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Power transformers being among the power system key components, are very important to protect. Various approaches have so far been proposed for this topic. Artificial intelligence (AI) has provided a concrete basis for numerous power transformer differential protection methodologies. However, the capabilities of AI-based methods have never been put into comparison. This paper provides a comparative analysis of various AI-based approaches for differential protection of power transformers. The performances of AI-based differential protection schemes are investigated in the presence of current transformer (CT) saturation condition, series capacitors compensation, and superconductor fault current limiter (SFCL), which possibly deteriorate the capability of differential protections to correctly tell inrush currents and internal faults apart. The PSCAD/EMTDC simulation tool is applied in producing the necessary test dataset for performance evaluation of the suggested novel strategy. The attained outcomes from the assessment of various methods have been analyzed to introduce the most superior AI-based differential protection scheme.

Background The management of melasma is still challenging, and new treatment modalities with favorable side effect profile are required. Methimazole, a peroxidase inhibitor, seems to have a beneficial effect in the management of melasma but there is a paucity of studies for evaluation of its efficacy. This double-blinded trial was aimed to evaluate the efficacy and safety of methimazole vs hydroquinone 4% which is the gold standard treatment in the management of melasma. Methods Fifty patients with melasma were enrolled and randomly divided into two groups to receive 4% hydroquinone or 5% methimazole once daily for 8 weeks. Forty patients completed the study. The clinical response was assessed at 4th, 8th, and 12th weeks after treatment by MASI score, patient satisfaction, and physician scores. Results Both groups showed a reduction in the MASI score at the 8th week which was more significant in hydroquinone group but higher relapse rate was also observed in this group after discontinuing the drug. The side effects were similar between groups. Also, patient and physician satisfaction scores were also more in favor of hydroquinone 4%. Conclusion Methimazole could be an alternative treatment of melasma alone or in combination with other depigmenting drugs. Although not as effective as hydroquinone, the noncytotoxic and nonmutagenic aspects of methimazole may make it a promising alternative for the treatment of melasma.

Nowadays, wireless mesh networks are known as important parts of different commercial, scientific, and industrial processes. Their prevalence increases day-by-day and the future of the world is associated with such technologies for better communication. However, the issue of improving quality of service for dealing with more complex and intense flow of data has been always a remarkable research problem, as a result of improved wireless communication systems. In this sense, objective of this study is to provide a new algorithm for contributing to the associated literature. In the study, peer to peer wireless mesh networks and the concept of service quality were examined first and then an approach for improving service quality in such networks has been proposed accordingly. In detail, the proposed an approach allows profiting data transfer capability by data packet and using this information for routing and preventing overcrowd in network nodes and finally, distributing the load over it. When middle nodes overcrowd, they withhold to send control messages of route creating or do that by delay. The proposed approach has been evaluated and the findings revealed that at least 10% of undue delays through network can be prevented while permittivity does not reduce, thanks to the approach. Also energy consumption within network nodes partially increases due to adding table and the search which can be overlooked.

Background: The World Wide Web houses an abundance of information that is used every day by billions of users across the world to find relevant data. Website owners employ webmasters to ensure their pages are ranked top in search engine result pages. However, understanding how the search engine ranks a website, which comprises numerous web pages, as the top ten or twenty websites is a major challenge. Although systems have been developed to understand the ranking process, a specialized tool based approach has not been tried. Objective: This paper develops a new framework and system that process website contents to determine search engine optimization factors. Methods: To analyze the web page dynamically by assessing the web site content based on specific keywords, elimination method was used in an attempt to reveal various search engine optimization techniques. Conclusion: Our results lead to conclude that the developed system is able to perform a deeper analysis and find factors which play a role in bringing the site on the top of the list.

Stakeholder satisfaction is the main motive of the software industry. Consumer and producer satisfaction means achieving a software-quality product. There are so many techniques, methods, and models are present for the software-quality prediction. Computational intelligence is also playing a crucial role in the prediction of quality characteristics. This paper gives a new optimal mathematical model for the prediction of the degree of stakeholder satisfaction (Q). Optimal models validate the real data using the relationship impacts of various quality attributes. It uses the equations of constraints. The optimal model gives the maximum and minimum values for Q. Constraints constitutes of software quality characteristics. In the given case study example, the idle value of Q is 30 but using optimal model it gives the maximum optimal value of Q = 22.788020075 for xLAB IT consulting services on their project In-Reg Molecule Registration using the MATLAB. It means if there is any change in the value of any software quality characteristics, then it will decrease the value of Q. It proves that the given result is an optimal solution.

