Operational Method Research Articles

The outcomes of corneal sight rehabilitating surgery in Stevens-Johnson syndrome: case series

PurposeTo summarize the outcomes of corneal sight rehabilitating surgery in Stevens-Johnson syndrome (SJS).MethodsThis is a retrospective analysis of a consecutive case series. Twenty-four eyes of 18 SJS patients were included in this study. The ocular parameters, surgical procedures, postoperative complications, and additional treatments of the cases were reviewed.ResultsA total of 29 corneal sight rehabilitating surgeries, which consists of 9 keratoplasties, 8 Keratolimbal allograft (KLAL) and 12 combined surgeries (keratoplasty and KLAL simultaneously) were performed on the 24 eyes. All patients were treated with glucocorticoid eyedrops and tacrolimus eyedrops for anti-rejection treatment without combining systemic immunosuppression, except two patients who were prescribed prednisone tablets for the management of systemic conditions. The mean follow-up period was 50.6 ± 28.1 months. The optimal visual acuity (VA) (0.74 ± 0.60 logarithm of the minimum angle of resolution [logMAR]) and endpoint VA (1.06 ± 0.82 logMAR) were both significantly better than the preoperative VA (1.96 ± 0.43 logMAR) (95% CI, p = 0.000). 57.1% patients (8/14) were no longer in the low vision spectrum, and 88.9% patients (8/9) were no longer blind. The mean epithelialization time was 7.1 ± 7.6 weeks. The success rate was 86.7%. Additional treatments for improving epithelialization included administration of serum eyedrops (n = 10), contact lens (n = 15), amniotic membrane transplantation (n = 6), and tarsorrhaphy (n = 8). Complications included delayed epithelialization (n = 4, over 12 weeks), glaucoma (n = 11), and severe allograft opacity (n = 4). Only one graft rejection was observed.ConclusionsKeratoplasty and KLAL can remarkably enhance VA and improve low vision or even eliminate blindness for ocular complications of SJS. The outcome of the surgeries was correlated with the preoperative ocular situation and choice of operative methods.

Pulse pile-up correction by auto-regression on linear operations (ARLO) method: A comparison with integration-based algorithms

Radiation detection at high count rate suffers from pulse pile-up, where the counting data and energy information of the system are affected by the overlapping of the system output pulses. There exist various pile-up correction strategies to recover the true information of the pulses, among which pulse-tail extrapolation is a well-known method focused on in this study.Present work aims to use a mono-exponential model for extrapolating the pileup-distorted trailing edge of a pulse, to provide a reference line for calculating the true amplitude of its subsequent overlapping pulse. To this goal, the auto-regression on linear operations (ARLO) method is examined and compared with two integration-based methods (the Foss and the Matheson methods), as well as the non-linear least squares (NLS) method.Despite a higher sensitivity to noise, the ARLO method was able to provide a simple, non-iterative solution with a performance over 400 times faster than the NLS algorithm, according to the analysis of a high count rate set of experimental pulses from a NaI(Tl) detection system. Foss and Matheson methods also provided solutions reasonably faster than NLS (but not surpassing ARLO), performing exactly the same as each other with results very close to NLS, benefiting from their non-iterative nature.

Incident Response Simulation Framework

Incident response is a pivotal security role in organizations that aimed to manage incidents quickly and economically. Cybersecurity Incident Response is a valuable development in the mitigation and operational security and data protection methods to safeguard employees and their assets. Cybersecurity awareness training is a powerful approach that leverage companies to cultivate employees into developing their knowledge and awareness of best practices and strategies for safeguarding sensitive data. Incident response is an emerging field due to the exceptional rise in the security breaches. The organizations need to implement such incident responses for the data breaches. The operational teams should be equipped with the hands-on experience of the incidents. The real-world scenarios must be used as a method to enhance the knowledge of the security team. The proposed system responds to such security demands generating an environment to test the security architecture, measure, track and report Cybersecurity KPIs as overall threat exposure to reduce exposure risk. The system is an educative framework for giving a real-world experience to the users and also test their ability and agility to respond to the incidents in the given time and correctly. Keywords—Incident response, Cybersecurity, data breaches, security

A Lateral Flow-Recombinase Polymerase Amplification Method for Colletotrichum gloeosporioides Detection

