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Abstract Background and Aims Given the growing utilization of critical care services by an aging population, development of population‐level risk models which predict intensive care unit (ICU) survivorship and mortality may offer advantages for researchers and health systems. Our objective was to develop a risk model for ICU survivorship and mortality among community dwelling older adults. Methods This was a population‐based cohort study of 48,127 patients who were 50 years and older with at least one primary care visit between January 1, 2017, and December 31, 2017. We used electronic health record (EHR) data to identify variables predictive of ICU survivorship. Results ICU admission and mortality within 2 years after index primary care visit date were used to divide patients into three groups of “alive without ICU admission”, “ICU survivors,” and “death.” Multinomial logistic regression was used to identify EHR predictive variables for the three patient outcomes. Cross‐validation by randomly splitting the data into derivation and validation data sets (60:40 split) was used to identify predictor variables and validate model performance using area under the receiver operating characteristics (AUC) curve. In our overall sample, 92.2% of patients were alive without ICU admission, 6.2% were admitted to the ICU at least once and survived, and 1.6% died. Greater deciles of age over 50 years, diagnoses of chronic obstructive pulmonary disorder or chronic heart failure, and laboratory abnormalities in alkaline phosphatase, hematocrit, and albumin contributed highest risk score weights for mortality. Risk scores derived from the model discriminated between patients that died versus remained alive without ICU admission (AUC = 0.858), and between ICU survivors versus alive without ICU admission (AUC = 0.765). Conclusion Our risk scores provide a feasible and scalable tool for researchers and health systems to identify patient cohorts at increased risk for ICU admission and survivorship. Further studies are needed to prospectively validate the risk scores in other patient populations.

Abstract Severe delirium is associated with an increased risk of mortality, institutionalization, and length of stay. Few studies have examined differences in delirium severity between different populations of critically ill patients. The objective of the study was to compare delirium severity and the presence of the four core features between adults in the surgical intensive care unit (SICU) and medical intensive care unit (MICU) while controlling for variables known to be associated with delirium. This is a secondary analysis of two parallel randomized multi-center trials conducted from March 2009 to January 2015 at 3 Indianapolis hospitals. A total of 474 adults with delirium were included in the analysis. Subjects were randomized in a 1:1 ratio in random blocks of 4 by a computer program. Patients were randomized to either haloperidol prescribing or de-prescribing regimen vs usual care. Delirium severity was assessed daily or twice-daily using the CAM-ICU-7 beginning after 24 h of ICU admission and until discharge from the hospital, death, or 30 days after enrollment. Secondary outcomes included hospital length of stay, hospital and 30-day mortality, and delirium-related adverse events. These outcomes were compared between SICU and MICU settings for this secondary analysis. Out of 474 patients, 237 were randomized to intervention. At study enrollment, the overall cohort had a mean age of 59 (SD 16) years old, was 54% female, 44% African-American, and 81% were mechanically ventilated upon enrollment. MICU participants were significantly older and severely ill with a higher premorbid cognitive and physical dysfunction burden. In univariate analysis, SICU participants had significantly higher mean total CAM-ICU-7 scores, corresponding to delirium severity, (4.15 (2.20) vs 3.60 (2.32), p = 0.02), and a lower mean RASS score (− 1.79 (1.28) vs − 1.53 (1.27), p

