Operational Factors Research Articles

374. INCIDENCE AND PREDICTORS OF STRICTURE DEVELOPMENT FOLLOWING ESOPHAGECTOMY: A RETROSPECTIVE ANALYSIS

Abstract Objective Anastomotic stricture (AS) is a well described complication after esophagectomy and not only affects nutritional status but also has a detrimental impact on long-term quality of life. This retrospective study explores the incidence of clinically relevant AS in patients undergoing esophagectomy for cancer and investigates the potentially reversible factors associated with AS. Methods A prospectively entered clinical database of consecutive patients undergoing esophagectomy at a high-volume referral center over a decade (1/2013-12/2022) was queried for the presence of post-operative clinically significant AS, defined as stricture requiring endoscopic dilation. Multiple variables encompassing patient-related risk factors, tumor pathology, prior treatment, operative factors, and post-op complications were included in logistic regression analyses to delineate predictors of stricture formation. Results Of 1015 patients in the database, 115 (11.3%) developed AS requiring at least 1 post-op dilation. Although higher American Society of Anesthesiologists (ASA) grading was associated with elevated AS rate impact with most patients being ASA 2 and 3; 24% and 49% respectfully (p < 0.05). Specific patient factors/comorbidities such as age, peripheral or coronary vascular disease, and diabetes mellitus did not emerge as significant predictors. Surprisingly, neither histology, nor neoadjuvant therapy (chemo or chemoradiation) were associated with AS. Both a cervical anastomosis and a intra-operative pyloromyotomy had a higher AS rate than an intra-thoracic anastomosis (OR 13.3, p=0.006) and patients without a myotomy (p=<0.006). Other operative factors including approach (open vs MIE) conduit type (stomach/jejunum/colon) or width (3/4/5/6 cm) did not impact AS rate. All patients had a hand-sewn anastomosis. No post-operative outcome measures (e.g. leak, epidural use, hypotension) was associated with the development of AS. Conclusion Our results highlight the interplay of patient-related risk factors, tumor pathology, prior treatment, and operative factors in the development of post esophagectomy strictures. Understanding these predictors could potentially influence risk stratification and may facilitate tailored postoperative care strategies for improved patient outcomes.

537. ASSESSING THE EFFECT OF HIATAL HERNIA SIZE ON PERIOPERATIVE OUTCOMES AND HOSPITAL READMISSION RATES AFTER PRIMARY REPAIR

Abstract Background Minimally invasive hiatal hernia (HH) repair remains the gold standard for correcting mechanical defects due to its safety and favorable clinical outcomes (i.e., relief of patient symptoms). However, several operative factors, including the HH size, may negatively impact the postoperative course. We aimed to determine if an increase in HH size was related to an increased risk of perioperative complications or hospital readmissions. Methods After IRB approval, we performed a retrospective analysis using a prospectively maintained database containing demographic, perioperative, and clinical data from all patients who underwent HH repair by a single experienced foregut surgeon between September 2016 and July 2023. Four groups were defined based on the proportion of stomach at the thoracic cavity determined during the surgery: A (small HH: <25%), B (moderate HH: 25-49%), C (large HH: 50-74%), and D (intrathoracic stomach [ITS]: ≥75%). Non-parametric tests were used to assess differences between the groups, and logistic regressions were used to determine the relevant odds ratios (OR). Results A total of 391 patients who underwent primary HH repair met the inclusion criteria (73.7% women; mean age 64.4±12.5 years; mean BMI 28.9±4.9 kg/m2). The distribution of groups was: A (n=160, 40.9%), B (n=63, 16.1%), C (n=64, 16.4%), and D (n=104, 26.6%). Patients presenting with ITS (group D) were older, had longer operative duration, greater blood loss (p<.001), and a significantly increased risk of presenting with early postoperative complications (OR 2.78 [CI95: 1.52-5.06]) and being admitted to the ICU (OR 12.35 [CI95: 3.41-44.71]). Conclusion The HH size, defined by the proportion of the stomach at the thoracic cavity, is associated with an increased risk of early postoperative complications and ICU admission; moreover, a trend toward higher 30- and 90-day hospital readmission rates was noted. This factor may be a consequence of the progressive nature of the disease; hence, it should be considered when choosing between continued medical observation and surgical treatment of patients presenting with asymptomatic HH. An early intervention may reduce the risk of postoperative comorbidity.

