Information For Management Research Articles

Повышение эффективности деятельности предприятия в условиях цифровой экономики России

The development of industrial enterprises requires new approaches to management and adaptation to modern trends. The rapid development and dissemination of digital technologies have a profound impact on the land-scape of production processes and the business models employed. The priority task of any modern enterprise is to identify and reduce losses, as this is the basis for successful activity. The “Lean Manufacturing” system effectively addresses this task, as its objective also lies in improving the efficiency of enterprise activities. The developed methodology of “strengthening the competitiveness of the enterprise by increasing the profitability of the project of pre-production and release of automotive components” allows at the stage of technological design not only to obtain information for quality management of the automotive component, but also to prevent potential losses, that is, to increase the profitability of the project. Thus, the use of digital technologies is of great importance for improving the efficiency of enterprises, their competitiveness and profitability. This becomes a prerequisite for their successful work in the modern world.

Advancing aquifer vulnerability mapping through integrated deep learning approaches

Groundwater vulnerability maps are crucial for safeguarding groundwater quality. A research gap exists in using advanced data fusion techniques to identify areas subject to seawater intrusion. To address this gap, this research enhances the GALDIT method and applies diverse deep learning models, combined with machine learning techniques, to improve the precision of aquifer vulnerability mapping. The new GALDITMW model incorporates the seawater mixing index and the parameters related to the production well density and aquifer porous medium. For the first time, supervised and unsupervised deep learning models, such as deep neural networks, deep belief networks, deep stacked autoencoders, and convolutional neural networks, are used for vulnerability mapping. In the second stage, the results of various machine learning models are fused to improve performance. The models' effectiveness is evaluated using a vulnerability index based on total dissolved solids (TDS) in an aquifer hydraulically connected with Salt Lake in central Iran, which faces groundwater depletion and salinization. The evaluation of the models based on performance metrics and the confusion matrix demonstrates that initial deep-learning models perform well. Significant improvements were observed in the second stage involving machine learning models, confirming their strong correlation (R2 > 0.985) with observed chloride values. The GPR model achieved an F1 score of 86.92%, an NSE of 0.911, and an RMSE reduction of 0.026 mg/L compared to the first-stage models. The proposed method offers a novel and accurate method for identifying vulnerable areas and provides helpful information for groundwater resource management.

Longitudinal Investigation of Groundwater and Surface Water Interaction of Two Gravel Pit Lakes in Central Texas: Chemical and Flow Implications

Two gravel pit lakes in central Texas were examined over the course of two years with upgradient and downgradient piezometer installations. Groundwater and lake water were sampled bimonthly for nutrients, water levels, and groundwater chemistry, and in addition, rain and lake gauges and mini-piezometers were installed, depth surveys were conducted, and a simple 2D flow model was constructed. The project goal was evaluating and examining flow dynamics and chemical effects as groundwater flows to surface water and back to groundwater with the intent to understand the effects that gravel pit lake systems have on connected shallow groundwater. Both lake systems were shown to be flow-through systems that influence the water quality by decreasing the dissolved nutrients in the groundwater in their vicinity while oxygenating the water and altering the pH. However, the lakes are also prone to high levels of evaporation, meaning that minor improvements to water quality come at the cost of decreasing the quantity of water in storage within the aquifer. Similar groundwater and mine lake systems may show comparable tendencies, providing new information for water managers, regulators, and stake-holders about the potential roles that non-remediated gravel pit lakes may play in local ecosystems and aquifer dynamics.

Designing fit‐for‐purpose monitoring – A case study of a cryptic songbird

AbstractMonitoring threatened species is essential for understanding their conservation needs and developing effective recovery strategies. However, designing and implementing monitoring programs can be challenging in resource‐constrained environments, where conservation practitioners must balance the need for detailed information with limited resources. We present a case study focusing on the design of a range‐wide monitoring program for the Endangered rufous scrub‐bird (Atrichornis rufescens) in the mountain forests of eastern Australia. We first developed a ‘wish list’ of monitoring questions and then trialed the methods needed for answering them using sequence of pilot studies. We implemented a phased approach comprising (i) a study of whether individuals could be identified by their songs, (ii) identification of a ‘core range’ using species distribution models to refine the search area, and (iii) a trial of the efficacy of a preferred feasible monitoring approach. We offer a practical pathway for designing question‐driven monitoring programs for threatened species. Our study highlights the importance of clarifying explicit monitoring goals and tailoring methods to suit species' ecological and life history characteristics. By following this systematic approach, conservation efforts can obtain valuable information for effective management, even with limited resources and prevailing uncertainty about species ecology.

