Search results for: nano on-chip network

Authors: Nungki Rositaningsih, Emil Budianto

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Starch has been widely used as an encapsulation material for drug delivery system. However, starch hydrogel is very easily degraded during metabolism in human stomach. Modification of this material is needed to improve the encapsulation process in drug delivery system, especially for gastrointestinal drug. In this research, three modified starch-based hydrogels are synthesized i.e. Crosslinked starch hydrogel, Semi- and Full- Interpenetrating Polymer Network (IPN) starch hydrogel using Poly(N-Vinyl-Pyrrolidone). Non-modified starch hydrogel was also synthesized as a control. All of those samples were compared as biomaterials, floating drug delivery, and their ability in loading drug test. Biomaterial characterizations were swelling test, stereomicroscopy observation, Differential Scanning Calorimetry (DSC), and Fourier Transform Infrared Spectroscopy (FTIR). Buoyancy test and stereomicroscopy scanning were done for floating drug delivery characterizations. Lastly, amoxicillin was used as test drug, and characterized with UV-Vis spectroscopy for loading drug observation. Preliminary observation showed that Full-IPN has the most dense and elastic texture, followed by Semi-IPN, Crosslinked, and Non-modified in the last position. Semi-IPN and Crosslinked starch hydrogel have the most ideal properties and will not be degraded easily during metabolism. Therefore, both hydrogels could be considered as promising candidates for encapsulation material. Further analysis and issues will be discussed in the paper.

Keywords: biomaterial, drug delivery system, interpenetrating polymer network, poly(N-vinyl-pyrrolidone), starch hydrogel

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Authors: Imtiaz Ahmed Khan, Sabu John, Sania Waqar, Lijing Wang, Mac Fergusson, Ilija Najdovski

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Evolution of textiles, from its orthodox to more interactive role has stirred the researchers to uncover its application in numerous arenas. The idea of using textile based materials for wearable energy harvesting and storage devices have gained immense popularity. This is mainly due to textile comfort and flexibility features. In this work, nano-carbonous materials were infused on cellulosic fibers using caustic soda treatment. This paper presents the complete procedure of yarn supercapacitors fabrication process through dip coating technique and its characterization method. The main objective is to study, the effect of varying caustic soda concentration on mass loading of activated carbon on yarns and the related capacitance output of the designed yarn supercapacitor. Polyvinyl alcohol and Phosphoric acid were used as electrolyte in a two-electrode cell assembly to measure device electrochemical performance. The results show a promising increase in capacitance value using this technique.

Keywords: yarn supercapacitors, activated carbon, dip coating, caustic soda, electrolyte, electrochemical characterization

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Authors: Jung Lee

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The last decade has witnessed more people than ever before using social media and broadening their social circles. Social media users connect not only with their friends but also with professional acquaintances, primarily coworkers, and clients; personal and professional social circles are mixed within the same social media platform. Considering the positive aspect of social media in facilitating communication and mutual understanding between individuals, we infer that social media interactions with co-workers could indeed benefit one’s professional life. However, given privacy issues, sharing all personal details with one’s co-workers is not necessarily the best practice. Should one connect with coworkers via social media? Will social media connections with coworkers eventually benefit one’s long-term career? Will the benefit differ across cultures? To answer, this study examines how social media can contribute to organizational communication by tracing the foundation of user motivation based on social capital theory, leader-member exchange (LMX) theory and expectancy theory of motivation. Although social media was originally designed for personal communication, users have shown intentions to extend social media use for professional communication, especially when the proper incentive is expected. To articulate the user motivation and the mechanism of the incentive expectation scheme, this study applies those three theories and identify six antecedents and three moderators of social media use motivation including social network flaunt, shared interest, perceived social inclusion. It also hypothesizes that the moderating effects of those constructs would significantly differ based on the relationship hierarchy among the workers. To validate, this study conducted a survey of 329 active social media users with acceptable levels of job experiences. The analysis result confirms the specific roles of the three moderators in social media adoption for organizational communication. The present study contributes to the literature by developing a theoretical modeling of ambivalent employee perceptions about establishing social media connections with co-workers. This framework shows not only how both positive and negative expectations of social media connections with co-workers are formed based on expectancy theory of motivation, but also how such expectations lead to behavioral intentions using career success model. It also enhances understanding of how various relationships among employees can be influenced through social media use and such usage can potentially affect both performance and careers. Finally, it shows how cultural factors induced by social media use can influence relations among the coworkers.

Keywords: the social network, workplace, social capital, motivation

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Authors: Muhammad Ahnaf Zahin, Yaw Adu-Gyamfi

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Bus transit is a crucial component of transportation networks, especially in urban areas. Any intelligent transportation system must have accurate real-time information on bus travel times since it minimizes waiting times for passengers at different stations along a route, improves service reliability, and significantly optimizes travel patterns. Bus agencies must enhance the quality of their information service to serve their passengers better and draw in more travelers since people waiting at bus stops are frequently anxious about when the bus will arrive at their starting point and when it will reach their destination. For solving this issue, different models have been developed for predicting bus travel times recently, but most of them are focused on smaller road networks due to their relatively subpar performance in high-density urban areas on a vast network. This paper develops a deep learning-based architecture using a single-step multi-station forecasting approach to predict average bus travel times for numerous routes, stops, and trips on a large-scale network using heterogeneous bus transit data collected from the GTFS database. Over one week, data was gathered from multiple bus routes in Saint Louis, Missouri. In this study, Gated Recurrent Unit (GRU) neural network was followed to predict the mean vehicle travel times for different hours of the day for multiple stations along multiple routes. Historical time steps and prediction horizon were set up to 5 and 1, respectively, which means that five hours of historical average travel time data were used to predict average travel time for the following hour. The spatial and temporal information and the historical average travel times were captured from the dataset for model input parameters. As adjacency matrices for the spatial input parameters, the station distances and sequence numbers were used, and the time of day (hour) was considered for the temporal inputs. Other inputs, including volatility information such as standard deviation and variance of journey durations, were also included in the model to make it more robust. The model's performance was evaluated based on a metric called mean absolute percentage error (MAPE). The observed prediction errors for various routes, trips, and stations remained consistent throughout the day. The results showed that the developed model could predict travel times more accurately during peak traffic hours, having a MAPE of around 14%, and performed less accurately during the latter part of the day. In the context of a complicated transportation network in high-density urban areas, the model showed its applicability for real-time travel time prediction of public transportation and ensured the high quality of the predictions generated by the model.

