In this study, the effect of hot stamping forming process on the properties change of compound layer in Al–Si coated high-strength steel sheet with different thickness was investigated. The coating layer in hot stamped high-strength steel sheet was composed of a diffusion layer and a compound layer. As the hot stamping temperature and holding time for forming increased, the thickness of the compound layer in the Al–Si coated high-strength steel sheet increased. The thickness of coating layer with the hot stamping for 500 sec at 890, 910 and 950 °C was obtained 8.9, 11.8, and 20.6 micrometer, respectively. The thickness of coating layer with hot stamping for 180, 500 and 550 sec at 910 ^oC was obtained 5.7, 11.8, and 17.8 micrometer, respectively. The compound layer in hot stamped high-strength steel sheet with Al–Si coating layer consists of Al_5.4Fe₂ and Fe₂Si phases. In the compound layer, Al and Si were irregularly distributed.

Intermetallic alloys like e.g. Iron-Aluminides, Titanium-Aluminides or Molybdenum- Silizides are prospective materials for high-temperature applications. For additive manufacturing (AM) intermetallic structural materials are particularly challenging due to their high melting points, oxygen susceptibility and low temperature brittleness. The feasibility of manufacturing intermetallic Mo-Si-B alloys with the laser additive manufacturing process of direct energy deposition (DED) is demonstrated and recent results in characterizing rapidly solidified material with respect to correlations between process, composition and microstructures are presented. The possibility to dope the material with Yttrium oxide (Y2O3) for dispersion is successfully demonstrated. Current challenges, e.g. homogenous distribution of alloying elements and applicability are addressed.

A high-performance Lead-free Piezoelectric Energy Harvester (LPEH) based on a Ba0.85Ca0.15Ti0.90Zr0.10O3 + CuO 0.3 wt% (BCTZC0.3) composite was fabricated by sintering at 1450℃. The BCTZC0.3 composite, which has an enhanced high-energy-conversion constant (〖d_33×g〗_33), shows improved piezoelectric power-generation performance when compared with conventional piezoelectric energy harvesters. The BCTZC0.3-based LPEH produces instantaneous maximum power of 8.2 mW and an energy density of 107.9 mW/cm3 in a weak magnetic field of 250 μT. This energy harvester can be used to charge a capacitor and operate a wireless sensor network (WSN) system to provide temperature sensing and radio-frequency (RF) transmission in a 250 μT magnetic field. The proposed LPEH is a promising green-energy device for potentially self-powering WSN systems when applied.

This paper describes the packaging models that are fundamental for the design of ultra-high-performance concrete (UHPC), and their evolution. They are divided into two large groups: continuous and discrete models. The latter are those that provide the best answer in obtaining an adequate simulation of the packing of the particles up to nanometric size. This includes the interaction among the particles by means of loosening and wall coefficients, allowing a simulation of the virtual and real compactness of such particles. In addition, a relationship between virtual and real compactness is obtained, through the compaction index, which may simulate the energy of compaction that the particles undergo in their placement in the mold. The use of last-generation additives allows such models to be implemented with water-cement (w/c) ratios close to 0.18. However, the premise of maximum packing as a basic pillar for the production of UHPC should not be the only one. The cement hydration process affected by nanoadditions and the ensuing effectiveness in the properties in both fresh and hardened state according to the respective percentages in the mixture should also be studied. An adequate ratio and proportion of these additions may lead to an obtaining of better results even with lower levels of compactness.

Concrete has become the most common construction material showing among other advantages good behaviour when subjected to high temperatures. Nevertheless, concrete is usually reinforced with elements of other materials such as steel in the form of rebars or fibres. Thus, the behaviour under high temperatures of these other materials can be critical for structural elements. In addition, concrete spalling occurs when concrete is subjected to high temperature due to internal pressures. Micro polypropylene fibres (PP) have shown to be effective for reducing such spalling although this type of fibres barely improve any of the mechanical properties of the element. Hence, a combination of PP with steel rebars or fibres can be effective for the structural design of elements exposed to high temperatures. New polyolefin fibres (PF) have become an alternative to steel fibres. PF meet the requirements of the standards to consider the contributions of the fibres in the structural design. However, there is a lack of evidence about the behaviour of PF and elements made of polyolefin fibre reinforced concrete (PFRC) subjected to high temperatures. Given that these polymer fibres would be melt above 250 °C, the behaviour in the intermediate temperatures was assessed in this study. Uni-axial tests on individual fibres and three-point bending tests of PFRC specimens were performed. The results have shown that the residual load-bearing capacity of the material is gradually lost up to 200 °C, though the PFRC showed structural performance up to 185°C.

We are concerned with the use of some classical spectral collocation methods as well as with the new software system Chebfun in order to compute high order (index) eigenpairs of singular as well as regular Schrodinger eigenproblems. We want to highlight both the qualities as well as the shortcomings of these methods and evaluate them vis-a-vis the usual ones. In order to resolve a boundary singularity we use Chebfun with the simple domain truncation technique. Although this method is equally easy to apply with spectral collocation, things are more nuanced in the case of these methods. A special technique to introduce boundary conditions as well as a coordinate transform which maps an unbounded domain to a nite one are the ingredients. A challenging set of "hard" benchmark problems, for which usual numerical methods (f. d., f. e. m., shooting etc.) fail, are analysed. In order to separate "good"and "bad"eigenvalues we estimate the drift of the set of eigenvalues of interest with respect to the order of approximation and/or scaling of domain parameter. It automatically provides us with a measure of the error within which the eigenvalues are computed and a hint on numerical stability. We pay a particular attention to problems with almost multiple eigenvalues as well as for problems with a mixed (continuous) spectrum. In the latter case we try to numerically highlight its existence. Special attention will be paid to the higher eigenpairs (the pair of eigenvalue and the corresponding eigenfunction approximated by an eigenvector spanning its nodal values).

Based on electromagnetic heat transfer and metal phase transformation co-simulations, we modeled an AISI 1045 specimen under high-frequency heat treatment. Hardening zone predictions were confirmed through cooling and metal phase transformation simulations after obtaining the results from electromagnetic heat transfer simulations. The cooling process was modeled by applying the cooling coefficient of the cooling water in the same way as the actual heat-treatment process. To obtain the current flowing through the coil during high-frequency induction heating, the voltage was measured and applied using the resistance–inductance–capacitance circuit calculation method. Experimental and simulated results of the heating temperature and curing depth of an AISI 1045 specimen with a carbon content of 0.45% were compared; the comparison indicated good agreement between the two. Using the simulation results, we established a method for obtaining the current flowing through the induction coil for predicting the extent and depth of the hardening zone during high-frequency induction heat treatment.

The response of the Cold-Electron Bolometers (CEBs), integrated into a 2-D array of dipole antennas, has been measured by irradiation from YBa$_2$Cu$_3$O$_{7-\delta}$ (YBCO) 50 $\mu$m long Josephson junction into the THz region at frequencies from 0.1 to 0.8 THz. The possibility of controlling the amplitude-frequency characteristic is demonstrated by the external magnetic field in the traveling wave regime of a long Josephson junction. YBCO junction has been formed on the bicrystal Zr$_{1-x}$Y$_x$O$_2$ (YSZ) substrate by magnetron sputtering and etching of the film. CEBs have been fabricated using an Al multilayer structure by a self-aligned shadow evaporation technique on Si substrate. Both receiver and oscillator have been located inside the same cryostat at 0.3K and 2.7K plates, respectively.

In bioprocess development, the host and the genetic construct for a new biomanufacturing process are selected in the early developmental stages. This decision, made at the screening scale with very limited information about the performance of the selected cell factory in larger reactors, has a major influence on the performance of the final process. To overcome this, scaledown approaches are essential to run screenings that show the real cell factory performance at industrial like conditions. We present a fully automated robotic facility with 24 parallel mini-bioreactors that is operated by a model based adaptive input design framework for the characterization of clone libraries under scale-down conditions. The cultivation operation strategies are computed and continuously refined based on a macro-kinetic growth model that is continuously re-fitted to the available experimental data. The added value of the approach is demonstrated with 24 parallel fed-batch cultivations in a mini-bioreactor system with eight different Escherichia coli strains in triplicate. The 24 fed-batches ran under the desired conditions generating sufficient information to define the fastest growing strain in an environment with varying glucose concentrations similar to industrial scale bioreactors.

Abstract The COVID-19 pandemic is thought to began in Wuhan, China in December 2019. Mobility analysis identified East-Asia and Oceania countries to be highly-exposed to COVID-19 spread, consistent with the earliest spread occurring in these regions. However, here we show that while a strong positive correlation between case-numbers and exposure level could be seen early-on as expected, at later times the infection-level is found to be negatively correlated with exposure-level. Moreover, the infection level is positively correlated with the population size, which is puzzling since it has not reached the level necessary for population-size to affect infection-level through herd immunity. These issues are resolved if a low-virulence Corona-strain (LVS) began spreading earlier in China outside of Wuhan, and later globally, providing immunity from the later appearing high-virulence strain (HVS). Following its spread into Wuhan, cumulative mutations gave rise to the emergence of an HVS, known as SARS-CoV-2, starting the COVID-19 pandemic. We model the co-infection by an LVS and an HVS, and show that it can explain the evolution of the COVID-19 pandemic and the non-trivial dependence on the exposure level to China and the population-size in each country. We find that the LVS began its spread a few months before the onset of the HVS, and that its spread doubling-time is $\sim 1.59\pm 0.17$ times slower than the HVS. Although more slowly spreading, its earlier onset allowed the LVS to spread globally before the emergence of the HVS. In particular, in countries exposed earlier to the LVS and/or having smaller population-size, the LVS could achieve herd-immunity earlier, and quench the later-spread HVS at earlier stages. We find our two-parameter (the spread-rate and the initial onset time of the LVS) can accurately explain the current infection levels (R^2$\mathrm{=0.74}$; correlation p-value (p) of 5x10^-13$$). Furthermore, countries exposed early should have already achieved herd-immunity. We predict that in those countries cumulative infection levels could rise by no more than 2-3 times the current level through local-outbreaks, even in the absence of any containment measures. We suggest several tests and predictions to further verify the double-strain co-infection model and discuss the implications of identifying the LVS.

The rhizosphere fungal community can play an important role in determining plant growth and health. In this study, using high-throughput sequencing, we investigated the fungal diversity and community composition in the roots and rhizosphere soil of 21 potato (Solanum tuberosum L.) cultivars. The samples were collected at three different sampling points. Furthermore, we assessed the differences in both diversity and composition of pathogen and saprotroph communities. In soil and roots, the fungal richness and relative abundance of pathogens and saprotrophs were mainly affected by sampling time. However, root fungal communities were also significantly affected by cultivar. The most substantial effect of cultivar was on root pathogen diversity. Moreover, the occurrence of most pathogens strongly varied among cultivars. Soil fungal community composition was primarily determined by sampling time; whereas in roots, the primary determinant was cultivar. Our results demonstrate changes in fungal communities over the potato growing season, as well as highlight the importance of potato cultivar on root fungal communities, and emphasise their importance in plant breeding.

Uniform illumination is a key requirement in different research fields. However, this requirement is often difficult to achieve when high intensity is required at the same time. Recent advancements in LED lamps allow nowadays for compact and economical solutions. In this work we present a suitable solution for various laboratory purposes requiring stable, uniform and high intensity illumination. The system is composed of four identical high power white LED arrays of 30 mm diameter each, placed on a supporting and cooling structure having a minimum volume of 26 cm x 26 cm x 8 cm. A numerical model has been developed, based on a ray tracing software, in order to simulate the performances. These have then been experimentally validated with measurements of the power density map, carried out with a 1% uncertainty pyranometer. Data show that the built system is very stable over time and provides an illumination uniformity higher than 98%, on a surface of 50 mm radius, which reduces to 95% on a surface of 75 mm radius. The power density can be adjusted in the 390-1360 W m-2 range, not affecting uniformity.

Diurnal and seasonal changes of abiotic environmental factors shape plant performance and distribution. Changes of growth temperature and light intensity may vary significantly on a diurnal, but also on a weekly or seasonal scale. Hence, acclimation to a changing temperature and light regime is essential for plant survival and propagation. In the present study, we analyzed photosynthetic CO₂ assimilation and metabolic regulation of the central carbohydrate metabolism in two natural accessions of Arabidopsis thaliana originating from Russia and south Italy during exposure to heat and a combination of heat and high light. Our findings indicate that it is hardly possible to predict photosynthetic capacities to fix CO₂ under combined stress from single stress experiments. Further, capacities of hexose phosphorylation were found to be significantly lower in the Italian than in the Russian accession which could explain an inverted sucrose-to-hexose ratio. Together with the finding of significantly stronger accumulation of anthocyanins under heat/high light these observations indicate a central role of hexokinase activity in stabilization of photosynthetic capacities within a changing environment.

A tunable quantum cascade laser (QCL) spectrometer was used to develop methods for detecting and quantifying high explosives (HE) in soil based on multivariate analysis (MVA) and artificial intelligence (AI). For quantification, mixes of 2,4-dinitrotoluene (2,4-DNT) with concentrations from 0% to 20% w/w were investigated using three types of soils: bentonite, synthetic soil, and natural soil. A Partial least squares regression model was generated for predicting 2,4-DNT concentrations. To increase its selectivity, the model was trained and evaluated using additional analytes as interferences, including other HEs such as PETN, RDX, and TNT and non-explosives such as benzoic acid and ibuprofen. For detection, mixes of different explosives in soils were used to implement two AI strategies. In the first strategy, the spectra of the samples were compared with those of soils recorded in a database to identify the most similar soils based on QCL spectroscopy. Next, a Classical Least Squares preprocessing (Pre-CLS) was applied to soils spectra selected from the database. The parameter obtained based on the sum of the weights of Pre-CLS was then used to generate a simple binary discrimination model for distinguishing between contaminated and uncontaminated soils, achieving an accuracy of 0.877. In the second AI strategy, the same parameter was added to a principal component matrix obtained from spectral data of samples and used to generate multi-classification models based on different machine learning algorithms. A Random Forest model worked best with 0.997 accuracy and allowing to distinguish between soils contaminated with DNT, TNT, or RDX and uncontaminated soils.

