Miracle-dz/UniFAR-FTUs huggingface dataset:
Limite thermodynamique pour des modèles de type Thomas-Fermi

Nous etudions la limite thermodynamique, ou limite des grands volumes, pour des modeles de Chimie Quantique Moleculaire de type Thomas-Fermi, en particulier ceux de Thomas-Fermi-von Weizsacker et de Thomas-Fermi-Dirac-von Weizsacker. Dans le cas d'une geometrie cristalline, nous prouvons la convergence de l'energie par unite de volume et celle de la densite electronique respectivement vers l'energie fondamentale d'un probleme periodique et vers la densite periodique qui lui correspond. Nous montrons en outre un resultat d'existence et d'unicite pour un systeme couple (de type Schrodinger-Poisson) d'equations aux derivees partielles elliptiques non lineaires.
Limit Distributions of the Maximum Filling of Cells in One Allocation Scheme

This article examines a model for allocating particles to N different cells, wherein the chance quantities ξ1, …, ξN , which are equal to the number of particles in cells, are independent and have a Poisson distribution. The author obtains the limit distributions of the maximum filling of cells for the subset of realizations of such a scheme which satisfy the condition ξ1+…+ξN ≤ n, at N→∞.
Endometrial Adenocarcinoma with Discordant Microsatellite Stability Status Treated with First-Line Pembrolizumab: A Case Report and Narrative Review

Patient: Female, 67-year-old Final Diagnosis: MSI endometrial adenocarcinoma Symptoms: Abdominal pain • nausea • vomiting Clinical Procedure: — Specialty: Obstetrics and Gynecology • Oncology Objective: Unusual clinical course Background: Microsatellite instability (MSI) is a hallmark of specific cancers and can be diagnosed using both tissue- and liquid-based approaches. When these tissue- and liquid-based approaches give differing results, they are known as discordant or being at variance. MSI-H tumors are well-researched candidates for treatment with programmed cell death protein 1 (PD-1) inhibitor-based immunotherapy, but the efficacy of immunotherapy in MSI-H discordant endometrial cancer, especially as first-line therapy, is not yet well documented in the literature. Case Report: A 67-year-old woman presented with a retroperitoneal mass positive for recurrent adenocarcinoma of endometrial origin. Her stage I endometrial adenocarcinoma 7 years ago demonstrated microsatellite stable (MSS) by immunohistochemical (IHC) stain and indeterminant due to insufficient tissue by Caris Next-Generation Sequencing (NGS). She then presented with a retroperitoneal mass that was MSI-H on IHC stain and Caris NGS, as well as MSI high on liquid biopsy @Guardant360 (@G360). The patient proceeded with pembrolizumab treatment 1 year ago and has sustained a complete clinical response at the time of writing. Conclusions: Our case provides further evidence for the need to retest the microsatellite stability of metastatic sites, especially after a long disease-free survival. Here, we providing a literature review of case reports and a review of studies outlining discordance of testing modalities. Our case also highlights the importance of considering the use of immunotherapy as a first-line agent in patients who may have a poor ECOG performance status, as it can significantly improve their quality of life and reduce the number of adverse effects compared to chemotherapy.
Towards precision β-decay measurements with laser cooled 35Ar

We present modeling and preliminary experimental results towards the development of our magnetooptical trap (MOT) setup and polarisation scheme for 35Ar. The atomic beam that is used for loading the MOT includes a novel transverse cooling arrangement based on a frequency broadened ’white-light molasses’. Our modeling shows that, under certain experimental conditions, such a setup can be beneficial in comparison to conventional transverse cooling techniques. We will report on experimental realization of such a setup.
Intrusion Detection Framework for Industrial Internet of Things Using Software Defined Network

