Changes In Conditions Research Articles

Fault Detection Technology for Ultrapure Water Plant using Virtual Sensors for Pressure Control Valve and Indicators in Return Line

Objectives:This study aims to propose a technology that utilizes virtual sensors to quickly and accurately diagnose faults in valves and measurement devices that may occur in the return line of an ultrapure water plant.Methods:The empirical equations were derived, and the error range was calculated using operational data collected from three pieces of equipment (pressure control valve, pressure transmitter, and flow transmitter) in the recovery system of the ultrapure water process. Based on this, a virtual sensor is established.Results and Discussion:It was confirmed that the utilization of 24-hour data collected from the operation of the ultrapure water plant was enough to establish virtual sensors and could also estimate monthly data with high accuracy. In Phase 1, the fault diagnosis technology was found to estimate values more accurately and had a meaningful margin of error compared to Phase 2.Conclusion:It was possible to develop a fault detection technology using the virtual sensor derived from the empirical equation. The technology showed high performance in detecting anomalies in the flow meter and pressure control valve opening but had limitations in estimating consistently pressure values. Additionally, considering that there was no issue in estimating monthly data using the equations derived using 24 hours operational data. The fault detection algorithm could be used continuously if the empirical equations are updated by collecting a day's data when operating conditions change.

Analysis of natural and man-made factors of landslide development in the Carpathian region using GIS

Purpose. Determination of the dependencies of spatial relationships between landslides in the Carpathian region of Ukraine and the factors causing them, taking into account the differences in geomorphological, geological, climatic conditions and natural and geographical zoning according to the landscape principle. Methodology. The morphometric analysis of the territory was carried out using QGIS tools to determine the slope angles and exposure; linear characteristics were calculated: distances to the river, road, and houses. Based on the image interpretation data, we calculated the total annual rainfall and average annual air temperature. The impact of the factors considered on landslide formation was assessed using multivariate statistical analysis: factor analysis and linear multiple regression. Findings. Studies on the impact of natural and topographical conditions and anthropogenic activity on the development of landslide processes have been conducted. Orographic and climatic factors play the most important role. Construction of business facilities results in a decrease in the slope stability in 14–19 % of cases. The analysed independed factors showed good consistency between the distribution of existing landslides and the parameters under consideration: the share of the total variance of the factors under consideration is 71–76 %, the coefficient of determination of the regression model is 0.7. Based on the results of geoinformation and statistical analyses, it is proved that differences in geomorphological conditions and human activity (construction of roads, economic facilities) are dominant in the formation of landslides in different landscape zones. Originality. It is established that there is a dynamic coherence between the spatial change in natural conditions and human settlement and activity, which interact with each other to create prerequisites for the development of landslides. Practical value. This study is important from the point of view of understanding and mitigating the cause-and-effect relationship of landslide development for certain territories, and the results obtained can be useful in developing land use planning strategies, infrastructure development, and planning new construction works.

Challenges of high-fidelity air quality modeling in urban environments – PALM sensitivity study during stable conditions

Abstract. Urban air quality is an important part of human well-being, and its detailed and precise modeling is important for efficient urban planning. In this study the potential sources of errors in large eddy simulation (LES) runs of the PALM model in stable conditions for a high-traffic residential area in Prague, Czech Republic, with a focus on street canyon ventilation, are investigated. The evaluation of the PALM model simulations against observations obtained during a dedicated campaign revealed unrealistically high concentrations of modeled air pollutants for a short period during a winter inversion episode. To identify potential reasons, the sensitivities of the model to changes in meteorological boundary conditions and adjustments of model parameters were tested. The model adaptations included adding the anthropogenic heat from cars, setting a bottom limit of the subgrid-scale turbulent kinetic energy (TKE), adjusting the profiles of parameters of the synthetic turbulence generator in PALM, and limiting the model time step. The study confirmed the crucial role of the correct meteorological boundary conditions for realistic air quality modeling during stable conditions. Besides this, the studied adjustments of the model parameters proved to have a significant impact in these stable conditions, resulting in a decrease in concentration overestimation in the range 30 %–66 % while exhibiting a negligible influence on model results during the rest of the episode. This suggested that the inclusion or improvement of these processes in PALM is desirable despite their negligible impact in most other conditions. Moreover, the time step limitation test revealed numerical inaccuracies caused by discretization errors which occurred during such extremely stable conditions.

