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Pandemics and political responses to them can bring about short- and long-term economic and environmental effects. This paper aimed to understand the effects of a pandemic and the policy responses to it on Iran's economy and environmental conditions using a Bayesian dynamic stochastic general equilibrium model. The results suggested that a pandemic can decrease the value of macroeconomic variables. In the health sector, a pandemic reduces health capital stock, thereby increasing quarantine hours and household health expenditures. Following an increase in quarantine hours and a decrease in economic activities, air pollution decreases, causing a short-term improvement in the quality of the environment. Moreover, an increase in public health expenditure during a pandemic leads to an accelerated convergence of economic and environmental variables into a steady state. Considering that the positive environmental effects of the outbreak of an infectious disease are short-term, and since industrialization is necessary for economic growth, it is recommended that in order to achieve sustainable development, we should move toward energy-efficient industries and clean fuels and technologies. [ABSTRACT FROM AUTHOR]

The synthesis and characterization of metal complexes have garnered significant attention due to their versatile applications in scientific and biomedical fields. In this research, two novel copper (Cu) complexes, [Cu(L)(L′)(H2O)2] (1) and [Cu(L)(Im)H2O] (2), where L = pyridine-2,6-dicarboxylic acid, L′ = 2,4-diamino-6-hydroxypyrimidine, and Im = imidazole, were investigated concerning their sonochemical synthesis, spectroscopic analysis, and biological activity. The complexes' structural characterization was achieved using analytical techniques, including single-crystal X-ray structure determination, FTIR, PXRD, TGA and DTA, SEM, TEM, and EDS. Complex (1) displayed a six-coordinated Cu2+ ion, while complex (2) exhibited a five-coordinated Cu2+ ion. The crystal structures revealed monoclinic (C2/c) and triclinic (P-1) space groups, respectively. Both complexes showcased zero-dimensional (0D) supramolecular networks, primarily driven by hydrogen bonding and π–π stacking interactions, which played pivotal roles in stabilizing the structures and shaping the unique supramolecular architecture. Both complexes demonstrated significant antioxidant activity, suggesting their capability to neutralize free radicals and mitigate oxidative stress-related diseases. Hemolysis percentages were less than 2%, per the ASTM F756-00 standard, indicating non-hemolytic behavior. Low cytotoxicity was observed against fibroblast and MCF-7 cell lines. They do not exhibit antibacterial activity against Escherichia coli and Staphylococcus aureus. These findings suggest that the synthesized Cu2+‒complexes hold considerable promise for applications in drug delivery and cancer treatment. This research contributes to the advancement of supramolecular chemistry and the development of multifunctional materials for diverse scientific and medical applications. [ABSTRACT FROM AUTHOR]

Scene classification and recognition have always been one of the most challenging tasks of scene understanding due to the inherent ambiguity in visual scenes. The core of scene classification and recognition tasks is scene representation. Deep learning advances in computer vision, especially deep CNNs, have significantly improved scene representation in the last decade. Deep convolutional features extracted from deep CNNs provide discriminative representations of the images and are widely used in various computer vision tasks, such as scene classification. Deep convolutional features capture the appearance characteristics of the image and the spatial information about different image regions. Meanwhile, the semantic and context information obtained from high-level concepts about scene images, such as objects and their relationships, can significantly contribute to identifying scene images. Therefore, in this paper, we divide visual scenes into two categories, object-based and layout-based. Object-based scenes are scenes that have scene-specific objects and, based on those objects, can be described and identified. In contrast, the layout-based scenes do not have scene-specific objects and are described and identified based on the appearance and layout of the image. This paper proposes a new neural network model for representing and classifying visual scenes, which we call G-CNN (GNN-CNN). The proposed model includes two modules, feature extraction and feature fusion, and the feature extraction module composes of visual and semantic branches. The visual branch is responsible for extracting deep CNN features from the image, and the semantic branch is responsible for extracting semantic GNN features from the scene graph corresponding to the image. The feature fusion module is a novel two-stream neural network that fuses the CNN and GNN feature vectors to produce a comprehensive representation of the scene image. Finally, a fully-connected classifier classified the obtained comprehensive feature vector into one of the pre-defined categories. The proposed model has been evaluated on three benchmark scene datasets, UIUC Sports, MIT67, and SUN397, and obtained classification accuracy of 99.91%, 96.01%, and 85.32%, respectively. In addition, a new dataset named Scene40, which has been introduced in our previous paper, is also used for further evaluation of the proposed method. The comparison results based on classification accuracy criteria show that the proposed model can outperform the best previous methods on three benchmark scene datasets. [ABSTRACT FROM AUTHOR]

Deploying virtual machines poses a significant challenge for cloud data centers, requiring careful consideration of various objectives such as minimizing energy consumption, resource wastage, ensuring load balancing, and meeting service level agreements. While researchers have explored multi-objective methods to tackle virtual machine placement, evaluating potential solutions remains complex in such scenarios. In this paper, we introduce two novel multi-objective algorithms tailored to address this challenge. The VMPMFuzzyORL method employs reinforcement learning for virtual machine placement, with candidate solutions assessed using a fuzzy system. While practical, incorporating fuzzy systems introduces notable runtime overhead. To mitigate this, we propose MRRL, an alternative approach involving initial virtual machine clustering using the k-means algorithm, followed by optimized placement utilizing a customized reinforcement learning strategy with multiple reward signals. Extensive simulations highlight the significant advantages of these approaches over existing techniques, particularly energy efficiency, resource utilization, load balancing, and overall execution time. [ABSTRACT FROM AUTHOR]

Efficient virtual machine (VM) placement is vital for optimizing the performance of cloud data centers. While recent studies have addressed this challenge, many have overlooked the heterogeneity of cloud environments and the importance of scalability. This paper introduces a novel multi-objective algorithm designed specifically for VM placement in heterogeneous and large-scale cloud data centers. Our approach leverages the K-means algorithm to group VMs based on demand characteristics. Subsequently, a multi-reward reinforcement learning algorithm is employed to allocate these VMs to physical hosts. Despite its simplicity, the proposed method demonstrates exceptional efficiency. Simulation results reveal that our approach significantly outperforms established algorithms such as GMPR, GRVMP, FFD, NSGA-II, RLVMP, and BFD. Key performance metrics include the number of active devices, energy consumption, resource utilization (CPU and memory), VM migrations, and adherence to service level agreements, highlighting the superiority of our method. [ABSTRACT FROM AUTHOR]

In the digital era, there has been a growing focus on seeking online academic help-seeking as an effective factor for success in the virtual learning environment. However, the Social Networking Self-efficacy (SNS) and social presence of students in online learning environments remain underexplored. This study employed a structural model to investigate the relationship between students' SNS, academic help-seeking, and social presence, as well as the mediating role of academic help-seeking between these two factors. The research design was quantitative, using a descriptive and correlational approach. Data were collected from 339 students at an Iranian university in Hamedan and analyzed using structural equation modeling. The findings indicated that SNS had both direct and indirect influences on social presence, through academic help-seeking. Additionally, academic help-seeking was found to impact social presence, thus mediating the relationship between SNS and social presence. Therefore, educators and policy-makers should consider the role of academic help-seeking and SNS to enhance social presence. [ABSTRACT FROM AUTHOR]

