Aid Of Information Research Articles

Design of a WiFi sensor network to identify transmission zones of respiratory diseases through air quality indicators

infants and postoperative patients. While air extraction and droplet filtration systems are effective in containing these viruses, interconnected ventilation ducts can still facilitate virus transmission in areas with lower viral concentration. This study introduces a Wireless Sensor Network based on WiFi technology, designed to monitor crucial environmental variables such as CO2, TVOC, temperature, and humidity, collectively influencing indoor air quality. Moreover, this network connects to an online server, collaborating with subscribers to store historical data. The stored information aids in identifying patterns and high-risk zones associated with the transmission of respiratory diseases. The outcomes demonstrate a comprehensive, adaptable, and scalable WiFi-based Indoor Air Quality sensor network. Employing the publish-subscribe pattern, the MQTT message transport protocol, and open-access platforms like Streamlit, Supabase, and HiveMQ, along with affordable boards and sensors, this solution offers an innovative, scalable, and cost-effective approach to identifying areas at risk of airborne disease transmission. The system's design prioritizes data precision and reliability, making it a valuable addition to indoor air quality monitoring systems.

Deep learning algorithms applied to computational chemistry.

Recently, there has been a significant increase in the use of deep learning techniques in the molecular sciences, which have shown high performance on datasets and the ability to generalize across data. However, no model has achieved perfect performance in solving all problems, and the pros and cons of each approach remain unclear to those new to the field. Therefore, this paper aims to review deep learning algorithms that have been applied to solve molecular challenges in computational chemistry. We proposed a comprehensive categorization that encompasses two primary approaches; conventional deep learning and geometric deep learning models. This classification takes into account the distinct techniques employed by the algorithms within each approach. We present an up-to-date analysis of these algorithms, emphasizing their key features and open issues. This includes details of input descriptors, datasets used, open-source code availability, task solutions, and actual research applications, focusing on general applications rather than specific ones such as drug discovery. Furthermore, our report discusses trends and future directions in molecular algorithm design, including the input descriptors used for each deep learning model, GPU usage, training and forward processing time, model parameters, the most commonly used datasets, libraries, and optimization schemes. This information aids in identifying the most suitable algorithms for a given task. It also serves as a reference for the datasets and input data frequently used for each algorithm technique. In addition, it provides insights into the benefits and open issues of each technique, and supports the development of novel computational chemistry systems.

Anomaly detection method based on temporal spatial information enhancement

The proposed Anomaly Detection Method Based on Temporal Spatial Information Enhancement addresses the limitations of unsupervised techniques in detecting abnormal events beyond boundaries and limited samples. It incorporates a Serial Depth Separable Residual Block (Serial Block) as the backbone for predicting future frame. Additionally, a DenseReserve Subsample Module (DRSM) facilitates feature scale scaling, and a U-shaped Pyramid Attention Module (UPAM) guides feature fusion and enhances spatial details. During the prediction stage, reconstructed optical flow information aids in distinguishing abnormal and normal event features, with the abnormal score determined by a weighted fusion of optical flow reconstruction error and prediction error for future frames. Experimental results demonstrate the method’s outstanding performance, achieving area under the curve metrics of 99.7%, 92.1%, and 78.3% on UCSD Ped2, CUHK Avenue, and ShahanghaiTech datasets, respectively. This method offers significant advancements in detecting anomalous events in complex and multi-scene surveillance videos, with improved operational speed and reduced parameters.

Impact of neck angle variation on particle and virus-laden droplet transport from lung to lung using eighth-generation airway model

In this study, the motion of particles from the respiratory tract of an infected person to that of an exposed person was simulated using computational fluid dynamics. The angle of the exposed person’s neck was varied from 0 ° to 20 ° to assess its impact on particle motion. The airway models for the infected and exposed individuals were based on software and CT data, respectively. Particles, generated 1.5 cm from the exposed person’s mouth, were analyzed for deposition on the lung inlet patches, considering the suction effect. The study focused on correlations between the neck angle changes and particle size, excluding considerations of evaporation, death, and coalescence. Results showed larger particles (>15 µm) were not suctioned in and fell, with size influencing attachment locations in the respiratory tract. In virus-laden droplet simulations, the droplets generated inside the infected person’s bronchi were tracked over 60 s. Most of the droplets dispersed in the space were less than 3.0 µm, and the amount of droplets adhering to the lung inlet patches was characteristic. Notably, the data on particle and droplet volumes adhering to specific lung regions at different neck angles and time intervals provide insights for devising efficient drug inhalation methods to mitigate disease progression at targeted lung locations. Additionally, this information aids in understanding the susceptibility of specific lung regions to pulmonary diseases on the basis of virus-laden droplet distribution.

