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Under the influence of neo-liberalism and marketization, education is increasingly becoming more content-focused than character one. Ignoring the fact that money, science, and technology may take a person to the moon, these are ethical and moral values that take him/her to the even loftier heights of humanity. Recent COVID-19-driven focus on information and communication technology (ICT) and digital learning have further added to these woes by focusing more on human-machine interaction than human-human ones. Traditional models for inculcating these values through education which heavily rely on the physical presence of teachers do not seem to work in these circumstances. This demands a model for inculcating these values in learning management systems/ e-learning platforms. This study contributes in this regard by first identifying key players and factors, and then proposing a model for it. Using the Delphi model, it gathers opinions from 59 experts in two rounds. Academic institutions, society and online community members, teachers, and e-contents were identified as key factors and players. It suggests a holistic approach-based model through which all of them play their role and collaborate through an e-learning platform. That platform can be used to disseminate information, create awareness, monitor, and report the e-learners. It uses pull and push strategies to help the e-learners to develop those values.

The world has gradually but steadily paid more attention to the use of bacteria to break down acrylamide as a bioremediation technique. Using a two-level factorial design, a previously obtained molybdenum-reducing bacterium with the ability to degrade amides was further identified on important factors influencing its optimal development on acrylamide. In order to screen five distinct parameters impacting the development of the bacterium on acrylamide, a two-level factorial design was used. Three center point replications were used in a total of 32 tests. These variables include pH, temperature, the length of the incubation period, the concentrations of acrylamide and glucose. Acrylamide concentration, pH, and incubation time were found to be key factors in this bacterium's growth on acrylamide by the two-factor factorial design and were successfully adjusted using RSM in subsequent studies. Using ANOVA, Pareto's chart, pertubation's plot, and other diagnostic plots, the significant contributing components or parameters were analyzed. The two-level factorial conclusion was supported by diagnostic plots including half-normal, Cook's distance, residual vs runs, leverage vs runs, Box-Cox, DFFITS, and DFBETAS. The acrylamide range used in this investigation is well within the range that most acrylamide-degrading bacteria have been found to tolerate. Longer incubation times allow for higher growth, and many acrylamide-degrading microorganisms have been observed to have incubation times of two to five days for optimized growth. The majority of acrylamide-degrading microorganisms thrive at circumstances that are close to neutral, and the findings of this study are consistent with published literature trends in this regard.

In the long run, bioremediation is the utmost cost-effective way, particularly at low concentrations while other methods like physical or chemical procedures would be ineffective, for the elimination of heavy metals and organic pollutants. The process of reducing molybdenum (sodium molybdate) with an oxidation state of (VI) to molybdenum blue (oxidation state from V to VI) serves as a form of detoxification. Important characteristics, such as specific reduction rate, theoretical reduction maximum, and the lag duration of reduction, can be shown by mathematical modeling of the reduction process. While natural logarithm transformation is a common linearization approach, it is not precise and can only provide a rough estimate of the most important single measurable parameter; the specific growth rate. In this study, for the first time, values for the aforementioned parameters or constants were calculated using a wide range of models, including the logistic, Gompertz, Richards, Schnute, Baranyi-Roberts, Buchanan three-phase, von Bertalanffy and most recently, the Huang model. Based on statistical tests including root-mean-square error (RMSE), bias factor (BF), adjusted coefficient of determination (adjR2), accuracy factor (AF), and corrected Akaike information criterion (AICc), the logistics model was found to be the best model for representing the Mo-blue production curve of Bacillus sp. strain khayat. The fitting technique resulted in the calculation of three parameters: specific reduction rate (h-1), Lag period (h), and maximum Mo-blue production (nmole Mo-blue). In this study, we utilize a mathematical technique to determine the reduction parameters for Mo-blue production from sodium molybdate. The calculated parameter constants will be used to create secondary models, such as the influence of substrate and environment on Mo-blue synthesis.

Phenol, in particular, is one of several dangerous synthetic compounds created by humans. There were more than 80,000 chemicals produced in the US for industrial use, and many of these are phenol and phenolic compounds that end up in the environment without being subjected to adequate safety assessment. There are several types of bacteria that may use phenol as a carbon source, making bioremediation of this dangerous material a promising possibility. We found that at very high concentrations of phenol, the growth rate of Pseudomonas putida NAUN-16 was significantly slowed down. The primary growth model modified Gompertz was utilized to obtain the growth parameter specific growth rate. In this study, we continue the work by further modelling the effect of substrate or phenol on the growth rate of the bacterium using several substrate inhibition kinetic models such as Monod, Haldane, Teissier, Aiba, Yano and Koga, Han and Levenspiel, Luong, Moser, Webb and Hinshelwood. The resultant fittings show appreciable fitting with the exception of the Monod model. The Teissier model, as opposed to the more widely used Haldane model, better suited the growth rate data at different concentrations of phenol as judged by the results of the RMSE, AICc, adjustedR2, F-test, and bias and accuracy factor. The designated values of the Teissier constants were maximal reduction rate, half saturation constant for maximal reduction and half inhibition constant which are symbolized by max, Ks and Ki were 0.150 1/hr (95% confidence interval 0.120 to 0.180), 162.19 mg/L (95% C.I.55.58 to 268.79) and 1291.94 mg/L (95% C.I. 1067.24 to 1516.65), respectively. The value generated from curve fitting interpolation should not be taken as the actual value and it should be warned of this as the true mumax should be where the gradient for the slope is zero and in this case the value was approximately 0.097 1/h at 385 mg/L phenol.

Acrylamide pollution and contamination can come from a variety of sources and is an emerging toxic pollutant that need remediation. A molybdenum-reducing bacteria that had been previously isolated and demonstrated the ability to degrade amides was further studied of its critical parameters contributing to optimum growth on acrylamide. The Box-Behnken design was utilized in optimizing the three previously identified significant components (pH, incubation time and acrylamide concentration). ANOVA, the pertubation's plot, and several other diagnostic plots were utilized in the analysis of the significant factors or parameters that contributed. The model was supported by the diagnostic plots including the half-normal, Cook's distance, leverage vs runs, residual vs runs, Box-Cox, DFFITS, and DFBETAS. Conditions that were predicted to be optimal were found and analyzed in order to find the optimal growth given the factors that were used and to determine the optimal concentration, which was 1 g/L. The solutions for finding the optimal growth predicted a growth maximum of 12.055 Log CFU/mL (95 percent confidence interval (C.I.) from 11.550 to 12.593), and verification using experimental results resulted in a growth of 12.908 Log CFU/mL (12.744 to 13.072) with the results being close to the predicted values but was significantly higher than the predicted data. The second numerical optimization was for predicting the highest acrylamide concentration tolerable for growth and the solution shows a predicted a growth maximum of 12.055 Log CFU/mL (95 percent confidence interval from 11.550 to 12.593). This solution was experimentally verified resulting in a growth of 12.195 Log CFU/mL (95 percent confidence interval from 11.806 to 12.584) with the actual results being in accordance with the predicted values. The results of the RSM exercise showed that growth on acrylamide may be optimized more effectively with RSM than with OFAT, which indicates that RSM is more useful than OFAT in this regard.

