Miracle-dz/UniFAR-FTUs huggingface dataset:
Ultra-wide-bandwidth (UWB) microstrip monopole antenna using split ring resonator (SRR) structure

This paper presents a procedure to model an ultra wide-bandwidth (UWB) microstrip monopole antenna. The proposed antenna is composed of three different lengths of semi-circular shapes connected with circular disk and half circular modified ground plane. The proposed antenna has a size of 50 × 50 mm2 on a low-cost FR4 substrate. The antenna demonstrates impedance bandwidth of −10 dB extended from 1.5 to 11 GHz with discontinuous bandwidth at different interior operating bands. Two pairs of split ring resonator as metamaterial structure cells are inserted closely located from feeding transmission line of the antenna to achieve good impedance matching over the entire band of operation and improve the antenna performance. The fundamental parameters of the antenna including reflection coefficient, gain, radiation pattern and group delay are obtained and they meet the acceptable UWB antenna standard. High-frequency structure simulator ver. 14 is used as full-wave electromagnetic solver then the prototypes are fabricated and measured. Results show that the antenna is very suitable for the applications in UWB as well as wireless communication systems.
Top Down and Bottom Up Synthesized Graphene Quantum Dots As Nanothermometers For I
 n Vitro Imaging

Non-invasive temperature sensing is necessary to analyze biological processes occurring in the human body, including cellular enzyme activity, protein expression, and ion regulation. To probe temperature-sensitive processes at the nanoscale, novel luminescence nanothermometers are developed based on graphene quantum dots (GQDs) synthesized via top-down (RGQDs) and bottom-up (N-GQDs) approaches from reduced graphene oxide and glucosamine precursors, respectively. Because of their small 3–6 nm size, non-invasive optical sensitivity to temperature change, and high biocompatibility, GQDs enable biologically safe sub-cellular resolution sensing. Both GQD types exhibit temperature-sensitive yet photostable fluorescence in the visible and near-infrared for RGQDs, utilized as a sensing mechanism in this work. Distinctive linear and reversible fluorescence quenching by up to 19.3% is observed for the visible and near-infrared GQD emission in aqueous suspension from 25 °C to 49 °C. A more pronounced trend is observed with GQD nanothermometers internalized into the cytoplasm of HeLa cells as they are tested in vitro from 25 °C to 45 °C with over 40% quenching response. Our findings suggest that the temperature-dependent fluorescence quenching of bottom-up and top-down-synthesized GQDs studied in this work can serve as non-invasive reversible/photostable deterministic mechanisms for temperature sensing in microscopic sub-cellular biological environments. Figure 1
Estimate contribution of prescribed rangeland burning in Kansas to ambient PM2.5 through source apportionment with unmix receptor model

The Unmix receptor model was applied to the 2002-2014 speciated PM2.5 data from the IMPROVE site at Tallgrass National Preserve near Strong City, Kansas, to investigate the contributions of prescribed rangeland burning on local air quality. This investigation found the following five source categories that contribute to annual local ambient PM2.5: nitrate/agricultural (22%), vegetative burning (5%), secondary organic aerosol (29%), sulfate/industrial (30%), and crustal/soil (14%). In the month of April, the contributions of vegetative burning and secondary organic aerosol increased to 11% and 49%, respectively, indicating the influence of the prescribed burning season. The contribution of smoke from prescribed burning was estimated to be 1.05 g m-3 as primary aerosols and 4.03 g m-3 as secondary aerosols, which in total accounted for 42% of the average PM2.5 concentration in April.
Putative Biosynthesis of Talarodioxadione & Talarooxime from Talaromyces stipitatus

Polyesters containing 2,4-dihydroxy-6-(2-hydroxypropyl)benzoate and 3-hydroxybutyrate moieties have been isolated from many fungal species. Talaromyces stipitatus was previously reported to produce a similar polyester, talapolyester G. The complete genome sequence and the development of bioinformatics tools have enabled the discovery of the biosynthetic potential of this microorganism. Here, a putative biosynthetic gene cluster (BGC) of the polyesters encoding a highly reducing polyketide synthase (HR-PKS) and nonreducing polyketide synthase (NR-PKS), a cytochrome P450 and a regulator, was identified. Although talapolyester G does not require an oxidative step for its biosynthesis, further investigation into the secondary metabolite production of T. stipitatus resulted in isolating two new metabolites called talarodioxadione and talarooxime, in addition to three known compounds, namely 6-hydroxymellein, 15G256α and transtorine that have never been reported from this organism. Interestingly, the biosynthesis of the cyclic polyester 15G256α requires hydroxylation of an inactive methyl group and thus could be a product of the identified gene cluster. The two compounds, talarooxime and transtorine, are probably the catabolic metabolites of tryptophan through the kynurenine pathway. Tryptophan metabolism exists in almost all organisms and has been of interest to many researchers. The biosynthesis of the new oxime is proposed to involve two subsequent N-hydroxylation of 2-aminoacetophenone.
Composition of Anopheles Meigen (Diptera: Culicidae) in a peri-urban area of the Eastern Amazon

