The study of co-fusion was one of the essential topics in the history of metallurgy in China. Simulation experiments had been an essential concept in the study of the co-fusion steelmaking process. This paper mainly studied the simulation experiments of co-fusion from two aspects: the replication of co-fusion swords by three different methods, and the micro-analysis of the co-fusion samples. The experimental results indicated that several co-fusion swords could be made by different processes, but the carbon content and surface hardness were quite different. During repeated forging welded, the microstructure of the samples transformed from laminated to homogenized, finally the steel with a uniform carbon content was obtained. It was challenging to find the characteristics of co-fusion from the homogenized samples. The results prompted people to rethink the microstructure characteristics of ancient co-fusion artifacts.

Sensor fusion technology is one of extensive used methods in the field of robot, aerospace and target tracking control. In this paper, the generalized sensor fusion framework, named the closed-loop fusion (CLF) is analyzed and the optimal design principle of filter is proposed in detail. Fusion error optimization problem, which is the core issue of fusion design, is also solved better through the feedback compensation law of CLF framework. Differently from conventional methods, the fusion filter of CLF can be optimally designed and the determination of superposition of fusion information is avoided. To show the validity, simulation and experimental results are to be submitted.

Recent deep learning frameworks draw a strong research interest in the application of ego-motion estimation as they demonstrate a superior result compared to geometric approaches. However, due to the lack of multimodal datasets, most of these studies primarily focused on a single sensor-based estimation. To overcome this challenge, we collect a unique multimodal dataset named LboroAV2, using multiple sensors including camera, Light Detecting And Ranging (LiDAR), ultrasound, e-compass and rotary encoder. We also propose an end-to-end deep learning architecture for fusion of RGB images and LiDAR laser scan data for odometry application. The proposed method contains a convolutional encoder, a compressed representation and a recurrent neural network. Besides feature extraction and outlier rejection, the convolutional encoder produces a compressed representation which is used to visualise the network's learning process and to pass useful sequential information. The recurrent neural network uses this compressed sequential data to learn the relation between consecutive time steps. We use the LboroAV2 and KITTI VO datasets to experiment and evaluate our results. In addition to visualising the network's learning process, our approach gives superior results compared to other similar methods. The code for the proposed architecture is released in GitHub and accessible publicly.

The framework proposed by Alison Druin about 20 years ago, which defined the roles children play in technology design, has been widely adopted by the Child-Computer Interaction (CCI) community. While some studies have adopted relevant roles as presented in the framework, others have argued for extending the framework to include newly identified roles. Still, other studies argue that Druin's framework failed to account for roles children may take up as they interact with peers or with tools. Consequently, this systematic literature review examines children’s emerging and changing roles in the codesign of new technologies. Specifically, we answered the research question: What new roles emerge in research as children co-design new technologies? Our effort aims at providing evidence of new roles children have adopted in literature, which may help researchers in the CCI community make more informed decisions about participatory design approaches with children.

Ocean big data is the scientific practice of using big data technology in the marine field. Data from satellites, manned spacecraft, space stations, airship, unmanned aerial vehicles, shore-based radar and observation stations, exploration platforms, buoys, underwater gliders, submersibles, and submarine observation networks are seamlessly combined into the ocean’s big data. Increasing numbers of scholars have tried to fully analyze the ocean’s big data. To explore the key research technology knowledge graphs related to ocean big data, articles between 1990 and 2020 were collected from the “Web of Science”. By comparing bibliometric software and using the visualization software Cite-Space, the pivotal literature related to ocean big data, as well as countries, institutions, categories, and keywords, were visualized and recognized. Journal co-citation analysis networks can help determine the national distribution of core journals. Co-citation analysis networks for documents show authors who are influential at key technical levels. Key co-occurrence analysis network keywords can determine research hot spots and research frontiers. The three supporting elements of marine big data research are shown in the co-citation network. These elements are author, institution, and country. By examining the co-occurrence of keywords, the key technology research directions for future marine big data were determined.

Nuclear fusion is essential for the sexual reproduction of various organisms, including plants, animals, and fungi. During the life cycle of flowering plants, nuclear fusion occurs three times: once during female gametogenesis and twice during double fertilization, when two sperm cells fertilize the egg and the central cell. Haploid nuclei migrate in an actin filament-dependent manner to become in close contact, then two nuclei fuse. The nuclear fusion process in plant reproduction is achieved by the sequential nuclear membrane fusion events. Recent molecular genetic analyses using Arabidopsis thaliana showed the conservation of nuclear membrane fusion machinery between plants and the budding yeast Saccharomyces cerevisiae. These include the heat shock protein 70 in the endoplasmic reticulum and conserved nuclear membrane proteins. Analyses of A. thaliana mutants of these components show that completion of the sperm nuclear fusion at fertilization is essential for proper embryo and endosperm development.

PG9, PG16, PGT121, and PGT145 antibodies were identified from culture media of activated memory B-cells of an infected donor and shown to neutralize many HIV-1 strains. Since HIV-1 spreads via both free virions and cell-cell fusion, we examined the effect of the antibodies on HIV-1 Env-mediated cell-cell fusion. Clone69TRevEnv cells that express Env in the absence of tetracycline were labeled with Calcein-AM Green, and incubated with CD4+ SupT1 cells labeled with CellTrace™ Calcein Red-Orange, with or without antibodies. Monoclonal antibodies PG9, PG16, 2G12, PGT121, and PGT145 (at up to 50 µg/mL) had little or no inhibitory effect on fusion between HIV-Env and SupT1 cells. By contrast, Hippeastrum hybrid agglutinin completely inhibited fusion. Our results indicate that transmission of the virus or viral genetic material would not be inhibited by these broadly neutralizing antibodies. Thus, antibodies generated by HIV-1 vaccines should be screened for their inhibitory effect on Env-mediated cell-cell fusion.

Integrating sustainable processes and innovative waste utilization not only addresses environ-mental challenges but also aligns with evaluating energy sustainability and creating the circular waste management. This study presents a comparative analysis of liquid fuel production from waste tires and water hyacinth using two thermochemical methods: co-pyrolysis (direct method) and co-gasification integrated with the Fischer-Tropsch (FT) process (indirect method). The As-pen Plus simulation software version 9 is employed to develop models, determining optimal operating conditions for maximum liquid fuel, and assessing economic viability. Co-pyrolysis simulations reveal an increase in oil products and a decrease in gas products with higher blending weight ratios of waste tires/water hyacinth (W/B) and lower pyrolyser temperatures. Operating at 400°C with a blending weight ratio of 75:25 provided the maximum liquid fuel rate of 6649.22 gal/day. For co-gasification, optimal conditions (W/B = 50:50, T = 800°C, steam to feed ratio (S/F) = 1) result in the highest syngas yield of 115.92 kmol/h. Fischer-Tropsch simulations demonstrate an increase in gasoline and a decrease in diesel with rising reactor temperatures. At 230°C, the maximum liquid fuel rate reaches 8817.15 gal/day. The economic and production yield analysis indicates that the indirect method better than the direct method, providing higher liquid fuel yields and investment worthiness.

The severe respiratory distress syndrome (SRDS) has been a significant clinical issue in modern respiratory medicine. Its role in COVID-19 pandemic is not well defined. Outside-the-hospital SRDS is usually community-acquired septic pneumonia; however, in-hospitals incidences are complicated by co-infections. While SRDS is genetically selected in European and African origins, these are not clear in Middle East, particularly in COVID-19 backgrounds. There is a severe paucity in high quality data on correlations between COVID-19, ARDS, co-infectome, and patient demographics. We have conducted a comprehensive investigation on 298 patients for associations of SRDS, coinfections, and patient demographics on COVID-19 patients’ outcomes. Of these, 9.4% (n=28) had SRDS, and the rest (90.6%) had not. 54% of those with SRDS died while 84% survived; SRDS fatality was highly significant (Chi-square test P-value = 0.00000246). Irrespective of gender, the age of patients was significantly associated with SRDS (72.9 +/-8.9) compared to those without it (56.2 +/-15.1). However, there was no significant difference neither in the age of admitted patients before COVID-19 (58.5 +/-15.3) and during COVID-19 (57.2 +/-15.5) nor in the gender and COVID-19 fatality (Fisher Exact test 2-sided 1.000, 1-sided .546) ruling out that SRDS age-specificity were selected by virus susceptibility. A 100% of SRDS patients without bacterial co-infections survived while only 25% of those with co- infectome did not; this association was highly significant (P value= 0.00041). Co-infections alone without underlying SRDS was also associated with high fatality among patients (P value= 0.00000000076). Almost all COVID-19 patients without co-infectome (99.2%) survived while 28% of those with bacterial co-infection died. The major bacterial pathogens that potentially predisposed to SRDS, were Acinetobacter baumannii, and Escherichia coli either alone or in a mixed infection with Klebsiella pneumoniae were predominant species identified during SRDS attack. Thus, Gram-negative co-infectome potentially induced fatal SRDS aggravating COVID-19 outcome. These findings have significant clinical implications in specific differential diagnosis of SRDS syndromes for subsequent empiric therapy and patient management strategies. Future vertical investigation for similar mechanisms of cytokine-induced SRDS by Gram negative pathogens is imperative since hypervirulent strains are rapidly circulating in the region. The study is limited by a single center study confined to Ha’il hospitals; large scale investigation in major national hospitals would gain more insights.

Leishmania parasites present astonishing adaptative abilities that represent a matter of life or death within disparate environments during the heteroxenous parasite life cycle. From an evolutionary perspective, organisms develop methods of overcoming such challenges. Strategies that extend beyond the genetic diversity have been discussed and include variability between parasite cells during the infections of their hosts. The occurrence of Leishmania subpopulation fluctuations with variable structural genomic contents demonstrates that a single strain might shelter the variability required to overcome inconsistent environments. Such intrastrain variability provides parasites with an extraordinary ability to adapt and thus survive and propagate. However, different perspectives on this evolution have been proposed. Strains or species living in the same environment can cooperate but also compete. These interactions might increase the replication rate of some parasites but cause the loss of more aggressive competitors for others. Adaptive responses to intra- and interspecific competition can evolve as a fixed strategy (replication is adapted to the average genetic complexity of infections) or an optional strategy (replication varies according to the genetic complexity of the current infection). This review highlights the complexity of interspecies and intrastrain interactions among Leishmania parasites as well as the different factors that influence this interplay.

Gender recognition is trivial for physiotherapist, but it is considered a challenge for computers. The electromyography (EMG) and heart rate variability (HRV) were utilized in this work for gender recognition during the stepping exercise using a stepper. The relevant features were extracted and selected. The selected features were then fused to automatically predict gender recognition. However, the feature selection for gender classification became a challenge to ensure better accuracy. Thus, in this paper, a feature selection approach based on both the performance and the diversity between the two features from the rank-score characteristic (RSC) function in a combinatorial fusion approach (CFA) was employed. Then, the features from the selected feature sets were fused using a CFA. The results were then compared with other fusion techniques such as naive bayes (NB), decision tree (J48), k-nearest neighbor (KNN) and support vector machine (SMO). Besides, the results were also compared with previous researches in gender recognition. The experimental results showed that the CFA was efficient for feature selection. The fusion method was also able to improve the accuracy of the gender recognition rate. The CFA provides much better gender classification results which is 94.51% compared to Nazarloo's work (90.34%) and other classifiers.

Tungsten fibre-reinforced tungsten composites (Wf/W) have been in development to overcome the inherent brittleness of tungsten as one of the most promising candidate for the first wall and divertor armour material in a future fusion power plant. As the development of Wf/W continues, the fracture toughness of the composite is one of the main design drivers. In this contribution the efforts on size upscaling of Wf/W based on Chemical Vapour Deposition (CVD) is shown together with fracture mechanical tests of two different size samples of Wf/W produced by CVD. Three-point bending tests according to ASTM E399 for brittle materials were used to get a first estimation of the toughness. A provisional fracture toughness value of up to 346MPam1/2 was calculated for the as-fabricated material. As the material does not show a brittle fracture in the as-fabricated state, the J-Integral approach based on the ASTM E1820 was additionally applied for this state. A maximum value of the J-integral of 41kJ/m2 (134,8MPam1/2) was determined for the largest samples. Post mortem investigations were employed to detail the active mechanisms and crack propagation.

The quality of digital elevation models (DEMs) is inevitably affected by the limitations of the imaging modes and the generation methods. One effective way to solve this problem is to merge the available datasets through data fusion. In this paper, a fusion-based global DEM dataset (82°S-82°N) is introduced, which we refer to as GSDEM-30. This is a 30-m DEM mainly reconstructed from the unfilled SRTM1, AW3D30, and ASTER GDEM v2 datasets combining the multi-source and multi-scale fusion techniques. A comprehensive evaluation of the GSDEM-30 data, as well as the 30-m ASTER GDEM v2 and AW3D30 DEM, was presented. Global ICESat GLAS data and the local National Elevation Dataset (NED) were used as the reference for the vertical accuracy validation, while GlobeLand30 was introduced for the landscape analysis. Furthermore, we employed the maximum slope approach to detect the potential artefacts in the DEMs. The results show that the GDEM data are seriously affected by noise and artefacts. With the advantage of the multiple datasets and the refined post-processing, the GSDEM-30 are contaminated with fewer anomalies than both ASTER GDEM and AW3D30. The fusion techniques used can also be applied to the reconstruction of other fused DEM datasets.

