Reference Ones Research Articles

Cooling Effectiveness of the Sustainable Cooling Solution for Cattle: Case Study in Poland

Recently, the dairy sector has been ever more affected by global warming. This study aimed to test a novel conductive cooling system for cattle that was successfully implemented and evaluated under summer thermally challenging weather conditions in Poland. The system consists mainly of the chiller, tank, and chilled water-driven mattress, designed to prioritize animal well-being. The experimental evaluation was carried out on three Friesian dry cows, housed on different types of bedding—commercial water mattress, straw, and cooling water mattress—and supplied with water at 10 °C (day) and 16 °C (night). The cooling water mattress’ surface temperature was twice as low as that of the commercial water mattress. The animal’s thermal comfort was assessed with physiological and behavioral reactions. The cooling effect on animals’ bodies was demonstrated with a lower reticulorumen temperature of the cooled cow (p < 0.05) than the reference ones. The local effect of cooling was proved with an 8 °C-lower skin temperature after the cow’s resting period. The presented study opens a new research direction toward dairy cattle’s welfare, sustainability, and the food–energy–water nexus, based on potential energy and water savings.

Investigation of new confined concrete-filled aluminum tube piles: Experimental and numerical approaches

This research aims to introduce and test a Confined Concrete-Filled Aluminum Tube Pile (CCFAT) as an innovative composite pile that embodies a distinctive amalgamation of favourable material characteristics. Experimental tests were carried out to achieve this goal by analysing the vertical and lateral responses of various configurations and slenderness ratios (Lm/D) (ranging from 10 to 20) of CCFAT piles. As a reference group, two traditional piles were also manufactured and tested under identical conditions for comparison purposes. Additionally, the finite element approach was applied to validate the experimental results. The findings indicated that CCFAT piles have either higher or at least equivalent ultimate vertical capacity to that of reference piles. Additionally, the results proved the superior ultimate lateral capacity of the CCFAT piles compared to the reference ones. The results also showed a constant maximum bending moment dept in the CCFAT piles with a Lm/D ratio of 10, with a slight increase observed for CCFAT with a Lm/D ratio of 20 under lateral loading, which could be attributed to the rigidity of the CCAFT piles. Moreover, the outcomes of the finite element analysis indicated that both ultimate vertical and lateral capacities improve with the increase in the number of piles. The sensitivity analysis showed that the dilatancy angle plays the most important role in determining the vertical capacity of the piles, while the lateral capacity was significantly determined by the internal friction angle. Finally, fitted charts were produced and validated in this study to help researchers estimate the ultimate vertical and lateral capacities of CCFAT piles depending on the stiffness of the pile groups.

Association of fluoroquinolones with the risk of spontaneous pneumothorax: nationwide case–time–control study

IntroductionFluoroquinolones can cause severe collagen-associated adverse effects, potentially impacting the pulmonary connective tissue. We investigated the association between fluoroquinolones and spontaneous pneumothorax.MethodsA case–time–control study was performed using the nationwide French...

Prostate magnetic resonance imaging (MRI) in patients with hip implants-presetting a protocol using a phantom.

Metal structures are a source of artifacts that significantly complicate the interpretation of magnetic resonance imaging (MRI). The use of prostate MRI as a preliminary test in men with a suspicion on prostate cancer leads to an increased use of the test. The aim of this study was to solve a clinically significant problem: to ensure the reduction of artifacts from metal hip implants during prostate MRI. Another goal was to evaluate the impact of artifact reduction methods on quantitative measurements. The prostate gland (PG) phantom model was a cylinder filled with an aqueous solution of polyvinylpyrrolidone at the concentrations of 40%, 30%, and 20% [central zone (CZ), peripheral zone (PZ), and "lesion", respectively]. Phantom MRI study was conducted on Philips Ingenia 1.5T and Philips Ingenia 3T scanners. For 1.5 T, the reduction in the influence of artifacts inside region of interest (ROI) was observed, expressed in a decrease in the average apparent diffusion coefficient (ADC) (CZ, PZ, "lesion") for the manual artifact reduction (MAR) and ZOOM (title of software artifact reduction) techniques compared to the standard method. For 3T this effect was not detected. The same ADC results were obtained for Standard and MAR techniques, and increased ADC values for ZOOM. Despite the fact that the spread of ADC values on 3.0T scanners was minimal, there was a significant deviation of ADC values from the reference ones (up to 30.4%). Therefore, it is necessary to use a correction coefficient in the ADC calculation for the 3.0 T device. In the presented clinical case, high-quality tomograms were obtained without any artifacts, despite the presence of two hip replacement devices in the scanning area. The accurate prostate MRI in the presence of implants is essential for an accurate diagnosis. This approach allows to reduce artifacts from hip implants, to visualize PG and periprostatic tissue in the best way, and to detect malignant and benign changes.