In this paper, using a new technique from harmonic analysis called sparse domination, we characterize the positive Borel measures including forward, vanishing, and reverse Bergman Carleson measures. In the case of forward and vanishing Bergman Carleson measures, our results extend the results of [J Funct Anal 280(6):26, 2021] from 1 ⩽ p ⩽ q < 2 p to all 0 < p ⩽ q < ∞ . In a more general case, we characterize the positive Borel measures μ on B so that the radial differentiation operator R k : A ω p (B) → L q (B , μ) is bounded and compact. Although we consider the weighted Bergman spaces induced by two-side doubling weights, the results are new even on classical weighted Bergman spaces. [ABSTRACT FROM AUTHOR]

Many types of gynecological cancer (GC) are often silent until they reach an advanced stage, and are therefore often diagnosed too late for effective treatment. Hence, there is a real need for more efficient diagnosis and treatment for patients with GC. During recent years, researchers have increasingly studied the impact of microRNAs cancer development, leading to a number of applications in detection and treatment. MicroRNAs are a particular group of tiny RNA molecules that regulate regular gene expression by affecting the translation process. The downregulation of numerous miRNAs has been observed in human malignancies. Let-7 is an example of a miRNA that controls cellular processes as well as signaling cascades to affect post-transcriptional gene expression. Recent research supports the hypothesis that enhancing let-7 expression in those cancers where it is downregulated may be a potential treatment option. Exosomes are tiny vesicles that move through body fluids and can include components like miRNAs (including let-7) that are important for communication between cells. Studies proved that exosomes are able to enhance tumor growth, angiogenesis, chemoresistance, metastasis, and immune evasion, thus suggesting their importance in GC management. Impact of let-7 on female malignancies and diseases of the female reproductive tract. Let-7 expression is dysregulated in a variety of gynaecological and obstetric disorders. [ABSTRACT FROM AUTHOR]

In recent years, spiking neural networks (SNNs) have gained popularity as a biologically plausible and energy-efficient alternative to artificial neural networks. Unlike non-spiking networks, SNNs use asynchronous, scattered pulses to communicate between spiking neurons, making them suitable for portable systems with limited hardware and energy resources. In this paper, we propose a feed-forward spiking neural network (SNN) with two spiking convolutional layers, one spiking classification layer, and a single non-spiking leaky integrator for readout. This network uses reverse pixel values and a type of time encoding known as constant-current-leaky integrate and fire (LIF) coding. Here, for the first time, the idea of adjusting the threshold voltage parameter of network neurons and inverting input images is introduced to improve recognition accuracy. We demonstrate that decreasing the threshold voltage parameter below its default voltage and optimizing input images by inverting pixel values can improve the recognition accuracy of the network. Using this approach, we test the network on the popular MNIST and Fashion-MNIST benchmarks, achieving test accuracies of 99.28% and 90.43%, respectively. We also test our approach on models from several studies and different datasets to prove its validity and generality. Results show that our proposed approach is effective in improving recognition accuracy compared to the initial accuracies of the models. [ABSTRACT FROM AUTHOR]

Enzymes have become important tools in many industries. However, the full exploitation of their potential is currently limited by a lack of efficient and cost-effective methods for enzyme purification from microbial production. One technology that could solve this problem is foam fractionation. In this study, we show that diverse natural foam-stabilizing proteins fused as F-Tags to β-lactamase, penicillin G acylase, and formate dehydrogenase, respectively, are able to mediate foaming and recovery of the enzymes by foam fractionation. The catalytic activity of all three candidates is largely preserved. Under appropriate fractionation conditions, especially when a wash buffer is used, some F-Tags also allow nearly complete separation of the target enzyme from a contaminating protein. We found that a larger distance between the F-Tag and the target enzyme has a positive effect on the maintenance of catalytic activity. However, we did not identify any particular sequence motifs or physical parameters that influenced performance as an F-tag. The best results were obtained with a short helical F-Tag, which was originally intended to serve only as a linker sequence. The findings of the study suggest that the development of molecular tags that enable the establishment of surfactant-free foam fractionation for enzyme workup is a promising method. Key points: • Foam-stabilizing proteins mediate activity-preserving foam fractionation of enzymes • Performance as an F-Tag is not restricted to particular structural motifs • Separation from untagged protein benefits from low foam stability and foam washings [ABSTRACT FROM AUTHOR]

Tetracycline has a robust structure that is difficult to remove from groundwater systems and can cause various side effects on human health. This study aimed to remove tetracycline by incorporating tungsten and copper intermediate metals onto the surface of g-C3N4. The two-dimensional heterogeneous composite was synthesized by degrading melamine through heat and then modified with tungsten and copper. The structure of g-C3N4/WO3/CuO was characterized using various methods, including XRD, mapping, EDS, SEM, and FTIR. The study also investigated parameters that could potentially affect the removal of tetracycline, such as pH, time, g-C3N4/WO3/CuO, temperature, and tetracycline concentration. SEM images and EDS analysis confirmed the presence of WO3, CuO, and C loaded onto the surface of g-C3N4/WO3/CuO, forming the g-C3N4 structure. Tungsten and copper doping in this form facilitated the removal of tetracycline under optimal conditions (tetracycline concentration = 10.0 mg/L, time = 20 min, g-C3N4/WO3/CuO dosage = 200 mg, pH = 4.0 at 25 °C), achieving a removal rate of up to 98%. The addition of tungsten and copper atoms to the g-C3N4 structure enhanced its photocatalytic and electrocatalytic efficiency in removing tetracycline. [ABSTRACT FROM AUTHOR]

The process of remapping virtual machines (VMs) to host machines (HMs), which is defined as VM replacement, affects cloud data centers (DCs) performance. To enhance the performance, optimal replacement of VMs regarding conflicting objectives has been proposed in some research, most of which use the non-dominance method to compare generated solutions. Although the non-dominance approach reaches acceptable results, it is not desirable in the VM replacement problem since we need only one mapping of VMs to HMs as the optimal solution to this problem. Indeed, in this method, a solution is considered better if it outperforms another solution regarding all parameters otherwise, two solutions are considered equally good. Also, a solution can be better even though it demonstrates poor performance regarding some parameters. In this paper, we propose two enhanced multi-objective algorithms, Fuzzy-RLVMrB and Fuzzy-MOVMrB, to address the mentioned problems of the non-dominance algorithm. The proposed algorithms aim to balance the horizontal and vertical load between PMs in terms of processor, bandwidth, and memory. We simulated all algorithms using the CloudSim simulator and compared them in terms of horizontal and vertical load balance, energy consumption, and execution time. The simulation results depict that Fuzzy-RLVMrB and Fuzzy-MOVMrB algorithms outperform other algorithms in terms of vertical load balancing and horizontal load balancing. In addition, Fuzzy-RLVMrB surpasses other approaches in terms of energy consumption. [ABSTRACT FROM AUTHOR]

