In this study, a novel binary nanocomposite system based on TiO₂-SiO₂ was functionalized with trimethylolpropane triacrylate (TMPTA) and characterized by XPS and XRD. Results revealed that TiO₂-SiO₂ nanoparticles were covalently functionalized. Functionalized nanoparticles at low concentrations (0.1 wt% and 0.5 wt%) were dispersed in acrylic acid acting as a polymer matrix. Nanocomposite coatings analysis demonstrate to achieve superhydrophilic properties as well as very good optical characteristics. Water contact angle characterization showed the functionalization effect by achieving a superhydrophilic behavior with a contact angle less than 5°. UV-Vis measurements demonstrated high optical transmittance above 95% for the coatings. Based on the obtained results a mechanism describing the chemical interactions of the constituents responsible for the synergy in the nanocomposite as well as the morphological play role in the behavior are presented.

Some contaminants of emerging concern (CECs) are known to survive conventional wastewater treatment plants, which introduce them back to the environment and can potentially cycle up in drinking water supplies. This is especially concerning because of the inherent ability of some CECs to induce physiological effects in humans at very low doses. Advanced oxidation processes (AOPs) such as TiO2 based photocatalysis are of prominent interest for addressing CECs in aqueous environments. Natural water resources often contain dissolved metal cations concentrations in excess of targeted CEC concentrations. These cations may significantly, adversely impact degradation of CECs by scavenging TiO2 surface generated electrons. Consequently, simple pseudo first order or Langmuir-Hinshelwood kinetics are not sufficient for reactor design and process analysis in some scenarios. Rhodamine B dye and dissolved copper cations were studied as reaction surrogates to demonstrate that TiO₂ catalyzed degradation for very dilute solutions is very nearly completely due to homogeneous reaction with hydroxyl radicals and that in this scenario the hole trapping pathway has negligible impact. Chemical reaction kinetic studies were then carried out to develop a robust model for RB/metal reactions that is exact in the electron pathways for hydroxyl radical production and metal scavenging.

The wide range of applications of nanoparticles (NPs) has increased the probability of environmental and occupational exposure. In a previous comparative study on cell line A549, we observed that oxidative stress caused by Co₃O₄ NPs affects the energetic homeostasis and the detoxification capacity, preventing autophagy induced by TiO₂ NPs. In this study, we have investigated the effects of NPs on the cell cycle.Cytofluorimetric analysis showed a slow-down of the cell cycle progression for both NPs, with increases in the percentage of resting cells in the G0/G1. These observations were confirmed by a reduced expression of all cyclins, especially of CCNE1 and CDK2, involved in the late stages of the G1 phase, coupled with a significant increase in the expression of p21 only for Co₃O₄ NP exposure. On the contrary, the effects of TiO₂ NPs were modest. Cell cycle related miRNA-34a, miRNA-126 and miRNA-1290 resulted increased at different early time-points (4-8h) but were down-expressed at 24h-48h only after TiO₂ NP exposure. Our results show that NPs have an antiproliferative effect and deregulate cell cycle on A549 cells. These effects should not be underestimated because regulation of cycle progression is crucial for cell survival and repair of genetic damage.

This work emphasizes to use silver decorative method to enhance the antibacterial activity of TiO₂ and ZnO nanoparticles. These silver decorated nanoparticles (hybrid nanoparticles) were synthesized by using sodium borohydride as a reducing agent, with the weight ratio of Ag precursors: oxide nanoparticles = 1: 30. The morphology and optical property of these hybrid nanoparticles were investigated using transmission electron microscopy (TEM) and UV–vis spectroscopy. The agar-well diffusion method was used to evaluate their antibacterial activity against both Staphylococcus aureus and Escherichia coli bacteria, with or without light irradiation. The TEM images indicated clearly that silver nanoparticles (AgNPs, 5-10 nm) were well deposited on the surface of nano-TiO₂ particles (30-60 nm). Besides, smaller AgNPs (< 2 nm) were dispersed on the surface of nano-ZnO particles (20-50 nm). UV-vis spectra confirmed that the hybridization of Ag and oxide nanoparticles led to shift the absorption edge of oxide nanoparticles to the lower energy region (visible region). The antibacterial tests indicated that both oxide pure nanoparticles did not exhibit inhibitory against bacteria, with or without light irradiation. However, the presence of AgNPs in their hybrids, even at low content (< 40 mg/mL) leads to a good antibacterial activity and the higher inhibition zones under light irradiation as compared to that in dark was observed.

MoS₂/TiO₂ nanostructures made of MoS₂ nanoparticles covering TiO₂ nanosheets have been synthesized, either via ex-situ or in-situ approaches. Morphology and structure of MoS₂/TiO₂ hybrid nanostructures have been investigated and imaged by means of X-ray diffraction (XRD) analysis and high-resolution transmission electron microscopy (HRTEM), while the vibrational and the optical properties have been investigated by Raman, Fourier-transform infrared spectroscopy (FTIR) and UV−visible (UV-Vis) techniques. The different stacking degrees together with the size distribution of the MoS₂ nanosheets, decorating the TiO₂ nanosheets, have been carefully obtained from HRTEM images. The nature of the surface sites on the main exposed faces of both materials has been detected by means of in-situ FTIR spectra of adsorbed CO probe molecule. The results coming from the ex-situ and in-situ approaches will be compared, by highlighting the role of the synthesis processes in affecting morphology and structure of MoS₂ nanosheets, including their curvature, surface defects, and stacking order. Some more, it will be shown that the in-situ approach is affecting the reactivity of the TiO₂ nanosheets too, hence in turn affects the MoS₂/TiO₂ nanosheets interaction.

Hot rolling tests of a low-alloy steel were conducted at a rolling temperature of 850 ℃ under different lubrication conditions, including benchmarks (dry condition and water) and water-based nanolubricants containing different concentrations of nano-TiO₂ from 1.0 to 8.0 wt%. The effects of nanolubricants on rolling force, surface roughness, thickness of oxide scale and microstructure were systematically investigated through varying nano-TiO₂ concentrations. The results show that the application of nanolubricants can decrease the rolling force, surface roughness and oxide scale thickness of rolled steels, and refine ferrite grains. In particular, the nanolubricant containing an optimal concentration (4.0 wt%) of nano-TiO₂ demonstrates the best lubrication performance, owing to the synergistic effect of lubricating film, rolling, polishing and mending generated by nano-TiO₂.

Wound infections evidently appeared in times of World War I that accounted a significant mortality and morbidity rate among injured soldiers. Currently, around 11 million people worldwide require medical treatment for wound infections and 300,000 die every year due to untreated wound infection. The extensive use of antibiotics to treat wound infection leads to emerging new microbial strains that are resistant to many antibiotics. There is a growing concern on the emergence and re-emergence of drug-resistant pathogens such as multi-resistant bacterial strains. Hence, the development of new antimicrobial compounds or the modification of those that already exist to improve antibacterial activity is a high priority area of research. During the past few decades, nanotechnology has arisen with new promising technology for synthesis of nanobiomaterials. Metallic nanoparticles (NPs) are considered as new alternative treatment with superior antibacterial activity. In this study, new formulation of titanium oxide (TiO2) NPs with different sizes were synthesized and characterized. Genotoxicity, mutagenicity and antibacterial activities of TiO2 NPs against the causative agents of wound infection were investigated. Antibacterial activity of TiO2 NPs was conducted against three ATCC ® bacterial strains: methicillin-resistant Staphylococcus aureus (MRSA), Escherichia coli and Pseudomonas aeruginosa. The results clearly illustrate a superior antibacterial activity of all newly formulated TiO2 NPs against the most causative agents of wound infection. Most of our TiO2 NPs showed non-genotoxic and non-mutagenic results at the maximum concentrations. Findings of this study will enhance the future of the therapeutic strategies against the resistant pathogenic strains that cause wound infections.

Read-Across Structure-Activity Relationship (RASAR) is an emerging cheminformatic approach that combines the usefulness of a QSAR model and similarity-based Read-Across predictions. In this work, we have generated a simple, interpretable, and transferable quantitative-RASAR (q-RASAR) model which can efficiently predict the cytotoxicity of TiO2-based multi-component nanomaterials. The data set involves 29 TiO2-based nanomaterials which contain specific amounts of noble metal precursors in the form of Ag, Au, Pd, and Pt. The data set was rationally divided into training and test sets and the Read-Across-based predictions for the test set were generated using the tool Read-Across-v4.1 available from https://sites.google.com/jadavpuruniversity.in/dtc-lab-software/home. The hyperparameters were optimized based on the training set data and using this optimized setting, the Read-Across-based predictions for the test set were obtained. The optimized hyperparameters and the similarity approach, which yields the best predictions, were used to calculate the similarity and error-based RASAR descriptors using the tool RASAR-Desc-Calc-v2.0 available from https://sites.google.com/jadavpuruniversity.in/dtc-lab-software/home. These RASAR descriptors were then clubbed with the physicochemical descriptors and were subjected to features selection using the tool Best Subset Selection v2.1 available from https://dtclab.webs.com/software-tools. The final set of selected descriptors was used to develop multiple linear regression based q-RASAR models, which were validated using stringent criteria as per the OECD guidelines. Finally, a random forest model was also developed with the selected descriptors. The final machine learning model can efficiently predict the cytotoxicity of TiO2-based multi-component nanomaterials superseding previously reported models in the prediction quality.

Rapid progress in the development of highly efficient nanoparticle-based construction technologies has not always been accompanied by a corresponding understanding of their effects on human health and ecosystems. Here, we compare toxicological effects of pristine TiO₂, ZnO and SiO₂, and coated SiO₂ nanoparticles and evaluate their suitability as additives to consolidants of weathered construction materials. First, WST-1 and LDH assays were used to determine the viability of human alveolar A549 cells at various nanoparticle concentrations (0–250 μg mL⁻¹). While the pristine TiO₂ and coated SiO₂ nanoparticles did not exhibit any cytotoxic effect up to the highest tested concentration, the pristine SiO₂ and ZnO nanoparticles significantly reduced cell viability. Second, as all the developed nanoparticle-modified consolidants increased the mechanical strength of weathered sandstone, the decisive criterion for the selection of the most suitable nanoparticle additive was as low toxicity as possible. We believe that this approach will be of high importance for industry to identify materials representing top functional properties and low toxicity at an early stage of the product development.

Various crystallite size estimation methods were used to analyze X-ray diffractograms of spherical cerium dioxide and donut-like titanium dioxide anatase nanoparticles aiming to evaluate their reliability and limitations. The microstructural parameters were estimated from Scherrer, Monshi, Williamson-Hall, and their variants: i) uniform deformation model, ii) uniform strain deformation model, and iii) uniform deformation energy density model, and also size-strain plot, and Halder-Wagner method. For that, and improved systematic Matlab code was developed to estimate the crystallite sizes and strain, and the linear regression analysis was used to compare all the models based on the coefficient of determination, where the Halder Wagner method gave the highest value (close to 1). Therefore, being the best candidate to fit the X-ray Diffraction data of metal-oxide nanoparticles. Advanced Rietveld was introduced for comparison purposes. Refined microstructural parameters were obtained from a nanostructured 40.5 nm Lanthanum hexaboride nanoparticles and correlated with the above estimation methods and transmission electron microscopy images. In addition, electron density modelling was also studied for final refined nanostructures, and μ-Raman spectra were recorded for each material estimating the mean crystallite size and comparing by means of a phonon confinement model.

The TiO₂ nanostructures resulted by pyrolysis of TiCl₄ at low temperature of 80 ^oC are found to be a mixture of amorphous TiO₂ complexes and anatase nanostructure whose ratio depends on the pH of the pyrolysis medium. At low pH level, the resulting TiO₂ nanostructure is predominant anatase and gradually shifts to the amorphous TiO₂ complexes with pH level increasing. By means of heat treatment, the amorphous TiO₂ complexes can be converted back to the anatase nanostructure and then transform to rutile with the elevating temperature. Amongst of the TiO₂ nanostructure recovered from amorphous TiO₂ complexes, the anatase shows to be the most effective photocatalyst in decomposition of methylene blue.

