The paper presents an error model of a measurement chain containing link performing discrete wavelet transform algorithm which is most often the last stage of measurement signal processing. The goal is to determine the uncertainty budget of the input quantities of the wavelet transform algorithm. The error model takes into account parts of analog, analog-to-digital and digital processing, describing the properties of subsequent fragments of the chain using their transmittance and processing functions. The proposed model enables the description of both deterministic and non-deterministic properties of signal errors. The proposed model was validated using an example measurement chain created for this purpose.

This paper proposed three-dimensional numerical simulation method by coupling of electrostatic and fluid fields to evaluating the performance of electrical sensor in the concentration measurement of gas/solid two-phase flow. Compared with the static numerical simulation, this real-time dynamic 3-D simulation method can research on a designed capacitance sensor combining the dynamic characteristics of the two-phase flows for concentration measurement. Several fluid-electrostatic models of transmission pipes with different sensor structures are built. Under different test positions and different particle concentrations, the flow characteristics and the corresponding electric signals can be obtained, and the correlation coefficient between the concentration values and the capacitance values are used for performance evaluation of the sensors. The effects of flow regimes on concentration measurement are also been investigated in this paper. To validate the results of simulation, an experimental platform with horizontal straight pipe for phase volume concentration measurement of solid/air two-phase flow is built, and the experimental results agree well with simulation conclusions. The simulation and test results show that the coupling models can give constructive reference opinions for the sensor design and collection of installation position in different transmission pipelines, which are very important for the practical process of pneumatic conveying system.

In higher education, the cultivation of research competency is pivotal for students’ critical thinking development and their subsequent transition into the professional workforce. While statistics plays a fundamental role in supporting the completion of a research project, it is often perceived as challenging, particularly by students in majors outside mathematics or statistics. The connection between students’ statistical proficiency and their research competency remains unexplored despite its significance. To address this gap, we utilized the supervised machine learning approach to predict students’ research competency, as represented by their performance in a research methods class, with predictors of students’ proficiency in statistical topics. Predictors relating to students’ learning behavior in a statistics course such as assignment completion and academic dishonesty are also included as auxiliary variables. Results indicate that the three primary categories of statistical skills—namely, understanding of statistical concepts, proficiency in selecting appropriate statistical methods, and statistics interpretation skills— can be used to predict students’ research competency, as demonstrated by their final course scores and letter grades. This study advocates for strategic emphasis on the identified influential topics to enhance efficiency in developing students’ research competency. Findings could inform instructors in adopting a strategic approach to teaching the statistical component of research for enhanced efficiency.

This article is about a framework for determining the degree of realism of any given 1 passenger ride motion discomfort measurement formula. After providing some context and reviewing 2 evidence of deficiency in currently popular ride motion discomfort measurement formulas, the article 3 outlines the research program that needs to be carried out in order to establish such a framework. 4 The research begins with gathering recordings of uncomfortable ride motion episodes encountered in 5 a chosen type of passenger transport service. It then has test subjects compare the episodes via a ride 6 motion simulator and adjust their amplitudes pair wise until they cause equal discomfort. It explains 7 how to take the pair wise amplitude adjustments and determine amplitude adjustments that bring all 8 of the motion episode recordings to a common level of discomfort so that they form a normalized set. 9 Then, the lower the scatter of the scores assigned by any given discomfort measurement formula to 10 the members of that set, the more realistic that formula will be for the chosen service.

The building envelope has the most significant contribution in the reduction of the building energy consumption. Application of new, alternative and improved materials and systems has an important impact on the buildings performances. This paper is focused on the thermal transmittance, as an indicator of the thermal conductance of the construction element. It includes comparisons of the U-values, calculated by software, with those measured in situ on three representative façade walls. The walls have been constructed with the new wall system Fragmat NZ-1, a new product in Macedonian buildings. This research provides basic information on the thermal transmittance of the system. The results of the analysis show that the in situ measuring is a useful tool in validation of the precision of analytically calculated values, since it was difficult to obtain precise results from the analytical calculations only, especially when the layers are with non-uniform thickness.

The mechanism underlying microbiologically induced carbonate precipitation have not been thoroughly characterized, although numerous scholars and experts have specifically investigated questions regarding minerals induced by bacteria. The study of the precipitation of carbonate minerals induced by halophilic bacteria has aroused wide concern. The present study aimed to investigate the characterization and process of biomineralization in high salt systems by a halophilic bacterium, Chromohalobacter israelensis strain LD532 (GenBank: KX766026), which was isolated from the Yinjiashan Saltern in China. Carbonate minerals induced by LD532 were investigated in several sets of comparative experiments that employed magnesium sulfate and magnesium chloride as Mg resources. Magnesium calcite and aragonite were induced by LD532 bacteria, whereas these minerals did not appear in the control group. The mineral phases, micromorphologies, and crystal structures were analysed using X-ray powder diffraction, scanning electron microscopy, and energy dispersive X-ray detection. The carbonic anhydrase and urease secreted by strain LD532 through metabolism increased the pH value of the liquid medium and promoted the process of carbonate precipitation. Further study using high resolution transmission electron microscopy, energy dispersive X-ray detection and analysis of ultrathin slices showed that the nucleation sites of carbonate minerals were located on extracellular polymeric substances and the membranes of intracellular vesicles of LD532 bacteria, which provided favourable conditions for the growth of carbonate mineral crystals. The morphologies and compositions of minerals formed in solutions of MgSO₄ and MgCl₂ display significant differences, indicating that different sources of Mg²⁺ may also affect the physiological and biochemical activities of microorganisms and thus mineral deposition. This study will be of some interest for the interpretation of carbonate biomineralization in natural salt environments and has some value as a reference in understanding sedimentary carbonates in ancient marine environments, such as tidal flats.

The up-to-date challenge towards clean road transport are non-exhaust emissions. Important advances regarding measurement systems, including well defined characterisation techniques, as well as regulation, will happen in the next few years. In this work we present detailed results of particle emissions from a test bed for wheel suspension and brakes, consisting of aerosol (size distribution, particle number (PN) and mass (PM)) and electron microscopy measurements (EM) under different load conditions. Standard tyres and brakes from series production were tested with a high-load driving cycle while particle measurements were conducted by gravimetric measurements and with a TSI SMPS, a TSI APS and a GRIMM OPS. Furthermore, samples were analyzed by electron microscopy. A bimodal particle size distribution (PSD) was obtained with the SMPS, with peaks at 20nm and around 400nm. EM analysis of >1400 single particles from the electrostatic sampler matches the PSD results. EM analysis also showed ultrafine particles, mainly from O, Fe, Si, Ba, Mg and S and also fractal particles with high C fractions. Our results suggest, in agreement with previously published literature, that particulate emissions are related to brake disc temperature and occur in significant amounts above a threshold temperature.

The paper presents a method to assess the effect of electrolyte additives on the energy capacity of Pb-acid batteries. The method applies to any chemically unreactive additive, including suspensions and gels. The approach is thermodynamically based and it leads to the definition of a region of admissible concentrations –the battery’s admissible range– where the battery can undergo an indefinite number of charge/discharge cycles without suffering permanent damage. An experimental procedure to determine this range is presented. The obtained results provide a way to assess the potential of electrolyte additives to improve the energy capacity of Pb-acid batteries. The same results also provide a means to determine the additive concentration that produces the maximum energy capacity increase of the battery. The paper closes with an example of application of the proposed approach to a practical case.

The increasing regulatory pressure to monitor and reduce GHG emissions and air pollutants requires cost-effective methods for their surveillance. The most common technique used for scientific investigations on gas concentration monitoring in barns are accurate but expensive and with a complex maintenance. This research study analysed the potential use of a low-cost portable measurement devices for the measurement of ammonia (NH3) and carbon dioxide (CO2) concentrations in an open dairy barn. A comparison between gas concentrations acquired at different heights from the floor by using portable devices and those acquired by a photoacoustic infrared multigas spectroscope (i.e., reference measurement) in the same sampling locations was carried out to determine the precision of the low-cost portable devices. The performance of low-cost portable devices was statistically analysed by the application of the one-way analysis of variance, correlation analysis and regression analysis. The results showed a significant difference between gas concentration values at various heights from the floor for both NH3 and CO2. The correlations between concentrations acquired by the low-cost portable device and the INNOVA were statistically significant (r=0.83; P<0.001) for gas concentrations monitored at 0.4 m from the floor. Compared with the reference measurement device, the low-cost devices were effective in the monitoring of NH3 concentrations at 0.40 m from the floor though it underestimated them in the barn at increasing of the height from the floor, whereas the device was not adequate for CO2 concentrations. In detail, the relative measurement error of the low-cost devices compared to INNOVA was reduced close to the floor during NH3 concentration measurements. Within these limitations, this device could be useful for monitoring NH3 concentration in the barn and to assess variation in NH3 concentrations mainly related to the animal occupied zone. Further efforts are needed in this field of research to identify low-cost device that could simplify emission estimation from open dairy barns.

The scope of this study was twofold: first, to introduce a new method in examining measurement invariance, especially with large-scale studies where a large number of group comparisons are involved: the alignment approach, where only configural invariance is necessary to achieve measurement invariance. Second, to evaluate the psychometric robustness of this approach using real-life data. Particularly, we applied this approach to examine whether the factor structure of a cognitive ability test (PGAT) exhibits measurement invariance across the 26 universities of the Kingdom of Saudi Arabia. The sample consisted of 9,849 graduate students from 26 universities around the Kingdom. The results indicated a robust configural model suggesting that the P-GAT subscales were invariant across the 26 universities. Finally, the aligned factor mean values were estimated, and factor mean comparisons of every group’s mean with all other group means were conducted for both cognitive domains (Verbal and Quantitative). In both domains, King Saud University had the highest mean score among all universities. Moreover, its mean factor score was significantly higher than any other university besides Dammam University. On the other hand, several universities allocated at the northern and Southern borders of the country exhibited the lowest factor mean scores.

