Search results for: index structural equation model

Authors: Ruthanne Tobin

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As our data-driven, cloud-based, knowledge-centric lives become ever more global, mobile, and digital, educational systems everywhere are struggling to keep pace. Schools need to prepare students to become critical-thinking, tech-savvy, life-long learners who are engaged and adaptable enough to find their unique calling in a post-industrial world of work. Recognizing that no nation can afford poor achievement or high dropout rates without jeopardizing its social and economic future, the thirty-two nations of the OECD are launching initiatives to redesign schools, generally under the banner of Personalized Learning or 21st Century Learning. Their intention is to transform education by situating students as co-enquirers and co-contributors with their teachers of what, when, and how learning happens for each individual. In this focused review of the 2007-2017 literature on personalized learning, the author sought answers to two main questions: “What are the theoretical frameworks that guide personalized learning?” and “What is the conceptual understanding of the model?” Ultimately, the review reveals that, although the research area is overly theorized and under-substantiated, it does provide a significant body of knowledge about this potentially transformative educational restructuring. For example, it addresses the following questions: a) What components comprise a PL model? b) How are teachers facilitating agency (voice & choice) in their students? c) What kinds of systems, processes and procedures are being used to guide the innovation? d) How is learning organized, monitored and assessed? e) What role do inquiry based models play? f) How do teachers integrate the three types of knowledge: Content, pedagogical and technological? g) Which kinds of forces enable, and which impede, personalizing learning? h) What is the nature of the collaboration among teachers? i) How do teachers co-regulate differentiated tasks? One finding of the review shows that while technology can dramatically expand access to information, expectations of its impact on teaching and learning are often disappointing unless the technologies are paired with excellent pedagogies in order to address students’ needs, interests and aspirations. This literature review fills a significant gap in this emerging field of research, as it serves to increase conceptual clarity that has hampered both the theorizing and the classroom implementation of a personalized learning model.

Keywords: curriculum change, educational innovation, personalized learning, school reform

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Authors: Mennatallah M. Hussein, Olivier de Weck

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The advancement of space exploration demands a robust space launch services program capable of reliably propelling payloads into orbit. Despite rigorous testing and quality assurance, launch failures still occur, leading to significant financial losses and jeopardizing mission objectives. Traditional failure prediction methods often lack the sophistication to account for multi-mode failure scenarios, as well as the predictive capability in complex dynamic systems. Traditional approaches also rely on expert judgment, leading to variability in risk prioritization and mitigation strategies. Hence, there is a pressing need for robust approaches that enhance launch vehicle reliability from lift-off until it reaches its parking orbit through comprehensive simulation techniques. In this study, the developed model proposes a multi-mode launch vehicle simulation framework for predicting failure scenarios when incorporating new technologies, such as new propulsion systems or advanced staging separation mechanisms in the launch system. To this end, the model combined a 6-DOF system dynamics with comprehensive data analysis to simulate multiple failure modes impacting launch performance. The simulator utilizes high-fidelity physics-based simulations to capture the complex interactions between different subsystems and environmental conditions.

Keywords: launch vehicle, failure prediction, propulsion anomalies, rocket launch simulation, rocket dynamics

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Authors: Swanand Patil, Pankaj Agarwal

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In past few decades, seismic performance objectives have shifted from earthquake resistance to earthquake resilience of the structures, especially for the lifeline buildings. Features such as negligible post-earthquake damage and replaceable damaged components, makes energy dissipating systems a valid choice for a seismically resilient building. In this study, various energy dissipation devices are applied on an eight-storey moment resisting RC building model. The energy dissipating devices include both hysteresis-based and viscous type of devices. The seismic response of the building is obtained for different positioning and mechanical properties of the devices. The investigation is carried forward to the deficiently ductile RC frame also. The performance assessment is done on the basis of drift ratio, mode shapes and displacement response of the model structures. Nonlinear dynamic analysis shows largely improved displacement response. The damping devices improve displacement response more efficiently in the deficient ductile frames than that in the perfectly moment resisting frames. This finding is important considering the number of deficient buildings in India and the world. The placement and mechanical properties of the dampers prove to be a crucial part in modelling, analyzing and designing of the structures with supplemental energy dissipation.

Keywords: earthquake resilient structures, lifeline buildings, retrofitting of structures, supplemental energy dissipation

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Authors: Marinos Dimitropoulos, George Trakakis, Nikolaus Meyerbröker, Raphael Dalpke, Polina Angelova, Albert Schnieders, Christos Pavlou, Christos Kostaras, Costas Galiotis, Konstantinos Dassios

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Intended for purifying water, water separation technologies are widely employed in a variety of contemporary household and industrial applications. Ultrathin Carbon Nanomembranes (CNMs) offer a highly selective, fast-flow, energy-efficient water separation technology intended for demanding water treatment applications as a technological replacement for biological filtration membranes. The membranes are two-dimensional (2D) materials with sub-nm functional pores and a thickness of roughly 1 nm; they may be generated in large quantities on porous supporting substrates and have customizable properties. The purpose of this work was to investigate and analyze the mechanical characteristics of CNMs and their substrates in order to ensure the structural stability of the membrane during operation. Contrary to macro-materials, it is difficult to measure the mechanical properties of membranes that are only a few nanometers thick. The membranes were supported on atomically flat substrates as well as suspended over patterned substrates, and their inherent mechanical properties were tested with atomic force microscopy. Quantitative experiments under nanomechanical loading, nanoindentation, and nano fatigue demonstrated the membranes' potential for usage in water separation applications.

