Miracle-dz/UniFAR-FTUs huggingface dataset:
A half-century of contributions to landslide knowledge in QJEGH

Now that the Quarterly Journal of Engineering Geology and Hydrogeology (QJEGH) has reached volume 52, it is timely to consider and review the significance of papers published in it over 50 volumes and a little more than a half-century. Articles published in the journal over this period on landslides have related to conditions in Europe; North, Central and South America; Asia; Africa; The Middle East; The Indian Subcontinent; Australasia; and, extraterrestrially, on Mars. The coverage of topics within landslide science and engineering has been similarly diverse, with papers on coastal and inland slopes, shear strength measurement from back analysis and laboratory tests, and field recognition of landslide morphology on the ground and from aerial photography – in the Martian case, from satellite photography.
La distribution des kystes de dinoflagellés dans les sédiments hémipélagiques (Ardèche), et pélagiques (Arc de Castellane, S. E. De la France), en domaine vocontien, du Valanginien terminal au Barrémien inférieur : biostratigraphie et relations avec la stratigraphie séquentielle

Deux coupes du Cretace inferieur vocontien (SE de la France) representant les milieux pelagiques (Clue de Vergons ; Alpes de Haute-Provence) et hemipelagiques (Ravin des Buissieres ; Ardeche) ont ete etudiees d’un point de vue palynologique (Dinoflagelles essentiellement). Bien datees par les faunes d’Ammonites, ces series ont ete recalees sur la stratigraphie sequentielle (modele de VAIL) dont les discontinuites ont ete reconnues in situ sur chacun des affleurements. Realise sur 105 echantillons, l’inventaire original des dinokystes de ces series a abouti a la reconnaissance de pres de 190 taxons. Une biozonation basee sur les extensions stratigraphiques et les dinokystes est proposee. Elle est comparee a celle fournie par les faunes d’Ammonites ainsi qu’a la stratigraphie sequentielle : la dinozonation etablie s’avere etre une echelle biostratigraphique rarement dependante des deux autres. Au niveau des cycles de 3eme ordre, aucune relation systematique n’est observable entre les discontinuites sequentielles et les assemblages de dinokystes. Quelques correlations sont proposees au niveau des cycles de 2eme ordre (reconnaissance de l’intervalle transgressif ; remontee generale du niveau marin). D’un point de vue biostratigraphique, ces resultats locaux sont replaces dans un cadre plus global et compares avec les dinozonations des principaux bassins du Cretace inferieur. S’appuyant sur les variations du contenu des assemblages de dinokystes, sur les variations de frequences de certains taxons, un essai de paleoecologie a ete realise : certains parametres de milieu tels que variations du niveau marin, eloignement de la cote ou salinite ont pu etre apprehendes, indiquant une remontee globale du niveau marin de la base au sommet de l’Hauterivien. Le rapport des genres Muderongial/Phoberocysta permet un schema des variations du niveau marin, en particulier pour l’Hauterivien.
Surveillance of Nipah virus in Pteropus medius of Kerala state, India, 2023

Introduction Since 2018, the Indian state of Kerala has reported four Nipah virus (NiV) disease outbreaks, raising concerns about NiV spillover from bats to the human population. Considering this, a cross-sectional study was undertaken in the Pteropus medius bat population around the Nipah virus-affected regions of Kozhikode, Kerala, India, during February, July, and September 2023. Methods Throat swabs, rectal swabs, and organ samples were collected from bats to test for NiV using the real-time reverse transcriptase polymerase chain reaction (RT-PCR), while serum samples were screened for anti-Nipah IgG antibodies through ELISA. Results An overall seroprevalence of 20.9% was observed in 272 P. medius bats tested. The throat and rectal swab samples of 321 bats were negative for NiV RNA. However, 4 of 44 P. medius bats tested positive for NiV in their liver/spleen samples. The partial N gene retrieved showed more than 99% similarity with the earlier reported NiV genome from Kerala state, India. Discussion The findings of the study caution that there is a spillover risk in the region and necessary precautions should be taken.
Reconstruction-Based Supervised Contrastive Learning for Unknown Device Identification in Nonintrusive Load Monitoring