Objective: This study aimed to demonstrate the availability of portable devices for nasal FeNO measurement, which could replace exhaled NO measurement based on the continuous aspiration of multiple flow measurement systems. Methods: A descriptive cross-sectional study. The healthy subjects without rhinosinusis disorders (control group) and those with diagnosed allergic rhinitis (AR group) were enrolled in the study. They underwent nasal and bronchial FeNO measurements by both fixed flow NObreath® connected to nasal mask and multiple flows HypAir FeNO®. Results: A total of 153 people were recruited including 63 healthy subjects and 90 subjects with AR. There were no statistically significant differences in anthropometric characteristics between the two groups (P > 0.05). There were a significant increase in FeNO values in the AR group compared to the control group; concentrations of nasal and bronchial FeNO mearsured by NObreath® were 76.0 ± 50.7 ppb (vs 36.0 ± 28.1 ppb, P < 0.01) and 32.3 ± 15.4 ppb (vs 9.2 ± 5.6 ppb, P < 0.001), and those mearsured by NObreath® Hypair FeNO® were 1796.9 ± 523.3 ppb (vs 400.2 ± 123.1 ppb, P < 0.001) and 37.3 ± 23.0 ppb (vs 17.4 ± 18.3 ppb, P < 0.01). A weak correlation between the values measured by NObreath® and Hypair FeNO® devices was observed (r = 0.023 and r = 0.089, respectively; p < 0.05). Conclusions: The handheld NObreath® device is effective in measuring FeNO concentrations in both normal subjects and AR patients. The advantages in price and size, creating a compact, low-cost device that is convenient for use and research.

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.

The group delay response of chirped fiber Bragg gratings (CFBG) written in polarization-maintaining fiber can be measured using the beat spectrum of the reflections from the two polarization axis, with a resolution and reproducibility better than 50 fs. The method is theoretically described, and we analyze the effect of group delay ripples (GDR) on the performance of a stretcher-compressor pair used in chirped pulse amplification systems. Ripples with a spectral period of the order of the pulse bandwidth are the most deleterious. Those are readily captured with our method, despite the limit on resolution due to the fiber polarization beat length. As a rule of thumb, the GDR should not exceed half the pulse duration. The reconstructed phase of the CFBG is also used to predict the pulse compression performance for a given device. Measurement of GDR as low as 161 fs is experimentally demonstrated.

The relation between CO2 emissions and atmospheric CO2 concentration has traditionally been treated with more or less complex models with several boxes. Our approach is motivated by the question of how much CO2 must necessarily be absorbed by sinks. Observations lead to the model assumption, that carbon sinks like oceans or biosphere are linearly dependent on CO2 concentration on a decadal scale. In particular this implies the falsifiable hypothesis that oceanic and biological CO2 buffers have not significantly changed in the past 50 years and are not saturated in the forseeable future. The simple model with 2 parameters explains very well the CO2 emission and historical CO2 concentration data. The model gives estimates of the natural emissions, the pre-industrial CO2 equilibrium concentration levels, the half-life time of an emission pulse, and the future CO2 concentration level from a given emission scenario. This is validated by an ex-post forecast of the last 20 years. The important result is that with the stated polices scenario of the IEA future CO2 concentrations will not rise above 475 ppm. The model is compared with the Carbon modul of the Bern model, mapping their complex IRFs to a single time variant parameter.

Tumor to stroma ratio is a highly debated prognostic factor in the management of several solid tumors and there is no universal agreement on its practicality. In our study we proposed to confirm or dismiss the hypothesis that a simple measurement of stroma quantity is an easy-to-use and strong prognostic tool. We have included 74 consecutive patients with colorectal cancer who underwent primary curative abdominal surgery. The tumors have been grouped into stroma-poor (stroma &lt;10%), medium-stroma (between 10 and 50%) and stroma-rich (over 50%). The proportion of tumor stroma ranged from 5% to 70% with a median of 25%. Very few, only 6.8% of patients had stroma-rich tumors, 4% stroma-poor tumors and 89.2%tumors with a medium quantity of stroma. The proportion of stroma, at any cut-off, had no statistically significant influence on the disease specific survival. This can be explained by the low proportion of stroma-rich tumors in our patient group and the inverse correlation of stroma proportion with tumor grade. The real-life proportion of stroma-rich tumors and the complex nature of the stroma-tumor interaction has to be further elucidated.

1) Landsat operational land imager (OLI) data and consequent laboratory measurements were used to predict Chlorophyll-a (Chl-a) concentration and the trophic states for an inland lake within the East Kolkata Wetland, India; 2) The most suitable band ratio was identified by performing Pearson correlation analysis between Chl-a concentrations and possible OLI band and band ratios from the study points; 3) The results showed highest correlation coefficient from the band ratio OLI5/OLI4 with an R value of 0.85. The prediction model was then developed by applying regression analysis between the band ratio OLI5/OLI4 and Chl-a concentration of the study points. The reflectance ratios of the validation points were given as input on the prediction model and the model output was considered as predicted Chl-a values of the validation points to check the efficiency of the prediction model. The regression model between laboratory-derived Chl-a value and model-fitted Chl-a value of the validation points revealed a high correlation with an R² value of 0.78. Trophic State Index (TSI) of the lake was also calculated from laboratory-derived Chl-a value and model-fitted Chl-a value of the validation points. The study presented a high correlation of TSI determined from predicted data with TSI from laboratory reference data (R = 0.88). The TSI values of the lake ranged from 65 to 75 which indicate that the lake is appeared to be eutrophic to hypereutrophic conditions. 4) This empirical study showed that Landsat 8 OLI imagery can be effectively applied to estimate Chl-a levels and trophic states for inland lakes.

Energy Measurement and Verification (M&V) aims to make inferences about the savings achieved in energy projects, given the data and other information at hand. Traditionally, a frequentist approach has been used to quantify these savings and their associated uncertainties. We demonstrate that the Bayesian paradigm is an intuitive, coherent, and powerful alternative framework within which M&V can be done. Its advantages and limitations are discussed, and two examples from the industry-standard International Performance Measurement and Verification Protocol (IPMVP) are solved using the framework. Bayesian analysis is shown to describe the problem more thoroughly and yield richer information and uncertainty quantification than the standard methods while not sacrificing model simplicity. We also show that Bayesian methods can be more robust to outliers. Bayesian alternatives to standard M&V methods are listed, and examples from literature are cited.

This paper presents a novel approach to power management techniques in energy storage system (ESS) interoperability with the energy power system (EPS) by inserting a SCADA controlled directional protection relay for improving the mode switching sequence. According with latest European standards, all necessary measures for re-synchronization and reconnection for health work of the system must be taken. The proposed approach intends to improve the “interface” between storage systems and electric power grid by using a directional relay which provides interoperability improvement by automatic recognizing and differentiating the switching sequence of the mode of operation from the fault mode. Simulated results from a small scale electrical generating system are provided. The results demonstrate that the proposed power management solution is technically ideal to achieve high quality energy while retaining the stability of the power grid network. The interoperability of PHS systems integrated with the electric power grid usually leads to perturbations in terms of frequency of the generated voltage, and for improving it we designed an automatic treating and re-connecting software module. This work regards the importance of producing electricity from green and renewable energy sources, while retaining the stability and reliability of the power grid. ESS systems are widely used to help balancing of intermittent forms of load demand on the electrical power grid at specific key moments. In this article, the pumped hydro storage (PHS) technologies are proposed as an economical way to utilize smoothly the off-peak energy or surplus energy, by pumping water to a reservoir at a higher level. During peak load periods, the stored water is discharged through the reversible pump-turbine to generate electricity to meet the peak demand controlled by designed SCADA application.

This study examines the absorption and concentration of anthracene (AN) in the garden radish. Studies were conducted to grow radishes from the sowing stage in soil contaminated with AN, and to grow radishes in soil contaminated with AN following maturity (27 days after sowing). For the growth in AN-containing soil from sowing onward, AN levels immediately after seeding ranged from 12,500-36,300 ng/g-ww. AN concentrations during growing period ranged from 7140-16,000 ng/g-ww in soil and from 38.2-2160 ng/g-ww in radish, respectively. For the growth in AN-containing soil after maturity, AN concentrations in soil and radish ranged from 9560-22,100 ng/g-ww and 342-2270 ng/g-ww. The concentrations of AN in the roots and leaves had a higher density than those in the stems. In these experiments, positive relationships between AN levels in soil and radishes were observed. It is inferred that the greater the degree of soil contamination, the greater the effect on the amount of AN assimilated by the radishes. The concentration ratio (radish-to-soil; Cr/Cs) decreased exponentially with days since AN application. This indicates that the concentration ratio is affected by time in contact with AN. According to the results for the change over time of Cr/Cs and contents by radish part, it is thought that AN in the soil has good absorption through the roots to circulate within the organism, and is preferentially distributed and accumulated in the roots and leaves, which have high organic matter content.

This paper evaluates the potential of solar concentration technologies—compound parabolic collector (CPC), linear Fresnel collector (LFC) and parabolic trough collector (PTC)—as an alternative to conventional sources of energy for industrial processes in Latin America, where high levels of solar radiation and isolated areas without energy supply exist. The analysis is addressed from energy, economic and environmental perspective. A specific application for Argentina in which fourteen locations are analyzed is considered. Results show that solar concentration technologies can be an economically and environmentally viable alternative. Levelized cost of energy (LCOE) ranges between 2.5 and 16.9 c€/kWh/m² and greenhouse gas (GHG) emissions avoided range between 33 and 348 kgCO₂/(m²·year). CPC technology stands out as the most recommendable technology when the working fluid temperature ranges from 373K to 423K. As the working fluid temperature increases the differences between the LCOE values of the CPC and LFC technologies decrease. When 523K is reached LFC technology is the one which presents the lowest LCOE values for all analyzed sites, while the LCOE values of PTC technology are close to CPC technology values. Results show that solar concentration technologies have reached economic and environmental competitiveness levels under certain scenarios, mainly linked to solar resource available, thermal level requirements and solar technology cost.

Models of quantum measurements are presented, including observers subject to the laws of quantum mechanics. Observers perform multiple measurements in an attempt to disprove the collapse hypothesis. It is shown that under reasonable assumptions the effort cannot succeed. Under a unitary evolution the end state is a correlation between the result of the first measurement and the result(s) of the others, consistent with the observer's collapse hypothesis. The observer may conclude that the laws of nature include a non-unitary collapse mechanism, even if one does not actually exist. Discard of information is the crucial factor which distinguishes entanglement from measurement.