Keywords: gated recurrent unit, mean absolute percentage error, single-step forecasting, travel time prediction.

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Authors: Sokratis Koskinakis, Georgia Frakolaki, Magdalini Krokida

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Regular consumption of omega-3 fatty acid-rich lipids is said to provide a wide range of health benefits, including prevention of inflammation, cardiovascular disease, diabetes, arthritis, and ulcerative colitis. Because of their potential nutritional and health benefits, the omega-3 PUFAs are increasingly being supplemented in functional food products meant to improve human health and wellbeing. However, dietary fortification with PUFAs is difficult due to their low water solubility, tendency to oxidize quickly, and inconsistent bioavailability. These issues can be solved through application of modern encapsulation technologies, which typically entail integrating omega-3 oils into well-designed matrices made from food-grade components. Electrospinning, for example, is an effective encapsulation method for producing sub-micron or nano-scale polymer fibers. For this purpose, various combinations of hydroxypropyl-β-cyclodextrin and cellulose nanocrystals/ nanofibers were assessed for the encapsulation of omega-3 fatty acids through the innovative technology of electrospinning. The encapsulation yield was evaluated through GC-analysis, and the morphology of the final products was assessed through SEM analysis.

Keywords: electrospinning, encapsulation, omega-3 fatty acids, cellulose nanocrystals / nanofibers

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Authors: Shalini Rajput, Dinesh Mohan

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Water is the most important and essential resources for existing of life on the earth. Water quality is gradually decreasing due to increasing urbanization and industrialization and various other developmental activities. It can pose a threat to the environment and public health therefore it is necessary to remove hazardous contaminants from wastewater prior to its discharge to the environment. Recently, magnetic iron oxide nanoparticles have been arise as significant materials due to its distinct properties. This article focuses on the synthesis method with a possible mechanism, structure and application of magnetic iron oxide nanoparticles. The various characterization techniques including X-ray diffraction, transmission electron microscopy, scanning electron microscopy with energy dispersive X-ray, Fourier transform infrared spectroscopy and vibrating sample magnetometer are useful to describe the physico-chemical properties of nanoparticles. Nanosized iron oxide particles utilized for remediation of contaminants from aqueous medium through adsorption process. Due to magnetic properties, nanoparticles can be easily separate from aqueous media. Considering the importance and emerging trend of nanotechnology, iron oxide nanoparticles as nano-adsorbent can be of great importance in the field of wastewater treatment.

Keywords: nanoparticles, adsorption, iron oxide, nanotechnology

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Authors: Wann-Ming Wey

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In recent years, the problems of global climate change and natural disasters have induced the concerns and attentions of environmental sustainability issues for the public. Aside from the environmental planning efforts done for human environment, Transit-Oriented Development (TOD) has been widely used as one of the future solutions for the sustainable city development. In order to be more consistent with the urban sustainable development, the development of the built environment planning based on the concept of Green TOD which combines both TOD and Green Urbanism is adapted here. The connotation of the urban development under the green TOD including the design toward environment protect, the maximum enhancement resources and the efficiency of energy use, use technology to construct green buildings and protected areas, natural ecosystems and communities linked, etc. Green TOD is not only to provide the solution to urban traffic problems, but to direct more sustainable and greener consideration for future urban development planning and design. In this study, we use both the TOD and Green Urbanism concepts to proceed to the study of the built environment planning and design. Fuzzy Delphi Technique (FDT) is utilized to screen suitable criteria of the green TOD. Furthermore, Fuzzy Analytic Network Process (FANP) and Quality Function Deployment (QFD) were then developed to evaluate the criteria and prioritize the alternatives. The study results can be regarded as the future guidelines of the built environment planning and designing under green TOD development in Taiwan.

Keywords: green TOD, built environment, fuzzy delphi technique, quality function deployment, fuzzy analytic network process

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Authors: Belal Mohamadi Kalesar, Raouf Hasanpour

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Proper placement of Distributed Generation (DG) units such as wind turbine generators in distribution system are still very challenging issue for obtaining their maximum potential benefits because inappropriate placement may increase the system losses. This paper proposes Particle Swarm Optimization (PSO) technique for optimal placement of wind based DG (WDG) in the primary distribution system to reduce energy losses and voltage profile improvement with four different wind levels modeling in year duration. Also, wind turbine is modeled as a DFIG that will be operated at unity power factor and only one wind turbine tower will be considered to install at each bus of network. Finally, proposed method will be implemented on widely used 69 bus power distribution system in MATLAB software environment under four scenario (without, one, two and three WDG units) and for capability test of implemented program it is supposed that all buses of standard system can be candidate for WDG installing (large search space), though this program can consider predetermined number of candidate location in WDG placement to model financial limitation of project. Obtained results illustrate that wind speed increasing in some months will increase output power generated but this can increase / decrease power loss in some wind level, also results show that it is required about 3MW WDG capacity to install in different buses but when this is distributed in overall network (more number of WDG) it can cause better solution from point of view of power loss and voltage profile.

