Search results for: energy models

Authors: Martin Georgiev, Milena Nanova, Damyan Damov

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Architects, engineers, and developers need to analyse and implement a wide spectrum of data in different formats, if they want to produce viable residential developments. Usually, this data comes from a number of different sources and is not well structured. The main objective of this research project is to provide parametric tools working with real geodesic data that can generate residential solutions. Various codes, regulations and design constraints are described by variables and prioritized. In this way, we establish a common workflow for architects, geodesists, and other professionals involved in the building and investment process. This collaborative medium ensures that the generated design variants conform to various requirements, contributing to a more streamlined and informed decision-making process. The quantification of distinctive characteristics inherent to typical residential structures allows a systematic evaluation of the generated variants, focusing on factors crucial to designers, such as daylight simulation, circulation analysis, space utilization, view orientation, etc. Integrating real geodesic data offers a holistic view of the built environment, enhancing the accuracy and relevance of the design solutions. The use of generative algorithms and parametric models offers high productivity and flexibility of the design variants. It can be implemented in more conventional CAD and BIM workflow. Experts from different specialties can join their efforts, sharing a common digital workspace. In conclusion, our research demonstrates that a generative parametric approach based on real geodesic data and collaborative decision-making could be introduced in the early phases of the design process. This gives the designers powerful tools to explore diverse design possibilities, significantly improving the qualities of the building investment during its entire lifecycle.

Keywords: architectural design, residential buildings, urban development, geodesic data, generative design, parametric models, workflow optimization

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Authors: Ruth Diego, Luis M. Romeo, Antonio Morán

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In the present work, a study of the coupling of a Bioelectrochemical System together with an oxy-combustion boiler is carried out; specifically, it proposes to connect the combustion gas outlet of a boiler with a microbial electrolysis cell (MEC) where the CO2 from the gases are transformed into methane in the cathode chamber, and the oxygen produced in the anode chamber is recirculated to the oxy-combustion boiler. The MEC mainly consists of two electrodes (anode and cathode) immersed in an aqueous electrolyte; these electrodes are separated by a proton exchange membrane (PEM). In this case, the anode is abiotic (where oxygen is produced), and it is at the cathode that an electroactive biofilm is formed with microorganisms that catalyze the CO2 reduction reactions. Real data from an oxy-combustion process in a boiler of around 20 thermal MW have been used for this study and are combined with data obtained on a smaller scale (laboratory-pilot scale) to determine the yields that could be obtained considering the system as environmentally sustainable energy storage. In this way, an attempt is made to integrate a relatively conventional energy production system (oxy-combustion) with a biological system (microbial electrolysis cell), which is a challenge to be addressed in this type of new hybrid scheme. In this way, a novel concept is presented with the basic dimensioning of the necessary equipment and the efficiency of the global process. In this work, it has been calculated that the efficiency of this power-to-gas system based on MEC cells when coupled to industrial processes is of the same order of magnitude as the most promising equivalent routes. The proposed process has two main limitations, the overpotentials in the electrodes that penalize the overall efficiency and the need for storage tanks for the process gases. The results of the calculations carried out in this work show that certain real potentials achieve an acceptable performance. Regarding the tanks, with adequate dimensioning, it is possible to achieve complete autonomy. The proposed system called OxyMES provides energy storage without energetically penalizing the process when compared to an oxy-combustion plant with conventional CO2 capture. According to the results obtained, this system can be applied as a measure to decarbonize an industry, changing the original fuel of the oxy-combustion boiler to the biogas generated in the MEC cell. It could also be used to neutralize CO2 emissions from industry by converting it to methane and then injecting it into the natural gas grid.

Keywords: microbial electrolysis cells, oxy-combustion, co2, power-to-gas

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Authors: Shubhangi R. Deshmukh, Anupam B. Soni

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Clean water and electricity are vital services needed in all communities. Bio-degradation of wastewater contaminants and desalination technologies are the best possible alternatives for the global shortage of fresh water supply. Osmotic microbial fuel cell (OMFC) is a versatile technology that uses microorganism (used for biodegradation of organic waste) and membrane technology (used for water purification) for wastewater treatment and energy generation simultaneously. This technology is the combination of microbial fuel cell (MFC) and forward osmosis (FO) processes. OMFC can give more electricity and clean water than the MFC which has a regular proton exchange membrane. FO gives many improvements such as high contamination removal, lower operating energy, raising high proton flux than other pressure-driven membrane technology. Lower concentration polarization lowers the membrane fouling by giving osmotic water recovery without extra cost. In this review paper, we have discussed the principle, mechanism, limitation, and application of OMFC technology reported to date. Also, we have interpreted the experimental data from various literature on the water recovery and electricity generation assessed by a different component of OMFC. The area of producing electricity using OMFC has further scope for research and seems like a promising route to wastewater treatment.

Keywords: forward osmosis, microbial fuel cell, osmotic microbial fuel cell, wastewater treatment

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Authors: Marek Dosbaba

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Within the mining sector, SEM-based Automated Mineralogy (AM) has been the standard application for quickly and efficiently handling mineral processing tasks. Over the last decade, the trend has been to analyze larger numbers of samples, often with a higher level of detail. This has necessitated a shift from interactive sample analysis performed by an operator using a SEM, to an increased reliance on offline processing to analyze and report the data. In response to this trend, TESCAN TIMA Mineral Analyzer is designed to quickly create a virtual copy of the studied samples, thereby preserving all the necessary information. Depending on the selected data acquisition mode, TESCAN TIMA can perform hyperspectral mapping and save an X-ray spectrum for each pixel or segment, respectively. This approach allows the user to browse through elemental distribution maps of all elements detectable by means of energy dispersive spectroscopy. Re-evaluation of the existing data for the presence of previously unconsidered elements is possible without the need to repeat the analysis. Additional tiers of data such as a secondary electron or cathodoluminescence images can also be recorded. To take full advantage of these information-rich datasets, TIMA utilizes a new archiving tool introduced by TESCAN. The dataset size can be reduced for long-term storage and all information can be recovered on-demand in case of renewed interest. TESCAN TIMA is optimized for network storage of its datasets because of the larger data storage capacity of servers compared to local drives, which also allows multiple users to access the data remotely. This goes hand in hand with the support of remote control for the entire data acquisition process. TESCAN also brings a newly extended open-source data format that allows other applications to extract, process and report AM data. This offers the ability to link TIMA data to large databases feeding plant performance dashboards or geometallurgical models. The traditional tabular particle-by-particle or grain-by-grain export process is preserved and can be customized with scripts to include user-defined particle/grain properties.