New setting is introduced to study types of coloring numbers, degree of vertices, degree of hyperedges, co-degree of vertices, co-degree of hyperedges, neutrosophic degree of vertices, neutrosophic degree of hyperedges, neutrosophic co-degree of vertices, neutrosophic co-degree of hyperedges, neutrosophic number of vertices, neutrosophic number of hyperedges in neutrosophic hypergraphs. Different types of procedures including neutrosophic (r, n)−regular hypergraphs and neutrosophic complete r−partite hypergraphs are proposed in this way, some results are obtained. General classes of neutrosophic hypergraphs are used to obtain chromatic number, the representatives of the colors, degree of vertices, degree of hyperedges, co-degree of vertices, co-degree of hyperedges, neutrosophic degree of vertices, neutrosophic degree of hyperedges, neutrosophic co-degree of vertices, neutrosophic co-degree of hyperedges, neutrosophic number of vertices, neutrosophic number of hyperedges in neutrosophic hypergraphs. Using colors to assign to the vertices of neutrosophic hypergraphs and characterizing representatives of the colors are applied in neutrosophic (r, n)−regular hypergraphs and neutrosophic complete r−partite hypergraphs. Some questions and problems are posed concerning ways to do further studies on this topic. Using different ways of study on neutrosophic hypergraphs to get new results about number, degree and co-degree in the way that some number, degree and co-degree get understandable perspective. Neutrosophic (r, n)−regular hypergraphs and neutrosophic complete r−partite hypergraphs are studied to investigate about the notions, coloring, the representatives of the colors, degree of vertices, degree of hyperedges, co-degree of vertices, co-degree of hyperedges, neutrosophic degree of vertices, neutrosophic degree of hyperedges, neutrosophic co-degree of vertices, neutrosophic co-degree of hyperedges, neutrosophic number of vertices, neutrosophic number of hyperedges in neutrosophic (r, n)−regular hypergraphs and neutrosophic complete r−partite hypergraphs. In this way, sets of representatives of colors, degree of vertices, degree of hyperedges, co-degree of vertices, co-degree of hyperedges, neutrosophic degree of vertices, neutrosophic degree of hyperedges, neutrosophic co-degree of vertices, neutrosophic co-degree of hyperedges, neutrosophic number of vertices, neutrosophic number of hyperedges have key points to get new results but in some cases, there are usages of sets and numbers instead of optimal ones. Simultaneously, notions chromatic number, the representatives of the colors, degree of vertices, degree of hyperedges, co-degree of vertices, co-degree of hyperedges, neutrosophic degree of vertices, neutrosophic degree of hyperedges, neutrosophic co-degree of vertices, neutrosophic co-degree of hyperedges, neutrosophic number of vertices, neutrosophic number of hyperedges are applied into neutrosophic hypergraphs, especially, neutrosophic (r, n)−regular hypergraphs and neutrosophic complete r−partite hypergraphs to get sensible results about their structures. Basic familiarities with neutrosophic hypergraphs theory and hypergraph theory are proposed for this article.

At Mae-Moh power plant, Thailand, superheater tubes, which are exposed in fly ash environ-ment, often degrade due to solid particle erosion. To extend the service lifetime of the superheater tubes, the high velocity oxy-fuel (HVOF) thermal spray technique is used to deposit a protective coating on the material, SA213-T22 steel. In this work, the solid particle erosion of the Co-28Cr and WC-12Co coatings was investigated using erodent particle impingement at the angles of 30o and 90o with an average particle size of 60 μm. The erosion behavior of SA213-T22 with and without Co-28Cr and WC-12Co coatings was explained using ductile and brittle erosion modes. The erosion test resulted in the brittle mode for both Co-28Cr and WC-12Co coatings, while SA213-T22 without coating indicated the ductile mode. On the investigation of surface morphology, the Co-28Cr coating showed mostly microcracks in contrast with the WC-12Co coating, fracture, de-bonding and deep cavities were also observed. Erosion resistance of the Co-28Cr coating was significantly higher than the WC-12Co coating, due to high hardness, low porosity and high density of the coating.

The main objective of this paper is to identify the major research areas of ChatGPT through term and keyword co-occurrence network mapping techniques. For conducting the present study, total of 577 publications were retrieved from the Lens database for the network visualization. The findings of the study showed that “chatgpt” occurrence in maximum number of times followed by its related terms such as artificial intelligence, large language model, gpt, study etc. This study will be helpful to library and information science as well as computer or information technology professionals.

Sign language recognition is essential in hearing-impaired people’s communication. Sign language recognition is an important concern in computer vision and has been developed with rapid progress in image recognition technology. However, sign language recognition using a general monocular camera has problems with occlusion and recognition accuracy in sign language recognition. In this research, we aim to improve accuracy by using a 2-axis bending sensor as an aid in addition to image recognition. We aim to achieve higher recognition accuracy by acquiring hand keypoint information of sign language actions captured by a monocular RGB camera and adding sensor assist. To improve sign language recognition, we need to propose new AI models. In addition, the amount of dataset is small because it uses the original data set of our laboratory. To learn using sensor data and image data, we used MediaPipe, CNN, and BiLSTM to perform sign language recognition. MediaPipe is a method for estimating the skeleton of the hand and face provided by Google. In addition, CNN is a method that can learn spatial information, and BiLSTM can learn time series data. Combining the CNN and BiLSTM methods yields higher recognition accuracy. We will use these techniques to learn hand skeletal information and sensor data. Additionally, the 2-axis Bending sensor glove data support training AI model. Using these methods, we aim to improve the recognition accuracy of sign language recognition by combining sensor data and hand skeleton data. Our method performed better than using skeletal information, achieving 96.5% accuracy in Top-1.

In computer vision and image analysis, Convolutional Neural Networks (CNNs) and other deep learning models are at the forefront of research and development. These advanced models have proven to be highly effective in tasks related to computer vision. One technique that has gained prominence in recent years is the construction of ensembles using Deep CNNs. These ensembles typically involve combining multiple pre-trained CNNs to create a more powerful and robust network. The purpose of this study is to evaluate the effectiveness of building CNN ensembles by combining several advanced techniques. Tested here are CNN ensembles constructed by replacing ReLU layers with different activation functions, employing various data augmentation techniques, and utilizing several algorithms, including some novel ones, that perturb network weights. Experimental results performed across many data sets representing different tasks demonstrate that our proposed methods for building deep ensembles produces superior results. All the resources required to replicate our experiments are available at https://github.com/LorisNanni.

Oncogenic fusion proteins, arising from chromosomal rearrangements, have emerged as prominent drivers of tumorigenesis and crucial therapeutic targets in cancer research. In recent years, the potential of small molecular inhibitors in selectively targeting fusion proteins has exhibited significant prospects, offering a novel approach to combat malignancies harboring these aberrant molecular entities. This review provides a comprehensive overview of the current state of small molecular inhibitors as therapeutic agents for oncogenic fusion proteins. We discuss the rationale for targeting fusion proteins, elucidate the mechanism of action of inhibitors, assess the challenges associated with their utilization, and provide a summary of the clinical progress achieved thus far. The objective is to provide the medicinal community with current and pertinent information and to expedite the drug discovery programs in this area.

One of the challenges in Content-Based Image Retrieval (CBIR) is to reduce the semantic gaps between low-level features and high-level semantic concepts. In CBIR, the images are represented in the feature space and the performance of CBIR depends on the type of selected feature representation. Late fusion also known as visual words integration is applied to enhance the performance of image retrieval. The recent advances in image retrieval diverted the focus of research towards the use of binary descriptors as they are reported computationally efficient. In this paper, we aim to investigate the late fusion of Fast Retina Keypoint (FREAK) and Scale Invariant Feature Transform (SIFT). The late fusion of binary and local descriptor is selected because among binary descriptors, FREAK has shown good results in classification-based problems while SIFT is robust to translation, scaling, rotation and small distortions. The late fusion of FREAK and SIFT integrates the performance of both feature descriptors for an effective image retrieval. Experimental results and comparisons show that the proposed late fusion enhances the performances of image retrieval.

The PAX8/PPARγ rearrangement, producing the PAX8–PPARγ fusion protein (PPFP), is thought to play an essential role in the oncogenesis of thyroid follicular tumors. To identify PPFP-targeted drug candidates and establish an early standard of care for thyroid tumors, we performed ensemble docking-based compound screening. Specifically, we investigated which pocket structure should be adopted to search for a promising ligand compound for the PPFP; the position of the ligand binding pocket on the PPARγ side of the PPFP is common to that of PPARγ; however, the shape is slightly different between them due to environmental factors. We developed a method for selecting a PPFP structure with a relevant pocket and high prediction accuracy for ligand binding. This method was validated using PPARγ, whose structure and activity values are known for many compounds. Then, we performed docking calculations to PPFP for 97 drug or drug-like compounds with a thiazolidine backbone, which is one of the characteristics of ligands that bind well to PPARγ, registered in the DrugBank database. Furthermore, the binding affinities of promising ligand candidates were estimated more reliably using the molecular mechanics-Poisson–Boltzmann surface area method. Thus, we propose promising drug candidates for the PPFP with a thiazolidine backbone.

Background and Objectives: Although adult spinal deformity (ASD) surgery brought about the improvement of quality of life in patients, it accompanied with a high invasiveness of surgery and several complications. Specifically, mechanical complications of rod fracture, instrumentation failures, and pseudarthrosis are still unsolved issues. To better improve these problems, the oblique lateral interbody fusion at L5/S1 (OLIF51) was introduced since 2015 in my institution. The objective of this study was to compare the clinical and radiographic outcomes of anterior-posterior combined surgery for ASD between the use of OLIF51 versus transforaminal interbody fusion (TLIF) at L5/S1. Materials and Methods :A total of 117 ASD patients received anterior-posterior correction surgeries either use of OLIF51 (35 patients) or L5/S1 TLIF (82 patients). In both groups, L1-5 OLIF and minimally invasive posterior procedures of hybrid or circumferential MIS were employed. The sagittal and coronal spinal alignment and spino-pelvic parameters are recorded preoperatively and at follow-up. The quality of life parameters and visual analogue scale were evaluated as well as surgical complications at follow-up. Results: The average follow-up period was thirty months (13-84). The average fused segments were eight (4-12). The operation time and estimated blood loss were significantly smaller in OLIF51 that those in TLIF. The PI-LL mismatch, LLL, L5/S1 segmental lordosis, and L5 coronal tilt were significantly better in OLIF51 than TLIF. The complication rate was statistically equivalent between two groups. Conclusion: The introduction of OLIF51 for adult spine deformity surgery led to the decrease of operation time and estimated blood loss as well as the improvement of sagittal and coronal correction when compared to TLIF.

Cervical injuries from athletic activities are rare; they can have severe consequences if not diagnosed and managed promptly. The choice of diagnostic imaging modality is pivotal in ensuring timely and accurate diagnosis. We detail the case of a 19-year-old female athlete who sustained a C2 Durel Type II Subclass C fracture during a short-track speed skating championship. Initial evaluation using X-ray imaging at the athletic center medical facility did not detect the injury, allowing her to continue competing. Persistent pain led to further evaluation at our institution, where MRI and CT scans confirmed the fracture. Approximately 45 days post-injury, the patient underwent a successful surgical intervention utilizing O-arm CBCT navigation for C1-C2 dorsal fusion. Post-surgery, she embarked on a comprehensive rehabilitation program and fully recovered within 12 weeks. This case underscores the limitations of relying solely on X-ray imaging for diagnosing cervical fractures post-trauma. Our findings advocate prioritizing CT scans as a primary diagnostic tool in such scenarios, emphasizing the need for a robust diagnostic approach to ensure athlete safety and well.

Frailty, an age-related decline in homeostatic reserves, markedly proceeded during the coronavirus disease 2019 pandemic. To continuously assess frailty status, a remote system is urgently required. We aimed to co-design/co-develop an online frailty check (FC) application alongside FC supporters who were facilitators in a pre-existing onsite FC program. The online FC included a screening measurement for sarcopenia and an 11-item questionnaire covering dietary, physical, and social behaviors. Using prototype applications, 55 opinions obtained from 32 FC supporters (median 74.0 years) were categorized and reflected refinement. Regarding the self-efficacy of FC supporters, a significant increase in social positioning was seen after the mock test (P=.031). For FC supporters and participants, the average system usability scale (SUS) score was 70.2±10.3 points, which was “marginally high” for acceptability and “good” for the adjective range. Multiple regression analysis showed that the SUS score was significantly correlated with online-onsite reliability but not online communication, even after adjusting by age, sex, education level, and ICT proficiency (b=0.400, 95% CI: 0.243-1.951, P=.013). Additionally, a significant association between onsite and online FC scores was observed (R=0.670, P=.001). Our online FC application was evaluated to be a valuable tool to practically assess frailty status remotely.