Comparative Study on the Application Efficacy of Small Disturbance Equation versus One-Dimensional Euler Equation in Nozzle Flow Analysis

This paper presents a numerical simulation study of subsonic and supersonic nozzle flow regimes utilizing the Small Disturbance Equation (SDE), implemented through Python to analyze flow stability under various boundary conditions. The SDE, extensively applied in aerospace, meteorology, and fluid mechanics, offers a critical framework for examining aircraft stability and maneuverability, essential for ensuring flight safety. Additionally, its application extends to spacecraft stability and control in aerospace science. The findings from this study reveal that subsonic flows, characterized by their stability and smoothness, respond more predictably under varying boundary conditions compared to their supersonic counterparts. Conversely, supersonic flows demonstrate increased sensitivity to changes in boundary conditions, resulting in more complex flow patterns. This sensitivity underscores the need for precise control mechanisms in supersonic applications to maintain flow stability and ensure the safety and efficiency of aerospace operations. The simulations underscore the practical importance of the SDE in advancing the understanding of dynamic flow problems across different scientific and engineering disciplines.

Rethinking the four-wing problem in plesiosaur swimming using bio-inspired decentralized control

A locomotor system that can function across different environmental conditions and produce a range of performances is one of the most critical abilities needed for extant and extinct animals in order to survive and maximise their competitive fitness. Recent engineering-inspired paleontological studies have reconstructed feasible locomotor patterns in extinct animals. However, it is still challenging to describe how extinct animals successfully adjust their locomotor patterns to new situations (e.g., changes in locomotor speed and morphology). In this study, we develop a novel reconstruction method based on a bio-inspired control system. We focus on plesiosaurs, an extinct aquatic reptile group which has two pairs of flipper-shaped limbs, and demonstrate that a highly optimised, flexible locomotor pattern for all four flippers can be reconstructed based on a decentralized control scheme formulated from extant animals’ locomotion. The results of our robotic experiments show that a simple, local sensory feedback mechanism allows the plesiosaur-like robot to exploit the fluid flow between the flippers and generate efficient swimming patterns in response to changes in locomotor conditions. Our new method provides further evidence how decentralized control systems can produce a pathway between extinct and extant animals in order to understand the how extinct animals moved and how these movement patterns may have evolved.

Improved prognosis prediction of idiopathic pulmonary arterial hypertension using targeted plasma proteomics in disease management

Abstract Background Idiopathic pulmonary arterial hypertension (IPAH), a special subgroup of PAH with unclear etiology, is characterized by rapid progression and poor prognosis underscoring the need for optimization of IPAH management and the accurate prediction of prognosis. However, it is disappointing that specific plasma biomarkers for IPAH management and prognosis are lacking in clinical practice. Up to date, the plasma biomarkers used for assessment of IPAH severity and prognosis are relied solely on indicators such as N-terminal prohormone of brain natriuretic peptide, or brain natriuretic peptide, which could reflect cardiac function but fail to promptly response to the dynamic change of disease condition due to the complexity of IPAH pathogenesis. Purpose We evaluated the prognostic value of plasma proteins in addition to current clinical predictors for prognosis prediction of IPAH. Methods Olink Immune-Response panel was used to measure 92 plasma proteins in a prospective IPAH cohort with 169 patients and a mean follow-up period of 2.4 ± 0.9 years. Six machine learning methods were used to construct predictive models, including plasma proteins-based Olink models, clinical parameters-based clinical models, and integrative models. Results A total of 18 proteins showed differential expression between patients with or without adverse clinical outcomes. Three proteins (STC1, CXADR, and IL6) were strongly correlated with clinical indicators of IPAH severity and their concentrations showed upward trends along with increased risk stratification. Elevated levels of STC1, CXADR, and IL6 are all associated with an increased risk of adverse clinical events, indicated by survival analysis, restricted cubic splines, and multivariable Cox regression analysis (STC1 HR=3.474, 95%CI: 1.129-10.692, P=0.030; CXADR: HR=1.602, 95%CI: 1.074-2.387, P=0.021; IL6: HR=1.883, 95%CI: 1.376-2.576, P<0.001). The inclusion of these three proteins into the predictive model could significantly increase the predictive power on the basis of the clinical model (AUC: 0.746 vs 0.626). Conclusions High levels of STC1, CXADR, and IL6 in plasma were associated with severe clinical phenotype and increased risk of adverse clinical events in patients with IPAH. These plasma proteins could significantly improve the prognostic performance of pre-existing clinical models, facilitating the clinical management of IPAH patients.The predictive efficient of models

