Miracle-dz/UniFAR-FTUs huggingface dataset:
From systemic financial risk to grid resilience: Embedding stress testing in electric utility investment strategies and regulatory processes

ABSTRACT In response to major system disruptions, policymakers have prioritized enhancing the resilience of the financial services and energy sectors, with a particular focus on banking and electricity regulation. In both sectors, ‘regulating for resilience’ requires bridging system-level policy goals and institution-level policy instruments as well as tailoring institutional requirements to firms’ idiosyncratic risk profiles. Stress testing has enabled financial regulators to partially overcome these analytical and governance challenges, resulting in better capitalized and managed banks, increased attentiveness to systemic risk, and a more resilient financial system. Recognizing the opportunity for translation across sectors and disciplines, this article develops a novel methodology and an actionable policy framework for embedding stress testing in electric utility investment strategies and regulatory processes. It demonstrates how stress testing could enhance the resilience and sustainability of the U.S. electric grid and explores opportunities for regulatory coordination in multi-sector analyses of climate-related risk and resilience.
iChip-Inspired Isolation, Bioactivities and Dereplication of Actinomycetota from Portuguese Beach Sediments

Oceans hold a stunning number of unique microorganisms, which remain unstudied by culture-dependent methods due to failures in establishing the right conditions for these organisms to grow. In this work, an isolation effort inspired by the iChip was performed using marine sediments from Memoria beach, Portugal. The isolates obtained were identified by 16S rRNA gene analysis, fingerprinted using BOX-PCR and ERIC-PCR, searched for the putative presence of secondary metabolism genes associated with polyketide synthase I (PKS-I) and non-ribosomal peptide synthetases (NRPS), screened for antimicrobial activity against Escherichia coli ATCC 25922 and Staphylococcus aureus ATCC 29213, and had bioactive extracts dereplicated by LC/HRMS. Of the 158 isolated strains, 96 were affiliated with the phylum Actinomycetota, PKS-I and NRPS genes were detected in 53 actinomycetotal strains, and 11 proved to be bioactive (10 against E. coli, 1 against S. aureus and 1 against both pathogens). Further bioactivities were explored using an “one strain many compounds” approach, with six strains showing continued bioactivity and one showing a novel one. Extract dereplication showed the presence of several known bioactive molecules and potential novel ones in the bioactive extracts. These results indicate the use of the bacteria isolated here as sources of new bioactive natural products.
Magnetic Resonance Imaging Findings in Infants with Severe Traumatic Brain Injury and Associations with Abusive Head Trauma

Young children with severe traumatic brain injury (TBI) have frequently been excluded from studies due to age and/or mechanism of injury. Magnetic resonance imaging (MRI) is now frequently being utilized to detect parenchymal injuries and early cerebral edema. We sought to assess MRI findings in infants with severe TBI, and to determine the association between specific MRI findings and mechanisms of injury, including abusive head trauma (AHT). MRI scans performed within the first 30 days after injury were collected and coded according to NIH/NINDS Common Data Elements (CDEs) for Neuroimaging in subjects age < 2 years old with severe TBI enrolled in the Approaches and Decisions in Acute Pediatric Traumatic Brain Injury Trial. Demographics and injury characteristics were analyzed. A total of 81 children were included from ADAPT sites with MRI scans. Median age was 0.77 years and 57% were male. Most common MRI finding was ischemia, present in 57/81 subjects (70%), in a median of 7 brain regions per subject. Contusion 46/81 (57%) and diffuse axonal injury (DAI) 36/81 (44.4%) subjects followed. Children were dichotomized based on likelihood of AHT with 43/81 subjects classified as AHT. Ischemia was found to be significantly associated with AHT (p = 0.001) and “inflicted” injury mechanism (p = 0.0003). In conclusion, the most common intracerebral injury seen on MRI of infants with severe TBI was ischemia, followed by contusion and DAI. Ischemia was associated with AHT, and ischemia affecting > 4 brain regions was predictive of AHT.
NATURAL SCIENCES TEACHERS’ PERCEIVED COGNITIVE ACADEMIC LANGUAGE PROFICIENCY (CALP) NEEDS

