Management Decisions Research Articles

Quality and reliability of short Chinese videos related to acute pancreatitis on TikTok and Bilibili

Background Acute pancreatitis (AP) is becoming a growing public health problem worldwide, with an increasing incidence year by year. Social media platforms such as TikTok and Bilibili are becoming increasingly popular, and they can be a source of information on AP. However, the quality of information in these videos remains unknown. Objective The objective of this study is to assess the information quality of Chinese AP short videos shared on TikTok and Bilibili short video platforms. Methods In April 2024, we conducted an assessment of the information quality and reliability of Chinese AP short videos (200 videos in total) from TikTok and Bilibili. This assessment was conducted using the JAMA, GQS, and DISCERN tools. Additionally, we explored the factors affecting video quality. Results Compared to Bilibili short videos, TikTok short videos are shorter in length but have more thumbs up, comments, favorites and shares, indicating that they are more popular. The quality of TikTok's and Bilibili's AP shorts is not as good as it could be, with Tiktok shorts being even worse, with median GQS scores of 1 and 2, median DISCERN scores of 34 and 42, and median JAMA scores of 2 and 1, respectively. Video duration is positively correlated with video quality, while thumbs up, comments, favorites and shares are negatively correlated with video quality. Conclusions The study demonstrated that short videos containing AP-related health information on Bilibili and TikTok were of poor quality, and that videos uploaded by healthcare professionals did not exhibit a significant advantage in terms of quality and reliability. Consequently, short videos providing healthcare information on TikTok and Bilibili must be meticulously evaluated for their scientific soundness before making healthcare management decisions. Overall, videos uploaded by healthcare professionals were of higher quality than those uploaded by others, but there was no significant difference in DISCERN scores.

The economic burden of asthma in Italy: evaluating the potential impact of different treatments in adult patients with severe eosinophilic asthma.

Asthma is a prevalent chronic respiratory condition that significantly impacts public health, with severe asthma subtypes, such as severe eosinophilic asthma, imposing substantial socioeconomic burdens. Real-world data from the Italian Health Information System were analyzed to evaluate the economic consequences of asthma in Italy. An in-depth comparative analysis was conducted to investigate the economic implications of various asthma subtypes, focusing on severe eosinophilic asthma. Additionally, the study projected the potential cost-effectiveness of novel treatments aimed at reducing hospitalization rates, specialist visits, and oral corticosteroid use for patients with severe eosinophilic asthma in Italy. The analysis revealed that severe asthma, and notably severe eosinophilic asthma, places a substantial economic burden on the Italian National Health System. Estimates demonstrated that implementing innovative treatments to mitigate the risks of hospitalization and specialist visits, as well as reducing oral corticosteroid usage in severe eosinophilic asthma patients, could lead to significant cost savings. The cost-consequence analysis indicated potential yearly reductions of €50.0 million (27%) for the treatment of severe asthma and €31.7 million (26%) for severe eosinophilic asthma. This study presents a comprehensive evaluation of the economic repercussions of severe asthma in Italy. The findings emphasize the necessity of identifying and developing effective therapeutic strategies to improve the management of severe asthma while simultaneously reducing the economic burden on the healthcare system. These results offer valuable insights for healthcare policymakers and practitioners, facilitating evidence-based decisions in asthma management and healthcare policy in Italy.

Beyond neuropsychological tests: AI speech analysis in PKU.