Keywords: carbon nanomembranes, mechanical properties, AFM

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Authors: Bilge Meral Koc, Elvan Yilmaz Akyuz, Tugce Ozlu

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This study aimed to discover the effects of coconut oil intake and diet therapy on anthropometric measurements, biochemical findings and irisin levels in overweight individuals. Materials and Methods: Overweight individuals (n=44, 19-30 years) without any chronic disease were included. In this randomized controlled crossover study, the participants were divided into two groups (Group 1: 23 people, Group 2: 21 people). In the first phase, Group 1 received diet therapy to lose 0.5-1 kg of weight per week and 20 mL of coconut oil/day, while Group 2 only received diet therapy. In the second phase, Group 1 received diet therapy while Group 2 received diet therapy and 20 mL of coconut oil/day. Anthropometric measurements were taken four times. Irisin was measured four times by enzyme-linked immunosorbent (ELISA) method and other biochemical findings were measured twice. Statistical analysis was made on SPSS 20. Results: The irisin level decreased significantly when the participants only took coconut oil (p≤0.05). There was a significant decrease in the participants' body weight, body mass index (BMI) level and body fat percentage (p≤0.01). Insulin, total cholesterol, low density lipoproteins (LDL) cholesterol, and triglyceride (TG) levels of all participants decreased significantly (p≤0.05). There was no significant difference in irisin level due to body weight loss (p≤0.05); coconut oil provided a significant decrease in irisin level (p≤0.05). Conclusion: Diet therapy and weight loss did not have an effect on irisin level, but coconut oil alone was found to reduce irisin level. Coconut oil had no impact on anthropometric and biochemical findings.

Keywords: coconut oil, diet therapy, irisin, overweight

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Authors: Alexander Vandesompele, Joni Dambre

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The diversity in dendritic arborization, as first illustrated by Santiago Ramon y Cajal, has always suggested a role for dendrites in the functionality of neurons. In the past decades, thanks to new recording techniques and optical stimulation methods, it has become clear that dendrites are not merely passive electrical components. They are observed to integrate inputs in a non-linear fashion and actively participate in computations. Regardless, in simulations of neural networks dendritic structure and functionality are often overlooked. Especially in a machine learning context, when designing artificial neural networks, point neuron models such as the leaky-integrate-and-fire (LIF) model are dominant. These models mimic the integration of inputs at the neuron soma, and ignore the existence of dendrites. In this work, the LIF point neuron model is extended with a simple form of dendritic computation. This gives the LIF neuron increased capacity to discriminate spatiotemporal input sequences, a dendritic functionality as observed in another study. Simulations of the spiking neurons are performed using the Bindsnet framework. In the common LIF model, incoming synapses are independent. Here, we introduce a dependency between incoming synapses such that the post-synaptic impact of a spike is not only determined by the weight of the synapse, but also by the activity of other synapses. This is a form of short term plasticity where synapses are potentiated or depressed by the preceding activity of neighbouring synapses. This is a straightforward way to prevent inputs from simply summing linearly at the soma. To implement this, each pair of synapses on a neuron is assigned a variable,representing the synaptic relation. This variable determines the magnitude ofthe short term plasticity. These variables can be chosen randomly or, more interestingly, can be learned using a form of Hebbian learning. We use Spike-Time-Dependent-Plasticity (STDP), commonly used to learn synaptic strength magnitudes. If all neurons in a layer receive the same input, they tend to learn the same through STDP. Adding inhibitory connections between the neurons creates a winner-take-all (WTA) network. This causes the different neurons to learn different input sequences. To illustrate the impact of the proposed dendritic mechanism, even without learning, we attach five input neurons to two output neurons. One output neuron isa regular LIF neuron, the other output neuron is a LIF neuron with dendritic relationships. Then, the five input neurons are allowed to fire in a particular order. The membrane potentials are reset and subsequently the five input neurons are fired in the reversed order. As the regular LIF neuron linearly integrates its inputs at the soma, the membrane potential response to both sequences is similar in magnitude. In the other output neuron, due to the dendritic mechanism, the membrane potential response is different for both sequences. Hence, the dendritic mechanism improves the neuron’s capacity for discriminating spa-tiotemporal sequences. Dendritic computations improve LIF neurons even if the relationships between synapses are established randomly. Ideally however, a learning rule is used to improve the dendritic relationships based on input data. It is possible to learn synaptic strength with STDP, to make a neuron more sensitive to its input. Similarly, it is possible to learn dendritic relationships with STDP, to make the neuron more sensitive to spatiotemporal input sequences. Feeding structured data to a WTA network with dendritic computation leads to a significantly higher number of discriminated input patterns. Without the dendritic computation, output neurons are less specific and may, for instance, be activated by a sequence in reverse order.

Keywords: dendritic computation, spiking neural networks, point neuron model

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Authors: Redouane Krini, Lutz Nuhn, Hicham El Mard Cheol Woo Ha, Yoondeok Han, Kwang-Sup Lee, Dong-Yol Yang, Jinsoo Joo, Rudolf Zentel

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To use Quantum Dots (QDs) in the two photon initiated polymerization technique (TPIP) for 3D patternings, QDs were modified on the surface with photosensitive end groups which are able to undergo a photopolymerization. We were able to fabricate fluorescent 3D lattice structures using photopatternable QDs by TPIP for photonic devices such as photonic crystals and metamaterials. The QDs in different diameter have different emission colors and through mixing of RGB QDs white light fluorescent from the polymeric structures has been created. Metamaterials are capable for unique interaction with the electrical and magnetic components of the electromagnetic radiation and for manipulating light it is crucial to have a negative refractive index. In combination with QDs via TPIP technique polymeric structures can be designed with properties which cannot be found in nature. This makes these artificial materials gaining a huge importance for real-life applications in photonic and optoelectronic. Understanding of interactions between nanoparticles and biological systems is of a huge interest in the biomedical research field. We developed a synthetic strategy of polymer functionalized nanoparticles for biomedical studies to obtain hybrid systems of QDs and copolymers with a strong binding network in an inner shell and which can be modified in the end through their poly(ethylene glycol) functionalized outer shell. These hybrid systems can be used as models for investigation of cell penetration and drug delivery by using measurements combination between CryoTEM and fluorescence studies.