Keywords: Tescan, electron microscopy, mineralogy, SEM, automated mineralogy, database, TESCAN TIMA, open format, archiving, big data

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Authors: S. H. Abo Sabah, A. B. H. Kueh, M. A. Megat Johari, T. A. Majid

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In a recent study, a new bio-inspired honeycomb sandwich beam (BHSB) mimicking the head configuration of the woodpecker was developed. The beam consists of two carbon/epoxy composite face sheets, aluminum honeycomb core, and rubber core to enhance the repeated low-velocity impact resistance of sandwich structures. This paper aims to numerically enhance the repeated low-velocity impact resistance of the BHSB via optimizing the aluminum honeycomb core thickness. The beam was investigated employing three core thicknesses: 20 mm, 25 mm, and 30 mm at three impact energy levels (13.5 J, 15.55 J, 21.43 J). The results revealed that increasing the thickness of the aluminum honeycomb core to a certain level enhances the sandwich beam stiffness. The beam with the 25 mm honeycomb core thickness was the only beam that can sustain five repeated impacts achieving the highest impact resistance efficiency index, especially at high energy levels. Furthermore, the bottom face sheet of this beam developed the lowest stresses indicating that this thickness has a relatively better performance during impact events since it allowed minimal stress to reach the bottom face sheet. Overall, increasing the aluminum core thickness will increase the height of its cells subjecting it to buckling phenomenon. Therefore, this study suggests that the optimal thickness of the aluminum honeycomb core should be 65 % of the overall thickness of the sandwich beam to have the best impact resistance.

Keywords: sandwich beams, core thickness, impact behavior, finite element analysis, modeling

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Authors: M. H. Aldahrob, A. Kokce, S. Altindal, H. E. Lapa

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In order to obtain the detailed information about the effect of (Zn-doped PVA) interfacial layer, surface states (Nss) and series resistance (Rs) on electrical characteristics, both Au/n- type 4H-SiC (MS) with and without (Zn doped PVA) interfacial layer were fabricated to compare. The main electrical parameters of them were investigated using forward and reverse bias current-voltage (I-V), capacitance-voltage (C-V) and conductance –voltage (G/W –V) measurements were performed at room temperature. Experimental results show that the value of ideality factor (n), zero –bias barrier height (ΦBo), Rs, rectifier rate (RR=IF/IR) and the density of Nss are strong functions interfacial layer and applied bias voltage. The energy distribution profile of Nss was obtained from forward bias I-V data by taking into account voltage dependent effective BH (ΦBo) and ideality factor (n(V)). Voltage dependent profile of Rs was also obtained both by using Ohm’s law and Nicollian and Brew methods. The other main diode parameters such as the concentration of doping donor atom (ND), Fermi energy level (EF).BH (ΦBo), depletion layer with (WD) were obtained by using the intercept and slope of the reverse bias C-2 vs V plots. It was found that (Zn-doped PVA) interfacial layer lead to a quite decrease in the values Nss, Rs and leakage current and increase in shunt resistance (Rsh) and RR. Therefore, we can say that the use of thin (Zn-doped PVA) interfacial layer can quite improved the performance of MS structure.

Keywords: interfacial polymer layer, thickness dependence, electric and dielectric properties, series resistance, interface state

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Authors: Khodzhaberdi Allaberdiev

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In order to understand the interactions on the interface polyamide fibers and epoxy matrix in fiber- reinforced composites were investigated industrial aramid fibers: armos, svm, terlon using individual epoxy matrix components, epoxies: diglycidyl ether of bisphenol A (DGEBA), three- and diglycidyl derivatives of m, p-amino-, m, p-oxy-, o, m,p-carboxybenzoic acids, the models: curing agent, aniline and the compound, that depict of the structure the primary addition reaction the amine to the epoxy resin, N-di (oxyethylphenoxy) aniline. The chemical structure of the surface of untreated and treated polyamide fibers analyzed using Fourier transform infrared spectroscopy (FTIR). The impregnation of fibers with epoxy matrix components and N-di (oxyethylphenoxy) aniline has been carried out by heating 150˚C (6h). The optimum fiber loading is at 65%.The result a thermal treatment is the covalent bonds formation , derived from a combined of homopolymerization and crosslinking mechanisms in the interfacial region between the epoxy resin and the surface of fibers. The reactivity of epoxy resins on interface in microcomposites (MC) also depends from processing aids treated on surface of fiber and the absorbance moisture. The influences these factors as evidenced by the conversion of epoxy groups values in impregnated with DGEBA of the terlons: industrial, dried (in vacuum) and purified samples: 5.20 %, 4.65% and 14.10%, respectively. The same tendency for svm and armos fibers is observed. The changes in surface composition of these MC were monitored by X-ray photoelectron spectroscopy (XPS). In the case of the purified fibers, functional groups of fibers act as well as a catalyst and curing agent of epoxy resin. It is found that the value of the epoxy groups conversion for reinforced formulations depends on aromatic polyamides nature and decreases in the order: armos >svm> terlon. This difference is due of the structural characteristics of fibers. The interfacial interactions also examined between polyglycidyl esters substituted benzoic acids and polyamide fibers in the MC. It is found that on interfacial interactions these systems influences as well as the structure and the isomerism of epoxides. The IR-spectrum impregnated fibers with aniline showed that the polyamide fibers appreciably with aniline do not react. FTIR results of treated fibers with N-di (oxyethylphenoxy) aniline fibers revealed dramatically changes IR-characteristic of the OH groups of the amino alcohol. These observations indicated hydrogen bondings and covalent interactions between amino alcohol and functional groups of fibers. This result also confirms appearance of the exo peak on Differential Scanning Calorimetry (DSC) curve of the MC. Finally, the theoretical evaluation non-covalent interactions between individual epoxy matrix components and fibers has been performed using the benzanilide and its derivative contaning the benzimidazole moiety as a models of terlon and svm,armos, respectively. Quantum-topological analysis also demonstrated the existence hydrogen bond between amide group of models and epoxy matrix components.All the results indicated that on the interface polyamide fibers and epoxy matrix exist not only covalent, but and non-covalent the interactions during the preparation of MC.