Limitations of the pinhole method and astigmatic defocus detection have difficulties in determining the direction of defocus and a restricted linear correction range. Here, a distance-measuring approach based on the laser triangulation principle is proposed with a corresponding mathematical model to overcome these problems and to satisfy the requirements of an industrial thin-film transistor liquid-crystal display (TFT-LCD) inspection microscope system in active auto-focus applications. The approach combines infrared light at a wavelength of 808 nm with visible light. The light reflected from the surface of the object reaches a CCD camera and forms a spot via a set of optical devices. To control a PZT to achieve real-time auto-focusing, a Gaussian curve fitting method is used to process the spot information with the presented mathematical model giving the relationship between the detection value and the defocus value focus error signal (FES). The preliminary experiments with a $50\times $ objective lens show that the measured values are consistent with the theoretical values, have good linearity and possess a focusing accuracy of 0.2 $\mu \text{m}$ within $\pm 30~\mu \text{m}$ of the focal plane. The analysis of the experimental results proves the feasibility of using this method in industrial applications. Compared with the traditional method of microscope focus correction, this method has the advantages of high accuracy, good linearity, and fast focus speed for the actual requirements of industrial inspection processes. This method has been applied to the circuit board component defect detection in our laboratory.

Recently, IoT has greatly influenced our daily lives through various applications. One of the most promising application is smart city that leverages IoT devices to manage cities without any human intervention. The high possibility of sensing and publishing sensitive data in this smart environment leads to three significant issues: (1) privacy-preserving (2) heterogeneity, and (3) real-time services. We observe that current studies are in lack of addressing these challenges. In this paper, we propose a new privacy-preserving architecture for IoT devices in the smart city by leveraging ontology, a data model, at the edge of the network. At first, we propose an ontology that consists of privacy information of devices. Then, we mount a real-time privacy-preserving method on top of it that is achieved by providing a dynamic environment from the privacy-preserving point of view. Based on the simulation results using Protege and Visual Studio on a synthetic dataset, we find that our solution provides privacy at real-time while addressing heterogeneity issue so that many IoT devices can afford it. Thus, our proposed solution can be widely used for smart cities.

The main purpose of this paper is the allocation of orders to suppliers in an agile and flexible manner suitable to the automobile industry. In this paper, parts supplied by a single source were eliminated from the set of parts. Using mathematical modeling and through the interval-valued fuzzy-rough numbers best worst method (IVFRN-BWM), we try to achieve the results that can meet the proposed model's needs and provide the ideal results by introducing new modes. This paper addressed some new aspects of the subject and achieved robust results by considering five objective functions. These five functions are as follows: minimization of production line disruptions due to the performance of suppliers, minimization of the complaints of production line about supplied parts, minimization of defective parts received from suppliers (PPM), maximization of on-time delivery services, and minimization of overall costs of supplied parts. Reviewing the literature, the originality of this study are as follows: 1) identifying the structure of a supply chain (SC) in general and particularly in an automobile industry SC; 2) investigating the modeling techniques of the existing SC models for coordinating all the members of a product SC; 3) building a hybrid model of IVFRN-BWM and a robust goal programming agile and flexible supply chain in an uncertain situation; and 4) identifying the suitable scenarios/cases for testing the proposed models to validate the models. This paper can help decision makers and managers to opt for the best suppliers and also allocate the right numbers of parts to those supplier(s) based on a real situation of each firm.

Arising from solar storms, the emerging disturbances imposed on Earth’s magnetic field, can drive the flow of quasi-DC geomagnetically induced currents (GICs) in power transmission systems. The ground connections of power transformers provide a closed path through which GICs flow and push their cores into half-cycle saturation. In addition, series capacitor units are often utilized to compensate HV transmission systems. The half-cycle saturation of power transformers due to GICs, on the one hand, and the proximity of such saturated transformers to capacitor compensation units on the other can lead to the inception of ferroresonance in series compensated power systems. To prevent catastrophic equipment failures due to ferroresonance during GICs, it is crucial to determine ferroresonance solutions of networks. This paper’s principal contribution is to develop an approach to analyze ferroresonance in series capacitor compensated networks during GICs. This is attained by employing a simplified equivalent single-phase model on which to mount the analysis. The authenticity of this method is verified through an EMTP-RV simulation of a benchmark example power system.

In this paper, Deep Neural Networks (DNN) with Bat Algorithms (BA) offer a dynamic form of traffic control in Vehicular Adhoc Networks (VANETs). The former is used to route vehicles across highly congested paths to enhance efficiency, with a lower average latency. The latter is combined with the Internet of Things (IoT) and it moves across the VANETs to analyze the traffic congestion status between the network nodes. The experimental analysis tests the effectiveness of DNN-IoT-BA in various machine or deep learning algorithms in VANETs. DNN-IoT-BA is validated through various network metrics, like packet delivery ratio, latency and packet error rate. The simulation results show that the proposed method provides lower energy consumption and latency than conventional methods to support real-time traffic conditions.