Polyacrylamide is one of the most important sources of acrylamide in soil because it degrades into acrylamide over time. The breakdown of acrylamide by bacteria has experienced a steady but consistent increase in interest all over the world as a bioremediation technique. In this investigation, a previously obtained molybdenum-reducing bacterium with amide-degrading capabilities was found on critical parameters leading to optimum growth on acrylamide utilizing a two-level factorial design. The two-level factorial design was used in the screening of five independent parameters impacting the bacterium's growth on acrylamide. These variables include pH, temperature, incubation period, acrylamide concentration, and ammonium sulphate concentration. The two-factor factorial design was successful in identifying major contributing parameters in the growth of this bacterium on acrylamide, which were acrylamide concentration, pH, and incubation time (p

In the foreseeable future, bioremediation is by far the most cost-effective method for removing noxious chemical toxins and organic contaminants, especially at low concentrations when other methods like physical or chemical procedures wouldn't be successful. For the objective of bioremediation, we have isolated a molybdenum-reducing bacteria from agricultural soil. The ideal pH and temperature ranges for the bacterium to reduce molybdate to molybdenum blue (Mo-blue) are 6.3 and 6.8, respectively. The best electron donor for molybdate reduction was glucose, which was followed in descending order by sucrose, lactose, l-rhamnose, d-mannose, raffinose, d-adonitol, maltose, d-mannitol, melibiose, cellobiose, glycerol, and d-sorbitol. Phosphate concentrations of 7.5 mM and molybdate concentrations of 15 – 20 mM are also necessary. The Mo-blue that was formed had an absorption spectrum that was comparable to that of earlier Mo-reducing bacteria and closely resembled that of reduced phosphomolybdate. At 2 ppm, copper (II), mercury (I), and silver I hindered molybdenum reduction by 80.2, 74.8, and 30.4%, respectively. The bacterium was tentatively identified as Enterobacter aerogenes strain Amr-18 after phenotypic and biochemical identifications. The bacterium could thrive on the amides, acrylamide, acetamide, and propionamide and could use acrylamide as an electron donor for molybdenum reduction. This bacterium has a highly valued trait that makes it useful for bioremediation: the capacity to detoxify a variety of toxicants.

Bioremediation of pollutants, such as herbicides, is an economic and environmentally friendly process. Glyphosate is an active ingredient in most herbicides utilized for weed control and desiccation on cereal and other grain crops globally. Glyphosate pollution poses a threat to the environment and the habitats in it. In this study, an isolated molybdenum-reducing bacterium was characterized for its potential to degrade glyphosate and utilized as the sole source of carbon and electron donor. The effects of incubation time, glyphosate concentration (carbon source), inoculum size, pH, temperature, aeration and heavy metals on the growth of this bacterium were spectrophotometrically assayed as OD600 nm. The bacterium degrades glyphosate faster under shaking conditions, optimally at pH 7.0, concentration 1.0 g/L, temperature 40 ºC, and inoculum size 400 µL. Growth of this bacterium was significantly inhibited by heavy metals in the order of Cu>Zn>Pb>Hg>Ag>Fe compared to the control. Glyphosate can serve as an electron donor source in hexavalent molybdenum reduction, but poorly supports molybdenum blue (Mo-blue) production compared to glucose. The dual role of this isolate as a metal reducer and glyphosate degrader makes it unique already and an important instrument for the bioremediation of mixed pollutants.

Mycotoxins are harmful secondary metabolites generated by a variety of fungi, and they may be found in a vast array of food and feed commodities and processed meats from animals fed infected meal. Numerous mycotoxins are extremely resistant and survive food processing, entering the food chain and posing a concern to human health. The "optical waveguide lightmode spectroscopy" (OWLS) method was used to detect aflatoxin B1 in plant sample matrices. The calibration curve for the detection of aflatoxin B1 utilizing "optical waveguide lightmode spectroscopy" (OWLS) displayed a sigmoidal shape; hence, the 5-PL or 4-PL model should be used to fit the data rather than a linear model. Using error function analysis with functions such as AICc, HQC, BIC, RMSE, adjR2, Bias Factor, and Accuracy Factor, the 5-PL and 4-Pl models are distinguished inconsistently. The overlapping confidence intervals of the LogEC50 values suggested that the two techniques did not differ much, and the 4-PL model was selected due to its smaller number of parameters. The Limits of Detection for aflatoxin B1 value based on the 4-PL equation was 8.787 ng/mL with the 95% confidence interval from 5.728 to 13.100. In this study, the use of the 4-PL model was successful and was able to represent the entire date curve, not only the linear section. The linear component is crucial as a handy and swift approach for assessing the sensitivity of a developed biosensor technology and is often a more beneficial method for field applications when a quick and straightforward evaluation is required.

As the most pristine and one of the biggest continents in the southern hemisphere, Antarctica has over the decade accumulated hydrocarbon pollution mainly due to human activities related to logistics and transportation in this area. Acetonitrile spills caused by the sinking of the cargo ships call for research into acetonitrile-degrading microorganisms in the form of bioremediation in order to be ready for disasters in the future. The efficiency of a previously isolated acetonitrile-degrading sludge consortium as a bioremediation technique has been demonstrated. However, as the acetonitrile concentration rises, its growth was severely restrained. Acetonitrile's inhibitory effect on this consortium's development rate is modeled in this work using the Luong, Aiba, Haldane, Hans-Levenspiel, Yano, Teissier and Monod models. Statistical evaluations indicated that the most suitable kinetic model to fit the growth rate on acetonitrile was the Teissier-Edwards’s model. The computed values for the Teissier constants like maximal reduction rate (max), half saturation constant for maximal degradation (Ks) and half inhibition constant (Ki) were 0.934 1/H (95% confidence interval 0.301 to 1.567), 1.504 g/L (95% confidence interval 0.877 to 2.131), and 4.574 g/L (95% confidence interval 2.764 to 6.383), respectively. The parameters obtained from this study will be beneficial in acetonitrile biodegradation works.

