Miracle-dz/UniFAR-FTUs huggingface dataset:
Risk-chasing behaviour in on-site construction decisions

Risk-chasing behaviour in on-site construction decision-making can result in illogical decisions and, thus, significant project losses. Accordingly, the authors conducted a set of experiments in order to detect the existence of such behaviour under a range of typical project conditions within a set of common situations. Fifty-three project leaders participated in the experiments by making choices framed by a set of 24 questions. Each question related to a known behavioural tendency, included the influence of an external parameter, and contained information from which expected values could be derived. Participants were well distributed by geography, age and experience. Contrary to the common perception that construction decision-makers are relentlessly risk-averse, they demonstrated risk-chasing behaviour when the decision occurred in over-budget project conditions. Younger participants were even more risk chasing in such conditions. Understanding and identifying where such behaviour occurs could ultimately lead to the development of means of avoiding the resulting losses.
Clinical, Laboratory, and Molecular Epidemiology of an Outbreak of Aseptic Meningitis Due to a Triple-Recombinant Echovirus in Ashburton, New Zealand

Here, we describe a small enterovirus outbreak including nine cases of aseptic meningitis in a New Zealand hospital in 2017. Most patients had a lymphocytic predominance in the CSF, their length of stay was short, and there were no paediatric cases or ICU admissions. VP1 genotyping revealed that the outbreak was caused by an echovirus E30 strain closely related to strains reported from the US, UK, Brazil, and Denmark. They all form a separate cluster within lineage “h”, which leads to the proposal of establishing a new lineage tentatively named “j” for this group of echovirus E30 strains. However, whole genome sequencing and reference mapping to echovirus E30 sequences showed very poor mapping of reads to the 3′ half of the genome. Further bioinformatic analysis indicated that the causative agent of this outbreak might be a mosaic triple-recombinant enterovirus composed of echovirus E6, echovirus E11, and echovirus E30 genome segments.
Forecast of Medical Costs in Health Companies Using Models Based on Advanced Analytics

Forecasting medical costs is crucial for planning, budgeting, and efficient decision making in the health industry. This paper introduces a proposal to forecast costs through techniques such as a standard model of long short-term memory (LSTM); and patient grouping through k-means clustering in the Keralty group, one of Colombia’s leading healthcare companies. It is important to highlight its implications for the prediction of cost time series in the health sector from a retrospective analysis of the information of services invoiced to health companies. It starts with the selection of sociodemographic variables related to the patient, such as age, gender and marital status, and it is complemented with health variables such as patient comorbidities (cohorts) and induced variables, such as service provision frequency and time elapsed since the last consultation (hereafter referred to as “recency”). Our results suggest that greater accuracy can be achieved by first clustering and then using LSTM networks. This implies that a correct segmentation of the population according to the usage of services represented in costs must be performed beforehand. Through the analysis, a cost projection from 1 to 3 months can be conducted, allowing a comparison with historical data. The reliability of the model is validated by different metrics such as RMSE and Adjusted R2. Overall, this study is intended to be useful for healthcare managers in developing a strategy for medical cost forecasting. We conclude that the use of analytical tools allows the organization to make informed decisions and to develop strategies for optimizing resources with the identified population.
Pressing and Rubbing: Physics-Informed Features Facilitate Haptic Terrain Classification for Legged Robots

Non-geometric hazards like sinkage and slipping, correlated to terrain categories, have an apparent effect on the locomotion of legged robots. Tactile-based terrain classification is a more accurate way to distinguish terrains in different properties than the vision, but selecting representative features instead of cumbersome ones in the complex foot-terrain interaction for efficient classification is still a challenge. In this letter, two specific leg motions are designed to inspect terrain bearing and friction properties, and manually designed features are extracted based on the foot-terrain interaction model for classification. These features are physics-informed, tidy and interpretable, and can be used with different classifiers under different foot configurations. Four classic classifiers with physics-informed features are trained for terrain classification and evaluated on our self-developed dataset. At the same time, the proposed method was compared with other two methods: an artificial feature extraction method and a CNN-based method. The results show that our proposed method reaches remarkable precision in terrain classification and can still guarantee a high accuracy under a small number of training samples.
Enduring Effect of Antibiotic Timentin Treatment on Tobacco In Vitro Shoot Growth and Microbiome Diversity

