Search results for: viscosity solutions

Authors: Gyorgy Deak, Marius C. Raischi, Lucian P. Georgescu, Tiberius M. Danalache, Elena Holban, Madalina G. Boboc, Monica Matei, Catalina Iticescu, Marius V. Olteanu, Stefan Zamfir, Gabriel Cornateanu

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At present, on the Lower Danube, different types of pressures have been identified that affect the anadromous sturgeons stocks with an impact that leads to their decline. This paper presents techniques and procedures used by Romanian experts in the tagging and monitoring of anadromous sturgeons, as well as unique results at international level obtained on the basis of an informational volume collected in over 7 years of monitoring on these species behavior (both for adults as well as for ultrasonically tagged juveniles) on the Lower Danube. The local impact of hydrotechnical constructions (bottom sill, maritime navigation channel), the global impact of the poaching phenomenon and the impact of the restocking programs with sturgeon juveniles were assessed. Thus, the bottom sill impact on the Bala branch, the Bastroe Channel (cross-border impact) and the poaching phenomenon at the level of the Lower Danube was analyzed on the basis of a unique informational volume obtained through the use of patented monitoring systems by the Romanian experts (DKTB respectively, DKMR-01T). At the same time, the results from the monitoring of ultrasonically tagged sturgeon juveniles from the 2015 repopulation program are presented. Conclusions resulting from research can ensure favorable premises for finding some conservation solutions for CITES-protected sturgeon species that have survived for millions of years, currently being 1 species on the brink of extinction - Russian sturgeon, 2 species in danger of extinction - Beluga sturgeon and Stellate sturgeon and 2 species already extinct from the Lower Danube, namely common sturgeon and ship sturgeon.

Keywords: Lower Danube, sturgeons monitoring (adults and juveniles), tagging, impact on conservation

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Authors: Hamza Ouachtouk, Amine Harbi, Said Azerblou, Youssef Naimi, El Mostafa Tace

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This study delves into the structural, vibrational, magnetic, and electronic properties of La₂MMnO₆ double perovskites, where M denotes Ni, Co, and Zn. Recognized for their versatile ionic configurations within the A and B sub-lattices, double perovskite oxides have attracted considerable interest due to their extensive array of physical properties, which include multiferroic behavior, colossal magnetoresistance, and ferroelectric/piezoelectric functionalities. These materials are pivotal for energy-related technologies like solid oxide fuel cells and water-splitting catalysis, attributed to their superior oxygen ion transport and storage capabilities. This research places particular emphasis on La₂NiMnO₆ and La₂CoMnO₆, known for their distinct magnetic, electric, and multiferroic properties, and extends the investigation to La₂ZnMnO₆, synthesized via high-temperature solid-state chemistry. This addition aims to ascertain the impact of zinc substitution on these properties. Structural analysis through X-ray diffraction has confirmed a monoclinic structure within the P2₁/n space group. Comprehensive vibrational studies utilizing infrared and Raman spectroscopy, alongside additional XRD assessments, provide a detailed examination of the dynamic and electronic behaviors of these compounds. The results underscore the significant role of chemical composition in modulating their functional properties. Comparatively, this study highlights that zinc substitution notably alters the electronic and magnetic responses, which could enhance the applicability of these materials in advanced energy technologies. This expanded analysis not only reinforces our understanding of La₂MMnO₆'s physical characteristics but also highlights its potential applications in the next generation of energy solutions.

Keywords: double perovskites, structural analysis, vibrational spectroscopy, magnetic properties, electronic properties, high-temperature solid-state chemistry, La₂MMnO₆, monoclinic structure, x-ray diffraction

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Authors: Ivana R. Moser, Joao C. Souza

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Building fires are random phenomena that can be extremely violent, and safe evacuation of people is the most guaranteed tactic in saving lives. The correct evacuation of buildings, and other spaces occupied by people, means leaving the place in a short time and by the appropriate way. It depends on the perception of spaces by the individual, the architectural layout and the presence of appropriate routing systems. As historical buildings were constructed in other times, when, as in general, the current security requirements were not available yet, it is necessary to adapt these spaces to make them safe. Computer models of evacuation simulation are widely used tools for assessing the safety of people in a building or agglomeration sites and these are associated with the analysis of human behaviour, makes the results of emergency evacuation more correct and conclusive. The objective of this research is the performance evaluation of historical interest buildings, regarding the safe evacuation of people, through computer simulation, using PTV Viswalk software. The buildings objects of study are the Colégio Catarinense, centennial building, located in the city of Florianópolis, Santa Catarina / Brazil. The software used uses the variables of human behaviour, such as: avoid collision with other pedestrians and avoid obstacles. Scenarios were run on the three-dimensional models and the contribution to safety in risk situations was verified as an alternative measure, especially in the impossibility of applying those measures foreseen by the current fire safety codes in Brazil. The simulations verified the evacuation time in situations of normality and emergency situations, as well as indicate the bottlenecks and critical points of the studied buildings, to seek solutions to prevent and correct these undesirable events. It is understood that adopting an advanced computational performance-based approach promotes greater knowledge of the building and how people behave in these specific environments, in emergency situations.

Keywords: computer simulation, escape routes, fire safety, historic buildings, human behavior

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Authors: Jean-Jacques Randrianarimanana, Nassim Sebaibi, Mohamed Boutouil

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In order to solve problems associated with stormwater runoff in urban areas and their effects on natural and artificial water bodies, the integration of new technical solutions to the rainwater drainage becomes even more essential. Permeable pavement systems are one of the most widely used techniques. This paper presents a laboratory analysis of stormwater runoff hydraulic and pollutant removal performance of permeable pavement system using pervious pavements based on seashell products. The laboratory prototype is a square column of 25 cm of side and consists of the surface in pervious concrete, a bedding of 3 cm in height, a geotextile and a subbase layer of 50 cm in height. A series of constant simulated rain events using semi-synthetic runoff which varied in intensity and duration were carried out. The initial vertical saturated hydraulic conductivity of the entire pervious pavement system was 0.25 cm/s (148 L/m²/min). The hydraulic functioning was influenced by both the inlet flow rate value and the test duration. The total water losses including evaporation ranged between 9% to 20% for all hydraulic experiments. The temporal and vertical variability of the pollutant removal efficiency (PRE) of the system were studied for total suspended solids (TSS). The results showed that the PRE along the vertical profile was influenced by the size of the suspended solids, and the pervious paver has the highest capacity to trap pollutant than the other porous layers of the permeable pavement system after the geotextile. The TSS removal efficiency was about 80% for the entire system. The first-flush effect of TSS was observed, but it appeared only at the beginning (2 to 6 min) of the experiments. It has been shown that the PPS can capture first-flush. The project in which this study is integrated aims to contribute to both the valorization of shellfish waste and the sustainable management of rainwater.