"Teachers Cognitive Academic Language Proficiency (CALP) has been found to be important for meaningful teaching and learning of any subject. Over the years research has focused more on English second language learners’ CALP needs and less on the teachers. Because teachers are the cornerstones who drive the process of teaching and learning in the classrooms, their proficiency in the language of teaching and learning are vital. In the South African context, English is regarded as the official language of teaching and learning from grade 4 onwards despite that both teachers and learners come from diverse linguistic backgrounds where English is a second or third language. Underpinned by the socio-cultural theory as the theoretical framework, the paper reports on a study that determined both in-service and pre-service teachers’ perceived CALP needs when teaching Natural Sciences in multicultural township schools. In a qualitative research approach 12 teachers were randomly selected who comprised of six in-service teachers and six final year pre-service teachers enrolled for a Natural Sciences course at a University in South Africa. Each teacher was interviewed once using a semi-structured interview schedule which allowed them to freely express their perceived CALP needs. The data was analysed using a constant comparative method. Findings from the analysis of data showed that teachers experienced many challenges when teaching Natural Sciences using English, a language different from their home languages and those of their learners. They indicated that because science is a unique language on its own they struggle to spell, pronounce, understand and most importantly to explain to the learners using English. The teachers indicated their little to non-exposure to English other than in the classrooms compared to their home languages. Whilst some of the teachers perceived English as an important language due to its universality, they however indicated that code switching to own home language and those of the learners was inevitable when it comes to meaningfully explain some scientific concepts and processes in a way that learners would comprehend. However, others acknowledged the challenges of using code switching in the linguistic diverse classroom environments. Most teachers suggested training workshops intended to develop them with skills to identify appropriate terms and expressions, and explain complex scientific concepts in English. These findings have implications on both pre-service and in-service teacher professional development programmes. "
Unified End-to-End YOLOv5-HR-TCM Framework for Automatic 2D/3D Human Pose Estimation for Real-Time Applications

Three-dimensional human pose estimation is widely applied in sports, robotics, and healthcare. In the past five years, the number of CNN-based studies for 3D human pose estimation has been numerous and has yielded impressive results. However, studies often focus only on improving the accuracy of the estimation results. In this paper, we propose a fast, unified end-to-end model for estimating 3D human pose, called YOLOv5-HR-TCM (YOLOv5-HRet-Temporal Convolution Model). Our proposed model is based on the 2D to 3D lifting approach for 3D human pose estimation while taking care of each step in the estimation process, such as person detection, 2D human pose estimation, and 3D human pose estimation. The proposed model is a combination of best practices at each stage. Our proposed model is evaluated on the Human 3.6M dataset and compared with other methods at each step. The method achieves high accuracy, not sacrificing processing speed. The estimated time of the whole process is 3.146 FPS on a low-end computer. In particular, we propose a sports scoring application based on the deviation angle between the estimated 3D human posture and the standard (reference) origin. The average deviation angle evaluated on the Human 3.6M dataset (Protocol #1–Pro #1) is 8.2 degrees.
Design Considerations and Research Needs for Expanding the Current Perceptual Model of Spatial Orientation into an In-Cockpit Spatial Disorientation Warning System

Abstract : Spatial disorientation (SD) in flight occurs when a pilot incorrectly perceives the orientation or motion of the aircraft, due to vestibular, somatosensory, or visual illusions. Mathematical models of SD predict a pilots perceived orientation, based on quantitative analysis of external and internal factors, e.g., a resultant gravitoinertial force exerted on a pilots body versus the vestibular response to the force. The current application of mathematical modeling involves analyzing flight mishaps post-hoc to determine whether the pilot likely experienced SD in the moments prior to the mishap. Lawson, McGrath, Newman, and Rupert (2015) propose applying current modeling principles to the creation of an in-cockpit warning system to allow for proactive prediction and pilot warning of imminent SD and prevention of SD-related mishaps. The present report discusses the feasibility, desirability, and design considerations of the proposed expansion of the current model into an in-cockpit SD warning system.
Going Big, Going Small, Strategies for Researching Audit Quality

