Amirkabir University of Technology

<h3>Importance</h3> Cancer and other noncommunicable diseases (NCDs) are now widely recognized as a threat to global development. The latest United Nations high-level meeting on NCDs reaffirmed this observation and also highlighted the slow progress in meeting the 2011 Political Declaration on the Prevention and Control of Noncommunicable Diseases and the third Sustainable Development Goal. Lack of situational analyses, priority setting, and budgeting have been identified as major obstacles in achieving these goals. All of these have in common that they require information on the local cancer epidemiology. The Global Burden of Disease (GBD) study is uniquely poised to provide these crucial data. <h3>Objective</h3> To describe cancer burden for 29 cancer groups in 195 countries from 1990 through 2017 to provide data needed for cancer control planning. <h3>Evidence Review</h3> We used the GBD study estimation methods to describe cancer incidence, mortality, years lived with disability, years of life lost, and disability-adjusted life-years (DALYs). Results are presented at the national level as well as by Socio-demographic Index (SDI), a composite indicator of income, educational attainment, and total fertility rate. We also analyzed the influence of the epidemiological vs the demographic transition on cancer incidence. <h3>Findings</h3> In 2017, there were 24.5 million incident cancer cases worldwide (16.8 million without nonmelanoma skin cancer [NMSC]) and 9.6 million cancer deaths. The majority of cancer DALYs came from years of life lost (97%), and only 3% came from years lived with disability. The odds of developing cancer were the lowest in the low SDI quintile (1 in 7) and the highest in the high SDI quintile (1 in 2) for both sexes. In 2017, the most common incident cancers in men were NMSC (4.3 million incident cases); tracheal, bronchus, and lung (TBL) cancer (1.5 million incident cases); and prostate cancer (1.3 million incident cases). The most common causes of cancer deaths and DALYs for men were TBL cancer (1.3 million deaths and 28.4 million DALYs), liver cancer (572 000 deaths and 15.2 million DALYs), and stomach cancer (542 000 deaths and 12.2 million DALYs). For women in 2017, the most common incident cancers were NMSC (3.3 million incident cases), breast cancer (1.9 million incident cases), and colorectal cancer (819 000 incident cases). The leading causes of cancer deaths and DALYs for women were breast cancer (601 000 deaths and 17.4 million DALYs), TBL cancer (596 000 deaths and 12.6 million DALYs), and colorectal cancer (414 000 deaths and 8.3 million DALYs). <h3>Conclusions and Relevance</h3> The national epidemiological profiles of cancer burden in the GBD study show large heterogeneities, which are a reflection of different exposures to risk factors, economic settings, lifestyles, and access to care and screening. The GBD study can be used by policy makers and other stakeholders to develop and improve national and local cancer control in order to achieve the global targets and improve equity in cancer care.

IMPORTANCE: The Global Burden of Diseases, Injuries, and Risk Factors Study 2019 (GBD 2019) provided systematic estimates of incidence, morbidity, and mortality to inform local and international efforts toward reducing cancer burden. OBJECTIVE: To estimate cancer burden and trends globally for 204 countries and territories and by Sociodemographic Index (SDI) quintiles from 2010 to 2019. EVIDENCE REVIEW: The GBD 2019 estimation methods were used to describe cancer incidence, mortality, years lived with disability, years of life lost, and disability-adjusted life years (DALYs) in 2019 and over the past decade. Estimates are also provided by quintiles of the SDI, a composite measure of educational attainment, income per capita, and total fertility rate for those younger than 25 years. Estimates include 95% uncertainty intervals (UIs). FINDINGS: In 2019, there were an estimated 23.6 million (95% UI, 22.2-24.9 million) new cancer cases (17.2 million when excluding nonmelanoma skin cancer) and 10.0 million (95% UI, 9.36-10.6 million) cancer deaths globally, with an estimated 250 million (235-264 million) DALYs due to cancer. Since 2010, these represented a 26.3% (95% UI, 20.3%-32.3%) increase in new cases, a 20.9% (95% UI, 14.2%-27.6%) increase in deaths, and a 16.0% (95% UI, 9.3%-22.8%) increase in DALYs. Among 22 groups of diseases and injuries in the GBD 2019 study, cancer was second only to cardiovascular diseases for the number of deaths, years of life lost, and DALYs globally in 2019. Cancer burden differed across SDI quintiles. The proportion of years lived with disability that contributed to DALYs increased with SDI, ranging from 1.4% (1.1%-1.8%) in the low SDI quintile to 5.7% (4.2%-7.1%) in the high SDI quintile. While the high SDI quintile had the highest number of new cases in 2019, the middle SDI quintile had the highest number of cancer deaths and DALYs. From 2010 to 2019, the largest percentage increase in the numbers of cases and deaths occurred in the low and low-middle SDI quintiles. CONCLUSIONS AND RELEVANCE: The results of this systematic analysis suggest that the global burden of cancer is substantial and growing, with burden differing by SDI. These results provide comprehensive and comparable estimates that can potentially inform efforts toward equitable cancer control around the world.

Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) have revolutionized the field of advanced robotics in recent years. AI, ML, and DL are transforming the field of advanced robotics, making robots more intelligent, efficient, and adaptable to complex tasks and environments. Some of the applications of AI, ML, and DL in advanced robotics include autonomous navigation, object recognition and manipulation, natural language processing, and predictive maintenance. These technologies are also being used in the development of collaborative robots (cobots) that can work alongside humans and adapt to changing environments and tasks. The AI, ML, and DL can be used in advanced transportation systems in order to provide safety, efficiency, and convenience to the passengers and transportation companies . Also, the AI, ML, and DL are playing a critical role in the advancement of manufacturing assembly robots, enabling them to work more efficiently, safely, and intelligently. Furthermore, they have a wide range of applications in aviation management, helping airlines to improve efficiency, reduce costs, and improve customer satisfaction. Moreover, the AI, ML, and DL can help taxi companies in order to provide better, more efficient, and safer services to customers. The research presents an overview of current developments in AI, ML, and DL in advanced robotics systems and discusses various applications of the systems in robot modification. Further research works regarding the applications of AI, ML, and DL in advanced robotics systems are also suggested in order to fill the gaps between the existing studies and published papers. By reviewing the applications of AI, ML, and DL in advanced robotics systems, it is possible to investigate and modify the performances of advanced robots in various applications in order to enhance productivity in advanced robotic industries.

The universal increase in the number of patients with nonhealing skin wounds imposes a huge social and economic burden on the patients and healthcare systems. Although, the application of traditional wound dressings contributes to an effective wound healing outcome, yet, the complexity of the healing process remains a major health challenge. Recent advances in materials and fabrication technologies have led to the fabrication of dressings that provide proper conditions for effective wound healing. The 3D-printed wound dressings, biomolecule-loaded dressings, as well as smart and flexible bandages are among the recent alternatives that have been developed to accelerate wound healing. Additionally, the new generation of wound dressings contains a variety of microelectronic sensors for real-time monitoring of the wound environment and is able to apply required actions to support the healing progress. Moreover, advances in manufacturing flexible microelectronic sensors enable the development of the next generation of wound dressing substrates, known as electronic skin, for real-time monitoring of the whole physiochemical markers in the wound environment in a single platform. The current study reviews the importance of smart wound dressings as an emerging strategy for wound care management and highlights different types of smart dressings for promoting the wound healing process.

In this article, the homotopy analysis method is applied to solve nonlinear fractional partial differential equations. On the basis of the homotopy analysis method, a scheme is developed to obtain the approximate solution of the fractional KdV, K(2,2), Burgers, BBM-Burgers, cubic Boussinesq, coupled KdV, and Boussinesq-like B(m,n) equations with initial conditions, which are introduced by replacing some integer-order time derivatives by fractional derivatives. The homotopy analysis method for partial differential equations of integer-order is directly extended to derive explicit and numerical solutions of the fractional partial differential equations. The solutions of the studied models are calculated in the form of convergent series with easily computable components. The results of applying this procedure to the studied cases show the high accuracy and efficiency of the new technique. © 2009 Wiley Periodicals, Inc. Numer Methods Partial Differential Eq, 2010

Many naturally occurring biomolecules, such as amino acids, sugars and nucleotides, are inherently chiral. Enantiomers, a pair of chiral isomers with opposite handedness, often exhibit similar physical and chemical properties due to their identical functional groups and composition, yet show different toxicity to cells. Detecting enantiomers in small quantities has an essential role in drug development to eliminate their unwanted side effects. Here we exploit strong chiral interactions with plasmonic metamaterials with specifically designed optical response to sense chiral molecules down to zeptomole levels, several orders of magnitude smaller than what is typically detectable with conventional circular dichroism spectroscopy. In particular, the measured spectra reveal opposite signs in the spectral regime directly associated with different chiral responses, providing a way to univocally assess molecular chirality. Our work introduces an ultrathin, planarized nanophotonic interface to sense chiral molecules with inherently weak circular dichroism at visible and near-infrared frequencies.