Keywords: epoxies, interface, modeling, polyamide fibers

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Authors: Masahiro Ohmura, Koh Kakusho, Takeshi Okadome

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This paper presents a regression model with autocorrelated errors in which the inputs are social moods obtained by analyzing the adjectives in Twitter posts using a document topic model. The regression model predicts Dow Jones Industrial Average (DJIA) more precisely than autoregressive moving-average models.

Keywords: stock market prediction, social moods, regression model, DJIA

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Authors: Poonam Magu, Kumud Khanna, Premavathy Seetharaman

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The two important resources of any worker performing any type of work at any workplace are time and energy. These are important inputs of the worker and need to be utilised in the best possible manner. The kitchen is an important workplace where the homemaker performs many essential activities. Its layout should be so designed that optimum use of her resources can be achieved.Ideally, the shape of the kitchen, as determined by the physical space enclosed by the four walls, can be square, rectangular or irregular. But it is the shape of the arrangement of counter that one normally refers to while talking of the layout of the kitchen. The arrangement can be along a single wall, along two opposite walls, L shape, U shape or even island. A study was conducted in 50 kitchens belonging to middle income group families. These were DDA built kitchens located in North, South, East and West Delhi.The study was conducted in three phases. In the first phase, 510 non working homemakers were interviewed. The data related to personal characteristics of the homemakers was collected. Additional information was also collected regarding the kitchens-the size, shape , etc. The homemakers were also questioned about various aspects related to meal preparation-people performing the task, number of items cooked, areas used for meal preparation , etc. In the second phase, a suitable technique was designed for conducting time and motion study in the kitchen while the meal was being prepared. This technique was called Path Process Chart. The final phase was carried out in 50 kitchens. The criterion for selection was that all items for a meal should be cooked at the same time. All the meals were cooked by the homemakers in their own kitchens. The meal preparation was studied using the Path Process Chart technique. The data collected was analysed and conclusions drawn. It was found that of all the shapes, it was the kitchen with L shape arrangement in which, on an average a homemaker spent minimum time on meal preparation and also travelled the minimum distance. Thus, the average distance travelled in a L shaped layout was 131.1 mts as compared to 181.2 mts in an U shaped layout. Similarly, 48 minutes was the average time spent on meal preparation in L shaped layout as compared to 53 minutes in U shaped layout. Thus, the L shaped layout was more time and energy saving layout as compared to U shaped.

Keywords: kitchen layout, meal preparation, path process chart technique, workplace

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Authors: Nagham Ismail, Djamel Ouahrani

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Thermal resilience in the built environment reflects the building's capacity to adapt to extreme climate changes. In hot climates, power outages in office buildings pose risks to the health and productivity of workers. Therefore, it is of interest to quantify the thermal resilience of office buildings by developing a user-friendly simplified model. This simplified model begins with creating an assessment metric of thermal resilience that measures the duration between the power outage and the point at which the thermal habitability condition is compromised, considering different power interruption times (morning, noon, and afternoon). In this context, energy simulations of an office building are conducted for Qatar's summer weather by changing different parameters that are related to the (i) wall characteristics, (ii) glazing characteristics, (iii) load, (iv) orientation and (v) air leakage. The simulation results are processed using SPSS to derive linear regression equations, aiding stakeholders in evaluating the performance of commercial buildings during different power interruption times. The findings reveal the significant influence of glazing characteristics on thermal resilience, with the morning power outage scenario posing the most detrimental impact in terms of the shortest duration before compromising thermal resilience.

Keywords: thermal resilience, thermal envelope, energy modeling, building simulation, thermal comfort, power disruption, extreme weather

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Authors: Wei Hu, Wenguang Chen, Chong Dong

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In order to improve the efficiency and safety of photovoltaic power generation devices, this photovoltaic power generation system combines Artificial Intelligence (AI) and the Internet of Things (IoT) to control the chasing photovoltaic power generation device to track the sun to improve power generation efficiency and then convert energy management. The system uses artificial intelligence as the control terminal, the power generation device executive end uses the Linux system, and Exynos4412 is the CPU. The power generating device collects the sun image information through Sony CCD. After several power generating devices feedback the data to the CPU for processing, several CPUs send the data to the artificial intelligence control terminal through the Internet. The control terminal integrates the executive terminal information, time information, and environmental information to decide whether to generate electricity normally and then whether to convert the converted electrical energy into the grid or store it in the battery pack. When the power generation environment is abnormal, the control terminal authorizes the protection strategy, the power generation device executive terminal stops power generation and enters a self-protection posture, and at the same time, the control terminal synchronizes the data with the cloud. At the same time, the system is more intelligent, more adaptive, and longer life.

Keywords: photo-voltaic power generation, the pursuit of light, artificial intelligence, internet of things, photovoltaic array, power management

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Authors: Robert L. Burdett, Bayan Bevrani

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Analytical techniques for measuring and planning railway capacity expansion activities have been considered in this article. A preliminary mathematical framework involving track duplication and section sub divisions is proposed for this task. In railways, these features have a great effect on network performance and for this reason they have been considered. Additional motivations have also arisen from the limitations of prior models that have not included them.