Effective RV ejection fraction by CMR: a new index of RV function in patients with severe TR

Abstract Background Right ventricle (RV) dysfunction represent an formal indication for intervention in patients with significant tricuspid regurgitation (TR). RV ejection fraction (RVEF) by Cardiac Magnetic Resonance (CMR) is considered the gold standard of RV function; however it is influenced by changes of preload conditions and may remain unaffected until late stages in severe TR. Effective RV ejection fraction (eRVEF) is corrected by the amount of TR and may reflect an earlier parameter of RV dysfunction. Purpose To compare the prognostic impact of both indices of RV function: RVEF and eRVEF in a multicentre cohort of patients with severe TR. Methods Patients with at least severe TR assessed by 2D echocardiography with a contemporary cardiac magnetic resonance (CMR) study were included in this study. In addition to conventional parameters of biventricular volume and function, eRVEF was assessed in all patients. eRVEF was calculated according to the formula: eRVEF=net pulmonary forwardflow/RV− EDV (figure). A combined endpoint of hospital admission due to right heart failure and cardiovascular mortality was defined. Results 271 patients with severe TR recruited from 5 tertiary care hospitals were included in this study (age 71 ± 11 years, 67% female, 83% NYHA I or II). Regarding the etiology, 10% were primary TR, 1% CIED-related TR, 46 % atrial secondary TR and 43% ventricular secondary TR. After a median follow-up of 27 months (IQR: 10-53 months), 41% of the patients (n=112) experienced the combined endpoint (n=97 were admitted due to HF, n=49 died). After adjusting for age, NYHA class, comorbidities, type of TR and LVEF in multivariate Cox proportional models, both RVEF and eRVEF were independently associated with all-cause mortality and heart failure (adj HR for RVEF HR per 1%=0.96 [0.94-0.98], p<0.001 and for eRVEF per 1%=0.98 [0.96-0.99], p<0.001). A value of eRVEF of ≤37% were associated with impaired prognosis (figure). eRVEF identified higher rates of RV dysfunction compared to RVEF (49% vs 38%, p<0.001). eRVEF was superior to RVEF to predict outcomes (higher AUC 0.70 [0.63-0.76] vs 0.66 [0.59-0.73, p<0.001; Δ C-statistic 0.139 [0.040-0.237], p=0.05). Conclusion RV function is crucial for determining optimal timing for TR intervention. eRVEF is corrected by the amount of TR and identify higher rates of RV dysfunction in severe TR. eRVEF held stronger association with outcome compared to RVEF.eRVEF calculationKaplan Meier Curves

Body mass index change and risk of poor oral health in Norwegian adults: the HUNT longitudinal study

Abstract Background Oral diseases and obesity share common risk factors and are highly prevalent. However, the relationships between body mass index (BMI), BMI change and oral health conditions in adults are less studied. In this study, we investigate the associations of long-term obesity and BMI change with risk of poor self-rated oral health among adults. Methods This study include individuals aged 29-90 years (57.8 % women, mean age at baseline, HUNT3, was 54.9 years) who participated in the first (HUNT1, 1984-86), second (HUNT2, 1995-97), third (HUNT3, 2006-08) and fourth (HUNT4, 2017-19) survey of the Trondelag Health Study (HUNT). Weight and height were measured at each survey. We estimated average BMI values and BMI change over a 10-year (HUNT2- HUNT3, N = 19,729) and 20-year (HUNT1- HUNT3, N = 14,276) period and linked to their information on oral health status at HUNT4. We employed logistic regression models with adjustment for confounders and computed odds ratio (OR) with 95 % Confidence Interval (CI). Results At HUNT4, 1812 (9.2 %) participants rated their oral health as poor or very poor. The multivariable-adjusted ORs for average BMI over 30 kg/m2 were 1.3 (95 % CI: 1.1-1.5) and 1.2 (95 % CI: 1.0-1.5) over a 10-year and 20-year period, respectively, when compared to normal weight. After adjustment for most recent BMI (HUNT4), the associations of long-term obesity with poor self-rated oral health weakened. Compared with stable BMI, both loss and gain in BMI over a 10-year period were associated with increased risk of poor oral health. In the adjusted analysis, we found that a BMI loss of more than 2.5 kg/m2 and a BMI gain of more than 5 kg/m2 was associated with 1.5 times (OR = 1.5, 95 % CI: 1.1-1.9) and 1.3 times (OR = 1.3, 95 % CI: 1.1-1.6) greater risk of poor oral health. Conclusions Our findings suggest that individuals with long-term obesity and BMI change have a markedly higher risk of poor self-rated oral health. Key messages • Long-term obesity was associated with increased risk of poor self-rated oral health. • Compared with stable body mass index (BMI), loss- and gain in BMI were associated with increased risk of poor self-rated oral health.