In this changing world, we all are surrounded by the surmountable risk of getting injured. Amongst various risk factors, major burns are the most distressing and catastrophic. Burn wounds are not easy to heal via natural healing process and ultimately ended up with scar formation. If the degree of burn is high then the loss of tissue and its function is very common. To fasten-up the natural burn wound healing; zinc, an essential trace element is found to be very much effective. But due to its’ particle size limitation, less contact with wounded cells and tissues, and high inherent toxicity restrict its use. Needlessly, zinc is an element with dual action i.e. both antimicrobial and wound healing it is a prime choice to apply its aptitude in burn wound healing. To overcome the documented limitations zinc has converted to nanoparticle form. Zinc oxide nanoparticles, in particular, have attained ample of interest due to their unique properties and potential antimicrobial activity along with wound healing activity which makes it promising for the healing of topical burn wounds. Plant mediated green synthesis of nano-metal oxide particles is gaining a lot of significance due to its simplicity, eco-friendliness and extensive antimicrobial activity and recommended as an appealing substitute to not only physical methods but also chemical methods avoiding the use of the high rate of toxic chemicals and extreme surroundings. This study includes ZnO NPs role in burn wound healing with Phyto-mediated synthesis methods to provide evidence of their potential applications. Additionally, it provides an overview of traditional methods used for the synthesis of ZnO nanoparticles and characterization techniques to obtain information concerning the size, shape and optical properties along with toxicity and safety concern of ZnO NPs and its biomedical applications.

In this research we are reporting gas sensing properties of TiO_2-x/TiO₂-based hetero-structure, which was ‘self-heated’ by current that at constant potential passed through the structure. Amperometric measurements were applied for the evaluation of sensor response towards ethanol, methanol, n-propanol and acetone gases/vapors. The sensitivity towards these gases was based on electrical resistance changes, which were determined by amperometric measurements of current at fixed voltage applied between Pt-based contacts/electrodes deposited on TiO_2-x/TiO₂-based layer. XRD analysis revealed the formation of TiO_2-x/TiO₂-based hetero-structure, which is mainly based on Ti₃O₅/TiO₂ formed during hydro-thermal oxidation based sensing layer preparation process. Additionally, photoluminescence and time-resolved photoluminescence decay kinetics based signals of this sensing structure revealed the presence of TiO₂ mainly in the anatase phase in the TiO_2-x/TiO₂-based hetero-structure, which was formed at 400°C annealing temperature. The evaluation of TiO_2-x/TiO₂-based gas sensing layer was performed at several different temperatures (25°C, 72°C, 150°C, 180°C) and at these temperatures different sensitivity to aforementioned gaseous materials was determined.

Electron-hole recombination and narrow range utilization of sunlight limit the photocatalytic efficiency of TiO2. We synthesized a carbon dots (CDs) modified TiO2 nanoparticles (NPs) with flower-like mesoporous structure, i.e., porous TiO2/CDs nanoflowers. Among such hybrid parti-cles, CDs worked as photosensitizers for the mesoporous TiO2 and enabled the resultant TiO2/CDs nanoflowers with a wide-range light absorption. Rhodamine B (Rh-B) was employed as a model organic pollutant to investigate the photocatalytic activity of the TiO2/CDs nanoflowers. The results demonstrated that the decoration of CDs on both TiO2 nanoflowers and P25 NPs enabled a significant improvement of the photocatalytic degradation efficiency compared with the pristine TiO2. TiO2/CDs nanoflowers with porous structure and larger surface areas than P25 showed a higher efficiency owing to prevent local aggregation of carbon materials. All the results revealed that the introduced CDs and the unique mesoporous structure, large surface areas and loads of pore channels of the prepared TiO2 NPs played important roles in the enhancement of the photocatalytic efficiency of the TiO2/CDs hybrid nanoflowers. Such TiO2/CDs composite NPs also opens a door for photodegradation, photocatalytic water splitting and enhanced solar sun-light as light source.

BODIPY dyes have recently raised attention as potential photosensitizers. In this work, commercial and novel photosensitizers (PSs) based on BODIPY chromophores (haloBODIPYs and orthogonal dimers strategically designed with intense bands in the blue, green or red region of the Visible spectra and high singlet oxygen production) were covalently linked to mesoporous silica nanoparticles (MSNs) further functionalized with PEG and folic acid (FA). MSNs of approximately 50 nm in size with different functional groups were synthesized to allow multiple alternatives of PS-PEG-FA decoration of their external surface. Different combinations varying the type of PS (commercial Rose Bengal, Thionine and Chlorine e6 or custom-made BODIPY-based), the linkage design and the length of PEG are detailed. All the nanosystems were physicochemically characterized (morphology, diameter, size distribution and PS loaded amount) and photophysically studied (absorption capacity, fluorescence efficiency, and singlet oxygen production) in suspension. For the most promising PS-PEG-FA silica nanoplatforms, the biocompatibility in dark conditions and the phototoxicity under suitable irradiation wavelengths (blue, green, or red) at regulated light doses (10-15 J/cm2) were compared with PSs free in solution in HeLa cells in vitro.

TiO₂ nanorod as a superior nanostructure has attracted a lot of attention to exert in the photocatalytic and photoelectrocatlytic applications in recent years. Nevertheless, its practical usage is restricted by a number of limitations such as the large band gap energy, the low rate of photo-induced carriers generation and the high rate of charge carriers recombination. Therefore in this study, incorporation of TiO₂ nanorod with WO₃ is proposed as a suitable approach to overcome these defects. In this regard, WO₃-TiO₂ nanorod was constructed by a facile one pot hydrothermal method in two incessant steps and was then employed as a potent photoanode for photoelectrocatalytic hydrogen generation. The morphology, elemental compositions and optical properties were characterized by the FESEM, EDS and DRS analysis, respectively. Furthermore, voltammetry analyses were performed to assay the photoelectrochemical features of WO₃-TiO₂ nanorod. The results confirmed that the incorporation of TiO₂ nanorod with WO₃ not only significantly made the band gap energy narrower (from 3eV to 2eV), but also dramatically intensified the photocurrent density and photoconversion efficiency from 1mA.cm^-2 to 1.8mA.cm^-2 and from 0.3% to 0.45%, respectively. As a consequence of improving optical properties and photoelectrochemical features, WO₃-TiO₂ nanorod could generate 2.43 mmol H₂ during 100 min under UV irradiation, which was 1.71 times more than hydrogen generated over pure TiO₂ nanorod

Heavy metals are non-biodegradable and have a high toxicity effect to living things which makes their presence in the environment extremely dangerous. The method of handling heavy metals waste by photocatalysis techniques using TiO2/SiO2 composite showed a good performance in reducing harmful pollutants. In this study, SiO2 from Bengkulu beach sand was used as a support material for TiO2 photocatalyst to reduce Cr(VI) and Pb(II) concentrations. SiO2 was obtained through leaching techniques using NaOH as a solvent. The TiO2/SiO2 composite photocatalyst were synthesized using a solvothermal method at 130 °C and then characterized using XRD, FTIR, SEM and PSA. Based on the XRD diffractogram, the synthesized TiO2 showed the anatase structure while the SiO2 showed the amorphous structure. Ti-O-Si bond is defined in the IR spectra, which indicates that the relationship between TiO2 and SiO2 is a chemical interaction. The results of SEM and PSA characterizations show agglomerated spherical (round) particles with a mean particle size of 616.9 nm. The TiO2/SiO2 composite of 7:1 ratio showed the highest photocatalytic activity after 180 minutes of UV irradiation, with a concentration-decrease percentage of 93.77% and 93.55% for for Cr(VI) and Pb(II), respectively.

This study investigated dry reforming of methane with combined catalysts supported on γ-Al2O3 support doped with 3.0 wt. % TiO2. The physicochemical properties of all the catalysts were determined by inductively-coupled plasma/mass spectrometry metal analysis, nitrogen physisorption, X-ray diffraction, temperature programmed reduction/desorption, thermogravimetric analysis, and scanning electron microscopy. The addition of CeO2 and MgO to Ni strengthened the interaction between the Ni and the support. The catalytic activity results indicated that the CeO2 and MgO addition to Ni did not do much in retarding carbon deposition, but they improved the activity of the catalysts. Among the tested catalysts, it was found that the catalyst with the composition of 5.0 wt % NiO-10.0 wt % CeO2/3.0 wt %TiO2-γ-Al2O3 resulted in the highest CH4 and CO2 conversion with H2/CO mole ratio close to unity. The optimum reaction conditions in terms of reactant conversion and H2/CO mole ratio were achieved by varying space velocity and CO2/CH4 mole ratio.

In this work, pure TiO₂ and nano-magnetic of Fe₃O₄/TiO₂ were synthesized for degradation of 2,4-dichlorophenol (2, 4-DCP) as an organic pollutant. A range of analytical techniques including XRD, DRS, FESEM, and VSM were employed to reveal the crystal structure, morphology and property of the nanocomposite. The XRD results showed the prepared samples including 100% anatase phase. We obtained the band gap energy 2.9 and 2.8 eV for pure TiO₂ and Fe₃O₄/TiO₂ respectively. VSM results demonstrate that easy, fast separation and redispersion of Fe₃O₄/TiO₂ sample can be realized. We obtained 62% and 31% degradation of 2,4-DCP in the presence of Fe₃O₄/TiO₂ and pure TiO₂ under visible light respectively.

The present study aims at deposition of zinc phosphate coatings with the incorporation of nano Titanium dioxide particles by chemical phosphating method. Zinc phosphate coatings were developed on low carbon steel by using nano TiO2 in the standard phosphating bath. The Coated low carbon steel samples were assessed for corrosion studies using electrochemical impedance spectroscopy and potentiodynamic polarisation techniques in 3.5% NaCl solution. Chemical composition of the coatings was analysed by energy dispersive X-ray spectroscopy (EDX). Significant variations in the coating weight, porosity and corrosion resistance were observed with the addition of nano TiO2 in the phosphating bath. Corrosion rate of nano TiO2 incorporated chemical phosphate coated samples was found to be 3.5 mpy which was 4 times less than the bare uncoated low carbon steel (~14 mpy). Electrochemical impedance spectroscopy studies revels in the reduction of porosity in nano TiO2 phosphate coated samples. It was found that nano TiO2 particles in the phosphating solution yielded phosphate coatings of higher coating weight, greater surface coverage and enhanced corrosion resistance than the normal zinc phosphate coatings (developed using normal phosphating bath).

In this research, first a binary nanocomposite of magnetic recyclable photocatalyst Fe₃O₄/TiO₂, was synthesized by sol gel technique. Then, in order to enhance the photocatalytic activity of the synthesized nanocomposite, it was deposited by silver nanoparticles for using in degradation of organic pollutants 2, 4-dichlorophenol (2, 4-DCP) under visible light. A range of analytical techniques including XRD, FESEM/EDX, DRS, VSM and N₂ physisorption were employed to reveal the crystal structure, morphology and property of the nanocomposites. We obtained 32% and 55% degradation of 2, 4-DCP under visible light after 180 min irradiation in the presence of Fe₃O₄/TiO₂ and Fe₃O₄/TiO₂/Ag respectively. Thus, the excellent visible light photocatalytic activity of Fe₃O₄/TiO₂/Ag sample can be attributed to the surface plasmon resonance effect of Ag nanoparticles deposited on Fe₃O₄/TiO₂ nanocomposite.

In this work, TiO₂ QDs modifed NiO nanosheets was employed to imporve the room-temperature NO₂ sensing properties of NiO. The gas-sensing studies showed that the response of nanocomposites with the optimal ratio to 60 ppm NO₂ was nearly 10 times larger than that of bare NiO, exhibiting potential application in gas-sensing. Considering the commonly reported immature mechanism that the effective charge transfer between two phases contribute to enhanced sensitivity, QDs sensitization mechanism was further detailed by designing a seirs of contrast experiments. First, the important role of QDs size effect was revealed by comparing a little enhanced sensitivity of TiO₂ particle-modified NiO with largely enhanced senstivity of TiO₂ QDs-NiO. Second, and more important, the direct evidence of heterointerface charge transfer efficiency was detailed by extracted interface bond (Ti-O-Ni) using XPS peak fitting. We hope this work can provide guideline to design more QDs-modified nanocomposites with the higher sensitivty for practical application.

