Influence of leaders' loneliness on voice-taking : the role of social self-efficacy and performance pressure

This paper attempts to unlock how and when leaders’ loneliness influences their voice-taking behavior in the workplace by integrating the regulatory loop model of loneliness and the affect theory of social exchange. Through collecting a daily diary study of 87 paired leader-follower samples from two electronics industry companies based in Guangzhou, China, this study finds that (1) leaders’ loneliness has a significant negative impact on social self-efficacy and voice-taking behavior; (2) leaders’ social self-efficacy mediates the relationship between their loneliness and voice-taking behavior; (3) performance pressure moderates the relationship between leaders’ loneliness and voice-taking behavior; and, (4) the indirect effect between leaders’ loneliness and voice-taking behavior (through social self-efficacy) becomes stronger when performance pressure is higher. Therefore, this study provides some practical implications on: (1) how to provide a series of loneliness interventions to address loneliness in all areas of life; and, (2) how to establish an internal culture or atmosphere within the organization to encourage leaders to adopt followers’ suggestions for improvement

Effect of dry-heating with pectin on gelatinization properties of sweet potato starch

Purpose: To evaluate the effect of dry-heating with pectin at different dry heating temperatures, heating times and pH on the gelatinization properties of sweet potato starch.Methods: The gelatinization properties of sweet potato starch - pectin blend were analyzed using a rapid viscosity analyzer (RVA), differential scanning calorimeter (DSC), and gel texture analyzer (TPA).Results: The viscosity of the blends of sweet potato starches and pectin increased initially, and then decreased. Viscosity was highest at 120 °C, with a value of 744 cp. High viscosity values were also obtained after dry-heating for 2 and 7 h (540 cp and 639 cp, respectively). The enthalpy of the blend declined with increasing heat-treatment temperature from 3.973 J/g at 0 °C to 3.021 J/g at 150 °C. The initial (T0), peak (Tp), and terminal (Tc) gelatinization temperatures of the blends were all lower than corresponding values at 0 °C. Gelatinization enthalpy values gradually increased with increase in dryheating time and pH although they were still lower than for the control samples. In addition, as T0, Tp, and Tc values of the blend increased, the gelatinization temperature range became narrower. The hardness and viscosity of the blends increased initially, and then decreased after the dry-heat treatment. The hardness of treated samples was higher than that of control, and peaked at 130 °C, 4 h, and pH 11. The resilience of the blends attained a peak value after 2 h of dry-heat treatment at 120 °C and pH 9.Conclusion: The results show that dry-heating with pectin is an effective way of improving the gelatinization and gel properties of sweet potato starch. This finding is considered significant for the developing of new modified starch from sweet potatoes.Keywords: Sweet potato starch, Pectin, Dry heat, Gelatinization, Viscosity, Hardness, Enthalp

Effect of steam explosion pre-treatment on molecular structure of sweet potato starch

Purpose: To examine the effect of steam-explosion (SE) strength on the molecular structure of sweet potato starch.Methods: Sweet potato starch was pre-treated using SE method. The effects of SE pressure and pressure-holding time on the molecular structure of the sweet potato starch were investigated by gel chromatography (GPC), infrared spectroscopy, and grading analysis.Results: The molecular weight (MW) of the starch pre-treated by SE technology decreased with increasing explosion pressure and pressure-holding time; however, the individual MW of amylopectin and amylose declined from 439,834 and 6578 to 238,603 and 4845, respectively. Furthermore, the peak area ratio (obtained by GPC) of amylopectin decreased from 84.39 to 65.16 % while that of amylose increased from 15.61 to 34.84 %. No new absorption peaks were found in the infrared spectra of sweet potato starch following SE pre-treatment. Crystallization index and median diameter of sweet potato starch increased from 1.661 to 1.959 and from 13.73 μm to 76.36 μm, respectively, with rising pressure and pressure-holding time, following SE pre-treatment.Conclusion: SE pre-treatment effectively degrades the degree of polymerisation of molecular chains in sweet potato starch and enhances the degree of crystallinity thereof. SE method is an approach for the production of sweet potato starch with high-level anti-digestion characteristics.Keywords: Sweet potato starch, Steam-explosion, Molecular weight, Degree of crystallinity, Particle diamete

Spiritual Leadership on Proactive Workplace Behavior: The Role of Organizational Identification and Psychological Safety

This study investigates whether and why spiritual leadership may contribute to enhanced proactive employee workplace behavior. Based on self-determination theory (SDT), we examine the effects of two sequential mediators (i.e., organizational identification and psychological safety) on the relationship between spiritual leadership and proactive workplace behavior. Data collected from 188 subordinate-leader dyads in Chinese firms suggested that spiritual leadership has a significant positive effect on proactive workplace behavior. In addition, both organizational identification and psychological safety mediate the relationship between spiritual leadership and proactive workplace behavior. Furthermore, spiritual leadership positively influences organizational identification, and such identification nurtures psychological safety, which, in turn, fosters the proactive behavior of employees. It extends the existing impact of spiritual leadership to proactive workplace behavior and shed lights on the mediating mechanisms through which spiritual leadership exerts influences on proactive workplace behavior. Finally, it considers the important roles played by leaders in modern organizations

