Standard Test Research Articles

Identification and antimicrobial susceptibility profiles of Staphylococcus species isolated from raw cow milk, and swabs in smallholder dairy farms in Meta district, Eastern Ethiopia

BackgroundThe safety of milk production in terms of foodborne infections is a worldwide issue, particularly in developing countries where production is often unhygienic. A cross-sectional study was conducted from December 2018 to August 2019 in the Meta District of Eastern Hararghe Zone, Oromia Regional State, Ethiopia. We aim to assess milk hygiene practices among smallholder dairy farmers, estimate the prevalence of Staphylococcus aureus in raw cow milk and swabs, assess associated risk factors, and the antimicrobial susceptibility test of S. aureus isolates. Face-to-face interviews with 30 respondents randomly selected from smallholder dairy farmers were used to assess the potential risk factors for S. aureus contaminations in milk. A total of 177 samples were examined using standard microbiological testing. The disc diffusion technique was also employed to assess the antibiotic susceptibility of the isolates. The data was analyzed using STATA® version 14.0 statistical software.ResultsAccording to the milk hygiene assessment, 80% of respondents did not wash cow udder before milking, did not use detergent to clean milk containers, and did not keep milk refrigerated before consumption or sale, while 63.3% of milk consumers ingested raw milk. They had never heard of staphylococci foodborne disease. Likewise, the overall prevalence of S. aureus was 12.42% (95%CI: 8.32–18.98). The prevalence of S. aureus in udder milk, equipment swabs, and milkers’ hands was 18.8%, 26.7%, and 30%, respectively. The prevalence of S. aureus in milk is significantly associated with age, and mastitis history (p < 0.05). Moreover, old and mastitis positive animals were eight (OR: 8.40; 95%CI: 1.68–41.89) and four (OR: 4.33; 95%CI: 1.37–13.66) times more likely to be infected by S. aureus than adult, and mastitis negative animal. The isolates were resistant to penicillin G (97.4%) and tetracycline (69.2%) whereas susceptible to kanamycin, streptomycin, vancomycin, and cefotaxime, at 84.6%, 71.8%, 64%, and 58.8%, respectively.ConclusionThis study revealed the presence of antimicrobial-resistant patterns of S. aureus on commonly used antibiotics, as well as inadequate milk handling practices in the study area. Thus, awareness should be created on proper milk handling and hygiene as well as appropriate uses of antibiotics should be encouraged.

Predictive capacity of fetal pancreatic circumference for gestational diabetes mellitus.

To assess the capacity of fetal pancreatic size, before standard blood testing for screening and diagnosis, to predict maternal gestational diabetes mellitus (GDM). This was a retrospective cohort study of low-risk pregnant women recruited during routine second-trimester fetal anatomical screening at 20-25 weeks' gestation at two ultrasound units in Israel between 2017 and 2020. The predictive performance of fetal pancreatic circumference ≥ 80th and ≥ 90th centiles and glucose challenge test (GCT) was examined for the outcome of GDM. The independent-samples t-test was used to compare mean pancreatic circumference centile between pregnancies with GDM and those without GDM. Diagnostic performance was evaluated with 2 × 2 contingency tables and receiver-operating-characteristics (ROC) curves. Overall, 195 women were selected for statistical analysis. Twenty-four (12.3%) women were diagnosed subsequently with GDM. The mean ± SD pancreatic circumference centile was significantly higher in the GDM group compared with the non-GDM group (82.4 ± 14.6 vs 62.8 ± 27.6; P < 0.001). The pancreatic circumference centile was correlated positively with the estimated fetal weight centile (Pearson's coefficient, 0.243; P = 0.001). The 80th centile cut-off for pancreatic circumference had the highest sensitivity (70.8%) and positive predictive value (23.3%) for future maternal GDM, with the best trade-off between sensitivity and specificity achieved at the 75th centile cut-off (sensitivity, 79%; specificity, 60%). The GCT had better specificity (90.2%) and negative predictive value (97.9%) compared with both cut-offs in pancreatic circumference. The area under the ROC curve was higher for pancreatic circumference compared with GCT (0.71 vs 0.64) and only the former was statistically significant (P = 0.001). Fetal pancreatic circumference has a higher positive predictive capacity compared with GCT. Measuring pancreatic circumference can identify pregnancies at high risk for maternal GDM, thereby promoting earlier diagnosis and treatment, decreasing the time period during which the fetus is exposed to high maternal glucose levels and improving infant outcome. © 2024 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