Keywords: wind turbine, DG placement, wind levels effect, PSO algorithm

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Authors: Chao Hu, Xinwen Liao, Qing-Hua Qin, Gang Wang

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The hierarchical carbon nanotube (CNT)/carbon fiber (CF)/high density polyethylene (HDPE) was fabricated via compound extrusion and injection molding, in which to author’s best knowledge CNT was employed as a nano-coatings on the surface of CF for the first time by spray coating technique. The CNT coatings relative to CF was set at 1 wt% and the CF content relative to the composites varied from 0 to 25 wt% to study the influence of CNT coatings and CF contents on the mechanical, thermal and morphological performance of this hierarchical composites. The results showed that with the rise of CF contents, the mechanical properties, including the tensile properties, flexural properties, and hardness of CNT/CF/HDPE composites, were effectively improved. Furthermore, the CNT-coated composites showed overall higher mechanical performance than the uncoated counterparts. It can be ascribed to the enhancement of interfacial bonding between the CF and HDPE via the incorporation of CNT, which was demonstrated by the scanning electron microscopy observation. Meanwhile, the differential scanning calorimetry data indicated that by the introduction of CNT and CF, the crystallization temperature and crystallinity of HDPE were affected while the melting temperature did not have an obvious alteration.

Keywords: carbon fibers, carbon nanotubes, extrusion, high density polyethylene

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Authors: Ioanna H. Lioliou, Despoina D. Zavraka

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The radical reformation that Greek urban space, has undergone over the last century, due to the socio-historical developments, technological development and political–geographic factors, has left its imprint on the urban landscape. While the big cities struggle to regain urban landscape balance, small towns are considered to offer high quality lifescapes, ensuring sustainable development potential. However, their unplanned urbanization process led to the loss of significant areas of nature, lack of essential infrastructure, chaotic built environment, incompatible land uses and urban cohesiveness. Natural environment reference points, such as springs, streams, rivers, forests, suburban greenbelts, and etc.; seems to be detached from urban space, while the public, open and green spaces, unequally distributed in the built environment, they are no longer able to offer a complete experience of nature in the city. This study focuses on Greek mainland, a small town Elassona, and aims to restore spatial coherence between the city’s homonymous river and its urban space surroundings. The existence of a linear aquatic ecosystem, is considered a precious greenway, also referred as blueway, able to initiate natural penetrations and ecosystems empowering. The integration of disconnected natural ecosystems forms the basis of a strategic intervention scheme, where the river becomes the urban integration tool / feature, constituting the main urban corridor and an indispensible part of a wider green network that connects open and green spaces, ensuring the function of all the established networks (transportation, commercial, social) of the town. The proposed intervention, introduces a green network highlighting the old stone bridge at the ‘entrance’ of the river in the town and expanding throughout the town with strategic uses and activities, providing accessibility for all the users. The methodology used, is based on the collection of design tools used in related urban river-design interventions around the world. The reinstallation/reactivation of the balance between natural and urban landscape, besides the environmental benefits, contributes decisively to the illustration/projection of urban green identity and re-enhancement of the quality of lifescape qualities and social interaction.

Keywords: green network, rehabilitation scheme, urban landscape, urban streams

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Authors: Sandeep Kaur, Jenny Vuong, Marcel Julliard, Sean O'Donoghue

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Time-series data are useful for modelling as they can enable model-evaluation. However, when reconstructing models from phosphoproteomic data, often non-exact methods are utilised, as the knowledge regarding the network structure, such as, which kinases and phosphatases lead to the observed phosphorylation state, is incomplete. Thus, such reactions are often hypothesised, which gives rise to uncertainty. Here, we propose a framework, implemented via a web-based tool (as an extension to Minardo), which given time-series phosphoproteomic datasets, can generate κ models. The incompleteness and uncertainty in the generated model and reactions are clearly presented to the user via the visual method. Furthermore, we demonstrate, via a toy EGF signalling model, the use of algorithmic verification to verify κ models. Manually formulated requirements were evaluated with regards to the model, leading to the highlighting of the nodes causing unsatisfiability (i.e. error causing nodes). We aim to integrate such methods into our web-based tool and demonstrate how the identified erroneous nodes can be presented to the user via the visual method. Thus, in this research we present a framework, to enable a user to explore phosphorylation proteomic time-series data in the context of models. The observer can visualise which reactions in the model are highly uncertain, and which nodes cause incorrect simulation outputs. A tool such as this enables an end-user to determine the empirical analysis to perform, to reduce uncertainty in the presented model - thus enabling a better understanding of the underlying system.

Keywords: κ-models, model verification, time-series phosphoproteomic datasets, uncertainty and error visualisation

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Authors: M. Rahimnejad, B. Vahidi, B. Ebrahimi Hoseinzadeh, F. Yazdian, P. Motamed Fath, R. Jamjah

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In this study, we developed and simulated nano-drug delivery systems efficacy in compare to free drug prescription. Computational models can be utilized to accelerate experimental steps and control the experiments high cost. Molecular dynamics simulation (MDS), in particular NAMD was utilized to better understand the anti-cancer drug interaction with cell membrane model. Paclitaxel (PTX) and dipalmitoylphosphatidylcholine (DPPC) were selected for the drug molecule and as a natural phospholipid nanocarrier, respectively. This work focused on two important interaction parameters between molecules in terms of center of mass (COM) and van der Waals interaction energy. Furthermore, we compared the simulation results of the PTX interaction with the cell membrane and the interaction of DPPC as a nanocarrier loaded by the drug with the cell membrane. The molecular dynamic analysis resulted in low energy between the nanocarrier and the cell membrane as well as significant decrease of COM amount in the nanocarrier and the cell membrane system during the interaction. Thus, the drug vehicle showed notably better interaction with the cell membrane in compared to free drug interaction with the cell membrane.

