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Face recognition methods achieve their highest accuracy when faces are captured in the frontal view. However, the accuracy of these methods decreases when the angle of a person's face changes relative to the camera. The problem of pose variation in face recognition can be addressed in either the feature space or the image space. While generating a frontal face in the image space can be costly, face recognition relies on feature vectors. This research proposes a method to effectively modify the feature vectors of angular face images. The proposed method involves segmenting the angular face image elements using a fine-tuned DeepLabv3 network. Subsequently, an Attention-equipped U-Net network transforms the angular face elements into frontal face elements. Features are then extracted from the normalized element image using a deep convolutional network to capture general information about the features. Detailed features are additionally obtained using the pre-trained VGGFace architecture. These detailed features are combined with the overall feature vector extracted from the facial elements, enabling the feature vector of an angular image to exhibit similarity to the feature vector of a frontal image of the same person. The proposed model was trained using the MUT1NY and FERET datasets and evaluated on a subset of the FERET dataset, which includes images from 200 individuals captured at various angles. The proposed model achieved an impressive average recognition accuracy of 99.81% on this evaluation set. [ABSTRACT FROM AUTHOR]

Cell suspension culture has the potential to be a valuable source for the bioactive compound productions. In this study, an optimized procedure was established for callus and cell suspension culture of Physalis alkekengi for the first time, and the impact of static magnetic field (SMF, 6 mT) was studied on the high-value metabolic compounds through investigation of signaling molecules and gene expressions at the late log-to-stationary phase. Results showed that the growth regulators of 6-benzyl amino purine (BAP, 1.5 mg−1 L) and 1-naphthaleneacetic acid (NAA, 0.4 mg−1 L) induced the highest fresh weight, callus rate, callus index, and total withanolides. Cell suspension culture was established in the liquid MS medium supplied with BAP (1.5 mg−1 L) and NAA (0.1 mg−1 L). SMF application decreased slightly the cell growth and viability and enhanced the number of round-shaped cells. The hydrogen peroxide (H2O2) and nitric oxide (NO) levels increased at an all-time series after SMF exposure, and their maximum contents were observed after 12 h. A significant alteration of malondialdehyde content was also identified after 12 h of SMF exposure. The expression of 3-hydroxy-3-methylglutaryl coenzyme A reductase (HMGR), 1-deoxyD-xylulose 5-phosphate synthase (DXS), squalene synthase (SQS), sterol Δ7-reductase (DWF5), and C-7,8 sterol isomerase (HYD1) genes was upregulated significantly after 24 and 48 h. An increase in the total withanolides was related to more activity of HMGR and DXS enzymes in SMF-exposed cells and the maximum physalin A (12.8 mg g−1 DW) and physalin B (1.92 mg g−1 DW) obtained after 24 h compared to controls. Findings suggest that SMF can play a supportive factor in inducing steroidal compounds in P. alkekengi through modulating H2O2 and NO levels and the related-gene expressions. [ABSTRACT FROM AUTHOR]

Background: Patients with inborn errors of immunity (IEI) are susceptible to developing cancer due to defects in the immune system. The prevalence of cancer is higher in IEI patients compared to the immunocompetent population and cancers are considered as an important and common cause of death in IEI patients. Objectives: To systematically review demographic, genetic and cancer-related data of IEI patients with a history of malignancy. Moreover, we performed a meta-analysis aiming to determine the frequency of cancer in patients with different types of IEI. Methods: We conducted electronic searches on Embase, Web of Science, PubMed, and Scopus (until September 2023) introducing terms related to IEI and cancer. Studies with human subjects with confirmed IEI who had developed at least one malignancy during their lifetime were included. Results: A total number of 4607 IEI patients with a cancer history were included in the present study. Common variable immunodeficiency (CVID) had the highest number of reported cases (1284 cases), mainly due to a higher relative proportion of patients with predominantly antibody deficiencies (PAD) and their increased life expectancy contributing to the higher detection and reporting of cancers among these patients. The most common malignancy was hematologic/blood cancers (3026 cases, mainly diffuse large B cell lymphoma). A total number of 1173 cases (55.6%) succumbed to cancer, with the highest rate of bone marrow failure (64.9%). Among the patients with monogenic defects in IEI-associated genes, the majority of cases had ATM deficiency (926 cases), but the highest cancer frequency rate belonged to NBS1 deficiency (50.5%). 1928 cases out of total 4607 eligible cases had detailed data to allow further statistical analysis that revealed BRCA2 deficiency had the earliest cancer development (~ 38 months), lowest cure frequency, and highest fatality rate (85%), while ATM deficiency had the lowest cure frequency and highest fatality rate (72%) among total cases reviewed with exclusion of Fanconi anemia. Conclusion: The overall reported cancer frequency in the cases reviewed with and without exclusion of Fanconi anemia was 11.1% (95% confidence interval: 9.8–12.5%) and 12.0% (95% confidence interval: 10.6–13.5%), respectively. Our study revealed that the incidence of cancer is significantly dependent on the molecular and pathway defects in IEI patients, and individualized early screening and appropriate treatment, might improve the prognosis of these patients. [ABSTRACT FROM AUTHOR]

Face super-resolution, commonly referred to as face hallucination, is a specific domain of super-resolution that focuses on generating high-resolution face images from their corresponding low-resolution versions. Face hallucination has received evident advances and significant attention with the expansion of deep learning methods. However, the state-of-the-art methods do not show much ability to preserve the inherent structure of the image. To address this limitation, we propose an Edge-Attention architecture that effectively maintains both local and global information in face super-resolution. Additionally, we introduce a novel loss function, the Frechet VGG Distance, which minimizes the discrepancy between the features of generated images and ground-truth images, thereby producing more realistic and high-quality results. Furthermore, we leverage the use of Unsharp Masking (UM) and Local Binary Pattern (LBP) techniques to enhance the edges of the low-resolution image. By employing the LBP method to refine the delicate edges and applying Unsharp Masking to sharpen all edges, our network excels at retrieving image structures in the super-resolution process. Experimental results provide evidence that our approach outperforms existing face super-resolution approaches in preserving facial structure and generating exceptional image quality. Moreover, our proposed method exhibits remarkable performance in enhancing the accuracy of face recognition systems when working with real-world low-resolution facial images. [ABSTRACT FROM AUTHOR]

Purpose: After the Tokyo 2018 guidelines (TG2018) were published, evidence from the 2018 CHOCOLATE RCT supported early cholecystectomy for acute cholecystitis (AC), even in high-risk patients. This study aims to investigate AC management at our tertiary care center in the years following these publications. Methods: A retrospective cohort study was performed on patients admitted from 2018 to 2023. AC severity was graded using TG2018 definitions. Comorbidities were summarized using Charlson Comorbidity Index (CCI) and frailty using the 5-item modified Frailty Index (5mFI). Compliance with TG2018 recommendations for management strategy was investigated. Outcomes were compared between patients who underwent surgery versus non-operative management (NOM). Subset analysis based on patients' age, frailty, and comorbidities was performed. Results: Among 642 AC patients, 57% underwent cholecystectomy and 43% NOM (22% percutaneous cholecystostomy, 21% antibiotics only). NOM patients had greater length of stay (LOS), complications, deaths, readmissions, and discharge to nursing/rehab versus surgery patients. In 70% of patients managed non-operatively, TG2018 were not followed. Patients managed non-operatively despite TG2018 were more likely to undergo delayed cholecystectomy compared to those in whom guidelines were followed (17% vs. 4%). In subset analysis, healthy octogenarians were significantly less likely to be managed according to TG2018 (9.4%); patients undergoing surgery had a trend towards shorter LOS (3.1 vs. 4.8 days) than those managed non-operatively but no difference in other outcomes. Conclusion: Most patients undergoing NOM could potentially undergo cholecystectomy if guidelines are considered. A more objective approach to risk assessment may optimize patient selection and outcomes. [ABSTRACT FROM AUTHOR]