A study on the diagnosis of compound faults in rolling bearings based on ITD-SVD

Considering the difficulty in the diagnosis of compound faults in rolling bearings, the paper combines Intrinsic Time-scale Decomposition (ITD) and Singular Value Decomposition (SVD) for extracting the characteristics of compound faults from rolling bearings. Rotational components obtained from ITD decomposition are denoised according to Singular Value Decomposition algorithm; signal is reconstructed by denoised rotational components; at last, characteristics of compound faults of rolling bearings are extracted by Hilbert spectrum envelope of reconstructed signal. In validation, the paper has made a comparative study on the proposed ITD-SVD method and conventional one based on ITD algorithm and PCA method, and the result shows that ITD-SVD method works better on noise control and thereby provides more precise extraction of characteristic frequency of compound faults from rolling bearings of aero-engine

Simultaneous evolutionary expansion and constraint of genomic heterogeneity in multifocal lung cancer.

Recent genomic analyses have revealed substantial tumor heterogeneity across various cancers. However, it remains unclear whether and how genomic heterogeneity is constrained during tumor evolution. Here, we sequence a unique cohort of multiple synchronous lung cancers (MSLCs) to determine the relative diversity and uniformity of genetic drivers upon identical germline and environmental background. We find that each multicentric primary tumor harbors distinct oncogenic alterations, including novel mutations that are experimentally demonstrated to be functional and therapeutically targetable. However, functional studies show a strikingly constrained tumorigenic pathway underlying heterogeneous genetic variants. These results suggest that although the mutation-specific routes that cells take during oncogenesis are stochastic, genetic trajectories may be constrained by selection for functional convergence on key signaling pathways. Our findings highlight the robust evolutionary pressures that simultaneously shape the expansion and constraint of genomic diversity, a principle that holds important implications for understanding tumor evolution and optimizing therapeutic strategies.Across cancer types tumor heterogeneity has been observed, but how this relates to tumor evolution is unclear. Here, the authors sequence multiple synchronous lung cancers, highlighting the evolutionary pressures that simultaneously shape the expansion and constraint of genomic heterogeneity

CPIA Dataset: A Comprehensive Pathological Image Analysis Dataset for Self-supervised Learning Pre-training

Pathological image analysis is a crucial field in computer-aided diagnosis, where deep learning is widely applied. Transfer learning using pre-trained models initialized on natural images has effectively improved the downstream pathological performance. However, the lack of sophisticated domain-specific pathological initialization hinders their potential. Self-supervised learning (SSL) enables pre-training without sample-level labels, which has great potential to overcome the challenge of expensive annotations. Thus, studies focusing on pathological SSL pre-training call for a comprehensive and standardized dataset, similar to the ImageNet in computer vision. This paper presents the comprehensive pathological image analysis (CPIA) dataset, a large-scale SSL pre-training dataset combining 103 open-source datasets with extensive standardization. The CPIA dataset contains 21,427,877 standardized images, covering over 48 organs/tissues and about 100 kinds of diseases, which includes two main data types: whole slide images (WSIs) and characteristic regions of interest (ROIs). A four-scale WSI standardization process is proposed based on the uniform resolution in microns per pixel (MPP), while the ROIs are divided into three scales artificially. This multi-scale dataset is built with the diagnosis habits under the supervision of experienced senior pathologists. The CPIA dataset facilitates a comprehensive pathological understanding and enables pattern discovery explorations. Additionally, to launch the CPIA dataset, several state-of-the-art (SOTA) baselines of SSL pre-training and downstream evaluation are specially conducted. The CPIA dataset along with baselines is available at https://github.com/zhanglab2021/CPIA_Dataset

Immobilization of lipase on chitosan beads for removal of pitch particles from whitewater during papermaking

Pitch deposits originating from alkaline peroxide bleaching of mechanical pulps can seriously decrease the runnability of the paper machine when efforts have been made to increase the reuse of process water. In order to degrade pitch particles present in whitewater, lipase was immobilized on chitosan beads using a binary method. The operational stability of the immobilized lipase and its efficacy for treating whitewater were also preliminary studied. The results showed that the highest activity of immobilized lipase was achieved by using 0.5% 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide (EDC) for activation and 0.0025% glutaraldehyde for cross-linking chitosan. The immobilized lipase also exhibited very good operational stability, and the pitch particles present in whitewater could be reduced by 66.8% after treatment with the immobilized lipase