Miracle-dz/UniFAR-FTUs huggingface dataset:
Patient satisfaction with anesthesia care services and associated factors in AHQ Hospital Bajaur Agency, KP, Pakistan

Patient satisfaction is the balance between expectation and perception of what is received. It is an important component and quality indicator in anesthesia care services. It can be affected by Anesthetist patient interaction, peri-operative anesthesia management, and post-procedure followup. There is no previous study conducted in our institute. This study aimed to assess the level of patient satisfaction with anesthesia care services and to determine the factors that affect patient satisfaction. Two hundred and sixty-three patients were selected among scheduled patients for a surgical procedure under different types of anesthesia were surveyed. The standardized questionnaire was used for post-operative patient interviews. Data was entered and analyzed through the Statistical Package for Social Science (SPSS) version 22. Overall, the proportion of patient satisfaction with anesthesia care services was 76%. Of these, educated were less satisfied (43.5%) compared with non-educated (56.5%). Factors that affect patient satisfaction negatively are sore throat, shivering, peri-operative pain, nausea, and vomiting. Patient's satisfaction with anesthesia care services was low in our institute with previously many published studies. Factors that affect patient satisfaction negatively may be preventable and every health care provider should work on these factors to decrease dissatisfaction level. Awareness creation about the current problem and training need to be given for anesthetists.
The Use of Gamification in Academic Teaching – Evidence from Polish State Universities

The purpose of the article is to provide answers to the following research questions: How popular are digital games as the first step to gamification, comparing to other teaching methods used in such fields of study as economics, humanities and natural science in Poland? What is the practice of using gamification in academic teaching? The subject literature studies and empirical research carried out in the form of auditorium survey in the third quarter of 2019 across a sample of 200 students (50 people representing each field of study) were used in the article. In order to collect additional information, in-depth interviews with students (4 people representing each field of study) were carried out in the first quarter of 2020. The problem of applying gamification in tertiary education is gaining importance, as evidenced by the growing number of scientific publications addressing this issue. The conducted empirical research shows that digital-game-based learning method is marginally used in academic teaching in Poland and, thus, it is hard to talk about gamification. The article also presents the research process limitations and directions of further research.
Effectiveness of an mHealth Application to Overcome Problematic Smartphone Use: Comparing Mental Health of a Smartphone Control-Use Group and a Problematic-Use Group

We developed an mHealth application that can help alleviate the problematic use of smartphones and allied psychological symptoms. This study observed the change in patterns of users’ problematic smartphone use, depression, and anxiety while using the mHealth application. We conducted this study from 9 January to 10 April 2019. The Korean Smartphone Addiction Proneness Scale for Adults, Generalized Anxiety Disorder Scale, and the Patient Health Questionnaire were measured at week 0, 8, 12. A post hoc test of Repeated Measurement Anova analysis and Linear Mixed Model analysis were used. Overall, 190 participants were allocated into two groups. Sixty-six were in the smartphone control-use group and 124 were in the problematic-use group. The study elucidated the difference between the two groups in terms of problematic smartphone use and depression and anxiety after 13 weeks of using the mHealth application. This study showed the use of the mHealth application reducing problematic smartphone use scores and negative symptoms such as anxiety and depression in the PSU group. The results can be used as the basis for similar qualitative studies to further resolve the problematic use of smartphones.
In vitro investigation of the cytotoxic, apoptotic and genotoxic effects of pulp capping materials on L929 mouse fibroblast cells