Traceability and measurement uncertainty of non-removable field flowmeters using clamp-on ultrasonic flowmeters as reference

This study examines the traceability and measurement uncertainty of in situ hydraulic calibration of flowmeters using clamp-on ultrasonic flowmeters as reference. The procedure compares the equipment readings with the reference ones. Measurement uncertainty evaluation uses Guide to the expression of Uncertainty in Measurement (GUM) formulation, considering the linearity conditions of the mathematical models applied. Experimental values are used to test the procedure and its suitability for actual cases where the expected accuracy needs to be achieved.

Non-Invasive Quantification of the Brain [¹⁸F]FDG-PET Using Inferred Blood Input Function Learned From Total-Body Data With Physical Constraint.

Full quantification of brain PET requires the blood input function (IF), which is traditionally achieved through an invasive and time-consuming arterial catheter procedure, making it unfeasible for clinical routine. This study presents a deep learning based method to estimate the input function (DLIF) for a dynamic brain FDG scan. A long short-term memory combined with a fully connected network was used. The dataset for training was generated from 85 total-body dynamic scans obtained on a uEXPLORER scanner. Time-activity curves from 8 brain regions and the carotid served as the input of the model, and labelled IF was generated from the ascending aorta defined on CT image. We emphasize the goodness-of-fitting of kinetic modeling as an additional physical loss to reduce the bias and the need for large training samples. DLIF was evaluated together with existing methods in terms of RMSE, area under the curve, regional and parametric image quantifications. The results revealed that the proposed model can generate IFs that closer to the reference ones in terms of shape and amplitude compared with the IFs generated using existing methods. All regional kinetic parameters calculated using DLIF agreed with reference values, with the correlation coefficient being 0.961 (0.913) and relative bias being 1.68±8.74% (0.37±4.93%) for [Formula: see text] ( [Formula: see text]. In terms of the visual appearance and quantification, parametric images were also highly identical to the reference images. In conclusion, our experiments indicate that a trained model can infer an image-derived IF from dynamic brain PET data, which enables subsequent reliable kinetic modeling.

Correcting force error-induced underestimation of lattice thermal conductivity in machine learning molecular dynamics

Machine learned potentials (MLPs) have been widely employed in molecular dynamics simulations to study thermal transport. However, the literature results indicate that MLPs generally underestimate the lattice thermal conductivity (LTC) of typical solids. Here, we quantitatively analyze this underestimation in the context of the neuroevolution potential (NEP), which is a representative MLP that balances efficiency and accuracy. Taking crystalline silicon, gallium arsenide, graphene, and lead telluride as examples, we reveal that the fitting errors in the machine-learned forces against the reference ones are responsible for the underestimated LTC as they constitute external perturbations to the interatomic forces. Since the force errors of a NEP model and the random forces in the Langevin thermostat both follow a Gaussian distribution, we propose an approach to correcting the LTC by intentionally introducing different levels of force noises via the Langevin thermostat and then extrapolating to the limit of zero force error. Excellent agreement with experiments is obtained by using this correction for all the prototypical materials over a wide range of temperatures. Based on spectral analyses, we find that the LTC underestimation mainly arises from increased phonon scatterings in the low-frequency region caused by the random force errors.

Automated modal parameter tracking with neural network based normalization of environmental perturbations

Automated modal parameter tracking is an essential part of vibration-based structural health monitoring of engineering structures, e.g., bridges, high-rise building, wind turbines, amongst others. In this work, we conceive a robust algorithm for accomplishing this task. First, the modal parameters are extracted with by greedy clustering the stabilization diagram, which is based on covariance-driven subspace identification and the related uncertainty quantification. After the selection of a set of relevant modal parameters to be monitored, the tracking is performed by an active search of stable modes close to the reference ones, again using statistical criteria and automated clustering. The applied strategies allow for a robust method, allowing also for relatively strong variations in the natural frequencies or the MAC without losing track of the monitored modes. Finally, when EOVs (Environmental and Operational Variables) are measured and training and testing periods are defined, a neural network is trained based on the tracked frequencies and the EOVs, with the goal of correcting the environmental influence on the estimated frequencies based on the model predictions. In doing so, a distance metric is defined for damage detection, which is robust to environmental perturbations under the measured EOVs. The whole framework is showcased on monitoring data of a full-scale bridge.

