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As the emerging technology offers more economic and efficient mechanisms for hydrogen production, fuel cell electric vehicles (FCEVs) are expected to be deployed more extensively in the near future. Proliferation of hydrogen fueling stations throughout the transportation network and justifying their economic viability are key factors to the success of the FCEVs. In today’s deregulated market environment, many governments are encouraging private investors to invest in key infrastructures including the hydrogen fueling stations. To that end, this paper proposes a new model for optimal scheduling of privately owned hydrogen storage stations to both serve the transport sector and the electricity market operator. The model mainly aims to: 1) exploit the lower electricity market prices to reduce the power purchase cost and 2) contribute to the capacity–based demand response program to further enhance the economic feasibility of the investment. The profitability constraints and dynamic hydrogen pricing mechanisms are incorporated into the optimization process to guarantee the economic feasibility of the investment. Through such constraints, hydrogen sale prices would dynamically change to maintain system profitability at the lowest possible hydrogen price. Numerical studies reveal that the stacked profit from the two aforementioned sources of revenue under the proposed model would lead to a stronger rate of return.

The proliferation of gas-fired generation (GfG) units and emerging power-to-gas (PtG) technology can set the stage for an integrated natural gas and power distribution system. PtG and gas-fired units have the potential to mitigate several existing and imminent issues of power distribution systems. This paper investigates how PtG and GfG facilities can be added to the portfolio of conventional resolutions when the motivation is (partly) congestion management in power distribution systems. It demonstrates how PtG and GfG units as merchant investments can change the operation philosophy from the traditional preventive to the novel corrective mode. To that end, a new real-time optimal scheduling algorithm is proposed to enable a PtG–GfG unit to optimally contribute to the congestion management. Merchandise operators profit, in addition to the arbitrage benefit, by relieving the distribution grid's congestion, thereby achieving a more stable return on investments. Slack variables are incorporated into the optimization problem to measure the contribution of the PtG–GfG unit to the congestion management. A new mechanism is proposed through which the merchandise operator is financially compensated by the power system operator, due to its contribution to the congestion management. Numerical studies using real-world data on a test system validate the efficacy and feasibility of the algorithm.

This paper proposes a new online-calibrated time series based model with the application to the day-ahead natural gas demand (GD) forecasting. A double-stage parallel process is developed for creating the forecasting model. The two stages include analysis of the temperature-independent and temperature-dependent components of the GD. The former stage is executed by online processing of the historical GD information considering the intertemporal variation of the GD. The latter stage, however, is conducted by exploiting the features of the GD information correlated with the ambient temperature. The forecast of the temperature is incorporated into the GD forecasting model through a correlation-based function. The model can generate the day-ahead GD forecast with both the hourly and intrahourly resolutions without compromising the forecast accuracy. The model is calibrated online using the historical GD and temperature information to achieve a higher forecast accuracy. The practical challenges associated with the industrial application of the model are also discussed. The application of the proposed model is numerically examined using real-world GD and temperature data, and the results are comprehensively studied. The outcomes reveal the efficacy and feasibility of the proposed model under various cases.

Balance disorders are one of the most important complications for patients with chronic obstructive pulmonary disease (COPD). To investigate the effect of adding balance training to pulmonary rehabilitation program in improving balance in patients with COPD. A total of 48 male patients diagnosed as having COPD were selected from the outpatient clinic of Wadi El-Neel Hospital, Cairo, and their ages ranged from 60 to 65 years. Patients were assigned randomly into two equal groups. The study group received balance training with pulmonary rehabilitation program, and the control group received pulmonary rehabilitation program only. Exercise training was performed for both groups three times a week for 8 weeks. Balance assessment was performed by Berg Balance Scale, Balance Evaluation Systems Test, and 6-min walking test before and after training. The 2×2 mixed-model analysis of variance analysis demonstrated significant increase in the Berg Balance Scale and Balance Evaluation Systems Test after treatment in both groups, with a percentage of improvement in control group was 5.01 and 9.15%, respectively, whereas in the study group was 16.04 and 25.46%, respectively. However, the study group showed significant improvement than the control group after treatment in both tests. Regarding 6-min walking test, both groups showed significant increase after treatment, with a similar percentage of improvement in the control group (23.95%) and the study group (24.93%). There was no significant difference between the control and the study group after treatment. Addition of balance training to pulmonary rehabilitation program was more effective in improving balance in elderly patients with COPD.