An evaluation rule to manage productivity properties performance of male date palms

ABSTRACT Male palm trees almost prominently display minute morphological variations; however, date palm growers rely on readily available pollen from unproven male genotypes without giving correct type selection any thought, which may result in low productivity and/or poor fruit quality. This study sought to develop an evaluation rule by calculating an evaluation index for managing the productivity characteristics performance of nine male date palms, which were examined for their pollen productivity, nutritional status and morphological traits from their leaves, pinnae and spathes. The findings showed that the evaluation rule for a male date palm should depend on pollen grains productivity and germination percentage traits with a weight of 5, spathe morphological traits with a weight of 4, pinnae morphological traits with a weight of 3, leaf morphological traits with a weight of 2 and leaf nutritional status with a weight of 1. The best productivity characteristics performance of male date palms was male No. 8 ‘M8’ due to its high evaluation index. The proposed evaluation index criterion will contribute to better information and analytical support for management of the date palm industry to maximise the effectiveness of germplasm conservation and exploitation, as well as procedural and methodological aspects of the analysis.

Assessing the efficacy of difficult airway alerts in electronic medical records: a quality improvement study

Study designRetrospective analysis of difficult airway alerts in a major tertiary centre.ObjectiveTo investigate the completeness, utility and efficacy of difficult airway alerts and their impact on future airway management episodes.Design, data sources and methodsPatients who had a “difficult airway” entry on electronic medical records (EMR) from 2011 to 2021 were included. Each alert was analyzed by a team of anesthetists with expertise in difficult airway management for its quality, appropriateness, and impact on future airway management episodes. Alert quality was defined as to whether the content of the alert contained pertinent information for emergent airway management. Alert appropriateness was defined as to whether the experts would be unhappy to perform a rapid sequence induction and intubation, if required, following review of all available documentation.Results141 patients were included for this study, with a mean age of 58.6 +/- 15.3 years. Ninety-three (66%) alerts were created by medical staff, of which 52 were recorded by consultant anesthetists. 117 alerts (83%) were deemed to be appropriate by the airway expert team, but only 40 alerts (28%) were found to have sufficient quality to be helpful in emergent airway management. Sixty-five patients (47%) had at least one subsequent airway management episode, of which 35 patients (56%) underwent a change of management following alert creation. We proceeded to modify 103 alerts (73%) to improve their quality to aid future encounters.ConclusionDifficult Airway encounters are an uncommon event in anesthesia, but clear, comprehensive and effectively communicated documentation is required to minimize the risk in future encounters. In our institution, while most difficult airway alerts were appropriate, we found significant heterogeneity in the quality of this documentation, which limits the clinical utility of the alert system. We have taken measures to improve local processes of difficult airway documentation and considered the implications of our project for the broader airway management community.Trial registrationNot applicable.

Quantitative study on the impact of perceived corporate social responsibility on employee performance at plant protection companies in the Mekong Delta, Vietnam

This article presents the results of a formal quantitative survey (Main Study or Official Survey) on the impact of Corporate Social Responsibility Awareness on Employee Performance at plant protection products manufacturing enterprises in the Mekong Delta, Vietnam. The objective is to examine the impact of Perceived Corporate Social Responsibility (PCSR) on employee performance (EP), with the mediating role of organizational trust (OT) and the moderating role of organizational reputation (OR). The Main Study with 385 samples, used SPSS and AMOS to test Cronbach's Alpha, EFA, CFA and SEM models. The results of the impact coefficients showed that PCSR positively affects EWR with OT as the mediator, and OR as the moderator of this relationship. The coefficients obtained prove that the research hypothesis is appropriate. The research results also provide useful information for managers to better understand the impact of PCSR on employee performance, thereby making appropriate strategic adjustments to business goals. Due to the limited space and sample size, this is a limitation of the study.