Malaria vector mosquitoes belong to the genus Anopheles Meigen. The Amazon has been changing due to economic activities such as mining, logging, agriculture, and urbanization, leading to changes in malaria transmission patterns in this region. Therefore, this study aimed to survey Anopheles species in a peri-urban area of Macapá, state of Amapá, Eastern Amazon, Brazil. Human landing catches (HLC) and Shannon light traps were used to collect Anopheles adults at three points. We screened breeding sites in all accessible water reservoirs within a 2 km radius of each collection point to collect immatures and found two species: Anopheles (Nyssorhynchus) albitarsis s.l. Lynch-Arribalzága (35.7%) and Anopheles (Nyssorhynchus) braziliensis (Chagas) (64.3%). A total of 267 winged specimens of Anopheles were collected: A. (N.) braziliensis (62.9%), Anopheles (Anopheles) mattogrossensis Lutz & Neiva (11.6%), Anopheles (Nyssorhynchus) triannulatus s.l. (Neiva & Pinto) (11.6%), A. (N.) albitarsis s.l. Lynch-Arribálzaga (6.7%), Anopheles (Nyssorhynchus) darlingi Root (5.2%), Anopheles (Anopheles) peryassui Dyar & Knab (1.5%), and Anopheles (Nyssorhynchus) nuneztovari Galbadón (0.4%). Considering that Macapá has autochthonous malaria cases, our findings can contribute to developing public health measures in this municipality, therefore helping to protect its habitants.
Trees and people determine the feeding activity of a migratory bird in an urban mega-park of Mexico city

Feeding research is relevant to comprehend wildlife use of urban systems and to guide management practices. Coupling foraging with habitat assessments is important because environmental conditions affect animal access to food, leading to variations in behaviours and the numbers of feeding individuals. Still, we have little comprehension about the foraging ecology of animals in Neotropical cities. We analyzed the feeding use of an urban mega-park by a migratory bird in Mexico City, central Mexico. We used distance sampling and hierarchical models to identify the habitat traits that determined the feeding density of the Yellow-rumped (Audubon’s) Warbler (Setophaga coronata auduboni) in the Chapultepec mega-park. Moreover, we evaluated the spatial variation of the feeding behavior of the species across the site and compared the substrates that this warbler used for foraging by utilizing a Bayesian modelling approach. We included observations from a grey area adjacent to the mega-park for comparison purposes. Our results demonstrated that the number of feeding individuals of the Yellow-rumped Warbler was determined by tree species richness and the number of pedestrians. Greater numbers of tree species might foster the diversity and availability of food resources for the warbler, whereas the number of pedestrians might increase risk perception by birds, reducing their foraging activity. The variation in the proportion of feeding occasions among the sections of Chapultepec supported the pattern associated with our feeding density analysis. The species fed most frequently on trees than in any other substrate. Thus, we showed that urban green areas provide important feeding grounds for the Yellow-rumped Warbler during the migratory period, particularly where tree species richness increases and human activity reduces. Management and restoration activities across the mega-park should be directed to foster tree species richness and mitigate the impact of human activities to enhance the feeding activity of migratory birds.
Selecting Non-Line of Sight Critical Scenarios for Connected Autonomous Vehicle Testing

The on-board sensors of connected autonomous vehicles (CAVs) are limited by their range and inability to see around corners or blind spots, otherwise known as non-line of sight scenarios (NLOS). These scenarios have the potential to be fatal (critical scenarios) as the sensors may detect an obstacle much later than the amount of time needed for the car to react. In such cases, mechanisms such as vehicular communication are required to extend the visibility range of the CAV. Despite there being a substantial body of work on the development of navigational and communication algorithms for such scenarios, there is no standard method for generating and selecting critical NLOS scenarios for testing these algorithms in a scenario-based simulation environment. This paper puts forward a novel method utilising a genetic algorithm for the selection of critical NLOS scenarios from the set of all possible NLOS scenarios in a particular road environment. The need to select critical scenarios is pertinent as the number of all possible driving scenarios generated is large and testing them against each other is time consuming, unnecessary and expensive. The selected critical scenarios are then validated for criticality by using a series of MATLAB based simulations.
Persistence of Metabolomic Changes in Patients during Post-COVID Phase: A Prospective, Observational Study

