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Background: Innovative treatments for non‐melanoma skin cancers (NMSCs) are required to enhance patient outcomes. Aims: This review examines the effectiveness and safety of receptor tyrosine kinase inhibitors (RTKIs). Methods: A comprehensive review was conducted on the treatment potential of several RTKIs, namely cetuximab, erlotinib, gefitinib, panitumumab, and lapatinib. Results: The findings indicate that these targeted therapies hold great promise for the treatment of NMSCs. However, it is crucial to consider relapse rates and possible adverse effects. Further research is needed to improve treatment strategies, identify patient groups that would benefit the most, and assess the long‐term efficacy and safety, despite the favorable results reported in previous studies. Furthermore, it is crucial to investigate the potential benefits of integrating RTKIs with immunotherapy and other treatment modalities to enhance the overall efficacy of therapy for individuals with NMSC. Conclusions: Targeted therapies for NMSCs may be possible with the use of RTKIs. The majority of studies focused on utilizing epidermal growth factor receptor inhibitors as the primary class of RTKIs for the treatment of NMSC. Other RTKIs were only employed in experimental investigations. Research indicates that RTKIs could potentially serve as a suitable alternative for elderly patients who are unable to undergo chemotherapy and radiotherapy. [ABSTRACT FROM AUTHOR]

Background Materials and Methods Results Conclusion Macular amyloidosis is a form of primary localized cutaneous amyloidosis presented by pruritic pigmented macules in rippled or reticulate pattern. The aim of this study was to assess the efficacy of using topical tranexamic acid with micro‐needling comparing to micro‐needling alone in patients with macular amyloidosis.Patients with bilaterally located macular amyloidosis on trunk or upper extremities were recruited in this trial. The skin lesions in all patients were divided into two parts which were randomly assigned to the group of treatment with micro‐needling plus tranexamic acid and the group of micro‐needling alone. There were four sessions of treatment with 2 weeks interval. The percentage of improvement in pigmentation (based on photographs and dermoscopy) and rippling of each group was determined by three blinded dermatologists. The level of patient satisfaction and reduction of pruritus was measured by a questionnaire and defined as a percentage.Twenty females were enrolled in this study. The mean (SD) patients' age was 39.7 (±10.13) years. Both groups showed improvement in pigmentation based on images, dermoscopy, and rippling pattern. Patients' satisfaction was 46.5% in tranexamic acid group and 47.5% in micro‐needling alone. Nevertheless, there was no significant difference between both groups (p value >0.05). Interestingly, the pruritus improved 61.66% after four sessions of treatment in both groups.Micro‐needling is a suitable modality for decreasing pruritus and pigmentation in macular amyloidosis. However, topical application of tranexamic acid does not lead to additional improvement. [ABSTRACT FROM AUTHOR]

An alarm or an alarm system is a device that warns or detects any violation of privacy in different places by making noise, sound, or warning the person in a variety of ways, including via email, SMS, phone call, or sounding. Alarms that are currently available in the market have different shapes and types. Generally, they have a common structure and their main purpose is similar to each other. There is another type of burglar alarm in the market, which is used today in certain places to protect property and assets, and in certain organizations such as banks and car alarms. This article reviews and presents a different alarm, whose main purpose is to provide possible security in public and private places, especially military places. [ABSTRACT FROM AUTHOR]

Working with pushbroom imagery in photogrammetry and remote sensing presents a fundamental challenge in object-to-image space transformation. For this transformation, accurate estimation of Exterior Orientation Parameters (EOPs) for each scanline is required. To tackle this challenge, Best Scanline Search or Determination (BSS/BSD) methods have been developed. However, the current BSS/BSD methods are not efficient for real-time applications due to their complex procedures and interpolations. This paper introduces a new non-iterative BSD method specifically designed for line-type pushbroom images. The method involves simulating a pair of sets of points, Simulated Control Points (SCOPs), and Simulated Check Points (SCPs), to train and test a Multilayer Perceptron (MLP) model. The model establishes a strong relationship between object and image spaces, enabling a direct transformation and determination of best scanlines. This proposed method does not rely on the Collinearity Equation (CE) or iterative search. After training, the MLP model is applied to the SCPs for accuracy assessment. The proposed method is tested on ten images with diverse landscapes captured by eight sensors, exploiting five million SCPs per image for statistical assessments. The Root Mean Square Error (RMSE) values range between 0.001 and 0.015 pixels across ten images, demonstrating the capability of achieving the desired sub-pixel accuracy within a few seconds. The proposed method is compared with conventional and state-of-the-art BSS/BSD methods, indicating its higher applicability regarding accuracy and computational efficiency. These results position the proposed BSD method as a practical solution for transforming object-to-image space, especially for real-time applications. [ABSTRACT FROM AUTHOR]