The integration of electronics into textiles, commonly referred to electronic textiles (e-textiles), has sparked significant interest in recent years owing to their vast potential across diverse industries including healthcare, fashion, sports, and wearable technology. This review paper offers an extensive examination of the current landscape of e-textiles, focusing on their types, applications, conductive materials, and fabrication methods. Regarding fabrication methods, two primary approaches as main groups were introduced and are scrutinized in detail: (1) Fabricating/using conductive yarn/thread and inserting it into the textile using traditional textile techniques such as weaving, knitting, embroidery and so on. (2) Direct applying of conductive coatings onto existing textiles which include sub groups such as deposition techniques, wet coating techniques, printing techniques and in situ polymerization for integrated conductivity. Notably, this review not only elucidates these methodologies but also encapsulates the latest advancements in e-textile fabrication, serving as a vital resource for researchers and developers navigating this rapidly evolving domain. It also acknowledges the main challenges that need to be addressed to fabricate high efficent e-textile. These include ensuring durability with has direct relation with long-term washability and flexibility. Different strategies to improve durability such as using elastic substrates, stretchable conductive ink, improving adhesion between conductive layer and textile along with encapsulation of conductive layer on textile are discussed. By offering a comprehensive overview and highlighting recent innovations, this paper aims to propel further advancements in the realm of e-textiles, facilitating the realization of their full potential across various sectors. [ABSTRACT FROM AUTHOR]

The complex interaction between the cutters and rocks in the tunnel face makes it difficult to predict the cutter wear, exactly. Therefore, many researchers have tried to study this process and introduce different ways to predict the wear extent of cutters and the number of cutters required to complete a mechanized tunneling project. In this study, in addition to investigating the effect of geological parameters on cutters wear/life, new empirical equations were proposed for predicting cutter wear/life, based on data collected from a long tunnel constructed in central parts of Iran, namely Kerman Water Conveyance Tunnel (KrWCT). The data collected from this project, including information related to cutter change stations, variations of geological parameters along the bored section of the tunnel, and actual machine’s operational and performance parameters, were compiled in a database and analyzed statistically. The results of statistical analyses revealed a significant relationship between the cutter wear/life and intact rock properties. Consequently, the proposed empirical prediction equations just employ two important intact rock properties, including rock strength (UCS) and Cerchar abrasivity index (CAI), as inputs. The results showed that the presence of discontinuities with moderate-wide spacing has a negligible effect on cutter consumption. These results also proved that models focusing only on rock abrasivity without considering the rock strength as an input will not provide an accurate assessment of the cutting tool wear. The new models are based on information from a wide range of igneous, pyroclastic, and sedimentary rocks with the UCS and CAI ranges of 50–250 MPa and 0.5-5.0, respectively. [ABSTRACT FROM AUTHOR]

Endothelial inflammation plays a crucial role in vascular-related diseases, a leading cause of global mortality. Among various cellular players, endothelial progenitor cells (EPCs) emerge as non-differentiated endothelial cells circulating in the bloodstream. Recent evidence highlights the transformative role of EPCs in shifting from an inflammatory/immunosuppressive crisis to an anti-inflammatory/immunomodulatory response. Despite the importance of these functions, the regulatory mechanisms governing EPC activities and their physiological significance in vascular regenerative medicine remain elusive. Surprisingly, the current literature lacks a comprehensive review of EPCs' effects on inflammatory processes. This narrative review aims to fill this gap by exploring the cutting-edge role of EPCs against inflammation, from molecular intricacies to broader medical perspectives. By examining how EPCs modulate inflammatory responses, we aim to unravel their anti-inflammatory significance in vascular regenerative medicine, deepening insights into EPCs' molecular mechanisms and guiding future therapeutic strategies targeting vascular-related diseases. [ABSTRACT FROM AUTHOR]

The necessity of predicting geotechnical parameters in soft ground tunnelling is crucial for selecting the appropriate tunnel boring machine (TBM), evaluating the operating limit of earth pressure balance (EPB) machines' parameters, and ensuring the safety and efficiency of TBMs during tunnel construction. In this research, various EPB operating parameters such as cutterhead torque, thrust force, chamber pressure, and cutterhead rotation speed (RPM) were utilized to estimate geotechnical parameters like friction angle (φ) and shear strength (τ) for engineering geological units ET1 to ET5 (fine-grained and coarse-grained soils) along the tunnels route, which serve as indicative units for the entire tunnels path. Statistical methods and computational techniques, namely support vector regression (SVR) and feed-forward neural network (FFNN), were trained using EPB operating parameters and geotechnical data from Tehran metro line 6—southern extension sector (TML-SE6) and the East–west section of line 7, Tehran metro project (TML-EW7). A comprehensive dataset comprising borehole logging results along the tunnel path was gathered, with 85% of the data randomly selected for training and the remaining 15% reserved for model testing. Various loss functions and statistical metrics were employed to evaluate the accuracy and precision of the method. The results of the proposed models demonstrate satisfactory and reliable accuracy of the approaches. Highlights: Database collected, generated, and analyzed using daily operational records, TBM data logger, in-situ analysis, laboratory tests, and statistical investigations; New formulas developed to predict geotechnical parameters of soil materials by incorporating various operating parameters of the Tunnel boring machine; Investigation of predictive abilities of smart algorithms in estimating shear strength and internal friction angle; Comprehensive evaluation conducted to compare and contrast empirical and machine learning outcomes; Accuracy of models evaluated using multiple assessment metrics. [ABSTRACT FROM AUTHOR]

In today's urban development, Earth Pressure Balance (EPB) Tunnel Boring Machines (TBMs) play a vital role. It's crucial to design a comprehensive monitoring system to control surface settlement and prevent damage to surface structures. This study focuses on creating prediction models for estimating ground surface settlement. Two soft computing techniques, namely ANN-CFB and ANN-BP, were used for this purpose. The models were validated using operational data from the Qom metro Line A, specifically the section between A14 and A10 stations. Additional input parameters were incorporated using an image processing approach to include soil properties for each segment. As a result, the most accurate ANN technique was employed to predict ground surface settlements for the mentioned project. The correlation coefficients for training, testing, validation, and the overall result were found to be 0.99439, 0.97873, 0.96381, and 0.98824, respectively. Through sensitivity analysis, the study explored the connections between different parameters and ground surface settlement. The outcomes reveal strong agreement between predicted values and real data. Notably, the parameter 'cutter head torque' exhibited the highest impact on surface settlement (8.48%), while 'Pressiometric Modulus (Ep)' had the least impact (4.24%). [ABSTRACT FROM AUTHOR]

Knowing accurate values of rock engineering parameters in hard rock condition is the key in estimating and adjusting TBM performance. In this study, TBM penetration per revolution (Pr) as driving parameter, TBM operational parameters including cutterhead torque (Tq), field penetration index (FPI), thrust force (Th), cutter load (Fn), cutterhead rotational speed revolution per minute (RPM), and also cutterhead diameter as a mechanical machine specification are used to predict geomechanical parameters including rock quality designation (RQD) and unconfined compressive strength (UCS) based on reverse analysis in three types of strong rocks (Tuff, Andesite, Diorite) along the Southern lot of Kerman water transfer tunnel; KrWCT. A soft computing method called least squares-support vector machine (Ls-SVM), is trained using operating and driving data as well as rock engineering parameters gathered from the KrWCT project which is excavated in hard rock condition using double shield TBM. Due to the lack of access to the excavation face in mechanized tunneling, the collection of geomechanical data on the rock mass is possible only through the examination of excavated material and limited inspections during cutterhead repairs. Therefore, this paper has tried to predict and classify the rock engineering factors using some indicators related to machine performance, mechanical specification, and TBM operational parameters. Among the data collected during the pre-construction and construction phases of the project, the dataset was classified into 42 zones, and the reasonable distribution intervals of the main tunneling factors corresponding to each zone were defined. New empirical equations are developed to estimate the properties of igneous rocks based on linear and non-linear multivariable regression (MR). Several loss functions were used to assess the performance and precision of the applied methods. The results of the proposed models indicate an acceptable and reliable accuracy. Highlights: TBM data predicts rock engineering properties in complex geological condition. Forecasting RQD and UCS in deep tunnels through strong rocks using reverse analysis. Developing empirical models for calculating UCS and RQD based on statistical analysis. Detailed analysis of Ls-SVM supervised network for rock geomechanical prediction. Examining model accuracy with various statistical indices and loss functions. [ABSTRACT FROM AUTHOR]

Carbonate rocks have been used as a building material for centuries all around the world. Construction and reconstruction projects still commonly employ them, particularly for replacing damaged ashlars in monuments. Unfortunately, Carbonate rocks are highly vulnerable to salt weathering, leading to their eventual breakage. This study focuses on analyzing how dolostones used in the construction of Falak-ol-Aflak castle behave when exposed to salt crystallization weathering. To achieve our goal, we conducted 40 salt crystallization test cycles on the selected dolostones using Na2SO4 and MgSO4 solutions. After every 10 cycles, we assessed the visual changes and physico-mechanical properties of the salt-crystallization samples. We measured the damage rate (DR) of weight (W), P-wave velocity (Vp), porosity (n), and point load index (PLI) to determine these properties. SEM observations were conducted to examine the structural changes of the building stones resulting from the salt crystallization tests. Based on the findings, it can be concluded that saline solutions containing Na2SO4 cause more damage to samples than those containing MgSO4. [ABSTRACT FROM AUTHOR]

