Dynamic Shift Research Articles

Navigating global HR challenges and safeguarding long-term sustainability

This research delves into the dynamic shifts in human resource management strategies prompted by the COVID-19 pandemic. It investigates the mediating influence of information technology (IT) challenges on the connection between pandemic-induced international human resource management (IHRM) practices and the competitiveness of multinational corporations (MNCs) in Malaysia with focusing on sustainable development. Through the analysis of data collected from 172 respondents via self-administered questionnaires in Malaysian MNCs across various sectors including education, general services, ICT, property, construction, and healthcare, the study employs partial least squares structural equation modeling (PLS-SEM) to validate the proposed hypotheses. The findings highlight the substantial impact of compensation and staffing practices on technology transfer challenges within MNCs. Furthermore, the study reveals that the implementation of remote work, particularly during and post-lockdowns, is associated with elevated compensation and enhances overall company competitiveness. These outcomes offer theoretical and practical insights, furnishing human resource managers, especially in multinational corporations, with valuable guidance for maintaining competitiveness amidst the disruptions of a pandemic and promoting sustainability in HR practices. By highlighting the potential benefits of working from home in terms of both IHRM outcomes and competitiveness, the study contributes to ongoing discussions about the future of work and the role of technology-enabled practices in driving organizational success and sustainable development.

Gene markers generating polygenic resistance in melon-Fusarium wilt-FOM1.2 interaction pathosystem.

Developing melon genotypes with resistance to Fusarium oxysporum f. sp. Melonis-(FOM) race1.2 is a major goal in any breeding program. In this study, we identified the role of 11 gene markers that contribute to polygenic resistance during the FOM1.2-melon interaction. qRT-PCR analysis elucidated upregulation of candidate marker genes AMT, DXPR, Fom-2, GLUC, GalS, GRF3, MLO, PRK, RuBlsCo, TLP and WRKY in resistant 'Shante-F1' and 'Khatouni', and susceptible 'Shante-T' and 'Shahabadi' at 7, 14 and 21 days post-inoculation (dpi). We also studied changes in defence-related enzyme activity: chitinase (CHI), β-1,3-glucanase (GLU) and peroxidase (POX) in melon roots. AMT, GLUC and DXPR transcripts were upregulatied in leaf and root tissues of the resistant 'Shante-F1' and 'Shahabadi'. Transcript levels for GalS and GRF3 increased 6.77- and 6.83-fold in roots of 'Shante-F1' at 7 dpi, whereas in PRK, TLP and WRKY theye increased by 7.84-, 5.15- and 12.26-fold at 14 dpi, respectively. However, transcript levels increased by 5.18-fold for Fom-2 and 8.46-fold for MLO at 21 dpi. Also, RBC transcript level peaked at 14 dpi with 4.9-fold increase in leaves of resistant genotypes, whereas AMT increased 2.94-fold at 21 dpi, and GLUC and DXPR increased 7.11- and 2.91-fold at 14 dpi in 'Shante-F', respectively. Defence-related-enzyme activity was also upregulated three-fold in resistant varieties. The dynamic shifts in the melon transcriptome induced by FOM1.2 emphasize that resistance mechanisms are predominantly regulated through signalling pathways involving CHI, GLU, and POX defence response. Surprisingly, the AMT gene, basically resistant to downy mildew, Pseudoperonospora cubensis; GLUC, MLO and PRK resistant to powdery mildew (Sphaerotheca fusca); TLP and WRKY resistant to Phytophthora blight (Phytophthora capsici); and GRF3 and RBC resistant to root knot nematodes (Meloidogyne spp.) were upregulated in resistant genotypes, indicating a dual role of these genes in resistance to more than one disease at a time.

