs much better than the earlier hydrostatic 10-km Norwegian Hindcast Archive (NORA10) in complex terrain. NORA3 recreates the detailed structures of mesoscale cyclones with sharp gradients in wind and with clear frontal structures, which are particularly important when modeling polar lows. In extratropical windstorms, NORA3 exhibits significantly higher maximum wind speeds and compares much better to observed maximum wind than do NORA10 and ERA5. The activity of the model is much more realistic than that of NORA10 and ERA5, both over the ocean and in complex terrain.
Device-to-Device Aided Cooperative NOMA Transmission Exploiting Overheard Signal

A novel device-to-device (D2D) aided cooperative non-orthogonal multiple access (NOMA) scheme (termed as D2D-SG-NOMA) is proposed, where two similar gain (SG) near users (NUs) with the capability of D2D communication and one far user (FU) are served within two time slots. The NOMA pair is formed with a NU and the FU. The paired NU is employed as a decode-and-forward relay to assist FU. Contrarily, the unpaired NU can receive signals simultaneously from the base station (BS) and the other NU during the second time slot. Two different scenarios (i.e., S1 and S2) are investigated insightfully. In S1, the direct link between the BS and FU does not exist, whereas the direct link between the BS and FU exists in S2. The delay-tolerant capacity (DTC), outage probability, diversity order, and delay-limited capacity are investigated along with analytical formulation. The D2D-SG-NOMA achieves an increase of around 66% and 85% in DTC at 0 dB signal-to-noise (SNR) under S1 and S2, respectively than the existing NOMA scheme with successive relaying (termed as SR-NOMA). Contrarily, a reduced DTC improvement (i.e., around 3% and 10% in S1 and S2, respectively) is obtained at 40 dB SNR due to increased inter-symbol interference.
Physicochemical analysis of apple and grape pomaces

This study details a comprehensive analysis of apple and grape pomaces that were generated in the course of juice and wine production, respectively. An extensive physicochemical analysis of these pomaces was performed to determine the elemental composition, ash content, sugar profile, and lignocellulose content. Scanning electron microscopy (SEM) images were taken to examine the morphology of the pomaces. Thermal stability was also examined using thermogravimetric analysis (TGA). Infrared spectroscopy was performed to observe the functional groups on the surfaces of the pomace samples. Grape pomace (GP) had better thermal stability than apple pomace (AP), but washing AP improved its thermal stability. The results from this study provide crucial information for various value-added applications of both apple and grape pomaces, especially for applications which are temperature-dependent. The diversion of these materials from waste back into the economic stream can alleviate their environmental burden and promote sustainable product development.
Forecasting Vegetation Condition with a Bayesian Auto-regressive Distributed Lags (BARDL) Model

Abstract. Droughts form a large part of climate/weather-related disasters reported globally. In Africa, pastoralists living in the Arid and Semi-Arid Lands (ASALs) are the worse affected. Prolonged dry spells that cause vegetation stress in these regions have resulted in the loss of income and livelihoods. To curb this, global initiatives like the Paris Agreement and the United Nations recognised the need to establish Early Warning Systems (EWS) to save lives and livelihoods. Existing EWS use a combination of Satellite Earth Observation (EO) based biophysical indicators like the Vegetation Condition Index (VCI) and socio-economic factors to measure and monitor droughts. Most of these EWS rely on expert knowledge in estimating upcoming drought conditions without using forecast models. Recent research has shown that the use of robust algorithms like Auto-Regression, Gaussian Processes and Artificial Neural Networks can provide very skilled models for forecasting vegetation condition at short to medium range lead times. However, to enable preparedness for early action, forecasts with a longer lead time are needed. The objective of this research work is to develop models that forecast vegetation conditions at longer lead times on the premise that vegetation condition is controlled by factors like precipitation and soil moisture. To achieve this, we used a Bayesian Auto-Regressive Distributed Lag (BARDL) modelling approach which enabled us to factor in lagged information from Precipitation and Soil moisture levels into our VCI forecast model. The results showed a ∼2-week gain in the forecast range compared to the univariate AR model used as a baseline. The R2 scores for the Bayesian ARDL model were 0.94, 0.85 and 0.74, compared to the AR model's R2 of 0.88, 0.77 and 0.65 for 6, 8 and 10 weeks lead time respectively.
Fabrication of SA-SiO2 capsules with 3D microscopic re-entrant structures via one-step titration-gel method for the removal of methylene blue from water

In this paper, the eco-friendly sodium alginate-silicon oxide capsule (SASC) with a brilliantly wide pH tolerance property was obtained via the one-step titration-gel method and in-situ sol-gel progress. The spherical droplets with SA and tetraethyl orthosilicate (TEOS) casting mixture were directly injected into the calcium chloride (CaCl 2 ) solution. The effects of SiO 2 nanoparticles (SiO 2 NPs) on the morphology and adsorptive properties of the capsules were investigated. The interface of the SASC with micro-porous fracture aperture and microscopic re-entrant structures help to provide a stronger interaction between MB and surface channel thus increased its removed capacity during the courses of adsorption. The maximum absorption amount of the SASC against methylene blue (MB) was found to be 350.80 mg/g at 25°C and the solution pH value of 8, which had a 12.82% enhancement compared with the neat capsule. The adsorptive performance of the prepared capsules was literally fitted the pseudo-second-order kinetic equation and Langmuir absorption isothermal model. Moreover, the pH of the MB solution was evidently declined after adsorption, indicating that the adsorption mechanism of the capsules against MB might be dominated by ion-exchange and electrostatic attraction. This facile method which was used to generate free-standing spherical support structures with specialized morphology might be more suitable for removing cationic pollutants from alkaline wastewater.