This research was presented the special designed microfluidic device generated for sperm separation based on assumption of different surface electrical charged of sperms X and Y. However, to avoid ethical problem, the microfluidic chip has been tested with the mimic electrical charged particles, TiO₂-coated Polystyrene beads, (TiO₂-coated Ps-beads), instead of spermatozoa. The work has been separated into three main parts. Firstly, the simply but efficient fabrication of negatively charged TiO₂-coated Ps-beads has been presented. In addition, various characterization techniques such as X-ray diffraction (XRD), Tungsten Scanning Electron Microscopy (W-SEM) with energy-dispersive X-ray spectroscopy (EDS) mode, and X-ray Absorption Spectroscopy (XAS), have been reported in this work to elucidate the reasons behind the persistence of negatively charged on the surface of TiO₂-coated Ps-beads. Results show that the fabricated TiO₂-coated Ps-beads was partly coated in the mixed forms of amorphous Ti⁴⁺ and had caused a negatively charge to appear on the surface after fabrication and had sustained its electrical charged for long. Secondly, process of simulation and fabrication of microfluidic device was presented. Finally the negatively charged TiO₂-coated Ps-beads were tested in this microfluidic devices. For design of microfluidic devices integrated with a couple of microelectrodes, the simulated structures were fabricated by photolithographic technique and tested with the Ps-beads. Percentage of validation for Ps-beads separation indicated that the 100 mm-distance-between-electrodes microfluidic device exhibits to be the highest performance prototype at 86.96%. For further confirmation, another model so called the single path prototype has been established. It is confirmed by 92.59% of validation for the utilization of the device. The successfully designed microfluidic devices can be examined with actual spermatozoa later. Furthermore, process to fabricate the negatively charged TiO₂-coated Ps-beads can be established as testified samples for development of other microfluidic devices.

Hybrid metal-halide perovskites have emerged as leading class of semiconductors for photovoltaic devices with remarkable light harvesting efficiencies. The formation of methylammonium lead iodide (CH₃NH₃PbI₃) perovskite into mesoporous titania (TiO₂) scaffold by a sequential deposition technique is known to offer better control over the perovskite morphology. The growth reactions at the mesoporous TiO₂ film depend on reactants concentration in the host matrix and the reaction activation energy. Here, we are characterizing formation of CH₃NH₃PbI₃ perovskite in mimic solar cell photoelectrodes utilizing the developed NanoPlasmonic Sensing (NPS) approach. Based on dielectric changes at the TiO₂ mesoporous film interface, the technique provides time-resolved spectral shifts of the localized surface plasmon resonance that varies widely depending on the different operating temperatures and methylammonium iodide (CH₃NH₃I) concentrations. Analytical studies included Ellipsometry, Scanning Electron Microscopy, and X-ray diffraction. The results show that perovskite conversion can be obtained at lower CH₃NH₃I concentrations if reaction activation energy is lowered. A significant finding is that the NPS response at 350 nm mesoporous TiO₂ can widely change from red shifts to blue shifts depending on extent of conversion and morphology of perovskite formed at given reaction conditions.

A four stage semi-pilot scale RFR reactor with ceramic disks as support for TiO₂ modified with silver particles was developed for the removal of organic pollutants. The design presented in this article is an adaptation of the rotating biological reactors (RBR) and its coupling with the modified catalyst provides additional advantages to designs where a catalyst in suspension is used. The optimal parameter of rotation was 54 rpm and the submerged surface of the disks offer a total contact area of 387 M². The modified solid showed a decrease in the value of its bandgap compared to commercial titanium. The system has a semi-automatic operation with a maximum reaction time of 50 h. Photo-activity tests show high conversion rates at low concentrations. The results conform to the Langmuir heterogeneous catalysis model.

Ionic liquids (ILs) have gained interest among researchers due to its tunable properties that can be used in wide applications. However, toxicity and bio-degradation studies of ILs proved that most of the aromatic ILs, such as imidazolium is highly toxic and non-biodegradable. Several advance oxidation processes (AOPs) have been investigated by researchers to evaluate the efficiency of the systems for the removal of ILs from wastewater. However, the issue on relative high cost and environmental concern has limited the application of these AOPs in industry. In this research, photocatalytic study using hybrid nano-materials was conducted to evaluate the efficiency of this system as an alternative AOP system for removal of ILs from wastewater. The synergistic effect of adsorption-photodegradation was introduced by depositing Fe-TiO₂ onto the functionalized activated carbon (AC). Nano-TiO₂ was synthesized using micromulsion method before modification with transition metal and deposited onto the oxidized AC. Photodegradation reaction of 1-butyl-3-methylimidazolium chloride [bmim]Cl was investigated under simulated visible light irradiation. It was observed that the overall efficiency of the system was increased with the increasing amount of Fe dopant. Investigation on the extrinsic factors such as solution pH, initial concentration of ILs and photocatalyst dosage showed to significantly affect the overall efficiency of the systems where the optimum condition for the system was observed at pH 10, with initial ILs at 1mM at 1 g/L of photocatalyst. The best performance photocatalyst was 0.2Fe-TiO₂/AC.

The photocatalytic hydrogen evolution reaction (HER) by water splitting has been studied, using catalysts based on TiO2 nanowires (TiO2NWs), which were synthesized by a hydrothermal procedure. This nanomaterial was subsequently modified by incorporating different loadings of gold nanoparticles (AuNPs) on the surface, previously exfoliated MoS2 nanosheets, and CeO2 nanoparticles (CeO2NPs). These nanomaterials, as well as the different synthesized catalysts, were characterized by electron microscopy (HR-SEM and HR-TEM), XPS, XRD, Raman, Reflectance and BET surface area. HER studies were performed in aqueous solution, under irradiation at different wavelengths, which were selected through the appropriate use of optical filters. The results obtained show that there is a synergistic effect between the different nanomaterials of the catalysts. The specific area of the catalyst, and especially the increased loading of MoS2 and CeO2NPs in the catalyst substantially improved the H2 production. Recyclability studies showed only a decrease in activity of approx. 7% after 15 cycles of use, which opens many possibilities regarding the potential use and scaling of these heterostructures in photocatalytic production of H2 from water.

Direct interaction with the neuronal cells is a prerequisite to deciphering useful information in understanding the underlying causes of diseases and functional abnormalities in the brain. Precisely fabricated nanoelectrodes provide the capability to interact with the brain in its natural habitat without compromising its functional integrity. Considerable research has been focused on the employment of vertical nanotubes as nanoelectrodes due to large-scale intracellular recording capability and longer-term intracellular access that arise from their unique geometry. Despite many types of nanotube structures reported in the literature, a limited subset of the nanotubes has been investigated for neural interfacing. This work reports on the fabrication and optimisation of vertically oriented titania nanotube arrays as a scalable electrode platform for neural interface application. To this end, the doping was performed by incorporating a selected group of biologically active metallic ions, including zinc, strontium, and copper, into TiO2 lattice and its effect was studied with respect to the structural, electrochemical and biological properties of the nanotube arrays. It was found that doping can change the length, diameter and wall thickness of the nanotubes. Among pure and doped samples, the copper-doped TiO2 nanotubes demonstrated the highest electrochemical and biological performance. Our results suggest that the doping can be used as a promising method to optimise the properties of nanotube arrays for the development of high-performance neural electrodes.

The photocatalysis process over N-doped TiO2 under visible light is examined for Pb(II) oxidation to form the less toxic and handleable PbO2 suggesting a new method for Pb(II) remediation. The doping TiO2 with N element was conducted by simple hydrothermal technique and using urea as the N source with various concentrations. The doped photocatalysts were characterized by DRUVS, XRD, FTIR and SEM-EDX instruments. Photocatalysis of Pb(II) through batch experiment was performed for evaluation of the doped TiO2 activity under visible light, with applying various fractions of N doped, photocatalyst weigh, irradiation time, and solution pH. The research results attributed that N doping has been successfully performed, that shifted TiO2 absorption into visible region, allowing it to be active under visible irradiation. The photocatalytic removal of Pb(II) under visible ligth over N-TiO2 showed more effective than that of over the un-doped photocatalyst. The removal of Pb(II) has notably taken place through oxidation, that may form PbO2. The highest photocatalytic oxidation of Pb(II) 15 mg/L in 25 mL of the solution could be reached by using TiO2 doped with 10%w of N, 15 mg of N-TiO2 weight, 30 minutes of time, and at pH 8, suggesting a feseable method for Pb(II) remediation.

The preparation of immobilized graphene–based photocatalyst layers is highly desired for environmental applications. In this study, the preparation of an immobilized reduced graphene oxide (rGO)/TiO₂ composite by electrophoretic deposition (EPD) was optimized. It enabled quantitative deposition without sintering and without the use of any dispersive additive. The presence of rGO had beneficial effects on the photocatalytic degradation of 4-chlorophenol in an aqueous solution. A marked increase in the photocatalytic degradation rate was observed, even at very low concentrations of rGO. Compared with the TiO₂ and GO/TiO₂ reference layers, use of the rGO/TiO₂ composite (0.5 wt% of rGO) increased the first-order reaction rate constant by about 70%. This enhanced performance was due to the increased formation of hydroxyl radicals that attacked the 4-chlorophenol molecules. The direct charge transfer mechanism had only limited effect on the degradation. Thus, EPD-prepared rGO/TiO₂ layers appear to be suitable for environmental application.

Two-dimensional arrays of hollow nanotubes made of TiO2 are a promising platform for sensing, spectroscopy and light harvesting applications. Their straightforward fabrication via electrochemical anodization, growing nanotube pillars of finite length from a Ti foil, allows precise tailoring of geometry and, thus, material properties. We investigate these photonic crystal structures with respect to reduction of front surface reflection, achievable field enhancement, and photonic bands. With the Rigorous Coupled Wave Analysis (RCWA), we study the optical response of photonic crystals made of thin-walled nanotubes relative to the bare Ti foil substrate, including under additional charge carrier doping.

In this study, TiO2 nanostructured coatings on Ti-6A-4V alloys were fabricated by two methods: H2O2 oxidation and RF sputtering. In the annealing temperature range of 25 C - 500 C, there were the peaks at 35, 37, 40 and 52 corresponding to {100}, {002}, {101} and {102} crystal planes of hcp structure of α-Ti. At the annealing temperature of 600 C, there was the presence of peaks corresponding to crystal planes of anatase and rutile TiO2. The relative intensities of anatase and rutile phases of the sample fabricated by RF sputtering were 3.62 and 10.25 %, respectively; while those of the sample fabricated by H2O2 oxidation were 21.27 and 3.20 %, respectively (The relative intensity of α-Ti phase was 100 %). The results investigated the peak shift of α-Ti phase in TiO2/Ti-6Al-4V nanostructured coatings fabricated by the two methods which was reasonably explained from the difference in the thermal expansion coefficients of Ti alloy and TiO2 components, as well as the difference in the ratio of anatase to rutile phases.

Microplastics (MPs) and nanoplastics (NPs) are distributed and transferred among the four major environmental compartments (air, water, soil, and biota) and have been already found in humans, making crucial to develop remediation technologies to tackle this kind pollution. Photocatalysis can be used to eliminate MPs present in contaminated wastewater effluents before their discharge into waterbodies. In this work, several green TiO2-based semiconductors were prepared using the extrapallial fluid (EPF) of Mytilus edulis sea water mussels as doping precursor. The semiconductors were then used as films or powders to photocatalytically degrade polystyrene (PS) NPs and MPs and polyethylene (PE) MPs. It was found that the obtention of green TiO2-based semiconductors with good characteristics for photocatalytic purposes (anatase crystalline phase, presence of porosity, activity in visible light and high surface area) seems not enough to achieve high degradation efficiency. The operational conditions of the reaction system should be also taken into account. For instance, the convenience of using semiconductors in the form of films can be overcome by their limited exposed surface area or the null adsorption of the semiconductor in the MPs particles. Additionally, crystallinity of the semiconductor can be a more determinant factor to take into account when performing photocatalysis of MPs.

Titanium and its alloys are used biomaterials for medical and dental applications, due to their mechanical and physical properties. The surface modifications of titanium with bioactive molecules can increase the osseointegration by improving the interface between the bone and implant. Titanium dioxide nanotubes (TiO₂NTs) have excellent bioactivity inducing cell adhesion, spreading, growth and differentiation. In this work, TiO₂NTs were functionalized with a lectin from the plasma of the fish Oreochromis niloticus aiming to favour the adhesion and proliferation of osteoblast-like cells, improving its biocompatibility. The TiO₂NTs were obtained by anodization of titanium and annealed at 400 °C for 3 h. The resulting TiO₂NTs were characterized by high-resolution scanning electron microscopy. The successfully incorporation of OniL on the surface of TiO₂NTs by spin coating was demonstrated by cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIE) and attenuated total reflection-Fourier transform infrared spectrum (ATR-FTIR). Our results showed that TiO₂-NTs were successfully synthesized in a regular and well-distributed way. The functionalization of TiO₂-NTs with OniL favoured adhesion, proliferation, and the osteogenic activity of osteoblast-like cells, suggesting its use to improve the quality and biocompatibility of titanium-based biomaterials.