Assessing Trade-Offs and Synergies in Ecosystem Services within the Tianshan Mountainous Region

In managing ecosystem services (ESs), it is vital to understand and effectively regulate the trade-offs and synergies (ToSs) involved. This study investigates the Tianshan Mountains (TSMs), utilizing the InVEST (Integrated Valuation of ESs and Tradeoffs) model to evaluate ecosystem service changes from 2000 to 2020, while employing univariate linear regression to examine their spatiotemporal dynamics. Pearson correlation analysis was also conducted to assess how climatic variables (temperature and precipitation) and vegetation indicators (NDVI, normalized difference vegetation index) influence the overall ecosystem service benefits. The findings reveal notable spatial heterogeneity and dynamic shifts in ESs across the TSMs, with strong synergies observed between carbon storage (CS) and other services (such as habitat quality, HQ; soil conservation, SC; and water yield, WY), especially in areas experiencing increased vegetation. However, the connection between HQ and WY was comparatively weaker and occasionally exhibited negative correlations during specific periods, highlighting the intricate trade-offs among various services. The correlation analysis further showed that climate and vegetation changes significantly impact ecosystem service benefits, with declining precipitation and rising temperatures reducing these benefits, whereas higher NDVI was associated with improved service functions. Ultimately, this study emphasizes the necessity of recognizing and managing ToSs in ESs to promote sustainable regional ecosystem development.

Reassessing water resource challenges in a changing climate in the Kagera transboundary river basin, Tanzania

The dynamic shifts in climatic patterns, particularly alterations in precipitation, have significantly impacted water resource availability and accessibility. These climate-induced changes affect hydrological processes, encompassing runoff, groundwater replenishment, water demand, and biophysical patterns within river basins. This study seeks to unravel the multifaceted implications encountered and challenges in water resource management within the river basin. It employed a survey-based approach for data collection, including Key informant interviews (KI), consultation methods and documentary reviews. The study utilized Statistical Package for the Social Sciences (SPSS) and Microsoft Excel for quantitative analysis and thematic synthesis for qualitative insights, including local community perspectives. The findings reveal substantial fluctuations in precipitation, protracted droughts, severe flooding, and other climatic extremes. The observed annual mean rainfall of 832 mm, with a standard deviation of 248, a standard error of 361, and a skewness of −945, accentuates the pronounced variability in mean precipitation, exhibiting a declining trend indicative of climatic shifts (R2 = 0.1797 and P = 0.002). The challenges are limited access to hydrological and meteorological data, undermining prediction accuracy, infrastructure planning, and response strategies for water resource allocation and management. The absence of unified approaches, influenced by the politics of riparian states, feeble coordination, conflicting sectoral policies, and ambiguous priorities, hinders effective transboundary water resource management. The study addresses these complexities and advocates for institutionalizing robust water management strategies that capitalize on existing resources and foster innovative capacities among critical stakeholders. Central to these efforts is harmonizing and enforcing policies, regulations, and laws governing water use, coupled with a concerted focus on inclusive governance to ensure the sustainability of water resource management. Such effort entails synchronized strategies, programs, plans, and livelihood practices underpinned by active stakeholder involvement in pivotal facets of water resources management.

Alterations in the Renin-Angiotensin System in Experimental Septic Shock.

To analyze dynamic changes in the renin-angiotensin system (RAS) during septic shock, focusing on angiotensin-converting enzyme (ACE) activity and the balance between angiotensin peptides, using a mass spectrometry method. Experimental septic shock model induced by peritonitis in swine. Experimental Laboratory, Department of Intensive Care, Erasme Hospital, Université Libre de Bruxelles. Forty time points from eight mechanically ventilated pigs. Septic shock was induced using intraperitoneal instillation of autologous feces, followed by standardized fluid resuscitation, norepinephrine infusion, antibiotic administration, and peritoneal lavage. The induction of sepsis resulted in a significant increase in plasma renin activity and levels of angiotensin I and II, with a significant decrease in ACE activity observed from 4 hours post-resuscitation and a notable rise in the angiotensin I/angiotensin II ratio at 12 hours. Additionally, a shift toward the angiotensin-(1-7) axis was observed, evidenced by an increased angiotensin-(1-7)/angiotensin II ratio. The study highlighted dynamic shifts in the RAS during septic shock, characterized by reduced circulating ACE activity, elevated angiotensin I/II ratio, and a shift toward the angiotensin-(1-7) axis. These findings suggest an adaptive response within the RAS, potentially offering new insights into sepsis management and therapeutic targets.