Utility of the Vestibular/Ocular Motor Screening in Military Medicine: A Systematic Review.

The Vestibular/Ocular Motor Screening (VOMS) was created as a brief clinical screening tool for identifying vestibular and ocular motor symptoms and impairments post-concussion. It was found to have predictive validity in correctly identifying concussed athletes from healthy controls. In 2018, the Military Acute Concussion Evaluation 2 (MACE2) replaced the original Military Acute Concussion Evaluation (MACE); the most prominent change between the MACE and MACE2 was the addition of the VOMS. Despite its adoption into military medicine, it is not known if the addition of the VOMS to the MACE2 is acutely helpful, and if it provides additional information for diagnosis, prognosis, and/or management. The purposes of this systematic review were: (1) to determine the utility of the VOMS in correctly identifying concussed individuals, particularly as it pertains to military medicine; (2) to explore the extent to which the VOMS can inform concussion prognosis; and (3) to establish the value of the VOMS as a measure for monitoring the evolution of symptoms throughout a service member's course of care. A comprehensive search of PubMed was performed from January 1, 2014 through August 16, 2023. Articles were included if they researched concussion or a related health condition or healthy controls and administered the VOMS. Articles were excluded if they discussed health conditions other than concussion; did not administer the VOMS; or were written in languages other than English. The tools used to assess methodological quality and risk of bias varied according to study design. Articles were classified into three primary domains: diagnosis, prognosis, and/or rehabilitation/recovery over time. A total of 231 articles were retrieved and 3 were duplicates, leaving 228 articles for review. Of the 228 articles screened, 100 relevant full-text articles were assessed for eligibility. Fifty-nine articles met our inclusion and exclusion criteria while the other 41 articles were rejected. Thirty-two articles helped to inform diagnosis, 15 prognosis, and 16 rehabilitation/recovery over time. The VOMS had excellent internal consistency and moderate to good test-retest reliability; however, a false-positive rate of 21.9% was found. Most studies indicated that a positive VOMS was associated with a delayed recovery. Several studies indicated that VOMS scores improved with targeted, active interventions and/or a symptom-guided progressive return to activity. The greatest limitation was the paucity of published evidence in the military population. More research is needed on the use of the VOMS in service members.

Inversion of biophysical parameters of potato based on an active learning pool-based sampling strategy

ABSTRACT Timely estimations of leaf chlorophyll content (LCC) and leaf area index (LAI) can provide critical information for potato field management. We employed a hybrid method that integrated machine learning with a radiative transfer model to estimate potato growth parameters. A look-up table was generated using the PROSAIL model, which was used as an unlabelled sample set. Measurements were taken from a potato field, and the data were labelled according to growth period and variety. Then, training samples for potato LCC, LAI, and canopy chlorophyll content (CCC) were selected from the simulated unlabelled sample set using the Euclidean distance-based diversity algorithm based on different labelled data sets. The training sample size required to accurately estimate the parameters varied considerably depending on the parameter, variety, and growth period, despite using the same labelled data set. Moreover, our results indicate that the growth period has a substantial impact on model accuracy and needs to be considered when constructing the labelled data set. The study results indicate that the hybrid method combined with the radiative transfer model and active learning can effectively select informative training samples from a data pool and improve the accuracy of potato parameter estimation, which provides a valid tool for accurately monitoring crop growth and growth health.

Deep Learning Empowered Water Quality Assessment: Leveraging IoT Sensor Data with LSTM Models and Interpretability Techniques

Addressing the imperative demand for accurate water quality assessment, this paper delves into the application of deep learning techniques, specifically leveraging IoT sensor datasets for the classification and prediction of water quality parameters. The utilization of LSTM (Long Short-Term Memory) models navigates the intricacies inherent in environmental data, emphasizing the balance between model accuracy and interpretability. This equilibrium is achieved through the deployment of interpretability methods such as LIME, SHAP, Anchor, and LORE. Additionally, the incorporation of advanced parameter optimization techniques focuses on fine-tuning essential parameters like learning rates, batch sizes, and epochs to optimize model performance. This comprehensive approach ensures not only precise predictions but also enhances the transparency and interpretability of the model, addressing the critical need for actionable information in water quality management. The research significantly contributes to the convergence of deep learning, IoT, and environmental science, offering valuable tools for informed decision-making while highlighting the importance of fine-tuning parameters for optimal model performance

