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Zinc oxide (ZnO) as a commonly used semiconductor material has aroused extensive research attention in various fields, such as field-effect transistors, solar cells, luminescent devices, and sensors, because of its excellent light-electrical features and large exciton bonding energy. Herein, ultrasmall Au nanoparticles with tunable size decorated mesoporous ZnO nanospheres were synthesized via facile formaldehyde-assisted metal-ligand cross-linking strategy, where these active Au species could be transferred into Au nanoparticles in the frameworks by various reduction strategies. Typically, mesoporous ZnO-Au with a photoreduction technique showed superior ethanol sensing performance (ca. 159 for 50 ppm at 200 °C) because of its high surface area, dual-mesoporous structure, and interface effect (electron effect, surface catalytic/adsorption). Moreover, the mesoporous ZnO-Au composites by photoreduction show much better performance than those via H2 reduction and NaBH4 reduction, which is ascribed to the providential size of Au nanoparticles (ca. 6.6 nm) and abundant oxygen defects in the composites. In particular, the selectivity and sensitivity of mesoporous ZnO-Au far exceeds those of materials loaded with other noble metals (Pt, Pd, and Ag). The sensing mechanism of mesoporous ZnO-Au for ethanol is attributed to classical surface adsorption/catalytic reaction, where strong sensitization effect (electron and chemical) and the spillover effect of Au nanoparticles in the catalytic reaction cause superior ethanol sensing performances. In situ FTIR and GC-MS measurement revealed that the catalytic oxidation of ethanol follows the process of dehydrogenation and deep oxidation, that is, dehydrogenation to acetaldehyde, and then further oxidation to carbon dioxide and water.

Green and recyclable solid acid catalysts are in urgent demand as a substitute for conventional liquid mineral acids. In this work, a series of novel sulfonic acid-functionalized core-shell Fe3O4@carbon microspheres (Fe3O4@C-SO3H) have been designed and synthesized as an efficient and recyclable heterogeneous acid catalyst. For the synthesis, core-shell Fe3O4@RF (resorcinol-formaldehyde) microspheres with tunable shell thickness were achieved by interfacial polymerization on magnetic Fe3O4 microspheres. After high-temperature carbonization, the microspheres were eventually treated by surface sulfonation, resulting in Fe3O4@C-x-SO3H (x stands for carbonization temperature) microspheres with abundant surface SO3H groups. The obtained microspheres possess uniform core-shell structure, partially-graphitized carbon skeletons, superparamagnetic property, high magnetization saturation value of 10.6 emu/g, and rich SO3H groups. The surface acid amounts can be adjusted in the range of 0.59–1.04 mmol/g via sulfonation treatment of carbon shells with different graphitization degrees. The magnetic Fe3O4@C-x-SO3H microspheres were utilized as a solid acid catalyst for the acetalization reaction between benzaldehyde and ethylene glycol, demonstrating high selectivity (97%) to benzaldehyde ethylene glycol acetal. More importantly, by applying an external magnetic field, the catalysts can be easily separated from the heterogeneous reaction solutions, which later show well preserved catalytic activity even after 9 cycles, revealing good recyclability and high stability.

The rapid development of internet and internet of things brings new opportunities for the expansion of intelligent sensors, and acetone as a major disease detection indicator (i.e., diabetes) making it become extremely important clinical indicator. Herein, uniform mesoporous ZnO spheres were successfully synthesized via novel formaldehyde-assisted metal-ligand crosslinking strategy. In order to adjust the pore structure of mesoporous ZnO, various mesoporous ZnO spheres were synthesized by changing weight percentage of Zn(NO3)2·6H2O to tannic acid (TA). Moreover, highly active heterojunction mesoporous ZnO/Co3O4 has been fabricated based on as-prepared ultra-small Co3O4 nanocrystals (ca. 3 nm) and mesoporous ZnO spheres by flexible impregnation technique. Profit from nano-size effect and synergistic effect of p-n heterojunction, mesoporous ZnO/Co3O4 exhibited excellent acetone sensing performance with high selectivity, superior sensitivity and responsiveness. Typically, 5 wt% Co3O4 embedded mesoporous ZnO sphere showed prominent acetone response (ca. 46 for 50 ppm), which was about 11.5 times higher than that in pure ZnO sensing device, and it was also endowed high cyclic stability. The nanocrystals embedded hybrid material is expected to be used as promising efficient material in the field of catalysis and gas sensing.

The antifungal effect of zirconium dioxide nanoparticles (ZrO2NPs) incorporated into denture base material has been inadequately investigated; additionally, to the authors’ knowledge, no studies have assessed the influence of artificial aging on the antifungal activity of these particles. Methodology. Heat-polymerized acrylic resin disks were fabricated and divided into four groups (0%, 1%, 2.5%, and 5% ZrO2NPs by weight). Antifungal activity was assessed using the direct culture and disk diffusion methods. Surface roughness and contact angles were measured using a profilometer and a goniometer, respectively. The artificial aging procedure was performed by repeating all tests at 7, 14, and 30 days following 2 rounds of thermocycling. Data were analyzed using ANOVA and Tukey’s post-hoc test ( p < 0.05 ). Results. The addition of ZrO2NPs significantly decreased the adhesion of Candida albicans with and without artificial aging procedures ( p < 0.001 ), while the disk diffusion methods did not reveal inhibition zones. ZrO2NP-modified specimens displayed significantly higher surface roughness compared to specimens in the control group ( p < 0.05 ) and showed the same behaviors with artificial aging procedures. The contact angle was significantly decreased in all modified groups in comparison to the control group ( p < 0.05 ). Conclusion. The addition of ZrO2NPs to polymethylmethacrylate denture base material reduced the adhesion of Candida albicans with a long-term antifungal effect. With the addition of ZrO2NPs, contact angles were decreased and surface roughness was increased; 1% was the most appropriate concentration. Clinical significance. The addition of ZrO2NPs to denture base material confers a long-term antifungal effect and could be used as a possible method for preventing and treating denture stomatitis.

Acephate pesticide contamination in agricultural production has caused serious human health problems. Metal oxide semiconductor (MOS) gas sensor can be used as a portable and promising alternative tool for efficiently detection of acephate. In this study, hierarchical assembled SnO2 nanosphere, SnO2 hollow nanosphere and SnO2 nanoflower were synthesized respectively as high efficiency sensing materials to build rapid and selective acephate pesticide residues sensors. The morphologies of different SnO2 3D nanostructures were characterized by various material characterization technology. The sensitive performance test results of the 3D SnO2 nanomaterials towards acephate show that hollow nanosphere SnO2 based sensor displayed preferable sensitivity, selectivity, and rapid response (9 s) properties toward acephate at the optimal working temperature (300 °C). This SnO2 hollow nanosphere based gas sensor represents a useful tool for simple and highly effective monitoring of acephate pesticide residues in food and environment. According to the characterization results, particularly Brunauer-Emmett-Teller (BET) and Ultraviolet-Visible Spectroscopy (UV–vis), the obvious and fast response can be attributed to the mesoporous hollow nanosphere structure and appropriate band gap of SnO2 hollow nanosphere.