MEDIA EDUCATION AS A FACTOR IN THE DEVELOPMENT OF STUDENTS' CRITICAL THINKING IN THE LESSONS OF FOREIGN LITERATURE IN SENIOR CLASSES

The article examines the process of implementing media education for the development of students' critical thinking in foreign literature lessons in high school. It is noted that media education helps students develop critical thinking skills about the information they consume in the media, helps them analyze, evaluate and perceive various media formats, making them less vulnerable to manipulation and inaccurate information. The article notes that media education is a component of modern education, which is aimed at developing students' media literacy and covers various aspects of media work. It is emphasized that the appropriate use of media education, the ability to analyze, understand, critically perceive and use various media formats will contribute to the development of students' critical thinking. It has been proven that the use of informational teaching aids in foreign literature lessons will contribute to the use of multimedia resources to improve the understanding of texts, create content for literary analysis, and more actively study the material. Internet resources are offered that will help effectively plan lessons and extracurricular activities in educational institutions. It is emphasized that in high school foreign literature classes, it is appropriate to use a variety of media sources: films, videos, websites, etc., related to the works studied and offered for additional reading. We emphasized that media literacy consists in the ability to critically evaluate these sources and their correspondence to the original text. A comparison of the theoretical concepts of media education of research scientists is carried out, which proves the need to explore not only the theoretical possibilities of media resources, but also to emphasize the practical importance of media literacy, not forgetting the problems of media violence, the consequences of its influence on a minor audience. It was found that in the process of media education, the student's information competence is purposefully formed and developed. This involves the ability to work with various information, create and interpret media text, and possess skills.

Selection of microhabitats, plants, and plant parts eaten by a threatened tortoise: observations during a superbloom

Populations of the threatened desert tortoise (Gopherus agassizii) continue to decline throughout the geographic range, in part because of degraded and fragmented habitats in the Mojave and western Sonoran deserts. The species is herbivorous and highly selective in choice of plant species. To increase options for recovery, we analyzed behaviors, patterns of movements while foraging, and parts of plants consumed during a superbloom. We characterized foraging routes and the habitat strata and microhabitats where tortoises traveled to eat preferred wildflower species. Tortoises walked one foraging route per day in early spring, often switched to two routes per day in middle and late spring with rise of midday temperatures. They chose habitat strata (primarily hills and ephemeral stream channels) and three of seven microhabitats for foraging on preferred food plants. Preferred microhabitats were intershrub open space and small (1–2 m wide) ephemeral stream channels. They rarely took bites of forbs growing under and in the dripline of shrubs or nonnative forbs and grasses. Tortoises typically did not select specific plant parts to eat but important exceptions occurred. For example, they usually ignored the inflorescences of the annual Eremothera boothii and, when eating the non-native annual Erodium cicutarium, tended to focus on fruits. All such information aids recovery efforts to restore declining tortoise populations.

Chronic Myeloid Leukemia and Myocardial Infarction: A Nationwide Readmission Database Analysis