The Industrial Internet of Things (IIoT) refers to the employment of the Internet of Things in industrial management, where a substantial number of machines and devices are linked and synchronized with the help of software programs and third platforms to improve the overall productivity. The acquisition of the industrial IoT provides benefits that range from automation and optimization to eliminating manual processes and improving overall efficiencies, but security remains to be forethought. The absence of reliable security mechanisms and the magnitude of security features are significant obstacles to enhancing IIoT security. Over the last few years, alarming attacks have been witnessed utilizing the vulnerabilities of the IIoT network devices. Moreover, the attackers can also sink deep into the network by using the relationships amidst the vulnerabilities. Such network security threats cause industries and businesses to suffer financial losses, reputational damage, and theft of important information. This paper proposes an SDN-based framework using machine learning techniques for intrusion detection in an industrial IoT environment. SDN is an approach that enables the network to be centrally and intelligently controlled through software applications. In our framework, the SDN controller employs a machine-learning algorithm to monitor the behavior of industrial IoT devices and networks by analyzing traffic flow data and ultimately determining the flow rules for SDN switches. We use SVM and Decision Tree classification models to analyze our framework’s network intrusion and attack detection performance. The results indicate that the proposed framework can detect attacks in industrial IoT networks and devices with an accuracy of 99.7%.
Fifty years of forecasting chaos and the shadow of imperfect models

In this contribution we review progress on the problem of forecasting chaotic dynamical systems. The nature of chaos was initially illusive, having escaped discovery by several great minds who were in a position to find it. Once the essential features of chaos were uncovered, the concept greatly influenced the thinking of physicists and forecasters, in particular, it brought into focus the limitation of forecasting nonlinear dynamical systems. This resulted in a dichotomy between prediction methods for (nearly) linear systems and nonlinear systems; the important features and distinctions of these two approaches are reviewed. An important issue that arises is the role of model error in forecasting; many methods either ignore or over-simplify the nature of model error, largely because this allows adaption of existing techniques. Finally it is argued that the Isis Programme (Imperfect-model Shadowing and Indistinguishable States) provides a theoretical and practical basis for dealing with all sources of uncertainty, including observational noise and model error.
Changes in the Bacterial Community Composition of Cultivated Soil after Digging up Operations for Laying a Pipeline

Our study aimed to evaluate the impact of the pipeline installation on the bacterial composition in cultivated soil by metagenomic analyses performed before the excavation and in the following three years. Differential abundance analysis was obtained using DESeq2 from the GAIA pipeline to verify the bacteriological diversity in soils collected after the reference year (2013). Soil samples presented a different distribution of taxa, especially in 2014, in which a further allocation at the phylum and family levels was observed compared to the previous year (2013). The phyla Bacteroidetes and Firmicutes increased significantly, while the phylum Actinobacteria, most abundant in 2013, showed reduced abundance; moreover, Chloroflexi and Planctomycetes decreased considerably, and Verrucomicrobia was absent. The significant differences in the taxonomic composition and structure of the soil microbial community were due to critical stress conditions following the soil excavations. The bacterial communities were capable of profound physiological and genetic changes, implementing different mechanisms for survival and adaptation to an environment with changed conditions. The implication of changes in microbial diversity before and after the mechanical insult of soil has been determined.
A discontinuous Galerkin method/HLLC solver for the Euler equations

This paper proposes a fully three‐dimensional non‐linear Euler methodology for solving aerodynamic and acoustic problems in the presence of strong shocks and rarefactions. It uses a discontinuous Galerkin method (DGM) within the element, and a Riemann solver (HLLC) at the boundaries to propagate rarefactions while preserving the entropy condition and capturing shocks with no spurious oscillations. This approach is thought to marry the best aspects of finite element and finite volume methods, achieving conservation while not requiring the solution of a large matrix. Examples in which shock and rarefaction waves are well captured are presented and the propagation of acoustic pulses is well demonstrated. Copyright © 2003 John Wiley & Sons, Ltd.
Multifunctional Oxidized Dextran Cross-Linked Alkylated Chitosan/Drug-Loaded and Silver-Doped Mesoporous Bioactive Glass Cryogel for Hemostasis of Noncompressible Wounds

