Miracle-dz/UniFAR-FTUs huggingface dataset:
Ensemble Learning for Multi-type Classiﬁcation in Heterogeneous Networks

—Heterogeneous networks are networks consisting of different types of objects and links. They can be found in several ﬁelds, ranging from the Internet to social sciences, biology, epidemiology, geography, ﬁnance and many others. In the literature, several methods have been proposed for the analysis of network data, but they usually focus on homogeneous networks, where all the objects are of the same type, and links among them describe a single type of relationship. More recently, the complexity of real scenarios has impelled researchers to design methods for the analysis of heterogeneous networks, especially focused on classiﬁcation and clustering tasks. However, they often make assumptions on the structure of the network that are too restrictive or do not fully exploit different forms of network correlation and autocorrelation. Moreover, when nodes which are the main subject of the classiﬁcation task are linked to several nodes of the network having missing values, standard methods can lead to either building incomplete classiﬁcation models or to discarding possibly relevant dependencies (correlation or autocorrelation). In this paper, we propose an ensemble learning approach for multi-type classiﬁcation. We adopt the system Mr-SBC, which is originally able to analyze heterogeneous networks of arbitrary structure, within an ensemble learning approach. The ensemble allows us to improve the classiﬁcation accuracy of Mr-SBC by exploiting i) the possible presence of correlation and autocorrelation phenomena, and ii) the classiﬁcation of instances (which contain missing values) of other node types in the network. As a beneﬁcial side effect, we have also that the models are more stable in terms of standard deviation of the accuracy, over different samples used for training. Experiments performed on real-world datasets show that the proposed method is able to signiﬁcantly outperform the standard implementation of Mr-SBC. Moreover, it gives Mr-SBC the advantage of outperforming four other well-known algorithms for the classiﬁcation of data organized in a network.
The opportunity costs of reducing carbon emissions in an Amazonian agroindustrial region: the Xingu River headwaters

Negotiations are proceeding for a new international climate change regime that will compensate tropical nations that reduce their carbon emissions from deforestation and forest degradation. In anticipation of this new mechanism designed to slow deforestation, regional projects to reduce tropical deforestation will provide important training grounds for the development of deforestation-reduction programs that are compensated by the carbon market. One of the world’s largest regional forest carbon “products” is under development in the headwater region of the Xingu River in the southeastern Brazilian Amazon. This approximately 177,000 km area contains the Xingu Indigenous Park at its core, home to 14 indigenous tribes. Surrounding the park is a rapidly expanding soy and cattle sector. We estimated annual deforestation-driven carbon emissions in this region for 2000 through 2007 as a basis for estimating the historical baseline of emissions. We then estimated the opportunity cost of maintaining forestlands using spatially-explicit rent models for soy production, cattle ranching, and sustainable timber harvest. We estimated a baseline of 10.9 million tons of annual carbon emissions. The average annual opportunity cost of reducing carbon emissions from deforestation to nearly zero was $270 million and $23 per ton of reduced carbon emission. Over a five year period, ca. 55 million tons of carbon emissions reductions could be achieved for a total opportunity cost (of foregone profits from soybean cultivation and ranching) of $1.2 billion. By law, however, private landholders are not allowed to clear more than 20% of their forests (in the forest biome) or 65% of their cerrado savanna vegetation. If this law were enforced within each tributary of the Xingu River headwaters, and compensation of opportunity costs were applied only to forests in excess of the legal requirement, then costs would decline to nearly zero, since the vast majority of landholders in this region are not in compliance with the law. If the maintenance of those forests required to comply with the law are compensated at the rate of 50% of opportunity costs as an incentive to keep forests standing, then the five-year cost of reducing deforestation to zero declines to $600 million and $12 per ton of reduced carbon emissions. To provide each of the 940 indigenous families in the Xingu Park with a forest subsidy of $2400 per family per year would cost $2,300,000 annually, which translates to a mere $0.06 per ton of carbon emission reductions. Given the historical baseline for deforestation in the Xingu region, it would take nearly 50 years to completely clear the forests that lie outside of protected areas, providing a long-term stream of revenue for the region that is tied to ongoing success in maintaining forest carbon stocks.
Four Days Are Enough to Provide a Reliable Daily Step Count in Mild to Moderate Parkinson’s Disease through a Commercial Smartwatch