Infertility is a reproductive health problem in the male or female reproductive system. Traditional assisted reproductive technology (ART) has been unable to solve various cases of infertility for years. Clinical researchers have sought to treat infertility using new methods that are more effective and noninvasive than the old methods. Recently, Mesenchymal stem cells (MSCs) and MSCs-derived Exosomes (MSC-Exos) via paracrine activity play an important role in treating various causes of infertility and improving pregnancy outcomes. In this review, we focus on the roles of MSCs and MSC-Exos cell therapy in female infertility in the different types of female reproductive disorders. [ABSTRACT FROM AUTHOR]

Planar hypergraphs are widely used in several applications, including VLSI design, metro maps, information visualisation, and databases. The minimum s - t hypercut problem in a weighted hypergraph is to find a partition of the vertices into two nonempty sets, S and S ¯ , with s ∈ S and t ∈ S ¯ that minimizes the total weight of hyperedges that have at least two endpoints in two different sets. In the present study, we propose an approach that effectively solves the minimum s - t hypercut problem in (s, t)-planar hypergraphs. The method proposed demonstrates polynomial time complexity, providing a significant advancement in solving this problem. The modelling example shows that the proposed strategy is effective at obtaining balanced bipartitions in VLSI circuits. [ABSTRACT FROM AUTHOR]

Recently, increased attention has been paid to the raw materials of plants as a source of biologically active substances. Black rosehip (Rosa pimpinellifolia L.) fruits could be a good resource for potential functional components in the food, cosmetic and pharmaceutical industries. Also, drying can influence the composition of heat-sensitive phytochemicals. However, less attention is given to comparing black rosehip bioactive compounds particularly compositions of fatty acid, amino acids, and phenolic content in fresh and dried fruits. So in this study, the amino acid constituents (by amino acid analyzer), fatty acids (by GC–MS), mineral elements (by atomic absorption spectrometer), antioxidant (by DPPH) and phenolic compounds (by HPLC) present in fresh and dried fruits of black rosehip naturally grown in Iran were comprehensively investigated. The results showed that dried fruits had a lower level moisture by 51.55%, and a higher level of total phenolic compounds and total sugar by 786.20 mg GAE/100 g and 15.77 g/100 g, respectively. Chlorogenic acid and gallic acid were the major phenolic compounds (109.3 mg/g). Whilst, linoleic acid, oleic acid, and arachidic acid (85.34%) were the most dominant fatty acids. The most dominant amino acids were glutamic acid, phenylalanine, and arginine (29.41 g/100 g). Also, Fe and Mn as micro-elements were the most dominant elements. In general, the results illustrated the potentials and differences of black rosehip fruits grown in the Arasbaran region as promising resources for food sources, pharmaceutics, cosmetics, and breeding programs. Also, these findings confirm that black rosehip fruits contain significant amounts of secondary metabolites that may positively affect human health. [ABSTRACT FROM AUTHOR]

Physalis alkekengi L. is a valuable medicinal plant from the Solanaceae family and has multiple therapeutic applications. This study aimed to develop an optimized protocol for callogenesis in P. alkekengi to obtain friable calluses with high biomass. The effect of different concentrations of picloram, casein hydrolysate (CH), basal media (Murashige and Skoog (MS) and Gamborg (B5)), and static magnetic field (SMF) were investigated on the callus induction and growth, signaling molecules, and enzymatic and non-enzymatic antioxidants. Results showed that CH (200 mgL−1) and SMF4 mT for 90 min increased callus induction and fresh weight in P. alkekengi, while different concentrations of picloram reduced callogenesis. Hypocotyl explants showed various callogenesis and metabolic responses depending on the basal medium type. The 2B5 medium supplied with CH 200 (mgL−1) induced friable and cream calluses with high biomass (0.62 g) compared to the MS medium (control). The maximum activity of superoxide dismutase and catalase activities was identified in the 2B5 medium and peroxidase in the 2MS medium. The highest total phenolic (129.44 µg g−1DW) content and phenylalanine-ammonia lyase activity were obtained in the 2MS medium, and total withanolides (49.86 µg g-1DW) and DPPH radical scavenging activity were observed in the 2B5 medium. The 2MS medium boosted the hydrogen peroxide and nitric oxide levels, while their contents alleviated in the 2B5 medium, although these parameters were higher than the control. The findings of this study suggest that an effective protocol for successful callogenesis in P. alkekengi and the nutrient composition of culture medium by affecting the level of signaling molecules can control the antioxidant defense system and callus growth. [ABSTRACT FROM AUTHOR]

Face recognition is one of the most important research topics in computer vision. Indeed, the face is an important means of communication with humans and it is highly needed for daily contact. Face recognition technology is applied in many biometric applications such as security, video surveillance, access control systems, and forensics. In this technology, hashing has recently made encouraging progress due to its fast retrieval speed and low storage cost. In this work, we propose an effective face recognition framework based on hashing functions. It attempts to leverage a cascaded architecture with two stages of analyzing different visual information based on image hashing. Specifically, we first introduce a filter to overlook a large number of dissimilar identities in terms of local visual information. Similar identities are found quickly through random independent hash functions inspired by Locality Sensitive Hashing (LSH). Next, we further refine candidates and recognize the most similar identities according to global visual information. The global feature is obtained by hashing each face into a high-quality binary feature space using Discrete Cosine Transform (DCT) coefficients. The proposed method is evaluated on three well-known and one combined face dataset. The obtained results, and the provided face recognition application program, demonstrate that the proposed framework improves the recognition rate and significantly reduces recognition time. [ABSTRACT FROM AUTHOR]

Polymer nanocomposites (PNCs) have emerged as cutting-edge solutions in the realm of composite materials, revolutionizing the polymer industry. Traditionally, the augmentation of polymer properties relies on the integration of various micrometer-sized fillers such as carbon black, calcium carbonate, glass fibers, and talc. However, this approach often requires high filler concentrations, resulting in elevated material viscosities and processing challenges. Recent advancements have highlighted the remarkable potential of incorporating nanomaterials (NMs) into polymers. Even at minimal quantities, these nanofillers exhibit a profound impact on enhancing polymer properties while preserving processability. However, challenges such as poor dispersion, agglomeration, and interfacial adhesion remain significant hurdles to achieving optimal performance. In this review, a new classification of polymer non-covalently modified nanomaterials (PNCMNMs) and polymer-grafted nanomaterials (PGNMs) as the most efficient methods to fabricate High-Performance PNCs are introduced. Furthermore, recent studies have addressed the influence of significant factors on these methods, such as the type of NMs and polymers, grafting density, length of the polymer, surface modification and so on are examined. For surface modification, coupling agents that facilitate the attachment of polymer chains to nanomaterial surfaces are discussed. Overall, this study offers valuable insights into the advancements, challenges, and future prospects of PNCMNMs and PGNMs, paving the way for their continued development and widespread use in diverse applications. [ABSTRACT FROM AUTHOR]

The generation maintenance scheduling deals with a time sequence of preventive maintenance outages for a given set of generation units in an electricity market subject to power system restrictions. Incorporating a leader–follower structure in generation maintenance scheduling models is essential because of the inherent conflict between the interests of an independent system operator (ISO) and generation companies (GENCOs). The present paper proposes a new preventive maintenance scheduling model for generation companies facing the risk of involving generation units' disruption and demand variations while ensuring the reliability of the power system. Each GENCO proposes the maintenance schedule of its generation units to the ISO in a non-cooperative manner intending to maximize its net profit. Then ISO reacts to the aggregated schedule according to the power system's reliability index. Thus, a new formula is developed to consider all the interactions between the power system's stakeholders. In this regard, a stochastic multi-leader one-follower approach is applied. The GENCOs are considered independent leaders at the upper-level and the ISO is considered a follower at the lower-level. Then an equivalent single-level counterpart model is presented for each leader. So, the whole problem is converted into multiple individual stochastic single-level models, and then the Nash Equilibrium concept is used to determine GENCO equilibrium strategies. The proposed methodology is evaluated using some modified IEEE reliability test systems. The numerical analysis confirms that the proposed model is more effective in cases with higher uncertainties. Moreover, the performed analysis demonstrated the importance of applying a bi-level approach to the problem. Finally, the superiority of the proposed approach compared to the existing one is confirmed. [ABSTRACT FROM AUTHOR]