We report on the application of femtosecond laser micromachining to the fabrication of complex glass microdevices, for high-order harmonic generation in gas. The three-dimensional capabilities and extreme flexibility of femtosecond laser micromachining allow us to achieve accurate control of gas density inside the micrometer interaction channel. This device gives a considerable increase in harmonics generation efficiency if compared with traditional harmonic generation in gas jets. We propose different chip geometries that allow to control the gas density and driving field intensity inside the interaction channel to achieve quasi-phase matching conditions in the harmonic generation process. We believe that these glass micro-devices will pave the way to future downscaling of High-order Harmonic Generation beamlines.

In the present paper, an aerodynamic investigation of a high-speed train is performed. In the first section of this article, a generic high-speed train against a turbulent flow is simulated, numerically. The Reynolds-Averaged Navier-Stokes (RANS) equations combined with the SST turbulence model are applied to solve incompressible turbulent flow around a high-speed train. Flow structure, velocity and pressure contours and streamlines at some typical wind directions are the most important results of this simulation. The maximum and minimum values are specified and discussed. Also, the pressure coefficient for some critical points on the train surface is evaluated. In the following, the wind direction influence the aerodynamic key parameters as drag, lift, and side forces at the mentioned wind directions are analyzed and compared. Moreover, the effects of velocity changes (50, 60, 70, 80 and 90 m/s) are estimated and compared on the above flow and aerodynamic parameters. In the second section of the paper, various data-driven methods including Gene Expression Programming (GEP), Gaussian Process Regression (GPR), and random forest (RF), are applied for predicting output parameters. So, drag, lift and side forces and also minimum and a maximum of pressure coefficients for mentioned wind directions and velocity are predicted and compared using statistical parameters. Obtained results indicated that RF in all coefficients of wind direction and most coefficients of free stream velocity provided the most accurate predictions. As a conclusion, RF may be recommended for the prediction of aerodynamic coefficients.

This paper presents the systematic development and performance characterization of a non-proprietary 3D-printable ultra-high-performance fiber-reinforced concrete (UHPFRC) for digital construction. Several fresh and hardened properties of the developed 3D-printable UHPFRC matrix (without fiber) and composite (with 2% volume fraction of steel fibers) were evaluated and compared to that of conventionally mold-cast UHPFRC. Additionally, the effects of testing direction on the compressive and flexural strengths of the printed UHPFRC were investigated. The fresh properties of the UHPFRC developed in this study satisfied the criteria for extrudability, buildability, and shape-retention-ability, which are relevant for ensuring printability. The printed UHPFRC exhibited superior flexural performance to the mold-cast UHPFRC due to alignment of the short fibers in the printing direction. The high compressive and flexural strengths, along with the deflection-hardening behavior, of the developed UHPFRC can enable the production of thin 3D-printed components with significant reduction or complete elimination of conventional steel bars.

This paper presents the microstructural and mechanical properties of low and medium carbon advanced high-strength forging steels developed based on the third generation advanced high-strength sheet steels, in conjunction with those of conventional high-strength forging steels. Hot-forging followed by an isothermal transformation process considerably improved the mechanical properties of the forging steels. The improvement mechanisms of the mechanical properties were summarized by relating to the matrix structure, the strain-induced transformation of metastable retained austenite and/or a mixture of martensite and austenite.

Background: Multifunctional nanoparticles are known for their wide range of biomedical applications. Controlling the magnetic properties of these nanoparticles is imperative for various applications, including therapeutic angiogenesis. The study was performed to evaluate the magnetic properties and their control mechanisms by the external magnetic field. Methods: A 100nm magnetic nanoparticle was placed in the magnetic field, and parametrically the magnet field strength and distance was evaluated. Various models of magnetic strength and disposition were evaluated. Magnetic flux density, force/weight, and magnetic gradient strength were the parameters evaluated in electromagnetic computational software. Results: The seven-coil method with three centrally placed coils as Halbach array, and each coil with a flux density of 7 Tesla, and with a coil dimension of 20cmx20cm (square model) of each coil showed a good magnetic strength and force/weight parameters in a distance of 15cm from the centrally placed coil. The particles were then evaluated for their motion characteristics in saline. It showed good displacement and acceleration properties. After that, the particles were theoretically assessed in a similar mathematical model after parametrically correcting the drag force. After application of high drag forces, the particles showed adequate motion characteristics. When the particle size was reduced further, the motion characteristics were preserved even with high drag forces. Conclusion: There is potential for a novel method of controlling multifunctional magnetic nanoparticles using high magnetic fields. Further studies are required to evaluate the motion characteristics of these particles in-vivo and invitro.

Increasing salt intake has substantial negative impacts on health and well-being. This review article focusses on the effect of salinity intrusion (SI) on the water quality and community health of coastal Bangladesh and to find out the effectiveness of interventions for reducing the negative effects of salinity. Saline water is a noteworthy reason for hypertension or high blood pressure in the coastal areas. Health status of women especially the pregnant women are vulnerable because of drinking water sodium (DWS) prompting to pre-eclampsia, high blood pressure and hypertension as well as infant mortality. Several interventions such as rainwater harvesting and Pond sand filter (PSF) system as well as managed aquifer recharge (MAR) usage and the integration of mixed sources were reviewed on the content of drinking water sodium (DWS). Although rainwater has the positive impact of low or no sodium intake on human health, it still possesses negative impacts from not having vital minerals. Despite what might be expected, in MAR a steady increment in sodium concentration through the span of the dry season was observed. It is, subsequently, important to increase awareness about drinking water sodium (DWS) intake by providing and adopting correct technological interventions.

The increased consumption of high fat-containing foods has been linked to the prevalence of obesity and abnormal metabolic syndromes. Rhizopus oligosporus, a fungus in the family Mucoraceae, is widely used as a starter for homemade tempeh. Although R. oligosporus can prevent the growth of other microorganisms, it grows well with lactic acid bacteria (LAB). Lactobacillus plantarum can produce β-glucosidase, which catalyzes the hydrolysis of glucoside isoflavones into aglycones (with greater bioavailability). Therefore, the development of a soybean-based functional food by the co-inoculation of R. oligosporus and L. plantarum is a promising approach to increase the bioactivity of tempeh. In this study, the ameliorative effect of L. plantarum in soy tempeh on abnormal carbohydrate metabolism in high-fat diet (HFD)-induced hyperglycemic rats was evaluated. The co-incubation of L. plantarum with R. oligosporus during soy tempeh fermentation reduced the homeostatic model assessment of insulin resistance, HbA1c, serum glucose, total cholesterol, triglyceride, free fatty acid, insulin, and low-density lipoprotein contents and significantly increased the high-density lipoprotein content in HFD rats. It also increased the LAB counts as well as the bile acid, cholesterol, triglyceride, and short-chain fatty acid contents in the feces of HFD rats. Our results suggested that the modulation of serum glucose and lipid levels by LAB occurs via alterations in the internal microbiota, leading to the inhibition of cholesterol synthesis and promotion of lipolysis. Tempeh, produced with both L. plantarum and R. oligosporus, may be a beneficial dietary supplement for individuals with abnormal carbohydrate metabolism.

Integrated ultra-low-loss waveguides are highly desired for integrated photonics to enable applications that require long delay lines, high-Q resonators, narrow filters, etc. Here we present an ultra-low-loss silicon waveguide on 500 nm thick SOI platform. Meter-scale delay lines, million-Q resonators and tens of picometer bandwidth grating filters are experimentally demonstrated. We design a low-loss low-reflection taper to seamlessly integrate the ultra-low-loss waveguide with standard heterogeneous Si/III-V integrated photonics platform to allow realization of high-performance photonic devices such as ultra-low-noise lasers and optical gyroscopes.

The purpose of this study is to investigate the moderating effect of technology configuration capability on the relationship between strategic flexibility and organizational performance through different stages of technological life cycle. Through the empirical research on the 439 Chinese high-tech organizations, it shows that a technological configuration capability has enhanced the effect of strategic flexibility to the organizational performance in the complex dynamic environment. However, the impact on the different stages of technological life cycle is different. In addition, this paper explored strategic flexibility on different stages of technological life cycle on the basis of empirical study.

In networked driving simulation, two or more human drivers participate interactively within a shared virtual environment. Thereby, typical applications of driving simulation can be extended to consider multi-driver scenarios, where a much closer approximation of reality with its unpredictability is achieved. However, the utilized network is typically prone to a considerable amount of message traffic. In addition to restricted system scalability, the resulting degradation of network performance leads to invalid simulation outcomes or unacceptable system behavior. High-level architecture (HLA) is an IEEE standard for networked simulation. Data distribution management (DDM) is one of the service groups provided by HLA standard. The aim of the DDM service is to reduce network traffic and to save effort required to process unnecessary received data. However, different approaches for current DDM implementations show major drawbacks in terms of utilization complexity, inefficiency, and yet added network overhead. This paper presents a concept of an interest manager that takes over the DDM functionality and avoids these drawbacks. Simulation data is exchanged between the participating driving simulators only when it is necessary according to the driving situations. The concept is validated by analyzing the network load of two driving maneuvers with and without the interest manager.

Semantic image segmentation has recently witnessed considerable progress by training deep convolutional neural networks (CNNs). The core issue of this technique is the limited capacity of CNNs to depict visual objects. Existing approaches tend to utilize approximate inference in a discrete domain or additional aides and do not have a global optimum guarantee. We propose the use of the multi-label manifold ranking (MR) method in solving the linear objective energy function in a continuous domain to delineate visual objects and solve these problems. We present a novel embedded single stream optimization method based on the manifold ranking (MR) model to avoid approximations without sacrificing expressive power. In addition, we propose a novel network, which we refer to as dual multi-scale manifold ranking (\textbf{DMSMR}) network, that combines the dilated, multi-scale strategies with the single stream MR optimization method in the deep learning architecture to further improve the performance. Experiments on high resolution images, including close-range and remote sensing datasets, demonstrate that the proposed approach can achieve competitive accuracy without additional aides in an end-to-end manner.

Aerial image classification has become popular and has attracted extensive research efforts in recent decades. The main challenge lies in its very high spatial resolution but relatively insufficient spectral information. To this end, spatial-spectral feature extraction is a popular strategy for classification. However, parameter determination for that feature extraction is usually time-consuming and depends excessively on experience. In this paper, an automatic spatial feature extraction approach based on image raster and segmental vector data cross-analysis is proposed for the classification of very high spatial resolution (VHSR) aerial imagery. First, multi-resolution segmentation is used to generate strongly homogeneous image objects and extract corresponding vectors. Then, to automatically explore the region of a ground target, two rules, which are derived from Tobler’s First Law of Geography (TFL) and a topological relationship of vector data, are integrated to constrain the extension of a region around a central object. Third, the shape and size of the extended region are described. A final classification map is achieved through a supervised classifier using shape, size, and spectral features. Experiments on three real aerial images of VHSR (0.1 to 0.32 m) are done to evaluate effectiveness and robustness of the proposed approach. Comparisons to state-of-the-art methods demonstrate the superiority of the proposed method in VHSR image classification.

The present work investigates primarily the morphology evolution of the body-centered-cubic (BCC)/B2 phases in AlxNiCoFeCr high-entropy alloys (HEAs) with increasing Al content, which has been neglected so far. There exist two types of microscopic morphologies of BCC and B2 phases in this HEA series: one is the weave-like morphology induced by the spinodal decomposition, and the other is the microstructure of a spherical disordered BCC precipitation on the ordered B2 matrix that appears in HEAs with a much higher Al content. The shape of coherent precipitates is found to be closely related to the lattice misfit between BCC and B2 phases, which is sensitive to Al. The mechanical properties, including the compressive yielding strength and microhardness of the AlxNiCoFeCr HEAs, are also discussed in light of the concept of the valence electron concentration (VEC).

A space charge density wireless measurement system based on the idea of distributed measurement is proposed for collecting and monitoring the space charge density in an ultra-high-voltage direct-current (UHVDC) environment. The proposed system architecture is composed of a number of wireless nodes connected with space charge density sensors and a base station. The space charge density sensor based on atmospheric ion counter method is elaborated and developed, and the ARM microprocessor and Zigbee radio frequency module are applied. The wireless network communication quality and the relationship between energy consumption and transmission distance in the complicated electromagnetic environment is tested. Based on the experimental results, the proposed measurement system demonstrates that it can adapt to the complex electromagnetic environment under the UHVDC transmission lines and can accurately measure the space charge density.

There is a growing interest among researchers in the creation of innovative power supply systems that incorporate a range of generators, with a specific emphasis on renewable energy sources, especially wind energy. Battery-operated independent Microgrids powered by wind energy are increasingly recognized worldwide as a standalone power source for consumers. The power produced by the wind power conversion system depends on the wind speed, which can change quickly and without warning. It is essential to establish a robust energy management system accompanied by a responsive control approach to attain optimal energy balance and guarantee the delivery of high-quality power. In order to facilitate a rapid and efficient reaction to unexpected variations in the power supply system, the control strategy for the inverter and bidirectional DC to DC converter employs super twisting sliding mode controllers. The voltage at the DC link is controlled to maintain energy equilibrium within the standalone Microgrid, while a distinctive control approach for the three-phase inverter guarantees the delivery of high-quality power to AC loads. The proposed control methodologies in this paper employ super twisting sliding mode controllers to achieve rapid and effective responses during rapid changes in the system, whether on the generation or load side. The Hippopotamus optimization method is developed to obtain accurate values of various parameters used in super twisting sliding mode controllers under various operating conditions. The paper emphasizes the diverse outcomes and knowledge acquired through the execution of Hardware-in-the-Loop simulations utilizing the OPAL-RT platform. By employing this cutting-edge technology, researchers successfully tested and validated various hardware components within a simulated environment, facilitating a more efficient and cost-effective approach to analyzing and optimizing system performance. Further, detailed small signal analysis for the proposed methodology is also included in this paper.