Keywords: hydraulic, pervious concrete, pollutant removal efficiency, seashell by-products, stormwater runoff

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Authors: Fuyuan Ma, Yuhan Wang, Junhe Zhang, Ying Wang

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Identifying the sources of information dissemination is a pivotal task in the study of collective behaviors in networks, enabling us to discern and intercept the critical pathways through which information propagates from its origins. This allows for the control of the information’s dissemination impact in its early stages. Numerous methods for source detection rely on pre-existing, underlying propagation models as prior knowledge. Current models that eschew prior knowledge attempt to harness label propagation algorithms to model the statistical characteristics of propagation states or employ Graph Neural Networks (GNNs) for deep reverse modeling of the diffusion process. These approaches are either deficient in modeling the propagation patterns of information or are constrained by the over-smoothing problem inherent in GNNs, which limits the stacking of sufficient model depth to excavate global propagation patterns. Consequently, we introduce the ODESI model. Initially, the model employs a label propagation algorithm to delineate the distribution density of infected states within a graph structure and extends the representation of infected states from integers to state vectors, which serve as the initial states of nodes. Subsequently, the model constructs a deep architecture based on GNNs-coupled Ordinary Differential Equations (ODEs) to model the global propagation patterns of continuous propagation processes. Addressing the challenges associated with solving ODEs on graphs, we approximate the analytical solutions to reduce computational costs. Finally, we conduct simulation experiments on two real-world social network datasets, and the results affirm the efficacy of our proposed ODESI model in source identification tasks.

Keywords: source identification, ordinary differential equations, label propagation, complex networks

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Authors: Marius Gavrilescu, Sabina-Adriana Floria, Florin Leon, Silvia Curteanu, Costel Anton

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Natural sciences provide a wide range of experimental data whose related problems require study and modeling beyond the capabilities of conventional methodologies. Such problems have solution spaces whose complexity and high dimensionality require correspondingly complex regression methods for proper characterization. In this context, we propose an optimization method which consists in a hybrid dual optimizer setup: a global optimizer based on a modified variant of the popular Imperialist Competitive Algorithm (ICA), and a local optimizer based on a gradient descent approach. The ICA is modified such that intermediate solution populations are more quickly and efficiently pruned of low-fitness individuals by appropriately altering the assimilation, revolution and competition phases, which, combined with an initialization strategy based on low-discrepancy sampling, allows for a more effective exploration of the corresponding solution space. Subsequently, gradient-based optimization is used locally to seek the optimal solution in the neighborhoods of the solutions found through the modified ICA. We use this combined approach to find the optimal configuration and weights of a fully-connected neural network, resulting in regression models used to characterize the process of obtained bricks using silicon-based materials. Installations in the raw ceramics industry, i.e., bricks, are characterized by significant energy consumption and large quantities of emissions. Thus, the purpose of our approach is to determine by simulation the working conditions, including the manufacturing mix recipe with the addition of different materials, to minimize the emissions represented by CO and CH4. Our approach determines regression models which perform significantly better than those found using the traditional ICA for the aforementioned problem, resulting in better convergence and a substantially lower error.

Keywords: optimization, biologically inspired algorithm, regression models, bricks, emissions

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Authors: Vojtech Stejskal, Hana Skalova, Petr Kvapil, George Hutchinson

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Algae growth has been an important issue in water management of water plants, ponds and lakes, swimming pools, aquaculture & fish farms, gardens or golf courses for last decades. There are solutions based on chemical or biological principles. Apart of these traditional principles for inhibition of algae growth and biofilm production there are also physical methods which are very competitive compared to the traditional ones. Ultrasonic technology is one of these alternatives. Ultrasonic emitter is able to eliminate the biofilm which behaves as a host and attachment point for algae and is original reason for the algae growth. The ultrasound waves prevent majority of the bacteria in planktonic form becoming strongly attached sessile bacteria that creates welcoming layer for the biofilm production. Biofilm creation is very fast – in the serene water it takes between 30 minutes to 4 hours, depending on temperature and other parameters. Ultrasound device is not killing bacteria. Ultrasound waves are passing through bacteria, which retract as if they were in very turbulent water even though the water is visually completely serene. In these conditions, bacteria does not excrete the polysaccharide glue they use to attach to the surface of the pool or pond, where ultrasonic technology is used. Ultrasonic waves decrease the production of biofilm on the surfaces in the selected area. In case there are already at the start of the application of ultrasonic technology in a pond or basin clean inner surfaces, the biofilm production is almost absolutely inhibited. This paper talks about two different pilot applications – one in Czech Republic and second in United States of America, where the used ultrasonic technology (AlgaeControl) is coming from. On both sites, there was used Mezzo Ultrasonic Algae Control System with very positive results not only on biofilm production, but also algae growth in the surrounding area. Technology has been successfully tested in two different environments. The poster describes the differences and their influence on the efficiency of ultrasonic technology application. Conclusions and lessons learned can be possibly applied also on other sites within Europe or even further.