The greater yam (Dioscorea alata), a widely cultivated and nutritious food crop, suffers from widespread yield reduction due to anthracnose caused by Colletotrichum gloeosporioides. Latent infection often occurs before anthracnose phenotypes can be detected, making early prevention difficult and causing significant harm to agricultural production. Through comparative genomic analysis of 60 genomes of 38 species from the Colletotrichum genus, this study identified 17 orthologous gene groups (orthogroups) that were shared by all investigated C. gloeosporioides strains but absent from all other Colletotrichum species. Four of the 17 C. gloeosporioides-specific orthogroups were used as molecular markers for PCR primer designation and C. gloeosporioides detection. All of them can specifically detect C. gloeosporioides out of microbes within and beyond the Colletotrichum genus with different sensitivities. To establish a rapid, portable, and operable anthracnose diagnostic method suitable for field use, specific recombinase polymerase amplification (RPA) primer probe combinations were designed, and a lateral flow (LF)-RPA detection kit for C. gloeosporioides was developed, with the sensitivity reaching the picogram (pg) level. In conclusion, this study identified C. gloeosporioides-specific molecular markers and developed an efficient method for C. gloeosporioides detection, which can be applied to the prevention and control of yam anthracnose as well as anthracnose caused by C. gloeosporioides in other crops. The strategy adopted by this study also serves as a reference for the identification of molecular markers and diagnosis of other plant pathogens.

Road infrastructure maintenance: Operative method for interventions’ ranking

Planned maintenance of transportation infrastructure is a milestone in maintaining the functionality and safety of road networks. This paper is part of this process and aims to propose an easily applicable and versatile operational methodology for prioritizing maintenance interventions generally scheduled on road networks of considerable extent. An operational methodology for ranking and prioritizing maintenance interventions is proposed; this method is applicable to road networks of such size that direct inspection of each situation is impossible. The core of the paper is the analytical description of this methodology, based on a weighted sum function of three blocks: i) Category − is a score related to the purpose of the intervention; ii) Asset − is a score due to the road on which the intervention is located (considering Average Daily Traffic, Accidentality, Social Cost, Road Type, Routes); iii) Typology − is a score related to the element on which the intervention is being carried out. After describing the parameters and the implementation procedure for each block, the calibration of the relative weights is described, and a sensitivity analysis is performed. In the case study, the proposed methodology is applied to the ANAS corporate network in Italy. This case study will highlight the usefulness, versatility, and operability of the methodology with GIS (Geographic Information System) tools for implementing thematic maps. A concluding section concerns the addition of a scoring block − Spatial Context − as an additional differentiating factor due to the spatial context of each road.

Trends and determinants of mental illness in humanitarian migrants resettled in Australia: Analysis of longitudinal data.

Given the frequent exposure of humanitarian migrants to traumatic or stressful circumstances, there exists a potential predisposition to mental illness. Our objective was to pinpoint the trends and determinants of mental illness among humanitarian migrants resettled in Australia. This study considered five waves of longitudinal data involving humanitarian migrants resettled in Australia. Post-traumatic stress disorder (PTSD) and psychological distress were assessed using PTSD-8 and Kessler-6 screening tools. Through a Generalised Linear Mixed model (GLMM), variables displaying a 95% CI that excluded the value of 1.0 for the odds ratio were identified as associated factors for both PTSD and elevated psychological distress. The selection of multivariable covariates was guided by causal loop diagrams and least absolute shrinkage and selection operators methods. At baseline, there were 2399 humanitarian migrants with 1881 retained and at the fifth yearly wave; the response rate was 78.4%. PTSD prevalence decreased from 33.3% (95% CI: 31.4-35.3) at baseline to 28.3% (95% CI: 26.2-30.5) at year 5. Elevated psychological distress persisted across all waves: 17.1% (95% CI: 15.5-18.6) at baseline and 17.1% (95% CI: 15.3-18.9) at year 5. Across the five waves, 34.0% of humanitarian migrants met screening criteria for mental illness, either PTSD or elevated psychological distress. In the multivariate model, factors associated with PTSD were loneliness (AOR 1.5, 95% CI: 1.3-1.8), discrimination (AOR 1.6: 1.2-2.1), temporary housing contract (AOR 3.7: 2.1-6.7), financial hardship (AOR 2.2:1.4-3.6) and chronic health conditions (AOR 1.3: 1.1-1.5), whereas the associated factors for elevated psychological distress were loneliness (AOR 1.8: 1.5-2.2), discrimination (AOR 1.7: 1.3-2.2) and short-term lease housing (AOR 1.6: 1.0-1.7). The prevalence, persistence and consequential burden of mental illness within this demographic underscore the urgent need for targeted social and healthcare policies. These policies should aim to mitigate modifiable risk factors, thereby alleviating the significant impact of mental health challenges on this population.

