Miracle-dz/UniFAR-FTUs huggingface dataset:
Environmental Assessment of Al-Hammar Marsh Sediments, Southern Iraq

Concentrations and distribution of major, minor, and trace elements were studied in thirteen sediment samples from Al-Hammar Marsh. Multivariate statistical techniques such as Principal Component Analysis (PCA) and Agglomerative Hierarchal Cluster Analysis (AHCA) as well as pollution analysis such as Enrichment Factor (EF) were used to process the data and identify the possible sources of elemental constituents in sediment samples.Results of chemical analysis revealed that Major element mean concentrations were in the order of Ca> Si> K> Mg> and minor elements were in the order of Al> Fe>S>Cl> Ti> P>Mn> Sr> N and trace elements were in the order of Cr> Ni> Zr>V>Zn> Cu>Br> Co>Pb >Mo>As>U> Se> Cd. Mainly increasing of Salinity in Marsh water and sediments led to increasing of Mg, S, Ca, Br, Cl concentrations in Al-Hammar Marsh Sediments. Multivariate statistical techniques PCA and AHCA revealed that V, Zn, As, Se, Mo, Pb, Co, Fe, Ni, and Cu were most probably derived from fertilizers and petroleum extraction wastes in and near the study site. U (at StR1R) and Sr came from fertilizers and for U might be from military weapon. Br, Cd, Cl, Ca, S, P and N indicated anthropogenic source (fertilizers, animal waste, and domestic sewage). While Mg, Cr, Mn were mainly associated with anthropogenic activities (fertilizers and animal wastes). On the other hand Al, Si, Ti, K، and Zr were primarily of natural sourcing from erosion of parent rocks. Enrichment Factor gave compatible results with PCA and AHCA findings and revealed that Al-Hammar Marsh sediments were highly contaminated by S, Mg, Cl, Ca, P, Br, Se, Mo, Ni, Co, Cu, and Sr. and it were minimally contaminated by Zn, V, U, Cr (excluding SR3R), As, Fe, Mn, and N.
Revenue Forecasting for Enterprise Products

For any business, planning is a continuous process, and typically business-owners focus on making both long-term planning aligned with a particular strategy as well as short-term planning that accommodates the dynamic market situations. An ability to perform an accurate financial forecast is crucial for effective planning. In this paper, we focus on providing an intelligent and efficient solution that will help in forecasting revenue using machine learning algorithms. We experiment with three different revenue forecasting models, and here we provide detailed insights into the methodology and their relative performance measured on real finance data. As a real-world application of our models, we partner with Microsoft's Finance organization (department that reports Microsoft's finances) to provide them a guidance on the projected revenue for upcoming quarters.
Multiple Sclerosis

Multiple sclerosis (MS) is a demyelinating disease of the central nervous system that commonly leads to inﬂammatory and atrophic brain pathology, often causing cognitive impairment. MS-associated cognitive impairment was ﬁrst described over a century ago. However, with the advent of standardized neuropsychological testing and quantitative brain imaging, the frequency, quality, and correlates of cognitive impairment are better understood. Dementia is rare in MS, although it is known to occur in 10 to 25% of patients. Our data suggest a frequency of 22% among clinic attendees. In addition to the cognitive impairments evident in MS dementia, changes in personality and social behavior also occur. For example, some patients develop euphoria sclerotica and marked deﬁciency in social empathy, conditions that in combination with executive dysfunction cause considerable hardship for patients and caregivers. These neuropsychiatric manifestations of MS dementia are correlated with magnetic resonance imaging indicators of brain atrophy, including ventricle enlargement, neocortical volume, and normalized whole brain volume. Recent developments in pharmacological treatment for disease progression and management of cognitive symptoms hold promise for patients suffering from the degenerative aspects of MS.
A SIR-UC EPIDEMIC MODEL: THE ANALYSIS OF SUSCEPTIBLE-INFECTED-REMOVED (SIR) EPIDEMIC MODEL WITH THE COVERAGE OF HEALTH INSURANCE (UNCOVERED AND COVERED INDIVIDUALS)