Objective In critically ill adults with delirium, biomarkers of systemic inflammation, astrocyte activation, neuroprotection, and systemic inflammation measured at one week of critical illness may be associated with mortality. Design Prospective observational study. Setting Intensive care unit (ICU). Patients 178 ICU patients with delirium, alive and remaining in ICU at one week. Interventions None Measurements and main results Blood samples collected for a pair of previously published, negative, clinical trials were utilized. Samples were collected at study enrollment/ICU admission (Day 1 sample) and one week later (Day 8 sample), and analyzed for interleukins (IL)-6, 8, 10, Insulin-like Growth Factor (IGF), S100 Binding Protein (S100B), Tumor Necrosis Factor Alpha (TNF-A) and C-Reactive Protein (CRP). Delirium, delirium severity, and coma were assessed twice daily using Confusion Assessment Method for the Intensive Care Unit (CAM-ICU), CAM-ICU-7, and Richmond Agitation-Sedation Scale (RASS), respectively. Mortality was assessed until discharge using the electronic medical record. Logistic regression models adjusting for age, sex, severity of illness, comorbidities, sepsis, and randomization status, were used to assess the relationship among biomarkers and mortality. Higher IL-10 quartiles at day 8 were associated with increased odds of hospital mortality (IL-10: OR 2.00 95%CI: 1.1–3.65, p = 0.023). There was a significant interaction between day 1 and day 8 biomarker quartiles only for IL-6. Patients with IL-6 values in the first three quartiles on admission to the ICU that transitioned to higher IL-6 quartiles at day 8 had increased probability of hospital mortality. Conclusion In this hypothesis-generating study, higher IL-6 and IL-10 quartiles at one week, and increase in IL-6 from day 1 to day 8 were associated with increased hospital mortality. Studies with larger sample sizes are needed to confirm the mechanisms for these observations.

Importance:. Delirium severity has been associated with a higher risk of mortality and an increasing morbidity burden. Recently defined delirium severity trajectories were predictive of 30-day mortality in a critically ill patient population. No studies to date have examined associations between delirium severity trajectories and 2-year mortality and healthcare utilization outcomes. Objectives:. To examine the associations between recently defined delirium severity trajectories and 2-year healthcare utilization outcomes of emergency department visits, rehospitalizations, and mortality. Design, Setting, and Participants:. This is a secondary analysis using data from the randomized controlled clinical trial Pharmacological Management of Delirium in the Intensive Care Unit and Deprescribing in the Pharmacologic Management of Delirium trial conducted from 2009 to 2015. Patients who were greater than or equal to 18 years old, were in the ICU for greater than or equal to 24 hours, and had a positive delirium assessment (Confusion Assessment Method for the ICU) were included in the original trial. Participants were included in the secondary analysis if 2-year healthcare utilization and mortality data were available (n = 431). Main Outcomes and Measures:. Healthcare utilization data within 2 years of the initial discharge date were pulled from the Indiana Network for Patient Care. Data over a 2-year period on emergency department visits (days to first emergency department visit, number of emergency department visits), inpatient hospitalizations (days to first hospitalizations, number of hospitalizations), and mortality (time to death) were extracted. Univariate relationships, Cox proportional hazard models, and competing risk modeling were used to examine statistical relationships in SAS v9.4. Results:. The overall sample (n = 431) had a mean age of 60 (sd, 16), 56% were females, and 49% African-Americans. No significant associations were identified between delirium severity trajectories and time to event for emergency department visit, mortality, or rehospitalization within 2 years of the index hospital discharge. Conclusions and Relevance:. This secondary analysis did not identify a significant relationship between delirium severity trajectories and healthcare utilization or mortality within 2 years of hospital discharge.

A 66 year old man was diagnosed with CNS diffuse large B-cell lymphoma, and underwent treatment with Temozolomide, Dexamethasone, Rituximab, and radiation therapy, and prolonged steroid taper with Dexamethasone. Approximately one month after this, he presented with severe acute hypoxemic respiratory failure, and was admitted to the Medical Intensive Care Unit. Imaging showed diffuse ground glass opacities. Patient underwent diagnostic bronchoalveolar lavage which was positive for Pneumocystis jiroveci. He did not respond well to appropriate therapy and was transitioned to comfort care per his family's wishes, and expired. Pneumocystis jiroveci should always be included in the differential diagnosis of pneumonia in patients treated with Temozolomide, especially when this agent is used in combination with long term, high dose corticosteroids and radiation therapy.