Phenylketonuria (PKU) is a rare inherited metabolic disorder characterized by toxic phenylalanine (Phe) concentrations in blood and brain. State-of-the-art analyses of speech detected a dimension of verbal discourse providing insights that extend beyond those captured by existing paradigms to measure performance associated with biochemical markers in PKU. The Cookie Theft Picture Task provided a standardized stimulus for eliciting spontaneous speech from 42 adults with PKU and 41 adults without PKU. Subtests measuring language and memory from the Wechsler Adult Intelligence Scale-Fourth Edition showed no differences between the groups and no correlations with biomarkers in PKU. In contrast, AI analyses of responses to the Cookie Theft Task revealed significant differences between the PKU and non-PKU groups on 23 linguistic features. Using multidimensional scaling (MDS), these features were aggregated into a single quantifiable Dimension 1 that significantly correlated with biomarkers. When extreme examples of Dimension 1 were presented to chatGPT, the differences noted reflected attention to detail, clarity in word choice, expression cohesion, contextual awareness and emotion recognition. We subsequently defined Dimension 1 as Proficiency in Verbal Discourse. This novel measure elucidated discourse styles possibly associated with suboptimal achievement and learning disabilities, often reported in PKU. In summary, AI captured a characteristic associated with metabolic status undetectable through traditional neuropsychological measures. Future studies will expand upon this novel paradigm, leveraging speech AI to quantify meaningful aspects of everyday functioning and possibly provide information for management decisions. Once validated, this measure holds promise for extension to other rare diseases and incorporation into clinical trials.

Методика анализа исполнения бюджета энергосбытовой компании в комбинированных моделях аддитивно-мультипликативного типа

The article presents a methodology developed by the authors for analyzing the budget execution of the power supply company utilizing combined additive-multiplicative models. The relevance of this methodology is underscored by the need for organizations to enhance the effectiveness of management decisions through such analytical frameworks. The novelty of this work lies in the adaptation of classical deterministic analysis models to the specific context of power supply companies, taking into account the peculiarities of their financial and economic activities. A plan-fact analysis of the budget execution of the power supply company was conducted using the chain substitution method, which was implemented across all types of deterministic factor models: additive, multiplicative, multiple, and mixed (combined). This analytical approach enabled the determination of the impact of individual factors on the variation of the performance indicator by gradually substituting the baseline value of each factor indicator within the performance measure with the actual value for the reporting period. The authors conclude that the proposed methodology facilitates the analysis of changes in the performance indicator (marginal profit) attributable to factors of the I, II, III levels. It is applied in practice for the formulation of managerial reporting and the adjustment of the marketing policy of the power supply company operating at the territory of Saint Petersburg.

Predicting nursing workload in digestive wards based on machine learning: A prospective study

BackgroundThe process of assessing and allocating nursing staff, as well as evaluating performance, relies heavily on nursing workload, which is strongly associated with patient safety outcomes. Nevertheless, most previous studies have utilized cross-sectional data collection methods, which limit the precision of workload prediction. Static workload models do not incorporate longitudinal changes in influential factors, potentially resulting in delayed or erroneous nursing management decisions and ultimately causing imbalances in nurses’ workload.AimTo employ machine learning algorithms to facilitate the dynamic prediction of nursing workload on the basis of patient characteristics.MethodsThis prospective cohort quantitative study was conducted between March 2019 and August 2021 in two general hospitals located in China. Data on the characteristics of 133 patients over the course of 1339 hospital days, as well as direct nursing time, were collected. A longitudinal investigation of nursing workload was carried out, applying multiple linear regression to identify measurable factors that significantly impact nursing workload. Additionally, machine learning methods were applied to dynamically predict the nursing time needed for each patient.ResultsThe mean direct nursing workload varied greatly across hospitalizations. Significant factors contributing to increased care needs included complications, comorbidities, body mass index (BMI), income, history of past illness, simple clinical score (SCS), and activities of daily living (ADL). The predictive performance improved through machine learning, with the random forest model demonstrated the best performance (root mean square error (RMSE): 1148.38; coefficient of determination (R2): 0.74; mean square error (MSE): 1318744.64).ConclusionsThe variability in nursing workload during hospitalization is influenced primarily by patient self-care capacity, complications, and comorbidities. The random forest algorithm, a machine learning algorithm, effectively handles a wide range of features, such as patient characteristics, complications, comorbidities, and other factors. This algorithm has demonstrated good performance in predicting workload.Implications for nursing managementThis study introduces a quantitative model designed to evaluate nursing workload throughout the duration of hospitalization. By employing the model, nursing managers can consider multiple factors that impact workload comprehensively, resulting in enhanced comprehension and interpretation of workload variations. Through the application of a random forest algorithm for workload prediction, nursing managers can anticipate and estimate workload in a proactive and precise manner, thereby facilitating more efficient human resource planning.