Various synthesis methods such as deep-deposition-ultrasonication (DPU), co-precipitation-ultrasonication (CPU), deposition-precipitation (DP), co-precipitation (CP) and wet-impregnation (IMP) have been reported for the preparation of lanthanum-modified zirconia (La/ZrO2) catalysts. The acoustic cavitational effect by the DPU method decreased the particles size and enlarged the pores of the La/ZrO2 catalysts. Besides, the La ions well-interacted with the ZrO2 in each catalyst, thus, all the La/ZrO2 catalysts have a great potential to be employed in ketonization reaction. It had found that both DP and DPU methods exhibited smaller catalyst particles than that of the CP, CPU and IMP methods, in which 15 – 20 nm for the La/ZrO2-DPU and 28 – 56 nm for the La/ZrO2-DP. Even though the ultrasonication helped to reduce the particle size notably, adversely the small particles tend to aggregated . Meanwhile, larger nanoparticles can be prevented particle aggregation leading to higher dispersion for the La/ZrO2-DP as compared to the La/ZrO2-DPU. All the catalysts were tested in ketonization of palmitic and lauric acids, showing the La/ZrO2-DP exhibited the best catalyst with free fatty acid (FFA) conversion ~80% and 51% of ketone selectivity. In addition, the 10 wt.% of La dosage gave the optimum concentration for the maximum ketonization activity. The La/ZrO2-DP catalyst also promising for the ketonization of real feedstocks such as palm kernel oil (PKO) and palm fatty acid distillate (PFAD) into their ketone species.

This article reports the synthesis β-SnWO4–rGO nanocomposite (NC) by a simple solution combustion method followed by low temperature hydrothermal method. The β-SnWO4–rGO NC has been characterized using various analytical tools such as X-ray diffraction (XRD), Raman spectroscopy, Scanning Electron Microscopy (SEM), High-Resolution Transmission Electron Microscopy (HR-TEM), Ultraviolet-Differential reflectance spectroscopy (UV-DRS). X-ray diffraction pattern shows the formation of cubic structured β-SnWO4 nanoparticles (NPs) and Raman spectrum shows the presence of rGO in the composite. Transmission Electron Microscopy image shows that SnWO4 NPs were embedded on the surface of rGO. β-SnWO4 NPs and β-SnWO4-rGO NC has been examined as an electrode material for Li-ion battery (LIB). β-SnWO4 NPs and β-SnWO4-rGO NC displays an initial discharge capacity of 1351 mAhg−1 and 1662 mAhg−1 which is about 23% increase in capacity. Electrochemical performance of β-SnWO4-rGO NC at different current densities proves that it is one of the good candidates as an electrode material for LIB. β-SnWO4-rGO NC shows enhanced photocatalytic activity against rose bengal (RB) and methylene blue (MB) compared to pure β-SnWO4 NPs.

Magnetic assembly at the nanoscale level brings potential possibilities in obtaining novel delicate nanostructures with unique physical, photonic or electronic properties. Interface surfactant micelle-directed assembly strategy holds great promising in fabricating ordered mesoporous materials with multifunctionality and pore parameter tunability. Combing these, herein, one-dimensional (1D) nanochains with well-aligned silica-coated magnetic particles as core and mesoporous aluminosilicate as shell are rational fabricated for the first time through magnetic field induced interface coassembly in biliquid system followed by the incorporation of Al species via in-situ chemical modification and transformation strategy. The obtained magnetic mesoporous aluminosilicate nanochains (MMAS-NCs) possess well-defined core-shell-shell sandwich nanostructure, tunable perpendicular mesopore channels in the shell (2.7–7.6 nm), high surface area (359 m2·g−1), abundant acidic sites, and superparamagnetism with a magnetization saturation of 13.8 emu·g−1. Thanks to the unique properties, the MMAS-NCs exhibit excellent performance in acting as magnetically recyclable superior solid acid catalysts and nanostirrers with high conversion of over 96.8%, selectivity of 95.0% in the deprotection reaction of benzaldehyde dimethylacetal to benzaldehyde. Moreover, MMAS-NCs exhibit an interesting pore size effect on the catalytic activity, namely, in the pore size range of 2–8 nm, the catalysts with larger pores show significantly enhanced catalytic activity due to the balanced mass transport and density of surface active sites.

The effect of various pretreatments on the bonding of a resin cement to resin-composite CAD/CAM blocks (RCBs) was examined. The surface of dispersed-filler RCBs (DF-RCBs) and a polymer infiltrated ceramic network RCB (PICN-RCB) was roughened using hydrofluoric acid etching (HF) or sandblasting, and followed by silanization and/or universal adhesive (UA) application. Microtensile bond strength (µTBS), surface roughness parameters (arithmetical mean height (Sa); developed interfacial area ratio (Sdr)), and critical surface energy (γc) were determined. For most DF-RCBs, the highest µTBS was obtained using HF+UA. UA application to DF-RCBs resulted in similar or higher µTBS compared to silanization, which indicates that silane treatment is not crucial for DF-RCBs, especially after HF. In contrast, the highest µTBS to PICN-RCB was obtained with silanization. Both roughening pretreatments significantly increased the surface roughness parameters and the γc of all RCBs. The γc was positively correlated with Sa (r=0.756, p

Certainty, artificial intelligence (AI) has a remarkable role in the control of the COVID-19 pandemic globally This review article aimed to determine the outcomes/benefits associated with the use of artificial intelligence during the COVID-19 pandemic in different specialties in healthcare Out of 144 articles, 100 publish article abstracts were reviewed using keywords artificial intelligence, intelligent health systems during COVID-19 pandemic, medical education This review determined that artificial intelligence has a significant role in predicting the spread of disease by chasing the infected population and can prove as a powerful tool for public health professionals There is a remarkable role of AI-assisted diagnostic features in radiology to specifically diagnose infected cases with COVID-19 AI assists in taking quicker decision making among health professionals through AI operated apps This review highlights the need for future research which should emphasize determining the effectiveness and challenges of the use of robotics during pandemics Copyright © 2021, IGI Global Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited

Clustering is considered to be the most significant method for resolving conflicts of data transmission and maximizing the life span of the network in Wireless Sensor Networks (WSNs). The sensor nodes are densely deployed to satisfy the coverage requirement; this causes some nodes to lazy mode. Some algorithms of cluster heads (CHs) selection were already proposed for sufficient energy management. However, it remains as a challenging task in WSN due to network scalability, protocol characteristics, and data transfer rate. This paper aims to propose a novel clustering model is proposed by this research work for cluster head selection (CHS) that considers four primary constraints: namely energy consumption, delay, distance, and security. In addition, for optimal selection of CH, a novel algorithm, which is the hybridization of the Dragon Fly (DA) algorithm and firefly algorithm, is proposed. The proposed hybrid algorithm is named as FireFly replaced Position Update in Dragonfly (FPU-DA). The performance of the proposed work is compared with conventional algorithms. Subsequently, a parametric analysis is performed by varying the weight factor of the proposed FPU-DA model to investigate its impact on the performance of the CHS problem. The proposed FPU-DA model at round 2000 shows 9%, better than KNN and SOM. Thus, the analysis results proved that the proposed model attains a better life span when compared to that of other conventional models.