Volunteering among older adults in the United States is rising, with rates up by 65% since 1974. With this tremendous growth in volunteering among seniors, examining how it affects them is essential. One such volunteering program we look at in this research is the Foster Grandparents Program (FGP) of the High Country, which allows older adults to volunteer at local schools to help in-need children. Previous research has shown how volunteering as an older adult positively impacts people's quality of life. This paper will explore the quality-of-life changes for the FGP older adult volunteers, explicitly comparing the quality-of-life changes with demographics and program satisfaction. This study looked at 93 participants of the FGP and their survey responses. We used cross-tabulation and correlation to look for relationships between demographics, satisfaction with volunteer experience, and overall changes in the quality-of-life of volunteers. Age, gender, and years of service were not good predictors of quality-of-life changes. On the other hand, overall satisfaction with the program proved to be the best predictor for change in quality of life. When satisfaction with positive program experiences is high, volunteers are more likely to have less symptoms of depression, state they have a greater sense of belonging to a community and were able to build a positive identity for themselves, all of which impacted their overall quality-of-life.

Knowledge on river quality variations and of exceeding quality limits is essential for the allocation of water to different uses and for applying remedial measures. Thessaly plain was extremely fertile, and up until the early 20th century the area was a breadbasket for Greece. The highly important for the national agricultural production, albeit severely degraded Pinios river, has been assessed for its Chemical-Physicochemical (C-P) status, based on the results of the National Monitoring Program for the years 2018-2020, considering 218 seasonal samples. Forty percent (40%) of the total sample number, and 70% of the 30 monitoring stations revealed a lower than good C-P status, predominately as a result of elevated phosphate, total phosphorous and nitrate concentrations. Exceptionally, the Pinios river seems to be predominately affected by point sources of organic pollution, and secondarily by agricultural return flows and land flushing processes, whereas dominant mineralization and nitrification processes control the concentration and speciation of N and P compounds. The COVID lock-down seems not to have affected aquatic quality through an increase of WWT effluents or/and diminishing of atmospheric pollution, whereas the improvement of C-P status at the river outflow via dilution by local mountain springs is threatened by an ongoing dry spell affecting the country. Within the upcoming RBMPs, urgent remediation measures in Pinios basin should both target point sources of pollution and control agrochemicals, particularly focusing on adaptation strategies on extreme weather events.

When predicting the health impacts of PM2.5 from future air quality changes, it’s crucial to consider both air quality improvements and population aging. This study divided future emission scenarios into a Base and Control scenario to project air quality from 2015 to 2030 and assess health outcomes. The GUIDE model, an Integrated Assessment Model (IAM), was used to estimate future emissions, while the CMAQ (Chemical Transport Model) and BenMAP (Health Impact Model) evaluated health impacts resulting from changes in air quality in Korea. The study focused on the impact of population aging on future health outcomes. Both scenarios showed improved PM2.5 concentrations, with the Control scenario seeing more substantial improvements due to stronger policy measures. When applying current age patterns, health impacts decreased as PM2.5 concentrations. However, when considering future population aging, health impacts increased despite improved air quality. This finding suggests that, although PM2.5 concentrations are expected to decline, the increasing proportion of elderly individuals will exacerbate health risks. Therefore, accounting for aging population trends is essential when studying the health impacts of future air quality changes.

As a result of the low organic matter content of the sandy soils in Romania, for the success of most crops, large amounts of chemical fertilizers are needed, which can often lead to the pollution of groundwater with nitrates, given the poor hydrophysical properties in terms of retaining chemical elements by these soils. In this sense, the study carried out in the period 2020-2023 within the rotation cowpea-rye+cowpea successive crop-sorghum for grains, aimed to promote the system of sustainable agriculture, by incorporating into the soil, in the form of green manure, the cowpea sown in succession after the rye. The soil quality analyses, carried out the following year after harvesting sorghum for grains, showed that by incorporating 52.4 t/ha of cowpea biomass into the soil between October 15-20, the quality characteristics of the sandy soil improved significantly. Thus, compared to the initial state of soil fertility, there were annual increases of 0.017-0.029%, in total nitrogen, by 9.5-13.3 ppm, in extractable phosphorus, by 11.333-24 ppm, in exchangeable potassium and by 0.008-0.012%, to organic carbon, also depending on the sorghum fertilization system. Also, the incorporation of green cowpea manure into the soil contributed to reducing the acidity of the soil pH and improving the water holding capacity of the soil profile.

Nanopore raw read accuracy has improved to over 99%, making it a potential tool for metabarcoding. For broad adoption, guidelines on quality filtering are needed to ensure reliable taxonomic unit recovery. This study aims to provide those guidelines for a fungal metabarcoding context and to apply them to a case-study of ectomycorrhizae in decaying bark of Fagus sylvatica.We introduce the eNano pipeline to test two standard metabarcoding approaches: (1) reference-based mapping leveraging the UNITE’s species hypothesis system (SH-approach) and (2) constructing 98% OTUs (OTU-approach). We evaluate these approaches using a mock and natural community. Our results demonstrate that both approaches are effective with Nanopore data. When using a reference database, we recommend strict mapping criteria rather than Phred-based filtering. For 98% OTUs, filtering reads at ≥Q25 is recommended. Our case-study reveals that the decay gradient is a primary determinant of community composition, and that specific mycorrhizal fungi colonize decaying bark. Complementing our metabarcoding results with root tip morphotypification, we identify Laccaria amethystina and Tomentella sublilacina as key ectomycorrhizae of saplings on decaying logs. These findings demonstrate that Nanopore sequencing can provide valuable ecological insights and support its broader use in fungal metabarcoding as read quality continues to improve.

Statistics modules are included in most university degrees, independent of the degree area. They have an important role in preparing students for the real world. The overall goal of this paper is to identify the common statistical issues students face during the transition from secondary education to tertiary education. Drawing upon data from the University College Dublin (UCD) Math Support Center (MSC) and Universidad Rey Juan Carlos (URJC), our approach aims to optimize learning experiences while advancing sustainability objectives. In this paper, we conducted a categorization of statistical concepts taught in university (based on URJC). Using this categorization, UCD MSC tutor comments were categorized and validated, and subsequently descriptive analyses and text mining were used on the UCD MSC comments to achieve a deeper understanding of the statistical issues. Building on this study, we plan to develop a suite of evidence-based sustainable educational applications and games to support undergraduate students internationally in first-and second-year statistical modules. Our findings on students’ main statistical issues contribute to the cultivation of lasting statistical literacy among students. This research advances the sustainability agenda within statistical education.

The Atlantic Canada Together Enhancing Acute Stroke Treatment (ACTEAST) project is a Modified Quality Improvement Collaborative (mQIC) designed to improve ischemic stroke treatment rates and time-based efficiency in Atlantic Canada. This study specifically evaluates the implementation of the mQIC in Nova Scotia using qualitative methods. The mQIC spanned six months and included two Learning Sessions, multiple webinars, and a per-site virtual visit. Each session was followed by an action planning period to guide implementation efforts over the following 2-4 months. The Consolidated Framework for Implementation Research (CFIR) was utilized to develop a pre-tested, semi-structured interview guide, which aimed to uncover barriers and facilitators to mQIC implementation. Interviews were conducted with 14 healthcare professionals, generating 454 references that were coded into 28 CFIR constructs. Notably, 84% of these references were positively framed as facilitators. Despite this, significant barriers were identified, including resource availability, competing priorities, communication challenges, and difficulties engaging key stakeholders. Some barriers were particularly prominent during specific phases of implementation. The study findings offer valuable insights into the implementation of quality improvement initiatives in stroke care. They underscore the importance of recognizing and addressing context-specific barriers, while also leveraging identified facilitators to drive successful implementation and ultimately improve patient outcomes.

Following the transfer of hospital services to provincial government oversight, it is essential to understand how such changes impact service quality and efficiency. This study aims to identify the factors affecting hospital service quality post-transfer and evaluate the role of professional nurses in maintaining service standards under new governance.We conducted the study at sub-district health-promoting hospitals using a mixed-methods design based on the Global Fund-HSS framework (2012), which categorizes factors into accessibility, processes, productivity, and outcomes. We collected data from 340 nurses and 400 patients using structured questionnaires. We divided the questionnaires into seven sections, which captured a range of metrics such as the personal data of nurses, hospital service activities, and leadership qualities. We employed a Likert scale to gauge perceptions and expectations of service quality. We used paired t-tests to compare performance metrics before and after the administrative transfer, one-way ANOVA to assess variability among different service units, and binary logistic regression to identify key determinants of service quality in our statistical analysis. The analysis revealed a significant correlation between the attitudes and competencies of healthcare teams and the levels of service quality. Notably, service units transferred less than 50% exhibited minimal changes, indicating that the degree of transfer significantly impacts service outcomes. Despite these variations, the fundamental mission of promoting health remained consistent. The study emphasizes the critical role of nurses and recommends further research to identify additional factors that could improve service quality in transferred healthcare facilities. This could contribute to improved healthcare delivery across restructured health systems.

Following the transfer of hospital services to provincial government oversight, it is essential to understand how such changes impact service quality and efficiency. This study, conducted from 1 March 2023 to 31 March 2024 at sub-district health-promoting hospitals in Thailand, aims to identify the factors affecting hospital service quality post-transfer and evaluate the role of profes-sional nurses in maintaining service standards under new governance. Utilizing a mixed-methods design based on the Global Fund-HSS framework (2012), which categorizes factors into accessibility, processes, productivity, and outcomes, we collected data from 340 nurses and 400 patients through structured questionnaires. These questionnaires were divided into seven sec-tions, capturing metrics such as the personal data of nurses, hospital service activities, and lead-ership qualities. We employed a Likert scale to gauge perceptions and expectations of service quality and conducted paired t-tests to compare performance metrics before and after the admin-istrative transfer. One-way ANOVA was used to assess variability among different service units, and binary logistic regression helped identify key determinants of service quality. The analysis revealed a significant correlation between the attitudes and competencies of healthcare teams and the levels of service quality. Notably, service units transferred less than 50% exhibited mini-mal changes, indicating that the degree of transfer significantly impacts service outcomes. Despite these variations, the fundamental mission of promoting health remained consistent. The study emphasizes the critical role of nurses and recommends further research to identify additional factors that could improve service quality in transferred healthcare facilities, potentially contributing to enhanced healthcare delivery across restructured health systems.

Milk consumption is crucial for a balanced diet, yet recent trends indicate a decline, especially in Italy. A significant factor in this decline is the altered perception of milk quality among consumers, creating a communication gap between them and other stakeholders. This study aimed to explore the discourse on social media and sentiment towards the concept of milk quality among consumers, farmers, and processors. The research adopted a Social Media Analysis to examine online community messages. A sample of 19,906 Italian comments and posts mentioning keywords Milk, Quality, Cow, and Vaccine was collected and categorized using term frequency analysis, correspondence analysis, and sentiment analysis. Results highlighted gaps in the perceptions of milk quality: farmers focused on economic issues, consumers on animal welfare and health, and processors on lactose content. For farmers, almost all comments were negative, while for processors, nearly all comments were positive. Consumers presented a more mixed picture. This work contributes to the literature by expanding research on milk quality using social media as a source of information. The findings suggest that enhancing communication and understanding among these groups could lead to more effective strategies for addressing consumer concerns, potentially reversing the declining of milk consumption.

This qualitative study explores the dynamics of customer satisfaction and supplier collaboration within Italian restaurant operations. Through in-depth interviews, participant observations, and document analysis, the research investigates key factors influencing these relationships. Trust and communication emerged as foundational elements, crucial for ensuring reliable ingredient supply and maintaining culinary authenticity. Quality and authenticity of ingredients were identified as primary drivers of customer satisfaction, underscoring the strategic role of suppliers in delivering superior dining experiences. Customer feedback played a pivotal role in shaping operational practices, highlighting the iterative process of adapting to customer preferences to enhance service delivery and loyalty. Emotional intelligence among managers facilitated effective supplier relationships, fostering collaborative partnerships and navigating operational challenges with empathy and skill. Economic considerations were vital in balancing cost efficiencies with quality standards, guiding strategic decisions in supplier management. Technological integration enhanced supply chain management, optimizing logistics and responsiveness to market demands. The adoption of sustainable sourcing practices reinforced restaurants’ commitment to environmental stewardship and community engagement, aligning with consumer preferences for ethical dining options. The findings suggest actionable insights for restaurant managers to optimize supplier collaborations, enhance operational efficiency, and sustain competitive advantage in the hospitality industry.

Sparkling wines elaborated by means Ancestral method, also called Pét-Nats, are nowadays gaining an increasing share of the market. However, the scientific information about these wines is very scarce. For that reason, the aim of this research was to compare the physicochemical composition and sensory attributes of a representative sampling of commercial sparkling wines elaborated by Ancestral and Traditional methods. Ancestral sparkling wines were more heterogenous than Traditional sparkling wines because some of them showed lower internal pressure, higher turbidity, higher colour intensity and less foamability. These differences would be probably because the ancestral elaboration protocol is not so well defined as in the case of Traditional sparkling wines. However, Ancestral method has the advantage of being able to work with riper grapes and with lower doses of sulphur dioxide.

Context: In Software Engineering, there must be clarity in communication among interested parts to elicit the requirements aimed at software development through frameworks to achieve the behaviors expected by the software. Problem: Lack of clarity in the requirements elicitation stage can impact subsequent stages of software development. Solution: We proposed a case study to achieve the proposed goal focusing on the performance efficiency characteristic expressed in the ISO/IEC/IEEE 25010 Standard using Behavior-Driven Development (BDD). Method: The case study was performed with professionals who use BDD to elicit the non-functional requirements of a company that develops software. Summary of Results: The results obtained were aspects related to the elicitation of non-functional requirements aimed at the performance efficiency characteristic of the ISO/IEC/IEEE 25010 Standard using BDD through the point of view of industry professionals. Contributions and impact: The article’s main contribution is to demonstrate the effectiveness of using BDD to elicit non-functional requirements about the performance efficiency characteristic of the ISO/IEC/IEEE 25010 Standard.