Wildfire management decisions outweigh mechanical treatment as the keystone to forest landscape adaptation

BackgroundModern land management faces unprecedented uncertainty regarding future climates, novel disturbance regimes, and unanticipated ecological feedbacks. Mitigating this uncertainty requires a cohesive landscape management strategy that utilizes multiple methods to optimize benefits while hedging risks amidst uncertain futures. We used a process-based landscape simulation model (LANDIS-II) to forecast forest management, growth, climate effects, and future wildfire dynamics, and we distilled results using a decision support tool allowing us to examine tradeoffs between alternative management strategies. We developed plausible future management scenarios based on factorial combinations of restoration-oriented thinning prescriptions, prescribed fire, and wildland fire use. Results were assessed continuously for a 100-year simulation period, which provided a unique assessment of tradeoffs and benefits among seven primary topics representing social, ecological, and economic aspects of resilience.ResultsProjected climatic changes had a substantial impact on modeled wildfire activity. In the Wildfire Only scenario (no treatments, but including active wildfire and climate change), we observed an upwards inflection point in area burned around mid-century (2060) that had detrimental impacts on total landscape carbon storage. While simulated mechanical treatments (~ 3% area per year) reduced the incidence of high-severity fire, it did not eliminate this inflection completely. Scenarios involving wildland fire use resulted in greater reductions in high-severity fire and a more linear trend in cumulative area burned. Mechanical treatments were beneficial for subtopics under the economic topic given their positive financial return on investment, while wildland fire use scenarios were better for ecological subtopics, primarily due to a greater reduction in high-severity fire. Benefits among the social subtopics were mixed, reflecting the inevitability of tradeoffs in landscapes that we rely on for diverse and countervailing ecosystem services.ConclusionsThis study provides evidence that optimal future scenarios will involve a mix of active and passive management strategies, allowing different management tactics to coexist within and among ownerships classes. Our results also emphasize the importance of wildfire management decisions as central to building more robust and resilient future landscapes.

Invasion stress mitigates climate stress in a brackish marsh amphipod

Abstract Organisms in coastal brackish ecosystems face not only highly variable environmental conditions, but the intensity and stochasticity of these environmental conditions are anticipated to increase due to climate change. While environmental changes are often presented unilaterally as stressors, there are some anthropogenic environmental transformations, such as the introduction of habitat forming plant species, that may mitigate physiological stress imposed by warming. In Suisun Marsh in the California Delta, native plant canopies allow light and heat to penetrate to the understory yet the canopies of the introduced Phragmites australis reed block out sunlight and heat for organisms living below. We set out to understand the physiological performance of mud‐dwelling invertebrates in this context: can invasion stress mitigate climate stress? We raised field collected Gammarus amphipods in the laboratory under simulated ‘native canopy’ and ‘Phragmites canopy’ temperature/light conditions based on data from our field environmental loggers. We assessed survival, body mass, fecundity, glycogen and protein content every 2 weeks from our lab population of amphipods. We found that amphipods raised under the Phragmites conditions had better survival, greater stores of protein, and similar body mass and stores of glycogen, which could positively impact available food resource quality for juvenile fishes. We support this with field data showing higher use of Phragmites canopies by amphipods, especially in the water column, across the year of sampling. Synthesis and applications: Understanding the potential benefits of Phragmites as climate stress refugia can inform management decisions around its mitigation in future restoration.

Targeted thoracic ultrasonography shows high diagnostic potential for interstitial pneumonia in feedyard cattle.