Unravelling the shift: exploring consumers’ adoption or resistance of E-Pharmacy through behavioural reasoning theory

In the ever-evolving nature of the healthcare sector, the advent of electronic-Pharmacy introduces a dynamic shift in how consumers acquire and access medical and pharmaceutical products. The research utilized the behaviour reasoning theory. The study evaluated the reasons for adopting and against adopting electronic-Pharmacy. By employing the qualitative approach, this study unravels rich contextual and narrative insights, shedding light on the complexities of individual decision-making processes. The study received responses from 28 through an in-depth interview, and thematic data analysis was employed for the data analysis. The outcome of the research is summarized as follows. The respondents indicated that essential reasons for adopting electronic pharmacy services include convenience and accessibility, prescription management, cost and affordability, logistics, and timely delivery. On the other hand, the reasons against adoption include trust and security concerns, regulatory challenges and legal uncertainties, lack of internet access and privacy concerns. As technology changes healthcare delivery, this research closes the knowledge gap between theory and practice by offering crucial insights into the behavioural aspects influencing electronic-Pharmacy adoption or resistance. The findings are anticipated to significantly impact the academic discourse surrounding electronic-health and the practical implementation of strategies to enhance the integration of electronic-Pharmacy services into conventional healthcare systems.

Constraining the Possible Mechanisms Underlying Performance Improvements Following Peripheral Vision Training

AbstractSome training paradigms can improve performance specific to the trained portion of the visual field. Similarly, experience with both pathological and simulated central vision loss can result in compensatory improvement in performance specific to a spared retinal location. The mechanisms underlying these improvements are still debated. Modifications in the capacity to allocate attention to trained locations might explain some of the changes in performance after learning, especially given similarities between behavioral improvements due to training and improvements due to changes in attention. Using a gaze-contingent simulated scotoma paradigm which simulates central vision loss, we tested whether training to use peripheral vision influenced three aspects of visual attention: habitual attention, dynamic exogenous attention, and dynamic endogenous attention. After training, performance improvements were consistent with increased habitual attention to the trained location. Conversely, measures of dynamic shifts of attention (exogenous and endogenous attention) improved similarly in both trained and untrained locations. The lack of retinotopic specificity in dynamic attention improvements suggests that retinotopically specific perceptual improvements following simulated central vision loss are not mediated by dynamic attention changes. On the other hand, habitual attention did change retinotopically, leaving the possibility open that this aspect of attention may drive some retinotopically specific training effects. This work constrains the range of mechanisms that could underlie performance improvements after peripheral vision training, suggesting that habitual attention and dynamic attention are affected independently.

Outcomes of Patients With Early and Locally Advanced Lung Cancer: Protocol for the Italian Lung Cancer Observational Study (LUCENT).

Lung cancer, predominantly non-small cell lung cancer (NSCLC), remains a formidable challenge, necessitating an in-depth understanding of evolving treatment paradigms. The Italian Lung Cancer Observational Study (LUCENT) addresses this need by investigating the outcomes of patients with early and locally advanced lung cancer in Italy. With a focus on real-world data and patient registries, this study aims to provide comprehensive insights into clinical, psychosocial, and economic impacts, contributing to informed decision-making in health care. LUCENT is a prospective observational multicenter cohort study enrolling patients eligible for minimally invasive manual, robot-assisted, or traditional open surgery. The study will develop a web-based registry to collect longitudinal surgical, oncological, and socioeconomic outcome data. The primary objectives include performance assessment through the establishment of national benchmarks based on risk-adjusted outcomes and processes of care indicators. The secondary objectives encompass economic and psychosocial impact assessments of innovative technologies and treatment pathways. The multicenter design ensures a diverse and representative study population. The evolving landscape of NSCLC treatment necessitates a nuanced approach with consideration of the dynamic shifts in therapeutic strategies. LUCENT strives to fill existing knowledge gaps by providing a platform for collecting and analyzing real-world data, emphasizing the importance of patient-reported outcomes in enhancing the understanding of the disease. By developing a web-based registry, the study not only facilitates efficient data collection but also addresses the limitations of traditional methods, such as suboptimal response rates and costs associated with paper-and-pencil questionnaires. Recruitment will be conducted from January 01, 2024, to December 31, 2026. Follow-up will be performed for a minimum of 2 years. The study will be completed in the year 2028. LUCENT's potential implications are substantial. Establishing national benchmarks will enable a thorough evaluation of outcomes and care processes, guiding clinicians and policymakers in optimizing patient management. Furthermore, the study's secondary objectives, focusing on economic and psychosocial impacts, align with the contemporary emphasis on holistic cancer care. Insights gained from this study may influence treatment strategies, resource utilization, and patient well-being, thereby contributing to the ongoing refinement of lung cancer management. ClinicalTrials.gov NCT05851755; https://clinicaltrials.gov/study/NCT05851755. ISRCTN 67197140; https://www.isrctn.com/ISRCTN67197140. PRR1-10.2196/57183.