Susceptible-Infected-Removed (SIR) model is a widely used epidemic model that simulates the spread of infectious diseases within a population. It classifies individuals into susceptible, infected, and removed states, with the number of individuals in each state being time-dependent variables denoted by S(t), I(t), and R(t), respectively. The model considers direct contact transmission between infected and susceptible individuals. In developed countries, some people cannot afford medical treatment. In contrary, the recovery rate of infected individual in the population is directly proportional to the number of people receiving medical treatment. Affordable health insurance increases the number of people receiving medical treatment thus insurance should be considered aspect in epidemic model. The main purpose of this research is to analyze the effect of insurance on the SIR epidemic model. This research classifies individuals in both S(t) and I(t) based on their insurance coverage status. This model assumes permanent immunity for R(t), thus it is unnecessary to classify individuals in this state based on their insurance coverage status because they do not spread the disease nor have potential to be re-infected. Numerical simulation is organized to find the effect of insurance in SIR model by analyzing the equilibrium point. The result based on the equilibrium point suggests that the insurance in SIR epidemic model: (1) decrease the I(t) because it accelerate the recovery rate; (2) decrease theR(t) because there is less infected people for recovery; (3) increase the S(t) because there is less infected people to transmit the disease, compared to the SIR model without the insurance.
The new mutation, E46K, of α‐synuclein causes parkinson and Lewy body dementia

Familial parkinsonism and dementia with cortical and subcortical Lewy bodies is uncommon, and no genetic defect has been reported in the previously described sibships. We present a Spanish family with autosomal dominant parkinsonism, dementia, and visual hallucinations of variable severity. The postmortem examination showed atrophy of the substantia nigra, lack of Alzheimer pathology, and numerous Lewy bodies which were immunoreactive to α‐synuclein and ubiquitin in cortical and subcortical areas. Sequencing of the α‐synuclein gene showed a novel, nonconservative E46K mutation in heterozygosis. The E46K mutation was present in all affected family members and in three young asymptomatic subjects, but it was absent in healthy and pathological controls. The novel mutation, that substitutes a dicarboxylic amino acid, glutamic acid, with a basic amino acid such as lysine in a much conserved area of the protein, is likely to produce severe disturbance of protein function. Our data show that, in addition to the previously described hereditary α‐synucleinopathies, dementia with Lewy bodies is related to mutation of α‐synuclein.
HyperCuP – Hypercubes , Ontologies and Efficient Search on P 2 P Networks

Peer-to-peer networks are envisioned to be deployed for a wide range of applications. However, P2P networks evolving in an unorganized manner suffer from serious scalability problems, limiting the number of nodes in the network, creating network overload and pushing search times to unacceptable limits. We address these problems by imposing a deterministic shape on P2P networks: We propose a graph topology which allows for very efficient broadcast and search, and we describe a broadcast algorithm that exploits the topology to reach all nodes in the network with the minimum number of messages possible. We provide an efficient topology construction and maintenance algorithm which, crucial to symmetric peer-to-peer networks, does neither require a central server nor super nodes in the network. Nodes can join and leave the self-organizing network at any time, and the network is resilient against failure. Moreover, we show how our scheme can be made even more efficient by using a global ontology to determine the organization of peers in the graph topology, allowing for efficient concept-based search.
Assembly of complex organelles: pilus biogenesis in gram-negative bacteria as a model system.

Pathogenic bacteria assemble a variety of adhesive structures on their surface for attachment to host cells. Some of these structures are quite complex. For example, the hair-like organelles known as pili or fimbriae are generally composed of several components and often exhibit composite morphologies. In gram-negative bacteria assembly of pili requires that the subunits cross the cytoplasmic membrane, fold correctly in the periplasm, target to the outer membrane, assemble into an ordered structure, and cross the outer membrane to the cell surface. Thus, pilus biogenesis provides a model for a number of basic biological problems including protein folding, trafficking, secretion, and the ordered assembly of proteins into complex structures. P pilus biogenesis represents one of the best-understood pilus systems. P pili are produced by 80-90% of all pyelonephritic Escherichia coli and are a major virulence determinant for urinary tract infections. Two specialized assembly factors known as the periplasmic chaperone and outer membrane usher are required for P pilus assembly. A chaperone/usher pathway is now known to be required for the biogenesis of more than 30 different adhesive structures in diverse gram-negative pathogenic bacteria. Elucidation of the chaperone/usher pathway was brought about through a powerful combination of molecular, biochemical, and biophysical techniques. This review discusses these approaches as they relate to pilus assembly, with an emphasis on newer techniques.
Combined Effect of frans-Diamminedichloroplatinum(ll) and Hyperthermia on Murine and Human Tumor Cells1