A variant of the von Neumann-Wigner Interpretation is proposed. It does not make use of the familiar language of wave functionsand observers. Instead it pictures the state of the physical world as a vector in a Fock space and, therefore not, literally, a functionof any spacetime coordinates. And, rather than segregating consciousness into individual points of view (each carrying with it asense of its proper time), this model proposes only unitary states of consciousness, Q(t), where t represents a fiducial time withrespect to which both the state of the physical world and the state of consciousness evolve. States in our world's Fock space areclassified as either 'admissible' (meaning they correspond to definite states of consciousness) or 'inadmissible' (meaning they donot). The evolution of the state vector of the world is such as to always keep it restricted to 'admissible' states. Consciousness istreated very much like what Chalmers calls an "M-Property." But we try to show that problems with the quantum Zeno effect do not arise from this model.

Background: It is known that Preeclampsia affects the lactogenesis. However, data on effects of this pathology on the human milk neurobiomarkers composition are not available. The aim of this study is to investigate the effects of this gestational pathology on Activin A levels, a neurobi-omarker known to play an important role in the development and protection of the central nerv-ous system. Methods: The women recruited were divided in two different study groups: preeclamptic or normotensive women. All the human milk samples were collected using the same procedure. Activin A was quantified using an ELISA test. To investigate the effect of Preeclampsia on the Activin A concentration in the 3 lactation phases, mixed linear model with unistructural covariance structure, mother as random effect, and fixed effects were performed. Results: Activin A was detected in all samples. There were no significant differences between Preeclamptic and Normotensive women. The only significant effect is related to the lactation phase: it is significant the difference between colostrum and mature milk (p<0.01). In conclusion these results allow us to affirm that breast milk beneficial properties are maintained even if preeclampsia occurs.

Different values of the Hubble constant for extragalactic objects are not considered here. We give a number of examples of the extreme accordance of expansion rates of different fields of knowledge with the cosmological expansion rate. The coincidence of the expansion rates means that a common cause is almost inevitable. All these examples are gravitationally bound in themselves and in this case are subject to cosmological expansion. According to standard theory, this should not happen. We therefore question the common boundary of gravity and expansion for both theoretical and observational reasons and conclude that all gravitationally dominated objects participate in cosmological expansion or scale drift, contrary to general doctrine. The space expands with its contents while numerically maintaining distance, radius, rotation time and density. What is generally interpreted as an expansion is obviously a scale drift with a drift rate that corresponds to the size of the Hubble constant. The Earth is subject to expansion and scale drift. This results in numerically constant measured values. This drift apparently also applies to distant galaxies and other objects. The cosmological red shift is not interpreted here as a Doppler effect and numerical increase in distances, but in accordance with standard theory as an expansion or drift of the space-time scale. The expansion of the radii of galaxies makes the assumption of dark matter superfluous. The continents and our everyday environment are not subject to expansion or scale drift.

As a model for economic and ecological systems, replicator dynamics represents a basic form of agent competition for finite resources. Here, we investigate the effects of stochastic resetting in this kind of processes. Random reset events abruptly lead individual resources to a small value from which dynamics must start anew. Numerical results show that resource distribution over the population of competing agents develops highly nonuniform profiles, exhibiting clustering and fluctuations with anomalous dependence on the population size. This non-standard statistical behavior jeopardizes an analytical treatment based on mean-field assumptions. We propose alternative simplified analytical approaches which provide a stylized description of entropy evolution for the clustered distribution of resources and explain the unusually slow decrease of fluctuations.

To achieve efficient utilization of low-concentration mine gas, reduce resource waste, and alleviate environmental pollution, high-temperature oxidation of low-concentration gas at a concentration range of 1.00% to 1.50% that is directly discharged into the atmosphere during coal mine production was oxidized to recover heat for reuse. The gas oxidation equipment was improved for the heating process, and the safety of low-concentration gas oxidation under high-temperature environment was evaluated. Experimental results showed that the reactor could provide a 1000 ℃ high-temperature oxidation environment for gas oxidation after installing high-temperature resistant ceramics. The pressure variation curves of the reactor with air and different concentrations of gas were similar. Due to the thermal expansion, the air pressure slightly increased and then returned to normal pressure. In contrast, the low-concentration gas exhibited a stable pressure response in the high-temperature environment of 1000 ℃. The outlet pressure was significantly greater than the inlet pressure, and the pressure difference between the inlet and outlet exhibited a trend to increase with the gas concentration. The explosion limit varied with the temperature and the blend with oxidation products. The ratio of measured gas pressure to air pressure after oxidation was below the explosion criterion, indicating that the measured concentration gas is still safe after the shift of explosion limit, which provides a safe concentration range for efficient use of low-concentration gas in the future.

The present work studies the concept of productivity in shipbuilding and how it should be measured. The existing metrics, shipbuilding process and shipyard organization were studies in order to choose the most adequate metrics which would allow the measuring of a shipyard productivity in a systematic and holistic way. This is achieved by gathering the man-hours spent in each ship organized by cost centre and using Compensated Gross Tonnages as the measure of output from the shipyard. Data was gathered for thirty ships built in the same European yard organized by cost centre. From the data collected it was found that the ratio of hours spent in outfitting to the hours spent in structures is proportional to the complexity of the ship. There was also opportunity to study the work reduction resulting from building ships in series and the shares of labour for ships series and across ship types.

Qualitative and quantitative values estimation is a crucial aspect of social data science and plays a vital role in social and psychological research. Numerous methods of personal values measurement such as Schwartz Value Survey (SVS) and its re-modified versions have been proposed and invented, but many are challenged with one or more limitations. In this article, an alternative approach in a new paradigm of values measurement called Kabiru’s Value Survey (KVS) was proposed to measure the relative degree of importance or significance attached to particular value-actions of an individual(s) in a given population over a period. The methodological innovations in KVS unlike other existing methods of human value measurement include the use of habitually reported practices associated with a particular value-action in place of judging the series of Schwartz hypothetical statements, the use of multiple dependent variables rather than a single coded hypothetical statement. In terms of data analysis, a new approach of multivariate compression is introduced which merges the chain of multiple dependent variables into one coded scale. Psychometric result interpretation is also another innovative aspect of KVS methodology. Finally, the proposed methodology however solved some of the criticized limitations of the other methods of human value measurement.

Shrubs are a significant component of urban vegetation residing in parks, but they experience various influences of biotic and abiotic agents, among which aphids play an important role. In this work, the effect of aphid colonization on three shrub species in urban environment was examined. Fourteen parameters have been analyzed, describing photosynthetic pigment content and gas exchange to carbon, nitrogen, and hydrogen partition. While no significant effect of colonization was found on photosynthetic pigment parameters, the effect was significant on gas exchange parameters. The strongest effect aphid colonization achieved on nitrogen partition and C/N ratio, parameters that could be suggested in further similar studies. All parameters were classified in two groups according to principal component analysis, suggesting correlation between nitrogen and carbon content, C/N ratio, measured gas exchange parameters and chlorophyll a content. The ratio between net photosynthesis and dark respiration (A/K) was in the second group, suggesting that this parameter provide additional information on the effect of aphid colonization, and deserve special attention in further studies. There were differences in reaction of examined shrub species, where the strongest reaction by gross primary productivity (GPP) achieved Hybiscus syriacus, and by nitrogen partition and C/N ratio Spirea trilobata and Cydonia japonica.

Beer fermentation is typically monitored by periodic sampling and off-line analysis. In-line sensors would remove the need for time-consuming manual operation and provide real-time evaluation of the fermenting media. This work uses a low-cost ultrasonic sensor combined with machine learning to predict the alcohol concentration during beer fermentation. The highest accuracy model (R2=0.952, MAE=0.265, MSE=0.136) used a transmission-based ultrasonic sensing technique along with the measured temperature. However, the second most accurate model (R2=0.948, MAE=0.283, MSE=0.146) used a reflection-based technique without the temperature. Both the reflection-based technique and the omission of the temperature data are novel to this research and demonstrate the potential for a non-invasive sensor to monitor beer fermentation.

The mass concentration of particulate matter (PM) has been systematically used in epidemiological studies as exposure indicator, to relate airborne concentrations with a wide variety of human health effects, which can be hardly explained by using this single parameter. In fact, PM is a “particle cocktail” that includes a complex mixture of compounds with a wide range of sizes, chemical compositions and emission sources. Current research hypothesizes that many of the adverse health effects are derived from oxidative stress in biological systems caused by the deposition of PM into the lungs. This emerging hypothesis is called the oxidative stress paradigm. In this commentary article we analize how this new paradigm could help to answer the as-of-yet unanswered questions related to the mechanism of action of PM pollution on human health. Acellular oxidative potential (OP) assays have been emerged as a promising approach to quantify the PM potential to induce oxidative stress and to relate it with the chemical composition and size distribution of PM. Recent researches have shown that the OP is related to the presence of metals, organic carbon, polyaromatic hydrocarbons and quinones. However, the association between PM and particle-induced toxicity is still largely unknown. Therefore, additional research is needed to identify the specific PM characteristic(s), such as its specific size, emission source or chemical content, which contribute the most to its redox activity. Thus, the OP measurements provide information that allows us to evaluate and integrate the toxic potential of PM in a unique parameter, whose relationships with emission sources, size distribution and/or chemical composition should be faced in the near future.

Starting with unitary quantum dynamics, we investigate how to add quantum measurements. Quantum measurements have four essential components: the furcation, the witness production, an alignment projection, and the actual choice decision. The first two components still lie in the domain of unitary quantum dynamics. The decoherence concept explains the third contribution. It can be based on the requirement that witnesses reaching the end of time on the wave function side and the conjugate one have to be identical. In this way, it also stays within the quantum dynamics domain. The surjection hypothesis explains the actual choice decision. It is based on a two boundary interpretation applied to the complete quantum universe. It offers a simple way to reduce these seemingly random projections to purely deterministic unitary quantum dynamics, eliminating the measurement problem.

