Search Results (6)

Work–family conflict (WFC) is a common issue faced by employees balancing work and family roles, but research exploring individual strategies to reduce its negative effects has been limited. Leaders’ positive humor is a mutually (leader–subordinates) amusing communication tool in the workplace. It has been shown to enhance peer relationships (coworker socializing (CWS)) and may serve as an effective coping mechanism that mitigates the adverse effects of workplace stress (work–family conflict). This study strives to examine the relationship between leaders’ positive humor (LPH) and work–family conflict (WFC), with coworker socializing (CWS) mediating this relationship and sensitivity to favorable interpersonal treatment (SFIT) moderating the relationship between leaders’ positive humor and coworker socializing in the tourism and hospitality industry. The research addresses a significant gap in previous studies by investigating these variables together. A total of 387 valid questionnaires were collected from employees of five-star hotels and tourism organizations in Egypt. This study employed PLS-SEM to analyze the data. The results showed that leaders’ positive humor negatively impacts work–family conflict, positively influences coworker socializing and that coworker socializing negatively affects work–family conflict. Additionally, coworker socializing mediated the association between leaders’ positive humor and work–family conflict, and sensitivity to favorable interpersonal treatment moderated the relationship between leaders’ positive humor and coworker socializing. This study provides theoretical and practical insights by validating the proposed model based on the Stimulus–Organism–Response (S-O-R) framework and the Conservation of Resources (COR) theory. Regarding practical implications, the study recommends leadership training on the effective use of humor to foster follower socialization and promote work–family balance. Full article

Sorting particles or cells of specific sizes in complex systems has long been a focus of many researchers. Acoustic surface waves, which generate acoustic radiation forces on particles or cells and, thus, influence their motion, are commonly used for the non-destructive separation of particles or cells of specific sizes. In previous studies, the frequency of acoustic surface wave generation has been limited by the interdigitated transducer (IDT). To extend the effective operating frequency range of the IDT, a slanted-finger interdigitated transducer (SFIT) with a wide acoustic path and multiple operating frequencies was designed. Compared with traditional acoustic sorting devices, which suffer from a limited frequency range and narrow acoustic paths, this new design greatly expands both the operating frequency range and acoustic path width, and enables adjustable operating frequencies, providing a solution for sorting particles or cells with uneven sizes in complex environments. The optimal resonance frequency is distributed within the 32–42 MHz range, and the operating frequencies within this range can generate a standing wave acoustic path of approximately 200 $\mathsf{\mu }$m, thus enhancing the effectiveness of the operating frequencies. The microfluidic sorting device based on SFIT can efficiently and accurately sort polystyrene (PS) with particle sizes of 20 $\mathsf{\mu }$m, 30 $\mathsf{\mu }$m, and 50 $\mathsf{\mu }$m from mixed PS microspheres (5, 10, 20 $\mathsf{\mu }$m), (5, 10, 30 $\mathsf{\mu }$m), and (5, 10, 50 $\mathsf{\mu }$m), with a sorting efficiency and purity exceeding 96%. Additionally, the device is capable of sorting other types of mixed microspheres (5, 10, 20, 30, 50 $\mathsf{\mu }$m). This new wide-acoustic-path, multi-frequency sorting device demonstrates the ability to sort particlesin a high-purity, label-free manner, offering a more alternative to traditional sorting methods. Full article

Background: Shinrin-yoku, forest bathing, has been shown to improve the pain experience in arthritis patients and the immune system in normal healthy patients. Yet, a simulated forest immersion therapy (SFIT) experience has not been tested in these two populations and specifically not in cancer patients. If SFIT complementary therapy in these two populations progresses, the intervention environment as designed needs to be tested. The purpose of this paper is to describe the SFIT setting and test the stability of the interventional environment. Methods: To operationalize SFIT, a protocol of dose delivery was designed and measured. Ambient and surface room temperatures, relative humidity, ambient ultrafine particulate matter, and volatile organic compounds, specifically terpenes, were measured prior to terpene dose delivery, every 15 min for 1 h, ending with the conclusion of terpene delivery. Results: There were nearly imperceptible differences within session means for ambient and surface room temperatures, relative humidity, ambient ultrafine particulate matter, and volatile organic compounds showing no practical significance. Room temperature and surface temperature were moderately correlated, as expected. Conclusions: The intervention room environment for the diffusion of terpenes remained stable throughout two studies. The next steps proposal to employ SFIT in the home setting is warranted, with precautions. Full article

The Bag Index (TBI) is a novel approach using standardized materials (i.e., commercial tea bags) to evaluate organic matter decomposition by determining two indexes: the early stage decomposition constant k (k_TBI) and litter stabilization factor S (S_TBI). k_TBI is defined as the decomposition constant of an asymptote model describing the decomposition curve of rooibos tea, whereas S is the ratio of the stabilized to total hydrolysable fractions of green tea. However, it was recently revealed that both k_TBI and S_TBI deviate from the actual S and k values accurately determined by fitting an asymptote model to the time series mass of green and rooibos teas remaining (k_fitting and S_fitting, respectively). Nevertheless, k_TBI and S_TBI, which can be determined in a cost- and labor-effective manner, might indicate the relative values of k_fitting and S_fitting across different soils and be useful for comparative analyses. Therefore, this study investigated the positive correlations of k_TBI and S_TBI with k_fitting and S_fitting, respectively, in which case these indexes are useful for comparative analyses. However, the result showed that k_TBI was negatively correlated with k_fitting. This study underscores the importance of obtaining time-series data for accurately determining the decomposition constant of an asymptote model describing the decomposition curve of rooibos tea. S_TBI was positively correlated with S_fitting, implying that S_TBI can be used as an indicator of S. Full article

A portable Fourier Transform Spectrometer (B3M-IR) is built and used to measure atmospheric trace gases in the city of Beijing during Olympic Games in 2008. A short description of the instrument is first provided in this paper. A detailed spectral analysis is then presented. The total columns of ozone (O₃), carbon monoxide (CO), methane (CH₄) and nitrous oxide (N₂O) are retrieved from the ground-based solar absorption spectra recorded by the B3M-IR during the Olympic Games. Lacking validation data, only the retrieved total column of O₃ is compared with that retrieved by MAX-DOAS, which is deployed at the same station. The mean difference between the two methods of measurement is 6.5%, demonstrating the performance and reliability of B3M-IR. Full article

The variable Zagreb ^vM₂ index is introduced and applied to the structure-boiling point modeling of benzenoid hydrocarbons. The linear model obtained (thestandard error of estimate for the fit model S_fit=6.8 ^oC) is much better than thecorresponding model based on the original Zagreb M₂ index (S_fit=16.4 ^oC). Surprisingly,the model based on the variable vertex-connectivity index (S_fit=6.8 ^oC) is comparable tothe model based on ^vM₂ index. A comparative study with models based on the vertex-connectivity index, edge-connectivity index and several distance indices favours modelsbased on the variable Zagreb ^vM₂ index and variable vertex-connectivity index.However, the multivariate regression with two-, three- and four-descriptors givesimproved models, the best being the model with four-descriptors (but ^vM₂ index is notamong them) with S_fit=5 ^oC, though the four-descriptor model contaning ^vM₂ index isonly slightly inferior (S_fit=5.3 ^oC). Full article