Noncompressible wounds resulting from accidents and gunshots are typically associated with excessive bleeding, slow wound healing, and bacterial infection. Shape-memory cryogel presents great potential in controlling the hemorrhaging of noncompressible wounds. In this research, a shape-memory cryogel was prepared using a Schiff base reaction between alkylated chitosan (AC) and oxidized dextran (ODex) and then incorporated with a drug-laden and silver-doped mesoporous bioactive glass (MBG). Hydrophobic alkyl chains enhanced the hemostatic and antimicrobial efficiency of the chitosan, forming blood clots in the anticoagulated condition, and expanding the application scenarios of chitosan-based hemostats. The silver-doped MBG activated the endogenous coagulation pathway by releasing Ca2+ and prevented infection through the release of Ag+. In addition, the proangiogenic desferrioxamine (DFO) in the mesopores of the MBG was released gradually to promote wound healing. We demonstrated that AC/ODex/Ag-MBG DFO(AOM) cryogels exhibited excellent blood absorption capability, facilitating rapid shape recovery. It provided a higher hemostatic capacity in normal and heparin-treated rat-liver perforation-wound models than gelatin sponges and gauze. The AOM gels simultaneously promoted infiltration, angiogenesis, and tissue integration of liver parenchymal cells. Furthermore, the composite cryogel exhibited antibacterial activity against Staphylococcus aureus and Escherichia coli. Thus, AOM gels show great promise for clinical translation in treating lethal, noncompressible bleeding and the promotion of wound healing.
Penerapan Aplikasi Sistem Keuangan Desa Dalam Pengelolaan Dana Desa Sipare-Pare Tahun 2021

This study aims to determine the application of the Village Finance system in the management of Si Pare-Pare village funds in 2021. By using a descriptive method with a qualitative approach. The subject of this research is SiPare-pare Village in 2021, and the object of this research is the application of the village financial system. Data collection techniques used were interviews with 10 informants and observation. Then the data were analyzed by data reduction, data presentation and drawing conclusions. The results of the research on the Application of the Siskeudes Application in the Management of Village Funds for the 2021 fiscal year Sipare-pare Village, Kec. District white water Coal, namely with consideration of inefficient expenditure and income, in 2021 the efficiency ratio is 101.2 %, indicating that the performance is less efficient. And based on the level of development, the application of the Siskeudes Application at the Sipare-Pare village office can be concluded that the efficiency level gets 101.2%, this shows what has happened in the financial management of the Sipare-pare village is still less effective even though the implementation of the Siskeudes Application in the Management of Village Funds for the 2021 Fiscal Year continues to run but is still said or can not be categorized as sufficient or efficient. Keywords: SISKEUDES Application, Village Fund, Sipare-pare
Assessment of the Incentive Rate to Favor the Energy Retrofit of Public Buildings: A Comprehensive Approach for an Italian University Facility

The Renovation Wave for Europe highlighted the role of the public building stock for which Directive 2012/27/EU has set an annual renewal rate of 3%, which should rise to reach the goal of decarbonization by 2050. In this paper, the energy retrofit of an educational building—at the academic level—in Southern Italy was investigated. The aim was to evaluate the incentive share, which could accelerate the energy efficiency process, to achieve a cost-effective nZEB. The results show that the highest incentive rate is required for interventions on the opaque building envelope, which are also those that allow the least energy savings. An incentive rate of about 45% for the energy efficiency of the transparent envelope is necessary to reduce the payback time by about 7 years. The efficiency of the plants and the installation of a PV system are energetically and economically convenient even without forms of economic incentive. Finally, if the building is brought to high energy standards—a primary energy saving of 46% and energy class A3—an incentive rate of 40% is required to repay the intervention in about 10 years.
Cool carbon stars in the halo