One of the TBM performance prediction models that has been introduced in recent years and used for estimating penetration rate of TBM in hard rock conditions is the QTBM model. This model was introduced by Barton in the early 2000s. There have been many reviews of this model and the estimated penetration rates in various projects. This study was also conducted to check the validity of this model and propose modifications to models for different geological conditions. For this purpose, a database of TBM field performance along with geological information was prepared from 109 tunnel sections (with reliable geological and machine data). The results of calculated penetration rate by the QTBM model were compared with the field observation in the database. The results showed that this model offers low accuracy in predicting the machine penetration rate in different geological conditions. Subsequently, the relationship between input parameters of the QTBM model with the penetration rate was re-examined to see the impact of individual input parameters on the penetration rate of the machine. A new model is proposed, where the input parameters with lower impact on the penetration rate were removed and an attempt was made to obtain an empirical relationship between the more influential parameters and the field penetration index (FPI). New empirical relationships are more accurate in predicting machine penetration rates due to their simplicity and the need for fewer input data. [ABSTRACT FROM AUTHOR]

In this paper, we present an entangled state controlled semi-quantum secret sharing CSQSS protocol for the first time. In this scheme, with the permission of a trusted classical user, B o b 1 , Alice, as a quantum user, can share a one-bit specific message with n classical users, and the secret can only be recovered by the cooperation of all classical users. Then, the protocol is extended where m-bit specific messages, K (k 1 , k 2 ,... , k m) , can be shared with n classical users. The security of the proposed protocol against common attacks is analysed in detail, which shows that the proposed protocol is theoretically secure. Compared with previous SQSS protocols, the proposed protocol can achieve a lower cost because it does not use returning qubits for producing the secret message, uses fewer returning qubits for eavesdropping check, and does not perform entangled state measurement. Moreover, the proposed protocol has the highest qubit efficiency among the previous SQSS schemes. [ABSTRACT FROM AUTHOR]

Catamenial seizures refer to a form of epilepsy that occurs in women as a result of hormonal imbalances during the menstrual cycle. The purpose of this study was to examine the impact of betaine on seizures induced by pentylenetetrazol (PTZ) during the estrus cycle in rats. In this experiment, thirty female Wistar rats were randomly divided into five groups: control, valproic acid (75 mg/kg), and betaine (10, 20, and 30 mg/kg, i.p), each further divided into subgroups based on the phases of the estrous cycle (proestrus, estrus, metestrus, and diestrus). The rats received an intraperitoneal injection of betaine followed by PTZ (80 mg/kg) injection. The initiation time of myoclonic seizures (ITMS), initiation time of tonic–clonic seizures (ITTS), and seizure duration (SD) were then measured. The results revealed that betaine (20 and 30 mg/kg) significantly increased ITTS and ITMS during different phases of the estrous cycle in comparison to the control group (P < 0.05). Furthermore, seizure duration was significantly reduced with the administration of betaine (20 and 30 mg/kg) compared to the control group (P < 0.05). Additionally, betaine (20 and 30 mg/kg) was found to significantly delay the onset of ITMS and ITTS during the metestrus and diestrus phases when compared to the proestrus and estrus phases (P < 0.05). In conclusion, the findings of this study suggest that betaine exhibits anticonvulsant effects in the PTZ model of rats, with greater efficacy observed during the luteal phase than the follicular phase. [ABSTRACT FROM AUTHOR]

The parasitoid wasp Diadegma semiclausum Hellen (Hymenoptera: Ichneumonidae) is an effective endoparasitoid for controlling the larvae of Plutella xylostella (L.) (Lepidoptera: Plutellidae). Fertilizer application can induce resistance mechanisms in plants against herbivores. In bottom-up effects, resistance-related signaling pathways triggered by fertilizers in plants may affect the fitness of natural enemies. This study aimed to investigate the effect of induced resistance by vermiwash on some fitness-related parameters of D. semiclausum, including immature survival, development time, reproduction, and life table parameters. The experiment was conducted in a standard climate chamber set at 25 ± 1 °C, a photoperiod of 16 h light: 8 h dark, and 65 ± 5% RH. The results showed that D. semiclausum developing within P. xylostella larvae reared on vermiwash-treated canola plants had a longer duration and lower survivorship of immature stages than those developing within P. xylostella larvae reared on untreated canola plants (control). Furthermore, the parasitoid females that emerged from the vermiwash treatment deposited fewer eggs compared to those emerging from the control treatment. The R0 and r values of D. semiclausum were lower on the vermiwash treatment (9.96 offspring/female and 0.150 day−1, respectively) compared to the control population (15.94 offspring/female and 0.198 day−1, respectively). These results suggest that if vermiwash is sprayed on canola and P. xylostella larvae feed on the plant, it has the potential to adversely affect the population growth of D. semiclausum. Therefore, more care should be taken regarding the application of this fertilizer in D. semiclausum-based integrated pest management (IPM) programs. [ABSTRACT FROM AUTHOR]

Identifying the optimal azimuth and inclination for wellbore drilling in sandy formations can be considered a valuable aid in reducing sand production risks, lost time, and decreasing drilling costs in the petroleum industry. Therefore, a numerical systematic approach was provided to predict sand production in wellbore SDX-5, drilled in a deep-water sandstone reservoir in the Shah-Deniz gas field (South Caspian Basin), which has never been done previously. Additionally, this systematic approach uses geomechanical and geodynamical criteria, along with petrophysical information (density and sonic log) and tectonic characteristics of the study area, which are influenced by the active tectonic stresses of the Apsheron-Balkhan zone. The subsurface data sources employed are more eco-friendly, available, and continuous than experimental tests. The computations conducted achieved azimuth, inclination, polar, and depth profile plots for the Lower Balakhany Formation. The calculations reveal that the optimum azimuth for the wellbore drilling trajectories is parallel to SHmax and oblique drilling to near horizontal is the result of optimum inclination. Polar plots showed optimum azimuth, inclination, and effect of wellbore trajectory on critical collapse pressure and collapse drawdown pressure with pressure values simultaneously, which identify safer alternatives for achieving higher petroleum production rates without sanding. Depth profile plots provide a simultaneous overview of the values of critical collapse pressure, critical sanding pressure for instantaneous drawdown, and optimum wellbore production pressure during drilling and production operations. Moreover, optimum reservoir fluid production (maximum discharge) rates can be identified and imposed as upper limits to prevent sand production. [ABSTRACT FROM AUTHOR]

This study aimed to investigate the effects of clinorotation induced by 2-D clinostat on the growth, tropane alkaloid production, gene expression, antioxidant capacity, and cellular defense responses in the callus tissue of Hyoscyamus niger. Callus induction was conducted by putting hypocotyl explants in the MS culture medium supplemented with 1 mgL−1 2,4-D and 1 mgL−1 BAP growth regulators. The sub-cultured calli were placed on a clinostat for 0, 3, 7, and 10 days (2.24 × 10–5 g on the edge of the callus ring). Clinorotation significantly increased callus fresh weight, dry weight, protein, carbohydrate, and proline contents compared to the control, and their maximum contents were obtained after 7 and 10 days. H2O2 level enhanced under clinorotation with a 76.3% rise after 10 days compared to control and positively affected the atropine (77.1%) and scopolamine (69.2%) productions. Hyoscyamine 6-beta hydroxylase and putrescine N-methyltransferase gene expression involved in the tropane alkaloid biosynthesis were upregulated markedly with 14.2 and 17.1-folds increase after 10 days of clinorotation, respectively. The expressions of jasmonic acid, mitogen-activated protein kinase, and ethylene-responsive element-binding transcription factor were upregulated, and the activity of peroxidase and catalase showed a 72.7 and 80% rise after 10 days. These findings suggest that microgravity can enhance callogenesis by stimulating the ROS level, which can impact the antioxidant enzymes, tropane alkaloid formation, and gene expression. [ABSTRACT FROM AUTHOR]

Neutrons can be generated in medical linear accelerators (Linac) due to the interaction of high-energy photons (> 10 MeV) with the components of the accelerator head. The generated photoneutrons may penetrate the treatment room if a suitable neutron shield is not used. This causes a biological risk to the patient and occupational workers. The use of appropriate materials in the barriers surrounding the bunker may be effective in preventing the transmission of neutrons from the treatment room to the outside. In addition, neutrons are present in the treatment room due to leakage in the Linac's head. This study aims to reduce the transmission of neutrons from the treatment room by using graphene/hexagonal boron nitride (h-BN) metamaterial as a neutron shielding material. MCNPX code was used to model three layers of graphene/h-BN metamaterial around the target and other components of the linac, and to investigate its effect on the photon spectrum and photoneutrons. Results indicate that the first layer of a graphene/h-BN metamaterial shield around the target improves photon spectrum quality at low energies, whereas the second and third layers have no significant effect. Regarding neutrons, three layers of the metamaterial results in a 50% reduction in the number of neutrons in the air within the treatment room. [ABSTRACT FROM AUTHOR]