Several issues have recently arisen in power distribution systems, stemmed from large penetration of renewable energy resources; among which, voltage regulation is the most salient. A newly emerging technology, referred to as power-to-gas (PtG), has brought about new opportunities to utilize the gas grid for mitigation of some existing and imminent issues in active distribution systems (ADSs). PtG units can convert the surplus electricity into the synthetic natural gas, which is then injected into the gas grid for more useful operations. Distributed gas-to-power (GtP) units, on the other hand, could exploit the gas as the feedstock to generate power, when it is needed during high power demand. A balance between the distributed generation and demand can eliminate the voltage magnitude issues in the system. In this paper, a new algorithm is proposed for optimal real-time scheduling of a PtG-GtP unit, to mitigate over/under voltage issues in ADSs with high penetration of renewables. Besides, using optimization slack variables, two indices are formulated for quantifying the contribution of the PtG-GtP facility towards voltage regulation. Using the proposed algorithm, the facility profits by providing voltage regulation services to the ADSs, in addition to the arbitrage benefit as a merchant function. Real-world data and test systems are employed to numerically validate the efficacy of the proposed algorithm.

Background: Accumulation of fluid in pleural space may affect on function of respiratory muscles primarily because of increase of chest wall volume. Force-length relationship of respiratory muscles indicate that for a given neural acti-vation, the pressure developed by muscles decrease with decreasing length. An increase of chest wall volume decrease length of respiratory muscles mainly diaphragm and increase of expiratory muscles length. It follows that with pleural effusion, all else being the same for a given, neural activation, pressure developed by the inspiratory and expiratory muscles should decrease and increase, respectively. So, the aim of the study to maintain flexibility of the diaphragm and intercostal muscles in order to get the optimum action of theses muscles, increase chest expansion, improve the respiratory function of these patients.Aim of Study: To evaluate the effect of of myofascial release for diaphragm and intercostal muscles on vital capacity and diaphragmatic excursion in post surgical pleural effusion.Subject and Methods: Forty subjects (male only) were randomly assigned into two groups equal in number. (Study group A): Consisted of 20 patients was enrolled in the myo-fascial release protocol in addition to traditional physical therapy program for pleural effusion. (Study group B): Con-sisted of 20 patients was enrolled in the traditional physical therapy program for pleural effusion only. Their vital capacity and diaphragmatic excursion were measured before and after 8 weeks of training program for both groups. The myofascial release protocol performed a 1-hour session 3 times a week for 8 weeks.Results: Group (A) myofascial release group, showed a statistical significant improvement in vital capacity and diaphragmatic excursion, that was 13.49%, more than the improvement in group (B) traditional physical therapy group, that was 8.68%.Conclusions: The myofascial release for diaphragm and intercostal muscles is effective on vital capacity and diaphrag-matic excursion in post surgical pleural effusion.

The integration of electrolyzer and photovolatic (PV) systems has proven its economical feasibility for dean hydrogen production. However, the uncertainty associated with solar energy has impact on the reliability of clean hydrogen production. Economical dispatch for the hydrogen system integrated with PV and Battery Energy Storage System (BESS) can be used to maintain high hydrogen production reliability and efficiency. In this work, an optimal economical dispatch model for reliable scheduling operations of clean hydrogen production system is proposed. The model aims to minimize Cost-of-Hydrogen (CoH) production through; i) minimizing total system costs, ii) maximizing hydrogen production efficiency, and iii) maximizing solar energy utilization. The model takes into consideration CoH production sensitivity to the variation of electrolyzer efficiency. Electrochemical hydrogen production mechanism and operational balance constraints are incorporated into the optimization model to guarantee accurate and stable system performance. The simulation results verified the economical feasibility of the proposed dispatch model in terms of meeting hydrogen demand, system stability, and storage capability. The optimization results revealed that the average CoH production for the proposed model is 2.67 $/kg during the studied period. The results of this study highlights the correlation between hydrogen production rate, electrolyzer efficiency, and CoH production. A comparative analysis with and without the consideration of the variability of the electrolyzer efficiency indicates the efficacy and feasibility of the proposed model in minimizing hydrogen production costs and maximizing solar power utilization.