Software-Defined Networking (SDN) represents a significant paradigm shift in network architecture, separating network logic from the underlying forwarding devices to enhance flexibility and centralize deployment. Concurrently, the Internet of Things (IoT) connects numerous devices to the Internet, enabling autonomous interactions with minimal human intervention. However, implementing and managing an SDN-IoT system is inherently complex, particularly for those with limited resources, as the dynamic and distributed nature of IoT infrastructures creates security and privacy challenges during SDN integration. The findings of this study underscore the primary security and privacy challenges across application, control, and data planes. A comprehensive review evaluates the root causes of these challenges and the defense techniques employed in prior works to establish sufficient secrecy and privacy protection. Recent investigations have explored cutting-edge methods, such as leveraging blockchain for transaction recording to enhance security and privacy, along with applying machine learning and deep learning approaches to identify and mitigate the impacts of Denial of Service (DoS) and Distributed DoS (DDoS) attacks. Moreover, the analysis indicates that encryption and hashing techniques are prevalent in the data plane, whereas access control and certificate authorization are prominently considered in the control plane, and authentication is commonly employed within the application plane. Additionally, this paper outlines future directions, offering insights into potential strategies and technological advancements aimed at fostering a more secure and privacy-conscious SDN-based IoT ecosystem. [ABSTRACT FROM AUTHOR]

Key Clinical Message: Rituximab‐induced serum sickness (RISS) is a rare complication of Rituximab (RTX) in immunobullous disorders. Clinicians should be aware of the occurrence of serum sickness symptoms during RTX administration, and prompt initiation of corticosteroid therapy is crucial in these patients. Additionally, RISS may occur with subsequent RTX doses and patients should be counseled accordingly. Rituximab (RTX) is a chimeric monoclonal anti‐CD20 antibody which has gained approval for the treatment of various autoimmune and lymphoproliferative disorders. While RTX‐induced minor reactions, including immediate infusion‐related reactions, are common, serum sickness is rare. Limited data exist regarding rituximab‐induced serum sickness (RISS) in pemphigus vulgaris (PV) and mucous membrane pemphigoid (MMP). We report two cases of RISS following RTX administration in PV and MMP patients. Both patients presented with typical symptoms of serum sickness after RTX infusion, necessitating drug cessation and corticosteroid therapy for resolution. RISS represents a rare complication of RTX therapy. Clinicians should maintain awareness of serum sickness presentations during and post‐RTX administration. [ABSTRACT FROM AUTHOR]

This study explores the effect of incorporating steel fibres and fly ash into self‐compacting concrete (SCC) in various combinations on its mechanical properties. The study begins with thoroughly investigating the fresh properties to ensure compliance with SCC standards when adding steel fibres. Subsequently, mixes that meet SCC standards are evaluated for their mechanical properties. The study aims to enhance the mechanical properties of SCC while maintaining its flowability, filling ability, and passing ability. The research findings provide valuable insights into the optimal combination of steel fibres and fly ash for improving the mechanical properties of SCC. The addition of hooked end type steel fibres increases the compressive strength. When compared to crimped type the mechanical properties increased to 14.4%; however, the strength decreases beyond 1% of steel fibres. Satisfactory results are obtained for fresh properties test. [ABSTRACT FROM AUTHOR]

