Miracle-dz/UniFAR-FTUs huggingface dataset:
Understanding knowledge management and upskilling in Fourth Industrial Revolution: transformational shift and SECI model

Purpose The adoption of knowledge management (KM) to steer new skills and capabilities among people provides evidence that KM not only offers competitive advantages but also provides a means for organisational survival, by improvising core capabilities or generate new ones that can drive people in the Fourth Industrial Revolution (4IR) era. This paperaim to identify critical new skills and capabilities among people within an organisation to stay competitive, innovative and relevant. Design/methodology/approach The paper presents the findings on new skills assessment for Fourth Industrial Revolution. The study was carried out through an interview with a focus group discussion technique to gather data on the role of KM in creating new set of skills or capabilities in Fourth Industrial Revolution’s landscape. The study also reports a bibliographic study of critical skills based on more than a decade of related academic and industry publications to portray research trends and future directions. Findings There is a demand in “must-have” skills related to Industry 4.0 such as capability for complex decision-making, complex problem-solving, collaborative innovation, project management, creativity and critical thinking, social skill and social responsibility. While these skills are critical enablers to aiding individuals in the scenarios of plausible 4IR futures, several important new research trends that emerge have also not been adequately explored including KM and Industry 4.0 skill gap, skill evolution, machine knowledge, intuitive decision-making, rational decision-making, technostress, digital fluency, collaborative innovation, industrial policies, human–machine interaction and societal systems. Research limitations/implications This research provides a roadmap for the next research trends and topics in the area of Fourth Industrial Revolution and new skills requirements. The study discusses some of the essential issues and challenges with upskilling required for Industry 4.0. It also focuses on how upskilling learning initiatives influence new knowledge creation. This primarily contributes to the educational field in deciding how and when to adopt appropriate strategies and identify which initiatives to best meet the needs of its community. Practical implications KM enables individuals to utilise their existing core capabilities or generate new ones for immediate investment in upskilling to meet current and future skills needs required by an organisation. Simply put, KM will improve the organisation’s talent-driven learning strategy and increase individuals’ ability to learn faster and attain sustainable competitive advantage in a fast-paced ever changing environment. Originality/value This paper is useful to academics, practitioners and policymakers in the fields of KM. The research provides initial insight into new skills mapping in the context of Fourth Industrial Revolution and the needs for researchers to understand the recent research trends in KM.
Performance Evaluation of SOCA-CFAR Detectors in Weibull-Distributed Clutter Environments

In this letter, we derive a novel exact expression for the probability of false alarm (PFA) and an approximate closed-form solution for the probability of detection (PD) of a smallest of cell-averaging constant false alarm rate (SOCA-CFAR) detector operating over Weibull-distributed clutter. For the analysis, we consider an exponentially distributed target and allow arbitrary values for the shape parameter of clutter interference. To the best of our knowledge, there are no exact or approximate performance evaluations for an SOCA-CFAR detector considering arbitrary values for the shape parameter of the Weibull interference samples (i.e., different from 1) contained within the CFAR window. Therefore, our analytical derivations generalize previous performance evaluation studies and take a small step toward a better understanding of more realistic SOCA-CFAR detectors. Moreover, we obtain exact formulations for the probability density function (PDF) and the cumulative distribution function (CDF) for a minimum of two sums of independent and identically distributed (i.i.d.) Weibull random variables. Numerical results indicate that the system performance improves as the shape parameter of the Weibull interference increases. The validity of all our expressions is confirmed via Monte Carlo simulations.
HPV E1 qPCR, a Low-Cost Alternative Assay to Roche Diagnostic Linear Array is Effective in Identifying Women at Risk for Developing Cervical Cancer