Keywords: algae growth, biofilm production, ultrasonic solution, ultrasound

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Authors: D. Zhigulskaya, V. Anisimov, A. Pikunov, K. Babanova, S. Zuev, A. Latyshkova, K. Сhernozatonskiy, A. Revazov

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Electrophysiology of information processing in reading is certainly a popular research topic. Natural reading, however, has been relatively poorly studied, despite having broad potential applications for learning and education. In the current study, we explore the relationship between text categories and spontaneous electroencephalogram (EEG) while reading. Thirty healthy volunteers (mean age 26,68 ± 1,84) participated in this study. 15 Russian-language texts were used as stimuli. The first text was used for practice and was excluded from the final analysis. The remaining 14 were opposite pairs of texts in one of 7 categories, the most important of which were: interesting/boring, fiction/non-fiction, free reading/reading with an instruction, reading a text/reading a pseudo text (consisting of strings of letters that formed meaningless words). Participants had to read the texts sequentially on an Apple iPad Pro. EEG was recorded from 12 electrodes simultaneously with eye movement data via ARKit Technology by Apple. EEG spectral amplitude was analyzed in Fz for theta-band (4-8 Hz) and in C3, C4, P3, and P4 for alpha-band (8-14 Hz) using the Friedman test. We found that reading an interesting text was accompanied by an increase in theta spectral amplitude in Fz compared to reading a boring text (3,87 µV ± 0,12 and 3,67 µV ± 0,11, respectively). When instructions are given for reading, we see less alpha activity than during free reading of the same text (3,34 µV ± 0,20 and 3,73 µV ± 0,28, respectively, for C4 as the most representative channel). The non-fiction text elicited less activity in the alpha band (C4: 3,60 µV ± 0,25) than the fiction text (C4: 3,66 µV ± 0,26). A significant difference in alpha spectral amplitude was also observed between the regular text (C4: 3,64 µV ± 0,29) and the pseudo text (C4: 3,38 µV ± 0,22). These results suggest that some brain activity we see on EEG is sensitive to particular features of the text. We propose that changes in theta and alpha bands during reading may serve as electrophysiological tools for assessing the reader’s cognitive state as well as his or her attitude to the text and the perceived information. These physiological markers have prospective practical value for developing technological solutions and biofeedback systems for reading in particular and for education in general.

Keywords: EEG, natural reading, reader's cognitive state, theta-rhythm, alpha-rhythm

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Authors: Abd El-Aziz Khairy Abd El-Aal, Yuji Yagi, Heba Kamal

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In this study, an integrated multi-channel analysis of Surface Waves (MASW) technique is applied to explore the geotechnical parameters of subsurface layers at the Zafarana wind farm. Moreover, a seismic hazard procedure based on the extended deterministic technique is used to estimate the seismic hazard load for the investigated area. The study area includes many active fault systems along the Gulf of Suez that cause many moderate and large earthquakes. Overall, the seismic activity of the area has recently become better understood following the use of new waveform inversion methods and software to develop accurate focal mechanism solutions for recent recorded earthquakes around the studied area. These earthquakes resulted in major stress-drops in the Eastern desert and the Gulf of Suez area. These findings have helped to reshape the understanding of the seismotectonic environment of the Gulf of Suez area, which is a perplexing tectonic domain. Based on the collected new information and data, this study uses an extended deterministic approach to re-examine the seismic hazard for the Gulf of Suez region, particularly the wind turbine towers at Zafarana Wind Farm and its vicinity. Alternate seismic source and magnitude-frequency relationships were combined with various indigenous attenuation relationships, adapted within a logic tree formulation, to quantify and project the regional exposure on a set of hazard maps. We select two desired exceedance probabilities (10 and 20%) that any of the applied scenarios may exceed the largest median ground acceleration. The ground motion was calculated at 50th, 84th percentile levels.

Keywords: MASW, seismic hazard, wind turbine towers, Zafarana wind farm

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Authors: Stephanie Boue, Nicolas Sierro, Julia Hoeng, Manuel C. Peitsch

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Systems biology relies on large numbers of data points and sophisticated methods to extract biologically meaningful signal and mechanistic understanding. For example, analyses of transcriptomics and proteomics data enable to gain insights into the molecular differences in tissues exposed to diverse stimuli or test items. Whereas the interpretation of endpoints specifically measuring a mechanism is relatively straightforward, the interpretation of big data is more complex and would benefit from comparing results obtained with diverse analysis methods. The sbv IMPROVER project was created to implement solutions to verify systems biology data, methods, and conclusions. Computational challenges leveraging the wisdom of the crowd allow benchmarking methods for specific tasks, such as signature extraction and/or samples classification. Four challenges have already been successfully conducted and confirmed that the aggregation of predictions often leads to better results than individual predictions and that methods perform best in specific contexts. Whenever the scientific question of interest does not have a gold standard, but may greatly benefit from the scientific community to come together and discuss their approaches and results, datathons are set up. The inaugural sbv IMPROVER datathon was held in Singapore on 23-24 September 2016. It allowed bioinformaticians and data scientists to consolidate their ideas and work on the most promising methods as teams, after having initially reflected on the problem on their own. The outcome is a set of visualization and analysis methods that will be shared with the scientific community via the Garuda platform, an open connectivity platform that provides a framework to navigate through different applications, databases and services in biology and medicine. We will present the results we obtained when analyzing data with our network-based method, and introduce a datathon that will take place in Japan to encourage the analysis of the same datasets with other methods to allow for the consolidation of conclusions.

Keywords: big data interpretation, datathon, systems toxicology, verification

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Authors: El Harraj Abdeslam, Raissouni Naoufal

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The detection of moving objects from a video image sequences is very important for object tracking, activity recognition, and behavior understanding in video surveillance. The most used approach for moving objects detection / tracking is background subtraction algorithms. Many approaches have been suggested for background subtraction. But, these are illumination change sensitive and the solutions proposed to bypass this problem are time consuming. In this paper, we propose a robust yet computationally efficient background subtraction approach and, mainly, focus on the ability to detect moving objects on dynamic scenes, for possible applications in complex and restricted access areas monitoring, where moving and motionless persons must be reliably detected. It consists of three main phases, establishing illumination changes in variance, background/foreground modeling and morphological analysis for noise removing. We handle illumination changes using Contrast Limited Histogram Equalization (CLAHE), which limits the intensity of each pixel to user determined maximum. Thus, it mitigates the degradation due to scene illumination changes and improves the visibility of the video signal. Initially, the background and foreground images are extracted from the video sequence. Then, the background and foreground images are separately enhanced by applying CLAHE. In order to form multi-modal backgrounds we model each channel of a pixel as a mixture of K Gaussians (K=5) using Gaussian Mixture Model (GMM). Finally, we post process the resulting binary foreground mask using morphological erosion and dilation transformations to remove possible noise. For experimental test, we used a standard dataset to challenge the efficiency and accuracy of the proposed method on a diverse set of dynamic scenes.