Summary: Wireless sensor networks (WSNs) are faced with the challenge of energy conservation, which makes efficient routing protocols crucial for prolonging network lifetime. In addition, delay time from sensors to the base station is critical in applications such as military, medical, and security monitoring systems. Chain‐based protocols like PEGASIS, CCBRP, and CCM have been developed to address routing in WSNs, with the aim of reducing energy consumption and delay. However, node failures are inevitable due to energy reduction and node mobility. Therefore, fault tolerance techniques must be integrated into routing protocols. A new fault tolerance method has been proposed to prevent early chain failures in WSNs by formulating network availability and reliability using Markov chain analysis. The results indicate that chain‐based routing protocols with one spare node are more reliable than those with two spare nodes. [ABSTRACT FROM AUTHOR]

Background: Psoriasis as a common cutaneous inflammatory disease affect many aspects of patients' life. Disease registries render it possible to collect valuable data regarding a disease prevalence and burden as well as long‐term observations concerning possible therapeutic regimens. Methods: This registry was designed for the ongoing systematic data collection on patients with psoriasis at two referral dermatology centers in Iran. The pilot phase of the registry was used to identify possible obstacles in the application and execution of systematic registration. Results: A total of 281 patients were registered with the mean age of 42.02 years. The disease duration was 12.06 ± 10.90 years with the variety of clinical presentations. There was no significant difference between males and females in the age of disease onset (p = 0.53). Notably, 167 patients had children. Among them, 13 had children with psoriasis. The gender of the affected parent did not affect the possibility of psoriasis transmission to the child, and no significant difference was seen between the two sexes (P = 0.569). Regarding treatment, 99.4% of patients (n = 280) had used topical agents, 52.3% (n = 147) biologics, and 60.9% (n = 171) nonbiologic medications. Conclusion: Clinical trials report the efficacy and safety data regarding limited study populations in a restricted time window, and the results may differ from the general population. This highlights the importance of registry‐based studies for collecting and analyzing longitudinal information. In terms of long‐term disease complications such as malignancies, cardiovascular events, and serious adverse events, registry‐based studies will help clinicians better recognize and manage each disease. [ABSTRACT FROM AUTHOR]

This document is a summary of a special issue on privacy-preserving techniques in cloud/fog and Internet of Things (IoT) networks. The issue explores various methods and strategies for protecting privacy in these networks, including cryptographic algorithms, federated learning models, and password-less authentication. The authors also discuss the challenges of securing IoT devices with limited computational power and the importance of safeguarding data in large networks. The special issue includes 10 selected papers out of a total of 21 submissions, covering topics such as true random number generation, shared key generation, watermarking, dependability assessment, authentication schemes, federated learning, batch processing, stylometry, and searchable encryption. The authors express their gratitude to the contributors for their valuable research in this field. [Extracted from the article]

Tinea capitis is a common dermatophyte infection of the scalp in children. It is an uncommon infection in adults and usually affects postmenopausal women and immunocompromised patients. We report an immunocompetent elderly female with inflammatory tinea capitis caused by Trichophyton violaceum and review the literature for the past 5 years to describe the disease, its epidemiologic characteristics, dermatophyte species involved and treatment options used. The total number of cases was 11, including 8 women and 3 men, with an average age of 48.36. The most commonly isolated dermatophyte was Trichophyton tonsurans, and most cases were treated successfully with oral terbinafine with no side effects. In our case, the diagnosis was established by direct examination, culture and histological examination. Remedy with itraconazole and prednisolone was very successful. Early diagnosis of tinea capitis in adults is necessary to provide early treatment and minimize sequelae of the disease. [ABSTRACT FROM AUTHOR]