This research uses ARM-based FPGA to implement the computation of a virtual-real fusion hardware system. It also evaluates the acceleration effect of virtual-real fusion execution speed after connecting related hardware acceleration and provides a reference for real-time information fusion system design. The hardware uses Xilinx Zynq UltraScale+ MPSoC ZCU102 Evaluation Kit. It also obtains color and depth images with Intel® RealsenseTM D435i depth cameras. This system receives image data through the Linux system built on the ARM and fed to the FPGA for object detection using CNN models. In addition, it develops a module for rapidly performing registration between the color images and the depth images. It can calculate the size and position of the display information on the transparent display according to the pixel coordinates and depth values of the human eye and the object. The fusion took about 47ms on a personal computer with a GPU RTX2060 and 25ms on the ZCU102. The acceleration is nearly 168%. Finally, the results were successfully transplanted into the retail display system for demonstration.

Abstract: (1) Background: Minimally-invasive sacroiliac joint (SIJ) fusion is the preferred surgical intervention to treat chronically severe pain associated with SIJ degeneration and dysfunction. (2) Methods: This paper details the ten-step surgical procedure associated with the postero-inferior approach using the PsiF™DNA Sacroiliac Joint Fusion System. (3) Results: The posterior surgical approach with an inferior operative trajectory (postero-inferior) utilizes easily identifiable landmarks to provide the safest, most direct access to the articular joint space for transfixing device placement. Implanting the device through the subchondral bone, provides maximum fixation and stabilization of the joint by utilizing an optimal amount of cortical bone-implant interface. Approaching the joint from the inferior trajectory also places the implant perpendicular to the S1 endplate at a “pivot point” near the sacral axis of rotation, which addresses the most significant motion of the joint. (4) Conclusions: Further observational data from real-world clinical use are encouraged to further validate this procedure as the surgical preference for minimally-invasive SIJ fusion.

According to the World Health Organization (WHO), dementia is the seventh leading reason of death among all illnesses and one of the leading causes of disability among the world’s elderly people. Day by day the number of Alzheimer’s patients is raising. Considering the increasing rate and the dangers, Alzheimer’s disease should be diagnosed carefully. Machine learning is a potential technique for Alzheimer’s diagnosis but general users do not trust machine learning models due to the black-box nature. Even, some of those models do not provide the best performance because of using only neuroimaging data. To solve these issues, this paper proposes a novel explainable Alzheimer’s disease prediction model using a multimodal dataset. This approach performs a data-level fusion using clinical data, Freesurfer MRI segmentation data, and psychological data. For Alzheimer’s disease vs cognitively normal prediction, the random forest classifier provides 100% accuracy. Furthermore, Alzheimer’s disease and non-Alzheimer’s dementia should be classified properly because their symptoms are similar. To the best of our knowledge, we are the first to present a three-class classification on Alzheimer’s disease vs cognitively normal vs non-Alzheimer’s dementia and achieved 99.86% accuracy using an ensemble model. Besides, a novel Alzheimer’s patient management architecture is also proposed in this work..

In antimicrobial-peptide/protein engineering, understanding the peptide/protein’s adaptability to harsh environmental conditions such as urea, proteases, fluctuating temperatures, high salts provide enormous insight into the pharmacokinetics and pharmacodynamics of the engineered peptide/protein and its ability to survive the harsh internal environment of the human body such as the gut or the harsh external environment to which they are applied. A previous work in our laboratory demonstrated that our cloned Eɛ34 TSP showed potent antimicrobial activity against Salmonella newington, and more so, could prevent biofilm formation on decellularized tissue. In this work, the effects of urea-acid on the Eɛ34 stability is studied, and the results demonstrates that at lower pHs of 3 and 4 with urea the protein was denatured into monomeric species. However, the protein withstood urea denaturation above pH of 5 and thus remained as trimeric protein. The mechanism of denaturation of Eɛ34 TSP seems to show that urea denatures proteins by depleting hydrophobic core of the protein by directly binding to the amide units via hydrogen bonds. The results of our in-silico investigation determined that urea binds with Eɛ34 TSP with relative free energies range of -3.4 to -2.9 kcal/mol at the putative globular head binding domain of the protein. The urea molecules interacts with with the protein’s predicted hydrophobic core, thus, disrupting and exposing the shielded hydrophobic moieties of Eɛ34 TSP to the solvent. We further showed that after the unfolding of Eɛ34 TSP via urea-acid, renaturation of the protein to its native conformation was possible within few hours. This unique characteristic of refolding of Eɛ34 TSP which is similar to that of the P22 phage tailspike protein is of special interest to protein scientists and can also be exploited in antimicrobial-protein engineering.

Classification of human actions from uni-modal and multi-modal datasets is an ongoing research problem in computer vision. This review is aimed to scope current literature on data-fusion and action-recognition techniques and to identify gaps and future research direction. Success in producing cost-effective and portable vision-based sensors has dramatically increased the number and size of datasets. The rise in number of action recognition datasets intersects with advances in deep-learning architectures and computational support, both of which offer significant research opportunities. Naturally, each action-data modality - such as RGB, depth, skeleton, and infrared - has distinct characteristics; therefore, it is important to exploit the value of each modality for better action recognition. In this article we will focus solely on areas such as data fusion and recognition techniques in the context of vision with a uni-modal and multi-modal perspective. We conclude by discussing research challenges, emerging trends, and possible future research directions.

Multinucleate cells can be produced in Dictyostelium by electric-pulse induced fusion. In these cells unilateral cleavage furrows are formed at spaces between areas that are controlled by aster microtubules. A peculiarity of unilateral cleavage furrows is their propensity to join laterally with other furrows into rings to form constrictions. This means, cytokinesis is biphasic in multinucleate cells, the final abscission of daughter cells being independent of the initial direction of furrow progression. Myosin-II and the actin-filament cross-linking protein cortexillin accumulate in the unilateral furrows, as they do in the normal cleavage furrows of mononucleate cells. Myosin-II is not essential for cytokinesis, but stabilizes and confines the position of the cleavage furrows.

Purinergic receptors are inflammatory mediators activated by extracellular nucleotides released by dying or injured cells. Several studies have described an important role for these receptors in HIV-1 entry, particularly regarding their activity on HIV-1 viral membrane fusion. Several reports identify purinergic receptor antagonists that inhibit HIV-1 membrane fusion; these drugs are suspected to act through antagonizing Env-chemokine receptor interactions. They also appear to abrogate activity of downstream mediators that potentiate activation of the NLRP3 inflammasome pathway. Here we review the literature on purinergic receptors, the drugs that inhibit their function, and the evidence implicating these receptors in HIV-1 entry.

Charcot-Marie-Tooth disease is a hereditary polyneuropathy caused by mutations in Mitofusin-2 (MFN2), a GTPase in the outer mitochondrial membrane involved in the regulation of mitochondrial fusion and bioenergetics. Autosomal-dominant inheritance of a R94Q mutation in MFN2 causes the axonal subtype 2A2A which is characterized by early onset and progressive atrophy of distal muscles caused by motoneuronal degeneration. Here, we studied mitochondrial shape, respiration, cytosolic and mitochondrial ATP content as well as mitochondrial quality control in MFN2-deficient fibroblasts stably expressing wildtype or R94Q MFN2. Under normal culture conditions, R94Q cells had slightly more fragmented mitochondria but a similar mitochondrial oxygen consumption, membrane potential and ATP production as wildtype cells. However, when inducing mild oxidative stress 24 h before analysis using 100 µM hydrogen peroxide, R94Q cells exhibited significantly increased respiration but decreased mitochondrial ATP production. This was accompanied by increased glucose uptake and an upregulation of hexokinase 1 and pyruvate kinase M2 suggesting increased pyruvate shuttling into mitochondria. As these changes coincided with decreased levels of PINK1/Parkin-mediated mitophagy in R94Q cells, we conclude that the disease-causing R94Q mutation in MFN2 causes uncoupling of mitochondrial respiration from ATP production by a less efficient mitochondrial quality control triggered by oxidative stress.

This paper aims at tackling with the task of fusion feature from images and its corresponding point clouds for 3D object detection in autonomous driving scenarios basing on AVOD, an Aggregate View Object Detection network. The proposed fusion algorithms fuse features targeted from Bird’s Eye View (BEV) LIDAR point clouds and its corresponding RGB images. Differs in existing fusion methods, which are simply the adoptions of concatenation module, element-wise sum module or element-wise mean module, our proposed fusion algorithms enhance the interaction between BEV feature maps and its corresponding images feature maps by designing a novel structure, where single level feature maps and another utilizes multilevel feature maps. Experiments show that our proposed fusion algorithm produces better results on 3D mAP and AHS with less speed loss comparing to existing fusion method used on the KITTI 3D object detection benchmark.

This paper presents a new and enhanced fusion module for the Multi-Sensor Precipitation Estimator (MPE) that would objectively blend real-time satellite quantitative precipitation estimates (SQPE) with radar and gauge estimates. This module consists of a preprocessor that mitigates systematic bias in SQPE, and a two-way blending routine that statistically fuses adjusted SQPE with radar estimates. The preprocessor not only corrects systematic bias in SQPE, but also improves the spatial distribution of precipitation based on SQPE and makes it closely resemble that of radar-based observations. It uses a more sophisticated radar-satellite merging technique to blend preprocessed datasets, and provides a better overall QPE product. The performance of the new satellite-radar-gauge blending module is assessed using independent rain gauge data over a 5-year period between 2003-2007, and the assessment evaluates the accuracy of newly developed satellite-radar-gauge (SRG) blended products versus that of radar-gauge products (which represents MPE algorithm currently used in the NWS operations) over two regions: I) inside radar effective coverage and II) immediately outside radar coverage. The outcomes of the evaluation indicate a) ingest of SQPE over areas within effective radar coverage improve the quality of QPE by mitigating the errors in radar estimates in region I; and b) blending of radar, gauge, and satellite estimates over region II leads to reduction of errors relative to bias-corrected SQPE. In addition, the new module alleviates the discontinuities along the boundaries of radar effective coverage otherwise seen when SQPE is used directly to fill the areas outside of effective radar coverage.

Rare diseases are characterized by a wide diversity of signs and symptoms and vary not only from disease to disease, but also from person to person, and living with a disease leads patients to peculiar experiences and treatments, without limits of time and space, as they extend to various environments and relationships of their lives. The objective of this study is the theoretical interaction between Value Co-creation (VC) and the Stakeholder Theory (ST) with the Shared Decision Making (SDM) health care theory. It is configured as a multiparadigmatic proposal by enabling the analysis of multiple perspectives of different stakeholders in health care. Thus, Co-created Decision Making (CDM) emerges in a logic dominated by service, with emphasis on intangible aspects and the interactivity of the relationships. It goes beyond the clinical office and the doctor-patient relationships, as studied in SDM, extending to all environments and interactions that add value to the patient's treatment. It was concluded that the essence of this new theory proposed here is neither in patient-centered care nor in patient self-care, but in co-created relationships with and between stakeholders in both directions, including non-health care environments that are important to the patient, such as relationships with friends, family, other patients with the same disease, social media, public policies, and the practice of pleasurable activities.

Recently, many authors have been interested to introduce fuzzy implications over t-norms and t-conorms. In this paper, we introduce (S,N) and residuum fuzzy implication for Dubois t-norm and Hamacher's t-norm. Also, new concepts so-called (T,N) and residual fuzzy co-implication in dual Heyting Algebra are investigated. Some examples as well as application are discussed as well.

As one of the important components of underwater propulsion systems, water lubricated bearings are often failure due to mechanical wearing and vibrating, especially under high loads and prolonged friction. In this paper, a dual-network co-crosslinking strategy based on HNBR is proposed, in which the epoxy network connects with the rubber network through Epoxidized Eommia ulmoides gum. The damping, tribological and mechanical properties of the prepared composite are systematically investigated. The results show that this material has excellent friction and vibration damping properties, with a water-lubricated coefficient of friction as low as 0.022 and a wear resistance as high as 3.87 × 10-6mm3/Nm. Preparing HNBR-based composite by dual network co-crosslinked is proved being a feasible solution to improve the reliability and service life of water-lubricated bearings.

The 2022-2023 influenza season in Romania was characterized by high pediatric hospitalization rates, predominated by influenza A subtypes H1N1 and H3N2. Lowered population immunity to influenza after the SARS-CoV-2 pandemic and subsequent stoppage of influenza circulation, particularly in children who had limited pre-pandemic exposures, influenced hospitalization among children immunosuppressed, and patients with concurrent medical conditions who are at increased risk for developing severe forms of influenza. This study focused on the characteristics of influenza issues among paediatric patients, as well as the relationship between different influenza virus types and viral and bacterial coinfections and illness severity in the 2022-2023 season after the SARS-CoV-2 pandemic. We conducted a retrospective clinical analysis on 301 cases of influenza in pediatric inpatients (age ≤ 18 years), hospitalized at the National Institute of Infectious Diseases "Prof. Dr. Matei Balș" IX Pediatric Infectious Diseases Clinical Section between October 2022 and February 2023. The most significant age group was 57.8% representing children between one to four years old and female. The average clinical forms were found in 61.7%, whereas severe versions represented 18.2% of cases. Most of the complications were respiratory (acute interstitial pneumonia, 76.1%), hematological (72.1%), represented by intra-infectious and deficiency anemia, leukopenia, thrombocytopenia), 33.6% were digestive, such as diarrheal disease, liver cytolysis syndrome, and the acute dehydration syndrome associated with electrolyte imbalance (71.4%). Severe complications were associated with a risk of unfavorable evolution: acute respiratory failure and neurological complications (convulsions, encephalitis). No deaths were reported. We noticed that the flu season 2022-2023 was characterized by the association of co-infections (viral, bacterial, fungal and parasitic) more frequent than in previous years (26.2% vs. 16%), which evolved more severely, with prolonged hospitalization and more complications (p<0.05), and time of use of oxygen therapy was statistically significant (p > 0.05); influenza vaccination in this group was zero. In conclusion, coinfections with respiratory viruses increase the severity of the pediatric population's immunity to influenza, especially among young children who are more vulnerable to developing a serious illness. All people above the age of six months should get vaccinated against influenza to prevent the illness and its severe complications.

