Miracle-dz/UniFAR-FTUs huggingface dataset:
Sustainable Governance of Coastal Areas and Tourism Impact on Waste Production: Panel Analysis of Croatian Municipalities

The research problem this paper is concerned with is the effect of tourism on solid waste generation in Croatia’s coastal area. We are aware of the fact that this has not been thoroughly addressed, especially considering tourism’s share in the Croatian economy and the pressure it generates on sustainable coastal management. This is of particular importance considering the governing complexity of coastal areas. Thus, we ask a simple question regarding the role of the tourism industry in the solid waste generation in the Croatian coastal area: Do tourists generate relatively more solid waste than the domestic population? The falsifiable hypothesis is stated in terms of the difference in the production of communal waste between domestic population and tourists, taking into account local idiosyncratic factors, when such a difference is recoverable through statistical analysis of measurable tourist presence in panel data. The first hypothesis is thus: The amount of solid waste produced by local residents in Croatian coastal municipalities diverges significantly in statistical terms from the amount of solid waste produced by tourists. The second hypothesis is: The amount of waste-streams is influenced by local idiosyncrasies of coastal settlements, their economic structure, per capita GDP and/or cultural background of local people. Our dataset is a panel of 160 municipalities in the Croatian coastal area spanned across a time period of 12 months during 2019, giving us a total of 1920 panel observations. We performed a Panel Estimated Generalized Least Squares cross-section fixed effects analysis with Panel Corrected Standard Errors on domestic population and tourist overnight stays and their solid waste generation. We used the above mentioned method to achieve better results with higher significance, and lower Standard Errors than comparable methods. We complemented the analysis with a dynamic Panel Generalized Method of Moments First Differences test. Results show a relatively larger relative impact of tourist overnight stays on municipal solid waste generation than what is to be expected from the locals only. Our different methods of analysis ended with non-contradicting results. The number of tourist overnight stays in some municipalities shadows the overnight stays of the local population as an indicator of solid waste generation, exacerbating the problem of sustainability of waste disposal. We conclude that the relative waste disposal impact of the tourists is at least 22% greater and possibly up to 55% greater than the one of local inhabitants, contradicting some other research. We also found evidence of possible Environmental Kuznets Curve behavior.
Comparing the diversity and composition of waterbird functional traits between natural, restored, and artificial wetlands

B.A.A. was supported by grant PDSE/88881.133362/2016‐01 from the Brazilian Coordination for the Improvement of Higher Education Personnel (CAPES). E.S. G. was supported by a Juan de la Cierva contract (Ministerio de Economia y Competitividad, IJCI‐2015‐24947) and Generalitat Valenciana (SEJI/2018/024). L.d. A. received grant 307643/2018‐2 from the Brazilian Council for Development of Science and Technology (CNPq). A.J.G. was supported by Spanish Ministerio de Economia, Industria y Competitividad project CGL2016‐76067‐P (AEI/FEDER, EU).
ANALYSIS OF TIMES AND EFFICIENCIES OF THE MECHANIZED HARVEST OF SUGARCANE (Saccharum spp.)

Sugarcane culture directed to sugar mills is of great economic and social importance in Brazil. Harvesters are the most important equipment in the sugarcane mechanized harvesting system, since the production process in sugar mills depends on machine operating performance, which is directly related to field efficiency. Therefore, efficiency is relevant because it involves the service time and operational efficiency of the harvester and it takes place when the operation is implemented. The current study aims to analyze the times and efficiencys in sugarcane mechanized harvesting. To current study took under consideration primary data on the mechanized harvesting of a sugarcane plant, which were analyzed using descriptive statistics. The reduction in time lost increases the time worked. Operational and use efficiency have strong impact on the mechanized harvesting performance.
Effects of Enzymatically Synthesized Glycogen on Lipid Metabolism in Diet Induced Obese Mice

Previously, we reported that 4-week enzymatically synthesized glycogen (ESG) supplementation reduced lipid accumulation in diet-induced obese rats. The aim of this study was to investigate the effects of long-term dietary ESG supplementation on lipid metabolism of diet-induced obese mice. Male C57BL/6NCr mice were fed a control or a high-fat diet containing 0%, 10%, or 20% ESG for 15 weeks. In the high-fat diet groups, ESG showed significant suppressive effect on adipose tissue weight. Supplementation of ESG decreased plasma cholesterol and liver lipid levels. Although, ESG substantially increased fecal lipid, ESG did not affect lipid metabolism related gene expression. In control groups ESG increased body temperature and plasma NO, although the effects were not observed in high-fat groups. In the test of single administration, ESG significantly suppressed lipid absorption. In this study, we confirmed the anti-obese effect of ESG. It is mainly due to inhibition of lipid absorption by ESG.
A Comparative Approach of the Environmental Performance between Periods with Positive and Negative Accounting Returns of EEA Companies