Jatropha curcas is a highly toxic plant that produces seed containing viscous oil with productivity (2 ton/ha), it grows in tropical and sub-tropical regions and offer greater adaptability to a wide range of climatic and soil conditions. Its oils have been noted as an important alternative to produce green diesel via deoxygenation reaction. This study, deoxygenation of jatropha curcas oil (JCO) was carried out over NiO–Fe2O3 and NiO–ZnO catalysts that supported onto multi-walled carbon nanotube (MWCNT). It had found that high Fe and Zn dosages were ineffective in deoxygenation and greatest activity was observed on NiO(20) Fe2O3(5)/MWCNT catalyst. Structure-activity correlations revealed that low metal loading, large density of weak + medium acidic sites and strong basic sites play key role in enhancing the catalytic activities and n-(C15+C17) selectivity. Comparing carbon nanostructures and carbon micron size supported NiO-Fe2O3 revealed that green diesel obtained from NiO–Fe2O3/MWCNT catalysed deoxygenation had the highest heating value and the lowest amounts of oxygen content. Thereby, it confirmed the importance of carbon nanostructure as the catalyst support in improving the diesel quality. Considering the high reusability of NiO-Fe2O3/MWCNT (6 consecutive runs) and superior green diesel properties (flash point, cloud properties and cetane index) demonstrated the NiO–Fe2O3/MWCNT catalyst offers great option in producing excellent properties of green diesel for energy sector.

Isoproturon (IP), a systemic herbicide, is also considered as a potential groundwater contaminant. In the present study, the radiation-induced degradation of IP employing gamma-rays is investigated. Several factors such as radiation dose, pH and the presence of co-contaminants such as H2O2, isopropanol, tert-butanol, coffee waste (CW), carbonized coffee waste (CWC) and TiO2, which might affect the degradation process are examined. The IP concentration decreased with the increase of radiation dose and the degradation obtained at pH = 7.0 is found to be 90%. The degradation efficiency decreases with the increase of initial concentration at the same radiation dose. Co-contaminants such as H2O2, TiO2 and CW had increased the degradation efficiency. The process followed by first order reaction kinetics. Furthermore, the increase of the concentration of H2O2, isopropanol, tert-butanol and the weight of TiO2, CW and CWC resulted in the decrease of the degradation values. The pH value was found to effect the removal efficiency and the degradation process was enhanced under neutral condition. IP concentration of 30µ M was selected as standard, while 0.63 kGy was selected as the standard radiation dose.

Energy efficiency has become a primary issue in wireless sensor networks (WSN). The sensor networks are powered by battery and thus they turn out to be dead after a particular interval. Hence, enhancing the data dissipation in energy efficient manner remains to be more challenging for increasing the life span of sensor devices. It has been already proved that the clustering method could improve or enhance the life span of WSNs. In the clustering model, the selection of cluster head (CH) in each cluster regards as the capable method for energy efficient routing, which minimizes the transmission delay in WSN. However, the main problem dealt with the selection of optimal CH that makes the network service prompt. Till now, more research works have been processing on solving this issue by considering different constraints. Under this scenario, this paper attempts to develop a new clustering model with optimal cluster head selection by considering four major criteria like energy, delay, distance, and security. Further, for selecting the optimal CHs, this paper proposes a new hybrid algorithm that hybridizes the concept of dragon fly and firefly algorithm algorithms, termed fire fly replaced position update in dragonfly. Finally, the performance of the proposed work is carried out by comparing with other conventional models in terms of number of alive nodes, network energy, delay and risk probability.

The Internet of Things (IoT) industry is growing very fast to transform factories, homes, farms and practically everything else to make them efficient and intelligent. IoT is applied in different resilient scenarios and applications. IoT faces lots of challenges due to lack of computational power, battery and storage resources. Fortunately, the rise of blockchain technology facilitates IoT in many security solutions. Using blockchain, communication between IoT and emerging computing technologies is made efficient. In this work, we propose a secure service provisioning scheme with a fair payment system for Lightweight Clients (LCs) based on blockchain. Furthermore, an incentive mechanism based on reputation is proposed. We use consortium blockchain with the Proof of Authority (PoA) consensus mechanism. Furthermore, we use Smart Contracts (SCs) to validate the services provided by the Service Providers (SPs) to the LCs, transfer cryptocurrency to the SPs and maintain the reputation of the SPs. Moreover, the Keccak256 hashing algorithm is used for converting the data of arbitrary size to the hash of fixed size. AES128 encryption technique is used to encrypt service codes before sending to the LCs. The simulation results show that the LCs receive validated services from the SPs at an affordable cost. The results also depict that the participation rate of SPs is increased because of the incentive mechanism.

Internet of Things enabled Underwater Wireless Sensor Networks (IoT-UWSNs) are quite useful in monitoring different tasks including: from instrument monitoring to the climate recording and from pollution control to the prediction of natural disasters. However, there are some challenges, which affect the performance of a network, i.e., void hole occurrence, high Energy Consumption (EC) and low Packet Delivery Ratio (PDR). Therefore, in this work, two energy efficient routing protocols are proposed to maximize the PDR by minimizing the ratio of void hole occurrence. Scalability analysis of the proposed routing protocols is also performed. Additionally, feasible regions are computed to check the optimality of the proposed protocol in terms of EC. Furthermore, proposed protocols are compared with benchmark routing protocols in counterparts. Simulation results clearly show that proposed routing protocols achieved 80-81% higher PDR than GEographic and opportunistic routing with Depth Adjustment based topology control for communication Recovery (GEDAR) and Transmission Adjustment Neighbor-node Approaching Distinct Energy Efficient Mates (TA-NADEEM). Moreover, the ratio of void hole occurrence is minimized upto 30% approximately.

In this study, the antibacterial activity of tannic acid/amphiphilic cationic polymer (poly{2-[(methacryloyloxy)ethyl]trimethyl-ammonium chloride}, PMADQUAT) and tannic acid mixtures was examined on the strains of Gram-positive (S. aureus) and Gram-negative (E. coli CI2, E. coli K12, Klebsiella pneumonia and P. aeruginosa) bacteria. Tannic acid exhibited the antibacterial activity against all the studied bacterial strains. The ester linkage between glucose and gallic acid is vital for the antimicrobial activity of tannic acid. Tannic acid inhibited the growth of S. aureus and E. coli K12 (1 wt%) and reduced the growth of P. aeruginosa to 23%. Mixing cationic polymers having different structures (statistical copolymer, homopolymer and diblock polymer) with tannic acid lead to an increase in antibacterial activity of tannic acid and the stability and clarity of mixtures was higher than that of a pure tannic acid solution. Tannic acid/diblock polymer and tannic acid/homopolymer mixtures (0.1 wt%) were excellent for inhibiting the growth of planktonic E. coli K12 bacteria, and a low concentration (0.0001 wt%) of tannic acid/diblock polymer reduced its growth to 19%. By contrast, the tannic acid/statistical polymer mixture (0.0001 wt%) was excellent for inhibiting the growth of Gram-positive S. aureus bacteria.