Recently, the amount of waste generated has been rapidly increasing, there have been difficulties disposing of waste in Korea. As a solution to this, treating waste using a cement kiln has suggested, but the environmental and economic effects have not been specifically studied. In this study, the effects of alternative resources, and reducing the social costs(Installation and Operation) associated with waste treatment facilities were analyzed. Through a co-processing method, a reduction of approximately 53kg of CO2 can be realized during the production of one ton of cement, and cost savings of about 3,815 milion USD. Another effect is an extension of the expiration date for landfills by 7.55 years.

New setting is introduced to study quasi-degree and quasi-co-degree arising from co-neighborhood. quasi-degree and quasi-co-degree is about a vertex which are applied into the setting of neutrosophic graphs. . The structure of set is studied and general results are obtained. Also, some classes of neutrosophic graphs namely path-neutrosophic graphs, cycle-neutrosophic graphs, complete-neutrosophic graphs and star-neutrosophic graphs, complete-bipartite-neutrosophic graphs and complete-multipartite-neutrosophic graphs are investigated in the terms of a vertex which is called either quasi-degree or quasi-co-degree. Neutrosophic number is reused in this way. It’s applied to use the type of neutrosophic number in the way that, three values of a vertex are used and they’ve same share to construct this number to compare with other vertices. Summation of three values of vertex makes one number and applying it to a comparison. This approach facilitates identifying vertices which form quasi-degree and quasi-co-degree. Quasi-degree is a value of a vertex which is maximum amid all values of vertices which are neighbors to a fixed vertex. Quasi-co-degree is a value of an edge which is maximum amid all values of edges which are neighbors to a fixed vertex but corresponded vertex is representative for this notion. Using different values which are related to a vertex inspire us to focus on edge and vertices which are corresponded to a fixed vertex. The notion of neighborhood is used to collect either vertices are titled neighbors or edges are incident to fixed vertex. In both settings, some classes of well-known neutrosophic graphs are studied. Some clarifications for each result and each definitions are provided. Using fixed vertex has key role to have these notions in the form of vertex or edge. The value of an edge has eligibility to call quasi-co-degree but the value of a vertex has eligibility to call quasi-degree. Some results get more frameworks and perspective about these definitions. The way in that, two vertices have connection together, open the way to define neighborhood and co-neighborhood. The maximum values in neighborhood and co-neighborhood introduces quasi-degree and quasi-co-degree, respectively. New name is chosen from degree. Since amid all vertices with different degrees, one vertex is chosen. In other words, one vertex is fixed and its degree turns out quasi-degree where two degrees could be assigned to a vertex. Degree of edges and degree of vertices. The number of edges which are incident to the vertex and the number of vertices which are neighbors to the vertex. Degree and co-degree are the notions which are transformed to use in quasi-style. Two neutrosophic values introduce two neutrosophic vertices separately in each settings. These notions are applied into neutrosophic graphs as individuals but not family of them as drawbacks for these notions. Finding special neutrosophic graphs which are well-known, is an open way to purse this study. Some problems are proposed to pursue this study. Basic familiarities with graph theory and neutrosophic graph theory are proposed for this article.

Potential of co-digestion mixing thickened secondary sludge (TS) from extended aeration wastewater treatment plant and locally available substrates (whey, grease and septage) has been studied using three steps. The first step was a batch test to determine biological methane potential (BMP) of different mixtures of the three co-substrates with TS. The second step has been carried out with lab-scale reactors (20 L) simulating anaerobic continuous stirred tank reactors fed by three mixtures of co-substrates determined according to previous step results. Modelling using ADM1 as a mechanistic model was applied in the third step to help understanding the co-digestion process. According to BMP step, septage used as co-substrate has a negative effect on performance and addition of 10 to 30% grease or 10% whey would lead to a higher production of biogas and with an increase of the methane content. The results from the reactor showed less evi-dence of the positive effects observed with the BMP assay. Protein and lipid fractions of particu-late biodegradable COD are important variables for digester stability and methane production as predicted by modelling. Results of simulations with ADM1 model adapted to co-digestion confirmed that this model is a powerful tool to optimize the process of biogas production.

There is compelling evidence that the nuclear receptor TRβ, a member of the thyroid hormone receptor (TR) family, is a tumor suppressor in thyroid, breast and other solid tumors. Cell-based and animal studies reveal that the liganded TRβ induces apoptosis, reduces an aggressive phenotype, decreases stem cell populations, and slows tumor growth through modulation of a complex interplay of transcriptional networks. TRβ-driven tumor suppressive transcriptomic signatures include repression of known drivers of proliferation such as PI3K/Akt pathway and activation of novel signaling (JAK1/STAT1) and metabolic reprogramming in both thyroid and breast cancers. The presence of TRβ is also correlated with a positive prognosis and response to therapeutics in BRCA+ and triple-negative breast cancers respectively. Ligand activation of TRβ enhances sensitivity to chemotherapeutics. TRβ co-regulators and bromodomain-containing chromatin remodeling proteins are emergent therapeutic targets. This review considers TRβ as a potential biomolecular diagnostic and therapeutic target.

The sense of uncertainty and fragility due to the effects and magnitude of global challenges we are facing (from pandemic circumstances to climate change impacts) requires – much more than in the past – the capacity to generate a visionary and forefront design approach in the young gen-erations aiming at stimulating their reaction attitude rather than providing consolidated tools from past conditions that no longer exist or will rapidly evolve. Within this general framework, we have investigated the effectiveness and impacts of experienced-based methods of learning and innovative educational tools in architecture aimed at shaping expertise in which the environ-mental dimension and the climate-change challenge dialogues with the context's complexity in terms of socio-cultural dynamics, real potentialities and constrains, addressing their transdisci-plinary trajectories. The paper analyses 5 international pioneering teaching experiences that provide the opportunity to understand the outcomes of collaborative and experiential learning processes in which the educational activities leverage a dialogue between diverse communities (academia-citizens-policymakers-practitioners). The study outcomes show that shifting the pedagogical paradigm towards in-field-experience-based models can improve the awareness of future practitioners for climate implications of architectural design, implement their analysis and project skills while triggering processes of knowledge transfer and co-production at community level, and allow them to better address the societal and cultural issues involved within decision making.

The purpose of this study is to explore conceptual approaches in co-production studies and to examine current research trends of the study. The conceptual paper includes research articles related to co-production in public administration field. By thoroughly scrutinizing 32 research works of co-production, this study highlights major loopholes in the field of the study. The contributions of the study are: (1) identifying two common characteristics of co-production, (2) categorising three types of co-producing by end-users, and (3) finding that goals and success of co-production are more beneficial for service providers though its initial approach is citizen-centric approach. We suggest that future studies should be (1) to focus on reasons for co-production failures or success, (2) to discover further hindrances for co-production in service production, (3) to examine influencing factors on service providers as well as institutional impacts on co-production process, and (4) to include practical assessment in co-production study.

Elevated antimony concentrations in aqueous environments from anthropogenic sources is becoming of global concern, here iron oxides are known to strongly adsorb aqueous antimony species with different oxidation states, but the effect of silica on the removal characteristics is not well understood despite being a common component in the environment. In this study, ferrihydrite was synthesized at various Si/Fe molar ratios to investigate its adsorption and co-precipitation behaviors with aqueous antimony anionic species, Sb(III) and Sb(V). The XRD analyses of the precipitates showed two broad diffraction features at approximately 35° and 62° 2θ, which are characteristic of 2-line ferrihydrite, no significant shifts in peak positions in the ferrihydrite regardless of the Si/Fe ratios. The infrared spectra showed a sharp band at ~990 cm⁻¹, corresponding to asymmetric stretching vibrations of Si-O-Fe bonds which increased in intensity with increasing Si/Fe molar ratios. Further, the surface charge on the precipitates became more negative with increasing Si/Fe molar ratios. The adsorption experiments indicated that Sb(V) was preferentially adsorbed at acidic conditions and decreased dramatically with increasing pH while the adsorption rate of Sb(III) ions was independent of pH, however, the presence of silica suppressed the adsorption of both Sb(III) and Sb(V) ions. The results showed that Sb(III) and Sb(V) ions were significantly inhibited by co-precipitation with ferrihydrite even in the presence of silica by isomorphous substitution in the ferrihydrite crystal structure.

Background: Previously, our laboratory has provided evidence that pre-administration of the antioxidant, lipoic acid covalently bonded to various naturally occurring antioxidants, enhanced neuroprotective capacity compared to the administration of lipoic acid on its own. The naturally occurring compound scopoletin, a coumarin derivative, has been shown in various in vitro studies to have both antioxidant and anti-inflammatory mechanism of actions. To date, the effect of scopoletin on neuronal cell death in an in vivo model of ischemia or ischemia-reperfusion has not been investigated. Therefore, the present investigation was designed to determine if scopoletin on its own, or a co-drug consisting of lipoic acid and scopoletin covalent bond, named UPEI-400, would be capable of demonstrating a similar neuroprotective efficacy. Methods: Using a rodent model of stroke in male rats (anesthetized with Inactin®; 100 mg/kg, iv), the middle cerebral artery was permanently occluded for 6 hours (pMCAO), or in separate animals, occluded for 30 min followed by 5.5 hrs of reperfusion (ischemia/reperfusion; I/R). Results: Pre-administration of either scopoletin or UPEI-400 significantly decreased infarct volume in the I/R model (p<0.05), but not in the pMCAO model of stroke. However, UPEI-400 was ~1000 times more potent as compared to scopoletin on its own. The optimal dose of UPEI-400 was then injected during the occlusion and at several time points during reperfusion and significant neuroprotection was observed for up to 150 mins following the start of reperfusion (p<0.05). Conclusion: The data suggest that synthetic combination of scopoletin with lipoic acid (UPEI-400) is a more effective neuroprotectant that either compound on their own. Also, since UPEI-400 was only effective in a model of I/R, it is possible that it may act to enhance neuronal antioxidant capacity and/or upregulate anti-inflammatory pathways to prevent the neuronal cell death.

Poly(vinyl butyral-co-vinyl alcohol-co-vinyl acetate) named further PVBA was investigated as protective coating for copper corrosion in 0.9 % NaCl solution using electrochemical measurements such as, electrochemical impedance spectroscopy (EIS) and potentiodynamic polarization associated with Atomic Force Microscopy (AFM). The PVBA coating on the copper surface (Cu-PVBA) was modeled in methanol containing PVBA. Its inhibitory properties against corrosion was comparatively discussed with those of the copper sample treated in methanol without polymer (Cu-Me) and of untreated sample (standard copper). A protective performance of PVBA coating of 80 % was computed from electrochemical measurements, for copper corrosion in NaCl solution. Also, AFM images designed a specific surface morphology of coated surface with PVBA, clearly highlighting a polymer film adsorbed on the copper surface, which presents certain deterioration after corrosion, but metal surface was not significantly affected compared to those of untreated samples or treated in methanol, in the absence of PVBA.

Background/Objectives:The first attempts of posterior lumbar interbody fusion can be traced back to the 1940s, where their performance was marked by animosity due to high rates of failure. Nowadays, the use of interbody fusion involves a much more complicated consideration of factors such as global alignment, disc height, fusion rates, and operative risk, all combined at once.Our study aims to examine all these effects using Flarehawk 9 as a means of interbody fusion.Materials and methods: A total of 58 patients underwent open posterior lumbar surgery using Flarehawk 9 between September 2021 and February 2023 with a mean follow up of 1 year.The mean age was 59.8 years old ( range between 33 and 79 years old), 36 of them are males while 22 of them are females. The diagnostic groups included spinal canal stenosis (n=40), failed back surgery syndrome-revision surgery (n=5),spondylolisthesis with slip percentage 25% (n=4),recurrent herniated disc (n=7) and adjacent segment disease (n=2). Results: The majority of patients demonstrated remarkable improvement based on ODI scores.The rate of union varied based on the fused levels and whether the patients had previous surgery or not.The amount of lordosis postoperatively is increased by 2±0.4 degrees.Conclusions: Even though anterior approaches become more and more popular and advanced nowadays, posterior fusion with interbody cage still remains a safe and effective method to treat various spine surgical pathologies with optimal results.

Using the senses is essential to interact with objects in real-world environments. However, not all the senses are available when interacting with virtual objects in virtual environments. This paper presents a diamond methodology to fuse two technologies to represent the senses of sight and touch when interacting with a virtual object. The sense of sight is represented through augmented reality, and the sense of touch is represented through kinesthetic haptics. The diamond methodology is centered on the user experience and comprises five general stages: Experience design, Sensory representation, Development, Display, and Fusion. The first stage comes from the expected, proposed, or needed user experience. Then, each technology takes its homologous activities from the second to the fourth stage, diverging from each other along their development. Finally, the technologies converge to the fifth and final stage for fusion in the user experience. The diamond methodology was tested by generating a user's dual sensation when interacting with the elasticity of a tension virtual spring. The user can simultaneously perceive the visual and tactile change of the virtual spring during the interaction, representing the object's deformation. The experimental results demonstrated that an interactive experience can be felt and seen in augmented reality following the diamond methodology.