To use a novel approach of targeted thoracic point-of-care ultrasound (TT-POCUS) of the caudodorsal right lung to determine potential associations between TT-POCUS measurements and the presence of interstitial pneumonia (IP) in feedyard cattle. Cross-sectional study evaluated feedyard animals (n = 62; 358.4 ± 10.5 kg; heifer, n = 38; steer, n = 24) using TT-POCUS at time of respiratory disease treatment and microscopic assessment of lesions at subsequent mortality. Evaluations took place from July through December 2023. Pulmonary samples were collected at necropsy for histopathologic assessment, and lesions were used to diagnose IP or non-IP. Statistical models determined potential associations between IP, cattle demographic, and TT-POCUS measured variables. Evaluations of animals enrolled (n = 62) displayed significant associations with IP, including ultrasound lung score (ULS), B-line count, A-line count, and days on feed at treatment. Cattle with a ULS of 5 had the lowest probability of IP (0.12 ± 0.16) compared to cattle with a ULS of 2, 3, or 4 (0.72 ± 0.18, 0.93 ± 0.06, and 0.85 ± 0.08, respectively). Cattle with B-line counts > 5 had a higher probability of IP (0.86 ± 0.11) compared to cattle with 3 to 5 B-lines (0.38 ± 0.14). The probability of IP was higher in cattle with A-line counts < 3 (0.83 ± 0.10) compared to cattle with ≥ 3 A-lines (0.51 ± 0.15). Strategic targeted thoracic ultrasonography has potential a value of timely IP diagnosis in feedyard cattle, thereby offering important insights into therapeutic and management decisions. Targeted thoracic ultrasonography can be utilized as a method for IP diagnosis in feedyard cattle.

Land Use Conflicts Identification and Multi‐Scenario Simulation in Mountain Cities, Southwest China: A Coupled Structural and Functional Perspective

ABSTRACTLand use conflicts (LUCs) arise during land use change, causing an uncoordinated spatial structure of the land and negatively affecting the synergistic development of multifunctionality, especially in mountain cities. Previous studies have focused on identifying and measuring land use structural conflicts (LUSC), with less attention paid to land use functional conflicts (LUFC), and a lack of simulation for future multi‐scenarios. Thus, taking Chongqing as an example, based on the perspective of LUSC–LUFC coupling, this study constructed a comprehensive conflict index to identify and assess LUCs, then applied the PLUS model to predict LUCs under three development scenarios in 2030. This study found that (1) there was a significant positive spatial association between LUSC and LUFC, with high–high agglomeration types in areas of severe LUCs and low–low agglomeration types in areas of light LUCs. (2) During 2000–2020, the LUCs in Chongqing displayed a trend of upward and then downward from 2000 to 2020, with significant agglomeration in their spatial pattern. (3) Two typical areas of LUCs intensification were identified, namely the topographic transition zone located in the Daba and Wuling mountains and the urban–rural interface in the Chongqing metropolitan area. (4) In 2030, the LUCs in Chongqing manifest an overall mitigation in the ecological protection (EP) scenario, while displaying an intensification in the natural development (ND) and economic development (ED) scenarios. Based on the types of spatial interaction between LUSC and LUFC, land use optimization strategies were formulated. The findings will provide scientific references for sustainable land use management decisions in Chongqing and other mountainous cities.

The physics of citation growth

ABSTRACT Purpose This study investigates the physics of annual fractional citation growth and its impact on journal bibliographic metrics, focusing on the interplay between journal publication growth and citation dynamics. Design/methodology/approach We analyze bibliometric data from three prominent fluids journals—Physics of Fluids, Journal of Fluid Mechanics, and Physical Review Fluids—over the period 1999–2023. The analysis examines the relations among annual fractional journal publication growth, citation growth, and bibliographic metric suppressions. Findings Our findings reveal that the suppression of impact factor growth is significantly influenced by annual fractional journal publication growth rather than citation growth. All three journals exhibit similar responses to publication growth with minimal scatter, following a consistent functional relation. We also identify narrow, nearly Gaussian distributions for annual fractional journal publication growth. Furthermore, we introduce a new growth-independent dimensionless bibliometric metric, journal urgency, the ratio of annual fractional citation growth to the 4-year running average immediacy index. This metric captures effectively the dependency of citation growth on urgency and reveals consistent distributions across the journals analyzed. Research limitations The study is limited to three major fluids journals and to the availability of bibliometric data from 1999 to 2023. Future work could extend the analysis to other disciplines and journals. Practical implications Understanding the relation between publication growth and bibliometric suppressions can inform editorial and strategic decisions in journal management. The proposed journal urgency metric offers a novel tool for assessing and comparing journal performance independent of growth rates. Originality/value This study introduces a new bibliometric metric—journal urgency—that provides fresh insights into citation dynamics and bibliographic metric behavior. It highlights the critical role of publication growth in shaping journal impact factors and CiteScores, offering a unified framework applicable across multiple journals.

