Investigation of a Gas Hydrate Dissociation-Energy-Based Quick-Freezing Treatment for Sludge Cell Lysis and Dewatering

A gas Hydrate dissociation-energy-based Quick-Freezing treatment (HbQF) was applied for sewage sludge cell rupture and dewatering. Carbon dioxide (CO2) and water (H2O) molecules in sewage create CO2 gas hydrates, and subsequently the sludge rapidly freezes by releasing the applied pressure. Cell rupture was observed through a viability evaluation and leachate analysis. The decreased ratios of live cell to dead cells, increased osmotic pressure, and increased conductivity showed cell lysis and release of electrolytes via HbQF. The change in physicochemical properties of the samples resulting from HbQF was investigated via zeta potential measurement, rheological analysis, and particle size measurement. The HbQF treatment could not reduce the sludge water content when combined with membrane-based filtration post-treatment because of the pore blocking of fractured and lysed cells; however, it could achieve sludge microbial cell rupture, disinfection, and floc disintegration, causing enhanced reduction of water content and enhanced dewatering capability via a sedimentation post process. Furthermore, the organic-rich materials released by the cell rupture, investigated via the analysis of protein, polysaccharide, total organic carbon, and total nitrogen, may be returned to a biological treatment system or (an) aerobic digester to increase treatment efficiency

A Study on the Relationship between Servant Leadership, Organizational Culture, and Job Satisfaction in Fitness Clubs

In the fi eld of organizational behavior theory, the infl uence of servant leadership and organizational culture on the job satisfaction of organization members has been actively studied to eff ectively achieve the goals set by the organization. However, there is a severe lack of studies on the relationship between servant leadership, organizational culture, and job satisfaction in the sport industry. Therefore, this study empirically analyzed the causal relationships among the three variables by surveying 320 employees in fi tness clubs located in Pusan, Korea. Surveys were conducted using the convenience sampling method, and a total of 300 surveys were used in the analysis. Data analysis methods included descriptive statistics analysis, exploratory factor analysis, reliability analysis, correlation analysis, and multiple regression analysis using SPSS 19.0. Key results from this study were as follows. First, servant leadership in fi tness clubs had a positive infl uence on organizational culture. Second, servant leadership in fi tness clubs had a positive infl uence on the job satisfaction of their employees. Third, the organizational culture of fi tness clubs had a positive infl uence on the job satisfaction of employees. The results of this study can contribute to establishing strategies to advance the organizational performance and eff ective human resource management of fi tness clubs

An Index to Better Estimate Tropical Cyclone Intensity Change in the Western North Pacific

A revised predictor called the net energy gain rate (NGR) is suggested by considering wind dependent drag coefficient based on the existing maximum potential intensity theory. A series of wind speed dependent NGR, known as NGR‐w, is calculated based on pre‐tropical cyclone (TC) averaged ocean temperatures from the surface down to 120 m (at 10‐m intervals) to include the TC‐induced vertical mixing for 13 years (2004–2016) in the western North Pacific. It turns out that the NGR50‐w (NGR‐w based on temperature averaged over top 50 m) has the highest correlation with 24‐h TC intensity change compared with the commonly used sea surface temperature‐based intensification potential (POT), depth‐averaged temperature‐based POT (POTDAT), and constant drag coefficient in the NGR. To demonstrate the effectiveness of the NGR50‐w, we designed and conducted experiments for training (2004–2014) and testing (2015–2016). The model with the NGR50‐w shows greater skill than the model with POTDAT or POT by reducing prediction errors by about 16%

New parameterization of air-sea exchange coefficients and its impact on intensity prediction under major tropical cyclones

Understanding and quantifying air-sea exchanges of enthalpy and momentum fluxes are crucial for the advanced prediction of tropical cyclone (TC) intensity. Here, we present a new parameterization of air-sea fluxes at extreme wind speeds from 40 m s−1 to 75 m s−1, which covers the range of major TCs. Our approach assumes that the TC can reach its maximum potential intensity (MPI) if there are no influences of external forces such as vertical wind shear or other environmental constraints.This method can estimate the ratio of the enthalpy and momentum exchange coefficient (Ck/Cd) under the most intense TCs without direct flux measurements. The estimation showed that Ck/Cd increases with wind speed at extreme winds above 40 m s−1. Two types of surface layer schemes of the Hurricane Weather and Research Forecast (HWRF) were designed based on the wind speed dependency of the Ck/Cd found at high winds: (i) an increase of Ck/Cd based on decreasing Cd (Cd_DC) and (ii) an increase of Ck/Cd based on increasing Ck (Ck_IC). The modified surface layer schemes were compared to the original HWRF scheme (using nearly fixed Cd and Ck at extreme winds; CTRL) through idealized experiments and real-case predictions. The idealized experiments showed that Cd_DC reduced frictional dissipation in the air-sea interface as well as significantly reduced sea surface cooling, making the TC stronger than other schemes. As a result, Cd_DC reduced the mean absolute error and negative bias by 15.0% (21.0%) and 19.1% (32.0%), respectively, for all lead times of Hurricane Irma in 2017 (Typhoon Mangkhut in 2018) compared to CTRL. This result suggests that new parameterization of Ck/Cd with decreasing Cd at high winds can help improve TC intensity prediction, which currently suffers from underestimating the intensity of the strongest TCs

Predicting rapid intensification of tropical cyclones in the western North Pacific: a machine learning and net energy gain rate approach