Keywords: biomedical study models, lithography, photo induced polymerization, quantum dots

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Authors: Bernard Moeketsi Hlalele

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Drought is a complicated natural phenomenon that creates significant economic, social, and environmental problems. An analysis of paleoclimatic data indicates that severe and extended droughts are inevitable part of natural climatic circle. This study characterised drought in Lejweleputswa using both Standardised Precipitation Index (SPI) and neural networks (NN) to quantify and predict respectively. Monthly 37-year long time series precipitation data were obtained from online NASA database. Prior to the final analysis, this dataset was checked for outliers using SPSS. Outliers were removed and replaced by Expectation Maximum algorithm from SPSS. This was followed by both homogeneity and stationarity tests to ensure non-spurious results. A non-parametric Mann Kendall's test was used to detect monotonic trends present in the dataset. Two temporal scales SPI-3 and SPI-12 corresponding to agricultural and hydrological drought events showed statistically decreasing trends with p-value = 0.0006 and 4.9 x 10⁻⁷, respectively. The study area has been plagued with severe drought events on SPI-3, while on SPI-12, it showed approximately a 20-year circle. The concluded the analyses with a seasonal analysis that showed no significant trend patterns, and as such NN was used to predict possible SPI-3 for the last season of 2018/2019 and four seasons for 2020. The predicted drought intensities ranged from mild to extreme drought events to come. It is therefore recommended that farmers, agri-business owners, and other relevant stakeholders' resort to drought resistant crops as means of adaption.

Keywords: drought, risk, neural networks, agri-businesses, project, Lejweleputswa

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Authors: Amauri Josafat Gomez Aguilar, Jean Pierre Kenné

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This research presents the development of a self-sustainable manufacturing system from a circular economy perspective, structured by a multi-stage serial production system consisting of a series of machines under deterioration in charge of producing a single product and a reverse remanufacturing system constituted by the same productive systems of the first scheme and different tooling, fed by-products collected at the end of their life cycle, and non-conforming elements of the first productive scheme. Since the advanced production manufacturing system is unable to satisfy the customer's quality expectations completely, we propose the development of a mixed integer linear mathematical model focused on the optimal search and assignment of quality stations and preventive maintenance operation to the machines over a time horizon, intending to segregate the correct number of non-conforming parts for reuse in the remanufacturing system and thereby minimizing production, quality, maintenance, and customer non-conformance penalties. Numerical experiments are performed to analyze the solutions found by the model under different scenarios. The results showed that the correct implementation of a closed manufacturing system and allocation of quality inspection and preventive maintenance operations generate better levels of customer satisfaction and an efficient manufacturing system.

Keywords: closed loop, mixed integer linear programming, preventive maintenance, quality inspection

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Authors: Zhang Kehan, Du Luona

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Wireless power transfer (WPT) systems have been widely investigated for advantages of convenience and safety compared to traditional plug-in charging systems. The research contents include impedance matching, circuit topology, transfer distance et al. for improving the efficiency of WPT system, which is a decisive factor in the practical application. What is more, coil structures such as spiral circular coil and helical coil with variable distance between two turns also have indispensable effects on the efficiency of WPT systems. This paper compares the efficiency of WPT systems utilizing spiral or helical coil with variable distance between two turns, and experimental results show that efficiency of spiral circular coil with an optimum distance between two turns is the highest. According to efficiency formula of resonant WPT system with series-series topology, we introduce M²/R₋₁ to measure the efficiency of spiral circular coil and helical coil WPT system. If the distance between two turns s is too close, proximity effect theory shows that the induced current in the conductor, caused by a variable flux created by the current flows in the skin of vicinity conductor, is the opposite direction of source current and has assignable impart on coil resistance. Thus in two coil structures, s affects coil resistance. At the same time, when the distance between primary and secondary coils is not variable, s can also make the influence on M to some degrees. The aforementioned study proves that s plays an indispensable role in changing M²/R₋₁ and then can be adjusted to find the optimum value with which WPT system achieves the highest efficiency. In actual application situations of WPT systems especially in underwater vehicles, miniaturization is one vital issue in designing WPT system structures. Limited by system size, the largest external radius of spiral circular coil is 100 mm, and the largest height of helical coil is 40 mm. In other words, the turn of coil N changes with s. In spiral circular and helical structures, the distance between each two turns in secondary coil is set as a constant value 1 mm to guarantee that the R2 is not variable. Based on the analysis above, we set up spiral circular coil and helical coil model using COMSOL to analyze the value of M²/R₋₁ when the distance between each two turns in primary coil sp varies from 0 mm to 10 mm. In the two structure models, the distance between primary and secondary coils is 50 mm and wire diameter is chosen as 1.5 mm. The turn of coil in secondary coil are 27 in helical coil model and 20 in spiral circular coil model. The best value of s in helical coil structure and spiral circular coil structure are 1 mm and 2 mm respectively, in which the value of M²/R₋₁ is the largest. It is obviously to select spiral circular coil as the first choice to design the WPT system for that the value of M²/R₋₁ in spiral circular coil is larger than that in helical coil under the same condition.

Keywords: distance between two turns, helical coil, spiral circular coil, wireless power transfer

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Authors: Sahila Chopra, Hemdeep, Arshdeep Kaur, Raj K. Gupta

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In recent times, we noticed an interesting and important role of non-coplanar degree-of-freedom (Φ = 00) in heavy ion reactions. Using the dynamical cluster-decay model (DCM) with Φ degree-of-freedom included, we have studied three compound systems 246Bk∗, 164Yb∗ and 105Ag∗. Here, within the DCM with pocket formula for nuclear proximity potential, we look for the effects of including compact, non-coplanar configurations (Φc = 00) on the non-compound nucleus (nCN) contribution in total fusion cross section σfus. For 246Bk∗, formed in 11B+235U and 14N+232Th reaction channels, the DCM with coplanar nuclei (Φc = 00) shows an nCN contribution for 11B+235U channel, but none for 14N+232Th channel, which on including Φ gives both reaction channels as pure compound nucleus decays. In the case of 164Yb∗, formed in 64Ni+100Mo, the small nCN effects for Φ=00 are reduced to almost zero for Φ = 00. Interestingly, however, 105Ag∗ for Φ = 00 shows a small nCN contribution, which gets strongly enhanced for Φ = 00, such that the characteristic property of PCN presents a change of behaviour, like that of a strongly fissioning superheavy element to a weakly fissioning nucleus; note that 105Ag∗ is a weakly fissioning nucleus and Psurv behaves like one for a weakly fissioning nucleus for both Φ = 00 and Φ = 00. Apparently, Φ is presenting itself like a good degree-of-freedom in the DCM.