In recent years, sustainable growth has become an important issue in the business field. Environment, social, and governance (ESG) actions of companies have come to represent key elements in adopting decisions by stakeholders. The question is to what extent they validate the companies’ environmental behaviour, as profitability varies over time. The answer can be obtained by analysing the relationship between environmental performance (EP) and financial performance (FP) of the firms. The paper proposes a new perspective of this relationship, namely, the separate assessment of the EP–FP in the case of positive and negative FP (expressed through accounting returns). A survey on 299 companies in the European Economic Area (EEA), operating in extractives and minerals processing and health care, was conducted. The data were extracted from the Refinitiv database for the period 2009–2018. The findings showed a significant EP–FP correlation in the case of the extractives and minerals processing industry, but their dependency slightly varied on the positive and negative returns’ scenario. As for the healthcare industry, the best result was a moderate correlation between EP and the negative return. Our findings support a managerial design of environmental policy, as well as the future academic research of the EP–FP relationship.
Organizational Adoption of Social Media in the Hospitality Industry: An Integrated Approach Based on DIT and TOE Frameworks

The importance of the organizational adoption of social media is increasingly raised in hospitality literature because of the recognition of Web 2.0 technologies as a significant tool for improving customer information searching and experience, as well as for enriching firm digital strategy. The present study seeks to empirically explore the determinant factors that affect a hospitality firm’s decision to adopt social media by following a theoretical approach that integrates the Diffusion of Innovation Theory (DIT) with the Technology-Organization-Environment (TOE) framework. Using survey data from 106 hospitality firms operating in Greece, and by applying structural equation modelling (SEM), we identify seven factors that influence the adoption of organizational social media adoption. These factors are grouped into three categories: Technological, organizational, and environmental. Out of the three groups of factors, technological features are considered as the most important ones in terms of their predicting power. Theoretical and practical implications of our findings are discussed.
Integrity verification and behavioral classification of a large dataset applications pertaining smart OS via blockchain and generative models

Malware analysis and detection over the Android have been the focus of considerable research, during recent years, as customer adoption of Android attracted a corresponding number of malware writers. Antivirus companies commonly rely on signatures and are error‐prone. Traditional machine learning techniques are based on static, dynamic, and hybrid analysis; however, for large scale Android malware analysis, these approaches are not feasible. Deep neural architectures are able to analyze large scale static details of the applications, but static analysis techniques can ignore many malicious behaviors of applications. The study contributes to the documentation of various approaches for detection of malware, traditional and state‐of‐the‐art models, developed for analysis that facilitates the provision of basic insights for researchers working in malware analysis, and the study also provides a dynamic approach that employs deep neural network models for detection of malware. Moreover, the study uses Android permissions as a parameter to measure the dynamic behavior of around 16,900 benign and intruded applications. A dataset is created which encompasses a large set of permissions‐based dynamic behavior pertaining applications, with an aim to train deep learning models for prediction of behavior. The proposed architecture extracts representations from input sequence data with no human intervention. The state‐of‐the‐art Deep Convolutional Generative Adversarial Network extracted deep features and accomplished a general validation accuracy of 97.08% with an F1‐score of 0.973 in correctly classifying input. Furthermore, the concept of blockchain is utilized to preserve the integrity of the dataset and the results of the analysis.
“We’re all travelers, all sojourners” : A pseudo-ethnography of incarceration and adaptation

The study intends to describe the dynamics in jail, the notable features of incarceration, and cultural premises used by inmates to achieve adaptation to a different environment. Using participant observation and several indigenous methods of gathering data twenty inmates in a city jail were purposively selected for this qualitative study. Several findings are notable. First, traveling is a fitting metaphor to depict the inmate culture developed inside the jail, more so that it is consistent with how the inmates call their incarceration as a momentary “biyahe,” i.e., a sojourn. Second, the inmates reveal that a must-learn code of conduct “patakaran” or “magna carta” which is rooted in respect and discipline, is essential to survival. Third, by tacit agreement with the jail management, the inmates have organized themselves with distinctive hierarchical roles that should be respected to maintain discipline and order. Each cell has it its own structure to impose discipline and to accomplish every member’s task. Fourth, a system of meting out punishment to disobedience of rules is strictly enforced. Ultimately then, inmates adapt to a new environment and acquire behaviors appropriate to their community. Fifth, pockets of resistance are afforded, albeit in small and imperceptible manners. The study concludes that culture inside the facility is dynamic and inmates assert their roles beyond the prevailing social and structural forces.
Monitoring the Own Spatial Thinking in Second Grade of Primary Education in a Spanish School: Preliminary Study Analyzing Gender Differences