In this work, we propose an approach for the autonomous navigation of mobile robots using fusion of sensor data by a Double Deep Q-Network with collision avoidance by detecting moving people via computer vision techniques. We evaluate two data fusion methods for the proposed autonomous navigation approach: Interactive and Late fusion strategy. Both are used to integrate mobile robot sensors through the following sensors: GPS, IMU and, an RGB-D camera. The proposed collision avoidance module is implemented along with the sensor fusion architecture in order to prevent the autonomous mobile robot from colliding with moving people. The simulation results indicate a significant impact on the success of completing the proposed mission by the mobile robot with the fusion of sensors, indicating a performance increase (success rate) of 27% in relation to navigation without sensor fusion. With the addition of moving people in the environment, deploying the people detection and collision avoidance security module has improved about 14% the success rate when compared to that of the autonomous navigation approach without the security module. Video was developed with robot navigation using the DDQN-Late Fusion https://www.loom.com/share/684afa6a5b0148afadc9a200ab9f3483.

This study compares the performance of existing studies on multimodal emotion recognition, and proposes a model that fuses two modalities with the speaker's text and voice signals as input values and detects depression. Based on the DAIC-WOZ dataset, voice features were extracted using CNN, text features were extracted using Transformers, and two modalities were fused through a tensor fusion network. We also build a model to detect whether the speaker is depressed or not using LSTM in the final layer. This study suggests the possibility of increasing access to mental illness diagnosis by enabling patients to detect depression on their own in daily conversations. If the model proposed in this study is developed and the voice conversation system is connected, it will be easier for patients who cannot visit the hospital periodically or who are reluctant to visit the hospital to check their condition and seek recovery. Furthermore, it can be expanded to multi-label classification for various mental diseases and used as a simple self-mental disease diagnosis tool.

The Stellarator Power Plant Studies Prospective R&amp;D Work Package among the Eurofusion Programme was settled to bring the stellarator engineering to maturity, so that stellarators and particularly the HELIAS (HELical-axis Advanced Stellarator) configuration could be a possible alternative to tokamaks. However, its complex geometry makes designing a Breeding Blanket (BB) that fully satisfies the requirements for such an HELIAS configuration a difficult task. Taking advantage of the acquired experience in BB design for DEMO tokamak, CIEMAT is leading the development of a Dual Coolant Lithium Lead (DCLL) BB for a HELIAS configuration. To answer the specific HELIAS challenges new and advanced solutions have been proposed, as the use of fully detached First Wall (FW) based on liquid metal Capillary Porous Systems (CPS). These proposed solutions have been studied in a simplified 1D model that can help to estimate the relative variations in Tritium Breeding Ratio (TBR) and displacement per atom (dpa) to verify their effectiveness to simplify the BB integration, improve the machine availability while keeping the main BB nuclear functions (i.e. tritium breeding, heat extraction and shielding). This preliminary study demonstrates that the use of FW CPS would reduce the radiation damage received by the blanket without compromising its tritium breeding performance.

Fusion device and its structure may be designed by various means. Two of most popular are; weight basis (described in previous study by author) and energy basis. In present research, later method is explored and described. Energy basis is based on amount of energy released from device upon detonation followed by explosion. Its beneficial in a sense that device size can be kept as independent variable as compared to dependent in former case. Further, it shortens the design procedure. For example, heat transfer pattern in such approach directly helps in quantifying wall thickness which dictates material, fabrication, and manufacturing route. It may also eliminate anisotropy as wall thickness is direct function of amount of heat at which it will rupture and can be much thinner. Device geometry can also be flexibility controlled as it is no longer dependent on pay load bay capacity. This allows more freedom in designing subsystems (compartments, their locations, focusing, switches, and mixers). Such devices can be more compact and simpler. Few such design configurations are proposed.

The initial stability after implantology is paramount to the survival of the dental implant and the surface roughness of the implant plays a vital role in this regard. The characterisation of surface topography is a complicated branch of metrology, with a huge range of parameters available. Each parameter contributes significantly towards the survival and mechanical properties of 3D-printed specimens. The purpose of this paper is to experimentally investigate the effect of surface roughness of 3D-printed dental implants and 3D-printed dogbone tensile samples under areal height (Ra) parameters, amplitude parameters (average of ordinates), skewness (Rsk) parameters and mechanical properties. During the experiment, roughness values were analysed and the results showed that the skewness parameter demonstrated a minimum value of 0.596%. The 3D-printed dental implant recorded Ra with a 3.4 mm diameter at 43.23% and the 3D-printed dental implant with a 4.3 mm diameter at 26.18%. Samples with a complex geometry exhibited a higher roughness surface, which was the greatest difficulty of additive manufacturing when evaluating surface finish. The results show that when the ultimate tensile stress (UTS) decreases from 968.35 MPa to 955.25 MPa, Ra increases by 1.4% and when UTS increases to 961.18 MPa, Ra increases by 0.6%. When the cycle decreases from 262142 to 137433, Ra shows that less than a 90.74% increase in cycle is obtained. For 3D-printed dental implants, the higher the surface roughness, the lower the mechanical properties, ultimately leading to decreased implant life and poor performance.

A method for infrared and cameras sensor fusion, applied to indoor positioning in intelligent spaces, is proposed in this work. The fused position is obtained with a maximum likelihood estimator from infrared and camera independent observations. Specific models are proposed for variance propagation from infrared and camera observations (phase shifts and image respectively) to their respective position estimates and to the final fused estimation. Model simulations are compared with real measurements in a setup designed to validate the system. The difference between theoretical prediction and real measurements is between 0.4 cm (fusion) and 2.5 cm (camera), within a 95% confidence margin. The positioning precision is in the cm level (sub-cm level can be achieved at most tested positions) in a 4x3 m locating cell with 5 infrared detectors on the ceiling and one single camera, at distances from target up to 5 m and 7 m respectively. Due to the low cost system design and the results observed, the system is expected to be feasible and scalable to large real spaces.

Mitochondria are highly dynamic organelles that continuously change their shape. Their main function is ATP production; however, they are additionally involved in a variety of cellular phenomena, such as apoptosis, cell cycle, proliferation, differentiation, reprogramming, and aging. The change in mitochondrial morphology is closely related to the functionality of mitochondria. Normal mitochondrial dynamics are critical for cellular function, embryonic development, and tissue formation. Thus, defect in proteins involved in mitochondrial dynamics that control mitochondrial fusion and fission can affect cellular differentiation, proliferation, cellular reprogramming, and aging. Here we review the processes and proteins involved in mitochondrial dynamics and its various associated cellular phenomena.

Aiming at the problems that are poor generalization performance, low retrieval accuracy and large time consumption of existing content-based image retrieval system, the hierarchical image retrieval method based on multi feature fusion is proposed in this paper. The retrieval accuracy rates on Corel5K, UKbeach and Holidays are 68.23(Top 1), 3.73(N-S) and 88.20(mAp), respectively. The experimental results show that the method proposed in this paper can effectively improve the deficiency of single feature retrieval and save time significantly in the premise of a small amount of loss of accuracy.

New setting is introduced to study co-neighborhood, neutrosophic t-neighborhood, neutrosophic quasi-vertex set, neutrosophic quasi-order, neutrosophic neighborhood, neutrosophic co-t-neighborhood, neutrosophic quasi-edge set, neutrosophic quasi-size, Neutrosophic number, neutrosophic co-neighborhood, co-neutrosophic number, quasi-number and quasi-co-number. Some classes of neutrosophic graphs are investigated.

Digital Twin Cities (DTCs) play a fundamental role in city planning and management. They allow three-dimensional modeling and simulation of cities. 3D semantic segmentation is the foundation for automatically creating enriched DTCs, as well as their updates. Past studies indicate that prior level fusion approaches demonstrate more promising precisions in 3D semantic segmentation compared to point level fusion, features level fusion, and decision level fusion families. In order to improve point cloud enriched semantic segmentation outcomes, this article proposes a new approach for 3D point cloud semantic segmentation through developing and benchmarking three prior level fusion scenarios. A reference approach based on point clouds and aerial images was proposed to compare it with the different developed scenarios. In each scenario, we inject a specific prior knowledge (geometric features,classified images ,etc) and aerial images as attributes of point clouds into the neural network’s learning pipeline. The objective is to find the one that integrates the most significant prior knowledge and enhances neural network knowledge more profoundly, which we have named the "smart fusion approach". The advanced Deep Learning algorithm "RandLaNet" was adopted to implement the different proposed scenarios and the reference approach, due to its excellent performance demonstrated in the literature. The introduction of some significant features associated with the label classes facilitated the learning process and improved the semantic segmentation results that can be achievable with the same neural network alone. Overall, our contribution provides a promising solution for addressing some challenges, in particular more accurate extraction of semantically rich objects from the urban fabric. An assessment of the semantic segmentation results obtained by the different scenarios is performed based on metrics computation and visual investigations. Finally,the smart fusion approach was derived based on the obtained qualitative and quantitative results.

Type 2 Diabetes Mellitus (T2DM) is one of the most common metabolic disorders, with a major involvement of oxidative stress in its onset and progression. Pioglitazone (Pio) is an antidiabetic drug which primarily works by reducing insulin resistance while Curcumin (Cur) is powerful antioxidant with o important hypoglycemic effect, also. The both drugs are associated with several drawbacks, such as reduced bioavailability, a short half-life time (Pio) as well as instability and poor water solubility (Cur), which limit their therapeutic use. In order to overcome these disadvantages, a new co-delivery (Pio, Cur) nanosystem based chitosan (CS) (CS-Pio-Cur NPs), was developed, and characterized in reference with simple nanosystems (CS-Pio NPs, CS-Cur NPs). The developed CS-based NPs (CS-Pio-Cur NPs, CS-Pio NPs, CS-Cur NPs) were physico-chemical characterized in terms of particle size (PS), entrapment efficiency (EF%) and loading capacity (LC%). The CS-Pio-Cur NPs proved increased or similar values of EE (88.95% ± 7.79 for Cur; 94.83% ± 9.89 for Pio) and LC% (24.25 % ± 1.62 for Cur; 3.5% ± 0.98 for Pio), in reference with simple nanosystems, CS-Cur NPs (EE = 82.46% ± 1.74; LC = 20.34% ± 0.94) and CS-Pio NPs) (EE = 96.31% ± 0.68; LC = 4.11% ± 0.47), respectively. The identification of APIs (Cur, Pio) loaded into CS matrix was performed using FR-IR spectroscopy and for simultaneously quantification of APIs (Cur, Pio) released from CS-Pio-Cur NPs, a HLPC method was developed and validated. Based on release study performed in different simulated fluids (SGF, SIF, SCF) it can be appreciated that developed CS-APIs NPs have favorable pharmacokinetic profile with good release in gastrointestinal tract.

The COVID-19 pandemic and tuberculosis have epidemiological similarities, being transmitted airborne, favored by direct contact, crowded environments and vulnerable biological status. We performed a retrospective study of 45 cases of pulmonary tuberculosis associated with COVID-19 (TB+COV+) compared to 45 cases with tuberculous monoinfection (TB+COV-), hospitalized during 2021-2022. The demographic characteristics were similar in the two groups, predominating men, a median age of 51 years, living in rural areas, medium level of education and smoking. Common symptoms of the two groups were cough, weight loss, profuse sweating, loss of appetite and hemoptysis, while fever, headache, myo-arthralgias and digestive symptoms characterized the TB+COV+ forms. The scores of radiological lesions in the TB+COV+ compared to TB+COV- group were significantly higher and persistent, revealing more frequent bilateral extensive lung lesions. There were no significant differences in the biological parameters between the two groups. Mortality was 2.2%, regardless of the association of COVID-19. The frequency of infections with Clostridioides difficile was higher in TB+COV+ cases. In conclusion, the co-infection of COVID-19 had an impact on the clinical and biological expression of tuberculosis diagnosed in a pandemic context.

The amalgamation of mineral and targeted bacterial preparations represents a new generation of agricultural technology. Inoculation with combined preparations of microorganisms is more effective than inoculation with a single microorganism in stimulating plant growth by providing a more balanced diet for various crops. In this work, the effect of inoculation of 20 consortium variants on the yield indicators of three crops (wheat, buckwheat, corn) and the soil microbiome in the open field was investigated. The soil microbiome was defined by 16S rRNA sequences through NGS. Species richness of the soil microbial community (alpha diversity) was similar for all studied samples. Beta-diversity analysis revealed that the microbial diversity of three soil samples (C.bw, F.bw and Soil.bw) differed significantly from all others. At the phylum level, the number of Acidobacteriota and Firmicutes in these samples was increased. For the combination “Consortium C (Rothia endophytic GMG9 and Azotobacter chroococcum GMG39) - buckwheat”, a systemic positive improvement in all growth and yield indicators was observed. The soil of the site where buckwheat grew, inoculated by Consortium C, contained significantly more available phosphorus than all other soil samples. Such results can be explained both by the direct action of a consortium of phosphate-immobilizing and nitrogen-fixing bacteria and to acidification of the medium due to an increase in phylum Acidobacteriota bacteria in the soil.