Due to the fact that it breaks down into acrylamide over time, polyacrylamide is one of the most important sources of acrylamide in soil. As a strategy for bioremediation, the breakdown of acrylamide by the action of microbes has seen a gradual but consistent increase in attention all over the world. A previously isolated molybdenum-reducing bacterium with amide-degrading capability was further identified on significant parameters contributing to optimized growth on acrylamide using a two-level factorial design in this study. The two-level factorial design was adopted in the screening of five independent factors influencing the growth of the bacterium on acrylamide. These factors include pH, temperature, incubation time, acrylamide concentration and glucose concentration. The two-factor factorial design was successful in finding important contributing parameters in the growth of this bacterium on acrylamide, which were acrylamide concentration, pH and incubation time (p

In ruminants, even trace amounts of molybdenum can be lethal. In areas with high pollution, molybdenum levels in soil and mine tailings can exceed 20,000 ppm. Bioremediation of molybdenum can be challenging when toxic mercury is also present. This research presents a novel approach using dialysis tubing and the molybdenum-reducing activity of Enterobacter sp. strain Dr. Y13 for molybdenum removal from aqueous solutions. Molybdenum blue (Mo-blue), produced during enzymatic reduction, is insoluble in dialysis tubing and this can be a twofold advantage as a method of removal and as a method to protect bacterial cells from heavy metal inhibition, especially mercury. In this experiment, we assess the toxicity-shielding effect of dialysis tubing for molybdenum reduction to Mo-blue by this bacterium in the presence of mercury. As the concentrations of mercury were increased, both free and immobilized cells were strongly inhibited. Modelling using the dissociationone phase exponential decay model gave an IC50 value for the immobilized form of 0.1107 mg/L (95% confidence interval from 0.073 to 0.217 while the IC50 value for the free cell system was 0.023 mg/L (95% C.I. from 0.019 to 0.028). Since the confidence interval for the IC50 values did not overlap, the immobilized system gave better protection from mercury than the free cell system. Toxicity to free cells was higher than toxicity to cells trapped in dialysis tubes, suggesting that trapping Mo-reducing cells may be an effective strategy for bioremediation of water or wastewater contaminated with multiple heavy metals.

Sodium dodecyl sulfate (SDS) or sodium lauryl sulfate (SLS) is a common anionic surfactant found in various cleaning and personal hygiene products. It has both a polar "headgroup" and a hydrocarbon tail, giving it amphiphilic properties that make it effective as a detergent. However, this also makes it a major pollutant in aquatic environments. Researchers have studied the biodegradation of SDS by microorganisms, particularly bacteria, as a potential cleanup method. It has been found that mercury can significantly inhibit the degradation of SDS by the Serratia marcescens strain DRY6 bacteria. At different mercury concentrations, the bacteria exhibited sigmoidal growth with lag times of 7 to 10 hours, but overall growth was decreased with higher mercury concentrations, with a concentration of 1.0 g/L virtually stopping all growth. A modified Gompertz model was used to calculate growth rates at various mercury concentrations, and these rates were then modeled using five different models: modified Han-Levenspiel, Wang, Liu, modified Andrews, and Amor. Only three of the models (Wang, modified Han-Levenspiel, and Liu) were able to accurately fit the curve, with the Wang model performing the best statistically. The Wang model yielded estimates of 0.216 (95% confidence interval: 0.193 to 0.239) for the critical heavy metal ion concentration, 1.05 (95% confidence interval: 0.938 to 1.167) for the maximum growth rate, and 0.389 (95% confidence interval: 0.148 to 0.636) for the empirical constant , represented by Ccrit, max and m, respectively.

Acetamiprid is a kind of broad-spectrum systemic pesticide that works on the nicotinic acetylcholine receptor. This chemical disrupts the transmission of a signal and causes a buildup of neurotransmitters, which leads to pests being paralyzed and eventually dying as a result. The calibration curve for the detection of acetamiprid utilizing a gold nanoparticle-based visual aptasensor showed a sigmoidal shape profile; hence, the 5-PL or 4-PL model should be used to fit the data rather than a linear model. The result of the error function analysis shows that the simpler 4-PL model is more reliable having smaller AICc, R2 and adjR2, values whilst the other error functions such as RMSE, BIC and HQF, BF and AF values indicated that the 5-PL model shows that the 5-PL model was marginally superior to the 4-PL. As the 95% confidence interval overlap, the IC50 values were deemed not significantly different, and when this occur, based on Occam’s razor, the model having a lower number of parameters, which was 4-PL, should be chosen instead. The 4-PL equation produced a value for the LOD of 0.159 mM, and the confidence interval for 95 percent of the results ranged from 0.132 to 0.177. According to the first study, the LOD was 3.81 mM, and the calculated LOD using 4-PL model with pooled standard deviations was much more sensitive. This indicates that utilizing only the linear portion of a sigmoidal curve to report the LOD values gave a less sensitive value than it should be.

Acrylamide is often used to strengthen soil structure and usually leachate from this application forms a major source of acrylamide pollution in the environment. The soil matrix means physicochemical methods of removal will be costly if not difficult. Bioremediation using acrylamide-degrading bacteria is an appealing technique. In this investigation, a previously isolated molybdenum-reducing bacterium with the ability to degrade amides was discovered based on critical characteristics contributing to optimal growth on acrylamide utilizing a two-level factorial design. Five independent parameters that influence the growth of the bacterium on acrylamide were evaluated using a two-level factorial design. Among these variables are pH, temperature, incubation period, acrylamide content, and glucose concentration. The two-factor factorial design was successful in identifying significant contributing parameters to the growth of this bacterium on acrylamide, namely acrylamide concentration, pH, and incubation time, which can be further otpimized using RSM in future studies. Using ANOVA, Pareto's chart, perturbation's plot, and other diagnostic plots, the significant contributing factors or parameters were examined. Half-normal, Cook's distance, residual vs runs, leverage versus runs, Box-Cox, DFFITS, and DFBETAS diagnostic plots all supported the two-level factorial result. This work was conducted using acrylamide concentrations well within the known tolerance range of most acrylamide-degrading bacteria. Incubation time is an expected consequence, as longer incubation time permits more growth. The majority of acrylamide-degrading microorganisms thrive under near-neutral circumstances, as indicated by the results of our investigation, which are consistent with previous literature trends.

Acrylamide is often used in soil stabilization works. It is a neurotoxin and leachate from such stabilization works contaminate soils all around the world. E. cloacae strain UPM2021a which had been previously isolated and demonstrated the ability to degrade acrylamide was further studied for its critical parameters contributing to the optimum growth of acrylamide. The Box-Behnken design was utilized in optimizing the three previously identified significant components (pH, incubation time and acrylamide concentration). Of the three factors, acrylamide and pH were the significant factors. The response surface plot exhibited evidence of interactions. Predicted optimal conditions were determined using the "Numerical Optimisation" toolbox of the Design Expert software. Two optimal conditions were tested. The model predicted a maximum growth of 10.686 (95% C.I., 10.458 to 10.913) which was verified through experimental results with a growth of 11.257 (95% C.I., 11.051 to 11.462) with the actual results being near to the predicted values but was significantly higher than the predicted values. The second numerical optimization gave a solution with a predicted maximum growth of 9.305 log CFU/mL (95% C.I. from 9.011 to 9.614) which was verified through experimental results with a growth of 9.978 log CFU/mL (95% C.I. from 9.830 to 10.126) with the actual results were also significantly higher than the predicted values. This means that other methods which employ more runs such as CCD or a different optimization approach such as Artificial Neural Network may be employed in the future to close the difference between the model predicted and actual experimental values. Despite this, the RSM exercise gave far better growth on acrylamide than OFAT with a higher response of about 2 log CFU/mL unit indicating the utility of RSM over OFAT in the optimization of growth of this bacterium on acrylamide.