Dynamic reinforcement learning reveals time-dependent shifts in strategy during reward learning.

Different brain systems have been hypothesized to subserve multiple "experts" that compete to generate behavior. In reinforcement learning, two general processes, one model-free (MF) and one model-based (MB), are often modeled as a mixture of agents (MoA) and hypothesized to capture differences between automaticity vs. deliberation. However, shifts in strategy cannot be captured by a static MoA. To investigate such dynamics, we present the mixture-of-agents hidden Markov model (MoA-HMM), which simultaneously learns inferred action values from a set of agents and the temporal dynamics of underlying "hidden" states that capture shifts in agent contributions over time. Applying this model to a multi-step, reward-guided task in rats reveals a progression of within-session strategies: a shift from initial MB exploration to MB exploitation, and finally to reduced engagement. The inferred states predict changes in both response time and OFC neural encoding during the task, suggesting that these states are capturing real shifts in dynamics.

Distributional learning drives statistical suppression and deafening.

Organisms as diverse as honeybees and humans pick up on probabilities in the world around them. People implicitly learn the likelihood of a color, price range, or even syntactic structure. How does statistical learning affect how we detect events and make decisions, especially when probabilities are completely irrelevant to the task at hand, and can change without warning? We find that people learn and track changes in perceptual probabilities irrelevant to a task and that this learning drives dynamic shifts in perception characterized by graded effects of enhancement and primarily - suppression across acoustic frequency. This can result in a remarkably long-lived 'statistical deafening' that seems maladaptive but may instead reflect use of likelihood to guide and sharpen perception.

Breaking the board: the rise of female Go players in Korea

In the historically male-dominated world of Go—a game with a rich history and a current global player base of 46 million—recent years have marked a significant shift in gender dynamics, highlighted by Choi Jeong’s historic achievement as the first female to reach the open major world tournament finals. This study investigates the rise of female Go players in Korea through multiple lenses: descriptive analyses cover demographic data, Elo ratings, and competition statistics, while social representation analyses employ in-depth interviews and core-periphery analysis. A core finding is the profound transformation within the Korean Go community, where female players are not just witnessing increased representation but also significant enhancements in performance, opportunities, and financial rewards. Narratives from the players unravel the intricate web of performance disparities, community engagement, and evolving infrastructures. Economic incentives, societal and cultural shifts, and institutional support are identified as key contributors to their success. Beyond its application to professional Go, this research underscores a paradigmatic shift, illuminating strategies for fostering gender inclusivity in fields traditionally overshadowed by male dominance.

Desertification Mitigation in Northern China Was Promoted by Climate Drivers after 2000

Desertification greatly threatens the ecological environment and sustainable development over approximately 30% of global land. In this study, the contributions of climate drivers and human activity in shaping the desertification process from 1984 to 2014 were quantified in the desertification-prone region (DPR) in Northern China (NC) by employing net primary productivity (NPP) as a proxy. The results reveal that 72.74% of the DPR experienced desertification mitigation and 27.26% experienced exacerbation. Climate drivers acted as primary drivers, contributing to both the mitigation (47.2%) and exacerbation (48.5%) of desertification, while human activity also played a crucial role, with contributions of 39.6% to mitigation and 41.0% to exacerbation of desertification. Furthermore, a shift in desertification dynamics emerged around 2000, with climate drivers promoting the mitigation process (66.8%), and precipitation was a dominant climatic factor for the mitigation of desertification after 2000, which was related to internal atmospheric variability. This study highlights changes in the contributions of different factors to desertification, underscoring the need for policy adjustment to attain sustainable land management in NC.