Keywords: anti-cancer drug, center of mass, interaction energy, molecular dynamics simulation, nanocarrier

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Authors: Jianli Jiang, Bai-Chen Xie

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The climate issue has aroused global concern. Achieving sustainable development is a good path for countries to mitigate environmental and climatic pressures, although there are many difficulties. The first step towards sustainable development is to evaluate the environmental efficiency of the energy industry with proper methods. The power sector is a major source of CO2, SO2, and NOx emissions. Evaluating the environmental efficiency (EE) of power systems is the premise to alleviate the terrible situation of energy and the environment. Data Envelopment Analysis (DEA) has been widely used in efficiency studies. However, measuring the efficiency of a system (be it a nation, region, sector, or business) is a challenging task. The classic DEA takes the decision-making units (DMUs) as independent, which neglects the interaction between DMUs. While ignoring these inter-regional links may result in a systematic bias in the efficiency analysis; for instance, the renewable power generated in a certain region may benefit the adjacent regions while the SO2 and CO2 emissions act oppositely. This study proposes a spatial network DEA (SNDEA) with a slack measure that can capture the spatial spillover effects of inputs/outputs among DMUs to measure efficiency. This approach is used to study the EE of China's power system, which consists of generation, transmission, and distribution departments, using a panel dataset from 2014 to 2020. In the empirical example, the energy and patent inputs, the undesirable CO2 output, and the renewable energy (RE) power variables are tested for a significant spatial spillover effect. Compared with the classic network DEA, the SNDEA result shows an obvious difference tested by the global Moran' I index. From a dynamic perspective, the EE of the power system experiences a visible surge from 2015, then a sharp downtrend from 2019, which keeps the same trend with the power transmission department. This phenomenon benefits from the market-oriented reform in the Chinese power grid enacted in 2015. The rapid decline in the environmental efficiency of the transmission department in 2020 was mainly due to the Covid-19 epidemic, which hinders economic development seriously. While the EE of the power generation department witnesses a declining trend overall, this is reasonable, taking the RE power into consideration. The installed capacity of RE power in 2020 is 4.40 times that in 2014, while the power generation is 3.97 times; in other words, the power generation per installed capacity shrank. In addition, the consumption cost of renewable power increases rapidly with the increase of RE power generation. These two aspects make the EE of the power generation department show a declining trend. Incorporation of the interactions among inputs/outputs into the DEA model, this paper proposes an efficiency evaluation method on the basis of the DEA framework, which sheds some light on efficiency evaluation in regional studies. Furthermore, the SNDEA model and the spatial DEA concept can be extended to other fields, such as industry, country, and so on.

Keywords: spatial network DEA, environmental efficiency, sustainable development, power system

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Authors: Li Qian, Jinchao Tong, Daohua Zhang, Weijun Fan, Fei Suo

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Photonic applications based on group IV semiconductors have always been an interest but also a challenge for the research community. We report manufacturing group IV Ge₁₋ₓSnₓ alloys with tuneable energy band gap on (100) GaAs substrate by a modified radio frequency magnetron co-sputtering. Images were taken by atomic force microscope, and scanning electron microscope clearly demonstrates a smooth surface profile, and Ge₁₋ₓSnₓ nano clusters are with the size of several tens of nanometers. Transmittance spectra were measured by Fourier Transform Infrared Spectroscopy that showed changing energy gaps with the variation in elementary composition. Calculation results by 8-band k.p method are consistent with measured gaps. Our deposition system realized direct growth of Ge₁₋ₓSnₓ thin film on GaAs (100) substrate by sputtering. This simple deposition method was modified to be able to grow high-quality photonic materials with tuneable energy gaps. This work provides an alternative and successful method for fabricating Group IV photonic semiconductor materials.

Keywords: GeSn, crystal growth, sputtering, photonic

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Authors: Satya Eswari Jujjavarapu, Swasti Dhagat, Lata Upadhyay, Reecha Sahu

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Silver nanoparticles have a broad range of antimicrobial and antifungal properties ranging from soaps, pastes to sterilization and drug delivery systems. These can be synthesized by physical, chemical and biological methods; biological methods being the most popular owing to their non-toxic nature and reduced energy requirements. Microbial surfactants, produced on the microbial cell surface or excreted extracellularly are an alternative to synthetic surfactants for the production of silver nanoparticles. Hence, they are also called as green molecules. Microbial lipopeptide surfactants (biosurfactant) exhibit anti-tumor and anti-microbial properties and can be used as drug delivery agents. In this study, biosurfactant was synthesized by using a strain of acillus subtilis. The biosurfactant thus produced was analysed by emulsification assay, oil spilling test, and haemolytic test. Biosurfactant-mediated silver nanoparticles were synthesised by microwave irradiation of the culture supernatant and further characterized by UV–vis spectroscopy for a range of 400-600 nm. The UV–vis spectra showed a surface plasmon resonance vibration band at 410 nm corresponding to the peak of silver nanoparticles.

Keywords: biosurfactant, Bacillus subtilis, silver nano particle, lipopeptide

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Authors: Mehwish Asghar

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Breast Cancer (BC) is a common type of cancer among women. Its screening is usually performed using different imaging modalities such as magnetic resonance imaging, mammogram, X-ray, CT, etc. Among these modalities’ mammogram is considered a powerful tool for diagnosis and screening of breast cancer. Sophisticated machine learning approaches have shown promising results in complementing human diagnosis. Generally, machine learning methods can be divided into two major classes: one is Radiomics analysis (RA), where image features are extracted manually; and the other one is the concept of convolutional neural networks (CNN), in which the computer learns to recognize image features on its own. This research aims to improve the incidence of early detection, thus reducing the mortality rate caused by breast cancer through the latest advancements in computer science, in general, and machine learning, in particular. It has also been aimed to ease the burden of doctors by improving and automating the process of breast cancer detection. This research is related to a relative analysis of different techniques for the implementation of different models for detecting and classifying breast cancer. The main goal of this research is to provide a detailed view of results and performances between different techniques. The purpose of this paper is to explore the potential of a convolutional neural network (CNN) w.r.t feature extractor and as a classifier. Also, in this research, it has been aimed to add the module of Radiomics for comparison of its results with deep learning techniques.