Herewith we report a facile synthesis of zinc oxide doped with (5, 10, 15, and 20 wt%) titanium oxide nanocomposites in gelatin under ultra-sonication. The X-ray diffraction (XRD) data revealed ZnO the formation in addition to a rutile phase TiO2. The ZnO phase size decreased, and the rutile TiO2 phase increased with a TiO2 loading increment. The scanning electron microscopy (SEM) displayed a combination of spherical and hexagonal particles with a 60 – 80 nm size distribution. The prepared nanostructures photocatalytic activity was assisted using Rhodamine B dye, where they showed enhanced photodegradation competence under visible light irradiation. The kinetics of photodegradation followed the first-order kinetics with the 20 % wt sample having the maximum activity. The mechanistic investigation revealed the dominance of h+ and •O2- species during the dye photodegradation. The results indicate the potential application of such gelatin stabilized nanostructures for dye illumination from aqueous solutions under sunlight.

Geopolymers are ecologically-friendly inorganic materials which can be produced at low temperatures from industrial wastes such as fly ash, blast furnace slags or mining residues. Although to date their principal applications have been as alternatives to Portland cement building materials, their properties make them suitable for a number of more advanced applications, including as photocatalytic nanocomposites for removal of hazardous pollutants from waste water or the atmosphere. For this purpose, they can be combined with photocatalytic moieties such as metal oxides with suitable bandgaps to couple with UV or visible radiation, or with carbon nanotubes or graphene. In these composites the geopolymers act as supports for the photoactive components, but geopolymers formed from wastes containing oxides such as Fe2O3 show intrinsic photoactive behaviour. This review discusses the structure and formation chemistry of geopolymers and the principles required for their utilisation as photocatalysts. The literature on existing photocatalytic geopolymers is reviewed, suggesting that these materials have a promising potential as inexpensive, efficient and ecologically-friendly candidates for the remediation of toxic environmental pollutants and would repay further development.

In two-dimensional materials research, oxidation is usually considered as a common source for the degradation of electronic and optoelectronic devices or even device failure. However, in some cases a controlled oxidation can open the possibility to widely tune the band structure of 2D materials. In particular, we demonstrate the controlled oxidation of titanium trisulfide (TiS₃), a layered semiconductor that attracted much attention recently thanks to its quasi-1D electronic and optoelectronic properties and its direct bandgap of 1.1 eV. Heating TiS₃ in air above 300 °C gradually converts it into TiO₂, a semiconductor with a wide bandgap of 3.2 eV with applications in photo-electrochemistry and catalysis. In this work, we investigate the controlled thermal oxidation of individual TiS₃ nanoribbons and its influence on the optoelectronic properties of TiS₃-based photodetectors. We observe a step-wise change in the cut-off wavelength from its pristine value ~1000 nm to 450 nm after subjecting the TiS₃ devices to subsequent thermal treatment cycles. Ab-initio and many-body calculations confirm an increase of the bandgap of titanium oxysulfide (TiO_2-xS_x) when increasing the amount of oxygen and reducing the amount of sulfur.

Photoelectrocatalytic water splitting by using various TiO₂ nanostructures is a promising approach to generate hydrogen without harmful byproducts. However, their effective performance is restricted by some drawbacks such as high rapid electron-hole pair recombination and backward reaction producing H₂O. Thus in this study, the probability of enhancing hydrogen generation rate by adding methanol as a sacrificial agent to the anodic chamber of a two-compartment photoelectrochemical cell is investigated. Herein, one-dimensional elongated TiO₂ nanorods that were fabricated via a facile one-pot hydrothermal method are utilized as potent photoanode. Voltammetric characterizations confirm that addition of alcoholic sacrificial agent has a significant effect on photoelectrochemical properties of TiO₂ nanorods which by adding 10 wt% of methanol, the photocurrent density and photoconversion efficiency increased from 0.8mA.cm^-2 to 1.5mA.cm^-2 and from 0.28% to 0.45%, respectively. The results of photoelectrocatalytic water splitting indicated that the hydrogen generation rate in the presence of methanol was about 1.2 times higher than that from pure water splitting. These enhancements can be attributed to the key role of methanol. Methanol molecules not only inhibit the electron-hole pair recombination but also accelerate the hydrogen generation rate by sharing their hydrogen atoms.

The size of TiO2 (either nanometric or micrometric) can significantly affect both its photocatalytic and photoelectrochemical properties, thus altering the photooxidation of organic pollutants in air or water. The purpose of this work is to give an account of the photoelectrochemical and photocatalytic features of some nano- and micro-sized TiO2 commercial powders towards a model reaction, the photooxidation of acetone. Cyclic voltammograms (CV) of TiO2 particulated electrodes under UV illumination experiments were carried out in either saturated O2 or N2 solutions for a direct correlation with the photocatalytic process. In addition, the effect of different reaction conditions on the photocatalytic efficiency under UV light in both aqueous and gaseous phases was also investigated. CV curves with the addition of acetone under UV light showed a negative shift of the photocurrent onset, confirming the efficient transfer of photoproduced reactive oxygen species (ROSs), e.g., hydroxyl radicals, or holes to acetone molecules. The photocatalytic experiments showed that the two nano-sized samples exhibit the best photocatalytic performance. The different photoactivity of the micro-sized samples is probably attributed to their morphological differences, affecting both the amount and distribution of free ROSs involved in the photooxidation reaction.

Optical and mechanical properties of multilayer coatings depend on the selected layer materials and the deposition technology; therefore, knowledge of the performances of thin films is essential. In the present work, titanium dioxide (TiO2) and silicon dioxide (SiO2) thin films have been prepared by plasma ion-assisted deposition (PIAD). The optical, structural, and mechanical properties of thin films have been investigated using spectrometer/ellipsometer, X-ray diffraction (XRD), atomic force microscopy (AFM), and laser interferometer. The results show that TiO2 film fabricated by PIAD induces a high refractive index, wide optical band gap, amorphous structure, smooth surface, and tensile stress. In the case of SiO2 film, high bias voltage leads to dense structure and compressive stress. As an application, a three-wavelength high reflectance at 632.8, 808, and 1550nm is optimized and deposited. The dependence of total stress in the multilayer on the substrate temperature is studied as well. In conclusion, it is demonstrated that PIAD is an effective method for the preparation of ultralow stress TiO2/SiO2 multilayer films. The achieved stress is as low as 1.4Mpa. The result could provide guidance to the stress optimization of most optical components without prefiguring, backside coating, and post-deposition treatments.

Iron Doped TiO₂ nanoparticles (Fe-TiO₂) were synthesized and photocatalitically investigated under high and low fluence values of UV-radiation. The Fe-TiO₂ physical characterization was performed using X-ray Powder Diffraction (XRD), Brunauer-Emmett-Teller (BET) surface area analysis, Transmission Electron Microscope (TEM), Scanning Electron Microscope (SEM), Diffuse Reflectance Spectroscopy (DRS), and X-Ray Photoelectron Spectroscopy (XPS) technique. The XPS evidenced that ferric ion (Fe³⁺) was in the lattice of TiO₂ and co-dopants no intentionally added were also present due to the precursors of the synthetic method. The Fe³⁺ concentration played a key role in the photocatalytic generation of hydroxyl radical (•OH) and estriol (E3) degradation. Fe-TiO₂ materials accomplished E3 degradation, and it was found that the catalyst with 0.3 at. % content of Fe (0.3 Fe-TiO₂) enhanced the photocatalytic activity under low UV-irradiation compared with no intentionally Fe-added TiO₂ (zero-iron TiO₂) and Aeroxide^® TiO₂ P25. Furthermore, the enhanced photocatalytic activity of 0.3 Fe-TiO₂ under low UV-irradiation may have applications when radiation intensity must be controlled, as in medical applications, or when strong UV absorbing species are present in water.

Cloud Computing is a promising and emerging technology that is rapidly being adopted by many IT companies due to a number of benefits that it provides, such as large storage space, low investment cost, virtualization, resource sharing, etc. Users are able to store a vast amount of data and information in the cloud and access it from anywhere, anytime on a pay-per-use basis. Since many users are able to share the data and the resources stored in the cloud, there arises a need to provide access to the data to only those users who are authorized to access it. This can be done through access control schemes which allow the authenticated and authorized users to access the data and deny access to unauthorized users. In this paper, a comprehensive review of all the existing access control schemes has been discussed along with analysis. Keywords: role-based access control, attribute-based access control, attribute-based encryption

High purity TiO2 and CuO powders were synthesized by the Pechini method, an inexpensive and easy-to-implement procedure to synthetize metal oxides. The variables of synthesis were the ethylene glycol:citric acid molar ratio and the pH. High reproducibility of the anatase and tenorite phase was obtained for all synthesis routes. The degree of purity of the powders was confirmed by XRD, FTIR, UV-vis absorption and XPS spectra. SEM and TEM images revealed the powders are composed by micrometer grains that can have a spherical shape (only in the TiO2) or formed by a non-compacted nanocrystalline conglomerate. FTIR spectra only vibrational modes associated to the TiO2 or CuO with a nanoparticle behavior. UV-vis absorption spectra revealed the values of maximum absorbance percentage of both systems are reached in the ultraviolet region, with percentages above 83 % throughout the entire visible light spectrum for the CuO system, a relevant result for solar cell applications. Finally, XPS experiments allow the observation of the valence bands and the calculation of the energy bands of all oxides.

In this paper, the phases in the Mg-Ti-O system using the 1:1 formulation of MgO:TiO2 mixing synthetic brucite of Mexican origin with TiO2 microparticles of high purity and with a heat treatment at 1100°C for 1 h were studied. The raw materials and formulation by XPS and DRX techniques were characterized. The results demonstrate the presence of different oxidation states in titania and the formation of different oxides in the Mg-Ti-O system when mixed and calcined at 1100°C; additionally, the formation of vacancies in the crystal lattice during the transformation from hexagonal brucite to magnesia with a cubic structure centered on the faces is estimated. With the results, its thermal behavior is warned based on the MgO-TiO2 phase diagram.

Mesoporous TiO2/reduced graphene oxide/Ag (TiO2/RGO/Ag) ternary nanocomposite with effective electrons transfer pathway is obtained by an electrostatic self-assembly method and photo-assisted treatment. Compared with bare mesoporous TiO2 (MT) and mesoporous TiO2/RGO (MTG), the ternary mesoporous TiO2/RGO/Ag (MTGA) nanocomposite exhibited superior photocatalytic performance for the degradation of MB under visible light, and the degradation rate reached 0.017 min-1, which was 3.4 times higher than that of MTG. It is proposed that Ag nanoparticles can form the local surface plasmon resonance (LSPR) to absorb the visible light and distract the electrons into MT, and RGO can accept the electrons from MT to accelerate the separation efficiency of carriers. The establishment of MTGA ternary nanocomposite make the three components act synergistic effect to enhance the photocatalytic performance.

Vertically aligned Fe, S, and Fe-S doped anatase TiO₂ nanotube arrays are prepared by electrochemical anodization process using an organic electrolyte in which lactic acid is added as an additive. In the electrolyte, nanotube layers of greater length (12 μm) and high order with inner diameter of approx. 90 nm and outer diameter of approx. 170 nm are achieved. Doping of Fe, S, and Fe-S via simple wet impregnation method substituted Ti and O sites with Fe and S, which leads to enhance the rate performance at high discharge current densities. Discharge capacities of TiO₂ tubes increased from 82 mAh g-1 (bare) to 165 mAh g-1 for Fe-S doped TiO₂ at high current densities of 0.3 mAcm-2 after 100 cycles with exceptional capacity retention of 85% after 100 cycles. Owing to the enhancement of thermodynamic and kinetic properties by doping of Fe-S, Li-diffusion increas2ed resulting in remarkable discharge capacities of 143 mAh g-1 and 89 mAh g-1 at a current density of 7.4 mA cm-2 and 19 mA cm-2, respectively.

Indonesia is one of the largest banana producing countries in the world remaining abundance solid waste of banana fruit bunch. The banana fruit bunch contains high natural fibers which were obtained by an impregnation process using potassium hydroxide (KOH) and followed by a carbonization process under steam at 250°C for 5 h. The nanomaterial of TiO₂/fibre was prepared by a hydrothermal process at 200°C for 4 h. Surface morphology proved that the TiO₂ was loaded into the fibre by an increasing roughness of the surface and irregular size of porosity. The development of amorphous to crystalline phase of TiO₂/fibre was clearly observed. The effectiveness of TiO₂/fibre for removal of rhodamine B was investigated from different parameters of adsorptions in aqueous solution. The equilibrium adsorptions show that the Langmuir and Freundlich isotherm exhibited the best correlation coefficient (R² > 0.94) relating to the chemisorption and physisorption interaction in the adsorption process. Kinetic models were well described by the pseudo-first and second-order with the best correlation coefficient (R² > 0.99). These results indicate that nanomaterial TiO₂/fibre can be used as an effective adsorbent for removal of rhodamine B in aqueous solution.