Construction of heterojunction superparamagnetic Cd0.5Ag0.5Fe2O4 nanocomposite photocatalyst for simulated textile effluent oxidation

Abstract Significant attempts have been recently made regarding nanomaterials due to their several environmental applications especially in wastewater treatment technologies. Among the available nanoparticles, ferrite based substances are gaining a special interest since their superior characteristics such as their magnetic nature, high adsorption capacity and large specific surface area. In this regard, Cd0.5Ag0.5Fe2O4 was prepared using the green simple co-precipitation route. Then, the sample is characterized via Scanning Electron Microscopy (SEM) that proved the produced material’s surface morphology. The substance is then employed as a catalyst source for Fenton reaction to oxidize textile effluent solution containing Rhodamine B (Rh-B 6G) dye. The oxidation experiment conducted under ultraviolet (UV) light with the ferrite-based Fenton catalyst supplemented with hydrogen peroxide showed an exceptional removal rate of up to 94% removals. Notably, the oxidation system is significantly impacted by the operational variables. The oxidation efficiency of the dye was maximized at pH 3.0 and 50 mg/L and 1600 mg/L for ferrite-based Fenton catalyst and H2O2, respectively. The impacts of the operational factors, i.e. initial pH value, initial dye concentration, catalyst, and H2O2 concentrations were also investigated. This perspective introduces the role of a superparamagnetic material to be a recyclable sustained catalyst.

How the designed processing parameters affect the liquid mixture density and viscosity of the tretinoin-loaded niosomes at different temperatures?

The current study was conducted to present novel thermophysical data on tretinoin-loaded niosomes paired with a combination of span 60 and tween 80. Measurements were carried out to analyze the liquid mixture density and viscosity of the mentioned multilayered structures for the first time, with consideration given to the diverse molecular weights of surfactants and various stabilizers at different temperatures. Through the application of equations of state, this study has the ability to set the stage for thermodynamic modeling of solutions that involve niosomes, presenting a promising avenue for further research. So, tretinoin-loaded formulations were prepared by investigating the effects of different co-surfactants, including cholesterol or dodecanol, as well as the impact of surfactant molecular weight limited to 650.525–1090.175 g mol−1. This novel investigation was conducted to assess the superior stabilizing capabilities of dodecanol in comparison to cholesterol, with a specific emphasis on optimized vesicle size, highest incorporation efficiency, and lowest zeta potential. In particulars, the response surface methodology (RSM) was applied to optimize the operative factors and the number of experiments. The experimental evidence clearly indicates that the use of dodecanol in the manufacturing process significantly improves the stability of niosomes, while the inclusion of cholesterol leads to higher liquid mixture density and viscosity in the prepared niosomes.

Enhanced operational modal analysis and change point detection for vibration-based structural health monitoring of bridges

One of the most promising uses of vibration-based structural health monitoring (VBSHM) in bridge damage detection is the tracking of modes through long-term repeated or continuous operational modal analysis (OMA). Any shifts in modal parameters over time can signal structural damage. However, in real-world applications, noise and environmental uncertainties introduce variability in the data, potentially obscuring damage-related changes. To address this, it is essential to establish and understand the temporal trends and behavior of the estimated modal parameters, enabling accurate interpretation of the engineering data. This paper presents a detailed study focusing on data-driven techniques to improve the OMA results by determining the causes of modal variability and establishing modal models to filter out these known causes of variability. It explores the use of data continuously collected over a period of one month in November 2017 on the Confederation Bridge in eastern Canada. Operational modal analysis is conducted to extract modal frequencies and mode shapes, revealing correlations with environmental and operational factors such as wind, temperature and vehicular traffic. A novel approach using the residuals from regression modal models for damage detection is proposed, utilizing a change point detection algorithm. Results indicate the potential to detect shifts in modal frequencies corresponding to damage scenarios, at lower levels than was previously possible, highlighting the feasibility of using enhanced modal features for sensitive damage identification. Overall, the paper contributes to advancing the understanding of variability in vibration-based structural health monitoring and presents a promising practical technique for improving damage detection results using enhanced operational modal estimates in realistic field applications of a real-world structure.

VNOTES versus Laparoscopic Uterosacral Ligament Suspension for Apical Pelvic Organ Prolapse: Perioperative and Short-Term Outcomes.