The aim of this study was to develop a ready-to-eat vegetable-herb mixes with high nutritional and sensory values, as well as good storability. In this regard the suitability of fresh herbs (peppermint, oregano, green basil, red basil, and parsley) was tested for use in mixes with fresh-cut iceberg lettuce. Lettuce-herb mixtures were stored for 6 days at 5°C. The reason for the decrease in the appearance of the salads was the browning of the cut surface of the lettuce, as well as discoloration on the cut herbs. Comparing the storage ability of cut herbs, red basil and parsley retained the best appearance for 6 d at 5 °C. A small addition of herbs to fresh-cut iceberg lettuce caused a significant increase in contents of pro-health ingredients in the mixes. There were large discrepancies in the sensory quality of the mixes, but the highest quality and consumer acceptance were found for salads with parsley (5% and 10%) and red basil (5%). After harvest, the fresh herbs were more contaminated by molds than the iceberg lettuce. Bacterial, yeast and mold contamination increased during storage, but the rate of mold growth was much lower in the mixes with parsley compared to lettuce alone.

Carbon monoxide (CO) is a colorless, odorless gas emitted from carbon fuel combustion. In this study we monitored indoor carbon monoxide (CO) levels for 120 homes over three seasons in the North Denver metropolitan region as part of an environmental justice initiative to quantify health and social well-being impacts from a major freeway construction upgrade nearby. Urban outdoor CO levels are typically very low (less than 1 ppm in Denver) due to air pollution control strategies and technologies implemented over the past several decades. However, people can still be exposed to higher than outdoor levels of CO in their homes due to the operation of indoor appliances that use carbon fuels such as natural gas. Our data show that ~10% of the homes had consistent daily average levels of CO above 3.5 ppm and 24-57% of the homes showed peaks greater than 9 ppm. While much higher levels can result in CO poisoning and fatalities, these lower levels of CO have been associated with adverse health impacts, especially pregnant women, and sensitive populations. Our results highlight the need for increasing awareness regarding CO exposures in homes with gas appliances and motivate the transition from non-electrified homes toward electrification.

The purpose of this research is to examine the benefits and limitations of implementation of novel digital academic advising systems using automated collection and reporting processes for ABET student outcomes data based on principles of authentic OBE for effective developmental advising. We examine digital developmental advising models of undergraduate engineering programs in two universities that employ customized features of the web-based software EvalTools® - Advising Module based on assessment methodology incorporating the Faculty Course Assessment Report, Performance Indicators and hybrid rubrics classified according to the affective, cognitive and psychomotor domains of Bloom’s learning model. A case study approach over a six-year period is adopted for this research. The two case studies present results of samples of developmental advising activity employing sequential explanatory mixed methods models using a combination of quantitative and qualitative analyses of a) detailed students’ outcomes and Performance Indicators information; and b) self-evaluation of their professional development and lifelong learning skills. The findings of this study show that digital advising systems employing the Faculty Course Assessment Report using Performance Indicators and hybrid rubrics can provide comprehensive and realistic outcomes data to help both developmental advisors and students easily identify the specific cause of performance failures, implement practical recommendations for remedial actions and track improvements. Inherent strong skills can also be identified in academically weak students by observing patterns or trends of relatively better performing outcomes to reinforce natural affinity for learning specialized competencies and pursue related and successful career paths.

Assessing observation noise is a critical step in the development of a stochastic model for GNSS navigation and positioning. This process ensures that the statistical properties of the observational data are accurately characterized, leading to more reliable and precise positioning results. Traditionally, the one sigma values for observation noise, 0.3 m for code and 3 mm for carrier phase, alongside elevation-dependent weighting schemes, have been standard. However, these may no longer be suitable due to significant advancements in GNSS systems, receivers, and antennas. Previous research predominantly focused on code type and PPP techniques, often limited by the inability to separately assess observation types across different frequency bands due to ionospheric delay. Furthermore, these studies were generally constrained by limited experimental data. This research advocates for the use of ultra-short baselines to eliminate atmospheric delay and other error sources, providing a detailed assessment of observation noise for various frequency bands, GNSS systems, and receiver & antenna types over an extensive period and across multiple baselines. The findings suggest a need to reconsider traditional one sigma values and elevation-dependent weighting schemes for current applications.

This paper presents a groundbreaking approach to real-time image processing in electronic component assembly, enhancing quality control in manufacturing. By capturing images from pick and place machines between component pickup and mounting, defects are identified and addressed in-line, significantly reducing the likelihood of defective products. Leveraging fast network protocols like gRPC and orchestration with Kubernetes, along with C++ programming and TensorFlow, this method achieves an average turnaround time of less than 5 milliseconds. Tested on 20 live production machines, it ensures compliance with IPC-A-610, and IPC-STD-J-001 standards while optimizing production efficiency and reliability.

Few young Japanese adults regularly consume a well-balanced diet composed of staples, course dishes, and sides. We hypothesised that adopting the recommended planetary health diet with regular breakfast consumption would promote well-balanced diets among young Japanese male undergraduates. This study aimed to examine the structural association between a planetary health diet with regular breakfast consumption and well-balanced diet intake. Participants were 142 male undergraduates who completed a 2022 online questionnaire via Google Forms in a cross-sectional study at a public university in Hyogo Prefecture. A planetary health diet comprises the consumption of the recommended eight items. A covariance structure analysis was performed in a hypothetical model with factors (regular breakfast consumption and eight items) potentially associated with the intake of a well-balanced diet at least twice daily. Acceptable goodness-of-fit was obtained by excluding chicken dishes and nuts from the eight recommended items of the planetary health diet. Frequent consumption of the remaining six recommended items (fish, eggs, soybeans/soybean products, dairy foods, vegetables, and fruits) was significantly positively correlated with regular breakfast consumption and a significant positive path to a well-balanced diet. Among male university students, regular breakfast consumption and a planetary health diet may lead to a well-balanced diet.

The quality prediction of quaternary structure models of a protein complex, in the absence of its true structure, is known as the Estimation of Model Accuracy (EMA). EMA is useful for ranking predicted protein complex structures and using them appropriately in biomedical research, such as protein-protein interaction studies, protein design, and drug discovery. With the advent of more accurate protein complex (multimer) prediction tools, such as AlphaFold2-Multimer and ESMFold, the estimation of the accuracy of protein complex structures has attracted increasing attention. Many deep learning methods have been developed to tackle this problem; however, there is a noticeable absence of a comprehensive overview of these methods to facilitate future development. Addressing this gap, we present a review of deep learning EMA methods for protein complex structures developed in the past several years, analyzing their methodologies and impacts. We also provide a prospective summary of some potential new developments for further improving the accuracy of the EMA methods.

Conducting quantitative research involving adolescents demands a thoughtful approach to the question of supervision, given that each option comes with its distinct set of implications. This study reviews these implications and empirically tests whether differences in data quality can be found among three modes of standardized survey research with medium sized groups of adolescents (12-17 years). Data basis is a quasi-experimental survey study testing different forms of digital, hybrid or in-person supervision, that took place in 2021 in secondary schools in Germany (N=923). Aim of this study is testing how aspects of data quality – item-nonresponse, interview duration, drop-out-rate and response patterns – differ between these forms of supervision. Results could help researchers surveying young people to decide (1) whether they allow confidants or other adults to be present during interviews, (2) if they can rely on teachers alone when surveying classrooms and (3) if it is cost-efficient to send out external supervisors for classroom sessions. While dropout-rates do not differ, item non-response, interview duration, and response patterns differ significantly, students supervised at home by external interviewers answered more questions, took more time to answer and are less likely to give potentially meaningless answers in grid questions. The implications drawn from the findings question the common approach to solely rely on teachers for survey administration without the support of external supervisors or adequate training. Recruiting respondents via schools and surveying them online in their homes during school hours shows to be a robust method with regard to the analyzed indicators.

This study has two main focuses: the first focus is to explore the design and the behavior of a locally built solar dryer during processing henna leaves. This was performed through the determination of the most important parameters that have effect on the drying process. Appropriately, it was found that the outlet air temperature of the solar collector depends entirely on the solar radiation, Moreover, the inlet temperature of the air to the drying chamber has also an important impact on the moisture content of the product. It was found that most of the studies dealing with solar drying do not take into consideration the quality of the final product. Accordingly, the second objective of this study is to present the effect of drying process on the quality of the drier samples. For this purpose, the bioactivity of the samples, in terms of determination of the total phenol content, total flavonoid content, and antioxidant activities was performed. Three different samples: fresh sample, samples dried with the presented solar dryer and open solar dried samples are tested. It was found that samples dried with the solar dryer presented the best results.

In precision grinding of hard and brittle materials, coarse-grained diamond grinding wheels are increasingly favored for their efficiency and contour accuracy. However, challenges in dressing these grinding wheels have hindered their widespread adoption. In this paper, the effects of dressing parameters on the surface profile and morphological characteristics of electroplated coarse-grained diamond were studied, thereby optimizing the dressing accuracy and dressing efficiency of the coarse-grained diamond grinding wheel. Models for the surface morphology of the large-grained diamond grinding wheel and its grinding surface were established. With a focus on optimizing dressing accuracy, we explored how the grain’s protruding height post-dressing affects the surface morphology of both the diamond grinding wheel and the grinding surface. The model’s accuracy was verified by electroplated coarse-grained diamond grinding wheel grinding experiments with different grain protrusion heights, and the causes of surface morphology formation were analyzed based on morphological characteristic parameters such as surface roughness and surface height difference. The results showed that compared with the undressed grinding wheel, the surface roughness Sa and Sq of the workpiece by the dressing wheel are reduced by 97.75%−99.77% and 97.57%−99.73%, respectively. Precision dressing enables the surface roughness of the electroplated coarse-grained diamond grinding wheel to reach nanometer levels, enhancing its feasibility and application potential.

Indoor comfort is a critical determinant of the holistic educational experience, significantly influencing the well-being, concentration, and performance of students within the confines of school environments. Despite the widespread implementation of heating, ventilation, and air conditioning (HVAC) systems in educational institutions, achieving satisfactory thermal conditions, acceptable acoustics, and optimal daylight levels for occupants continues to pose a considerable challenge. In this review, we specifically delves into the parameters characterizing Italian school environments, recognizing their direct impact on students’learning and concentration. The primary objectives of this review are conducting a thorough examination of the current acustic conditions in Italian schools. The initial phase of our search strategy involved retrieving data from key databases, namely, Scopus, Web of Science, ScienceDirect, PubMed, and Google Scholar. Following the elimination of duplicate articles (n = 289), a total of 135 distinct papers remained for analysis. A critical review of the existing literature is presented based on these criteria, offering guidelines and recommendations for forthcoming studies. The critical review underscores various shortcomings in the current design, deployment, and documentation of multi-domain studies, signaling the need for enhanced quality in future research efforts.

The study analyzed Ecuador's presence in the Web of Science (WoS) post-pandemic from a multivariate dynamic, highlighting a significant transformation in scientific communication towards open access (OA). The methodology integrated multivariate statistical techniques, using R and specialized tools, to process 9,085 relevant articles, 52% of the Ecuadorian publications in WoS between 2019 and 2021 were open access. This movement reflects a commitment to quality research and accessibility, showing an increase in publications and citations under OA. The research underscores the importance of establishing robust national OA policies in Ecuador to promote scientific collaboration and an equitable distribution of knowledge. Despite funding challenges and the lack of specific regulations, educational institutions in Ecuador have maintained a constant scientific output, adapting to the global environment and the demand for transparent information. The study concludes that there is an urgent need for a holistic approach to OA in the country, recognizing the progress made despite the difficulties.

This study explores the interplay between web-based professional development, teachers' self-efficacy, resilience, and work values in the context of the Davao Region. The investigation reveals significant findings in three key areas: web-based professional development, teachers' resilience, and teachers' work values. The survey indicates that web-based professional development significantly impacts teachers' self-efficacy, with interaction self-efficacy registering the highest mean score. Moreover, teachers' resilience is manifested across emotional, motivational, and social dimensions, with emotional resilience scoring the highest mean. Teachers' work values, encompassing physical facilities, social environment, job security, new challenges, professional growth, personal growth, and interpersonal relationships, all demonstrate high descriptive equivalents. The study establishes a significant positive correlation between web-based professional development and teachers' self-efficacy, as well as a significant relationship between teachers' resilience and their work values. Furthermore, both web-based professional development and teachers' resilience exert a significant influence on teachers' work values.The conclusions drawn from the study highlight the prominence of web-based professional development, teachers' resilience, and work values in the educational landscape of the Davao Region. The findings underscore the interconnectedness of these factors and their crucial role in shaping the teaching profession. In light of these results, recommendations are made to inform policy decisions and enhance professional development programs for teachers in the region. The study encourages a holistic understanding of the relationships between web-based professional development, self-efficacy, resilience, and work values, aiming to contribute to the continuous improvement of education quality in the Davao Region. Additionally, future research is suggested to delve deeper into specific aspects of teachers' general self-efficacy, social resilience, and interpersonal relationships for a more comprehensive understanding.