In order to improve the strength of PVA/xylan composite films and endow them with ultraviolet (UV) shielding ability, TiO2-KH550 nanoparticle was synthesized and added into the PVA/xylan matrix. The TiO2-KH550 nanoparticle dispersed well in the 0.04% sodium hexametaphosphate (SHMP) solution under ultrasonic and stirring treatments. Investigations on the properties of films showed that TiO2-KH550 had the positive impact on improving the strength, moisture and oxygen barrier properties of the composite films. The maximum tensile strength (27.3 MPa), the minimum water vapor permeability (2.75×10-11 g•m-1•s-1•Pa-1) and oxygen permeability (4.013 cm3•m-2•24h-1•0.1MPa-1) were obtained under the addition of 1.5% TiO2-KH550. The tensile strength of TiO2-KH550 reinforced composite film was increased by 70% than that of the pure PVA/xylan composite film, and the water vapor and oxygen permeability were decreased by 31% and 41%, respectively. Moreover, the UV transmittance of film at the wavelength of 400 nm was almost zero when adding 1.5~2.5% of TiO2-KH550, which indicated the PVA/xylan composite films were endowed with excellent UV light shielding ability.

According to research, we have learned that Mg and TiO2 are new types material of marine protective coatings. We found that the addition of Mg can improve the performance of Zn-Al coating passivation film, and TiO2 has excellent photocatalytic self-cleaning performance. In this paper Zn-Al pseudo alloy coating was prepared by cold spray technique, and Zn-Al-Mg-TiO2 pseudo alloy composite coating was prepared by adding Mg and nano-TiO2. The effects of Mg and TiO2 to the marine protective properties of Zn-Al coatings were studied by friction and wear test, dynamic salt water corrosion test, electrochemical test, scanning electron microscope(SEM), energy dispersive spectrometer(EDS) and super deep scene 3D microscope. The results show that the addition of Mg and nano-TiO2 not only fills the gap of the coating and improves the density of the coating, but also generates grid-like flocculent corrosion products on the surface of the coating which can gather other corrosion products to improve the density of corrosion products, reduce the friction coefficient and corrosion rate of the coating surface, effectively prevent the invasion of Cl- in solution, and improve the wear and corrosion resistance of the coating.

Lake Rawapening, Semarang Regency, Indonesia, has incorporated a holistic plan in its management practices. However, despite successful target achievements, some limitations remain that a review of its management plan is needed. This paper identifies and analyzes existing lake management strategies as a standard specifically in Lake Rawapening by exploring various literature, both legal frameworks and scholarly articles indexed in Google Scholar and published in Water by MDPI about lake management in many countries. There are two major types of lake management, namely pillar-based and object-based. While the former is the foundation of a conceptual paradigm that does not comprehensively consider the roles of finance and technology in the lake management, the latter indicates the objects to manage so as to create standards or benchmarks for the implementation of various programs. Overall, Lake Rawapening management should include more programs on erosion-sedimentation control and monitoring of operational performance using information systems.

Nature-based solutions (NbS) are increasingly recognised for their potential to address both the climate and biodiversity crises. These outcomes are interdependent, and both rely on the capacity of NbS to support and enhance the health of an ecosystem: its biodiversity, the condition of its abiotic and biotic elements, and its capacity to function normally despite environmental change. However, while understanding of ecosystem health outcomes of nature-based interventions for climate change mitigation is growing, the outcomes of those implemented for adaptation remain poorly understood with evidence scattered across multiple disciplines. To address this, we conducted a systematic review of the outcomes of 109 nature-based interventions for climate change adaptation using 33 indicators of ecosystem health across eight broad categories (e.g. diversity, biomass, ecosystem functioning and population dynamics). We showed that 88% of interventions with positive outcomes for climate change adaptation also reported measurable benefits for ecosystem health. We also showed that interventions were associated with a 67% average increase in local species richness. All eight studies that reported benefits in terms of both climate change mitigation and adaptation also supported ecosystem health, leading to a triple win. However, there were also trade-offs, mainly for forest management and creation of novel ecosystems such as monoculture plantations of non-native species. Our review highlights two major limitations of research to date. First, only a limited selection of metrics are used to assess ecosystem health and these rarely include key aspects such as functional diversity and habitat connectivity. Second, taxonomic coverage is poor: 67% of outcomes assessed only plants and 57% did not distinguish between native and non-native species. Future research addressing these issues will allow the design and adaptive management of NbS to support healthy and resilient ecosystems, and thereby enhance their effectiveness for meeting both climate and biodiversity targets.

For disciplines like biological science, security, and the medical field, link prediction is a popular research area. To demonstrate the link prediction many methods have been proposed. Some of them that have been demonstrated through this review paper are TransE, Complex, DistMult, and DensE models. Each model defines link prediction with different perceptions. We argue that the practical performance potential of these methods, having similar parameter values, using the fine-tuning technique to evaluate their reliability and reproducibility of results. We describe those methods and experiments; provide theoretical proofs and experimental examples, demonstrating how current link prediction methods work in such settings. We use the standard evaluation metrics for testing the model's ability.

Zoos are increasingly putting in place formalized animal welfare assessment programs to allow monitoring of welfare over time, as well as to aid in resource prioritization. These programs tend to rely on assessment tools that incorporate resource-based and observational animal- focused measures since it is rarely feasible to obtain measures of physiology in zoo-housed animals. A range of assessment tools are available which commonly have a basis in the Five Domains framework. A comprehensive review of the literature was conducted to bring together recent studies examining welfare assessment methods in zoo animals. A summary of these methods is provided with advantages and limitations of the approach es presented. We then highlight practical considerations with respect to implementation of these tools into practice, for example scoring schemes, weighting of criteria, and innate animal factors for consideration. It is concluded that would be value in standardizing guidelines for development of welfare assessment tools since zoo accreditation bodies rarely prescribe these. There is also a need to develop taxon or species- specific assessment tools to inform welfare management.

Transparent binder is used to substitute conventional black asphalt binder and to provide light-colored pavements, whereas nano-TiO2 has the potential to promote photocatalytic and self-cleaning properties. Together, these materials provide multifunction effects and benefits when the pavement is submitted to high solar irradiation. This paper analyses the physicochemical and rheological properties of a transparent binder modified with 0.5%, 3.0%, 6.0%, and 10.0% of nano-TiO2 and compares it to the transparent base binder, and conventional and polymer modified binders (PMB) without nano-TiO2. Their penetration, softening point, dynamic viscosity, master curve, black diagram, Linear Amplitude Sweep (LAS), Multiple Stress Creep Recovery (MSCR), and Fourier-Transform Infrared Spectroscopy (FTIR) were obtained. The transparent binders (base and modified) seem to be workable considering their viscosity and exhibited values between the conventional binder and PMB regarding rutting resistance, penetration, and softening point. They showed similar behavior as the PMB, demonstrating signs of polymer-modification. The addition of TiO2 seems to reduce fatigue life, except for the 0.5% content. Nevertheless, its addition in high contents increases the rutting resistance. The TiO2 modification seems to have little effect on the chemical functional indices. The best percentage of TiO2 was 0.5%, considering fatigue and 10.0% concerning permanent deformation.

This article investigates the prospect of implementing multidisciplinary and multicultural student teamwork (MMT) involving Case-based Learning (CBL) and Problem-based Learning (PBL) as a sustainable teaching practice. Based on a mixed methods approach, which includes direct observation (both physical and virtual), questionnaire distribution and focus-group interviews the study reveals that MMT through CBL and PBL can both facilitate and hinder sustainable learning. Our findings show that while MMT enhances knowledge sharing, it also poses a wide range of challenges, raising questions about its social significance as a sustainable teaching practice. The study suggests the implementation of certain mechanisms, such as ‘Teamwork Training’ and ‘Pedagogical Mentors’, aiming to strengthen the sustainable orientation of MMT through CBL and PBL.

In MBSE there is yet no converged terminology. The term ’system model’ is used in different contexts in literature. In this study we elaborated the definitions and usages of the term ’system model’, to find a common definition. 104 publications have been analyzed in depth for their usage and definition as well as their meta-data e.g., the publication year and publication background to find some common patterns. While the term is gaining more interest in recent years it is used in a broad range of contexts for both analytical and synthetic use cases. Based on this three categories of system models have been defined and integrated into a more precise definition.

This article discusses the use of game design as a method for interdisciplinary project-based teaching in secondary school education to convey informatics and society topics. There is a lot of knowledge about learning games but little background on project-based teaching using game design as a method. We present the results of an analysis of student-created games and an evaluation of a student-authored database on learning contents found in commercial off-the-shelf games. We further contextualise these findings using a group discussion with teachers. Results underline the effectiveness of project-based teaching to raise awareness for informatics and society topics. We further outline informatics and society topics that are particularly interesting to students, genre preferences and potentially engaging game mechanics stemming from our analyses.

The ubiquity of mobile sensors (such as GPS, accelerometer and gyroscope) together with increasing computational power have enabled an easier access to contextual information, which proved its value in next generation of the recommender applications. The importance of contextual information has been recognized by researchers in many disciplines, such as ubiquitous and mobile computing, to filter the query results and provide recommendations based on different user status. A context-aware recommendation system (CoARS) provides a personalized service to each individual user, driven by his or her particular needs and interests at any location and anytime. Therefore, a contextual recommendation system changes in real time as a user’s circumstances changes. CoARS is one of the major applications that has been refined over the years due to the evolving geospatial techniques and big data management practices. In this paper, a CoARS is designed and implemented to combine the context information from smartphones’ sensors and user preferences to improve efficiency and usability of the recommendation. The proposed approach combines user’s context information (such as location, time, and transportation mode), personalized preferences (using individuals past behavior), and item-based recommendations (such as item’s ranking and type) to personally filter the item list. The context-aware methodology is based on preprocessing and filtering of raw data, context extraction and context reasoning. This study examined the application of such a system in recommending a suitable restaurant using both web-based and android platforms. The implemented system uses CoARS techniques to provide beneficial and accurate recommendations to the users. The capabilities of the system is evaluated successfully with recommendation experiment and usability test.

Hospital-based programs democratize mRNA therapeutics by facilitating the processes to translate a novel RNA idea from the bench to the clinic. Because mRNA is essentially biological software, therapeutic RNA constructs can be rapidly developed. The generation of small batches of clinical grade mRNA to support IND applications and first-in-man clinical trials, as well as personalized mRNA therapeutics delivered at the point-of-care, is feasible at a modest scale of cGMP manufacturing. Advances in mRNA manufacturing science and innovations in mRNA biology, are increasing the scope of mRNA clinical applications.

Noise in requirements has been known to be a defect in software requirements specifications (SRS). Detecting defects at an early stage is crucial in the process of software development. Noise can be in the form of irrelevant requirements that are included within a SRS. A previous study had attempted to detect noise in SRS, in which noise was considered as an outlier. However, the resulting method only demonstrated a moderate reliability due to the overshadowing of unique actor words by unique action words in the topic-word distribution. In this study, we propose a framework to identify irrelevant requirements based on the MultiPhiLDA method. The proposed framework distinguishes the topic-word distribution of actor words and action words as two separate topic-word distributions with two multinomial probability functions. Weights are used to maintain a proportional contribution of actor and action words. We also explore the use of two outlier detection methods, namely Percentile-based Outlier Detection (PBOD) and Angle-based Outlier Detection (ABOD), to distinguish irrelevant requirements from relevant requirements. The experimental results show that the proposed framework was able to exhibit better performance than previous methods. Furthermore, the use of the combination of ABOD as the outlier detection method and topic coherence as the estimation approach to determine the optimal number of topics and iterations in the proposed framework outperformed the other combinations and obtained sensitivity, specificity, F1-score, and G-mean values of 0.59, 0.65, 0.62, and 0.62, respectively.