Fully automated operational modal identification based on scale-space peak picking algorithm and power spectral density estimation

Modal analysis is a fundamental and essential research direction in the field of structural engineering. The ultimate goal is to determine the modal parameters of the structures. However, the existing modal analysis algorithms often require a large number of parameter adjustments and manual intervention during operation, which cannot be fully automated. In order to realize the automatic identification of modal parameters, the automatic operational modal identification method (AOMI) is proposed based on the interpolated power spectral density estimation (IPSE). To achieve more precise spectrum analysis in the low-frequency band, IPSE is employed to perform Fourier transform on the original frequency domain segment with optimized frequency resolution. This enhances the sharpness of the obtained spectrum in the low-frequency range, making peak frequencies more discernible. Subsequently, the scale-space peak picking algorithm is used to automatically obtain the peak of the power spectral density (PSD), thus enabling the automatic identification of the natural frequency. Finally, the frequency domain decomposition method (FDD) is used to identify modal parameters based on the natural frequencies. The effectiveness of AOMI is verified through the modal identification of the old steel truss bridge and the three layer framework. Under the environmental excitation, the frequencies identified by the IPSE method is close to that of FDD, Bayesian fast fourier transform (FFT) and covariance driven stochastic subspace identification (SSI-COV). Furthermore, the PSD obtained through IPSE has sharper peak than that of FDD and the Welch’s method. The damping ratio identification accuracy and modal assurance criterion (MAC) are satisfactory in AOMI, which can improve the automatic performance.

Deep operational audio-visual emotion recognition

Emotions play a large role in interpersonal communication, marketing, healthcare and the service industry. For this reason, much research has been carried out on emotion classification until today. Audio-visual emotion recognition is a field within artificial intelligence and machine learning that focuses on recognizing and understanding human emotions from both visual and audio cues. It combines computer vision and audio processing techniques to analyze and interpret emotional states expressed by individuals. This paper presents a deep learning model developed over an operational neural network using multiple inputs and aimed at audio-visual emotion recognition. The proposed network utilizes both visual and audio information in an end to end approach. The primary objective of this work is to demonstrate that multi-input models can produce more efficient outcomes compared to single-input models in emotion classification. Another objective is to demonstrate the superior performance of weight calculation methods employed in operational neural networks compared to the conventional weight calculation methods used in convolutional neural networks. Therefore, we want to demonstrate that substituting convolutional neural network approaches with operational neural network methods can yield superior outcomes in emotion categorization models. In the proposed architecture, regular convolutional layers are replaced with operational layers. The experimental results demonstrate that the operational convolutional architecture performs better compared to the classical convolutional neural network architecture.

The Methodology for Evaluating the Operating State of SF6 HVCBs Based on IDDA.

To enhance the precision of evaluating the operational status of SF6 high-voltage circuit breakers (HVCBs) and devise judicious maintenance strategies, this study introduces an operational state assessment method for SF6 HVCBs grounded in the integrated data-driven analysis (IDDA) model. The relative degradation weight (RDW) is introduced as a metric for quantifying the relative significance of distinct indicators concerning the operational condition of SF6 HVCBs. A data-driven model, founded on critical factor stability (CFS), is formulated to convert environmental indicators into quantitative computations. Furthermore, an optimized fuzzy inference (OFI) system is devised to streamline the system architecture and enhance the processing speed of continuous indicators. Ultimately, the efficacy of the proposed model is substantiated through validation, and results from instance analyses underscore that the presented approach not only attains heightened accuracy in assessment compared to extant analytical methodologies but also furnishes a dependable foundation for prioritizing maintenance sequences across diverse components.