Keywords: dynamical cluster-decay model, fusion cross sections, non-compound nucleus effects, non-coplanarity

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Authors: Lacramioara Ochiuz, Aurelia Vasile, Iulian Stoleriu, Cristina Ghiciuc, Maria Ignat

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Topical administration of chemotherapeutic agents (eg. carmustine, bexarotene, mechlorethamine etc.) in local treatment of cutaneous T-cell lymphoma (CTCL) is accompanied by multiple side effects, such as contact hypersensitivity, pruritus, skin atrophy or even secondary malignancies. A known method of reducing the side effects of anticancer agent is the development of modified drug release systems using drug incapsulation in biocompatible nanoporous inorganic matrices, such as mesoporous MCM-41 silica. Mesoporous MCM-41 silica is characterized by large specific surface, high pore volume, uniform porosity, and stable dispersion in aqueous medium, excellent biocompatibility, in vivo biodegradability and capacity to be functionalized with different organic groups. Therefore, MCM-41 is an attractive candidate for a wide range of biomedical applications, such as controlled drug release, bone regeneration, protein immobilization, enzymes, etc. The main advantage of this material lies in its ability to host a large amount of the active substance in uniform pore system with adjustable size in a mesoscopic range. Silanol groups allow surface controlled functionalization leading to control of drug loading and release. This study shows (I) the amino-grafting optimization of mesoporous MCM-41 silica matrix by means of co-condensation during synthesis and post-synthesis using APTES (3-aminopropyltriethoxysilane); (ii) loading the therapeutic agent (carmustine) obtaining a modified drug release systems; (iii) determining the profile of in vitro carmustine release from these systems; (iv) assessment of carmustine release kinetics by fitting on four mathematical models. Obtained powders have been described in terms of structure, texture, morphology thermogravimetric analysis. The concentration of the therapeutic agent in the dissolution medium has been determined by HPLC method. In vitro dissolution tests have been done using cell Enhancer in a 12 hours interval. Analysis of carmustine release kinetics from mesoporous systems was made by fitting to zero-order model, first-order model Higuchi model and Korsmeyer-Peppas model, respectively. Results showed that both types of highly ordered mesoporous silica (amino grafted by co-condensation process or post-synthesis) are thermally stable in aqueous medium. In what regards the degree of loading and efficiency of loading with the therapeutic agent, there has been noticed an increase of around 10% in case of co-condensation method application. This result shows that direct co-condensation leads to even distribution of amino groups on the pore walls while in case of post-synthesis grafting many amino groups are concentrated near the pore opening and/or on external surface. In vitro dissolution tests showed an extended carmustine release (more than 86% m/m) both from systems based on silica functionalized directly by co-condensation and after synthesis. Assessment of carmustine release kinetics revealed a release through diffusion from all studied systems as a result of fitting to Higuchi model. The results of this study proved that amino-functionalized mesoporous silica may be used as a matrix for optimizing the anti-cancer topical therapy by loading carmustine and developing prolonged-release systems.

Keywords: carmustine, silica, controlled, release

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Authors: Colin Schmidt, Adrien Lecossier, Pascal Crubleau, Philippe Blanchard, Simon Richir

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Introduction:The widespread availability of artificial intelligence, exemplified by Generative Pre-trained Transformers (GPT) relying on large language models (LLM), has caused a seismic shift in the realm of knowledge. Everyone now has the capacity to swiftly learn how these models can either serve them well or not. Today, conversational AI like ChatGPT is grounded in neural transformer models, a significant advance in natural language processing facilitated by the emergence of renowned LLMs constructed using neural transformer architecture. Inventiveness of an LLM : OpenAI's GPT-3 stands as a premier LLM, capable of handling a broad spectrum of natural language processing tasks without requiring fine-tuning, reliably producing text that reads as if authored by humans. However, even with an understanding of how LLMs respond to questions asked, there may be lurking behind OpenAI’s seemingly endless responses an inventive model yet to be uncovered. There may be some unforeseen reasoning emerging from the interconnection of neural networks here. Just as a Soviet researcher in the 1940s questioned the existence of Common factors in inventions, enabling an Under standing of how and according to what principles humans create them, it is equally legitimate today to explore whether solutions provided by LLMs to complex problems also share common denominators. Theory of Inventive Problem Solving (TRIZ) : We will revisit some fundamentals of TRIZ and how Genrich ALTSHULLER was inspired by the idea that inventions and innovations are essential means to solve societal problems. It's crucial to note that traditional problem-solving methods often fall short in discovering innovative solutions. The design team is frequently hampered by psychological barriers stemming from confinement within a highly specialized knowledge domain that is difficult to question. We presume ChatGPT Utilizes TRIZ 40. Hence, the objective of this research is to decipher the inventive model of LLMs, particularly that of ChatGPT, through a comparative study. This will enhance the efficiency of sustainable innovation processes and shed light on how the construction of a solution to a complex problem was devised. Description of the Experimental Protocol : To confirm or reject our main hypothesis that is to determine whether ChatGPT uses TRIZ, we will follow a stringent protocol that we will detail, drawing on insights from a panel of two TRIZ experts. Conclusion and Future Directions : In this endeavor, we sought to comprehend how an LLM like GPT addresses complex challenges. Our goal was to analyze the inventive model of responses provided by an LLM, specifically ChatGPT, by comparing it to an existing standard model: TRIZ 40. Of course, problem solving is our main focus in our endeavours.