frans-Diamminedichloroplatinum(ll), a paradigm of an inactive platinum compound, exhibited cytotoxic effect against HEP-2 human tumor cells, TA3Ha murine tumor cells, and freshly col lected human ovarian carcinoma cells when combined with hyperthermia (43Â°,30 min). The heat treatment reduced the D0 of frans-platinum from 56 to 16.5 ng/m\ in the HEP-2 system and from an undeterminable value at 37Â°to 8.2 jig/ml in the TASHa system. Heat treatment before frans-platinum was more cyto toxic than that after frans-platinum in the TASHa system (P < 0.001). TASHa cells treated in vitro with 40 ng/m\ TDDP at 43Â° failed to form tumors in mice upon subcutaneous implantation into the tails of mice. In contrast, these agents given singly did not alter the tumor-forming ability of TASHa cells. In vivo admin istration of frans-platinum after hyperthermia (43Â°for 30 min) retarded the growth of TASHa tumors compared to either treat ment alone. frans-Platinum did not form detectable DNA-interstrand cross links in the HEP-2 cells treated at 37Â°or 43Â°. However, the DNA-protein cross-links were detectable under these conditions. The frequencies of DNA-protein cross-links were higher in the cells treated at 43Â°than in those treated at 37Â°,both immediately after and 12 h after the treatment with frans-platinum. Heat alone did not induce the formation of either DNA-interstrand or DNA-protein cross-links. Heat treatment did not appear to enhance the entry of frans-platinum into the cells.
FORECASTING THE NUMBER OF AIRPLANE PASSENGERS USING HOLT WINTER'S EXPONENTIAL SMOOTHING METHOD AND EXTREME LEARNING MACHINE METHOD

Airplanes provide comfort and speed for their users, especially for those who have limited time. The number of passengers has continued to increase in the last few months at Ahmad Yani International Airport, so a forecast is needed in making decisions to predict the number of passengers in order to maximize existing performance. The data used is secondary data on the number of airplane passengers at Ahmad Yani International Airport from 2012 to 2022 obtained from PT Angkasa Pura 1 (Persero). The Holt Winters Exponential Smoothing method is used because it aligns with the data pattern that includes trends and seasonality in the research, and it has a low level of accuracy. In this study also used the Extreme Learning Machine (ELM) method, apart from being a relatively new method, it has a fast learning speed and has low accuracy. This study aims to predict the number of airplane passengers at Ahmad Yani International Airport in Semarang using the Holt Winters Exponential Smoothing and ELM methods. The results of the analysis show that the MAPE value in the Holt Winters Exponential Smoothing method is 8,18% and in the ELM method using 12 input neurons and 43 neurons in the hidden layer, a MAPE of 6,04% is obtained. so that the ELM method is the right method for predicting the number of airplane passengers at Ahmad Yani International Airport in Semarang.
Mean flow and turbulence responses in airflow over foredunes: New insights from recent research

^^^^^ ^^^^^ ^^^^^ ^^ ^^ H Walker, I.J., R.G. D. Davidson-Arnott, P.A. Hesp, B.O. Bauer, and J. Ollerhead, 2009. Mean flow and turbulence responses in airflow over foredunes: Has new instrumentation improved our understanding? Journal of Coastal Research, SI 56 (Proceedings of the 10th International Coastal Symposium), 366 370. Lisbon, Portugal, ISSN 0749-0258 This paper reviews recent progress in quantifying airflow over foredunes using traditional velocity profiles, location-specific time-averaged flow properties, vectors of non-uniform flow, and turbulence measurements. Though velocity profiles remain essential for characterizing flow structure, their use for estimating shear stress is limited as near-surface airflow is often non-uniform and unsteady. Topographic forcing and roughness effects produce distinct inflection points, slope segments, and shear layers. Further limitations result from the bulkiness of conventional instruments that are unable to measure within the thin constant stress region over dunes. Popu lations of time-averaged flow properties and flow vectors reveal location-specific flow responses to changing incident wind conditions and resulting topographic forcing and steering effects. For instance, streamwise ve locity and steadiness are sensitive to topographic forcing on the stoss slope, but not at the dune toe due to the dominance of flow stagnation. Vertical velocity is most responsive at the crest and to changes in incident flow angle. Flow vectors are deflected onshore and resulting transport pathways have greater effective fetch than those identified by the regional wind. This response also varies with height above the surface and for incident angle and speed.Continued field research with turbulence instruments is needed to validate simulated and wind tunnel findings of turbulent Reynolds stresses over dunes and assess implications for sand transport, such as the role of micro-turbulent events in grain entrainment and transport. ADDITIONAL INDEX WORDS: aeolian, beach, sediment transport, ultrasonic anemometers
3-D Range Imaging Using Stripe-Like Illumination and SPAD-Based Pulsed TOF Techniques