Keywords: video surveillance, background subtraction, contrast limited histogram equalization, illumination invariance, object tracking, object detection, behavior understanding, dynamic scenes

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Authors: Georgios Pardalis, Krushna Mahapatra, Brijesh Mainali

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Compared to other sectors, the residential and service sector in Sweden is responsible for almost 40% of the national final energy use and faces great challenges towards achieving reduction of energy intensity. The one- and two-family (henceforth 'detached') houses, constituting 60% of the residential floor area and using 32 TWh for space heating and hot water purposes, offers significant opportunities for improved energy efficiency. More than 80% of those houses are more than 35 years of old and a large share of them need major renovations. However, the rate of energy renovations for such houses is significantly low. The renovation market is dominated by small and medium-sized local companies (SMEs), who mostly offer individual solutions. A one-stop-shop business framework, where a single actor collaborates with other actors and coordinates them to offer a full package for holistic renovations, may speed up the rate of renovation. Such models are emerging in some European countries. This paper aims to understand the willingness of the SMEs to adopt a one-stop-shop business framework. Interviews were conducted with 13 SMEs in Kronoberg county in Sweden, a geographic region known for its initiatives towards sustainability and energy efficiency. The examined firms seem reluctant to adopt one-stop-shop for nonce due to the perceived risks they see in such a business move and due to their characteristics, although they agree that such a move will advance their position in the market and their business volume. By using threat-rigidity and prospect theory, we illustrate how this type of companies can move from being reluctant to adopt one-stop-shop framework to its adoption. Additionally, with the use of behavioral theory, we gain deeper knowledge on those exact reasons preventing those firms from adopting the one-stop-shop framework.

Keywords: construction SMEs, innovation adoption, one-stop-shop, perceived risks

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Authors: Mahan Qwamizadeh, Kun Zhou, Zuoqi Zhang, Yong Wei Zhang

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Typical load-bearing biological materials like bone, mineralized tendon and shell, are biocomposites made from both organic (collagen) and inorganic (biomineral) materials. This amazing class of materials with intrinsic internally designed hierarchical structures show superior mechanical properties with regard to their weak components from which they are formed. Extensive investigations concentrating on static loading conditions have been done to study the biological materials failure. However, most of the damage and failure mechanisms in load-bearing biological materials will occur whenever their structures are exposed to dynamic loading conditions. The main question needed to be answered here is: What is the relation between the layout and architecture of the load-bearing biological materials and their dynamic behavior? In this work, a staggered model has been developed based on the structure of natural materials at nanoscale and Finite Element Analysis (FEA) has been used to study the dynamic behavior of the structure of load-bearing biological materials to answer why the staggered arrangement has been selected by nature to make the nanocomposite structure of most of the biological materials. The results showed that the staggered structures will efficiently attenuate the stress wave rather than the layered structure. Furthermore, such staggered architecture is effectively in charge of utilizing the capacity of the biostructure to resist both normal and shear loads. In this work, the geometrical parameters of the model like the thickness and aspect ratio of the mineral inclusions selected from the typical range of the experimentally observed feature sizes and layout dimensions of the biological materials such as bone and mineralized tendon. Furthermore, the numerical results validated with existing theoretical solutions. Findings of the present work emphasize on the significant effects of dynamic behavior on the natural evolution of load-bearing biological materials and can help scientists to design bioinspired materials in the laboratories.

Keywords: load-bearing biological materials, nanostructure, staggered structure, stress wave decay

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Authors: Biniam Bahiru Tufa, Hana Delil Tesfaye, Seife Demisse Legesse, Manaye Tamire

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The healthcare industry is witnessing a digital transformation, with artificial intelligence (AI) offering potential solutions for challenges in health supply chain management (HSCM). However, the adoption of AI in this field remains limited. This research aimed to assess the knowledge, attitude, and practice of AI among students and employees in the health supply chain sector in Ethiopia. Using an explanatory case study research design with a concurrent mixed approach, quantitative and qualitative data were collected simultaneously. The study included 153 participants comprising students and employed health supply chain professionals working in various sectors. The majority had a pharmacy background, and one-third of the participants were male. Most respondents were under 35 years old, and around 68.6% had less than 10 years of experience. The findings revealed that 94.1% of participants had prior knowledge of AI, but only 35.3% were aware of its application in the supply chain. Moreover, the majority indicated that their training curriculum did not cover AI in health supply chain management. Participants generally held positive attitudes toward the necessity of AI for improving efficiency, effectiveness, and cost savings in the supply chain. However, many expressed concerns about its impact on job security and satisfaction, considering it as a burden Graduate students demonstrated higher knowledge of AI compared to employed staff, while graduate students also exhibited a more positive attitude toward AI. The study indicated low previous utilization and potential future utilization of AI in the health supply chain, suggesting untapped opportunities for improvement. Overall, while supply chain experts and graduate students lacked sufficient understanding of AI and its significance, they expressed favorable views regarding its implementation in the sector. The study recommends that the Ethiopian government and international organizations consider introducing AI in the undergraduate pharmacy curriculum and promote its integration into the health supply chain field.

Keywords: knowledge, attitude, practice, supply chain, articifial intellegence

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Authors: Selim Kara, Ertan Arda, Fahrettin Dolastir, Önder Pekcan

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Biomaterials and thin film coatings play a fundamental role in medical, food and pharmaceutical industries. Carrageenan is a linear sulfated polysaccharide extracted from algae and seaweeds. To date, such biomaterials have been used in many smart drug delivery systems due to their biocompatibility and antimicrobial activity properties. Poly (N-isopropylacrylamide) (PNIPAm) gels and copolymers have also been used in medical applications. PNIPAm shows lower critical solution temperature (LCST) property at about 32-34 °C which is very close to the human body temperature. Below and above the LCST point, PNIPAm gels exhibit distinct phase transitions between swollen and collapsed states. A special class of gels are microgels which can react to environmental changes significantly faster than microgels due to their small sizes. Quartz crystal microbalance (QCM) measurement technique is one of the attractive techniques which has been used for monitoring the thin-film formation process. A sensitive QCM system was designed as to detect 0.1 Hz difference in resonance frequency and 10-7 change in energy dissipation values, which are the measures of the deposited mass and the film rigidity, respectively. PNIPAm microgels with the diameter around few hundred nanometers in water were produced via precipitation polymerization process. 5 MHz quartz crystals with functionalized gold surfaces were used for the deposition of the carrageenan molecules and microgels in the solutions which were slowly pumped through a flow cell. Interactions between charged carrageenan and microgel particles were monitored during the formation of the film layers, and the Sauerbrey masses of the deposited films were calculated. The critical phase transition temperatures around the LCST were detected during the heating and cooling cycles. It was shown that it is possible to monitor the interactions between PNIPAm microgels and biopolymer molecules, and it is also possible to specify the critical phase transition temperatures by using a QCM system.

