Search Results (75)

Coir is widely used as a soilless substrate yet partially replacing it with walnut shells in coir-based mixes may improve the sustainability of lettuce production and quality. This study evaluated the effect of incorporating walnut shells, with or without biochar, into coir-based substrates on lettuce yield and quality. Lettuce was grown in five substrates: coir (C), three coir–walnut mixes (1:1, 1:0.5, and 1:0.25 v/v), and one coir–walnut–biochar mix (C:W:B, 10:1.5:1 v/v). Increasing the walnut-shell proportion increased the cumulative leaching fraction, likely because of the coarse walnut particles, and reduced head fresh weight. However, shoot dry weight in the 1:0.5 and 1:0.25 mixes was similar to that in coir alone and reduced leaf nitrate content. In contrast, the C:W:B mix maintained head fresh weight (7.1 kg m⁻²) and shoot dry weight comparable to coir, while markedly lowering leaf nitrate concentration from 4130 to below 200 mg NO₃⁻ kg⁻¹ fresh weight. Leaf nitrate content increased linearly with shoot Zn uptake, suggesting a Zn-mediated control of nitrate accumulation. The coir–walnut–biochar mix emerges as a suitable alternative to pure coir, as it maintains lettuce productivity, reduces leaf nitrate accumulation, enhances anthocyanin content, and reflects more favorable physiological conditions by not requiring a strong activation of antioxidant defenses. Full article

Background: Non-muscle invasive bladder cancer (NMIBC) has limited therapeutic options and high recurrence rates. Photoimmunotherapy (PIT) enables targeted tumor ablation using antibody-photosensitizer conjugates and light activation. We evaluated EGFR, Nectin-4, and TROP-2 as PIT targets using cysteine-modified antibodies conjugated to the photosensitizer WB692-CB2. Methods: Antibodies derived from Cetuximab (Cmb, anti-EGFR), Enfortumab (Enf, anti-Nectin-4), and Sacituzumab (Sac, anti-TROP-2) were engineered with T120C and D265C mutations in the heavy chains for site-specific dye conjugation. Binding of the conjugates to BC cells was tested by flow cytometry and light-induced cytotoxicity of the conjugates, alone or in combination, was assessed by viability assays following irradiation. Results: Cysteine-modified antibodies were produced as intact IgG molecules and were efficiently conjugated with WB692-CB2 without loss of antigen specificity. Sac^T120C/D265C-WB692-CB2 showed the highest target binding and achieved near-complete cell killing at a red-light dose of 32 J/cm². Cmb^T120C/D265C-WB692-CB2 required a fourfold higher light dose for comparable efficacy, while Enf^T120C/D265C-WB692-CB2 demonstrated lower potency. No cytotoxicity was observed in antigen-negative cells. Combined treatment enhanced cytotoxicity, indicating additive phototherapeutic effects. Conclusions: Our findings suggest that PIT targeting EGFR, Nectin-4, or TROP-2 merits further preclinical development as a targeted therapeutic approach for NMIBC, including potential combinatorial or personalized strategies. Full article

Grounded in the Conservation of Resources (COR) theory, this study investigates how negative workplace gossip (NWG) influences counterproductive work behavior (CWB) in the hospitality industry. It further examines the mediating role of self-esteem and the moderating influence of emotional contagion in shaping this relationship. While prior research has predominantly treated NWG as a social stressor or reputational threat, this study extends the COR theory by explicitly modeling the resource depletion mechanism, specifically, the erosion of self-esteem as a key pathway linking NWG to CWB. By doing so, it posits that gossip erodes self-esteem, a fundamental psychological resource that eventually leads to behavioral retreat or revenge. Within the COR framework, the study also presents emotional contagion as a unique moderating variable, emphasizing how individual differences in emotional susceptibility may either accelerate or buffer the process of resource loss. Data was collected from 437 employees working in five-star hotels in Sharm El-Sheikh using a structured questionnaire. Analysis via PLS-SEM revealed that NWG significantly increases CWB, both directly and indirectly, by undermining employees’ self-esteem. Additionally, self-esteem was found to mediate the NWG–CWB link, while emotional contagion moderated the impact of NWG on self-esteem, suggesting that individuals with better emotional regulation can maintain self-worth in the face of workplace gossip. The study offers both theoretical and practical insights, highlighting the value of incorporating emotional contagion within the COR theory to understand and manage gossip-induced stress. It also underscores the importance of emotional intelligence and HR practices such as training and selection in minimizing the harmful effects of gossip at work. Full article