Animal-based measures are the measure of choice in animal welfare assessment protocols as they can often be applied completely independently to the housing or production system employed. Although there has been a small body of work on potential animal-based measures for farmed crocodilians [1-3], they have not been studied in the context of an animal welfare assessment protocol. Potential animal-based measures, that could be used to reflect the welfare state of farmed crocodilians, were identified and aligned with the Welfare Quality® principles of good housing, good health, good feeding and appropriate behaviour. A consultation process with a panel of experts was used to evaluate and score the potential measures in terms of validity and feasibility. This resulted in a toolbox of measures being identified for further development and integration into animal welfare assessment on the farm. Animal-based measures related to ‘good feeding’ and ‘good health’ received the highest scores for validity and feasibility by the experts. There was less agreement on the animal-based measures that could be used to reflect ‘appropriate behaviour’. Where no animal-based measures were deemed to reliably reflect a welfare criterion nor be useful as a measure on the farm, additional measures of resources or management were suggested as alternatives. Future work in this area should focus on the reliability of the proposed measures and involve further evaluation of their validity and feasibility as they relate to different species of crocodilian and farming system.

The exploitation of lipid membranes in biosensors has provided the ability to reconstitute a considerable part of their functionality to detect trace of food toxicants and environmental pollutants. Nanotechnology enabled sensor miniaturization and extended the range of biological moieties that could be immobilized within a lipid bilayer device. This chapter reviews recent progress in biosensor technologies based on lipid membranes suitable for environmental applications and food quality monitoring. Numerous biosensing applications are presented, putting emphasis on novel systems, new sensing techniques and nanotechnology-based transduction schemes. The range of analytes that can be currently detected include, insecticides, pesticides, herbicides, metals, toxins, antibiotics, microorganisms, hormones, dioxins, etc. Technology limitations and future prospects are discussed, focused on the evaluation/ validation and eventually commercialization of the proposed sensors.

The exploitation of lipid membranes in biosensors has provided the ability to reconstitute a considerable part of their functionality to detect trace of food toxicants and environmental pollutants. Nanotechnology enabled sensor miniaturization and extended the range of biological moieties that could be immobilized within a lipid bilayer device. This chapter reviews recent progress in biosensor technologies based on lipid membranes suitable for environmental applications and food quality monitoring. Numerous biosensing applications are presented, putting emphasis on novel systems, new sensing techniques and nanotechnology-based transduction schemes. The range of analytes that can be currently detected include, insecticides, pesticides, herbicides, metals, toxins, antibiotics, microorganisms, hormones, dioxins, etc. Technology limitations and future prospects are discussed, focused on the evaluation/ validation and eventually commercialization of the proposed sensors.

Given the increase in consumers’ preferences for coffee, it is becoming important to understand their decision-making processes in the coffee chain context. To deepen the understanding of sustainable outcomes in this context, this study investigates the role of dedication- and constraint-based mechanisms in forming consumers’ repurchase and positive word-of-mouth (WOM) intentions, two critical sustainable outcomes. We examined the effects of coffee quality, the quality of the physical environment, and service quality in accelerating the formation of dedication-based factors. Moreover, this study offers an in-depth understanding of the enablers of perceived switching costs. Data collected from 238 university students that frequently visit coffee chains are empirically tested against the proposed theoretical framework by using structural equation modeling. The results confirm that both dedication- and constraint-based factors substantially predict consumers’ sustainable outcomes in the coffee chain context. Brand image and perceived switching costs play an important role in enhancing consumers’ repurchase and positive WOM intentions compared with customer satisfaction. Coffee quality is significantly associated with both customer satisfaction and brand image, whereas the quality of the physical environment and service quality are only significantly associated with brand image. Habit is found to be the key enabler of perceived switching costs, while loyalty programs have no significant impact on perceived switching costs.

Effectively mapping and monitoring rubber plantation is still changing. Previous studies have explored the potential of phenology features for rubber plantation mapping through a pixel-based approach (pixel-based phenology approach). However, in fragmented mountainous Xishuangbanna, it could lead to noises and low accuracy of resultant maps. In this study, we investigated the capability of an integrated approach by combining phenology information with an object-based approach (object-based phenology approach) to map rubber plantations in Xishuangbanna. Moderate Resolution Imaging Spectroradiometer (MODIS) data were firstly used to acquire the temporal profile and phenological features of rubber plantations and natural forests, which delineates the time windows of defoliation and foliation phases. Landsat images were then used to extract a phenology algorithm comparing three different approaches: pixel-based phenology, object-based phenology, and extended object-based phenology to separate rubber plantations and natural forests. The results showed that the two object-based approaches achieved higher accuracy than the pixel-based approach, having overall accuracies of 96.4%, 97.4%, and 95.5%, respectively. This study proved the reliability of a phenology-based rubber mapping in fragmented landscapes with a distinct dry/cool season using Landsat images. This study indicated that the object-based phenology approaches can effectively improve the accuracy of the resultant maps in fragmented landscapes.

Saudi Arabia is an oil-reliant nation as a large percentage of its GDP comes from oil resources. Oil dependency leaves a county at the mercy of the international crude market, and a decrease in the price of crude can seriously destabilize the economy of such nations. An example is the case of Venezuela whose dependence on oil caused a national disaster (McCarthy, 2017). As such, the nation’s exports, GDP, and government revenue are primarily dependent on oil revenue, and the recent decrease in the oil prices has decreased Venezuela’s national revenue resulting in economic collapse as well as inflation. A shift from a resource based economy to a knowledge based economy will help Saudi Arabia become less reliant on its oil revenues for its economic stability and growth (Nurunnabi, 2017).

After the great success of Mobile wallet, the Internet of Things (IoT) leaves the door wide open for consumers to use their connected devices to access their bank accounts and perform routine banking activities from anywhere, anytime and with any device. However, consumers need to feel safe when interacting with IoT-based payment systems, and their personal information should be protected as much as possible. Unlike as usually done in the literature, in this paper, we introduce two lightweight and secure IoT-based payment protocols based on an identity-based signature scheme. We adopt a server-aided verification technique to construct the first scheme. This technique allows to outsource the heavy computation overhead on the sensor node to a cloud server while maintaining the user's privacy. The second scheme is built upon a pairing-free ECC-based security protocol to avoid the heavy computational complexity of bilinear pairing operations. The security reduction results of both schemes are held in the Random Oracle Model (ROM) under the discrete logarithm and computational Diffie-Hellman assumptions. Finally, we experimentally compare the proposed schemes against each other and against the original scheme on the most commonly used IoT devices: a smartphone, a smartwatch and the embedded device Raspberry Pi. Compared with existing schemes, our proposed schemes achieve significant efficiency in the term of communication and computational overheads

The study aims to elaborate a neural model and algorithm for optimising hardness and porosity of coatings and thus ensure that they have superior cavitation erosion resistance. Al2O3-13wt.%TiO2 ceramic coatings were deposited onto 316L stainless steel by atmospheric plasma spray (ASP). The coatings were prepared with different values of two spray process parameters: the stand-off distance and torch velocity. Microstructure, porosity and microhardness of the coatings were examined. Cavitation erosion tests were conducted in compliance with the ASTM G32 standard. Artificial neural networks (ANN) were employed to elaborate the model, and the multi-objectives genetic algorithm (MOGA) was used to optimise both properties and cavitation erosion resistance of the coatings. Results were analysed with Matlab software by Neural Network Toolbox and Global Optimization Toolbox. The fusion of artificial intelligence methods (ANN+MOGA) is essential for future selection of thermal spray process parameters, especially for the design of ceramic coatings with specified functional properties. Selection of these parameters is a multicriteria decision problem. The proposed method made it possible to find a Pareto front, i.e. trade-offs between several conflicting objectives – maximising the hardness and cavitation erosion resistance of Al2O3-13%TiO2 coatings and, at the same time, minimizing their porosity.

One of the most important objectives of the studies worldwide is to improve the performance of automotive engines to reduce fuel consumption and environmental pollution. Accordingly, the principal motivation of this research study is improving the tribological behavior of the piston ring/cylinder liner interfaces as a promising and straightforward approach in automotive fuel economy and increasing engine durability using Al₂O₃ and TiO₂ nanomaterials as smart nano-lubricant additives that adapted to different operating conditions by replenishing mechanisms anti-friction and anti-wear in automotive engines.

Paper-based analytical devices have been substantially developed in recent decades. Many fabrication techniques for paper-based analytical devices have been demonstrated and reported. Herein we report a relatively rapid, simple, and inexpensive method for fabricating paper-based analytical devices using parafilm hot pressing. We studied and optimized the effect of the key fabrication parameters, namely pressure, temperature, and pressing time. We discerned the optimal conditions, including pressure of 3.8 MPa (3 tons), temperature of 80oC, and 3 minutes of pressing time, with the smallest hydrophobic barrier size (821 µm) being governed by laminate mask and parafilm dispersal from pressure and heat. Physical and biochemical properties were evaluated to substantiate the paper functionality for analytical devices. Wicking speed in the fabricated paper strips was slightly slower than that of non-processed paper, resulting from reducing paper pore size. A colorimetric immunological assay was performed to demonstrate the protein binding capacity of the paper-based device after exposure to pressure and heat from the fabrication. Moreover, mixing in two-dimensional paper-based device and flowing in a three-dimensional counterpart were thoroughly investigated, demonstrating that the paper device from this fabrication process is potentially applicable as analytical devices for biomolecule detection. Fast, easy, and inexpensive parafilm hot press fabrication presents an opportunity for researchers to develop paper-based analytical devices in resource-limited environments.

Abstract: Calcium-based catalysts are of a high interest for glycerol polymerization due to their high catalytic activity and large availability. However, their poor stability under reaction conditions is an issue. In the present study, we investigated the stability and catalytic activity of Ca-hydroxyapatites (HAps) as one of the most abundant Ca-source in nature. A stochiometric, a Ca-deficient and a Ca-rich HAps have been synthetized and tested as catalysts in the glycerol polymerization reaction. Deficient and stochiometric HAps exhibited a remarkable 100% selectivity to triglycerol at 15 % of glycerol conversion at 245 °C after 8 h of reaction in the presence 0.5 mol.% of catalyst. Moreover, under the same reaction conditions, Ca-rich HAp showed a high selectivity (88 %) to di- and triglycerol at a glycerol conversion of 27 %. Most importantly, these catalysts were unexpectedly stable towards leaching under the reaction conditions based on the ICP-OES results. However, based on the catalytic tests and characterization analysis performed by XRD, XPS, IR, TGA-DSC and ICP-OES, we found that HAps can be deactivated by the presence of the reaction products themselves, i.e., water and polymers.

A project-based module on Sustainable Development Goal number 5, Gender Equality, was im-plemented on 5 different groups of Business English students consisting of a total number of 62 students in higher education. The main purpose of this project was to raise awareness of this goal by means of a flipped method in which students were required to carry out some research on specific areas of the aforementioned goal and work in teams to elaborate oral presentations. Once their findings were shared in class, students were expected to answer a written questionnaire of open-ended questions which were part of a qualitative analysis. Results of this survey showed that not only 90% of the students gained in depth knowledge of this goal, but also 85% had built a positive attitude to take initiative and 80% were optimistic about future gender equality. Finally, 70% of students suggested further social action to curb the problem of gender discrimination. On the whole, the flipped classroom method of learning combined with project-based group work have proven to be an effective way to raise awareness of this goal, create a more positive attitude, in-crease their willingness to take action as well as widening their English lexical resources.

Object-Based Image Analysis (OBIA) has been successfully used to map slums. In general, the occurrence of uncertainties in producing geographic data is inevitable. However, most studies concentrated solely on assessing the classification accuracy and neglecting the inherent uncertainties. Our research analyses the impact of uncertainties in measuring the accuracy of OBIA-based slum detection. We selected Jakarta as our case study area, because of a national policy of slum eradication, which is causing rapid changes in slum areas. Our research comprises of four parts: slum conceptualization, ruleset development, implementation, and accuracy and uncertainty measurements. Existential and extensional uncertainty arise when producing reference data. The comparison of a manual expert delineations of slums with OBIA slum classification results into four combinations: True Positive, False Positive, True Negative and False Negative. However, the higher the True Positive (which lead to a better accuracy), the lower the certainty of the results. This demonstrates the impact of extensional uncertainties. Our study also demonstrates the role of non-observable indicators (i.e., land tenure), to assist slum detection, particularly in areas where uncertainties exist. In conclusion, uncertainties are increasing when aiming to achieve a higher classification accuracy by matching manual delineation and OBIA classification.

Web-Based GIS is a platform that deals with the representation, management and storage of locational information for real-time online retrieval, viewing and manipulations. Web-based GIS incorporate all the functions of information systems: gathering, storing, retrieving, visualizing and dissemination of spatial information on the Internet. In modern-day GIS serve as vital means to not only geo-referenced locational information that are been retrieved but also the development in web-based technologies as well as there involvements in decision making processes. In recent time the increased used of GIS on the Internet have totally transformed and made three distinct changes across our GIS environment. These are: (i) how are GIS data being accessed (ii) what are modes of its transmission and (iii) what available GIS functionalities are within the environment for analysis. This paper examines the applications and technologies associated with web-based GIS architectures with an emphasis on the internet GIS based structure and case studies of GIS Web-based applications in MapInfo, Microsoft Silverlight Technology and the ArcGIS Server using ArcGIS JavaScript API.