Laminar graphene oxide (GO) is a promising candidate material for next-generation highly water-permeable membranes. Despite extensive research, there is little information known concerning GO's ion-sieving properties at high acidic/basic pH and temperatures. In this study, the ion-blockage properties of the pristine GO and GO/zinc oxide (ZnO) nanocomposite membranes were tested using a non-pressure-driven filtration setup over a wide range of pH and temperatures. The ZnO nanoparticles within the composite membranes were synthesized via the room-temperature oxidation of zinc acetate and zinc acrylate precursors and were uniformly distributed across the composite membrane. It is observed that partially replacing the zinc acetate precursor with zinc acrylate improves the blockage performance of the composite membranes under extreme basic conditions by 42%. Moreover, photocatalytically-reduced composite membranes blocked copper sulfate ions 28% more than as-prepared composite membranes. Further, it was discovered that the composition of the membrane plays a vital role in its ion blockage performance at higher temperatures. [ABSTRACT FROM AUTHOR]

In this paper, a computer-aided method is proposed for abnormality detection in Wireless Capsule Endoscopy (WCE) video frames. Common abnormalities in WCE images include ulcers, bleeding, Angiodysplasia, Lymphoid Hyperplasia, and polyp. In this paper, deep features and Hand-crafted features are combined to detect these abnormalities in WCE images. There are not sufficient images available to train deep structures, therefore the ResNet50 pre-trained model is used to extract deep features. Hand-crafted features are associated with color, shape, and texture. We used a novel idea to reveal unexpected color changes in the background due to existing lesions as a color feature set. Histogram of gradient (HOG) and local binary pattern (LBP) were used respectively for shape and texture features. They are extracted from the region of interest (ROI), i.e. suspicious region. The expectation Maximization (EM) algorithm is used to extract more distinct areas in the background as ROI. The expectation Maximization (EM) algorithm is configured in a way that can extract areas with a distinct texture and color as ROI. The EM algorithm is also initialized with a new fast method which leads to an increase in the accuracy of the method. A large number of features are created by the method, so the minimum redundancy maximum relevance approach is used to select a subset of more effective features. These selected features are then fed to a Support Vector Machine for classification. The results show that the proposed approach can detect mentioned abnormalities in WCE frames with the accuracy of 97.82% [ABSTRACT FROM AUTHOR]

Background: Diabetes is a life-threatening health condition that requires expensive treatment and places a significant financial burden on society. Consequently, this study aimed to explore the potential of low and high concentrations of ginger extract, ZnO-NPs, and a combination of both to help manage diabetes and reduce high levels of lipids in diabetic rats. Methods and results: The research focused on agglomerated nanoparticles under 100 nm, specifically ZnO nanoparticles. The size of the nanoparticles was determined using X-ray diffraction analysis and scanning electron microscopy analysis, with a monodisperse particle size distribution of 20 to 48 nm and an average size of 38 nm, as shown by dynamic light scattering. Fourier transform infrared spectroscopy revealed the presence of typical peaks of ginger extract and ZnO-NPs in the nanocomposite structure. The pancreatic tissue histopathological study indicated that a concentration of 10 mg/kg of the composite had the most significant antidiabetic effect compared to other treatments. Lower concentrations could significantly reduce and balance fasting blood sugar and triglycerides levels while also increasing the high-density lipoproteins levels. However, all treatments induced a significant decrease in total cholesterol and low-density lipoproteins levels. Only metformin and ZnO-NPs in lower concentrations could decrease very low-density lipoproteins levels. The molecular technique showed that a low concentration of the composite led to the most significant decrease in Tnf-α gene expression compared to the diabetic group. The expression of the glutathione peroxidase 1 (Gpx1) gene in treated groups had no significant difference with the level of Gpx1 expression in the control rats. Conclusions: In general, this study demonstrated that lower concentrations of the treatments, especially composite, were more effective for treating diabetic rats due to reduced pancreatic tissue damage. [ABSTRACT FROM AUTHOR]

In mechanized tunneling, the ability to accurately predict the performance of the tunnel boring machine (TBM) is critical, because of its impacts on the project schedule and cost. A substantial amount of research has been conducted on predicting the penetration rate of TBMs in rocks but sometimes the actual cutting process of the disc cutter has been ignored, as most of the available models have been developed based on the assumption that the chipping process is the dominant mode of rock breakage. This might be true in many cases, but there are also situations where tensile fractures do not extend long enough to form chips, instead the tracks get deeper, and fines and rock powder are generated instead of chipping. This situation happens when the cutter load is insufficient to form chips, or so called sub-critical loading occurs. Two of the recent tunneling projects where subcritical cutter load has been the dominant mode are the southern extension of Tehran subway Line 6 (SEL6), and the southern lot of Kerman water conveyance tunnel (KrWCT). The issue in SEL6 was insufficient thrust of the machine and in KrWCT the high strength of the rock. Evaluation of the FPIs in SEL6 shows that the FPIs were less than 100 (kN/cutter/mm/rev) and the prediction errors of the existing models are low. However, in KrWCT project in rocks with higher strength and higher FPIs, the prediction errors are considerable. This indicates that the common models cannot offer an accurate estimate of the performance of TBM in subcritical loading in rocks with high strength. This study attempts to use statistical and machine learning methods to develop a new relation for TBM performance prediction in such conditions based on actual machine operating data and rock engineering geological features. New equations are introduced for the estimation of FPI in subcritical loading conditions to achieve more reliable and accurate prediction of TBM penetration rate. Highlights: Issues of hard rock TBM performance predictions in subcritical cutter load conditions. Development of a new performance prediction model for subcritical loading conditions using regression analysis and AI algorithms. Consideration of geological and geotechnical parameters and machine specification in model development. [ABSTRACT FROM AUTHOR]

Nitrogen is an essential nutrient for plant growth and yield, however excess nitrogen fertilizer application can lead to detrimental environmental impacts. Identifying cucumber genotypes with high nitrogen use efficiency (NUE) could facilitate sustainable crop production through optimized nitrogen management. This study was conducted in March 2021 at the research greenhouse of Department of Horticultural Sciences, University of Guilan, Iran. The objective of this study was to assess growth, yield components, nitrogen accumulation, NUE, and nitrate reductase activity in 60 cucumber genotypes under sufficient (NS) and deficient (ND) nitrogen conditions. Nitrogen deficiency caused reductions in growth and yield across all genotypes, although the severity varied. Nitrogen content was higher in all plant organs under NS compared to ND. NUE and its components nitrogen uptake efficiency (NUpE) and nitrogen utilization efficiency (NUtE) were significantly higher under ND versus NS. Line 57 exhibited the best NUE and yield under both NS and ND, and could be considered a nitrogen-efficient genotype. Based on NUE performance, lines were categorized as efficient, semi-efficient, low-efficient, and inefficient. Nitrate reductase activity was higher in leaves versus roots, and positively correlated with NUE, suggesting a relationship between enzyme activity and nitrogen uptake efficiency in roots. This study demonstrates genotype-specific responses to nitrogen availability in cucumber. The identification of genotypes efficient in NUE, such as line 57, can inform breeding efforts to improve nitrogen responsiveness. Characterizing nitrogen responsiveness across genotypes also allows for optimized, genotype-specific nitrogen management recommendations to be made, facilitating sustainable crop production. [ABSTRACT FROM AUTHOR]