The main purpose of this study was to explore the self esteem among high school athletes with regard to their participation in recreational and leisure activities and also to see the differences of self esteem level between both sexes (male and female). To achieve the study purpose, 250 (124 male and 126 female) adolescent athletes at the high school level were invited to participate in this survey. Their ages were ranged from 12 to 17 years. They were invited on the basis of their active participation in games and sports and also those who used to participate in various tournaments conducted by the District Sports Office, under the authority of Directorate of Sports, Assam. They were asked to indicate their perception of self esteem on their games and sports participation. The Principal Component analysis extraction and Varimax Rotation methods were adopted for analysis the 10 items in this survey. Three items showed low factor loading (< .50) after EFA. Description of the three items is “I feel that I have a number of good qualities”; “I feel that I’m a person of worth, at least on an equal plane with others”, and “On the whole, I am satisfied with myself ”. Level of self esteem between male and female was found significantly different as it was hypothesized earlier. The results were further enhanced with Confirmatory factor analysis where the result of the Confirmatory factor analysis Model Fit Summary indicated: χ2 = 36.928 with df = 32 to be significant as CFI = .978, RMSEA = .025, GFI = .972, AGFI = .952, PGFI = .566, PCLOSE = .905.

This research aims to understand current patterns, trends, and gaps in personal finance by conducting a systematic literature review of 20 years. The study collected and analyzed the articles published between 2004 to 2024. The research articles were collected from the Scopus database using the PRISMA framework. The review shows changes in the research area, including behavioural finance, digital financial planning tools, and its impact on individuals' financial literacy and planning. The major limitation of this study is that the literature search for personal financial planning might not have incorporated all publications in this area. Furthermore, there is a possibility of bias in this review concerning the papers selected for review and how the researchers interpreted the results. The findings of this systematic literature review can assist policymakers, financial planners, and practitioners in making more informed financial planning decisions and regulations. Thus, by identifying the trends and gaps in personal financial planning, strategies can be defined to provide individuals and society with the necessary level of support. The research is helpful to existing knowledge in that it presents a critical discussion of the personal financial planning literature evident in the last twenty years. The research is original and provides valuable information for upcoming research and practical application in personal financial planning.

Reactive power dispatch (RPD) in electric power systems, integrated with renewable energy sources, is gaining popularity among power engineers because of its vital importance in the planning, designing, and operation of advanced power systems. The goal of RPD is to upgrade the power system performance by minimizing the transmission line losses, enhancing voltage profiles, and reducing the total operating costs by tuning the decision variables such as transformer tap setting, generator’s terminal voltages, and capacitor size. But the complex, non-linear, and dynamic characteristics of the power networks, as well as the presence of power demand uncertainties and non-stationary behavior of wind generation, pose a challenging problem that cannot be solved efficiently with traditional numerical techniques. In this study, a new fractional computing strategy, namely, fractional hybrid particle swarm optimization (FHPSO), is proposed to handle RPD issues in electric networks integrated with wind power plants (WPPs) while incorporating the power demand uncertainties. To improve the convergence characteristics of the Particle Swarm Optimization and Gravitational Search Algorithm (PSOGSA), the proposed FHPSO incorporates the concepts of Shannon entropy inside the mathematical model of traditional PSOGSA. Extensive experimentation validates FHPSO effectiveness by computing the best value of objective functions, namely, voltage deviation index and line loss minimization in standard power systems. The proposed FHPSO shows an improvement in percentage of 61.62%, 85.44%, 86.51%, 93.15%, 84.37%, 67.31%, 61.64%, 61.13%, 8.44%, and 1.899%, respectively, over ALC_PSO, FAHLCPSO, OGSA, ABC, SGA, CKHA, NGBWCA, KHA, PSOGSA, and FPSOGSA in case of traditional optimal reactive power dispatch(ORPD) for IEEE 30 bus system. Furthermore, the stability, robustness, and precision of the designed FHPSO are determined using statistical interpretations such as cumulative distribution function graphs, quantile-quantile plots, boxplot illustrations, and histograms.