Keywords: capacity analysis, capacity expansion, railways, track sub division, track duplication

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Authors: Gabriela D. Silva, Rodrigo L. O. R. Cunha, Mauricio D. Coutinho-Neto

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In the last four decades the biological activities of selenium compounds has received great attention, particularly for hypervalent derivates from selenium (IV) used as enzyme inhibitors. The unregulated activity of cysteine proteases are related to the development of several pathologies, such as neurological disorders, cardiovascular diseases, obesity, rheumatoid arthritis, cancer and parasitic infections. These enzymes are therefore a valuable target for designing new small molecule inhibitors such as selenuranes. Even tough there has been advances in the synthesis and design of new selenuranes based inhibitors, little is known about their mechanism of action. It is a given that inhibition occurs through the reaction between the thiol group of the enzyme and the chalcogen atom. However, several open questions remain about the nature of the mechanism (associative vs. dissociative) and about the nature of the reactive species in solution under physiological conditions. In this work we performed a theoretical investigation on model systems to study the possible routes of substitution reactions. Nucleophiles may be present in biological systems, our interest is centered in the thiol groups from the cysteine proteases and the hydroxyls from the aqueous environment. We therefore expect this study to clarify the possibility of a route reaction in two stages, the first consisting of the substitution of chloro atoms by hydroxyl groups and then replacing these hydroxyl groups per thiol groups in selenuranes. The structures of selenuranes and nucleophiles were optimized using density function theory along the B3LYP functional and a 6-311+G(d) basis set. Solvent was treated using the IEFPCM method as implemented in the Gaussian 09 code. Our results indicate that hydrolysis from water react preferably with selenuranes, and then, they are replaced by the thiol group. It show the energy values of -106,0730423 kcal/mol for dople substituition by hydroxyl group and 96,63078511 kcal/mol for thiol group. The solvatation and pH reduction promotes this route, increasing the energy value for reaction with hydroxil group to -50,75637672 kcal/mol and decreasing the energy value for thiol to 7,917767189 kcal/mol. Alternative ways were analyzed for monosubstitution (considering the competition between Cl, OH and SH groups) and they suggest the same route. Similar results were obtained for aliphatic and aromatic selenuranes studied.

Keywords: chalcogenes, computational study, cysteine proteases, enzyme inhibitors

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Authors: Kim Bower

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Evaluating and researching motivation in language learning is a complex and multi-faceted activity. Various models for investigating learner motivation have been proposed in the literature, but no one model supplies a complex and coherent model for investigating a range of motivational characteristics. Here, such a methodological framework, which includes exemplification of sources of evidence and potential methods of investigation, is proposed. The process model for the investigation of motivation within language learning settings proposed is based on a complex dynamic systems perspective that takes account of cognition and affects. It focuses on three overarching aspects of motivation: the learning environment, learner engagement and learner identities. Within these categories subsets are defined: the learning environment incorporates teacher, course and group specific aspects of motivation; learner engagement addresses the principal characteristics of learners' perceived value of activities, their attitudes towards language learning, their perceptions of their learning and engagement in learning tasks; and within learner identities, principal characteristics of self-concept and mastery of the language are explored. Exemplifications of potential sources of evidence in the model reflect the multiple influences within and between learner and environmental factors and the possible changes in both that may emerge over time. The model was initially developed as a framework for investigating different models of Content and Language Integrated Learning (CLIL) in contrasting contexts in secondary schools in England. The study, from which examples are drawn to exemplify the model, aimed to address the following three research questions: (1) in what ways does CLIL impact on learner motivation? (2) what are the main elements of CLIL that enhance motivation? and (3) to what extent might these be transferable to other contexts? This new model has been tried and tested in three locations in England and reported as case studies. Following an initial visit to each institution to discuss the qualitative research, instruments were developed according to the proposed model. A questionnaire was drawn up and completed by one group prior to a 3-day data collection visit to each institution, during which interviews were held with academic leaders, the head of the department, the CLIL teacher(s), and two learner focus groups of six-eight learners. Interviews were recorded and transcribed verbatim. 2-4 naturalistic observations of lessons were undertaken in each setting, as appropriate to the context, to provide colour and thereby a richer picture. Findings were subjected to an interpretive analysis by the themes derived from the process model and are reported elsewhere. The model proved to be an effective and coherent framework for planning the research, instrument design, data collection and interpretive analysis of data in these three contrasting settings, in which different models of language learning were in place. It is hoped that the proposed model, reported here together with exemplification and commentary, will enable teachers and researchers in a wide range of language learning contexts to investigate learner motivation in a systematic and in-depth manner.

Keywords: investigate, language-learning, learner motivation model, dynamic systems perspective

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Authors: Andrey Norov

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In the recent years, Samoilov Research Institute for Mineral Fertilizers JSC “NIUIF”, the oldest (established in September 1919) industry-oriented institute in Russia, has developed a range of sustainable, environment-friendly, zero-waste technologies that ensure minimal consumption of materials and energy resources and fully consistent with the principles of Green Chemistry that include: - Ecofriendly energy and resource saving technology of sulfuric acid from sulfur according to DC-DA scheme (double conversion - double absorption); - Improved zero-waste technology of wet phosphoric acid (WPA) by dihydrate-hemihydrate process applicable to various types of phosphate raw materials; - Flexible, efficient, zero-waste, universal technology of NP / NPS / NPK / NPKS fertilizers with maximum heat recovery from chemical processes; - Novel, zero-waste, no-analogue technology of granular PK / PKS / NPKS fertilizers with controlled dissolution rate and nutrient supply into the soil, which allows to process a number of wastes and by-products; - Innovative resource-saving joint processing of wastes from the production of phosphogypsum and fluorosilicic acid (FSA) into ammonium sulfate with simultaneous neutralization of fluoride compounds with no lime used. - New fertilizer technology of increased environmental and agrochemical efficiency (currently under development). All listed green technologies are patented with Russian and Eurasian patents. The development of ecofriendly, safe, green technologies is ongoing in JSC “NIUIF”.

Keywords: NPKS fertilizers, FSA, sulfuric acid, WPA

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Authors: Rajat Mittal, Jung Hee Seo, Jacob Turner, Harshal Raut

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The perpetual advancement in computational capabilities, coupled with the continuous evolution of software tools and numerical algorithms, is creating novel avenues for research, exploration, and application at the nexus of computational fluid and structural mechanics. Fish leverage their remarkably flexible bodies and fins to harness energy from vortices, propelling themselves with an elegance and efficiency that captivates engineers. Bats fly with unparalleled agility and speed by using their flexible membrane wings. Wave-assisted propulsion (WAP) systems, utilizing elastically mounted hydrofoils, convert wave energy into thrust. Each of these problems involves a complex and elegant interplay between fluid dynamics and structural mechanics. Historically, investigations into such phenomena were constrained by available tools, but modern computational advancements now facilitate exploration of these multi-physics challenges with an unprecedented level of fidelity, precision, and realism. In this work, the author will discuss projects that harness the capabilities of high-fidelity sharp-interface immersed boundary methods to address a spectrum of engineering and biological challenges involving fluid-structure interaction.