Exploring acoustic wave transmission in micropolar plate in air

This study explores the behavior of sound wave propagation across a micropolar plate at diverse incident angles, specifically crafted from expanded polystyrene. Through a blend of theoretical formulations and practical experimentation, we scrutinize the alterations in transmission coefficients within the frequency spectrum, shedding light on the dynamic shifts in various vibrational modes. Utilizing a comprehensive setup comprising a loudspeaker, microphone, and National Instruments acquisition system, we meticulously discerned the initial trio of longitudinal vibration modes across a broad frequency span extending up to 70 kHz. Notably, despite the plate's inherent dispersion and attenuation traits, this experimental setup proved effective. A distinctive facet of our approach lies in the deliberate incorporation of multiple incident angles, which yielded crucial insights. Notable is the identification, within the experiments, of a critical angle, marking a transitional zone. Below this threshold, distinct Lamb modes dominate, while beyond it, the emergence of micropolar modes becomes apparent. These empirically validated findings, in alignment with theoretical projections, substantially enrich our comprehension of these materials' engineering applications.

Sufficiency Initiatives and Municipalities: Opportunities and Limitations for Bringing People and Politics Together

This article examines the potential and challenges of sufficiency initiatives within the urban environment, focusing on their ability to bring people and politics together. Drawing on research from the EU-funded “FULFILL” project, which includes surveys, interviews and case studies in five EU Member States, this study explores the role of civil society initiatives in fostering sufficiency—a concept that advocates for meeting human needs within planetary boundaries by altering lifestyles, societal norms, and regulatory frameworks. Sufficiency initiatives find themselves in a precarious position against a backdrop of growth-oriented urban development and face barriers such as lack of resources, legal and regulatory challenges, measurement difficulties, and inertia of municipalities. However, the study also identifies examples of fruitful cooperation between municipalities and initiatives and identifies enablers for successful collaboration, including aligned goals, engaged individuals, and effective communication. By providing an outlook for short-, mid-, and long-term governance perspectives, this article argues for strategic niche management in the short term, development of metrics for sufficiency in the medium term, and a systemic shift in urban dynamics in the long term. As urban sufficiency initiatives offer services and infrastructure to promote sustainable living, they are critical players in guiding cities towards ecological and social resilience. This article contributes to the discourse on urban sustainability by highlighting the importance of municipalities in nurturing sufficiency initiatives that can drive social well-being and environmental stewardship.

Uncovering the Dynamic Drivers of Floods Through Interpretable Deep Learning

AbstractThe formation of floods, as a complex physical process, exhibits dynamic changes in its driving factors over time and space under climate change. Due to the black‐box nature of deep learning, its use alone does not enhance understanding of hydrological processes. The challenge lies in employing deep learning to uncover new knowledge on flood formation mechanism. This study proposes an interpretable framework for deep learning flood modeling that employs interpretability techniques to elucidate the inner workings of a peak‐sensitive Informer, revealing the dynamic response of floods to driving factors in 482 watersheds across the United States. Accurate simulation is a prerequisite for interpretability techniques to provide reliable information. The study reveals that comparing the Informer with Transformer and LSTM, the former showed superior performance in peak flood simulation (Nash‐Sutcliffe Efficiency over 0.6 in 70% of watersheds). By interpreting Informer's decision‐making process, three primary flood‐inducing patterns were identified: Precipitation, excess soil water, and snowmelt. The controlling effect of dominant factors is regional, and their impact on floods in time steps shows significant differences, challenging the traditional understanding that variables closer to the timing of flood event occurrence have a greater impact. Over 40% of watersheds exhibited shifts in dominant driving factors between 1981 and 2020, with precipitation‐dominated watersheds undergoing more significant changes, corroborating climate change responses. Additionally, the study unveils the interplay and dynamic shifts among variables. These findings suggest that interpretable deep learning, through reverse deduction, transforms data‐driven models from merely fitting nonlinear relationships to effective tools for enhancing understanding of hydrological characteristics.