A light-weight and generalizable deep learning model for the prediction of COVID-19 from chest X-ray images

The detection of coronavirus disease (COVID-19) using standard laboratory tests, such as reverse transcription polymerase chain reaction (RT-PCR), is time-consuming. Complex medical imaging problems are currently being solved using machine learning and deep learning techniques. Our proposed solution utilizes chest radiography imaging techniques, which have shown to be a faster alternative for detecting COVID-19. We present an efficient and lightweight deep learning architecture for identifying COVID-19 using chest X-ray images which achieve 99.81% accuracy in intra-database testing and 100% accuracy in cross-validation testing on a separate data set. The results demonstrate the potential of our proposed model as a reliable tool for COVID-19 diagnosis using chest X-ray images, which can have a significant impact on improving the efficiency of COVID-19 diagnosis and treatment.

Machine Learning Allowed Interpreting Toxicity of a Fe-Doped CuO NM Library Large Data Set─An Environmental In Vivo Case Study.

The wide variation of nanomaterial (NM) characters (size, shape, and properties) and the related impacts on living organisms make it virtually impossible to assess their safety; the need for modeling has been urged for long. We here investigate the custom-designed 1-10% Fe-doped CuO NM library. Effects were assessed using the soil ecotoxicology model Enchytraeus crypticus (Oligochaeta) in the standard 21 days plus its extension (49 days). Results showed that 10%Fe-CuO was the most toxic (21 days reproduction EC50 = 650 mg NM/kg soil) and Fe3O4 NM was the least toxic (no effects up to 3200 mg NM/kg soil). All other NMs caused similar effects to E. crypticus (21 days reproduction EC50 ranging from 875 to 1923 mg NM/kg soil, with overlapping confidence intervals). Aiming to identify the key NM characteristics responsible for the toxicity, machine learning (ML) modeling was used to analyze the large data set [9 NMs, 68 descriptors, 6 concentrations, 2 exposure times (21 and 49 days), 2 endpoints (survival and reproduction)]. ML allowed us to separate experimental related parameters (e.g., zeta potential) from particle-specific descriptors (e.g., force vectors) for the best identification of important descriptors. We observed that concentration-dependent descriptors (environmental parameters, e.g., zeta potential) were the most important under standard test duration (21 day) but not for longer exposure (closer representation of real-world conditions). In the longer exposure (49 days), the particle-specific descriptors were more important than the concentration-dependent parameters. The longer-term exposure showed that the steepness of the concentration-response decreased with an increased Fe content in the NMs. Longer-term exposure should be a requirement in the hazard assessment of NMs in addition to the standard in OECD guidelines for chemicals. The progress toward ML analysis is desirable given its need for such large data sets and significant power to link NM descriptors to effects in animals. This is beyond the current univariate and concentration-response modeling analysis.

Deep Learning Artificial Intelligence Predicts Homologous Recombination Deficiency and Platinum Response From Histologic Slides.