Daily steps could be a valuable indicator of real-world ambulation in Parkinson’s disease (PD). Nonetheless, no study to date has investigated the minimum number of days required to reliably estimate the average daily steps through commercial smartwatches in people with PD. Fifty-six patients were monitored through a commercial smartwatch for 5 consecutive days. The total daily steps for each day was recorded and the average daily steps was calculated as well as the working and weekend days average steps. The intraclass correlation coefficient (ICC) (3,k), standard error of measurement (SEM), Bland–Altman statistics, and minimum detectable change (MDC) were used to evaluate the reliability of the step count for every combination of 2–5 days. The threshold for acceptability was set at an ICC ≥ 0.8 with a lower bound of CI 95% ≥ 0.75 and a SAM < 10%. ANOVA and Mann–Whitney tests were used to compare steps across the days and between the working and weekend days, respectively. Four days were needed to achieve an acceptable reliability (ICC range: 0.84–0.90; SAM range: 7.8–9.4%). In addition, daily steps did not significantly differ across the days and between the working and weekend days. These findings could support the use of step count as a walking activity index and could be relevant to developing monitoring, preventive, and rehabilitation strategies for people with PD.
Macrolide-Lincosamide Resistance and Virulence Genes in Staphylococcus aureus Isolated from Clinical Specimens in Ardabil, Iran

Background & Objective: Staphylococcus aureus causes various hospital- and community-acquired infections. This study aimed to investigate the phenotypic and genotypic characteristics of erythromycin and inducible clindamycin resistance, virulence gene profiles, and spa types of S. aureus isolates collected from patients in Ardabil Province, Iran. Methods: A total of 118 clinical S. aureus isolates, including 50 (42.4%) methicillin-resistant S. aureus (MRSA) and 68 (57.6%) methicillin-susceptible S. aureus (MSSA) strains, were investigated. Resistance patterns were determined by the disk diffusion method and minimum inhibitory concentration (MIC) test. Inducible macrolide-lincosamide-streptogramin B (iMLSB) resistance was detected using D-test method. The polymerase chain reaction (PCR) was used to identify the virulence and resistance-encoding genes. Additionally, the spa types of the isolates were determined using the PCR, followed by sequencing. Results: In total, 49.1% (58/118) and 44% (52/118) of the isolates were resistant to erythromycin and clindamycin, respectively. Overall, 13.5% (16/118) of the isolates showed the iMLSB resistance phenotype. The ermC gene (72.4% [42]) was the most frequent erythromycin resistance-encoding gene, followed by ermA (60.3% [35]), ermB (60.3% [35]), ermTR (51.7% [30]), and msrA (15.5% [9]) genes among erythromycin-resistant isolates. The virulence genes hla, hld, sea, LukS PV, tst, seb, sed, eta, sec, and etb were detected in 93.2%, 74.5%, 70.3%, 32.2%, 29.6%, 17%, 8.5%, 8.5%, 5.9%, and 4.2% of the isolates, respectively. Ten different spa types were identified for 58 erythromycin-resistant S. aureus strains, of which t030 and t078 types were the most common types. Conclusion: A high frequency of macrolide- and lincosamide-resistant S. aureus isolates with different genetic backgrounds of resistance and virulence may be found in patients in Ardabil Province, Iran.
The Effect of Affiliate Programs and Consumer Behavior on Profit Margins: The Mediating Role of Customer Acquisition Cost (CAC) and Customer Loyalty