MARKERS OF COMPLICATIONS AFTER LAPAROSCOPIC GASTRIC BYPASS IN PATIENTS WITH OBESITY

Introduction. Bariatric surgery is one of the most effective methods of treating morbid obesity, which allows for a long-lasting result. Along with the increase in the number of operative methods of obesity treatment, the relevance of issues related to postoperative complications is increasing. In recent years, the issue of using special checklists after surgery has been actively investigated. This will help optimize the process of monitoring patients' condition in the postoperative period.
 The aim of the study: to develop a check-list model to prevent the detection of complications after laparoscopic gastric bypass in obese patients.
 Materials and methods. On the basis of the developed checklist, a study of the condition of obese patients, who underwent laparoscopic gastric bypass during 2019-2023, was conducted on the basis of the Department of General Surgery No. 2 of the Bogomolets National Medical University. The checklist included the following criteria: the level of pain on the VAS scale, the level of nausea, eating, mobility, whether there is a desire to be discharged home, abdominal muscle tension, pain in the calf muscles, heart rate, oxygen saturation in the blood, the number drainage discharge within 24 hours, temperature, systolic blood pressure, central venous pressure, laboratory diagnosis, decrease in hemoglobin concentration, leukocyte level after surgery, C-reactive protein level after surgery, blood procalcitonin level, erythrocyte sedimentation rate level, the presence of a shift in the leukocyte formula to the left. The presence of complications was assessed, the parameters of the checklist were analyzed using univariate logistic regression and ROC analysis for early detection of complications and determination of the chance of complications in the future.
 Results. Complications occurred in 18/218 (8.2%). The most frequent complication was bleeding in 6/18 (33.3%). Reoperation was performed in 12 cases of 12/18 (66.6%), endoscopic treatment was performed in 1 case, and conservative methods were used in 5 cases. According to the checklist, 31.81% had a positive predictive value (PPV) and 99.56% had a negative predictive value (NPV). The optimal cut-off point of the total score of the checklist was 6. Patients with a positive prognosis of the checklist have a higher chance of developing complications of VSH – 4.5 (95% CI 1.8-9.72), p <0.001.
 Conclusions. The complication rate was 18/218 (8.2%). According to the checklist, heart rate, systolic blood pressure and mobility are very good predictors of postoperative complications. The checklist is the best option for determining the readiness of patients to be discharged from the hospital due to a high prognostic negative result. Due to the low prognostic positive result, the evaluated checklist needs additional modification and optimization taking into account the results already obtained.

Disinfection and hand hygiene knowledge, attitude, and practices among childcare facilities staff during the COVID-19 pandemic in Anhui, China: a cross-sectional study.

This study aimed to investigate the knowledge, attitude, and practice (KAP) regarding disinfection and hand hygiene, along with associated influencing factors among childcare facilities staff during the COVID-19 pandemic in Anhui, and to provide information for developing disinfection and hand hygiene strategies for childcare facilities. A web-based cross-sectional study was conducted among Anhui Province residents in China in September 2020. In this study, 60 childcare facilities in two cities of Anhui Province were selected using the convenient sampling method for questionnaires. The questionnaires were distributed through a web-based platform. The disinfection and hand hygiene KAP scores among childcare facilities staff were calculated, and their influencing factors were analyzed. The accuracy rates of knowledge, attitude, and practice of behavior were calculated and analyzed. A total of 1,029 participants were included in the study. The disinfection and hand hygiene knowledge, attitude and practice ranged from approximately 5 to 23, 1 to 5, 3 to 13, respectively. The score of urban areas was higher than that of rural areas. Higher education levels and more years of working were associated with higher scores. Additionally, staff who received training or supervision had higher scores than those without. The categories with the lowest knowledge accuracy rate (46.3%), lowest attitude accuracy rate (4.2%), and "always" practice rate (5.3%) among childcare facility staff were all related to the question categories concerning the appropriate range of disinfectants for use. The accuracy rates of hand hygiene knowledge and attitude among the childcare facility staff were high (83.7%-99.6%), but the "always" practice rate was in the middle range (63.0%). The disinfection and hand hygiene knowledge among childcare facilities staff was inadequate during the COVID-19 pandemic in Anhui. Continuous implementation of education and training, particularly in rural areas, is essential. Establishing a monitoring system to assess usage effectiveness and adverse reactions in China is critical. Interventions should focus on increasing compliance with hand hygiene practices. Further research should explore the training and intervention of disinfection and hand hygiene, the safety of disinfection measures, and more operational hand hygiene methods in childcare facilities.