Objective Since a quantitative polymerase chain reaction (qPCR) assay targeting the E1 region of HPV genome is cost-effective/simple to perform, we evaluated the agreement between the Roche Diagnostics Linear Array (RDLA) genotyping test and qPCR-based E1 assay to detect HR-HPV genotypes that are included or not included in HPV vaccines and compared their accuracy to detect CIN 2+. Methods Study population included 257 African American (AA) and 266 Caucasian American (CA) diagnosed with intraepithelial neoplasia (CIN) grades ≤CIN 1 or ≥CIN 2 (CIN 2+) and tested for HPV by the RDLA and E1 assay. The concordance was determined using Gwet’s AC1. The calculated positive predictive value (PPV) and negative predictive value (NPV) of the two assays were used to determine their suitability to detect CIN lesions. Results Overall, the E1 assay showed substantial agreement with the RDLA assay to detect any HR-HPV genotype and the agreement was higher in women diagnosed with CIN 2+ than ≤CIN 1. The concordance was largely higher in Cas than in Aas. The NPV and PPV values to detect CIN lesions were similar between the two assays. Conclusion Utilization of the HPV E1 assay as a tool for CC screening could be a cost-effective approach that applies to both vaccinated and unvaccinated populations.
Curcumin ameliorates H 2O 2-induced injury through SIRT1-PERK-CHOP pathway in pancreatic beta cells

Oxidative stress and endoplasmic reticulum (ER) stress play crucial roles in pancreatic β cell destruction, leading to the development and progression of type 1 diabetes mellitus (T1DM). Curcumin, extracted from plant turmeric, possesses multiple bioactivities such as antioxidant, anti-inflammatory and anti-apoptosis properties in vitro and in vivo. However, it remains unknown whether curcumin improves ER stress to prevent β cells from apoptosis. In this study, we aim to investigate the role and mechanism of curcumin in ameliorating H 2O 2-induced injury in MIN6 (a mouse insulinoma cell line) cells. Cell viability is examined by CCK8 assay. Hoechst 33258 staining, TUNEL and flow cytometric assay are performed to detect cell apoptosis. The relative amounts of reactive oxygen species (ROS) are measured by DCFH-DA. WST-8 is used to determine the total superoxide dismutase (SOD) activity. Protein expressions are determined by western blot analysis and immunofluorescence staining. Pretreatment with curcumin prevents MIN6 cells from H 2O 2-induced cell apoptosis. Curcumin decreases ROS generation and inhibits protein kinase like ER kinase (PERK)-C/EBP homologous protein (CHOP) signaling axis, one of the critical branches of ER stress pathway. Moreover, incubation with curcumin activates silent information regulator 1 (SIRT1) expression and subsequently decreases the expression of CHOP. Additionally, EX527, a specific inhibitor of SIRT1, blocks the protective effect of curcumin on MIN6 cells exposed to H 2O 2. In sum, curcumin inhibits the PERK-CHOP pathway of ER stress mediated by SIRT1 and thus ameliorates H 2O 2-induced MIN6 cell apoptosis, suggesting that curcumin and SIRT1 may provide a potential therapeutic approach for T1DM.
Craft industries and ribbon development: place change along the Colombo-Kandy Road, Sri Lanka

ABSTRACT Craft industries are an increasingly significant component of economic and social life in many Asian countries. However, their unique forms are not well documented. Future development may be harmed by importing concepts from western creative industries, which exhibit different histories and spatial dynamics. Unlike western urban craft industries, South and East Asian craft industries assume a distinct morphological pattern of ‘craft ribbon development’ in peri-urban areas. This article examines the spatial attributes of craft ribbon development in three craft industries in Sri Lanka- Pilimathalawa Brass, Molagoda Pottery, and Wewaldeniya Cane industry. We frame craft ribbon development in three historical phases associated with the country's distinct socio-economic changes. Surveys and semi-structured interviews were carried out to trace the changes in land uses and building typologies. Each case shows significant visual morphological transformation with the surrounding area, and that land-use change was accelerated subsequent to the introduction of market-oriented reform policies.
Assessment of the hepatorenal and hematological parameters of rats exposed to graded doses of lysine acetylsalicylate

