Miracle-dz/UniFAR-FTUs huggingface dataset:
A Fully Polynomial Time Approximation Scheme for Constrained MDPs Under Local Transitions

The fixed-horizon constrained Markov Decision Process (C-MDP) is a well-known model for planning in stochastic environments under operating constraints. Chance-constrained MDP (CC-MDP) is a variant that allows bounding the probability of constraint violation, which is desired in many safety-critical applications. CC-MDP can also model a class of MDPs, called Stochastic Shortest Path (SSP), under dead-ends, where there is a trade-off between the probability-to-goal and cost-to-goal. This work studies the structure of (C)C-MDP, particularly an important variant that involves local transition. In this variant, the state reachability exhibits a certain degree of locality and independence from the remaining states. More precisely, the number of states, at a given time, that share some reachable future states is always constant. (C)C-MDP under local transition is NP-Hard even for a planning horizon of two. In this work, we propose a fully polynomial-time approximation scheme for (C)C-MDP that computes (near) optimal deterministic policies. Such an algorithm is among the best approximation algorithms attainable in theory and gives insights into the approximability of constrained MDP and its variants.
The influence of extratropical cross-tropopause mixing on the correlation between ozone and sulfate aerosol in the lowermost stratosphere

The composition of the upper troposphere/lower stratosphere region (UTLS) is influenced by horizontal transport, vertical transport within convective systems and warm conveyor belts, rapid turbulent mixing, as well as photochemical production or loss of species. This results in the formation of the extratropical transition layer (ExTL), which has been defined by the vertical structure of CO profiles and studied by now mostly by means of trace gas correlations. Here, we extend the analysis to aerosol particles and derive the ozone to sulfate aerosol correlation in Central Europe from aircraft in-situ measurements 5 during the CAFE-EU/BLUESKY mission, probing the UTLS during the COVID-19 period with significant reduced anthropogenic emissions. We operated a compact time-of-flight aerosol mass spectrometer (C-ToF-AMS) to measure the chemical composition of non-refractory aerosol particles in the size range from about 40 to 800 nm. In our study, we find a correlation between the ozone mixing ratio (O 3 ) and the sulfate mass concentration in the lower stratosphere. The correlation exhibits some variability over the measurement period exceeding the background sulfate to ozone correlation. Especially during one 10 flight, we observed enhanced mixing ratios of sulfate aerosol in the lowermost stratosphere, where the analysis of trace gases shows tropospheric influence. Also, back trajectories indicate, that no recent mixing with tropospheric air occurred within the last 10 days. In addition, we analyzed satellite SO 2 retrievals from TROPOMI for volcanic plumes and eruptions. From these analyses, we conclude that gas-to-particle conversion of volcanic SO 2 leads to the observed enhanced sulfate aerosol mixing ratios. 15
Bibliometric Analysis of using social media for Education Purpose

The use of online tools in education has led to significant advancements in the field, giving rise to a specialized area of research. This has provided higher education institutions with increased opportunities to engage with their surroundings. One such avenue is the utilization of social media, which aims to enhance and streamline the educational process. The objective of this study is to comprehensively examine the research on the use of social media in higher education. This examination includes analysing publication findings, co-authorship patterns among authors and countries, frequency of author keywords, top institutions, and influential authors. By conducting a bibliometric analysis of 250 journal articles published between 2018 and 2022, using data from the Scopus database via the biblioshiny platform, this research has identified the leading countries in terms of publication output in this field, namely the United States, the United Kingdom, Australia, Malaysia, Saudi Arabia, and Spain. The term "social media in education" is gaining popularity as it aligns with the emerging global trends in online learning. The findings of this study can contribute to the expansion of collaborative networks and the exchange of global perspectives in teaching, learning, and research development.
The Foraminifera Assemblages from Miocene Deposits (Razak Formation) In SW Iran (Khorramabad,Azganeh )

the foraminifera assemblages from Miocene calcareous deposits(Razak Formation) in south-west of iran (west Kuh-e-Azganeh of Khorramabad )were studied with respect to proposed stratigraphical range of the identified benthic and pelagic foraminifera in Azganeh section.on base of micropaleontological research 32 genera and 15 species of benthic foraminifera and 3 genera and 2 species of pelagic foraminifera with a number of non-foraminifera have been identified and based on the associated index foraminifera two biozones have been selected : Archaias kirkukensisGlobigerina-Globorotalia Assemblage Zone and Pseudotaberina malabarica-Borelis melo curdicaElphidium Assemblage Zone that indicating a Aquitanian – Burdigalian age for the Razak Formation in the studied area. Diverse assemblages of benthic foraminifera and also the low planktonic/benthic (P/B) ratio show that strongly the sedimentary environment in the study area was oxygenated and shallow.
A Serious Game to Train Rhythmic Abilities in Children With Dyslexia: Feasibility and Usability Study

