This article is linked to Janssen et al papers. To view these articles, visit https://doi.org/10.1111/apt.17718 and https://doi.org/10.1111/apt.17745

The deep operator network (DeepONet) structure has shown great potential in approximating complex solution operators with low generalization errors. Recently, a sequential DeepONet (S-DeepONet) was proposed to use sequential learning models in the branch of DeepONet to predict final solutions given time-dependent inputs. In the current work, the S-DeepONet architecture is extended by modifying the information combination mechanism between the branch and trunk networks to simultaneously predict vector solutions with multiple components at multiple time steps of the evolution history, which is the first in the literature using DeepONets. Two example problems, one on transient fluid flow and the other on path-dependent plastic loading, were shown to demonstrate the capabilities of the model to handle different physics problems. The use of a trained S-DeepONet model in inverse parameter identification via the genetic algorithm is shown to demonstrate the application of the model. In almost all cases, the trained model achieved an R2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$R^2$$\end{document} value of above 0.99 and a relative L2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$L_2$$\end{document} error of less than 10% with only 3200 training data points, indicating superior accuracy. The vector S-DeepONet model, having only 0.4% more parameters than a scalar model, can predict two output components simultaneously at an accuracy similar to the two independently trained scalar models with a 20.8% faster training time. The S-DeepONet inference is at least three orders of magnitude faster than direct numerical simulations, and inverse parameter identifications using the trained model are highly efficient and accurate.

ABSTRACT Introduction Social knowledge is an important aspect of social cognition that pertains to broader knowledge of social concepts and norms. People with intellectual disabilities are more likely to experience mental health challenges, and it’s important to pay special attention to how comorbid conditions can affect their social cognition skills, potentially weakening these skills. Consequently, the present study seeks to compare social knowledge between two groups of adults in Bosnia and Herzegovina: those with intellectual disabilities and those diagnosed with a dual diagnosis encompassing intellectual disability and psychiatric conditions. An additional goal was to identify the factors contributing to social knowledge in these groups. Methods The study sample included 62 adults with mild intellectual disability, divided into two groups based on their comorbid psychiatric condition. We used a demographic questionnaire, Raven’s Progressive Matrices, Peabody Picture Vocabulary Test (PPVT), MINI PAS – ADD scale, and The Social Knowledge Test to assess social knowledge and intellectual functioning. We compared the social knowledge scores between the two groups and identified the predictors of social knowledge in each group. Results The results indicated that adult participants with dual diagnoses had lower social knowledge scores than those with intellectual disabilities only, even after controlling for intellectual functioning and verbal abilities. The predictors of social knowledge differed between the two groups, with age being the only statistically significant predictor in both groups. In individuals with intellectual disabilities, age and the presence of obsessive-compulsive disorder symptoms were important predictors of social knowledge, while in the group of participants with dual diagnoses, age and PPVT were significant predictors of social knowledge. Conclusion This study highlights the importance of social knowledge in individuals with intellectual disabilities and dual diagnoses. The findings suggest that individuals with dual diagnoses may have a specific deficit in social knowledge that is not fully explained by their intellectual functioning or verbal abilities. Clinicians and educators should focus on identifying and addressing social knowledge deficits in individuals with dual diagnoses to improve their overall social functioning.

The optimal reperfusion technique in patients with isolated posterior cerebral artery (PCA) occlusion is uncertain. We compared clinical and technical outcomes with first‐line stent retriever (SR), contact aspiration (CA), or combined techniques in patients with isolated PCA occlusion. This international case–control study was conducted at 30 sites in Europe and North America and included consecutive patients with isolated PCA occlusion presenting within 24 hours of time last seen well from January 2015 to August 2022. The primary outcome was the first‐pass effect (FPE), defined as expanded Treatment in Cerebral Infarction (TICI) 2c/3 on the first pass. Patients treated with SR, CA, or combined technique were compared with multivariable logistic regression. There were 326 patients who met inclusion criteria, 56.1% male, median age 75 (interquartile range 65–82) years, and median National Institutes of Health Stroke Scale score 8 (5–12). Occlusion segments were PCA‐P1 (53.1%), P2 (40.5%), and other (6.4%). Intravenous thrombolysis was administered in 39.6%. First‐line technique was SR, CA, and combined technique in 43 (13.2%), 106 (32.5%), and 177 (54.3%) patients, respectively; FPE was achieved in 62.8%, 42.5%, and 39.6%, respectively. FPE was lower in patients treated with first‐line CA or combined technique compared with SR (CA versus SR: adjusted odds ratio 0.45 [0.19–1.06]; P =0.07; combined versus SR: adjusted odds ratio 0.35 [0.016–0.80]; P =0.01). There were lower odds of functional independence (modified Rankin scale score 0–2) in the first‐line CA versus SR alone group (adjusted odds ratio 0.52 [0.28–0.95]; P =0.04). FPE was associated with higher rates of favorable outcomes (modified Rankin scale score 0–2: 58% versus 43.4%; P =0.01; modified Rankin scale score 0–1: 36.6% versus 25.8%; P =0.05). Overall, symptomatic intracranial hemorrhage was present in 5.6% (18/326) and mortality in 10.9% (35/326) without difference between first‐line technique. In patients with isolated PCA occlusion, SR was associated with a higher rate of FPE compared with CA or combined techniques with no difference in final successful reperfusion. Functional independence at 90 days was more likely with first‐line SR compared with CA. FPE was associated with better 90‐day clinical outcomes.