Keywords: immersed boundary methods, CFD, bioflight, fluid structure interaction

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Authors: Emanuele Bonamente, Andrea Aquino, Franco Cotana

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The exploitation of the low-temperature geothermal resource via ground-source heat pumps is often limited by the high investment cost mainly due to borehole drilling. From the monitoring of a prototypal system currently used by a commercial building, it was found that a simple upgrade of the conventional layout, obtained including a thermal storage between the ground-source heat exchangers and the heat pump, can optimize the ground energy exploitation requiring for shorter/fewer boreholes. For typical applications, a reduction of up to 66% with respect to the conventional layout can be easily achieved. Results from the monitoring campaign of the prototype are presented in this paper, and upgrades of the thermal storage using phase change materials (PCMs) are proposed using computational fluid dynamics simulations. The PCM thermal storage guarantees an improvement of the system coefficient of performance both for summer cooling and winter heating (up to 25%). A drastic reduction of the storage volume (approx. 1/10 of the original size) is also achieved, making it possible to easily place it within the technical room, avoiding extra costs for underground displacement. A preliminary optimization of the PCM geometry is finally proposed.

Keywords: computational fluid dynamics (CFD), geothermal energy, ground-source heat pumps, phase change materials (PCM)

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Authors: Hawon Lee, Young-Pil Kim

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Visualizing matrix metalloproteinases (MMPs) activity is necessary for understanding cancer metastasis because they are implicated in cell migration and invasion by degrading the extracellular matrix (ECM). While much effort has been made to sense the MMP activity, but extracellularly long-term monitoring of MMP activity still remains challenging. Here, we report a collagen-bound fluorescent bioprobe for the detection of MMP-2 activity in the extracellular environment. This bioprobe consists of ECM-immobilized part (including collagen-bound protein) and MMP-sensing part (including peptide substrate linked with fluorescence resonance energy transfer (FRET) coupler between donor green fluorescent protein (GFP) and acceptor TAMRA dye), which was constructed through intein-mediated self-splicing conjugation. Upon being immobilized on the collagen-coated surface, this bioprobe enabled efficient long-lasting observation of MMP-2 activity in the cultured cells without affecting cell growth and viability. As a result, the FRET ratio (acceptor/donor) decreased as the MMP2 activity increased in cultured cancer cells. Furthermore, unlike wild-type MMP-2, mutated MMP-2 expression (Y580A in the hemopexin region) gave rise to lowering the secretion of MMP-2 in HeLa. Conclusively, our method is anticipated to find applications for tracing and visualizing enzyme activity.

Keywords: collagen, ECM, FRET, MMP

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Authors: Nataša Todorović, Jovana Nikolov

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Despite the great interest in β⁻β⁻ decay, β⁺β⁺ decays are rarely investigated due to the low probability of detecting these processes with available low-level equipment. If β⁺β⁺, β⁺EC, or ECEC decay occurs in a thin sample of a material, the positrons will be stopped and annihilated inside the material, leading to the emission of two or four coincidence gamma photons energy of 511 keV. The paper presents the results of measurements of double beta decay of ⁶⁴Zn, ⁵⁰Cr, and ⁵⁴Fe isotopes. In the first experiment, 511-keV gamma rays originating from the annihilation of positrons in natural zinc were measured by a coincidence technique to obtain a non-zero value for the (0ν+2ν) half-life. In the second experiment, the result of measuring double beta decay of ⁵⁰Cr is presented, which suggests a result other than zero at 95% CL and gives the lowest limit for the half-life of this process. In the third experiment, neutrino-less ECEC decay of ⁵⁴Fe was examined. Under the decay theory, gamma rays are emitted whose energy does not coincide with the energies of gamma rays emitted by nuclei from known discrete excited states. Iron shield of an internal volume of 1 m³ and thickness of 25 cm served as a source for measuring the (0ν+2ν) process in ⁵⁴Fe, whose yield in natural iron is 5.4%. We obtain the lower limit for the half-life for ⁵⁴Fe: T(0ν, K, K)>4.4x10²⁰ yr, T(0ν, K, L)>4.1x10²⁰ yr, and T(0ν, L, L)>5.0x10²⁰ yr. For ⁵⁰Cr limit for the half-life is T(0ν+2ν)>1.3(6)x10¹⁸ yr, and for ⁶⁴Zn T(0ν+2ν, ECβ+)=1.1(0.9)x10⁹ years.

Keywords: neutrinoless double beta decay, half-life, ⁶⁴Zn, ⁵⁰Cr, and, ⁵⁴Fe

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Authors: Andreas Johansson

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Conceptual understanding needs to be grounded on observation of physical phenomena, experiences or metaphors. Observation of physical phenomena using demonstration experiments has a long tradition within physics education and students need to develop mental models to relate the observations to concepts from scientific theories. This study investigates how live and video experiments involving an acoustic trap to visualize particle-field interaction, field properties and particle properties can help develop students' mental models and how they can be used differently to realize their potential as teaching tools. Initially, they were treated as analogs and the lesson designs were kept identical. With a design-based approach, the experimental and video designs, as well as best practices for a respective teaching tool, were then developed in iterations. Variation theory was used as a theoretical framework to analyze the planned respective realized pattern of variation and invariance in order to explain learning outcomes as measured by a pre-posttest consisting of conceptual multiple-choice questions inspired by the Force Concept Inventory and the Force and Motion Conceptual Evaluation. Interviews with students and teachers were used to inform the design of experiments and videos in each iteration. The lesson designs and the live and video experiments has been developed to help teachers improve student learning and make school physics more interesting by involving experimental setups that usually are out of reach and to bridge the gap between what happens in classrooms and in science research. As students’ conceptual knowledge also rises their interest in physics the aim is to increase their chances of pursuing careers within science, technology, engineering or mathematics.