Agroeconomic justification of technologies of distributed application of the herbicide corum in soybean agrocenoses

Aim. The article analyses the feasibility of using a system of distributed application of insurance herbicides in intensive soybean cultivation technologies. Methods. The aim of the research was to establish the biological and economic performance of two-time consecutive sprayings of soybean crops with reduced norms of Corum herbicide. The three-year (2018–2020) field experiments were conducted in a stationary crop rotation at the separate subdivision of the National University of Life and Environmental Sciences "Agronomic Research Station". The effectiveness of the insurance herbicide Corum (l. c., 48% bentazon + 2.24% imazamox) was studied at application rates (1.5; 2.0 and 2.5 l/ha) and two consecutive sprayings of 0.75 l/ha in tank mixtures with the surfactant Metolat (1.0 l/ha). The insurance herbicides Bazagran (a. s., 48% bentazon) and Pulsar (w. s. c., 4% imazamox) were used as reference ones at the recommended application rates of 2.5 and 1.0 l/ha, respectively. Results. The results of the research established that the herbicide Corum together with the surfactant Metolat provided effective control of the dominant segetal vegetation in soybean crops at all rates and methods of application with a biological efficiency of more than 85%, which is by 5–10% higher than the indexes of reference insurance herbicides. A two-time sequential spraying with the herbicide at a rate of 0.75 l/ha was the most effective, which ensured almost complete elimination of dicotyledonous juveniles and 75–92% of cereal annuals, which is equal to the effectiveness of the maximum single rate (2.5 l/ha). The high biological efficiency of Corum herbicide in tank mixtures with surfactant Metolat with two consecutive applications provided the largest increase in the marketable crop of soybeans — 1.46 t/ha or 77% compared to the level of an untreated control in the absence of quantitative changes in the protein and oil content in seeds. Conclusions. A significant increase in crop and low additional investment in the system ensured obtaining a maximum net profit per 1 ha (UAH 12155). At the same time, the profitability of growing the crop reached 49.0% with a six-fold return on the funds invested in the technology. Given the combination of household, economic and environmental factors of the innovative system of distributed application of the herbicide Corum, it is advisable to introduce it into production.

Deposit sintering in modern Kraft recovery boilers − The role of NaOH?

Modern Kraft recovery boilers have become larger compared to earlier designs and burn higher black liquor dry solids (DS), leading to a more intense burning process and, therefore, increased sodium hydroxide (NaOH) concentration in the upper furnace. Indications of rapid deposit build-up and plugging issues in these boilers, specifically downstream of the superheaters, have been observed at lower temperatures than typically expected, which could be a consequence of the increased NaOH. Thermodynamic calculations were performed to explore the formation of NaOH(g) in boilers with high carbonate content in the fly ash particles and the effect of the presence of NaOH on the melting properties of the deposits. The results indicated that at low temperatures (<400 °C), almost no NaOH(g) is expected to be present in the flue gases. However, we propose that rapid cooling of flue gases across superheaters kinetically freezes the carbonation of NaOH(g), resulting in higher NaOH(g) concentrations than predicted by equilibrium calculations alone. At low temperatures, the remaining NaOH(g) vapors condense on the fly ash and form a melt, potentially leading to the sintering of deposits and plugging issues. To confirm this theory, sintering tests were carried out at 300–350 °C by doping electrostatic precipitator (ESP) ash from a recovery boiler with NaOH powder. It was observed that the doped pellets sintered and were much harder than the reference ones across various experimental conditions. The single particle reactor (SPR) test results showed that the pellets started to sinter immediately upon heating up to 350 °C, suggesting that NaOH melt-induced sintering is a rapid mechanism. The findings of this study may also have implications for boilers with a high sodium (Na) content.