In addition to its use as a pesticide, the chemical compound known as 2,4-dinitrophenol (2,4-DNP) is also utilized in the creation of wood preservatives and colors. Symptoms of acute (short-term) exposure to 2,4-DNP in humans include nausea or vomiting, sweating, headaches, disorientation, and a loss of weight. This type of exposure occurs when the substance is consumed orally. There are a few different models that may be used to simulate the growth rate of microorganisms on a variety of different medium at a range of temperatures. These models can be found online. One of the models that is employed the most frequently is the Arrhenius model, in part because it has a limited number of parameters. The development and metabolic activities of bacteria on the substrates they are grown on are commonly influenced by temperature. Temperature can also affect the growth of germs. Microbes are extremely sensitive to changes in temperature because of their small size. A discontinuous apparent activation energy with a chevron-like graph was used in order to describe the growth of a 2,4-dinitrophenol-degrading bacterium on 2,4-dinitrophenol. The break point of the graph was set at 28.05 °C. This was done so that the development of the bacterium could be described. Following the conclusion of the regression analysis, two temperature ranges for activation were determined. These temperature ranges were 20-27 °C and 30-42 °C, and their associated activation energies were 41.72 and 84.72 kilojoules per mole, respectively. It was anticipated that the Q10 value would be 2.905 and that the theta value would be 1.11 when considering the temperature range that was considered (30-42 °C). Due to the all-encompassing scope of this study, it is particularly useful for forecasting the effect of temperature on the breakdown and fate of 2,4-dinitrophenol during bioremediation.

Several models can be used to mimic the temperature-dependent growth rate of microorganisms on different media. Arrhenius is a popular model because of its small number of parameters. Microbial growth and metabolic activity on their substrates are generally affected by temperature. Microbes are vulnerable to temperature changes because of their small size. With a chevron-like discontinuous graph of apparent activation energy and a breakpoint, growth on diesel by Alcaligenes sp. YLA11 is described showing a breakpoint at 28.05 °C. Regression analysis resulted in two activation energies: 20–27 °C and 30–42 °C with the activation energies of 41.72 kJ/mol and 84.72 kJ/mol, respectively. For the examined temperature range (30-42 °C), a Q10 value of 2.905 and a theta value of 1.11 was calculated. Predicting the breakdown of diesel and its movement during bioremediation is an output that can be predicted by parts of this study.

Text in English ; Abstract: English and Turkish Includes bibliographical references (leaves 48-51) x, 52 leaves According to UNIDO (United Nations Industrial Development Organization) and TRTA (Trade-Related Technical Assistance Program), Pakistan's contribution to global fan trade is barely 1.3 %. The industry has experienced rapid expansion in recent years, but it is plagued by low productivity, outdated equipment, and a lack of knowledge. Because these institutions are opposed to change, Pakistan's fan business cannot compete with its overseas counterparts. Supply chain management methods have been shown in studies to increase a firm's overall performance by boosting competitive advantage and more efficient production. Supply chain management at the top level could improve results and improve organizational performance. The objective of this thesis is to explore the effects of supply chain management strategies on the performance of the organization of fan manufacturing SMEs in Pakistan. A questionnaire was given to 120 different fan manufacturing companies for data collection purposes, with an 83.33 percent response rate. The findings suggest that strategic supplier partnerships and supply chain management methods improve organizational performance. These findings show that many SMEs in the fan manufacturing industry are aware of supply-chain strategies to manage and employ them to improve their companies' performance. It is the first research in Pakistan about the influence of supply chain management practices on the organizational performance of fan manufacturing SMEs, to the best of my knowledge. As a result, this research is contributing to the field of supply chain management. Furthermore, it serves as a foundation for Pakistan's industrial sector, particularly the fan industry, in terms of supply chain management. UNIDO (Birleşmiş Milletler Endüstriyel Kalkınma Örgütü) ve TRTA'ya (Ticaretle İlgili Teknik Yardım Programı) göre, Pakistan'ın küresel fan ticaretine katkısı sadece % 1,3'tür. Endüstri son yıllarda hızlı bir genişleme yaşadı, ancak düşük üretkenlik, modası geçmiş ekipman ve bilgi eksikliği ile boğuşuyor. Bu kurumlar değişime karşı olduğu için, Pakistan fan endüstrisi denizaşırı meslektaşlarıyla rekabet edemez. Tedarik zinciri yönetimi yöntemleri, rekabet avantajını ve daha verimli üretimi artırarak bir firmanın genel performansını artırmaya yönelik çalışmalarda gösterilmiştir. En üst düzeyde tedarik zinciri yönetimi, sonuçları iyileştirebilir ve organizasyonel performansı artırabilir. Bu tezin amacı, tedarik zinciri yönetimi stratejilerinin Pakistan'daki fan imalat KOBİ'lerinin organizasyonunun performansı üzerindeki etkilerini araştırmaktır. Veri toplama amacıyla 120 farklı fan üreticisi şirkete anket uygulandı ve yanıt oranı yüzde 83,33 oldu. Bulgular, stratejik tedarikçi ortaklıklarının ve tedarik zinciri yönetimi yöntemlerinin organizasyonel performansı artırdığını göstermektedir. Bu bulgular, fan imalat endüstrisindeki birçok KOBİ'nin, şirketlerinin performansını artırmak için bunları yönetmek ve kullanmak için tedarik zinciri stratejilerinin farkında olduğunu göstermektedir. Bu çalışma, Pakistan'da tedarik zinciri yönetimi uygulamalarının fan üretimi KOBİ'lerinin organizasyonel performansı üzerindeki etkisi hakkındaki ilk araştırmadır. Sonuç olarak, bu araştırma tedarik zinciri yönetimi alanına katkıda bulunmaktadır. Ayrıca, Pakistan'ın sanayi sektörü, özellikle de fan endüstrisi için tedarik zinciri yönetimi açısından bir temel oluşturmaktadır. INTRODUCTION LITERATURE REVIEW Strategic partnership with suppliers (SPS) Internal supply chain practices (ISCP) Customer relationship management (CRM) /Level of information sharing Supply Chain Management Practices (SCMPs) Organizational performance (OP) RESEARCH METHODOLOGY Research Methodology Theoretical Framework Research Design Population Frame Sampling Technique Sample size Data collection Measurement scale Hypothesis Data Analysis Validity Analysis Reliability Analysis Descriptive Statistics Strategic Partnership with Suppliers Internal Supply Chain Management Practices Customer Relationship Management Supply Chain Practices Organization Performance Correlation Analysis Correlation Analysis amongst OP and SCM practices Simple Linear Regression Strategic Partnership with Suppliers Internal Supply Chain Management Customer Relationship Management Supply Chain Practices Multiple Regression Analysis RESULTS AND CONCLUSIONS Results and Conclusion Discussion Limitations Conclusion Recommendations Future Research

Online shopping platforms “Draz.pk,” “Homesopping.pk,” and “Telemart.pk,” were the most often used online stores in Pakistan. E-commerce platforms have not achieved their complete objectives, because they are faced with many usability issues. It is recommended that an evaluation of the usability of e-commerce platforms should be explored through different usability scales. This research study evaluates the usability of e-commerce platforms in Pakistan. In this research study, three e-commerce platforms were selected for usability evaluation. For this purpose total of 15 users were selected and performed the System Usability Scale method of assessing the usability. The result of the System Usability Scale method indicated usability of the “Homesopping.pk” and “Telemart.pk” was less than below 70%, which indicated that these websites need to improve the user interface. Five expert evaluators were also selected for Heuristic evaluation to perform on “Homesopping.pk” to find out the usability issues.