Lysine acetylsalicylate (LAS) is an analgesic used for the prevention of cardiovascular disease with few adverse though its effect on the hepatorenal and hematological parameters remains unclear. 45 mature male Wistar rats were equally divided into three groups. Group I, II, and III received daily intramuscular doses of 0.25 mL saline, 40, and 80 mg/kg b. wt. of LAS respectively for 2-weeks. After 2, 4, and 8 weeks from beginning of drug administration, 5 rats/group were assessed for hepatorenal function, complete blood-count, and histopathological findings of liver and kidney. LAS induced a significant increase (p ≤ 0.05) in serum levels of aspartate aminotransferase, alanine aminotransferase, urea, and creatinine in a dose-dependent manner, but a significant decrease (p ≤ 0.05) observed in the hematological parameters. Histopathological alterations were a dose-dependent manner, and persisted for 8-weeks at the higher dose. In conclusion, LAS induced reversible deleterious effects on hepatorenal functions and various hematological parameters in a dose-dependent manner.
How Pandemic Films Help Us Understand Outbreaks: Implications for Futures and Foresight

We analyzed 30 pandemic films and developed a processual model to explain the social-level coping mechanisms to confront pandemics as portrayed in films. The model describes the underlying collective understanding of disease outbreaks. The model suggests that pandemic films divide the disease outbreak into three phases: emergence, transmission, and termination. Concurrently, three social processes tend to be activated to cope with the pandemic: healthcare, political, and public awareness. This model is used to compare the social imaginary reflected in films with the current COVID-19 outbreak. The resemblance of the model and the current outbreak suggests that fictional pandemic films may still follow our collective understanding of the pandemic dynamics. Four scenarios are suggested as road maps for futures and foresight practice concerned with future pandemic outbreaks.
Inventarisasi Jenis dan Distribusi Habitat Rotan pada Hutan Dataran Tinggi dan Dataran Rendah di Kalimantan Selatan

Rattans are spiny climbing palms in the Old World tropics and subtropics. Some species are the source of cane for the cane furniture industry in Indonesia. The large number of rattan species and their wide geographical range is matched by great ecological diversity. The restriction of rattan species to different climatic zones and altitudinal range suggests that these species may have precise climatic requirements and also altitudes. The research was conducted on upland and lowland of natural forest in South Kalimantan. The data collection used survey with transect method. Volume of rattans in upland forest was relatively lower than lowland forest. In altitudinal range in South Kalimantan, rattans were found from sea-level up to 870 m, the highest altitude record being held by Calamus javensis, Daemonorops micracantha, Calamus pilocellus, and Calamus sp. (rotan tunggal). While the lowest altitude record was occupied by Calamus trachycoleus. Rattans in natural forest require light intensity, humidity and temperature were 18– 65%, 60 – 70%, 28 – 33oC, respectively.
Magnetic anisotropy of the van der Waals ferromagnet 
Cr2Ge2Te6
 studied by angular-dependent x-ray magnetic circular dichroism

The van der Waals ferromagnet Cr$_2$Ge$_2$Te$_6$ (CGT) has a two-dimensional crystal structure where each layer is stacked through van der Waals force. We have investigated the nature of the ferromagnetism and the weak perpendicular magnetic anisotropy (PMA) of CGT by means of X-ray absorption spectroscopy and X-ray magnetic circular dichroism (XMCD) studies of CGT single crystals. The XMCD spectra at the Cr $L_{2,3}$ edge for different magnetic field directions were analyzed on the basis of the cluster-model multiplet calculation. The Cr valence is confirmed to be 3+ and the orbital magnetic moment is found to be nearly quenched, as expected for the high-spin $t_{2g}$$^3$ configuration of the Cr$^{3+}$ ion. A large ($\sim 0.2$ eV) trigonal crystal-field splitting of the $t_{2g}$ level caused by the distortion of the CrTe$_6$ octahedron has been revealed, while the single-ion anisotropy (SIA) of the Cr atom is found to have a sign {\it opposite} to the observed PMA and too weak compared to the reported anisotropy energy. The present result suggests that anisotropic exchange coupling between the Cr atoms through the ligand Te $5p$ orbitals having strong spin-orbit coupling has to be invoked to explain the weak PMA of CGT, as in the case of the strong PMA of CrI$_3$.
A proof-of-concept study on mortality prediction with machine learning algorithms using burn intensive care data