Children with epilepsy are affected by several factors, including clinical and social variables, which can lead to reductions in quality of life (QOL). Among these variables, factors relating to seizure severity such as frequent seizures and status epilepticus (SE) have been identified as important predictors of QOL. In addition, frequency of interictal epileptiform discharges (IEDs) on the electroencephalogram (EEG) may also lead to cognitive declines and behavioral disturbances. Moreover, frequent seizures and/or IEDs may play a role in emotional mediators such as stigma and fatigue in childhood epilepsy. Seizure severity and/or IEDs are thus important QOL-related factors in childhood epilepsy. Frontal lobe dysfunctions such as cognitive decline and behavioral disturbances can result in reduced QOL for both the child and their family. Frontal and prefrontal lobe growth disturbances can be present during active-phase epilepsy in some children with neuropsychological impairments. Recovery from prefrontal lobe growth disturbance may depend on the active seizure period. Disturbance of prefrontal lobe growth can recover more rapidly in children with a shorter active seizure period. In contrast, recovery may be delayed in children with a longer active seizure period. Accordingly, severe seizures can lead to neuropsychological impairments in association with prefrontal lobe growth disturbance in children with epilepsy. Moreover, frequent seizures can lead to having seizure-associated headache, perception of self-stigma and parental stigma, and fatigue. In addition, IEDs on EEG, representing persistent pathological neuronal discharges, may be associated with several pathological aspects. Frontal IEDs can be a risk factor for recurrent seizures, cognitive decline, and behavioral disturbances and may also play a role as an emotional mediator similar to stigma. In addition, behavioral disturbances may result in the presence of secondary bilateral synchrony (SBS) on EEG. Behavioral disturbances can be improved in association with reduction of IEDs in children with frontal IED and SBS. Seizure severity and IEDs on EEG may thus be associated with neuropsychological impairments, leading to QOL reduction. Therapeutic management may be desirable to remit seizures and EEG abnormalities such as frontal IED and SBS as soon as possible to improve QOL in children with epilepsy.

For two-dimensional forward-looking sonar imaging, high sidelobes significantly degrade the quality of sonar images. The cosine window function weighting method is often applied to suppress the sidelobe levels in the angular and range dimensions at the expense of the main lobe resolutions. Therefore, the improved spatially variant apodization imaging method for forward-looking sonar is proposed to reduce the sidelobes without degrading the main lobe resolution in angular-range dimensions. The proposed method is a nonlinear post-processing operation in which the raw complex-valued sonar image produced by a conventional beamformer and matched filter is weighted by a spatially variant coefficient. To enhance the robustness of the spatially variant apodization approach, the array magnitude and phase errors are calibrated to prevent beam sidelobe heightening from occurring prior to beamforming operations. The analyzed results of numerical simulations and a lake experiment demonstrate that the proposed method can greatly reduce the sidelobes to approximately -40 dB, while the main lobe width remains unchanged. Moreover, this method has an extremely simple computational process.

The Sarcoma Assessment Measure (SAM) was developed as a sarcoma-specific patient-reported outcome measure to be used in clinical practice. We have reported in detail how SAM has been developed in collaboration with patients and healthcare professionals. The aim of this paper is to report the preliminary validation of SAM. The 22-item SAM was administered alongside a validated quality of life questionnaire and measure of activities of daily living. Linear modelling was used to build a measure, which had predictive validity in comparison to more established outcome measures. Of the 762 patients who participated in the study, 44.1% identified as male, and participant age ranged from 13-82 years. Clinically, participants presented with a range of soft tissue (82.2%) and bone (21.8%) sarcomas. Our preliminary analysis indicates that SAM accounts for 35% of the Global quality of life scale and 18% of the TESS so psychometrically it overlaps with quality of life and activities of daily living, but also measures distinct concerns. This demonstrates that this measure picks up issues that are important to patients with sarcoma that are not reflected in other measures. We have established the preliminary validity of SAM and believe it has utility as a patient-reported outcome measure both as a research tool and for assessing the impact of symptoms and dysfunction related to sarcoma as part of clinical care. Further validation using a larger and more clinically diverse sample is now needed.

Estimating Visual Quality of Street Space (VQoSS) is pivotal for urban design, environmental sustainability, civic engagement, etc. Recent advancements, notably in deep learning, have enabled large-scale analysis. However, traditional deep learning approaches are hampered by extensive data annotation requirements and limited adaptability across diverse VQoSS tasks. Multimodal Large Language Models (MLLMs) have recently demonstrated proficiency in various computer vision tasks, positioning them as promising tools for automated VQoSS assessment. In this paper, we pioneer the application of MLLMs to VQoSS change estimation, with our empirical findings affirming their effectiveness. In addition, we introduce Street Quality GPT (SQ-GPT), a model that distills knowledge from the current most powerful but inaccessible (not free) GPT-4, requiring no human efforts. SQ-GPT approaches GPT-4’s performance and is viable for large-scale VQoSS change estimation. In a case study of Nanjin, we showcase the practicality of SQ-GPT and knowledge distillation pipeline. Our work promises to be a valuable asset for future urban studies research.

Climate change will pose a challenge for the winemaking sector worldwide, bringing progressively drier and warmer conditions and increasing the frequency and intensity of weather extremes. The short-term adaptation strategy of applying biostimulants through foliar application serves as a crucial measure in mitigating the detrimental effects of environmental stresses on grapevine yield and berry quality. The aim of this study was to evaluate the effect of foliar application of a seaweed based biostimulant (A. nodosum – ANE) and glycine betaine (GB) on berry quality, bioactive compounds, antioxidant activity, and elucidated their action on the secondary metabolism. A trial was installed in a commercial vineyard (cv. ‘Touriga Franca’) in the Cima Corgo (Upper Corgo) sub-region of the Douro Demarcated Region. A total of four foliar sprayings were performed during the growing season: at flowering, pea size, bunch closer, and veraison. There was a positive effect of GB in the berry quality traits. Both ANE and GB increased the synthesis of anthocyanins and other phenolics in berries and influenced the expression of genes related to the synthesis and transport of anthocyanins (CHS, F3H, UFGT, MATE1 and GST). So, they have the potential to act as elicitors of secondary metabolism, leading to improved grape quality, but also sets the foundation for sustainable agricultural practices in the long run.

(1) Background: Environmental and public health research has given considerable attention to the impact of air quality on brain health, with systematic reviews widespread. No literature review has been done for cognitive frailty – a multidimensional syndrome combining physical frailty and cognitive impairment and their apparent co-dependence, linked to increased vulnerability and adverse health outcomes, including dementia. Instead, cognitive decline and frailty is implicitly explored through research on air quality and comorbid cognitive and physical decline in elderly populations. (2) Methods: A scoping review was conducted to explore the need for a systematic review. Combining Arksey and O’Malley [1] and PRISMA-ScR checklist [2], a scoping review of SCOPUS using ‘cogniti*’ + ‘resilience’ + ‘air quality’ or ‘cogniti*’ + ‘ageing’ + ‘air quality’ resulted in N=2503 articles, screened and reduced using inclusion and exclusion criteria, to N=16 articles. (3) Results: Air quality appears to be a critical risk factor for cognitive decline, even at air quality levels below WHO targets. Moderate long-term ambient air pollution appears linked to increased risk of cognitive frailty, suggesting earlier and more active interventions to protect older people. There are varied effects on cognition across the life course, with both emotional and functional impacts. Effects may be more detrimental to elderly people with existing conditions, including economic and health inequalities. Generalisation of results is limited due to the absence of a dose-response, variations in methods, controlling for comorbid effects, and variance across studies. (4) Conclusions: The findings support the need for more research and a more extensive summary of the literature.

Eutrophication is a major environmental issue with many negative consequences, such as hypoxia and harmful cyanotoxins production. Monitoring coastal eutrophication is a crucial, especially for island countries like the Republic of Cyprus, which are economically dependent on the touristic sector. Additionally, the open-sea aquaculture industry in Cyprus has been exhibiting an increase in the last decades and environmental monitoring to identify possible signs of eutrophication is mandatory according to the legislation. Therefore, in this modelling study, two different types of Artificial Neural Networks (ANNs) are developed based on in situ-data collected from stations located in the coastal waters of Cyprus. Theses ANNs aim to model the eutrophication phenomenon based on two different data-driven modelling procedures. Firstly, the self-organizing map (SOM) ANN examines several water quality parameters (specifically water temperature, salinity, nitrogen species, ortho-phosphates, dissolved oxygen and electrical conductivity) interactions with the Chlorophyll-a parameter. The SOM model enables us to visualize the monitored parameters relationships and to comprehend complex biological mechanisms related to Chlorophyll-a production. A second feed-forward ANN model is also developed for predicting the Chlorophyll-a levels. Based on this ANN model, several scenarios associated to the eutrophication-related water quality parameters can be extracted. The combination of these two ANNs models is considered a holistic modelling approximation for the identification of eutrophication scenarios, since it enables not only the prediction of the Chlorophyll-a parameter levels, but also the “capturing” of hidden biological mechanisms associated with algal production.

The human gut microbiota (GM) is a complex and dynamic ecosystem that hosts trillions of commensal and potentially pathogenic microorganisms. It is crucial in protecting humans from pathogens and in maintaining immune and metabolic homeostasis. Numerous studies have demonstrated that GM has a significant impact on health and disease, including Alzheimer’s disease (AD). AD is a progressive neurodegenerative disorder characterized by impaired short-term memory and cognitive deficits. Patients with AD have been reported to exhibit abnormalities in GM density and species composition. Oxidative stress (OS) has been implicated in the onset and progression of AD, however, the relationship between OS and gut microbiota in AD onset and progression is not clear. Twendee X®︎ (TwX), an oral supplement consisting of 8 active ingredients, has been shown to prevent dementia in mild cognitive impairment (MCI) in humans and substantially improve cognitive impairment in mouse models of AD. This positive effect is achieved through the potency of the combined antioxidants that regulate OS and therefore similar results cannot be achieved by a single antioxidant ingredient. To examine the impact of long-term OS elevation as seen in AD on the body and GM, we examined GM alterations during the initial OS elevation using a rat 2-week OS loading model, and examined the effects of TwX on OS and GM. Furthermore, using a questionnaire survey and fecal samples, we analyzed the impact of TwX on healthy individuals' gut bacteria and the associated effect on their quality of life (QOL). TwX was found to increase the number of bacteria species and their diversity in GM, as well as butyrate-producing bacteria, which tend to be reduced in AD patients. Additionally, TwX improved defecation condition and QOL. The gut bacteria function as part of the homeostatic function during OS elevation, and prophylactic administration of TwX strengthened this function. The results suggests that the preventative effect of TwX on dementia may involve the GM in addition to the other effects previously demonstrated.

AISI 1050 steel circular pocket milling under minimum quantity lubrication (MQL) surroundings including nozzle elevation angle, lubricant flow rate, air pressure and cutting speed was studied. The machined surface quality (Ra) was evaluated for Up-milling side and Down-milling side. In this study, to obtain an manifest explanation on the pivotal effective parameters of MQL surroundings and cutting speed on the machined surface quality (Ra) through analyzing Taguchi L9 (34-2) approach and ANOVA calculation to identify those parameters, by utilizing the experimental outcomes to interpret three-dimensional (3D) surface plots and the diagrams of Signal-to-Noise ratios and major impact plots of Mean. The obtained outcomes of optimal operating parameters indicated that the pivotal effective parameters of MQL surroundings are nozzle elevation angle and lubricant flow rate on the machined surface quality. Simultaneously, a quadratic mathematical paradigm generated by using response surface design (RSD) and desirableness function evaluation were utilized to forecast the optimal values of the machined surface quality compared to Taguchi method. The results unveiled that the optimal values of the machined surface quality are adjacent to experimental attained values. The machined surface quality has been significantly improved using MQL surroundings.

Calcium and magnesium are important not only for human health, but also for reducing problems related to the corrosive and aggressive effects of soft water on drinking water distribution materials. Experimental and mathematical modeling of the recarbonization process aimed at increasing the content of these biogenic elements in water was carried out using the novelty of a continuous laboratory and pilot scale fluidized bed reactors. Water remineralization using half-calcined dolomite (HCD) and carbon dioxide was used. The influence of operating conditions Q(CO2), freshwater inflow and HCD dose on quality indicators of treated drinking water (c(Ca2+), c(Mg2+), c(Ca2++Mg2+) and Ca/Mg) was studied. The results show that the concentration of Mg2+ is more significantly affected by the amount of HCD in the system and the flow of CO2. The influence of freshwater inflow on the Mg2+content is to a lesser extent. At a constant CO2 flow, therefore, as the tap water inflow increases, the Ca2+ content decreases and the Mg2+ content increases, which has results in a decrease in the Ca/Mg molar ratio. However, the Ca/Mg ratio can be effectively controlled by adding an appropriate amount of HCD at certain time intervals. Overproduction of ions is easily controlled by CO2 flow.

The present study was to investigate effects of total flavonoids from Taraxacum mongolicum Hand.-Mazz. (FT) on fermentation quality, antioxidant status and microbial community of Caragana korshinskii Kom. (CK) silage. CK was ensiled with no additive (CON), 1% FT and 2% FT on a fresh weight (FW) basis for 60 days. The results showed that 1% FT and 2% FT groups displayed higher DM content than CON group, and 2% FT group had the best effect on nutrient preservation. Compared with CON and 1% FT groups, 2% FT group exhibited the best silage fermentation quality and the highest antioxidant activity, including increased lactic acid, acetic acid concentrations and the activities of antioxidant enzymes, as well as decreased pH and the ammonia nitrogen (NH₃-N) concentration. Moreover, 2% FT addition significantly affected the microbial community, such as increased abundance of Lactobacillus and decreased abundances of Pseudomonas and unidentified Cyanobacteria. The abundances of Lactobacillus parafarraginis and Lactobacillus brevis were negatively correlated to pH, while they were positively correlated with T-AOC, GSH-Px and CAT activities. In conclusion, 2% FT may be used as additives to inhibit the growth of undesirable microorganisms and promote fermentation quality and antioxidant activity of CK silage.

The rapid progress in artificial intelligence, machine learning, and natural language processing has led to the emergence of increasingly sophisticated large language models (LLMs) enabling their use in healthcare. The study assesses the performance of two LLMs: the GPT-3.5 and GPT-4 models in passing the medical examination for access to medical specialist training in Spain MIR. Our objectives included gauging the model's overall performance, analyzing discrepancies across different medical specialties, discerning between theoretical and practical questions, estimating error proportions, and assessing the hypothetical severity of errors committed by a physician. We studied the 2022 Spanish MIR examination after excluding those questions requiring image evaluations or having acknowledged errors. The remaining 182 questions were presented to the LLM ChatGPT4 and GPT-3.5 in Spanish and English. Logistic regression models analyzed the relationships between question length and question sequence d performance. GPT-4 outperformed GPT -3.5, scoring 86.81% in Spanish (p<0.001). English translations had a slightly enhanced performance. Among medical specialties, GPT-4 achieved a 100% correct response rate in several areas, with specialties like Pharmacology, ICU, and Infectious Diseases showing lower performance. The error analysis revealed that while a 13.2% error rate existed, gravest categories like "error requiring intervention to sustain life" and "error resulting in death" had a 0% rate. Conclusions: GPT-4 performs robustly on the Spanish MIR examination, varying its capability to discriminate knoweldge across specialties. While the model's high success rate is commendable, understanding the error severity is critical, especially when considering AI's potential role in real-world medical practice and its implication on patient safety.