Supplemental material, sj-pdf-1-jva-10.1177_11297298231185793 for Surgical and endovascular assisted maturation procedures improve cannulation after arteriovenous fistula creation, but not after arteriovenous graft placement by Muhammad Saad Hafeez, Rabih A Chaer, Mohammad H Eslami, Othman M Abdul-Malak and Theodore H Yuo in The Journal of Vascular Access

Supplemental material, sj-pdf-2-jva-10.1177_11297298231151365 for Comparing post-maturation outcomes of arteriovenous grafts and fistulae by Muhammad Saad Hafeez, Mohammad H Eslami, Rabih A Chaer and Theodore H Yuo in The Journal of Vascular Access

Supplemental material, sj-pdf-2-jva-10.1177_11297298231151365 for Comparing post-maturation outcomes of arteriovenous grafts and fistulae by Muhammad Saad Hafeez, Mohammad H Eslami, Rabih A Chaer and Theodore H Yuo in The Journal of Vascular Access

Supplemental material, sj-pdf-1-jva-10.1177_11297298231151365 for Comparing post-maturation outcomes of arteriovenous grafts and fistulae by Muhammad Saad Hafeez, Mohammad H Eslami, Rabih A Chaer and Theodore H Yuo in The Journal of Vascular Access

The increasing use of cypermethrin in agricultural fields, household and industrial applications for effective pest control had increased the global burden of the pollutant over the years. Consequently, there is an urgent need to devise techniques to eliminate this pollutant from the environment. A bacterium capable of degrading cypermethrin has been successfully screened and characterized. The bacterium was grown in a mineral salt medium (MSM) supplemented with cypermethrin as its sole carbon and energy source at an optimum pH 7.5, temperature 40 ºC, a carbon source concentration of 4 g/L, optimum incubation time of 24 h and an inoculum size of 400 µL. The potential of Morganella sp. to degrade cypermethrin makes it an important instrument for the degradation of cypermethrin. This knowledge may be useful for the optimization of environmental conditions for cypermethrin bioremediation and important for detoxification of cypermethrin polluted sites.

One of the beneficial roles of the microbial population is their ability to convert toxic herbicides to lesser toxic compounds such as water and carbon (IV) oxide. Paraquat which is an acutely toxic herbicide is used on farmlands and has been found to affect human health. This study was aimed at characterizing bacteria with the potential to degrade paraquat. Previously isolated bacteria from culture collection labelled A-F were screened for their potential to degrade and utilized paraquat as the sole carbon source in Bushnell Hass agar media. Of the six isolates, isolate E (Morganella sp.) was observed to have the highest growth and tolerance to paraquat after 72 h of incubation at 37 ºC. Characterization study revealed that Morganella sp. can utilize and grow with optimum conditions of pH 6.5, the temperature of 30 ºC and can tolerate up to 400 mg/L paraquat concentration with an increase in growth as inoculum size increases. Thus, these findings showed that Morganella sp. can degrade toxic paraquat to a less toxic form and therefore can be a good isolate for the future bioremediation process of the pollutant.

Butachlor is a chloroacetanilide herbicide that is selective in action and commonly used for pre-emergence control of weeds. It is believed to have range of toxicity from acute to chronic and also can cause DNA strand breaks and chromosomal aberrations in humans. This study was aimed at characterizing the potential of previously isolated bacteria for butachlor degradation. The isolates from culture collection, labelled A-F were screened for butachlor degradation on Bushnell Hass agar media with butachlor as a sole carbon source. Isolate A (molybdenum-reducing and aniline-degrading Pseudomonas sp.) was observed to grow best and tolerated the highest concentration of butachlor supplemented in the media after 72 h of incubation at 37 ℃. Characterization study revealed that the Pseudomonas sp. can utilize and grow with butachlor at optimum pH between 6.0 - 6.5, temperature between 30 – 37 ℃ and can tolerate up to 600 mg/L butachlor concentration with increase in growth as inoculum size increases. Additionally, this bacterial strain shows no lag phase regardless of the concentration of the herbicide used and reach its maximum growth after 24 h of incubation. The ability of this isolate to tolerate and utilize butachlor as sole carbon source makes it suitable for future bioremediation of this toxicant.

This study aimed to isolate and identify biosurfactant producing and diesel alkanes degrading bacteria. For this reason, bacteria isolated from the diesel contaminated site were screened for their potential to produce biosurfactants and degrade diesel alkanes. Primary selection of diesel degraders was carried out by using conventional enrichment culture technique where 12 bacterial strains were isolated based on their ability to grow on minimal media supplemented with diesel as sole carbon source, which was followed by qualitative screening methods for potential biosurfactant production. Isolate B11 was the only candidate that shows positive signs for drop collapse, foaming, haemolytic test, oil displacement of more than 22 ± 0.05 mm, and emulsification (E24) of 14 ± 0.30%. The effect of various culture parameters (incubation time, diesel concentration, nitrogen source, pH and temperature) on biodegradation of diesel was evaluated. The optimum incubation time was confirmed to be 120 days for isolates B11, the optimum PH was confirmed as 8.0 for the isolate, Similarly, the optimum temperature was confirmed as 35oC. In addition, diesel oil was used as the sole carbon source for the isolates. The favourable diesel concentration was 12.5 % (v/v) for the isolate. The isolate has shown degradative ability towards Tridecane (C13), dodecane, 2, 6, 10-trimethyl- (C15), Tetradecane (C14), 2,6,10-Trimethyltridecane (C16), Pentadecane (C15). It degraded between 0.27% - 9.65% individual diesel oil alkanes. The strain has exhibited the potential of degrading diesel oil n-alkanes and was identified as Alcaligenes species strain B11 (MZ027604) using the 16S rRNA sequencing.

Microorganisms play an integral role in detoxification and removal of toxic compounds from the environment. Aniline is the simplest aromatic amine, consisting of a phenyl group attached to an amino group that is used as herbicide to control weeds. Aniline is detrimental to both environment and health. In this research, six previously isolated bacteria (isolate A-F) were screened on Bushnell Hass media for their potential to grow and utilize aniline as a sole carbon source. Isolate A (Pseudomonas sp.) was found to tolerate and grow best with aniline sole source of carbon. Optimum conditions for aniline degradation by this isolate were found to be pH 6.0, temperature between 30 and 37 °C, inoculums size of 600 μL, aniline concentration of 200 mg/L and incubation time of 96 h. The capacity of this isolate to reduce toxic aniline to less toxic form is novel and makes the bacterium important instrument for bioremediation of this pollutant.

