Explore the vast range of titles available.

The CERN-MEDICIS (MEDical Isotopes Collected from ISolde) facility has delivered its first radioactive ion beam at CERN (Switzerland) in December 2017 to support the research and development in nuclear medicine using non-conventional radionuclides. Since then, fourteen institutes, including CERN, have joined the collaboration to drive the scientific program of this unique installation and evaluate the needs of the community to improve the research in imaging, diagnostics, radiation therapy and personalized medicine. The facility has been built as an extension of the ISOLDE (Isotope Separator On Line DEvice) facility at CERN. Handling of open radioisotope sources is made possible thanks to its Radiological Controlled Area and laboratory. Targets are being irradiated by the 1.4 GeV proton beam delivered by the CERN Proton Synchrotron Booster (PSB) on a station placed between the High Resolution Separator (HRS) ISOLDE target station and its beam dump. Irradiated target materials are also received from external institutes to undergo mass separation at CERN-MEDICIS. All targets are handled via a remote handling system and exploited on a dedicated isotope separator beamline. To allow for the release and collection of a specific radionuclide of medical interest, each target is heated to temperatures of up to 2,300°C. The created ions are extracted and accelerated to an energy up to 60 kV, and the beam steered through an off-line sector field magnet mass separator. This is followed by the extraction of the radionuclide of interest through mass separation and its subsequent implantation into a collection foil. In addition, the MELISSA (MEDICIS Laser Ion Source Setup At CERN) laser laboratory, in service since April 2019, helps to increase the separation efficiency and the selectivity. After collection, the implanted radionuclides are dispatched to the biomedical research centers, participating in the CERN-MEDICIS collaboration, for Research & Development in imaging or treatment. Since its commissioning, the CERN-MEDICIS facility has provided its partner institutes with non-conventional medical radionuclides such as Tb-149, Tb-152, Tb-155, Sm-153, Tm-165, Tm-167, Er-169, Yb-175, and Ac-225 with a high specific activity. This article provides a review of the achievements and milestones of CERN-MEDICIS since it has produced its first radioactive isotope in December 2017, with a special focus on its most recent operation in 2020.

This work demonstrated the effect of functionalized magnesium oxide (MgO) nanoparticles with 3-(aminopropyl) triethoxysilane (APTES) as fillers on the mechanical and thermal properties of epoxy composite. The functionalization of MgO (S-MgO) considerably improved the interface between the MgO and epoxy resin. The mechanical properties of the composites revealed that the addition of functionalized MgO improved their tensile strength, modulus of elasticity, and ductility when compared to neat epoxy. In comparison to neat epoxy, the in-plane thermal conductivity of the epoxy composite with S-MgO filler is improved by 10 folds. These observations indicated that the silane functionalization on MgO contributes to the formation of a strong interfacial bond and a compact interconnected network between the filler and the epoxy matrix.

The challenge of re-identifying vehicles in urban city surveillance systems and major traffic arteries such as highways and roads is an important area of research. The advent of large-scale benchmarks such as VeRI-776 and Vehicle-ID has propelled efforts to enhance search operations from large databases for re-identification. However, several unresolved challenges associated with vehicle re-identification in unconstrained environments remain to be explored. In order to foster research in this field, we have compiled a new multi-perspective dataset, PAKVehicle-ReId, captured by real-world surveillance cameras in urban cities of the developing country of Pakistan. To the best of our knowledge, this is the first such dataset collected under unconstrained conditions in a developing Asian region. The dataset comprises 80,000 images of 20,000 unique vehicles. Additionally, a deep learning-based technique for extracting multi-dimensional robust features for vehicle re-identification using convolutional neural networks has been proposed. The results show the effectiveness of the proposed method on the PAKVehicle-ReId dataset as well as on two other existing datasets, VeRI-776 and VehicleID. The code and link to the dataset can be obtained from the following GitHub repository: https://github.com/Vision-At-SEECS/PakvehicleReId .