Background Rhythm perception and production are related to phonological awareness and reading performance, and rhythmic deficits have been reported in dyslexia. In addition, rhythm-based interventions can improve cognitive function, and there is consistent evidence suggesting that they are an efficient tool for training reading skills in dyslexia. Objective This paper describes a rhythmic training protocol for children with dyslexia provided through a serious game (SG) called Mila-Learn and the methodology used to test its usability. Methods We computed Mila-Learn, an SG that makes training remotely accessible and consistently reproducible and follows an educative agenda using Unity (Unity Technologies). The SG’s development was informed by 2 studies conducted during the French COVID-19 lockdowns. Study 1 was a feasibility study evaluating the autonomous use of Mila-Learn with 2500 children with reading deficits. Data were analyzed from a subsample of 525 children who spontaneously played at least 15 (median 42) games. Study 2, following the same real-life setting as study 1, evaluated the usability of an enhanced version of Mila-Learn over 6 months in a sample of 3337 children. The analysis was carried out in 98 children with available diagnoses. Results Benefiting from study 1 feedback, we improved Mila-Learn to enhance motivation and learning by adding specific features, including customization, storylines, humor, and increasing difficulty. Linear mixed models showed that performance improved over time. The scores were better for older children (P<.001), children with attention-deficit/hyperactivity disorder (P<.001), and children with dyslexia (P<.001). Performance improved significantly faster in children with attention-deficit/hyperactivity disorder (β=.06; t3754=3.91; P<.001) and slower in children with dyslexia (β=−.06; t3816=–5.08; P<.001). Conclusions Given these encouraging results, future work will focus on the clinical evaluation of Mila-Learn through a large double-blind randomized controlled trial comparing Mila-Learn and a placebo game.
Mindfulness-Based Stress Reduction and Transcendental Mindfulness-Based Stress Reduction and Transcendental Meditation: Current State of Research Meditation: Current State of Research

This article summarizes the current state of meditation research, specifically focusing on mindfulness-based stress reduction and transcendental meditation. Despite significant methodological problems with the studies reported to date on the subject, there is consistent evidence that meditation can produce changes in the nervous system and physiology of the meditator, and can help with various psychological markers of well-being. Regarding improvement in specific clinical diseases, research is generally mixed and preliminary. Strong recommendations cannot be made based on current evidence, and further studies are needed. In general, there is a stronger body of evidence supporting mindfulness-based stress reduction than for transcendental meditation. ( J Patient-Centered Res Rev. 2015;2:64-68.)
Late Quaternary dynamics of Arctic biota from ancient environmental genomics

Wang, Yucheng; Pedersen, Mikkel Winther; Alsos, Inger Greve; De Sanctis, Bianca; Racimo, Fernando; Prohaska, Ana; Colssac, Eric; Owens, Hannah Lois; Merkel, Marie Kristine Føreid; Fernandez-Guerra, Antonio; Rouillard, Alexandra; Lammers, Youri; Alberti, Adriana; Denoeud, France; Money, Daniel; Ruter, Anthony H. ; McColl, Hugh; Larsen, Nicolaj Krog; Cherezova, Anna A. ; Edwards, Mary E. ; Fedorov, Grigory B. ; Halle, James; Orlando, Ludovic; Vinner, Lasse; Korneliussen, Thorfinn Sand; Bellman, David W. ; Bjørk, Anders A. ; Cao, Jialu; Dockter, Christoph; Esdale, Julie; Gusarova, Galina; Kjeldsen, Kristian K. ; Mangerud, Jan; Rasic, Jeffrey T. ; Skadhauge, Birgitte; Svendsen, John Inge; Tikhonov, Alexei; Wincker, Patrick; Xing, Yingchun; Zhang, Yubin; Froese, Duane G. ; Rahbek, Carsten; Bravo Nogues, David Bravo; Holden, Philip B. ; Edwards, Neil R. ; Durbin, Richard; Meltzer, David J.; Kjaer, Kurt H. ; Möller, Per and Willerslev, Eske (2021). Late Quaternary dynamics of Arctic biota from ancient environmental genomics. Nature (Early Access).
Chemical Enterprises Social Responsibility -from the perspective of Stakeholders