Glioblastoma multiforme (GBM) is one of the deadliest brain tumors with an unfavorable prognosis and overall survival of approximately 20 months following diagnosis. The current treatment for GBM includes surgical resections and chemo‐ and radiotherapeutic modalities, which are not effective. CAR‐T immunotherapy has been proven effective for CD19‐positive blood malignancies, and the application of CAR‐T cell therapy for solid tumors including GBM offers great hope for this aggressive tumor which has a limited response to current treatments. CAR‐T technology depends on the use of patient‐specific T cells genetically engineered to express specific tumor‐associated antigens (TAAs). Interaction of CAR‐T cells with tumor cells triggers the destruction/elimination of these cells by the induction of cytotoxicity and the release of different cytokines. Despite the great promise of CAR‐T cell‐based therapy several challenges exist. These include the heterogeneity of GBM cancer cells, aberrant various signaling pathways involved in tumor progression, antigen escape, the hostile inhibitory GBM microenvironment, T cell dysfunction, blood‐brain barrier, and defective antigen presentation. All need to be addressed before full application at the clinical level can begin. Herein we provide a focused review of the rationale for the use of different types of CAR‐T cells (including FcγRs), the different GBM‐associated antigens, the challenges still facing CAR‐T‐based therapy, and means to overcome such challenges. Finally, we enumerate currently completed and ongoing clinical trials, highlighting the different ways such trials are designed to overcome specific problems. Exploitation of the full potential of CAR‐T cell therapy for GBM depends on their solution., Here, we provided a focused review on the rationale of the use of different types of CAR‐T cells including FcγRs CAR‐T cells, different GBM‐associated antigens, challenges still facing CAR‐T‐based therapy for GBM, and strategies to overcome such challenges. Finally, we enumerated the completed and ongoing clinical trials for GBM and highlighted the different ways such trials are designed to overcome specific challenges that guard against the exploitation of the full potential of CAR‐T cell therapy for GBM.

Management of non-healing and slow to heal diabetic wounds is a major concern in healthcare across the world. Numerous techniques have been investigated to solve the issue of delayed wound healing, though, mostly unable to promote complete healing of diabetic wounds due to the lack of proper cell proliferation, poor cell-cell communication, and higher chances of wound infections. These challenges can be minimized by using hydrogel based wound healing patches loaded with bioactive agents. Gelatin methacrylate (GelMA) has been proven to be a highly cell friendly, cell adhesive, and inexpensive biopolymer for various tissue engineering and wound healing applications. In this study, S-Nitroso-N-acetylpenicillamine (SNAP), a nitric oxide (NO) donor, was incorporated in a highly porous GelMA hydrogel patch to improve cell proliferation, facilitate rapid cell migration, and enhance diabetic wound healing. We adopted a visible light crosslinking method to fabricate this highly porous biodegradable but relatively stable patch. Developed patches were characterized for morphology, NO release, cell proliferation and migration, and diabetic wound healing in a rat model. The obtained results indicate that SNAP loaded visible light crosslinked GelMA hydrogel patches can be highly effective in promoting diabetic wound healing. Scopus