Background: Diabetes is a life-threatening health condition that requires expensive treatment and places a significant financial burden on society. Consequently, this study aimed to explore the potential of low and high concentrations of ginger extract, ZnO-NPs, and a combination of both to help manage diabetes and reduce high levels of lipids in diabetic rats. Methods and results: The research focused on agglomerated nanoparticles under 100 nm, specifically ZnO nanoparticles. The size of the nanoparticles was determined using X-ray diffraction analysis and scanning electron microscopy analysis, with a monodisperse particle size distribution of 20 to 48 nm and an average size of 38 nm, as shown by dynamic light scattering. Fourier transform infrared spectroscopy revealed the presence of typical peaks of ginger extract and ZnO-NPs in the nanocomposite structure. The pancreatic tissue histopathological study indicated that a concentration of 10 mg/kg of the composite had the most significant antidiabetic effect compared to other treatments. Lower concentrations could significantly reduce and balance fasting blood sugar and triglycerides levels while also increasing the high-density lipoproteins levels. However, all treatments induced a significant decrease in total cholesterol and low-density lipoproteins levels. Only metformin and ZnO-NPs in lower concentrations could decrease very low-density lipoproteins levels. The molecular technique showed that a low concentration of the composite led to the most significant decrease in Tnf-α gene expression compared to the diabetic group. The expression of the glutathione peroxidase 1 (Gpx1) gene in treated groups had no significant difference with the level of Gpx1 expression in the control rats. Conclusions: In general, this study demonstrated that lower concentrations of the treatments, especially composite, were more effective for treating diabetic rats due to reduced pancreatic tissue damage. [ABSTRACT FROM AUTHOR]

Catamenial epilepsy is one of the central brain-related disorders associated with a menstrual cycle in some epileptic women. This study aimed to determine the effects of berberine on pentylenetetrazole-induced seizures during the estrus cycle in rats. A total of 30 adult female Wistar rats were randomly allocated into 5 groups control (saline), valproic acid (75 mg/kg), berberine (10 mg/kg), berberine (20 mg/kg), and berberine (30 mg/kg). Each contains proestrus, estrus, metestrus, and diestrus. Then, each group followed the i.p. administration of saline or vehicle intraperitoneal administration of PTZ (80 mg/kg). Then, initiation time of myoclonic seizures (ITMS), initiation time of tonic–clonic seizures (ITTS), and seizure duration (SD) were recorded. According to the results, berberine (20 and 30 mg/kg) significantly increased the ITTS and ITMS during various phases of the estrous cycle compared to the controls (P < 0.05). Seizure duration significantly decreased using berberine (20 and 30 mg/kg) compared to the controls (P < 0.05). Berberine (20 and 30 mg/kg) significantly increased the onset of ITMS and ITTS in metestrus and diestrus compared to proestrus and estrus (P < 0.05). Findings suggested that berberine has anticonvulsant effects in the model of PTZ rats, and it was more prominent during the luteal phase than the follicular phase. [ABSTRACT FROM AUTHOR]

Face stability control of excavation with earth pressure balance machine (EPB) approach is the best available method to reduce the ground deformation and settlement of surface structures in a tunneling project in urban areas. In the present paper, several models have proposed through a statistical method, including feed-forward stepwise regression (FSR) and machine learning techniques such as support vector machine (SVM), Takagi–Sugeno fuzzy model (TS), and multilayer perceptron neural network (ANN-MLP), to provide a predictive strategy for EPB machine during the tunnel excavation. For this purpose, a monitoring dataset of machine performance parameters including advance speed, screw conveyor speed, screw conveyor torque, thrust force, and cutterhead rotation speed from Tehran Metro Line 6 Southern Extension Sector (TML6-SE) has been compiled. Then, the relation between the performance parameters and target values were investigated to analyze the available inputs and offer a new equation using the FSR. Moreover, evaluation metrics and loss functions were utilized for the evaluation of the developed models' efficiency. The results proved the significance of the presented methods in this paper that could be used to predict the earth pressure balance operation with high efficiency. Highlights: A robust database was generated and analyzed through daily operating records, TBM data logger, and statistical analysis. Novel equation was formulated to predict the earth pressure balance for EPB-TBM by considering various operating parameter of boring machine. The predictive capabilities of machine learning, neural network, and fuzzy algorithm in estimating earth pressure balance were explored. A comprehensive evaluation was conducted to compare and contrast the empirical and ML outcomes. The accuracy of the models was examined using multiple loss functions and evaluation metrics. [ABSTRACT FROM AUTHOR]

Text clustering is used in various applications of text analysis. In the clustering process, the employed document representation method has a significant impact on the results. Some popular document representation methods cannot effectively maintain the proximity information of the documents or suffer from low interpretability. Although the concept-based representation methods overcome these challenges to some extent, the existing semi-supervised document clustering methods rarely use this type of document representation. In this paper, we propose a concept-based semi-supervised framework for document clustering that uses both labeled and unlabeled data to yield a higher clustering quality. Concepts are composed of a set of semantically similar words. We propose the notion of semi-supervised concepts to benefit from document labels in extracting more relevant concepts. We also propose a new method of clustering documents based on the weights of such concepts. In the first and second steps of the proposed framework, the documents are represented based on the concepts extracted from the set of embedded words in the corpus. The proposed representation is interpretable and preserves the proximity information of documents. In the third step, the semi-supervised hierarchical clustering process utilizes unlabeled data to capture the overall structure of the clusters, and the supervision of a small number of labeled documents to adjust the cluster centroids. The use of concept vectors improves the process of merging clusters in the hierarchical clustering approach. The proposed framework is evaluated using the Reuters, 20-NewsGroups and WebKB text collections, and the results reveal the superiority of the proposed framework compared to several existing semi-supervised and unsupervised clustering approaches. [ABSTRACT FROM AUTHOR]

This study aimed to investigate the effect of microgravity and light spectral composition on DNA methylation levels and the expression of genes responsible for secondary metabolism in Physalis alkekengi. Seedlings were exposed to the microgravity treatments under two different light conditions, including white and red + blue (R + B). The microgravity treatments were more capable of rapidly influencing growth performance than the light spectrum quality. The microgravity treatment up-regulated the expression of the 7-sterol Δ7 reductase (DWF5) gene. The highest expression of 4–1-deoxy-d-xylulose-5-phosphate reductoisomerase (DXR) gene was recorded in the microgravity-treated seedlings grown under the white conditions. Microgravity treatment and R + B irradiation synergistically stimulated the 3–1-deoxy-d-xylulose-5-phosphate synthase 2 (DXS2) gene. The expression pattern of the 1-hydroxy-3-methylglutaryl coenzyme A reductase (HMGR) and 2-sterol C-7,8 isomerase (HYD1) genes was similar to that of the DXS2 gene. The transcription of the mevalonate kinase (MK) gene was slightly changed in response to the microgravity and light composition. In the microgravity-treated seedlings, the 5-squalene synthase (SQS) gene displayed a similar upward trend, whereas the R + B radiation conditions contributed to the slight down-regulation of this gene. The microgravity factor was more effective in generating epigenetic responses in terms of DNA methylation than the light spectrum quality. However, light conditions affected the molecular responses of the plant to the microgravity factor. The microgravity treatment under both radiation conditions also increased the concentration of soluble phenols and proline in leaves. These findings refer to the high efficacy of simulated microgravity conditions to up-regulate the secondary metabolism in medicinal plants. [ABSTRACT FROM AUTHOR]

Highlights: Engineering Fe-N4 electronic structure with adjacent Co-N2C2 and Co sub-nanoclusters to optimize the electronic structure of the Fe-N4 active center is first demonstrated. Electrochemical studies reveal that the amorphous carbon corrosion leads to significantly increased charge- and mass-transport resistances. The operando X-ray absorption spectroscopy allows an investigation of the effect of highly oxidative environments on electrochemical behavior. Regulating the local configuration of atomically dispersed transition-metal atom catalysts is the key to oxygen electrocatalysis performance enhancement. Unlike the previously reported single-atom or dual-atom configurations, we designed a new type of binary-atom catalyst, through engineering Fe-N4 electronic structure with adjacent Co-N2C2 and nitrogen-coordinated Co nanoclusters, as oxygen electrocatalysts. The resultant optimized electronic structure of the Fe-N4 active center favors the binding capability of intermediates and enhances oxygen reduction reaction (ORR) activity in both alkaline and acid conditions. In addition, anchoring M–N–C atomic sites on highly graphitized carbon supports guarantees of efficient charge- and mass-transports, and escorts the high bifunctional catalytic activity of the entire catalyst. Further, through the combination of electrochemical studies and in-situ X-ray absorption spectroscopy analyses, the ORR degradation mechanisms under highly oxidative conditions during oxygen evolution reaction processes were revealed. This work developed a new binary-atom catalyst and systematically investigates the effect of highly oxidative environments on ORR electrochemical behavior. It demonstrates the strategy for facilitating oxygen electrocatalytic activity and stability of the atomically dispersed M–N–C catalysts. [ABSTRACT FROM AUTHOR]