Purpose: To characterize delivery features and explore effectiveness of telehealth-based cancer rehabilitation interventions that address disability in adult cancer survivors. Methods: A systematic review of electronic databases (CINAHL Plus, Cochrane Library: Database of Systematic Reviews, Embase, National Health Service's Health Technology Assessment, PubMed, Scopus, Web of Science) was conducted in December 2019 and updated in April 2021. Results: Searches identified 3,499 unique studies. Sixty-eight studies met inclusion criteria. There were 81 unique interventions across included studies. Interventions were primarily delivered post-treatment and lasted an average of 16.5 weeks (SD = 13.1). They were most frequently delivered using telephone calls (59%), administered delivered by nursing professionals (35%), and delivered in a one-on-one format (88%). Risk of bias of included studies was primarily moderate to high. Included studies captured 55 measures of disability. Only 54% of reported outcomes had data that allowed calculation of effect sizes ranging -3.58 to 15.66. Conclusions: The analyses suggest small effects of telehealth-based cancer interventions on disability, though the heterogeneity seen in the measurement of disability makes it hard to draw firm conclusions. Further research using more diverse samples, common measures of disability, and pragmatic study designs is needed to advance telehealth in cancer rehabilitation. Implications for Cancer Survivors: Telehealth-based cancer rehabilitation interventions have the potential to increase access to care designed to reduce disability across the cancer care continuum. [ABSTRACT FROM AUTHOR]

Cumin (Cuminum cyminum L.) is one of the valuable medicinal plants that is cultivated in arid and semi-arid regions of Iran. This study aimed to investigate the effects of humic acid and seaweed extract under drought stress on the seed yield, essential oil yield and physiological characteristics of cumin in the Yasouj region, Iran, from 2019 to 2020. The experiment followed a split-plot factorial design based on a completely randomized block design with three replications, during two years. The three studied factors were three irrigation regimes: irrigation after 30% (control), 70% (moderate drought stress), and 90% (severe drought stress), of soil moisture consumption, two levels of humic acid (0 and 300 mg/L), and two levels of seaweed extract consumption (0 and 2%). The results indicated that under severe drought stress, there was a significant decrease in seed yield and essential oil yield by 32 and 10.9% compared to the control, respectively. The results of the present study revealed that both humic acid and seaweed extract factors had a positive impact on seed yield and essential oil yield when applied individually. However, the combined foliar spraying of seaweed extract (2%) and humic acid (300 mg/L) proved to be the most effective treatment in mitigating the adverse effects of drought stress. This improvement was attributed to enhanced physiological parameters such as total chlorophyll, total chlorophyll a, total chlorophyll b, proline accumulation, and antioxidant activity (peroxidase and catalase). This study emphasizes the potential role of humic acid and seaweed extract as effective strategies for alleviating the adverse effects of drought stress on cumin plants, particularly in areas where drought poses a significant challenge. [ABSTRACT FROM AUTHOR]

Burn injuries are among the common traumatic injuries, which can be accompanied with lifelong morbidity and mortality. The Lethal Area Fifty Percent (LA50) index is another reliable outcome measurement tool that assesses the standard of medical care at burn centers. It is widely used as a benchmark for assessing the quality of burn care and is considered the percentage at which 50% of burn patients are expected to die because of burn-related injuries. We aimed to determine and compare the LA50 in burn patients admitted to Shiraz Burn Referral Centers in 2018–2021 and 2011–2018 with regard to improving the quality of special care and infection control in the new hospital. We conducted a retrospective cohort analysis on patients admitted to Amir al-Momenin Burn Injury Hospital in Shiraz, Fars, Southern Iran. Data were retrospectively gathered from March 2011 to January 2022, and subsequently analyzed with standard statistical analysis, and also multivariate and probability analysis. A total of 7382 patients with acute burns injuries were identified. Among them, 4852 (65.7%) patients were men, and the median age was 27 years [Q1–Q3 7–40; range 1–98]. Most of the patients were in the pediatric and early adulthood age range, with 76.2% being younger than 40 years old. The median TBSA was 24% [IQR 14, 43], and the median duration of hospitalization was 11 [IQR 11] days. Most injuries were secondary to flame and fire (33.5%; n = 2472). The mortality rate in our study was 19.0% (n = 1403). We evaluated our patients based on two main time intervals: March 2011 till February 2018 (n = 3409; 46.2%), and March 2018 to January 2022 (n = 3973; 53.8%). Based on multivariate analysis, the second interval of our study was significantly correlated with a more female patients, higher age, lower TBSA, less burn injuries due to scald, contact, but more frequent fire and flame injuries, and also lower mortality rate. Factors correlated with higher mortality included male gender, older age, shorter hospitalization duration, higher TBSA, etiology of fire and flame, and accidental burn injuries. A Baux score of 76.5 had a sensitivity of 81.1%, specificity of 87.3%, accuracy of 86.1% in predicting mortality among our patients. The mortality probability for the study intervals were 20.67% (SD 33.0%) for 2011–2018, and 17.02% (SD 29.9%) for 2018–2022 (P < 0.001). The LA50 was 52.15 ± 2 for all patients. This ammount was 50 ± 2% in 2011–2018, and 54 ± 2 in 2018–2022 (P < 0.001). The mean LA50 values showed significant improvements following significant modifications in our critical care for burn victims, including augmented intensive care unit capacity, prompt relocation of inhalation burn cases to the intensive care unit, establishing a well-trained multidisciplinary team, and improved infection control. To improve outcomes for burn patients in developing countries, major changes should be made in the management of burn patients and LA50 is a reliable assessment tool for evaluating the how these changes affect patient's outcomes. [ABSTRACT FROM AUTHOR]

Adsorbents such as carbon-based materials, metal oxides, and metal-organic framework composites have been studied in recent years to remove toxic heavy metal ions from wastewater and water. Each of these adsorbents has a series of disadvantages, including that some cannot desorbed and reactivated, some have a complex production process and also powder materials cannot be well separated from the water after adsorption. Thus, the goal of this research is to create a new adsorbent based on a polymer nanocomposite made of resorcinol-formaldehyde (RF) aerogel and hydroxyapatite (HA) nanoparticles. To accomplish this, RF aerogels were prepared using the Pekala method with varying resorcinol to catalyst (R/C) ratios, and then HA filler in various concentrations was loaded into the aerogel. According to the results, the maximum surface area was obtained at R/C = 100, and the greatest adsorption occurred at pH = 7. With increasing contact time, the amount of metal ions adsorbed increased and could reach equilibrium in 48 h. The isotherm data were also examined using the Langmuir and Freundlich models. This study found that RF aerogels with HA nanoparticles can be used as a highly effective adsorbent to remove heavy metal ions from aqueous solutions. Highlights: Resorcinol-formaldehyde and HA were combined to develop a novel aerogel. Nanocomposite aerogel was mechanically strength due to the HA nanofillers. BET surface area was optimized according to resorcinol to catalyst ratio. Adsorption of metal ions increased with increasing contact time. Langmuir and Freundlich models were used to analyze the isotherm results. [ABSTRACT FROM AUTHOR]