Vaginal Natural Orifice Transluminal Endoscopic Surgery (vNOTES) is a novel approach in gynecological surgery. This study was aimed at comparing perioperative and short-term postoperative outcomes of vNOTES versus laparoscopic approaches to uterosacral ligament suspension (USLS) for apical pelvic organ prolapse. A retrospective cohort study included all women who underwent vNOTES versus laparoscopic USLS at two university-affiliated centers between 2017 and 2023. The relationships between variables were tested using Fisher's exact test or t test, including a sub-analysis comparing hysterectomy and hysteropexy outcomes within the groups. Logistic regression assessed the influence of baseline factors and operative factors on the primary and main secondary outcomes of interest. This study comprised 47 vNOTES and 54 laparoscopic USLS cases (including 11 and 15 hysteropexies respectively). Baseline demographics in the two groups were similar. There were no differences in operative outcomes and no instances of ureteral injury. The vNOTES technique allowed for the use of significantly more sutures per side (2.0 [2.0-4.0] vs 1.0 [1.0-1.0], p = 0.001). Postoperative complications within 6 weeks demonstrated no significant differences. Both groups exhibited comparable rates of baseline subjective POP symptoms (100% vs 96.2%, p = 1.00) which improved significantly at 6 weeks (4.3% vs 11.1%, p = 0.282). At 6 weeks, anatomical success was achieved by significantly more patients with vNOTES (93.5% vs 78.6%, p = 0.042). Baseline and 6-week POP symptoms in the hysterectomy and hysteropexy subgroups were similar. Both vNOTES and laparoscopic USLS demonstrated comparable subjective success rates at 6 weeks postoperatively. The vNOTES approach demonstrated improved anatomical success at 6 weeks, but the difference was not significant after adjusting for operative factors.

Machine Learning-Driven Reconfigurable EONs with Neuromorphic Computing for Network Slicing and On-Demand Service Provisioning: A Review and Survey

Abstract: This paper delves into the substantial potential of integrating advanced technologies within Reconfigurable Elastic Optical Networks (REONs). By leveraging machine learning and neuromorphic computing, these networks can significantly enhance performance, scalability, and efficiency. Machine learning models facilitate dynamic resource management, allowing for the on-demand reconfiguration of optical networks to improve service provisioning and maintain high Quality of Service (QoS). Neuromorphic processors further boost network-slicing capabilities, optimizing bandwidth management and enabling the creation of customized virtual networks. Additionally, the incorporation of neuromorphic computing into REONs contributes to substantial energy savings, a critical factor for sustainable network operations. Techniques such as differential privacy and secure multi-party computation effectively address security and privacy challenges within optical networks. Future research should focus on developing scalable architectures, formulating energy-efficient algorithms, and designing solutions tailored to specific applications to maximize the potential of REONs. In summary, the integration of advanced computing techniques within REONs promises to revolutionize network management and service delivery, equipping future networks to deliver exceptional performance, scalability, and adaptability, thus meeting the evolving demands of modern communication environments.

Surrogate based design space exploration and exploitation for an efficient airfoil optimization under uncertainties using transition models

The pursuit of sustainable, zero-emission air travel is heavily dependent on the creation of energy-efficient aircraft. Key strategies for achieving this sustainability in aviation include reducing fuel consumption through low-drag designs harnessing laminar flow. However, designing aircraft with laminar flow characteristics is complex due to their sensitivity to environmental and operational factors. This study tackles the challenge of developing energy-efficient aircraft by using computational fluid dynamics models and sophisticated optimization techniques that account for uncertainty. Our approach demonstrates the effectiveness of surrogate-based optimization and uncertainty quantification in optimizing airfoil drag for a natural laminar airfoil (NLF) design. We use surrogate models, trained with data from detailed airfoil simulations, which include a boundary layer code coupled with a linear stability method and a newly developed transition transport model. Transition location predicted using transition models facilitate an accurate drag prediction used in the optimization process. The accuracy of these surrogate models is enhanced through active sampling strategies. Our robust optimization method considers uncertainties in environmental and operational conditions, offering a deeper insight into their effects on crucial design parameters. Unlike traditional deterministic aerodynamic design optimization, our findings highlight the efficacy and precision of uncertainty-based optimization in achieving robust NLF airfoil designs over large (exploration mode) and small (exploitation mode) design spaces. Investigating design space parameterization based on the size of design variables reveals significant differences in optimal airfoil configurations. The optimized designs we propose favor delayed transition, in contrast to deterministic designs which often result in significant loss of laminarity when facing uncertainties. This study represents a significant advancement in aerospace engineering, providing a practical and effective methodology for creating energy-efficient airfoil designs. The application of these advanced optimization and uncertainty quantification techniques shows great potential for the wider field of aerospace engineering, paving the way for more resilient and robust aircraft designs.