In order to enhance the accuracy of the relative velocity measurement for the Mars explorer formation flight, we develop a relative velocity measurement method. In this method, the spectrometers at two Mars explorers are adopted to measure the starlight frequency shift and to estimate the velocity with respect to the star. Unfortunately, the instantaneous velocity of star can not be predicted accurately, which results in a large error in the velocity measurement. The difference of these two velocities, which does not include the proper motion of star, is the relative velocity between a pair of Mars explorers at the direction of the star. However, this navigation method can not work alone because of unobservability. To make the navigation system observable and improve the accuracy of both absolute and relative navigation for the Mars explorer formation flight, we combine it with X-ray pulsar navigation and the inter-satellite links, and propose an autonomous integrated navigation method with observability. In this integrated navigation scheme, the extended Kalman filter is adopted to deal with the relative velocity, the inter-satellite links and the pulse time-of-arrival, and estimate the absolute and relative navigation information for the Mars explorer formation flight. The simulation results demonstrate that both absolute and relative navigation accuracy of the proposed method are higher than that of the pulsar navigation, especially the relative one.

Objective: To explore the inter-rater reliability of the Measurement Of adherence Via Exercise Demonstration (MOVED) adherence tool. Design: Reliability study of a patient adherence measurement tool.Setting: Simulated physiotherapist-patient consultations. Participants: Sixteen experienced physiotherapists rated patient adherence to exercise. Interventions: N/A Main Outcome Measure: Inter-rater reliability of MOVED.Methods: The MOVED tool consists of two parts. Part one asks patients to self-report their adherence to exercise dose (including number of completed sessions, sets and repetitions in the last seven days). Part two asks patients to demonstrate each exercise. Component scores are totalled to give an overall level of patient adherence to each exercise.Participants were provided with a copy of five physiotherapist-prescribed exercises. Participants were then shown five corresponding video vignettes of simulated physiotherapist-patient consultations where patients were asked to self-report exercise frequency, sets and repetitions and demonstrate each exercise within the context of a consultation. Participants were asked to rate the level of patient adherence to each of the five exercises using the MOVED tool. Inter-rater reliability of MOVED scores was assessed using Intraclass Correlation Coefficient (ICC) and 95% Confidence Intervals. Results: The ICC of part one (self-report) was .90 (95%CI .74-.98), part two (demonstration) was .98 (95%CI .94-.99) and total score was .96 (95%CI .88-.99), demonstrating excellent inter-rater reliability. Conclusion: The MOVED tool, which can highlight whether patients are adhering to exercise technique as well as exercise dose, may provide clinicians and researchers with a more robust measure of exercise adherence when compared with other measures currently available.

Spider silk has excellent strength and elasticity in natural, researchers have been working for decades try to achieve natural spider silk outstanding mechanical properties using recombinant spider silk protein (spidroin) through artificial spinning. In this work, we chose wet spinning method to explore the relationship between concentration of coagulation bath and fiber performance. It was found that the concentration of methanol has important effect on fiber continuity, diameter and mechanical properties. Lower concentration favors spinning continuous thinner, fibers with high strain. Secondary stretching benefits spinning silk fibers with stable mechanical properties, and thermal stability. Through applying different methanol concentration and additional stretching, we obtained silk fibers with Young’s modulus of 3.052± 2.626 GPa, stress of 25.3944 ± 17.48 MPa, and strain of 140 ± 95.4%.

The concentration of cerebrospinal fluid total protein (CSF-TP) is important for the diagnosis of neurological emergencies. Recently, some Western studies have shown that the current upper reference limit of CSF-TP is quite low for older patients. However, little is reported about the concentration of CSF-TP in older Asian population. In this study, we retrospectively analyzed the CSF-TP concentrations in Japanese healthy older volunteers. CSF samples in 69 healthy Japanese volunteers (age range: 55–73 years) were collected by lumbar puncture, and the data of CSF were retrospectively analyzed. The mean (standard deviation) CSF-TP was 41.7 (12.3) mg/dL. The older group (≥ 65 years old) had higher CSF-TP concentration than the younger group (55–64 years old). The 2.5th percentile and 97.5th percentile of CSF-TP were estimated as 22.5 and 73.2 mg/dL, respectively, which were higher than the current reference range in Japan (10–40 mg/dL).

MEMThe PdNi film hydrogen sensors with Wheatstone bridge structure were designed and fabricated by the micro-electro-mechanical system (MEMS) technology. The integrated sensors consisted of four PdNi alloy film resistors. The interval two of them were shielded with silicon nitride film and used as reference resistance, while the others were used for hydrogen sensing. The PdNi alloy films and SiN films were deposited by magnetron sputtering. The morphology and microstructure of the PdNi films were characterized with X-ray diffraction (XRD). The output resistance signal was converted to millivolt output voltage signal for easy data acquisition. Hydrogen (H2) sensing properties of PdNi film hydrogen sensor with Wheatstone bridge structure was investigated under different temperatures (30℃, 50℃ and 70℃) and H2 concentrations (from 10 ppm to 0.4%). The hydrogen sensor demonstrated good response at different hydrogen concentrations and high repeatability in cycle testing under 0.4% H2 concentration. Under 10ppm hydrogen, the PdNi film hydrogen sensor had evident and collectable output voltage of 600 μV.

The kinetics and efficacy profiles of photoinitiated polymerization are theoretically presented. For the same dose, lower light intensity achieves a higher steady-state-efficacy (SSE) in type-I; in contrast, type-II has an equal SSE. Higher light intensity has a faster rising efficacy, due to faster depletion of photoinitiator (PS) concentration. However, type-II process is also affected by the available oxygen. Higher light intensity produces more efficient singlet oxygen, resulting a higher transient efficacy, in which all intensities reach the same SSE when oxygen is completely depleted. With external oxygen, type-II efficacy increases with time, otherwise, it is governed only by the light dose, i.e., same dose achieves same efficacy. Moreover, type-II has an efficacy follows Bunsen Roscoe law (BRL), whereas type-I follows non-BRL. The measured type-I efficacy and gelation profile are analyzed by our analytic formulas. Schematics of the photocrosslinking stage defined by the availability of oxygen is developed, where both type-I and –II coexist until the oxygen is depleted. The overall efficacy may be enhanced by resupply of PS or oxygen during the light exposure. The roles of light dose and PS concentration on the efficacy of photoinitiated polymerization should be are governed a new concept of a volume efficacy (Ve), defined by the product of the crosslink (or gelation) depth (CD) and local [efficacy].

One of the most popular techniques for determining electrical properties of material is the free-space measurement technique. With the potential for new applications requiring efficient, accurate and broadband material measurement systems using higher millimeter-wave and terahertz frequencies, the free-space measurement method has received renewed interest. This is mainly due to its simplicity, favorable properties as a non-destructive method, and it allows transmission and reflection measurements without any physical contact with the sample. This paper reviews and discusses state- of-the-art free space material measurement systems, starting with the different measurement techniques available for material characterization, their important concepts, post-processing in determining their properties, and progress towards expanding their use at higher frequencies. Also, this paper reviews dielectric material characterization using the free space method focusing on their application extension towards the higher frequencies. Besides, the algorithms for conversion methods and usage of lens in free space material measurement system was discussed in this paper. Finally, a future perspective on the outlook of this free space method is presented prior to the conclusion.

Acquisition of real-time hydraulic data is an essential component for flood forecasting. However, we frequently face difficulties in obtaining discharge data using classical contact methods during high magnitude floods and for systems experiencing rapid hydro-geomorphological adjustment. Therefore, we developed low-cost, non-contact sensors and platforms that are designed to overcome these difficulties. These advances enable flood flow properties to be monitored at multiple locations across a river catchment, at low-cost, and communicated in near real-time by using an image velocimetry method. This is an optics-based approach for stream flow measurement using commercially available near-infrared digital cameras to acquire video footage in full HD (30fps). Video footage is then subjected to optical flow tracking techniques based on cross-correlation, and feature-based tracking, enabling the displacement rates of detected features (for example natural foam, seeds, woody debris, and turbulent structures) to be computed. This manual provides step by step guidance to install an image-based gauging station. It contains the list of necessary components, the calibration process of a new camera and the assembly procedure of the system.

Self-report measurement is frequently used in human sports to assess training adaptations [1, 2]. This is a technique novel to the equestrian sport. The aim of this study was to describe how elite event riders of Germany evaluate their own fitness as well as that of their horses for the entire duration of an eventing season. Additionally, correlations with possible influencing external factors such as type of training or duration of grazing were also investigated. Short online questionnaires were used to allow eight riders to describe the training of their horses. Five criteria (general performance, ability to concentrate, general state of mind, general muscular condition and emotional wellbeing) were used to assess both, their horse's, as well as their own wellbeing. A 1-10 rating scale was used to score each criterion resulting in an average of 38 points out of 50 (maximum wellbeing) for horse (Std. dev. 0.55) and rider (Std. dev. 0.65) respectively. A total of 120 questionnaires were analysed. A correlation could be demonstrated (Spearman's correlation coefficient = 0.5) between rider and horse score, whereby it only became a linear correlation above 30 points. In addition, the horse score correlates positively with its success at competitions. While the horses were rated similarly throughout the season, the riders’ perceived welfare was higher in the middle of the season compared with the beginning and end of the season. Regularly turned-out horses resulted in higher horse scores (Linear mixed model, p=0,04, n=120). It can be concluded that the self-report measurement of fatigue and wellbeing can be a useful tool for trainers and riders to better determine the horse’s fatigue and recovery. It should be noted that external factors influence both, rider and horse assessment.