Cancers with homologous recombination deficiency (HRD) can benefit from platinum salts and poly(ADP-ribose) polymerase inhibitors. Standard diagnostic tests for detecting HRD require molecular profiling, which is not universally available. We trained DeepHRD, a deep learning platform for predicting HRD from hematoxylin and eosin (H&E)-stained histopathological slides, using primary breast (n = 1,008) and ovarian (n = 459) cancers from The Cancer Genome Atlas (TCGA). DeepHRD was compared with four standard HRD molecular tests using breast (n = 349) and ovarian (n = 141) cancers from multiple independent data sets, including platinum-treated clinical cohorts with RECIST progression-free survival (PFS), complete response (CR), and overall survival (OS) endpoints. DeepHRD predicted HRD from held-out H&E-stained breast cancer slides in TCGA with an AUC of 0.81 (95% CI, 0.77 to 0.85). This performance was confirmed in two independent primary breast cancer cohorts (AUC, 0.76 [95% CI, 0.71 to 0.82]). In an external platinum-treated metastatic breast cancer cohort, samples predicted as HRD had higher complete CR (AUC, 0.76 [95% CI, 0.54 to 0.93]) with 3.7-fold increase in median PFS (14.4 v 3.9 months; P = .0019) and hazard ratio (HR) of 0.45 (P = .0047). There were no significant differences in nonplatinum treatment outcome by predicted HRD status in three breast cancer cohorts, including CR (AUC, 0.39) and PFS (HR, 0.98, P = .95) in taxane-treated metastatic breast cancer. Through transfer learning to high-grade serous ovarian cancer, DeepHRD-predicted HRD samples had better OS after first-line (HR, 0.46; P = .030) and neoadjuvant (HR, 0.49; P = .015) platinum therapy in two cohorts. DeepHRD can predict HRD in breast and ovarian cancers directly from routine H&E slides across multiple external cohorts, slide scanners, and tissue fixation variables. When compared with molecular testing, DeepHRD classified 1.8- to 3.1-fold more patients with HRD, which exhibited better OS in high-grade serous ovarian cancer and platinum-specific PFS in metastatic breast cancer.

Serum sST2 Levels Predict Cardiovascular Events in Patients Undergoing Incident Peritoneal Dialysis: A Prospective Cohort Study.

Biomarkers are urgently required to identify peritoneal dialysis (PD) patients at risk of cardiovascular (CV) events. This study aimed to investigate the predictive value of soluble suppression of tumorigenicity-2 (sST2) for CV events in patients undergoing incident PD. In this prospective cohort study, incident PD patients were enrolled. Blood samples to measure sST2 levels were obtained before PD catheter implantation. The patients underwent a standard peritoneal equilibration test (PET) after initiation of PD for 4-6 weeks. The sST2 levels both in serum and dialysate were determined using enzyme-linked immunosorbent assay. CV events were recorded during the follow-up period. A total of 137 patients were enrolled. During the follow-up period of 17.3 months, 49 (35.76%) patients experienced CV events. When patients were dichotomized based on the median values and the calculated cutoff values of sST2, the higher sST2 group had 2.980- and 3.048-fold increased risks of CV events, respectively, when compared with the lower sST2 group. Moreover, the prognostic value of sST2 remained significant as a continuous variable (per 1 standard deviation increase, hazard ratio [HR]=1.037, 95% confidence interval [CI] 1.010-1.066, P=0.008). N-terminal pro-brain natriuretic peptide (NT-proBNP) levels were found to indicate a higher risk only when dichotomized based on the calculated cut-off values. Furthermore, serum sST2 and NT-proBNP levels simultaneously above the calculated cutoff values were associated with a higher risk of CV events (HR=3.398, 95% CI 1.813-6.367, P&lt;0.001). Baseline serum sST2 level is an independent predictor of the risk of CV events in patients receiving incident PD, and in combination with NT-proBNP level, it can provide a more accurate predictive value.

Properties of Cementitious Composite Reinforced with Recycled Pulp from Beverage Cartons

This study presents a comprehensive evaluation of the effects of the refining level of recycled pulp from beverage cartons (RPBC) on the properties of its cementitious composite. The RPBC with various freeness levels, ranging from 400 to 650 mL of the Canadian Standard Freeness test method (CSF), was prepared using a high-speed fruit blender. The specimens were formed by the slurry de-watering method with 8wt% fiber content and mortar matrix with a sand-to-cement ratio of 1:1. The key findings reveal that the cementitious composites reinforced with the RPBC exhibited a maximum value of flexural strength of 11.17 MPa and the freeness of 550 mL CSF. The fracture toughness values of the RPBC composites were significantly improved compared to that of the control specimen. However, the values decreased by about 14% to 20 % as the freeness reduced from 650 to 400 mL CSF. The bulk density and porosity of the RPBCC were not significantly affected by the freeness of RPBC.