Event-based vision is an emerging field of computer vision that offers unique properties such as asynchronous visual output, high temporal resolutions, and dependence on brightness changes to generate data. These properties can enable robust high-temporal-resolution object detection and tracking when combined with frame-based vision. In this paper, we present a hybrid, high-temporal-resolution, object detection and tracking approach, that combines learned and classical methods using synchronized images and event data. Off-the-shelf frame-based object detectors are used for initial object detection and classification. Then, event masks, generated per each detection, are used to enable inter-frame tracking at varying temporal resolutions using the event data. Detections are associated across time using a simple low-cost association metric. Moreover, we collect and label a traffic dataset using the hybrid sensor DAVIS 240c. This dataset is utilized for quantitative evaluation using state-of-the-art detection and tracking metrics. We provide ground truth bounding boxes and object IDs for each vehicle annotation. Further, we generate high-temporal-resolution ground truth data to analyze the tracking performance at different temporal rates. Our approach shows promising results with minimal performance deterioration at higher temporal resolutions (48 – 384 Hz) when compared with the baseline frame-based performance at 24 Hz.

The recent covid crisis has proven important lessons for academia and industry regarding digital reorganization. Among fascinating lessons from these times is the huge potential of data analytics and artificial intelligence. The crisis exponentially accelerated the adoption of analytics and artificial intelligence, and this momentum is predicted to continue into the 2020s and over. Moreover, drug development is a costly and time-consuming business, and only a minority of approved drugs return the revenue that exceeds the research and development costs. As a result, there is a huge drive to make drug discovery cheaper and faster. With modern algorithms and hardware, it is not too surprising that the new technologies of artificial intelligence and other computational simulation tools can help drug developers. In only two years of covid research, many novel molecules have been designed/identified using artificial intelligence methods with astonishing results in terms of time and effectiveness. This paper will review the most significant research on artificial intelligence in the de novo drug design for COVID-19 pharmaceutical research.

Maternal-child care is one of the foundations of primary health care. Nurses’ competency skills they have been taught. Community awareness is an important part of preventive healthcare, and nurses must be aware of the factors that impact the health of the community. This study examines the effectiveness of lecture-based instructions in maternal and child care and its implications to students' social competency skills and community awareness in Nursing Colleges in Nueva Ecija, Philippines. The researcher uses survey questionnaire and employed the descriptive design where fifteen (15) nursing students and five (5) teachers were purposively selected. The findings revealed that the weighted mean for the effectiveness of lecture based instruction in maternal and child care is 3.91 with verbal description of “Effective”, the effects of lecture based instruction in maternal and childcare to students’ social competency skills and community awareness got the weighted mean of 3.87 and interpreted as “very satisfactory” and the effectiveness of actual community-based instruction is very effective with weighted mean of 4.25 and is higher compare to lecture based instruction. The results also revealed that students and teachers were challenged in lecture-based instruction in maternal and chi8ldcare during distance learning. Recommendations for the enhancement of lecture-based instruction in maternal and childcare in social competency skills and community awareness were also made.

Over the last decade, a significant literature has emerged that advocates the potential of different Additive manufacturing (AM) technologies and printable polymeric materials. Nevertheless, large scale printing and complex geometric shapes, with curvatures and non-planar layer deposition, are a challenging process for the traditional gantry-based machine. The 3 degrees of freedom cartesian configuration restricted their capability to planar layered printing and restricted part dimensions. To date, many researchers have used industrial robots to overcomes this limitation. This review gives the reader a good overview of the FDM technique due to its scalability, cost efficiency and a wide range of material printability. A strong emphasis is laid on the PLA and PLA-based composites as promising materials for the FDM process applications. The second part of this paper links the successful use of these materials in the traditional printing process to large scale printing using the robot-based FDM process. This survey presents representative setups for robot-based AM and works that have been used these setups for non-planar material deposition. Finally, we conclude this paper by identifying opportunities for realizing new functional capabilities by exploiting robot-based AM, and we also present the future trends in this area.

Saccharomyces cerevisiae are a phenotypically diverse species that adapt to a wide variety of environments by exploiting standing genetic diversity and selecting for advantageous mutations. Glyphosate and copper-based herbicides/ fungicides affect non-target organisms, these incidental exposures can impact microbial populations. In this study, glyphosate resistance was found in the historical collection of yeast which was collected over the last century, but only in yeast isolated after the introduction of glyphosate. The highest glyphosate-resistant yeasts were isolated from agricultural sites. However, herbicide application at these sites was not recorded. In an effort to assess glyphosate resistance and impact on non-target microorganisms, yeast were harvested from 15 areas with known herbicidal histories, including an organic farm, conventional farm, remediated coal mine, suburban locations, state park, and a national forest. Yeast representing 23 genera were isolated from 237 samples of plant, soil, spontaneous fermentation, nut, flower, fruit, feces, and tree material samples. Saccharomyces, Candida, Metschnikowia, Klyveromyces, Hanseniaspora, and Pichia were other genera commonly found across our sampled environments. Managed areas had less species diversity and at the brewery, only Saccharomyces and Pichia were isolated. A conventional farm growing RoundUp Ready™ corn had the lowest phylogenetic diversity and the highest glyphosate resistance. The mine was sprayed with multiple herbicides including a commercial formulation of glyphosate; however, the yeast did not have elevated glyphosate resistance. In contrast to the conventional farm, the mine was exposed to glyphosate only one year prior to sample isolation. Glyphosate resistance is an example of the anthropogenic selection of nontarget organisms.

For centuries, crop plants have represented the basis of the daily human diet. Among them, cereals and legumes, accumulating oils, proteins and carbohydrates in their seeds, distinctly dominate modern agronomic practice. Indeed, these plants play an essential role in the food industry and fuel production. Therefore, the seeds of crop plants are intensively studied by food chemists, biologists, biochemists, and nutritional physiologists. Accordingly, not only seed development and germination, but also age- and stress-related alterations in seed vigor, longevity, nutritional value and safety can be addressed by a broad panel of analytical, biochemical and physiological methods. Currently, functional genomics is one of the most powerful tools, giving direct access to characteristic metabolic changes, accompanying plant development, senescence and response to biotic or environmental stress. Among individual methodological platforms, proteomics represents one of the most effective ones, giving access to cellular metabolism at the level of proteins. Here we discuss the main methodological approaches employed by seed proteomics in the context of physiological changes related to seed development, ageing and response to environmental stress.

G protein-coupled receptors (GPCRs) are amongst the most pharmaceutically relevant and well-studied protein targets, yet unanswered questions in the field leave significant gaps in our understanding of their nuanced structure and function. 3D pharmacophore models are powerful computational tools in silico drug discovery, presenting myriad opportunities for the integration of GPCR structural biology and cheminformatics. This review highlights success stories in the application of 3D pharmacophore modeling to de novo drug design, discovery of biased and allosteric ligands, scaffold hopping, QSAR analysis, hit-to-lead optimization, GPCR de-orphanization, mechanistic understanding of GPCR pharmacology and elucidation of ligand-receptor interactions. Furthermore, advances in the incorporation of dynamics and machine learning will be highlighted. The review will analyze challenges in the field of GPCR drug discovery, detailing how 3D pharmacophore modeling can be used to address them. Finally, we will present opportunities afforded by 3D pharmacophore modeling in the advancement of our understanding and targeting of GPCRs.

The deployment of Electro-Mechanical Actuators plays an important role towards the adoption of the More Electric Aircraft (MEA) philosophy. On the other hand, a seamless substitution of EMAs in place of more traditional hydraulic solutions is still set back due to the shortage of real-life and reliability data regarding their failure modes. One way to work around this problem is providing a capillary EMA Prognostics and Health Management (PHM) system, capable of recognizing failures before they actually undermine the ability of the safety-critical system to perform its functions. The authors have developed a model-based prognostic framework for PMSM based EMAs leveraging a metaheuristic algorithm: Evolutionary (Differential Evolution (DE)) and swarm intelligence (particle swarm (PSO), grey wolf (GWO)) methods are considered. Several failures (dry friction, backlash, short circuit, eccentricity and proportional gain) are simulated thanks to a Reference Model, acting as a Numerical Test Bench, then detected and identified thanks to the envisioned prognostic method, which leverages a low fidelity Monitoring Model. The employed algorithms showed good results and prove that this strategy could be executed in pre-flight checks or during the flight at specific time intervals, with positive impacts on system safety and availability.

Initial choice of Learning Rate is a key part of gradient based methods and has a great effect on the performance of the Deep Learning Model.This paper studies the behavior of multiple gradient based optimization algorithm which are commonly used in Deep Learning and compare their performance on various learning rate. As observed popular choice of optimization algorithms are highly sensitive to various choice of learning rates. Our goal is to find which optimizer has an edge over others for a specific setting. We look at two datasets namely MNIST and CIFAR10 for benchmarking. The results are quite surprising, and it will help us to choose a learning rate more efficiently.

Agent-based models (ABMs) are computational models for simulating the actions and interactions of autonomous agents in time and space. These models allow users to simulate the complex interactions between individual agents and the landscapes they inhabit and are increasingly used in epidemiology to understand complex phenomena and make predictions. However, as the complexity of the simulated systems increases, notably when disease control interventions are considered, model flexibility and processing speed can become limiting. Here we introduce SamPy, an open-source Python library for stochastic agent-based modeling of epidemics. SamPy is a modular toolkit for model development, providing adaptable modules that capture host movement, disease dynamics, and disease control interventions. Memory optimization and design provide high computational efficiency allowing modelling of large, spatially-explicit populations of agents over extensive geographical areas. In this article, we demonstrate the high flexibility and processing speed of this new library. The version of SamPy considered in this paper is available at https://github.com/sampy-project/sampy-paper .

Good estimators are characterized as robust, unbiased, efficient, and consistent. However, the commonly used estimators are weak or lack one or more of these properties. In this article, eight (8) estimators for statistical and geometrical estimations of symmetry/asymmetry, similarity/dissimilarity, identity/unidentity, and feature transformation were proposed following Kabirian-based optinalysis and other operations. The proposed estimators are characterized as invariant (robust) under scaling, location shift, and rotation or reflection. A computing code was written in python language for each of the proposed estimators so that peers can have working codes for application and performance evaluation.

Decision making as a result of system dynamics analysis requires, in practice, a straightforward and systematic modelling capability as well as a high-level of customisation and flexibility to adapt to situations and environments that may vary very much from each other. While in general terms a completely generic approach could be not as effective as ad-hoc solutions, the proper application of modern technology may facilitate agile strategies as a result of a smart combination of qualitative and quantitative aspects. In order to address such a complexity, we propose a knowledge-based approach that integrates the systematic computation of heterogeneous criteria with open semantics. The holistic understanding of the framework is described by a reference architecture and the proof-of-concept prototype developed can support high-level system analysis, as well as it suitable within a number of applications contexts - i.e. as a research/educational tool, communication framework, gamification and participatory modelling. Additionally, the knowledge-based philosophy, developed upon Semantic Web technology, increases the capability in terms of holistic knowledge building and re-use via interoperability. Last but not least, the framework is designed to constantly evolve in the next future, for instance by incorporating more advanced AI-powered features.

There is increasing interest in automating train operations of mainline services, e.g. to increase network capacity. Automatic train operation (ATO) is already achieved by several pilot projects, but not implemented on a large scale. Before the general introduction of new or adapted technologies can have a transformative effect on the operation of such a complex system as train operation on mainlines, they have to pass functional, interoperability and performance tests. A virtual preliminary analysis is one way to ensure a smooth as well as safe introduction and implementation. This paper aims to present an approach that applies to the performance testing of ATO systems. Therefore, methods and test standards for technologies enabling automatic operation in other transport sectors are reviewed. The main findings have been adapted, transformed and combined to be used as a general strategy for virtual performance testing in the railway sector. Specifically, universal performance indicators, namely punctuality, accuracy, energy consumption, safety and comfort, are presented. A layer model for scenario description is adapted from the automotive sector, as well as the definition of different scenario types. Lastly, factors that can influence the performance of an ATO algorithm are identified. To demonstrate the developed approach, a straightforward investigation of a case study is conducted using a microscopic train simulator in combination with an ATO algorithm.