Wind Power Plant Location Selection with Fuzzy Logic and Multi-Criteria Decision-Making Methods

This study aims to examine the effectiveness of the fuzzy multi-criteria decision-making methods, especially Fuzzy Weight by Envelope and Slope (F-WENSLO) and Fuzzy Ranking Alternatives with Weights of Criterion (F-RAWEC) for evaluating the potential locations for wind power plants. The study's objective is to provide a solid framework for deciding which locations are most suitable for wind energy projects, taking into account various criteria and expert opinion. The study includes the evaluation of five potential places including Gürün, Kangal, Divriği, Ulaş and Zara in Sivas province of Turkey. The evaluation criteria include wind speed and direction, altitude, land use, environmental impacts, infrastructure proximity, social acceptance, economic costs, security and risk factors, climatic conditions and legal and permit requirements. Scores from experts from various fields and weights of criteria were determined. The analysis revealed that Ulaş and Kangal got the highest point for the wind power plant installation. As Ulaş gets the highest point due to favorable wind conditions, favorable altitude and advantageous land use; Kangal stood out as a strong candidate because of its acceptable wind speed, positive social acceptance and low economic costs. The study highlights the importance of integrating multiple criteria and expert assessments in the decision-making process. The findings suggest that fuzzy multi-criteria decision-making methods can be effectively supportive of wind power plant site selection. The study provides valuable information for project managers and policy makers, emphasizing the importance of criteria such as security in the choice of location, legal requirements and social acceptance. Future research may expand these findings to examine the integration of additional criteria, alternative locations, and other multi-criteria decision-making techniques.

How African Ungulates Respond to Tourist Vehicles in Kruger National Park

ABSTRACTManagers of protected areas need to balance how they use or preserve their resources, especially regarding ‘road ecology’. This study focuses on Kruger National Park's (KNP) common ungulates’ response to tourist vehicles. We answered the following questions for impala, zebra, giraffe, blue wildebeest, greater kudu and steenbok: What mediates animal flight and flight distance from a vehicle? How much of KNP is affected by roads? Are ungulates using or avoiding roads? We sampled 55.9% of KNP's tourist roads, where we approached animals and determined whether and how far they fled. We georeferenced sightings and estimated the amount of land area along KNP's tourist roads where animals would be expected to flee from vehicles. Of 517 animal sightings, Impala were sighted most (263) and steenbok least (32). Impala had the highest flight propensity (42.6%) and wildebeest lowest (13%). Steenbok were found closest to the road (22.13 m) and wildebeest furthest (77.6 m). Impala had the closest tolerance distance (16.63 m), with zebra furthest (44.74 m). Impala fled the least distance (9.93 m) and zebra fled furthest (24.52 m). Binary logistic regressions (BLRs) showed that all species fled more consistently when closer to the road. The amount of KNP affected by animal flight based on BLRs was largest for zebra (2.32% of the park) and smallest for kudu (0.84%). Impala used the first 10 m of the roadside more than expected and 10–20 m from the road less. KNP's ungulates are habituated to vehicles since flight propensity was low, distribution analysis showed no‐road avoidance, flight distance was short, and animals > 50 m from the road generally do not flee. Given the amount of KNP that is already affected by vehicle traffic, as tourism increases, the land solely devoted to wildlife will necessarily decrease. This study aims to provide information for the best management of roads and traffic in KNP.

Integrated geochemical analysis of urban and peri-urban soils: a case study of Lamia City, Greece.