Transportation electrification has been identified as a crucial shift to be made for achieving energy security and emission reduction targets. Electric Vehicles (EVs) play a significant role in achieving these targets; therefore, there is a growing trend to develop new EV technologies and associated infrastructure. Along with these developments, EVs' Quality of Service (QoS) aspects should be enhanced to increase the number of EVs on the road. Various QoS factors are defined to assess the QoS of EVs, and one of the two aims of this paper is to provide a comprehensive review of these factors. The other aim is to review recent developments of associated communication technologies which are essential for exchanging information between EVs and charging stations. This paper serves as a comprehensive review and useful reference for researchers working on QoS aspects of EVs and associated communication systems aiming to enhance the QoS.

The health of inmates living in a restricted environment are affected by oral health behaviours and is related to their oral health-related quality of life (OHRQoL). We investigated oral health behaviours and oral symptoms among male inmates and analysed factors related to OHRQoL. Three hundred and seventy-six male inmates in two prisons were investigated using a self-reported questionnaire. The survey items included oral health behaviours, oral symptoms, self-esteem, and OHRQoL level. We analysed cross-correlations and factors related to OHRQoL. Toothbrushing after lunch and dinner was practiced by 83.5% of male inmates. ‘Food impaction’ was experienced by 45.4%. The OHRQoL level among male inmates was low, at 39.90 points. A hierarchical multiple regression model that controlled for general characteristics identified the following OHRQoL factors, in order of significance: trouble biting/chewing (β = -0.307), toothache (β = -0.154), temporomandibular joint disorder (β = -0.099), and periodontal health (β = 0.089). Self-esteem and OHRQoL were not significantly correlated. To ensure oral health in male inmates, the results of this study suggests that an oral health education programme, as well as provision of adequate dental care services, is required to increase appropriate oral health practice rates.

The Douro Demarcated Region (DDR) has peculiar edaphoclimatic characteristics that provide a suitable terroir for premium wine production. As climate change effects continue to emerge, ensuring productivity and quality becomes increasingly important for viticulturists, as those directly determine their profits. Cultural approaches, such as the use of biostimulants, are actively being developed to mitigate abiotic stress. The main objective of this work was to assess the effect of foliar sprays of a seaweed (Ascophyllum nodosum) based extract (ANE) and glycine betaine (GB) on grape berry quality, bioactive compounds, and antioxidant activity. A trial was installed in a commercial vineyard (cv. Touriga Franca) in the Douro Superior (Upper Douro) sub-region of the Douro Demarcated Region. In 2020, a total of three foliar sprayings were performed during the growing season, namely at pea-size, bunch closure, and veraison. There was a positive effect of both biostimulants (ANE and GB) on the physiological and biochemical performance of cv. Touriga Franca exposed to summer stress. In general, the GB 0.2% spraying was the most promising treatment for this grape cultivar, as it increased berry quality, the concentration of bioactive compounds (total phenolics, flavonoids and ortho-diphenols), and the antioxidant activities. These results revealed the efficacy of biostimulants sprayings as sustainable viticultural practice, improving berry quality under summer stress conditions.

Water is one of the most critical factors affecting environmental health. For this reason, estimating and monitoring the behavior of water in nature and preventing water pollution before it occurs are advantageous to avoid problems that may occur in terms of environmental health. In order to predict the behavior of water, the hydrological cycle needs to be evaluated on a basin basis. At this point, hydrological models can be used to make mathematical representations of hydrologi-cal processes. These models play an essential role in predicting and monitoring problems such as poor water quality, pollution, particle and sediment transport, and proliferation of oil and petro-leum derivatives among frequently encountered issues in environmental health. In this study, a 2D surface water model was created using soil and water assessment tool (SWAT) to simulate the lotic ecosystem and existing water quality in Tatlıçay Basin and to propose solutions for im-proving environmental health in Cankiri provincial center in Türkiye. The accuracy of the input data and the validity of the model were checked with the calibration and validation studies by using the monthly or 3-monthly observation data of the General Directorate of State Hydraulic Works’ flow observation & water quality stations from 2016 to 2020. The aim was to provide the opportunity to produce fast, accurate, and practical solutions in the face of negative scenarios with this model. This modelling study obtained successful results in the calibration and valida-tion process with very few observed data. With this study, a significant contribution to the litera-ture on environmental health is made, as there aren't many examples of hydrological modeling from the Middle East.

The current study aimed to investigate the effects of feeding silage of Napier Pakchong 1 fermented with mung bean concentrate on production performance, nutrient digestibility, carcass yield, and meat quality of male dairy goats. Silage made for experimental treatments was prepared as follows: Treatment 1 (T1) containing 100% Napier Pakchong 1 grass (without mung bean concentrate added) as a control, while Treatment 2 (T2) and Treatment 3 (T3) containing 90% and 80% Napier Pakchong 1 grass, respectively, mixed with 10% and 20% mung bean concentrate, respectively. Fifteen weaned male Saanen-growing goats were assigned to 3 experimental treatments in a completely randomized design; the study lasted for 150 days. The nutritive value of feed, production performance, nutrient digestibility, blood urea nitrogen, carcass yield and dressing, basic meat quality, and composition of meat were collected or analyzed. The results found that the goats fed with the silage made from Napier Pakchong 1 added 10% and 20% mung bean concentrate showed improvements in nutritive value, growth rate, key nutrient digestibility, blood urea nitrogen, carcass yield, the water-holding capacity of cooked meat, and fat content in meat. However, adding 10% mung bean concentrate had a trend of more beneficial value added into the production chain of male Saanen dairy goats for meat purposes. Thus, silage made from Napier Pakchong 1 fermented with 10% mung bean concentrate as a roughage source for male Saanen dairy goats intended for meat purposes is recommended.

Abstract: This study aimed to evaluate the application of chemical defensives and long-life inoculant, in mixtures or not, under the nodulation process of plants and the quality of soy seeds during storage. The first was carried out in a greenhouse and completely randomized design was used, in an 8 x 2 factorial scheme, with three replications, and the treatments consisted of applications of seed treatments via industrial: (T1 - control; T2 - MaximAdvanced; T3 - Fortenza; T4 - long-life inoculant; T5 - MaximAdvanced + Fortenza); T6 - MaximAdvanced + long-life inoculant; T7 - Fortenza + long-life inoculant; T8 - MaximAdvanced + Fortenza + long-life inoculant), which were sown in pots containing soils from two cultivation areas; the second in the laboratory, using a completely randomized design, in a factorial scheme 8 x 7, with four replications, with treatments consisting of eight combinations of industrial seed treatment in the greenhouse, stored for two months. That seed treatment industrial with fungicide/insecticide/inoculant, applied in isolation or not, does not influence the soy nodulation process. Soy seeds, regardless of the type of treatment received with fungicide/insecticide/long-life inoculant products, in mixtures or in isolation, may be stored for a period of 40 days for commercial purposes.

Advances towards smart ecosystems showcases Internet of Things (IoT) as a transversal strategy to improve energy efficiency in buildings, to enhance their comfort and environmental conditions, and to grow knowledge about building behavior, its relationships with the users and the interconnections among themselves and with the environmental and ecological context. EU estimates that 75% of the building stock is inefficient and aged with +40 years old. Although many buildings have some kind of system for regulating their indoor temperature, only a small subset provides integrated Heating, Ventilation, and Air Conditioning (HVAC) systems; within that subset, only a low percentage includes smart sensors, and only a minimum of that percentage integrates those sensors into IoT ecosystems. This work proposes several contributions. On the one hand, to understand the built environment as a set of interconnected systems that constitute a complex framework where IoT ecosystems are key enabling technologies to improve energy efficiency and Indoor Air Quality (IAQ) by filling the gap between theoretical simulations and real measurements. On the other hand, to understand IoT ecosystems as cost-effective solutions where: acquire data through connected sensors, analyze information in real-time, and build knowledge to make data-driven decisions. Furthermore, data set is public for third-party use to contribute scientific community to their research studies. Thus, this paper also contributes with a detailed functional scheme of IoT ecosystem deployed in 3 buildings of University of Zaragoza (Spain) with +200 geolocated wireless sensors with +100 representative spaces. The obtained results, through real installations with IoT as learning factory, show several learned lessons (about building complexity; energy consumption, costs and savings; and IAQ and health improvement) and contribute, as a proof-of-concept, with a proposal of prediction of building performance based on both correlations (between CO2 and occupancy) and neural networks (applied to CO2 and temperature). In summary, in a real context of economic restrictions, complexity, higher energy costs, social vulnerability and climate change, IoT-based strategies, as proposed in this work, highlight as an open, modular and interoperable approach to move towards smart communities (buildings, cities, regions, etc.) by improving energy efficiency and environmental quality (indoor and outdoor) with low cost, quick implementation, and low impact on users within great challenges for growth, interconnection, climate change and sustainability.

Abstract: The diffusion of competition under the coexistence of multi-generation products has become one of the important challenges faced by enterprises in their daily and sustainable operations. At the same time, the competition between different brands has intensified the difficulty and complexity of decision-making in the process of multi-generation product operation, Therefore, based on the Norton-Bass model diffusion process, this paper introduces two marketing variables, dynamic price and quality level, builds a multi-generation product diffusion model under the dual-brand competition, and analyzes the impact of the company's revenue on the launch time to market, pricing, quality or technical level. By using system dynamics (SD) method, From the perspective of strong brand and weak brand enterprises, the competition diffusion model is built and simulated. The simulation shows that: i) When enterprises have the same brand competitiveness, reducing the pricing level cannot obtain more revenue, but diminish the overall revenue of the industry; Raising the pricing level can get more revenue, but also improve the revenue of competitors. ii) When the competitive strength of enterprises is different, the strong brand tends to maintain a stable pricing on the basis of improving the quality level, or slightly raise the price. Weak brands tend to raise the pricing of new products significantly on the basis of improving the quality level. iii) The launch time to market decision of new product is influenced by the degree of product quality upgrade. Therefore, the frequency of releasing new products should trade-off against the degree of technological upgrading of product quality. This paper provides the theoretical basis and new insights for the new product launch and operation decision of enterprises.

Habitat quality has great significance for regional ecological conservation and human welfare. In this study, we evaluated the spatial and temporal characteristics of land use and habitat quality in the temperate desert sub-region of Ordos Plateau using patch-generating land use simulation (PLUS) and integrated valuation of ecosystem services and trade-offs (InVEST) models. From 2000 to 2020, the areas of grassland, cropland, and unused land in the study area increased significantly; the areas of water bodies and woodland increased slightly; and the area of wasteland decreased significantly. Moreover, the habitat quality in the temperate desert subzone of the Ordos Plateau showed a trend of increasing and then decreasing from 2000 to 2020. The areas of lower and low habitat quality first decreased and then increased, and the overall area decreased over time. Conversely, the areas of high and higher habitat quality initially increased and then decreased, and the overall area increased over time. The area of medium habitat quality first decreased and then increased, although the overall change was minimal. Based on the PLUS model, the habitat quality of the study area in 2025 predicted under the natural development scenario was compared with that predicted under the ecological conservation scenario, showing higher habitat quality and lower habitat degradation under the ecological conservation development scenario. These results can be used to provide a scientific basis and decision reference for the sustainable use of land resources and high-quality socio-economic development in the temperate desert sub-region of the Ordos Plateau.

Introduction: When analyzing the current situation in Spain, derived from our current lifestyles far from following a Mediterranean lifestyle, there is an alarming prevalence of diabesity, which increases the global risk of suffering from cardiovascular disease (CVD) and decreases the quality of life related to health (QLRH). In order to guarantee, beyond glycemic control of patients with type 2 diabetes (DM2), adequate control of cardiovascular risk factors (CVRF) in DM2, it will be necessary to carry out a community intervention focused on the application of education programs focused on promoting the acquisition of healthy eating habits through the Mediterranean diet (DMED). This dietary pattern, together with physical exercise, has been shown to contribute to improving the QLRH of patients. Objective: To analyze the quality of life related to health, present in patients with poorly controlled type 2 diabetes, to determine the possible relationship between this and the degree of adherence to the Mediterranean diet and to examine whether there are differences between the sexes. Material and methods: Observational descriptive study in 93 patients diagnosed with DM2 with poor glycemic control (1Ac ≥ 7%), carried out in various health centers in Albacete and Cuenca, in which the baseline relationship between adherence to DMed and the HRQoL. They were administered a data collection sheet that included a survey of the degree of adherence to the DMed (MEDAS-14) and QLRH (SF-12v2) in the Primary Care (PC) medical and nursing consultations. The variables were analyzed: age groups, sex, years of evolution of DM2, body mass index (BMI), as well as basal glycemia (GB) and glycosylated hemoglobin (HbA1c). The “MEDAS-14” (adherence to DMED) was the main variable and the “SF-12v2” (QLRH) was the secondary variable. Material and methods: Observational descriptive study in 93 patients diagnosed with DM2 with poor glycemic control (1Ac ≥ 7%), carried out in various health centers in Albacete and Cuenca, in which the baseline relationship between adherence to DMed and the HRQoL. They were administered a data collection sheet that included a survey of the degree of adherence to the DMed (MEDAS-14) and QLRH (SF-12v2) in the Primary Care (PC) medical and nursing consultations. The variables were analyzed: age groups, sex, years of evolution of DM2, body mass index (BMI), as well as basal glycemia (GB) and glycosylated hemoglobin (HbA1c). The “MEDAS-14” (adherence to DMED) was the main variable and the “SF-12v2” (QLRH) was the secondary variable. Results: Patients with poorly controlled DM2 and with low adherence to the MedDM show a non-significantly greater affectation in the physical sphere: fair general state of health, physical function I (limitation to make moderate efforts such as moving a table, vacuuming or walk more than an hour), physical function II (limitation to climb several flights of stairs), physical role (problems at work or daily activities doing less than loved ones), physical role II (they had to stop performing some tasks at work or activities of daily living) and regular body pain. Presenting less affectation in the mental field: emotional role I, emotional role II, mental health I, vitality and mental health II. Without affectation in the social function since they consider that rarely the emotional or physical problems have hindered their social activities. Conclusions: Diabetic patients with poor glycemic control have low adherence to the MedMD (<9 points) and have poor QLRH. Low adherence to the DMed and obesity are related to a greater affectation in the physical dimension and less affectation in the mental dimension without affectation in the "social function".