We present new results from an ongoing survey of carbon-rich asymptotic giant (AGB) stars in the halo of our Galaxy. After selecting candidates primarily through their 2MASS colours, slit spectroscopy was achieved at the ESO NTT telescope. Twenty-one new AGB carbon stars were discovered, increasing the total of presently known similar AGB C stars to ∼120. A further four were observed again in order to confirm their carbon-rich nature and measure radial velocities. Two main findings emerge from this work. First, we found a C star located at ≈130 kpc from the Sun and at b = −62 ◦ . This distant star is remarkably close (5 kpc) to the principal plane of the Stream of the Sagittarius dwarf galaxy, and is likely to be a tracer of a distant poorly populated southern warp of the Stream. Such a warp is predicted by model simulations, but it passes ∼45 kpc from that star. The second result is that, mainly in the North, several already known or newly discovered AGB carbon stars lie far, up to 60 kpc, from the mean plane of the Sagittarius Stream.
Studies in the Mathematical Theory of Inventory and Production, by K.J. Arrow, S. Karlin, H. Scarf with contributions by M.J. Beckmann, J. Gessford, R.F. Muth. Stanford, California, Stanford University Press, 1958, X p.340p., $ 8.75.

The Assessment Division of The Applied Physics Laboratory has undertaken new responsibilities and is expanding its Senior Analytical Staff. Senior Scientists in such fields as Mathematics, Physics and Physical Chemistry have in the past proven very effective in solving the types of problems involved which include analyses of tactical situations, the employment of future weapon systems and the application of the most recent advances in science and technology. Performance of the work requires close association with scientists of other laboratories, operations research personnel of all branches of the Armed Services, and with senior military and civilian personnel. Studies undertaken by this group will provide guide lines for the hardware research of future years. Staff members are expected to initiate ideas in support of a broad program of National Defense needs and carry them through appropriate analyses with assurance that sound results will be given consideration by the responsible agencies. The Laboratory's locale, equidistant between Baltimore and Washington, D. C , allows staff members to select urban, suburban or rural living and either of these two outstanding centers of culture as a focal point for fine living. These appointments offer exceptional opportunities. For information and arrangements for interview, write in confidence to:
Incorporating High-Speed Rail Development Scenario for Tourism Land Use Simulation: A Case Study of Xinxing County, China

High-speed rail (HSR) has been proven to drive the development of regional tourism. However, few studies paid attention to the impact of HSR on future tourism land use. In this study, points of interest (POI) were used to obtain the locations and types of tourism facilities, and high-resolution remote sensing images helped us determine the spatial extents of the tourism facilities, so that tourism land could be identified. A system dynamics (SD) model was coupled with the patch-generating land use simulation (PLUS) model to simulate future tourism land by considering two scenarios, including HSR-led development (HRD) and the historical development pattern (HD) scenario. The SD model was employed to project the amount of tourism land and determine the HSR effects via empirical analysis. The PLUS model was applied to simulate the spatial distribution of tourism land and model the HSR effect by adopting a planned tourism area as the development area. The study area is Xinxing County in Guangdong Province, China, a county dominated by rural tourism, with the HSR expected to open in 2025. The results revealed that the SD-PLUS model has great advantages in simulating tourism land use change, and the HRD scenario leads to major changes in the sources of tourism land growth. This research provides new insights for policymakers on making countermeasures for the sustainability of tourism and rural revitalization at the county level.
A New Deep-Learning-Based Model for Breast Cancer Diagnosis from Medical Images

Breast cancer is one of the most prevalent cancers among women worldwide, and early detection of the disease can be lifesaving. Detecting breast cancer early allows for treatment to begin faster, increasing the chances of a successful outcome. Machine learning helps in the early detection of breast cancer even in places where there is no access to a specialist doctor. The rapid advancement of machine learning, and particularly deep learning, leads to an increase in the medical imaging community’s interest in applying these techniques to improve the accuracy of cancer screening. Most of the data related to diseases is scarce. On the other hand, deep-learning models need much data to learn well. For this reason, the existing deep-learning models on medical images cannot work as well as other images. To overcome this limitation and improve breast cancer classification detection, inspired by two state-of-the-art deep networks, GoogLeNet and residual block, and developing several new features, this paper proposes a new deep model to classify breast cancer. Utilizing adopted granular computing, shortcut connection, two learnable activation functions instead of traditional activation functions, and an attention mechanism is expected to improve the accuracy of diagnosis and consequently decrease the load on doctors. Granular computing can improve diagnosis accuracy by capturing more detailed and fine-grained information about cancer images. The proposed model’s superiority is demonstrated by comparing it to several state-of-the-art deep models and existing works using two case studies. The proposed model achieved an accuracy of 93% and 95% on ultrasound images and breast histopathology images, respectively.
The Influence of Soil and Vegetation on the Development of Mesoscale Circulations