In this work, the mesoporous magnetic heterogeneous catalyst was synthesized by anchoring copper (II) onto the nitrogen-rich poly (melamine) Schiff base networks magnetic nanocomposite. First, MNP (Fe3O4@SiO2) was functionalized with chlorosilane (CPTS). Then, the chlorine of these functionalized magnetic nanoparticles could react with the –NH2 groups of the melamine through a nucleophilic substitution reaction. Simultaneously, the condensation polymerization of melamine and benzene-1, 3, 5-tricarbaldehyde was carried out in the presence of surface-modified magnetic nanoparticles. Later, Fourier-transform infrared spectroscopy (FT-IR), X-ray diffraction (XRD), thermogravimetric analysis (TGA), transmission electron microscopy (TEM), scanning electron microscopy (SEM), atomic absorption spectroscopy (AAS), Brunauer–Emmett–Teller surface analysis (BET), and energy dispersive analysis were deployed to characterize the catalyst. The results of the AAS measurement showed that the copper ion loading on the mesoporous nitrogen-rich supported catalyst was about 0.82 mmol g−1. The synthesized nanocomposite was used as a catalyst and shows excellent activity in the three-component coupling reaction of amines, carbon disulfide, and boronic acids. In the presence of 70 mg of the catalyst, a wide range of functionalized dithiocarbamates were synthesized leading to excellent yields. Moreover, this MNP@SNWMe@Cu catalyst was easily recovered and reused seven times without significant loss of its activity. The results of this research exhibited that the synthesized catalyst functioned with high catalytic activity in this reaction. [ABSTRACT FROM AUTHOR]

Aflatoxins (AFs), an important category of pollutants, are formed in many foods and adversely affect human health. Therefore, their determination is critical to ensuring human food health. An efficient dispersive solid-phase microextraction technique was developed as a simple and straightforward sample preparation technique for determination of four aflatoxins using a high-performance liquid chromatography (HPLC) fluorescence detector. A novel efficient, green sorbent for extracting AFs was synthesized based on hydrothermal and chemical strategies. The amounts of three sorbent components were optimized using a mixture design (simplex lattice design), including 14 experiments. The optimal amount of amino-bimetallic Fe/Ni-MIL-53 nanospheres, chitosan, and magnetic Fe3O4 nanoparticles as sorbent components was 0.87, 0.67, and 0.47 g, respectively. Also, various factors affecting the process of AF determination were studied and optimized in two successive experimental designs, including the definitive screening design and the Box–Behnken design. Under optimal conditions, the linear ranges for measuring aflatoxin B1, aflatoxin B2, aflatoxin G1, and aflatoxin G2 were 0.05–82.6, 0.07–86.4, 0.08–85.7, and 0.07–89.5 ng mL−1, respectively. The relative standard deviations under inter-day and intra-day conditions for measuring AFs at three analyte concentrations were determined in triplicate analysis and were in the ranges of 3.7–4.6% and 4.9–6.1% for water sample analysis, respectively. The qualitative detection limits for determining AFs were between 0.01 and 0.05 ng mL−1. The pre-concentration factor of the method for measuring AFs ranged from 739.7 to 802.1. The proposed method was used for determining AFs in several real samples, including herbal distillate, black tea, corn, and real water samples. The relative recovery and standard deviation were 87.8–97.8% and 4.10–6.82%, respectively. [ABSTRACT FROM AUTHOR]

The design and application of multiple tools to map soil micronutrients is key to efficient land management. While collecting a representative number of soil samples is time consuming and expensive, digital soil mapping could provide maps of soil properties fast and reliably. The objective of this research was to predict the spatial distribution of soil micronutrients within the piedmont plain in northeastern Iran using random forest (RF) and support vector regression (SVR) algorithms. Sixty-eight locations with different land uses were sampled to determine the content of iron, manganese, zinc and copper in the topsoil (0–20 cm). Forty-one digital covariates were used as input to the models and were derived from a digital elevation model, open-source remote sensing (RS) data (Landsat 8 OLI and Sentinel 2A MSI images), WorldClim climate database and maps of soil properties. Covariates were grouped into 11 scenarios: I–III, based on RS data; IV–VI, including RS, topographic, climate and soil covariates; VII, VIII and IX, based only on topographic, climate and soil covariates, respectively; X and XI, based on recursive feature elimination and expert opinion, respectively. The RF algorithm gave 91, 94, 91 and 108% normalized root mean squared error values for iron, manganese, zinc and copper, respectively, for the validation dataset with scenario XI. The most important digital covariates for micronutrients prediction with both RF and SVR models were precipitation seasonality, mean annual temperature and the mean saturation index based on Sentinel 2A MSI data. Digital maps produced at 30 m spatial resolution using scenario XI could be used to effectively identify micronutrient deficiencies and excess hotspots. [ABSTRACT FROM AUTHOR]

To reach antibacterial decorative faucets with gold color as a controlling parameter, TiCuN thin films containing different amounts of copper (Cu), namely 0.24%, 0.51%, and 1.78%, were prepared on the brass alloy. These different Cu contents were reached by applying various amount of titanium (Ti) and deposition time. The combination of magnetron sputtering and cathode arc deposition physical vapor deposition methods (PVD) in a single chamber was used to fabricate these layers. XRD, XPS, EDS, and FE-SEM analyses were applied to explore physical and chemical properties, and antibacterial tests were used to study the efficiency of modification at different times (1 h, 6 h, and 24 h). The results indicate that all samples benefit from nanoparticle size (20–50 nm), and Cu contact boosts the antibacterial rate. The model with copper content of 1.78% has the best and most stable antibacterial activity against Staphylococcus aureus and Escherichia coli (99.9% after 6 h). [ABSTRACT FROM AUTHOR]

The rapid development of internet of things (IoT) gadgets and the increase in the rate of sending requests from these devices to cloud data centers resulted in congestion and consequently service provisioning delays in the cloud data centers. Accordingly, fog computing emerged as a new computing model to address this challenge. In fogging, services are provisioned at the edge of the network using devices with computing and storage capabilities, which are located through the way to connect IoT devices to cloud data centers. Fog computing aims to alleviate the computing load in data centers and cut the delay of requests down, notably real-time and delay-sensitive requests. To achieve these goals, vitally important challenges such as scheduling requests, balancing the load, and reducing energy consumption, which affects performance and reliability in the edge-fog-cloud computing architecture, should be considered into account. In this paper, a reinforcement learning fog scheduling algorithm is proposed to address these challenges. The experimental results indicate that the proposed algorithm raises the load balance and diminishes the response time compared to the existing scheduling algorithms. Additionally, the proposed algorithm outperforms other approaches in terms of the number of used devices. [ABSTRACT FROM AUTHOR]

Klebsiella pneumoniae is an opportunistic bacterium, which is globally recognized for its high prevalence and antimicrobial resistance (AMR). Biofilm-forming capability, susceptibility testing, and phenotypic confirmatory test for extended-spectrum beta-lactamase (ESBL)-producing isolate recognition of 104 K. pneumoniae isolates were performed according to the Clinical Laboratory Standard Institute (CLSI) guidelines. The prevalence of ESBL-associated genes bla-VIM, bla-NDM, and bla-OXA-48, as well as biofilm-associated genes luxS, fimH1, wza, and mrkD, was determined by multiplex PCR. The highest resistance rate was against ampicillin (100.0%). Among the 104 K. pneumoniae isolates, 52 (50.0%) and 31 (29.8%) isolates were determined as multi- and extensively drug resistant (MDR, XDR), respectively. Moreover, 21 (40.4%) isolates were determined as ESBL producing. Among 50 biofilm-producing K. pneumoniae isolates, 7 (14.0%), 15 (30.0%), and 28 (56.0%) isolates exhibited high, moderate, and weak levels of biofilm formation, respectively. A number of 41 (78.8%) isolates were susceptible to colistin, and 10 (19.2%) were resistant. AMR was significantly higher (P < 0.05) in the biofilm-forming isolates compared with non-biofilm formers. [ABSTRACT FROM AUTHOR]