This study evaluated the in vitro cytotoxic, apoptotic and genotoxic effects of MTA, TheraCal and Dermabond (2-octyl cyanoacrylate) on L929 mouse fibroblast cells. Culture medium was exposed to the materials for 24 hours, 1 week and 2 weeks. Cells were seeded in 96 well plates with 5x103 cells/100 μL media per well for MTT assay, 6 well plates with 2x105 cells /2 mL media per well for comet assay,12-well plates with 2x105 cells/well for apoptosis assay and cells were exposed to the material eluates. The cell viability, genotoxicity and apoptotic status were evaluated by MTT, comet and apoptosis assays respectively at three different times (24 hours, 1 week and 2 weeks). There was no statistically significant difference (p˃0.05) between MTA and Dermabond at 24 hours, 1 week and 2 weeks exposures. However, TheraCal significantly reduced the cell viability at 1-week exposure to 66.70% (p˂0.05). TheraCal caused DNA damage at all exposures and there was a statistically significant difference (p˂0.05). According to flow cytometry results, TheraCal at 24-hour and 1-week showed significantly higher cytotoxic effects compared to MTA and Dermabond. No significant differences were detected between MTA and Dermabond. As observed from the current study it can be concluded that MTA and Dermabond are biocompatible capping materials in vital endodontic treatments. Since TheraCal exhibited cytotoxic and genotoxic effects caution should be exercised when it is being used.
Robot Anticipation Learning System for Ball Catching

Catching flying objects is a challenging task in human–robot interaction. Traditional techniques predict the intersection position and time using the information obtained during the free-flying ball motion. A common pain point in these systems is the short ball flight time and uncertainties in the ball’s trajectory estimation. In this paper, we present the Robot Anticipation Learning System (RALS) that accounts for the information obtained from observation of the thrower’s hand motion before the ball is released. RALS takes extra time for the robot to start moving in the direction of the target before the opponent finishes throwing. To the best of our knowledge, this is the first robot control system for ball-catching with anticipation skills. Our results show that the information fused from both throwing and flying motions improves the ball-catching rate by up to 20% compared to the baseline approach, with the predictions relying only on the information acquired during the flight phase.
Nursing in front of the hospitalized smoking patient: diagnosis and interventions established in clinical practice / A enfermagem frente ao paciente tabagista hospitalizado: Diagnósticos e intervenções estabelecidos na prática clínica

Objetivo: identificar diagnósticos e intervenções de enfermagem estabelecidos para pacientes tabagistas hospitalizados. Métodos: estudo transversal realizado em hospital universitário brasileiro entre agosto e setembro/2017 com entrevistas à beira do leito, consultas ao prontuário e query extraída do sistema informatizado da instituição. Resultados: participaram 69 pacientes tabagistas, para os quais identificaram-se 41 diagnósticos de enfermagem distintos, com mediana de quatro (intervalo interquartil: 3;6) por paciente. As intervenções prescritas totalizaram 237, com mediana de 18,5 (intervalo interquartil: 10,5;28,25) por prescrição. Quatro pacientes possuíam diagnóstico com etiologia relacionada ao abuso de substância e para esses foram prescritas 17 intervenções de enfermagem. Em 33(48%) anamneses constava que o paciente era tabagista e, destes, nove(27%) havia o tempo de fumo e número de cigarros consumidos diariamente. Conclusão: a prevalência de tabagistas hospitalizados é expressiva, entretanto, as anamneses, os diagnósticos e intervenções de enfermagem não retratam esta realidade, havendo necessidade de sensibilizar e capacitar a equipe.
Ignore risk; Maximize expected moral value

Many philosophers assume that, when making moral decisions under uncertainty, we should choose the option that has the greatest expected moral value, regardless of how risky it is. But their arguments for maximizing expected moral value do not support it over rival, risk-averse approaches. In this paper, I present a novel argument for maximizing expected value: when we think about larger series of decisions that each decision is a part of, all but the most risk-averse agents would prefer that we consistently choose the option with the highest expected value. To the extent that what we choose on a given occasion should be guided by the entire series of choices we prefer, then on each occasion, we should choose the option with the highest expected moral value.
Developing single‐substrate steady‐state model for biohydrogen production in continuous anaerobic activated sludge–rotating biological contactor system: Novel insights on the process