Super-resolution (SR) is a powerful technique for enhancing the quality of remote sensing imagery, which in turn can improve the accuracy of various computer vision tasks, such as object detection, classification, and segmentation. Deep convolutional neural networks (CNNs) have demonstrated significant progress in this field, and attention mechanisms are widely adopted in deep CNNs as they allow the models to assign weights to important areas within the feature map. In this paper, we propose the channel-wise gated attention (CGA) module, which integrates attention across the feature map channels and scales the resulting feature map through a gating parameter, leading to performance improvements. Furthermore, we present an SR framework that employs multiple attention blocks, with the CGA module serving as the core of each block, to enhance the spatial resolution of remote sensing imagery. Our proposed network, the channel-wise gated attention Network (CGA-Net), outperforms other attention-based deep SR models for 4 × - and 8 × -upsampling on two remote sensing datasets: Satellite Imagery Multi-Vehicles Dataset (SIMD), consisting of 5000 high-resolution remote sensing images, and DOTA, a large-scale satellite imagery dataset. We conduct several experiments to evaluate the effectiveness of our SR framework for object detection on the SIMD dataset. The code and trained weights for the proposed framework can be found at this link: https://github.com/Vision-At-SEECS/CGA-Net .

With the burgeoning global demand for seafood, potential solutions like aquaculture are increasingly significant, provided they address issues like pollution and food security challenges in a sustainable manner. However, significant obstacles such as disease outbreaks and inaccurate biomass estimation underscore the need for optimized solutions. This paper proposes “Fish-Sense”, a deep learning-based pipeline inspired by the human visual system’s ability to recognize and classify objects, developed in conjunction with fish farms, aiming to enhance disease detection and biomass estimation in the aquaculture industry. Our automated framework is two-pronged: one module for biomass estimation using deep learning algorithms to segment fish, classify species, and estimate biomass; and another for disease symptom detection symptoms, employing deep learning algorithms to classify fish into healthy and unhealthy categories, and subsequently identifying symptoms and locations of bacterial infections if a fish is classified as unhealthy. To overcome data scarcity in this field, we have created four novel real-world datasets for fish segmentation, health classification, species classification, and fish part segmentation. Our biomass estimation algorithms demonstrated substantial accuracy across five species, and the health classification. These algorithms provide a foundation for the development of industrial software solutions to improve fish health monitoring in aquaculture farms. Our integrated pipeline facilitates the transition from research to real-world applications, potentially encouraging responsible aquaculture practices. Nevertheless, these advancements must be seen as part of a comprehensive strategy aimed at improving the aquaculture industry’s sustainability and efficiency, in line with the United Nations’ Sustainable Development Goals’ evolving interpretations. The code, trained models, and the data for this project can be obtained from the following GitHub repository: https://github.com/Vision-At-SEECS/Fish-Sense .

An effective anticoagulation therapy is required for patients with atrial fibrillation because it presents a significant risk of stroke. The current study evaluates the relative safety as well as efficacy of rivaroxaban in patients who are diagnosed with atrial fibrillation. A thorough literature review of relevant databases was conducted, focusing on academic and clinical studies that were published from 2017 onward. Inclusion criteria comprised randomized controlled trials and other observational studies comparing the incidence of stroke and the safety index of rivaroxaban in atrial fibrillation. We followed the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) for data overview reporting and overview. A total of 21 studies were selected based on the inclusion criteria. A total of 19/21 studies advocated the adoption of rivaroxaban for minimizing stroke incidence. Rivaroxaban also showed superiority in achieving the therapeutic objectives, i.e., reduction in the incidence of stroke. The results for rivaroxaban against warfarin showed an improved safety index and effectiveness of rivaroxaban. The total effect size for the analysis was calculated to be Z=2.62 (p-value=0.009). The individual effect of all studies favored the \"rivaroxaban\" group. The heterogeneity in the study was as follows: tau =0.10; chi =110.10, df=6; I =95%. The second analysis for risk reduction and incidence of stroke after rivaroxaban therapy also showed a bias towards rivaroxaban therapy. The combined effect for the analysis was found to be as follows: HR=0.73 ((95% CI: 0.50, 1.07). The total effect was calculated to be Z=1.61 (p-value= 0.10). The heterogeneity was found to be as follows: tau = 0.20, chi =89.97, df=6, I =93%. Standard dosing of rivaroxaban emerges as a preferred strategy for stroke prevention, balancing efficacy and safety. Clinical decision-making should consider individual patient characteristics and future research should delve into specific subpopulations and long-term outcomes to further refine treatment guidelines.