Long-lasting residual efficacy of Actellic®300CS and Icon®10CS on different surfaces against Anopheles stephensi, an invasive malaria vector.

Anopheles stephensi, a malaria-transmitting mosquito species, has developed resistance to various insecticides such as DDT, Dieldrin, Malathion, and synthetic pyrethroids. To combat this issue, the World Health Organization (WHO) suggests using Actellic®300CS and Icon®10CS for Indoor Residual Spraying to tackle pyrethroid-resistant mosquitoes. The aim of this research project was to evaluate the susceptibility of An. stephensi to certain insecticides at the diagnostic concentration + intensity 5x diagnostic concentration (5XDC) assays in Iran and to study the lasting effectiveness of Actellic®300CS and Icon®10CS against this particular malaria vector. This study assessed the susceptibility of An. stephensi populations in southern Iran to various insecticides, including deltamethrin 0.05%, DDT 4%, malathion 5%, bendiocarb 0.1%, a synergist assay with PBO 4% combined with deltamethrin 0.05%, and an intensity assay using 5x the diagnostic concentration of deltamethrin (0.25%) and bendiocarb 0.5%. Laboratory cone bioassay tests were conducted to determine the residual effectiveness of Actellic®300 and Icon®10CS insecticides on different surfaces commonly found in households, such as cement, mud, plaster, and wood. The tests were carried out following the WHO test kits and standard testing protocols. The An. stephensi populations in Bandar Abbas were found to be susceptible to malathion 5% and deltamethrin 0.25% (5XDC), but exhibited resistance to DDT, standard concentration of deltamethrin, and both standard and intensity concentrations of bendiocarb. In laboratory cone bioassay tests, An. stephensi mortality rates when exposed to Actellic®300CS and Icon®10CS on different surfaces remained consistently more than 80%. Actellic®300CS achieved more than 80% mortality on all substrates for the entire 300-day post-spraying period. Conversely, Icon®10CS maintained mortality rates more than 80% on plaster and wood surfaces for 165 days and on mud and cement surfaces for 270 days post-spraying. Both Actellic®300CS and Icon®10CS demonstrated 100% mortality within 72 h of each test on all surfaces throughout the entire 300-day post-spraying period. The study shows the varying levels of resistance of An. stephensi Bandar Abbas population to different insecticides and demonstrates the consistent performance of Actellic®300CS in controlling these mosquitoes on various surfaces. The findings suggest that long-lasting CS formulations may be more effective for malaria vector control compared to the current options. Further research is needed to validate these findings in field settings and assess the impact of these insecticides on malaria transmission.

Modeling Glucose, Insulin, C-Peptide, and Lactate Interplay in Adolescents During an Oral Glucose Tolerance Test.

Lactate is not considered just a "waste product" of anaerobic glycolysis anymore. It has been proved to play a key role in several metabolic diseases, such as in the metabolic dysfunction-associated steatotic liver disease, obesity, and diabetes. The capability of simulating glucose-insulin-lactate interaction would be useful to design and test drugs targeting lactate metabolism in such pathological conditions. Minimal models are available, which describe and quantify glucose-lactate interaction but models to simulate postprandial glucose-insulin-C-peptide-lactate time courses are missing. The aim of this study is to fill this gap. Starting from the Padova Type 2 Diabetes Simulator (T2DS), we first added a description of glucose-lactate kinetics and then created a population of 100 in silico subjects to match glucose-insulin-C-peptide-lactate data of 44 adolescents with/without obesity who underwent a standard oral glucose tolerance test (OGTT) of 75 g. The developed model accurately predicts all molecules time courses, guaranteeing precise model parameter estimates (percent coefficient of variation [CV%] median [25th-75th percentile] = 19 [9-29]%). The generated in silico population shows good agreement with the clinical data in terms of area under the curve (AUC) (P = .6, .6, .9, .6 for glucose, insulin, C-peptide, and lactate, respectively) and parameter distributions (P > .1). We have developed a simulator to describe glucose, insulin, C-peptide, and lactate kinetics during an OGTT, which captures the behavior of a real population of adolescents with/without obesity both in terms of average and intersubject variability. Such simulator can be used to investigate the pharmacodynamics of drugs targeting lactate metabolic pathway in various pathological conditions.

