Multivariate analysis on blackgram genotypes for bruchine (Callosobruchus maculatus F.) resistance towards selection of parental lines

Black gram (Vigna mungo (L.) Hepper) is one of the most important pulse crops in daily diets. However, black gram production and post-harvest preservation are still tedious due to the losses caused by the storage pest bruchine, Callosobruchus maculatus (F.), both quantitatively and qualitatively.   Hence, the present study involves the utilization of the multivariate analysis by effectively understanding variation among the genotypes based on their level of bruchine infestation. The multivariate studies indicated that the traits viz., the total number of adult emergence (AE), seed damage % (SD) and seed weight loss % (SWL) had more variation and with more significant correlation among them.  Also, these traits are the most influential principal component traits governing 88% of the variation among genotypes. The divergence analysis showed that the genotype TU 68 found in cluster II would have the potential to create the variation for bruchine infestation among the black gram genotypes involved in the study.  As it has scored lesser adult emergence (AE) (7 adults), seed damage % (SD) (14 %) and seed weight loss % (SWL) (17.79 %)  than the other genotypes. It shows the resistant nature of the genotype against bruchine beetles. Hence, TU 68 could be utilized in the future hybridization programme as a donor for bruchine resistance

Impact of opioid-free analgesia on pain severity and patient satisfaction after discharge from surgery: multispecialty, prospective cohort study in 25 countries

Background: Balancing opioid stewardship and the need for adequate analgesia following discharge after surgery is challenging. This study aimed to compare the outcomes for patients discharged with opioid versus opioid-free analgesia after common surgical procedures.Methods: This international, multicentre, prospective cohort study collected data from patients undergoing common acute and elective general surgical, urological, gynaecological, and orthopaedic procedures. The primary outcomes were patient-reported time in severe pain measured on a numerical analogue scale from 0 to 100% and patient-reported satisfaction with pain relief during the first week following discharge. Data were collected by in-hospital chart review and patient telephone interview 1 week after discharge.Results: The study recruited 4273 patients from 144 centres in 25 countries; 1311 patients (30.7%) were prescribed opioid analgesia at discharge. Patients reported being in severe pain for 10 (i.q.r. 1-30)% of the first week after discharge and rated satisfaction with analgesia as 90 (i.q.r. 80-100) of 100. After adjustment for confounders, opioid analgesia on discharge was independently associated with increased pain severity (risk ratio 1.52, 95% c.i. 1.31 to 1.76; P < 0.001) and re-presentation to healthcare providers owing to side-effects of medication (OR 2.38, 95% c.i. 1.36 to 4.17; P = 0.004), but not with satisfaction with analgesia (beta coefficient 0.92, 95% c.i. -1.52 to 3.36; P = 0.468) compared with opioid-free analgesia. Although opioid prescribing varied greatly between high-income and low- and middle-income countries, patient-reported outcomes did not.Conclusion: Opioid analgesia prescription on surgical discharge is associated with a higher risk of re-presentation owing to side-effects of medication and increased patient-reported pain, but not with changes in patient-reported satisfaction. Opioid-free discharge analgesia should be adopted routinely

Multivariate analysis on blackgram genotypes for bruchine (Callosobruchus maculatus F.) resistance towards selection of parental lines

Black gram (Vigna mungo (L.) Hepper) is one of the most important pulse crops in daily diets. However, black gram production and post-harvest preservation are still tedious due to the losses caused by the storage pest bruchine, Callosobruchus maculatus (F.), both quantitatively and qualitatively.   Hence, the present study involves the utilization of the multivariate analysis by effectively understanding variation among the genotypes based on their level of bruchine infestation. The multivariate studies indicated that the traits viz., the total number of adult emergence (AE), seed damage % (SD) and seed weight loss % (SWL) had more variation and with more significant correlation among them.  Also, these traits are the most influential principal component traits governing 88% of the variation among genotypes. The divergence analysis showed that the genotype TU 68 found in cluster II would have the potential to create the variation for bruchine infestation among the black gram genotypes involved in the study.  As it has scored lesser adult emergence (AE) (7 adults), seed damage % (SD) (14 %) and seed weight loss % (SWL) (17.79 %)  than the other genotypes. It shows the resistant nature of the genotype against bruchine beetles. Hence, TU 68 could be utilized in the future hybridization programme as a donor for bruchine resistance.</jats:p

Enhancement of soil properties using bottom ash, fly ash and coconut ash - An application of waste to wealth