The United States Environmental Protection Agency (USEPA) has identified 16 substances as priority polycyclic aromatic hydrocarbons (PAHs) that are harmful to humans, including anthracene and phenanthrene. These substances are pervasive pollutants introduced into the environment through anthropogenic and natural processes, causing ecological concerns and necessitating the quest for new strains capable of biodegrading these toxins. A novel strain of the genus Pseudomonas was isolated and molecularly identified based on partial 16S rRNA and phylogenetic analysis as Pseudomonas stutzeri strain BUK_BTEG1 from petrochemical contaminated soil. One factor at a time (OFAT) in Bushnell-Haas (BH) media was used to optimize the strain’s biodegradation conditions. The isolate could grow up to 600 mgL−1 and 400 mgL−1 of anthracene and phenanthrene as the sole carbon source at an optimum pH of 7.0 and 7.5 respectively, inoculum concentration of 4% (v/v), and temperature of 35°C during 72 hours of incubation. The strain could degrade phenanthrene and anthracene to a maximum of 99 and 72 percent, respectively, under ideal conditions. The breakdown products’ GC-MS analysis revealed the existence of the pathway’s main metabolites, catechol, salicylic acid, and derivatives of phthalic acid. The strain exhibits promising potential for use in the bio-cleansing of environments contaminated by PAHs.metabolites.

One of the strategic objectives of China is to increase renewable energy consumption by reducing non-renewable energy consumption. This motivates us to carefully investigate the asymmetric effects of financial deepening on renewable and non-renewable energy consumption for China, using annual data from 1990 to 2019. The results show that in China, a positive shock in bank deposits and broad money has a significant increasing effect on renewable energy consumption, while a negative shock in bank deposits and broad money has also a significant increasing effect on renewable energy consumption in the long-run. Moreover, positive change in bank deposits and broad money has an inverse impact on non-renewable energy consumption, while negative change has stimulating non-renewable energy consumption in long run. Thus, government and policymaker’s policies aimed at promoting financial deepening in China must be persistent and sustainable to foster renewable energy consumption.

The Internet of Things is a system of interconnected smart devices that can communicate with each other and with other devices over the Internet, with or without human-to-human or human-to-computer interaction. Although IoT devices, which have IPs, make living easier, they are also a threat to the security and privacy of people. This research work presents a solution to the problem of security in the network of IoT, based on the idea of implementing the blockchain in IoT. Blockchain is a decentralized technology that adds blocks at the end of the chain. It saves the hash value for every block, and corresponds to the previous block. The decentralized behavior of blockchain is best for IoT as an extensive network, because IoT must not have a single point of failure, and one entity must not decide what to do. All the capable storage devices will save the same data entered from any device, removing the risk of receiving altered data.

Social media influencers, as opposed to celebrities or public figures who are well-known through traditional media, are "ordinary individuals" who have become "online celebrities" through creating and posting content on social media. They frequently have some understanding of specific topics, including lifestyle, healthy living, travel, food, and fashion. This study attempts to provide "a clearer understanding of what drives the effectiveness of influencer marketing" in terms of their capacity to affect consumer brand attitudes, in accordance with past research. To accomplish the aforementioned, this study experimentally assesses a conceptual model examining how SMI power can influence consumer perceptions of the marketed brands. This research study is quantitative. For this study, researcher gathered the data from the populations of two twin cities Rawalpindi and Islamabad. As of 2022, the current population of Rawalpindi and Islamabad is 2,327,000 and 1,198.000. The main focus of this study is on the individuals who are directly or indirectly involve in the purchase of ready-to-wear clothes recommended by Social Media Influencers to see how Social Media Influencers (SMI) affect the brand experience of customer. Researchers collected the data by using the survey method through personal visits to respondents and used aConvenience sampling because in convenience sampling samplesare easy to collect. Before collecting data, it enables to refine your questionnaire through reliability of instrument. Cronbach’s alpha is used in the present study. Based on research results, Social Media Influencers have a greater effect on the perceived satisfaction of customers in the purchase of ready-to-wear clothing. Managers of Ready-to-wear clothing brands should pay attention to improving their expertise and authenticity especially if they intend to establish their business in ready-to-wear clothing. This research implies that SMIs performing high levels of expertise and authenticity are considered to have high perceived satisfaction. Comparatively, those with a low level of expertise and authenticity are considered to have low perceived satisfaction.

The optic nerve is surrounded by the same meningeal coverings that surround the brain. This anatomic relationship allows the use of Optic Nerve Sheath Diameter (ONSD) as a non-invasive, bedside estimate of elevated Intracranial Pressure (ICP). Despite the increasing research interest in ultrasonographic ONSD, it is not widely used clinically. This can be due to variability in ONSD measurements as identified by several meta-analyses that showed significant heterogeneity in ONSD measurement techniques. We propose that this heterogeneity is due to lack of consensus on ONSD measurement technique, which can cause variations in image acquisition and measurement. In this review, We will identify published ONSD imaging and measurement criteria through a scoping systematic review of ultrasound ONSD studies. We will use a piloted data sheet to extract ONSD imaging and measurement criteria. We will then use the output of the review to develop a checklist for ONSD Quality Criteria Consensus (ONSD QCC). This checklist will undergo further refinement in the future by using the modified Delphi method to reach expert consensus on ONSD quality criteria.

Introduction/aimsIt is unknown if patients with neuromuscular diseases prefer in-person or virtual telemedicine visits. We studied patient opinions and preference on virtual versus in-person visits, and the factors influencing such preferences.MethodsTelephone surveys, consisting of 11 questions, of patients from 10 neuromuscular centers were completed.ResultsFive hundred and twenty surveys were completed. Twenty-six percent of respondents preferred virtual visits, while 50% preferred in-person visits. Sixty-four percent reported physical interaction as "very important." For receiving a new diagnosis, 55% preferred in-person vs 35% reporting no preference. Forty percent were concerned about a lack of physical examination vs 20% who were concerned about evaluating vital signs. Eighty four percent reported virtual visits were sufficiently private. Sixty eight percent did not consider expenses a factor in their preference. Although 92% were comfortable with virtual communication technology, 55% preferred video communications, and 19% preferred phone calls. Visit preference was not significantly associated with gender, diagnosis, disease severity, or symptom management. Patients who were concerned about a lack of physical exam or assessment of vitals had significantly higher odds of selecting in-person visits than no preference.DiscussionAlthough neither technology, privacy, nor finance burdened patients in our study, more patients preferred in-person visits than virtual visits and 40% were concerned about a lack of physical examination. Interactions that occur with in-person encounters had high importance for patients, reflecting differences in the perception of the patient-physician relationship between virtual and in-person visits.