Early diagnosis and treatment of brain cancer depend on the detection and categorization of brain tumors. Deep learning algorithms have produced amazing results in medical imaging applications including tumor identification. Most of this field's research has concentrated on applying CNN algorithms like VGG16, DNN, and ANN to this problem. This work describes the identification and classification of brain tumors using the Python Imaging Library (PIL) and the VGG16 deep learning algorithm. A dataset of 7000 MRI pictures categorized by tumor type served as the foundation for the research. The main objective of this study was to develop a high-efficiency, high-accuracy model. We suggested utilizing the VGG16 architecture and preprocessing images with PIL to ensure consistent images for training on a sizable dataset of brain magnetic resonance imaging (MRI) images. A novel technique we have used in our work is one that can analyze a single image and predict the presence of a tumor from the results. The research's methods produced robust tumor detection across the dataset with 96, 9% accuracy, indicating the value of the method in helping medical professionals make informed decisions when diagnosing the presence of tumors.

The COVID-19 pandemic, since SARS-CoV2 was discovered in December 2019, has resulted in significant morbidity and mortality. Since then, several countries have witnessed the collapse of the health care system due to the great need to treat patients with COVID-19. At the global level, drastic measures have been taken to combat the spread of the virus. However, these measures have led to disruptions in other aspects of health care, diagnosis and treatment of other diseases and conditions. There is also a stalemate in achieving the ambitious goal set by the World Health Organization to eliminate viral hepatitis as a threat to public health by 2030. Hepatitis B and C are chronic conditions with a significant global burden, and COVID-19 has slowed or stopped many hepatitis elimination programs.

Presently, the main cause of pollution of natural water resources is heavy metal ions. The removal of metal ions such as nickel (Ni2+) and cadmium (Cd2+) has been given considerable attention due to their health and environmental risks. In this regard, for wastewater treatment containing heavy metal ions, graphene oxide (GO) nanocomposites with metal oxide nanoparticles (NPs) attained significant importance. In this study, graphene oxide stacked with copper oxide nanocomposites (GO/CuO-NCs) were synthesized and characterized by Fourier transform infrared (FTIR), X-ray diffraction (XRD), scanning electron microscopy (SEM), energy dispersive X-ray (EDX), and atomic force microscopy (AFM) analytical procedures. The prepared GO/CuO-NCs were applied for the removal of Ni2+ and Cd2+ ions from a binary metal ion system in batch and continuous experiments. The obtained results revealed that GO/CuO-NCs exhibited the highest removal efficiencies of Ni2+ (89.60% ± 2.12%) and Cd2+ (97.10% ± 1.91%) at the optimum values of pH: 8, dose: 0.25 g, contact time: 60 min, and at 50 ppm initial metal ion concentration in a batch study. However, 4 mL/min flow rate, 50 ppm initial concentration, and 2 cm bed height were proved to be the suitable conditions for metal ion adsorption in the column study. The kinetic adsorption data exhibited the best fitting with the pseudo-second-order model. The adsorption isotherm provided the best-fitting data in the Langmuir isotherm model. This study suggested that the GO/CuO nanocomposites have proved to be efficient adsorbents for Ni2+ and Cd2+ ions from a binary metal system.

Xanthene derivatives are an important class of heterocyclic compounds with a wide spectrum of pharmacological activities. In our previous investigations, we found the good antiproliferative activity of two xanthene derivatives, with minimal toxicity investigated by in vitro tests. In this study, we tested the interaction of compound 1 (powerful potent antiproliferative compound) with calf thymus DNA (CT-DNA) under physiological conditions by spectrophotometric titration. The probable prediction of binding and the type of interaction forces involved in the arrangement between xanthene derivatives and CT-DNA were explored also through molecular docking studies. The results indicated that compound 1 interacts with CT-DNA by grove binding. The binding constant was found to be 2.5 ∙ 10 4 M −1 indicating the non-covalent binding of compound 1 to CT-DNA. Docking study results proposed possible binding modes, with binding energies of −9.39 and −8.65 kcal mol −1 for compounds 1 and 2, respectively, which supported previously obtained in vitro results for antiproliferative activity. In addition to experimental investigation, density functional theory (DFT) calculation with B3LYP/6-31G*, B3LYP/6-31G**, and B3LYP/6-31+G* levels of theories was performed on compounds 1 and 2 to obtain optimised geometry, spectroscopic and electronic properties. These studies could help in understanding the mechanisms of toxicity, resistance, side effects of xanthene derivatives, and their binding action mechanism to DNA