This research presents a novel methodology for tackling the combined thermal-wind economic load dispatch (ELD) issue in contemporary power system. The proposed approach involves hybridizing active-set algorithm (ASA), interior point algorithm (IPA) and sequential quadratic programming (SQP) into grey wolf optimization (GWO) algorithm, while effectively incorporating the intricacies associated with renewable energy sources (RES). A more accurate model is made possible by hybridization for complex systems with memory and hereditary characteristics. The GWO is used as a tool for global search while ASA, IPA and SQP methods are used for rapid local optimization mechanism. The performance evaluation of the design heuristics is carried out on 37 thermal and 3 wind power generating units and outcomes endorse the effectiveness of the proposed scheme over state-of-the-art counterparts. The worthy performance is further validated on statistical assessments in case of thermal-wind integrated ELD problem in terms of measure of central tendency and variation on cost and complexity indices.

The modern power generation systems are increasing their reliance on high penetrations of distributed energy resources (DERs). However, the optimal dispatching mechanisms mainly rely on central controls which receive the load demand information from the electricity utility providers and allocate the electricity production targets to participating generating units. The lack of transparency and control over the DER fuel inputs makes the physical power purchase agreements (PPAs) a cumbersome task. This research work proposes an innovative fractal moth flame optimization (FMFO) approach to tackle the problem of integrated load dispatch (ILD). The proposed methodology provides a mechanism to integrate the information of the proposed optimizer, i.e., FMFO into the smart contracts enabled by the blockchain technology. This problem entails the allocation of loads to power-generating units in a manner that minimizes the total generation cost in a decentralized manner. To improve the efficiency of dispatch operations in the presence of a substantial integration of wind energy, this study proposes a novel framework based on the principles of fractal heritage, drawing inspiration from the classical MFO method. To assess the effectiveness and adaptability of the algorithm suggested, various non-convex scenarios in the context of optimization for ILD are considered. These scenarios incorporate valve-point loading effects (VPLEs), capacity limitations, power plants with multiple fuel options, and the presence of stochastic wind (SW) power uncertainty, following a Weibull distribution. The findings demonstrate exceptional performance in terms of minimizing fuel generation costs compared to traditional algorithms.

This article introduces a novel optimization approach known as fractional order whale optimization algorithm (FWOA). The proposed optimizer incorporates the idea of fractional calculus (FC) into the mathematical structure of the conventional whale optimization algorithm (WOA). To validate the efficiency of the proposed FWOA, it is applied to address the challenges associated with the economic load dispatch (ELD) problem, which is a nonconvex, nonlinear, and non-smooth optimization problem. The objectives associated with ELD such as fuel cost and wind power generation cost minimization are achieved by taking into consideration different practical constraints like valve point loading effect (VPLE), transmission line losses, generator constraints, and stochastically variation of renewable energy sources (RES) integration. RES, particularly wind energy, has garnered more attention in recent times due to a range of environmental and economic factors. Stochastic wind (SW) power is also included in the ELD problem formulation. The incomplete gamma function (IGF) quantifies the influence of wind power. To assess its efficacy, the suggested approach is applied to a range of power systems including 3 generating units, 13 generating units and 40 generating units, consisting of 37 thermal units and 3 wind power units. To further strengthen the performance of the optimizer, the FWOA is hybridized with the interior point algorithm (IPA) to further refine the outcomes of the FWOA. The FWOA and IPA are used to address the problem of ELD while including the unpredictable nature of wind power. The simulation results of the suggested technique are compared with the most advanced heuristic optimization methods available, and it has been observed that the proposed optimizer obtained a superior and refined solution when compared to other state of the art optimization techniques. Furthermore, the efficacy of the suggested strategy in enhancing the solution of the ELD issue is validated through statistical analysis in terms of minimum fitness value.