The affected upper limb in children with Unilateral Spastic Cerebral Palsy (US CP) has motor and somatosensory impairments, that contribute negatively to children’s bimanual performance and quality of life. Mirror Therapy (MT) is being studied to become an approachable intensive and home-based therapy, suitable for children with US CP. The aim of this study is to examine the feasibility of a 5-week home-based program of MT for children with US CP. Six children aged 8-12 years old performed the therapy, five days per week, 30 minutes per day. A minimum of an 80% of compliance was required. The evaluations included the feasibility of the therapy (compliance, total dosage, perceived difficulty of the exercises, and losses of follow-ups and evaluations), the bimanual performance, the somatosensory function and the quality of life at baseline, at the end of the intervention, and at 1-month follow-up. All children completed the therapy and were included in the analysis. The total accomplishment was 86.47 ± 7.67. The perceived difficulty of the exercises ranged from 2,37 to 4,51. As a conclusion, a home-based program of Mirror Therapy is suitable and feasible for children with US CP.

Blind image quality assessment (BIQA) aims to evaluate image quality in a way that closely matches human perception. To achieve this goal, the strengths of deep learning and the characteristics of human visual system (HVS) can be combined. In this paper, inspired by the ventral pathway and dorsal pathway of HVS, a dual-pathway convolutional neural network is proposed for BIQA task. The proposed method consists of two pathways: “what” pathway, which mimics the ventral pathway of HVS to extract the content features of distorted images, and the “where” pathway, which mimics the dorsal pathway of HVS to extract the global shape features of distorted images. Then, the features from the two pathways are fused and mapped to an image quality score. Additionally, the gradient images weighted by the contrast sensitivity are used as the input to the “where” pathway, allowing it to extract global shape features that are more sensitive to human perception. Moreover, a dual-pathway multi-scale feature fusion module is designed to fuse the multi-scale features of the two pathways, enabling the model to capture both global features and local details, thus improving the overall performance of the model. The experiments conducted on six databases show that the proposed method achieves the state-of-the-art performance.

The purpose of this work was to achieve non-destructive detection of the internal defects of in-shell walnuts using X-ray radiography technology based on improved Faster R-CNN network model. First, the FPN structure was added to the feature extraction layer to extract richer image information. Then ROI Align was used to instead of ROI Pooling for eliminating the localization bias problem caused by quantization operation. Finally, the Softer-NMS module was introduced to the final regression layer with the predicted bounding box for improving the localization accuracy of the candidate boxes. The results indicated that the internal defects in intact walnuts with shells could be identified effectively using the proposed improved network model in this study. Specifically, the discrimination accuracy of the in-shell sound, shriveled and empty-shell walnuts were 96.14%, 91.72% and 94.80% respectively, and the highest overall accuracy can reach 94.22 %. Contrasted with original Faster R-CNN network model, the mAP and F1-value of the improved Faster R-CNN model increased by 5.86% and 5.65%, respectively. Consequently, the proposed method can be applied for the in-shell walnuts with shriveled and empty-shell defects.

The COVID-19 pandemic measures have negatively impacted education worldwide via travel restrictions, student visas, and physical attendanc,e among many other fac-tors. As one of the first places to impose strict pandemic measures and one of the last places to lift the measures, Mainland China provided a unique venue to investigate the effect of public health pandemic control policies on tertiary education. Considering the large portion of international students in medical schools and the higher susceptibility to the pandemic measures due to the natural synergy with teaching hospitals, medical schools can be an early forefront indicator of the impact of the pandemic on tertiary education. We surveyed 513 participants international medical students from Wen-zhou Medical University’s school of international studies in 2019 and 2022 about their satisfaction and demographic and cultural adaptation parameters. We found that the pandemic restrictions did not generally impact student satisfaction. Further analyzing the associated parameters, we found teaching satisfaction to be independent of age (P=.159), years in China (P=.896) and Chinese Level (P=.577) in the medical university. Teaching satisfaction is associated with the region of origin (P <0.001), acceptance of local social norms (P <0.001), satisfaction with the core values of Chinese culture (P <0.001), acclimatization to life in China (P <0.001), can easily make Chinese friends (P <0.001) among other factors. The findings of this study provide an understanding of the effects of pandemic measures on tertiary education satisfaction and other factors that can aid in international student satisfaction.

Abstract: This research aims at developing a virtual reality destination experience (VRDE) model as a moderating variable between sustainable tourist behavior (STB) and tourist visit intention (TVI). The portability variable strengthens VRDE, and the content quality variable supports VRDE. The research method used was purposive convenience sampling covering 204 respondents who visited the vicinity of Kebon batik village in Klaten, Central Java, Indonesia. The research findings were H1: STB has a significant effect on VRDE, H2: VDRE has an impact on TRVI, H3: portability has a significant effect on VRDE, and H4: content quality did not have an impact on VRDE. The novelty of this research is the VRDE application applied to Community Sustainable Tourist Behavior in developing countries.

Due to rising global warming and climate change, biodiversity protection has become a critical ecological concern. The rich biodiversity zones are under threat and are deteriorating, necessitating national, regional, and provincial efforts to safeguard these natural areas. The effective conservation of National Parks and Nature-protected Areas helps to improve biodiversity conservation, forest, and urban air quality. The continuous encroachment and abuse of these protected areas have degraded the ecosystem over time. While exploring the geophysical ecology and biodiversity conservation of these areas in West Africa, Kainji National Park was selected for this study because of its notable location, naturalness, rich habitat diversity, topographic uniqueness, and landmass. The conservation of national parks and nature-protected areas is a cornerstone of biodiversity conservation globally. This study is aimed at the target of United Nations Sustainable Development Goal 13, 2030- Climate Action, targeted at taking urgent action towards combating climate change and its impacts. The study captures both flora and fauna that are dominant in the study area. The 15 identified tree species were selected from over 30 species with 563,500,000 (an average of 3,700,000 in each sample frame) trees for every tree species/type with a total of 63% tree green canopy cover. The study areas divided into three zones were randomly sampled within a stratum of 25x25km frames divided into 150 sample frames for proper analyses using the i-Tree Eco v6.0.23. The following microclimatic data were captured and analyzed; photosynthetically active radiation, rain/precipitation, temperature, transpiration, evaporation, water intercepted by trees, avoided a runoff by trees, potential evaporation by trees, isoprene and monoterpene by trees. This study also further discusses the tree benefits of a green, low carbon, and sustainable environment within the context of biodiversity conservation considering carbon storage, carbon sequestration, hydrology effects, pollution removal, oxygen production, and volatile organic compounds (VOCs). There is a quick need for remotely-sensed information about the protected areas at regular intervals and government policies must be strict against illegal poaching, logging activities and other hazardous human impacts.

The water quality of the river is becoming deteriorated due to human interference. It is essential to understand the relationship between human activities and land-use types to assess the water quality of a region. GIS has the latest tool for analyzing the spatial correlation. Land use land cover and change detection is the best illustration to show the human interactions on land features. The study assessed water quality index of upper Ganga River near Haridwar, Uttarakhand and spatially correlated them with changing land use to reach a logical conclusion. At the upper course of Ganga along 78 Km long from Kaudiyala to Bhogpur, water samples were collected from five stations. For water quality index the physicochemical parameters like pH, EC, DO, TDS, CaCO3-, CaCO3, Cl¯, Ca++, Mg++, Na+, K+, F-, Fe2+ were considered. The result of the spatial analysis was evaluated through error estimation and spatial correlation. The root mean square error between spatial land use and water quality index of selected sampling sites was estimated as 0.1443. The spatial correlation between land-use change and site-wise differences in water quality index has also shown a high positive correlation with R² = 0.8455. The degree of positive correlation and root mean square error has strongly indicated that the water quality of the river at the upper course of Ganga is highly impacted through human activities.

Use of a multi-sensor approach can provide citizens a holistic insight in the air quality in their immediate surroundings and assessment of personal exposure to urban stressors. Our work, as part of the ICARUS H2020 project, which included over 600 participants from 7 European cities, discusses data fusion and harmonization on a diverse set of multi-sensor data streams to provide a comprehensive and understandable report for participants, and offers possible solutions and improvements. Harmonizing the data streams identified issues with the used devices and protocols, such as non-uniform timestamps, data gaps, difficult data retrieval from commercial devices, and coarse activity data logging. Our process of data fusion and harmonization allowed us to automate the process of generating visualizations and reports and consequently provide each participant with a detailed individualized report. Results showed that a key solution was to streamline the code and speed up the process, which necessitated certain compromises in visualizing the data. A thought-out process of data fusion and harmonization on a diverse set of multi-sensor data streams considerably improved the quality and quantity of data that a research participant receives. Though automatization accelerated the production of the reports considerably, manual structured double checks are strongly recommended.

Call set up success rate (CSSR) in a mobile network is an important quality parameter, which directly influences overall key performance indicators (KPIs) of the network service providers. Network KPIs especially the CSSR is the fraction of the attempts to make a call that result in a successful connection to the dialled number. Nevertheless, all call attempts do not end with a connection to the dialled number. In this research, six sigma methodology is applied to improve the call quality of a legacy mobile network and subsequently to boost comprehensive CSSR of a telecom service provider. This research elucidates an empirical study of improving overall CSSR by employing DMAIC methodology consisting of five stages, e.g. Define, Measure, Analysis, Improve and Control. In addition, analytic hierarchy process (AHP) technique is used for determining the vital causes out of all the identified network parameters affecting overall CSSR. Furthermore, the identified vital parameters are being upgraded in order to improve the overall CSSR and finally the system achieved a higher CSSR.

The novel coronavirus pneumonia epidemic is still raging around the world. Therefore, during the period of a global pandemic, maintaining the normal circulation of medicine and health fields is the key to fight against the epidemic. This paper based on relevant data such as the export volume of cross-border e-commerce in Hangzhou, China from 2015 to 2019, the article uses system dynamics modeling to explore the impact of overseas warehouse services on cross-border e-commerce export transactions. Studies have shown that the introduction of overseas warehouses has significantly improved customer satisfaction and improved the quality of cross-border logistics services, which has a positive impact on cross-border e-commerce export transactions. Through sensitivity analysis, it can be seen that under the same conditions, the efficiency of customs clearance has the greatest impact on overseas warehouse services. Therefore, when allocating various investments in overseas warehouses, you can favor the customs clearance process to enhance the competitiveness of the cross-border e-commerce market and provide a feasible experience for healthcare supplies export from cross-border e-commerce.

Dupilumab is used to treat atopic dermatitis patients who have proven to be refractory to previous treatments. The aim of this study was to assess evolution and patient reported outcome measures in adult patients with moderate-to-severe atopic dermatitis treated with Dupilumab in routine clinical practice. The outcomes were evaluated and registered at baseline and weeks-16, 40 and 52. The variables evaluated were: diseases severity, pruritus, stressful life events, difficulty to sleep, anxiety and depression, quality of life, satisfaction, adherence to the treatment, efficacy and safety. Eleven patients were recruited between Nov 14th 2017 and Jan 16th 2018. Demographic variables: 90% Caucasian, 82% women. Clinical variables: Mean duration of AD =17.7 (±12.8), 91% had severe disease severity. At baseline, SCORAD mean score = 61.7 (±15.5); itch was reported by 100% of patients; itch Visual Analogue Scale mean range of 8 (6-10); HADS mean total score =13.9 (±5.5); DLQI mean score =13.3 (±8.3): EQ-5D-3L mean range = 57 (30-99). At week-52 there is a significant reduction of SCORAD scores, HADS total score and improved quality of life. ¡This study confirms that Dupilumab, used for 52-weeks under routine clinical practice, maintains the improved atopic dermatitis signs and symptoms obtained at week-16, with a good safety profile.

The overrun of transient power quality index caused by the large-capacity electric arc furnace (EAF) has become a prominent problem affecting the safe and stable operation of the power system. (1) In this paper, the relationship between arc furnace volt-age and current is derived based on the different stages of arc combustion, and the random variation of chaotic phenomenon of the arc voltage are simulated. Established an EAF model suitable for the study of transient power quality problems. (2) Take 50t AC EAF as an example to analyze the reactive power impact and the influence on the point of common coupling (PCC) voltage caused by the three-phase short circuit of the electrode. The results show that the experimental results are consistent with the theoretical analysis, verifying the correctness and effectiveness of the model. (3) When the three-phase short-circuit occurs, the reactive power impact is nearly 6 times that of normal operation, the short-circuit current is 2.66 times that of normal operation, and the effective value of the PCC voltage has dropped by 40.37%, which provides a theoretical basis for real-time compensation of impulsive reactive power and improvement of the transient power quality of the EAF.

