Miracle-dz/UniFAR-FTUs huggingface dataset:
Predicting Stock Market Trends Based on Macroeconomic Indicators through Machine Learning Approach: A Case Study of KSE 100 INDEX

The purpose of our research is to model the monthly price of the KSE 100 index based on Pakistan's macroeconomic indicators using a Machine Learning (ML) approach. The novelty of the study is forecasting the future value of the stock market using ML. Monthly data was collected for the period from Feb 2004 to Dec 2020. The output layer of our study is the closing price of the KSE 100 index, and the input layer consists of 16 macroeconomic variables of the Pakistan economy, which are the industrial production index (IPI), the exchange rate (EX-RATE), money supply (M2), consumer price index (CPI), foreign direct investment (FDI), Treasury bill on 3-months treasury, interest rate as KIBOR – Month Average (1 Month), Foreign Exchange reserves (FXR), Consumer Financing for house building (house financing), Balance of Trade (BOT), crude oil, Gold, Labor force participation rate, GDP growth (annual %), Households and NPISHs Final consumption expenditure (household consumption) (current US$), and Domestic savings. The prediction uses the Artificial Neural Network (ANN) Backpropagation algorithm. The model developed in this research achieved 99% accuracy using macroeconomic indicators. The accuracy level indicates that the model of the KSE 100 index can predict future trends. This study also forecasts the future monthly values of the KSE 100 index from Jan 21 to Jun 23 and daily future values from Oct 1, 2022, to Dec 31, 2020.
Serum Level of Interleukin-31 in Patients with Uremic Pruritus Undergoing Hemodialysis

: Background: Uremic pruritus is a common symptom in patients with end-stage renal disease who are undergoing maintenance hemodialysis. This symptom is frequently refractory to most treatments, and is associated with substantial medical, psychological, and social disturbances in patients receiving dialysis. This study aimed to estimate serum level of IL31, in patients with uremic pruritus and to relate it with different clinical parameters. Methods: This was a prospective case-control study conducted on participants recruited from the hemodialysis unit of the Urology and Nephrology Center, Mansoura University. Results: serum IL-31 is significantly higher in patients receiving hemodialysis with pruritus symptoms, along with a positive exposure-response relationship between serum IL-31 and pruritus intensity. Conclusion: Uremic pruritus, is a distressing symptom in end-stage renal disease patients on hemodialysis, which lacks a definitive explanation, though factors like immune processes and IL-31 are considered. Its impact on patients' quality of life varies, making it challenging to characterize. Unraveling mechanisms like IL-31 may guide future treatments for this condition, which significantly affects patients' well-being.
The Standardization of Daruharidradi Ghanavati

Background: Many effective formulations are available in Ayurveda for various diseases. These formulations are lagging in standardization due to the absence of reference standards, whereas maintaining quality standards of given medicines is the need of an hour. Daruharidradi Ghanvati is one such combination of six herbal drugs containing Daruharidra, Meshshrungi, Vijaysar, Mamajjak, Jambubija, and Methikabij. Each drug is described in various Ayurvedic antidiabetic formulations. Aim: The present study was aimed at setting a standard pharmacognostical and pharmaceutical profile of Daruharidradi Ghanavati. Materials and Methods: The study included the preparation of Daruharidradi Ghanavati using raw drugs. Later, Daruharidradi Ghanavati was subjected to pharmacognostical, physiochemical, and thin-layer chromatography analysis as per standard protocols. Results: The final observations were recorded. Pharmacognostical findings matched with that of individual raw drugs with no major change in the microscopic structure of the raw drugs during the preparation of Ghanavati. Conclusion: The quality of Daruharidradi Ghanavati tablet can be tested by pharmacognostical, physiochemical screening for the observations of the present study.
Circulation type classifications for temperature and precipitation stratification in Italy