This study's context emphasizes the growing need for effective safety management in residential construction projects. Building Information Modeling (BIM) has been recognized as a potential solution for managing safety in various construction projects, but its adoption could have been more active due to several obstacles. This study identifies and validates the obstacles to implementing BIM-based safety management practices in residential construction projects. The research employed a two-step methodology comprising exploratory factor analysis (EFA) and structural equation modelling (SEM). The data was collected through an online design, construction, and management professional survey. The study reveals four significant obstacles: integration complexity, data quality and consistency, initial investment and cost, and regulatory and standardization. By identifying and validating the obstacles to the adaptation of BIM-based safety management practices, the findings make theoretical contributions to the literature. The small sample size from a limited geographic region and cross-sectional design are limitations. However, the findings provide important practical implications by highlighting key obstacles organizations must address to facilitate BIM adoption for safety management in residential construction. This quantitative study makes a theoretical contribution by validating and ranking key impediments to BIM for safety management in a new context.

This research utilizes the innovative fractional-order Archimedean spiral moth–flame optimization (FO-AMFO) technique to address the issues of the optimal reactive power dispatch (ORPD) problem. The formulated fitness function aims to minimize power losses and determine the ideal flow of reactive power for the IEEE 30- and 57-bus test systems. The extensive functions of the fractional evolutionary computing strategy are utilized to address the minimization problem of ORPD. This involves determining the control variables, such as VAR compensators, bus voltages, and the tap setting of the transformers. The effective incorporation of reactive compensation devices into traditional power grids has greatly reduced power losses; however, it has resulted in an increase in the complexity of optimization problems. A comparison of the findings indicates that swarming fractional intelligence using FO-AMFO surpassed the state-of-the-art competitors in terms of minimizing power losses.

In this current study, collagen protein extracted from eggshell membrane and calcium carbonate (a main component of eggshell) are used as additive to enhance the stability and hardness of the zirconia crystals. Five different samples are prepared by adding membrane containing eggshell content as, 1 g, 2 g, 3 g, 4 g and 5 g in aqueous zirconium oxychloride sol. Phase purity is confirmed by XRD and FTIR. Phase pure and dense particles divulges the high hardness (∼1389 HV) and fracture toughness (12.89 MPa m1/2). FESEM analysis illustrates the formation of dense, well separated, non-agglomerated and spherical nanoparticles at 5 g of eggshell content. Eggshell works as a surfactant and stabilizer for formation of phase pure tetragonal spherical nanoparticles. Biodegradation study of optimized tetragonal zirconia (t-ZrO2 )in phosphate buffered saline (PBS) presents that minor change in weight and hardness after 72 h of immersion. Antioxidant study shows the 96% of radical scavenging activity (RSA). In vitro bio-mineralization study shows the formation of new bone after 5 weeks. After 5 weeks all pores were filled and minerals were deposited on the surface of the scaffolds. SEM images confirms that eggshell-zirconia composite form new bone. So eggshell addition results in formation of phase pure t-ZrO2 nanoparticles with well-defined boundaries which exhibit higher hardness, fracture toughness, stability and enhanced antioxidant properties.

The present study demonstrates the synthesis of phase pure hematite (α-Fe2O3) nanoparticles (NPs) using collagen protein and calcium carbonate extracted from eggshell membranes and eggshells, respectively, as organic additives. To test the influence of organic additives on the quality of the resulting NPs, the amount of eggshell powder was varied between 1 to 5 g in aqueous iron nitrate solution. X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), and RAMAN analysis confirmed the formation of hematite NPs without any impurities. FTIR spectra revealed the presence of polyphenolic constituents on the surface of the resulting NPs as stabilizers, which may potentially be responsible for the observed antioxidant and antibacterial properties. Furthermore, the stable phase and the presence of low defects divulged the high hardness value (~983 HV) and fracture toughness (8.59 MPa m1/2), which can be exploited for bone implantation. The FE-SEM results demonstrate the formation of spherical particles, which are well-separated NPs. The results of a biodegradation study which was carried out in phosphate-buffered saline (PBS) revealed that the as-prepared NPs retained their hardness even after 72 h of soaking. These prepared NPs showed 95% radical scavenging activity (RSA) and were good carriers against S. aureus bacteria. Moreover, the SEM images of the mineralization of iron oxide NPs confirmed the formation of new bone. After 5 weeks, all pores were filled, and the minerals were deposited on the surfaces of the scaffolds.