Integration of power and gas grids has recently attracted significant attention from researchers around the globe. Utilization of power-to-gas (PtG) and gas-fired generation (GfG) facilities can allow bi-directional energy flow between the two grids. In such a case, PtG and GfG facilities can be jointly operated for multiple purposes including power restoration within an integrated power and gas grid. To that end, this paper proposes a new optimization-based model for power restoration in an integrated power and gas distribution grid. Besides, the model aims to schedule PtG and GfG units for exploiting gas and electricity price arbitrage opportunities in the market. Using historical values of optimization variables, the participation of PtG and GfG facilities in power restoration is measured. A 33-bus power distribution grid is integrated with a 7-node gas grid and employed for numerical studies. The results demonstrate that utilization of PtG and GfG units for power restoration in addition to the main functionality of arbitrage brings a larger revenue for the PtG and GfG units operator. As such, the proposed model in this paper can open up new opportunities for proliferation of PtG and GfG systems and facilitate the integration of power and gas grids in the near future.

Introduction Surgical site infection (SSI) is one of the most common healthcare-associated infections (HAIs). However, there is a lack of data available about SSI in children worldwide, especially from low-income and middle-income countries. This study aimed to estimate the incidence of SSI in children and associations between SSI and morbidity across human development settings. Methods A multicentre, international, prospective, validated cohort study of children aged under 16 years undergoing clean-contaminated, contaminated or dirty gastrointestinal surgery. Any hospital in the world providing paediatric surgery was eligible to contribute data between January and July 2016. The primary outcome was the incidence of SSI by 30 days. Relationships between explanatory variables and SSI were examined using multilevel logistic regression. Countries were stratified into high development, middle development and low development groups using the United Nations Human Development Index (HDI). Results Of 1159 children across 181 hospitals in 51 countries, 523 (45·1%) children were from high HDI, 397 (34·2%) from middle HDI and 239 (20·6%) from low HDI countries. The 30-day SSI rate was 6.3% (33/523) in high HDI, 12·8% (51/397) in middle HDI and 24·7% (59/239) in low HDI countries. SSI was associated with higher incidence of 30-day mortality, intervention, organ-space infection and other HAIs, with the highest rates seen in low HDI countries. Median length of stay in patients who had an SSI was longer (7.0 days), compared with 3.0 days in patients who did not have an SSI. Use of laparoscopy was associated with significantly lower SSI rates, even after accounting for HDI. Conclusion The odds of SSI in children is nearly four times greater in low HDI compared with high HDI countries. Policies to reduce SSI should be prioritised as part of the wider global agenda. ©

Tissue engineering (TE) is an interdisciplinary field integrating engineering, material science and medical biology that aims to develop biological substitutes to repair, replace, retain, or enhance tissue and organ-level functions. Current TE methods face obstacles including a lack of appropriate biomaterials, ineffective cell growth and a lack of techniques for capturing appropriate physiological architectures as well as unstable and insufficient production of growth factors to stimulate cell communication and proper response. In addition, the inability to control cellular functions and their various properties (biological, mechanical, electrochemical and others) and issues of biomolecular detection and biosensors, all add to the current limitations in this field. Nanoparticles are at the forefront of nanotechnology and their distinctive size-dependent properties have shown promise in overcoming many of the obstacles faced by TE today. Despite tremendous progress in the use of nanoparticles over the last 2 decades, the full potential of the applications of nanoparticles in solving TE problems has yet to be realized. This review presents an overview of the diverse applications of various types of nanoparticles in TE applications and challenges that need to be overcome for nanotechnology to reach its full potential.