Explainable Machine Learning to Map the Impact of Weather and Soil on Wheat Yield and Revenue Across the Eastern Australian Grain Belt

Understanding the causes of spatiotemporal variation in crop yields across large areas is important in closing yield gaps and producing more food for the growing global population. While there has been much focus on using data-driven models to predict crop yield, there is also an opportunity to use these empirical models to understand which factors are driving variations in yield and to quantify their contributions. This study uses a large database of 625 rainfed wheat yield maps from 14 different seasons (2007–2020) across the eastern grain belt of Australia. XGBoost models were used, with predictors including maps of soil attributes (e.g., pH and sodicity), along with weather indices (rainfall, frost, heat, growing degree days). The model and predictors could accurately predict field-scale yield, with a Lin’s concordance correlation coefficient (LCCC) of 0.78 with 10-fold cross-validation. SHapley Additive exPlanation (SHAP), a form of interpretive machine learning (IML), values were then used to assess the impact of the variables on yield. The SHAP values for each predictor were also mapped onto a grid of the study area for the 2020 season, which showed the impact of each predictor on wheat yield (t ha−1) and revenue (AUD ($) ha−1) in interpretable units. Weather variables, such as rainfall and heat events, had the largest impact on yield. Although generally less significant, soil constraints such as soil sodicity were still important in driving yield. The results also showed that despite their largely temporally stable nature, soil constraints impact yield differently, depending on seasonal conditions. Overall, data-driven models and IML proved valuable in understanding the impact of important weather and soil variables on wheat yield and revenue across the eastern Australian grain belt. This could be used to determine the magnitude and economic impact of soil constraints and extreme weather on crops across regions and to inform policies and farm management decisions.

Both Structural Variant and Single Nucleotide Polymorphism Load Impact Lifetime Fitness in a Threatened Bird Species.

The field of conservation genomics is becoming increasingly interested in whether, and how, structural variant (SV) genotype information can be leveraged in the management of threatened species. The functional consequences of SVs are more complex than for single nucleotide polymorphisms (SNPs), as SVs typically impact a larger proportion of the genome due to their size and thus may be more likely to contribute to load. While the impacts of SV-specific genetic load may be less consequential for large populations, the interplay between weakened selection and stochastic processes means that smaller populations, such as those of the threatened Aotearoa hihi/New Zealand stitchbird (Notiomystis cincta), may harbour a high SV load. Hihi were once confined to a single remnant population, but have been reestablished into six sanctuaries and reserves, often via secondary bottlenecks, resulting in low genetic diversity, low adaptive potential, and inbreeding depression. In this study, we use whole genome resequencing of 30 individuals from the Tiritiri Matangi population to identify the nature and distribution of both SNPs and SVs within this small avian population. We find that SNP and SV individual mutation load is only moderately correlated, likely because SVs arise in regions of high recombination and that are less evolutionarily conserved. Finally, we leverage a long-term monitoring dataset of pedigree and fitness data to assess the impact of SNP and SV mutation loads on individual fitness, and find that SNP and SV realised load had similar negative correlations with lifetime fitness. However, of the masked load metrics, only SVs had a positive significant correlation with lifetime fitness, indicating that masking of deleterious alleles may be more important for SVs than for SNPs. The results of this study indicate that only examining SNPs neglects important aspects of intra-specific variation and that studying SVs has direct implications for linking genetic diversity and genomic health to inform management decisions.