ObjectiveIn critically ill adults with delirium, biomarkers of systemic inflammation, astrocyte activation, neuroprotection, and systemic inflammation measured at one week of critical illness may be associated with mortality.DesignProspective observational study.SettingIntensive care unit (ICU).Patients178 ICU patients with delirium, alive and remaining in ICU at one week.InterventionsNone.Measurements and main resultsBlood samples collected for a pair of previously published, negative, clinical trials were utilized. Samples were collected at study enrollment/ICU admission (Day 1 sample) and one week later (Day 8 sample), and analyzed for interleukins (IL)-6, 8, 10, Insulin-like Growth Factor (IGF), S100 Binding Protein (S100B), Tumor Necrosis Factor Alpha (TNF-A) and C-Reactive Protein (CRP). Delirium, delirium severity, and coma were assessed twice daily using Confusion Assessment Method for the Intensive Care Unit (CAM-ICU), CAM-ICU-7, and Richmond Agitation-Sedation Scale (RASS), respectively. Mortality was assessed until discharge using the electronic medical record. Logistic regression models adjusting for age, sex, severity of illness, comorbidities, sepsis, and randomization status, were used to assess the relationship among biomarkers and mortality. Higher IL-10 quartiles at day 8 were associated with increased odds of hospital mortality (IL-10: OR 2.00 95%CI: 1.1-3.65, p = 0.023). There was a significant interaction between day 1 and day 8 biomarker quartiles only for IL-6. Patients with IL-6 values in the first three quartiles on admission to the ICU that transitioned to higher IL-6 quartiles at day 8 had increased probability of hospital mortality.ConclusionIn this hypothesis-generating study, higher IL-6 and IL-10 quartiles at one week, and increase in IL-6 from day 1 to day 8 were associated with increased hospital mortality. Studies with larger sample sizes are needed to confirm the mechanisms for these observations.

In this study, ZnO nanoparticles (NPs) were synthesized in the presence of almond oil at various molar ratios of zinc acetate and sodium hydroxide, including 0.5:1, 0.75:1, 1:1, 1.25:1, and 1.5:1, to obtain pH values of 11, 10, 9, 8, and 7, respectively. The XRD results revealed that ZnO NPs exhibit a hexagonal structure, with high crystallinity. SEM results showed that dense and large sized ZnO NPs were formed at pH 11, and relatively small (~30–40 nm) NPs were obtained at pH 9. The size distribution can be explained in terms of the presence of OH− ions at different pH levels. However, the larger size of the NPs at pH 7 compared to those at pH 8–11 were due to the coalescence of NPs suitable for antioxidant/antibacterial activities. ZnO NPs demonstrated a high degradation efficiency (~93%) in 90 min, with a high rate constant for Methyl Orange (MO), which is better than the previously reported rate. The larger sized almond oil capped ZnO NPs also showed excellent radical scavenging activity (94%) and are proven to be good carriers to resist Escherichia coli (E. coli) bacteria.

The Adaptive User Interface (AUI) adapts to the changes in the context of use and provides improved interaction abilities for different users. The adaptivity in the user interfaces requires in depth knowledge of context. There is a need to enrich user profiles to achieve the personalized services with the ability to adapt the user’s context. The context can be reflected in a particular kind of knowledge and hence modeled as ontology. Ontology based context models are effective means to handle complex situations that support the sharing or integration of context information. This paper presents ontology based context model using OWL for adaptive mobile devices. It models the context over its four major elements including device, user, environment (location and time) and activity. The proposed ontology was derived in different classes, relationships, associations, dependencies and constraints to model dynamic context. Ontologies present a standardized, consistent and shareable context model. The context model and consequent context snapshots can be acknowledged by AUI to present a suitable user interface. The ontology was developed using Protégé on the basis of each context type having different values. Semantic querying (SPARQL) was used for knowledge acquisition. Moreover, the Pellet and HermiT Reasoner were used to verify the rules, relations and constraints to avoid the inconsistency between classes. Comparative to other context models for adaptive interfaces, ontological model provides more of scalability and growth with learning new context in to the shared context knowledge.