It is essential to mitigate gaseous emissions that result from poultry and livestock production to increase industry sustainability. Odorous volatile organic compounds (VOCs), ammonia (NH3), hydrogen sulfide (H2S), and greenhouse gases (GHGs) have detrimental effects on the quality of life in rural communities, the environment, and climate. This study's objective was to evaluate the photocatalytic UV treatment of gaseous emissions of odor, odorous VOCs, NH3, and other gases (GHGs, O3 – sometimes considered as by-products of UV treatment) from stored swine manure on a pilot-scale. The manure emissions were treated in fast-moving air using a mobile lab equipped with UV-A and UV-C lights and TiO2-based photocatalyst. Treated gas airflow (0.25 to 0.76 m3/s) simulates output from a small ventilation fan in a barn. Through controlling the light intensity and airflow, UV dose was tested for techno-economic analyses. The treatment effectiveness depended on the UV dose and wavelength. Under UV-A (367 nm) photocatalysis, the percent reduction of targeted gases was up to i) 63% of odor, ii) 51%, 51%, 53%, 67%, and 32% of acetic acid, propanoic acid, butanoic acid, p-cresol, and indole, respectively, iii) 14% of nitrous oxide (N2O), iv) 100% of O3, and 26% generation of CO2. Under UV-C (185+254 nm) photocatalysis, the percent reductions of target gases were up to i) 54% and 47% for p-cresol and indole, respectively, ii) 25% of N2O, iii) 71% of CH4, and 46% & 139% generation of CO2 & O3, respectively. The results proved that the UV technology was sufficiently effective in treating odorous gases, and the mobile lab was ready for farm-scale trials. The UV technology can be considered for the scaled-up treatment of emissions and air quality improvement inside livestock barns.

In this paper, the power quality of interconnected microgrids is managed using a Model Predictive Control (MPC) methodology which manipulates the power converters of the microgrids in order to achieve the requirements. The control algorithm is developed for the microgrids working modes: grid-connected, islanded and interconnected. The results and simulations are also applied to the transition between the different working modes. In order to show the potential of the control algorithm, a comparison study is carried out with classical Proportional-Integral Pulse Width Modulation (PI-PWM) based controllers. The proposed control algorithm not only improves the transient response in comparison with classical methods but also shows an optimal behavior in all the working modes, minimizing the harmonics content in current and voltage even with the presence of non-balanced and non-harmonic-free three-phase voltage and current systems

Soil water loss by evaporation influences the sodium adsorption ratio (SAR) of irrigation drainage water. Evaporation concentrates sodium and magnesium but calcite precipitation has a more complicated effect on soluble calcium and alkalinity. Here we propose a revised sodicity hazard assessment that quantifies the impact of evaporative water loss and calcite precipitation on drainage water SAR. This paper shows sodicity hazard is determined by the initial composition of irrigation water as originally suggested by previous researchers, and provide a simple, accurate way to identify the potential sodicity hazard of any irrigation water. In particular, the initial equivalent concentration of alkalinity and calcium determine the salinization pathway followed during evaporation. If the irrigation water alkalinity exceeds soluble calcium expressed as equivalent concentrations, drainage water SAR approaches an upper limit determined by the initial relative concentration of sodium and magnesium. If irrigation water alkalinity is less than soluble calcium, drainage water SAR approaches a lower limit determined by the initial calcium, magnesium and sodium. In both cases the SAR is scaled by the square root of the concentration factor √Fc quantifying soil water loss. To assess the impact of evaporation and calcite precipitation on the SAR and test the accuracy of the new sodicity hazard assessment, we evaluated data from previously published lysimeter studies. We plotted water composition boundaries for each source water, comparing these boundaries to the drainage water composition recorded in the lysimeter studies. As salinity increased by evaporation, each drainage water followed a distinct salinization path.

Soil quality assessment based on crop yields and identification of key indicators of it can be used for better management of agricultural production. In the current research, the weighted additive soil quality index (SQIw), factor analysis (FA) and multiple linear regression (MLR) method are used to assess the soil quality of rainfed winter wheat fields with two soil orders on 53.20 km2 of agricultural land in western Iran. A total of 18 soil quality indicators were determined for 100 soil samples (0-20 cm depth) from two soil orders (Inceptisols and Entisols). The soil properties measured were: pH, soil texture, organic carbon (OC), cation exchange capacity (CEC), electrical conductivity (EC), soil microbial respiration (SMR), carbonate calcium equivalent (CCE), soil porosity (SP), bulk density (BD), exchangeable sodium percentage (ESP), mean weight diameter (MWD), available potassium (AK), total nitrogen (TN), available phosphorus (AP), available Fe (AFe), available Zn (AZn), available Mn (AMn), and available Cu (ACu). Mean wheat grain yield for the two years for all of the 100 sampling sites was also gathered. The SQIw was calculated using two weighting methods (FA and MLR) and maps were created using a digital soil mapping framework. The soil indicators taken in the minimum data set (MDS) were AK, clay, CEC, AP, SMR, and sand. The correlation between the MLR weighting technique (SQI-M) and the rainfed wheat yield (r=0.62) was slightly larger than that the correlation of yield with the FA weighted technique (SQI-F) (r=0.58). Results showed that the means of both SQI-M and SQI-F and rainfed wheat yield for Inceptisols were higher than for Entisols although these differences were not statistically significant. Both SQI-M and SQI-F showed that areas with Entisols had lower proportions of good soil quality grades (Grade I and II), and higher proportions of poor soil quality grades (Grade IV and V) compared to Inceptisols. Based on these results, soil type must be considered for soil quality assessment in future studies to maintain and enhance soil quality and sustainable production. The overall soil quality of the study region was of poor and moderate grades. To improve soil quality, it is therefore recommended that effective practices such as the implementation of scientific integrated nutrient management involving the combined use of organic and inorganic fertilizers in rainfed wheat fields be promoted.

Methods for high-quality DNA extraction and knowledge of sex expression and flowering time are essential for applying genomic-assisted breeding and improve the success with hybridization in Guinea yam. A dioecious or monoecious pattern of flowering and sometimes non-flowering is a common phenomenon within and between the Dioscorea species. The flowering in yam plants raised from botanical seeds often takes an extended period, mostly till the first clonal generation after propagation from the tubers. The prolonged process of testing required to identify plant sex and flowering intensity in yam breeding often poses a challenge to realize reduced breeding cycle and apply genomic selection. This study assessed sample preservation methods for DNA quality during extraction and potential of DNA marker to diagnose plant sex at the early seedling stage in white Guinea yam. The predicted sex at the seedling stage was further validated with the visual score for the sex phenotype at the flowering stage. DNA extracted from leaf samples preserved in liquid nitrogen, silica gel, dry ice, and oven drying methods was similar in quality with a high molecular weight than samples stored in ethanol solution. Yam plant sex diagnosis with the DNA marker (sp16) identified a higher proportion of ZW genotypes (female or monoecious phenotypes) than the ZZ genotypes (male phenotype) in the studied materials with 74% prediction accuracy. The results from this study provided valuable insights on suitable sample preservation methods for quality DNA extraction and the potential of DNA marker sp16 to predict sex in white Guinea yam.

Easy to use satellite-based water quality visualizations are needed for monitoring and understanding coastal and inland waters, but to date, no publicly accessible real-time global visualization system was in place. Here we introduce the Ulyssys Water Quality Viewer (UWQV), a Sentinel Hub EO Browser Custom script designed for qualitative views of aquatic chlorophyll and suspended sediment concentrations. The viewer avoids unmixing of the chlorophyll and suspended sediment spectral signal by visualizing these parameters together, with high concentrations of suspended sediment obscuring chlorophyll if present. Cloud masking uses the Hollstein and Braaten algorithms (existing EO Browser custom script code), additionally water surfaces are masked using the Normalized Differential Water Index. Chlorophyll is estimated using reflectance line height-based indicators such as fluorescence line height and maximum chlorophyll index. Suspended sediment is visualized based on single-band reflectances at 620 or 700 nm. Data sources are Sentinel-2 and Sentinel-3 images, allowing either 20 m spatial resolution or up to daily imaging. This visualization system is easy to operate and interpret, and combined with the data service capacity of the Sentinel Hub, it is expected that UWQV will contribute to monitoring of remote water bodies and to our overall understanding of physical limnology and aquatic ecology.

In order to solve the problem of the poor oil displacement effect of high molecular weight alkali/surfactant/polymer (ASP) solution in low permeability reservoirs, Daqing Oilfield uses a partial quality tool to improve the oil displacement effect in low permeability reservoirs. Without changing the oil displacement capability of high molecular weight ASP solution in high permeability oil layers, the ASP solution is actively sheared in low permeability oil layers by using a partial quality tool to increase the injection capability of the solution and improve the overall oil recovery. In order to study the ability of the partial quality tool to improve the oil displacement effect, firstly, the matching degree of high molecular weight ASP solution to low permeability cores is studied, and the ability of quality control tools to change the molecular weight is studied. Then, experimental research on the pressure and oil displacement effect of high molecular weight ASP solution before and after the actions of the partial quality tool is carried out. The results show that ASP solutions with molecular weights of 1900 × 104 and 2500 × 104 have a poor oil displacement effect in low permeability reservoirs. After the action of the partial quality tool, the injection pressure is reduced by 5.22 MPa, and the oil recovery is increased by 7.79%. The injection pressure of the ASP solution after shearing by the partial quality tool is lower than that of the ASP solution with the same molecular weight and concentration without shearing, but the oil recovery is lower. On the whole, the use of the partial quality tool can obviously improve the oil displacement effect in low permeability reservoirs.

The amount of outdoor particles that indoor environments receive depends on the particle infiltration factors (Fin), peculiar of each environment, and on the outdoor aerosol concentrations and size distributions. The respiratory doses received, while residing indoor, will change accordingly. This study aims to ascertain to what extent such doses are affected by the vertical distance from the traffic sources. Particle number size distributions have been simultaneously measured at street level and at about 20 m height in a street canyon in downtown Rome. The same Fin have been adopted to estimate indoor aerosol concentrations, due to the infiltration of outdoor particles and then the relevant daily respiratory doses. Aerosol concentrations at ground floor were more than double than at 20 m height and richer in ultrafine particles. Thus, although aerosol infiltration efficiency was on average higher at 20 m height than at ground floor, particles more abundantly infiltrated at ground level. On a daily basis, this involved a 2.5-fold higher dose at ground level than at 20 m height. At both levels, such doses were greater than those estimated over the period of activity of some indoor aerosol sources, therefore they represent an important contribution to the total daily dose.

1) Background: The use of linked data in Semantic Web are promising approaches to add value to nutrition research. An ontology, which defines the logical relationships between well-defined taxonomic terms, enables linking and harmonizing research output. To enable the description of domain-specific output in nutritional epidemiology, we propose the Ontology for Nutritional Epidemiology (ONE) according to authoritative guidance for nutritional epidemiologic research; 2) Methods: First, a scoping review was conducted to identify existing ontology terms for reuse in ONE. Second, existing data standards and manuscript reporting guidelines for nutritional epidemiology were converted into ontology, and the terms used in the standards were summarized and listed separately in a taxonomic hierarchy. Third, the ontologies of the nutritional epidemiologic standards, reporting guidelines and the core concepts were gathered in ONE. Three case studies were illustrated for its potential applications. (i) annotation of existing manuscripts and data, (ii) ontology-based inference, and (iii) estimation of reporting completeness in a sample of nine manuscripts; 3) Results: Ontologies for “food and nutrition” (n=33), “disease and special population” (n=86), “data description” (n=21), “research description” (n=32) and “supplementary (meta) data description” (n=44) were reviewed and listed. ONE consists of 339 classes (79 new classes to describe nutrition data and 24 new classes to describe the content of nutrition manuscripts). The case studies demonstrated the application of ONE. 4) Conclusion: ONE is a resource to automate data integration, searching and browsing, and can be used to assess reporting completeness in nutritional epidemiology.

The incorporation of plastic matrix composite materials into structural elements of the aeronautical industry requires contour machining and drilling processes along with metallic materials prior to final assembly operations. These operations are usually performed using conventional techniques, but they present problems derived from the nature of each material that avoid implementing One Shot Drilling strategies that work separately. In this work, the study focuses on the evaluation of the feasibility of Abrasive Waterjet Machining (AWJM) as a substitute for conventional drilling for stacks formed of Carbon Fiber Reinforced Plastic (CFRP) and aluminum alloy UNS A97050 through the study of the influence of abrasive mass flow rate, traverse feed rate and water pressure in straight cuts and drills. For the evaluation of the straight cuts, Stereoscopic Optical Microscopy (SOM) and Scanning Electron Microscopy (SEM) techniques are used inspection techniques have been used. In addition, the kerf taper through the proposal of a new method and the surface quality in different cutting regions have been evaluated. For the study of holes, the macrogeometric deviations of roundness, cylindricity and straightness have been evaluated. Thus, this experimental procedure reveals the conditions that minimize deviations, defects, and damage in straight cuts and holes obtained by AWJM.

Polluted rivers are a primary problem in Changhua County, Taiwan, due to rapid and massive developments in agriculture and industry. In this study, samples consisted of water influent from the Yangzi-Cuo River, Ci-Tong Jiao, Changhua County. Ecology technology, a combination of gravel contact oxidation and surface flow constructed wetlands, was employed to enhance the water quality. Ecology technology is a useful and ordinary process that focuses on original treatment of pollution through chemical, physical, and biological procedures based on the mediums of soil, plant, water, and microorganisms from pure environments. Moreover, this study aimed to minimize the river pollution index (RPI) of the Yangzi-Cuo River by using combinations of gravel contact oxidation and surface flow constructed wetlands. The inflow volume of the water samples in situ was found to be 1534–2261 cubic meters per day (CMD). The pollution in the water sample mostly involved suspended solid (SS), ammoniacal nitrogen (NH₃–N), total phosphorus (TP), total nitrogen (TN), and biochemical oxygen demand (BOD), and the values of the above indexes were found to be 10.0–26.7 mg/L, 0.9–14.0 mg/L, 1.2–14.1 mg/L, 11.1–18.2 mg/L, and 0.5–3.6 mg/L, respectively. Efficiencies of pollution elimination in SS, NH₃–N, TP, TN, and BOD were found to be 24.2–93.1%, 58.3–86.2%, 5.2–85.0%, 59.4–77.2%, and 46.3–76.4%, correspondingly, after purification treatment via ecology technology. Thus, ecology technology is a valid means of purification treatment for polluted rivers.