Mapping Windthrow Severity as Change in Canopy Cover in a Temperate Eucalypt Forest

Storm events are significant disturbance agents that can cause considerable forest damage through windthrow. Assessment and mapping of the extent and severity of windthrow is critical to provide reliable information to forest managers to prioritize post-storm hazard reduction (including public safety and fire risk) and to guide restoration activities. Detailed on-ground assessments after windthrow are often impossible due to lack of access and safety concerns. In 2021, severe windstorms caused unprecedented and extensive windthrow in a temperate eucalypt forest in south-eastern Australia. The purpose of this study is to quantify the severity and extent of the damaged forest area as the change in percentage canopy cover using remotely sensed data. We assessed percentage canopy cover from high-resolution aerial images of 455 randomly selected plots in disturbed and undisturbed areas to train a model and machine learning framework to predict landscape scale canopy cover from Sentinel-2 images. A random forest model using all single bands and percentiles best predicted the canopy cover (R2 = 0.69). Sentinel-2 images were then used to predict canopy cover pre- and post-windthrow to assess and map the severity of windthrow as the change in percentage canopy cover. Of the total 63,471 ha of forest area assessed, 63% (39,987 ha) was impacted by windthrow, with 46% at low severity (&lt;30% canopy cover loss), 11% at moderate (30–50% canopy cover loss) and 6% at high severity (&gt;50% canopy cover loss). Our study provides the first quantitative mapping of windthrow severity mapping for a temperate eucalypt forest in Australia that demonstrates an effective remote assessment methodology and provides critical information to support post-windthrow management decisions.

Clinical Decision-Making and Process Complications During Anticipated Difficult Airway Management for Elective Surgery.

Difficult airway management (DAM) is a challenging aspect of anesthetic care. Although nearly all DAM episodes result in successful intubation, complications are common and clinical decision-making may be complex. In adults with anticipated DAM scheduled for nonemergent surgery, we prospectively observed clinical decisions made during DAM such as awake/sedated versus anesthetized, choice of initial and subsequent devices, case cancellation/postponement, conversions between awake and anesthetized approaches, and process complications such as multiple intubation/supraglottic airway (SGA) insertion attempts, difficult bag-mask ventilation (BMV), hypoxemia, and cardiovascular destabilization. From 2009 to 2014, we prospectively observed 1295 episodes of anticipated DAM in a convenience sample of 1245 adults scheduled for nonemergent surgery. Trained observers recorded airway management decisions and process complications during DAM. We described clinical decisions made during DAM and outcomes including number of attempts, need for BMV, hypoxemia, and cardiovascular destabilization. No cases were canceled/postponed for airway management failure and all intubations were eventually successful. Of the 1295 episodes of airway management in our study cohort, 166 (13%) were intubated awake. Patients intubated awake had more difficult airway indicators than those intubated anesthetized, their first-pass success rate was 49%, 30% required ≥3 attempts, 4% required a device change, 50% experienced hypoxemia, and 29% experienced cardiovascular destabilization. Among the 1129 patients intubated while anesthetized, first-pass success rate was 64% and 20% required ≥3 attempts, 11% required a device change, hypoxemia occurred in 30%, and cardiovascular destabilization in 20%. One patient (0.08%) was converted from an anesthetized to an awake approach. Patients with a failed anesthetized intubation attempt and difficult BMV between attempts were at high risk for multiple attempts (67%) and hypoxemia (100%). Airway management was successful in all patients and the incidence of process complications was higher than in routine airway management. Despite a high risk of DAM, 87% of patients were intubated anesthetized and conversions between awake and anesthetized approaches were rare. That patients intubated awake had more difficult airway indicators implies that clinicians reserve awake intubation for particularly difficult airways. The high incidence of multiple attempts, hypoxemia, and cardiovascular destabilization in patients intubated awake suggests that awake airway management remains challenging. We found no clear pattern in device choices after a first failed attempt. Patients with a first failed anesthetized intubation attempt and difficult BMV were at particularly high risk for hypoxemia.