My Inaugural Lecture at Maastricht University updates how archival audit research has evolved since the summary in Francis (1994) of what we then knew from archival research, and describes my own journey from “going big” and asking basic questions about the audit market and audit quality, to “going small” with a focus on smaller units of analysis (offices, partners, and engagement teams) as the key to understanding audit quality. I used to believe that audit firm differences, and differences across offices within firms, were the most important audit-related sources of variation in quality, and that differences in people and audit teams were relatively unimportant. The evidence in Cameran, Campa and Francis (2022) convinced me otherwise, and I now believe that understanding partner-led engagement teams is more important than the combined effects of audit firms and offices in studying audit quality. Audit firms are still something of a black box, and our knowledge to date has been limited to what we can publicly observe about their organizational structures. However, we cannot observe people and engagement teams beyond the identity of the engagement partner, at least not with publicly available data. To learn more means going inside the black box of audit firms, and that means getting the assistance of audit firms to help with such research. I started my career as an applied economist using publicly available data to ask basic questions about the audit market and the demand for and supply of quality-differentiated audits. As I get closer to the end of my career, I now see myself as more of a management scientist, moving inside the organization to understand the consequences for audit quality arising from the internal culture of an audit firm, the personal characteristics of the people who work in audit firms, and the behaviors within the partner-led engagement teams that result in high-quality audit outcomes. To do this research requires proprietary data from audit firms, and interaction with the professionals who work in these firms. I thank the Foundation for Auditing Research in the Netherlands for facilitating my access to audit firms and their staff, and for the assistance of these firms in helping me to research the organizational drivers of high-quality audits.
Assessments of Ceanothanes Triterpenes as Cholinesterase Inhibitors: An Investigation of Potential Agents with Novel Inspiration for Drug Treatment of Neurodegenerative Diseases

The purpose of this study was to determine the inhibitory capacity of ceanothanes triterpenes isolate from Chilean Rhamnaceae on acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) enzymes. Seven ceanothanes triterpenes were isolated from aerial parts of plant material by classical phytochemical methods or prepared by the hemisynthetic method. Structures were determined by the spectroscopic method (1H-NMR and 13C NMR) and mass spectrometry (MS). AChE and BChE activity were determined by the Ellmann method for all compounds. All tested compounds exerted a greater affinity to AChE than to BChE, where compound 3 has an IC50 of 0.126 uM for AChE and of >500 uM to BChE. Kinetic studies indicated that its inhibition was competitive and reversible. According to the molecular coupling and displacement studies of the propidium iodide test, the inhibitory effect of compound 3 would be produced by interaction with the peripheral anionic site (PAS) of AChE. The compounds tested (1–7) showed an important inhibitory activity of AChE, binding to PAS. Therefore, inhibitors that bind to PAS would prevent the formation of the AChE-Aβ complex, constituting a new alternative in the treatment of Alzheimer’s disease (AD).
Netting Damage Detection for Marine Aquaculture Facilities Based on Improved Mask R-CNN

Netting damage limits the safe development of marine aquaculture. In order to identify and locate damaged netting accurately, we propose a detection method using an improved Mask R-CNN. We create an image dataset of different kinds of damage from a mix of conditions and enhance it by data augmentation. We then introduce the Recursive Feature Pyramid (RFP) and Deformable Convolution Network (DCN) structures into the learning framework to optimize the basic backbone for a marine environment and build a feature map with both high-level semantic and low-level localization information of the network. This modification solves the problem of poor detection performance in damaged nets with small and irregular damage. Experimental results show that these changes improve the average precision of the model significantly, to 94.48%, which is 7.86% higher than the original method. The enhanced model performs rapidly, with a missing rate of about 7.12% and a detection period of 4.74 frames per second. Compared with traditional image processing methods, the proposed netting damage detection model is robust and better balances detection precision and speed. Our method provides an effective solution for detecting netting damage in marine aquaculture environments.
Structure simplification of planar quadrilateral meshes

