Introduction Nearly 25% of systemic symptoms of autoimmune disorders are misdiagnosed and mismanaged and often come with flare-ups or complications. The coexistence of multiple rheumatic diseases makes it more challenging regarding both management and diagnosis. Several types of overlap syndrome are documented in the literature. While two or more rheumatic diseases coexist, one disease often is clinically predominant. Rhupus syndrome, which combines the clinical and laboratory aspects of rheumatic arthritis (RA) and systemic lupus erythematosus (SLE), is one of the uncommon and sporadically documented overlaps. SLE and RA are systemic autoimmune rheumatic illnesses that affect multiple organs and systems and have unique clinical and serological traits.  (1)“ Rhupus” was first coined in 1971 to describe patients who satisfy the criteria for both systemic lupus erythematosus(SLE) and rheumatoid arthritis(RA). (2) it has been defined as a deforming and symmetric polyarthritis accompanied by symptoms of SLE and the presence of antibodies such as ant-ds-DNA, anti-smith, and rheumatoid factor with or without ant-CCP antibody. (a)  because of the rarity of the disease the prevalence, pathophysiology, natural history, and radiological and immunological profiles profile of rhupus are poorly described.There is no known etiology causing the disease but there are limited studies suggesting the combined role of genetic, immunological, hormonal, and environmental factors in the progression of the disease. (3) identification of rhupus is very essential owing that their therapy and outcome differ from those patients having RA or SLE alone. (4)We report one such rare case below.Case presentation :

A document by Trung Le. Click on the document to view its contents.

Triangular Lunulae in Papillon-Lefèvre Syndrome_ A Case Report

Recurrent unilateral periorbital cellulitis: Case report on challenges in differential diagnosis between periorbital cellulitis and idiopathic orbital cellulitis in the absence of inflammatory markersVera Gulácsy1,*, Mohamed Mahdi2,3, Tibor Kalmár4, Marianna Csenki4, Csaba Bereczki4, Hajnalka Szabó 41 Department of Pediatrics, Fejér County Szent György University Teaching Hospital, Székesfehérvár, Hungary.2 Infectology Clinic, University of Debrecen Clinical Center, Debrecen, Hungary.3 Department of Biochemisstry and Molecular Biology, University of Debrececn, Debrecen, Hungary.4 Department of Pediatrics and Pediatric Health Center, Albert Szent-Györgyi Health Centre, University of Szeged, Szeged, Hungary.* Corresponding author VG, email: [email protected]

Rapid evolution contributes to plant invasion success. Previous studies have rarely considered the coevolution of multidimensional traits in invasive plants. We compared multiple traits related to growth, fecundity, and herbivore palatability of the widespread invader Spartina alterniflora in its native (US) and introduced (China) families across large geographic scales. Of 18 tested variables, ten revealed genetic-based differences between native and introduced ranges, and nine exhibited latitudinal clines within the introduced range. Introduced families compared to natives exhibited superior syndromes with larger growth, higher fecundity, and lower palatability, which were linked to provenance climates and could enhance plant competitiveness and spread. We conclude that within only 40 years since its introduction to China, Spartina has evolved an integrated ecological strategy to enhance invasiveness under climate selective pressure, making it the most successful invader along China’s coast. Our study underscores the importance of considering multivariate traits to understand plant invasion success.

Inverted (p-i-n) perovskite solar cells (PSCs) are favored by researchers owing to their superior compatibility with flexible substrates and tandem device fabrication. Additionally, the hole transport layer (HTL) serves as a template for perovskite growth, which is critical for enhancing the device performance. However, the current research on how the HTL promotes perovskite crystallization is insufficient. Here, 4PADCB, a self-assembled monolayer (SAM) hole transport material, was optimized as a superior template for perovskite growth through comparative analysis; accordingly, compact perovskite film with vertical growth was prepared. The better matched energy level alignment between 4PADCB and perovskite suppressed nonradiative recombination at the interface and enabled rapid hole extraction. Moreover, high-quality perovskite film growth on 4PADCB exhibited lower Young’s modulus and less residual stress. By integrating 4PADCB into p-i-n PSCs, the optimal device achieved a power conversion efficiency of 24.80%, with an open-circuit voltage of 1.156 V, thus achieving the best rank among devices without perovskite post-treatment, additives, dopants, or intermediate layers. Furthermore, the unencapsulated device demonstrated exceptional thermostability and photostability under maximum power point tracking. Thus, this work provides a new understanding for the development of novel SAMs and perovskite growth, and it is expected to further improve device performance.