Faced with the unprecedented changes and challenges of global economic recovery, CSR (CSR) is becoming an important contribution force and path choice. The chemical enterprise social responsibility performance is relat-ed to various stakeholders, this paper analyzes the performance characteristics of the chemical enterprise social responsibility in our country at present through the stakeholder theory and CSR practice combined, and then through analysis of the chemical enterprise in the performance of social responsibility in three problems, In other words, managers of some chemical enterprises have weak awareness of sustainable development strategy, inadequate disclosure of chemical enterprises' social responsibility information and insufficient motivation for chemical SMEs to fulfill their social responsibility. Effective measures to promote chemical enterprises to actively practice their CSR are put forward. To improve and deepen the social responsibility consciousness of chemical enterprises, establish and improve the legal system of information disclosure of chemical enterprises, stabilize and optimize the business environment of chemical SMEs, so as to promote the sustainable development of the chemical industry.
MISSISSIPPI STATE UNIVERSITY AUTONOMOUS VEHICLE SIMULATION LIBRARY

Simulation is a critical step in the development of autonomous systems. This paper outlines the development and use of a dynamically linked library for the Mississippi State University Autonomous Vehicle Simulator (MAVS). The MAVS is a library of simulation tools designed to allow for real-time, high performance, ray traced simulation capabilities for off-road autonomous vehicles. It includes features such as automated off-road terrain generation, automatic data labeling for camera and LIDAR, and swappable vehicle dynamics models. Many machine learning tools today leverage Python for development. To use these tools and provide an easy to use interface, Python bindings were developed for the MAVS. The need for these bindings and their implementation is described.
A New Open‐Access HUC‐8 Based Downscaled CMIP‐5 Climate Model Forecast Dataset for the Conterminous United States

Watershed‐scale hydrologic simulation models generally require climate data inputs including precipitation and temperature. These climate inputs can be derived from downscaled global climate simulations which have the potential to drive runoff forecasts at the scale of local watersheds. While a simulation designed to drive a local watershed model would ideally be constructed at an appropriate scale, global climate simulations are, by definition, arbitrarily determined large rectangular spatial grids. This paper addresses the technical challenge of making climate simulation model results readily available in the form of downscaled datasets that can be used for watershed scale models. Specifically, we present the development and deployment of a new Coupled Model Intercomparison Project phase 5 (CMIP5) based database which has been prepared through a scaling and weighted averaging process for use at the level of U.S. Geological Survey (USGS) Hydrologic Unit Code (HUC)‐8 watersheds. The resulting dataset includes 2,106 virtual observation sites (watershed centroids) each with 698 associated time series datasets representing average monthly temperature and precipitation between 1950 and 2099 based on 234 unique climate model simulations. The new dataset is deployed on a HydroServer and distributed using WaterOneFlow web services in the WaterML format. These methods can be adapted for downscaled General Circulation Model (GCM) results for specific drainage areas smaller than HUC‐8. Two example use cases for the dataset also are presented.
Transformer and Snowball Graph Convolution Learning for Brain Functional Network Analysis

Advanced deep learning methods, especially graph neural networks (GNNs), are increasingly expected to learn from brain functional network data and predict brain disorders. In this paper, we proposed a novel Transformer and snowball encoding networks (TSEN) for brain functional network classification, which introduced Transformer architecture with graph snowball connection into GNNs for learning whole-graph representation. TSEN combined graph snowball connection with graph Transformer by snowball encoding layers, which enhanced the power to capture multi-scale information and global patterns of brain functional networks. TSEN also introduced snowball graph convolution as position embedding in Transformer structure, which was a simple yet effective method for capturing local patterns naturally. We evaluated the proposed model by two large-scale brain functional network datasets from autism spectrum disorder and major depressive disorder respectively, and the results demonstrated that TSEN outperformed the state-of-the-art GNN models and the graph-transformer based GNN models.
Efficient Computation and FPGA implementation of Fully Homomorphic Encryption with Cloud Computing Significance