Herein, we report a micro-plasma assisted solvothermal synthesis and characterization of zinc oxide nanosheets (ZnO-NSs) and their application for the removal of Cr6+ ion from aqueous solution. The morphological investigations by scanning electron microscopy (SEM) and transmission electron microscopy (TEM) confirmed the high-density growth of nanosheets with the typical sizes in the range of 145.8&ndash, 320.25 nm. The typical surface area of the synthesized ZnO-NSs, observed by Brunauer-Emmett-Teller (BET), was found to be 948 m2/g. The synthesized ZnO-NSs were used as efficient absorbent for the removal of Cr6+ ion from aqueous solution. Various parameters such as pH, contact time, amount of adsorbate and adsorbent on the removal efficiency of Cr6+ ion was optimized and presented in this paper. At optimized conditions, the highest value for removal was 87.1% at pH = 2 while the calculated maximum adsorption capacity was ~87.37 mg/g. The adsorption isotherm data were found to be best fitted to Temkin adsorption isotherm and the adsorption process followed the pseudo-first-order kinetics. Furthermore, the toxicity of ZnO-NSs were also examined against fibroblast cells, which show favorable results and proved that it can be used for wastewater treatment.

Higher education institutions (HEIs) consume significant energy and water and contribute to greenhouse gas (GHG) emissions. HEIs are under pressure internally and externally to improve their overall performance on reducing GHG emissions within their boundaries. It is necessary to identify critical areas of high GHG emissions within a campus to help find solutions to improve the overall sustainability performance of the campus. An integrated probabilistic-fuzzy framework is developed to help universities address the uncertainty associated with the reporting of water, energy, and carbon (WEC) flows within a campus. The probabilistic assessment using Monte Carlo Simulations effectively addressed the aleatory uncertainties, due to the randomness in the variations of the recorded WEC usages, while the fuzzy synthetic evaluation addressed the epistemic uncertainties, due to vagueness in the linguistic variables associated with WEC benchmarks. The developed framework is applied to operational, academic, and residential buildings at the University of British Columbia (Okanagan Campus). Three scenarios are analyzed, allocating the partial preference to water, or energy, or carbon. Furthermore, nine temporal seasons are generated to assess the variability, due to occupancy and climate changes. Finally, the aggregation is completed for the assessed buildings. The study reveals that climatic and type of buildings significantly affect the overall performance of a university. This study will help the sustainability centers and divisions in HEIs assess the spatiotemporal variability of WEC flows and effectively address the uncertainties to cover a wide range of human judgment.

Wireless sensor networks (WSNs) comprise tiny devices known as sensors. These devices are frequently employed in short-range communications and can perform various operations such as monitoring, collecting, analyzing, and processing data. WSNs do not require any infrastructure, are reliable, and can withstand adverse conditions. Sensor networks are autonomous structures in which the sensor nodes can enter or leave the network at any time instant. If the entering node is attacker node it will monitor the network operation and can cause security issues in the network that can affect communication. Existing literature presents security improvements in such networks in the form of cryptography, asymmetric techniques, key distribution, and various protocols. However, these techniques may not be effective in the case of autonomous structures and can increase computational complexity. In this paper, a convolutional technique (CT) is proposed that generates security bits using convolutional codes to prevent malicious node attacks on WSNs. Different security codes are generated at different hops and the simulation results demonstrate that the proposed technique enhances network security and reduces computational complexity compared to existing approaches.

This paper experimentally observed at a small level the influence of nozzle temperature change on warping deformation (WD), dimensional Accuracy (DA) and density. The materials chosen are pure PLA and advanced PLA+ specimens of rectangular shape of 63.5 mm × 9.53 mm × 3.2 mm produced by the end-user 3D printer based on fused deposition modeling (FDM). During the printing work, the nozzle temperature was conducted at twelve different values 195°C to 250°C with 5°C increments. Additionally, the infill density was set at 20% along with infill line direction of 0°, 90°, 45° and ±45°. After the fabrication, the FDM 3D printed parts naturally cooled down to room temperature at T = 23±2°C. As a result, the higher the nozzle temperature, the lower the deformed shape errors (with low uncertainty) of the specimens were. Experimental results show that the measured dimensions are always more than the original CAD file dimension along the height but less than the original CAD file dimensions along the width and length. The density measurements of both materials at 90° infill line direction have higher values compared with other directions (0°, 45°, ±45°), which have very similar results. The data and knowledge obtained from this investigation can be helpful for both an academic and an industrial perspective to set optimum nozzle temperature at small scale level and also it can be used to fabricate low-cost functional objects. Furthermore, it will also allow us to redesign the original CAD file in order to compensate the warping deformation encountered when using end-user FDM 3D additive manufacturing.

A versatile wet impregnation method was employed to conveniently and controllably deposit Fe2O3 nanoparticles on zeolites including commercial Y, mordenite and ZSM-5 with the similar framework Si/Al ratios and crystal sizes, respectively. The ultrafine Fe2O3 nanoparticles in size of 5 nm can be highly dispersed on zeolite Y matrix due to its much better wettability than ZSM-5 and mordenite. By using the obtained Fe2O3/zeolite composite as the heterogeneous Fenton-like catalysts, the degradation of phenol as a model reaction was systematically investigated, including the zeolite supports, particle size and dispersion of Fe2O3, and reaction conditions of H2O2 concentration, temperature, and pH value. The catalyst based on zeolite Y with Fe loading of 9% exhibited the best phenol degradation efficiency (> 90%) in neutral pH within 2 h. Its high catalytic activity in Fenton reaction can be attributed to the bifunctional properties of strong surface Bronsted acidity and high reactivity of octahedral Fe3+ in the highly-dispersed ultrafine Fe2O3 nanoparticles in size of 5 nm, which were the primary active centers to quickly decompose H2O2 into hydroxyl radicals. Since phenol degradation can be performed under mild conditions of ambient temperature (283-323 K) and a wide pH range (4.0-7.0), the catalysts can be easily recovered for recyclable use with stable degradation activity, which own the immense potential in deep treatment of organic pollutants in industrial wastewater. This work was sponsored by Shanghai Pujiang Program, China (No. 16PJ1401100 ), and the Shanghai Committee of Science and Technology, China (No. 15ZR1402000 ), Key Basic Research Program of Science and Technology Commission of Shanghai Municipality (No. 17JC1400100 ), the NSF of China (No. 21673048 ), National Youth Top Talent Support Program of National High-Level Personnel of Special Support Program (Youth Top-notch Talent Support Program) , the State Key Laboratory of Transducer Technology of China (No. SKT1503 ). The authors extend their appreciation to the International Scientific Partnership Program ISPP at King Saud University for funding this research work through ISPP# 0094. Appendix A Scopus

Poly(2‑(tert-butylamino)ethyl methacrylate) brushes (PTBAEMA) are grown from mesoporous silica nanoparticles via surface-initiated atom transfer radical polymerization (SI-ATRP). Linear PTBAEMA brushes are protonated and highly swollen at low pH; brushes are collapsed at pH higher than 7.7 due to deprotonation, as determined by dynamic light scattering (DLS). Quaternization of these brushes is conducted using 2-iodoethanol in alkali media. DLS measurement of nanoparticles shows that surface-confined quaternization occurs and produces pH-responsive brushes with a hydrophobic upper surface. Variation of the 2-iodoethanol reaction time enables the mean degree of surface quaternization. The pH-responsive behaviour of quaternized PTBEAMA brushes at 1 h reaction time indicates low degrees of surface quaternization, dictated by the spatial location of 2-iodoethanol. Almost uniformly quaternized brushes prepared when the conducted for 3 h and became less swollen at low pH than brushes that conducted for 1 h. The intensity of the C − C − O component (286.5 eV) in the C1s X-ray photoelectron spectrum increased, suggesting that the reaction with iodoethanol was successful occurred.