Background: Acne vulgaris is a common skin disease that is more common in young population and it can be associated with some sequels after resolving the lesions. Post‐inflammatory erythema is one of these complications that can be disturbing for patients and does not have any definite treatment. This study was aimed to evaluate the efficacy and safety of tranexamic acid (TA) as mesotherapy in treatment of post‐acne erythema (PAE) treatment. Method: This clinical trial study was performed in the dermatology clinic on 17 patients with persistent PAE (3 months after acne recovery). Two sessions of treatment were performed by a physician with 2‐week intervals; TA was injected as mesotherapy into the right side of each patient's face as the case group, while the opposite side was used as the control group. A Visioface device was used to compare before and after treatment photographs of each side of the face in color mode with quantitative measures such as lesions count, area, and area percent. Results: Finally, 15 patients completed treatment sessions. There were statistically significant differences in right side lesions before and after treatment with p‐values of 0.047, 0.002, and 0.035 for count, area, and area percent, respectively. There was no significant difference before and after treatment in terms of count, area. and area‐percent on the left side. Conclusion: According to the results of this study, TA injection as mesotherapy for resolving PAE can be effective. However, due to small sample size, further studies are needed. [ABSTRACT FROM AUTHOR]

Centralized training of deep learning models poses privacy risks that hinder their deployment. Federated learning (FL) has emerged as a solution to address these risks, allowing multiple clients to train deep learning models collaborativelywithout sharing rawdata. However, FL is vulnerable to the impact of heterogeneous distributed data, which weakens convergence stability and suboptimal performance of the trained model on local data. This is due to the discarding of the old local model at each round of training, which results in the loss of personalized information in the model critical for maintaining model accuracy and ensuring robustness. In this paper, we propose FedTC, a personalized federated learning method with two classifiers that can retain personalized information in the local model and improve the model's performance on local data. FedTC divides the model into two parts, namely, the extractor and the classifier, where the classifier is the last layer of the model, and the extractor consists of other layers. The classifier in the local model is always retained to ensure that the personalized information is not lost. After receiving the global model, the local extractor is overwritten by the globalmodel's extractor, and the classifier of the globalmodel serves as an additional classifier of the localmodel to guide local training. The FedTCintroduces a two-classifier training strategy to coordinate the two classifiers for local model updates. Experimental results on Cifar10 and Cifar100 datasets demonstrate that FedTC performs better on heterogeneous data than current studies, such as FedAvg, FedPer, and local training, achieving a maximum improvement of 27.95% in model classification test accuracy compared to FedAvg. [ABSTRACT FROM AUTHOR]

Deep Learning (DL) is a subfield of machine learning that significantly impacts extracting new knowledge. By using DL, the extraction of advanced data representations and knowledge can be made possible. Highly effective DL techniques help to find more hidden knowledge. Deep learning has a promising future due to its great performance and accuracy. We need to understand the fundamentals and the state‐of‐the‐art of DL to leverage it effectively. A survey on DL ways, advantages, drawbacks, architectures, and methods to have a straightforward and clear understanding of it from different views is explained in the paper. Moreover, the existing related methods are compared with each other, and the application of DL is described in some applications, such as medical image analysis, handwriting recognition, and so on. [ABSTRACT FROM AUTHOR]

Owing to increased energy demand, renewable energy sources have recently reached greater heights in the power industry. In this regard, integrating renewable energy with the power grid system has become essential in meeting consumer's energy demands. The novelty in this article is the design of an advanced Aalborg inverter with a reduced number of switches which results in enhanced system performance by reducing the switching losses. Integrating renewable energy sources with the power grid network has gained massive importance in supplying electric power to consumers. Integrating the power grid with renewable energy has become possible with the implementation of grid tie inverters. The only drawback in implementing renewable energy sources with the power grid is that the output of the resources varies from time to time in nature. Voltage Source Inverter‐based grid system requires two or three‐stage inverters for interfacing power units to transfer DC energy into the power grid network. To reduce the switching frequency across the system, many new excellent inverters have been designed to ensure the healthy operation of the system operating at a higher frequency. This article has been coined with the investigation of a novel buck and boosts converter‐based inverter operation named Aalborg inverter. The inverter operates at a higher frequency and minimum voltage drop across the inductor, where only one power stage has been implied to enhance the system's reliability and efficiency. This novel Aalborg inverter is applied and investigated for photovoltaic application. [ABSTRACT FROM AUTHOR]