Previous studies on metacognitive performance have explored children’s abilities during primary school (7–11 years) in abstract and mathematical reasoning tasks. However, there have been no studies evaluating the metamemory processes with spatial tasks in primary school children, and even more generally, only a few studies have explored spatial metacognition in adults. Taking as a preliminary study a Spanish school, the present work explores the validity of the confidence judgment model when thinking about one’s own performance in a spatial test, for boys and girls in Second Year of Primary Education (mean age of 7 years). A total of 18 boys and 15 girls applied a 4-point scale to evaluate, item by item, the confidence of their responses in the Spatial aptitude test “E” of the EFAI-1 (Factorial Assessment of Intellectual Abilities to mentally process visual stimuli). Accessibility and Accuracy Indexes were calculated for each item of the spatial task. The effect of gender was analyzed too. The tasks were administered in small groups; at the end examiners interviewed each participant, performing the confidence judgment task, item by item, of the EFAI-1 previously answered. The results (analyses carried out by SPSS) showed a high mean confidence (3 mean points out of a maximum of 4), without finding any significant differences either in the spatial performance or in the mean confidence rating between boys and girls. A significant relationship between confidence judgments and spatial task performance accuracy was found. The relationship between confidence judgments and spatial performance cannot be confirmed. The procedure adapted for testing spatial judgments about the own responses has been useful for showing the well calibrated perception about performance at this stage. The implications of the results of this exploratory study and the potential of the application of the procedure to promote thought about one’s own spatial performance and the development of strategies that modulate the effective approach of this type of spatial tasks are discussed within an educational approach.
Customer Satisfaction Analysis Based On SERVQUAL Method to Determine Service Level of Academic Information Systems on Higher Education

Higher education institutions such as universities or institutes that create graduate students with high qualifications must be able to provide the best services to their stakeholders. One kind of higher education service is academic information system services. The service quality level of the academic information system in a university can be decided by measuring the level of users’ perception and the level of users’ expectations that can be fulfilled. As an organization that offers academic information system services, the university must be able to measure the level of academic information system services as an approach to ensure the quality of services. This study aims to determine the level of customer satisfaction index in terms of service of higher education academic information systems using the service quality method. The service quality method is used to identify academic information system services that are analyzed based on the service quality dimensions. The results show that the value of the customer satisfaction index is 77.37% which refers to the satisfied category.
Investigating the Productivity and Sustainability of Weathered Basement Aquifers in Tropical Africa Using Numerical Simulation and Global Sensitivity Analysis

Groundwater stored in weathered basement aquifers (WBAs) is a strategic water resource. In this study, we investigate the productivity of WBAs and sustainability of groundwater abstractions using a novel process‐based stochastic modeling approach, which is applied to simulate abstractions in the Precambrian basement aquifer in Ghana. The statistical distribution of the generated synthetic yield data was found in very good agreement with observed yield data from the same Ghanaian aquifer. Further analysis provided robust insights regarding how different hydrogeological parameters of the WBA, and their interplay, control aquifer productivity and sustainability. Results indicate that 97% of the simulated abstractions could sustain the yield of a hand pump (6 L/min), approximately 30% could also sustain yields >60 L/min, while only 1% could sustain yields greater than 300 L/min. The model indicates that an aquifer transmissivity value of approximately 1.4 m2/day is required for a successful hand‐pumped borehole, while a higher yielding source (60 L/min) requires a transmissivity value of at least 9.5 m2/day. A global sensitivity analysis of 13 model input parameters shows that the thickness of the regolith and the maximum hydraulic conductivity developed at the base of the saprolite are the critical factors controlling success and sustainability for low yielding hand‐pumped boreholes. For higher yielding supplies, the net recharge, the depth to groundwater, and the aquifer extent become increasingly significant. Results from this work have important implications for the potential for increased development of groundwater from WBAs in tropical Africa.
Trend analysis of evapotranspiration over Iran based on NEX‐GDDP high‐resolution dataset