Introduction and Problem: With conventional mechanical rotation measurement of joints, only static measurements are possible with the patient at rest. In the future, however, it would be interesting to carry out dynamic rotation measurements, for example when walking or doing sports. Therefore, a measurement method with an elastic capacitive measuring system was developed and validated. Material and Methods: The measurement system consists of a capacitive strain gauge connected to a flexible printed circuit board. The electronics on the printed circuit board are used for data acquisition and transmission. When the sensor strip is stretched, the distance between the fingers of the strain gauge changes and with it the capacitance. Consequently, the strain can be measured via the change in capacitance. The measurement system is taped to the knee with the sensor on the skin in the direction of the anterolateral ligament (ALL). The bottom of the sensor (silicone) and the bottom of the circuit board are in contact with the knee surface. The sensor must be attached to the knee without pre-stretching The system is validated with an in vivo test on 11 patients. For this purpose, the internal rotational laxity of the knee was tested on healthy volunteers and the results compared with the measurements on the static measuring device (Laxitester). The subjects are placed in the supine position. First the left and then the right leg is clinically examined one after the other and documented using an examination form. Exclusion criteria are the presence of a pathological ligament findings in the area of the collateral/cruciate ligaments, previous knee operations or limitations in the range of motion. The distal thigh rests on a support bench on which a knee joint flexion of 30° is set by height adjustment. The femoral condyles are secured against rotation in the positioning aid by posts. This also prevents internal rotation and displacement of the thigh. The foot is strapped into the holding device without shoes. The second toe beam is centered using an adjustable side clamp on the medial and lateral edge of the foot. Dorsiflexion is set at 2 Nm with a torque meter, in accordance with previous studies, to rule out rotational laxity in the ankle. The strain gauge sensor is taped to Gerdii’s tubercle in the course of the antero-lateral ligament below the lateral epicondyle of the thigh. Then, in three repeated measurements, the internal rotation of the foot and thus the lower leg is measured with a torque of 2 Nm. The change in length of the stretch mark is compared with the measured internal rotation angle in the static measuring device (Laxitester). Results: A significant difference between the sexes was found in the internal rotation range of the knee (p=0.003). The range of rotation was greater for female participants than for male participants. Regarding the measured length change values, the measurements presented showed an individual result for each participant, which tended to decrease with increasing internal rotation angle, with no age or gender differences being observed. The stiffness of the strain gauge was in the linear range for all measurements, within the first 20% strain of the sensor. The differences determined do not result from a different stretching of the sensor, but from individual differences between the test persons. The comparison between length change and internal rotation angle of the knee showed a strong positive correlation (r=1, p&lt;0.01). Conclusion: Elastic capacitive strain gauges can be used to reliably measure the internal rotation angle of the knee joint. This will allow dynamic measurements in the future.

To solve the problem of complex sensor installation and easy damage in contact displacement measurement, a non-contact measurement method of brace displacement in bridge swivel construction based on binocular vision is proposed in this study. Combined with monitoring data in a swivel construction interchange project, binocular vision system was compared and analyzed with the traditional displacement meter and total station. Results showed that force versus displacement variation plots were obtained by binocular visual measurement in the weighing test, the inflection point can be clearly distinguished, and the position of the inflection point was the same as that of the displacement meter; monitoring data of binocular vision measurement and total station were compared and analyzed in the bridge swivel process, the average error was no more than 0.18 mm, the maximum error was no more than 0.42 mm, and the standard deviation was no more than 0.12. The method proposed in this study can be used as an alternative to displacement meter and total station measurement methods in bridge swivel construction, the problem of complex sensor installation and easy damage is solved in brace displacement measurement, equipment and labor costs can be effectively saved.

The exponential growth in the consumption of electronics, in combination with the reduction in their useful life, leads to a significant increase in the volume of electronic material discarded. Printed Circuit Boards (PCBs) are modules composed of ceramic, polymer and metallic materials of high economic value and with a great potential for damage to biotic and anthropic environments when inadequately discarded. The aims of this work was to study the main environmental impacts and the efficiency of mechanical operations in the electronic waste recycling process in optimizing the concentration of metallic copper. For this, the samples obtained were characterized according to their morphology and chemical composition, and subjected to physical and mechanical treatments: dismantling, grinding, separation by granulometry, density and magnetic property. The environment impacts were estimated by the Life Cycle Assessment of the pre-treatment processes, associated with copper extraction operations in WPCBs. According to the results obtained, it is possible to infer that the NM +1mm Concentrated product presents in its metallic composition around 78% of copper, which contributes to the efficiency of the hydrometallurgical extraction processes. It is noteworthy that the Concentrated class represents about 14% of copper (wt) taking into account the amount of 3.789 kg of PCB waste input material. The potential for reinsertion of the dust in the material recovery process is highlighted, given that the chemical composition of this particulate has a significant presence of metals. In general, it was found that due to the higher concentration (wt %) of the sample being allocated in the range of - 0.15mm + 0.05mm, the elements Fe (18.30%), Si (10.73%), Ca (9.21%) and Cu (8.89%) stand out regarding the participation of the elemental composition of this fraction and also regarding the general composition of the sample. Furthermore, the generation of dust during the fragmentation process, can be associated with occupational respiratory diseases when not managed. About the Life Cycle Assessment, in seven of the nine categories evaluated, crushing and screening activities accounted for more than 90% of the recorded impact values. In general, it is estimated that in the pre-treatment phase be generated 15.4 kg CO2 eq.

Minerals play many important functions in plant and animal metabolism. Therefore, we investigated the concentration of Se and other minerals and their relationships in soils and fodder plants in Kosovo. Seventy-three samples of each soil and fodder plants (grass, maize, and wheat) from 30 farms were collected. Both soil and plant samples, after processing and digestion, were analyzed for mineral concentration by ICP-MS. Mineral concentrations in soil and fodder crops, and the best predicting/explanatory models for micro minerals concentration, achieved by stepwise linear regression, are presented. Results showed very low concentration of Se in most of the soil and all fodder samples. In addition, the concentration of Co, Zn and Fe was not sufficient to satisfy requirements for all categories of farm animals. Plant Se concentration showed a positive relationship with Se concentration in soils. Plant Zn, Mo, Mn, Fe and Pb, in general, showed no significant relationship with their concentration in soil, while plant Co and Cd showed positive relationship only in maize, and Cu in wheat grain. Among the soil properties, pH had the highest effect on the concentrations of Co, Mo, Mn, Cd and Pb in fodder crops.

Spatiotemporal variations of sediments transported along rivers play a crucial role in a wide spectrum of uses, such as navigation, recreation, habitats or hydropower production. The advancement in technology has made it possible to use various indirect techniques to study and evaluate the transport of suspended sediment in fluvial environments. To investigate large-scale phenomena, remote sensing is becoming a largely utilized approach, as it allows to combine spatially-distributed and local information. Dam-induced sediment reduction occurs in large and small rivers worldwide, having profound implications on the fluvial systems. However, the systematic change of suspended sediment concentration (SSC) and its dynamic processes are not well known, and generally investigated only at the very local scale using field information. In this work, SSC maps were created by combining satellite images with local monitoring SSC data, using the Zhijiang -Chenglingji reach of the Changjiang River (China) as a case study, and analyzing how SSC dynamics changed over the period 2017-2022 in correspondence of extreme events. Multiple relationships between measured SSC and bands reflectance were tested, showing the potential of the best-performing one (R2=0.43) in mapping SSC spatiotemporal variations over an extent of dozens of kilometres, eventually providing new insights into the SSC dynamics at hotspots of the river systems, such as confluence zones, barriers, and reservoirs.

As a major coal country, China faces the issue of significant gas emissions during the coal mining process. This study aims to improve the utilization efficiency of mine gas, reduce greenhouse gas emissions, and promote the low-carbon and green transformation of the coal industry. A 10kW gas regenerative thermal oxidation (RTO) experimental system was constructed. The effects of initial methane concentration, low-temperature flue gas proportion, and operating load on combustion temperature, methane oxidation rate, high-temperature flue gas energy, and system thermal efficiency were studied. The results show that when the combustion temperature is below 600°C, the CH4 combustion reaction cannot proceed effectively, and the system temperature continuously decreases and cannot be maintained stable. The experiment determines the stable operating methane concentration range of RTO. In this experimental system, the lower limit of the initial methane concentration is 0.28%, corresponding to an 86% methane oxidation rate. As the initial methane concentration decreases, the combustion temperature also decreases, and the methane oxidation rate follows suit. The higher the low-temperature flue gas proportion, the higher the combustion temperature, and the system thermal efficiency and output heat decrease with the increase of the low-temperature flue gas proportion. This experiment explores multiple factors affecting regenerative thermal oxidation, providing an basis for ensuring the safe and stable operation of the system and optimization. Improving the thermal insulation and heat exchange performance of the storage body can expand the lower limit of the initial methane concentration, thereby increasing the stability and thermal efficiency of the system.

The use of antibiotics grown promoter has been banned, due led problems with drug residues in animal products and increased bacterial resistance. For several reasons there is a growing interest in the scientific community in immunoglobulin Y as antibiotic alternative and their oral administration in the polyclonal antibody (pAb) format, to maintain animal health and performance, do not require IgY purification for large-scale production, resulting in protein impurities and high concentration of biotin in the samples. The signal amplification through non-covalent interaction of biotin with streptavidin has been extensionally used by many laboratories for several diagnosis diseases and scientific research in enzyme-linked immunosorbent assay (ELISA). However, the riches sources of biotin as egg yolk, leading to high biotin concentrations in samples, harming the accuracy of diagnostic and proteins concentrations tests. This study aimed to evaluate the biotin influence on measurement of Immunoglobulin Y in egg yolk freeze dried samples from immunized laying hens by immunoassays using biotin-avidin/streptavidin. The IgY concentration changed down in immunoassays using biotin-avidin/streptavidin. The detection of IgY in yolk samples by ELISA using streptavidin–biotin binding as part of the assay methodology requires some technology to neutralize high concentration of biotin on sample or more steps beyond delipidation to isolate the target protein. Otherwise, an ELISA without the use of streptavidin-biotin binding would be more advisable to avoid biotin and targets protein relationship and prevent biotin interference on results.

Using the unique combination of atomically resolved atom probe tomography (APT) and volume averaged neutron (resonance) spin echo (NRSE and NSE) experiments, the influence of nano-scaled clusters on the spin relaxation in spin glasses was studied. For this purpose, the phase transition from the paramagnetic phase to the spin glass phase in a Fe-Cr spin glass with a composition of Fe_17.8Cr_82.2 was studied in detail by means of NRSE. The microstructure was characterised by APT measurements, which show local concentration fluctuations of Fe and Cr on a length scale of 2 to 5 nm, which lead i) to the coexistence of ferro- and anti-ferromagnetic clusters and ii) a change of the magnetic properties of the whole sample, even in the spin glass phase, where spins are supposed to be randomly frozen. We show that a generalized spin glass relaxation function, which was successfully used to describe the phase transition in diluted spin glasses, can also be used for fitting the spin dynamics in spin glasses with significant concentration fluctuations.