Heavy metals can be remediated using microorganism by altering the redox function i.e. reduction from more toxic oxidation state to non-toxic one. Molybdenum reduction to molybdenum blue by bacteria is an emerging tool for remediation of the metal. Mathematical modelling via nonlinear regression of the heavy metal’s reduction can yield important reduction parameters such as theoretical maximum reduction, specific reduction rate, and the lag period of reduction. Nonlinear regression can be utilized using various models such as logistic, Richards, Gompertz, Baranyi-Roberts, Schnute, Buchanan 3-phase, Von Bertalanffy and Huang with the best model yielding an underlying mechanistic property for the reduction. We demonstrate that the Baranyi-Roberts model was the best model in modelling the Mo-blue production curve of the bacterium Bacillus sp. strain Neni-10 based on statistical tests such as root-mean-square error (RMSE), corrected AICc (Akaike Information Criterion), adjusted coefficient of determination (R2), accuracy factor (AF) and bias factor (BF). The model parameters or constants obtained were maximum lag time (λ), Mo-blue production rate (μm), and maximal Mo-blue production (Ymax). The construction of secondary models will benefit greatly from the use of bacterial growth models to acquire realistic Mo-blue production rates. According to a literature search, this technique is wholly unique for molybdenum reduction to Mo-blue in particular, and in the heavy metals’ detoxification process in general. The results of this study have demonstrated the usefulness of these models in simulating Mo-blue synthesis in bacteria.

Azo dyes are the most common chemical family of dyes, with a wide range of structural and color variations. They account for up to 70% of yearly dye production. Azo dyes are one of the first man-made compounds, and they are still commonly used in the food and textile industries. The discharge of Azo dyes is undesirable not only because many Azo dyes and their breakdown products are toxic to aquatic life and mutagenic to people, but also because many Azo dyes and their breakdown products are harmful to aquatic life and mutagenic to humans. We report different primary kinetics models such as Huang, modified Gompertz, Buchanan-3-phase, modified Logistics, Baranyi-Roberts, modified Richards and Von Bertalanffy were used to get the best model for Candida tropicalis TL-F1 growth on different Azo dyes concentrations. The best model was found to be Buchanan-3-phase with the lowest values for AICc, RMSE and the highest value for adjusted R2. The AF and BF values were also excellent for the model with their values were the closest to 1.0. The poorest performance was found to be Baranyi-Roberts where it failed to model the growth curve. Baranyi-Roberts has the highest values for AICc, RMSE and the highest value for adjusted R2. The Buchanan-3-phase parameters such as Y0, λ, k and Ymax were found to be 0.290, 3.244, 0.543 and 3.825 respectively. These constant would provide insight for the actual Candida tropicalis TL-F1 growth curve.

During the current emergency of Pandemic disease of Covid-19, the importance of online learning strategy has much increased due to closure of schools, colleges and universities in most part of the globe. To evaluate the effectiveness of online learning, a statistical study has been conducted on the academic achievements of postgraduate students learned by online versus face-to-face learning modes. The statistical analysis of academic achievements of postgraduate students has been done by SPSS-20 statistical tool. The t-test analysis showed that the t-value was 0.549 and p-value was 0.583. The significance level for t-test analysis was 0.05. As, the p-value was more that 0.05 (p˃0.05) so, no significant relation has been found in the academic achievements of the students learned by online and face to face modes of learning. The null hypothesis (Ho) was proved true and the alternative hypothesis (H1) rejected. The reasons for no significant relation were abruptly shifting of learning modes from face-to-face to online, slow working of LMS accounts due to over burden, login and voice problems during the online classes. Overall, the students performed better in the online modes of learning. Some students performed good in face-to-face learning and performed poor in online modes of learning. So, to generalize, it is necessary to do more research on online modes of learning under regional context

The progress of the health sector in a sustainable manner is crucial for the development of human capital, a significant and vital driver of economic growth. Hence, we aim to investigate the impact of FinTech on health outcomes in Asian economies over the period 2007–2019. The empirical estimation of the study is based on the 2SLS and GMM techniques. The outcomes confirmed the negative impact of ATMs and Debit cards on the infant mortality rate in both 2SLS and GMM models. Whereas, ATMs and Debit cards positively impact the life expectancy of people living in Asian economies irrespective of the estimation technique. Similarly, the association between the Internet and infant mortality rate is negative; whereas, this association is positive in the context of the Internet and life expectancy both with 2SLS and GMM. From these findings, we can confirm that the amalgamation of technology and the financial sector helps to improve health outcomes in Asian economies. Therefore, the integration of FinTech into the health sector should be part and parcel of every health policy in emerging Asian economies.

The primal contribution of present research work is to analyze and predict the environmental degradation indicators for Pakistan; by the implications of the marginal impact of economic growth, ener...

Microbial heavy metals reduction has an important role in the biological system and in environmental metals recycling to remove its toxic effects in soil and wastewater. A molybdenum-reducing bacterium with the potential to reduce toxic hexavalent molybdenum to colloidal molybdenum blue (Mo-blue) was isolated from agricultural land in Northwest-Nigeria. The Gram’s stain and microscopic examination reveal that the isolate is a Gram-negative, however, phylogenetic analysis of the 16S rRNA identifies the isolate as Pseudomonas sp. Molybdenum reduction in this bacterium is optimally supported by glucose at 1.0% (w/v). The optimum phosphate and molybdate concentrations supporting molybdate reduction were between 3.5 and 7.5 mM for phosphate and 100 mM molybdate. Molybdate reduction is optimum at 37 ᵒC and pH between 6.5 and 7.5. The capacity of this isolate to reduce toxic molybdenum to a less toxic form is novel and makes the bacterium an important instrument for bioremediation of this pollutant.

The novel corona virus (2019-nCoV) infection has spread rapidly to other provinces and neighbouring countries since the emergence of the first cases at Wuhan, China. Estimation of the death cases by mathematical modelling can help to determine the potential and severity of the outbreak and to provide critical information on the type and intensity of disease response. In this paper, we present different growth models such as Von Bertalanffy, Baranyi-Roberts, Morgan-Mercer-Flodin (MMF), modified Richards, modified Gompertz, modified Logistics and Huang in fitting and analyzing the epidemic trend of COVID-19 in the form of total number of death cases of SARS-CoV-2 in Brazil as of 15th of July 2020. The MMF model was found to be the best model with the highest adjusted R2 value with the lowest RMSE value. The Accuracy and Bias Factors values were close to unity (1.0). The parameters obtained from the MMF model include maximum growth of death rate (log) of 0.03 (95% CI from 0.02 to 0.028), curve constant (d) that affects the inflection point of 0.7057 (95% CI from 0.68 to 0.73) and maximal total number of death (ymax) of 17,619,760 (95% CI from 9,705,100 to 34,994,517). The MMF model predicted that the total number of death cases for Brazil on the coming 15th of August and 15th of September 2020 will be 132,787 (95% CI of 123,422 to 142,863) and 212,166 (95% CI of 192,578 to 233,746), respectively. The predictive ability of the model utilized in this study is a powerful tool for epidemiologist to monitor and assess the severity of COVID-19 in Brazil in months to come. However, as with any other model, these values need to be taken with caution due to the unpredictability of the COVID-19 situation locally and globally.