Background: In an age where information is generally accessible, most of the interest these days has focused on how accessible and convenient technology can be. So small and personal, mobile devices can transform our perception of learning by combining both mobility and convenience. Mobile learning is part of the digital learning landscape alongside e-learning and serious games. However, knowledge about effective design of mobile learning experiences remains of interest with a focus on appropriate design models and the embodiments that can be implemented to achieve the intended educational outcomes. Exploring the instructor's perspective on mobile learning is essential. Therefore, the aim of this study was to investigate the Moroccan instructors' perception and practice of mobile learning to inform the development of an ecologically valid mobile learning integration model. Methods: Higher education Instructors (n=41) were recruited to the study. The Moroccan instructors' perception and their experiences regarding their adoption of mobile learning were collected using an online survey. The analysis focused on their mobile use, perceived IT competency, and opinions on mobile learning. Results: We described most of the instructors' considerations regarding integrating mobile technologies into their teaching activities. We found that most of the mobile learning activities defined by the respondents corresponded to relatively advanced use of mobile devices. More promising, instructors have found innovative ways to use the educational potential of mobile devices. However, the prospect of mobile devices was still to challenge. No or poor Wi-Fi connection, number of devices or limited access, sometimes fees or applications incompatibility were identified as reasons and obstacles to mobile learning usage. Conclusion: Mobile learning is mostly perceived positively among Moroccan instructors allowing many applications and usage to enhance teaching and learning. In this study, a better understanding of aspects and factors influencing the integration of mobile learning in the Moroccan educational context is exposed, helping further the development of an ecologically valid mobile learning integration model. Future work on mobile learning should consider the highly paced evolution of mobile technologies, emphasizing the flexibility of integration frameworks to support instructors and learners.

Gender-based violence is considered a serious social and public health problem. Overcoming this situation implies a process that results in the favorable biopsychosocial rehabilitation, the resilient of women. The objective of this study was to analyze the tools, resources and personal and psychosocial mechanisms used by women survivors of gender-based violence. The design was an interpretative phenomenology. It carried out with 22 women who have overcome gender-based violence. Data was collected through personal interviews and narration. The results were grouped into four themes: "Process of violence", "Social resources for coping and overcoming GBV", "Personal tools for coping and overcoming GBV", and "Feelings identified, from the abuse stage to the survival stage". Several studies concluded that overcoming abuse is influenced by the women social network, and it can be the action of these people determining their survival to gender violence. Despite the recognized usefulness of these available resources, it would be desirable to strengthen them in order to be able to drive more women toward survival, assuming a strengthening of coping and overcoming, without forgetting the importance of other support mechanisms such as their family and group therapies.

Malnutrition in children is a global health problem, particularly in developing countries. The effects of an insufficient supply of nutrients on body composition and physiological functions may have implications for drug disposition and ultimately affect the clinical outcome in this vulnerable population. Physiologically based pharmacokinetic (PBPK) modeling can be used to predict the effect of malnutrition as it links physiological changes to pharmacokinetic (PK) consequences. However, the absence of detailed information on body composition and the limited availability of controlled clinical trials in malnourished children complicates the establishment and evaluation of a generic PBPK model in this population. In this manuscript we describe the creation of physiologically-based bridge to a malnourished pediatric population, by combining information on a) the differences in body composition between healthy and malnourished adults and b) the differences in physiology between healthy adults and children. Model performance was confirmed using clinical reference data. This study presents a physiologically-based translational framework for prediction of drug disposition in malnourished children. The model is readily applicable for dose recommendation strategies to address the urgent medicinal needs of this vulnerable population.

This work presents the development and implementation of a distributed navigation system based on computer vision. The autonomous system consists of a wheeled mobile robot with an integrated colour camera. The robot navigates through a laboratory scenario where the track and several traffic signals must be detected and recognized by using the images acquired with its on-board camera. The images are sent to a computer server that processes them and calculates the corresponding speeds of the robot using a cascade of trained classifiers. These speeds are sent back to the robot, which acts to carry out the corresponding manoeuvre. The classifier cascade should be trained before experimentation with two sets of positive and negative images. The number of images in these sets should be considered to limit the training stage time and avoid overtraining the system.

Has anyone ever missed an event because he was confused in days and dates? Do we remember the date of any day without looking at a calendar? Is the current Gregorian Calendar efficient enough for use, and does it facilitate our life or make it more complicated? Have you ever thought about a much simpler way to calculate days and dates in a year? All these questions are answered in this paper, in which the author proposes original optimization algorithm that creates optimal perennial calendars. Results show that there is more than one way to create a perennial calendar, in which the number of days in each month does not change, neither the dates. Hence, all months have the same sequence of days and dates. In other meaning, Monday becomes the first day of every month, and Sunday becomes the last day. Consequently, the calendars become much easier to memorize and very simple to predict the days and dates in any year.

Paper-based sensors, microfluidic platforms and electronic devices have attracted attention in the past couple of decades because they are flexible, can be recycled easily, environmentally friendly, and inexpensive. Here we report a paper aptamer-based potentiometric sensor to detect the whole Zika virus for the first time with a minimum sensitivity of 2.6 nV/Zika and the minimum detectable signal (MDS) of 0.8x1e6 Zika. Our paper sensor works very similar to a P-N junction where a junction is formed between two different wet regions with different electrochemical potentials near each other on the paper. These two regions with slightly different ionic contents, ionic species and concentrations, produce a potential difference given by the Nernst equation. Our paper sensor consisted of a 2-3 mm x 10 mm segments of a paper with a conducting silver paint contact patches on its two ends. The paper is soaked in a buffer solution containing aptamers designed to bind to the capsid proteins on Zika. Atomic force microscopy studies were carried out to show both the aptamer and Zika become immobilized in the paper. We then added the Zika (in its own buffer or simulant Urine) to the region close to one of the silver-paint contacts. The Zika virus (40 nm diameter with 43 kDa or 7.1x10-20 gm weight), became immobilized in the paper’s pores and bonded with the resident aptamers creating a concentration gradient. The potential measured between the two silver paint contacts reproducibly became more negative as upon adding the Zika. We also showed that an LCD powered by the sensor, can be used to detect the sensor output.

Paper-based sensors, microfluidic platforms and electronic devices have attracted attention in the past couple of decades because they are flexible, can be recycled easily, environmentally friendly, and inexpensive. Here we report a paper aptamer-based potentiometric sensor to detect the whole Zika virus for the first time with a minimum sensitivity of 2.6 nV/Zika and the minimum detectable signal (MDS) of 1.2x10⁶ Zika. Our paper sensor works very similar to a P-N junction where a junction is formed between two different wet regions with different electrochemical potentials near each other on the paper. These two regions with slightly different ionic contents, ionic species and concentrations, produce a potential difference given by the Nernst equation. Our paper sensor consisted of a 2-3 mm x 10 mm segments of a paper with a conducting silver paint contact patches on its two ends. The paper is soaked in a buffer solution containing aptamers designed to bind to the capsid proteins on Zika. Atomic force microscopy studies were carried out to show both the aptamer and Zika become immobilized in the paper. We then added the Zika (in its own buffer) to the region close to one of the silver-paint contacts. The Zika virus (40 nm diameter with 43 kDa or 7.1x10^-20 gm weight), became immobilized in the paper’s pores and bonded with the resident aptamers creating a concentration gradient. The potential measured between the two silver paint contacts reproducibly became more negative as upon adding the Zika. We also showed that an LCD powered by the sensor, can be used to detect the sensor output.

Many physiotherapy treatments begin with a diagnosis process. The patient describes symptoms, upon which the physiotherapist decides which tests to perform until a final diagnosis is reached. The relationships between the anatomical components are too complex to keep in mind and the possible actions are abundant. A trainee physiotherapist with little experience naively applies multiple tests to reach the root cause of the symptoms, which is a highly inefficient process. This work proposes to assist students in this challenge by presenting three main contributions: (1) A compilation of the neuromuscular system as components of a system in a Model-Based Diagnosis problem; (2) The PhysIt is an AI-based tool that enables an interactive visualization and diagnosis to assist trainee physiotherapists; and (3) An empirical evaluation that comprehends performance analysis and a user study. The performance analysis is based on evaluation of simulated cases and common scenarios taken from anatomy exams. The user study evaluates the efficacy of the system to assist students in the beginning of the clinical studies. The results show that our system significantly decreases the number of candidate diagnoses, without discarding the correct diagnosis, and that students in their clinical studies find PhysIt helpful in the diagnosis process.

This study proposes a new algorithm termed rain cell identification and tracking (RCIT) to identify and track rain cells from high resolution weather radar data. Previous algorithms have limitations when tracking non-consequent rain cells owing to their use of maximum correlation coefficient methods and their lack of an alternative way to handle the variation stages of rain cells during their life cycles. To address these deficiencies, various methods are implemented in the new algorithm. These include the particle image velocimetry (PIV) method for motion estimation and the rain cell matching rule to obtain the stage changes of rain cells. High resolution (5-min and 1-km) radar reflectivity data from three rainy days over the German federal state North Rhine Westphalia (NRW) are used to evaluate the proposed algorithm. The performance of the new algorithm is compared with a radar reflectivity map and verified by two object-oriented methods: structure–amplitude–location (SAL) and geometric index. The verification results suggest that the performance of the new algorithm is good. Application of the RCIT algorithm to the selected cases shows that the inner structure of rainfall events in the experimental region present extreme value distributions, with most rainfall events having a short duration with less intensity. The new algorithm can effectively capture the stage changes of rain cells during their life cycles. The proposed algorithm can serve as the basis for further hydro-meteorological applications such as spatial and temporal analysis of rainfall events and short-term flood forecasting.

The quadruple burden of diseases, early discharge from hospital and hospital at home have resulted in home-based care services becoming a requirement in South Africa. The home-based care services generate a significant amount of health care risk waste that is mismanaged. However, more attention is given to the health care risk waste generated in hospitals and clinics than to health care risk waste generated by home-based caregivers. Therefore, this study investigates the health care risk waste management practices by home-based caregivers. The study adopted a mixed research approach, qualitative and quantitative methods, using a literature review, interviews, and questionnaires as means of data collection. Results show that there are different types of health care risk waste generated as a result of different activities performed by home-based caregivers, but that the waste was found to be managed in an unsafe manner. The majority of households receiving home-based care did not have basic sanitation facilities such as toilets, running water and waste removal services, aggravating the issue of health care risk waste mismanagement. The study recommends a new policy framework that will lead to safe management practices of generated health care risk waste to be adopted by home-based caregivers.

The application of graph theory in chemical and molecular structure research far exceeds people's expectations, and it has recently grown exponentially. In the molecular graph, atoms are represented by vertices and bonded by edges. Closed forms of multiplicative degree-based topological indices which are numerical parameters of the structure and determine physico-chemical properties of the concerned molecular compound. In this article, we compute and analyze many multiplicative degree-based topological indices of silicon-carbon Si₂C₃-I[p,q] and Si₂C₃-II[p,q].

Recent discovery of triangular boron Nanotubes makes it a competitor of carbon in many respects. Closed forms of M-polynomial of nanotubes produce closed forms of many degree-based topological indices which are numerical parameters of the structure and, in combination, determine properties of the concerned nanotubes. In this report, we give M-polynomials of triangular boron nanotubes and recover many important topological degree-based indices of these nanotubes. We also plot surfaces associated to these nanotubes.

This review focuses on Cu/TiO2 sequentially and Cu-TiO2 co-sputtered catalytic/photocatalytic surfaces leading to bacterial inactivation discussing their stability, synthesis, adhesion and antibacterial kinetics. The intervention of TiO2, Cu and the synergic effect of Cu and TiO2 on films prepared by a colloidal approach and other techniques is also reviewed leading to bacterial inactivation. Processes in aerobic media and anaerobic media leading to bacterial loss of viability on multidrug resistant (MDR) pathogens, Gram-negative (-) and Gram-positive(+) bacteria are described. Insight is provided for the interfacial charge transfer mechanism under solar irradiation occurring between TiO2 and Cu. surface properties of 2D TiO2/Cu and TiO2-Cu films are correlated with the bacterial inactivation kinetics observed in the dark and under light. The intervention of these antibacterial sputtered surfaces in health-care facilities leading to MRSA-isolates is described in the dark and under the actinic light. The synergic intervention of the Cu and TiO2 films leading to bacterial inactivation prepared by direct current magnetron sputtering (DCMS), pulsed direct current magnetron sputtering (DCMSP) and highly ionized pulse plasma magnetron sputtering (HIPIMS) is reported in a detailed way.