Glutamine is the main amino acid which is substrate for gluconeogenesis in postoperative period. It is suggested that this leads to a substantial and a long-term decline in glutamine concentration. Glutamine is a source of energy for the synthesis of nucleotides, lymphocytes and cells of gastrointestinal tract. In this study, 79 patients were qualified to a coronary artery bypass surgery (Group I) or a surgery in the large intestine area (Group II). The objectives of this study were: evaluation of the impact of surgical procedures on the serum concentration of glutamine of the operated patients, assessment of gender, weight and BMI impact on glutamine concentration and analysis of the correlation between glutaminę serum concentration and laboratory parameters. The mean concentration of glutamine before surgery, the 3rd and 5th day after surgery was higher in Group I. CRP level in the 3rd and 5th postoperative day was higher in Group II. There were no significant differences betweengroups when it comes to BMI and the concentration of CRP (p <0.05). Glutamine concentration depends on the severity of inflammation, the operated body cavity and the intensified catabolism which results from different pathophysiology of digestive system diseases and coronary arterial disease.

In the rapidly evolving landscape of the AI era, the measurement of Computational Thinking ability among Computer Science (CS) University students is of paramount importance. This study introduces UniCTCheck, a novel method designed to assess the main components of Computational Thinking in CS students. Utilizing two key instruments, namely the web application CTScore and the psychometric scale CTProg, this research aims to precisely evaluate seven core components of Computational Thinking and six programming concepts skills essential for CS students. The study, conducted at Rey Juan Carlos University and Atlantic Technological University Galway, involved a diverse sample of students from different year levels and program specializations. Through a rigorous research design, including sampling strategies and data collection tools, this study seeks to address critical research questions related to measurement of variations in students' Computational Thinking and programming skills by gender, university level, and location. By shedding light on the significance of Computational Thinking and programming in the educational realm, this research contributes to the existing literature and underscores the essential role of computational skills in the modern era.

This research work was aimed at investigating and determining the depth resolution of a 500Mhz GPR Antenna. The survey was conducted in an open space at the Physics Department, College of science-KNUST. The MALA GPR equipment with 500MHz shielded Antenna in the common offset-mode was used to investigate the depth at which materials were buried. Concrete block, tree roots, plastic bottle with water, glass bottle and Electric wire were each buried in cavities with five different burial depths. The real depth of each material was measured both along and across the cavity and compared to their corresponding GPR measured depth. The comparison of the Real depth and the GPR depth showed almost identical depth measurements with a root mean square deviation of 0.028m. The implication of this is that the 500 Mhz GPR antenna can accurately locate and detect the position of buried materials in the subsurface at a depth within the range (0.20-0.66) m.

This review paper provides a comprehensive overview of machine vision pose measurement algorithms. The paper focuses on the state-of-the-art algorithms and their applications. The paper is structured as follows: The introduction in Section 1 provides a brief overview of the field of machine vision pose measurement. Section 2 describes the commonly used algorithms for machine vision pose measurement. Section 3 discusses the factors that affect the accuracy and reliability of machine vision pose measurement algorithms. Section 4 presents the applications of machine vision pose measurement in various fields. The paper provides specific examples of how machine vision pose measurement is used in each of these fields. Finally, Section 5 summarizes the paper and provides future research directions. The paper highlights the need for more robust and accurate algorithms that can handle varying lighting conditions and occlusion. It also suggests that the integration of machine learning techniques may improve the performance of machine vision pose measurement algorithms. Overall, this review paper provides a comprehensive overview of machine vision pose measurement algorithms, their applications, and the factors that affect their accuracy and reliability. It provides a valuable resource for researchers and practitioners working in the field of computer vision.

Although advertising literacy leads to critical thinking in the face of advertising, but so far, no action has been taken in Iran regarding a tool to measure this type of literacy. And after the investigations, it was determined that although much research has been done on advertising, but the lack of appropriate measurement tools to measure the level of advertising literacy is clearly evident. Therefore, this research provides a valid tool for measuring advertising literacy from students' perspective. In this study, referring to the dimensions of advertising literacy from the perspective of Malmelin (2010) and the views of related professors, a questionnaire was developed and to determine the validity of the structure, confirmatory factor analysis was used. In this study, the statistical population was high school students, considering the impact of advertising in this age range; finally, a tool with four dimensions of informational literacy, aesthetic literacy, rhetorical literacy and promotional literacy was obtained. According to the confirmation of this tool in the present study, it can be used to examine the status of items, their order and prioritization from the perspective of the mentioned population.

Ethics is a research field that is obtaining more and more attention in Computer Science due to the proliferation of artificial intelligence software, machine learning algorithms, robot agents (like chatbot), and so on. Indeed, ethics research has produced till now a set of guidelines, such as ethical codes, to be followed by people involved in Computer Science. However, a little effort has been spent for producing formal requirements to be included in the design process of software able to act ethically with users. In the paper, we investigate those issues that make a software product ethical and propose a set of metrics devoted to quantitatively evaluate if a software product can be considered ethical or not.

Online social networking techniques and large-scale multimedia retrieval are developing rapidly, which not only has brought great convenience to our daily life, but generated, collected, and stored large-scale multimedia data as well. This trend has put forward higher requirements and greater challenges on massive multimedia retrieval. In this paper, we investigate the problem of image similarity measurement, which is one of the key problems of multimedia retrieval. Firstly, the definition of similarity measurement of images and the related notions are proposed. Then, an efficient similarity measurement framework is proposed. Besides, we present a novel basic method of similarity measurement named SMIN. To improve the performance of similarity measurement, we carefully design a novel indexing structure called SMI Temp Index (SMII for short). Moreover, we establish an index of potential similar visual words off-line to solve to problem that the index cannot be reused. Experimental evaluations on two real image datasets demonstrate that the proposed approach outperforms state-of-the-arts.

Three-dimensional (3D) imaging has attracted more and more interests because of its widespread applications, especially in information and life science. These techniques can be broadly divided into two types: ray-based and wavefront-based 3D imaging. Issues such as imaging quality and system complexity of these techniques limit the applications significantly, and therefore many investigations have focused on 3D imaging from depth measurements. This paper presents an overview of 3D imaging from depth measurements, and provides a summary of the connection between these the ray-based and wavefront-based 3D imaging techniques.

: Nonylphenol is an endocrine disruptor who belongs to alkylphenol group of chemicals and its high occurrence in the environment can caused an adverse effect on human health. The breast milk can serve as a marker to take measure of human exposure to these chemicals through different routes of exposure. In this study, the influence of different factors (kind of wastes mothers drink, consummation of fish, pork and beef; using gloves, mail polish, using vitamins and medication) on the concentration on nonylphenol in breast milk were studied. Concentrations of nonylphenol in breast milk were determined by high-performance liquid chromatography (HPLC) with fluorescence detection. The lowest and highest concentration of nonylphenol in breast milk was 0.97 ng/mL and 4.37 ng/mL, respectively. The selected factors such as pork, beef, fish consumption, vitamin supplementation, medication, using of gloves, nail polish and gel nails were observed in relation to 4-nonylphenol concentration.

In light of the hazardous effects of global warming brought on by climate change, bioethanol production is one of the key alternatives in which the world has expressed a great deal of interest. Two factors—indigenous production and price—are crucial for bioethanol to be appealing in Africa and, for that matter, Ghana. The objective of this research is to produce bioethanol from cheap lignocellulosic materials using onsite enzymes produced from cassava peels degrading fungi. Due to Ghana's prominent position as one of the leading cassava producers in the world, the study focused on utilizing cassava peels, which are underutilized in the country. The research was conducted in multiple stages. In the first stage, the peels were prepared by washing, drying, and manually crushing them using mortar and pestle. The second stage involved analyzing the chemical composition of the peels, including starch and insoluble fibre, which were determined as Acid Detergent Fiber (ADF), Neutral Detergent Fiber (NDF), and Acid Detergent Lignin (ADL). The results showed significant levels of cellulose (39.78%) and starch (31.21%), indicating that cassava peels are valuable raw materials for bioethanol production. The content of hemicellulose (21.11%) and lignin (3.84%) were also determined. In the third stage, using a Petri dish, three fungi (ICPF1, ICPF2, and ICPF3) were isolated from two different cassava peels. ICPF1 was only identified from fresh cassava peels (FCP), while all three fungi were identified from decayed cassava peels (DCP). Morphologically, these fungi were identified as Aspergillus niger, Aspergillus flavus, and Rhizopus stolonifer. The fourth stage focused on optimizing the enzyme activity of the three isolates for potential applications, with A. niger demonstrating the highest enzyme activity with a diameter of zone of clearance of 16 mm. Stage five involved optimizing the production of the onsite enzyme in a 50ml flask using A. niger, basal salt medium (BSM), and cassava peels as a substrate. The DNSA method was used to measure the absorbance of maltose and glucose at 540 nm for various substrate concentrations (1%, 3%, 5%, 8%, and 10%) at specific intervals of 2, 4, 6, 8, and 10 days with a spore concentration of 2.1 x 105 cells/ml. The maltose and glucose concentrations were calculated as 7.138mg/ml and 6.398 mg/ml, respectively, and the corresponding enzyme activity was determined as 4.759U/ml and 4.265U/ml. The optimal conditions of Day 4 and a substrate concentration of 10%, along with a fixed temperature of 30°C and a pH of 5.5, were used to prepare the onsite enzymes in a 500 ml flask for the fermentation process. The onsite enzymes were used for saccharification and Saccharomyces cerevisiae for fermentation under simultaneous saccharification and fermentation (SSF) process. A mixture of 20 ml of onsite enzymes and 1.5 g of S. cerevisiae were added to substrate concentrations of 5%, 10%, and 20%, and the ethanol concentration was analyzed daily for 7 days using Gas Chromatography (GC). The highest ethanol concentration (1.316%) was observed on Day 5 with a substrate concentration of 20%, while the lowest concentration (0.123%) was recorded on Day 1 with a substrate concentration of 5%.