In this study, a machine learning (ML)-based Tropical Cyclones (TCs) Rapid Intensification (RI) prediction model has been developed by using the Net Energy Gain Rate Index (NGR). This index realistically captures the energy exchanges between the ocean and the atmosphere during the intensification of TCs. It does so by incorporating the thermal conditions of the upper ocean and using an accurate parameterization for sea surface roughness. To evaluate the effectiveness of NGR in enhancing prediction accuracy, five distinct ML algorithms were utilized: Decision Tree, Logistic Regression, Support Vector Machine, K-Nearest Neighbors, and Feed-forward Neural Network. Two sets of experiments were performed for each algorithm. The first set used only traditional predictors, while the second set incorporated NGR. The outcomes revealed that models trained with the inclusion of NGR exhibited superior performance compared to those that only used traditional predictors. Additionally, an ensemble model was developed by utilizing a hard-voting method, combining the predictions of all five individual algorithms. This ensemble approach showed a noteworthy improvement of approximately 10% in the skill score of RI prediction when NGR was included. The findings of this study emphasize the potential of NGR in refining TC intensity prediction and underline the effectiveness of ensemble ML models in RI event detection

Analyzing Norm Violations in Live-Stream Chat

Toxic language, such as hate speech, can deter users from participating in online communities and enjoying popular platforms. Previous approaches to detecting toxic language and norm violations have been primarily concerned with conversations from online forums and social media, such as Reddit and Twitter. These approaches are less effective when applied to conversations on live-streaming platforms, such as Twitch and YouTube Live, as each comment is only visible for a limited time and lacks a thread structure that establishes its relationship with other comments. In this work, we share the first NLP study dedicated to detecting norm violations in conversations on live-streaming platforms. We define norm violation categories in live-stream chats and annotate 4,583 moderated comments from Twitch. We articulate several facets of live-stream data that differ from other forums, and demonstrate that existing models perform poorly in this setting. By conducting a user study, we identify the informational context humans use in live-stream moderation, and train models leveraging context to identify norm violations. Our results show that appropriate contextual information can boost moderation performance by 35\%.Comment: 17 pages, 8 figures, 15 table

The Relationship between Transformational Leadership of Immediate Superiors, Organizational Culture, and Affective Commitment in Fitness Club Employees

In an uncertain global business environment, eff ective human resource management is a crucial element in improving organizational eff ectiveness. However, relatively little research has examined the characteristics of transformational leadership and the types of organizational culture suitable for improving organizational eff ectiveness in the sport management fi eld. Thus, the purpose of this study was to examine the relationship between transformational leadership of immediate superiors, organizational culture, and aff ective commitment in fi tness club employees. For this purpose, a survey was given to a convenience sample of 300 employees of fi tness clubs working in the Gwangju and Dae-gu metropolitan cities in South Korea. The data were then analyzed using descriptive statistics, correlations, and multiple regression analysis. The major fi ndings of this study were as follows. First, transformational leadership had a signifi cant eff ect on the organizational culture in fi tness clubs. Second, transformational leadership had a signifi cant eff ect on aff ective commitment of employees of the fi tness clubs. Third, organizational culture had a signifi cant eff ect on aff ective commitment of employees in fi tness clubs. The fi ndings of this study may be helpful for fi tness clubs to determine the characteristics of transformational leadership and the types of organizational culture needed to improve aff ective commitment of employees

An Alternative Multi-Model Ensemble Forecast for Tropical Cyclone Tracks in the Western North Pacific

This study introduces an unequally weighted technique for Multi-model Ensemble (MME) forecasting for western North Pacific Tropical Cyclone (TC) tracks. Weights are calculated by partial least square regression, and members are selected by paired t-test. The performances for shorter forecast time ranges, such as 24, 48 and 72 h, are examined in order to improve the MME model, in which the weights for members are equally assigned. For longer forecast time ranges, such as 96 and 120 h, weights for MME members are thought to be less reliable, since the modeling is more likely to be influenced by the climate variability in the data period. A combination of both techniques for the shorter and the longer forecast time ranges is suggested as an alternative MME forecast procedure in operational meteorological agencies

Surface modification of polyvinylidene fluoride membrane for enhanced wetting resistance

Modifications of polyvinylidene fluoride (PVDF) membranes were carried out to improve both hydrophobicity and stability through four steps: pore expansion by a plasma treatment, hydroxylation of the membrane by the Fenton reaction, generation and growth of microparticles (MPs) on the hydroxylated functional groups in pores, and hydrophobic modification. The membranes modified by the methods proposed in this study did not lose their hydrophobicity and maintained the flux over a significantly longer period. The PVDF membrane modified by hydrophobic MPs attached inside enlarged pores exhibited a minimized flux reduction and significantly higher antiwetting stability

Investigation of Hydrate-induced Ice Desalination (HIID) and its application to a pretreatment of reverse osmosis (RO) process

In this study, freeze desalination which utilizes CO2 gas hydrate itself as a refrigerant (referred to as Hydrate-induced Ice Desalination, HIID) was systematically investigated and evaluated as a pretreatment method for seawater reverse osmosis (RO) process. To the best of the authors' knowledge, the HIID is the first approach to use the hydrate dissociation energy to freeze seawater in an instant for desalination. The endothermic energy related to hydrate dissociation was the most dominant factor in the freezing of seawater. Using the HIID technique, the rejection of ions with 3.5 wt% NaCl was about 67%. Increasing the concentration of salts enhanced rejection of component ions. However, humic acid organic rejection decreased due to agglomeration of organics in presence of salts. The HIID process showed similar levels of cation rejections-approximately 65% of seawater, except boron and potassium. The rejection of cations might be determined by the solubility of salts at various brine concentration. Using HIID as a pretreatment of seawater at 225 psi, the RO process showed ~ 14 LMH and about 99% cation rejections except boron. This study shows that HIID can be utilized as a pretreatment of seawater desalination and further development might make HBID technology run on its own.clos