Nowadays, constrained battery life expectancy is an important issue for reliable data delivery in an Underwater Wireless Sensor Network (UWSN). Conventional transmission methodologies increase the transmission overhead, i.e., the collision of packets, which influence the data transmission. Replacement of the sensors' battery in brutal underwater environment is a difficult task. Therefore, to maintain a strategic distance from the unexpected failure of the network and to increase the life expectancy of the network, energy efficient routing protocols are required. At this end, in this paper, a proactive routing protocol with three different network types is proposed to solve the aforementioned issues. The proposed protocol adaptively changes its communication strategy depending on the type of the network, i.e., dense network, partially dense network and sparse network. This adaptive strategy helps the routing protocols to continue their transmission by avoiding the void holes. In the proposed protocol named Proactive routing Approach with Energy efficient Path Selection (PA-EPS-Case I), vertical inter-transmission layering concept is introduced (using shortest and fastest path) in the dense and partially dense region. In addition, cluster formation concept is also appended to make transmission successful in the sparse regions. The Packet Delivery Ratio (PDR) is improved by the proposed protocol with minimum End to End (E2E) delay and packet drop ratio. Scalability of the proposed routing protocols is also analyzed by varying the number of nodes from 100-500. A comparative analysis is performed with two cutting edge routing protocols namely: Weighting Depth and Forwarding Area Division Depth Based Routing (WDFAD-DBR) and Cluster-based WDFAD-DBR (C-DBR). Simulation results demonstrate that proposed protocol achieved 12.64% higher PDR with 20% decrease in E2E delay than C-DBR. Furthermore, the proposed routing protocol outperformed C-DBR in terms of packet drop ratio up to 14.29% with an increase of EC up to 30%.

Smart Grid (SG) plays vital role in modern electricity grid. The data is increasing with the drastic increase in number of users. An efficient technology is required to handle this dramatic growth of data. Cloud computing is then used to store the data and to provide numerous services to the consumers. There are various cloud Data Centers (DC), which deal with the requests coming from consumers. However, there is a chance of delay due to the large geographical area between cloud and consumer. So, a concept of fog computing is presented to minimize the delay and to maximize the efficiency. However, the issue of load balancing is raising; as the number of consumers and services provided by fog grow. So, an enhanced mechanism is required to balance the load of fog. In this paper, a three-layered architecture comprising of cloud, fog and consumer layers is proposed. A meta-heuristic algorithm: Improved Particle Swarm Optimization with Levy Walk (IPSOLW) is proposed to balance the load of fog. Consumers send request to the fog servers, which then provide services. Further, cloud is deployed to save the records of all consumers and to provide the services to the consumers, if fog layer is failed. The proposed algorithm is then compared with existing algorithms: genetic algorithm, particle swarm optimization, binary PSO, cuckoo with levy walk and BAT. Further, service broker policies are used for efficient selection of DC. The service broker policies used in this paper are: closest data center, optimize response time, reconfigure dynamically with load and new advance service broker policy. Moreover, response time and processing time are minimized. The IPSOLW has outperformed to its counterpart algorithms with almost 4.89% better results.

A series of poly(ethylene-co-vinyl alcohol)/poly(ε-caprolactone) blends with different compositions were prepared using solvent casting. The miscibility of this pair of polymers was investigated using differential scanning calorimetry (DSC), and proved by a negative Flory interaction parameter value calculated from the Nishi–Wang equation. The miscibility of this blend was also confirmed by scanning electronic microscopy (SEM). The thermal behaviors of the obtained materials were investigated by DSC, thermogravimetric analysis, and direct analysis in real-time–time-of-flight mass spectrometry and the results obtained were very relevant. Furthermore, the crystalline properties of the obtained materials were studied by DSC and X-ray diffraction where the Ozawa approach was adopted to investigate the non-isothermal crystallization kinetics. The results obtained revealed that this approach described the crystallization process well.

The dwindling of global petroleum deposits and worsening environmental issues have triggered researchers to find an alternative energy such as biodiesel. Biodiesel can be produced via transesterification of vegetable oil or animal fat with alcohol in the presence of a catalyst. A heterogeneous catalyst at an economical price has been studied widely for biodiesel production. It was noted that various types of natural waste shell are a potential calcium resource for generation of bio-based CaO, with comparable chemical characteristics, that greatly enhance the transesterification activity. However, CaO catalyzed transesterification is limited in its stability and studies have shown deterioration of catalytic reactivity when the catalyst is reused for several cycles. For this reason, different approaches are reviewed in the present study, which focuses on modification of waste-shell derived CaO based catalyst with the aim of better transesterification reactivity and high reusability of the catalyst for biodiesel production. The catalyst stability and leaching profile of the modified waste shell derived CaO is discussed. In addition, a critical discussion of the structure, composition of the waste shell, mechanism of CaO catalyzed reaction, recent progress in biodiesel reactor systems and challenges in the industrial sector are also included in this review.

The marked rise in criminal activity in society has made a difficult task for forensic scientists who aim to track any crime scene effectively, therefore visualization of latent fingerprints (LFPs) plays an increasingly vital role in forensics. In the present report, a highly sensitive solvatochromism, aggregation-induced emission-based 2-(4-nitrophenyl)-3H-benzocoumarin fluorescent dye (CFD) was fabricated using an ultrasonication protocol. The fluorescence properties of the CFD were analyzed using fluorescence spectrophotometer. The CFD produced a greenish yellow emission in solid and fluid states. An in-depth visualization of LFPs showed detailed ridge patterns under normal and ultraviolet light sources (254 and 365 nm) due to the excellent chemisorption of CFD onto the ridge patterns on the finger. All three types of ridge details were visualized without any background interference when using a simple and quick powder dusting method. Results revealed that, the present fluorescent dye can be used successfully for detection of latent fingerprints (LFPs) on various nonporous substrates surfaces, in organic light-emitting diodes applications (OLEDs), and for electrochemical sensing.

The composite of ceria has been widely studied as an electrode material for supercapacitors applications due to its high energy density. Herein, we synthesize CeO2/NiO nanocomposite via a hydrothermal route and explore its different aspects using various characterization techniques. The crystal structure is investigated using X-ray diffraction, Fourier transform infrared, and Raman spectroscopy. The formation of nanoflakes which combine to form flower-like morphology is observed from scanning electron microscope images. Selected area scans confirm the presence of all elements in accordance with their stoichiometric amount and thus authenticate the elemental purity. Polycrystalline nature with crystallite size 8&ndash, 10 nm having truncated octahedron shape is confirmed from tunneling electron microscope images. Using X-ray photoelectron spectroscopy the different oxidation states of Ce and Ni are observed which play the role of active sites in the electrochemical performance of this nanocomposite material. Cyclic Voltammetry(CV) measurements at different scan rates and Galvanic Charge Discharge (GCD) measurements at different current densities are performed to probe the electrochemical response which revealed the potential of CeO2/NiO nanocomposite as an electrode material for energy storage devices.