Kinetic‐modeling studies are a key step to attain economically practical technology in terms of efficient scheme and bioreactor scale‐up to describe the substrate utilization, biomass growth, and product formation in the biohydrogen production process. Kinetic‐modeling study of biohydrogen production from molasses using mixed culture was investigated in an anaerobic activated sludge‐rotating biological contactor. Single‐substrate with endogenous metabolism and Luedeking–Piret model was used to describe the kinetic parameters at different dilution rate (0.032‐0.167 h−1) with influent concentration of 6, 15, and 24 g COD/L. The maximum experimentally estimated value of μmax, kS, and Yx/s was found to be 0.053 h−1, 9.98 g/L, and 0.11 g/g in dilution 0.167 h−1, respectively. It can be concluded that increase in dilution rate is a suitable for microbial activities in the biological hydrogen production process. Accordingly, maximum specific growth rate and hydrogen production rate will be increased. Contrariwise, decrease in dilution rate is associated with lower biomass concentration and higher endogenous metabolism. Therefore, dilution rate is an important parameter in production of biohydrogen in this bioreactor and should be kept in an appropriate range.
How Servant Leadership Drives Project Team Performance Through Collaborative Culture and Knowledge Sharing

Drawing on social learning theory, this research compared and tested how two distinct mediating mechanisms—collaborative culture and knowledge sharing—influence the servant leadership–project team performance relationship. Survey data were collected from 275 employees representing 70 project teams, and multilevel structural equation modeling was adopted to test the hypotheses. The findings indicated that collaborative culture fully mediates, whereas knowledge sharing does not mediate, the servant leadership–project team performance relationship. These findings reveal collaborative culture as the intervening mechanism that translates servant leadership to project team performance. For project-based organizations, the research puts forth theoretical and practical implications.
Can Eco-Evo Theory Explain Population Cycles in the Field?

Efforts to explain animal population cycles often invoke consumer-resource theory, which has shown that consumer-resource interactions alone can drive population cycles. Eco-evo theory instead argues that population cycles are partly driven by fluctuating selection for resistance in the resource, but support for eco-evo theory has come almost entirely from laboratory microcosms. Here we ask, Can eco-evo theory explain population cycles in the field? We compared the ability of eco-evo models and classical “eco-only” models to explain data on cycles in the insect Lymantria dispar, in which outbreaks of the insect are terminated by a fatal baculovirus. We carried out a statistical comparison of the ability of eco-only and eco-evo models to explain combined data from L. dispar outbreak cycles and baculovirus epizootics (epidemics in animals). Both models require high host variation in resistance to explain the epizootic data, but high host variation in the eco-evo model leads to consistently accurate predictions of outbreak cycles, whereas in the presence of high host variation the eco-only model can explain outbreak cycles only by invoking high levels of stochasticity, which leads to highly variable and often inaccurate predictions of outbreak cycles. Our work provides statistically robust evidence that eco-evo models can explain population cycles in the field.
Soil moisture retrieval over agricultural fields through integration of synthetic aperture radar and optical images

ABSTRACT The soil roughness and two-way vegetation transmissivity parameters affect the radar backscattered signal; therefore, the results of the soil moisture retrieval from Synthetic Aperture Radar (SAR) images. In this paper, the Improved Water Cloud Model was extended to specify the effects of the above parameters. The surface roughness parameter values were calculated for each ground measurement site using an artificial neural network. This parameter was then used in the proposed models to rectify the effects of surface roughness on soil moisture estimation. Also, the Normalized Difference Water Index, derived from Landsat 5 imagery, was used to account for the impact of the vegetation canopy on the SAR backscatter. The accuracy of the proposed model was assessed using AIRSAR C-, L-, and P-band data, ALOS PALSAR L-band and two reference data were collected during NASA’s SMEX03 and SMAPVEX08 campaigns. The experimental results indicated that the proposed models had improved the RMSE and R values with respect to those in the IWCM in all bands and polarizations, with the highest values concerning the L band and VV polarization. In this band, the value of RMSE decreased by 0.002 (6.25%), and R increased by 0.054 (9.45%).
The Restorative Power of Nostalgia: Thwarting Loneliness by Raising Happiness During the COVID-19 Pandemic