Quantitative Detection of Refrigerant Charge Faults in Multi-unit Air Conditioning Systems Based on Machine Learning Algorithms: Détection quantitative des défauts de charge de réfrigérant dans les systèmes de climatisation multi-unités basée sur des algorithmes d'apprentissage automatique

Refrigerant charging discrepancies constitute the predominant malfunctions in air conditioning systems. Achieving the optimal charging level is crucial for system performance, underscoring the importance of precise refrigerant level prediction. This study introduces an algorithm designed for the quantitative detection of refrigerant charging errors by integrating the Markov Transition Field (MTF), Convolutional Neural Networks (CNN), and Multi-head Self-Attention (MSA) mechanisms. A high-precision enthalpy difference chamber was employed to establish a Variable Refrigerant Flow (VRF) refrigerant charging test bench. This setup facilitated the analysis of system parameter sensitivity to charging faults and aided in the creation of a training dataset for the algorithm. Comparative analysis was conducted against Support Vector Machines (SVM), Random Forests (RF), CNN with Self-Attention (AT), and MTF-CNN-MSA. The findings reveal that our method adeptly captures temporal dependencies and dynamic shifts in time series as visual representations, offering novel insights for discerning fault patterns within such data. Notably, the maximum pressure variations at high-pressure and low-pressure points were 0.25 MPa and 0.07 MPa, respectively, with temperature shifts of 12°C and 3.5°C at the high and low-temperature points. The high-pressure and high-temperature points are particularly sensitive to changes in refrigerant charging, and parameters from these sections were utilized to construct the dataset. The CNN-MSA algorithm demonstrates consistent performance across various fault types, effectively delineating fault characteristics. The accuracies achieved by SVM, RF, CNN-AT, and MTF-CNN-MSA were 84.38%, 73.75%, 88.13%, and 93.75%, respectively. In comparison, the CNN-MSA algorithm was able to more accurately detect refrigerant charge faults at different levels.

Structural build-up of 3D printed earth by drying

In recent years, the potential of earth materials in construction has emerged as a sustainable pathway, offering environmental benefits compared to traditional methods. When used in raw form, earth materials can be recycled at the end of a building life, reducing construction waste. In parallel, integrating additive manufacturing into the architecture, engineering, and construction (AEC) sector has brought about a shift in construction dynamics, combining efficiency with precision. This paper bridges the study of 3D printing with earth-based fresh mortars, emphasising the capabilities of the “Forced Layer Drying” (FLD) technique in the additive manufacturing process to increase the mechanical performance of the printing mortar.This paper begins by defining the requisite rheological properties for successful 3D printing. A chosen material for this paper is speswhite kaolin. An instrumental aspect of our research is exploring an established model for the drying rate of saturated porous media, such as earth and concrete, and its application to predict the evaporation rate of saturated earth-based mortar in 3D printing with forced drying conditions. The Wind-Tunnel experiment was conducted to validate this model, examining the interplay of airflow speed and temperature on the evaporation rate. Further deepening this study, the soil water content and undrained shear strength are correlated, specifically based on models derived from oedometer geotechnical standard tests. This facilitated a comprehensive understanding of porous earth-based materials in various moisture scenarios. Our findings confirm that airflow, temperature, and the geometry of the printed object play instrumental roles in affecting evaporation rate, consequent mechanical performance, and structural build-up of the material. The paper wraps up by offering insights into the practical application of 3D printing using earth-based mortars, with a special focus on FLD technique.

Vertical Distribution of Rocky Intertidal Organisms Shifts With Sea-Level Variability on the Northeast Pacific Coast.