The occurrence of Potentially Toxic Elements (PTEs) and other chemical elements in urban and peri-urban soils impacts human health and quality of life, posing a challenge for geoscientists. This study investigated the soil geochemistry of Lamia City, focusing on identifying the geogenic and anthropogenic origins of elements. A total of 168 topsoil samples (0-10cm) were collected in April 2023, and the analysis included the near-total concentrations of 51 elements. Descriptive, correlation, multivariate statistics (i.e., Factor Analysis-FA and Hierarchical Cluster Analysis-HCA), Geographic Information Systems (GIS) mapping, and mineralogical analysis were employed to identify potential element sources. The results indicated that the elements in soils originated from geogenic, anthropogenic, and mixed sources. Geogenic origins are associated with ultramafic rocks (e.g., Mg, Cr, Ni, Co, Fe, Sc, Mn), carbonate rocks (e.g., Ca, Sr), and Quaternary sediments (e.g., K, Na, Ba, Tl, Be, Rb, Ti, V, Ga, and Rare Earth Elements-REEs); associations are linked to specific identified minerals. All applied statistical analyses reveal that the mobility of chemical elements in the urban and peri-urban soils of Lamia city is primarily affected by geochemical processes such as element substitution, chemical weathering, pedogenesis, adsorption, precipitation, evaporation, and organic matter presence. The P, Ag, Hg, Pb, Sn, Zn, Sb, Cd, Cu, and U were associated with anthropogenic influences, particularly in areas with high population density, heavy vehicle traffic, and intensive agricultural practices. Additionally, some elements (e.g., Ca, Cd, Cu, Mo, Mn, and Li) exhibited mixed origins. This integrated approach offers valuable insights into the spatial distribution and sources of PTEs in urban and peri-urban environments, providing critical information for environmental management and public health protection strategies.

Quantifying NO x Emission Sources in Houston, Texas Using Remote Sensing Aircraft Measurements and Source Apportionment Regression Models.

Air quality managers in areas exceeding air pollution standards are motivated to understand where there are further opportunities to reduce NO x emissions to improve ozone and PM2.5 air quality. In this project, we use a combination of aircraft remote sensing (i.e., GCAS), source apportionment models (i.e., CAMx), and regression models to investigate NO x emissions from individual source-sectors in Houston, TX. In prior work, GCAS column NO2 was shown to be close to the "truth" for validating column NO2 in model simulations. Column NO2 from CAMx was substantially low biased compared to Pandora (-20%) and GCAS measurements (-31%), suggesting an underestimate of local NO x emissions. We applied a flux divergence method to the GCAS and CAMx data to distinguish the linear shape of major highways and identify NO2 underestimates at highway locations. Using a multiple linear regression (MLR) model, we isolated on-road, railyard, and "other" NO x emissions as the likeliest cause of this low bias, and simultaneously identified a potential overestimate of shipping NO x emissions. Based on the MLR, we modified on-road and shipping NO x emissions in a new CAMx simulation and increased the background NO2, and better agreement was found with GCAS measurements: bias improved from -31% to -10% and r2 improved from 0.78 to 0.80. This study outlines how remote sensing data, including fine spatial information from newer geostationary instruments, can be used in concert with chemical transport models to provide actionable information for air quality managers to identify further opportunities to reduce NO x emissions.

Fusarium Species Shifts in Maize Grain as a Response to Climatic Changes in Poland

Maize, along with wheat and rice, is the most important crop for food security. Ear rots caused by Fusarium species are among the most important diseases of maize. The distribution of Fusarium species provides essential epidemiological information for disease management. The effect of weather conditions, climate change and geographic localization on the Fusarium population in Poland was evaluated between 2015 and 2018. Grain samples (n = 233) were collected from hybrids at 16 locations (L1–L16). The differences in altitude between locations ranged from 39 to 243 m above sea level, longitude varied between 15°55′ and 23°12′ E, and latitude spanned from 50°12′ to 54°01′ N. Isolates were identified using molecular techniques. The highest Fusarium species frequency was recorded for 2016 (30.70%) and 2017 (28.18%), and the lowest for 2018 (5.36%). F. verticillioides and F. temperatum were the most frequent. Altitude has an effect on F. vericillioides frequency: F. graminearum showed a negative correlation with both latitude and longitude. In Polish conditions, from silking to harvesting, the number of days with higher precipitation and lower temperatures is associated with an increased frequency of F. verticillioides, F. temperatum, F. graminearum and F. avenaceum. This suggests that the Fusarium presence in Poland is significantly influenced not only by climate change but also by extreme weather changes.