Theory and practice for assessing structural integrity and dynamical integrity of high-speed trains

PurposeThe safety and reliability of high-speed trains rely on the structural integrity of their components and the dynamic performance of the entire vehicle system. This paper aims to define and substantiate the assessment of the structural integrity and dynamical integrity of high-speed trains in both theory and practice. The key principles and approaches will be proposed, and their applications to high-speed trains in China will be presented.Design/methodology/approachFirst, the structural integrity and dynamical integrity of high-speed trains are defined, and their relationship is introduced. Then, the principles for assessing the structural integrity of structural and dynamical components are presented and practical examples of gearboxes and dampers are provided. Finally, the principles and approaches for assessing the dynamical integrity of high-speed trains are presented and a novel operational assessment method is further presented.FindingsVehicle system dynamics is the core of the proposed framework that provides the loads and vibrations on train components and the dynamic performance of the entire vehicle system. For assessing the structural integrity of structural components, an open-loop analysis considering both normal and abnormal vehicle conditions is needed. For assessing the structural integrity of dynamical components, a closed-loop analysis involving the influence of wear and degradation on vehicle system dynamics is needed. The analysis of vehicle system dynamics should follow the principles of complete objects, conditions and indices. Numerical, experimental and operational approaches should be combined to achieve effective assessments.Originality/valueThe practical applications demonstrate that assessing the structural integrity and dynamical integrity of high-speed trains can support better control of critical defects, better lifespan management of train components and better maintenance decision-making for high-speed trains.

Assessment of large-scale multiple forest disturbance susceptibilities with AutoML framework: an Izmir Regional Forest Directorate case

Disturbances such as forest fires, intense winds, and insect damage exert strong impacts on forest ecosystems by shaping their structure and growth dynamics, with contributions from climate change. Consequently, there is a need for reliable and operational methods to monitor and map these disturbances for the development of suitable management strategies. While susceptibility assessment using machine learning methods has increased, most studies have focused on a single disturbance. Moreover, there has been limited exploration of the use of “Automated Machine Learning (AutoML)” in the literature. In this study, susceptibility assessment for multiple forest disturbances (fires, insect damage, and wind damage) was conducted using the PyCaret AutoML framework in the Izmir Regional Forest Directorate (RFD) in Turkey. The AutoML framework compared 14 machine learning algorithms and ranked the best models based on AUC (area under the curve) values. The extra tree classifier (ET) algorithm was selected for modeling the susceptibility of each disturbance due to its good performance (AUC values > 0.98). The study evaluated susceptibilities for both individual and multiple disturbances, creating a total of four susceptibility maps using fifteen driving factors in the assessment. According to the results, 82.5% of forested areas in the Izmir RFD are susceptible to multiple disturbances at high and very high levels. Additionally, a potential forest disturbances map was created, revealing that 15.6% of forested areas in the Izmir RFD may experience no damage from the disturbances considered, while 54.2% could face damage from all three disturbances. The SHAP (Shapley Additive exPlanations) methodology was applied to evaluate the importance of features on prediction and the nonlinear relationship between explanatory features and susceptibility to disturbance.

Spectral collocation with generalized Laguerre operational matrix for numerical solutions of fractional electrical circuit models

In this paper, we introduce a pioneering numerical technique that combines generalized Laguerre polynomials with an operational matrix of fractional integration to address fractional models in electrical circuits. Specifically focusing on Resistor-Inductor ($RL$), Resistor-Capacitor ($RC$), Resonant (Inductor-Capacitor) ($LC$), and Resistor-Inductor-Capacitor ($RLC$) circuits within the framework of the Caputo derivative, our approach aims to enhance the accuracy of numerical solutions. We meticulously construct an operational matrix of fractional integration tailored to the generalized Laguerre basis vector, facilitating a transformation of the original fractional differential equations into a system of linear algebraic equations. By solving this system, we obtain a highly accurate approximate solution for the electrical circuit model under consideration. To validate the precision of our proposed method, we conduct a thorough comparative analysis, benchmarking our results against alternative numerical techniques reported in the literature and exact solutions where available. The numerical examples presented in our study substantiate the superior accuracy and reliability of our generalized Laguerre-enhanced operational matrix collocation method in effectively solving fractional electrical circuit models.