This paper presents a novel cheminformatics approach for the design and synthesis of hydroxyapatite/collagen nanocomposites, which have potential biomedical applications in tissue engineering, drug delivery, orthopedic and dental implants. The nanocomposites are synthesized by the co-precipitation method with different ratios of hydroxyapatite and collagen, and their mechanical, biological, and degradation properties are analyzed using various experimental and computational techniques, such as attenuated total reflection Fourier-transform infrared spectroscopy, X-ray diffraction, thermogravimetric analysis, scanning electron microscopy with energy-dispersive X-ray spectroscopy, and molecular simulation. The antimicrobial activity of the nanocomposites is evaluated in vitro against several bacterial and fungal strains, demonstrating their medical potential. Additionally, in silico analyses are performed to predict the absorption, distribution, metabolism, and excretion properties and the bioavailability of the collagen samples. This work opens new avenues for the development of novel biomaterials using cheminformatics tools and methods, which can facilitate the optimization of the design and synthesis parameters, as well as the prediction of the biological outcomes. Future research directions include the investigation of the biocompatibility and bioactivity of the nanocomposites in vivo, as well as the exploration of other applications and functionalities of these nanocomposites.

Recently, there has been a lot of interest in the phenolics of pomegranate peels because of their health-promoting effects. The incorporation of encapsulated phenolic extracts in functional foods, beverages, and dietary supplements can enhance their nutritional and health benefits. This paper aims to provide an overview of the encapsulation of pomegranate peel phenolic extract by co-crystallization, focusing on the properties of the encapsulated extract. Pomegranate peel extract encapsulated in sucrose by co-crystallization at conditions determined in our previous work is characterized by evaluating its properties; moisture content, bulk density, solubility, hygroscopicity, color, degree of encapsulation by thermograms, crystallinity by X-ray scattering, microstructure by scanning electron microscope, and storage stability in terms of total phenolic content and antioxidant activity. The co-crystallized powder had a low moisture content (0.59%) and hygroscopicity (0.011%) and a high bulk density (0.803 g/cm3) and solubility (61 s). Its total phenolic content decreased by only 0.56% after storage at 60oC for 45 days, whereas its antioxidant activity was maintained at levels higher than 84%. The differential scanning calorimetry and the X-ray scattering techniques proved the successful encapsulation in the sucrose matrix and the fact that the extract remained liquid inside the porosity of the sucrose crystals.

This paper presents a bibliometric analysis of highly cited papers published in the journal Sustainability between 2009 and 2023. The aim is to identify influential countries, authors, and papers, as well as patterns in authorship and citation trends. The analysis focuses on frequently cited sources, the most cited research papers and references within the journal, and trends in author keywords. The analysis shows that Sustainability is a leading publication in sustainability research, with an annual growth rate of 53.57%. The selected papers, published between 2013 and 2022, have an average age of 2.11 years and an average of 88.12 citations each. The study highlights the most influential countries in sustainability research published in Sustainability, with China leading, followed by the United States and Germany. The most prolific authors are from China, Spain, and Italy. Interdisciplinary collaboration is essential to address complex sustainability challenges, as shown in the papers published in Sustainability. The study emphasizes the importance of staying informed about emerging trends and research directions in the field of sustainability published in this journal Sustainability. It underscores the significance of fostering international collaborations and partnerships to address complex sustainability challenges facing our world today, as evidenced by the papers published in Sustainability. Overall, this bibliometric analysis provides valuable insights into the current state of sustainability research published in Sustainability and its implications for policy and practice. It highlights key areas for future research and underscores the need for interdisciplinary collaboration to address complex sustainability challenges, as demonstrated by the papers published in Sustainability. These findings have important implications for policymakers, researchers, and practitioners interested in promoting sustainable development in the field of sustainability., as published in Sustainability.

Introduction: Increasing cannabis legalization raises concerns that tobacco use, frequently used with cannabis, will also increase. This study investigated the association between legal status of cannabis in place of residence and prevalence of cannabis and tobacco co-use, simultaneous use, and mixing by comparing the prevalence among adults in Canada (prior to cannabis legalization) vs. adults in US states that had legalized recreational cannabis vs. US states that had not as of September 2018. Methods: Data were drawn from the 2018 International Cannabis Policy Study, conducted with respondents aged 16-65 in Canada and the US recruited from non-probability consumer panels. Differences in the prevalence of co-use, simultaneous use, and mixing between tobacco and different cannabis products were examined using logistic regression models by legal status of place of residence among past 12-month cannabis consumers (N=6744). Results: Co-use and simultaneous use in the past 12 months were most common among respondents in US legal states. Among cannabis consumers, co-use and simultaneous use were less common in US legal states, while mixing was less frequent in US states with both legal and illegal cannabis compared to Canada. Use of edibles was associated with lower odds of all three outcomes, while smoking dried herb or hash was associated with higher odds. Conclusions: The proportion of cannabis consumers who used tobacco was lower in legal jurisdictions despite higher prevalence of cannabis use. Edible use was inversely associated with co-use suggesting that edible use does not appear to be associated with increased tobacco use.

As a typical form of value co-creation, crowdsourcing has been increasingly applied by firms to generate business value. By engaging a crowd, a platform, and other stakeholders, a crowdsourcer can foster the co-creation of a portfolio of value for diverse stakeholders. In analyzing the value co-creation in crowdsourcing, we propose a framework by combining the theories and frameworks in value co-creation and crowdsourcing. The framework examines the key stakeholders, joint purpose, engaged value co-creation processes, contributions, bidirectional relationships of the engagement, and perceived value, exhibiting a holistic view of the value co-creation in a crowdsourcing project. Results of the analysis reveal the business performance of the crowdsourcing project and identify areas of improvement regarding business sustainability. This is a major theoretical contribution of this study. The research design applied a case study approach to empirically investigate a crowdsourcing project. Both the theoretical and practical implications are discussed.

This pot-based study investigated the influence of co-composted wood-derived biochar on lettuce growth performance under salinity and drought stress conditions. Biochar of two particle sizes; > 2 mm and < 1 mm were co-composted with the mixture (1:1 ratio of dry weight) of cow and poultry manures. Co-composted biochars were applied at 5% and 7% rates in soil. Control treatments included the amendment of mixture of biochar with manure in soil. Pots were subjected to slight drought (48-55% water filled pore space (WFPS) of soil) and non-drought conditions (60% WFPS) and under 0 and 1.3 dS m-1 salinity. Results revealed that plants growth performance was significantly better under treatments of co-composted biochar and no salt stress conditions, than when mixture of biochar and manure was applied to soil as non-composted fertilizer. Under no stress condition, small particle-sized co-composted biochar increased root biomass by 786.2% than the large particle-sized co-composted biochar at same application rate. As compared to large-sized co-composted biochar, small sized co-composted biochar at high application rates increased root biomass by 167 – 245% but not leaf biomass under both stress conditions. Small particle-sized co-composted biochar amendment also increased the phosphorus use efficiency (PUE) of lettuce leaves than large particle-sized co-composted biochar under no stress condition. The amendment of small-sized co-composted biochar also increased significantly the concentration of Olsen phosphorus in soil than the amendment of large-particle-sized co-composted biochar. In conclusion, amendment of small particle-sized co-composted biochar has the potential of attenuating salinity and drought stress in lettuce and promoting P cycling in soil.

Applications in high-performance computing (HPC) may not use all available computational resources, leaving some of them underutilized. By co-scheduling, i.e. running more than one application on the same computational node, it is possible to improve resource utilization and overall throughput. Some applications may have conflicting requirements on resources and co-scheduling may cause performance degradation, so it is important to take it into account in scheduling decisions. In this paper, we formalized co-scheduling problem and proposed multiple scheduling strategies to solve it: an optimal strategy, an online strategy and heuristic strategies. These strategies vary in terms of the optimality of the solution they produce and a priori information about the system they require. We showed theoretically that the online strategy provides schedules with a competitive ratio that has a constant upper limit. This allowed us to solve the co-scheduling problem using heuristic strategies that approximate this online strategy. Numerical simulations showed how heuristic strategies compare to the optimal strategy for different input systems. We proposed a method for measuring input parameters of the model in practice and evaluated this method on HPC benchmark applications. We showed high accuracy of measurement method, which allows to apply proposed scheduling strategies in scheduler implementation.

The social distancing as a response to COVID 19 pandemic has led to the exceptional reductions of daily routine people activities and vehicle uses mainly in city. This same situation was also experienced by several busy, large, and populous cities in Southeast Asia (SA) countries. Correspondingly, this study aimed to test the hypothesis that the social distancing implementation period has increased the air quality in the term of carbon monoxide (CO) emission reduction as drawn from Jakarta city as an example of the one of populated cities in SA region. The CO was measured in parts per billions (ppb) and monitored on the daily basis employing remote sensor platform. The monitor periods were started from January, February, March, and April 2020 with 10 measurement days for each month. The social distancing was implemented from mid of March to the recent April. The CO measurement data were statistically tested to justify the significant effects of social distancing on the CO levels. Based on the CO data analysis, the order of CO mean by months is February > January > March > April. The CO levels for January, February, March, and April were 87.46 ppb (95%CI: 83.54-91.37), 88.20 ppb (95%CI: 81.65-94.74), 86.38 (95%CI: 81.06-91.69), and 78.68 (95%CI: 74.03-83.32) respectively. This study also find significant difference (p<0.05) of CO levels especially in April when social distancing has been implemented. Hence, these findings illustrate the potential air pollutant reduction gained from implementing social distancing as can be seen in April.

Degussa P25 is a benchmark form of TiO₂ used worldwide in photocatalysis studies. Currently no such benchmark exists for co-catalysts, which are essential for many photocatalytic reactions. Here, we present the preparation of Pt nanocluster co-catalysts on TiO₂ using an unmodified commercial source and equipment that is commonly available. Transmission electron microscopy reveals that the procedure produces TiO₂ decorated with Pt atom and nanoclusters (1-5 atoms). Optical reflectance and X-ray diffraction measurements show that the procedure does not affect the TiO₂ polymorph or UV-Vis absorbance. Gas phase photocatalytic splitting of heavy water (D₂O) shows that the Pt nanocluster decorated TiO₂ outperforms Pt nanoparticle (produced by photodeposition) decorated TiO₂ in D₂ production. Pt nanoclusters, produced directly from a commercial source, with high co-catalyst activity are prime candidates to be used in benchmark photocatalytic reactions.

In order to understand the effect of Pb-CuI co-doping on the thermoelectric performance of Bi₂Te₃, n-type Bi₂Te₃ co-doped with x at% CuI and 1/2x at% Pb (x = 0, 0.01, 0.03, 0.05, 0.07, and 0.10) were prepared via high temperature solid state reaction and consolidated using spark plasma sintering. Electron and thermal transport properties, i.e., electrical conductivity, carrier concentration, Hall mobility, Seebeck coefficient, and thermal conductivity, of CuI-Pb co-doped Bi₂Te₃ were measured in the temperature range from 300 K to 523 K and compared to corresponding x% of CuI-doped Bi₂Te₃ and undoped Bi₂Te₃. The addition of a small amount of Pb significantly decreased the carrier concentration, which could be attributed to the holes from Pb atoms, thus the CuI-Pb co-doped samples show a lower electrical conductivity and a higher Seebeck coefficient compared to CuI-doped samples with similar x values. The incorporation of Pb into CuI-doped Bi₂Te₃ rarely changed the power factor because of the trade-off relationship between the electrical conductivity and the Seebeck coefficient. The total thermal conductivity(κ_tot) of co-doped samples (κ_tot ~1.4 W/m∙K at 300 K) is slightly lower than that of 1% CuI-doped Bi₂Te₃ (κ_tot~1.5 W/m∙K at 300 K) and undoped Bi₂Te₃ (κ_tot ~1.6 W/m∙K at 300 K) due to the alloy scattering. The 1% CuI-Pb co-doped Bi₂Te₃ sample shows the highest ZT value of 0.96 at 370 K. All data on electrical and thermal transport properties suggest that the thermoelectric properties of Bi₂Te₃ and its operating temperature can be controlled by co-doping.

Ambulatory heart rate (HR) monitors that acquire electrocardiogram (ECG) or/and photoplethysmographm (PPG) signals from the torso, wrists, or ears are notably less accurate in tasks associated with high levels of movement compared to clinical measurements. However, reliable estimation of HR can be obtained through data fusion from different sensors. These methods are especially suitable for multimodal hearable devices, where heart rate can be tracked from different modalities, including electrical ECG, optical PPG, and sounds (heart tones). Combined information from different modalities can compensate for single source limitations. In this paper, we evaluate the possible application of data fusion methods in hearables. We assess data fusion for heart rate estimation from simultaneous in-ear ECG and in-ear PPG, recorded on eight subjects while performing 5-minute sitting and walking tasks. Our findings show that data fusion methods provide a similar level of mean absolute error as the best single-source heart rate estimation but with much lower intra-subject variability, especially during walking activities. We conclude that data fusion methods provide more robust HR estimation than a single cardiovascular signal. These methods can enhance the performance of wearable devices, especially multimodal hearables, in heart rate tracking during physical activity.