Особливості бізнес-планування у сфері гостинності

The article concentrates on the evolving context of business planning in the hospitality industry, exploring flexible strategies for addressing the negative industry-wide factors that have an impact. The hospitality industry is subject to several operational factors, including revenue generation, cost management, human resources, and marketing, which are influenced by seasonal variations. This necessitates the implementation of strategies to mitigate the impact of fluctuating demand. The high level of competition in the hospitality sector requires a clear competitive advantage, which may be achieved through factors such as location, the provision of high-quality service, innovative design, or a thematic focus. These factors must be strategically employed to distinguish businesses from one another. External factors, including economic conditions, political stability, and environmental risks, significantly influence the hospitality industry. Implementing robust scenario planning, risk management, and service diversification strategies is essential to mitigate these risks. Financial planning is critical to business planning and success, as financial obligations in the hospitality industry underscore the importance of a comprehensive investment analysis. The hospitality industry’s primary asset is its human capital. , strategies should be employed to create a positive working environment, invest in staff training, and implement incentive programs to attract, develop, and retain talent. Guests’ safety and maintaining a positive reputation for hospitality establishments are contingent upon monitoring reviews, responding to negative comments, and utilizing a positive image. The study highlights the necessity for an integrated methodology to be employed in planning business operations within the hospitality sector. Keywords: business planning, hotel and restaurant complex, hospitality industry, stages of organizational culture formation, business.

Multiaxial fatigue life assessment of dental implants

As screwed joints, dental restorations may suffer mechanical failures such as screw loosening and implant or prosthetic screw failure due to fatigue. This work is focused on the failure of the implant and develops a numerical methodology to predict its fatigue life under cyclic loading conditions. This methodology is based on the combination of Critical Plane Methods and the Theory of Critical Distances to account for stress multiaxiality and notch effects. The obtained predictions were validated experimentally, which can be used to identify the main geometrical, assembly and operational factors affecting the fatigue behavior of dental implants. As a result, a powerful and efficient design tool for fatigue life prediction of dental implants is presented. This methodology complements a previously presented one focused on the fatigue life prediction of the prosthetic screw, thereby, offering now a complete design tool package regardless the critical component of the dental restoration, predicting accurately the fatigue response of the restoration, with no need for long-term fatigue test campaigns. This is a pioneering work since no other fatigue design methodology for dental implants with such a solid foundation and experimental validation has been published to date.

Reducing non-technical losses in electricity distribution networks: Leveraging explainable AI and three lines of defence model to manage operational staff-related factors

This study presents a multidisciplinary approach involving Explainable Artificial Intelligence (ExAI) and operational risk management to reduce Non-Technical Losses (NTL) in electricity distribution. It empirically explores how the activities of employees of utility companies contribute to NTL, a phenomenon often overlooked in existing empirical research. An ensemble classification algorithm is used to analyse utility operations data, and the SHAP explainability technique establishes the predictive significance of staff activities for NTL. Subsequently, these staff activities are mapped into risk cells using the BASEL II and III operational risk definitions, and the Three Lines of Defence (3LoD) model is developed for optimizing electricity distribution. The paper makes three original contributions to the literature: first, it empirically links staff operations to NTL; second, it maps NTL causes to Basel II/III operational risk categories; and finally, to the best of the authors’ knowledge, it is the first study to use the 3LoD model for electricity distribution optimization.

Machine learning revealing overlooked conjunction of working volume and mixing intensity in anammox optimization