Plant in vitro cultures initiated from surface-sterilized explants often harbor complex microbial communities. Antibiotics are commonly used to decontaminate plant tissue culture or during genetic transformation; however, the effect of antibiotic treatment on the diversity of indigenous microbial populations and the consequences on the performance of tissue culture is not completely understood. Therefore, the aim of this study was to assess the effect of antibiotic treatment on the growth and stress level of tobacco (Nicotiana tabacum L.) shoots in vitro as well as the composition of the plant-associated microbiome. The study revealed that shoot cultivation on a medium supplemented with 250 mg L−1 timentin resulted in 29 ± 4% reduced biomass accumulation and a 1.2–1.6-fold higher level of oxidative stress injury compared to the control samples. Moreover, the growth properties of shoots were only partially restored after transfer to a medium without the antibiotic. Microbiome analysis of the shoot samples using multivariable region-based 16S rRNA gene sequencing revealed a diverse microbial community in the control tobacco shoots, including 59 bacterial families; however, it was largely dominated by Mycobacteriaceae. Antibiotic treatment resulted in a decline in microbial diversity (the number of families was reduced 4.5-fold) and increased domination by the Mycobacteriaceae family. These results imply that the diversity of the plant-associated microbiome might represent a significant factor contributing to the efficient propagation of in vitro tissue culture.
Townsendialemhiensis (Asteraceae, Astereae): A narrowly endemic new species from Idaho, USA

﻿Abstract Townsendialemhiensis (Asteraceae) is described from the Lemhi Valley of east-central Idaho. From a genus with weak intrinsic isolating barriers, T.lemhiensis remains distinct apparently due to apomixis and to its isolation and habitat specialization on spatially limited occurrences of ashy white soils in the Lemhi Valley. Despite similarities to T.spathulata, this new species differs in its persistent pappus, fewer series of phyllaries and sericeous rather than long woolly hairs.
LoRaWAN Technology for Internet of Things

LoRaWAN as base technology for the Internet of Things is recently treated as one of the standard technology of the global industry. LoRa Alliance with its focus on global representative corporations defines the needs of communications technology for Internet of Things and is in the process of standard development. LoRaWAN is a communications technology with a low data rate based on low-power technology, and provides a wide communication radius. Thus, LoRaWAN can be utilized in a variety of things through internet application. In June 2015, The LoRaWAN R1.0 was released, and the data transmission technology was introduced through many of LoRaWAN alliances. In this thesis, we summarized the data transmission technology standards that are expected of LoRaWAN, and the higher utilization from Internet of things applications by studying the applications of LoRaWAN.
Efficacy of Lauromacrogol Injection for Ablation of Benign Predominantly Cystic Thyroid Nodules and Related Factors: A Prospective Study

Objective To prospectively evaluate the efficacy of lauromacrogol injection for ablation (LIA) of benign predominantly cystic thyroid nodules and its related factors. Materials and Methods A total of 142 benign predominantly cystic thyroid nodules (median volume, 12.5 mL; range, 0.4–156 mL) in 137 patients (male:female sex ratio, 36:101; mean age ± standard deviation [SD], 49 ± 13 years) were treated with LIA after being confirmed as benign via cytology. The volume reduction rate (VRR) of the nodules and cosmetic score were evaluated during follow-up at 1, 3, and 6 months after treatment and every 6 months thereafter. A VRR of ≥ 50% at the 12-month follow-up was considered to indicate effective treatment. The associations between the clinical factors and nodular ultrasound features, including the initial nodule volume, proportion of solid components, vascularity grade and ineffective treatment (VRR of < 50% at the 12-month follow-up), and regrowth were analyzed. Results All patients completed follow-up for at least 12 months. The average ± SD follow-up period was 32 ± 11 months (range, 12–54 months). The effective treatment rate was 73.2% (104/142), while the regrowth rate was 12.0% (17/142) at the last follow-up. Grade 2–3 intranodular vascularity in the solid components of the nodules was the only independent factor associated with ineffective treatment, with an odds ratio (reference category, grade 0–1) of 3.054 (95% confidence interval, 1.148–8.127) (p = 0.025). Conclusion LIA is an effective treatment for predominantly cystic thyroid nodules. Grade 2–3 intranodular vascularity in the solid components of nodules is the only independent risk factor for ineffective LIA.
Factors Affecting Generation Z Attitudes and Purchase Behavior towards Buying Luxury Fashion Product