Introduction Chronic myeloid leukemia (CML) is a hematological malignancy with an excellent outcome. After advancements in CML treatment and the introduction of different Tyrosine kinase inhibitors (TKI), their life expectancy is equivalent to the normal population. As a result of that, coronary artery disease is anticipated to be the leading cause of death among CML patients. It was particularly noted that TKI use is associated with the risk of endothelial dysfunction and it associated risk of cardiovascular events, including myocardial infarction. In this study, we compare the outcome of PCI in patients with CML to their matched non-CML group. Method The National readmission database (NRD) was searched from January 2016 to December 2020 for the study population. Adults above (age ≥ 18 years) with chronic myeloid leukemia hospitalized with a primary diagnosis of myocardial infarction, ST Elevation Myocardial Infarction (STEMI), and Non-ST-elevation myocardial infarction (NSTEMI) were identified using ICD 10 code. The primary outcomes were in-hospital mortality and 30-day readmission, and the secondary outcome was to compare the complications. The weighting of patient-level observations was implemented to obtain national estimates. Multivariate regression analysis models were built by including all confounders significantly associated with the outcome on univariable analysis with a cutoff P-value of 0.2. Variables deemed important determinants of the outcomes based on literature were forced into the models. For readmission comparison, we used the time-to-event Cox regression analysis. Propensity matching was done by the Greedy method. Proportions were compared using the Mantel-Haenszel Chi-square test or Fisher exact test, and continuous variables were compared using the Student t-test. All P values were two-sided, with .05 as the threshold for statistical significance. Results Out of 2727619 patients with myocardial infarction, 2124 CML patients were identified, and 888 CML patients had Percutaneous Coronary Intervention (PCI). Patients' baseline characteristics and major outcomes were compared (table 1). The mean age of CML patients was 68.34 ± 11.14 (P<0.001). The analysis showed no significant difference between CML and non-CML patients after PCI for the primary outcome of death 0.93 (CI 0.49-1.80) P value 0.527 and 30 days readmission rate 1.41 (0.99-2.01) P value 0.056. Also, there was no statistical significance in developing major complications, including cardiac arrest, coronary artery dissection, cardiac tamponade, stroke, thrombosis, major bleeding, AKI, and dialysis. Discussion and Conclusion Patients with hematologic malignancies, including chronic myeloid leukemia, are at increased risk of thrombosis. In CML, thrombosis can be venous or arterial (myocardial infarction, cerebrovascular accidents, and peripheral artery disease). Arterial thrombosis in CML is primarily linked to using different TKIs, and thrombotic events were reported with the second-generation TKIs like nilotinib, dasatinib, and ponatinib more often than with first-generation TKIs. The mechanism of TKI use-associated thrombosis is likely related to TKI-associated endothelial dysfunction and vascular toxicity that lead to accelerated atherosclerosis and subsequent vascular thrombosis. This increased risk might lead to an assumption of an increased risk of complications with vascular intervention like PCI. Some studies showed that PCI for hematological cancer patients with STEMI have no significant difference regarding in-hospital mortality. This analysis of patients with CML with myocardial infarction ( STEMI and NSTEMI ) showed no statistically significant difference in outcome after PCI between the two groups. There were no significant differences in mortality, 30 days readmission rate, and other complications post PCI. Therefore, diagnosis of chronic myeloid leukemia shouldn't prevent patients from receiving routine therapy and intervention because of the theoretical risk of thrombosis. This information aid in patient counseling and achieving the objective of maintaining a normal quality of life for chronic myeloid leukemia patients.

ANALYSIS OF THE GUITAR MUSIC LEARNING OF BEGINNER USING PROBLEM-BASED LEARNING

This present study aims at exploring the implementation of Beginner Guitar Music Learning through the application of the Problem Based Learning (PBL) model. The research focuses on understanding how the Problem Based Learning model is employed in the context of learning beginner guitar music. The qualitative method with a pedagogical approach was employed for data collection, utilizing observation, interviews, and documentation. The findings reveal that, in the preparatory phase for implementing music learning activities at SMA Negeri 1 Tondano, comprehensive planning is essential. This involves developing semester programs, syllabuses, lesson plans, learning media, and teaching materials. Moreover, the cultural arts (music) teachers conduct a thorough assessment of each student's abilities, considering their interests, needs, and profiles. This information aids in tailoring the learning process to accommodate different learning styles. The study contributes valuable insights into the practical application of the Problem Based Learning model in the domain of beginner guitar music education.

Does mixed frequency variables help to forecast value at risk in the crude oil market?

We construct nine generalized autoregressive condition heteroskedasticity (GARCH) mixed data sampling (MIDAS) models and compare their accuracy in forecasting value at risk (VaR) in the crude oil market with that of benchmark models such as historical simulation (HS) and traditional GARCH models. The main empirical results are as follows. First, we find that mixed frequency information on the demand side of the crude oil market is most helpful for forecasting VaR. Second, although GARCH-MIDAS models generally produce more accurate forecasts than benchmark models, some of the GARCH-MIDAS models tested in this study show poor forecasting accuracy. That is, not all mixed frequency information aids in forecasting VaR in the crude oil market. Third, the HS method, which is widely used by financial institutions, is the least accurate forecasting approach; thus, we do not recommend using HS to forecast VaR in the crude oil market.

Application analysis and evaluation of BIM in engineering design and construction stages

With the development of modern engineering technology, more attention is paid to the aid of digitization and information in the process of engineering project design and construction. Building Information Model (BIM) realizes the transformation from traditional building project to modern building project. At the same time, it also greatly promotes the digital development of construction projects. BIM technology as a modern information technology in the application of construction engineering, has a variety of benefits. For example, it can improve the quality of projects. In addition, the application of BIM technology in the whole process of construction projects can reduce costs and improve efficiency. However, there are many risks associated with using BIM in construction projects. This paper analyzes the advantages of BIM technology in visualization and coordination, and the application of BIM in design, construction, management and other aspects. Then, the risks and countermeasures in BIM application are discussed. The research results are of great significance to improve the informatization level of construction projects.