Coronary artery disease (CAD) is the leading cause of death worldwide and is commonly caused by a constellation of risk factors called the metabolic syndrome. We characterized a family with autosomal dominant early CAD, features of the metabolic syndrome (hyperlipidemia, hypertension, and diabetes), and osteoporosis. These traits showed genetic linkage to a short segment of chromosome 12p, in which we identified a missense mutation in LRP6, which encodes a co-receptor in the Wnt signaling pathway. The mutation, which substitutes cysteine for arginine at a highly conserved residue of an epidermal growth factor-like domain, impairs Wnt signaling in vitro. These results link a single gene defect in Wnt signaling to CAD and multiple cardiovascular risk factors.

Nanomedicines can be used for a variety of cancer therapies including tumor-targeted drug delivery, hyperthermia, and photodynamic therapy. Poly (lactic-co-glycolic acid) (PLGA)-based materials are frequently used in such setups. This review article gives an overview of the properties of previously reported PLGA nanoparticles (NPs), their behavior in biological systems, and their use for cancer therapy. Strategies are emphasized to target PLGA NPs to the tumor site passively and actively. Furthermore, combination therapies are introduced that enhance the accumulation of NPs and, thereby, their therapeutic efficacy. In this context, the huge number of reports on PLGA NPs used as drug delivery systems in cancer treatment highlight the potential of PLGA NPs as drug carriers for cancer therapeutics and encourage further translational research.

The Internet of Things (IoT) is playing a significant role in the transformation of traditional factories into smart factories in Industry 4.0 by using network of interconnected devices, sensors, and software to monitor and optimize the production process. Predictive maintenance using the IoT in smart factories can also be used to prevent machine failures, reduce downtime, and extend the lifespan of equipment. To monitor and optimize energy usage during part manufacturing, manufacturers can obtain real-time insights into energy consumption patterns by deploying IoT sensors in smart factories. Also, IoT can provide a more comprehensive view of the factory environment to enhance workplace safety by identifying potential hazards and alerting workers to potential dangers. Suppliers can use IoT-enabled tracking devices to monitor shipments and provide real-time updates on delivery times and locations in order to analyze and optimize the supply chain in smart factories. Moreover, IoT is a powerful technology which can optimize inventory management in smart factories to reduce costs, improve efficiency, and provide real-time visibility into inventory levels and movements. To analyze and enhance the impact of internet of thing in smart factories of industry 4.0, a review is presented. Applications of internet of things in smart factories such as predictive maintenance, asset tracking, inventory management, quality control, production process monitoring, energy efficiency and supply chain optimization are reviewed. Thus, by analyzing the application of IoT in smart factories of Industry 4.0, new ideas and advanced methodologies can be provided to improve quality control and optimize part production processes.

Rapidly growing interest in using nanoparticles (NPs) for biomedical applications has increased concerns about their safety and toxicity. In comparison with bulk materials, NPs are more chemically active and toxic due to the greater surface area and small size. Understanding the NPs' mechanism of toxicity, together with the factors influencing their behavior in biological environments, can help researchers to design NPs with reduced side effects and improved performance. After overviewing the classification and properties of NPs, this review article discusses their biomedical applications in molecular imaging and cell therapy, gene transfer, tissue engineering, targeted drug delivery, Anti-SARS-CoV-2 vaccines, cancer treatment, wound healing, and anti-bacterial applications. There are different mechanisms of toxicity of NPs, and their toxicity and behaviors depend on various factors, which are elaborated on in this article. More specifically, the mechanism of toxicity and their interactions with living components are discussed by considering the impact of different physiochemical parameters such as size, shape, structure, agglomeration state, surface charge, wettability, dose, and substance type. The toxicity of polymeric, silica-based, carbon-based, and metallic-based NPs (including plasmonic alloy NPs) have been considered separately.