Lockdowns during the COVID-19 pandemic increased the risk for loneliness. We tested whether nostalgia counteracts loneliness via rises in happiness. We conducted surveys in China (N = 1,546), the United States (N = 1,572), and the United Kingdom (N = 603). Although feeling lonely was associated with unhappiness, it was also associated with nostalgia, which in turn conduced to increased happiness. We complemented these findings with three experiments testing MTurk workers (Study 4, N = 209; Study 5, N = 196; Study 6, N = 190), where we manipulated nostalgia and assessed happiness. Nostalgia increased happiness immediately after the manipulation (Studies 4–6) and, following an induction booster, up to 2 days later (Studies 4–5). Nostalgia is a psychological resource that can be harnessed to raise happiness and help combat loneliness.
Evaluating Arctic clouds modelled with the Unified Model and Integrated Forecasting System

Abstract. By synthesising remote-sensing measurements made in the central Arctic into a model-gridded Cloudnet cloud product, we evaluate how well the Met Office Unified Model (UM) and European Centre for Medium-Range Weather Forecasting Integrated Forecasting System (IFS) capture Arctic clouds and their associated interactions with the surface energy balance and the thermodynamic structure of the lower troposphere. This evaluation was conducted using a four-week observation period from the Arctic Ocean 2018 expedition, where the transition from sea ice melting to freezing conditions was measured. Three different cloud schemes were tested within a nested limited area model (LAM) configuration of the UM – two regionally-operational single-moment schemes (UM_RA2M and UM_RA2T), and one novel double-moment scheme (UM_CASIM-100) – while one global simulation was conducted with the IFS, utilising its default cloud scheme (ECMWF_IFS). Consistent weaknesses were identified across both models, with both the UM and IFS overestimating cloud occurrence below 3 km. This overestimation was also consistent across the three cloud configurations used within the UM framework, with > 90 % mean cloud occurrence simulated between 0.15 and 1 km in all model simulations. However, the cloud microphysical structure, on average, was modelled reasonably well in each simulation, with the cloud liquid water content (LWC) and ice water content (IWC) comparing well with observations over much of the vertical profile. The key microphysical discrepancy between the models and observations was in the LWC between 1 and 3 km, where most simulations (all except UM_RA2T) overestimated the observed LWC. Despite this reasonable performance in cloud physical structure, both models failed to adequately capture cloud-free episodes: this consistency in cloud cover likely contributes to the ever-present near-surface temperature bias simulated in every simulation. Both models also consistently exhibited temperature and moisture biases below 3 km, with particularly strong cold biases coinciding with the overabundant modelled cloud layers. These biases are likely due to too much cloud top radiative cooling from these persistent modelled cloud layers and were interestingly consistent across the three UM configurations tested, despite differences in their parameterisations of cloud on a sub-grid-scale. Alarmingly, our findings suggest that these biases in the regional model were inherited from the driving model, thus triggering too much cloud formation within the lower troposphere. Using representative cloud condensation nuclei concentrations in our double-moment UM configuration, while improving cloud microphysical structure, does little to alleviate these biases; therefore, no matter how comprehensive we make the cloud physics in the nested LAM configuration used here, its cloud and thermodynamic structure will continue to be overwhelmingly biased by the meteorological conditions of its driving model.
Analysis on Tourism Environmental Pollution and Tourism Economy-Ecological Environmental Coordination Degree: A Case Study from China