IMPACT OF FALSE FIRST AID INFORMATION AND MYTHS ON PARAMEDIC EDUCATION

Aim: The purpose of this study was to evaluate the effect of false information and myths related to first aid on paramedic education that have been formed in society.
 Method: A two-level qualitative approach was employed. Focus group interviews with paramedic students were conducted at the beginning of their paramedic training and subsequently, at the end of the second semester, when they had completed their basic paramedic training. An independent qualitative researcher conducted thematic analysis in two stages. Furthermore, to complete the analysis and triangulation of data, paramedic educators involved in the research team reviewed and interpreted the presented themes independently.
 Findings: Ten themes emerged from the first focus group interviews, including misinformation about first aid and practices that may be considered myths. The participants also revealed that the media and family elders disseminated false information and myths related to first aid. Furthermore, while false information could be corrected in subjects such as foreign body aspiration and hemorrhages that are taught mainly in practice in the curriculum, there was resistance when attempting to rectify false information in more theoretical subjects such as poisoning and epilepsy.
 Conclusion: Paramedic students are affected by false information related to first aid. Despite the academic education they received to become professional emergency medical service (EMS) employees, they appeared to resist replacing some incorrect first aid information with that which is correct. It is deemed that the media is the most important means to replace false information with true information and spread scientific information.

Spatiotemporal variability in the C-factor: An analysis using high resolution satellite imagery

Estimating the cover and management factor (C-factor) for Universal Soil Loss Equation (USLE) that varies spatially and temporally within a watershed is time-consuming and resource-intensive. The Normalized Difference Vegetation Index (NDVI) approach can offer a potential alternative for this process. The current study examines nine NDVI models to compare and evaluate their performance in estimating the C-factor values for an agricultural watershed in southwestern Ontario, Canada. Satellite imagery from 2013 to 2020 was used to analyze the models’ similarities and differences on a detailed spatial and temporal scale. The results showed different C-factor values for each model, reflecting that they were developed for different geographical areas and purposes. While the Karaburun model differed from all other models on an annual basis, a detailed combined analysis of different spatial and temporal scales revealed that it was similar to other models. Seasonal analysis was found to be adequate for the current study, as it reduced the resources required and provided an overall view of the vegetation situation. However, a detailed monthly analysis may be necessary when investigating a specific season. The current analysis found that the summer months of June, July, and August have similar trends when comparing different models for different land uses and individual months, which aligns with the seasonal analysis. In conclusion, the current study highlights the importance of incorporating spatial and temporal scales in hydrological modeling and provides valuable insight into the applicability of different NDVI models for estimating the C-factor for southwestern Ontario watersheds. These findings can help inform future research and aid in developing accurate models for estimating soil erosion in this region. The results also emphasize that the NDVI approach has the potential for estimating the USLE C-factor and improving the estimation of soil erosion from agricultural watersheds by incorporating a variable C-factor over time and space. However, further research is needed to validate each model and determine which model best suits the study area.

Organizational Leadership Styles in Startups in Nepal

This study investigates the organizational leadership styles typical of startups in Nepal, a nation renowned for its developing entrepreneurial ecosystem. The study employs a mixed-method approach, integrating qualitative and quantitative data collection techniques, with an emphasis on comprehending the leadership behaviors that promote success and growth in these early businesses. In-depth interviews with company founders, executives, and important stakeholders are conducted as part of the qualitative aspect in order to learn more about their managerial styles, decision-making procedures, and leadership styles. Additionally, observations and case studies of chosen startups provide actual instances of good leadership techniques and how they affect the growth of the firm. A structured questionnaire is given to a different sample of startup employees to gather their impressions of leadership styles inside their individual firms. This complements the qualitative findings. This quantitative information aids in finding patterns, connections, and possible areas for development. This study provides important insights for business owners, investors, and policymakers looking to support a creative and robust startup ecosystem by acquiring a thorough understanding of leadership style in Nepalese companies. The results may also provide a basis for future studies on leadership in developing economies and offer helpful advice for startups as they confront possibilities and obstacles on their way to long-term growth and success.