Biomass gasification for syngas production is one of key operating units in the biomass utilization process, however its overall efficiency and stability are normally limited by the presence of complex impurities including particulate matters (PMs) and tars. Herein, a highly integrated ceramic membrane-based reactor was developed for high temperature syngas cleaning to allow the efficient in situ removal of PMs and tars from bio-vapours generated by biomass gasification. In specific, silicon carbide (SiC) membrane could in situ separate the PMs from biomass volatiles, while structured Ni 15La 5/S1-SiC catalyst (nickel and lanthanum-laden silicalite-1 zeolite supported on SiC foam) could promote the catalytic reforming of tars. Compared to other control reactors (i.e., with either membrane or catalyst alone), the integrated reactor demonstrated synergistic intensification in producing clean syngas from biomass gasification, with PM and tar removal efficiencies up to ~97% and ~90%, respectively, and excellent stability in five-cycle evaluations at 800 °C.

Spatial synchrony, the tendency for temporal fluctuations in an ecological variable to be positively associated in different locations, is a widespread and important phenomenon in ecology. Understanding of the nature and mechanisms of synchrony, and how synchrony is changing, has developed rapidly over the past two decades. Many recent developments have taken place through the study of long-term datasets. Here, we review and synthesize some important recent advances in spatial synchrony, with a focus on how long-term data have facilitated new understanding. Longer time series do not just facilitate better testing of existing ideas or more precise statistical results; more importantly, they also frequently make possible the expansion of conceptual paradigms. We discuss several such advances in our understanding of synchrony, how long-term data led to these advances, and how future studies can continue to improve the state of knowledge.

A document by Amin Zeraatkar . Click on the document to view its contents.

There has been a pressing necessity to tax Sugar-Sweetened Beverages (SSB) taxation in Indonesia. Despite the rising prevalence of obesity and diabetes, past attempts at introducing SSB excise taxes have been repeatedly rejected or delayed. Reflecting on other similar policies in other countries, this commentary highlights the potential of SSB taxation as a public health intervention to curb consumption and mitigate associated health risks. It examines historical legislative efforts, current challenges, and the pivotal role of political commitment in overcoming industry lobbying. The commentary outlines strategic steps for advancing SSB taxation policy, including policy design, stakeholder engagement, and robust enforcement mechanisms. Emphasis is placed on evidence-based policymaking, cross-sector collaboration, and the allocation of excise revenue towards public health initiatives. The article concludes with a call for decisive action to address Indonesia’s burgeoning public health crisis through effective SSB taxation implementation.

The antireflection(AR) coating applied to solar glass in photovoltaic modules has remained largely unchanged for decades, despite its well-documented lack of durability. Traditional porous structured single-layer AR coatings last as little as 5 years in the field. In this paper, we propose a novel 5-layer dense AR coating design that offers improved durability and effectiveness compared to traditional coatings. This paper provides detailed insights into the development and characterization of the novel 5-layer AR coating, providing guidance to the photovoltaic community seeking to improve the efficiency and longevity of solar modules.

This study validated an UPLC-MS/MS analysis method to simultaneously detect twelve cannabinoids. The concentration-response relationship for all analyzed cannabinoids was linear with R 2 values > 0.99 using the developed method, the relative standard deviations of recovery for the three levels of spiked samples are between 66.1%~104.1%. The method was used to analyze 43 industrial hemp flower and leaf samples, with the data being statistically analyzed. The analysis results showed that the cannabinoids content varied significantly among different varieties and different pretreatment methods, sample heating treatment led to the decarboxylation of acidic cannabinoids and the mutual conversion of cannabinoids. Based on the statistical analysis of the cannabinoids, hemp from different regions and different varieties were well distinguished by the PLS-DA model, with the main contributing substances being Cannabidiol, Δ 9-tetrahydrocannabinol, and Δ 8-tetrahydrocannabinol.

In the global monitoring of smart cities, the demands of global object detection systems based on cloud and fog computing in intelligent systems can be satisfied by photographs with globally recognized properties. Nevertheless, conventional techniques are constrained by the imaging depth of field and can produce artifacts or indistinct borders, which can be disastrous for accurately detecting the object. In light of this, this paper proposes an artificial intelligence-based gradient learning network that gathers and enhances domain information at different sizes in order to produce globally focused fusion results. Gradient features, which provide a lot of boundary information, can eliminate the problem of border artifacts and blur in multi-focus fusion. The multiple-receptive module (MRM) facilitates effective information sharing and enables the capture of object properties at different scales. In addition, with the assistance of the global enhancement module (GEM), the network can effectively combine the scale features and gradient data from various receptive fields and reinforce the features to provide precise decision maps. Numerous experiments have demonstrated that our approach outperforms the seven most sophisticated algorithms currently in use.