Study of the effectiveness of the criteria used to evaluate the work of specialists of a pharmaceutical company in an unfavorable epidemiological situation (using the example of the sales department)

Introduction. During the coronavirus pandemic, due to the current situation in the pharmaceutical sector of the economy, specialists from a number of departments of pharmaceutical companies were forced to switch completely or partially to remote work. This transformation has necessitated the need to adapt the employee performance assessment systems that have developed in organizations, including revising the list of indicators and criteria. However, to date there are no unified scientifically based methods for assessing the labor efficiency of specialists, based on the selection and measurement of criteria that take into account the characteristics of both the external and internal environment of the organizational structures of pharmaceutical organizations, including those forced to work in unfavorable epidemiological conditions. The proposed methodological approach based on the use of Key Performance Indicators (KPI) will allow the management of a pharmaceutical company to create a more balanced and flexible assessment system that stimulates both individual achievements and teamwork, as well as to form an intelligent analytical basis for making management decisions that bring the company closer to its organizational goals. The purpose of the study is to analyze the effectiveness of the employee performance assessment system that has developed in a pharmaceutical company and to justify the effectiveness of using KPIs in an unfavorable epidemiological situation (using the example of the sales department). Material and methods. The evaluation study is based on primary data from reports of pharmaceutical companies and data from a survey of 20 sales employees in pharmaceutical companies using a developed questionnaire. Results. A system for evaluating the work of employees in the sales department of a pharmaceutical company based on KPIs is proposed using three table layouts that allow ratings to be translated into a 10-point scale out of 100 possible. The assessment is carried out according to two main criteria: 1) achievement of sales volume and 2) implementation of the plan for the target product, taking into account the quality of the employee’s work, confirmed by his immediate supervisor. This approach will create a more balanced and flexible assessment system in the organization, stimulating both individual achievements and teamwork. Conclusion. As part of the study, proposals were developed for the development of KPIs for the criteria for assessing the work of specialists of a pharmaceutical company in an unfavorable epidemiological situation.

Model of selecting an optimal management decision for restoration of fixed assets of oil producing enterprises

Subject. The article explores the problem of oil refineries modernization. Objectives. The study aims at analyzing the options for organization of works on restoration of fixed assets of oil producing enterprises and devising an algorithm for cost optimization. Methods. The study employs methods of complex and comparative analysis. Results. We developed an economic and mathematical model enabling to choose the optimal management decision for the restoration of fixed assets of oil producing enterprises, taking into account geographical and technological factors. Conclusions. The findings may be taken into account when devising development programs for strategically important enterprises in conditions of economic uncertainty.

THE PUBLIC ADMINISTRATION OF INFORMATION TECHNOLOGIES IN HEALTH CARE FIELD UNDER THE CONDITIONS OF MARTIAL STATE

In the conditions of martial state, the need for fast and accurate processing of large volumes of information, especially in the field of health care, is increasing. This is due to a lack of resources, an increase in the number of victims of military operations, displaced persons, the complication of access to medical services in connection with hostilities, the loss of individual specialists and information arrays, as well as increased risks for information security and the entire process of public management of information technologies in the health care field. The public administration of information technologies in health care is becoming critical to ensure the stability of healthcare services, support communications between healthcare facilities and government agencies, and effectively process and protect healthcare data. The analysis of scientific works on the issue of the public administration of information technologies in health care under the conditions of martial state is insufficiently researched. The article highlights the main challenges of the industry related to the war: ensuring the continuity of medical services, the appropriateness of public administration decision-making in conditions of limited access to open information, problems with logistics, and stable power supply, information protection and cyber security, shortage of qualified personnel; adopted management decisions, and information technology tools, which were used by authorities at the state and regional levels to respond to new challenges, were investigated. In the article, we are offered some recommendations for the further development and management of information technologies in the healthcare field. The main ones are further measures to strengthen cybersecurity, namely the widespread implementation of the Digital Competency Framework for Healthcare Workers in various areas, the implementation of modern information protection systems, the implementation of an information security policy, measures to legalize and update software, deepening the integration of mHealth into the existing eHealth system to enable rapid and remote collection of medical information and the introduction of artificial intelligence elements into healthcare management processes.