Assessing downscaling methods to simulate hydrologically relevant weather scenarios from a global atmospheric reanalysis: case study of the upper Rhône River (1902–2009)

Abstract. We assess the ability of two modelling chains to reproduce, over the last century (1902–2009) and from large-scale atmospheric information only, the temporal variations in river discharges, low-flow sequences and flood events observed at different locations of the upper Rhône River catchment, an alpine river straddling France and Switzerland (10 900 km2). The two modelling chains are made up of a downscaling model, either statistical (Sequential Constructive Atmospheric Analogues for Multivariate weather Predictions – SCAMP) or dynamical (Modèle Atmosphérique Régional – MAR), and the Glacier and SnowMelt SOil CONTribution (GSM-SOCONT) model. Both downscaling models, forced by atmospheric information from the global atmospheric reanalysis ERA-20C, provide time series of daily scenarios of precipitation and temperature used as inputs to the hydrological model. With hydrological regimes ranging from highly glaciated ones in its upper part to mixed ones dominated by snow and rain downstream, the upper Rhône River catchment is ideal for evaluating the different downscaling models in contrasting and demanding hydro-meteorological configurations where the interplay between weather variables in both space and time is determinant. Whatever the river sub-basin considered, the simulated discharges are in good agreement with the reference ones, provided that the weather scenarios are bias-corrected. The observed multi-scale variations in discharges (daily, seasonal, and interannual) are reproduced well. The low-frequency hydrological situations, such as annual monthly discharge minima (used as low-flow proxy indicators) and annual daily discharge maxima (used as flood proxy indicators), are reproduced reasonably well. The observed increase in flood activity over the last century is also reproduced rather well. The observed low-flow activity is conversely overestimated, and its variations from one sub-period to another are only partially reproduced. Bias correction is crucial for both precipitation and temperature and for both downscaling models. For the dynamical one, a bias correction is also essential for getting realistic daily temperature lapse rates. Uncorrected scenarios lead to irrelevant hydrological simulations, especially for the sub-basins at high elevation, due mainly to irrelevant snowpack dynamic simulations. The simulations also highlight the difficulty in simulating precipitation dependency on elevation over mountainous areas.

Experimental study on seismic performance of squat RC shear walls reinforced with hybrid steel and GFRP rebars

This laboratory study investigates the effect of using steel and glass fiber reinforced polymer (GFRP) rebars in shear walls with aspect ratios less than two. The study evaluates six full-scale shear walls subjected to constant axial load and cyclic lateral loading, with aspect ratios of 1.08 and 1.75. The aim is to analyze how the use of steel and GFRP rebars affects crack patterns, fracture, seismic performance, dissipated energy, and ductility of shear walls. The six specimens consist of two reference ones (SRC1 and SRC2) reinforced with steel rebars, two specimens (GRC1 and GRC2) reinforced with GFRP rebars, and two specimens (S-GRC1 and S-GRC2) reinforced with a hybrid of steel and GFRP rebars. The conclusions drawn suggest that employing a hybrid combination of steel and GFRP rebars resulted in a notable alteration of crack propagation behavior and failure mode, transitioning from flexural compression to flexural tension. Additionally, compared to the specimens reinforced solely with GFRP rebars, there was an observed expansion of the hysteresis curve. Additionally, parameters such as cumulative dissipated energy, ductility, and load modification factor based on ductility increased in the S-GRC1 and S-GRC2 specimens compared to the GRC1 and GRC2.

Assessing pressure wave components for aortic stiffness monitoring through spectral regression learning.

The ageing process notably induces structural changes in the arterial system, primarily manifesting as increased aortic stiffness, a precursor to cardiovascular events. While wave separation analysis is a robust tool for decomposing the components of blood pressure waveform, its relationship with cardiovascular events, such as aortic stiffening, is incompletely understood. Furthermore, its applicability has been limited due to the need for concurrent measurements of pressure and flow. Our aim in this study addresses this gap by introducing a spectral regression learning method for pressure-only wave separation analysis. Leveraging data from the Framingham Heart Study (2640 individuals, 55% women), we evaluate the accuracy of pressure-only estimates, their interchangeability with a reference method based on ultrasound-derived flow waves, and their association with carotid-femoral pulse wave velocity (PWV). Method-derived estimates are strongly correlated with the reference ones for forward wave amplitude ( ), backward wave amplitude ( ), and reflection index ( ) and moderately correlated with a time delay between forward and backward waves ( ). The proposed pressure-only method shows interchangeability with the reference method through covariate analysis. Adjusting for age, sex, body size, mean blood pressure, and heart rate, the results suggest that both pressure-only and pressure-flow evaluations of wave separation parameters yield similar model performances for predicting carotid-femoral PWV, with forward wave amplitude being the only significant factor (P < 0.001; 95% confidence interval, 0.056-0.097). We propose an interchangeable pressure-only wave separation analysis method and demonstrate its clinical applicability in capturing aortic stiffening. The proposed method provides a valuable non-invasive tool for assessing cardiovascular health.