Keywords: breast cancer (BC), machine learning (ML), convolutional neural network (CNN), radionics, magnetic resonance imaging, artificial intelligence

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Authors: Mohamed S. Selim, Nesreen A. Fatthallah, Shimaa A. Higazy, Zhifeng Hao, Xiang Chen

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After the prohibition of tin-based fouling-prevention coatings in 2003, the researchers were directed toward eco-friendly coatings. Because of their nonstick, environmental, and economic benefits, foul-release nanocoatings have received a lot of attention. They use physical anti-adhesion terminology to deter any fouling attachment.Natural bioinspired surfaces have micro/nano-roughness and low surface free energy features, which may inspire the design of dynamic antifouling coatings. Graphene-based nanocomposite surfaces were designed to combat marine-fouling adhesion with ecological as well as eco-friendly effects rather than biocidal solutions. Polymer–graphenenanofiller hybrids are a novel class of composite materials in fouling-prevention applications. The controlled preparation of nanoscale orientation, arrangement, and direction along the composite building blocks would result in superior fouling prohibition. This work representsfoul-release nanocomposite top coats for marine coating applications with superhydrophobicity, surface inertness against fouling adherence, cost-effectiveness, and increased lifetime.

Keywords: foul-release nanocoatings, graphene-based nanocomposite, polymer, nanofillers

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Authors: J. Palán, M. Zemko

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COMTES FHT has been active in a field of research and development of high-strength wires for quite some time. The main material was pure titanium. The primary goal of this effort is to develop a continuous production process for ultrafine and nanostructured materials with the aid of severe plastic deformation (SPD). This article outlines mechanical and microstructural properties of the materials and the options available for testing the components made of these materials. Ti Grade 2 and Grade 4 wires are the key products of interest. Ti Grade 2 with ultrafine to nano-sized grain shows ultimate strength of up to 1050 MPa. Ti Grade 4 reaches ultimate strengths of up to 1250 MPa. These values are twice or three times as higher as those found in the unprocessed material. For those fields of medicine where implantable metallic materials are used, bulk ultrafine to nanostructured titanium is available. It is manufactured by SPD techniques. These processes leave the chemical properties of the initial material unchanged but markedly improve its final mechanical properties, in particular, the strength. Ultrafine to nanostructured titanium retains all the significant and, from the biological viewpoint, desirable properties that are important for its use in medicine, i.e. those properties which made pure titanium the preferred material also for dental implants.

Keywords: CONFORM, ECAP, rotary swaging, titanium

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Authors: Natasa Ilic, Alisa Gruden-Movsesijan, Maja Kosanovic, Sofija Glamoclija, Marina Bekic, Ljiljana Sofronic-Milosavljevic, Sergej Tomic

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As a very promising candidate for modulation of immune response in the sense of biasing the inflammatory towards an anti-inflammatory type of response, Trichinella spiralis infection was shown to successfully alleviate the severity of experimental autoimmune encephalomyelitis, the animal model of human disease multiple sclerosis. This effect is achieved via its excretory-secretory muscle larvae (ES L1) products which affect the maturation status and function of dendritic cells (DCs) by inducing the tolerogenic status of DCs, which leads to the mitigation of the Th1 type of response and the activation of a regulatory type of immune response both in vitro and in vivo. ES L1 alone or via treated DCs successfully mitigated EAE in the same manner as the infection itself. On the other hand, it has been shown that T. spiralis infection slows down the tumour growth and significantly reduces the tumour size in the model of mouse melanoma, while ES L1 possesses a pro-apoptotic and anti-survival effect on melanoma cells in vitro. Hence, although the mechanisms still need to be revealed, T. spiralis infection and its ES L1 products have a bit of controversial potential to modulate both inflammatory diseases and malignancies. The recent discovery of T. spiralis extracellular vesicles (TsEVs) suggested that the induction of complex regulation of the immune response requires simultaneous delivery of different signals in nano-sized packages. This study aimed to explore whether TsEVs bare the similar potential as ES L1 to influence the status of DCs in initiation, progression and regulation of immune response, but also to investigate the effect of both ES L1 and TsEVs on myeloid derived suppressor cells (MDSC) which present the regular tumour tissue environment. TsEVs were enriched from the conditioned medium of T. spiralis muscle larvae by differential centrifugation and used for the treatment of human monocyte-derived DCs and MDSC. On DCs, TsEVs induced low expression of HLA DR and CD40, moderate CD83 and CD86, and increased expression of ILT3 and CCR7 on treated DCs, i.e., they induced tolerogenic DCs. Such DCs possess the capacity to polarize T cell immune response towards regulatory type, with an increased proportion of IL-10 and TGF-β producing cells, similarly to ES L1. These findings indicated that the ability of TsEVs to induce tolerogenic DCs favoring anti-inflammatory responses may be helpful in coping with diseases that involve Th1/Th17-, but also Th2-mediated inflammation. In MDSC in vitro model, although both ES L1 and TsEVs had the same impact on MDSC phenotype i.e., they acted suppressive, ES L1 treated MDSC, unlike TsEVs treated ones, induced T cell response characterized by the increased RoRγT and IFN-γ, while the proportion of regulatory cells was decreased followed by the decrease in IL-10 and TGF-β positive cells proportion within this population. These findings indicate the interesting ability of ES L1 to modulate T cells response via MDSC towards pro-inflamatory type, suggesting that, unlike TsEVs which consistently demonstrate the suppresive effect on inflammatory response, it could be used also for the development of new approaches aimed for the treatment of malignant diseases. Acknowledgment: This work was funded by the Promis project – Nano-MDCS-Thera, Science Fund, Republic of Serbia.