Abstract Abundant waste materials are being produced nowadays due to rapid commercialisation and urbanisation. Disposal of these waste materials is a challenging task since it causes both air and water pollution. Since the production of waste materials is inevitable, a suitable strategy has to adopted to convert this waste into wealth. In this study, the red soil was collected from the field and the same was composted with organic matter to enhance its organic carbon content. Further, bottom ash, fly ash and coconut waste ash (CWA) has been added to the composted soil in a ratio of 1:4. Subsequently, the organic carbon content and strength parameters of the mixtures were determined. Soil organic carbon content was determined using Walkley Black method while the strength parameters were determined using standard proctor compaction test (SPCT) and Vane shear test. The N, P and K of the original collected soil were 160 kg ha-1, 14 kg ha-1, and 139 kg ha-1 respectively. The soil organic carbon content is highest with 65% when composted soil is mixed with bottom ash. The maximum dry density of soil increased from 0.765 to 0.81 due to addition of bottom ash. The Shear strength increases gradually with the increase in percentage of Coconut Waste Ash (CWA) and torque of soil also attained the effective value.</jats:p

Advancing hyperspectral imaging and machine learning tools toward clinical adoption in tissue diagnostics: A comprehensive review

Hyperspectral imaging (HSI) has become an evident transformative apparatus in medical diagnostics. The review aims to appraise the present advancement and challenges in HSI for medical applications. It features a variety of medical applications namely diagnosing diabetic retinopathy, neurodegenerative diseases like Parkinson's and Alzheimer's, which illustrates its effectiveness in early diagnosis, early caries detection in periodontal disease, and dermatology by detecting skin cancer. Regardless of these advances, the challenges exist within every aspect that limits its broader clinical adoption. It has various constraints including difficulties with technology related to the complexity of the HSI system and needing specialist training, which may act as a drawback to its clinical settings. This article pertains to potential challenges expressed in medical applications and probable solutions to overcome these constraints. Successful companies that perform advanced solutions with HSI in terms of medical applications are being emphasized in this study to signal the high level of interest in medical diagnosis for systems to incorporate machine learning ML and artificial intelligence AI to foster precision diagnosis and standardized clinical workflow. This advancement signifies progressive possibilities of HSI in real-time clinical assessments. In conclusion despite HSI has been presented as a significant advanced medical imaging tool, addressing its limitations and probable solutions is for broader clinical adoption

Cloud-Internet of Health Things (IOHT) Task Scheduling Using Hybrid Moth Flame Optimization with Deep Neural Network Algorithm for E Healthcare Systems

Considering task dependencies, the balancing of the Internet of Health Things (IoHT) scheduling is considered important to reduce the make span rate. In this paper, we developed a smart model approach for the best task schedule of Hybrid Moth Flame Optimization (HMFO) for cloud computing integrated in the IoHT environment over e-healthcare systems. The HMFO guarantees uniform resource assignment and enhanced quality of services (QoS). The model is trained with the Google cluster dataset such that it learns the instances of how a job is scheduled in cloud and the trained HMFO model is used to schedule the jobs in real time. The simulation is conducted on a CloudSim environment to test the scheduling efficacy of the model in hybrid cloud environment. The parameters used by this method for the performance assessment include the use of resources, response time, and energy utilization. In terms of response time, average run time, and lower costs, the hybrid HMFO approach has offered increased response rate with reduced cost and run time than other methods.</jats:p

Predicting opioid consumption after surgical discharge: a multinational derivation and validation study using a foundation model

Opioids are frequently overprescribed after surgery. We applied a tabular foundation model to predict the risk of post-discharge opioid consumption. The model was trained and internally validated on an 80:20 training/test split of the ‘Opioid PrEscRiptions and usage After Surgery’ (ACTRN12621001451897p) study cohort, including adult patients undergoing general, orthopaedic, gynaecological and urological operations (n = 4267), with external validation in a distinct cohort of patients discharged after general surgical procedures (n = 826). The area under the receiver operator curve was 0.84 (95% confidence interval [CI] 0.81–0.88) at internal testing and 0.77 (95% CI 0.74–0.80) at external validation. Brier scores were 0.13 (95% CI 0.12–0.14) and 0.19 (95% CI 0.17–0.2). Patients with a <50% predicted risk of opioid consumption consumed a median of 0 oral morphine equivalents in the first week after surgery. Applying this model would reduce opioid prescriptions by 4.5% globally, and counterfactual modelling suggests without increasing time in severe pain (−4.3%, 95% CI −17.7 to 8.6)