The objective of this paper is to establish the significance of the mycoremediation of contaminants such as Cd2+ to achieve sustainable and eco-friendly remediation methods. Industries such as electroplating, paint, leather tanning, etc. release an enormous amount of Cd2+ in wastewater, which can drastically affect our flora and fauna. Herein, we report on the in vitro bioadsorption of Cd2+ ions using fungal isolates obtained from different contaminated industrial sites. The detailed studies revealed that two fungal species, i.e., Trichoderma fasciculatum and Trichoderma longibrachiatum, were found to be most effective against the removal of Cd2+ when screened for Cd2+ tolerance on potato dextrose agar (PDA) in different concentrations. Detailed adsorption studies were conducted by exploring various experimental factors such as incubation time, temperature, pH, inoculum size, and Cd2+ salt concentrations. Based on optimum experimental conditions, T. fasciculatum exhibited approximately 67.10% removal, while T. longibrachiatum shows 76.25% removal of Cd2+ ions at pH 5.0, 120 h incubation time, at 30&deg, C. The inoculum sizes for T. fasciculatum and T. longibrachiatum were 2.5% and 2.0%, respectively. Finally, the morphological changes due to Cd2+ accumulation were examined using scanning electron microscopy (SEM). Further, Fourier transform infrared spectroscopy (FTIR) spectroscopy reveals the presence of various functional groups (-CH, &ndash, C=O, NH and &ndash, OH), which seem to be responsible for the efficient binding of Cd2+ ions over the fungal surfaces.

A polystyrene sulfonic acid-functionalized mesoporous silica (SBA-15-PSSA) catalyst was synthesized via an established multistep route, employing 2-bromo-2-methylpropionyl bromide as initiator of atom transfer radical polymerization. Fourier-transform infrared spectroscopy, thermogravimetric/differential thermal, Brunauer&ndash, Emmett&ndash, Teller, and transmission electron microscopy analyses revealed outstanding structural characteristics of the catalyst, including highly ordered mesopores, high surface area (726 m2/g), and adequate estimated concentrations of active sites (0.70 mmol H+/g). SBA-15-PSSA&rsquo, s catalytic performance was evaluated in the esterification of acetic acid and n-heptanol as a model system at various temperatures (50&ndash, 110 &deg, C), catalyst loads (0.1&ndash, 0.3 g), and reaction times (0&ndash, 160 min). The conversion percentage of acetic acid was found to increase with the temperature, catalyst load, and reaction time. Furthermore, results indicated a fast conversion in the first 20 min of the reaction, with remarkable conversion values at 110 &deg, C, reaching 86%, 94%, and 97% when the catalyst load was 0.1, 0.2, and 0.3 g, respectively, notably, at this temperature, 100% conversation was achieved after 60 min. At 110 &deg, C, the reaction conducted in the presence of 0.3 g of catalyst displayed more than 6.4 times the efficiency of the uncatalyzed reaction. Such activity is explained by the concomitant presence in the polymer of strong sulfonic acid moieties and a relatively high hydrophobic surface, with adequate numbers of active sites for ester production.

In order to improve the cell adhesion on poly(&epsilon, caprolactone) (PCL) scaffolds, poly(ethylene-co-vinyl alcohol) (E-VAL) which has hydroxyl groups capable of developing hydrogen bonds with celling was blended with this polymer. To reach this goal, a series of E-VAL/PCL blends with different compositions were prepared by the solvent casting method. The miscibility of the polymer blend was proved by differential scanning calorimetry and Fourier-transform infrared spectroscopy spectrometry. Furthermore, the mechanical properties of the polymer blends were assessed in their wet state by dynamic mechanical analysis. The surfaces wettability of blends and their components were examined through static contact angle measurements. The pore interconnections in the resulted scaffolds were achieved by the incorporation of naphthalene microparticles which were used as porogen and then removed in its gas state by sublimation under reduced pressure. The presence of pores interconnected inside the polymeric materials and their surface morphologies was examined by scanning electron microscopy. The in-vitro cytotoxicity and cell adhesion on the prepared materials were examined by an MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) assay.

The quality of communication between any two users in multi-hop wireless sensor networks directly depends upon the path selection among the available paths between end-users. The issue of selecting the optimized path from source to a destination becomes the necessary criteria for effective communication between end-users. The art of work mainly focuses on the selection of the path which has the best available bandwidth however they do not consider other network parameters such as distance, energy, the intensity of traffic which plays a critical role in routing. In this paper, an algorithm is presented for the selection of optimized route from source to destination by considering different network parameters along with the bandwidth and rank is given to all the available routes from source to destinations per their weights. The paper is validated using network simulator.

Breast Cancer (BC) is the second most common cancer in women after skin cancer and has become a major health issue. As a result, it is very important to diagnose BC correctly and categorizing the tumors into malignant or benign groups. We know that Machine Learning (ML) techniques have unique advantages and that is why they are widely used to analyze complex BC dataset and predict the disease. Wisconsin Diagnosis Breast Cancer (WDBC) dataset has been used to develop predictive models for BC by researchers in this field. The dataset has 573 instances and 32 features. In this paper, we have proposed a method for analyzing and predicting BC on the same dataset using Apache Spark. This big data framework is a very powerful tool for working on huge volume of data, such as healthcare data [4]. Principle Component Analysis (PCA) has been applied on the dataset for selecting the most important features. We have run experiments with top 6 and 10 features. The experiments are executed on Hadoop cluster, a cloud platform provided by the Electrical Engineering and Computer Science (EECS) department of University of Cincinnati. We have also made a comparison between the performance of different machine learning techniques: Decision Tree and Random Forest Classifier. We have set the performance of Decision Tree with top 10 features as a benchmark in our work. Random forest Classifier performs better than Decision Tree algorithm with top 6 as well as top 10 features. Random Forest achieves 97.52 % accuracy using top 10 features. Our results show that selecting the right features significantly improves accuracy in predicting BC.

Various ZnO nanomaterials such as nanorods, nanoparticles, and nanosheets were synthesized using Salvadora persica leaf extract via the sol&ndash, gel method. The prepared nanomaterials possess a large number of nanocavities. The synthesized nanomaterials were characterized using X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FT-IR), UV-visible diffuse reflectance studies (UV-DRS), scanning electron microscopy (SEM), and high resolution transmission electron microscopy (HT-TEM), and these nanomaterials were used to test photocatalytic applications for the degradation of highly hazardous methylene blue dye. The degradation efficiency was higher for materials with nanorods and nanosheets with nanocavities, this was due to the presence of the nanocavities, which made the catalyst more sensitive to light absorption. This method offers a green synthesis of different nanomaterials in bulk quantity at low cost.