Sex-Related Differences in the Severity of Neonatal Opioid Withdrawal Syndrome: A Single-Center, Retrospective Cohort Study.

Factors associated with the development and expression of Neonatal Opioid Withdrawal Syndrome (NOWS) are poorly understood. There are conflicting data on the role of infant sex in NOWS. Some studies have suggested that infant sex predicts NOWS severity and adverse outcomes, with male infants being more vulnerable. This study aimed to analyze if infant sex is associated with the severity of NOWS among those who require pharmacologic treatment. This is a retrospective cohort study of term and late-preterm infants (≥35 weeks gestation) exposed to in utero opioids, born between September 2006 and August 2022, and required pharmacologic treatment for NOWS. Maternal and infant demographics were collected. Indicators of the severity of NOWS (duration of medical treatment (DOT), duration of hospitalization, maximum dose of opioid treatment, and use of secondary medications) were compared between male and female infants. Standard statistical tests and regression analysis were used to establish the differences in outcomes after accounting for confounders and baseline differences. Out of the 1,074 infants included in the study, 47.9% were female, and 52.1% were male. There was no significant difference in demographic and baseline clinical characteristics between groups except for anthropometry (birth weight, head circumference, and length) and Apgar score at 5 minutes. The median DOT (25 days [14, 39] vs. 23 days [13, 39], p = 0.57), length of hospital stay (31.5 days [20, 44] vs. 28 days [20, 44], p = 0.35), treatment with phenobarbital (24.7 vs. 26.3%, p = 0.56), and clonidine (3.9 vs. 3.8%, p = 0.9) were similar in both groups. The differences remained nonsignificant after adjusting for birth anthropometric measurements, gestational age, 5-minute Apgar score, small for gestational age status, and maternal exposure to benzodiazepines. In this cohort of neonates, sex-related differences were not identified to influence the severity of NOWS among those who required pharmacological treatment. · Vulnerability to NOWS is multifactorial.. · The role of infant sex in the severity of NOWS is not concrete.. · We noted that sex did not impact NOWS severity in those treated..

An experimental and theoretical investigation on the hyper-viscoelasticity of polyamide 12 produced by selective laser sintering.

Polyamide 12 (PA12) is vastly utilized in many additive manufacturing methods, such as Selective Laser Sintering (SLS), and a better understanding of its mechanical behaviors promotes available knowledge on the behaviors of 3D-printed parts made from this polymer. In this paper, SLS-produced standard tensile specimens are studied under monotonic and cyclic tension tests, as well as stress relaxation experiments, and the obtained force-displacement responses are shown to be consistent with a hyper-viscoelastic material model. This finding is also observed in typical pantographic structures produced by the same manufacturing parameters. To propose a constitutive model for predicting these behaviors, the convolution integral of a strain-dependent function and a time-dependent function is developed where the material parameters are determined with the use of both short-term and long-term responses of the specimens. Numerical results of the presented model for standard test specimens are shown to be in good agreements with the experimental ones under various loading conditions. To prove the capabilities of the proposed model in studying any SLS-produced part, finite element implementation of the constitutive equations is shown to provide numerical results in agreement with the empirical findings for tensile loading of the 3D-printed pantographic structure.