This research article presents a design parameter assessment technique for three-dimensional printed hip joint implants. A coupled experimental-simulation-based design technique, addressing minimum coating thickness, hardness, and adhesion requirements, is proposed for safe designs of individual three-dimensional printed hip joint implants. The purpose of this study is to analyze the mechanical properties of individual three-dimensional scanned hip joint human bone geometry through numerical simulation and relate these properties to hardness and adhesion values of bio-compatible coatings. The hardness and adhesion experimental results are discussed, which are then related to numerically obtained normal and shear stresses. Finite element analysis on original bone three-dimensional scanned model along with experimental results for investigating the minimum design requirements has not been reported before. Four ceramic coating materials, that is, alumina, CoCrMo, TiN, and zirconia, are discussed for each routine human physical activity. A comprehensive mesh independence study is conducted to ensure that the mesh has no effect on the variation of results. After finite element analysis, it was concluded that the pelvis bone can be taken as a vital bone for recommending design conditions. The finite element results are then coupled with experimental results as the maximum principal stress obtained from the finite element analysis is used to obtain minimum hardness requirements. Similarly, maximum shear stress obtained from the finite element analysis is used to obtain minimum adhesion requirements for three-dimensional printed implants. The coating thickness necessary to obtain minimum hardness and adhesion requirements is then predicted for TiN coating case.

ABSTRACT Owing to growing exploration in nanotechnology, nano-particles application in various fields of industries and medicine is growing. However, limited study is available on their toxicological impacts which can adversely affect the organism's health and their environment. Current research was designed to study the possible toxicity of iron oxide nano-particles on common carp, C. carpio after exposure period of 96 hours by the analysis of their haematological parameters. Fish were segregated into three groups (10fish/treatment). The iron oxide nano-particles at 0.25g/l doze were administered orally to treatment T1 and intravenously from caudal vein of fish to treatment T2. After 96h of exposure period, the blood was collected from fishes by the caudal vein puncture method into tubes containing anticoagulants EDTA and transferred immediately to the laboratory for the assessment of their blood profile. There was recorded no mortality after 96h of exposure period. IONPs significantly affected the counts of WBCs, Hb, MCH and MCHC of experimental and control groups. The analysis of blood profile demonstrated that haematological parameters; the number of WBCs and Hb were increased in T1 and decreased in T2 in relation to T0. The counts of RBCs, HCT, MCV and PLT were found to be increased in both experimental groups as compared to control one. It is inferred from current results that IONPs have toxic effect on the haematology of C. carpio. Moreover, oral route of administering IONPs was found to be more toxic than intravenous one. Present study can be beneficial for the safety of aquatic environment and management of aquatic toxicity.

The first decade of doing bioethics through Pakistan's Centre of Biomedical Ethics and Culture (CBEC) was an on the job learning experience with no similar centres in the region to show the way. Although periodic evaluations from faculty, students, alumni and others helped in developing the academic initiatives and research undertaken by the Centre, the risk of bias inherent in stakeholders' opinions was always a possibility. The faculty therefore came to believe that an external review by a peer group would provide an impartial assessment of the Centre's accomplishments and help identify future directions. While external reviews of clinical departments of hospitals are routinely undertaken, no similar process for bioethics centres has been reported in the literature, necessitating the development of the entire review process de novo. Eight scholars from within Pakistan and abroad, with relevant backgrounds, were invited to conduct the review over a four day period. Their interactions included examining documents, attending academic sessions and interviewing faculty, students and alumni. Their review report, while noting the academic and research achievements of the Centre in its first decade also highlighted areas needing attention. This paper shares with the international bioethics community the authors' experience of organizing an external review of a bioethics centre, and its short-term impact. Even though such reviews for bioethics centres are neither mandatory nor simple to conduct, an objective external assessment can prove invaluable for future planning. Based on this experience, the authors believe that other bioethics centres would also benefit from conducting this exercise.