Keywords: carrageenan, phase transitions, PNIPAm microgels, quartz crystal microbalance (QCM)

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Authors: Wenzheng Fu, Yue Fu, Zhijiang Dong, Yujian Fu

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The integration of artificial intelligence (AI) and machine learning (ML) into project management is transforming how engineering projects are executed, monitored, and controlled. This paper provides a comprehensive survey of AI and ML applications in project management, systematically categorizing their use in key areas such as project data analytics, monitoring, tracking, scheduling, and reporting. As project management becomes increasingly data-driven, AI and ML offer powerful tools for improving decision-making, optimizing resource allocation, and predicting risks, leading to enhanced project outcomes. The review highlights recent research that demonstrates the ability of AI and ML to automate routine tasks, provide predictive insights, and support dynamic decision-making, which in turn increases project efficiency and reduces the likelihood of costly delays. This paper also examines the emerging trends and future opportunities in AI-driven project management, such as the growing emphasis on transparency, ethical governance, and data privacy concerns. The research suggests that AI and ML will continue to shape the future of project management by driving further automation and offering intelligent solutions for real-time project control. Additionally, the review underscores the need for ongoing innovation and the development of governance frameworks to ensure responsible AI deployment in project management. The significance of this review lies in its comprehensive analysis of AI and ML’s current contributions to project management, providing valuable insights for both researchers and practitioners. By offering a structured overview of AI applications across various project phases, this paper serves as a guide for the adoption of intelligent systems, helping organizations achieve greater efficiency, adaptability, and resilience in an increasingly complex project management landscape.

Keywords: artificial intelligence, decision support systems, machine learning, project management, resource optimization, risk prediction

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Authors: Juan A. G. Carrio, Prasad Talluri, Sergio G. Echeverrigaray, Antonio H. Castro Neto

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Hydrogen as a fuel and environmentally pleasant energy carrier is part of this transition towards low-carbon systems. The extensive deployment of hydrogen production, purification and transport infrastructures still represents significant challenges. Independent of the production process, the hydrogen generally is mixed with light hydrocarbons and other undesirable gases that need to be removed to obtain H₂ with the required purity for end applications. In this context, membranes are one of the simplest, most attractive, sustainable, and performant technologies enabling hydrogen separation and purification. They demonstrate high separation efficiencies and low energy consumption levels in operation, which is a significant leap compared to current energy-intensive options technologies. The unique characteristics of 2D laminates have given rise to a diversity of research on their potential applications in separation systems. Specifically, it is already known in the scientific literature that graphene oxide-based membranes present the highest reported selectivity of H₂ over other gases. This work explores the potential of a new type of 2D materials-based membranes in separating H₂ from CO₂ and CH₄. We have developed nanostructured composites based on 2D materials that have been applied in the fabrication of membranes to maximise H₂ selectivity and permeability, for different gas mixtures, by adjusting the membranes' characteristics. Our proprietary technology does not depend on specific porous substrates, which allows its integration in diverse separation modules with different geometries and configurations, looking to address the technical performance required for industrial applications and economic viability. The tuning and precise control of the processing parameters allowed us to control the thicknesses of the membranes below 100 nanometres to provide high permeabilities. Our results for the selectivity of new nanostructured 2D materials-based membranes are in the range of the performance reported in the available literature around 2D materials (such as graphene oxide) applied to hydrogen purification, which validates their use as one of the most promising next-generation hydrogen separation and purification solutions.

Keywords: membranes, 2D materials, hydrogen purification, nanocomposites

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Authors: Fiona Gibson

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This study is on sustainable capacity building in tourism management of the touristic destination of forts and castles within the Accra Metropolis, of the Greater Accra Region of Ghana, notably, the Christianbough Castle, the James and Ussher Forts. These forts and castle mentioned above have a rich colonial historical past that emerged from the 17th century onwards on the Gulf Coast of Guinea of the West Africa Sub-Region. Unfortunately, apart from the Christianbough Castle, which used to be the seat of government until recently, the environment of James and Ussher Forts are in a deployable state of decay due to years of neglect. Jamestown and Usshertown fishing communities with historical colonial past of a rich touristic heritage sites are predominantly indigenous Gas who speak only the Ga language, one of the languages of the six local languages spoken in Ghana, as a medium for sustainable tourism management. The purpose of this study is to investigate the reasons for years of decay and neglect, using both qualitative and quantitative research approach for individual interviews, to develop a rich picture of life situational story of the people of James and Ussher Forts environs and finding solutions to their predicaments through internal generated funds for sustainability of tourism management within the communities. The study recommends nation-wide educational campaigns and programmes on culture of maintenance and management for sustainable tourism development and management at all historical heritage sites in the country, specifically with the aim of promoting tourism in Ghana, using the indigenous local languages. The study also recommends formal and informal education for the residents, especially the youth to help them learn skills, either through local training or the formal education and this call for collaboration between the government of Ghana and other local and international bodies.

Keywords: sustainable capacity building, tourism management, forts, castles

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Authors: Karim Monir Halim Salib

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The article discusses the use of modern technology to achieve environmental marketing goals in business and customer relations. The purpose of this article is to show the possibilities of the application of modern technology. In B2C relationships, marketing departments face challenges arising from the need to quickly segment customers and share information across multiple systems, which seriously hinders the achievement of marketing objectives. Therefore, the Article states that modern IT solutions are used in the marketing of business activities, taking into account environmental objectives. For this reason, its importance in the economic and social development of developing countries has increased. While traditional companies emphasize profit as the most important business principle, social enterprises have to address social issues at the expense of profit. This mindset gives social enterprises more than traditional businesses to meet the needs of those at the bottom of the pyramid. This also poses a great challenge for social business, as social business works for the public good on the one hand and financial stability on the other. Otherwise, the company cannot be evacuated. Cultures are involved in business communication and research. Using the example of language in international relations, the article poses the problem of cultural discourse in management and linguistic and cultural studies. After reviewing current research on language in international relations, this article presents communication methods in the international economy from a linguistic perspective and attempts to explain communication problems in business from the perspective of linguistic research. A step towards multidisciplinary research combining research in management and linguistics.