Inorganic hole-transport materials (HTMs) such as copper indium disulfide (CIS) have been applied in perovskite solar cells (PSCs) to improve the poor stability of the conventional Spiro-based PSCs. However, CIS-PSCs' main drawback is their lower efficiency than Spiro-PSCs. In this work, copolymer-templated TiO2 (CT-TiO2) structures have been used as an electron transfer layer (ETL) to improve the photocurrent density and efficiency of CIS-PSCs. Compared to the conventional random porous TiO2 ETLs, copolymer-templated TiO2 ETLs with a lower refractive index improve the transmittance of input light into the cell and therefore enhance the photovoltaic performance. Interestingly, a large number of surface hydroxyl groups on the CT-TiO2 induce a self-healing effect in perovskite. Thus, they provide superior stability in CIS-PSC. The fabricated CIS-PSC presents a conversion efficiency of 11.08% (Jsc = 23.35 mA/cm2, Voc = 0.995, and FF = 0.477) with a device area of 0.09 cm2 under 100 mW/cm2. Moreover, these unsealed CIS-PSCs retained 100% of their performance after aging tests for 90 days under ambient conditions and even increased from 11.08 to 11.27 over time due to self-healing properties. [ABSTRACT FROM AUTHOR]

Pandemics are not new, but they continue to prevail in the last three decades. A variety of reasons such as globalization, trade growth, urbanization, human behavior change, and the rise of the prevalence of viral diseases among animals can account for this issue. Outbreaks of COVID-19 indicated that viral diseases have spread easily among nations, influencing their economic stability. In this vein, the motivation behind the present study was to get an understanding of the effect of the rise of the health disaster risk on the dynamics of Iran's macroeconomic variables by using Bayesian Dynamic Stochastic General Equilibrium. As opposed to Computable General Equilibrium models, DSGE models can be evaluated in a stochastic environment. Since the duration of the virus outbreak and its effect on the economy is not known, it is more appropriate to use these models. The results demonstrated that increased health disaster risk has a remarkable negative effect on macroeconomic variables. According to the findings of the research and the significance of public vaccination as an essential solution for improving health status and quality of life, it was suggested that the government pave the path for the thriving of businesses and socio-economic activities as early as possible by employing specific policies such as tax exemption or budget allocation for vaccine manufacturing companies or importers. [ABSTRACT FROM AUTHOR]

Visual scene understanding is a hot and challenging topic in image processing that aims to understand the general (global) concept of a scene image. In this paper, we propose a novel image embedding algorithm using a learned embedded space, which introduces a high-level semantic representation of the scene images. The learned embedded space as a suitable semantic framework for visual concepts can be used in most applications such as image captioning, Visual Question Answering (VQA), and scene recognition or classification. Inspired by the human inference mechanism in visual scene understanding, the proposed method learns a semantic embedded space of visual concepts using prior semantic knowledge. Prior knowledge is extracted from ConceptNet as one of the most comprehensive knowledge graphs in the form of semantic vectors and is transformed to the learned embedded space with a transformation function. The transformation function is learned by solving a minimization problem. To evaluate our proposed approach, we introduce a scene image dataset called "Scene23", which is based on the VisualGenome dataset. A non-linear SVM classifier is utilized to classify the representations of images to the scene categories. The experimental results show 99.44% classification accuracy on the "Scene23" dataset. Also, we evaluated our proposed method by the "UIUC Sports" and "MIT67" datasets. Experimental results indicate that our proposed method outperforms other state-of-the-art methods on the "UIUC Sports" dataset and achieves competitive results on the "MIT67" dataset. [ABSTRACT FROM AUTHOR]

The COVID-19 continues to take its toll on human life. Even though to a less threatening extent, and insignificant to some, noise turns out to be one of its consequences without consensus. While individuals experience multiple restrictions and restrain from exuberant activities by spending most of their time at home, reducing public transportation and personal vehicles, overall, they end up reduce anthropogenic noise pressure. On another level, people continue reporting noise concerns at various degrees during the COVID-19 pandemic. To draw a bigger picture as to whether or not these complaints have increased during the COVID-19 compared to the same period last year, this research examines them in five major American cities: New York, Chicago, San Francisco, Phoenix, and Dallas. Furthermore, the study also assessed the complaint patterns, whether reported in compact or sprawled areas. The findings highlight that either the noise complaints increased or decreased during the COVID-19 crisis. Accordingly, four of the five selected cities, except San Francisco, showed a decrease in reported noise. As it turns out, compact developments correlate significantly and positively with noise complaints in all study areas, except in Phoenix. These findings call for regulating and prioritizing noise-related policies. Planners and urban designers can thus advise to sustain environmental planning and public health issues, especially in planning compact developments. [ABSTRACT FROM AUTHOR]

We study the composition operators on certain weighted Hilbert spaces H ω , consisting of analytic functions defined on D , that can be described as a weighted Dirichlet space with weight ω having certain properties. We will use the notion of vanishing ω -Carleson measure to characterize the compact composition operators on H ω . Also, we give some upper and lower estimates for the essential norm of these operators and investigate the Hilbert-Schmidt composition operators. [ABSTRACT FROM AUTHOR]

When faced with predatory threats, escape towards shelter is an adaptive action that offers long-term protection against the attacker. Animals rely on knowledge of safe locations in the environment to instinctively execute rapid shelter-directed escape actions1,2. Although previous work has identified neural mechanisms of escape initiation3,4, it is not known how the escape circuit incorporates spatial information to execute rapid flights along the most efficient route to shelter. Here we show that the mouse retrosplenial cortex (RSP) and superior colliculus (SC) form a circuit that encodes the shelter-direction vector and is specifically required for accurately orienting to shelter during escape. Shelter direction is encoded in RSP and SC neurons in egocentric coordinates and SC shelter-direction tuning depends on RSP activity. Inactivation of the RSP–SC pathway disrupts the orientation to shelter and causes escapes away from the optimal shelter-directed route, but does not lead to generic deficits in orientation or spatial navigation. We find that the RSP and SC are monosynaptically connected and form a feedforward lateral inhibition microcircuit that strongly drives the inhibitory collicular network because of higher RSP input convergence and synaptic integration efficiency in inhibitory SC neurons. This results in broad shelter-direction tuning in inhibitory SC neurons and sharply tuned excitatory SC neurons. These findings are recapitulated by a biologically constrained spiking network model in which RSP input to the local SC recurrent ring architecture generates a circular shelter-direction map. We propose that this RSP–SC circuit might be specialized for generating collicular representations of memorized spatial goals that are readily accessible to the motor system during escape, or more broadly, during navigation when the goal must be reached as fast as possible.The retrosplenial cortex and superior colliculus of mouse form a neural circuit that specifically encodes shelter location, facilitating rapid escape from predatory threats. [ABSTRACT FROM AUTHOR]