BACKGROUND Facial papules (FPs) are considered to be created by the inflammatory process, which involves facial vellus hairs, in frontal fibrosing alopecia. AIM To demonstrate the histopathological features of FPs and the composition of the inflammatory infiltrate. METHODS In total, 18 patients with FPs were enrolled in the study after histopathological confirmation of lichen planopilaris. Histopathological evaluation of the specimens was performed by two dermatopathologists. The samples were immunostained with CD4, CD8 and CD123 monoclonal antibodies, and the percentage and proportion of cells stained with these markers were investigated. RESULTS A follicular lichenoid reaction and perifollicular fibrosis were present in all cases. Vellus hairs were detected in 83.3% of biopsy specimens (15 cases), all of which were involved by the inflammation. The majority of the follicles (72%) revealed follicular plugs. Reduction and destruction of elastic fibres were visible in the perifollicular (adventitial) and the papillary dermis (100% and 78% of specimens, respectively). Prominent sebaceous glands and dilated ducts were detected in 78% and 72% of samples, respectively. CD4-positive T cells formed 67.72% and CD8-positive T cells 32.28% of the infiltrate, and the mean CD4/CD8 ratio was 2.48. In 13 (72.2%) biopsy specimens

Although Necrotizing fasciitis can evolve from a trivial lesion, whenever it develops it requires a prompt surgical intervention and broad‐spectrum antibiotic therapy.

The technological revolution during the past decades has resulted in the explosion of data leading to an emergence of cloud computing that subsequently led to fog computing. These technologies are continuously striving for increased computational capability so as to inculcate it in our daily lives and obtain ever larger infrastructures. However, inclusion of heterogeneous infrastructures in such systems poses different challenges like complexity, security, and manageability. For the same, it necessitates an autonomic, self-managing system to address the growing complexities in its realization in terms of cost and complexity. These challenges have opened avenues for Autonomic computing, an approach that aims to provide significant benefits in terms of speed and automation by managing complex and heterogeneous infrastructure. Additionally, autonomic computing overcomes the limitations of manual control by providing an economical and robust solution in minimum time. As a result, autonomic computing has observed its widespread application since its inception. The proposed chapter focuses on the various aspects of autonomic computing like self-healing, self-optimization, self-protection, and so on, and presents a simplistic architecture. The proposed architecture implements autonomic computing infrastructure to dynamically control and manage services to develop and deploy an intelligent application. Hence, the proposed framework achieves the autonomic services to maintain the autonomic requirements of a wide range of network applications and services.

Quantum-enhanced machine learning plays a vital role in healthcare because of its robust application concerning current research scenarios, the growth of novel medical trials, patient information and record management, procurement of chronic disease detection, and many more. Due to this reason, the healthcare industry is applying quantum computing to sustain patient-oriented attention to healthcare patrons. The present work summarized the recent research progress in quantum-enhanced machine learning and its significance in heart failure detection on a dataset of 14 attributes. In this paper, the number of qubits in terms of the features of heart failure data is normalized by using min-max, PCA, and standard scalar, and further, has been optimized using the pipelining technique. The current work verifies that quantum-enhanced machine learning algorithms such as quantum random forest (QRF), quantum K nearest neighbour (QKNN), quantum decision tree (QDT), and quantum Gaussian Naïve Bayes (QGNB) are better than traditional machine learning algorithms in heart failure detection. The best accuracy rate is (0.89), which the quantum random forest classifier attained. In addition to this, the quantum random forest classifier also incurred the best results in F 1 score, recall and, precision by (0.88), (0.93), and (0.89), respectively. The computation time taken by traditional and quantum-enhanced machine learning algorithms has also been compared where the quantum random forest has the least execution time by 150 microseconds. Hence, the work provides a way to quantify the differences between standard and quantum-enhanced machine learning algorithms to select the optimal method for detecting heart failure.

IoT devices generate data over time, which is going to be shared with other parties to provide high-level services. Smart City is one of its applications which aims to manage cities automatically. Because of the large number of devices, three critical challenges come up: heterogeneity, privacy-preserving of generated data, and providing high-level services. The existing solutions cannot even solve two of the mentioned challenges simultaneously. In this paper, we propose a three-module framework, named “Ontology-Based Privacy-Preserving” (OBPP) to address these issues. The first module includes an ontology, a data storage model, to address the heterogeneity issue while keeping the privacy information of IoT devices. The second one contains semantic reasoning rules to find abnormal patterns while addressing the quality of provided services. The third module provides a privacy rules manager to address the privacy-preserving challenges of IoT devices achieved by dynamically changing privacy behaviors of the devices. Extensive simulations on a synthetic smart city dataset demonstrate the superior performance of our approach compared to the existing solutions while providing affordability and robustness against information leakages. Thus, it can be widely applied to smart cities.