Extensive studies on improving anammox performance have taken place for decades with particular focuses on its operational and environmental factors, but such parameter-based optimization is difficult, because of the sheer number of possible combinations and multidimensional arrays of these factors. Utilizing machine-learning algorithm and published anammox data, Bayesian nonparametric general regression (BNGR) was applied to identify the possible governing variable(s) from among 11 operating and environmental parameters: reactor type, mixing type, working volume, hydraulic retention time, temperature, influent pH, nitrite, ammonium, nitrate concentration, nitrogen loading rate, and organic concentration. The results showed that working volume is a key but oft-overlooked governing parameter. By integrating the BNGR findings with computational fluid dynamics simulation, which assessed mixing properties, it became feasible to conclude that working volume and mixing intensity co-regulated flow fields in reactors and had a significant influence on anammox performance. Furthermore, this study experimentally validated how mixing intensity affected performance, and specific input power (x), a parameter that conjugates both working volume and mixing intensity, was used to establish the relationship with ammonium removal rate (NH4+-N RR, y) y = 49.90x+1.97 (R2 = 0.94). With specific input power increased from 3.4 × 10−4 to 2.6 × 10−2 kW m−3, the ammonium removal rate exhibited a rise from 1.8 to 3.2 mg L−1h−1. Following, a relationship among input power-working volume-nitrogen removal rate was also established with a view to determining the design variables for anammox reactor. Consequently, the study highlighted the necessity to consider the working volume-mixing intensity correlation when optimizing the anammox process.

The Constellation of Risk Factors and Paraneoplastic Syndromes in Cholangiocarcinoma: Integrating the Endocrine Panel Amid Tumour-Related Biology (A Narrative Review).

Cholangiocarcinomas (CCAs), a heterogeneous group of challenging malignant tumours which originate from the biliary epithelium, are associated with an alarming increasing incidence during recent decades that varies between different regions of the globe. Thus, awareness represents the key operating factor. Our purpose was to overview the field of CCAs following a double perspective: the constellation of the risk factors, and the presence of the paraneoplastic syndromes, emphasizing the endocrine features amid the entire multidisciplinary panel. This is a narrative review. A PubMed-based search of English-language original articles offered the basis of this comprehensive approach. Multiple risk factors underlying different levels of statistical evidence have been listed such as chronic biliary diseases and liver conditions, inflammatory bowel disease, parasitic infections (e.g., Opisthorchis viverrini, Clonorchis sinensis), lifestyle influence (e.g., alcohol, smoking), environmental exposure (e.g., thorotrast, asbestos), and certain genetic and epigenetic interplays. With regard to the endocrine panel, a heterogeneous spectrum should be taken into consideration: non-alcoholic fatty liver disease, obesity, type 2 diabetes mellitus, and potential connections with vitamin D status, glucagon-like peptide 1 receptor, or the galanin system, respectively, with exposure to sex hormone therapy. Amid the numerous dermatologic, hematologic, renal, and neurologic paraneoplastic manifestations in CCAs, the endocrine panel is less described. Humoral hypercalcaemia of malignancy stands as the most frequent humoral paraneoplastic syndrome in CCAs, despite being exceptional when compared to other paraneoplastic (non-endocrine) manifestations and to its reported frequency in other (non-CCAs) cancers (it accompanies 20-30% of all cancers). It represents a poor prognosis marker in CCA; it may be episodic once the tumour relapses. In addition to the therapy that targets the originating malignancy, hypercalcaemia requires the administration of bisphosphonates (e.g., intravenous zoledronic acid) or denosumab. Early detection firstly helps the general wellbeing of a patient due to a prompt medical control of high serum calcium and it also provides a fine biomarker of disease status in selected cases that harbour the capacity of PTHrP secretion. The exact molecular biology and genetic configuration of CCAs that display such endocrine traits is still an open matter, but humoral hypercalcaemia adds to the overall disease burden.

Volatile Fatty Acids from Household Food Waste: Production and Kinetics

Household food waste (HFW), which is rich in organic matter, is a good candidate for producing added-value bio-based chemicals, such as volatile fatty acids (VFAs), by acidogenic fermentation processes. However, the lack of design tools, such as appropriate kinetic models, hinders the implementation of this technology because the results of these processes are affected by operational factors. In this work, VFA production by the acidogenic fermentation of HFW under uncontrolled pH levels (4–5) was studied at thermophilic (55 °C) and mesophilic (35 °C) temperature conditions. Batch reactors were used to digest HFW, and VFA production and the individual acid distributions were measured at different fermentation times from 0 to 624 h. The results showed higher individual and total VFA production at 35 °C and 120 h of fermentation time as a consequence of the competition between the VFA production and decomposition reactions. Acetic and valeric acids were VFAs mainly produced as a result of a high content of proteins in the initial substrate, and a small amount of propionic and butyric acids were present. A simplified kinetic model was successfully developed to represent the complex process of VFA formation from the acidogenic fermentation of HFW. A simple mechanism for the production–decomposition of VFAs, corresponding to a zero-order reaction for the first 48 h and a single consecutive reaction from that time on, was proposed. For both mesophilic and thermophilic conditions, the suggested kinetic model was able to predict the individual and total concentrations of VFAs along the fermentation time.