How synchronized human networks escape local minima

Finding the global minimum in complex networks while avoiding local minima is challenging in many types of networks. In human networks and communities, adapting and finding new stable states amid changing conditions due to conflicts, climate changes, or disasters, is crucial. We studied the dynamics of complex networks of violin players and observed that such human networks have different methods to avoid local minima than other non-human networks. Humans can change the coupling strength between them or change their tempo. This leads to different dynamics than other networks and makes human networks more robust and better resilient against perturbations. We observed high-order vortex states, oscillation death, and amplitude death, due to the unique dynamics of the network. This research may have implications in politics, economics, pandemic control, decision-making, and predicting the dynamics of networks with artificial intelligence.

Projected 21st Century Drought Condition in the South Saskatchewan River Watershed: A Case Study in the Canadian Prairies

In this study, a CMIP6 ensemble of 26 GCMs and SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios from CanDCS-U6 is used to project drought conditions in the South Saskatchewan River Watershed. The near-current period (2015–2030) and two future periods (2041–2060 and 2071–2100) are analyzed based on the Standardized Precipitation Evapotranspiration Index (SPEI) at 1-, 3-, 6-, 12-, and 24-month timescales. Projections indicate a shift in average SPEI values from above zero (no drought) in the base period (1951–1990) to more negative values in the future. Results show an increase in drought severity and frequency under climate change conditions. The percentage of time with no drought conditions is projected to decline from 55–70% in the base period to 25–45% by 2071–2100. Severe and extreme droughts, rare in the base period (below 4%), are projected to increase to up to 19% by 2071–2100. The area experiencing drought is expected to expand from 36–49% (for different SPEI timescales) in the base period to up to 76% by 2071–2100. Drought frequency is projected to be higher under SSP1-2.6 and less frequent under SSP2-4.5. Results showed that longer SPEI timescales are associated with higher drought occurrence rates and severity. The spatial pattern of drought is also projected to significantly change, with higher frequencies expected in the eastern parts of the watershed under climate change.

The pivotal role of positive emotions in maintaining nurses’ trust and preventing pandemic fatigue

Abstract Background Nursing is a challenging profession that demands quick adaptation to changing conditions. The COVID-19 pandemic has placed unprecedented pressure on nursing teams, leading to high-stress levels and uncertainty. This study examines how nurses’ emotional response at the start of the pandemic predicts their trust in the healthcare system and pandemic fatigue after three morbidity waves. Methods This study included collecting self-reported data among Israeli nurses in three time periods: 346 nurses during March-May 2020 (T1), 260 nurses during June-July 2020 (T2), and 91 nurses during February 2022 (T3). Change in the study variables was assessed using repeated-measure ANOVA. Two multiple linear regression models were calculated for trust and pandemic fatigue at T3, with the emotions at T1 and professional seniority as predictors. Results A significant increase in negative emotions was observed between T1 and T2 (M = 2.65, SD = 1.12 and M = 3.20, SD = 1.29 respectively). Furthermore, there was a significant decrease in trust levels between T1 and T3 (M = 4.68, SD = 1.14 and M = 4.07, SD = 1.08 respectively). The regression model for trust was significant, with 20% of the variance explained in it, revealing that higher positive emotions at T1 predicted higher trust at T3. Similarly, the regression model for pandemic fatigue was significant (R2=22%), showing that lower professional seniority and lower positive emotions at T1 were predictors of higher pandemic fatigue at T3. Conclusions During a crisis, nurses may experience intense negative emotions like fear and anxiety. However, positive emotions, such as pride and a sense of mission, are crucial in maintaining their trust and preventing the onset of pandemic fatigue. Healthcare organizations should promote emotional support and provide emotional resources so that nurses can continue to deliver high-quality care even during challenging times. Key messages • During times of crisis, it’s crucial to foster positivity and encourage a sense of pride and accomplishment in nursing staff. • Healthcare organizations must provide emotional support to nursing teams in routine and crisis situations to prevent burnout and maintain trust and long-term functioning.