During the last few decades, weather circulation type classifications (CTCs) have been widely used to gain insight into processes at the synoptic scale, but also for studying the relationship between atmospheric circulation and surface climate variability. This study aims to evaluate the best performing CTCs based on COST733 software for the stratification of daily ground‐level precipitation and surface air temperature across Italy by means of four statistical metrics. Six classification methods belonging to the four COST733 groups (threshold‐based, PCA‐based, leader algorithms and optimization algorithms) were investigated on 32 and 26 data time series derived from Italian weather stations for daily mean temperature and daily mean precipitation, respectively. CTCs were computed using gridded mean sea level pressure and geopotential height at 500 hPa derived from the NCEP Reanalysis 2 dataset between 1979 and 2015 and tested on three different numbers of classes (8/9, 11/12 and 18 circulation types). Evaluation metrics showed an evident seasonal variability and high‐spatial heterogeneity reflecting the geographical complexity of the Italian territory. The study points out that the best classification, both for temperature and precipitation, is strongly dependent on the classification variable (mean sea level pressure and geopotential height at 500 hPa) showing relevant differences between surface temperature and precipitation. A low number of circulation types (8/9) resulted as the most appropriate grouping for the Italian domain and the Principal Component Transversal and Simulated Annealing were the best performing classification procedures for ground‐level precipitation and temperature stratification, respectively.
Review: Winding and Unwinding Webs: A Review of the State of the Science in 2005

A web is a material whose length is much in excess of the width and the width is much larger than the thickness. Various grades of paper, plastic films, metal foils and laminates can all be broadly categorized as webs. Web media are often stored for periods of time in the form of a wound roll. This form of storage is chosen because it is simply the most convenient and often the only form for storing vast lengths of web with minimal damage and loss. Winding can damage the web and has become a topic which has received considerable attention in the literature. Amongst operations in a web process line, the winder and the unwinder are often sites at which web defects appear that may result in a loss of quality or may lead to a break or burst of the web resulting in lost productivity. The purpose of this paper is to review the state of the science of winding and unwinding rolls. The threads of pertinent information in the literature focus on: the stresses that are wound into rolls, how those stresses are affected by the type of winder employed, how those stresses vary during roll storage, how the stresses predicted by models can be used to predict wound roll defects, and finally the measurements that are available to verify modeling efforts or help solve production problems. Each thread will be examined in this review from the perspective of what references exist but also giving enough detail that an appreciation for the significance of a topic can be developed.
Coralline Algae Archive Fjord Surface Water Temperatures in Southwest Greenland

One of the most dramatic signs of ongoing global change is the mass loss of the Greenland Ice Sheet and the resulting rise in sea level, whereby most of the recent ice sheet mass loss can be attributed to an increase in meltwater runoff. The retreat and thinning of Greenland glaciers has been caused by rising air and ocean temperatures over the past decades. Despite the global scale impact of the changing ice sheet balance, estimates of glacial runoff in Greenland rarely extend past several decades, thus limiting our understanding of long‐term glacial response to temperature. Here we present a 42‐year long annually resolved red coralline algal Mg/Ca proxy temperature record from a southwestern Greenland fjord, with temperature ranging from 1.5 to 4 °C (standard error = 1.06 °C). This temperature time series in turn tracks the general trend of glacial runoff from four West Greenland glaciers discharging freshwater into the fjord (all p < 0.001). The algal time series further exhibits significant correlations to Irminger Sea temperature patterns, which are transmitted to western Greenland fjords via the West Greenland Current. The 42‐year long record demonstrates the potential of annual increment forming coralline algae, which are known to live up to 650 years and which are abundant along the Greenland coastline, for reconstructing time series of sea surface temperature.
Fate and transport of free-phase and dissolved-phase hydrocarbons in peat and peatlands: developing a conceptual model

Physical and chemical, and pore-scale to field-scale properties of peat soil affect the migration of non-aqueous phase liquids (NAPLs) and dissolved-phase solutes in contaminated peatlands in a way not anticipated based on the current understanding derived from their behavior in mineral soil systems. Peat pore surface wettability, which is determined by pore surface chemistry, has strong hysteresis and shows hydrophilic and hydrophobic behaviors during water drainage from and water imbibition into pore spaces. This leads to high residual NAPL saturation in pore spaces. Systematic reduction of pore radius size with depth associated with greater peat decomposition in a typical peat profile leads to an increase in NAPL-entry capillary pressure and a reduction in peat permeability with increasing depth. The former leads to stronger capillarity in deeper peat horizons, causing resistance to NAPL percolation compared to that in shallow ones; along with decreased permeability with depth, this results in higher N.
Typisch Frysk? : Stancetaking in the linguistic landscape of Fryslân