To improve the interpretability or perception of information in images for human viewers is the main goal of image enhancement. Aiming at the problem that image edges are difficult to determine due to artefacts, plaques, and vascular branches in cardiovascular ultrasound, an edge ultrasound imaging detection algorithm based on spatial-frequency-domain image enhancement is proposed to improve the clarity of ultrasound images. Firstly, this paper uses the space-frequency-domain enhancement algorithm to enhance the image. This algorithm overcomes the problem of low contrast of conventional algorithms. The enhanced data matrix is used as the cost matrix, and then, the heuristic image search method is used to search the image of the cost matrix. The results show that the use of spatial-frequency-domain image ultrasound imaging algorithm can improve the contrast and sharpness of ultrasound images of cardiovascular disease, which can make the middle edge of the image clearer, the detection accuracy rate is increased to 92.76%, and the ultrasound of cardiovascular disease is improved. The edge of the image gets accuracy. The paper confirms that the ultrasound imaging algorithm based on spatial-frequency-domain image enhancement is worthy of application in clinical ultrasound image processing. The performance of the proposed technique is 32.54%, 75.30%, 21.19%, 21.26%, and 11.10% better than the existing technique in terms of edge energy, detail energy, sharpness, contrast, and information entropy, respectively.

In this study, the joint effects of developmental stage and soil water availability on biomass accumulation, harvest index, as well as essential oil content, yield and composition were investigated in Thymus armeniacus. For comparison purposes, Thymus kotschyanus was also considered. Plants were irrigated to either 75 or 50% of field capacity, and were sampled at 50 or 100% blooming. In both species, water deficit exerted limited effect on the time required to initiate or complete flowering. In most critical aspects of yield (harvestable organs dry weight, essential oil yield), T. armeniacus was found to be superior than T. kotschyanus. In these traits, however, T. armeniacus underwent a more drastic water deficit-induced decrease. Across treatments, metabolite levels fairly correlated to transcript accumulation profiles of terpene synthases and cytochrome P450 genes. Indices affiliated with reactive oxygen species were inter-correlated with the activity of five major antioxidant enzymes, while the same was noted between leaf water status and pigment content. Taken together, these results indicate that when water availability can be achieved, higher yields will be obtained by cultivation of T. armeniacus. Under water deficit conditions, instead, the more drought tolerant T. kotschyanus stands out as the primary choice.

Tracking moving objects has been an issue in recent years of computer vision and image processing and human tracking makes it a more significant challenge. This category has various aspects and wide applications, such as autonomous deriving, human-robot interactions, and human movement analysis. One of the issues that have always made tracking algorithms difficult is their interaction with goal recognition methods, the mutable appearance of variable aims, and simultaneous tracking of multiple goals. In this paper, a method with high efficiency and higher accuracy was compared to the previous methods for tracking just objects using imaging with the fixed camera is introduced. The proposed algorithm operates in four steps in such a way as to identify a fixed background and remove noise from that. This background is used to subtract from movable objects. After that, while the image is being filtered, the shadows and noises of the filmed image are removed, and finally, using the bubble routing method, the mobile object will be separated and tracked. Experimental results indicated that the proposed model for detecting and tracking mobile objects works well and can improve the motion and trajectory estimation of objects in terms of speed and accuracy to a desirable level up to in terms of accuracy compared with previous methods.

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The Micro-Electro-Mechanical Systems (MEMS) and Wireless Sensor Networks (WSNs) developments have had a crucial effect on our daily lives. The usage of wireless sensor networks is increasing daily. They can be used in various fields such as incident management, war detection and exploration, border protection and, security monitoring. Also, they are used in unattended environments as a remote. The sensors in WSNs are fully automatic. One of the efficient ways to manage WSN effectively is clustering because it can support the scalability of nodes. One of the main challenges in Wireless Sensor Network is not only its implementation but also finding the best clustering algorithm. Besides, wireless sensor networks' features should be considered in their design as the primary keys. In this paper, we present some of the most well-known available clustering algorithms and compare them based on the features and complexity of the network. These features include the rate of node convergence, the stability, the overlapping of each cluster, supporting node movement.

In-hospital transmission is one of the main routes of the 2019 novel coronavirus (SARS-CoV-2) spreading among health care workers (HCWs) who are the frontline fighters. However, coming into contact with COVID-19-positive patients is unavoidable. Therefore, hand hygiene is of utmost importance for the prevention of COVID-19 among HCWs. This purpose can be achieved by applying alcohol-based hand rubs, washing hands properly with soap and water, and applying other antiseptic agents. Nevertheless, regular hand hygiene could also be challenging, because water, detergents, and disinfectants may predispose HCWs to hand dermatitis. The current article reviews the risk factors for the development of hand dermatitis, with further focus on the most common agents used among HCWs. In addition, the risk of occupational hand dermatitis for each agent is evaluated to increase awareness of this common condition. Finally, some recommendations are discussed to reduce the effect of hand dermatitis on HCWs.