The essential resources for the survival of the living world are air, water and land. By its essence land is the only non-renewable natural resource, with a potentially rapid rate of degradation and a very slow process of formation and regeneration. Water and land are resources, characterized by climate, so climate variability inevitably affects the processes in the land and its use, whose testimonies today we could find through the fossil lands. Processes affecting the lands are intensified in the last few decades around the world, such as erosion, water logging, drought, fire, loss of organic matter and the like, are associated with climate change and are visible on the territory of Republika Srpska. The basic task of humans today is to use the land rationally and to preserve it for new generations. On the basis of available measured data and climate models in the future, the following conclusions came out: land use would not be significantly impaired, nor would crop production be endangered; favorable climatic conditions would continue to prevail for the production of corn, wheat, and potatoes, with increased year-on-year variations by the end of the century; due to earlier sowing, water logging would be pronounced; regular maintenance of existing drainage systems should be fully in function, and new ones to be built in geopardize places; for the new, highly intensive orchard establishments and vegetable production, irrigation system should be designed and built; comprehensive solutions of existing erosion processes and prevention of occurrence of new ones should be envisaged, because in future climatic conditions, dry periods of higher intensity might occur, followed by strong rainstorms could cause permanent soil loss due to dried vegetation prone to erosion; considering that the soils of Republika Srpska are very poor in humus, i.e. organic carbon, it is necessary to apply agrotechnical measures to increase the intake of organic matter. Intentional burning of crop residues must be severely punished. Continuous monitoring of soil fertility on georeferenced locations is indispensable (pH, macroelements (NPK), content of organic matter, water-physical properties of soil) for better data comparison and observation of the direction of impact, whether positive or negative, in order to plan and take timely adaptation measures, ensuring proper and sustainable land use and climate change mitigation.

With aging, the body’s ability to maintain regular functions declines, increasing susceptibility to age-related diseases. Therapeutic interventions targeting the underlying biological changes of aging hold promise for preventing or delaying multiple age-related diseases. Metformin, a drug commonly used for diabetes treatment, has emerged as a potential gerotherapeutic agent due to its established safety record and preclinical and clinical data on its anti-aging effects. Glycosylation, one of the most common and complex co- and post-translational protein modifications, plays a crucial role in regulating protein function and has been linked to aging and various diseases. Changes in immunoglobulin G (IgG) glycosylation patterns have been observed with age, and these alterations may serve as valuable biomarkers for disease predisposition, diagnosis, treatment monitoring, and overall health assessment. In this study, we analyzed the IgG glycosylation patterns of white men from Europe, aged 29–45 years, under treatment with metformin, testosterone, metformin plus testosterone, and placebo (trial registration number NCT02514629, 2013/07/04), and investigated the longitudinal changes in glycosylation over time. We observed statistically significant differences in the IgG glycome composition between participants on testosterone therapy and placebo, with decreased agalactosylation and increased galactosylation and sialylation. However, metformin therapy did not result in statistically significant changes in glycosylation patterns. These findings contribute to our understanding of the impact of therapeutic interventions on IgG glycosylation and confirm the value of IgG glycosylation as a significant biomarker, capable of assessing biological age using the GlycanAge index and providing insight into overall health compared to chronological age.