The intrinsic non-linearity and complexity of suspended sediment dynamics, which are impacted by the geographical variability of basin parameters and temporal climatic patterns, make it difficult to estimate suspended sediment concentration (SSC) accurately in hydrological processes. Deep neural networks (DNNs), a cutting-edge modeling method that can capture the innate non-linearity in hydrological systems, have emerged as a solution to this problem. Using primary data on discharge, SSC, and turbidity, the long short-term memory method of DNNs was employed in this study to simulate the discharge-suspended sediment connection for the Esopus Creek, NY, USA as the first objective. To develop effective modeling strategies, multiple scenarios of feature selection, including combinations of discharge, turbidity and SSC for preceding days, were considered. Secondly, the variations in SSC and discharge between the three USGS gages along Esopus Creek that were upper stream, lower stream, and downstream, adjacent to the pourpoint were analyzed. Statistical metrics and scenarios of feature importance were used to evaluate the effectiveness of the DNN-based models. The study shows that among 24 DNN approaches feature selection is crucial in simulating the daily SSC, and discharge and presenting novel research directions for utilizing machine learning algorithms in water quality.

China's economic development has shifted from high speed to high quality. This study constructs an evaluation index for China’s high-quality development utilizing a new development concept. The entropy method and cluster analysis were used to assess the level of high-quality development in China between 2015 and 2021. Kernel density estimation method was employed to explore spatiotemporal dynamics. The results reveal significant differences in the level of economic development among provinces in China; the eastern region is significantly better than the central, northeastern, and western regions. From the perspective of the sub-item evaluation, challenges with uneven, uncoordinated, and insufficient economic development exist in various Chinese provinces.

This study investigates the suitability of the timestamp approach algorithm for predicting blood pressure (BP) using wearable and comfortable devices, showcasing its accuracy even with low-frequency sampled signals. Developed within the SINTEC European project, the algorithm utilizes Electrocardiogram (ECG) and Photoplethysmogram (PPG) sensors, demonstrating promising results in both laboratory and hospital settings. The research emphasizes the algorithm’s potential to transform continuous and non-invasive BP monitoring through wearable technology, offering frequent measurements with minimal discomfort. While the study shows promise, further exploration is needed, focusing on optimizing machine learning coefficients for long-term monitoring applications and addressing potential changes over time. Technological improvements, including the implementation of edge computing algorithms, hold the key to enhancing BP accuracy, denoising techniques, and integrating alarm systems for future wearable solutions. This study emphasizes the adaptability of the algorithm for diverse healthcare environments, paving the way for broader applications in convenient and reliable BP monitoring.

The accurate assessment of wound size is a critical step in advanced wound care management. This study aims to introduce and validate a Light Detection and Ranging (LiDAR) technique for measuring wound size. Twenty-eight wounds treated from December 2022 to April 2023 at the Chunganam National University Hospital were analyzed. All wounds were measured using three techniques; conventional ruler methods, the LiDAR technique, and ImageJ analysis. Correlation analysis, linear regression, and Bland-Altman plot analysis were conducted to validate the accuracy of the newly introduced method. The measurement results (Mean ± Standard deviation) obtained using the Ruler method, LiDAR technique, and ImageJ analysis were 112.99 ± 110.07 cm², 73.59 ± 72.97 cm², and 74.29 ± 72.15 cm², respectively. The Pearson correlation coefficient was higher in the LiDAR application (0.995) than the conventional ruler methods (Mean difference; -5.0000 cm2), as was the degree of agreement (Mean difference; 38.6933 cm2). Wound size measurement using LiDAR is a simple and reliable method that allows practitioners to conveniently assess wounds with a flattened and irregular shape. However, non-flattened wounds cannot be assessed owing to the technical limitations of LiDAR.

The straightness error of guideway is one of the key indicators of ultra-precision machine, which plays an important role in the machining accuracy of work-piece. In order to measure straightness error of long distance ultra-precision guideway accurately, a splicing measurement for straightness error of guideway using high-precision flat mirror and displacement sensor was proposed in this paper, and the data splicing processing algorithm based on coordinate transformation was studied. Then comparative experiments on splicing measurement and direct measurement of straightness error were carried out on a hydrostatic guideway grinder. The maximum difference between the two measurements was about 0.3μm, which was far less than the straightness error of 5.8μm. The experiment demonstrated the correctness of the proposed splicing measurement method and data processing algorithm. To suppress the influence of straightness error on machining accuracy, a straightness error compensation algorithm based on error rotation transformation and vertical axis position correction was proposed, and the grinding experiment of a plane optics with size of 1400mm×500mm was carried out, whose flatness error after grinding was about 2.98μm. The straightness error of the grinding machine had been well suppressed.

A novel scheme that can simultaneously measure the Doppler frequency shift (DFS) and angle of arrival (AOA) of microwave signals is proposed. At the signal receiving unit (SRU), two echo signals and the reference signal are modulated by a Sagnac loop structure and sent to the central station (CS) for processing. At the CS, two low-frequency electrical signals are generated after polarization control and photoelectric conversion. The DFS without direction ambiguity and wide AOA measurement can be real-time acquired by monitoring the frequency and power of the two low-frequency electrical signals. In the simulation, an unambiguous DFS measurement with errors of ±3×10-3 Hz and a -90° to 90° AOA measurement range with errors of less than ±0.5° are realized. The safety and robustness of the system to environmental disturbance are improved, and it is more suitable for the modern electronic warfare system.

FPGA-based data acquisition and processing systems play an important role in modern high-speed, multichannel measurement systems, especially in High-Energy and Plasma Physics. Such FPGA-based systems require an extended control and diagnostics part corresponding to the complexity of the controlled system. Managing the complex structure of registers while keeping the tight coupling between hardware and software is a tedious and potentially error-prone process. Various existing solutions aimed at helping that task do not perfectly match all specific requirements of that application area. The paper presents a new solution based on the XML system description, facilitating the automated generation of the control system’s HDL code and software components and enabling easy integration with the control software. The emphasis is put on reusability, ease of maintenance in case of system modification, easy detection of mistakes, and the possibility of use in modern FPGAs. The presented system has been successfully used in data acquisition and preprocessing projects in High-Energy Physics experiments. It enables easy creation and modification of the control system definition and convenient access to the control and diagnostic blocks. The presented system is an open-source solution and may be adopted by the user for particular needs.

Cellular redox state is highly dynamic and delicately balanced between constant production of reactive oxygen species (ROS), and neutralization by endogenous antioxidants, such as glutathione. Physiologic ROS levels can function as signal transduction messengers, while high levels of ROS can react with and damage various molecules eliciting cellular toxicity. The redox state is reflective of the cell’s metabolic status and can inform on regulated cell-state transitions or various pathologies including aging and cancer. Therefore, methods that enable reliable, quantitative readout of the cellular redox state are imperative for scientists from multiple fields. Liquid-chromatography mass-spectrometry (LC-MS) based methods to detect small molecules that reflect the redox balance in the cell such as glutathione, NADH and NADPH, have been developed and applied successfully, but because redox metabolites are very labile, these methods are not easily standardized or consolidated. Here we report a robust LC-MS method for the simultaneous detection of several redox-reactive metabolites that is compatible with parallel global metabolic profiling in mammalian cells. We performed a comprehensive comparison between three commercial hydrophilic interaction chromatography (HILIC) columns, and we describe the application of our method in mammalian cells and tissues. The presented method is easily applicable and will enable the study of ROS function and oxidative stress in mammalian cells by researchers from various fields.

We present organic, diamagnetic materials based on structurally simple (hetero-) tolane derivatives. They form crystalline thin-film aggregates that are suitable for Faraday rotation (FR) spectroscopy. The resulting new materials are characterized appropriately by common spectroscopic (NMR, UV-Vis), microscopy (POM), and XRD techniques. The spectroscopic studies give extremely high FR activities thus makes these materials promising candidates for future practical applications. Other than a proper explanation, we insist in the complexity of designing efficient FR materials starting off from single molecules.

In this study, different configurations based on linear fiber lasers were proposed and experimentally demonstrated to measure the concentration of paracetamol liquid solutions in a range of 52.61 to 201.33 g/kg. The optical gain was provided by a commercial bidirectional Erbium-Doped Fiber Amplifier (EDFA) and the linear cavity was obtained using two commercial Fiber Bragg Gratings (FBGs). The main difference of each configuration was the coupling ratio of the optical coupler used to extract the system signal. The sensing head corresponded to a Single-Mode Fiber (SMF) tip that worked as an intensity sensor. The results reveal that, despite the optical coupler used (50:50, 60:40, 70:30 or 80:20), all the configurations reached the laser condition, however, the concentration sensing was only possible using a laser drive current near to the threshold value. The configurations using a 70:30 and an 80:20 optical coupler allowed to perform paracetamol concentration measurements with a higher sensitivity of (-3.00±0.24) pW/(g/kg). In terms of resolution, the highest value obtained was 1.75 g/kg, when it was extracted 20% of the output power to the linear cavity fiber laser configuration.

Ion current rectification (ICR) is the ratio of ion current by forward bias to by backward bias and is a critical indicator of diode performance. In previous studies, many attempts have been continued to improve the performance of this ICR, but there is the intrinsic problem for geometric changes that induce ionic rectification due to their fabrication problem. Additionally, the high ICR could be achieved in the narrow salt concentration range only. Here, we propose a multi-layered bipolar ionic diode based on an asymmetric nanochannel network membrane (NCNM), which is realized by soft lithography and self-assembly of homogenous-sized nanoparticles. Owing to the freely changeable geometry based on soft lithography, the ICR performance can be explored according to the variation of microchannel shape. Interestingly, very stable ICR performance can be achieved using the multi-layered 3D configuration for the bipolar diode in a broad range of salt concentrations (0.1mM ~ 100 mM). This demonstrates the promising potential of multi-layered NCNM for applications in highly concentrated electrolytes, such as biosensors, desalination, or energy harvesting.