Biological Removal of Zinc (II) by Fusarium solani under Different Modes of Operational Strategies: A Comparative Study

The goal of the current batch biosorption experiment was to determine how well Fusarium solani (isolated from soil) resting cells could remove zinc (II) from aqueous solution. With an increase in pH (up to pH 5.0) and an increase in initial zinc (II) concentration of up to 500 mg/L, the specific zinc (II) removal increases. By increasing biomass content from 2.5 to 5.5 g/L, the specific zinc (II) removal remained nearly constant. The investigations also utilised resting cells from various growth stages and at an initial zinc (II) concentration of 500 mg/L, the maximum specific zinc (II) uptake (51.7 mg/g) was accomplished (36 h old). The comparison of the results revealed that cells in a growing state (63.9 mg/g) can achieve the highest selective uptake. Hence, the uptake of zinc(II) under various operational strategies was only done with growing cells. The biological uptake of zinc (II) was then done in a fed batch mode of operation using Fusarium solani growing cells. Increased volume pulse feeding (IVPF) and constant volume pulse feeding (CVPF) were used to study the fed batch process and the impacts of these operational methods on biological performance were contrasted with those of a traditional batch process. According to batch experiments, at pH 5.0 and an initial zinc (II) ion concentration of 500 mg/l, the maximum specific zinc (II) removal was 63.9 mg/g. The maximal specific zinc (II) removal in the IVPF process was determined to be 45.47 mg/g and 33.58 mg/g, but the values in the CVPF process were 33.12 mg/g and 22.59 mg/g respectively for the first and second pulse feedings in both cases. The zinc (II) uptake found in prior investigations carried out by the current authors employing the continuous mode of operation was then compared with these results. The process could be run for a longer period of time with a maximum specific zinc (II) removal of 52.8 mg/g when operating in a continuous mode which was shown to be the optimal operational strategy.

A new operational matrix method to solve nonlinear fractional differential equations

Abstract This study aims to propose novel Zernike wavelets and a new method based on the operational matrices for solving nonlinear fractional differential equations. First, non-orthogonal Zernike wavelets are introduced using the Zernike polynomials. Then, a new technique based on combining these wavelets with the block pulse functions is presented to derive the operational matrix of fractional integration and to solve nonlinear fractional differential equations. Moreover, an error analysis is conducted by providing required theorems. Besides, the proposed method is employed to solve a nonlinear fractional competition model of breast cancer. Finally, a parametric study is performed to consider the effect of fractional order on the population of healthy, cancer stem, tumour, and immune cells, as well as the excess estrogen.

PRACTICAL SUBSTANTIATION OF THE EFFECTIVENESS OF OPERATIVE METHODS OF TREATMENT OF RENNET DISLOCATION

Increased milk potential of animals often leads to disturbance of substance metabolism and appearance of various diseases. Displacement of rennet causes serious economic damage to livestock farms, including reduction of milk productivity, culling, attrition of sick animals, organization of preventive measures and treatment costs. Moreover, after treatment it is impossible to exclude completely the recurrence of this pathology, in some animals we can diagnose the displacement of the abomasum again. In this regard, the aim of our research was to study the comparative effectiveness of operative methods of treatment of rennet displacement. Two groups of 10 cows each with rennet displacement of different age were formed for the research. As a result of the conducted researches, we found out that application of the method of operative suturing of the rennet to the abdominal wall, in the area of the right hungry fossa, is the most effective and reduces the time of recovery of milk productivity in the cow, as well as minimizes the appearance of recurrences of the disease. Treatment efficiency was 80% in the 1st experimental group and 100% in the 2nd experimental group. Recovery in the 1st experimental group came on average on 12,2±1,4 days, in the 2nd experimental group on average on 10,3±1,2 days. The economic efficiency of using the puncture method of treatment, taking into account postoperative therapy amounted to 49,1 rubles, and the economic efficiency of using the surgical method of treatment by suturing the rennet through the right gluteal fossa, taking into account postoperative therapy amounted to 49,3 rubles.

Improving Efficiency in Hospital Pharmacy Services: An Integrated Strategy Using the OCTAGON-P Framework and Lean 5S Management Practices.