The CRISPR/Cas9 technique is easily programmable, fast, more powerful, and efficient at generating a mutation compared to previous gene therapy methods. β-thalassemia is the most common autosomal recessive disorder worldwide. Appropriate genomic changes in the β gene can be modified to alleviate the symptoms of the disease using the CRISPR/Cas9 system. PubMed/Medline, Scopus, Web of Science, and SID databases were searched in Persian and English from February 2000 to September 2022. Finally, 39 articles had inclusion criteria which were reviewed by two separate individuals. Among the reviewed articles, articles were divided into three categories. In the first group, studies attemped to increase the expression of γ-globin and production of hemoglobin F. The strategy of second group of studies were the reduction of the α-globin chain to prevent hemolysis of RBCs by accumulation of excessive α-globins. The third group corrected the mutations causing β-thalassemia. Studies have shown that the genome of β-thalassemia patients can be modified using the CRISPR/Cas9 technique, and this approach might be promising for the treatment of β-thalassemia. [ABSTRACT FROM AUTHOR]

Amirkalayeh Wetland, listed as wetlands of International Importance in the Ramsar Convention, exposes to severe water quality stress resulted from increase in dissolved ions and nutrients concentrations. In addition to in situ measurements of physicochemical parameters (electrical conductivity, pH, and temperature), a total number of 28 water samples were collected from Amirkalayeh Wetland and surrounding surface and groundwater resources to investigate the most important factors increasing trophic state and decreasing the water quality of the wetland. Water samples were analyzed for major ions and dissolved plant nutrients (nitrate, nitrite, ammonium, and phosphate). Up to three-time increase in salinity and dramatic rising in nutrients level was observed in Amirkalayeh Wetland from 2017 to 2021. The excessive nutrients intake resulted in hyper-eutrophication trophic status of Amirkalayeh Wetland. Our hydrological, hydrochemical, and statistical studies investigating the role of a variety of possible water quality degrading factors show that surface and subsurface drainage of agricultural return water into the Amirkalayeh Wetland are the major cause of increase in trophic level and decreasing water quality. Results of this work indicate that Amirkalayeh Wetland is exposed to severe water quality stress that threatens the aquatic life and ecosystem of this wetland. Therefore, preventing the inflow of surface and subsurface agricultural drains to the wetland and providing a sustainable water management plan are vital to improve water quality of the wetland. [ABSTRACT FROM AUTHOR]

Peptides are reducing and capping agents that can be used for the synthesis of biocompatible metal nanoparticles under relatively mild conditions. However, the abundance of random and inactive amino acid sequences in peptides, the lack of peptide design rules have led to their studies being slow and make it difficult to use them. In this study, calcitonin-capped Au nanoparticles were synthesized by a simple and controlled method. The aim of this study was to determine the cytotoxicity of calcitonin-capped Au nanoparticles on the human breast cancer cells (MCF-7) and osteoblast cell lines (G292). The absorbance of calcitonin-capped Au nanoparticles is higher than bare AuNPs. FTIR analysis revealed that amino acides of present in calcitonin played dual roles as reducing and stabilizing agents during synthesis of AuNPs. TEM image analysis showed formation of predominantly spherical calcitonin-capped Au nanoparticles with mean particle diameter of about 2–20 nm. The interactions between the calcitonin-capped Au nanoparticles and calf thymus DNA in aqueous was studied by circular dichroism (CD), UV–Vis and fluorescence spectroscopy. The results indicated that the synthesized calcitonin-capped Au nanoparticles can successfully insert into calf thymus DNA. [L]1/2, concentrations of calcitonin-capped Au nanoparticles in the midpoint of transition, 0.32085 mM and o.28744 mM and the apparent binding constant (K × 104(M)−1), 79.52 and 81.04 were obtained at 300 and 310 K, respectively. The cytotoxicity of the prepared calcitonin-capped Au nanoparticles was measured on the human breast cancer cells (MCF-7) and osteoblast cell lines (G292) by cell viability (MTT assay) and apoptosis (TUNEL assay: Terminal deoxynucleotidyl transferase dUTP nick end labeling). According to the MTT assay, the CC50 values of calcitonin-capped Au nanoparticles and cisplatin are 12.7 μM and 8.3 μM, respectively in G292 which are very near to each other compared on MCF-7. Therefore, TUNEL assay was done on G292 cell lines. The results showed that apoptosis was obviously observable by 48% DNA fragmentation on G292 cell lines. Therefore, the calcitonin-capped Au nanoparticles are suitable drugs which have strong potential in DNA denaturation and apoptosis especially on osteoblast cell lines (G292). [ABSTRACT FROM AUTHOR]

Atomic devices such as atomic clocks and optically-pumped magnetometers rely on the interrogation of atoms contained in a cell whose inner content has to meet high standards of purity and accuracy. Glass-blowing techniques and craftsmanship have evolved over many decades to achieve such standards in macroscopic vapor cells. With the emergence of chip-scale atomic devices, the need for miniaturization and mass fabrication has led to the adoption of microfabrication techniques to make millimeter-scale vapor cells. However, many shortcomings remain and no process has been able to match the quality and versatility of glass-blown cells. Here, we introduce a novel approach to structure, fill and seal microfabricated vapor cells inspired from the century-old approach of glass-blowing, through opening and closing single-use zero-leak microfabricated valves. These valves are actuated exclusively by laser, and operate in the same way as the "make-seals" and "break-seals" found in the filling apparatus of traditional cells. Such structures are employed to fill cesium vapor cells at the wafer-level. The make-seal structure consists of a glass membrane that can be locally heated and deflected to seal a microchannel. The break-seal is obtained by breaching a silicon wall between cavities. This new approach allows adapting processes previously restricted to glass-blown cells. It can also be extended to vacuum microelectronics and vacuum-packaging of micro-electro-mechanical systems (MEMS) devices. [ABSTRACT FROM AUTHOR]

Objectives: Type 1 diabetes mellitus (T1DM) is a well-known autoimmune disease, characterized by β-cell destruction in pancreas islet cells, which results insulin deficiency and subsequent hyperglycemic sequelae. While there is screening for type 2 DM that leads to better glycemic control and outcome, the majority of T1DM patients are diagnosed when much of the pancreatic cells and their function are disturbed. The aim of this article is to present an overview of the effective factors in the positivity of Glutamic acid decarboxylase antibody)GADA(and identifying the high-risk individuals for T1DM. Methods: We searched English literature available at National Library of Medicine via PubMed, and Google Scholar through December 2020. Finally, 79 papers have been included in the study. Studies were summarized based on the number of positive autoantibodies and onset of T1DM over time and GADA correlation with different variables. Conclusions: GADA is an easy marker to measure that can be detected many months prior to the clinical presentation and remains positive even after early childhood. [ABSTRACT FROM AUTHOR]