β-Amyloid peptide (Aβ) is a potent neurotoxic protein associated with Alzheimer’s disease (AD) which causes oxidative damage to neurons. Incensole acetate (IA) is a major constituent of Boswellia carterii resin, which has anti-inflammatory and protective properties against damage of a large verity of neural subtypes. However, this neuroprotective effect was not studied on human olfactory bulb neural stem cells (hOBNSCs). Herein, we evaluated this effect and studied the underlying mechanisms. Exposure to Aβ25–35 (5 and 10 μM for 24 h) inhibited proliferation (revealed by downregulation of Nestin and Sox2 gene expression), and induced differentiation (marked by increased expression of the immature neuronal marker Map2 and the astrocyte marker Gfap) of hOBNSCs. However, pre-treatment with IA (100 μM for 4 h) stimulated proliferation and differentiation of neuronal, rather than astrocyte, markers. Moreover, IA pretreatment significantly decreased the Aβ25–35-induced viability loss, apoptotic rate (revealed by decreased caspase 3 activity and protein expression, downregulated expression of Bax, caspase 8, cyto c, caspase3, and upregulated expression of Bcl2 mRNAs and proteins, in addition to elevated mitochondrial membrane potential and lowered intracellular Ca+2). IA reduced Aβ-mediated ROS production (revealed by decreased intracellular ROS and MDA level, and increased SOD, CAT, and GPX contents), and inhibited Aβ-induced inflammation (marked by down-regulated expression of IL1b, TNFa, NfKb, and Cox2 genes). IA also significantly upregulated mRNA and protein expression of Erk1/2 and Nrf2. Notably, IA increased the antioxidant enzyme heme oxygenase-1 (HO-1) expression and this effect was reversed by HO-1 inhibitor zinc protoporphyrin (ZnPP) leading to reduction of the neuroprotective effect of IA against Aβ-induced neurotoxicity. These findings clearly show the ability of IA to initiate proliferation and differentiation of neuronal progenitors in hOBNSCs and induce HO-1 expression, thereby protecting the hOBNSCs cells from Aβ25–35-induced oxidative cell death. Thus, IA may be applicable as a potential preventive agent for AD by its effect on hOBNSCs and could also be used as an adjuvant to hOBNSCs in cellular therapy of neurodegenerative diseases.

Background: Chest physical therapy plays an important role in increasing Pao2 and SaO2 among ICU patients which is considered as a good indicator for the general improvement of the patient besides decreasing ICU staying and costs. Purpose: To figure out the effect of chest physical therapy on oxygen saturation and partial pressure of arterial oxygen. Patients and Method: Thirty patients post MV, their age ranged from 50 to 60 years old were recruited in this study. The patients were selected from ICUs of Kasr al Ainy hospital, Faculty of Medicine, Cairo University. The patients received chest physiotherapy (percussion, vibration, manual hyperinflation), positioning and upper and lower limbs exercises. Results: Increase in Pao2 and SaO2 in addition to decreased incidence of chest infection and decreased ICU stay. Conclusion: The results of this study support the importance of chest physiotherapy on increasing SaO2 and Pao2, decrease ICU duration and decrease health care costs.

A significant challenge in the current orthopedics is the development of suitable osteobiologic materials that can replace the conventional allografts, autografts, and xenografts and thereby serve as implant materials as bone substitutes for bone repair or remodelling. The complex biology behind the nanostructure and microstructure of bones and their repair mechanisms, which involve various types of chemical and biomechanical signalling amongst different cells, has set strong requirements for biomaterials to be used in bone tissue engineering. This review presents an overview of various types of osteobiologic materials to facilitate the formation of the functional bone tissue and healing of the bone, covering metallic, ceramic, polymeric, and cell-based graft substitutes, as well as some biomolecular strategies including stem cells, extracellular matrices, growth factors, and gene therapies. Advantages and disadvantages of each type, particularly from the perspective of osteoinductive and osteoconductive capabilities, are discussed. Although the numerous challenges of bone regeneration in tissue engineering and regenerative medicine are yet to be entirely addressed, further advancements in osteobiologic materials will pave the way towards engineering fully functional bone replacement grafts.

Power-to-gas (PtG) energy storage converts electricity to hydrogen or synthetic natural gas. The gas produced is stored and converted back to electricity at a later time; or it is directly used to supply a gas load and/or sell in the gas market. In the first case, due to double energy conversion in a relatively less efficient process, a large portion of the energy is wasted. The latter case is examined in this paper, where PtG storage is optimally scheduled to convert waste/inexpensive electricity to synthetic natural gas for some useful operations at appropriate time periods. To that end, a new model is proposed for optimal day-ahead scheduling of PtG storage and gas load management in electricity and gas markets to minimize the cost of gas consumption for the gas load. A gas demand forecasting algorithm is integrated into the scheduling model. Reserve provision is formulated as part of the optimization problem to optimally manage the gas load in case of an outage in the gas grid. The application of the proposed model to a test case is examined, and the results are studied.