High-quality single InGaAs/GaAs quantum dot growth on a silicon substrate for quantum photonic applications

Developing non-classical light sources for use in quantum information technology is a primary goal of quantum nanophotonics. Significant progress has been made in this area using quantum dots grown on III/V semiconductor substrates. However, it is crucial to develop quantum light sources based on silicon wafers to facilitate large-scale integration of electronic circuits and quantum photonic structures. We present a method for the direct heteroepitaxial growth of high-quality InGaAs quantum dots on silicon, which enables the fabrication of scalable and cost-effective quantum photonics devices that are compatible with silicon technology. To achieve high-quality GaAs heterostructures, we apply an intermediate GaP buffer and defect-reducing layers on a silicon substrate. The epitaxially grown quantum dots exhibit optical and quantum-optical properties similar to reference ones based on conventional GaAs substrates. The distributed Bragg reflector used as a backside mirror enables us to achieve bright emission with up to (18 ± 1)% photon extraction efficiency. Additionally, the quantum dots exhibit strong multi-photon suppression with g(2)(τ) = (3.7 ± 0.2) × 10−2 and high photon indistinguishability V = (66 ± 19)% under non-resonant excitation. These results indicate the high potential of our heteroepitaxy approach in the field of silicon-compatible quantum nanophotonics. Our approach can pave the way for future chips that combine electronic and quantum photonic functionality.

Geno-Species Composition of Borrelia Circulating on the Black Sea Coast of the Krasnodar Territory

The aim of the study was to assess the current epidemiological situation on Ixodidae tick-borne borreliosis (ITBB) (2017–2022) on the Black Sea coast of the Krasnodar Territory, to study the species composition of Borrelia.Materials and methods. Ixodidae ticks, Ixodes ricinus, Haemaphysalis concinna, H. inermis, Rhipicephalus sanguineus, were examined for infection with tick-borne borreliosis pathogens, followed by DNA sequencing of isolates. Species identification of Borrelia was carried out based on analysis of the nucleotide sequence of the 16S rRNA gene fragment using BLAST algorithm. Additionally, the OspC genotype was determined for isolates of pathogenic genovariants through comparing the obtained sequences with reference ones in the MEGA 5 program. The data were processed applying the cartographic method using the QGIS 2.18 software.Results and discussion. Between 2017 and 2022, 101 cases were registered on the Black Sea coast of the Krasnodar Territory, which accounted for 1.6 % of all ITBB cases in the Krasnodar Territory. The number of complaints with tick bites in Sochi was up to 191.4 per 100 thousand population. During the study, the predominant Borrelia geno-species on the territory of the Black Sea coast of the Krasnodar Territory was determined using sequencing – Borrelia lusitaniae (78.1 %). The circulation of geno-species B. garinii (6.8 %), B. valasiana (5.7 %), B. afzelii (3.6 %), B. miyamotoi (2.6 %), B. tanukii, B. bissettii (1.6 % each) was also observed. For Borrelia pathogenic species, appurtenance to OspC geno-groups was ascertained: four isolates were assigned to invasive OspC geno-groups, of which three B. afzelii isolates were genogroup A8, one B. garinii isolate was G7. High rate of infection of ticks with Borrelia was recorded in the surveyed area (up to 94.5 %). Borrelia of pathogenic species account for only 10.4 % of the total number of isolates studied. Mostly, genovariants that rarely cause diseases in humans (B. lusitaniae, B. valasiana, B. bissettii) and non-pathogenic Borrelia (B. tanukii) were found, which indicates a low risk of infection with ITBB pathogens.