Although Westlauwersk Frisian has an official status in the Netherlands, recent studies have revealed an ongoing decrease in the use of Frisian in the family context. At the same time, the language still has a central position in everyday life in the bilingual province of Fryslân. This thesis explores de facto language policies regarding Frisian. More specifically, by using a multimodal approach, it aims to identify stances toward this minority language, indexed in the linguistic landscape of Fryslân. As the linguistic landscape has been regarded as a powerful policy mechanism, both reflecting and influencing language ideologies, and eventually language practices, the study of beliefs beyond naïve signs in Frisian public space might be relevant to language maintenance questions.
Antarctic Summer Sea Ice Trend in the Context of High-Latitude Atmospheric Circulation Changes

AbstractThe potential mechanisms underlying the observed increasing trend in Antarctic summertime sea ice cover for the 1979–2017 period have been investigated using a relatively novel method called the self-organizing map (SOM). Among the nine nodes generated to explain the variability of Antarctic sea ice cover, two (nodes 3 and 7) exhibit a statistically significant linear trend in the time series of the frequency of the SOM pattern occurrence that together explain 40% of the total trend in the sea ice cover. These two nodes have completely opposite spatial patterns and directions of trend and are associated with different atmospheric circulation patterns. Node 3, which represents an increase in sea ice over the Weddell Sea and the eastern Ross Sea and a decrease over the other coastal seas of West Antarctica, appears to be related to the positive phase of the southern annular mode (SAM) linked with the La Nina pattern of sea surface temperature (SST) over the tropical Pacific Ocean. The opposite spati.
High‐Resolution Constraints on Pacific Upper Mantle Petrofabric Inferred From Surface‐Wave Anisotropy

Lithospheric seismic anisotropy illuminates mid‐ocean ridge dynamics and the thermal evolution of oceanic plates. We utilize short‐period (5–7.5 s) ambient‐noise surface waves and 15‐ to 150‐s Rayleigh waves measured across the NoMelt ocean‐bottom array to invert for the complete radial and azimuthal anisotropy in the upper ∼35 km of ∼70‐Ma Pacific lithospheric mantle, and azimuthal anisotropy through the underlying asthenosphere. Strong azimuthal variations in Rayleigh‐ and Love‐wave velocity are observed, including the first clearly measured Love‐wave 2θ and 4θ variations. Inversion of averaged dispersion requires radial anisotropy in the shallow mantle (2‐3%) and the lower crust (4‐5%), with horizontal velocities (VSH) faster than vertical velocities (VSV). Azimuthal anisotropy is strong in the mantle, with 4.5–6% 2θ variation in VSV with fast propagation parallel to the fossil‐spreading direction (FSD), and 2–2.5% 4θ variation in VSH with a fast direction 45° from FSD. The relative behavior of 2θ, 4θ, and radial anisotropy in the mantle are consistent with ophiolite petrofabrics, linking outcrop and surface‐wave length scales. VSV remains fast parallel to FSD to ∼80 km depth where the direction changes, suggesting spreading‐dominated deformation at the ridge. The transition at ∼80 km perhaps marks the dehydration boundary and base of the lithosphere. Azimuthal anisotropy strength increases from the Moho to ∼30 km depth, consistent with flow models of passive upwelling at the ridge. Strong azimuthal anisotropy suggests extremely coherent olivine fabric. Weaker radial anisotropy implies slightly nonhorizontal fabric or the presence of alternative (so‐called E‐type) peridotite fabric. Presence of radial anisotropy in the crust suggests subhorizontal layering and/or shearing during crustal accretion.
Persistent neurocognitive deficits in cognitively impaired survivors of sepsis are explained by reductions in working memory capacity