Machine learning predict the degradation efficiency of aqueous refractory organic pollutants by ultrasound-based advanced oxidation processes

Ultrasound based advanced oxidation processes (AOPs) are effective for removing refractory organic pollutants by generating reactive species. Machine learning (ML) can systematically provide an excellent opportunity to determine the relationship between feature variables and output variables through large amounts of data, thereby reducing the need for experimental measurements. In this study, a ML approach was applied for the first time to predict the degradation efficiency of aqueous refractory organic pollutants by ultrasound-based AOPs. The obtained dataset was normalized and introduced into four ML models. Among them, Random Forest Regressor and XGB Regressor models had the best fit with 0.9546 and 0.9749 for training set R2 and 0.9548 and 0.9740 for test set R2, respectively. Relative importance analysis and SHAP analysis showed that catalyst type, oxidant concentration, reaction time, and catalyst dosage are the important variables affecting the degradation efficiency of refractory organic pollutants. In addition, excessive ultrasonic intensity, ultrasonic frequency, oxidant concentration, and catalyst dosage had little effect on the increase of degradation efficiency. Based on the descriptive data analysis, high degradation efficiency was obtained with ultrasonic intensity of 2 W·mL−1, ultrasonic frequency of 20–40 kHz, reaction time of 60–90 min, pH 3–7, oxidant concentration of ∼7.5 mmol·L−1, and catalyst dosage of >0.4 g·L−1. This work demonstrated a new predictive method to understand the comprehensive influence of operative factors on degradation efficiency in US-based AOPs, guiding parameter and process optimization.

Activated sludge microbial community assembly: the role of influent microbial community immigration.

Wastewater treatment plants (WWTPs) are host to diverse microbial communities and receive a constant influx of microbes from influent wastewater. However, the impact of immigrants on the structure and activities of the activated sludge (AS) microbial community remains unclear. To gain insight on this phenomenon known as perpetual community coalescence, the current study utilized controlled manipulative experiments that decoupled the influent wastewater composition from the microbial populations to reveal the fundamental mechanisms involved in immigration between sewers and AS-WWTP. The immigration dynamics of heterotrophs were analyzed by harvesting wastewater biomass solids from three different sewer systems and adding to synthetic wastewater. Immigrating influent populations were observed to contribute up to 14% of the sequencing reads in the AS. By modeling the net growth rate of taxa, it was revealed that immigrants primarily exhibited low or negative net growth rates. By developing a protocol to reproducibly grow AS-WWTP communities in the lab, we have laid down the foundational principles for the testing of operational factors creating community variations with low noise and appropriate replication. Understanding the processes that drive microbial community diversity and assembly is a key question in microbial ecology. In the future, this knowledge can be used to manipulate the structure of microbial communities and improve system performance in WWTPs.IMPORTANCEIn biological wastewater treatment processes, the microbial community composition is essential in the performance and stability of the system. This study developed a reproducible protocol to investigate the impact of influent immigration (or perpetual coalescence of the sewer and activated sludge communities) with appropriate reproducibility and controls, allowing intrinsic definitions of core and immigrant populations to be established. The method developed herein will allow sequential manipulative experiments to be performed to test specific hypothesis and optimize wastewater treatment processes to meet new treatment goals.

Analysis of decision-making factors for defunctioning ileostomy after rectal cancer surgery and their impact on perioperative recovery: a retrospective study of 1082 patients.

To explore the decision-making factors for defunctioning ileostomy (DI) after rectal cancer surgery and to analyze the impact of the DI on perioperative outcomes. A retrospective case-control study was conducted that included rectal cancer patients who underwent low anterior resection from January 2013 to December 2023. Among them, 33 patients did not undergo DI but with anastomotic leakage (AL) after surgery, and 1030 patients were without AL. Preoperative, operative and tumor factors between these two groups were compared to explore the decision-making factors for DI. Meanwhile, the differences of perioperative outcomes between the DI group of 381 cases and non-DI group of 701 cases were compared. For preoperative factors, the proportions of male patients and preoperative chemoradiotherapy (CRT) in the AL with non-DI group were greater than those in the non-AL group (p < 0.05); for operative factors, the proportion of patients in the AL with non-DI group with a surgical time > 180min were greater (p < 0.05); for tumor factors, the proportion of T3-4 stage was higher in the AL with non-DI group (p < 0.05). Multiple regression analysis revealed that male sex and preoperative CRT were the independent risk factors affecting DI. For perioperative outcomes, the DI did not reduce the incidence of all and symptomatic AL and non-AL postoperative complications (p > 0.05) but with 12.07% stoma-related complications, and increase hospitalization costs (p < 0.05); however, it can shorten the postoperative hospital stay, pelvic drainage tube removal time, and reduce the anal tube placement rate and readmission rate (all p < 0.05). Male patients and preoperative CRT were the independent risk factors affect the decision of DI in our study, and DI can shorten the postoperative hospitalization, pelvic drainage tube removal time, and decrease the anal tube placement rate and readmission rate during the perioperative period but with a higher economic cost.