Keywords: artificial intelligence, Triz, ChatGPT, inventiveness, problem-solving

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Authors: Zohreh Rostami, Arezoo Khosravi, Mohammad Nikpoor Aghdam, Mahmood Salesi

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Background: Cardiovascular mortality in chronic kidney disease (CKD) and end stage renal disease (ESRD) patients have a strong relationship with baseline or progressive left ventricular hypertrophy (LVH) meanwhile in hemodialysis patients 10% decrement in left ventricular mass was associated with 28% reduction in cardiovascular mortality risk. In consonance with these arguments, we designed a study to measure morphological and functional echocardiographic variations early after transplantation. Method: The patients with normal renal function underwent two advanced echocardiographic studies to examine the structural and functional changes in left ventricular mass before and 3-month after transplantation. Results: From a total of 23 participants 21(91.3%) presented with left ventricular hypertrophy, 60.9% in eccentric and 30.4% in concentric group. Diastolic dysfunction improved in concentric group after transplantation. Both in pre and post transplantation global longitudinal strain (GLS)- average in eccentric group was more than concentric (-17.45 ± 2.75 vs -14.3 ± 3.38 p=0.03) and (-18.08 ± 2.6 vs -16.1 ± 2.7 p= 0.04) respectively. Conclusion: Improvement and recovery of left ventricular function in concentric group was better and sooner than eccentric after kidney transplantation. Although fractional shortening and diastolic function and GLS-4C in pre-transplantation in concentric group was worse than eccentric, but therapeutic response to kidney transplantation in concentric was more and earlier than eccentric group.

Keywords: chronic kidney disease, end stage renal disease, left ventricular hypertrophy, global longitudinal strain

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Authors: Olivia Anak Rayeg, Clotilda Binti Petrus, Arnel Reanturco Ascotia, Ang Chung Huap, Caroline Marajan, Rudy Tawie Joseph Sipi

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Concrete is essential for global infrastructure, yet enhancing its rheology and strength in an environmentally sustainable manner remains a significant challenge. Conventional chemical admixtures often pose environmental and health risks. This study explores the use of a phospholipid biosurfactant, derived from Rhizopus oryzae, as an environmentally friendly admixture in concrete. Various concentrations of the biosurfactant were integrated into fresh concrete, partially replacing the water content. The inclusion of the biosurfactant markedly enhanced the workability of the concrete, as demonstrated by Vertical Slump, Slump Flow, and T50 tests. After a 28-day curing period, the concrete's mechanical properties were assessed through compressive strength and bonding tests. Results revealed that substituting up to 10% of the water with the biosurfactant not only improved workability but also significantly increased both compressive and flexural strength. These findings highlight the potential of phospholipid biosurfactant as a biodegradable and non-toxic alternative to traditional admixtures, enhancing both structural integrity and sustainability in concrete. This approach reduces environmental impact and production costs, marking a significant advancement in sustainable construction technology.

Keywords: concrete rheology, green admixture, fungal biosurfactant, phospholipids, rhizopus oryzae

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Authors: Rudy Djamaluddin, Yasser Bachtiar, Rita Irmawati, Abd. Madjid Akkas, Rusdi Usman Latief

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The aesthetic qualities and the versatility of reinforced concrete have made it a popular choice for many architects and structural engineers. Therefore, the exploration of natural materials such as gravels and sands as well as lime-stone for cement production is increasing to produce a concrete material. The exploration must affect to the environment. Therefore, the using of the concrete materials should be as efficient as possible. According to its natural behavior of the concrete material, it is strong in compression and weak in tension. Therefore the contribution of the tensile stresses of the concrete to the flexural capacity of the beams is neglected. However, removing of concrete on tension zone affects to the decreasing of flexural capacity. Introduce the strut action of truss structures may an alternative to solve the decreasing of flexural capacity. A series of specimens were prepared to clarify the effect of the truss structures in the concrete beams without concrete on the tension zone. Results indicated that the truss system is necessary for the external reinforced concrete beams. The truss system of concrete beam without concrete on tension zone (BR) could develop almost same capacity to the normal beam (BN). It can be observed also that specimens BR has lower number of cracks than specimen BN. This may be caused by the fact that there was no bonding effect on the tensile reinforcement on specimen BR to distribute the cracks.

Keywords: external reinforcement, truss, concrete beams, flexural behavior

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Authors: Andrea Bellucci, Martina Tofi

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The aim of paper is to analyze business models of bancassurance in Italy for life business. The life insurance business is very developed in the Italian market and banks branches have 80% of the market share. Given its maturity, the life insurance market needs to consolidate its organizational form to allow for the development of non-life business, which nowadays collects few premiums but represents a great opportunity to enlarge the market share of bancassurance using its strength in the distribution channel while the market share of independent agents is decreasing. Starting with the main business model of bancassurance for life business, this paper will analyze the performances of life companies in the Italian market by balance sheet indicators and by main discriminant variables of business models. The study will observe trends from 2013 to 2015 for the Italian market by exploiting a database managed by Associazione Nazionale delle Imprese di Assicurazione (ANIA). The applied approach is based on a bottom-up analysis starting with variables and indicators to define business models’ classification. The statistical classification algorithm proposed by Ward is employed to design business models’ profiles. Results from the analysis will be a representation of the main business models built by their profile related to indicators. In that way, an unsupervised analysis is developed that has the limit of its judgmental dimension based on research opinion, but it is possible to obtain a design of effective business models.

Keywords: bancassurance, business model, non life bancassurance, insurance business value drivers

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Authors: Pooja Verma, Sumana Ghosh

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There is a growing need for alternative way of power generation worldwide. The reason can be attributed to limited resources of fossil fuels, environmental pollution, increasing cost of conventional fuels, and lower efficiency of conversion of energy in existing systems. In this context, one of the potential alternatives for power generation is wave energy. However, it is difficult to estimate the amount of electrical energy generation in an irregular sea condition by experiment and or analytical methods. Therefore in this work, a numerical wave tank is developed using the computational fluid dynamics software Open FOAM. In this software a specific utility known as waves2Foam utility is being used to carry out the simulation work. The computational domain is a tank of dimension: 5m*1.5m*1m with a floating object of dimension: 0.5m*0.2m*0.2m. Regular waves are generated at the inlet of the wave tank according to Stokes second order theory. The main objective of the present study is to validate the numerical model against existing experimental data. It shows a good matching with the existing experimental data of floater displacement. Later the model is exploited to estimate energy extraction due to the movement of such a point absorber in real sea conditions. Scale down the wave properties like wave height, wave length, etc. are used as input parameters. Seasonal variations are also considered.

