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Background Genome-wide association studies have successfully identified genetic variants associated with human disease. Various statistical approaches based on penalized and machine learning methods have recently been proposed for disease prediction. In this study, we evaluated the performance of several such methods for predicting asthma using the Korean Chip (KORV1.1) from the Korean Genome and Epidemiology Study (KoGES). Results First, single-nucleotide polymorphisms were selected via single-variant tests using logistic regression with the adjustment of several epidemiological factors. Next, we evaluated the following methods for disease prediction: ridge, least absolute shrinkage and selection operator, elastic net, smoothly clipped absolute deviation, support vector machine, random forest, boosting, bagging, naïve Bayes, and k -nearest neighbor. Finally, we compared their predictive performance based on the area under the curve of the receiver operating characteristic curves, precision, recall, F1-score, Cohen′s Kappa, balanced accuracy, error rate, Matthews correlation coefficient, and area under the precision-recall curve. Additionally, three oversampling algorithms are used to deal with imbalance problems. Conclusions Our results show that penalized methods exhibit better predictive performance for asthma than that achieved via machine learning methods. On the other hand, in the oversampling study, randomforest and boosting methods overall showed better prediction performance than penalized methods.

Organizational socialization literature has long emphasized learning organizational culture upon entry. However, most previous socialization studies have largely focused on learning job skills, such as role clarity and task mastery. Focusing on emotional culture, the author provides a review about the roles of emotions in an organizational socialization context. Further, drawing upon the organizational socialization and emotion literature, the author builds a theoretical model, an emotional model of organizational socialization highlighting how newcomers adjust to the emotional culture within an organization, which ultimately leads to successful organizational socialization. This article provides new conceptual insights into the roles of newcomers’ adjustment to an emotional culture in a socialization context, providing fruitful ways for future empirical testing.

Based on Hirschman’s theory of loyalty and Packer’s normative conflict model, the present study examined the roles of organizational identification in the voice emergence and reaction processes, wherein individuals provide voice and receive evaluations for their voice behavior, respectively. Using a survey method, data were collected from 455 cadets and their supervisors at a military educational institute in South Korea, who live and work together under an honor-based organizational system that encourages voice behavior through formal and informal channels. Structural equation modeling (SEM) was used for hypothesis testing. Our findings from multi-source data demonstrated that, when controlling for two social exchange variables (i.e., leader–member exchange and perceived organizational support), organizational identification not only increases voice behavior but also strengthens the positive relationship between voice behavior and supervisor performance evaluations. Specifically, voice behavior has a positive relationship with performance appraisal only when organizational identification is high. Theoretical and practical implications of the findings and directions for future research are discussed.

This study was conducted to evaluate the effects of high-temperature stress on dairy cow productivity and the correlation between rumen sensors. The data were collected on the temperature, humidity, milk productivity, milk components, blood components, and rumen sensor data from 125 dairy cows during the experimental period (1 May 2020 to 30 October 2020). High-temperature stress of dairy cows was evaluated based on the temperature–humidity index (THI). The correlations between the high-temperature stress, productivity, and sensor data were analyzed using SAS and R programs. The THI ranged from 46.9 to 81.0 during the experimental period, and a significant decrease was observed in the milk production of dairy cows during August (p < 0.05). Milk production was evaluated to decrease by 1.8% because of high-temperature stress during the experimental period. There was a significantly high negative correlation between the THI ratio of day and rumen temperature (r = 0.744; p < 0.001). The other rumen sensor data did not show a significant correlation with the productivity of dairy cows. The results can be utilized as a guideline for managing temperature and humidity to maintain dairy cow productivity on farms in high-temperature stress conditions.

Dendritic cell (DC) migration is crucial for mounting immune responses. Immature DCs (imDCs) reportedly sense infections, while mature DCs (mDCs) move quickly to lymph nodes to deliver antigens to T cells. However, their highly heterogeneous and complex innate motility remains elusive. Here, we used an unsupervised machine learning (ML) approach to analyze long-term, two-dimensional migration trajectories of Granulocyte-macrophage colony-stimulating factor (GMCSF)-derived bone marrow-derived DCs (BMDCs). We discovered three migratory modes independent of the cell state: slow-diffusive (SD), slow-persistent (SP), and fast-persistent (FP). Remarkably, imDCs more frequently changed their modes, predominantly following a unicyclic SD→FP→SP→SD transition, whereas mDCs showed no transition directionality. We report that DC migration exhibits a history-dependent mode transition and maturation-dependent motility changes are emergent properties of the dynamic switching of the three migratory modes. Our ML-based investigation provides new insights into studying complex cellular migratory behavior.