Exponential penetration of renewable generation has led to the new issues in power distribution systems, such as reverse power flow in the feeders. In the case of sizable distributed generation during lower demand, the power tends to travel in the reverse direction. This, in turn, could cause serious operational issues such as voltage rise, extra heat in the transformers, and maloperation of protective devices. Newly emerging technologies for power-to-gas (PtG) conversion are now offering effective solutions to the problem. The proliferation of PtG facilities can lead to the deployment of integrated natural gas and power systems in the near future. PtG and gas-fired, i.e. gas-to-power (GtP), units can be utilised to address several issues in an integrated power and gas network. This study unveils the application of bi-directional energy converters within an integrated gas and power system for distribution system reverse power management (DSRPM). To that end, a new real-time algorithm is proposed for optimal joint scheduling of PtG and GtP units for DSRPM. A new index is also developed that would quantify the contribution of the PtG-GtP system to DSRPM. Numerical results using real-world data on a test system substantiate the effectiveness of the proposed algorithm.

The massive deployment of plug-in electric vehicles (PEVs), renewable energy resources (RES), and distributed energy storage systems (DESS) has gained significant interest under the smart grid vision. However, their special features and operational characteristics have created a paradigm shift in distribution network resource allocation studies. This paper presents a combined model formulation for the concurrent optimal resource allocation of PEVs charging stations, RES and DESS in distribution networks. The formulation employs a general objective function that optimizes the total Annual Cost of Energy (ACOE). The decision variables in the formulation are the locations and capacities of PEVs charging stations, RES, and DESS units. A Markov Chain Monte Carlo (MCMC) simulation model is utilized to account for the uncertainties of PEVs charging demand and output generation of RES units. Also, in order to enhance the accuracy of the resource allocation problem, the coordinated control of PEVs charging, RES output power, and DESS charging/discharging are incorporated in the formulated model. The formulation is decomposed into two interdependent sub-problems and solved using a combination of metaheuristic and deterministic optimization techniques. A sample case study is presented to illustrate the performance of the algorithm.

The successful implementation of multi-agent control strategies (MAS) within smart grid applications is heavily reliant on communication frameworks that enable robust inter-agent messaging. In this regard, a promising communication framework is Data Distribution Service (DDS), which is fully distributed, enables low-latency messaging, and provides configurable Quality of Service (QoS) profiles that customize messaging parameters. As such, this paper proposes a DDS-based, fully distributed communication framework (DCF) for smart grid applications. The proposed DCF is configured with QoS profiles that discard outdated messages when agents experience intermittent connection issues, thereby preventing the misaligned execution of distributed control strategies. The performance of the proposed DCF is validated by developing a Software-In-The-Loop platform, where agents utilize the DCF to execute the Asynchronous Weak Commitment (AWC) control strategy within the application of distributed voltage regulation. Experimental results show that the proposed DCF delivers messages at latencies between 4-36 milliseconds, which is sufficient for smart grid applications. The proposed DCF also enhances the efficacy of the AWC strategy when performing voltage regulation by discarding outdated messages and preventing unnecessary control actions in resolving voltage violations. The proposed DCF is validated at a real-world Canadian microgrid, where overvoltage violations are resolved in a timely manner.