As Generation Z is aware of luxury fashion brands and started spending their money on luxury fashion products, the market of luxury fashion products was having a demographic shift in their consumer. Generation Z is becoming the potential main target in the luxury fashion industry. This study aims to identify the Generation Z attitude towards buying luxury fashion products and purchase behavior as Generation Z has unique and different behavior to other generations. Not only that, but this study also reveals the relationship between attitude, subjective norm, perceived behavioral control, and purchase intention as well as the behavior. The approach will be quantitative by using Partial-Least Square (PLS)-Structural Equation Modeling (SEM) analysis. The findings show that social media influencers, sustainability value, brand collaboration, hedonic value, and price-quality value have a positive and significant impact on Generation Z’s attitude towards buying luxury fashion products. The analysis obtained indicates that the attitudes towards buying luxury fashion give an indirect impact on Generation Z’s luxury fashion purchase behavior. The implication of the findings will become insights for luxury fashion brands as preparation for approaching Generation Z, the future biggest luxury customer.
Volatile Compound Characterization of Coffee (Coffea arabica) Processed at Different Fermentation Times Using SPME–GC–MS

Coffee is a beverage that is consumed due to its flavor and fragrance. In this investigation, we demonstrated the relations between different dry fermentation processes of coffee (aerobic, anaerobic, and atmosphere modified with CO2) and fermentation times (0, 24, 48, 72, and 96 h), with pH, acidity, and seven volatile marker compounds of coffee. Volatile compounds were extracted by solid phase microextraction (SPME) and an analysis was performed by gas chromatography–mass spectrometry (GC–MS). A significant effect (p < 0.05) between the fermentation time and a decrease in pH was demonstrated, as well as between the fermentation time and increasing acidity (p < 0.05). Acetic acid was positively correlated with the fermentation time, unlike 2-methylpyrazine, 2-furanmethanol, 2,6-dimethylpyrazine, and 5-methylfurfural, which were negatively correlated with the fermentation time. The aerobic and anaerobic fermentation treatments obtained high affinity with the seven volatile marker compounds analyzed due to the optimal environment for the development of the microorganisms that acted in this process. In contrast, in the fermentation process in an atmosphere modified with CO2, a negative affinity with the seven volatile compounds was evidenced, because this gas inactivated the development of microorganisms and inhibited their activity in the fermentation process.
The Absolute Age and Origin of the Giant Gypsum Geode of Pulpí (Almería, SE Spain)