The accelerated advancement of artificial intelligence (AI) has positioned it as a novel colleague. However, as employees collaborate with AI colleagues in daily work, their communication and interaction with human colleagues may decrease. This may result in feelings of loneliness and a potential reduction in emotional resources, potentially leading to counterproductive work behavior (CWB). Drawing from the conservation of resources (COR) theory, we hypothesize that employee–AI collaboration may amplify employees’ CWB due to loneliness and emotional fatigue. The potential mitigating effects of leader emotional support on these outcomes are also considered. To test these hypotheses, a 2 × 2 vignette experiment (N = 167) was conducted. The results demonstrate that employee–AI collaboration exerts a substantial positive influence on loneliness. Loneliness further increases employees’ emotional fatigue, which in turn increases CWB. Leader emotional support—the care and motivation demonstrated by leaders has been identified as a key factor in reducing loneliness. This research contributes to the extant literature on employee–AI collaboration and CWB, and expands the application scope of COR. Practical implications arise for managers, who are encouraged to consider the impact of employee–AI collaboration on interpersonal interaction and to address employees’ emotional needs in a timely manner. Full article

This study performed in-season yield prediction, about 2–3 months before the harvest, for cereals and rapeseed at the province level in Poland for 2009–2024. Various models were employed, including machine learning algorithms and multiple linear regression. The satellite-derived normalized difference vegetation index (NDVI) and climatic water balance (CWB), calculated using meteorological data, were treated as predictors of crop yield. The accuracy of the models was compared to identify the optimal approach. The strongest correlation coefficients with crop yield were observed for the NDVI at the beginning of March, ranging from 0.454 for rapeseed to 0.503 for rye. Depending on the crop, the highest R² values were observed for different prediction models, ranging from 0.654 for rapeseed based on the random forest model to 0.777 for basic cereals based on linear regression. The random forest model was best for rapeseed yield, while for cereal, the best prediction was observed for multiple linear regression or neural network models. For the studied crops, all models had mean absolute errors and root mean squared errors not exceeding 6 dt/ha, which is relatively small because it is under 20% of the mean yield. For the best models, in most cases, relative errors were not higher than 10% of the mean yield. The results proved that linear regression and machine learning models are characterized by similar predictions, likely due to the relatively small sample size (256 observations). Full article

(1) Background and Objective: The debate on the stability and variability of subjective wellbeing (SWB) is decades old. However, despite the wealth of literature on this topic, there are relatively few studies that aim to explain the “why” and “how” of the dynamics of SWB. In this context, the objective of this exploratory study is to test the plausibility of a model of the cognitive component of SWB (CWB) inspired by the control theory. In this model, a measure of future life expectations (FLEs) serves as a target in the control loop regulating cognitive wellbeing (CWB), while general self-efficacy (GSE) and affective wellbeing (AWB) are mediators in the direct and feedback loops. (2) Method: To test this model, we collected data from a convenience sample of N-98 Romanian students in Computer Science using well-established questionnaires measuring CWB, GSE, AWB, and FLE. Mediation analyses and path modeling were conducted to evaluate the feedback-based model of the interplay between these variables. (3) Results: The findings confirm a significant relationship between FLE and CWB (β = 0.62, p < 0.001). GSE partially mediates the link between FLE and CWB (β = 0.139, p = 0.02), while AWB mediates the feedback from CWB to FLE (β = 0.297, p < 0.001). The model explains 42% of the variance of CWB. (4) Conclusions: Our study remains exploratory in nature, but preliminary data suggest that a model of SWB based on feedback control is worth attention as it might provide a better understanding of the dynamics of SWB. Full article

This article aims to investigate the impact of toxic leadership (TL) on counterproductive work behavior (CWB) with the mediating roles of organizational cynicism (OC) and organizational injustice (OIJ), using 392 questionnaires collected from employees working in the Egyptian higher education sector. The data are examined using AMOS 25 for structural equation model (SEM) analysis. The results show that toxic leadership positively affects CWBs, organizational cynicism, and organizational injustice. Furthermore, organizational cynicism positively affects CWBs, and organizational injustice significantly affects CWBs. Finally, organizational cynicism and injustice partially mediate the relationship between toxic leadership and CWBs. This study adds novelty to the literature by exploring the influence of toxic leadership on CWBs, OC, and OIJ in Egypt’s higher education sector. As a result, addressing the prevalence of toxic leadership and its ripple effects is essential for fostering sustainable organizational cultures. Sustainable work environments prioritize fairness, employee well-being, and positive leadership practices, reducing counterproductive behaviors. Finally, this article reviews the limitations but also assesses the substantial contributions to theory and practice made by the paper. Full article