Keywords: international marketing, marketing mix, marketing research, small and medium-sized enterprises, strategic marketing, B2B digital marketing strategy, digital marketing, digital marketing maturity model, SWOT analysis consumer behavior, experience, experience marketing, marketing employee organizational performance, internal marketing, internal customer, direct marketing, mobile phones mobile marketing, Sms advertising.

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Authors: Iruka C. Anugwo, Winston M. Shakantu

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The objective of this study is to uncover the basic business-forces that necessitated the survival and sustainable performance of the medium scale contractors in the South African construction market. This study is essential as it set to contribute towards long-term strategic solutions for combating the incessant failure of start-ups construction organizations within South African. The study used a qualitative research methodology; as the most appropriate approach to elicit and understand, and uncover the phenomena that are basic business-forces for the active contractors in the market. The study also adopted a phenomenological study approach; and in-depth interviews were conducted with 20 medium scale contractors in Port Elizabeth, South Africa, between months of August to October 2015. This allowed for an in-depth understanding of the critical and basic business-forces that influenced their survival and performance beyond the first five years of business operation. Findings of the study showed that for potential contractors (startups), to survival in the competitive business environment such as construction industry, they must possess the basic business-forces. These forces are educational knowledge in construction and business management related disciplines, adequate industrial experiences, competencies and capabilities to delivery excellent services and products as well as embracing the spirit of entrepreneurship. Convincingly, it can be concluded that the strategic approach to minimize the endless failure of startups construction businesses; the potential construction contractors must endeavoring to access and acquire the basic educationally knowledge, training and qualification; need to acquire industrial experiences in collaboration with required competencies, capabilities and entrepreneurship acumen. Without these basic business-forces as been discovered in this study, the majority of the contractors gaining entrance in the market will find it difficult to develop and grow a competitive and sustainable construction organization in South Africa.

Keywords: basic business-forces, medium scale contractors, South Africa, sustainable organisations

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Authors: Gurli Olsen, Ida Bruheim Jensen

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Internationally, many young adults not in education, employment, or training (NEET) remain in temporary solutions such as labour market measures or other forms of welfare arrangements. These trends have been associated with ineffective labour market measures, an underfunded theoretical foundation for activation work, limited competence among social workers and labour market employees in using ordinary workplaces as job inclusion measures, and an overemphasis on young adults’ personal limitations such as health challenges and lack of motivation. Two competing models have been prominent in activation work: Place‐Then‐Train and Train‐Then‐Place. A traditional strategy for labour market measures has been to first motivate NEETs to sheltered work and training and then to the regular labour market (train then place). Measures such as Supported Employment (SE) and Individual Placement and Support (IPS) advocate for rapid entry into paid work at the regular labour market with close supervision and training from social workers, employees, and others (place then train). None of these models demonstrate unquestionable results. In this web of working life measures, young adults (NEETs) experience a lack of confidence in their own capabilities and coping strategies vis-á-vis labour market- and educational demands. Drawing on young adults’ own experiences, we argue that the Job Demands-Resources (JD-R) Theory can contribute to the theoretical and practical dimensions of activation work. This presentation will focus on what the JD-R theory entails and how it can be fruitful in activation work with NEETs (what and how). The overarching rationale of the JD-R theory is that an enduring balance between demands (e.g., deadlines, working hours) and resources (e.g., social support, enjoyable work tasks) is important for job performance for people in any job and potentially in other meaningful activities. Extensive research has demonstrated that a balance between demands and resources increases motivation and decreases stress. Nevertheless, we have not identified literature on the JD-R theory in activation work with young adults.

Keywords: activation work, job demands-resources theory, social work, theory development

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Authors: Dilek Dede

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This study aims at scrutinized the dilemma between education place and working place with professional socialization dimension over the beginning teachers in Turkey is to be found the solution for the dilemma in Turkey. The research question is that how can be explained the gap between education place and working place for beginning teachers in Turkey. That expected to contribute to literature with the solutions for shorting the gap between working area and education area of the teaching profession in Turkey case. The study is constructed in two section. Firstly, socialization of the teaching profession and teaching modules have been discussed through the profession, education, working place indicators. In the second section, Secondly, two educational specialists from Turkey has been interviewed about their observation on trainee teachers compelling to participate the class for candidate teachers after university grade. Then, the dilemma between education area and working area of the teaching profession has been detected by of semi-structured and in-depth interviews, the literature on the relationality of institutions and regulation is discussed. The following outcomes have been accessed in accordance with the data set and literature linkage axis: Firstly, teachers coming from the distinctive programmes as an educational background. Hence, teachers who pertain to distinctive cultures work in the same environment. That cause cultural conflicts and complication of socialization of profession. Secondly, the insufficient partnership between schools and universities besides, the education classes lead to a struggle of culture among these two institutions. Thirdly, the education classes are designed as bureaucratic form instead of coalescence between head teachers and trainee teachers around a common culture. That become deep the dilemma. In conclusion, on condition that applied-oriented education that advocates in-service learning is promoted and this programme is supported with well-structured the in-service training through the partnership of universities and schools, the gap between the working-area and education-area might be shortened.

Keywords: beginning teachers, construction of a common, social mobilization in the teaching profession, teacher training institution, the relationality of the regulations and institutions

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Authors: Daniel F. Sava, Anton Ficai, Bogdan S. Vasile, Georgeta Voicu, Ecaterina Andronescu

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The energy crisis and environmental contamination are very serious problems, therefore searching for better and sustainable renewable energy is a must. It is predicted that the global energy demand will double until 2050. Solar water splitting and photocatalysis are considered as one of the solutions to these issues. The use of oxide semiconductors for solar water splitting and photocatalysis started in 1972 with the experiments of Fujishima and Honda on TiO2 electrodes. Since then, the evolution of nanoscience and characterization methods leads to a better control of size, shape and properties of materials. Although the past decade advancements are astonishing, for these applications the properties have to be controlled at a much finer level, allowing the control of charge-carrier lives, energy level positions, charge trapping centers, etc. Graphene has attracted a lot of attention, since its discovery in 2004, due to the excellent electrical, optical, mechanical and thermal properties that it possesses. These properties make it an ideal support for photocatalysts, thus graphene composites with oxide semiconductors are of great interest. We present in this work the synthesis and characterization of graphene-related materials and oxide semiconductors and their different composites. These materials can be used in constructing devices for different applications (batteries, water splitting devices, solar cells, etc), thus showing their application flexibility. The synthesized materials are different morphologies and sizes of TiO2, ZnO and Fe2O3 that are obtained through hydrothermal, sol-gel methods and graphene oxide which is synthesized through a modified Hummer method and reduced with different agents. Graphene oxide and the reduced form could also be used as a single material for transparent conductive films. The obtained single materials and composites were characterized through several methods: XRD, SEM, TEM, IR spectroscopy, RAMAN, XPS and BET adsorption/desorption isotherms. From the results, we see the variation of the properties with the variation of synthesis parameters, size and morphology of the particles.