Synthetic chemicals are extremely harmful, particularly those man-made ones. Models are used to describe the behavior of microorganisms under different physical or chemical conditions such as temperature, pH, and water activity. Phenol is one of the potentially hazardous synthetic industrial contaminants capable of causing deteriorating effects in humans. In this paper, for the first time we present different kinetics models such as Von Bertalanffy, Baranyi-Roberts, modified Schnute, modified Richards, modified Gompertz, modified Logistics and the most recent Huang were used to get values for the above kinetic constants or parameters from simultaneous biodegradation of phenol from industrial effluents using immobilized Pseudomonas putida. All the curves present the best models with highest adjusted R2 value with the lowest RMSE and AICc value. The Accuracy and Bias Factors values were close to unity (1.0). Nearly all of the models best fit the curves indicating that Pseudomonas putida growth on phenol can be described mathematically the modelling parameters obtained can be utilized for predicting bioremediation of phenols in batch culture and perhaps in the future will be valuable in modelling growth eon industrial effluent containing phenol.

The current global COVID-19 pandemic is causing a lot of deaths and economic losses worldwide. The modelling of future death and cases is a very important aspect of managing the severity of the pandemic. In this paper, we demonstrated potential use of various growth models like modified Gompertz, Von Bertalanffy, Baranyi-Roberts, modified Logistics, Morgan-Mercer-Flodin (MMF), modified Richards and Huang in modeling the epidemic trend of COVID-19 in the form of total number of infection cases of SARS-CoV-2 in the United States as at 20th July 2020. The Morgan-Mercer-Flodin (MMF) model showed best fitting to the data set with least RMSE and AICc and the highest adjusted R2 values. The values for Accuracy and Bias Factors were closest to 1.0. Despite this, further statistical diagnosis of the data showed nonnormality with the residuals failing the runs and homoscedasticity tests. Interestingly, this was addressed by remodeling the data from day 132 onwards using the MMF model, which results in improving the statistical diagnosis. The fitting coefficients obtained include maximum growth rate (logmm) of 0.03 (95% CI 0.023 - 0.039), curve constant (d) that affects the inflection point of 1.42 (95% CI 1.304 - 1.540), lower asymptote value (b) of 6.454 (95% CI 6.451 - 6.456) and maximal total number of cases (ymax) of 7,906,786 (95% CI 6,652,732 - 10,839,269). The MMF model predicted that by 20th of August 2020 the total number of cases in the United States will be 5,560,168 (95% CI of 5,295,337 - 5,838,243), while the Fig. will rise to 6,366,506 (95% CI of 5,791,751 - 6,998,298) by 20th of September 2020. The predictive potential of the utilized model makes it a powerful tool for epidemiologist monitoring the severity of SARS-CoV-2 (COVID-19) in the United States in the near future. Although, predictions from this model as with any other model, need to be taken with caution due to unpredictable nature of COVID-19 situation locally and globally.

Chemical elements such as heavy metals significantly functions as trace elements but their bio-toxicity to human biochemical process poses a great concern for public health. The human exposure to heavy metals via food chain has been a documented risk factor for cancer development and other health-related implications. The levels of some carcinogenic (Chromium Cr; Cadmium Cd and Lead Pb) and non carcinogenic (Nickel Ni; Cobalt Co; Copper Cu and Zinc Zn) heavy metals in vegetables (Onion, Drumstick, Lettuce, Okra, and Carrot) grown in Sharada industrial area, Kano were evaluated. The human health risk implications were also determined by estimating the daily metal consumption, and calculating non cancer and cancer risks (Incremental Life Cancer Risk, ILCR and Target Hazard Quotients) using US-EPA probabilistic health risk assessment (US-EPA risk predicting model). The mean concentration of lead (Pb) ranged from 11.21±0.55 µg/g in Okra to 16.84±0.86 µg/g in onion. Carrot had the highest concentration of chromium (65.10±3.20 µg/g). The levels of various heavy metals found in the studied vegetables/plants differ generally with plant species. The predictive values of human developing cancer disease from the incessant intake of studied plant/vegetables was found higher than the standard threshold risk boundary set by US-EPA, (>10-4) for Cr, Pb, and Cd. The non cancer health risk values also predicted Pb, Cr and Cd as the dominant metal contaminants of the vegetables with the Health Risk Index greater than one (>1), while Ni, Co, and Zn showed safe quotients. Among the studied vegetables/plants, carrot has predicatively, the highest cancer risk (∑ILCR 1.25 with chromium contributing 92%), followed by lettuce, onion, Moringa oleifera, and okra (Carrot> Lettuce > Onion > Moringa > Okra). It is, therefore, suggests that the industrial area is unsafe for irrigation due to the heavy metals pollutions of the soil and irrigation water and the risk of high consumption of vegetables grown exposes the population to incremental cancer risks potential among others.

Supplemental material, sj-docx-1-ine-10.1177_15910199221138139 for Multicenter investigation of technical and clinical outcomes after thrombectomy for Proximal Medium Vessel Occlusion (pMeVO) by frontline technique by Jonathan A Grossberg, Reda M Chalhoub, Sami Al Kasab, Dominika Pullmann, Pascal Jabbour, Marios Psychogios, Robert M Starke, Adam S Arthur, Kyle M Fargen, Reade De Leacy, Peter Kan, Travis Dumont, Ansaar Rai, Roberto J Crosa, Kareem E Naamani, Ilko Maier, Nitin Goyal, Stacey Quintero Wolfe, C Michael Cawley, J Mocco, Muhammad Hafeez, Brian M Howard, Laurie Dimisko, Hassan Saad, Christopher S Ogilvy, R Webster Crowley, Justin Mascitelli, Isabel Fragata, Michael Levitt, Alejandro M Spiotta and Ali M Alawieh in Interventional Neuroradiology

Supplemental material, sj-docx-1-ine-10.1177_15910199221138139 for Multicenter investigation of technical and clinical outcomes after thrombectomy for Proximal Medium Vessel Occlusion (pMeVO) by frontline technique by Jonathan A Grossberg, Reda M Chalhoub, Sami Al Kasab, Dominika Pullmann, Pascal Jabbour, Marios Psychogios, Robert M Starke, Adam S Arthur, Kyle M Fargen, Reade De Leacy, Peter Kan, Travis Dumont, Ansaar Rai, Roberto J Crosa, Kareem E Naamani, Ilko Maier, Nitin Goyal, Stacey Quintero Wolfe, C Michael Cawley, J Mocco, Muhammad Hafeez, Brian M Howard, Laurie Dimisko, Hassan Saad, Christopher S Ogilvy, R Webster Crowley, Justin Mascitelli, Isabel Fragata, Michael Levitt, Alejandro M Spiotta and Ali M Alawieh in Interventional Neuroradiology

Supplemental material, sj-docx-1-ine-10.1177_15910199221118148 for Safety and efficacy of the surpass streamline for intracranial aneurysms (SESSIA): A multi-center US experience pooled analysis by Juan Vivanco-Suarez, Alan Mendez-Ruiz, Mudassir Farooqui, Kimon Bekelis, Justin A Singer, Kainaat Javed, David J Altschul, Johanna T Fifi, Stavros Matsoukas, Jared Cooper, Fawaz Al-Mufti, Bradley Gross, Brian Jankowitz, Peter T Kan, Muhammad Hafeez, Emanuele Orru, Andres Dajles, Milagros Galecio-Castillo, Cynthia B Zevallos, Ajay K Wakhloo and Santiago Ortega-Gutierrez in Interventional Neuroradiology