Estimation of evapotranspiration, representing a highly sensitive variable to global warming, is often required in water resources and agricultural studies. This study explores the possible effects of climate change on evapotranspiration (ETo) across Iran. The ETo was computed using the Penman‐Monteith Temperature (PMT) method that requires only minimum and maximum temperature (Tmin and Tmax), provided by the NASA Earth Exchange Global Daily Downscaled Projections dataset (NEX‐GDDP) with a 0.25° × 0.25° spatial resolution. Accuracy of the NEX‐GDDP Tmin and Tmax were evaluated against ground truth observations at 41 synoptic weather stations distributed across the country using a set of statistical measures, including the coefficient of determination (R2) and Nash‐Sutcliffe Efficiency (NSE). Similarly, the PMT estimated evapotranspiration based on the NEX‐GDDP Tmin and Tmax (ETo‐GDDP) were statistically evaluated against the ETo computed with observed variables at selected stations (ETo‐obs). Then, at each grid cell, the 45‐years ETo‐GDDP time series was partitioned into three 15‐years subperiods such that the differences between three subperiods were computed and inter‐compared. Furthermore, annual, seasonal, and monthly ETo time series trends of each cell were evaluated using the Mann–Kendall trend test (MK) while the corresponding change rates were estimated using Theil–Sen's slope estimator (TSSE). The results demonstrated a good agreement between ETo‐GDDP and ETo‐obs with R2 greater than 0.8 and NSE greater than 0.7 in 90.2% and 65.8% of the stations, respectively. The maps of differences between the three subperiods showed negligible changes in ETo between 1975–1990 and 1950–1975 subperiods. The spatial patterns of annual and seasonal MK statistics showed a significant increasing trend in most parts of Iran. On seasonal scale, the highest and lowest ETo changes were observed in spring (0.00035–0.0045) and in autumn (0.0005–0.0015), respectively.
Cloud point extraction and determination of Nickel (II) ions complex in real samples using New azo reagent

New azo reagent(2-[Ceffodoxime azo]-4-Nitro -2-Phenol) ( CefAN) preparation by coupled reaction. The reagent was diagnosed by spectral methods using infrared (FTIR) and (UV. –Vis.) as an identification using( HNMR) spectrum and (C.H.N). This reagent use to determination nickel (II) ion as a pair ion complex that extracted and estimated according to the cloud point extraction(CPE) technique in enrichment layer ,after adjusting the optimal conditions and factors affected in efficiency extraction processes . The ion pare complex of nickel(II) is estimated according to the spectral method at λmax =401 nm. The optimization of complexation and extraction conditions by (CPE) investigated as well as optimum pH =10, critical concentration of TX-100 was 0.2mL, heating time=80C˚. Thermodynamic parameters of CPE for extraction process of the ion-pair association complex in Triton X-100 were also considered ΔH = 129.107264KJ ,ΔG=-56.4845 KJ and ΔS =525.75552J That referred endothermic reaction, withLimit of Detection (LOD=5.044µg mL-1) and Limit of Quantitation (LOQ=50.044 µg mL-1) ,Molar absorptivity (Ɛ= 3888.4L.mol-1.cm-1). The Stiochoimetry study to determination complex stricture that ratios of metal: reagent obtained are (1:1). Under the optimized conditions of a 10 mL sample gave preconcentration and enrichment factors are(50 and 10.1055) respectively withSandell's sensitivity(1.4854 x10-6µg cm-2/0.001A.U). The calibration curve linear in the range of 1-8ppm with a correlation coefficient of 0.9972. The relative standard deviation for replicate determinations at (30) µg 10mL−1 level is58.63%. The proposed method applied for the determination of nickel in fish, vegetables, plant leaves and water which gave satisfactory results.
Determining the Factors That Influence the Effectiveness of The Health Sector in The OECD Countries

The purpose of this study is to determine the factors that influence the effectiveness of the health sector by combining Stochastic Frontier Analysis (SFA), Generalized Linear Models (GLM) and Heuristic Algorithms methods. In accordance with this purpose, firstly, the health system efficiencies of 29 OECD countries are estimated by the SFA method. Within the scope of this study, it is also aimed to select the factors influencing the efficiency of the health systems in OECD countries by employing Heuristic Algorithm methods such as Artificial Bee Colony Algorithm, Genetic Algorithm, and Differential Evolution Algorithm. Furthermore, GLM’s such as Truncated, Normal, Gamma and Tweedie distributions are employed for comparisons.
Classification of arc fault between broken conductor and high‐impedance surface: an empirical mode decomposition and Stockwell transform‐based approach

: The high-impedance arc fault (HIAF) is a result of the interaction between the current-carrying conductor and the high-impedance surface. This study presents a detailed and comparative time-frequency based analysis for the classification of different arcs, generated by the interaction of a broken conductor and different arcing surfaces. The real-time arcing voltage signals are considered as the basis of the whole time-frequency based analysis from a medium voltage distribution line. In this proposed approach, empirical mode decomposition (EMD) is used to study the real-time arc voltage signals of various surfaces. The intrinsic mode functions obtained by the application of the EMD technique is used as the input to various machine learning techniques, which later successfully classifies different HIAFs from their harmonic footprints. The Stockwell transform (ST) is additionally applied to the same test cases, and the classification of the arc is performed using similar learning algorithms to get a quantitative view of both outcomes of EMD and ST towards the selection of appropriate signal processing technique and machine learning algorithm for the same.