Keywords: composites, graphene, hydrothermal, renewable energy

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Authors: Xiaoqin Wang, Li Yin

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Background and purpose: In many practices, one estimates causal effects arising from a complex stochastic process, where a sequence of treatments are assigned to influence a certain outcome of interest, and there exist time-dependent covariates between treatments. When covariates are plentiful and/or continuous, statistical modeling is needed to reduce the huge dimensionality of the problem and allow for the estimation of causal effects. Recently, Wang and Yin (Annals of statistics, 2020) derived a new general formula, which expresses these causal effects in terms of the point effects of treatments in single-point causal inference. As a result, it is possible to conduct the modeling via point effects. The purpose of the work is to study the modeling of these causal effects via point effects. Challenges and solutions: The time-dependent covariates often have influences from earlier treatments as well as on subsequent treatments. Consequently, the standard parameters – i.e., the mean of the outcome given all treatments and covariates-- are essentially all different (null paradox). Furthermore, the dimension of the parameters is huge (curse of dimensionality). Therefore, it can be difficult to conduct the modeling in terms of standard parameters. Instead of standard parameters, we have use point effects of treatments to develop likelihood-based parametric approach to the modeling of these causal effects and are able to model the causal effects of a sequence of treatments by modeling a small number of point effects of individual treatment Achievements: We are able to conduct the modeling of the causal effects from a sequence of treatments in the familiar framework of single-point causal inference. The simulation shows that our method achieves not only an unbiased estimate for the causal effect but also the nominal level of type I error and a low level of type II error for the hypothesis testing. We have applied this method to a longitudinal study of COVID-19 mortality among Scandinavian countries and found that the Swedish approach performed far worse than the other countries' approach for COVID-19 mortality and the poor performance was largely due to its early measure during the initial period of the pandemic.

Keywords: causal effect, point effect, statistical modelling, sequential causal inference

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Authors: Amna Ali Al-Saadi, Riken Homma, Kazuhisa Iki

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Despite the fact that many places have successes in achieving some aspects of sustainable urban development, there are no scientific facts to convince decision makers. Also, each of them was developed to fulfill the need of specific city only. Therefore, objective method to generate the solutions from a successful case is the aim of this research. The questions were: how to learn the lesson from each case study; how to distinguish the potential criteria and negative one; snd how to quantify their effects in the future development. Walkability has been selected as a goal. This is because it has been found as a solution to achieve healthy life style as well as social, environmental and economic sustainability. Moreover, it has complication as every aspect of sustainable development. This research is stand on quantitative- comparative methodology in order to assess pedestrian oriented development. Three analyzed area (AAs) were selected. One site is located in Oman in which hypotheses as motorized oriented development, while two sites are in Japan where the development is pedestrian friendly. The study used Multi- criteria evaluation method (MCEM). Initially, MCEM stands on analytic hierarchy process (AHP). The later was structured into main goal (walkability), objectives (functions and layout) and attributes (the urban form criteria). Secondly, the GIS were used to evaluate the attributes in multi-criteria maps. Since each criterion has different scale of measurement, all results were standardized by z-score and used to measure the co-relations among criteria. As results, different scenario was generated from each AA. MCEM (AHP-OWA)-GIS measured the walkability score and determined the priority of criteria development in the non-walker friendly environment. The comparison criteria for z-score presented a measurable distinguished orientation of development. This result has been used to prove that Oman is motorized environment while Japan is walkable. Also, it defined the powerful criteria and week criteria regardless to the AA. This result has been used to generalize the priority for walkable development. In conclusion, the method was found successful in generate scientific base for policy decisions.

Keywords: walkability, policy decisions, sustainable development, GIS

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Authors: Maria Karidakis, Barbara Kelly

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The challenges precipitated by the advent of COVID-19 have brought to the fore the task governments and key stakeholders are faced with; ensuring public health communication is readily accessible to vulnerable populations. COVID-19 has presented challenges for the provision and reception of timely, accessible, and accurate health information pertaining to vaccine health messaging to Aboriginal and Torres Strait Islander peoples. The aim of this qualitative study was to explore strategies used by Aboriginal-led organisations to improve communication about COVID-19 and vaccination for their communities and to explore how these mediation and outreach strategies were received by community members. We interviewed 6 Aboriginal-led organisations and 15 community members from several states across Australian, and these interviews were analysed thematically. The findings suggest that effective public health communication is enhanced when aFirst nations-led response defines the governance that happens in First Nations communities. Pro-active and self-determining Aboriginal leadership and decision-making helps drive the response to counter a growing trend towards vaccine hesitancy. Other strategies include establishing partnerships with government departments and relevant non-governmental organisations to ensure services are implemented and culturally appropriate. The outcomes of this research will afford policymakers, stakeholders in healthcare, and cultural mediators the capacity to identify strengths and potential problems associated with pandemic health information and to subsequently implement creative and culturally specific solutions that go beyond the provision of written documentation via translation or interpreting. It will also enable governing bodies to adjust multilingual polices and to adopt mediation strategies that will improve information delivery and intercultural services on a national and international level.