Data for solar radiation resources play a pivotal role in assessing the energy yield capability of solar applications. A nationwide database for the typical meteorological year from the 30 weather stations of the Central Weather Bureau (CWB) in Taiwan is used to determine the spatial distribution of global radiation over the terrain of Taiwan. There is no available beam radiation information in daily reports from all CWB stations. Information on the diffuse fraction for all CWB stations is estimated using three available correlation models that account for topographical and geographical effects in Taiwan. The databases for beam radiation are generated using these estimated diffuse fractions. The mappings of global and beam radiation on the Taiwanese mainland are performed with databases from 24 CWB stations using the residual kriging method. There are no mappings of the remote islands, where six CWB stations are located. The databases for global and beam radiation for these six CWB stations are applied to nearby remote islands. The effects of topography and geography on the distributions of global and beam radiation are discussed. The spatial distributions of solar radiation presented are good scientific references for assessing the performances of solar energy systems in Taiwan. Full article

Despite advances in understanding the factors that predict unethical behaviors such as counterproductive workplace behavior (CWB), there is still substantial variance left unexplained in the occurrence of unethical behavior. Recent research has examined how unethical behavior may change beyond initially reported levels due to the gradual erosion of ethicality via justification processes such as moral disengagement. The present study extends this research by examining the role of personality in determining the extent to which individuals make subsequent unethical decisions at greater or lower levels beyond their initial levels. Studies 1 and 2 used an experimental design that presents half of participants with an opportunity to practice moral disengagement by allowing participants to justify their actions. Results in study 1 demonstrate that individuals with high levels of dark personality traits tend to increase their level of unethical decision making when given the chance to justify their actions, whereas those with low levels of dark personality become less unethical. Study 2 examines the extent to which the mediating role of perceived justice changes when participants are given an opportunity to justify their actions. Results from study 2 show the effects of justice as a mediating mechanism are significantly diminished when the justification manipulation is present. Implications emphasize the need to use both selection and development interventions in organizations to reduce gradual decreases in ethicality as well as reduced reliance on cross-sectional research to study a phenomenon that can change as unethical behavior is justified. Full article

This study investigates the complex interplay between organizationally prescribed perfectionism (OPP), job insecurity, counterproductive work behavior (CWB), and self-efficacy in learning artificial intelligence (AI) in the context of modern organizations. Based on several theories, the current research suggests and tests a moderated mediation model. Using a three-wave time-lagged design with data collected from 412 workers across various South Korean corporations, we examine how OPP influences CWB both directly and indirectly through job insecurity, and how self-efficacy in AI learning moderates the OPP–job insecurity link. Our results show that OPP is positively linked to CWB, and this association is partially mediated by job insecurity. Moreover, AI learning self-efficacy functions as a moderator in the OPP–job insecurity link, such that the positive link is weaker for members with higher levels of AI learning self-efficacy. These findings extend our understanding of perfectionism in organizational settings and highlight the role of technological self-efficacy in mitigating the negative impacts of perfectionist cultures. This research may contribute to the literature on perfectionism, CWB, and technological adaptation at work, and has important implications for managing high-performance cultures in the period of rapid technological advancement. Full article

Viscoelastic monitoring of horse coagulation is increasing due to its advantages over traditional coagulation testing. The use of a point-of-care viscoelastic coagulation monitor (VCM Vet™) has been validated for use in horses using native whole blood (NWB) but has not been assessed using citrated whole blood (CWB), a technique that might have advantages in practicality and precision. Blood was collected from 70 horses, tested in duplicate immediately using NWB (T0), and stored at room temperature as CWB for testing in duplicate at 1 (T1) and 4 (T4) hours after venipuncture for comparison to NWB. Of these horses, 20 were classified as clinically healthy and used to determine reference intervals for CWB at 1 and 4 h post-collection. There were clinically relevant differences in all measured viscoelastic parameters of CWB compared to NWB meaning that they cannot be used interchangeably. These differences were not consistent at T1 and T4 meaning the resting time of CWB influences the results and should be kept consistent. The use of CWB in this study also resulted in more machine errors when compared to NWB resulting in measurements that might not be interpretable. Full article