Student responsibility after using SE in gymnastics as support for the MBKM curriculum

Background Problems: Responsibility is an important part for students to study at university. In the learning process, students arrive late to take part in learning and do not complete assignments or even do not do them. By using Sport Education (SE) students are given assignments in a role to be responsible for the success of learning. SE has a strong connection to the Merdeka Belajar-Kampus Merdeka (MBKM) curriculum with students as the center of learning. Research Objectives: The aim of this research is to find out the responsibilities of each subscale according to the student's role after using SE and to test the effect of using SE on student responsibilities. Methods: The research method uses experimentation with a one-shot case study design. The participants involved in this research were 53 students at one of the universities in the sports studies program in Indramayu who were taken using convenience sampling techniques. The research instrument used the Contextual Self-Responsibility Questionnaire for sports program students. The data analysis technique uses statistical descriptions to determine the mean and standard deviation and tests hypotheses using the one-sample t test. Finding/Results: This research provides new findings regarding student responsibilities using SE at university level, especially in Indonesia as a support for the MBKM curriculum. Conclusion: This research concludes that there is an influence after using SE on student responsibility. Further investigation is needed regarding the administration of pretests, the existence of comparison classes, and the development of instruments to facilitate all roles according to the characteristics of roles in SE.

A thematic analysis of the perceptions of reversible inhibition of sperm under guidance as a potential family planning method in the United Kingdom.

This exploratory study aimed to look into public perceptions of Reversible Inhibition of Sperm Under Guidance (RISUG) as a family planning method in the United Kingdom (UK). It also aimed to discover if there were any sex differences in perceptions between males and females. Twelve semi-structured interviews were conducted, six with males and six with females, all residents of the UK. The audio data from the interviews then was transcribed for analysis. An inductive and a semantic thematic analysis was conducted on the data set. Three main themes were constructed, including: (i) RISUG Hesitancy, (ii) Females perceived benefits of RISUG and (iii) Males perceived concerns regarding RISUG. Hesitancy was related to vaccination hesitancy, females wanted males to have more reproductive autonomy and males placed their concerns through the lens of 'other' males that their may be unintended side effects. Together these three themes represent both perceived risk and overall benefits of the method. However, while randomized control trails have been completed to standard for RISUG, males perceived concerns, suggesting a disconnect between the public's perceptions and professionals understanding of trails. RISUG was perceived as a viable option for family planning in the future, however trust of the new contraceptive method will need to be fostered among the public in order to effectively transfer knowledge on the potential side effects and the standard of pre-market testing for these. Effective public health messages can result in better education of people concerning the new contraceptive method, including the risks and benefits. By using perceptions to inform health messages around RISUG, researchers and practitioners can learn from potential users how to best address misinformation or concerns, while at the same time building an evidence base for when new male methods reach the contraceptive market.

Seasonal hot spots of pollution and risks in Western Kenya: A spatial-temporal analysis of almost 800 organic micropollutants

The release of chemicals into the environment presents a significant threat to aquatic ecosystems dependent on the proximity to emission sources and seasonal dynamics of emission and mobilization. While spatial-temporal information on water pollution in Europe is increasing, there are substantial knowledge gaps on seasonal pollution dynamics in tropical countries. Thus, we took Lake Victoria South Basin in western Kenya as a case study to identify spatial and seasonal hot spots of contamination, quantified toxic risks to different groups of organisms, and identified seasonal risk drivers. For this purpose, we analyzed grab water samples from five rivers with agricultural and wastewater treatment plants in their catchment in four different seasons. We used liquid chromatography coupled to high resolution mass spectrometry (LC-HRMS) with a target list of 785 organic micropollutants. A total of 307 compounds were detected with concentrations ranging from 0.3 ng/L to 6.6 μg/L. Using a Toxic Unit (TU) approach based on mixture toxicity to standard test organisms, crustaceans were identified as the most affected group followed by algae and fish. For crustaceans, chronic risk thresholds were exceeded in 96 % of all the samples, while 56 % of all samples are expected to be acutely toxic, with the highest risk in February during the dry season. High toxic unit values for algae and fish were recorded in July dry season and May wet season. Diazinon, imidacloprid, clothianidin and pirimiphos-methyl were the major drivers for crustacean toxicity while triclosan and different herbicide mixtures drive risks to algae in dry and wet seasons, respectively. A total of 18 chemicals were found to exceed acute and chronic environmental risk thresholds. With this study, strong spatial-temporal patterns of pollution, risks and risk drivers could be confirmed informing prioritization of monitoring and abatement to enhance water quality and reduce toxic risks.