Organizational Leadership Styles in Startups in Nepal

This study investigates the organizational leadership styles typical of startups in Nepal, a nation renowned for its developing entrepreneurial ecosystem. The study employs a mixed-method approach, integrating qualitative and quantitative data collection techniques, with an emphasis on comprehending the leadership behaviors that promote success and growth in these early businesses. In-depth interviews with company founders, executives, and important stakeholders are conducted as part of the qualitative aspect in order to learn more about their managerial styles, decision-making procedures, and leadership styles. Additionally, observations and case studies of chosen startups provide actual instances of good leadership techniques and how they affect the growth of the firm. A structured questionnaire is given to a different sample of startup employees to gather their impressions of leadership styles inside their individual firms. This complements the qualitative findings. This quantitative information aids in finding patterns, connections, and possible areas for development. This study provides important insights for business owners, investors, and policymakers looking to support a creative and robust startup ecosystem by acquiring a thorough understanding of leadership style in Nepalese companies. The results may also provide a basis for future studies on leadership in developing economies and offer helpful advice for startups as they confront possibilities and obstacles on their way to long-term growth and success.

AUGMENTED REALITY-BASED NASAL ENDOSCOPE VIDEO RECONSTRUCTION AND REGISTRATION

Neuroendoscopic surgery is a minimally invasive surgical technique commonly used to remove a tumor through the patient’s mouth or nose, which requires the surgeon to avoid important neural and vascular structures. Augmented reality-based surgical navigation can provide surgeons with more information and visual aids, clarifying the structure and details of the surgical area. It requires real-time registration of intraoperative endoscopic video with pre-operative CT models. However, 3D reconstruction and camera tracking from nasal endoscopic video are challenging due to the narrow nasal cavity and the lack of texture. Besides, the nasal endoscopic datasets that can be used for deep learning-based depth estimation are scarce and hard to elaborate. To this end, a style-augmented module (SAM) is proposed in this study to minimize discrepancies between different endoscopic datasets. An unsupervised approach was trained to generate depth maps and camera motion paths, which were used to reconstruct the nasal scene’s 3D model. The obtained reconstruction was aligned with a pre-operative CT model for augmented reality-based surgical navigation. The results showed that the proposed SAM improved the generalization of the depth estimation model on nasal endoscopy data. The proposed approach to combining augmented reality technology with surgical navigation is considered instrumental in furnishing surgeons with richer information on the nasal endoscopic surgical scene.

Use of speckle tracking echocardiography in evaluating cardiac dysfunction in patients with acromegaly: an update.

In recent years, cardiovascular disease has garnered increasing attention as the second leading cause of death in individuals with acromegaly, following malignancy. Identifying cardiac dysfunction early in acromegaly patients for timely intervention has become a focal point of clinical research. Speckle tracking echocardiography, a well-established ultrasound technique, surpasses conventional Doppler ultrasound in its sensitivity to assess both local and global cardiac mechanics. It can accurately detect subclinical and clinical myocardial dysfunction, including myocardial ischemia, ventricular hypertrophy, and valvular changes. Over the past five years, the use of speckle tracking echocardiography in acromegaly patients has emerged as a novel approach. Throughout the cardiac cycle, speckle tracking echocardiography offers a sensitive evaluation of the global and regional myocardial condition by quantifying the motion of myocardial fibres in distinct segments. It achieves this independently of variations in ultrasound angle and distance, effectively simulating the deformation of individual ventricles across different spatial planes. This approach provides a more accurate description of changes in cardiac strain parameters. Importantly, even in the subclinical stage when ejection fraction remains normal, the strain parameters assessed by speckle tracking echocardiography hold a good predictive value for the risk of cardiovascular death and hospitalization in acromegaly patients with concomitant cardiovascular disease. This information aids in determining the optimal timing for interventional therapy, offering important insights for cardiac risk stratification and prognosis. In the present study, we comprehensively reviewed the research progress of speckle tracking echocardiography in evaluating of cardiac dysfunction in acromegaly patients, to pave the way for early diagnosis of acromegaly cardiomyopathy.