Nonintrusive load monitoring (NILM) involves deploying monitoring devices at the customer’s bus entrance to decompose the total power captured into individual operational data for each device. Existing NILM load identification algorithms primarily adopt closed-set identification, where the same types of devices are used for both training and testing. However, a more realistic scenario is open-set identification, where device types in the training and test sets differ, encompassing not only devices from the training set but also unknown devices. To address this challenge, we propose a method leveraging reconstruction and supervised contrastive learning based on voltage–current (<inline-formula> <tex-math notation="LaTeX">$V$ </tex-math></inline-formula>–<inline-formula> <tex-math notation="LaTeX">$I$ </tex-math></inline-formula>) trajectories. Supervised contrastive learning improves the coherence of <inline-formula> <tex-math notation="LaTeX">$V$ </tex-math></inline-formula>–<inline-formula> <tex-math notation="LaTeX">$I$ </tex-math></inline-formula> trajectories within identical appliance classes, facilitating the model’s precise comprehension and emulation of distinctive appliance behavioral patterns. By introducing an autoencoder (AE) into the model, associating each appliance class with its unique subset of features. Known <inline-formula> <tex-math notation="LaTeX">$V$ </tex-math></inline-formula>–<inline-formula> <tex-math notation="LaTeX">$I$ </tex-math></inline-formula> trajectories activate associated features, preserving the topological characteristics of the trajectory. In contrast, unknown <inline-formula> <tex-math notation="LaTeX">$V$ </tex-math></inline-formula>–<inline-formula> <tex-math notation="LaTeX">$I$ </tex-math></inline-formula> trajectories lack reconstruction mappings, resulting in thoroughly mutated trajectories. Moreover, we innovate data augmentation for contrastive learning by introducing a denoising AE (DAE). This approach introduces noise in <inline-formula> <tex-math notation="LaTeX">$V$ </tex-math></inline-formula>–<inline-formula> <tex-math notation="LaTeX">$I$ </tex-math></inline-formula> trajectories, the model learns to remove noise while preserving real appliance characteristics, generating more robust <inline-formula> <tex-math notation="LaTeX">$V$ </tex-math></inline-formula>–<inline-formula> <tex-math notation="LaTeX">$I$ </tex-math></inline-formula> trajectories. Experimental results on two publicly available datasets demonstrate the method’s outstanding performance.
The Dynamic Spatial Structure of Flocks

Studies of collective motion have heretofore been dominated by a thermodynamic perspective in which the emergent “flocked” phases are analyzed in terms of their time-averaged orientational and spatial properties. Studies that attempt to scrutinize the dynamical processes that spontaneously drive the formation of these flocks from initially random configurations are far more rare, perhaps owing to the fact that said processes occur far from the eventual long-time steady state of the system and thus lie outside the scope of traditional statistical mechanics. For systems whose dynamics are simulated numerically, the nonstationary distribution of system configurations can be sampled at different time points, and the time evolution of the average structural properties of the system can be quantified. In this paper, we employ this strategy to characterize the spatial dynamics of the standard Vicsek flocking model using two correlation functions common to condensed matter physics. We demonstrate, for modest system sizes with 800 to 2000 agents, that the self-assembly dynamics can be characterized by three distinct and disparate time scales that we associate with the corresponding physical processes of clustering (compaction), relaxing (expansion), and mixing (rearrangement). We further show that the behavior of these correlation functions can be used to reliably distinguish between phenomenologically similar models with different underlying interactions and, in some cases, even provide a direct measurement of key model parameters.
Neolithic Explanations Revisited: Modelling the Arrival and Spread of Domesticated Cattle into Neolithic Britain

ABSTRACT Set against the new chronological framework for the introduction and spread of the Neolithic into Britain this paper considers the logistics of introducing domestic cattle from continental Europe. Cattle were the most extensively utilised domestic animal at the start of the Neolithic and understanding the processes behind their introduction is critical for exploring early Neolithic farming systems. We begin by exploring the realities of creating a viable new animal population and then moving that population to Britain across the water from Continental Europe. Using a series of simulated models we demonstrate that only a very small number of cattle need to have been introduced into Britain in order to enable the uptake and spread of domestic cattle across the whole island. This, in turn, may effect how we consider the mechanisms involved in the adoption of the Neolithic, and can better inform our understanding of the kinds of processes involved in the transition to the Neolithic.
Evaluation of Warm‐Core Structure in Reanalysis and Satellite Data Sets Using HS3 Dropsonde Observations: A Case Study of Hurricane Edouard (2014)