Several relatively recently published studies have shown changes in plasma metabolites in various viral diseases such as Zika, Dengue, RSV or SARS-CoV-1. The aim of this study was to analyze the metabolome profile of patients during acute COVID-19 approximately one month after the acute infection and to compare these results with healthy (SARS-CoV-2-negative) controls. The metabolome analysis was performed by NMR spectroscopy from the peripheral blood of patients and controls. The blood samples were collected on 3 different occasions (at admission, during hospitalization and on control visit after discharge from the hospital). When comparing sample groups (based on the date of acquisition) to controls, there is an indicative shift in metabolomics features based on the time passed after the first sample was taken towards controls. Based on the random forest algorithm, there is a strong discriminatory predictive value between controls and different sample groups (AUC equals 1 for controls versus samples taken at admission, Mathew correlation coefficient equals 1). Significant metabolomic changes persist in patients more than a month after acute SARS-CoV-2 infection. The random forest algorithm shows very strong discrimination (almost ideal) when comparing metabolite levels of patients in two various stages of disease and during the recovery period compared to SARS-CoV-2-negative controls.
On the Discretization of Richards Equation in Canadian Land Surface Models

ABSTRACT Both the Canadian Land Surface Scheme (CLASS) and the Soil, Vegetation, and Snow (SVS) land surface models employ a potentially problematic discretization of Richards equation for unsaturated vertical flow in the soil column. It is shown here that this discretization will always overestimate the vertical moisture gradient compared to a better-constructed first-order scheme, which under some circumstances could lead to erroneous moisture drawdown. The problem stems from an interpolation calculation on the irregularly spaced grids traditionally used by these models. While vanishing on uniform grids, this numerical error progressively worsens with increasing layer thickness differences. In this brief technical note a systematic method for developing first and higher order schemes on irregular, staggered grids is presented. To demonstrate the potential impact of the new first – order scheme, multi-year simulations of five FLUXNET sites are presented and discussed. A dramatic improvement in first layer soil moisture is found for two of the sites, which contributes to potentially significant differences in evapotranspiration. Higher order schemes are also possible but must be constructed carefully, in concert with a judicious choice of soil layer spacing in order to minimize discretization error. Given the extensive use of CLASS and SVS in Canadian environmental prediction systems, and the freedom with which users can specify soil layer thicknesses, it is recommended that modellers consider this issue carefully in their applications.
Garlic varieties and drying methods affected the physical properties, bioactive compounds and antioxidant capacity of dried garlic powder

ABSTRACT This work aimed to determine the effect of freeze drying (FD), hot air drying (HD), vacuum drying (VD), and infrared hot air drying (IRD) on the quality of two key kinds of garlic varieties (white and purple garlic). The quality including colors, bioactive compounds, and antioxidant capacities of dried garlic slices were investigated. The highest whiteness of dried white and purple garlic was found in FD treatments with its values at 87.04 and 81.89, respectively. The higher active substances contents and antioxidant capacities was found in dried purple garlic slices compared to the white ones under the same drying methods. The allicin contents in FD and IRD treated purple garlic were 2.60 and 2.67 mg/g and the total phenolic in these two samples were 5.93 and 4.33 mg/g. Meanwhile, the highest DPPH, ABTS and FRAP (6.64, 2.85 and 5.70 mmol TE/g. DW) was found in the IRD treated purple samples. Principal component analysis revealed the higher allicin contents, total phenolic contents, and antioxidant capacities in purple garlic slices compared to the white one in different drying methods. These results suggested that dried purple garlic under IRD treatment is more suitable for drying industrials than white garlic.
A Systematic Literature Review on Machine Learning Algorithms for Human Status Detection

Human status detection (HSD) is important to understand the status of users when interacting with various systems under different conditions. Recently, although various machine learning algorithms have been applied to analyze and detect human status, there are no guidelines to utilize machine learning algorithms to analyze physical, cognitive, and emotional aspects of human status. Therefore, this study aimed to investigate measures, tools, and machine learning algorithms for HSD by applying a systematic literature review method. We followed the preferred reporting items for systematic reviews and meta-analysis (PRISMA) model to answer three research questions related to the research objective. A total of 76 articles were identified using two hundred keyword combinations addressing topics under HSD in the fields of human factors and human-computer interaction (HCI). The results showed that research on HSD becomes important in industrial systems, focusing on how intelligent systems based on machine learning (ML) differ from earlier generations of automated systems, and what these differences necessarily imply for HCI to design and evaluation. The tools used to collect data for HSD on different parameters are broadly discussed. Recent HSD studies seem to focus on cognitive load and emotion, whereas prior studies have focused on the detection of physical effort. This research assists domain researchers in identifying HSD approaches using different ML algorithms that are suitable for use in their research.
Short-term prediction for Ethereum with Deep Neural Networks