The purpose of this study is to investigate the influence of affiliate programs on profit margins in online businesses, with a focus on understanding the mediating role of Customer Acquisition Cost (CAC) and Customer Loyalty. The study aims to bridge the knowledge gap and provide insights for business practitioners and researchers to design more effective affiliate program strategies. This research adopts a comprehensive approach, reviewing current literature on affiliate programs and online businesses. The study focuses on the mediating role of Customer Acquisition Cost (CAC) and Customer Loyalty in the relationship between affiliate programs and profit margins. The research methodology includes data analysis and interpretation to unravel the impact of affiliate programs on CAC, customer loyalty, and profit margins with 200 respondents as participant and use SMART-PLS 3.0 as statistical tools. The findings of this research reveal that implementing affiliate programs can result in higher acquisition costs due to commissions paid to affiliate partners. However, effective affiliate programs can create customer attachment, leading to increased customer retention and maximizing customer lifetime value. Affiliate programs contribute to overall business profitability by increasing sales volume, broadening the customer base, and generating additional revenue. Moreover, the study highlights the significant positive effect of consumer behavior on customer acquisition cost. However, the influence of customer acquisition cost on profit margins is not significant, contrary to traditional business theory. This research makes an important contribution to the understanding of the influence of affiliate programs in online businesses and the mediating role of CAC and Customer Loyalty in driving profit margins. The study offers valuable insights for business practitioners and researchers to design more effective affiliate program strategies and maximize profit margins in the competitive e-commerce environment. Further research is needed to explore the relationship between customer acquisition cost and profit margins in more depth and identify other related factors.
An Overview of Short-Term Load Forecasting for Electricity Systems Operational Planning: Machine Learning Methods and the Brazilian Experience

The advent of smart grid technologies has facilitated the integration of new and intermittent renewable forms of electricity generation in power systems. Advancements are driving transformations in the context of energy planning and operations in many countries around the world, particularly impacting short-term horizons. Therefore, one of the primary challenges in this environment is to accurately provide forecasting of the short-term load demand. This is a critical task for creating supply strategies, system reliability decisions, and price formation in electricity power markets. In this context, nonlinear models, such as Neural Networks and Support Vector Machines, have gained popularity over the years due to advancements in mathematical techniques as well as improved computational capacity. The academic literature highlights various approaches to improve the accuracy of these machine learning models, including data segmentation by similar patterns, input variable selection, forecasting from hierarchical data, and net load forecasts. In Brazil, the national independent system operator improved the operation planning in the short term through the DESSEM model, which uses short-term load forecast models for planning the day-ahead operation of the system. Consequently, this study provides a comprehensive review of various methods used for short-term load forecasting, with a particular focus on those based on machine learning strategies, and discusses the Brazilian Experience.
Water-Use Efficiency of the Terrestrial Biosphere: A Model Analysis Focusing on Interactions between the Global Carbon and Water Cycles

AbstractCarbon and water cycles are intimately coupled in terrestrial ecosystems, and water-use efficiency (WUE; carbon gain at the expense of unit water loss) is one of the key parameters of ecohydrology and ecosystem management. In this study, the carbon cycle and water budget of terrestrial ecosystems were simulated using a process-based ecosystem model called Vegetation Integrative Simulator for Trace Gases (VISIT), and WUE was evaluated: WUEC, defined as gross primary production (GPP) divided by transpiration; and WUES, defined as net primary production (NPP) divided by actual evapotranspiration. Total annual WUEC and WUES of the terrestrial biosphere were estimated as 8.0 and 0.92 g C kg−1 H2O, respectively, for the period 1995–2004. Spatially, WUEC and WUES were only weakly correlated. WUES ranged from 1.5 g C kg−1 H2O in boreal and alpine ecosystems. The historical simulation implied that biospheric WUE increased from 1901 to 2005 (WUEC, +7%; WUES, +12%) ma.
ONLINE MAP OF BUILDINGS USING RADIANT TECHNOLOGIES