Using National Aeronautics and Space Administration Hurricane and Severe Storm Sentinel (HS3) dropsonde observations in the eye of Hurricane Edouard (2014), its warm‐core structure in reanalysis/analysis and satellite data sets are evaluated. All of the data sets generally underestimate the warm‐core strength of Edouard. Advanced Microwave Sounding Unit‐A shows the smallest error in the upper troposphere but the largest error in the lower troposphere. Its successor, Advanced Technology Microwave Sounder, significantly improves the representation of low‐level warming while maintaining its performance in the middle and upper troposphere. Two versions of the Global Forecast System analysis at different resolutions and Climate Forecast System Reanalysis version 2 show better performance than the other reanalyses. Modern Era Retrospective Analysis for Research and Application (MERRA)‐2, Japanese 55‐year Reanalysis, and European Centre for Medium‐Range Weather Forecasts Interim Reanalysis could represent the vertical warm‐core structure, but they markedly underestimate the warm‐core strength. MERRA and North American Regional Reanalysis (especially North American Regional Reanalysis) have the worst skills when reproducing warm cores. MERRA‐2 considerably outperforms its predecessor, MERRA. The warm‐core evolution of Edouard in six reanalysis/analysis data sets is diagnosed and compared. Different physical processes such as diabatic heating and vertical and horizontal advection may be responsible for warm‐core generation at different stages during its lifetime. The inaccurate representation of these physical processes in the reanalyses/analyses results in errors in the warm‐core strength and height. It is suggested that vortex relocation/bogusing, assimilation of tropical cyclone (TC) observation data, and model parameterizations are important to adequately represent warm cores in terms of strength and three‐dimensional structure. This study can shed some light on the selection of suitable data sets for estimating the real‐time warm‐core strength or for TC‐related climate studies. The need for better observations of TCs and model improvements is also highlighted.
OPTIMASI FUNGSI KEANGGOTAAN FUZZY BERBASIS ALGORITMA MODIFIED PARTICLE SWARM OPTIMIZATION

Pada penelitian ini optimasi berbasis algoritma Modified Particle Swarm Optimization (MPSO) diterapkan untuk mengoptimasi fungsi keanggotaan fuzzy. Terdapat dua metode MPSO yang diterapkan yaitu metode Linear Decreasing Inertia Weight (LDIW) dan Constriction Factor Method (FCM). Masing-masing metode tersebut diuji dengan 10 kali percobaan pada dua jenis jumlah particle yaitu 50 dan 20 particle. Dari hasil pengujian diperoleh bahwa pada jumlah particle yang sama, CFM memperoleh nilai global best fitness yang lebih optimal daripapa metode LDIW. Pengujian sebanyak 10 kali percobaan dan menerapkan 50 particle, pada percobaan pertama diperoleh nilai global best fitness yaitu 1,4; 1,4; 2,36 dan 3,28 untuk masing-masing variabel produktifitas, keterisolasian, hubungan sosial dan aksesibilitas. Pengujian sebanyak 10 kali percobaan dan menerapkan 20 particle diperoleh nilai global best fitness yaitu 2,34; 2,40; 2,37 dan 3,36 untuk masing-masing variabel. Di sisi lain metode CFM memperoleh hasil konvergensi yang lebih cepat dari pada metode LIDW. Pengujian pada 100 swarm metode LDIW menemukan global best fitness pada swarm 91, 84, 54 dan 38 untuk masing- masing variabel, sementara dengan metode CFM menemukan global best fitness pada swarm 81, 23, 34 dan 23
Improving Speaker Assignment in Speaker-Attributed ASR for Real Meeting Applications