How do working conditions change for in-person versus digital work? The case of schoolteachers

Abstract Background Telework has significantly increased in Europe and internationally in the aftermath of COVID-19 lockdowns, with estimates of 22% of Europeans now doing some form of telework. However, it is unclear how working conditions for the same job differ when work is conducted in-person versus digitally, and if occupational health risks can be considered as equal across formats. Our study addressed the profession of school teaching to examine online working conditions versus those for in-person teaching. Methods To allow for close consideration of employment contexts, a qualitative study was conducted. Focus groups and interviews took place in 2023-24 with 45 teachers and tutors who teach from kindergarten to secondary grades across Canada. Results We found that online teaching added to emotional labour of teaching work and involved new occupational exposures. These included challenges with engaging students via cameras and microphones, digital surveillance of teachers by parents and students, unwanted exposure to students’ intimate home lives, and technostress. Conclusions The work of being an online teacher was very different than teaching in-person, yet there has been slow recognition of working condition differences for understanding of OHS exposures and for collective agreements. Key messages • In the context of a significant expansion of telework, assumptions cannot be made that the job conditions and exposures are the same job when performed in-person or at-home. • These differences will need to be recognized in job agreements and occupational risk assessments.

Lockdown and Unrest: Inequality, Restrictions and Protests During COVID-19

This paper analyses how pre-pandemic levels of inequality across US counties have shaped the impact of the COVID-19 pandemic on the incidence of protests. The results from difference-in-differences and instrumental variable models using high-frequency weekly data show that more stringent measures to contain the pandemic increased the incidence of protests, but only in US counties with high levels of inequality before the start of the pandemic where grievances may have been initially stronger. The impact of government responses to COVID-19 on protests is largely explained by adverse changes in economic conditions in counties with the highest levels of pre-pandemic inequality. Policy stringency measures were also associated with more protests in the most unequal counties which voted for the Republican party in the 2016 elections and exhibited, at the start of the pandemic, lower levels of trust in the president and lower satisfaction with democracy.

Lessons from long‐term research: Diptera species turnover and dominance shifts with respect to climate‐driven changes

Abstract The diverse pressures of climate change have influenced many habitats, especially freshwater ones, due to their greater sensitivity to stressors. Aquatic Diptera make up more than 50% off all aquatic insect species described, which makes them an ideal group to monitor changing climate as their diverse assemblages can reflect functions within the entire community. The aim of this research was to identify variations in the aquatic dipteran community during a 15‐year period at a tufa barrier in a karst barrage lake system and to determine the environmental factors that have the highest influence on this community. We analysed monthly data collected between 2007 and 2021, when we collected adult specimens using 6 pyramid‐type emergence traps. In total, 167 taxa from 13 different families were gathered. NMDS based on Bray–Curtis similarity analysis amongst assemblages revealed the segregation of samples based on different current velocities and substrates, indicating the importance of microhabitats in dipteran community structuring. Dipteran taxa indicative of specific 5‐year time periods within the research were identified and were associated with changes in environmental conditions especially discharge. The threshold indicator taxa analysis revealed specific species' responses to changing discharge rates. The study shows that discharge rate, not water temperature, is the critical factor shaping dipteran composition, whether by removing or adding taxa to the community. Species turnover showed an overall decrease in species numbers, that is, species richness, throughout the research period. We conclude that changes in the dipteran community, because of the vast functional traits, niches, adaptations and species diversity of the group, are not visible when analysing just the diversity indices. When determining environmental influence on the community in long‐term research, they should be combined with other data such as the overall abundance, the total number of species, as well as the species turnover.

'It Made Me Change the Way I Do Business': Outcomes from Age-Friendly Community Initiatives as Systems Change.