Keywords: dendritic cells, myeloid derived suppressor cells, immunomodulation, Trichinella spiralis

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Authors: Sameena Malik, Ghosh Prakash, Sandeep Mudliar, Vishal Waindeskar, Atul Vaidya

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In this study, the biodegradability enhancement along with COD color and toxicity removal of pharmaceutical effluent by O₃, O₃/Fe²⁺, O₃/nZVI processes has been evaluated. The nZVI particles were synthesized and characterized by XRD and SEM analysis. Kinetic model was reasonably developed to select the ozone doses to be applied based on the ozonation kinetic and mass transfer coefficient values. Nano catalytic ozonation process (O₃/nZVI) effectively enhanced the biodegradability (BI=BOD₅/COD) of pharmaceutical effluent up to 0.63 from 0.18 of control with a COD, color and toxicity removal of 62.3%, 93%, and 75% respectively compared to O₃, O₃/Fe²⁺ pretreatment processes. From the GC-MS analysis, 8 foremost organic compounds were predominantly detected in the pharmaceutical effluent. The disappearance of the corresponding GC-MS spectral peaks during catalyzed ozonation process indicated the degradation of the effluent. The changes in the FTIR spectra confirms the transformation/destruction of the organic compounds present in the effluent to new compounds. Subsequent aerobic biodegradation of pretreated effluent resulted in biodegradation rate enhancement by 5.31, 2.97, and 1.22 times for O₃, O₃/Fe²⁺ and O₃/nZVI processes respectively.

Keywords: iron nanoparticles, pharmaceutical effluent, ozonation, kinetics, mass transfer

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Authors: Jinrui Zhang, Tianlong Yang, Ying Pan

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Methane and carbon dioxide are major greenhouse gases contributor. CO₂ dry reforming of methane (DRM) for syngas production is a promising approach to reducing global CO₂ emission and extensive utilization of natural gas. However, the reported catalysts endured rapid deactivation due to severe carbon deposition at high temperature. Here, CO₂ reduction by CH4 on hexagonal nano-nickel flakes packed by porous SiO₂ (Ni@SiO₂) catalysts driven by thermal and solar light are tested. High resistance to carbon deposition and higher reactive activity are demonstrated under focused solar light at moderate temperature (400-500 ℃). Furthermore, the photocatalytic DRM under different wavelength is investigated, and even IR irradiation can enhance the catalytic activity. The mechanism of light-enhanced reaction reactivity and equilibrium is investigated by Infrared and Raman spectroscopy, and the unique reaction pathway with light is depicted. The photo-enhanced DRM provides a promising method of renewable solar energy conversion and CO₂ emission reduction due to the excellent activity and durability.

Keywords: CO₂ emission reduction, methane, photocatalytic DRM, resistance to carbon deposition, syngas

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Authors: Judith Margaret Tymon

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As cities struggle to incorporate informal settlements into the fabric of urban areas, the focus has often been on the provision of housing. This study explores the underlying structure of street networks, with the goal of understanding the morphogenesis of informal settlements through the lens of the access network. As the stages of development progress from infill to consolidation and eventually, to a planned in-situ settlement, the access networks retain the form of the core segments; however, a majority of street patterns are adapted to a grid design to support infrastructure in the final upgraded phase. A case study is presented to examine the street network in the informal settlement of Gobabis Namibia as it progresses from its initial stages to a planned, in-situ, and permanently upgraded development. The Informal Development Stages framework of foundation, infill, and consolidation, as developed by Dr. Jota Samper, is utilized to examine the evolution of street networks. Data is gathered from historical Google Earth satellite images for the time period between 2003 and 2022. The results demonstrate that during the foundation through infill stages, incremental changes follow similar patterns, with pathways extended, lengthened, and densified as housing is created and the settlement grows. In the final stage of consolidation, the resulting street layout is transformed to support the installation of infrastructure; however, some elements of the original street patterns remain. The core pathways remain intact to accommodate the installation of infrastructure and the creation of housing plots, defining the shape of the settlement and providing the basis of the urban form. The adaptations, growth, and consolidation of the street network are critical to the eventual formation of the spatial layout of the settlement. This study will include a comparative analysis of findings with those of recent research performed by Kamalipour, Dovey, and others regarding incremental urbanism within informal settlements. Further comparisons will also include studies of street networks of well-established urban centers that have shown links between the morphogenesis of access networks and the eventual spatial layout of the city. The findings of the study can be used to guide and inform strategies for in-situ upgrading and can contribute to the sustainable development of informal settlements.

Keywords: Gobabis Namibia, incremental urbanism, informal development stages, informal settlements, street networks

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Authors: H. Alamri

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Natural fiber reinforced composites have attracted researchers for their desirable properties of toughness, high modulus, low density, recyclability, and renewability. In fact, the use of natural fibers in polymer composites has the potential to produce materials with higher specific strength and specific modulus due of their low density. Likewise, polymer-nano-filler composites have been widely investigated for their unique and significant improvement in strength, modulus, impact strength, barrier properties, heat resistance and thermal stability. In this paper, The addition of halloysite nanotubes (HNTs) with three different weight percentages (1%, 3% and 5%) on enhancing barrier and flexural strength and modulus of cellulose-fiber (CF) /epoxy composites after water treatment for six months was studied. Results indicated that water uptake decreased as HNT content increased. The presence of HNT improved flexural strength and flexural modulus of CF/epoxy composites. SEM results showed damages in fiber-matrix interfacial bonding due to water absorption. The addition of HNTs was found to enhance to adhesion between fibers and matrix.