Distribution of Subsurface Nitrogen and Phosphorus from Different Irrigation Methods in a Maize Field

With the advancement of agricultural technology, most crop cultivation adopts water-saving techniques to improve nutrient utilization efficiency. However, limited research has been carried out on the applicability of water-saving techniques for summer maize in the Shandong Province, and it is necessary to assess the risk of nutrient loss in farmland when applying these technologies. This study investigated the distribution of nitrogen and phosphorus under different irrigation methods and planting patterns through soil and water samples. It included sprinkler irrigation (SI), drip irrigation (DI), and subsurface irrigation (SUBI). Different planting patterns, i.e., monoculture (MP) and intercropping pattern (IP), were also selected in the SI zones. The results show variations in soil nitrogen distribution within the layers between 0.9 and 4.5 m, with a pronounced trend of NO3−-N accumulating in deeper layers in the SI zone. Under SI conditions, the IP effectively reduces the nutrient accumulation around the shallow root zone while controlling the accumulation of nitrogen in deep layers. The Olsen-P accumulation in each zone would increase after the accumulation ratio decreased. Compared with MP, the depth interval of the accumulation ratio mutation was shallower in the IP. The trend of NO3−-N accumulation in deep layers is consistent with that of nitrogen concentration in groundwater. Phosphorus that is accumulated in the deep layers is not easily leached into groundwater. In conclusion, these findings can provide basic information for irrigation management in existing cropping systems.

Implications of newly developed SNPs for conservation programmes for the threatened Nubian ibex (Capra nubiana) in Oman

Conservation of elusive species affected by habitat degradation, population fragmentation and poaching is challenging. The remaining wild populations of a desert-adapted ungulate, Nubian ibex (Capra nubiana), within Oman are small and fragmented. The appropriateness of captive insurance populations for reinforcing existing, or establishing new, wild populations remains uncertain for Oman due to ambiguity regarding their genetic provenance. For effective management of this threatened species, it is essential to assess the genetic relationships between the wild and captive populations, and to investigate hybridisation with domestic goats (Capra hircus). We identified 5,775 high-quality SNPs using double digest restriction-site associated DNA (ddRAD), to assess genetic structure, gene flow and divergence between Oman’s wild populations of Nubian ibex and in captivity, which are likely of North African provenance. We detected hybridisation with goats in captivity and recommend that genetic assessments of captive individuals are routinely used to evaluate their suitability for conservation programs. Building on previous mitochondrial evidence, substantial nuclear divergence (FST = 0.540) was found between wild Oman and captive populations, providing further evidence that Nubian ibex may be composed of multiple species and urgently needs a taxonomic review. Additionally, an appropriate insurance population should be established for Oman’s threatened wild population. The data provided here will be invaluable for developing marker systems to assess wild populations using low-quality DNA from non-invasive sampling. Consequently, it will support further research into Nubian ibex throughout their range and highlights the need to integrate genetic information for effective conservation management of Nubian ibex.

Impact of Smoking on Overall and Cancer-Specific Mortality in Prostate Cancer: Elevated Risks in Older and Early-Stage Patients—A Population-Based Study

Prostate cancer (PCa) ranks sixth in cancer mortality among Taiwanese men, with smoking rates remaining high despite the 2009 Tobacco Hazards Prevention Act. This study used the Taiwan Cancer Registry to evaluate smoking’s impact on PCa mortality, providing important information for healthcare strategies and patient management. From 2011 to 2017, 23,107 PCa patients were analyzed, with 7164 smokers and 15,943 non-smokers. The baseline characteristics, clinical stages, comorbidities, and treatment modalities were all included to estimate overall and cancer-specific mortality using the Cox regression model and Kaplan–Meier analysis. The stratified analysis of clinical stage and age group was also estimated. Our study found an association between smoking and increased overall and cancer-specific mortality in PCa patients. Although smokers over 60 had higher risks of overall mortality than non-smokers, cancer-specific mortality did not show significant differences in any age group. Smokers had higher overall mortality than non-smokers across all clinical stages, but cancer-specific mortality was significantly raised only in early-stage cases. In conclusion, smoking is associated with higher overall mortality in PCa patients, with a significant increase in cancer-specific mortality in early-stage cases. Therefore, active smoking management is critical for clinical urologists, particularly in the treatment of early-stage patients.