In this work, magnetic zirconium oxide (ZrO2/Fe3O4) nanocomposites were synthesized in different mass ratio as (1:1), (3:2), (5:2) and (7:2) and fairly characterized by various techniques like; X-ray diffraction, X-ray energy dispersion analysis, scanning electron microscope, transmission electron microscopy, Fourier transform infrared spectroscopy, and vibrating sample magnetometer. Characterization results showed the prepared nanocomposite had stable core/shell structure in nanometer scale, 12 nm, with magnetically property that nominate it for catalytic application in chemical reactions. The prepared nanocomposites were evaluated in the reduction reaction of methylene blue and in the presence of NaBH4 as a catalyst. Observed results revealed that the ZrO2/Fe3O4 nanocomposites in mass ratio as 5:2 exhibited remarkable catalytic activity with excellent reusability. Obtained results are presented and discussed here.

Pyodermatitis-pyostomatitis vegetans is a rare inflammatory dermatosis. There is a strong association between pyodermatitis-pyostomatitis vegetans and inflammatory bowel disease, particularly ulcerative colitis. Herein, we report a case of pyodermatitis-pyostomatitis vegetans with positive direct immunofluorescence staining findings and review the literature for the past 18 years to characterize the disease, its epidemiologic characteristics, its associations, and the pathology and direct and indirect immunofluorescence findings. The total number of cases was 38, including 22 men and 16 women, with an average age of forty. Direct immunofluorescence staining had been performed for 32 patients, of which 12 had positive findings. Of those with positive direct immunofluorescence, 6 patients showed IgA cell surface staining. A recent approach suggests that these immunological findings may not be accidental and indicates a possible overlap with autoimmune bullous diseases discussed in this review.

Protecting healthcare workers (HCWs) is crucial during Corona Virus Disease 2019 pandemic and requires wearing personal protective equipment (PPE) [1]. While most of the studies have focused on the skin reactions caused by gloves, other PPE such as gowns, respirator masks, face shields and goggles are also worn by HCWs for long hours during the current epidemic and skin irritations caused by these equipment may cause discouragement of health workers from using them [2]. In this letter we have focused on the reaction caused by non‐glove PPE.

BACKGROUND Microneedling and fractional lasers have been used in facial rejuvenation with acceptable results and low adverse effects. AIMS To compare the efficacy of microneedling with fractional Er:YAG in facial skin rejuvenation. PATIENTS/METHODS This study was planned as a split-face clinical trial. Volunteers were randomly allocated to receive three monthly treatments on each side of the face, one with fractional Er:YAG laser and one with microneedling. The assessments included investigating clinical outcomes by two blinded dermatologists accompanied by measuring skin biophysical characteristics including cutaneous resonance running time (CRRT) and transepidermal water loss (TEWL). Moreover, possible adverse effects, downtime, and patients' satisfaction were recorded at baseline, 1 month after each treatment, and 3 months after the last treatment session. The protocol was approved by the Iranian Registry of Clinical Trials (IRCT20160820029436N3). RESULTS Of the 32 selected volunteers, 24 subjects completed the study. The clinical assessment showed a significant improvement of the face appearance along with a significant reduction in dyschromia, and periorbital wrinkling (P-value

Neutrophil or platelet to lymphocyte ratio (NLR and PLR) has been proposed to be used as prognostic purposes in a variety of diseases. The aim of this study was to evaluate the usefulness of these ratios in monitoring of response to TNF-α-inhibitors in psoriatic patients. Eighty psoriatic patients were included and treated with TNF-α-inhibitors for 12 months based on drug protocol. Hematologic indices, including NLR and PLR values were assessed before and after treatment. Data on psoriasis area and severity index (PASI), smoking behavior, alcohol intake habit, nail abnormality, body mass index (BMI), joint involvement, and disease duration were also recorded. PASI scores were improved significantly after one-year treatment (P = .000). Furthermore, this type of treatment significantly reduced the NLR and PLR (P = .000). These changes were in accordance with PASI scores. Patients with BMI greater than 24.9 had higher, but non-significant NLR and PLR than normal or lean individuals. Cigarette smokers and alcohol consumers had lower NLR and PLR values than other individuals (P < .05). There was no significant association between NLR and PLR and joint or nail involvement. Although NLR and PLR will not be helpful in primary diagnosis of inflammatory diseases, they could be accounted as monitoring tools in management of psoriasis or globally indicators of inflammation.