The evolving fifth generation (5G) cellular wireless networks are envisioned to overcome the fundamental challenges of existing cellular networks, for example, higher data rates, excellent end-to-end performance, and user-coverage in hot-spots and crowded areas with lower latency, energy consumption, and cost per information transfer. To address these challenges, 5G systems will adopt a multi-tier architecture consisting of macrocells, different types of licensed small cells, relays, and device-to-device (D2D) networks to serve users with different quality-of-service (QoS) requirements in a spectrum and energy-efficient manner. Starting with the visions and requirements of 5G multi-tier networks, this article outlines the challenges of interference management (e.g. power control, cell association) in these networks with shared spectrum access (i.e. when the different network tiers share the same licensed spectrum). It is argued that the existing interference management schemes will not be able to address the interference management problem in prioritized 5G multi-tier networks where users in different tiers have different priorities for channel access. In this context a survey and qualitative comparison of the existing cell association and power control schemes is provided to demonstrate their limitations for interference management in 5G networks. Open challenges are highlighted and guidelines are provided to modify the existing schemes in order to overcome these limitations and make them suitable for the emerging 5G systems.

Tissue engineering holds great promise to develop functional constructs resembling the structural organization of native tissues to improve or replace biological functions, with the ultimate goal of avoiding organ transplantation. In tissue engineering, cells are often seeded into artificial structures capable of supporting three-dimensional (3D) tissue formation. An optimal scaffold for tissue-engineering applications should mimic the mechanical and functional properties of the extracellular matrix (ECM) of those tissues to be regenerated. Amongst the various scaffolding techniques, electrospinning is an outstanding one which is capable of producing non-woven fibrous structures with dimensional constituents similar to those of ECM fibres. In recent years, electrospinning has gained widespread interest as a potential tissue-engineering scaffolding technique and has been discussed in detail in many studies. So why this review? Apart from their clear advantages and extensive use, electrospun scaffolds encounter some practical limitations, such as scarce cell infiltration and inadequate mechanical strength for load-bearing applications. A number of solutions have been offered by different research groups to overcome the above-mentioned limitations. In this review, we provide an overview of the limitations of electrospinning as a tissue-engineered scaffolding technique, with emphasis on possible resolutions of those issues. Copyright © 2015 John Wiley & Sons, Ltd.

In this paper, a new topology for cascaded multilevel converter based on submultilevel converter units and full-bridge converters is proposed. The proposed topology significantly reduces the number of dc voltage sources, switches, IGBTs, and power diodes as the number of output voltage levels increases. Also, an algorithm to determine dc voltage sources magnitudes is proposed. To synthesize maximum levels at the output voltage, the proposed topology is optimized for various objectives, such as the minimization of the number of switches, gate driver circuits and capacitors, and blocking voltage on switches. The analytical analyses of the power losses of the proposed converter are also presented. The operation and performance of the proposed multilevel converter have been evaluated with the experimental results of a single-phase 125-level prototype converter.

Spot welding, particularly resistance spot welding (RSW), is a critical joining process in automotive industry. The development of advanced high strength steels for applications in automotive industry is accompanied with a challenge to better understand the physical and mechanical metallurgy of these materials during RSW. The present paper critically reviews the fundamental understanding of structure–properties relationship in automotive steels resistance spot welds. The focus is on the metallurgical characteristics, hardness–microstructure correlation, interfacial to pullout failure mode transition and mechanical performance of steel resistance spot welds under quasi-static, fatigue and impact loading conditions. A brief review of friction stir spot welding, as an alternative to RSW, is also included.