The positive relationship between leader behavioral integrity and an employee’s in-role performance is well-established, but explanations for why this effect exists are still in a nascent stage. Drawing upon leader behavioral integrity theory and job-demands resources theory, the authors explain how leader behavioral integrity facilitates employee in-role performance and the boundary conditions influencing the relationship between leader behavioral integrity and employee in-role performance. Using multisource data from 209 employee-manager dyads in South Korea, this paper found support for the mediating effect of coworker support in the positive relationship between leader behavior integrity and employees’ in-role autonomy. Furthermore, compared to those who perceive low job autonomy, the positive indirect effect of leader behavioral integrity on in-role performance via coworker support was stronger for employees who perceive high job autonomy. The findings emphasize the importance of a leader’s individual difference (i.e., leader behavioral integrity) and job resources (i.e., job autonomy) facilitating the receipt of team members’ supporting behaviors which, in turn, energize employee in-role performance. Theoretical and practical implications are discussed.

This paper investigates the positive influence of perceived organizational support (POS) on employees’ knowledge sharing behavior through their affective commitment. Moreover, it examines the moderating effect of task interdependence, as a situational factor, on this mediating relationship. The results from a total of 222 supervisor-subordinate dyads showed that POS was positively related to affective commitment, leading to knowledge sharing behaviors. Besides, the mediation effect of affective commitment was stronger when task interdependence was low than when it was high. These results imply that employees receiving high organizational support would share their knowledge when they perceive knowledge sharing as a voluntary behavior. Theoretical and practical implications are discussed.

Multinational corporations (MNCs) face significant reputational and performance risks from product recalls, yet the severity of these consequences varies across national markets. While prior research suggests that corporate social responsibility (CSR) can buffer against such crises, limited attention has been paid to how country-level institutions shape this effect. This study examines whether—and under what institutional conditions—CSR reputation mitigates the negative market consequences of product recalls. We focus on how the insurance-like effect of CSR varies with the level of corruption in a country’s institutional environment. Using panel regression analysis and hand-collected data from 14 global automotive manufacturers across eight countries (2007–2015), we find that firms with stronger CSR reputations experience significantly smaller declines in market share after recall announcements. Furthermore, this buffering effect is amplified in countries with higher corruption levels, suggesting that when formal institutional trust is weak, CSR signals play a greater role in stakeholder perceptions. These findings advance CSR literature by showing that its reputational benefits are contingent on institutional context and contribute to international business scholarship by revealing how national-level corruption interacts with firm-level reputational assets during crises.

There is increasing interest in membrane systems powered by renewable energy sources, including solar and wind, that are suitable for decentralized water supply in islands and remote regions. These membrane systems are often operated intermittently with extended shutdown periods to minimize the capacity of the energy storage devices. However, relatively little information is available on the effect of intermittent operation on membrane fouling. In this work, the fouling of pressurized membranes under intermittent operation was investigated using an approach based on optical coherence tomography (OCT), which allows non-destructive and non-invasive examination of membrane fouling. In reverse osmosis (RO), intermittently operated membranes were investigated by OCT-based characterization. Several model foulants such as NaCl and humic acids were used, as well as real seawater. The cross-sectional OCT images of the fouling were visualized as a three-dimensional volume using Image J. The OCT images were used to quantitatively measure the thickness of foulants on the membrane surfaces under different operating conditions. The results showed that intermittent operation retarded the flux decrease due to fouling compared to continuous operation. The OCT analysis showed that the foulant thickness was significantly reduced by the intermittent operation. The decrease in foulant layer thickness was found to occur when the RO process was restarted in intermittent operation.

Combined cycle power plants (CCPPs) use large amounts of water withdrawn from nearby rivers and generate wastewater containing ions and pollutants. Despite the need for wastewater reclamation, few technologies can successfully convert the wastewater into make-up water for CCPPs. Therefore, this study aimed to apply capacitive deionization (CDI) for wastewater reclamation in CCPPs. Using a bench-scale experimental unit, which included ion exchange membranes and carbon electrodes, response surface methodology (RSM) was used to optimize the operating conditions of the CDI process to increase the total dissolved solids (TDS) removal and product water ratio. The optimal conditions were found to be a voltage of 1.5 V, a flow rate of 15 mL/min, and an adsorption/desorption ratio of 1:0.8. The changes in CDI performance with time were also studied, and the foulants on the membranes, spacers, and electrodes were examined to understand the fouling mechanism. The TDS removal decreased from 93.65% to 55.70% after 10 days of operation due to the deposition of scale and organic matter. After chemical cleaning, the TDS removal rate recovered to 93.02%, which is close to the initial condition.