Keywords: OpenFOAM, numerical wave tank, regular waves, floating object, point absorber

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Authors: Mahdad M’hamed, Belaidi Idir

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This paper develops a meshless approach, called Element Free Galerkin (EFG) method, which is based on the weak form Moving Least Squares (MLS) of the partial differential governing equations and employs the interpolation to construct the meshless shape functions. The variation weak form is used in the EFG where the trial and test functions are approximated bye the MLS approximation. Since the shape functions constructed by this discretization have the weight function property based on the randomly distributed points, the essential boundary conditions can be implemented easily. The local weak form of the partial differential governing equations is obtained by the weighted residual method within the simple local quadrature domain. The spline function with high continuity is used as the weight function. The presently developed EFG method is a truly meshless method, as it does not require the mesh, either for the construction of the shape functions, or for the integration of the local weak form. Several numerical examples of two-dimensional static structural analysis are presented to illustrate the performance of the present EFG method. They show that the EFG method is highly efficient for the implementation and highly accurate for the computation. The present method is used to analyze the static deflection of beams and plate hole

Keywords: numerical computation, element-free Galerkin (EFG), moving least squares (MLS), meshless methods

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Authors: Mustafa Mutahari, Nao Sugiki, Kojiro Matsuo

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The four decades of war, lack of job opportunities, poverty, lack of services, and natural disasters in different provinces of Afghanistan have contributed to a rapid increase in the population of Kabul, the capital city of Afghanistan. Population census has not been conducted since 1979, the first and last population census in Afghanistan. However, according to population estimations by Afghan authorities, the population of Kabul has been estimated at more than 4 million people, whereas the city was designed for two million people. Although the major transport mode of Kabul residents is public transport, responsible authorities within the country failed to supply the required means of transportation systems for the city. Besides, informal resettlement, lack of intersection control devices, presence of illegal vendors on streets, presence of illegal and unstandardized on-street parking and bus stops, driver`s unprofessional behavior, weak traffic law enforcement, and blocked roads and sidewalks have contributed to the extreme traffic congestion of Kabul. In 2018, the government of Afghanistan approved the Kabul city Urban Design Framework (KUDF), a vision towards the future of Kabul, which provides strategies and design guidance at different scales to direct urban development. Considering traffic congestion of the city and its budget limitations, the KUDF proposes a BRT route network with seven lines to reduce the traffic congestion, and it is said to facilitate more than 50% of Kabul population to benefit from this service. Based on the KUDF, it is planned to increase the BRT mode share from 0% to 17% and later to 30% in medium and long-term planning scenarios, respectively. Therefore, a detailed research study is needed to evaluate the proposed system before the implementation stage starts. The integrated land-use transport model is an effective tool to evaluate the Kabul BRT because of its future assessment capabilities that take into account the interaction between land use and transportation. This research aims to analyze and evaluate the proposed BRT route network with the application of an integrated land-use and transportation model. The research estimates the population distribution and travel behavior of Kabul within small boundary scales. The actual road network and land-use detailed data of the city are used to perform the analysis. The BRT corridors are evaluated not only considering its impacts on the spatial interactions in the city`s transportation system but also on the spatial developments. Therefore, the BRT are evaluated with the scenarios of improving the Kabul transportation system based on the distribution of land-use or spatial developments, planned development typology and population distribution of the city. The impacts of the new improved transport system on the BRT network are analyzed and the BRT network is evaluated accordingly. In addition, the research also focuses on the spatial accessibility of BRT stops, corridors, and BRT line beneficiaries, and each BRT stop and corridor are evaluated in terms of both access and geographic coverage, as well.

Keywords: accessibility, BRT, integrated land-use and transport model, travel behavior, spatial development

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Authors: Esther Pearl Palmer

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Driven by the increased pressure on Higher Education Institutions (HEIs) to produce work-ready graduates for the modern world of work, this study reflects on triad teaching and learning practices to increase student engagement and employability. In the South African higher education context, the employability of graduates is imperative in strengthening the country’s economy and in increasing competitiveness. Within this context, the field of Human Resource Management (HRM) calls for innovative methods and approaches to teaching and learning and assessing the skills and competencies of graduates to render them employable. Digital competency in Human Resource Information Systems (HRIS) is an important component and prerequisite for employment in HRM. The purpose of this research is to reflect on the subject HRIS developed by lecturers at the Central University of Technology, Free State (CUT), with the intention to actively engage students in real-world learning activities and increase their employability. The Enrichment Triad Model (ETM) was used as theoretical framework to develop the subject as it supports a triad teaching and learning approach to education. It is, furthermore, an inter-structured model that supports collaboration between industry, academics and students. The study follows a mixed-method approach to reflect on the learning experiences of the industry, academics and students in the subject field over the past three years. This paper is a work in progress and seeks to broaden the scope of extant studies about student engagement in work-related learning to increase employability. Based on the ETM as theoretical framework and pedagogical practice, this paper proposes that following a triad teaching and learning approach will increase work-related skills of students. Findings from the study show that students, academics and industry alike regard educational opportunities that incorporate active learning experiences with the world of work enhances student engagement in learning and renders them more employable.

Keywords: digital competence, enriched triad model, human resource information systems, student engagement, triad pedagogy.

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Authors: A. Benaiche

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In the current situation, the automobile has become the main means of locomotion. It allows traveling long distances, encouraging urban sprawl. To counteract this trend, the train is often proposed as an alternative to the car. Simultaneously, the favoring of urban development around public transport nodes such as railway stations is one of the main issues of the coordination between urban planning and transportation and the keystone of the sustainable urban development implementation. In this context, this paper focuses on the study of the spatial structuring dynamics around the railway. Specifically, it is a question of studying the demographic dynamics in rail corridors of Nantes, Angers and Le Mans (Western France) basing on the radiation of railway stations. Consequently, the methodology is concentrated on the knowledge of demographic weight and gains of these corridors, the index of urban intensity and the mobility behaviors (workers’ travels, scholars' travels, modal practices of travels). The perimeter considered to define the rail corridors includes the communes of urban area which have a railway station and communes with an access time to the railway station is less than fifteen minutes by car (time specified by the Regional Transport Scheme of Travelers). The main tools used are the statistical data from the census of population, the basis of detailed tables and databases on mobility flows. The study reveals that the population is not tightened along rail corridors and train use is minimal despite the presence of a nearby railway station. These results lead to propose guidelines to make the train, a real vector of mobility across the rail corridors.