Homomorphic Encryption provides unique security solution for cloud computing. It ensures not only that data in cloud have confidentiality but also that data processing by cloud server does not compromise data privacy. The Fully Homomorphic Encryption (FHE) scheme proposed by Lopez-Alt, Tromer, and Vaikuntanathan (LTV), also known as NTRU(Nth degree truncated polynomial ring) based method, is considered one of the most important FHE methods suitable for practical implementation. In this thesis, an efficient algorithm and architecture for LTV Fully Homomorphic Encryption is proposed. Conventional linear feedback shift register (LFSR) structure is expanded and modified for performing the truncated polynomial ring multiplication in LTV scheme in parallel. Novel and efficient modular multiplier, modular adder and modular subtractor are proposed to support high speed processing of LFSR operations. In addition, a family of special moduli are selected for high speed computation of modular operations. Though the area keeps the complexity of O(Nn) with no advantage in circuit level. The proposed architecture effectively reduces the time complexity from O(NlogN) to linear time, O(N), compared to the best existing works. An FPGA implementation of the proposed architecture for LTV FHE is achieved and demonstrated. An elaborate comparison of the existing methods and the proposed work is presented, which shows the proposed work gains significant speed up over existing works.
Stigma pada tokoh utama dalam Novel 813 karya Maurice Leblanc

Tujuan penelitian ini adalah untuk mendeskripsikan fase-fase pembentuk stigma pada tokoh utama yang terdapat dalam Novel 813 karya Maurice Leblanc. Pendekatan yang digunakan adalah pendekatan kualitatif struktural karya sastra dengan metode analisis isi. Data berupa kata, frasa, kalimat atau dialog tentang fase-fase pembentuk stigma. Sedangkan sumber data adalah Novel 813 karya Maurice Leblanc. Teori yang digunakan dalam penelitian ini mengacu pada teori stigma menurut Jean-Yves Giordana berupa tiga fase-fase pembentukan stigma yaitu (1) fase pelabelan (Étiquetage) (2) prasangka (Préjudice), dan (3) diskriminasi (Discrimination). Analisis data menggunakan studi dokumen dan mengacu pada teknik analisis data untuk sumber data yaitu Novel 813 karya Maurice Leblanc dengan menganalisis pada setiap unsur intrinsik pada novel mulai dari alur, tokoh dan latar, kemudian mengacu pada teknik analisis data yang digunakan oleh Miles dan Huberman yaitu, reduksi data, penyajian data dan penarikan kesimpulan. Hasil penelitian ini menunjukkan bahwa ada dua puluh dua (22) kutipan yang menunjukkan sebuah fase-fase pembentuk stigma yang dirasakan tokoh utama dalam novel 813 karya Maurice Leblanc. Di antaranya yang pertama fase prasangka berjumlah sebelas (11) kutipan, fase pelabelan berjumlah tujuh (7) kutipan dan fase diskriminasi berjumlah empat (4) kutipan. Berdasarkan penelitian yang telah selesai dilakukan dapat disimpulkan fase prasangka menjadi fase yang paling banyak dirasakan oleh tokoh utama dalam novel 813 karya Maurice Leblanc, kemudian disusul oleh fase kedua adalah fase pelabelan dan yang terakhir adalah fase diskriminasi.
The cellular triumvirate: fibroblasts entangled in the crosstalk between cancer cells and immune cells

This review article will focus on subpopulations of fibroblasts that get reprogrammed by tumor cells into cancer-associated fibroblasts. Throughout this article, we will discuss the intricate interactions between fibroblasts, immune cells, and tumor cells. Unravelling complex intercellular crosstalk will pave the way for new insights into cellular mechanisms underlying the reprogramming of the local tumor immune microenvironment and propose novel immunotherapy strategies that might have potential in harnessing and modulating immune system responses.
Identifikasi Usulan Perbaikan Kualitas Pelayanan Dengan Metode Fuzzy Servqual dan Kano di Bengkel Honda Rahmat Motor