The intricate relationship between climate and society in a given region demands a profound understanding of climate patterns, especially in agricultural areas like Diamantina, Minas Gerais (MG), recognized by the Food and Agriculture Organization (FAO) as the birthplace of the first Globally Important Agricultural Heritage System (GIAHS) in Brazil, situated in the southwest region of the country. Given the growing concerns about climate change, we conducted a meticulous analysis of the climatic characteristics of Diamantina-MG. To achieve this, we examined historical meteorological data from 1973 to 2022, employing the Mann–Kendall and Sen’s slope tests to analyze trends. Additionally, we utilized three global climate models (GCMs) under different shared socioeconomic pathways (SSPs) to predict future climate scenarios (2021–2100) based on the projections of the sixth phase of the Coupled Model Intercomparison Project (CMIP6). Furthermore, we used Köppen and Thornthwaite climate classification methodologies to characterize both the current and future climate conditions of the region. Our results indicate that, historically, Diamantina-MG has experienced significant increases in minimum temperature, indicating a warmer climate in recent decades. For temperature, the projections show a consensus among models, projecting a continuous increase, potentially reaching up to 5.8 °C above the historical average temperature (19.2 °C) by the end of the century. Regarding rainfall projections, they show greater uncertainty, with discrepancies among models observed until 2060. However, specifically for the second half of the century (2060–2100), the models agree that there will be increases in annual rainfall. Regarding the climatic types of the region, we found that the current Köppen Cwb and Thornthwaite B3rB’3a’ classifications could shift to Aw and B1wA’a’, representing a humid tropical savanna climate with longer periods of water deficiency, considering the impacts resulting from increased air temperature and evapotranspiration. In summary, the study’s results indicate that climate changes are occurring and are likely to intensify in the Jequitinhonha Valley region, MG, in the future. The analysis of these data, from the perspective of the Brazilian GIAHS sustainability, reveals the importance of considering adaptation and mitigation measures to ensure the resilience of agricultural systems and local communities in the region that face these significant environmental changes. Full article

Given the dearth of systematic research and inconclusive results regarding the effectiveness of emotional intelligence (EI) training in adult training, this study was conducted to evaluate the effectiveness of EI training. This study aimed to assess the effectiveness of EI training on learning and transfer outcomes, considering underexplored moderation of social and organizational support with experimental and longitudinal research design. Training transfer was measured through changes in organizational citizenship behavior (OCB) and counterproductive work behavior (CWB). Participants self-assessed their OCB and CWB levels, while their supervisors also provided evaluations, allowing for separate analysis. Data, from a sample comprising 176 government officials, were collected across different periods and analyzed employing diverse analytical tools. The results revealed positive effects of EI training on training outcomes in both samples but positive moderation effect of social and organizational support on the effect of EI training on training outcomes was observed in the self-evaluation sample but not in the supervisor evaluation sample. The findings advance the debate on social exchange theory and organizational support theory by showing the boundary condition of their applicability. Furthermore, this study clarifies the impact of EI training on training outcomes by emphasizing the nuanced role of social and organizational support. Full article

Climate change poses a significant threat to humanity. Achieving net-zero emissions is a key goal in many countries. Among various energy resources, solar power generation is one of the prominent renewable energy sources. Previous studies have demonstrated that post-processing techniques such as bias correction can enhance the accuracy of solar power forecasting based on numerical weather prediction (NWP) models. To improve the post-processing technique, this study proposes a new day-ahead forecasting framework that integrates weather research and forecasting solar (WRF-Solar) irradiances and the total solar power generation measurements for five cities in northern, central, and southern Taiwan. The WRF-Solar irradiances generated by the Taiwan Central Weather Bureau (CWB) were first subjected to bias correction using the decaying average (DA) method. Then, the effectiveness of this correction method was verified, which led to an improvement of 22% in the forecasting capability from the WRF-Solar model. Subsequently, the WRF-Solar irradiances after bias correction using the DA method were utilized as inputs into the transformer model to predict the day-ahead total solar power generation. The experimental results demonstrate that the application of bias-corrected WRF-Solar irradiances enhances the accuracy of day-ahead solar power forecasts by 15% compared with experiments conducted without bias correction. These findings highlight the necessity of correcting numerical weather predictions to improve the accuracy of solar power forecasts. Full article

Earth’s forests are increasingly exposed to climate risks through climate change-related drought and heat waves. Here, we review the climate vulnerability of European beech (Fagus sylvatica), the most abundant tree species of Central Europe’s temperate forests, and its adaptation potential to a hotter and drier climate in northern Germany, close to the center of the species’ distribution range. About two-thirds of the studied beech forests show persistent negative growth trends of their dominant trees since the onset of rapid warming in the early 1980s, driven primarily by long-term deterioration of the climatic water balance (CWB) in summer and, locally, long-term decrease in June precipitation. Lower water storage capacity of the soil increases the climate sensitivity of growth. Even though beech populations of drier sub-regions reveal some acclimation to drought (reduced stomatal conductance, turgor loss point reduction, higher C allocation to roots), they are more climate-vulnerable than populations at moister sites, visible in larger growth decreases and greater CWB sensitivity of growth. Even though beech mortality is still lower in the study region than in other parts of Central Europe, our results identify beech forest regions with <350 mm growing-season precipitation as vulnerable to recent climate conditions, which refers to half of the study region. With further climate warming and aridification, most of northern Germany likely will become unfavorable for beech growth within the next tree generation, which suggests choosing in many production forests alternative, more drought- and heat-resistant timber species. Full article