Introduction Burn injuries are a common traumatic injury. Large burns have high mortality requiring intensive care and accurate mortality predictions. To assess if machine learning (ML) could improve predictions, ML algorithms were tested and compared with the original and revised Baux score. Methods Admission data and mortality outcomes were collected from patients at Uppsala University Hospital Burn Centre from 2002 to 2019. Prognostic variables were selected, ML algorithms trained and predictions assessed by analysis of the area under the receiver operating characteristic curve (AUC). Comparison was made with Baux scores using DeLong test Results A total of 17 prognostic variables were selected from 92 patients. AUCs in leave-one-out cross-validation for a decision tree model, an extreme boosting model, a random forest model, a support-vector machine (SVM) model and a generalised linear regression model (GLM) were 0.83 (95% confidence interval [CI] = 0.72–0.94), 0.92 (95% CI = 0.84–1), 0.92 (95% CI = 0.84–1), 0.92 (95% CI = 0.84–1) and 0.84 (95% CI = 0.74–0.94), respectively. AUCs for the Baux score and revised Baux score were 0.85 (95% CI = 0.75–0.95) and 0.84 (95% CI = 0.74–0.94). No significant differences were observed when comparing ML algorithms with Baux score and revised Baux score. Secondary variable selection was made to analyse model performance. Conclusion This proof-of-concept study showed initial credibility in using ML algorithms to predict mortality in burn patients. The sample size was small and future studies are needed with larger sample sizes, further variable selections and prospective testing of the algorithms. Lay Summary Burn injuries are one of the most common traumatic injuries especially in countries with limited prevention and healthcare resources. To treat a patient with large burns who has been admitted to an intensive care unit, it is often necessary to assess the risk of a fatal outcome. Physicians traditionally use simplified scores to calculate risks. One commonly used score, the Baux score, uses age of the patient and the size of the burn to predict the risk of death. Adding the factor of inhalation injury, the score is then called the revised Baux score. However, there are a number of additional causes that can influence the risk of fatal outcomes that Baux scores do not take into account. Machine learning is a method of data modelling where the system learns to predict outcomes based on previous cases and is a branch of artificial intelligence. In this study we evaluated several machine learning methods for outcome prediction in patients admitted for burn injury. We gathered data on 93 patients at admission to the intensive care unit and our experiments show that machine learning methods can reach an accuracy comparable with Baux scores in calculating the risk of fatal outcomes. This study represents a proof of principle and future studies on larger patient series are required to verify our results as well as to evaluate the methods on patients in real-life situations.
3D Urban Buildings Extraction Based on Airborne LiDAR and Photogrammetric Point Cloud Fusion According to U-Net Deep Learning Model Segmentation

The LiDAR and photogrammetric point clouds fusion procedure for building extraction according to U-Net deep learning model segmentation is provided and tested. Firstly, an initial geo-localization process is performed for photogrammetric point clouds generated using structure-from-motion and dense-matching methods. Then, point cloud segmentation is carried out based on U-Net deep learning model. The precision of the U-Net model for buildings extraction reachs 87%, with F-score of 0.89 and IoU of 0.80. It is shown that the U-Net method is effective for high-resolution image extraction. The detailed information can accurately be identified and extracted, such as vegetation located between buildings and roads. After segmentation, each chunk of the LiDAR and photogrammetric point clouds are finely registered and merged based on the iterative closest point algorithm. Finally, the fused point clouds are obtained. It shows that the structure and shape of the buildings could be delineated from the fused point clouds when both enough ground points and a higher point density are available. Furthermore, color information improves both visualization effect and properties identification. The experiments are conducted to extract individual buildings from three types of point clouds in three plots. A DoN (Difference of Normals) approach is used to isolate 3D buildings from other objects in densely built-up areas. It shows that most building extraction results have a Precision > 0.9 and favorable Recall and F-score values. Although the LiDAR extraction results have some advantages over the photogrammetric and fused ones in terms of Precision, the Recall and F-score results appear best for the fused point clouds. It shows that the fused data contains a high point density and RGB color information and could improve the building extraction.
Delayed HIV treatment, barriers in access to care and mortality in tuberculosis/HIV co-infected patients in Cali, Colombia