Improvement of an ionic wind blower’s flow characteristic by auxiliary electrodes for thermal management of light-emitting diodes

Electronic device advancements in power, size reduction, and integration have resulted in increased heat flux and operating temperatures, negatively impacting the reliability of electronics. Ionic wind cooling is a new, environmentally friendly, and energy-efficient thermal management approach that effectively cools high heat flux local heat sources. However, enhancing ionic wind strength continuously can be challenging. In this study, an ionic wind blower consisting of an emitting electrode, a collecting electrode, and auxiliary electrodes is constructed. The experimental verification confirms the supplemental acceleration capacity of the auxiliary electrodes. When determining the optimal operating voltage applied to the auxiliary electrodes, the power consumption of the system and the intensity of the output ionic wind are taken into consideration. Theblower’s operational and structural factors, such as the emitter structure, discharge gap, and distance between the auxiliary electrodes and collectors, are optimized according to how they affect the device’s functional qualities. The improved blower’s heat dissipation ability is evaluated by cooling an LED chip. The results demonstrate that the system performs optimally with an emitter having seven needles, a discharge gap of 5 mm, and 9 mm between the auxiliary electrodes and the collector. The wind speed reaches 2.47 m/s, while the power consumption is only 1.6 W. Compared to the absence of auxiliary electrodes (47.7 W/(m2∙K)), the system’s mean convective heat transfer coefficient can reach 61.12 W/(m2∙K), resulting in a temperature reduction of the LED chip by up to 41.6 °C. With increasing voltage, the heat transfer enhancement ratio improves, enabling a blower with auxiliary electrodes to provide significant cooling while consuming less power.

Optimasi Human Error pada Proses Produksi Air Minum Dalam Kemasan di PT. Telaga Tanjung Pomosda Nganjuk

PT. Telaga Tanjung Pomosda, a bottled mineral water manufacturer in Nganjuk, East Java, faces challenges in maintaining high production standards and addressing operational issues such as product rejection and production process errors, impacting overall company efficiency and reputation. This study identifies operational error factors and evaluates the effectiveness of improvement methods. Research procedures utilize HTA, SHERPA, and Poka-Yoke to identify and reduce human errors in bottled mineral water production at PT. Telaga Tanjung Pomosda Nganjuk, focusing on error analysis, probability assessment, and Poka-Yoke strategy implementation. The bottled water packaging process involves critical stages such as cup packaging, pressing, and packing. Errors in each stage can result in delays, decreased water volume, imperfectly pressed lids, and packing mistakes, hindering the entire production process. Research at PT. Telaga Tanjung Pomosda identifies operator issues in machine settings, water measurement, lid positioning, task interruptions, packaging, and cup positioning, with solutions including routine checks and training to enhance product quality

Trauma, Critical Incidents, Organizational and Operational Stressors: The Relationship Between Harms and Psychological Outcomes for Police

Early psychological health studies in policing often focused on trauma and critical incidents (CIs). More recent research builds a compelling argument that significant causes of psychological harm stems from other operational and organizational factors. The current study uses survey data from a large sample of Australian police ( N = 1763), producing strength metrics derived from mediated regression analyses. The relationships between stressors (trauma and CIs, operational and organizational) and psychological health (psychological distress and burnout) were studied. For the relationship between stress and psychological distress, compared to trauma stress, the relationship with organizational stress was three times stronger and the relationship with operational stress was two and half times stronger. No direct relationship between trauma stress and burnout was found. It was fully explained by organizational and operational stress. The findings suggest police leaders must consider the direct and combined impacts of different stressors on the psychological health of their staff.