A solid-state three-dimensional (3-D) range imager using the pulsed time-of-flight principle and a single photon avalanche diode (SPAD) based receiver is demonstrated. Contrary to conventional flood illumination, the suggested system uses sequentially scanned illumination stripes to increase the irradiance under the measured field of view and to reduce the receiver complexity. At equal average illumination power levels this approach increases the signal-to-noise ratio in the receiver enabling thus longer range and/or better performance in high background illumination conditions, albeit at the cost of lower transversal resolution. The transmitter uses eight sequentially driven laser diodes, each of which produces an optical pulse power, length and wavelength of ∼50 W, 2 ns and 905 nm, respectively at a pulse rate of ∼30 kHz so that the total effective pulsing rate is ∼250 kHz and the average illumination power is ∼30 mW. 3-D imaging is demonstrated outdoors in over 50 klux ambient lighting up to ∼10 m distance with 15 Hz frame rate and mm–cm level longitudinal precision in a field of view of about 40 × 10 degrees. The transversal resolution of the system is 16 × 128 pixels. The measurement results show 3-D measurement precision scaling according to the laser pulse width and averaging.
Effect of preventive treatment for tuberculosis in adults infected with HIV: systematic review of randomised placebo controlled trials

Objective: To determine whether preventive treatment for tuberculosis in adults infected with HIV reduces the frequency of tuberculosis and overall mortality. Design: Systematic review and data synthesis of randomised placebo controlled trials. Main outcome measures: Active tuberculosis, mortality, and adverse drug reaction requiring cessation of the study regimen. Outcomes stratified by status of purified protein derivative skin test. Results: Four trials comprising 4055 adults from Haiti, Kenya, the United States, and Uganda were included. All compared isoniazid (6-12 months) with placebo, and one trial also compared multidrug treatment for 3 months with placebo. Mean follow up was 15-33 months. Overall, frequency of tuberculosis (relative risk 0.57, 95% confidence interval 0.41 to 0.79) was reduced in those receiving preventive treatment compared with placebo: mortality was not significantly reduced (0.93, 0.83 to 1.05). In subjects positive for purified protein derivative receiving preventive treatment, the risk of tuberculosis was reduced substantially (0.32, 0.19 to 0.51) and the risk of death was reduced moderately (0.73, 0.57 to 0.95) compared with those taking placebo. In adults negative for purified protein derivative receiving preventive treatment, the risk of tuberculosis (0.82, 0.50 to 1.36) and the risk of death (1.02, 0.89 to 1.17) were not reduced significantly. Adverse drug reactions were more frequent, but not significantly so, in patients receiving drug compared with placebo (1.45, 0.98 to 2.14). Conclusions: Preventive treatment given for 3-12 months protects against tuberculosis in adults infected with HIV, at least in the short to medium term. Protection is greatest in subjects positive for purified protein derivative, in whom death is also less frequent. Long term benefits remain to be shown.
Two Antigenic Peptides from Genes m123 and m164 of Murine Cytomegalovirus Quantitatively Dominate CD8 T-Cell Memory in the H-2d Haplotype