A series of poly(ethylene‐co‐vinylalcohol)(PE‐VOL)/poly(D,L‐lactic‐co‐glycolic acid(PD,L‐LGA) blends with different compositions was prepared by solution casting, and its miscibilitywas proved through viscosimetry and differential scanning calorimetry (DSC) methods through apositive value of &alpha, (San et al. Eq.) and negative value of &chi, 1,2 (Nishi&ndash, Wang Equation). XRD analysisof the PE‐VOL/PD,L‐LGA system revealed a homogeneous distribution of PE‐VOL moleculesaggregated in the PD,L‐ LGA matrix and the crystalline structure of the semi crystalline copolymerwas conserved in the blend in aggregated form. It also revealed that the amorphous copolymerdispersed in the blend acted as a weak nucleating agent. The non‐isothermal crystallization kineticsof neat semi‐crystalline copolymer and the blend was used to describe the crystallization processusing the Ozawa approach. The thermal stability of these materials was investigated by the thermalgravimetry analysis. The isothermal decomposition of copolymers and their blend were carried outby high resolution mass spectrometry using direct‐analysis‐in‐real‐time method. Relevant resultsthat could highlight the miscible character of this blend are revealed through comparison of thedifferent fragments resulting from the decomposition of the blend with those of the purecomponents.

Novel Schiff bases of metformin hydrochloride and (ortho)para-nitrobenzaldehyde were synthesized by employing two efficient environmentally friendly methods, namely, stirring and microwave-assisted methods using water as the solvent. The advantage of microwave irradiation over the other methods was represented in the reduction of reaction time and wastes, and good yields, however, water in both methods plays the role of eco-friendly solvent. The structural properties of the (ortho)para-isomer products were analyzed by elemental analysis, Fourier transform infrared (FTIR) spectroscopy, UV-Visible (UV-Vis) spectroscopy, 1H nuclear magnetic resonance (NMR) spectroscopy, 13C NMR spectroscopy, mass spectroscopy, and differential scanning calorimetry (DSC). The newly synthesized compounds were screened for their antibacterial activity against selected Gram-positive (ATCC 25923, ATCC 43300, and ATCC 29212) and Gram-negative (ATCC 25922, ATCC 27853, and ATCC 700603) bacteria using the agar well diffusion method. Compared with the standard drug streptomycin, both Schiff bases exhibited moderate bactericidal activity against the tested bacteria with higher values of ortho-nitro compared with the para-nitro isomer, however, no effect on ATCC 43300 and ATCC 27853 was observed under the experimental conditions employed.

Underwater wireless sensor network (UWSN) is established in water bodies such as oceans, seas and rivers to observe the activity of military, to perform rescue operations and to do mining activity of resources. The sensor nodes communicate through acoustic channels. These nodes have limited battery life (energy), narrow bandwidth and a channel is incurred with delays and noise posing security thrust. The art of work presented different routing protocols in this era to utilize energy and bandwidth efficiently with less delay and to provide the security against black hole attack. However, these methods do not show an appropriate enhancement in the security and to utilize the bandwidth efficiently due to mobile environment. As a result of which, the delay also increases. In this paper a secured and bandwidth utilization path is enhanced using Bellman Inora Hex Hamming technique (BIHH), which not only improves the performance of the routing but also saves the energy. The presented approach is validated with network simulator.

The catalytic system of azo-bis-isobutyronitrile (AIBN) combined with (SiMes)Ru(PPH3)(Ind)Cl2 [M20] was investigated for the controlled radical polymerization of methyl methacrylate (MMA) in solution. Various factors that may influence the catalytic polymerization process, such as the aging time of the initiating system, AIBN/M20 ratio, concentration of monomer, polymerization time, temperature, and the nature of solvent were examined. The results showed that the yield, molecular weight, and molecular distribution are practically unaffected by these parameters; however, the syndiotactic stereo-structure tendency that characterizes the produced poly(methyl methacrylate) (PMMA) varied with temperature. The optimum conditions for PMMA synthesis were determined to produce an essentially syndiotactic material with uniformly high molecular weights. It was also revealed that the kinetics of MMA polymerization is of first order with respect to the concentration of monomer. A comparison was also made for some vinylic polymers synthesized either with the AIBN alone or with the AIBN/M20initiating system under the same conditions. Keywords: Catalytic effectiveness, Azobis-isisobutyronitrile/[(SiMes)Ru(PPh3)(Ind)Cl2] initiating system, Living radical, Polymerization conditions, Stereo-structure, Molecular weight distribution, Kinetics of polymerization

An n-butyl bromide/sodium dodecyl sulfate/n-butanol/water microemulsion system was chosen as a model of an organohalide-containing microemulsion. Two systems were prepared using the Bourayne method...

Herein, various poly(ethylene-co-vinylalcohol)/poly(δ-valerolactone) blends were prepared at different ratios by solvent casting for use in tissue engineering. The miscibility of these polymers was...

Wireless sensor networks (WSNs) consist of autonomous sensor nodes, which can predict the ambiance and act accordingly to transfer the data in adverse conditions. However, limited energy and security issues restrict the efficient communication in such networks. Art of the work presented energy-based approaches using cluster heads and security is provided using encryption. However, cluster head methodologies result in congestion, and security using encryption is difficult due to the self-organized structure. So, it degrades the performance of the network. In this paper, secure and energy-efficient method of optimization is being proposed using the Dij-Huff Method. The presented approach is validated by a network simulator.

A series of poly(acrylic acid)/poly(methyl vinyl ketone) (PAA/PMVK) blends with different compositions were prepared by the solvent casting method. The miscibility of this pair of polymers was investigated by differential scanning calorimetry(DSC), Fourier transform infra-red (FTIR) and X-Ray diffraction (XRD) techniques. An in-vitro cytotoxicity test of the drug-carrier system via MTT (3-(4,5-demethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) assay revealed no significant cytotoxic effects at concentrations up to 100 µg· ml−1. The STX/PAA-50 drug carrier systems were also prepared by solvent casting of solutions containing the sulfamethoxazole (STX) used as drug model and PAA/PMVK blend in N.N-dimethylformamide then crosslinked with acidified ethylene glycol. The release dynamic of STX from the prepared hydrogels was investigated in which the diffusion through the polymer matrix, the enhancement of the water solubility of STX, the influence of the initial drug concentration, the pH of the medium, and the effect of the degree of swelling of the polymer matrix on the release dynamic was evaluated. According to the total gastrointestinal transit time estimated by Belzer, the estimate distribution of STX released in the different organs indicated that the performance is obtained with the drug – carrier-system containing equal ratios of polymer and 10 wt% of STX (STX-10/PAA-50).