A new spectral conjugate subgradient method with application in computed tomography image reconstruction

A new spectral conjugate subgradient method is presented to solve nonsmooth unconstrained optimization problems. The method combines the spectral conjugate gradient method for smooth problems with the spectral subgradient method for nonsmooth problems. We study the effect of two different choices of line search, as well as three formulas for determining the conjugate directions. In addition to numerical experiments with standard nonsmooth test problems, we also apply the method to several image reconstruction problems in computed tomography, using total variation regularization. Performance profiles are used to compare the performance of the algorithm using different line search strategies and conjugate directions to that of the original spectral subgradient method. Our results show that the spectral conjugate subgradient algorithm outperforms the original spectral subgradient method, and that the use of the Polak–Ribière formula for conjugate directions provides the best and most robust performance.

Adopting a systems engineering approach to a feasibility study of a sidings development at the Midsomer Norton railway station

It is planned to reopen Midsomer Norton railway station, which is a station on the Somerset &amp; Dorset Heritage Railway Line, to traffic. As a first step, Midsomer Norton will be a terminus, and it is proposed to build sidings and a depot for the trains that terminate there. However, a ground investigation is essential before commencing construction of the sidings and the depot, as this is a vital part of any civil engineering process. The behaviour of the ground must be known in order for a structure to be supported by it; therefore, data from the ground investigation are used as reference for any kind of structure development. This study covers a site investigation that includes a desk study, walkover survey, sampling and laboratory testing in order to ascertain the feasibility of a suitable design. Moisture content testing, liquid limit and plastic limit tests, standard compaction testing, shear vane tests, and triaxial compression tests were carried out to determine the soil characteristics and to analyse the soil behaviour. A strong recommendation was made to follow a systems engineering approach in the construction phase, as well as in the design stage. The dependability of the system is ensured by the good use of V – process of systems engineering.

Captivating coloring and antimicrobial properties of tea leaf and eucalyptus bark on jute–cotton union fabric

Purpose The purpose of this study was to assess the repercussions of eucalyptus bark and tea leaf extract as natural dyes and antibacterial agents for jute–cotton union fabric. Design/methodology/approach The dye was collected from the eucalyptus tree’s bark and tea leaves by the aqueous extraction method. The fabric was dyed with potassium alum mordant, using pre-mordanting, post-mordanting and meta-mordanting methods. Examine the color performance analyzed the K/S, L*, a*, b*; fastness to washing using standard test method ISO 105 C06 A2S, rubbing fastness was performed by Crock meter using AATCC 115. The dyed fabrics were characterized by Fourier transform infrared radiation for the existence of various functional groups. Also, antimicrobial activity testing was done by the agar diffusion method (AATCC method SN 195 920) where Escherichia coli and Staphylococcus aureus were used. Findings The extracted dye tea leaves meta-mordant dyed samples were determined to have the strongest relative color. Fabrics pre-mordanted and post-mordanted with extracted eucalyptus and extracted tea dye produced the same outcome, which was excellent for wash fastness to staining and very good for wash fastness to fading. For both eucalyptus bark and tea, rubbing fastness on the pre-mordanted fabric produced very positive results. In mordanted colored fabric, significant antibacterial activity was discovered against S. aureus and E. coli. Originality/value This study demonstrates that the eucalyptus bark and tea leaves extract encompasses a solid antimicrobial action with amazing coloring execution for jute–cotton union fabric.

