Advancing Compressive Strength Prediction in Self-Compacting Concrete via Soft Computing: A Robust Modeling Approach

Self-Compacting Concrete (SCC) is a unique type of concrete that can flow and fill spaces without the need for vibrating compaction, resulting in a dense and uniform material. This article focuses on predicting the compressive strength of SCC using Artificial Neural Networks. Specifically, the study employs multilayer perceptrons with back-propagation learning algorithms, which are commonly used in various problem-solving scenarios. The study covers essential components such as structure, algorithm, data preprocessing, over-fitting prevention, and sensitivity analysis in MLPs. The input variables considered in the research include cement, limestone powder, fly ash, ground granulated blast furnace slag, silica fume, rice husk ash, coarse aggregate, fine aggregate, water, super-plasticizer, and viscosity-modifying admixtures. The target variable is the compressive strength. Through a sensitivity analysis, the study evaluates the relative importance of each parameter. The results demonstrate that the AI-based model accurately predicts the compressive strength of self-compacting concrete

Amino acid-mPEGs: Promising excipients to stabilize human growth hormone against aggregation

Objective(s): Today, the non-covalent PEGylation methods of protein pharmaceuticals attract more attention and possess several advantages over the covalent approach. In the present study, Amino Acid-mPEGs (aa-mPEGs) were synthesized, and the human Growth Hormone (hGH) stability profile was assessed in their presence and absence.Materials and Methods: aa-mPEGs were synthesized with different amino acids (Trp, Glu, Arg, Cys, and Leu) and molecular weights of polymers (2 and 5 KDa). The aa-mPEGs were analyzed with different methods. The physical and structural stabilities of hGH were analyzed by SEC and CD spectroscopy methods. Physical stability was assayed at different temperatures within certain intervals. Molecular dynamics (MD) simulation was used to realize the possible mode of interaction between protein and aa-mPEGs. The cell-based method was used to evaluate the cytotoxicity.Results: HNMR and FTIR spectroscopy indicated that aa-mPEGs were successfully synthesized. hGH as a control group is known to be stable at 4 °C; a pronounced change in monomer degradation is observed when stored at 25 °C and 37 °C. hGH:Glu-mPEG 2 kDa with a molar ratio of 1:1 to the protein solution can significantly increase the physical stability. The CD spectroscopy method showed that the secondary structure of the protein was preserved during storage. aa-mPEGs did not show any cytotoxicity activities. The results of MD simulations were in line with experimental results.Conclusion: This paper showed that aa-mPEGs are potent excipients in decreasing the aggregation of hGH. Glu-mPEG exhibited the best-stabilizing properties in a harsh environment among other aa-mPEGs

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Prioritizing of Strategy Implementation Obstacles among Energy sector's Contractors Using Fuzzy TOPSIS Method

The main purpose of this practical survey is devoted to identify the obstacles of strategic plan implementation among energy sector's contractors and then, to present a classification of identified obstacles on the basis of their priorities. In order to achieve this purpose, 8 factors were chosen as the obstacles of strategic plans in energy sector following the literature review and experts comments, and then applied to 87 managers and senior experts of strategic planning in contracting firms by a questionnaire. The Fuzzy TOPSIS technique is assumed as a well-known Multiple-criteria Decision Making (MCDM) approach. Results showed that organizational structure was received the most priority as an obstacle in implementing strategic plan in contracting industry and operational planning, resource allocation, quality of strategy, communication, strategy executors, control and commitment got subsequent ranks. So, findings of this survey could improve the efficiency of contracting firm's managers to direct the process of strategy implementation and to overcome on identified obstacle

Impact of Dialysis on Open Cardiac Surgery

Background: Dialysis patients frequently have coronary artery disease but are regarded as high risk patients for coronary artery bypass grafting (CABG). Methods: Between February 2002 and September 2006, seventeen dialysis-dependent patients underwent isolated CABG at our center. CABG was performed under cardiopulmonary bypass (CPB) for all the patients. All cases had been maintained on hemodialysis and the duration of preoperative hemodialysis ranged from 6 to 24 months (mean 13.4±6.4). The patients’ characteristics, clinical and operative data as well as perioperative and mid-term outcome were reviewed. Results: All patients were men with a mean age of 53±8.4 years. Mean preoperative ejection fraction was 45.5%±10.4% (range 25 to 60 %). One internal mammary graft was used in 16 (94.1%) patients. Cardiopulmonary bypass and aortic cross-clamp times were 71.3±18.7 and 40.5±8.3 minutes respectively. The more frequent complication was prolonged mechanical ventilation in 2 (11.7%), there was no perioperative mortality. In mid-term follow-up (mean time: 11.8±9.5 months) the mid-term mortality rate was 20% (3 patients). Conclusion: CABG in chronic renal dialysis patients can be accomplished with acceptable short and mid-term morbidity and mortality