Poly(2-hydroxyethylmethacrylate-graft-ibuprofen) (IpGH) of different ibuprofen (Ibu) contents was prepared by grafting of Ibu groups on poly(2-hydroxyethyl methacrylate) (PHEMA) in an esterification reaction route. The resulted copolymers were characterized by Fourier transform infrared spectroscopy, nuclear magnetic resonance, differential scanning calorimetry, thermal gravimetric analysis, X-ray diffraction, and scanning electron microscope analysis. The cytotoxicity test and the free radical scavenging ability of this material were examined by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide tetrazolium (MTT) and 1,1-diphenyl-2-picryl-hydrazyl assay methods, respectively. The in vitro release study of Ibu through a retro-esterification reaction of IpHG material during 3 days reveals that the release dynamic depends on the initial Ibu grafted, pH media, and the swelling degree of PHEMA. It was also revealed that the water solubility of Ibu easily reached a maximum of 0.216 mg mL−1. T...

Immobilization of a ligand that selectively interacts with cancer cells to nanomaterials can enhance their diagnostic and therapeutic efficiency. In this study, we firstly demonstrate the high expression of receptor for cyclic nine-amino acid peptide LyP-1 (Cys-Gly-Asn-Lys-Arg-Thr-Arg-Gly-Cys) in both mouse and human pancreatic cancer. Based on these findings, sub-50 nm multifunctional superparamagnetic mesoporous nanospheres with surface modified with LyP-1 are rationally designed. Theses nanospheres have a core of silica-protected magnetite nanoparticle and a shell of FITC-labeled mesoporous silica, and they are able to specifically recognize and conjugate with the pancreatic cancer cell in vitro, as verified by the combined techniques of fluorescent imaging and T2 weight magnetic resonance imaging. After systematic administration, these LyP-1 immobilized nanospheres are found to actively target to mouse orthotopic xenograft of pancreatic cancer, which opens up the door for applications in early probing and diagnosis of pancreatic cancer by the multimodal imaging.

The implications of change on local processes have attracted significant research interest in recent times. In urban settings, green spaces and forests have attracted much attention. Here, we present an assessment of change within the predominantly desert Middle Eastern city of Riyadh, an understudied setting. We utilized high-resolution SPOT 5 data and two classification techniques&mdash, maximum likelihood classification and object-oriented classification&mdash, to study the changes in Riyadh between 2004 and 2014. Imagery classification was completed with training data obtained from the SPOT 5 dataset, and an accuracy assessment was completed through a combination of field surveys and an application developed in ESRI Survey 123 tool. The Survey 123 tool allowed residents of Riyadh to present their views on land cover for the 2004 and 2014 imagery. Our analysis showed that soil or &lsquo, desert&rsquo, areas were converted to roads and buildings to accommodate for Riyadh&rsquo, s rapidly growing population. The object-oriented classifier provided higher overall accuracy than the maximum likelihood classifier (74.71% and 73.79% vs. 92.36% and 90.77% for 2004 and 2014). Our work provides insights into the changes within a desert environment and establishes a foundation for understanding change in this understudied setting.

In the last couple of decades, numerous energy management strategies have been devised to mitigate the effects of greenhouse gas emission, hence introducing the concept of microgrids. In a microgrid, distributed energy generators are used. Microgrid enables a point which ameliorates in exchanging power with the main grid during different times of day. Based on the system constraints, in this work, we aim to efficiently minimize the operating cost of the microgrid and shave the power consumption peaks. For this purpose, we introduce an improved binary bat (iBBat) algorithm which helps to schedule the load demand of smart homes and energy generation from distributed generator of microgrid to the load demand and supply. The proposed energy management algorithm is applied to both grid-connected and islanded modes of the microgrid. The constraints imposed on the algorithm ensure that the load of electricity consumer does not escalate during peak hours. The simulation results are compared with BBat and binary flower pollination algorithm, which validate that the iBBat reflects substantial reduction in operating cost of microgrid. Moreover, results also show a phenomenal reduction in the peak-to-average ratio of load demand from main the main grid.

An increase in the world&rsquo, s population results in high energy demand, which is mostly fulfilled by consuming fossil fuels (FFs). By nature, FFs are scarce, depleted, and non-eco-friendly. Renewable energy sources (RESs) photovoltaics (PVs) and wind turbines (WTs) are emerging alternatives to the FFs. The integration of an energy storage system with these sources provides promising and economical results to satisfy the user&rsquo, s load in a stand-alone environment. Due to the intermittent nature of RESs, their optimal sizing is a vital challenge when considering cost and reliability parameters. In this paper, three meta-heuristic algorithms: teaching-learning based optimization (TLBO), enhanced differential evolution (EDE), and the salp swarm algorithm (SSA), along with two hybrid schemes (TLBO + EDE and TLBO + SSA) called enhanced evolutionary sizing algorithms (EESAs) are proposed for solving the unit sizing problem of hybrid RESs in a stand-alone environment. The objective of this work is to minimize the user&rsquo, s total annual cost (TAC). The reliability is considered via the maximum allowable loss of power supply probability ( L P S P m a x ) concept. The simulation results reveal that EESAs provide better results in terms of TAC minimization as compared to other algorithms at four L P S P m a x values of 0%, 0.5%, 1%, and 3%, respectively, for a PV-WT-battery hybrid system. Further, the PV-WT-battery hybrid system is found as the most economical scenario when it is compared to PV-battery and WT-battery systems.

The feature of bidirectional communication in a smart grid involves the interaction between consumer and utility for optimizing the energy consumption of the users. For optimal management of the energy at the end user, several demand side management techniques are implemented. This work proposes a home energy management system, where consumption of household appliances is optimized using a hybrid technique. This technique is developed from cuckoo search algorithm and earthworm algorithm. However, there is a problem in such home energy management systems, that is, an uncertain behavior of the user that can lead to force start or stop of an appliance, deteriorating the purpose of scheduling of appliances. In order to solve this issue, coordination among appliances for rescheduling is incorporated in home energy management system using game theory. The appliances of the home are categorized in three different groups and their electricity cost is computed through the real-time pricing signals. Optimization schemes are implemented and their performance is scrutinized with and without coordination among the appliances. Simulation outcomes display that our proposed technique has minimized the total electricity cost by 50.6% as compared to unscheduled cost. Moreover, coordination among appliances has helped in increasing the user comfort by reducing the waiting time of appliances. The Shapley value has outperformed the Nash equilibrium and zero sum by achieving the maximum reduction in waiting time of appliances.

Deoxygenation processes that exploit milder reaction conditions under H2-free atmospheres appear environmentally and economically effective for the production of green diesel. Herein, green diesel was produced by catalytic deoxygenation of chicken fat oil (CFO) over oxides of binary metal pairs (Ni–Mg, Ni–Mn, Ni–Cu, Ni–Ce) supported on multi-walled carbon nanotubes (MWCNTs). The presence of Mg and Mn with Ni afforded greater deoxygenation activity, with hydrocarbon yields of >75% and n-(C15 + C17) selectivity of >81%, indicating that decarboxylation/decarbonylation (deCOx) of CFO is favoured by the existence of high amount of lower strength strong acidic sites along with noticeable strongly basic sites. Based on a series of studies of different Mg and Mn dosages (5–20 wt%), the oxygen free-rich diesel-range hydrocarbons produced efficiently by Ni10–Mg15/MWCNT and Ni10–Mn5/MWCNT catalysts yielded >84% of hydrocarbons, with n-(C15 + C17) selectivity of >85%. The heating value of the green diesel obtained complied with the ultra-low sulphur diesel standard.