Playgrounds are not only for play and fun; they are places that offer diverse experiences for all groups of children. Outdoor playgrounds have been studied as an element of public space for their ability to offer an array of amenities and attributes. In addition to design and planning aspects, inclusiveness is a vital attribute of playgrounds. Inclusiveness within playgrounds provides accessibility for all children regardless of age, gender, and ethnicity, as both physical and social access are considered. Given the rapidly changing global agenda affected dramatically by the COVID-19 pandemic and Black Lives Matter movement, playgrounds have gained even more attention and the importance of inclusiveness has become more prevalent. This study examined the inclusiveness of play-based experiences within a playground in San Antonio, Texas, using mixed methods. The study utilized observational methods, behavior mapping, secondary data for spatial mapping, and a survey conducted in order to understand the perception of playground users. This study evaluated the inclusiveness of the playground and analyzed social and physical accessibility relative to the playground by assessing the diversity of users in terms of age, gender, ethnicity, and disability. The findings of this study show that there is a need for additional studies yielding proposed improvements revolving around playground inclusivity. The study results show that urban designers, urban planners, and policymakers need to collaborate in order to create opportunities that work to eliminate social and physical disparities and that ultimately enhance inclusiveness in playgrounds. [ABSTRACT FROM AUTHOR]

In this study, the design, performance, and characteristics of a low-temperature argon plasma jet with cascading electrode technique (APJCE) are presented. APJCE is designed based on a tip-ring structure with a cascading ring. The effect of plasma jet driven by repetitive high-voltage microsecond pulses in APJCE structure was measured qualitatively in local surface temperature detection system. Then, by applying the generated plasma jet to biological surface and measuring and characterizing the electrical parameters, we obtained a plasma jet, which is electrically and thermally in the cold plasma regime. Simulation of the electric field distribution in the nozzle also yielded similar results to the experimental results. Finally, by cascading electrodes, we guided the plasma column to the nozzle output so that the plasma temperature within four centimeters of the nozzle output is 37 °C. The resulting plasma jets were studied by atomic emission spectroscopy and the intensity of the spectral lines of the atmospheric argon plasma jet spectra was obtained as a final experimental result at the output. [ABSTRACT FROM AUTHOR]

Sedimentation is almost a serious problem for reservoir dams due to loss of storage, malfunction of bottom intakes, corrosion, and damage to power generators, increased flood risk, water quality degradation, and other environmental degradation problems. There are some methods of sediment removal from the reservoir, such as dredging and flushing. The above techniques are not feasible for all reservoirs due to high cost and low efficiency. In this paper, a new sediment extractor referred hereafter as Dam-Type Sediment Excluder (DTSE) is introduced. The self-cleaning DTSE excludes suspended sediment from the river flow upstream of the reservoir and then bypasses the river downstream of the reservoir. The efficiency of the proposed DTSE was examined under different excluding flow rates, opening heights, inlet flow Froude numbers, and sediment concentrations. This research also investigates the influence of suspended- sediment concentration profile on the model efficiency. The results indicate that the efficiency of the DTSE is highly sensitive to the flow velocity and the middle intake location and height. The maximum extracted efficiency of the model was found to be about 40%, while the average optimal efficiency was 26%. [ABSTRACT FROM AUTHOR]

Plastics and their degradation products, microplastics (MPs), are ubiquitous in the environment, and urban and industrial soils may be the most polluted soils by this type of pollution. There is scarce information addressing human exposure to MPs from urban and industrial soils. This study assesses MP pollution in urban and industrial soils of two county capital cities in Iran, i.e. Abadan and Khorramshahr. The concentration of MPs ranged from 17 MPs/100 g industrial soil to 347 MPs/100 g urban soil, with a mean abundance of 122 MPs/100 g soil. Residential areas were the most contaminated by MPs among all the sampling sites. There, microfiber MPs, red and black, were the most abundant MPs, and it was also the case across sampling sites. Polyethylene terephthalate and polypropylene were the most common polymers among the investigated MPs, while nylon and polystyrene MPs were also present. Regarding MP sizes, those in the fraction 250–500 µm prevailed across all investigated sites. Estimated exposures to MPs through contact with the urban and industrial soils, for a normal scenario according to US EPA parameters, would lead to a daily intake < 1 MP for both adult and children, and their respective yearly intake of MPs is estimated in 6–127 and 12–253 MPs. Further research is needed to assess the health impact of current MP types and levels found in urban soil. [ABSTRACT FROM AUTHOR]

Herein, poly (acrylic acid) (PAA) microgels were synthesized via alcohol type cross-linked by a free radical precipitation polymerization approach. At the first time, 1,6-hexanediol (1–6 diol), trimethylolpropane (TMP), and pentaerythritol (PEN) were selected as multifunctional cross- linking agent to synthesize cross-linked poly(acrylic acid) microgels. Alcohol type cross-linking agents can connect the PAA chains. The cross-linking reaction takes place due to reaction between hydroxyl groups of various cross-linkers and carboxyl groups of PAA chains. All of the hydroxyl groups do not participate in the reaction with acid groups of polymer chains through the polymerization stage; therefore, unreacted hydroxyl groups will react through sample drying (post-curing stage). The influence of cross-linker functionality and its concentration on various properties like swelling capacity, gel content, Tg (glass transition temperature), and rheological behavior were examined. The PAA microgels prepared via this cross-linking approach were compared to properties of microgels synthesized by epoxy type and vinyl type cross-linking agents in the previous studies. As a result, synthesized microgels via novel mechanisms have higher properties (for example, rheological and thermal properties) than that of PAA microgels prepared via the conventional mechanism. These behaviors can be due to decreasing Mc ¯ (average molecular weight of two successive cross-links) in the polymeric network by utilizing new cross-linkers. [ABSTRACT FROM AUTHOR]

Automatic brain tumor segmentation in magnetic resonance images (MRIs) is an essential stage for treatment planning. However, MR image segmentation is challenging owing to non-uniformity in the intensity distribution, tumor shape, size, and location variation. The paper proposes a new level set method that is called Fuzzy Kernel Level Set (FKLS) for 3D brain tumor segmentation in MR images. To avoid computational complexity, fast bounding box based on symmetry analysis is used to extract the volume of interest (VOI) in brain MRIs. Then, a level set method is proposed based on fuzzy c-means clustering and kernel mapping. A kernel function is used to transfer the image into another domain, where the new proposed functional is minimized. To assess the proposed FKLS method, a synthetic image and natural brain MR images from BraTS 2017 are segmented. Experimental results show that our method is superior to the state-of-the-art segmentation methods regarding the segmentation accuracy based on Dice, Jaccard, Sensitivity, and Specificity metrics. The mean values of these metrics are 97.62% ± (0.94%), 95.41% ± (1.8%), 98.79% ± (0.63%), and 99.85% ± (0.09%), respectively. [ABSTRACT FROM AUTHOR]

