Evidence against strong correlation in 4d transition metal oxides, CaRuO3 and SrRuO3

We investigate the electronic structure of 4d transition metal oxides, CaRuO3 and SrRuO3. The analysis of the photoemission spectra reveals significantly weak electron correlation strength (U/W ~ 0.2) as expected in 4d systems and resolves the long standing issue that arose due to the prediction of large U/W similar to 3d-systems. It is shown that the bulk spectra, thermodynamic parameters and optical properties in these systems can consistently be described using first principle approaches. The observation of different surface and bulk electronic structures in these weakly correlated 4d systems is unusual.Comment: 4 pages, 4 figure

CSWin Transformer-CNN Encoder and Multi-Head Self-Attention Based CNN Decoder for Robust Medical Segmentation

Convolutional Neural Networks have demonstrated exceptional effectiveness in the field of medical image segmentation by effectively capturing intricate local details such as edges and textures. But still, their limited domain of view often impedes comprehensive representation of global information. Transformers, on the other hand, have shown promise in modeling long-range dependencies, yet, Convolutional Neural Networks occasionally face challenges in effectively capturing high-level spatial features. An ideal segmentation model ought to effectively harness both local and global features to achieve precision and semantic accuracy. This article introduces a novel Cross Shaped Window Transformer framework, employing U-shaped network architecture. This network combines a Convolutional Neural Network encoder with a Multi-Head Self-Attention based CNN decoder. Within the CNN encoder, a transformer path is integrated with a shifted window mechanism, enhancing the representation of both local and global information, thus ensuring robust medical image segmentation. The encoder\u27s skip connections are reinstated using a Multi-Head Self-Attention decoder. To decode a wide range of features and manage distortions in local details, a dilated-Uper decoder is introduced. The Synapse dataset is utilized to assess the effectiveness of the proposed method, revealing that it surpasses existing approaches with an impressive accuracy of approximately 93%

Knowledge, attitude and practices of antibiotic usage among the medical undergraduates of a tertiary care teaching hospital: an observational cross-sectional study

Background: Social aspect of antibiotic management forms a significant way to overcome the rapidly intensifying problem of antibiotic resistance. Medical students should not only be made aware of the current emerging health issues but also be directed towards rational antibiotics prescribing behavior as future medical practitioners. Aims and objective of the study was to assess the knowledge, attitude and practices (KAP) related to antibiotic usage in second year medical undergraduate students.Methods: The study design was cross sectional, questionnaire based survey. The questionnaire was distributed to a 3rd term and 4th term medical students in their second year of MBBS, to know the KAP regarding antibiotic usage and was assessed by a five point Likert scale and few questions were of true and false type. The data was analyzed by using SPSS.Results: Out of 162 students, 138 (85.19%) participated in the study; 63 (45.65%) were males and 75 (54.35%) were females. 84.06% of the participants known that irrational and indiscriminate antimicrobial use leads to the emergence of resistance. 96.38% agreed that Antibacterial resistance(ABR) was an important and a serious global public health issue and national problem. 71.01% of the respondents were aware that bacteria were not responsible for causing colds and flu. 86.23% said it can lead to more adverse drug reaction.Conclusions: The present survey on antibiotic usage gives useful information about the knowledge, attitudes and practices of second year medical undergraduates, which may be utilized to plan suitable educational interventions that aim at improving the antimicrobial prescribing and use to maximize their effective and efficient use and minimize the development of resistance

Genetic Algorithm for Object Oriented Reducts Using Rough Set Theory

Abstract Knowledge reduction is NP-hard problem. Many approaches are proposed to get the minimal reduction, which is mainly based on the significance of the attributes. There are some disadvantages of the reduction algorithms at present. In this paper,. We propose a heuristic algorithm based on C-Tree for objectoriented reducts and also present a genetic algorithm (GA) for object oriented reducts based on C-Tree using rough set theory

Disease burden of urinary tract infections among type 2 diabetes mellitus patients in the U.S.