Abstract Objective: To determine factors associated with mortality in tuberculosis/HIV co-infected patients in Cali, Colombia Methods: This retrospective cohort design included tuberculosis/HIV co-infected persons. Kaplan-Meier and Cox regression were used to estimate survival and risk factors associated with mortality. Results: Of the 279 tuberculosis/HIV co-infected participants, 27.2% died during the study. Participants mainly were adults and males. CD4 count information was available for 41.6% (the median count was 83 cells/mm3), and half were subject to tuberculosis susceptibility testing. The median time between HIV diagnosis and antiretroviral therapy initiation was 372 days. HIV was identified prior to tuberculosis in 53% and concurrent HIV-tuberculosis were diagnosed in 37% of patients. 44.8% had tuberculosis treatment success. Body mass index above 18 kg/m2, initiation of tuberculosis treatment within two weeks, having any health insurance coverage and CD4 count information conferred a survival advantage. Conclusions: Delays in treatment initiation and factors associated with limited health care access or utilization were associated with mortality. As HIV and tuberculosis are both reportable conditions in Colombia, strategies should be focused on optimizing treatment outcomes within both tuberculosis and HIV programs, particularly improving early HIV diagnosis, early antiretroviral therapy treatment initiation, and adherence to tuberculosis treatment.
Electronically tunable mixed-mode third-order universal filter using a single EX-CCCII

ABSTRACT A new Extra-X Current Controlled Conveyor (EX-CCCII) based electronically tunable mixed-mode third-order universal filter has been proposed, which is composed of a single EX-CCCII, three capacitors and a load resistor. The proposed circuit employs a least number of components and can operate in four possible modes of operation, namely voltage mode (VM), current mode (CM), transadmittance mode and transimpedance mode (TIM). Five possible filtering functions – low-pass, high-pass, band-reject, band-pas and all-pass are realised through suitable selection of input signals, operable in three modes (VM, CM and TIM). The angular frequency (ωo) of the proposed circuit is electronically tunable. Non-ideal effects and parasitic analysis is carried out. Exhaustive simulation results using ±0.5 V supply are included to support the present theory.
How Do Employees React When Their CEO Speaks Out? Intra- and Extra-Firm Implications of CEO Sociopolitical Activism

Business leaders have traditionally avoided wading into society’s debates. Yet more and more CEOs are taking visible public stands on hotly contested issues, engaging in what has come to be called CEO sociopolitical activism. Despite its growing prevalence and potentially major implications, this class of executive behaviors remains largely unexplored by organizational scholars. Our study tests and elaborates on stakeholder alignment theory to investigate the influence of CEO activism on employees’ attitudes and behaviors, particularly its effects on employees’ organizational commitment and support for the ideology underpinning the CEO’s public stance. Our theoretical predictions hinge on the degree of alignment between the CEO’s stance and the prevailing ideological tilt of the employee population, as well as the degree to which employees view the CEO as a credible leader. We test our ideas in the context of a highly publicized letter signed by nearly 100 public company CEOs in opposition to North Carolina’s controversial 2016 “bathroom bill. ” Relying on multiple data sources to examine differences between firms whose CEOs signed the letter and firms whose CEOs declined the invitation to sign, we find general support for our theory, indicating that CEO activism has important intra- and extra-firm implications.