Abstract A two-dimensional mesoscale model including a detailed representation of the planetary boundary layer, the soil and the vegetation is developed. A sea breeze over flat terrain is simulated, thereby confirming the ability of the model to reproduce the known properties of this mesoscale phenomenon. The atmospheric response to soil and vegetation inhomogeneities is then examined with no synoptic flow over flat terrain. The results reveal the large influence of soil texture on surface moisture availability. The transition zone between bare soil and vegetation appears to be a preferred location for the initiation of moist convection. A vegetation canopy over very dry or very wet surfaces reduces the spread between sensible and latent heat fluxes.
Hypoglycemic Response of Alloxan-Induced Diabetic Rats Fed with Sweet ‎Potato (Ipomoea Batatas) and Irish (Solanum Tuberosum) Potato Flour ‎Supplemented with Vitamins

The hypoglycemic effect of feeding normal and alloxan-induced diabetic rats with Sweet Potato (Ipomoea batatas)and Irish Potato (Solanum tuberosum)flour fortified with vitamin for 21 days was studied. Forty-five white albino rats were divided into groups of five rats each. The groups are Normal control, Normal control + diet, positive control, negative control, test control 1 and test control 2. Fasting blood glucose and 2 hours post-prandial were measured at 7 days, 14 days and 21 days. It was found that sweet potato and irish potato flour diet significantly (P<0.05) reduced the fasting blood glucose and 2 hours post-prandial blood glucose compared with those of diabetic and normal rats fed with control diet. Maximum reduction in fasting and 2 hours post-prandial blood glucose was observed at day 21 with 119.6 ± 5.59 mmol/L in the sweet potato fed group compared to the diabetic control (223.6 ± 9.31mmol/L and normal control (106.6 ± 7.83) mmol/L. While the Irish potato group had (133 ± 2.45) mmol/L, compared to the diabetic control (233.6 ±9.31) mmol/L and normal control (106.6 ±7.83) mmol/L. However Sweet potato showed a better hypoglycemic effect than irish potato. This shows that the hypoglycemic effect of sweet and irish potato is time dependent.
Probability and Randomness: Quantum Versus Classical

Creating a rigorous mathematical theory of randomness is far from being complete, even in the classical case. Probability and Randomness: Quantum versus Classical rectifies this and introduces mathematical formalisms of classical and quantum probability and randomness with brief discussion of their interrelation and interpretational and foundational issues. The book presents the essentials of classical approaches to randomness, enlightens their successes and problems, and then proceeds to essentials of quantum randomness. Its wide-ranging and comprehensive scope makes it suitable for researchers in mathematical physics, probability and statistics at any level.
Applied Research of the UAV Illumination Measurement System in Sports Stadiums

In this paper, an illumination measurement system is proposed and experimentally demonstrated. The system consists of two parts, including the illumination acquisition module mounted on the UAV and the real-time display interface of the cloud platform with control functions. The illuminance acquisition module consists of a light sensor, a distance sensor, a wireless communication module, and a power-supply component. For the other part, the OneNET cloud platform developed by China Mobile is chosen as the display interface for the system’s real-time data. In addition, the local-outlier factor (LOF) algorithm is used for outlier rejection to further improve the stability and accuracy of the system. The illuminance acquisition system designed and implemented was then applied to the illuminance measurement experiments in the stadium. In experiments, the illuminance data acquired by the system was used to investigate the illuminance distribution at different height levels in the stadium. It was learned that the root mean square error (RMSE) of the data acquired is calculated to be 2.45 compared to the illuminance standard values through experimentation, with an error range of −2.77% to −0.53% for dynamic measurements.