Introduction Sepsis is defined as life-threatening organ dysfunction caused by a dysregulated host response to infection. Mounting evidence suggests that many cognitively impaired sepsis survivors show long-term neurocognitive deficits in neuropsychological tasks. To date, the underlying mechanisms of these deficits are insufficiently understood. Based on previous evaluations we hypothesized that visual attention and working memory may be affected in a sample of cognitively impaired sepsis survivors. Methods We utilized psychophysical whole-and partial-report paradigms based on the computational theory of visual attention (TVA) to determine (i) whether sepsis survivors show changes in basic parameters of visual attention and working memory, (ii) whether the affected parameters are related to neuropsychological test results in a standard battery in sepsis survivors and matched healthy control participants, (iii) whether between-group differences in these basic parameters of visual attention could account for underperformance of sepsis survivors in neuropsychological tests when adjusting for potentially relevant clinical variables. Results We showed that, in sepsis survivors, the maximum number of elements consciously maintained in an instant, i.e. the working memory storage capacity K, is reduced (sepsis survivors: M = 3.0; healthy controls: M = 3.4). Moreover, K explained variance in neurocognitive outcomes –17% in attentional and 16 % in executive functions – in a standard neuropsychological battery. The association remained stable when adjusting for clinical variables. Discussion Thus, in our sample of cognitively impaired sepsis survivors, a reduction in working memory capacity seems to be a critical determinant of the neurocognitive sequelae. It should be the subject of future work on mechanisms but may also serve as surrogate outcome measure in interventional studies.
An Integrated Grassland Fire-Danger-Assessment System for a Mountainous National Park Using Geospatial Modelling Techniques

Grasslands are key to the Earth’s system and provide crucial ecosystem services. The degradation of the grassland ecosystem in South Africa is increasing alarmingly, and fire is regarded as one of the major culprits. Globally, anthropogenic climate changes have altered fire regimes in the grassland biome. Integrated fire-risk assessment systems provide an integral approach to fire prevention and mitigate the negative impacts of fire. However, fire risk-assessment is extremely challenging, owing to the myriad of factors that influence fire ignition and behaviour. Most fire danger systems do not consider fire causes; therefore, they are inadequate in validating the estimation of fire danger. Thus, fire danger assessment models should comprise the potential causes of fire. Understanding the key drivers of fire occurrence is key to the sustainable management of South Africa’s grassland ecosystems. Therefore, this study explored six statistical and machine learning models—the frequency ratio (FR), weight of evidence (WoE), logistic regression (LR), decision tree (DT), random forest (RF), and support vector machine (SVM) in Google Earth Engine (GEE) to assess fire danger in an Afromontane grassland protected area (PA). The area under the receiver operating characteristic curve results (ROC/AUC) revealed that DT showed the highest precision on model fit and success rate, while the WoE was used to record the highest prediction rate (AUC = 0.74). The WoE model showed that 53% of the study area is susceptible to fire. The land surface temperature (LST) and vegetation condition index (VCI) were the most influential factors. Corresponding analysis suggested that the fire regime of the study area is fuel-dominated. Thus, fire danger management strategies within the Golden Gate Highlands National Park (GGHNP) should include fuel management aiming at correctly weighing the effects of fuel in fire ignition and spread.
Exploring the Determinants and Consequences of Task-Technology Fit: A Meta-Analytic Structural Equation Modeling Perspective