Purpose Lichen planopilaris (LPP) is a chronic lymphocytic- mediated disorder that selectively involves hair follicles, leading to cicatricial alopecia. The eyelash follicle and meibomian gland (MG) might also be involved in the disease process leading to ocular surface problems. Methods In this Cross-sectional case -control study, twenty-three patients with histologically confirmed LPP and 23 healthy controls were recruited in this controlled study. To quantify the signs and symptoms of LPP, we used the Lichen Planopilaris Activity Index. The ophthalmologic examination was performed by the same ophthalmologist at Farabi Eye Hospital. Results Patients with LPP had a statistically significant lower tear breakup time (worse test outcome) compared with the control (7.1 6 4.1 vs. 9.6 6 4.4; respectively, P = 0.011). Both MG quality score and expressibility were higher in patients with LPP than in control subjects (14.1 6 4.3 vs. 9.3 6 4.4; P = 0.001; 1.5 6 1.0 vs. 0.4 6 0.8; P = 0.001; respectively). The Schirmer test score was not different between groups. A significant but weak correlation was found between the Lichen Planopilaris Activity Index and tear breakup time. Other ophthalmologic examinations including conjunctiva, lid margin shape, intraocular pressure, and funduscopy were normal in patients with LPP. Conclusions Patients with LPP, scored worse in ocular surface tests. This finding warrants special scrutiny for dry eye and MG dysfunction in these patients.

This paper presents a system that can recognize handwritten words expressed using broken letters of the Persian alphabet. The proposed system can be used for most activities related to the gathering of public information. Statistical features of the separated/broken letters are employed in the system. Each letter is recognized using interconnected fuzzy neural network. The advantages of this method include high precision owing to the strength of the neural network algorithm and the possibility of extending dataset instance codes in a simple manner. At last, an evaluation for the proposed method is provided experimentally.

The hydrolysis of a new type of diazonium salt immobilized on the surface of silica sulfuric acid was studied in this work. By using diazonium salt nanocomposites, a number of phenol derivatives were synthesized in good yields. In contrast to the previous works, the present procedure was conveniently carried out under mild and solvent-free conditions. The effects of solvent and temperature were studied on the dediazoniation products. The notable advantages of this methodology were operational simplicity, availability of reactants, short reaction time and easy work-up.

Background & Aim:The genus Salvia (commonly known as sage) is a broad genus belonging to the family Lamiaceae. This study is aimed at assessing the essential oil composition and antimicrobial activities of two Salvia species. Experimental: The chemical composition of the essential oils of Salvia officinalis L. and Salvia virgata Jacq, cultivated in Estahban (Fars, South Iran), was studied by means of GC-MSanalyses. Antimicrobial activity was tested against a panel of microorganisms including one Gram-positive (Staphylococcus epidermidis PTCC NO. 1435) and one Gram-negative (Escherichia coli) and three fungal strain (Alternaria alternata PTCC NO. 5224, Penicillium funiculosum PTCC NO. 5301 and P. funiculosum PTCC NO. 5169) using the disk diffusion and agar-well diffusion methods and the Minimum Inhibitory Concentration (MIC) technique. Results: In all, 57 compounds were identified, 42 for S. officinalis, accounting for 98.94% ofthe total oil, 29 for S. virgata (98.81%). The major components of S. officinalis essential oil were α-thujone (37.18%), 1,8-cineole (12.71%), β-thujone (9.10%) and the major components of S. virgata essential oil were caryophyllene oxide (30.23%), β-caryophyllene (22.63%), sabinene (11.82%). The antimicrobial activity of the total essential oil evaluated by the agar-well diffusion method, the results showed that the highest active against S. epidermidis and also the least active against E. coli. Inhibition of growth was tested by the disk diffusion method, the results showed that essential oil of S. officinalis and S. virgata were highest active against E. coli and P. funiculosum (PTCC NO. 5301), respectively. Also the least active against A. alternata. Recommended applications/industries: The results showed thatS. officinalis oil had higher antimicrobial activity compare to S. virgata

Sir,The immunosuppressive drugs used for the treatment of psoriasis may affect the clinical presentation and outcome of COVID-19 infection (1). Herein, we report a 73-year-old male patient with sev...