SUMMARY Radiant cooling and heating systems have the potential for energy savings in buildings. Yet, depending on the world region, type of system, and conditioning mode, they have not been uniformly adopted. To address this disparity, we collected data on notable buildings using radiant systems with a focus on North America, type of system, conditioning mode and architectural value. We then integrated these examples into a publicly available online map. The goal of this project is to provide resources to building stakeholders, to connect them and to contribute to on-going research and design on radiant systems. To collect the data, we used peer-reviewed publications on case-studies, articles from architectural magazines and we contacted buildings professionals. The map currently shows 90 buildings. Information for each building is classified into 12 categories. Buildings can be displayed by radiant system type (embedded surface systems; thermally active building systems; radiant panels) or by building type.
Aeromagnetic Anomalies Modeling and Their Tectonic Implications in the Middle Benue Trough, Nigeria

The middle Benue Trough has been studied on a reconnaissance stage, no detail subsurface modeling to reveal basin configuration has been undertaken. Twelve(12) Aeromagnetic maps on a scale of 1:100,000, covering the middle Benue Trough were digitized and processed using computer techniques which include; map merging, polynomial filtering, power spectrum, forward and inverse modeling. Eight (8) profiles were modeled to determine the structure of the basin and the presence of possible intrusives. The results indicate the presence of twenty three (23) intrusives; seven (7) are basaltic while sixteen (16) are rhyolites. The Saki model configuration reveals average sediment thickness ranging between 0.5 – 4.0km, these represent horst and graben structures. These variations are also revealed in the power spectrum depth estimate, which shows a range between 1.2 – 2.7km. The Doma and Agana areas have the largest accumulations of sediment thickness (0.5 – 4.0km) covering about 40km, other areas have shallow depths (0.5 – 2.0km), and cover distances between 19.5 – 23.8 km, these later areas are less favorable for hydrocarbon accumulation. The Doma and Agana areas remain the most favorable areas for hydrocarbon exploration based on their thick sediment accumulation. However, these areas reveal the presence of seven (7) intrusives; this may cause high geothermal temperatures that may not be favorable for hydrocarbon accumulation. Keywords: reconnaissance,forward and inverse modeling,configuration,intrusives
TRANSFER PROCESSES IN RHEOLOGICAL MEDIA INFLUENCE OF THE RHEOLOGICAL PROPERTIES OF A POLYMER MELT ON THE HYDRODYNAMIC CHARACTERISTICS OF ITS VORTEX FLOW IN A CONVERGENT CHANNEL

The in ﬂ uence of the temperature of the ﬂ ow of a polymer melt in a plane, convergent slot channel on the size of the vortex-ﬂ ow region at the inlet of its slot part was considered. The ﬁ elds of velocities, stresses, and pressure of the ﬂ ow of a polymer melt in such a channel were constructed with the use of the modi ﬁ ed Vinogradov–Pokrovskii model generalized with regard for the nonmonotonic dependence of the viscosity gradient of this melt on its tension. The dependences of the initial viscosity of the polymer melt and the sizes of its vortex ﬂ ow region in the channel on the temperature in it and the dependence of the sizes of the vortex zone of the polymer-melt ﬂ ow on its rate were determined.
Salinity monitoring of the Murray River using a towed TEM array

Successful implementation of a salt interception schemes (SIS) requires monitoring to determine locations where the scheme needs revision. Current monitoring methods involve near-surface water-salinity measurements, which are affected by water-flow displacement. A survey method that can determine the salinity of water contained in the top few metres of alluvial sediments immediately beneath the river would be a more accurate tool for SIS monitoring. A fast sampling Transient EM technique is investigated as a potential tool for imaging the conductivity of the top 5m of sediment, and thus monitoring the Waikerie SIS in South Australia’s Riverland. A towed TEM array was used to collect 9km of data that shows resistive anomalies correlating with SIS production bores. The system has the advantage of being a small, manageable array and the short inversion time allows same-day interpretation.
and Waste Management Association, Baltimore, MD, from June 23-27, 2002 Estimating Future-Year Ozone Design Values with Two Regional-Scale Modeling Systems in North Carolina