Subaqueous gypsum (CaSO4·2H2O) crystals are relatively common in epithermal systems where sulfide ore deposits are present. The Giant Geode of Pulpí (Almería, SE Spain) hosts some of the largest (up to 2 m in length) subaqueous gypsum crystals discovered to date. Here, we present the first U-series ages of its crystals and reconstruct the oxygen and hydrogen isotopic composition (δ18O and δ2H) of the Pulpí paleo-aquifer from which the crystals formed by using stable isotopes of gypsum hydration water. We successfully dated the onset of gypsum precipitation in the Geode at 164 ± 15 ka. However, the extremely low U concentration (<11 ppb) and relatively high detrital Th content (230Th/232Th < 3.2) hinder accurate dating other gypsum samples. The δ18O and δD values of the paleo-aquifer during the growth of the crystals aligned with the local meteoric water line, suggesting that the sulfate-enriched mother solution consisted of meteoric water that recharged the aquifer during that period. The mean isotopic composition of the Pulpí paleo-aquifer (δ18O = −6.5 ± 0.1‰ and δ2H = −42.3 ± 0.5‰) during the formation of the crystals was similar to the current groundwater in this area (δ18O = −6.1 ± 0.8‰, δ2H = −42 ± 6‰). The isotopic differences observed in samples collected from distinct locations and in individual crystals were probably related to changes in the isotopic composition of the aquifer, as a consequence of varying climate that impacted on the isotopic composition of rainwater during thousands of years in this region. Our results indicated that subaqueous selenite crystals may be useful for paleo-hydrological reconstructions. However, improving the current analytical techniques for dating gypsum with low U concentrations will be essential to obtain accurate and reliable records from Quaternary gypsum cave crystals in the future.
LwMLA-NET: A Lightweight Multi-Level Attention-Based NETwork for Segmentation of COVID-19 Lungs Abnormalities From CT Images

COronaVIrus Disease 2019 (COVID-19) emerged as a global pandemic in the last two years. Typical abnormal findings in chest computed tomography (CT) images of COVID-19 patients are ground-glass opacities (GGOs) and consolidation, which signify the extent of damage caused to the lungs. The manual annotation of these abnormalities for severity analysis is complex, tedious, and time-consuming. This motivated us to develop a vision-based analysis framework for automated segmentation of lung abnormalities. We proposed a deep learning framework, namely LwMLA-NET “Lightweight Multi-Level Attention-based NETwork,” to segment GGO and consolidation. The LwMLA-NET is based on an encoder–decoder architecture where depth-wise separable convolutions are employed at each stage, making it a light-weighted framework that significantly reduces the computational cost. Another distinguishable module in LwMLA-NET is the multilevel attention (MLA) mechanism that focuses on dominant and relevant features and avoids propagation of insignificant features from the encoder to the decoder, thereby aiding faster optimization. Integrating the atrous spatial pyramid pooling (ASPP) module in the bottleneck helps to handle scale variations. The LwMLA-NET was evaluated on two databases—MedSeg and Radiopedia—and obtained F1-scores of 76.7% and 73.1%, respectively. The experimental evaluation justifies that LwMLA-NET outperforms other state-of-the-art deep learning frameworks like Attention U-Net, PSP-Net, Cople-Net, Inf-Net, and Mobile-Net V2 in terms of segmentation performance and has an acceptable generalization capability. Moreover, our team, “LwMLA-NET-Team-KDD-JU,” participated in Kaggle’s “COVID-19 CT Images Segmentation” open challenge. The performance was evaluated on a separate test set, and we obtained fourth rank on the leaderboard among 40 teams with an F1-score of 71.196%.
Risk factors for third-generation cephalosporin-resistant and extended-spectrum β-lactamase-producing Escherichia coli carriage in domestic animals of semirural parishes east of Quito, Ecuador