This study investigated the prevalence of Clostridioides difficile by culture, multiplex polymerase chain reaction (M-PCR), and loop mediated isothermal amplification (LAMP) in patients with suspected C. difficile infections (CDIs). Also, the results of three methods were compared. All stool specimens collected from CDI suspected patients were cultured on selective C. difficile cycloserine-cefoxitin fructose agar and incubated in an anaerobic jar up to 7 days. The bacterial isolates were identified using standard tests. Multiplex-PCR (M-PCR) was performed for detection of tcdA, tcdB, and tpi genes. The LAMP assay was performed to detect the tcdB gene of C. difficile. C. difficile was isolated from 20.0% (n = 10/50) of samples by culture. M-PCR showed that 34.0% (n = 17/50) of the specimens were positive for C. difficile based on the presence of tpi gene. Out of the 17 C. difficile, 13 strains (76.0%) were positive for tcdB gene using M-PCR. However, the LAMP assay showed that 30.0% (15/50) of specimens were positive for the presence of tcdB gene. M-PCR and LAMP methods showed 100.0% sensitivity compared to the culture method. However, the specificity of the LAMP (87.5%) was relatively higher than the M-PCR (82.5%) compared to the culture. Based on the results of this study, the prevalence of toxigenic C. difficile strains was high in suspected CDI patients. So, the differentiation between toxigenic and non-toxigenic strains is necessary. Our data showed that the LAMP assay is a good method for direct detection of toxigenic C. difficile strains from stool specimens. [ABSTRACT FROM AUTHOR]

To investigate biostratigraphy of Albian sediments (Kazhdumi Formation) in the Zagros Basin, 280 samples in four sections were prepared which are nominated as Murshan-e-Bala, Fahliyan-e-Pain, Kupon and Tale-e-Afghani. Stratigraphic distribution of identified foraminifers confirms well developed orbitolinids which are associated with other Albian benthic foraminifers in all studied sections. The orbitolinids are recognized in surrounding strata [Dariyan (at the base which is marked by an oxidized zone) and Sarvak Formations (on the top, as gradtional contact)] as well as the Kazhdumi Formation. Obtained biostratigraphic data show that Early Albian is marked by the presence of Hemicyclammina sigali, which co-occurs with Mesorbitolina texana and Mesorbitolina subconcava, whereas Conicorbitolina conica and Meorbitolina parva support Late Albian age of the studied sections. Calcareous algae are associated with both benthic faunal assemblages. Albian planktons occur in the studied sections which are identified as Favusella washitensis and Calcisphaerula inomminata subzones. The stratigraphic position of planktons actually indicates vertical displacement in the sedimentary basin during Albian time. Other associated Albian pelagic foraminifera are identified which are obviously recognized in three sections of the Kazhdumi Formation. The presence of pelagic species in the study section of the Kazhdumi Formation indicates basement faulting during the Albian period. [ABSTRACT FROM AUTHOR]

In this paper, we study (uniformly) mean ergodic composition operators on H ∞ (B n) . Under some additional assumptions, it is shown that mean ergodic operators have norm convergent iterates in H ∞ (B n) , and that they are always uniformly mean ergodic. [ABSTRACT FROM AUTHOR]

Background: Lean NAFLD may differ from NAFLD found in overweight or obese patients. We used the UK biobank to conduct a cross-sectional study that examined features that distinguish lean NAFLD from overweight or obese NAFLD. Methods: MRI-PDFF data were used to identify patients with NAFLD, with NAFLD defined as PDFF ≥ 5%. BMI patient cohorts were identified, with lean defined as a BMI < 25, and overweight or obese defined as a BMI ≥ 25. Variables of interest to fatty liver disease, including single nucleotide polymorphisms, were chosen from the UK biobank data portal. Logistic regression was used to generate models predictive of NAFLD in each cohort. Results: 1007 patients had NAFLD, and of these, 871 had BMI ≥ 25, and 136 BMI < 25. Factors associated with NAFLD in patients with BMI < 25 included male sex, white blood cell count, red blood cell count, triglycerides, ALT, creatinine, visceral adipose tissue, rs58542926 T, and rs738409 G. In contrast, factors associated with NAFLD in patients with BMI ≥ 25 included male sex, waist circumference, HDL cholesterol, triglycerides, serum glucose, ALT, creatinine, urate, visceral adipose tissue, rs1260326 T, rs1044498 C, rs58542926 T, and rs738409 G. For lean patients, our generated prediction score had an AUC of 0.92, sensitivity of 0.90 and specificity of 0.81. For overweight or obese patients, the prediction score had an AUC of 0.86, sensitivity of 0.87 and specificity of 0.70. Conclusions: Our analysis suggests that lean and overweight or obese NAFLD are distinct entities. We have developed a risk score incorporating both clinical and genetic factors that accurately classify lean patients with NAFLD, with the potential to serve as a tool for screening purposes. [ABSTRACT FROM AUTHOR]

This work utilizes a realistic electro-optical coupled simulation to study the (i) impact of mesoporous TiO2 removal; (ii) the embedding of Ag@SiO2 and SiO2@Ag@SiO2 plasmonic nanoparticles; (iii) utilization of solution-processed inorganic p-type copper(I) thiocyanate (CuSCN) layer at the perovskite/carbon interface; and (iv) the increase of the work function of carbon electrodes (via incorporation of suitable additives/binders to the carbon ink) on the performance of carbon-based PSCs. Removal of mesoporous TiO2 increased the power conversion efficiency (PCE) of the device from 14.83 to 16.50% due to the increase in exciton generation rate and charge carriers' mobility in the vicinity of the perovskite-compact TiO2 interface. Subsequently, variable mass ratios of Ag@SiO2 and SiO2@Ag@SiO2 plasmonic nanoparticles are embedded in the vicinity of the perovskite-compact TiO2 interface. In the optimum cases, the PCE of the devices increased to 19.72% and 18.92%, respectively, due to light trapping, scattering, and strong plasmonic fields produced by the plasmonic nanoparticles. Furthermore, adding the CuSCN layer remarkably increased the PCE of the device with a 0.93% mass ratio of Ag@SiO2 nanoparticles from 19.72 to 26.58% by a significant improvement of Voc and FF, due to the proper interfacial energy band alignment and the reduction of the recombination current density. Similar results were obtained by increasing the carbon work function, and the cell PCE was enhanced up to 26% in the optimal scenario. Our results pave the way to achieve high efficiencies in remarkably stable printable carbon-based PSCs. [ABSTRACT FROM AUTHOR]

Deep learning's automatic feature extraction has been a revolutionary addition to computational drug discovery, infusing both the capabilities of learning abstract features and discovering complex molecular patterns via learning from molecular data. Since biological and chemical knowledge are necessary for overcoming the challenges of data curation, balancing, training, and evaluation, it is important for databases to contain information regarding the exact target and disease of each bioassay. The existing depositories such as PubChem or ChEMBL offer the screening data for millions of molecules against a variety of cells and targets, however, their bioassays contain complex biological descriptions which can hinder their usage by the machine learning community. In this work, a comprehensive disease and target-based dataset is collected from PubChem in order to facilitate and accelerate molecular machine learning for better drug discovery. MolData is one the largest efforts to date for democratizing the molecular machine learning, with roughly 170 million drug screening results from 1.4 million unique molecules assigned to specific diseases and targets. It also provides 30 unique categories of targets and diseases. Correlation analysis of the MolData bioassays unveils valuable information for drug repurposing for multiple diseases including cancer, metabolic disorders, and infectious diseases. Finally, we provide a benchmark of more than 30 models trained on each category using multitask learning. MolData aims to pave the way for computational drug discovery and accelerate the advancement of molecular artificial intelligence in a practical manner. The MolData benchmark data is available at https://GitHub.com/Transilico/MolData as well as within the additional files. [ABSTRACT FROM AUTHOR]