Literasi Keuangan dalam Meningkatkan Minat Investasi pada Generasi Milenial di Pulau Bawean

This research aims to analyze the influence of financial literacy, financial inclusion and lifestyle on the investment interest of the millennial generation on Bawean Island. The millennial generation in this region, numbering 18,095 people, has great potential to increase economic growth through investment. However, the level of financial literacy and understanding regarding financial inclusion among them is still low. The research used a quantitative method with a survey approach, involving 100 respondents selected using a simple random sampling technique. Data collection was carried out through questionnaires, and data analysis used multiple linear regression. The research results show that financial literacy, financial inclusion and lifestyle significantly influence investment interest. Financial literacy provides a deep understanding of risk management and investment decision making, while financial inclusion increases access to financial services. Lifestyle also plays an important role in encouraging more productive investment behavior. This research contributes to efforts to develop policies that support increasing financial literacy and inclusion to encourage wider investment participation among the millennial generation, especially in the Bawean Island area.

Prospects for the development of the communication system and the equipment of special purpose with the regulation of the implementation of measures LTE

Further development of the communication system of the Armed Forces of Ukraine is impossible without the recovery of advanced combat experience and the step-by-step implementation of current communication systems (complexes, equipment) for the highest task to face the Defense Forces of Ukraine. Therefore, the key is not only the selection of new information technologies and current standards in the field of communication, but also the investigation of their implementation in the minds of combatants (as close as possible to the combative ones) of action. Experience in carrying out tasks in the east of Ukraine, especially during offensive (counter-offensive) operations, clearly identifying the problems of securing communications in territories not prepared for communications, as well as in areas where telecommunications infrastructure is completely or partially destroyed. The purpose of this article is to outline the prospects for the development of the communication system and the equipment of special purpose with the understanding of not only theoretical research in radio communications, but also the results of practical research into the effectiveness of system-technical solution based by installed on the local radio station with mobile communication standards 3G and 4G. Based on the results of the research, conclusions and proposals were formed regarding the prospects for further development of the system, including the use of LTE in the communication system of the Armed Forces of Ukraine. The stated propositions are based on the results of the final experience of the assigned possession in the interests of the security of military units (subdivisions) in the Sumy region of Ukraine, as well as on the combat line the focus on the offensive (counter-offensive) actions of the Defense Forces of Ukraine in the east of our State. The presentation material of the article is relevant and necessary for training during the research, aimed at improving the forms and methods of combat stagnation of communication equipment (units), tying the decision to choose necessary communication equipment, as well as the formation of management decisions by military administration bodies to organize (secure) connections in future operations with the release of the immediate occupation of the territories of Ukraine.

Integrated response of crop yields and greenhouse gas emissions to cropland management practices and natural factors: A global meta-analysis

Abstract The effects of cropland management on yield and greenhouse gas (GHG) emissions vary among crops, and comprehensive and quantitative analyses of relevant factors are needed to make informed management decisions. The study assessed the response of global crop yields and GHG to cropland management and natural factors (including mean annual temperature (MAT), mean annual rainfall (MAP), soil pH (SPH), soil C N ratio (SCN), soil organic matter (SOC), crop type, biochar (application rate Brate, biochar feedstock Feedstock, C N ratio BCN, biochar pH BPH, biochar organic matter BTC), irrigation, N fertilizer (Nrate), tillage, straw management, plastic film mulch, duration of experiment, economic development, geographic location (state, country)) involving 167 papers from 17 crops in 27 countries, with a total of 1249 pairs of observations by using meta-analysis. The results showed that biochar application throughout the year improved crop yields, reduced GHG and was more suitable for use on C4 crops. The contribution of straw return to CH4 and CO2 was 78.3% and 35.6%, respectively. The effect of intermittent irrigation on the yield of C4 crop was 25.7% higher than that of C3 crop. The optimal nitrogen utilization rates for wheat and corn were 253.20 kg·N·hm-2 and 239.84 kg·N·hm-2, respectively, and N fertilizer was more effective in reducing GHG of C3 crops. Among the 20 influencing factors, the relative impact of annual rainfall was the most significant, accounting for 69.3% of N2O and 40.39% of CO2 emissions, respectively. SCN had the most obvious impact on CH4、GWP and Greenhouse Gas Intensity (GHGI), reaching up to 51.45%、35.98% and 43.46%, This study quantitatively assessed the response of different types of crop yields and GHG emissions to cropland management practices and natural factors, and provided a basis for making management decisions to enhance global crop yields and reduce GHG.