Past studies on end-to-end meeting transcription have focused on model architecture and have mostly been evaluated on simulated meeting data. We present a novel study aiming to optimize the use of a Speaker-Attributed ASR (SA-ASR) system in real-life scenarios, such as the AMI meeting corpus, for improved speaker assignment of speech segments. First, we propose a pipeline tailored to real-life applications involving Voice Activity Detection (VAD), Speaker Diarization (SD), and SA-ASR. Second, we advocate using VAD output segments to fine-tune the SA-ASR model, considering that it is also applied to VAD segments during test, and show that this results in a relative reduction of Speaker Error Rate (SER) up to 28%. Finally, we explore strategies to enhance the extraction of the speaker embedding templates used as inputs by the SA-ASR system. We show that extracting them from SD output rather than annotated speaker segments results in a relative SER reduction up to 20%.
Role of RUNX2 in Oral Squamous Cell Carcinoma (OSCC): A Systematic Scoping Review

RUNX2, known as the core-binding factor subunit alpha-1 (Cbfa1), is a protein-coding gene recognized and responsible for its involvement in bone development and osteoblast differentiation. However, its dysregulation and aberrant expression have been linked to the pathogenesis of many diseases, such as oral squamous cell carcinoma (OSCC). This review highlights the significance of the RUNX2 gene in oral squamous cell carcinoma. Objectives. To review the contribution of the RUNX2 gene in oral squamous cell carcinoma and its implication on clinical diagnosis and treatments. Materials and Methods. A systematic scoping review was conducted to elucidate the role of RUNX2 in OSCC. A framework of five stages for scoping reviews outlined by Arksey and O’Malley (2005) was adopted for the current study. Results. The review showed that RUNX2 plays a role in the development and progression of OSCC, a common form of head and neck cancer. Conclusion. RUNX2 is an essential player in the molecular mechanisms underlying the development and progression of oral squamous cell carcinoma, and its dysregulation promotes tumor initiation, progression, and metastasis, making it a potential target therapy for future research aimed at developing novel therapies for oral squamous cell carcinoma. Clinical Relevance. Understanding the precise mechanisms by which RUNX2 contributes to OSCC pathogenesis can lead to target treatment for this challenging form of cancer.
Atomic Structure Teaching Module with PhET Simulation to Increase Student Motivation and Learning Outcomes

This study aims to obtain the feasibility of teaching modules with PhET simulations to increase student motivation and learning outcomes in atomic structure content as a learning tool. The eligibility of teaching modules consists of valid, practical, and effective criteria. This development research uses the ADDIE research model which consists of five stages which include analysis, design, development, implementation, and evaluation. The trial design used was the One Group Pretest-Posttest Design. The subjects in this study were students of class X SMA Intensif Taruna Pembangunan Surabaya with a total of 30 students. The research instruments used included validation sheets, student response sheets, student activity observation sheets, learning motivation sheets and pretest-posttest sheets. Analysis of the data used using the validity test, analysis of the percentage of practicality and the percentage of effectiveness. The results of the validity test obtained a validation mode score of 4 so can be stated that the teaching modules developed are included in the good category. The results of the practicality test obtained the percentage of students' response results of 82.3% so can be stated that the teaching modules developed are categorized as very practical. Then the percentage of the effectiveness of motivation to learn before treatment obtained results of 50.6% and after treatment of 85.7%. Based on these percentages, it can be stated that the teaching modules created can increase students' learning motivation. The learning outcomes of students obtained an N-Gain score of 0.71 which means that the teaching module is in the high category.
Optimasi Sistem Pengelolaan Layanan Laundry (Studi Kasus: Findo Laundry)

Dalam proses pembayaran, Findo Laundry masih menggunakan metode manual. Dengan kata lain, pelanggan dapat datang ke Findo Laundry secara langsung. Pelanggan yang rumahnya jauh dari Findo Laundry mengalami kesulitan dengan hal ini, yang menghabiskan banyak waktu dan tenaga. Selain itu, transaksi masih ditulis dengan tangan, yang mengakibatkan kesalahan pencatatan dan perhitungan yang sering dan kemungkinan buku catatan hilang atau rusak. Proses penyusunan laporan juga membutuhkan waktu yang lama karena karyawan harus menyalin dari catatan lama, yang kadang-kadang tidak dapat dibaca karena tulisannya yang tidak rapi. Tujuan dari penelitian ini adalah untuk membuat aplikasi yang dapat membantu pelanggan memesan jasa cuci laundry dari rumah, menghemat waktu dan tenaga, dan membuat transaksi dan laporan lebih mudah.
Stratigraphic Formation of the Mekong River Delta and Its Recent Shoreline Changes