In this paper, we present a structure simplification framework for planar all-quad meshes with open boundaries. Our simplification framework can handle quad meshes with complex structures (e.g., quad meshes obtained via Catmull-Clark subdivision of the triangle meshes) to produce simpler meshes while preserving the boundary features. To achieve that, we introduce a set of separatrix-based semi-global operations and combine them with existing local operations to develop a new simplification framework. Additionally, we organize and order the individual simplification operations into groups and employ ranking strategies for each group to sort these operations to produce quad meshes with better quality and simpler structure. We provide a comprehensive evaluation of our framework using di ff erent input parameters on a number of representative planar quad meshes with various boundary configurations. To demonstrate the advantages of our method, we compare it with a few existing frameworks. Our comparison shows that our simplification framework usually produces simpler structure with faster computation than the state-of-the-art methods.
The Effects of ESG Activity Recognition of Corporate Employees on Job Performance: The Case of South Korea

Corporate environment, society, and governance (ESG) management activities have recently been consolidated in the business ecosystem, and many firms are considering their employees’ recognition and job changes according to organizational ESG strategy. This study aims to verify the effects of ESG activity recognition of corporate employees on job performance by mediating change support behavior, innovative organization culture, and job crafting. This study designs a structural equation model with a hypotheses based on previous studies. A questionnaire survey was carried out targeting large Korean manufacturing companies, and an analysis of 329 response copies was performed. As a result, ESG activity recognition did not directly affect job crafting, but it affected job crafting with the mediation of innovative organizational culture and change support behavior. ESG activity recognition also positively affected job crafting and job performance by mediating change support behavior and an innovative organization culture. Hence, the research shows that an innovative culture and change support behavior within an organization should be considered to improve ESG management performance.
Analisis Ketelitian Orthorektifikasi Citra Pleides dan SPOT6 Untuk Pembuatan Peta Dasar RDTR Wilayah Pesisir (Studi Kasus: Kecamatan Jenu, Tuban)

Wilayah pesisir Kabupaten Tuban dalam berbagai rencana tata ruang direncanakan menjadi salah satu pusat pertumbuhan ekonomi di Jawa Timur. Rencana tersebut memerlukan peta Rencana Detail Tata Ruang (RDTR), khususnya Wilayah Pesisir dengan ketelitian tinggi. Namun peta RDTR yang digunakan saat ini masih belum memiliki ketelitian tinggi. Oleh karena itu, tujuan dalam penelitian ini adalah melakukan analisis ketelitian orthorektifikasi citra satelit resolusi tinggi, sehingga dapat digunakan untuk pembuatan peta dasar RDTR.Dalam penelitian ini dilakukan proses orthorektifikasi menggunakan data citra satelit Pleiades 1A dan SPOT6 dengan metode Rational Polynomial Coefficient (RPC). Sebagai data penunjang yaitu data Titik Kontrol Tanah (GCP) sebanyak 11 titik dan titik Uji Akurasi (ICP) sebanyak 12 titik dan data DEM Astrium Terra SAR-X untuk koreksi ketinggian citra satelit, sehingga menjadi citra tegak.Berdasarkan pengolahan dan analisis data didapatkan nilai ketelitian horizontal citra Tegak Pleiades 1A sebesar 0,3 meter dan citra Tegak SPOT6 sebesar 1,8 meter. Berdasarkan nilai ketelitian horizontal tersebut bahwa citra satelit Pleiades 1A dan SPOT6 memenuhi standar ketelitian horizontal peta dasar skala 1:5000 dan 1:10.000 sesuai dengan Perka BIG No 15 tahun 2014.
Spinal Cord Compression Due to Tophaceous Vertebral Gout: A Case Report