Keywords: mechanical properties, epoxy, nanocomposites, halloysite nanotubes

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Authors: Craig A. Kaplan

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If AGI proves to be a “winner-take-all” scenario where the first company or country to develop AGI dominates, then the first AGI must also be the safest. The safest, and fastest, path to Artificial General Intelligence (AGI) may be to harness the collective intelligence of multiple AI and human agents in an AGI network. This approach has roots in seminal ideas from four of the scientists who founded the field of Artificial Intelligence: Allen Newell, Marvin Minsky, Claude Shannon, and Herbert Simon. Extrapolating key insights from these founders of AI, and combining them with the work of modern researchers, results in a fast and safe path to AGI. The seminal ideas discussed are: 1) Society of Mind (Minsky), 2) Information Theory (Shannon), 3) Problem Solving Theory (Newell & Simon), and 4) Bounded Rationality (Simon). Society of Mind describes a collective intelligence approach that can be used with AI and human agents to create an AGI network. Information theory helps address the critical issue of how an AGI system will increase its intelligence over time. Problem Solving Theory provides a universal framework that AI and human agents can use to communicate efficiently, effectively, and safely. Bounded Rationality helps us better understand not only the capabilities of SuperIntelligent AGI but also how humans can remain relevant in a world where the intelligence of AGI vastly exceeds that of its human creators. Each key idea can be combined with recent work in the fields of Artificial Intelligence, Machine Learning, and Large Language Models to accelerate the development of a working, safe, AGI system.

Keywords: AI Agents, Collective Intelligence, Minsky, Newell, Shannon, Simon, AGI, AGI Safety

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Authors: Mohamed Youssry, Dominique Guyomard, Bernard Lestriez

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In order to enhance the energy and power densities of electrodes for energy storage systems, the formulation and processing of electrode slurries proved to be a critical issue in determining the electrode performance. In this study, we introduce novel approach to formulate carbon black slurries based on microemulsion and lyotropic liquid crystalline phases (namely, lamellar phase) composed of non-ionic surfactant (Triton X100), decanol and water. Simultaneous measurements of electrical properties of slurries under shear flow (rheology) have been conducted to elucidate the microstructure evolution with the surfactant concentration and decanol/water ratio at rest, as well as, the structural transition under steady-shear which has been confirmed by rheo-microscopy. Interestingly, the carbon black slurries at low decanol/water ratio are weak-gel (flowable) with higher electrical conductivity than those at higher ratio which behave strong-gel viscoelastic response. In addition, the slurries show recoverable electrical behaviour under shear flow in tandem with the viscosity trend. It is likely that oil-in-water microemulsion enhances slurries’ stability without affecting on the percolating network of carbon black. On the other hand, the oil-in-water analogous and bilayer structure of lamellar phase cause the slurries less conductive as a consequence of losing the network percolation. These findings are encouraging to formulate microemulsion-based electrodes for energy storage system (lithium-ion batteries).

Keywords: electrode slurries, microemulsion, microstructure transition, rheo-electrical properties

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Authors: Moustafa Osman Mohammed

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The modeling of a spatial-economic database is crucial in recitation economic network structure to social development. Sustainability within the spatial-economic model gives attention to green businesses to comply with Earth’s Systems. The natural exchange patterns of ecosystems have consistent and periodic cycles to preserve energy and materials flow in systems ecology. When network topology influences formal and informal communication to function in systems ecology, ecosystems are postulated to valence the basic level of spatial sustainable outcome (i.e., project compatibility success). These referred instrumentalities impact various aspects of the second level of spatial sustainable outcomes (i.e., participant social security satisfaction). The sustainability outcomes are modeling composite structure based on a network analysis model to calculate the prosperity of panel databases for efficiency value, from 2005 to 2025. The database is modeling spatial structure to represent state-of-the-art value-orientation impact and corresponding complexity of sustainability issues (e.g., build a consistent database necessary to approach spatial structure; construct the spatial-economic-ecological model; develop a set of sustainability indicators associated with the model; allow quantification of social, economic and environmental impact; use the value-orientation as a set of important sustainability policy measures), and demonstrate spatial structure reliability. The structure of spatial-ecological model is established for management schemes from the perspective pollutants of multiple sources through the input–output criteria. These criteria evaluate the spillover effect to conduct Monte Carlo simulations and sensitivity analysis in a unique spatial structure. The balance within “equilibrium patterns,” such as collective biosphere features, has a composite index of many distributed feedback flows. The following have a dynamic structure related to physical and chemical properties for gradual prolong to incremental patterns. While these spatial structures argue from ecological modeling of resource savings, static loads are not decisive from an artistic/architectural perspective. The model attempts to unify analytic and analogical spatial structure for the development of urban environments in a relational database setting, using optimization software to integrate spatial structure where the process is based on the engineering topology of systems ecology.