Keywords: coordination between urban planning and transportation, rail corridors, railway stations, travels

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Authors: Vangelis Papadimitropoulos

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The paper is part of the research project “Techno-Social Innovation in the Collaborative Economy'', funded by the Hellenic Foundation of Research and Innovation for the years 2022-2024. The research project examines the normative and empirical conditions of grassroots technologically driven innovation, potentially enabling the transition towards a commons-oriented post-capitalist economy. The project carries out a conceptually led and empirically grounded multi-case study of the digital commons, open-source technologies, platform cooperatives, open cooperatives and Distributed Autonomous Organizations (DAOs) on the Blockchain. The methodological scope of research is interdisciplinary inasmuch as it comprises political theory, economics, sustainability science and computer science, among others. The research draws specifically on Michel Bauwens and Vasilis Kostakis' model of open cooperativism between the commons, ethical market entities and a partner state. Bauwens and Kostakis advocate for a commons-based counter-hegemonic post-capitalist transition beyond and against neoliberalism. The research further employs Laclau and Mouffe's discourse theory of hegemony to introduce a post-hegemonic conceptualization of the model of open cooperativism. Thus, the paper aims to outline the theoretical contribution of the research project to contemporary political theory debates on post-capitalism and the collaborative economy.

Keywords: open cooperativism, techno-social innovation, post-hegemony, post-capitalism

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Authors: Nuray Ucar, Pelin Altay, Ilkay Ozsev Yuksek

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Graphene oxide fibers have recently received increasing attention due to their excellent properties such as high specific surface area, high mechanical strength, good thermal properties and high electrical conductivity. They have shown notable potential in various applications including batteries, sensors, filtration and separation and wearable electronics. Carbon nanotubes (CNTs) have unique structural, mechanical, and electrical properties and can be used together with graphene oxide fibers for several application areas such as lithium ion batteries, wearable electronics, etc. Metals salts that can be converted into metal ions and metal oxide can be also used for several application areas such as battery, purification natural gas, filtration, absorption. This study investigates the effects of CNT and metal complex compounds (MnCl₂, metal salts) on the morphological structure of graphene oxide fibers. The graphene oxide dispersion was manufactured by modified Hummers method, and continuous graphene oxide fibers were produced with wet spinning. The CNT and MnCl₂ were incorporated into the coagulation baths during wet spinning process. Produced composite continuous fibers were analyzed with SEM, SEM-EDS and AFM microscopies and as spun fiber counts were measured.

Keywords: continuous graphene oxide fiber, Hummers' method, CNT, MnCl₂

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Authors: Mahsa Taghavi

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In the treatment of breast cancer, tamoxifen is a regularly prescribed medication. The effect of tamoxifen on breast cancer patients' EMT pathways was studied. In this study to see if it had any effect on the cancer cells' resistance to tamoxifen and to look for specific miRNAs associated with EMT. In this work, we used continuous and integrated bioinformatics analysis to choose the optimal GEO datasets. Once we had sorted the gene expression profile, we looked at the mechanism of signaling, the ontology of genes, and the protein interaction of each gene. In the end, we used the GEPIA database to confirm the candidate genes. after that, I investigated critical miRNAs related to candidate genes. There were two gene expression profiles that were categorized into two distinct groups. Using the expression profile of genes that were lowered in the EMT pathway, the first group was examined. The second group represented the polar opposite of the first. A total of 253 genes from the first group and 302 genes from the second group were found to be common. Several genes in the first category were linked to cell death, focal adhesion, and cellular aging. Two genes in the second group were linked to cell death, focal adhesion, and cellular aging. distinct cell cycle stages were observed. Finally, proteins such as MYLK, SOCS3, and STAT5B from the first group and BIRC5, PLK1, and RAPGAP1 from the second group were selected as potential candidates linked to tamoxifen's influence on the EMT pathway. hsa-miR-1204 and hsa-miR-639 have a very close relationship with the candidates genes according to the node degrees and betweenness index. With this, the action of tamoxifen on the EMT pathway was better understood. It's important to learn more about how tamoxifen's target genes and proteins work so that we can better understand the drug.

Keywords: tamoxifen, breast cancer, bioinformatics analysis, EMT, miRNAs

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Authors: B. O. Diyaolu, E. A. Okebanjo

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Children in today’s world need attention and care even with their physique as obesity is also at the increased. Several factors can be responsible for obesity in children and adequate attention is paramount in other not to accommodate it into adolescent period. This study investigated perceived determinants of obesity among primary school pupils in Eti Osa Local Government area of Lagos State. Descriptive survey research design was used and population was all obese pupils in Eti Osa Local Government Area of Lagos State. 92 pupils were selected from randomly picked 12 primary schools while purposive sampling technique was used to pick primary 4-6 pupils. With the aid of body mass index (BMI) and age percentile chart the obese pupils were selected. The instrument for the study was a self-developed and structured questionnaire on perceived determinant of obesity. The questionnaire was divided into three sections. The Cronbach’s Alpha reliability coefficient of 0.74 was obtained. The hypotheses were tested at 0.05 significant levels. The completed questionnaire was collated coded and analyzed using descriptive statistics of frequency counts and percentage and inferential statistics of chi-square (X²). Findings of this study revealed that physical activities and parental influences were determinant of obesity. Physical activity is essential in reducing the rate of obesity in Eti Osa Local Government Area both at home and within the school environment. Primary schools need to create more playing ground for pupils to exercise themselves. Parents need to cater for their children diet ensuring not just the quantity but the quality as well.