The rapid development of the tourism industry, range expansion, and intensity growth of human tourism activity have all caused intensifying ecological environmental problems while bringing considerable economic benefits. The ecological environment is currently faced with huge pressures due to the unreasonable tourism resource development, annual decrease in bearing capacity of the tourism environment, and excessive tourism consumption. To coordinate the relationship between tourism economic growth and ecological environment, this work carried out a case study based on Shandong Province, China. First, four aspects of environmental pollution caused by tourism were analyzed. Second, the tourism economy-ecological environmental coordination degree model and index system were established and then the coordination degree in Shandong Province from 2002 to 2019 was estimated. Results show that the tourism industry causes the following typical pollutions: water, soil, air, and noise. The coupling coordination degree (D) between the tourism economy and ecological environment in Shandong Province increased from 0.100 in 2002 to 0.995 in 2019, indicating the transition from serious imbalance to a high-quality coordination state. It is suggested to further promote tourism economy-ecological environment coordinated development by innovating the tourism-economy coupling development mode, creating the entire tourism industrial chain, increasing efforts in tourism reform, and exploring and implementing ecological compensation policies. Research conclusions have important significances to further study and explore the development status between the tourism industry and ecological environment and realize the coordinated development between the tourism industry and regional economy.
Structure of Integrated Reporting, Voluntary Disclosure and Firm-Specific Characteristics in Saudi Arabian Companies

The present study aims towards three research purposes. Firstly, it intends to reveal the pattern that associates the elements of the Integrated Reporting (IR) of companies listed on the Saudi Arabian Stock Exchange (Tadawul). Secondly, it verifies the existence of a relationship between IR practices and some firm-specific characteristics. Third, it examines the similarities between the IR practices of these companies. IR communicates how an organization's strategy, governance, performance, and prospects lead to value creation. The dataset used for the IR elements is retrieved from Tadawul and consists of data regarding integrated reports for 126 companies listed in 2019; while the data for the firm-specific characteristics, as the size of the company, the auditor type and the type of company are extracted from Marketscreener.com and Argaam.com portals. The methodology used consists of the empirical-analytical approach with the use of Optimal Scaling techniques. Main findings consist of a positive association found between the elements of the IR, as well as that the specific characteristics of the firms are not related to the elements of the IR. In our results a dissimilarity is found in the corporate information disclosure practices. These findings reveal a need for a deep investigation of the IR elements and firm characteristics in Saudi Arabian companies. One of the future research direction is a multilinear data for various years such that can reveal a more comprehensive understanding of IR elements and firm characteristics. This study becomes relevant in the context of IR elements and firm characteristics relations, that are not yet studies at their research potential.
Secondary ice production processes in wintertime alpine mixed-phase clouds

Abstract. Observations of orographic mixed-phase clouds (MPCs) have long shown that measured ice crystal number concentrations (ICNCs) can exceed the concentration of ice nucleating particles by orders of magnitude. Additionally, model simulations of alpine clouds are frequently found to underestimate the amount of ice compared with observations. Surface-based blowing snow, hoar frost and secondary ice production processes have been suggested as potential causes, but their relative importance and persistence remains highly uncertain. Here we study ice production mechanisms in wintertime orographic MPCs observed during the Cloud and Aerosol Characterization Experiment (CLACE) 2014 campaign at the Jungfraujoch site in the Swiss Alps with the Weather Research and Forecasting model (WRF). Simulations suggest that droplet shattering is not a significant source of ice crystals at this specific location – but break-up upon collisions between ice particles is quite active, elevating the predicted ICNCs by up to 3 orders of magnitude, which is consistent with observations. The initiation of the ice-ice collisional break-up mechanism is primarily associated with the occurrence of seeder-feeder events from higher precipitating cloud layers. The enhanced aggregation of snowflakes is found to drive secondary ice formation in the simulated clouds, the role of which is strengthened when the large hydrometeors interact with the primary ice crystals formed in the feeder cloud. Including a constant source of cloud ice crystals from blowing snow, through the action of the break-up mechanism, can episodically enhance ICNCs. Increases in secondary ice fragment generation can be counterbalanced by enhanced orographic precipitation, which seems to prevent explosive multiplication and cloud dissipation. These findings highlight the importance of secondary ice and "seeding" mechanisms – primarily falling ice from above and to a lesser degree blowing ice from the surface – which frequently enhance primary ice and determine the phase state and properties of MPCs.