Across the United States, significantly increased numbers of counties are likely to be designated nonattainment for ozone with the proposed 8-h form of the National Ambient Air Quality Standard (NAAQS). The U.S. Environmental Protection Agency has developed a draft guidance for potential nonattainment areas to demonstrate attainment of the standard through photochemical air quality simulation models. This has led to increased emphasis on the evolution and use of regional-scale models to study longer averaging periods in addressing the complex nature of the tropospheric ozone problem. We have applied two state-of-the-art regional-scale models, the Models-3/Community Multiscale Air Quality (CMAQ) model and the Multiscale Air Quality Simulation Platform (MAQSIP), which was developed as a prototype for CMAQ, to the June 1930, 1996, O3 episode in North Carolina. Both CMAQ and MAQSIP are fully modularized, threedimensional modeling systems, with various options for representing the physical and chemical processes for urban- and regional-scale pollution. We have previously compared and presented the relative performance of the two models for base-year modeling for this episode, a period characterized by high ozone in the Charlotte-Gastonia-Rock Hill, Greensboro-Winston SalemHigh Point, and Raleigh-Durham-Chapel Hill areas. Horizontally, the two modeling systems employ a nested 36/12/4-km grid resolution, with the 4-km grid covering the entire state of North Carolina. The base case modeling was performed with harmonized sets of inputs, and we still identified day-to-day performance variability between the two modeling systems for ozone. Our objective here is to emphasize the use of these models in a “relative” sense, by applying EPA’s draft modeling guidance and determining whether the modeling systems, when using an identical set of emissions inputs, produce different Relative Reduction Factors (RRFs) at each monitored location in the 4-km grid (RRFs are ratios of ozone concentrations from future-year modeling to those from base-year modeling). Differences in RRFs are likely to cause differences in computed future-year design values at these locations. The plausible causes of these differences and their policy-relevant impacts on demonstrating attainment of the NAAQS for ozone at monitored locations are discussed.
Moderated mediating effect of appearance satisfaction on the relationship between academic major satisfaction, self-esteem, and employment stress by airline service major students

Introduction. Airline service major students choose their academic major to be flight attendants after graduating from secondary education. They are therefore likely to be satisfied with the airline service major, as students can learn qualified airline service-related knowledge and skills. However, they also have higher employment stress than students majoring in other majors. This is because physical appearance is an important aspect of the job interview. It is therefore necessary to study academic major satisfaction, self-esteem, and appearance satisfaction to reduce employment stress among airline service major students. Methods. The participants in this study were 339 airline service major students from four universities. Data were collected from freshmen (31%), sophomore (14.7%), junior (28%), and senior (26.3%) students majoring in airline service. This study used SPSS Win.21. 0 statistics programs to conduct the frequency test, reliability and correlation tests. For the moderated mediation analysis, ‘Model 14 of PROCESS macro ver.4.0’ was used as the statistical method. Results. First, employment stress had negative correlations with both academic major satisfaction (r = -.326, p<.01) and self-esteem (r = -.401, p<.01), while academic major satisfaction had a positive correlation with self-esteem (r = .433, p < .01). Second, appearance satisfaction was found to have conditional indirect effects on the relationship between academic major satisfaction and employment stress through self-esteem that were significant (p < .01) when the appearance satisfaction values were 4.0 (-.2218~-.0776) and 5.0 (-.3775~-.1505), respectively. Therefore, the moderated mediation effect of resilience was verified. Conclusions. This study found that airline service major students with high appearance satisfaction have decreased employment stress. The results of this study indicate that students’ appearance satisfaction should be fostered and reinforced with the goal of increasing improving airline service major students’ self-esteem and decreasing their employment stress.