The main contribution of this research is to investigate whether an Artificial Neural Network is an option to predict Ethereum cryptocurrency close price on a time constrained scenario. The ANN training time and time lagged data availability are considered as constraints on finding the fastest and the most accurate regression model using ARIMA results as a baseline. As part of the study, hourly aggregated data is processed to generate a step-ahead forecast and then processing time is compared for each architecture. Previous work related to cryptocurrency forecasting usually focus the analysis only on accuracy, and use coarser data granularity. Results have shown that convolutional neural networks over performed other architectures for accuracy and time objectives.
Políticas de igualdad de género e interseccionalidad: estrategias y claves de articulación

El objetivo de este trabajo es doble. Primero, realizar una revisión crítica de las principales estrategias de abordaje político de las desigualdades múltiples; y, segundo, identificar los puntos clave para la transversalización del marco interseccional en las políticas de igualdad de género. La metodología se basa en una revisión bibliográfica del estado de la cuestión y en el examen de distintos planes y programas de igualdad y no discriminación desarrollados en los contextos europeo y latinoamericano. Los resultados muestran las características de las principales estrategias políticas para abordar las desigualdades múltiples (unitaria expandida, múltiple e interseccional), así como sus posibilidades y limitaciones. También se evidencia la pertinencia de incorporar el enfoque interseccional en todas las fases del ciclo de las políticas (problematización, diagnóstico, diseño, procedimientos y evaluación). En conclusión, el enfoque interseccional permite acceder a colectivos y problemáticas situados en los cruces de las desigualdades, incrementando la eficiencia, equidad e inclusividad de las políticas de igualdad al acceder a cuestiones habitualmente ignoradas y subestimadas tras categorías unitarias.
Everyday life information seeking in South Korea during the COVID-19 pandemic: daily topics of information needs in social Q&A

PurposeThis study investigated information needs on COVID-19 by identifying topics discussed on social questions and answers (Q&A) about daily routines, problems, and health issues for survival. A layered model of contexts for everyday life information seeking (ELIS) was adapted for interpreting topics to better understand the contexts in which users could relate information needs.Design/methodology/approachQuestions and answers posted on Naver Knowledge-iN were collected and analyzed during the first nine months following the outbreak. Time distribution, topic modeling, and association rule mining were applied to examine the topics on COVID-19 and their temporal variation.FindingsNumerous topics related to the cognitive context (symptoms and masks) and situational contexts (international affairs, financial support, study, and work) were discovered. Topics related to social context were discussed moderately, but the number of questions on this topic increased with time. Strong associations were observed between terms related to symptoms, indicating their importance as a COVID-19 topic in health.Originality/valueThis study investigated topics of information needs using social Q&A data in which not only information inquiry but also information sharing coexist. The findings can help bridge the theory of ELIS to topic modeling in practice. The insights gained from this study can be used by information service providers for developing guidance and programs about how to survive during a pandemic.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-10-2021-0547.
ALTERNATE PRICING STRATEGIES IN CONSTRUCTION

Recent research findings on pricing strategies both in general and in construction are reviewed and explored. First%2C pricing strategy in general%2C mostly in the manufacturing industry%2C is reviewed. It includes the concepts of pricing strategy%2C predatory pricing%2C price wars%2C and price policy development. Second%2C pricing strategy in construction is explored. It includes various pricing models for bid price determination%2C such as the Friedman-Gates models%2C expected utility models%2C risk-pricing model%2C and the crew-day%2C multiple regression%2C and fuzzy-set pricing models. In conclusion%2C pricing strategies in construction are still predominantly based on a cost-based approach. More recent models try to close the gap between the models and the real life conditions of a bidder%5C%27s decision-making process. It appears that there are more problems in cost-based pricing as opposed to market-based pricing. Consequently%2C it is highly recommended that%2C alternative pricing approach such as that are closer to the proposed market-based pricing model need to be explored and developed for use in the construction industry. Abstract in Bahasa Indonesia : Pricing+strategy%2C+cost-based+pricing%2C+market-based+pricing.
Engaging Pre-Service Teachers in Interactive Social Justice-Themed Read-Alouds

Reading aloud is a time-honored tradition that has worked its way from home environments to school settings. Shared reading experiences, like read-alouds, stimulate memories and experiences as well as inspire new connections and perspectives. Even if only for a short time, read-alouds expand readers’ horizons while simultaneously making sense of their own worlds. One by one, each read aloud experience cultivates a classroom into a community of empathetic readers. In a society where social justice efforts are constantly questioned, challenged, and advocated for, it is no surprise that these conversations are making their way into schools across the country, including post-secondary institutions. Children’s literature serves as a non-threatening tool to address and discuss social justice topics that reflect the current societal climate of the United States.