Objectives: Task-Technology Fit (TTF) is mainly used to determine the users’ performance based on the tasks and technological attributes. This study integrated and evaluated TTF with the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2). This paper aims to compile and analyze the literature on task-technology fit (TTF) since 2000. Method: Through the meta-analytic structural equation modeling (MASEM) approach, understand the application of TTF in the last 20 years and explore future research directions. In addition, this paper employs subgroup analysis and sample sub-grouping to better understand the differences between these studies. The samples were divided into two categories: identity groups (employee, individual, and student) and voluntary groups (voluntary and non-voluntary). Findings: The relationship between the variables belonging to the original TTF model (including TASK, TEC, TTF, PI, and UT) was found to be relatively stable. After combining the variables of UTAUT2 (including PEOU, BI, and PE) and IC, all paths were also found to have a medium or high effect. The TTF-BI path was significant in the identity-based subgroup analysis, and the IC-TTF path was significant in the voluntary-based subgroup analysis. Novelty:Given that the traditional TTF literature is too subjective, this paper adopts MASEM as applied in management research. There are few similar studies so far. Therefore, this paper not only analyzes TTF objectively through MASEM but also provides some directions and suggestions for expanding the TTF model and hopes to give a stronger explanation for future research. Doi: 10.28991/ESJ-2024-08-01-06 Full Text: PDF
Anthropogenic Change, Effects on Bee Populations, and Consequences for a Sub-Alpine Plant Community

Declines in pollinator populations due to anthropogenic influences have been well documented in recent years. However, the effects that these declines have had on floral visitors that utilize floral resources in exploitative manners have received little to no attention. Not all floral visitors are pollinators. Some rob nectar, which may impose fitness effects that range from negative to positive. Some plant-pollinator systems have seen dramatic declines not only in pollinators, but in nectar robbers, in recent years. What are the consequences to plants of these declines? I studied consequences of such a decline in Aquilegia caerulea, the Colorado Columbine. During the 1970s, the floral visitor community and nectar robbing rate of A. caerulea were documented by Miller (1978). Bombus occidentalis, the Western Bumblebee, acted at that time as both the major floral visitor and an active nectar robber. In the subsequent 45 years, many studies have reported declines in B. occidentalis, earning it an IUCN Vulnerable Red List classification. Building from this information, I quantified fitness effects of nectar robbing as well as differences in the floral visitor community to A. caerulea compared to past studies. I determined the effects and consequences of these changes, particularly in relation to nectar robbing, on the floral community. I also quantified the presence and ability of flies (Diptera), whose abundance has recently been exceptionally high, to act as pollinators in the absence of effective pollinators (bumble bees). I found that the floral visitor community has changed drastically since the studies of Miller (1978). Bombus occidentalis was nearly absent from the system in 2016, resulting in severely reduced nectar robbing rates. Nectar robbing was found to have no significant effect on fruit set, while Diptera floral visitors, which dominated the system in 2016, significantly reduced fruit set below the self-pollination rate for the flower in the absence of bumble bees. As a whole, the absence of a nectar robber for this system is insignificant as nectar robbing has no influence on the reproductive success of the plant, however, in the absence of all bumble bees, Diptera, now a primary floral visitor, does have a significant, negative influence on reproductive success.
Parameterization of In‐Cloud Aerosol Scavenging Due to Atmospheric Ionization: Part 3. Effects of Varying Droplet Radius

A new set of simulations of collision rate coefficients for aerosol particles with droplets (in‐cloud scavenging) extends to a droplet radius of 15 μm, with short‐range effects on collisions treated as an increment of droplet effective collision radius (ECR). The simulations are made with our Monte Carlo trajectory model for midtropospheric (~5 km) conditions. The use of ECR allows the results to be expressed as a modified analytic solution (MAS) for the rate coefficients, incorporating both long‐range and short‐range effects. For smaller particles with radius less than 0.2 μm, the increment of ECR is only caused by the particle charge inducing a short‐range image electric force, and results of the MAS match quite well that of our trajectory model. For larger particles, the short‐range effects become complex, including particle size effects (weight, intercept, and flow around the particle), with image forces induced by both droplet and particle charges. An ECR based on these factors gives average errors between the MAS and the trajectory model of less than 10%, with smaller errors for larger droplets. We have now completed the parameterizations of rate coefficients for midtropospheric conditions that can be applied to cloud models. One application would be to test whether electrically induced changes in scavenging rates, which have been proposed to significantly affect cloud processes dependent on condensation nucleus concentration and contact ice nucleation, can explain observed cloud responses to changes in current flow in the global electric circuit.