Biogenic routes for the synthesis of nanoparticles are environmentally friendly, nontoxic, biocompatible, and cost-effective compared to traditional synthesis methods. In this study, cobalt ferrite was synthesized using Zingiber officinale and Elettaria cardamom Seed extracts. Effect of copper contents (x = 0.0, 0.3, 0.6 and 0.9) on the plant extracted Cux(Co1−xFe2O4) was investigated by XRD, SEM, EDX, UV-Vis., PL, FE-SEM, FTIR and photocatalytic activity. XRD results revealed that nanoparticles exhibit a cubical spinel structure with an average diameter of 7–45 nm, calculated by the Debye Scherer formula. The value of the lattice parameter decreased from 8.36 Å to 8.08 Å with substitution of copper, which can be attributed to mismatch of ionic radii of Cu2+ (0.73 Å) and Co2+ (0.74 Å) ions. SEM analysis showed that nanoparticles exhibit a spherical shape (~13 nm diameter) for undoped samples and low Cu concentration, while they changed to a hexagonal structure at higher Cu concentration (x = 0.9) with a diameter ~46 nm and a decreased degree of agglomeration. FE-SEM further confirmed the nanoparticles’ size and shape. EDX analysis confirmed the presence of cobalt, iron, and oxygen without contamination. The optical absorption spectra of UV-vis and PL showed red-shift, which can be accredited to larger crystalline sizes of nanoparticles. FTIR spectra showed two main bands at 410 and 605 cm−1, indicating the presence of intrinsic vibrations of the octahedral and tetrahedral complexes, respectively. The photocatalytic activity of Co0.4Cu0.6 Fe2O4 nanoparticles was investigated using methylene blue (MB) and methyl orange (MO) dyes under visible light irradiation. The degradation rate (93.39% and 83.15%), regression correlation coefficient (0.9868 and 0.9737) and rate constant (0.04286 and 0.03203 rate·min−1) were calculated for MB and MO, respectively. Mechanisms for the formation and photocatalytic activity of Cu-substituted plant-extracted cobalt ferrite were discussed. The Co0.4Cu0.6 Fe2O4 nanoferrite was found to be an efficient photocatalyst, and can be exploited for wastewater treatment applications for MB/MO elimination.

In 1934 Lemmel was the first to report the presence of juxtapapillary diverticula and hepatocholangiopancreatic disease, excluding cholelithiasis. Obstructive jaundice caused by periampullary duodenal diverticulum (PAD) in absence of choledocholithiasis or tumor is known as Lemmel syndrome. A patient with an extraluminal duodenal diverticulum presenting with obstructive jaundice and pancreatitis is presented in this case. Although initially managed conservatively, the patient had recurrence of symptoms after 2 months but then had successful surgical resection of the duodenal diverticulum.

The effect of laser irradiation with different numbers of laser shots on the microstructure, the surface, and the hardness of gun metal alloy was studied by a KrF pulsed excimer laser system, X-ray diffraction, Raman spectroscopy, scanning electron microscopy, and Vickers hardness test. The influence of 100−500 laser shots was irradiated on the surface hardness profile and on the microstructure of gunmetal alloy. XRD results showed the maximum 2θ shift, the maximum full width of half maximum FWHM, the maximum dislocation density, and the minimum crystallite size for the sample irradiated with 300 laser shots. The hardness was measured in three different regions at the laser irradiated spot, and it was found that maximum hardness was present at the heat affected zone for all samples. The hardness value of the un-irradiated sample of gun metal was 180, and the value increased up to 237 by raising the number of laser shots up to 300. The peak value of surface hardness of the laser treated sample was 32% higher than the un-irradiated sample. The Raman shift of the un-exposed sample was 605 cm−1 and shifted to a higher value of wave number at 635 cm−1 at 300 laser shots. The hardness value was decreased by further increasing the number of laser shots up to 500. The samples irradiated with 400 and 500 laser shots exhibited smaller hardness and dislocation defect density, which was assigned to possible annealing caused by irradiation.