Laser powder bed fusion can fabricate porous structure through lattices, but it remains a challenge to prepare micropores (

Cracks on concrete surfaces are vital factors affecting construction safety. Accurate and efficient crack detection can prevent safety accidents. Using drones to photograph cracks on a concrete surface and detect them through computer vision technology has the advantages of accurate target recognition, simple practical operation, and low cost. To solve this problem, an improved CenterNet concrete crack-detection model is proposed. First, a channel-space attention mechanism is added to the original model to enhance the ability of the convolution neural network to pay attention to the image. Second, a feature selection module is introduced to scale the feature map in the downsampling stage to a uniform size and combine it in the channel dimension. In the upsampling stage, the feature selection module adaptively selects the combined features and fuses them with the output features of the upsampling. Finally, the target size loss is optimised from a Smooth L1 Loss to IoU Loss to improve its inability to adapt to targets of different sizes. The experimental results show that the improved CenterNet model reduces the FPS by 123.7, increases the GPU memory by 62MB, increases the FLOPs by 3.81, and increases the AP by 0.154 compared with the original model. The GPU memory occupancy remained stable during the training process and exhibited good real-time performance and robustness.

PURPOSE: The aim of this study was to identify the incidence of early mechanical failure in the first post-surgical year in patients who had undergone spinal surgery, and to assess the related risk factors. METHODS: Retrospective observational study of a prognostic cohort was conducted at an orthopaedic hospital, examining all patients with spine degenerative disease who consecutively underwent arthrodesis surgery between March 2018 and March 2019. The incidence of postoperative mechanical failure during the first year was calculated as primary outcome; the time between the date of the implant surgery and diagnosis of the mechanical failure was calculated as secondary outcome. RESULTS: A total of 237 patients were identified for statistical analysis. The median age of the group of patients was 47 years (IQR of 44), and 66.6% were female. The incidence of mechanical failure in the first postoperative year was 5.1% overall with 12 events and the median time between surgery and the need for revision surgery was 5 months (IQR=7.75). ASA score (OR= 2,39; p=0.134), duration of the surgical procedure (OR=1,27; p=0,006) and inability to walk at discharge (OR=7,86; p=0,072) were independent risk of factor associated with the mechanical failure. CONCLUSION: Higher ASA score and longer duration of surgery are risk factors for mechanical failure in the first year in patients who had undergone spinal surgery and must be carefully considered when planning spinal surgery. During hospitalization, recovery of ambulation must be encouraged to prevent mechanical failure. All these factors are useful in identifying patients with a closer follow-up is needed.

Single image deraining (SID) has shown its importance in many advanced computer vision tasks. Though many CNN based image deraining methods have been proposed, how to effectively remove raindrops while maintaining background structure remains a challenge that needs to be overcome. Most of the deraining work focuses on removing rain streaks, but in heavy rain images, the dense accumulation of rainwater or the rain curtain effect significantly interferes with the effective removal of rain streaks, and often introduces some artifacts that make the scene more blurry. In this paper, we propose a new network structure R-PReNet for single image deraining with good background structure maintaining. This framework fully utilizes the cyclic recursive structure of PReNet. Moreover, we introduce residual channel prior (RCP) and feature fusion modules for better deraining performance by focusing on background feature information. Compared with the previous methods, our method has significantly improvement effect on the rainstorm image with the artifacts removing and good visual detail restoring.

Buildings are responsible for approximately 40% of the world’s energy consumption and 36% of the total carbon dioxide emissions. Building occupancy is essential, enabling Occupant-Centric Control for zero emissions and decarbonization. Although existing machine learning and deep learning methods for building occupancy prediction have achieved remarked progress, their analyses remain limited when applied to complex real-world scenarios. Besides, there is a high expectation for Transformer algorithms to predict building occupancy accurately. Therefore, this paper presents an Occupancy Prediction Transformer network (OPTnet). We fuse and feed multi-sensor data (building occupancy, indoor environmental conditions, HVAC operations) into a Transformer model to forecast the future occupancy presence in multiple zones. We perform experimental analysis and compare it to different occupancy prediction methods (e.g., Decision Tree, Long Short-Term Memory networks, Multi-layer perceptron) and diverse time horizons (1,2,3,5,10,20,30mins). The performance metrics (e.g., Accuracy and Mean Squared Error) are employed to evaluate the effectiveness of prediction algorithms. Our OPTnet method achieves superior performance on our experimental two-week data compared to existing methods. The improved performance signifies its potential to enhance HVAC control systems and energy optimization strategies. We will make the code publicly available at https://github.com/kailaisun/occupancy-prediction-binary to promote transparency and reproducibility.

Traditional camera sensors rely on human eyes for observation. However, the human eye 1 is prone to fatigue when observing targets of different sizes for a long time in complex scenes, and 2 human cognition is limited, which often leads to judgment errors and greatly reduces the efficiency. 3 Target recognition technology is an important technology to judge the target category in camera 4 sensor. In order to solve this problem, a small size target detection algorithm for special scenarios was 5 proposed by this paper. Its advantage is that this algorithm not only has higher precision for small 6 size target detection, but also can ensure that the detection accuracy of each size is not lower than the 7 existing algorithm. In this paper, a new down-sampling method was proposed, which could better 8 preserve the context feature information. The feature fusion network was improved to effectively 9 combine shallow information and deep information. A new network structure was proposed to 10 effectively improve the detection accuracy of the model. In terms of accuracy, it is better than: YOLOX, 11 YOLOXR, YOLOv3, scaled YOLOv5, YOLOv7-Tiny and YOLOv8.Three authoritative public data sets 12 were used in this experiment: a) On Visdron data sets (small size targets), DC-YOLOv8 is 2.5% more 13 accurate than YOLOv8. b) On Tinyperson data sets (minimal size targets), DC-YOLOv8 is 1% more 14 accurate than YOLOv8. c) On PASCAL VOC2007 data sets (Normal size target), DC-YOLOv8 is 0.5% 15 more accurate than YOLOv8.

In the field of vision-based robot grasping, effectively leveraging RGB and depth information to accurately determine the position and pose of a target is a critical issue. To address this challenge, we propose a tri-stream cross-modal fusion architecture for 2-DoF visual grasp detection. This architecture facilitates the interaction of RGB and depth bilateral information and is designed to efficiently aggregate multiscale information. Our novel modal interaction module (MIM) with spatial-wise cross-attention algorithm adaptively captures cross-modal feature information. Meanwhile, the channel interaction modules (CIM) further enhance the aggregation of different modal streams. In addition, we efficiently aggregate global multiscale information through a hierarchical structure with skipping connections. To evaluate the performance of our proposed method, we conduct validation experiments on standard public datasets and real robot grasping experiments. We achieve the image-wise detection accuracy of 99.4% and 96.7% on Cornell and Jacquard datasets respectively. The object-wise detection accuracy reaches 97.8% and 94.6% on the same datasets. Furthermore, physical experiments using the 6-DoF Elite robot demonstrate a success rate of 94.5%. These experiments highlight the superior accuracy of our proposed method.

With recent developments in fusion engineering, interest has sparked in development of fusion devices for deterrent. Enormous amount of energy generated by combining two light nuclei could be contained and manipulated at will to trigger and accelerate micro explosions (from shock wave, x-rays or ion beam focusing) which finally result in full scale blast. Materials required to make such device are critical. They must possess high strength, high hardness, ductility, formability, drawability, and anisotropic properties. High entropy alloys (HEA) are new class of materials which nicely fulfils this requirement. Essentially, they are solid solutions of multi principal elements (usually > 5) eliminating the need of base metal as in conventional alloys. This gives them many unique properties which may be tailored at will (heat treatment, cold rolling, precipitation, irradiation). They also exhibit excellent directional properties with formation of distinct bands along certain preferred crystallographic planes even in hexagonal close packed structures. These anisotropic properties are strong function of rolling, working, or forging (swaging) direction and can be utilized to benefit. This study encompasses making outer shell of a typical fusion device selected on the basis of the weight, which is a function of area of pay load bay of carrier aircraft.

Land cover mapping provides spatial information on the physical properties of the Earth’s surface, for various classes of wetlands, artificial surface and constructions, vineyards, water bodies, etc. Having reliable information on land cover is crucial to developing solutions to a variety of environmental problems such as destruction of important wetlands/forests, and loss of fish and wildlife habitats. This has made land cover mapping one of the most widespread application areas in remote sensing computational imaging. However, due to the differences between modalities in terms of resolutions, content, and sensors, integrating complementary information that multi-modal remote sensing imagery exhibits into a robust and accurate system still remains challenging, and classical segmentation approaches generally do not give satisfactory results for land cover mapping. In this paper, we propose a novel dynamic deep network architecture, AMM-FuseNet, that promotes the use of multi-modal remote sensing images for the purpose of land cover mapping. The proposed network exploits the hybrid approach of the Channel Attention mechanism and Densely Connected Atrous Spatial Pyramid Pooling (DenseASPP). In the experimental analysis, in order to to verify the validity of the proposed method, we test AMM-FuseNet applied to four datasets whilst comparing it to the 6 state-of-the-art models of DeepLabV3+, PSPNet, UNet, SegNet, DenseASPP, and DANet. In addition, we also demonstrate the capability of AMM-FuseNet under minimal training supervision (reduced number of training samples) compared to the state-of-the-art, achieving less accuracy loss even for the case with 1/20 of the training samples.

Toxins present in cigarette and e-cigarette smoke constitute a significant cause of illnesses and are known to have fatal health impacts. Specific mechanisms by which toxins present in smoke impair cell repair are still being researched and are of prime interest for developing more effective treatments. Current literature suggests toxins present in cigarette smoke and aerosolized e-vapor trigger abnormal intercellular responses, damage mitochondrial function, and consequently disrupt the homeostasis of the organelle’s biochemical processes by increasing reactive oxidative species. Increased oxidative stress sets off a cascade of molecular events, disrupting optimal mitochondrial morphology and homeostasis. Furthermore, smoking-induced oxidative stress may also amalgamate with other health factors to contribute to various pathophysiological processes. An increasing number of studies show that toxins may affect mitochondria even though exposure to secondhand or thirdhand smoke. This review assesses the impact of toxins present in tobacco smoke and e-vapor on mitochondrial health, networking, and critical structural processes including mitochondria fission, fusion, hyperfusion, fragmentation, and mitophagy. The efforts are focused on discussing current evidence linking toxins present in first, second, and thirdhand smoke to mitochondrial dysfunction

Metastasis is the leading cause of cancer death and can be realized through the phenomenon of tumor cell fusion. The fusion of tumor cells with other tumor or normal cells leads to the appearance of tumor hybrid cells (THCs) exhibiting novel properties such as increased proliferation and migration, drug resistance, decreased apoptosis rate and avoiding immune surveillance. Experimental studies showed the association of THCs with a high frequency of cancer metastasis; however, the underlying mechanisms remain unclear. Many other questions also remain to be answered: the role of genetic alterations in tumor cell fusion, the molecular landscape of cells after fusion, the lifetime and fate of different THCs, and the specific markers of THCs, and their correlation with various cancers and clinicopathological parameters. In this review, we discuss the factors and potential mechanisms involved in the occurrence of THCs, the types of THCs, and their role in cancer drug resistance and metastasis, as well as potential therapeutic approaches for the prevention and targeting of tumor cell fusion. In conclusion, we emphasize the current knowledge gaps in the biology of THCs that should be addressed to develop highly effective therapeutics and strategies for metastasis suppression.

The advancement of precision medicine critically depends on the robustness and specificity of the carriers used for the targeted delivery of effector molecules in the human body. Numerous nanocarriers have been explored in vivo, to ensure the precise delivery of molecular cargos via tissue-specific targeting, including the endocrine part of the pancreas, thyroid, and adrenal glands. However, even after reaching the target organ, the cargo-carrying vehicle needs to enter the cell and then escape from lysosomal destruction. Most of artificial nanocarriers suffer from intrinsic limitations that either prevent them from completing the specific delivery of the cargo. In this respect, extracellular vesicles (EVs) seem to be the natural tool for payload delivery due to their versatility and low toxicity. However, EV-mediated delivery is not selective and usually short-ranged. By inserting the viral membrane fusion proteins into exosomes, it is possible to increase the efficiency of membrane recognition and also ease the process of membrane fusion. This review describes the molecular details of the viral-assisted interaction between the target cell and extracellular vesicles. We also discuss the question of the usability of viral fusion proteins in developing extracellular vesicle-based nanocarriers with higher efficacy of payload delivery. Finally, this review specifically highlights the role of Gag and RNA binding proteins in RNA sorting into extracellular vesicles.

Metal powder bed fusion (PBF) additive manufacturing (AM) builds metal parts layer by layer upon a substrate material. The strength of this interface between substrate and printed material is important to characterize, especially in applications where the substrate is retained and included in the finished part. This paper studied the tensile and torsional strengths of wrought and additively manufactured (through PBF) SS316L and compared them to specimens composed of half wrought material and half PBF material. The PBF specimens consistently exhibited higher strength and lower ductility than the wrought specimens. The hybrid PBF/wrought specimens performed similarly to the wrought material. In no specimens did any failure appear to occur at or near the interface between wrought substrate and PBF material. In addition, most of the deformation in the PBF/wrought specimens appeared to be limited to the wrought portion of the specimens. These results are consistent with microscopy showing smaller grain size in the PBF material, which often leads to increased strength in SS316L due to the Hall-Petch relationship.