Background Hospital pharmacy departments have a critical role in the healthcare system, as they aim to provide excellent patient services while also ensuring cost-effectiveness. Lean methodologies are well-known for improving efficiency and quality in various industries, but their impact on healthcare, particularly in hospital pharmacy settings, has not been thoroughly investigated. Aim This quality improvement (QI) study aimed to assess the impact of implementing the sort, set in order, shine, standardize, and sustain (5S) methodology using the innovative orientation, coordination, training, awareness, governance, observation, normalization, and promotion (OCTAGON-P) framework on the operations of Mediclinic Parkview Hospital (MPAR) Pharmacy in Dubai, UAE. Methods The QI project spanned a period of six weeks, from December 18th, 2023, to January 28th, 2024. Throughout this period, a new novel OCTAGON-P framework's eight crucial elements were methodically integrated. Simultaneously, an extensive preparation processencompassing the five stages of the 5S methodwas carried out. Results The findings indicated a notable enhancement in organization, orderliness, cleanliness, medication storage, and workspace standardization. The significant improvement of 217% in terms of organization highlighted the effectiveness of resource arrangement. The orderliness of the workspace saw an increase of 800%, indicating a transformation in the systematic organization. Additionally, cleanliness improved by 138%, demonstrating a significant advancement in maintaining a spotless environment. The standardization of processes experienced a boost of 300%, reflecting a solidified approach to consistent operational methods. These refinements resulted in an overall improvement of 90% from the initial baseline of 20% on the 5S checklist scores. Efficiency gains were observed, with outpatient medication retrieval times reduced by 50%, inpatient times by 40%, emergency prescription serving by 16.7%, and pediatric prescription serving by 11%. The inpatient medication return process saw a 67% improvement. Patient counseling time increased by 23.3%, indicating a more patient-centered approach. Prescription verification and medication expiry checks increased by 50% and 200%, respectively, enhancing the quality of care. Inventory management efficiency improved by 36%, and medication label printing time decreased by 70% with the additional label printers. Installing extra medication label printers was done through the OCTAGON-P framework, specifically in the "orientation" and "coordination" phases. These two initial phases focused on leadership's 5S orientation, management support, and securing additional resources. Therefore, the OCTAGON-P framework provided a structured approach that promoted continuous improvement and sustained lean practices. Conclusion This research study presented the remarkable effectiveness of the OCTAGON-P framework in structurally implementing the 5S methodology into hospital pharmacy operations. The findings underscored the potential of lean 5S to enhance and optimize operational efficiency and overall quality within the critical environment of hospital pharmacy settings. Consequently, these improvements can conclusively result in the provision of superior and enhanced patient care, which is truly fundamental and central to the mission and objectives of any healthcare institution.

Biological Treatment of Nitroaromatics in Wastewater

Nitroaromatic compounds (NACs), which are widely used in pesticides, explosives, dyes, and pharmaceuticals, include nitrobenzene, nitrotoluenes, nitrophenols, and nitrobenzoates. They are also significant industrial pollutants in the environment. These substances, as well as their derivatives, frequently have toxic or mutagenic properties. Wastewater containing nitroaromatic compounds can be effectively managed by using biological treatment methods that are accessible, cost-effective, and environmentally friendly. This review highlights the latest developments in biological treatment systems for removing NACs from wastewater. The large-scale implementation of biological treatment systems will be facilitated by future studies that focus on identifying the best operational methods and that determine how co-pollutants impact the removal of NACs from wastewater.

SỬ DỤNG TÁC PHẨM TRUYỆN TRONG TÍCH HỢP GIÁO DỤC DINH DƯỠNG - SỨC KHOẺ CHO TRẺ Ở TRƯỜNG MẦM NON

Nutrition and health education are the main content in physical development education for preschool children. To help children develop some good habits and behaviors in eating and hygiene to prevent disease, teachers can use many teaching resources. This study analyzes the advantages of the story works and directions for using them to integrate nutrition and health education for preschool children. Content analysis method, direct interview method, and operational product research method have been used. The results show that stories that can be used to integrate nutrition education for children in preschool are relatively rich and diverse. Teachers can use these stories to educate children about the habit of maintaining physical hygiene and educating children about hygienic and nutritious eating, thereby improving the quality of care, nurturing and education of children at preschool educational establishments.