Keywords: acoustic trap, design-based research, experiments, variation theory

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Authors: Vasileiou Apostolos, Theodosiou Chrysa, Tsitroulis Ioannis, Maris Fotios

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The severity of extreme phenomena is due to their ability to cause severe damage in a small amount of time. It has been observed that floods affect the greatest number of people and induce the biggest damage when compared to the total of annual natural disasters. The detection of potential flood-prone areas constitutes one of the fundamental components of the European Natural Disaster Management Policy, directly connected to the European Directive 2007/60. The aim of the present paper is to develop a new methodology that combines geographical information, fuzzy logic and multi-criteria evaluation methods so that the most vulnerable areas are defined. Therefore, ten factors related to geophysical, morphological, climatological/meteorological and hydrological characteristics of the basin were selected. Afterwards, two models were created to detect the areas pronest to flooding. The first model defined the gravitas of each factor using Analytical Hierarchy Process (AHP) and the final map of possible flood spots were created using GIS and Boolean Algebra. The second model made use of the fuzzy logic and GIS combination and a respective map was created. The application area of the aforementioned methodologies was in Ardas basin due to the frequent and important floods that have taken place these last years. Then, the results were compared to the already observed floods. The result analysis shows that both models can detect with great precision possible flood spots. As the fuzzy logic model is less time-consuming, it is considered the ideal model to apply to other areas. The said results are capable of contributing to the delineation of high risk areas and to the creation of successful management plans dealing with floods.

Keywords: analytical hierarchy process, flood prone areas, fuzzy logic, geographic information system

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Authors: A. Camões, M. Ferreira Dias, M. Amorim

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In recent years, the social economy is increasingly seen as a viable means to address social problems. Social enterprises, as well as public projects and initiatives targeted to meet social purposes, offer organizational models that assume heterogeneity, flexibility and adaptability to the ‘real world and real problems’. Despite the growing popularity of social initiatives, decision makers still face a paucity in what concerns the available models and tools to adequately assess its sustainability, and its impacts, notably the nature of its contribution to economic growth. This study was carried out at the local level, by analyzing the social impact initiatives and projects promoted by the Municipality of Albergaria-a-Velha (Câmara Municipal de Albergaria-a-Velha -CMA), a municipality of 25,000 inhabitants in the central region of Portugal. This work focuses on the challenges related to the qualifications and employability of citizens, which stands out as one of the key concerns in the Portuguese economy, particularly expressive in the context of small-scale cities and inland territories. The study offers a characterization of the Municipality, its socio-economic structure and challenges, followed by an exploratory analysis of multiple sourced data, collected from the CMA's documental sources as well as from privileged informants. The purpose is to conduct detailed analysis of the CMA's social projects, aimed at characterizing its potential impact for the model of qualifications and employability of the citizens of the Municipality. The study encompasses a discussion of the socio-economic profile of the municipality, notably its asymmetries, the analysis of the social projects and initiatives, as well as of data derived from inquiry actors involved in the implementation of the social projects and its beneficiaries. Finally, the results obtained with the Better Life Index will be included. This study makes it possible to ascertain if what is implicit in the literature goes to the encounter of what one experiences in reality.

Keywords: measurement, municipalities, social economy, social impact

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Authors: S. Sehar, S. Khan, N. Ali, S. Ahmed

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In the last decade, the hunt for cost-effective, eco-friendly and energy sustainable technologies for waste water treatment are gaining much attention due to emerging water crisis and rapidly depleting existing water reservoirs all over the world. In this scenario, constructed wetland being a “green technology” could be a reliable mean for waste water treatment especially in small communities due to cost-effectiveness, ease in management, less energy consumption and sludge production. Therefore, a low cost, lab-scale sub-surface flow hybrid constructed wetland (SS-HCW) was established for domestic waste water treatment.It was observed that not only the presence but also choice of suitable vegetation along with hydraulic retention time (HRT) are key intervening ingredients which directly influence pollutant removals in constructed wetlands. Another important aspect of vegetation is that it may facilitate microbial attachment in rhizosphere, thus promote biofilm formation via microbial interactions. The major factors that influence initial aggregation and subsequent biofilm formation i.e. divalent cations (Ca2+) and extra cellular DNA (eDNA) were also studied in detail. The presence of Ca2+ in constructed wetland demonstrate superior performances in terms of effluent quality, i.e BOD5, COD, TDS, TSS, and PO4- than in absence of Ca2+. Finally, light and scanning electron microscopies coupled with EDS were carried out to get more insights into the mechanics of biofilm formation with or without Ca addition. Therefore, the same strategy can be implemented in other waste water treatment technologies.

Keywords: hybrid constructed wetland, biofilm formation, waste water treatment, waste water

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Authors: Mohammadreza Sedighi, Mohammad Said Saidi, Hesamoddin Salarian

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A numerical study has been performed to investigate the effect of using different turbulent models on natural convection flow field and temperature distributions in partially heated square cavity compare to benchmark. The temperature of the right vertical wall is lower than that of heater while other walls are insulated. The commercial CFD codes are used to model. Standard k-w model provided good agreement with the experimental data.