USAGE Permission is granted to copy this article for use in teaching and research. Republication, systematic reproduction, or collective redistribution of any portion of this article by photocopy machine, reposting, or other means is permitted only with the approval of The Oceanography Society. Send all correspondence to: info@tos.org or The Oceanography Society, PO Box 1931, Rockville, MD 20849-1931, USA. Oceanography THE OFFICIAL MAGAZINE OF THE OCEANOGRAPHY SOCIETY
The Overview of Challenges in Detecting Patients' Hazards During Robot-Aided Remote Home Motor Rehabilitation

Home, minimally‐supervised rehabilitation has become an arising technological trend due to the shortages in medical staff. Implementing such requires providing advanced tools for automatic real‐time safety monitoring. The paper presents an approach to designing the mentioned safety system based on measurements and modelling the interface between a patient’s musculoskeletal system and a rehabilitation device. The content covers the segmentation of patients regarding their health conditions and assigns them suitable measurement techniques. The defined groups are described with the hazards, which they are most endangered, and their causes. Each case is correlated with the appropriate data type that may be used to detect potential risk. Moreover, a concept of using presented knowledge for tracking the safety of bones and soft tissues according to the biomechanical standards is included. The paper forms a set of guidelines for designing safety systems based on measurements for robot‐aided home kinesiotherapy. It can be used to select an appropriate approach regarding a specific case; so to decrease costs and increase the accuracy of the designed tools.
Neuropsychological Stimulation Program for Children from Low Socioeconomic Backgrounds: Study Protocol for a Randomized Controlled Trial

Background: Guatemala remains one of the poorest countries in Central America and suffers from high rates of social inequality and violence. In addition to the negative impact that two years without attending school has had on Guatemalan children due to the consequences of the COVID-19 pandemic, this unfavourable socioeconomic context poses a risk to children’s emotional and cognitive development. This work presents a protocol for implementing a cognitive and emotional stimulation program aimed at increasing the academic performance of these children and consequently improving their quality of life. Methods: The protocol proposes the implementation of a randomized controlled trial to assess the efficacy of a 24-session-long stimulation program. It targets the cognitive functions of attention, language, executive functions, and social cognition, using the digital neurorehabilitation platform NeuronUP. The participants (n = 480) will be randomly assigned to an Experimental or Control group. Pre- and post-intervention assessments will be carried out, together with a follow-up in the next academic year, in which both groups will change roles. Results will be compared for the first and second years, looking for differences in academic and cognitive performance between groups. Discussion: Mid- and long-term outcomes are still unknown, but effective interventions based on this protocol are expected to facilitate the following benefits for participants: (1) improved cognitive and emotional development; (2) improved academic performance; (3) improved well-being. We expect to create a validated neuropsychological stimulation program that could be applied in similar socioeconomically disadvantaged contexts around the world to help these children improve their life chances.
A Novel Approach for Enhancing Malaria Detection Accuracy Through Deep Learning With C3TR and BiFPN Architectures

Each year, millions of people experience the terrible effects of malaria in different parts of the world. Humans get sick with malaria through infected female Anopheles mosquitoes. Despite recent advancements in the field, microscopy remains the most common method for diagnosing malaria. Recent strides in the domains of signal processing, image processing, and sensing, through the application of artificial intelligence, especially machine learning and deep learning have yielded cost-effective solutions that improve diagnostic accuracy. In this letter, we propose a tweaked version of the You Only Look Once (YOLOv5) framework, incorporating image signal processing techniques for screening malaria-infected cells and comparing it with established methods that highlight the pivotal role of sensing technologies. Our innovation revolves around two pivotal modifications. The conventional C3 module in YOLOv5 is replaced by the innovative C3TR structure, leveraging signal processing to facilitate the extraction of precise object properties while minimizing the interference of the image background. The PANet structure in the neck has been upgraded to the state-of-the-art Bi-directional Feature Pyramid Network architecture harnessing image processing techniques to further extract the features of objects. The outcomes of our model are remarkable with an accuracy of 99.2%, a precision of 98.7%, and a recall of 98.5%. With these results, our model outperformed many of the existing methodologies which highlighted the crucial importance of image signal analysis and sensing technologies in transforming malaria detection and classification.