Gout tophi are deposits of urate crystals in subcutaneous tissues and joints which commonly affect the small joints of the feet and hands, causing painful arthritis. The axial skeleton is considered to be seldom affected by gout arthritis. Here we describe the clinical, MRI, and pathologic findings of a 61-year-old male patient with a previous diagnosis of gout who presented with progressive paraparesis and radicular pain. MRI showed extradural masses compressing the spinal cord and roots at two spinal levels. Two surgical interventions were performed to remove these extradural masses, which were pathologically identified as gout tophi. Pain and paraparesis had clinical improvement after surgery. This report highlights that gout can be a cause of paraparesis.
Availability of Facilities and Interest towards Entrepreneurship among Rural Small Holders’ Farmers of Coastal Districts in Tamil Nadu

Agriculture has been, for a very long period of time, the main activity for people in rural areas. The climate change, in addition, exiguity of farming land due to the growth of the population, farming has become difficult. Different regions of the world are not affected in an unequal number of disasters and coastal areas are more exposed. Governments, NGOs and researchers have tried to come up with some new remedies. The best way seems to be initiating some allied activities in farmers’ lives to improve their livelihoods. Are the farmers easily welcoming the new exit way to their misery? This study wants to know the interest of farmers towards livelihood enhancement activities through entrepreneurship from Thiurvallur district to Kanyakumari district in Tamil Nadu comprising 13 districts. The data was collected among 286 small landholders through a scheduled interview between October 2020 and February 2021. It wants to assess the existing facilities to improve farmers’ livelihood at their disposal. Major findings through SEM analysis have shown that, holding livestock, possessing machinery for agriculture, possessing other skills than farming to manage livelihood and the membership in self-help groups has a positive impact on the livelihood enhancement activity.
Future-proofing students in higher education with unmanned aerial vehicles technology: A knowledge management case study

In this paper we report experiences in implementing a new course ‘Understanding Drone & Robotics Technology – History, Usage, Ethics & Legal Issues’ at the Singapore Management University framed as a strategic knowledge management (KM) initiative in an institution of higher learning aimed at capturing, sharing and creating new knowledge about disruptive technologies such as unmanned aerial vehicles. We posit the new course as a knowledge innovation initiative (similar to a KM-enabled business case in a corporate setting) in support of the university’s mission and vision so as to deliver new value to students and to stay ahead of the latest technological developments. In line with a ‘normal’ KM initiative, we examine how the new learning and teaching initiative was conceived, pushed forward and eventually launched, creating a new multi-disciplinary learning experience for students, instructors and other stakeholders. We explain the knowledge strategy of the course and use I. Nonaka’s SECI framework to shed light on selected aspects of the pedagogical approach towards achieving the desired learning outcomes. Overall, the paper intends to make a case for more collaborative knowledge leadership as a strategic enabler of multi-disciplinary knowledge innovation in a rapidly changing higher education landscape.
A Bandwidth-Efficient Emulator of Biologically-Relevant Spiking Neural Networks on FPGA

Closed-loop experiments involving biological and artificial neural networks would improve the understanding of neural cells functioning principles and lead to the development of new generation neuroprosthesis. Several technological challenges require to be faced, as the development of real-time spiking neural network emulators which could bear the increasing amount of data provided by new generation High-Density Multielectrode Arrays. This work focuses on the development of a real-time spiking neural network emulator addressing fully-connected neural networks. This work presents a new way to increase the number of synapses supported by real-time neural network accelerators. The proposed solution has been implemented on the Xilinx Zynq 7020 All-Programmable SoC and can emulate fully connected spiking neural networks counting up to 3,098 Izhikevich neurons and 9.6e6 synapses in real-time, with a resolution of 0.1 ms.
Entangled Photon Source of Quantum Key Generator from Micro Ring Resonator for QKD Use

The powerful novel invention of entangled photon source by using a nonlinear silica micro ring resonator for quantum cryptography use was established and investigated. This entangled photon pair was generated under the degenerated four wave mixing process under the phase mismatch adjusment. The corresponding entangled photon generation Hamiltonian was established and studied in term of EPR pair. The obtained entangled photon pairs can be applied to the quantum cryptography distribution under quantum teleportation process showing the feasible and suitable for quantum information communication via the high visibility and $Q$ factor results. The advantage of this novel entangled photon source will be proved to become a part of quantum distribution device in the near future.