МАТЕМАТИЧНІ СИСТЕМИ ДЛЯ РЕАЛІЗАЦІЇ ШТУЧНИХ НЕЙРОННИХ МЕРЕЖ, ОРІЄНТОВАНИХ НА ХМАРОВІ ОБЧИСЛЕННЯ

The article provides a detailed overview of research focusing on artificial neural networks (ANNs) and their applications in cloud computing. Research methods of organizational development and changes based on artificial intelligence technologies and intellectual support systems are presented in the plane of: intellectual expert systems; inductive systems; semantic networks, neural networks, genetic algorithms. The aim of the study. The research is aimed at the study and analysis of modern mathematical systems used to implement artificial neural networks (ANNs). The main focus of the work is on how each artificial neuron in the network is characterized by its current state, which is similar to nerve cells in the brain that can be excited or inhibited. A detailed description of the functioning of neurons is provided, including the processes of summation of input signals and activation using activation functions. Special attention is paid to multilayer neural networks and their ability to form complex multidimensional functions. The methods of building decision-making models based on the analysis of unclear situations and reference states determined by experts are defined. The process of comparing the real states of organizations with reference ones for making optimal decisions is considered. The importance of fuzzy logical operations for determining the degree of closeness of various situations is described. Fuzzy reference situations for cloud computing and their impact on decision-making in various scenarios are proposed. Examples of real and hypothetical fuzzy situations are given, and methods of determining the fuzzy correspondence between different reference situations are also considered. The final part of the abstract emphasizes the possibilities and advantages of using such models in cloud computing, emphasizing their importance for the development of organizations and systems.

How do different modalities of land use practices impact the environmental features and macroinvertebrates? An assessment of mountain streams from Patagonia, Argentina

Agricultural intensification is a significant process, transforming the land and modifying stream water quality and biodiversity. Land-use practices are associated with substantial changes in vegetation structure, significant inputs of nutrients, erosion, and increased sedimentation, all of which profoundly impact aquatic biota and ecosystem functioning. The effect of different agricultural practices (horticulture, extensive and intensive livestock) on stream water quality was compared in terms of physicochemical features, bacteria, habitat condition, riparian ecosystem, and macroinvertebrate variables in a temperate rural landscape (Patagonia). The main objective was to identify which variables related to land use were determinants in the configuration of biotic communities. Significantly higher values in water temperature, conductivity, nutrients, and bacteria were found at intensively developed sites than at reference ones. The quality of the habitat and the riparian ecosystem had been profoundly modified. A multidimensional scaling analysis revealed that macroinvertebrate assemblages also differed among land use categories, with the variables: total phosphorous, total nitrogen, bacteria (E. coli, mesophilic and total coliforms), water temperature, and oxygen having the highest predictive power. Macroinvertebrate metrics (richness of EPT (Ephemeroptera+Plecoptera+Trichoptera), Plecoptera, shredders and scrapers, and the percentage of scrapers and collectors) proved appropriate bioindicators for discriminating intensive land use impacts and highlighted a trend of biodiversity loss. Plecoptera richness, a taxa group with a high level of endemism, responded significantly to habitat condition degradation. These results confirm that the intensification of land use leads to increased nutrient levels and suppressed aquatic-terrestrial interactions involved in the provision of allochthonous detrital input, shade, and habitat structure for larval stages and adults. The Habitat Condition Index appears to be a useful tool for rapid stream assessment and providing early warnings. Several ecological services are threatened in these Patagonian agroecosystems. Restoring riverbank heterogeneity and improving management practices that ameliorate nutrient and sediment inputs are crucial to enhance biodiversity.