Keywords: Buoyancy, Cavity, CFD, Heat Transfer, Natural Convection, Turbulence

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Authors: Mohammad Afkhami, Ali Hassanpour, Michael Fairweather

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The work described in this paper was undertaken to gain insight into fundamental aspects of turbulent gas-particle flows with relevance to processes employed in a wide range of applications, such as oil and gas flow assurance in pipes, powder dispersion from dry powder inhalers, and particle resuspension in nuclear waste ponds, to name but a few. In particular, the influence of particle interaction and fluid phase behavior in turbulent flow on particle dispersion in a horizontal channel is investigated. The mathematical modeling technique used is based on the large eddy simulation (LES) methodology embodied in the commercial CFD code FLUENT, with flow solutions provided by this approach coupled to a second commercial code, EDEM, based on the discrete element method (DEM) which is used for the prediction of particle motion and interaction. The results generated by LES for the fluid phase have been validated against direct numerical simulations (DNS) for three different channel flows with shear Reynolds numbers, Reτ = 150, 300 and 590. Overall, the LES shows good agreement, with mean velocities and normal and shear stresses matching those of the DNS in both magnitude and position. The research work has focused on the prediction of those conditions favoring particle aggregation and deposition within turbulent flows. Simulations have been carried out to investigate the effects of particle size, density and concentration on particle agglomeration. Furthermore, particles with different surface properties have been simulated in three channel flows with different levels of flow turbulence, achieved by increasing the Reynolds number of the flow. The simulations mimic the conditions of two-phase, fluid-solid flows frequently encountered in domestic, commercial and industrial applications, for example, air conditioning and refrigeration units, heat exchangers, oil and gas suction and pressure lines. The particle size, density, surface energy and volume fractions selected are 45.6, 102 and 150 µm, 250, 1000 and 2159 kg m-3, 50, 500, and 5000 mJ m-2 and 7.84 × 10-6, 2.8 × 10-5, and 1 × 10-4, respectively; such particle properties are associated with particles found in soil, as well as metals and oxides prevalent in turbulent bounded fluid-solid flows due to erosion and corrosion of inner pipe walls. It has been found that the turbulence structure of the flow dominates the motion of the particles, creating particle-particle interactions, with most of these interactions taking place at locations close to the channel walls and in regions of high turbulence where their agglomeration is aided both by the high levels of turbulence and the high concentration of particles. A positive relationship between particle surface energy, concentration, size and density, and agglomeration was observed. Moreover, the results derived for the three Reynolds numbers considered show that the rate of agglomeration is strongly influenced for high surface energy particles by, and increases with, the intensity of the flow turbulence. In contrast, for lower surface energy particles, the rate of agglomeration diminishes with an increase in flow turbulence intensity.

Keywords: agglomeration, channel flow, DEM, LES, turbulence

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Authors: Regina Rekuviene, Vykintas Samaitis, Liudas Mažeika, Audrius Jankauskas, Virginija Jankauskaitė, Laura Gegeckienė, Abdolali Sadaghiani, Shaghayegh Saeidiharzand

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Icing brings significant damage to aviation and renewable energy installations. Air-conditioning, refrigeration, wind turbine blades, airplane and helicopter blades often suffer from icing phenomena, which cause severe energy losses and impair aerodynamic performance. The icing process is a complex phenomenon with many different causes and types. Icing mechanisms, distributions, and patterns are still relevant to research topics. The adhesion strength between ice and surfaces differs in different icing environments. This makes the task of anti-icing very challenging. The techniques for various icing environments must satisfy different demands and requirements (e.g., efficient, lightweight, low power consumption, low maintenance and manufacturing costs, reliable operation). It is noticeable that most methods are oriented toward a particular sector and adapting them to or suggesting them for other areas is quite problematic. These methods often use various technologies and have different specifications, sometimes with no clear indication of their efficiency. There are two major groups of anti-icing methods: passive and active. Active techniques have high efficiency but, at the same time, quite high energy consumption and require intervention in the structure’s design. It’s noticeable that vast majority of these methods require specific knowledge and personnel skills. The main effect of passive methods (ice-phobic, superhydrophobic surfaces) is to delay ice formation and growth or reduce the adhesion strength between the ice and the surface. These methods are time-consuming and depend on forecasting. They can be applied on small surfaces only for specific targets, and most are non-biodegradable (except for anti-freezing proteins). There is some quite promising information on ultrasonic ice mitigation methods that employ UGW (Ultrasonic Guided Wave). These methods are have the characteristics of low energy consumption, low cost, lightweight, and easy replacement and maintenance. However, fundamental knowledge of ultrasonic de-icing methodology is still limited. The objective of this work was to identify the ice formation processes and its progress by employing ultrasonic guided wave technique. Throughout this research, the universal set-up for acoustic measurement of ice formation in a real condition (temperature range from +240 C to -230 C) was developed. Ultrasonic measurements were performed by using high frequency 5 MHz transducers in a pitch-catch configuration. The selection of wave modes suitable for detection of ice formation phenomenon on copper metal surface was performed. Interaction between the selected wave modes and ice formation processes was investigated. It was found that selected wave modes are sensitive to temperature changes. It was demonstrated that proposed ultrasonic technique could be successfully used for the detection of ice layer formation on a metal surface.

Keywords: ice formation processes, ultrasonic GW, detection of ice formation, ultrasonic testing

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Authors: Redhouane Ghernaout, Amira Fredj, Boualem Remini

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Suspended sediment transport is a serious problem worldwide, but it is much more worrying in certain regions of the world, as is the case in the Maghreb and more particularly in Algeria. It continues to take disturbing proportions in Northern Algeria due to the variability of rains in time and in space and constant deterioration of vegetation. Its prediction is essential in order to identify its intensity and define the necessary actions for its reduction. The purpose of this study is to analyze the concentration data of suspended sediment measured at Wadi El-Abtal Hydrometric Station. It also aims to find and highlight regressive power relationships, which can explain the suspended solid flow by the measured liquid flow. The study strives to find models of artificial neural networks linking the flow, month and precipitation parameters with solid flow. The obtained results show that the power function of the solid transport rating curve and the models of artificial neural networks are appropriate methods for analysing and estimating suspended sediment transport in Wadi Mina at Wadi El-Abtal Hydrometric Station. They made it possible to identify in a fairly conclusive manner the model of neural networks with four input parameters: the liquid flow Q, the month and the daily precipitation measured at the representative stations (Frenda 013002 and Ain El-Hadid 013004 ) of the watershed. The model thus obtained makes it possible to estimate the daily solid flows (interpolate and extrapolate) even beyond the period of observation of solid flows (1985/86 to 1999/00), given the availability of the average daily liquid flows and daily precipitation since 1953/1954.