Purpose：The primary objective of this study was to comprehensively evaluate and compare the therapeutic efficacy of trastuzumab in combination with capecitabine plus cisplatin versus capecitabine plus cisplatin in the management of patients diagnosed with advanced human epidermal growth factor receptor 2 (HER2)-positive gastric cancer. Aiming to facilitate clinical decision-making and ultimately improving treatment outcomes for this specific patient population. Methods：A comprehensive computerized search was conducted across multiple databases, including Cochrane Library, Web of Science, PubMed, Embase, CNKI, CBM, VIP, and Wanfang to identify domestic and foreign clinical randomized controlled trials (RCTs), investigating the efficacy of trastuzumab in combination with capecitabine plus cisplatin for the treatment of patients with advanced HER2-positive gastric cancer. The search encompassed articles published from the inception of the databases until July 1, 2022. Results：This meta-analysis comprised 12 studies involving a total of 1199 patients diagnosed with advanced HER2-positive gastric cancer. The results revealed that the experimental group exhibited significantly higher rates of total effectiveness and control compared to the control group. Moreover, the experimental group showed a significant increase in median survival time compared to the control group. Additionally, the experimental group exhibited a significantly higher quality of life score and demonstrated improved prognosis in terms of carbohydrate antigen 19-9 (CA19-9) levels, with a lower recurrence rate. The experimental group showed a decrease in the stage of gastric cancer based on carbohydrate antigen 72-4 (CA72-4) levels and (CEA) levels compared to the control group.. Furthermore, the experimental group exhibited a notable enhancement in the therapeutic efficacy of vascular endothelial growth factor (VEGF) and a superior prognosis compared to the control group. Conclusion：Trastuzumab in combination with capecitabine plus cisplatin can be a preferred first-line treatment option for advanced HER2-positive gastric cancer, accompanying by a promising therapeutic efficacy.

The integration of precise landing capabilities into UAVs is crucial for enabling autonomous operations, particularly in challenging environments such as the offshore scenarios. This work proposes a heterogeneous perception system that incorporates a multimodal fiducial marker, designed to improve the accuracy and robustness of autonomous landing of UAVs in both daytime and nighttime operations. This work presents ViTAL-TAPE, a visual transformer-based model, that enhance the detection reliability of the landing target and overcomes the changes in the illumination conditions and viewpoint positions, where traditional methods fail. VITAL-TAPE is an end-to-end model that combines multimodal perceptual information, including photometric and radiometric data, to detect landing targets defined by a fiducial marker with 6 degrees-of-freedom. Extensive experiments have proved the ability of VITAL-TAPE to detect fiducial markers with an error of 0.01 m. Moreover, experiments using the RAVEN UAV, designed to endure the challenging weather conditions of offshore scenarios, demonstrated that the autonomous landing technology proposed in this work achieved an accuracy up to 0.1 m. This research also presents the first successful autonomous operation of a UAV in a commercial offshore wind farm with floating foundations installed in the Atlantic Ocean. These experiments showcased the system's accuracy, resilience and robustness, resulting in a precise landing technology that extends mission capabilities of UAVs, enabling autonomous and Beyond Visual Line of Sight offshore operations.

In order to address the challenges of complex process and low precision in traditional device modeling, based on the double hidden layer conjugate gradient back propagation neural network (CG-BPNN) and the double hidden layer Levenberg-Marquardt back propagation neural network (LM-BPNN), two small signal models are proposed and analyzed for the gallium arsenide (GaAs) pseudomorphic high electron mobility transistor (pHEMT) here. At first, the scattering parameters (S-parameters) of GaAs pHEMT are divided into training set and test set randomly. Experimental results show that the CG-BPNN is better than another S-parameters when predicting ImS12 with mean square error (MSE) of 1.0449e-05, while LM-BPNN predicts ImS12 with MSE of 3.0954e-06. Meanwhile, the MSE of CG-BPNN is higher than LM-BPNN when predicting all the S-parameters. In addition, it shows a smaller fluctuation range for the error curve of LM-BPNN, which is more stable than the CG-BPNN. Therefore, the double hidden layer LM-BPNN is the better choice to model the small signal of GaAs pHEMT.

Case Report

A document by Abdus Ansari. Click on the document to view its contents.