Dasatinib is an anticancer drug that treats acute lymphoblastic leukemia, chronic myelogenous leukemia, and prostate cancer with several side effects. In this research, we suggest nanoparticle-modified screen-printed electrodes (SPCEs) as disposable electrochemical sensors for fast quantification of dasatinib in pharmaceutical formulations. Carbon nanotubes, single-walled carbon nanotubes (SWCNT), graphene, and graphene oxide-modified SPCEs were characterized by scanning electron microscopy. The study also recommends SWCNT-modified SPCEs as the best-performing electrode for determining dasatinib, demonstrating an excellent boosting effect on the oxidation response of dasatinib. This was accomplished using the square-wave voltammetry method. After optimization of the pH condition, pH 5.0 Britton–Robinson buffer, SWCNT-modified SPCEs demonstrated 94% recovery with optimum electro-oxidation activity. The oxidation currents exhibited linear relation with dasatinib concentration in the 0.1–100 µM. Based on the results, a limit of detection of 0.06 µM was obtained in the standard solution. The SWCNT-modified SPCEs have been applied to analyze dasatinib in pharmaceutical tablet samples. The demonstrated performance beats all comparable standard analytical tools and presumably may be used for general drug quantitation in pharmaceutical tablets. [ABSTRACT FROM AUTHOR]

Background: Diabetic retinopathy (DR) is one of the most common causes of vision loss worldwide; however, the limited access of the majority of the population to ophthalmologists and the lack of awareness among patients highlight the important role of family physicians in diagnosing this problem. This study aimed to determine the accuracy of direct ophthalmoscopy for DR screening by family physicians. Method: In this cross-sectional study, 121 patients were examined by three groups of physicians using direct ophthalmoscopy. Each of the two first groups (A and B) consisted of four family physicians who received written instructions and educational software regarding DR diagnosis, with group A also receiving a 2-h in-person class. The third group included four ophthalmologists (O). Based on the severity of diagnosis, results were compared with standard diagnosis provided by a retina fellow student. Results: Sensitivity of groups A, B, and O was calculated as 59%, 51%, and 78%, respectively. The specificity of the groups was also measured as 75.6%, 86.5%, and 80.0%, respectively. The study groups did not demonstrate a significant difference in regard to diagnostic parameters (p > 0.05). An additional analysis was conducted, only focusing on the diagnosis of severe DR, where the specificity of all groups improved. Still, no significant difference was observed between groups (p > 0.05). Conclusion: This was the first study investigating the role of family physicians in DR screening in Iran. The results indicated that trained family physicians could be reliable enough for diagnosing DR with the help of a direct ophthalmoscope. They can be used as a part of a referral protocol in deprived areas where access to an ophthalmologist is difficult. [ABSTRACT FROM AUTHOR]

Background and objectives: Skin conditions in humans can be challenging to diagnose. Skin cancer manifests itself without warning. In the future, these illnesses, which have been an issue for many, will be identified and treated. With the rapid expansion of big data healthcare framework summarization and precise prediction in early stage skin cancer diagnosis, the fuzzy AHP technique produces the best results in both of these fields. Big data is a potent technology that enhances the standard of research and generates better results more rapidly. This essay gives a way to group the stages of skin cancer treatment based on this information. The combination of support vector machine multi-class classification and fuzzy selector with radial basis function-based binary migration classification of virtual machines is put through a number of experiments. The connections have been categorized. Analysis method: These examinations have determined whether the tumors are malignant or benign and how malignant they are. The images of spots on the skin acquired from laboratory images make up the data set used for processing. We have talked about how to handle and process large datasets in the area of classification using MATLAB, like skin spot images. Findings: Our technique outperforms competing approaches by maintaining stability even as the size of the data set grows rapidly and with little error. In comparison to other methods, the suggested approach meets the accuracy criterion for correct classifications with a score of 90.86%. As a result, the proposed solution is viewed as a potentially useful tool for identifying mass stages and categorizing skin cancer severity. [ABSTRACT FROM AUTHOR]

Urological cancers have obtained much attention in recent years due to their mortality and morbidity. The most common and malignant tumor of urological cancers is prostate cancer that imposes high socioeconomic costs on public life and androgen-deprivation therapy, surgery, and combination of chemotherapy and radiotherapy are employed in its treatment. PI3K/Akt signaling is an oncogenic pathway responsible for migration, proliferation and drug resistance in various cancers. In the present review, the role of PI3K/Akt signaling in prostate cancer progression is highlighted. The activation of PI3K/Akt signaling occurs in prostate cancer, while PTEN as inhibitor of PI3K/Akt shows down-regulation. Stimulation of PI3K/Akt signaling promotes survival of prostate tumor cells and prevents apoptosis. The cell cycle progression and proliferation rate of prostate tumor cells increase by PI3K/Akt signaling induction. PI3K/Akt signaling stimulates EMT and enhances metastasis of prostate tumor cells. Silencing PI3K/Akt signaling impairs growth and metastasis of prostate tumor cells. Activation of PI3K/Akt signaling mediates drug resistance and reduces radio-sensitivity of prostate tumor cells. Anti-tumor compounds suppress PI3K/Akt signaling in impairing prostate tumor progression. Furthermore, upstream regulators such as miRNAs, lncRNAs and circRNAs regulate PI3K/Akt signaling and it has clinical implications for prostate cancer patients. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate the changes in macular blood flow after cataract surgery through optical coherence tomography angiography (OCT-A). Methods: In this prospective case series, 50 patients who underwent uncomplicated cataract surgery by the resident were included. OCT-A images and complete ocular examinations were performed at baseline, 1 and 3 months postoperatively. The changes in OCT-A parameters including foveal avascular zone (FAZ) area, vessel density (VD) of superficial and deep plexus, and central macular thickness were assessed before and after surgery. Cataract grading, intraocular inflammation, and duration of surgery were analyzed. Results: FAZ was significantly reduced from 0.36 ± 0.13 mm2 at baseline to 0.32 ± 0.12 mm2 at month 1 (P < 0.001) and this reduction continued until month 3. In the superficial layer, vessel density of the fovea, parafovea, and whole image significantly increased from 13.9 ± 6.8, 43.7 ± 4.7, and 43.2 ± 4.4 at baseline to 18.4 ± 7.9, 45.7 ± 4.9, and 44.9 ± 4.5 at month 1. The increase in the vessel density of the deep layer was similar to the superficial layer. Accordingly, CMT at the fovea was significantly increased from 240.5 ± 21.99 µm at baseline to 253.1 ± 23.2 microns at month 1 (P < 0.001) and the increase significantly continued and reached 259.5 ± 22.6 µm at month 3 (P < 0.001). Accordingly, the FAZ area significantly reduced one month postoperatively. In regression analysis, CMT changes positively correlated with cataract grading. FAZ area negatively correlated with intraocular inflammation on the first postoperative day. Conclusion: The present study shows that CMT and vessel density of the macula significantly increase after uncomplicated cataract surgery, while the FAZ area reduces. Postoperative inflammation could be the possible explanation for the findings of this study. [ABSTRACT FROM AUTHOR]

The aim of this study was to design a predictive radiobiological model of normal brain tissue in low-grade glioma following radiotherapy based on imaging and molecular biomarkers. Fifteen patients with primary brain tumors prospectively participated in this study and underwent radiation therapy. Magnetic resonance imaging (MRI) was obtained from the patients, including T1- and T2-weighted imaging and diffusion tensor imaging (DTI), and a generalized equivalent dose (gEUD) was calculated. The radiobiological model of the normal tissue complication probability (NTCP) was performed using the variables gEUD; axial diffusivity (AD) and radial diffusivity (RD) of the corpus callosum; and serum protein S100B by univariate and multivariate logistic regression XLIIIrd Sir Peter Freyer Memorial Lecture and Surgical Symposium (2018). Changes in AD, RD, and S100B from baseline up to the 6 months after treatment had an increasing trend and were significant in some time points (P-value < 0.05). The model resulting from RD changes in the 6 months after treatment was significantly more predictable of necrosis than other univariate models. The bivariate model combining RD changes in Gy40 dose-volume and gEUD, as well as the trivariate model obtained using gEUD, RD, and S100B, had a higher predictive value among multivariate models at the sixth month of the treatment. Changes in RD diffusion indices and in serum protein S100B value were used in the early-delayed stage as reliable biomarkers for predicting late-delayed damage (necrosis) caused by radiation in the corpus callosum. Current findings could pave the way for intervention therapies to delay the severity of damage to white matter structures, minimize cognitive impairment, and improve the quality of life of patients with low-grade glioma. [ABSTRACT FROM AUTHOR]