Keywords: suspended sediment, concentration, regression, liquid flow, solid flow, artificial neural network, modeling, mina, algeria

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Authors: Ermias A. Tegegn, Million Meshesha

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Human Immunodeficiency Virus and Acquired Immunodeficiency Syndrome (HIV/AIDS) is a major cause of death for most African countries. Ethiopia is one of the seriously affected countries in sub Saharan Africa. Previously in Ethiopia, having HIV/AIDS was almost equivalent to a death sentence. With the introduction of Antiretroviral Therapy (ART), HIV/AIDS has become chronic, but manageable disease. The study focused on a data mining technique to predict future living status of HIV/AIDS patients at the time of drug regimen change when the patients become toxic to the currently taking ART drug combination. The data is taken from University of Gondar Hospital ART program database. Hybrid methodology is followed to explore the application of data mining on ART program dataset. Data cleaning, handling missing values and data transformation were used for preprocessing the data. WEKA 3.7.9 data mining tools, classification algorithms, and expertise are utilized as means to address the research problem. By using four different classification algorithms, (i.e., J48 Classifier, PART rule induction, Naïve Bayes and Neural network) and by adjusting their parameters thirty-two models were built on the pre-processed University of Gondar ART program dataset. The performances of the models were evaluated using the standard metrics of accuracy, precision, recall, and F-measure. The most effective model to predict the status of HIV patients with drug regimen substitution is pruned J48 decision tree with a classification accuracy of 98.01%. This study extracts interesting attributes such as Ever taking Cotrim, Ever taking TbRx, CD4 count, Age, Weight, and Gender so as to predict the status of drug regimen substitution. The outcome of this study can be used as an assistant tool for the clinician to help them make more appropriate drug regimen substitution. Future research directions are forwarded to come up with an applicable system in the area of the study.

Keywords: HIV drug regimen, data mining, hybrid methodology, predictive model

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Authors: Xiaomin Zhong, Alexander Pate, Ya-Ting Yang, Ali Fahmi, Darren M. Ashcroft, Ben Goldacre, Brian Mackenna, Amir Mehrkar, Sebastian C. J. Bacon, Jon Massey, Louis Fisher, Peter Inglesby, Kieran Hand, Tjeerd van Staa, Victoria Palin

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Background: This study aimed to predict risks of potentially inappropriate antibiotic type and repeat prescribing and assess changes during COVID-19. Methods: With the approval of NHS England, we used the OpenSAFELY platform to access the TPP SystmOne electronic health record (EHR) system and selected patients prescribed antibiotics from 2019 to 2021. Multinomial logistic regression models predicted the patient’s probability of receiving an inappropriate antibiotic type or repeating the antibiotic course for each common infection. Findings: The population included 9.1 million patients with 29.2 million antibiotic prescriptions. 29.1% of prescriptions were identified as repeat prescribing. Those with same-day incident infection coded in the EHR had considerably lower rates of repeat prescribing (18.0%), and 8.6% had a potentially inappropriate type. No major changes in the rates of repeat antibiotic prescribing during COVID-19 were found. In the ten risk prediction models, good levels of calibration and moderate levels of discrimination were found. Important predictors included age, prior antibiotic prescribing, and region. Patients varied in their predicted risks. For sore throat, the range from 2.5 to 97.5th percentile was 2.7 to 23.5% (inappropriate type) and 6.0 to 27.2% (repeat prescription). For otitis externa, these numbers were 25.9 to 63.9% and 8.5 to 37.1%, respectively. Interpretation: Our study found no evidence of changes in the level of inappropriate or repeat antibiotic prescribing after the start of COVID-19. Repeat antibiotic prescribing was frequent and varied according to regional and patient characteristics. There is a need for treatment guidelines to be developed around antibiotic failure and clinicians provided with individualised patient information.

Keywords: antibiotics, infection, COVID-19 pandemic, antibiotic stewardship, primary care

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Authors: Silvia Grassi, Stefano Schiavon, Ernestina Casiraghi, Cristina Alamprese

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Dry-cured ham is an uncooked meat product particularly appreciated for its peculiar sensory traits among which lipid component plays a key role in defining quality and, consequently, consumers’ acceptability. Usually, fat content and distribution are chemically determined by expensive, time-consuming, and destructive analyses. Moreover, different sensory techniques are applied to assess product conformity to desired standards. In this context, visual systems are getting a foothold in the meat market envisioning more reliable and time-saving assessment of food quality traits. The present work aims at developing a simple but systematic and objective visual methodology to assess the fat amount of dry-cured ham slices, in terms of total, intermuscular and intramuscular fractions. To the aim, 160 slices from 80 PDO dry-cured hams were evaluated by digital image analysis and Soxhlet extraction. RGB images were captured by a flatbed scanner, converted in grey-scale images, and segmented based on intensity histograms as well as on a multi-stage algorithm aimed at edge enhancement. The latter was performed applying the Canny algorithm, which consists of image noise reduction, calculation of the intensity gradient for each image, spurious response removal, actual thresholding on corrected images, and confirmation of strong edge boundaries. The approach allowed for the automatic calculation of total, intermuscular and intramuscular fat fractions as percentages of the total slice area. Linear regression models were run to estimate the relationships between the image analysis results and the chemical data, thus allowing for the prediction of the total, intermuscular and intramuscular fat content by the dry-cured ham images. The goodness of fit of the obtained models was confirmed in terms of coefficient of determination (R²), hypothesis testing and pattern of residuals. Good regression models have been found being 0.73, 0.82, and 0.73 the R2 values for the total fat, the sum of intermuscular and intramuscular fat and the intermuscular fraction, respectively. In conclusion, the edge enhancement visual procedure brought to a good fat segmentation making the simple visual approach for the quantification of the different fat fractions in dry-cured ham slices sufficiently simple, accurate and precise. The presented image analysis approach steers towards the development of instruments that can overcome destructive, tedious and time-consuming chemical determinations. As future perspectives, the results of the proposed image analysis methodology will be compared with those of sensory tests in order to develop a fast grading method of dry-cured hams based on fat distribution. Therefore, the system will be able not only to predict the actual fat content but it will also reflect the visual appearance of samples as perceived by consumers.

Keywords: dry-cured ham, edge detection algorithm, fat content, image analysis

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