Extended-spectrum β-lactamase (ESBL)-producing and other antimicrobial resistant (AR) Escherichia coli threaten human and animal health worldwide. This study examined risk factors for domestic animal colonization with ceftriaxone-resistant (CR) and ESBL-producing E. coli in semirural parishes east of Quito, Ecuador, where small-scale food animal production is common. Survey data regarding household characteristics, animal care, and antimicrobial use were collected from 304 households over three sampling cycles, and 1195 environmental animal fecal samples were assessed for E. coli presence and antimicrobial susceptibility. Multivariable regression analyses were used to assess potential risk factors for CR and ESBL-producing E. coli carriage. Overall, CR and ESBL-producing E. coli were detected in 56% and 10% of all fecal samples, respectively. The odds of CR E. coli carriage were greater among dogs at households that lived within a 5 km radius of more than 5 commercial food animal facilities (OR 1.72, 95% CI 1.15–2.58) and lower among dogs living at households that used antimicrobials for their animal(s) based on veterinary/pharmacy recommendation (OR 0.18, 95% CI 0.04–0.96). Increased odds of canine ESBL-producing E. coli carriage were associated with recent antimicrobial use in any household animal (OR 2.69, 95% CI 1.02–7.10) and purchase of antimicrobials from pet food stores (OR 6.83, 95% CI 1.32–35.35). Food animals at households that owned more than 3 species (OR 0.64, 95% CI 0.42–0.97), that used antimicrobials for growth promotion (OR 0.41, 95% CI 0.19–0.89), and that obtained antimicrobials from pet food stores (OR 0.47, 95% CI 0.25–0.89) had decreased odds of CR E. coli carriage, while food animals at households with more than 5 people (OR 2.22, 95% CI 1.23–3.99) and located within 1 km of a commercial food animal facility (OR 2.57, 95% CI 1.08–6.12) had increased odds of ESBL-producing E. coli carriage. Together, these results highlight the complexity of antimicrobial resistance among domestic animals in this setting.
Experiences of social work students undertaking a remote research-based placement during a global pandemic

ABSTRACT Field education globally, has been highly disrupted by restrictions associated with COVID-19. This disruption has forced many students to engage with online learning. The current article presents a student-led co-operative inquiry exploring the experience of four social work students undertaking a remote research-based placement in regional Australia during a global pandemic. In this inquiry students’ critically self-reflected on the strengths and challenges of remote research-based placements. Despite some initial reservations, the students’ experience was positive overall. This article reports on four key themes that emerged from this inquiry: the translation of social work communication and relationship-building skills to online environments, the development of professional identity in a remote research-based placement, access to supervision in a remote context, and reflection on the experience of completing a research placement guided by the social work value of respect for persons. We conclude that undertaking a remote research placement helped forge students’ appreciation for the role of research in social work, enhanced their communication and research skills, and strengthened students’ sense of professional identity. These findings confirm remote research-based placements can offer relevant and effective placement opportunities that can inform social work field-education heutagogy as we move beyond the restrictions associated with the pandemic.
NetHCF: Filtering Spoofed IP Traffic With Programmable Switches

In this paper, we identify the opportunity of using programmable switches to improve the state of the art in spoofed IP traffic filtering, and propose <sc>NetHCF</sc>, a line-rate in-network system to filter spoofed traffic. One key challenge in the design of <sc>NetHCF</sc> is to handle the restrictions stemmed from the limited computational model and memory resources of programmable switches. We address this by decomposing the HCF scheme into two complementary parts, by aggregating the IP-to-Hop-Count (IP2HC) mapping table for efficient memory usage, and by designing adaptive mechanisms to handle routing changes, IP popularity changes, and network activity dynamics. We implement an open-source prototype of <sc>NetHCF</sc>, and conduct extensive evaluations. The evaluation results demonstrate that <sc>NetHCF</sc> is able to process most legitimate traffic in 1 <inline-formula><tex-math notation="LaTeX">$\mu$</tex-math><alternatives><mml:math><mml:mi>μ</mml:mi></mml:math><inline-graphic xlink:href="zhang-ieq1-3161015.gif"/></alternatives></inline-formula>s, filter spoofed IP traffic effectively under network dynamics, with less than 30% of switch resource occupation.
Semantic Competence Pull: A Semantics-Based Architecture for Filling Competency Gaps in Organizations

Despite its considerable growth and development during the last decades, the software industry has had to endure several significant problems and drawbacks which have undoubtedly had negative effects. One of these aspects is the lack of alignment between the curricula offered by Universities and other kinds of education and training centres and the professional profiles demanded by companies and organizations. This problem defines the objective of this work: to provide a set of mechanisms and a solution to allow companies to define and express their competency gaps and, at the same time, allow education centres to analyse those gaps and define the training plans to meet those needs.
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