Examine the Role of Indo-Pacific Sea Surface Temperatures in Recent Meteorological Drought in Sudan

Drought poses a serious threat to Sudan, causing water shortages, crop failures, hunger, and conflict. The relationships between Indo-Pacific teleconnections and drought events in Sudan are examined based on the Standardized Precipitation Index (SPI), anomalies, Empirical Orthogonal Function (EOF), correlation, composite analysis, sequential Mann–Kendall test, and MK-trend test during the period of 1993–2022. The results of the SPI-1 values indicate that the extreme drought in Sudan in 2004 was an exceptional case that affected the entire region, with an SPI-1 value of −2 indicating extremely dry conditions. In addition, Sudan experienced moderate to severe drought conditions for several years (1993, 2002, 2008, 2009 and 2015). The Empirical Orthogonal Function showed that the first EOF mode (42.2%) was the dominant variability mode and had positive loading over most of the country, indicating consistent rainfall variation in the central, eastern, and western regions. Correlation analysis showed a strong significant relationship between June–September rainfall and Indian Ocean sea surface temperature (SST) (r ≤ 0.5). Furthermore, a weak positive influence of the Indian Ocean Dipole (IOD) on JJAS precipitation was observed (r ≤ 0.14). Various time lags in the range of ±12 months were examined, with the highest correlation (0.6) found at 9 month among the time lags of ±12 months. This study contributes to a better understanding of drought dynamics and provides essential information for effective drought management in Sudan. Further research is needed to explore the specific mechanisms driving these interactions and to develop tailored strategies to mitigate the impacts of drought events in the future.

7055 Metabolic Disorders In Thalidomide Embryopathy

Abstract Disclosure: A. Tanabe: None. Thalidomide embryopathy (TE) is a congenital limb defect that occurs in neonates born to pregnant women who have taken thalidomide. Typical abnormalities of the TE are upper limb hypoplasia and and/or auditory dysfunction. In Japan, thalidomide was marketed as an agent for sleep-induce and digestive ulcers from 1958 to 1962. Up to now, approximately 290 cases have been certified and are supported by the government as drug-induced disease. Currently, many of the victims are in their late 50s, and in addition to congenital disabilities, various health issues such as lifestyle-related diseases can be developed. We investigated their metabolic condition using data of medical health checkup between 2017 and 2018. Fifty-one Japanese cases of TE (28 men and 23 women) were included in this study. The mean age was 56.4±1.6 years in men and 55.9±1.2 years in women. The prevalence of upper limb deformities was 64% in men and 74% in women; the remaining patients had only hearing impairment. The mean body mass index (BMI) was 22.7±2.1 in men and 22.5±4.0 in women. Eleven percent of men and 17% of women had a BMI between 25-30, while 9% of women and no men had a BMI of 30 or greater. Liver dysfunction was seen in 32% of men and 9% of women. The mean high-density lipoprotein cholesterol level was 60±17 mg/dL in men and 68±18 mg/dL in women. The mean low-density lipoprotein (LDL) cholesterol level was 120±28 mg/dL in men and 136±35 mg/dL in women, with 25% of men and 48% of women had LDL level of 140 mg/dL or greater. The mean triglyceride (TG) level was 144±85 mg/dL in men and 116±61 mg/dL in women, with 43% of men and 17% of women had a level of 150 mg/dL or greater. The mean HbA1c level was 6.0±1.0% in men and 5.9±0.4% in women. The prevalence of impaired glucose tolerance was 25% in men and 13% in women. Fatty liver (FL) evaluated by ultrasonography or CT scan was 61% in men and 39% in women. The patients with FL showed significantly high body fat percentage and TG level in men, high alanine aminotransferase, γ-glutamyl transpeptidase and TG levels in women, respectively, compared to the patients without FL. The prevalence of hypertriglyceridemia was significantly higher in men with FL compared with men without FL. There was no significant difference in with or without the upper limb abnormalities in both groups. Although without obvious overweight, more than 40 % of the patients had dyslipidemia and 50% of the patients had FL. The limb abnormalities can result in movement limitations however other factors may be involved in the development of metabolic disorders in TE. The results of this study provide valuable information for future health management in thalidomide embryopathy. (This study was conducted by a research grant from the National Center for Global Health and Medicine, Japan: 21A1015 and a Grant-in-Aid from the Ministry of Health, Labour, and Welfare, Japan: 20KC2005, 23KC2017). Presentation: 6/2/2024