ABSTRACT The importance of CD8 T cells for the control of cytomegalovirus (CMV) infection has raised interest in the identification of immunogenic viral proteins as candidates for vaccination and cytoimmunotherapy. The final aim is to determine the viral “immunome” for any major histocompatibility complex class I molecule by antigenicity screening of proteome-derived peptides. For human CMV, there is a limitation to this approach: the T cells used as responder cells for peptide screening are usually memory cells that have undergone in vivo selection. On this basis, pUL83 (pp65) and pUL123 (IE1 or pp68 to -72) were classified as immunodominant proteins. It is an open question whether this limited “memory immunome” really reflects the immunogenic potential of the human CMV proteome. Here we document an analogous focus of the memory repertoire on two proteins of murine CMV. Specifically, ca. 80% of all memory CD8 T cells in the spleen as well as in persisting pulmonary infiltrates were found to be specific for the known IE1 peptide 168YPHFMPTNL176 and for the peptide 257AGPPRYSRI265, newly defined here, derived from open reading frame m164. Notably, CD8 T-cell lines of both specificities protected against acute infection upon adoptive transfer. In contrast, the natural immune response to acute infection in draining lymph nodes and in the lungs indicated a somewhat broader specificity repertoire. We conclude that the low number of antigenic peptides identified so far for CMVs reflects a focused memory repertoire, and we predict that more antigenic peptides will be disclosed by analysis of the acute immune response.
Medical image segmentation via coupled curve evolution equations with global constraints

In this work the authors modify the coupled curve evolution approach to snakes presented by the authors in previous work for bimodal and trimodal imagery through the introduction of global constraints. The key idea, as before, is to derive curve evolution equations which "pull apart" the values of one or more statistics within the image. However, by imposing a new constraint on the evolution of these statistics, the authors are able to segment a larger class of medical imagery for which their original model would fail.
Algebraic modelling of an ad hoc network for mobile computing

We develop an algebraic model of an ad hoc network (Johnson, 1994) for mobile computing. The ad hoc network's structure and functionality is based (in our approach) on a pathset algebra. A pathset is the set of all paths in the network having specific source(s) and destination(s). The pathsets' set refers to a multi-digraph that constitutes the physical infrastructure of an ad hoc network. The applications, actions, and/or services (referred further under the general term services) are organized as multi-agent systems. The formal model of every multi-agent system is based on a modal algebra. An additional function (or special operation) couples the two algebras specifying thus the interface of their interoperability. This operation is analogous to the scalar multiplication of a vector space on a field.
Design Patterns for Legal Ontology Constructions

Ontology design is known to be a difficult task, requiring much more than expertise in an area; legal ontology design, due to the complexity of its domain, makes those difficulties worse. That may be partly due to poor requirement analysis in existing tools, but there is also an inherent gap between the purely logical constructs and methods that are expected to be used, and the actual competences and thought habits of domain experts. This paper presents some solutions, based on content ontology design patterns, which are intended to make life of legal ontology designers easier. An overview of the typical tasks and services for legal knowledge is presented, the notion of ontology design pattern is introduced, and some excerpts of a reference ontology (CLO) and its related patterns are included, showing their utility in a simple legal modeling case
An Explicit Data-Driven Model for Estimation of Free and Absorbed Gas Volumes in Shale Gas Reservoirs

Shale gas reservoir fluid flow is characterized by complex interactions between a number of variables, including stress sensitivity, matrix shrinkage, and critical desorption pressure. The behavior and productivity of shale gas reservoirs are significantly influenced by these variables. Therefore, in this study, an in-house finite element poro-elastic simulator was integrated with an in-house Fortran-coded artificial neural network model for accurate estimation of free and absorbed gas volumes in shale gas reservoirs, taking into account the combined effects of stress sensitivity, matrix shrinkage, and critical desorption pressure. The in-house finite element simulator was used to create a database of free and absorbed gas volumes under different reservoir, fluid, and geo-mechanical characteristics of shale gas, while the in-house neural network code was utilized using the outcomes of the poro-elastic simulator in order to propose an explicit data-driven mathematical formula of free and absorbed volumes of shale gas. The study findings indicate that the neural network model achieved high accuracy with an R-squared value exceeding 99% during both the training and blind-testing phases. The newly developed ANN-based correlations can be used as a quick and easy-to-use tool to forecast the volume of shale gas in place both free and adsorbed without any prior experience with utilizing or implementing machine learning models.