In the era of digital marketing, advertisements have become an indispensable part. One of the central challenges is advertising attribution which explains the amount of contribution every publisher has with the conversions. However, through observation, we have found that current advertising platforms attribution, advertisers attribution, or third‐party platforms attribution all have the problems of trust, data leakage, and data forgery. To fill the gap, our work's main contribution is combining blockchain with advertising attribution to propose an architecture for improving the privacy‐preserving degree and amount. In the proposed architecture, publishers, and advertisers can store real‐time data on a blockchain. The attribution results are credible because blockchain is decentralized, tamper‐proof, and traceable. We combine privacy set intersection and zero‐knowledge proof technology to increase the privacy of flowing data. In addition, we describe a preliminary prototype in which publishers, advertisers, and advertising platforms can get the corresponding attribution details. To show its effectiveness, we analyze it from different perspectives, including communication cost, attribution accuracy, and time cost. The results show that our communication cost has significantly reduced compared to the recent studies. [ABSTRACT FROM AUTHOR]

Key Clinical Message: Systemic lupus erythematosus (SLE) is a systemic autoimmune disease that affects several organs including the skin. Clinical cutaneous symptoms of SLE come in a broad range, consisting of both non‐specific and specific cutaneous lesions. Except for cases of amicrobial pustulosis of the folds, generalized pustular psoriasis, acneiform eruptions, pustular vasculitis, Wells' syndrome, subcorneal pustular dermatosis, and neutrophilic dermatosis, there are no reports of pustular lesions linked to SLE. The unusual cutaneous features of our patient were annular plaques with pustules and crusts on the margins. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) has been considered in various fields in the last decade. With the increasing number of IoT devices in the community, secure, accessible, and reliable infrastructure for processing and storing computed data has become necessary. Since traditional security protocols are unsuitable for IoT devices, IoT implementation is fraught with privacy and security challenges. Thus, blockchain technology has become an effective solution to the problems of IoT security. Blockchain is an empirical data distribution and storage model involving point-to-point transmission, consensus mechanism, asymmetric encryption, smart contract, and other computer technologies. Security and privacy are becoming increasingly important in using the IoT. Therefore, this study provides a comprehensive framework for classifying security criteria based on blockchain technology. Another goal of the present study is to identify causal relationship factors for the security issue using the Fuzzy Decision-Making Trial-and-Evaluation Laboratory (FDEMATEL) approach. In order to deal with uncertainty in human judgment, fuzzy logic is considered an effective tool. The present study's results show the proposed approach's efficiency. Authentication (CR6), intrusion detection (CR4), and availability (CR5) were also introduced as the most effective and essential criteria, respectively. [ABSTRACT FROM AUTHOR]

Network‐on‐Chip (NoC) is a key component in chip multiprocessors (CMPs) as it supports communication between many cores. NoC is a network‐based communication subsystem on an integrated circuit, most typically between modules in a system on a chip (SoC). Designing a reliable NoC against failures that can prevent failure using some measures or preventing error or system failure while failure happens and proper performance became a significant concern. For a reliable design against failures, first, the system should be analysed to discover the critical points. Hence, in this research, it is tried first to investigate the scale of fault tolerance effect on the mechanism in the router on the network by injecting simulated errors, and then these errors are prevented. As the major novelty, the authors implemented a router on a synchronised network and calculated the network buffering fault tolerance by injecting error in the buffer. Specifically, a new method for improving fault tolerance is proposed, which uses the existing resources efficiently. So, it does not impose any overhead on hardware and improves the error tolerance scale. The authors also evaluate it from different perspectives to show its superior performance. [ABSTRACT FROM AUTHOR]