Image fusion is a useful tool for producing a high-resolution multispectral image to be used for land use and land cover mapping. In this study, we use nine pansharpening algorithms namely Color Normalized (CN), Gram-Schmidt (GS), Hyperspherical Color Space (HCS), High Pass Filter (HPF), Nearest-Neighbor Diffusion (NND), Principal Component Analysis (PCA), Resolution Merge (RM), Stationary Wavelet Transform (SWT), and Wavelet Resolution Merge (WRM) to fusion Worldview-3 multispectral Bands and panchromatic band. In spectral and spatial fidelity, several image quality metrics are used to evaluate the performance of pansharpening algorithms. The SWT and PCA algorithms showed better results compared to other pansharpening algorithms while GS and CN algorithms showed the worst results for the original image fusion. The effect of fusion on each band was separately investigated and according to the calculations, we found that the CoastalBlue band and the Blue band showed the best result and the NIR-1 band and NIR-2 band show the worst result for the original image fusion. In the end, we conclude that the choice of fusion method depends on the requirement of remote sensing application.

Indoor navigation systems must deal with absence of GPS signals, since they are only available in outdoor environments. Therefore, indoor systems have to rely upon other techniques for positioning users. Recently various indoor navigation systems have been designed and developed to help visually impaired people. In this paper an overview of some existing indoor navigation systems for visually impaired people are presented and they are compared from different perspectives. The evaluated techniques are ultrasonic systems, RFID-based solutions, computer vision aided navigation systems, ans smartphone-based applications.

Visual inertial odometry (VIO) has recently received much attention for efficient and accurate ego-motion estimation of unmanned aerial vehicle systems (UAVs). Recent studies have shown that optimization-based algorithms achieve typically high accuracy when given enough amount of information, but occasionally suffer from divergence when solving highly non-linear problems. Further, their performance significantly depends on the accuracy of the initialization of inertial measurement unit (IMU) parameters. In this paper, we propose a novel VIO algorithm of estimating the motional state of UAVs with high accuracy. The main technical contributions are the fusion of visual information and pre-integrated inertial measurements in a joint optimization framework, and the stable initialization of scale and gravity using relative pose constraints. To count for ambiguity and uncertainty of VIO initialization, a local scale parameter is adopted in the online optimization. Quantitative comparisons with the state-of-the-art algorithms on the EuRoC dataset verify the efficacy and accuracy of the proposed method.

Ti-aluminosilicate gels were used as supports for immobilization of Fe, Co and Ni oxides (5%) by impregnation, and synthesis of efficient photocatalysts in degradation of β-lactam antibiotic from water. Titanium oxide (1 and 2%) was incorporated into zeolite network by modifying the gel during the zeolitation process. The formation of the zeolite Y structure and its microporous structure were evidenced by X-ray diffraction and N2 physisorption. The structure, composition, reduction and optical properties were studied by X-ray difraction, H2-TPR, XPS, Raman, photoluminiscence and UV-Vis spectroscopy. The obtained results indicated a zeolite Y structure for all photocatalysts with tetra-coordinate Ti4+ sites. The immobilized metals from group VIII are both in the form of metal oxides such as Fe2O3, Fe3O4, CoO, Co3O4 , NiO and also in the me-tallic state (Fe0, Co0, and Ni0). A red shift of the absorption edge was observed in UV-Vis spectra of photocatalysts upon addition of Fe, Co or Ni species. The photocatalytic performances were evaluated in degradation of cefuroxime from water under visible light irradiation. The best results were obtained for iron immobilized photocatalysts. Scavenger experiments explained the photocatalytic results and their mechanisms. A different contribution of the active species to the photocatalytic reactions was evidenced.

CD74 is a type II cell surface receptor found to be highly expressed in several hematological and solid cancers, due to its ability to activate pathways associated with tumor cell survival and proliferation. Over the past 16 years, CD74 is emerging as a commonly detected fusion partner in multiple oncogenic fusion proteins. Studies have found CD74 fusion proteins in a range of cancers including lung adenocarcinoma, inflammatory breast cancer, and pediatric acute lymphoblastic leukemia. To date, there are five known CD74 fusion proteins, CD74-ROS1, CD74-NTRK1, CD74-NRG1, CD74-NRG2a, and CD74-PDGFRB, with a total of 16 different variants, each with unique genetic signatures. Importantly, the occurrence of CD74 in the formation of fusion proteins has not been well explored despite the fact that ROS1 and NRG1 families utilize CD74 as the primary partner for the formation of oncogenic fusions. Fusion proteins known to be oncogenic drivers, including those of CD74, are typically detected, and targeted after standard chemotherapeutic plans fail and the disease relapses. The analysis reported herein provides insights into early intervention of CD74 fusions and highlight the need for improved routine assessment methods so that targeted therapies can be applied while they are most effective.

The SARS-CoV-2 have caused a devastating pandemic of all times in the recent human history. However, there is a serious paucity in high quality data on aggravating factors and mechanisms of co-infection. This study aimed to identify the trending patterns of bacterial co-infections and types and associated outcomes in three phases of the pandemic. Using quality hospital data, we have investigated the SARS-CoV-2 fatality rates, profiles, and types of bacterial co-infections before, during, and after COVID-19 vaccinations. Out of 389 isolates used in different aspects, 298 was examined before and during the pandemic (n=149 before, n=149 during), death rates were 32% during compared to only 7.4% before pandemic with significant association (P value = 0.000000075). Death rate was 34% in co-infected (n = 170) compared to non-co-infected patients (n = 128) indicating a highly significant value (P value = 0.00000000000088). However, analysis of patients without other respiratory problems (n=28) indicated that among the remaining 270 patients, death was 30% in co-infected patients (n=150) and only 0.8% in non-coinfected (n=120) with high significant P value= 0.00000000076. The trending patterns of co-infections before, during, and after vaccinations showed a significant decline in Staphylococcus aureus with concomitant peaks in Gram-negatives in totals of (n= 149 before/n= 149 during): Klebsiella pneumonia (n = 11/49 before/during; E. coli n=10/24, A. baumannii n=8/25, and Ps. Aeruginosa n= 5/16, and S. aureus 13/1. Nevertheless, in post vaccination phase, (n= 91) gender-specific co-infections were examined for potential differences in susceptibility. Methicillin resistant S. aureus (MRSA) dominated both genders followed by E. coli in males and females with the latter gender showing higher rates of isolations in both species. Klebsiella pneumoniae declined to third place mostly in male patients. The drastic decline in K. pneumoniae and Gram-negatives post-vaccination strongly imply a potential co-protection in vaccines. Future analysis would gain more insights into molecular mimicry.

In this article, we review about the nature of Kerr Blackhole, Kerr metric and express kerr metric in Boyer-Lindquist co-ordinates.

The increase in carbon dioxide emissions has a significant impact on human society and the global environment. As the most abundant and cheap C1 resource, the conversion and utilization of carbon dioxide has received extensive attention from researchers. In many methods of carbon dioxide conversion and utilization, the reverse water gas conversion reaction is considered to be one of the most effective ways. In this paper, the research progress of reverse water gas conversion reaction in recent years is introduced.

Abstract Congenital rubella syndrome is a constellation of birth defects that can have devastating consequences, impacting approximately 100,000 births worldwide each year. The incidence is much lower in countries that routinely vaccinate their population. In the US, postnatal immunization of susceptible women is an important epidemiological strategy for the prevention of rubella. However, concerns that co-administration of Rubella vaccine with other immunoglobins (i.e., Rhogam) could comprise vaccine efficacy has produced warnings that can delay the administration of Rubella vaccination postpartum, leaving women susceptible in a subsequent pregnancy. We aimed to address whether co-administration of Rubella vaccine and Rhogam decreased antibody responses as compared to those receiving only Rubella vaccination. This retrospective cohort study utilized clinical data from 80 subjects who received Rubella vaccine and Rhogam after delivery and 43 subjects received Rubella vaccine alone. Maternal demographics, pregnancy complications and rubella status at the start of a subsequent pregnancy were recorded for analysis. Overall, the two cohorts had similar baseline characteristics; however, lower parity was noted in the participants having both Rubella vaccination and Rhogam. Based on maternal antibody IgG index for rubella during the next pregnancy, we observed that 88% of the Rhogam + Rubella vaccine group had positive titers, which was not significantly different than the 81% in the Rubella vaccine only cohort (p=0.36). In conclusion, no differences in the rubella immunity status in a subsequent pregnancy were observed in those mothers administered both Rubella vaccine and Rhogam concurrently. Given these findings, warnings against co-administration of Rubella vaccine in combination with other immunoglobulins should be discontinued.

Vessel co-option correlates with resistance against anti-angiogenic agents and chemotherapy in colorectal cancer liver metastasis (CRCLM). We previously identified higher intensity of neutrophils in the tumour microenvironment of vessel co-opting CRCLM lesions compared to their angiogenic counterparts. Herein, we demonstrated that over 50% of the neutrophils in vessel co-opting lesions are expressing pro-apoptotic markers including cleaved caspase-3 and poly (ADP-ribose) polymerase-1 (PARP-1). Our previous publications suggested upregulation of transforming growth factor-beta (TGFβ1) in the microenvironment of vessel co-option CRCLM. Therefore, we examined the effect of TGFβ1 on the expression of cleaved caspase-3 and PARP-1 in neutrophils in vitro. Significantly, we noticed the upregulation of pro-apoptotic markers upon exposure to TGFβ1. This finding might pave the way to determine the role of neutrophils in developing vessel co-option in CRCLM in the future.

This study is focused on the mechanical properties of WC-Co composites obtained via Selective Laser Sintering using PA12 as a binder. The as-printed samples were thermally debonded, and sintered, first in vacuum, and then sinter-HIPed at 1400oC, using 50 bar Ar, which has led to relative densities up to 66 %. Optical metallographic images show a microstructure consisting of WC, with an average grain size in the range of 1.4 – 2.0 µm, with isolated large grains, in a well-distributed Co matrix. The shrinkage of the samples was 43 %, with no significant shape distortion. The printing direction of the samples has a great impact on the transversal rupture strength (TRS). Nevertheless, the bending strength was low, with a measured maximum of 612 MPa. SEM images of the fracture surface of TRS samples show the presence of defects that constitute the cause of the low measured values. The hardness values position the obtained composites in the range of medium coarse classical cemented carbides. The results were also related to the amount of free Co after sintering, close to the initial one, as assessed by magnetic measurements, indicating a low degree of interaction with PA12 decomposition products.

Age-related alterations in the gut microbiome composition and its impacts on the host’s health have been well described; however, detailed analyses of the gut microbial structure defining ecological microbe-microbe interactions is limited. One of the ways to determine these interactions is by understanding microbial co-occurrence patterns. We previously showed promising abilities of Lactobacillus acidophilus DDS-1 on the aging gut microbiome and immune system. However, the potential of the DDS-1 strain to modulate microbial co-occurrence patterns is unknown. Hence, we aimed to investigate the ability of L. acidophilus DDS-1 to modulate the fecal, mucosal and cecal-related microbial co-occurrence networks in young and aging C57BL/6J mice. Our Kendall’s tau correlation measures of co-occurrence revealed age-related changes in the gut microbiome, which were characterized by reduced number of nodes and associations across sample types when compared to younger mice. After four-week supplementation, L. acidophilus DDS-1 differentially modulated the overall microbial community structure in fecal and mucosal samples as compared to cecal samples. Beneficial bacteria such as Lactobacillus and Akkermansia acted as connectors in aging networks in response to L. acidophilus DDS-1 supplementation. Our findings provided the first evidence of the DDS-1-induced gut microbial ecological interactions revealing the complex structure of microbial ecosystems with age.

Plastid gene expression involves many post-transcriptional maturation steps resulting in a complex transcriptome composed of multiple isoforms. Although short read RNA-seq has considerably improved our understanding of the molecular mechanisms controlling these processes, it is unable to sequence full-length transcripts. This information is however crucial when it comes to understand the interplay between the various steps of plastid gene expression. Here, the study of the Arabidopsis leaf plastid transcriptome using Nanopore sequencing showed that many splicing and editing events were not independent but co-occurring. For a given transcript, maturation events also appeared to be chronologically ordered with splicing happening after most sites are edited.

Hormones must be balanced and dynamically controlled for the Female Reproductive Tract (FRT) to function correctly during the menstrual cycle, pregnancy, and delivery. Gamete selection and successful transfer to the uterus, where it implants and pregnancy occurs, is supported by the mucosal epithelial lining of the FRT ovaries, uterus, cervix, fallopian tubes, and vagina. Successful implantation and placentation in humans and other animals rely on complex interactions between the embryo and a receptive female reproductive system. The FRT's recent breakthroughs in three-dimensional (3D) organoid systems now provide critical experimental models that match the organ's physiological, functional, and anatomical characteristics in vitro. This article summarizes the current state of the art on organoids generated from various parts of the FRT. The current analysis examines recent developments in the creation of organoid models of reproductive organs, as well as their future directions.