New and natural antimicrobials as an alternative control system are now an urgent need to overcome stubborn bacterial infections. Salmonella Typhimurium has become the most frequent serovar responsible for salmonellosis in humans around the world. The high antimicrobial resistance and biofilm production make this pathogen more dangerous. We aimed to isolate a broad lytic phage to prevent Salmonella infection and reduce its biofilms. Using S. Typhimurium (ST-4) as a host, seven phages were isolated, and only three phages showed clear lytic plaques, two members of the Siphoviridae family (vB_STS-1 and vB_STS-3) and one of the Myoviridae family (vB_STM-2). The vB_STM-2 phage was the most potent broad lytic phage, infecting 100% of tested S. Typhimurium serovars and non-Salmonella strains. Additionally, the vB_STM-2 phage was thermostable at −20 to 55 °C up to 24 h, while at 65 and 75 °C, a significant (p &lt, 0.05) titer reduction was observed after 7 days. Moreover, the phage seemed to be stable at different pHs (4–11) after one to twelve hours (hrs), while increasing the time made the phage more sensitive to the alkaline medium rather than the acidic medium. Interestingly, the vB_STM-2 phage had the capacity to diminish or eradicate the biofilms of tested S. Typhimurium, e.g., ST-4, ST-19, ST-30, ST-37, ST-45 and ST-49 by 81.2%, 76.4%, 43.6%, 41%, 39.8% and 93.4%, respectively, at a titer concentration of 106 PFU/mL. Eventually, the vB_STM-2 phage showed significant (p &lt, 0.05) efficacy in the elimination of S. Typhimurium (ST-4) from contaminated chicken breasts at both storage periods with high titer stability. The Salmonella count showed a severe decline from 7.00 ± 0.63 log10 CFU/cm2 to 0.88 ± 0.17 log10 CFU/cm2 on the seventh day of the short-term storage, and from 5.13 ± 0.44 log10 CFU/cm2 to 1.10 ± 0.12 log10 CFU/cm2 on day 27 of the long-term assay. In both periods, the phage titers remained stable, with insignificant (p &lt, 0.05) loss. Therefore, this phage is considered a prime candidate to combat multi-drug-resistant S. Typhimurium and its biofilms.

Tumor treating fields (TTFields) are among clinically active anticancer modalities that utilize low‐intensity, intermediate frequency (IF), and alternating electric fields (AEFs) to selectively disrupt mitosis in cancerous cells. Application of TTFields in the range of 100–900 kHz in cancer therapy and its effect on normal and cancer cells have attracted a great deal of interest in recent years. TTFields affect solid tumors by introducing increased chromatid aberrations that reduce the capacity to repair DNA damage and chromosome segregation, resulting in autophagy and subsequent cell death. In this review, we present an overview of the applications of TTFields in the treatment of cancer. We discuss several practical applications of TTField frequencies combined with metallic nanoparticles (NPs) (magnetic or nonmagnetic NPs) for internalization into cancer cells. In addition, TTFields can be combined effectively with chemotherapy and radiotherapy.

Distributed voltage regulation schemes within active distribution networks (ADNs) are receiving plenty of attention because they reduce latency bottlenecks. However, previous schemes often employ a trusted moderator to govern agent communication, thereby exposing potential trust issues that may affect agent performance. Blockchain technology can avoid the need for intermediaries, since it is a fully decentralized network that is governed by agents using distributed consensus mechanisms. Thus, this paper proposes a blockchain-based system for voltage regulation in ADNs that provides a competitive marketplace wherein agents can rationally bid for voltage regulation services. The proposed system utilizes a smart contract that i) enables asynchronous negotiation between agents to mitigate multiple violations simultaneously using the extended contract net protocol (ECNP), and ii) maintains a credit score that reflects the trustworthiness of an agent in resolving voltage violations. The proposed system also develops a bidding and pricing scheme for voltage regulation services that considers both active and reactive power contributions. A permissioned blockchain implementation is used to ensure that only known agents are permitted to access the system. The proposed system is implemented on the Hyperledger Fabric platform, where simulations executed on a 69 bus system demonstrate the system’s ability to mitigate multiple voltage violations simultaneously. As demonstrated by the simulation results, the highlight of the main contribution of the paper is the ability of the proposed system to mitigate multiple voltage violations simultaneously via the ECNP, thereby utilizing less bidding cycles to resolve voltage violations as compared to the original contract net protocol.