Keywords: intercultural communication, qualitative, public health communication, COVID-19, pandemic, mediated communication, first nations people

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Authors: Susana Aragoneses Garrido

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Every day, the roads are scenery of numerous accidents involving vehicles, producing thousands of deaths and serious injuries all over the world. Investigations have revealed that Human Factors (HF) are one of the main causes of road accidents in modern societies. Distracted driving (including external or internal aspects of the vehicle), which is considered as a human factor, is a serious and emergent risk to road safety. Consequently, a further analysis regarding this issue is essential due to its transcendence on today’s society. The objectives of this investigation are the detection and assessment of the HF in order to provide solutions (including a better vehicle design), which might mitigate road accidents. The methodology of the project is divided in different phases. First, a statistical analysis of public databases is provided between Spain and The UK. Second, data is classified in order to analyse the major causes involved in road accidents. Third, a simulation between different paths and vehicles is presented. The causes related to the HF are assessed by Failure Mode and Effects Analysis (FMEA). Fourth, different car models are evaluated using the Rapid Upper Body Assessment (RULA). Additionally, the JACK SIEMENS PLM tool is used with the intention of evaluating the Human Factor causes and providing the redesign of the vehicles. Finally, improvements in the car design are proposed with the intention of reducing the implication of HF in traffic accidents. The results from the statistical analysis, the simulations and the evaluations confirm that accidents are an important issue in today’s society, especially the accidents caused by HF resembling distractions. The results explore the reduction of external and internal HF through the global analysis risk of vehicle accidents. Moreover, the evaluation of the different car models using RULA method and the JACK SIEMENS PLM prove the importance of having a good regulation of the driver’s seat in order to avoid harmful postures and therefore distractions. For this reason, a car redesign is proposed for the driver to acquire the optimum position and consequently reducing the human factors in road accidents.

Keywords: analysis vehicles, asssesment, ergonomics, car redesign

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Authors: Aniela Pop, Ianina Birsan, Corina Orha, Rodica Pode, Florica Manea

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Carbon nanofiber-epoxy composite electrode has been investigated through voltammetric and amperometric techniques in order to detect parabens from aqueous solutions. The occurrence into environment as emerging pollutants of these preservative compounds has been extensively studied in the last decades, and consequently, a rapid and reliable method for their quantitative quantification is required. In this study, methylparaben (MP) and propylparaben (PP) were chosen as representatives for paraben class. The individual electrochemical detection of each paraben has been successfully performed. Their electrochemical oxidation occurred at the same potential value. Their simultaneous quantification should be assessed electrochemically only as general index of paraben class as a cumulative signal corresponding to both MP and PP from solution. The influence of pH on the electrochemical signal was studied. pH ranged between 1.3 and 9.0 allowed shifting the detection potential value to smaller value, which is very desired for the electroanalysis. Also, the signal is better-defined and higher sensitivity is achieved. Differential-pulsed voltammetry and square-wave voltammetry were exploited under the optimum pH conditions to improve the electroanalytical performance for the paraben detection. Also, the operation conditions were selected, i.e., the step potential, modulation amplitude and the frequency. Chronomaprometry application as the easiest electrochemical detection method led to worse sensitivity, probably due to a possible fouling effect of the electrode surface. The best electroanalytical performance was achieved by pulsed voltammetric technique but the selection of the electrochemical technique is related to the concrete practical application. A good reproducibility of the voltammetric-based method using carbon nanofiber-epoxy composite electrode was determined and no interference effect was found for the cation and anion species that are common in the water matrix. Besides these characteristics, the long life-time of the electrode give to carbon nanofiber-epoxy composite electrode a great potential for practical applications.

Keywords: carbon nanofiber-epoxy composite electrode, electroanalysis, methylparaben, propylparaben

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Authors: Stefanache Stefania, Ioana R. Podina

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Background: Embodied Conversational Agents (ECAs) are revolutionizing education and healthcare by offering cost-effective, adaptable, and portable solutions. Research on the Uncanny Valley effect (UVE) involves various embodied agents, including ECAs. Achieving the optimal level of anthropomorphism, no consensus on how to overcome the uncanniness problem. Objectives: This systematic review aims to identify the user characteristics, agent features, and context factors that influence the UVE. Additionally, this review provides recommendations for creating effective ECAs and conducting proper experimental studies. Methods: We conducted a systematic review following the PRISMA 2020 guidelines. We included quantitative, peer-reviewed studies that examined human-ECA interaction. We identified 17,122 relevant records from ACM Digital Library, IEE Explore, Scopus, ProQuest, and Web of Science. The quality of the predictors, mediators, and moderators adheres to the guidelines set by prior systematic reviews. Results: Based on the included studies, it can be concluded that females and younger people perceive the ECA as more attractive. However, inconsistent findings exist in the literature. ECAs characterized by extraversion, emotional stability, and agreeableness are considered more attractive. Facial expressions also play a role in the UVE, with some studies indicating that ECAs with more facial expressions are considered more attractive, although this effect is not consistent across all studies. Few studies have explored contextual factors, but they are nonetheless crucial. The interaction scenario and exposure time are important circumstances in human-ECA interaction. Conclusions: The findings highlight a growing interest in ECAs, which have seen significant developments in recent years. Given this evolving landscape, investigating the risk of the UVE can be a promising line of research.

Keywords: human-computer interaction, uncanny valley effect, embodied conversational agent, systematic review

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Authors: Huan Ting Liao

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In a typical manufacturing environment, computer numerical control (CNC) machining is essential for automating production through precise computer-controlled tool operations, significantly enhancing efficiency and ensuring consistent product quality. However, traditional CNC production lines often rely on manual loading and unloading, limiting operational efficiency and scalability. Although automated loading systems have been developed, they frequently lack sufficient intelligence and configuration efficiency, requiring extensive setup adjustments for different products and impacting overall productivity. This research addresses the job shop scheduling problem (JSSP) in CNC machining environments, aiming to minimize total completion time (makespan) and maximize CNC machine utilization. We propose a novel approach using reinforcement learning (RL), specifically the Q-learning algorithm, to optimize scheduling decisions. The study simulates the JSSP, incorporating robotic arm operations, machine processing times, and work order demand allocation to determine optimal processing sequences. The Q-learning algorithm enhances machine utilization by dynamically balancing workloads across CNC machines, adapting to varying job demands and machine states. This approach offers robust solutions for complex manufacturing environments by automating decision-making processes for job assignments. Additionally, we evaluate various layout configurations to identify the most efficient setup. By integrating RL-based scheduling optimization with layout analysis, this research aims to provide a comprehensive solution for improving manufacturing efficiency and productivity in CNC-based job shops. The proposed method's adaptability and automation potential promise significant advancements in tackling dynamic manufacturing challenges.

Keywords: job shop scheduling problem, reinforcement learning, operations sequence, layout optimization, q-learning

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