AbstractAimsType 2 diabetes is a reported risk factor for more frequent and severe urinary tract infections (UTI). We sought to quantify the annual healthcare cost burden of UTI in type 2 diabetic patients.MethodsAdult patients diagnosed with type 2 diabetes were identified in MarketScan administrative claims data. UTI occurrence and costs were assessed during a 1-year period. We examined UTI-related visit and antibiotic costs among patients diagnosed with UTI, comparing those with versus without a history of UTI in the previous year (prevalent vs. incident UTI cases). We estimated the total incremental cost of UTI by comparing all-cause healthcare costs in patients with versus without UTI, using propensity score-matched samples.ResultsWithin the year, 8.2% (6,014/73,151) of subjects had ≥1 UTI, of whom 33.8% had a history of UTI. UTI-related costs among prevalent versus incident cases were, respectively, $603 versus$447 (p=0.033) for outpatient services, $1,607 versus$1,819 (p=NS) for hospitalizations, and $61 versus$35 (p<0.0001) for antibiotics. UTI was associated with a total all-cause incremental cost of $7,045 (95% CI: 4,130, 13,051) per patient with UTI per year.ConclusionsUTI is common and may impose a substantial direct medical cost burden among patients with type 2 diabetes

Efficacy and safety of dexlansoprazole: a comprehensive review

Gastroesophageal reflux disease (GERD) remains prevalent in medical practice. Proton pump inhibitors (PPIs) are the primary treatment, yet limitations exist. Dexlansoprazole modified release (MR), an R-enantiomer of lansoprazole, offers high efficacy. Its dual release in the duodenum and small intestine yields two peak concentrations at different times (2- and 5-hours post-administration), ensuring the longest maintenance of drug concentration and proton pump inhibitory effect among all PPIs. Dexlansoprazole MR effectively heals erosive esophagitis, maintains healed esophageal mucosa, and controls NERD symptoms. It also improves nocturnal heartburn, GERD-related sleep disturbances, and bothersome regurgitation. Importantly, it maintains good plasma concentration regardless of food intake, enabling flexible dosing. Furthermore, it does not significantly affect clopidogrel metabolism or platelet inhibition, eliminating the need for dose adjustments when co-prescribed. This review highlights dexlansoprazole's unique attributes, pharmacokinetics, advantages, and safety in comparison to traditional PPIs.

An open-label clinical trial to investigate the efficacy and safety of corifollitropin alfa combined with hCG in adult men with hypogonadotropic hypogonadism

Subject disposition. (EPS 1138 kb

A Case for Renewed Activity in the Giant Radio Galaxy J0116-473

We present ATCA radio observations of the giant radio galaxy J0116-473 at 12 and 22 cm wavelengths in total intensity and polarization. The images clearly reveal a bright inner-double structure within more extended edge-brightened lobe emission. The lack of hotspots at the ends of the outer lobes, the strong core and the inner-double structure with its edge-brightened morphology lead us to suggest that this giant radio galaxy is undergoing a renewed nuclear activity: J0116-473 appears to be a striking example of a radio galaxy where a young double source is evolving within older lobe material. We also report the detection of a Mpc-long linear feature which is oriented perpendicular to the radio axis and has a high fractional polarization.Comment: 25 pages, 10 figures, appeared in 2002 ApJ, 565, 25

Faculty perceptions regarding an individually tailored, flexible length, outcomes-based curriculum for undergraduate medical students

Purpose The perception of faculty members about an individually tailored, flexible-length, outcomes-based curriculum for undergraduate medical students was studied. Their opinion about the advantages, disadvantages, and challenges was also noted. This study was done to help educational institutions identify academic and social support and resources required to ensure that graduate competencies are not compromised by a flexible education pathway. Methods The study was done at the International Medical University, Malaysia, and the University of Lahore, Pakistan. Semi-structured interviews were conducted from 1st August 2021 to 17th March 2022. Demographic information was noted. Themes were identified, and a summary of the information under each theme was created. Results A total of 24 (14 from Malaysia and 10 from Pakistan) faculty participated. Most agreed that undergraduate medical students can progress (at a differential rate) if they attain the required competencies. Among the major advantages mentioned were that students may graduate faster, learn at a pace comfortable to them, and develop an individualized learning pathway. Several logistical challenges must be overcome. Providing assessments on demand will be difficult. Significant regulatory hurdles were anticipated. Artificial intelligence (AI) can play an important role in creating an individualized learning pathway and supporting time-independent progression. The course may be (slightly) cheaper than a traditional one. Conclusion This study provides a foundation to further develop and strengthen flexible-length competency-based medical education modules. Further studies are required among educators at other medical schools and in other countries. Online learning and AI will play an important role