Introduction The management of long-term physical conditions is a challenge worldwide, absorbing a majority resources despite the importance of acute care. The management of these conditions is done largely in primary care and so interventions to improve primary care could have an enormous impact. However, very little data exist on how to do this. Mental distress is frequently comorbid with long term physical conditions, and can impact on health behaviour and adherence, leading to poorer outcomes. DIALOG+ is a low-cost, patient-centred and solution-focused intervention, which is used in routine patient-clinician meetings and has been shown to improve outcomes in mental health care. The question arises as to whether it could also be used in primary care to improve the quality of life and mental health of patients with long-term physical conditions. This is particularly important for low- and middle-income countries with limited health care resources. Methods An exploratory non-controlled multi-site trial was conducted in Bosnia and Herzegovina, Colombia, and Uganda. Feasibility was determined by recruitment, retention, and session completion. Patient outcomes (quality of life, anxiety and depression symptoms, objective social situation) were assessed at baseline and after three approximately monthly DIALOG+ sessions. Results A total of 117 patients were enrolled in the study, 25 in Bosnia and Herzegovina, 32 in Colombia, and 60 in Uganda. In each country, more than 75% of anticipated participants were recruited, with retention rates over 90% and completion of the intervention exceeding 92%. Patients had significantly higher quality of life and fewer anxiety and depression symptoms at post-intervention follow-up, with moderate to large effect sizes. There were no significant improvements in objective social situation. Conclusion The findings from this exploratory trial suggest that DIALOG+ is feasible in primary care settings for patients with long-term physical conditions and may substantially improve patient outcomes. Future research may test implementation and effectiveness of DIALOG+ in randomized controlled trials in wider primary care settings in low- and middle-income countries. Trial registration All studies were registered prospectively within the ISRCTN Registry. ISRCTN17003451, 02/12/2020 (Bosnia and Herzegovina), ISRCTN14018729, 01/12/2020 (Colombia) and ISRCTN50335796, 02/12/2020 (Uganda).

Aktivnosti Centra za istraživanje moderne i savremene historije Tuzla u 2022. godini // Activities of Center for Research of Modern and Contemporary History Tuzla in 2022.

ABSTRACT Background The European Renal Association (ERA) Registry collects data on kidney replacement therapy (KRT) in patients with end-stage kidney disease (ESKD). This paper is a summary of the ERA Registry Annual Report 2021, including a comparison across treatment modalities. Methods Data was collected from 54 national and regional registries from 36 countries, of which 35 registries from 18 countries contributed individual patient data and 19 registries from 19 countries contributed aggregated data. Using this data, incidence and prevalence of KRT, kidney transplantation rates, survival probabilities and expected remaining lifetimes were calculated. Result In 2021, 533.2 million people in the general population were covered by the ERA Registry. The incidence of KRT was 145 per million population (pmp). In incident patients, 55% were 65 years or older, 64% were male, and the most common primary renal disease (PRD) was diabetes (22%). The prevalence of KRT was 1040 pmp. In prevalent patients, 47% were 65 years or older, 62% were male, and the most common PRDs were diabetes and glomerulonephritis/sclerosis (both 16%). On 31 December 2021, 56% of patients received haemodialysis, 5% received peritoneal dialysis, and 39% were living with a functioning graft. The kidney transplantation rate in 2021 was 37 pmp, a majority coming from deceased donors (66%). For patients initiating KRT between 2012–2016, 5-year survival probability was 52%. Compared to the general population, life expectancy was 65% and 68% shorter for males and females receiving dialysis, and 40% and 43% shorter for males and females living with a functioning graft.

Abstract Background To examine correlation between elevated levels of thyrotropin with the frequency of miscarriages. Methods A cross-sectional study was conducted on the 380 respondents and it investigated TSH (thyrotropin), thyroid peroxidase antibody(anti-TPO) and free thyroxine (FT4) in pregnant women who had a miscarriage (N = 179) and pregnant women with normal pregnancies (N = 201). Results The incidence of subclinical hypothyroidism in the miscarriages group was higher than in control group (61.4% vrs 15.79% (p < 0.001). In the miscarriages group with hypothyroidism (first trimester) mean value of TSH was significantly higher 4.31 ± 2.55 mIU/L compared to the control group 1.95 ± 0.86mIU/L (p < 0.001). Logistic multivariate regression revealed that TSH and body mass index (BMI) have a significant influence on the miscarriage; TSH level has a higher odds ratio (OR) 1.47 CI (95% 1.22–1.78) than BMI (OR) 1.14 CI (95% 1.06–1.23)) (p < 0.001). The combination of thyroid autoimmunity and TSH > 2.5mIU/L increase the risk of miscarriage (65.75%) compared to positive anti-TPO antibodies and TSH < 2.5mIU/L(14.15%)(p < 0.001). Conclusions Higher TSH levels correspond with obesity during early pregnancy and may be a sign of maternal thyroid dysfunction. Physiological thyroid function in the first trimester of pregnancy is important for perinatal outcome.

We posit that the distinct patterns observed in fermion masses and mixings are due to a minimally broken U(2)_{q+e} flavor symmetry acting on left-handed quarks and right-handed charged leptons, giving rise to an accidental U(2)^{5} symmetry at the renormalizable level without imposing selection rules on the Weinberg operator. We show that the symmetry can be consistently gauged by explicit examples and comment on realizations in SU(5) unification. Via a model-independent analysis of a standard model viewed as an effective field theory, we find that selection rules due to U(2)_{q+e} enhance the importance of charged lepton flavor violation as a probe, where significant experimental progress is expected in the near future.