Keywords: ecological modeling, spatial structure, orientation impact, composite index, industrial ecology

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Authors: Neveen AlQasas, Daniel Johnson

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Membranes for water treatment are an established technology that attracts great attention due to its simplicity and cost effectiveness. However, membranes in operation suffer from the adverse effect of membrane fouling. Bio-fouling is a phenomenon that occurs at the water-membrane interface, and is a dynamic process that is initiated by the adsorption of dissolved organic material, including biomacromolecules, on the membrane surface. After initiation, attachment of microorganisms occurs, followed by biofilm growth. The biofilm blocks the pores of the membrane and consequently results in reducing the water flux. Moreover, the presence of a fouling layer can have a substantial impact on the membrane separation properties. Understanding the mechanism of the initiation phase of biofouling is a key point in eliminating the biofouling on membrane surfaces. The adhesion and attachment of different fouling materials is affected by the surface properties of the membrane materials. Therefore, surface properties of different polymeric materials had been studied in terms of their surface energies and Hansen solubility parameters (HSP). The difference between the combined HSP parameters (HSP distance) allows prediction of the affinity of two materials to each other. The possibilities of measuring the HSP of different polymer films via surface measurements, such as contact angle has been thoroughly investigated. Knowing the HSP of a membrane material and the HSP of a specific foulant, facilitate the estimation of the HSP distance between the two, and therefore the strength of attachment to the surface. Contact angle measurements using fourteen different solvents on five different polymeric films were carried out using the sessile drop method. Solvents were ranked as good or bad solvents using different ranking method and ranking was used to calculate the HSP of each polymeric film. Results clearly indicate the absence of a direct relation between contact angle values of each film and the HSP distance between each polymer film and the solvents used. Therefore, estimating HSP via contact angle alone is not sufficient. However, it was found if the surface tensions and viscosities of the used solvents are taken in to the account in the analysis of the contact angle values, a prediction of the HSP from contact angle measurements is possible. This was carried out via training of a neural network model. The trained neural network model has three inputs, contact angle value, surface tension and viscosity of solvent used. The model is able to predict the HSP distance between the used solvent and the tested polymer (material). The HSP distance prediction is further used to estimate the total and individual HSP parameters of each tested material. The results showed an accuracy of about 90% for all the five studied films

Keywords: surface characterization, hansen solubility parameter estimation, contact angle measurements, artificial neural network model, surface measurements

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Authors: Qiming Wang

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Dynamic polymer networks (DPNs) crosslinked by dynamic bonds have received intensive attention because of their special crack-healing capability. Diverse DPNs have been synthesized using a number of dynamic bonds, including dynamic covalent bond, hydrogen bond, ionic bond, metal-ligand coordination, hydrophobic interaction, and others. Despite the promising success in the polymer synthesis, the fundamental understanding of their self-healing mechanics is still at the very beginning. Especially, a general analytical model to understand the interfacial self-healing behaviors of DPNs has not been established. Here, we develop polymer-network based analytical theories that can mechanistically model the constitutive behaviors and interfacial self-healing behaviors of DPNs. We consider that the DPN is composed of interpenetrating networks crosslinked by dynamic bonds. bonds obey a force-dependent chemical kinetics. During the self-healing process, we consider the The network chains follow inhomogeneous chain-length distributions and the dynamic polymer chains diffuse across the interface to reform the dynamic bonds, being modeled by a diffusion-reaction theory. The theories can predict the stress-stretch behaviors of original and self-healed DPNs, as well as the healing strength in a function of healing time. We show that the theoretically predicted healing behaviors can consistently match the documented experimental results of DPNs with various dynamic bonds, including dynamic covalent bonds (diarylbibenzofuranone and olefin metathesis), hydrogen bonds, and ionic bonds. We expect our model to be a powerful tool for the self-healing community to invent, design, understand, and optimize self-healing DPNs with various dynamic bonds.

Keywords: self-healing polymers, dynamic covalent bonds, hydrogen bonds, ionic bonds

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Authors: Isra Elfatih Salih Edrees, Mehmet Serdar Ufuk Türeli

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In this paper, an energy-aware method is presented, integrating energy-efficient relay-augmented techniques for correlated data routing with the goal of optimizing bottleneck throughput in wireless sensor networks. The system tackles the dual challenge of throughput optimization while considering sensor network energy consumption. A unique routing metric has been developed to enable throughput maximization while minimizing energy consumption by utilizing data correlation patterns. The paper introduces a game theoretic framework to address the NP-complete optimization problem inherent in throughput-maximizing correlation-aware routing with energy limitations. By creating an algorithm that blends energy-aware route selection strategies with the best reaction dynamics, this framework provides a local solution. The suggested technique considerably raises the bottleneck throughput for each source in the network while reducing energy consumption by choosing the best routes that strike a compromise between throughput enhancement and energy efficiency. Extensive numerical analyses verify the efficiency of the method. The outcomes demonstrate the significant decrease in energy consumption attained by the energy-efficient relay-augmented bottleneck throughput maximization technique, in addition to confirming the anticipated throughput benefits.

Keywords: correlated data aggregation, energy efficiency, game theory, relay-augmented routing, throughput maximization, wireless sensor networks

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Authors: Umar D. M., Aminu A. M., Izaddeen K. Y.

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Deployments of mini macrocell base stations also referred to as femtocells, improve the quality of service of indoor and outdoor users. Nevertheless, mobility management remains a key issue with regards to their deployment. This paper is leaned towards this issue, with an in-depth focus on the most important aspect of mobility management -handover. In handover management, making a handover decision in the LTE two-tier macrocell femtocell network is a crucial research area. Decision algorithms in this research are classified and comparatively analyzed according to received signal strength, user equipment speed, cost function, and interference. However, it was observed that most of the discussed decision algorithms fail to consider cell selection with hybrid access policy in a single macrocell multiple femtocell scenario, another observation was a majority of these algorithms lack the incorporation of user equipment residence parameter. Not including this parameter boosts the number of unnecessary handover occurrence. To deal with these issues, a sophisticated handover decision algorithm is proposed. The proposed algorithm considers the user’s velocity, received signal strength, residence time, as well as the femtocell base station’s access policy. Simulation results have shown that the proposed algorithm reduces the number of unnecessary handovers when compared to conventional received signal strength-based handover decision algorithm.

Keywords: user-equipment, radio signal service, long term evolution, mobility management, handoff

Procedia PDF Downloads 120