Since the early 2000s, a global age-friendly communities (AFC) movement has called for improving the built, social, and service environments of localities for aging. Yet research on the outcomes of AFC initiatives, as programmatic efforts toward AFC progress, remains in its nascence. Drawing on "The Water of Systems Change" framework, our study aimed to address this gap by exploring the extent to which accomplishments of AFC initiatives are indicative of altering six conditions for systems change: policies, organizational practices, resource allocations, power dynamics, relationships, and mental models. We analyzed qualitative data from 26 key informant interviews across eight mature AFC initiatives in the northeastern United States. We engaged in iterative phases of thematic analysis to explore how the initiatives' accomplishments, as described by the participants, align with each of six focal conditions for systems change. We found especially robust and consistent evidence for outcomes in terms of enhanced organizational practices on aging; resource flows; connections within and across communities; and mental models about older adults. Evidence for outcomes concerning changes in power dynamics and policy was more limited. Conceptualizing AFC initiatives as systems-change interventions can bolster research, evaluation, and program development as the movement proliferates and diversifies into the 21st century. Insights can help to advance praxis that empowers AFC leaders as changemakers for "successful aging" at the level of society.

In-situ biosynthesis of metallic nanoparticles using Allium sativum and Chondrilla juncea extract: characterization and application in dye decolorization

The synthesis of catalysts has gained specific concern due to their versatile applications in particular azo dye decolorization. In the current work, metallic nanoparticles (copper and silver) were In-situ biosynthesised using Allium sativum and Chondrilla juncea extract. The obtained Allium-copper oxide and Allium-silver oxide materials were analyzed using SEM, TEM, FT-IR, TGA-DTG, SEM, TEM, and XRD techniques. Allium peels had a rough surface, with nanoparticles equally distributed over it. The crystal structure of Allium peels was altered after the addition of CuO and AgO nanoparticles. The highest residual mass values in the prepared materials indicated that the metallic nanoparticles were, in situ, formed. The prepared materials had worse thermal stability than Allium peel powders. The azo dyes, Calmagite and Naphthol Blue Black B were tested in the catalytic power of the resulting materials. The decolorization process was affected by the dye structure, amount of H2O2, dye concentration, time of reaction, and temperature of the bath. The activation energy values for Allium-CuO were 18.44 kJ mol−1 for calmagite, and 23.28 kJ mol−1 for naphthol blue black, respectively. Nevertheless, the energy values for Allium-AgO were 50.01 kJ mol−1 for calmagite and 12.44 kJ mol−1 for Naphthol blue black. The calculated low energy values for the prepared materials suggested the high efficiency of the use of these catalysts in azo dye decolorization under the change of some main experimental conditions.

Machine learning-based assessment of regional-scale variation of landslide susceptibility in central Vietnam.

Recurrent landslide events triggered by typhoons and tropical storms over Vietnam pose a longstanding threat to the nation's population and infrastructure. Changes in hydroclimatic conditions, especially the growing intensity and frequency of storms, have elevated landslide susceptibility in many parts of the country. This research examines the spatio-temporal variations in landslide susceptibility across central Vietnam over several years, using multi-temporal landslide inventories from Typhoon Ketsana (2009), Tropical Storm Podul (2013), and Typhoon Molave (2020). Additionally, the research explores the impact of individual landslide causative factors on the probabilistic occurrences of landslides. The post-event landslide susceptibility models of these three climate extreme events were developed using nine causative factors and a Random Forest machine learning algorithm. The results indicate a notable areal expansion of high to very high landslide susceptibility in the northern and eastern regions and a moderate reduction in the central and southern areas during the post-Molave period compared to the post-Ketsana period. These changes may be early indicators of increasing landslide susceptibility in response to changing hydro-climatic conditions. The research found that annual average rainfall and topographic elevation are the two most important variables influencing landslide prediction, showing a nonlinear relationship with landslide probability. The landslide susceptibility models achieved high Area Under the Receiver Operating Characteristic Curve (AUC) (>95%), accuracy (>89%), and sensitivity (>90%) scores, signifying the robustness of the models. Additionally, the uncertainty of the models was quantified and spatially mapped. This multi-temporal analysis of landslide susceptibility is crucial for understanding the regional susceptibility trends and identifying areas with increasing, decreasing, and consistently high susceptibility to landslides. These insights are invaluable for prioritizing mitigation and risk reduction strategies in landslide-prone regions and guiding appropriate land use planning.