Keywords: feeding pattern, obese pupils, parental influence, physical activities

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Authors: M. Sanjarani, A. Danehkar, A. Mashincheyan, A. H. Javid, S. M. R. Fatemi

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The oil spill in marine water has direct impact on coastal resources and community. Environmental Sensitivity Index (ESI) map is the first step to assess the potential impact of an oil spill and minimize the damage of coastal resources. In order to create Environmental Sensitivity Maps for the Chabahar bay (Iran), information has been collected in three different layers (Shoreline Classification, Biological and Human- uses resources) by means of field observations and measurements of beach morphology, personal interviews with professionals of different areas and the collection of bibliographic information. In this paper an attempt made to prepare an ESI map for sensitivity to oil spills of Chabahar bay coast. The Chabahar bay is subjected to high threaten to oil spill because of port, dense mangrove forest,only coral spot in Oman Sea and many industrial activities. Mapping the coastal resources, shoreline and coastal structures was carried out using Satellite images and GIS technology. The coastal features classified into three major categories as: Shoreline Classification, Biological and Human uses resources. The important resources classified into mangrove, Exposed tidal flats, sandy beach, etc. The sensitivity of shore was ranked as low to high (1 = low sensitivity,10 = high sensitivity) based on geomorphology of Chabahar bay coast using NOAA standards (sensitivity to oil, ease of clean up, etc). Eight ESI types were found in the area namely; ESI 1A, 1C, 3A, 6B, 7, 8B,9A and 10D. Therefore, in the study area, 50% were defined as High sensitivity, less than 1% as Medium, and 49% as low sensitivity areas. The ESI maps are useful to the oil spill responders, coastal managers and contingency planners. The overall ESI mapping product can provide a valuable management tool not only for oil spill response but for better integrated coastal zone management.

Keywords: ESI, oil spill, GIS, Chabahar Bay, Iran

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Authors: A. Ribeiro, N. Pacheco, M. Soares, N. Valério, L. Nascimento, A. Silva, C. Vilarinho, J. Carvalho

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Hydrogen will play a key role in changing the current global energy paradigm, associated with the high use of fossil fuels and the release of greenhouse gases. This work intended to identify and quantify the potential of Solid Recovered Fuels (SFR) existing in Portugal and project the cost of hydrogen, produced through its steam gasification in different scenarios, associated with the size or capacity of the plant and the existence of carbon capture and storage (CCS) systems. Therefore, it was performed a techno-economic analysis simulation using an ASPEN base model, the H2A Hydrogen Production Model Version 3.2018. Regarding the production of SRF, it was possible to verify the annual production of more than 200 thousand tons of SRF in Portugal in 2019. The results of the techno-economic analysis simulations showed that in the scenarios containing a high (200,000 tons/year) and medium (40,000 tons/year) amount of SFR, the cost of hydrogen production was competitive concerning the current prices of hydrogen. The results indicate that scenarios 1 and 2, which use 200,000 tons of SRF per year, have lower hydrogen production values, 1.22 USD/kg H2 and 1.63 USD/kg H2, respectively. The cost of producing hydrogen without carbon capture and storage (CCS) systems in an average amount of SFR (40,000 tons/year) was 1.70 USD/kg H2. In turn, scenarios 5 (without CCS) and 6 (with CCS), which use only 683 tons of SFR from urban sources, have the highest costs, 6.54 USD/kg H2 and 908.97 USD/kg H2, respectively. Therefore, it was possible to conclude that there is a huge potential for the use of SRF for the production of hydrogen through steam gasification in Portugal.

Keywords: gasification, hydrogen, solid recovered fuels, techno-economic analysis, waste-to-energy

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Authors: Papon Thamvasupong, Kwanchanok Viravaidya-Pasuwat

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Osteoarthritis affects a lot of people worldwide. Local injection of glucosamine is one of the alternative treatment methods to replenish the natural lubrication of cartilage. However, multiple injections can potentially lead to possible bacterial infection. Therefore, a drug delivery system is desired to reduce the frequencies of injections. A hydrogel is one of the delivery systems that can control the release of drugs. Thermo-reversible hydrogels can be beneficial to the drug delivery system especially in the local injection route because this formulation can change from liquid to gel after getting into human body. Once the gel is in the body, it will slowly release the drug in a controlled manner. In this study, various formulations of Pluronic-based hydrogels were synthesized for the controlled release of glucosamine. One of the challenges of the Pluronic controlled release system is its fast dissolution rate. To overcome this problem, alginate and calcium sulfate (CaSO₄) were added to the polymer solution. The characteristics of the hydrogels were investigated including the gelation temperature, gelation time, hydrogel dissolution and glucosamine release mechanism. Finally, a mathematical model of glucosamine release from Pluronic-alginate-hyaluronic acid hydrogel was developed. Our results have shown that crosslinking Pluronic gel with alginate did not significantly extend the dissolution rate of the gel. Moreover, the gel dissolution profiles and the glucosamine release mechanisms were best described using the zeroth-order kinetic model, indicating that the release of glucosamine was primarily governed by the gel dissolution.

Keywords: controlled release, drug delivery system, glucosamine, pluronic, thermoreversible hydrogel

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Authors: Kyung Bae Park, Sung Ho Ha

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Online user-generated contents (UGC) significantly change the way customers behave (e.g., shop, travel), and a pressing need to handle the overwhelmingly plethora amount of various UGC is one of the paramount issues for management. However, a current approach (e.g., sentiment analysis) is often ineffective for leveraging textual information to detect the problems or issues that a certain management suffers from. In this paper, we employ text mining of Latent Dirichlet Allocation (LDA) on a popular online review site dedicated to complaint from users. We find that the employed LDA efficiently detects customer complaints, and a further inspection with the visualization technique is effective to categorize the problems or issues. As such, management can identify the issues at stake and prioritize them accordingly in a timely manner given the limited amount of resources. The findings provide managerial insights into how analytics on social media can help maintain and improve their reputation management. Our interdisciplinary approach also highlights several insights by applying machine learning techniques in marketing research domain. On a broader technical note, this paper illustrates the details of how to implement LDA in R program from a beginning (data collection in R) to an end (LDA analysis in R) since the instruction is still largely undocumented. In this regard, it will help lower the boundary for interdisciplinary researcher to conduct related research.

Keywords: latent dirichlet allocation, R program, text mining, topic model, user generated contents, visualization

Procedia PDF Downloads 177