Crocin is the main bioactive components of the saffron which has positive role in the nervous system; however, its neuroprotective activity is not fully elicited. So, the aim of the current study was to determine effects of the crocin on reflexive motor and anti-depressive behaviors as well as serum and brain tissue antioxidant activities in cuprizone-induced (CPZ) model of multiple sclerosis (MS) mice. Forty male C57BL/6 mice were randomly assigned into 4 groups. Mice in the control group were received normal diet. In group 2, mice received normal diet and orally received crocin (100 mg/kg) 3 times per week for 5 weeks. In group 3, CPZ-induced demyelination was done by chew palate containing 0.2% (w/w) CPZ for 5 weeks. In group 4, mice feed CPZ containing diet and orally received crocin (100 mg/kg) three times per for 5 weeks. After determination of the MS signs, reflexive motor behavior and depressive tests were done. Also, serum and brain tissue antioxidant activity was determined. According to the data, CPZ had negative effects on hind-limb foot angle, hind- and front-limb suspension, surface righting, grip strength, and negative geotaxis while crocin improved it. Co-administration of the CPZ + crocin reversed effect of the CPZ on the reflexive motor behaviors. CPZ increased immobility time in the forced swimming test (FST) and tail suspension test (TST), while co-administration of the CPZ + crocin reversed effect of the CPZ on immobility time. CPZ decreased number of cross in open field test (OFT) and spending time on rotarod, while co-administration of the CPZ + crocin reversed effect of the CPZ. Malondialdehyde (MDA) production increased, and glutathione peroxidase (GPx), superoxide dismutase (SOD), and total antioxidant status (TAS) levels decreased in serum and brain tissue of the mice treated with CPZ. Pretreatment with crocin decreased adverse effect of the CPZ on serum and brain tissue antioxidants. These results suggested crocin has protective effect against CPZ-induced MS in mice. [ABSTRACT FROM AUTHOR]

The Kighal porphyry Cu deposit, in the Arasbaran magmatic belt (AMB), is hosted by Late Eocene to Oligocene volcanic rocks and Miocene high–K calc–alkaline subvolcanic intrusions. The Miocene quartz monzonite stocks host porphyry–style Cu mineralization characterized by potassic, phyllic, argillic, and propylitic alteration zones and an advanced argillic lithocap. The Ar–Ar dating of secondary biotite from the potassic alteration and alunite from the lithocap yields precise ages of 20.10 ± 0.18 Ma and 19.15 ± 0.21 Ma, respectively, documenting the evolution of the hydrothermal system over ~ 1 Myr. Hydrothermal rutile occurs in the deposit from the proximal potassic to distal propylitic alteration zones, and their Ti–Fe–Cr–V–W contents can be used as a fertility indicator which suggests a decrease from the proximal zones towards the distal zones. The geochemical fingerprints of the Kighal (and in general the AMB) igneous rocks reflect a post–collisional arc setting. Their distinctly high Th/Yb and Ta/Yb ratios are typical of high–K calc–alkaline intrusions, suggesting that their parental melts were derived from an enriched upper mantle source modified by slab–derived components. Their 87Sr/86Sr(i) (0.70427 to 0.70452) and 143Nd/144Nd(i) (0.512712 to 0.512754) ratios reveal that the magmas experienced moderate crustal assimilation during their magmatic evolution, also supported by increasing Th/La and 87Sr/86Sr(i) and decreasing εNd(i) values with increasing SiO2 content. The 206Pb/204Pb, 207Pb/204Pb, and 208Pb/204Pb ratios of the intrusions (18.67 to 18.84, 15.60 to 15.66, and 38.83 to 39.06, respectively) reveal a crustal origin. Hence, a post–collisional arc setting is proposed for NW Iran, in which mantle–derived mafic melts underwent a MASH process and ascended into shallow magma chambers in the upper crust associated with moderate crustal contamination, which account for the formation of large–scale porphyry Cu mineralization in the AMB. [ABSTRACT FROM AUTHOR]

Hackberry (Celtisaustralis L.) is native to the Mediterranean region and is distributed in Europe, Turkey, North Africa, and Iran. To the best of our knowledge, no study has been conducted on C.australis L. in the Arasbaran region, Iran. In the present study, total phenol (TP), flavonoid (TF), antioxidant capacity based on DPPH and FRAP assays and phenolic compounds and sugars profiles were investigated. According to the results, the range of antioxidant capacity based on DPPH and FRAP assays was 14.12–88.24% and 44.35–117.87 mg Fe2+/100 g, respectively. Also, the range of gallic acid, caffeic acid, chlorogenic acid, rutin, p-coumaric acid, rosmaric acid, cinnamic acid, and apigenin content was 2.59–26.32, 2.03–9.32, 0.94–11.35, 1.80–4.857, 2.32–9.52, 4.74–51.38, 0.18–2.10 and 0.27–1.37 mg/g, respectively. The results of factor analysis showed that the C12, C14, C15, C20, C8, C16, C3, and C20 genotypes are positively characterized by the first principal component (PCA1) that have a higher caffeic acid, chlorogenic acid, rutin, p-coumaric acid, rosmaric acid, quercetin, cinnamic acid, and apigenin phenolic compounds. Based on cluster analysis, the twenty genotypes were located in 2 main clusters. In general, the obtained results can be useful for breeding programs and the introduction of cultivars in Celtisaustralis L. [ABSTRACT FROM AUTHOR]

In this paper, a novel method is proposed to detect common abnormalities in Wireless Capsule Endoscopy (WCE) video frames including Lymphoid Hyperplasia, ulcer, and angiodysplasia lesions. Inspecting WCE video frames to detect abnormality is a tedious task for physicians. One important step in the proposed approach is to extract the region of interest (ROI), i.e., suspicious region, using the expectation–maximization (EM) algorithm. Suspicious regions in WCE frames are segmented using the EM algorithm considering the color and texture information of the image. Then, suitable descriptors associated with the shape, texture, and color of ROIs are examined for further analysis. These descriptors include histogram of gradients for shape, local binary patterns for texture and different statistical characteristics from pixel values for color information. These features are then fed to a support-vector machine for classification. The results show that the proposed approach can detect abnormalities in WCE frames with the accuracy of 91.3%. [ABSTRACT FROM AUTHOR]

In this study, the impact of Fe3O4 nanoparticles (NPs) at different concentrations was studied on physiology, antioxidant enzymes, cell damage, and secondary metabolites of Physalis alkekengi seedlings under in vitro conditions. Seeds were grown on a solid MS medium containing different Fe3O4 NPs concentrations (0, 10, 20, and 30 mg/L). The results showed that Fe3O4 NP at 20 mg/L increased growth (fresh and dry weight, length of shoot and root, and the number of adventitious roots) and physiological (relative water content, chlorophyll pigments, carotenoid, carbohydrate, H2O2, and ion leakage) parameters through stimulation of protein content and antioxidant enzyme activities of catalase (CAT), superoxide dismutase (SOD), and ascorbate peroxidase. Fe3O4 NP at 20 mg/L was found to be the optimum concentration for enhancing secondary metabolites (total flavonoids, phenolics, and withanolides) and activity of DPPH radical scavenging and PAL, while the higher Fe3O4 NPs concentration (30 mg/L) showed toxicity impact on growth parameters through promoting H2O2 level, lipoxygenase activity, and ion leakage and inactivation of the antioxidant enzyme isoforms. The electrophoretic pattern displayed Fe3O4 NPs at 30 mg/L decreased the band intensity of SOD (Mn-SOD and Cu/Zn-SOD1) and CAT (CAT1 and 2) isoforms. These findings display that the optimal dose of Fe3O4 NPs (20 mg/L) acts as an elicitor to induce antioxidant functions of P. alkekengi cell system to suppress oxidative damage. [ABSTRACT FROM AUTHOR]

The aim of this paper is solving an intuitionistic fuzzy multi-objective linear programming problem containing intuitionistic fuzzy parameters, intuitionistic fuzzy maximization/minimization, and intuitionistic fuzzy constraints. To do this, a linear ranking function is used to convert the intuitionistic fuzzy parameters to crisp ones first. Then, linear membership and non-membership functions are used to manipulate intuitionistic fuzzy maximization/minimization and intuitionistic fuzzy constraints. Then, a multi-objective optimization problem is formulated containing maximization of membership functions and minimization of non-membership functions. To solve this problem, the minimax and weighted sum methods are used. Then, the described procedure is summarized as an algorithm to solve the problem, and a numerical example is solved by the proposed method. Finally, to investigate the capability and performance of the model, a supplier selection problem, which is one of the important applications in supply chain management, is solved by the proposed algorithm. [ABSTRACT FROM AUTHOR]