Bengkel Honda Rahmat Motor merupakan bengkel yang menyediakan service dan penggantian spare part khusus sepeda motor merk honda. Di jl. Sei Bangkatan terdapat tiga bengkel AHASS sehingga menimbulkan persaingan sesama bengkel AHASS dan dengan bengkel umum yang ada disekitarnya. Oleh karena itu untuk dapat bersaing, Bengkel Honda Rahmat Motor harus mampu memberikan pelayanan yang maksimal kepada konsumennya. Fuzzy servqual adalah suatu metode yang digunakan untuk mengetahui kesenjangan antara persepsi dan harapan konsumen. Sedangkan metode Kano bertujuan untuk mengkategorikan atribut dari produk ataupun jasa berdasarkan seberapa baik produk atau jasa tersebut mampu memuaskan kebutuhan konsumen. Berdasarkan hasil penelitian dengan menggunakan metode fuzzy servqual dan Kano diketahui bahwa terdapat 12 atribut layanan yang perlu ditingkatkan yaitu: Bengkel memiliki toilet yang bersih dan ruang tunggu yang nyaman, Karyawan berpakaian seragam, rapi dan sopan, Bengkel menyediakan jasa sesuai dengan yang dijanjikan, Bengkel dapat dipercaya dan diandalkan dalam menangani masalah sepeda motor konsumen, Pencatatan transaksi yang akurat, Bengkel memberikan pelayanan dengan cepat, Karyawan menginformasikan kerusakan pada kendaraan konsumen, Kemudahan konsumen untuk memperoleh informasi mengenai suku cadang asli Honda, Bengkel menepati janji sesuai waktu yang diberikan, Karyawan selalu bersikap sopan dan ramah kepada konsumen, Karyawan memahami kebutuhan konsumen, dan Mekanik bersedia mengunjungi konsumen
Progress in diagnosing and treating thyroid squamous cell carcinoma under the 5th edition of WHO classification

Squamous cell carcinoma of the thyroid (SCCT) is a rare thyroid gland malignancy, with only a few hundred cases reported in the literature, mostly as case reports or small sample studies. In the previous WHO classification, squamous cell carcinoma of the thyroid was defined as a carcinoma composed entirely of squamous cells without differentiated carcinoma components. It was once included in the WHO tumor classification separately. However, the 2022 WHO classification of squamous cell carcinoma of the thyroid was reclassified as a morphologic subtype of anaplastic thyroid carcinoma (ATC). The squamous cell carcinoma pattern is similar to the other histologic types of ATC, but the phenotype associated has a poorer prognosis. The typical clinical manifestation of this condition is a cervical mass, accompanied by indications and symptoms of compression on adjacent structures such as the esophagus and trachea in advanced stages. Secondary squamous cell carcinoma of the thyroid may occur due to the spread of squamous carcinoma of the larynx or esophagus or distant metastases from other sites. Diagnosis of squamous cell carcinoma of the thyroid includes neck Ultrasound (US), Computed Tomography (CT) or Magnetic Resonance Imaging (MRI), puncture tissue biopsy, and full endoscopy to identify metastatic lesions from the nasopharynx, oropharynx, hypopharynx, larynx, esophagus, or bronchi and to help with the initial staging of the tumor. Current treatment modalities include surgery, radiotherapy, chemotherapy, or a combination. Because of the poor prognosis of patients with this disease, the short survival period, usually less than one year, and the difficulty of preoperative diagnosis, this article reviews the epidemiological features, origin, clinical features, pathological features, and differential diagnosis to improve the diagnosis and treatment of this disease by clinicians.
Investigative algorithms for disorders affecting plasma magnesium: a narrative review

Magnesium is an abundant intracellular cation and is an essential cofactor for multiple enzymes. Most importantly, magnesium helps in the transfer of inorganic phosphate in many metabolic reactions such as in glycolysis, gluconeogenesis, citric acid cycle and ATP synthesis (1). Only 1% of total body magnesium resides in the extracellular space, 50–65% is complexed in bone and acts as a buffer pool to maintain magnesium homeostasis, and the remainder is found in the intracellular space (Figure 1) (2). Of the total extracellular magnesium, just over half circulates as a free divalent cation, 30% is bound to plasma proteins (particularly albumin), and 15% is complexed with anions (carbonate, phosphate, citrates, hydroxide and chloride). Therefore, changes in protein binding or anion quantity will influence serum magnesium concentration if measuring total magnesium (the most commonly used analytical method to quantitate magnesium in the UK) (1,3). Review Article
Biogeographie et biodiversite : Aires protegees et conservation des mammiferes au Cameroun

Une synthese des donnees disponibles sur la faune mammalienne des sept parcs nationaux et des sept reserves de faune du Cameroun montre que la quasi-totalite (97%) des especes connues de ce pays sont deja presentes dans au moins une aire protegee. Les richesses specifiques en Mammiferes des aires protegees sont approximativement reliees a leur surface par un coefficient de 0,25. Le dendrogramme de leurs affinites faunistiques revele une opposition marquee entre les aires situees en forets denses humides, les plus riches, et celles, plus pauvres, situees en forets claires et en savanes arborees ou herbeuses. Une altitude superieure a 1000 m confere a la faune des Mammiferes une originalite marquee.