Today, Internet of things (IoT), Cloud and Fog networks have spread out around the world. The more these networks grow, the more their energy consumption comes to attention. Many efforts have been made during recent years to decrease this energy consumption, mainly focused on utilizing low‐power devices. Green algorithms are recently proposed to reduce energy consumption by modifying the structure of many algorithms employed in the network and its protocols. This paper proposes a new green reliability algorithm for Transmission Control Protocol/Internet Protocol (TCP/IP protocol) in Fog computing. The proposed algorithm does not require extensive TCP/IP protocol changes or relevant hardware. It is based on transferring less number of packets in the network by using the advantage of differences between TCP and User Datagram Protocol (UDP). TCP and User Datagram Protocol (UDP) are different in nature as the number of total packets in UDP is half that of TCP. As a result, the number of complete packets in UDP is half that of TCP. The proposed method is built around the loss of some packets in applications, such as voice and online video, does not severely degrade the end results. Therefore, the UDP protocol can substitute TCP in such situations. The criterion to switch between the two is the minimum acceptable Quality of Service (QoS) of the overall network. In other words, the UDP protocol will be used as long as QoS requirements are met. The switching process between UDP and TCP is dynamic, optimized by estimating network noise in the period. Additionally, we evaluated the proposed method based on several QoS functions, including delay, throughput, and energy usage. [ABSTRACT FROM AUTHOR]

Evidence suggests that bullous pemphigoid (BP) is associated with multiple neurological disorders. We aimed to compare brain magnetic resonance (MRI) findings between BP patients and a control group. This case–control study included patients with BP referred to two dermatology clinics during a two‐year period. A group of individuals attending the same clinics for cosmetic procedures were selected as controls. First, participants' general information including age, gender, education, weight and underlying disease was recorded. For BP patients, the drugs and the BP Disease Area Index (BPDAI) were recorded as well. Then, all participants underwent brain MRI without contrast. The Fazekas scale, the general cerebral atrophy (GCA) score, and the Medial Temporal lobe Atrophy (MTA) score were used to assess MRI images. Overall, 24 BP patients and 24 controls were evaluated in this study. Both groups were comparable regarding age, gender and education. However, diabetes and hypertension were more frequent in the control group. The mean BPDAI total score was 51.39 ± 68.92 in BP patients and most of them used rituximab (41.7%). None of the participants had MS or Alzheimer MRI patterns. There was no difference between groups in terms of GCA and MTA scores. Furthermore, the frequency of partially empty sella did not differ significantly between BP patients and controls (p = 0.461); nevertheless, grade‐3 Fazekas was significantly higher in BP patients compared to controls (25% vs. 0%, p = 0.019). Of note, one BP patient had an epidermoid cyst and another had moderate enlargement of three ventricles. Also, new infarcts were observed in two and old infarcts in four BP patients. Although the majority of abnormal brain MRI findings were more frequent in BP patients compared to controls, only grade‐3 Fazekas was significantly higher and acute infarcts were exclusively observed in BP patients. [ABSTRACT FROM AUTHOR]

Nowadays, the unmanned aerial vehicle (UAV) has a wide application in transportation. For instance, by leveraging it, we are able to perform accurate and real-time vehicle speed detection in an IoT-based smart city. Although numerous vehicle speed estimation methods exist, most of them lack real-time detection in different situations and scenarios. To fill the gap, this paper introduces a novel low-altitude vehicle speed detector system using UAVs for remote sensing applications of smart cities, forging to increase traffic safety and security. To this aim, (1) we have found the best possible Raspberry PI's field of view (FOV) camera in indoor and outdoor scenarios by changing its height and degree. Then, (2) Mobile Net-SSD deep learning model parameters have been embedded in the PI4B processor of a physical car at different speeds. Finally, we implemented it in a real environment at the JXUST university intersection by changing the height (0.7 to 3 m) and the camera angle on the UAV. Specifically, this paper proposed an intelligent speed control system without the presence of real police that has been implemented on the edge node with the configuration of a PI4B and an Intel Neural Computing 2, along with the PI camera, which is armed with a Mobile Net-SSD deep learning model for the smart detection of vehicles and their speeds. The main purpose of this article is to propose the use of drones as a tool to detect the speeds of vehicles, especially in areas where it is not easy to access or install a fixed camera, in the context of future smart city traffic management and control. The experimental results have proven the superior performance of the proposed low-altitude UAV system rather than current studies for detecting and estimating the vehicles' speeds in highly dynamic situations and different speeds. As the results showed, our solution is highly effective on crowded roads, such as junctions near schools, hospitals, and with unsteady vehicles from the speed level point of view. [ABSTRACT FROM AUTHOR]