The Impact and Challenges of Digital Transformation on Supply Chain Resilience in Physical Enterprises

Abstract: In the digital era, supply chain resilience (SCR) has become a key pillar of the real economy. Enterprises face various challenges, including cybersecurity threats, market volatility, technological change and changing global conditions. A strong SCR not only ensures continued business operations but also maintains market stability and consumer well-being. Digital transformation helps businesses anticipate market changes, optimize inventory management, improve operational efficiency, and assist in management decisions when necessary by providing unprecedented data transparency and real-time insights. The purpose of this paper is to examine the extent of digital transformation in the supply chains of physical firms globally through a literature review, to identify the factors influencing the resilience of digital transformation in the supply chains of physical firms, and to discover the barriers to digital transformation in the supply chains of physical firms. The study finds that the digital transformation of physical firms' supply chains is still in its infancy, and there are barriers at both managerial and physical levels. Solutions to address these barriers include enhancing employee training, correctly introducing appropriate digital technologies, and improving information security.

Chronic heat stress upregulates pyruvate metabolic process and gluconeogenesis but downregulates immune responses in Sahiwal cattle.

Climate change and growing population and their strain on animal production are the impending challenges that the developing countries, like India, need to tackle in the coming days. This study aimed to detect and analyze the uncharacterized variation in the gene expression patterns with the change of condition, from thermoneutral to chronic hot-humid, in the Sahiwal cattle, one of the best breeds of milk-producing cattle in India, known for being heat-tolerant. Using RNA-Seq analysis on peripheral blood mononuclear cells (PBMCs), 4021 differentially expressed mRNAs (2772 upregulated, 1249 downregulated) and 1303 differentially expressed long non-coding RNAs (769 upregulated, 534 downregulated) were identified, with the thresholds of false discovery rate < 0.05 and|log2(fold change)| > 2. Significantly (p-adjusted < 0.05) overrepresented Gene Ontology (GO) terms, Kyoto Encyclopedia of Genes and Genomes (KEGG), and Reactome pathways were analyzed, revealing upregulation of processes like pyruvate metabolic process, gluconeogenesis, ion transmembrane transport, neuropeptide signaling pathway, and animal organ development, with genes like SHH, GRK1, CHRM3, CAMK2A, and HSPB7 were upregulated, while translation and immune responses, with genes like RPS3, EEF1A1, TNF, BoLA-DRB3, and UBB were downregulated. Analysis of cis-mRNAs of DE-lncRNAs showed presence of both up- and down-regulated cis-mRNAs for both up- and down-regulated lncRNAs indicating existence of positive and negative regulation of mRNA expression by lncRNAs. Managemental nudges that decrease metabolic heat generation, like betaine and chromium supplementation, and increase heat dissipation, like microenvironment cooling, should be utilized. This study highlights the role of pyruvate metabolism and gluconeogenesis in coping up with heat stress and offers an improved understanding of the heat stress response of Sahiwal cattle along with the genes and pathways responsible for it.

DEVELOPMENT OF SEISMIC METHODS FOR MONITORING THE GEOMECHANICAL CONDITION OF THE SAYANO-SHUSHENSKAYA HPP

Records obtained at seismological stations contain information not only about earthquakes, explosions, but also from various other sources of seismic waves. The sources of such waves can be various buildings and structures that vibrate with their own frequencies. Seismologists can understand the registered wave field, identify the waves from these sources and characterize them. It is possible to implement seismic methods of remote control over changes in the technical condition of various objects. Contemporary hydraulic structures were built a long time ago and aging processes in them lead to destruction of materials and formation of cracks, so these objects require continuous monitoring of their condition. The aim of this work is to investigate the possibility of determining the occurrence of cracks in the body of the dam of the Sayano-Shushenskaya hydroelectric power plant by analyzing its natural frequencies depending on the filling and drawdown of the reservoir. For this purpose, we placed a seismic station several kilometers away from the object of study. With the help of this station, as well as with the help of the seismological data obtained at the seismic station “Cheremushki”, located 4.5 km from the HPP, for 20 years, works were carried out to study the possibility of determining the natural frequencies of the dam with high accuracy when they change in time. The possibility of controlling the physical parameters of structures and operation of various units of the HPP for a long period of time was demonstrated. Examples of determination of frequencies of high- and low-quality signals are considered.