Papulonecrotic tuberculid (PNT) is a relatively rare subtype of cutaneous tuberculosis believed to represent a hypersensitivity reaction to tuberculosis antigens. Yet, the simultaneous occurrence of PNT and Erythema Induratum (EI) is even more uncommon. Here, we present a case of concomitant PNT and EI in a 53-year-old woman without any previous history of Mycobacterium tuberculosis infection who was successfully treated with anti-tuberculosis agents without recurrence in a subsequent follow-up

Steroid pulse therapy has shown satisfactory efficacy and safety in treating pemphigus vulgaris (PV). However, there is a paucity of data about the efficacy and safety of methylprednisolone, despite its frequent administration. The aim of this study is to evaluate the efficacy and safety of steroid pulse therapy in treating PV. In this 10-year retrospective cohort study, 312 patients with PV, who had received methylprednisolone pulse therapy, were included. Data of pulse therapy sessions, adjuvant medications, dosages, remission rates, complications, and mortalities were collected from all patients. A total of 276 patients out of 312 underwent the final follow-up at least 6 months after the last session of pulse therapy. Complete remission off therapy was achieved in 83 patients (30%), and 152 patients (55%) had complete remission on therapy. About 29 (10.5%) patients had lesions of pemphigus at the time of the study follow-up, and 26.8% of remained patients were on the minimal therapy. Methylprednisolone pulse therapy could be considered as an option for proper control of PV in severe cases. It might lead to shorter periods of hospitalization and reduce the need to take long-term high-dose oral steroid therapy.

A straightforward and effective procedure for the conversion of a variety of alcohols into the corresponding alkyl iodides and bromides is described using KX/P2O5 (X = I, Br). The reactions were easily carried out in acetonitrile under mild conditions. Using this method, the selective conversion of benzylic alcohols in the presence of aliphatic alcohols was achieved.

To supervise massive generated data by the Internet of Things (IoT) efficiently, we face two issues that should be addressed which are: (1) heterogeneity or satisfying diversity among IoT devices, and (2) privacy-preserving or preventing unintentional disclosure of sensitive data. Through observation, we found that existing solutions apply one common privacy-preserving rule for all devices while they address the heterogeneity issue separately that lead to unappealing performance. In this paper, we propose a framework for addressing the heterogeneity issue and privacy-preserving of IoT devices at the network edge using a novel proposed ontology data model. Besides, it leverages the proposed ontology to obtain a privacy-preserving method by frequently changing the privacy-preserving behaviors of IoT devices. Through simulation, we show that our solution overhead is less than 9 percent in the worst situation so that it is affordable to most IoT devices in one of its applications that is smart city.

FA 25-year-old man presented with a 12-month history of progressive skin lesions involving the face, upper areas of the trunk, arms, and natal cleft. There was moderate pruritus, disfiguring lesions of the face, and mild arthralgia. No therapy had been applied before the referral to our clinic. On physical examination, there were skin-colored nodules on the face (Figure 1A), along with multiple firm subcutaneous nodules and tumors with a fairly symmetrical distribution on the extensor surface of the hands and forearms (Figure 2A). Dense papular lesions were found on the upper part of the back (Figure 3A). There was also a waxy infiltrated plaque in the natal cleft area (Figure 4A).

Recently, advances in understanding the etiology of urticaria and updates of diagnostic and therapeutic management guidelines have drawn attention to chronic urticaria (CU) morbidity. The present study aimed to evaluate Iranian dermatologists' practice and real life management of CU patients. A total of 35 dermatologists and 443 patients were included in the study. Number of female patients was 321 (72.5%). Mean (standard deviation) age of the study patients was 38 (13) years and the median (inter quartile range) of disease duration was 12 (6-48) months. Severity of patients' symptoms was mild for 32.1%, moderate for 38.7%, severe for 18.8%, and 10.4% of them had no evident signs or symptoms. The most common diagnostic methods were physical examination (96.6%), differential blood count (83.5%), erythrocyte sedimentation rate (77.4%), and C-reactive protein (62.8%). The number of dermatologists prescribed nonsedating antihistamines (nsAH) in regular dose and high dose mono therapy were 26 (74%) and 6 (17%), respectively. About 66% of dermatologists were familiar with British Association of Dermatologists (BAD) guideline. The most common first-line treatment for CU by Iranian dermatologists was nonsedating antihistamines in regular or high doses. The real-life management of patients with CU in Iran was in accordance with the available practice guidelines.

Acral warts are considered as prevalent reasons for dermatologic consultations and remain an important continuing challenge until now because there is no consensus about optimal therapeutic modality. This study investigated the efficacy of long-pulsed Nd: YAG laser therapy and cryotherapy in treatment of acral warts. Patients who underwent treatment with cryotherapy or long-pulsed Nd: YAG laser therapy for symmetrical and bilateral warts on the extremities (hand and foot) that is confirmed by an expert dermatologist from May 2016 until March 2018 were assessed for enrollment in our study. Laser and cryotherapy sessions were applied every 2 weeks for a maximum of six sessions. Patients followed up and evaluated 3 months after the last treatment. Data were analyzed by SPSS (v.21. IBM Inc. IL). The P value less than 0.05 was considered significant. From 60 enrolled patients, 134 lesions were treated using cryotherapy and 114 other lesions treated with laser beam. Thirty-four males (average age 26.85 ± 7.528 years) and 26 females (average age 26.73 ± 5.640 years) participated. Finally, it was a significant reduction in both lesion width (P = 0.000) and length (P = 0.000) after the sessions of cryotherapy. The width and length of lesions is reduced significantly after each session of laser therapy similarly (P = 0.000). Cryotherapy and long-pulsed Nd: YAG laser are effective on the reduction of both width and length of lesions. Clinically, the methods are not different in their ultimate effects.