Abstract This paper reviews methods of modifying polydimethylsiloxane (PDMS) polymers to improve their properties for biomedical applications. The modification methods are discussed under three different categories: bulk, surface and other modification techniques. Surface modification techniques include physical and chemical techniques to modify polymer surfaces. Bulk modification techniques include blending, copolymerization, interpenetrating polymer networks (IPNs) and functionalization. The third category includes less common modification techniques. © 2001 Society of Chemical Industry

A variety of EMG features have been evaluated for control of myoelectric upper extremity prostheses. Movement class discrimination, robustness, and computational complexity of these features have been investigated for different time window sizes and noise levels. The measurements include novel application of the Davies-Bouldin index, a measure of cluster separability, and the K-nearest neighbor nonparametric classifier. The features evaluated are the integral of average value, the variance, the number of zero crossings, the Willison amplitude, the v-order and log detectors, and autoregressive model parameters. A new feature, the EMG Histogram, is introduced and shown to be the most effective of the group. The experiments were done on the data acquired from the residual biceps and triceps muscle of an above-elbow amputee.

The Internet of Things (IoT), as a pervasive paradigm, is becoming an integral part of the tech industry and academic research in recent years. It forms a ubiquitous heterogeneous network connecting humans and things. The basic premise is acquiring data from the environment with sensors and remote intelligent management via actuators. For IoT service providers, time and place are functional parameters. Whereas most IoT scenarios are in indoor spaces and GPS cannot fully cover them, applying an indoor positioning system (IPS) is necessary. Besides, indoor enabling technologies can leverage the capability of IoT in context-aware services. In this article, we aim to provide a panoramic view of IPSs and localization services with the centrality of IoT. First, we explain the main concepts and review the latest positioning methods, techniques, and technologies with IoT remarks. Then, we discuss technical implementation challenges and open issues with feasible solutions. Finally, we mentioned location-based services (LBSs), real IoT applications, and active vendors in the realm of positioning services. This article provides a real insight into LBSs in IoT for future research.

Increasing concentrations of greenhouse gases (GHGs) such as CO2 in the atmosphere is a global warming. Human activities are a major cause of increased CO2 concentration in atmosphere, as in recent decade, two-third of greenhouse effect was caused by human activities. Carbon capture and storage (CCS) is a major strategy that can be used to reduce GHGs emission. There are three methods for CCS: pre-combustion capture, oxy-fuel process, and post-combustion capture. Among them, post-combustion capture is the most important one because it offers flexibility and it can be easily added to the operational units. Various technologies are used for CO2 capture, some of them include: absorption, adsorption, cryogenic distillation, and membrane separation. In this paper, various technologies for post-combustion are compared and the best condition for using each technology is identified.

The degradation of methyl tert-butyl ether (MTBE) was investigated in the aqueous solution of coated ZnO onto magnetite nanoparticale based on an advanced photocatalytic oxidation process. The photocatalysts were synthesized by coating of ZnO onto magnetite using precipitation method. The sample was characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), and vibration sample magnetometer (VSM). Besides, specific surface area was also determined by BET method. The four effective factors including pH of the reaction mixture, Fe3O4/ZnO magnetic nanoparticles concentration, initial MTBE concentration and molar ratio of [H2O2]/ [MTBE] were optimized using response surface modeling (RSM). Using the four-factor-three-level Box-Behnken design, 29 runs were designed considering the effective ranges of the influential factors. The optimized values for the operational parameters under the respective constraints were obtained at PH of 7.2, Fe3O4/ZnO concentration of 1.78 g/L, initial MTBE concentration of 89.14 mg/L and [H2O2]/ [MTBE] molar ratio of 2.33. Moreover, kinetics of MTBE degradation was determined under optimum condition. The study about core/shell magnetic nanoparticles (MNPs) recycling were also carried out and after about four times, the percentage of the photocatalytic degradation was about 70%.

Plants are one of the best sources to obtain a variety of natural surfactants in the field of green synthesizing material. Sambucus ebulus, which has unique natural properties, has been considered a promising material in traditional Asian medicine. In this context, zinc oxide nanoparticles (ZnO NPs) were prepared using S. ebulus leaf extract, and their physicochemical properties were investigated. X-ray diffraction (XRD) results revealed that the prepared ZnO NPs are highly crystalline, having a wurtzite crystal structure. The average crystallite size of prepared NPs was around 17 nm. Green synthesized NPs showed excellent absorption in the UV region as well as strong yellow-orange emission at room temperature. Prepared nanoparticles exhibited good antibacterial activity against various organisms and a passable photocatalytic degradation of methylene blue dye pollutants. The obtained results demonstrated that the biosynthesized ZnO NPs reveal interesting characteristics for various potential applications in the future.