Nutrient enrichment undermines invasion resistance to Spartina alterniflora in a saltmarsh: Insights from modern coexistence theory

Abstract The ability of native communities to maintain invasion resistance in the face of environmental changes is crucial for biodiversity conservation. However, previous studies have primarily focused on the inhibitive effects experienced by invaders, providing limited insights into the ultimate outcome of resistance. In this study, we integrated modern coexistence theory into biotic resistance research to investigate the impact of nutrient enrichment on the resistance of Phragmites australis marshes to Spartina alterniflora invasion in the Yangtze estuary saltmarshes of China. Our results demonstrated that under non‐enriched conditions, successful invasion resistance was facilitated by stable coexistence between native and invasive species in the field. This prediction of invasion resistance aligned with the distribution dynamics of the two species in the Yangtze estuary saltmarshes over the past two decades. However, nutrient enrichment was likely to lead to a fundamental shift in their coexistence and ultimately, the failure of resistance. Synthesis and applications. Integrating modern coexistence theory into biotic resistance studies advances the assessment of invasion resistance by shifting from quantifying relative strength to predicting explicit resistance outcomes. Ecosystem managers can draw explicit conclusions about the potential establishment and impact of invaders by analysing observational or experimental data within the framework of modern coexistence theory. This information aids in identifying the most efficient strategies for addressing invasive species.

Comprehensive profiling of amino and carbonyl compounds in the Hong Yao sour soup, a type of fermented sour soup, in Huangluo Yao Village of Guangxi, China

Fermented sour soup is a traditional condiment in daily southwestern Chinese cuisine. Compounds found in Hong Yao sour soup were fractionated using size-exclusion chromatography. Amino compounds were identified through derivatization with 6-aminoquinolyl-N-hydroxysuccinimidyl carbamate and liquid chromatography tandem mass-spectrometry (LC-MS/MS) with precursor scan, followed by identification using product ion scan. Other compounds lacking amino groups were isolated using solid-phase extraction with a strong cation exchanger and detected through LC-MS in full scan mode. Carbonyl compounds, including carboxylic acids, were detected and identified by derivatization with 2-nitrophenylhydrazine and LC-MS/MS. Besides amino acids and carboxylic acids including lactic and acetic acid, amino acid metabolites such as monoamines (tyramine, pyrrolidine, tryptamine), polyamines (cadaverine, putrescine), N-acetyl- and N-lacoyl-amino acids, and α-keto acids from Val, Ile, and Leu were also detected. However, unlike Japanese rice wine, only a few dipeptides were detected. This information aids in understanding the unique characteristics of Hong Yao sour soup.

The impact of maize irrigation intervals and potassium fertiliser rates on mealybug populations, vegetative growth, and resulting yield

The mealybug, Phenacoccus solenopsis (Hemiptera: Coccomorpha: Pseudococcidae), is one of the main pests attacking maize plants in Egypt. Field trials were carried out in the maize field to assess the influence of irrigation periods and potassium fertiliser rates on the mealybug ( P. solenopsis) population estimates, vegetative growth, resulting yield, and its components for the maize cultivar (‘Single-Hybrid 168 Yellow’) in the Luxor Governorate, Egypt. Results revealed that unfertilised plants irrigated every seven days had higher pest population densities than other treatments over the two seasons. The fertilised treatments at 114 kg K 2O∙ha –1 that received water every 10 days had the smallest population of P. solenopsis in every season. Data during the two seasons (2021 and 2022) revealed that the maize to which potassium fertiliser was added by 114 kg K 2O∙ha –1 and irrigated every 10 days had vegetative growth (plant height, diameter, and number of green leaves per plant), yield and its components (average ear length, ear weight, number of grains per ear, weight of 1000 grains, and grain yield) significantly increased as compared to those of the plants that were irrigated every 7 days and without adding fertiliser. A higher dose of potassium fertiliser reduces the infestation of P. solenopsis but causes an increment of maize vegetative growth. This affects the final yield. This information aids farmers in comprehending the good agronomic techniques of maize plants to decrease the infestation of mealybugs and increase the yield.

Are Industrial Workers Ready to Intervene in Medical Emergencies? A Field Study Conducted in an Organised Industrial Zone

In organised industrial zones, where workplaces of different hazard classes operate, the risk of injury is high. Therefore, it is important that workers, who are prone to accidents, are prepared to intervene in medical emergencies. This study aimed to evaluate the first aid knowledge levels of industry workers and related factors. This descriptive and cross-sectional study was conducted with 444 industrial workers employed in different institutions in an organised industrial zone in a Turkish province. The data were collected using the descriptive information and first aid knowledge forms. The total score first aid knowledge level of the industrial workers who participated in the study was found to be 19.62 ± 6.02. The findings revealed that the first aid knowledge levels of the industrial workers aged between 36 and 45, married, graduates of high school or a higher educational institution, tenured for more than 1096 days or higher and recipients of first aid training were higher (p