Background/aim: Acute unintentional and deliberate poisoning by medications and chemicals is a frequent emergency, especially in Iran. This study aimed to evaluate the frequency and character of skin findings occurring in patients with acute intentional and aunintentional poisoning. Materials and methods: This prospective observational study was performed at the Loghman Hakim Hospital Poison Center over a period of 6 months from April 2016 to September 2016. Data including patient demographics, cause of poisoning, and level of consciousness were collected. Pediatric patients (under the age of 13) and patients who died in the first hours of admission were excluded from the study. Results: The most common cause of toxicity-related admission in our patients was methadone overdose. The most common skin finding in these patients was xerosis. According to our results, there was an association between tramadol poisoning and self-induced lesions. Shin hyperpigmentation was found to be significantly more frequent in patients with lead poisoning. Conclusion: Further study is recommended to shed light on the possible association of drug poisoning and skin lesions.

SummaryBackground and aim A comprehensive study comparing two different modalities, Nokor needle subcision (NNS) and blunt cannula subcision (BCS), for treatment of acne scars, has not been reported previously. The aim was to compare the effectiveness of these two methods based on patient's and doctor's satisfaction measures, in addition to the late complications 3 months postsubcision. Method of intervention Patients had 18-65 years old, with acne scars on both malar sides. They were treated at one malar side with NNS and with BCS at another side. They were monitored during the first week, at one and 3 months postintervention. Patient's and two dermatologist's satisfactions were compared during 3 months, for each modality and between modalities. Results From 34 patients, 29.4%, 55.9%, and 14.7% had mild, moderate, and severe acne scars, respectively. Ecchymosis, nodule formation post-NNS, and edema after BCS were the complications. Patients were satisfied with BCS during 3-month monitoring (P = .021), but not with NNS (P = .353). Physician-1 was satisfied from the outcome of both BCS and NNS procedures (P = .044 and .006, respectively). However, physician-2 was only satisfied with NNS at the month 3 than the month 1 (P = .002). All patients and physicians were significantly more satisfied with BCS than NNS (P = .000). Anyway, at the month 3, physician-2 had no significant different points of view about applied methods (P = .25). Discussion Considering the complications and satisfaction rates, BCS was more efficient than NNS for acne scar treatment. Then, we suggest BCS as a good replacement for NNS.

Multiple eccrine hidrocystomas (MEH) are benign cystic lesions of the sweat gland ducts. They are characterized by translucent, skin-colored or bluish dome-shaped papules on the face, causing cosmetic concern. Recently, botulinum toxin-A, because of its antiperspirant properties, has been used to treat facial MEH. However, there are only some case reports in the literature.Here, we conducted a prospective study to assess the efficacy and safety of intralesional injection of botulinum toxin-A (Dysport) for the treatment of MEH.Twenty patients (3 men and 17 women), aged from 31 to 75 years old, participated in this study. A 300 unit vial of botulinum toxin-A (Dysport, Ipsenn Biopharm, United Kingdom) was diluted with 4 ml of saline solution without preservative to achieve a concentration of 7.5U/.1 ml. Up to 1.5 unit of botulinum toxin was injected intradermally at the base of each lesion to raise a visible wheal. The patients were evaluated 7 days later, and any clinical changes or adverse effects were recorded.In all patients, more than 75% of eccrine hidrocystoma lesions resolved without any scaring. The result sustained for 2-5 months. In two patients mild smile asymmetry and in one patient lagophthalmos were noted approximately 5-7 days after injection that gradually resolved in 3 weeks.Intralesional botulinum toxin-A for treatment of multiple hidrocystomas is a simple and well-tolerated procedure. It is accompanied by excellent results, a good postoperative course, and no risk of scarring. It can be considered in patients who did not respond to other treatment or even as the first line therapy.

Sensor networks are dense wired or wireless networks used for collecting and disseminating environmental data. They have some limitations like energy that usually provide by battery and storages in order that we cannot save any generated data. The most energy consumer of sensors is transmitting. Sensor networks generate immense amount of data. They send collected data to the sink node for storage to response to users queries. Data storage has become an important issue in sensor networks as a large amount of collected data need to be archived for future information retrieval. The rapid development and deployment of sensor technology is intensifying the existing problem of too much data and not enough knowledge. Sensory data comes from multiple sensors of different modalities in distributed locations. In this chapter we investigate some major issues with respect to data storages of sensor networks that can be used for disaster management more efficiently.