ИЗУЧЕНИЕ ПРОСТРАНСТВЕННОЙ ТОЧНОСТИ МОДЕЛЕЙ ЧЕЛЮСТЕЙ В ЗАВИСИМОСТИ ОТ МЕТОДА ПОЛУЧЕНИЯ ОТТИСКА И ЕГО МАТЕРИАЛА

Methods for obtaining working and auxiliary dental impressions of patients have been revised in recent decades, which is associated with 3D scanning. At the same time, the policy of import substitution in dentistry is also developing quite actively, which is reflected in the introduction of domestic impression masses for analog prints into public health institutions.&#x0D; The aim of study. Reducing the number of complications of dental orthopedic treatment by optimizing the approach to choosing a method for obtaining a working anatomical impression.&#x0D; Methodology. Impressions of the mandible of 10 patients were obtained. 7 impressions were obtained from each patient using the most commonly used techniques, silicone impression materials and intraoral scanning. Further, jaw models of 4 types of plaster were made for each impression and scanned with an off-site dental scanner. With the help of a micrometer in the oral cavity, measurements of teeth 3.5, 4.4 and 4.2 were made according to the maximum vestibular-oral size of the clinical crown, which were taken as a standard. The reference size is compared with the dimensions obtained on digital models according to the selected parameters with an accuracy of up to thousandths of a millimeter. A statistical analysis of the data obtained was carried out.&#x0D; Results. The data obtained confirmed the manufacturer's claims about the accuracy of the impression masses. A slight decrease in the studied sizes was noted on the models obtained by intraoral scanning. Whereas on models obtained using silicone impressions, the dimensions, on the contrary, were slightly larger than the reference ones. A statistically significant difference was revealed when comparing models obtained using intraoral scanning and models obtained by laboratory scanning from analogues of jaws using silicone impressions. When comparing the data obtained with the standard, no critical differences were revealed.&#x0D; Conclusions. It is impossible to unequivocally assert the advantage of a digital or analog method of obtaining impressions in modern orthopedic dentistry. The method of obtaining an impression should be chosen depending on the indications for a particular type of treatment and clinical conditions.

Production of upgraded metallurgical-grade silicon for a low-cost, high-efficiency, and reliable PV technology

Upgraded metallurgical-grade silicon (UMG-Si) has the potential to reduce the cost of photovoltaic (PV) technology and improve its environmental profile. In this contribution, we summarize the extensive work made in the research and development of UMG technology for PV, which has led to the demonstration of UMG-Si as a competitive alternative to polysilicon for the production of high-efficiency multicrystalline solar cells and modules. The tailoring of the processing steps along the complete Ferrosolar’s UMG-Si manufacturing value chain is addressed, commencing with the purification stage that results in a moderately compensated material due to the presence of phosphorous and boron. Gallium is added as a dopant at the crystallization stage to obtain a uniform resistivity profile of ∼1 Ω cm along the ingot height. Defect engineering techniques based on phosphorus diffusion gettering are optimized to improve the bulk electronic quality of UMG-Si wafers. Black silicon texturing, compatible with subsequent gettering and surface passivation, is successfully implemented. Industrial-type aluminum back surface field (Al-BSF) and passivated emitter and rear cell (PERC) solar cells are fabricated, achieving cell efficiencies in the range of those obtained with conventional polysilicon substrates. TOPCon solar cell processing key steps are also tested to further evaluate the potential of the material in advanced device architectures beyond the PERC. Degradation mechanisms related to light exposure and operation temperature are shown to be insignificant in UMG PERC solar cells when a regeneration step is implemented, and PV modules with several years of outdoor operation demonstrated similar performance to reference ones based on poly-Si. Life cycle analysis (LCA) is carried out to evaluate the environmental impact of UMG-based PV technology when compared to poly-Si-based technology, considering different scenarios for both the manufacturing sites and the PV installations.

The Impact of Structural Pattern Types on the Electrochemical Performance of Ultra-Thick NMC 622 Electrodes for Lithium-Ion Batteries

An increase in the energy density on the cell level while maintaining a high power density can be realized by combining thick-film electrodes and the 3D battery concept. The effect of laser structuring using different pattern types on the electrochemical performance was studied. For this purpose, LiNi0.6Mn0.2Co0.2O2 (NMC 622) thick-film cathodes were prepared with a PVDF binder and were afterward structured using ultrafast laser ablation. Eight different pattern types were realized, which are lines, grids, holes, hexagonal structures, and their respective combinations. In addition, the mass loss caused by laser ablation was kept the same regardless of the pattern type. The laser-structured electrodes were assembled in coin cells and subsequently electrochemically characterized. It was found that when discharging the cells for durations of less than 2 h, a significant, positive impact of laser patterning on the electrochemical cell performance was observed. For example, when discharging was performed for one hour, cells containing laser-patterned electrodes with different structure types exhibited a specific capacity increase of up to 70 mAh/g in contrast to the reference ones. Although cells with a hole-patterned electrode exhibited a minimum capacity increase in the rate capability analysis, the combination of holes with lines, grids, or hexagons led to further capacity increases. In addition, long-term cycle analyses demonstrated the benefits of laser patterning on the cell lifetime, while cyclic voltammetry highlighted an increase in the Li-ion diffusion kinetics in cells containing hexagonal-patterned electrodes.