Disentangling the effects of cyclical variability in environmental forcing and long-term climate change on natural communities is a major challenge for ecologists, managers, and policy makers across ecosystems. Here we examined whether the vertical distribution of rocky intertidal taxa has shifted with sea-level variability occurring at multiple temporal scales and/or long-term anthropogenic sea-level rise (SLR). Because of the distinct zonation characteristic of intertidal communities, any shift in tidal dynamics or average sea level is expected to have large impacts on community structure and function. We found that across the Northeast Pacific Coast (NPC), sea level exhibits cyclical seasonal variability, tidal amplitude exhibits ecologically significant variability coherent with the 18.6-year periodicity of lunar declination, and long-term sea-level rise is occurring. Intertidal taxa largely do not exhibit significant vertical distribution shifts coherent with short-term (monthly to annual) sea-level variability but do exhibit taxa-specific vertical distribution shifts coherent with cyclical changes in lunar declination and long-term SLR at decadal timescales. Finally, our results show that responses to cyclical celestial mechanics and SLR vary among taxa, primarily according to their vertical distribution. Long-term SLR is occurring on ecologically relevant scales, but the confounding effects of cyclical celestial mechanics make interpreting shifts in zonation or community structure challenging. Such cyclical dynamics alternatingly amplify and dampen long-term SLR impacts and may modify the impacts of other global change related stressors, such as extreme heat waves and swell events, on intertidal organisms living at the edge of their physiological tolerances. As a result, intertidal communities will likely experience cyclical periods of environmental stress and concomitant nonlinear shifts in structure and function as long-term climate change continues. Our results demonstrate that consistent, large-scale monitoring of marine ecosystems is critical for understanding natural variability in communities and documenting long-term change.

Sea Ice Dynamics and Planktonic Adaptations: A Study of Terra Nova Bay’s Mesozooplanktonic Community during the Austral Summer

Phytoplankton and zooplanktonic communities form the base of the Antarctic food web. This study examines the evolution of the mesozooplanktonic system in Terra Nova Bay during the austral summer (December–February), focusing on the impact of sea ice dynamics and the resulting phytoplankton blooms. Terra Nova Bay (Ross Sea) offers a valuable context given its high productivity and ecological variability. Using a diachronic approach, we analyzed data spanning twelve years to understand how the system’s structure and functionality change over time. A novel key metric, Days since Sea Ice Melting, was employed to track shifts in phytoplankton community development and trophic dynamics. The results indicate that the system enters the summer season increasing primary productivity and creating the support for the development of a more complex and organized system during the season. The phytoplankton bloom recorded during mid-season, coped by an increase in biomass, is followed by the establishment of a well-organized grazing system. A secondary phytoplankton bloom is observed towards the end of the summer, but it does not significantly affect mesozooplankton communities. Overall, this study highlights the dynamic nature of Terra Nova Bay’s mesozooplanktonic community and evaluates the influence of climate change on Antarctic marine ecosystems.

Organic Food Products - A study on Consumers Perspective in Udgir Town of Maharashtra

In the recent decade we have observed a trend of emerging concern among human beings on the planet earth towards ecology and environment. The increasing concern among humans about environment has led to the increasing demand and requirement for Eco-friendly Organic Food products in the Indian market. As awareness of environmental issues and health concerns rises, consumers increasingly seek sustainable food options that align with their values. This study examines key factors influencing consumer choices, including perceived health benefits, environmental impact, and the importance of ethical sourcing. Through survey, insights are gathered on consumer knowledge of organic certifications, pricing concerns, and the role of marketing in shaping perceptions Considering the environmental concerns this articles states that today the consumers are optimistic and have a positive attitude towards Organic Food products and consumers do prefer to buy such products even if they have to pay a premium for the same which is usually influenced by certain variables that include their perceptions about the benefits that Eco-friendly Organic Food organic food products provide, along with the societal norms and personal values moreover including their understanding towards environmental concerns. The study is concluded with certain suggestions that emphasizes on various methods to increase the consumer awareness towards Eco-friendly Organic Food products and based on sustainability encourage the Eco-friendly Food consumption pattern. The findings reveal a growing trend towards prioritizing eco-friendly products, suggesting a shift in market dynamics that could influence future agricultural practices and food production. Understanding these consumer attitudes is essential for producers and retailers aiming to meet the demand for sustainable food options and to promote a healthier planet.