Adaptive grey wolf optimizer based on transfer function inertia weight of second-order high-pass filter

This paper proposes an Adaptive Grey Wolf Optimizer based on Transfer function Inertia Weight of Second-order High-pass Filter (SAGWO), aiming to overcome the limitations of Grey Wolf Optimizer (GWO) in terms of convergence speed and solution accuracy. SAGWO enhances the algorithm's dynamic adaptability and greatly speeds up convergence by incorporating the transfer function of the second-order high-pass filter into the modifications of inertia and leader wolves' weight. Furthermore, SAGWO incorporates an adaptive random search component, which significantly enhances the search range and the ability to explore globally. The performance of SAGWO is assessed and compared against three prominent Swarm Intelligence Algorithms (ALO, WOA, and EHO), along with GWO and GWO optimized by PSO. This evaluation is conducted through trials on the CEC2017 standard test set. The experimental results indicate that SAGWO outperforms in terms of both convergence speed and solution correctness. Moreover, SAGWO is utilized to address practical engineering problems such as pressure vessel design and robot gripper design, showcasing its remarkable effectiveness once more. This research enhances the theoretical development of Swarm Intelligence Algorithms and demonstrates the significant utility of SAGWO in practical applications, establishing it as a powerful instrument for scientific investigation and engineering optimization.

Sustained attention can be measured using a brief computerized attention task

The Continuous Visual Attention Test (CVAT) is a test that detects visuomotor reaction time (RT, alertness), variability of reaction time (VRT, sustained attention), omission errors (OE, focused attention), and commission errors (CE, response inhibition). The standard test takes 15 min, while the ultrafast version only 90 s. Besides overall task length, the two versions differ by target probability (20% and 80% in the 15-min vs. only 80% in the 90-s test) and stimulus-onset asynchrony (SOA) (1, 2, and 4 s in the 15-min vs. only 1 s in the 90-s test. We aimed to analyze the effect of target probability, SOA, and time length on the CVAT variables across the 15-min task and to verify correlations and agreements between the 15-min and the 90-s CVATs. 205 healthy participants performed the two CVATs on the same day. Considering the 15-min task, RT and CE were strongly affected by target probability. Conversely, VRT was not affected. When the 15-min task was compared to the 90-s task, we found no significant difference in the VRT variable. Additionally, a significant agreement between the two tasks was found for the VRT variable. We concluded that sustained attention can be measured with the 90-s CVAT.

Clinical phenotypes and short-term outcomes based on prehospital point-of-care testing and on-scene vital signs

Emergency medical services (EMSs) face critical situations that require patient risk classification based on analytical and vital signs. We aimed to establish clustering-derived phenotypes based on prehospital analytical and vital signs that allow risk stratification. This was a prospective, multicenter, EMS-delivered, ambulance-based cohort study considering six advanced life support units, 38 basic life support units, and four tertiary hospitals in Spain. Adults with unselected acute diseases managed by the EMS and evacuated with discharge priority to emergency departments were considered between January 1, 2020, and June 30, 2023. Prehospital point-of-care testing and on-scene vital signs were used for the unsupervised machine learning method (clustering) to determine the phenotypes. Then phenotypes were compared with the primary outcome (cumulative mortality (all-cause) at 2, 7, and 30 days). A total of 7909 patients were included. The median (IQR) age was 64 (51–80) years, 41% were women, and 26% were living in rural areas. Three clusters were identified: alpha 16.2% (1281 patients), beta 28.8% (2279), and gamma 55% (4349). The mortality rates for alpha, beta and gamma at 2 days were 18.6%, 4.1%, and 0.8%, respectively; at 7 days, were 24.7%, 6.2%, and 1.7%; and at 30 days, were 33%, 10.2%, and 3.2%, respectively. Based on standard vital signs and blood test biomarkers in the prehospital scenario, three clusters were identified: alpha (high-risk), beta and gamma (medium- and low-risk, respectively). This permits the EMS system to quickly identify patients who are potentially compromised and to proactively implement the necessary interventions.