(1) Background: Health Care-Associated Infections (HAIs)are a significant public health problem worldwide favoring multidrug-resistant (MDR) microorganisms. The SARS-CoV-2 infection had a negative association with the increase in antimicrobial resistance, and the ESKAPE group had the most significant impact on HAIs. The study aimed to evaluate the bactericidal effect of high concentration O3 gas on some reference and ESKAPE bacteria. (2) Material and Methods: Four standard strains and four clinical or environmental MDR strains were exposed to high ozone doses at different concentrations and times. Bacterial inactivation (growth and cultivability) was investigated using colony counts and resazurin as a metabolic indicator. Scanning electron microscopy (SEM) was performed. (3) Results: The culture exposure to a high level of O3 inhibited the growth of all bacterial strains tested with a statistically significant reduction in colony count compared to the control group. The cell viability of S. aureus (MRSA) (99,6%) and P. aeruginosa (XDR) (29,2%) was reduced considerably, and SEM showed damage on bacteria after O3 treatment (4) Conclusion: High doses of ozone were able to interfere in the growth of all strains studied, evidencing that ozone-based decontamination approaches may represent the future of hospital cleaning methods.

Microalgal harvesting is one of the most challenging processes in the development of algal research and development. Several methods, such as centrifugation, flocculation, and filtration, are available at the laboratory scale. However, the requirement of expensive pieces of equipment and the possibility of biomass contamination are recurring gaps that hinder the development of microalgae I+D in different parts of the world. Recently, the electroflotation has been proved as a suitable method for the harvesting of different species of microalgae and cyanobacteria. To this day, there are no companies that sell laboratory-scale electroflotation equipment; this is mainly due to the gap in the knowledge on which factors (time, mixing rate, number of electrodes, and others) will affect the efficiency of concentration without reducing the biomass quality. This paper aims to build an innovative low-cost electroflotation system under 300 USD with cheap and resistant materials. To achieve our goal, we test the interaction of three variables (time, mixing rate, and amount of electrodes) were evaluated. Results showed that an efficiency closer to 100% could be achieved under 20 minutes using >10 electrodes and 150 rpm. We hope this innovative approach can be used by different researchers to improve our knowledge of the concentration and harvesting of algae and cyanobacteria.

Crop digital twin is redefining traditional farming practices, offering unprecedented opportunities for real-time monitoring, predictive and simulation analysis, and optimization. This research embarks on an exploration of the synergy between precision agriculture, crop modeling, and regression algorithms to create a digital twin for augmenting farmers the concentration and composition prediction-based crop nutrient recovery. This captures the holistic representation of crop characteristics, considering the intricate relationships between environmental factors, nutrient concentrations, and crop compositions. However, the complexity arising from diverse soil and environmental conditions makes nutrient content analysis expensive and time-consuming. This paper presents the result of a predictive digital twin case study that employs six regression algorithms namely Elastic Net, Polynomial, Stepwise, Ridge, Lasso, and Linear Regression to predict rice nutrient content efficiently, particularly considering the coexistence and composition of multiple nutrients. Our research findings highlight the superiority of the Polynomial Regression model in predicting nutrient content, with a specific focus on accurate nitrogen percentage prediction. This insight can be used for nutrient recovery intervention by knowing the precise amount of nutrient to be added into the crop medium. The adoption of the Polynomial Regression model offers a valuable tool for nutrient management practices in the crop digital twin, potentially resulting in higher-quality rice production and a reduced environmental impact. The proposed method can be replicable in other low-resourced crop digital twin system.

Overuse and misuse of antibiotics can pose the risks of spreading mutant strains that show antimicrobial resistance (AMR), with negative impact on management of bacterial infections and economic implications on healthcare systems. Research and development of natural antibacterial agents could be a priority in the next years to improve number of effective antibacterial molecules and to reduce AMR phenomenon and its development. The present study identified the most effective concentration and contact time of Thymus vulgaris L. essential oil (TEO) to obtain bactericidal effect in vitro against different Gram + and Gram – bacterial strains. Six clinically isolated (wild types) bacterial strains, (Citrobacter freundii, Enterococcus feciorum, Proteus mirabilis, Acinetobacter cioffi, Pasteurella putrefaciens, Klebsiella pneumoniae) and two ATCC (Staphylococcus aureus and Streptococcus mutans) were tested after 1min, 3min and 5min of contact with TEO. Preliminary results on S. aureus after 24h incubation revealed a TEO concentration of 9.28mg/mL (w/v) that completely inhibited bacteria growth keeping cell viability. Total suppression of bacterial growth at all tested contact times was observed for all tested bacterial strains and the results were confirmed after 48h incubation. Bacterial growth suppression was confirmed even with presence of organic component. These preliminary results showed in vitro antimicrobial efficacy of TEO against different Gram+ and Gram- bacterial strains. Future studies are necessary to confirm the reproducibility of these results even on other strains and to define exactly the molecular mechanisms of EOs, in order to consider TEO as a valid alternative of classic antibiotic therapies and subsequently to reduce the occurrence of AMR.

The threat of fine particulate matter concentration (PM2.5) is increasing globally, Tackling this issue requires an accurate understanding of its trends and drivers. The article investigates the PM2.5 characteristics of 285 prefecture-level cities in China from 2000-2018 based on multiscale geographically weighted regression(MGWR), and the results show that（1）previous studies based on classical MGWR models may be somewhat unstable, while MGWR can reflect the scale of influence of different variables on the dependent variable, and its regression results are more reliable.（2）PM2.5 is very sensitive to carbon emission(CE) factors, and there is a high degree of spatial heterogeneity, and the influence scale of location is the smallest among all variables, close to the municipal scale.（3）In 2000, the constant term all, IS, OFT, CE, and LT positively affect PM2.5, while GDP (jurisdiction) and UR negatively affect PM2.5; in 2010, the constant term all, GDP (jurisdiction), IS, OFT and LT positively affect PM2.5, while UR and CE negatively affect PM2.5; in 2018 the constant term all, IS, OFT and CE factors positively affect PM2.5, and GDP (jurisdiction), UR and LT negatively affect PM2.5.

The problem of real-time estimation of occupancy of buildings (number of people in various zones at every time instant) is relevant to a number of emerging applications that achieve high energy efficiency through feedback control. The measurement of CO2 concentration can be considered an important indicator that allows to define the occupation of closed and crowded spaces. Interesting cases can be school buildings and other buildings used in civil and residential (shopping centres, hospitals, etc.). This paper, starting from an experimental analysis in different classrooms of a University campus in real operating conditions, in different period of the year, proposes a possible correlation between CO2 concentration and the occupancy profile of the spaces. The acquired data are used to present some graphical correlations and to understand the most important variables or combination of them. Starting from an accurate analysis of the data, attempts are made to define a preliminary estimation method through the development of a mathematical models of occupancy dynamics in a building, which show interesting results.

Federated learning is an effective approach for preserving data privacy and security, enabling machine learning to occur in a distributed environment and promoting its development. However, an urgent problem that needs to be addressed is how to encourage active client participation in federated learning. The Shapley Value, a classical concept in cooperative game theory, has been utilized for data valuation in machine learning services. Nevertheless, existing numerical evaluation schemes based on the Shapley Value are impractical as they necessitate additional model training, leading to increased communication overhead. Moreover, participants’ data may exhibit Non-IID characteristics, posing a significant challenge to evaluating participant contributions. Non-IID data weakens the marginal effects of participants, which in turn affects model accuracy and leads to underestimated contribution measurements. Current works often overlook the impact of heterogeneity on model aggregation. This paper presents a fair federated learning contribution measurement scheme that addresses the need for additional model computations. By introducing a noval aggregation weight, it enhances the accuracy of contribution measurement. Experiments on the MNIST dataset show that the proposed method can accurately compute the contributions of participants. Compared to existing baseline algorithms, the model accuracy is significantly improved, with a similar time cost.

The present paper reports an alternative solution of the measurement problem in quantum theory. The measurement problem can be characterized as that the U-procedure verses the R-procedure. The R-procedure is tested by the Yes/No measurement originally proposed by von Neuman and discussed in details by Penrose. We propose a novel stochastic sampling method to tackle the measurement paradox. Each testing sample produces a pair of Yes-number c and No-number d, which in turn generates a sample phase with respect to the exponential form of (c+id). All the sample phases forms a group G_R. Taking G_R as the sampling potential, combined with the dynamic phase group G_U，we establish a unified model of U-procedure and R-procedure for the evolution of wavefunction. Based on the Born rule, the probability of a sample is given by the squared magnitude of （c+id）. Some metaproperties of the new U-R model, such as natural transformation, consistency, and completeness, are presented. The present work provides a new picture of quantum mechanics and alike. The measurement problem widely exists in dynamic analysis, higher cognition, and large data modeling. Thus, the work reported here has a wide range of applications. Keywords: The measurement problem; U-R procedures; the Yes/No type measurement; stochastic sampling; sample phase; Born probability.

Market uncertainty has a significant impact on market performance. Previous studies put much efforts in investigations on market uncertainty related to information asymmetry and risk. However, they have neglected the uncertainty inherent in market transactions, which is also an important aspect of market performance, besides quantity of transactions and market efficiency. In this paper, we put forward the concept of transaction entropy to measure the market uncertainty and see how it changes with price. The definition of transaction entropy is the ratio of total information entropy of all traders to quantity of transactions, reflecting the level of uncertainty in making transactions. And the transaction entropy is the lowest at equilibrium, it will be decreasing in a shortage market, and increasing in a surplus market. Additionally, we make a comparison of total entropy of the centralized market with that of the decentralized market, revealing that the price filtering mechanism could effectively reduce market uncertainty. Overall, the introduction of transaction entropy enriches our understanding of market uncertainty and facilitates a more comprehensive assessment of market performance.

High-dimensional measurement error data are becoming more prevalent across various fields. Research on measurement error regression models has gained increasing attention due to the risk of drawing inaccurate conclusions if measurement errors are ignored. When the dimension p is larger than the sample size n, it is challenging to develop statistical inference methods for high-dimensional measurement error regression models due to the existence of bias, nonconvexity of objective function, high computational cost and many other difficulties. Over the past few years, some works have overcome the aforementioned difficulties and proposed several statistical inference methods. This paper mainly reviews the current development on estimation, hypothesis testing and variable screening methods for high-dimensional measurement error regression models and shows the theoretical results of these methods with some directions worthy of exploring for future research.

This paper presents a calibration and thermal compensation method that aims to minimize cost and processing time while maintaining high accuracy. First, the number of positions to perform the calibration procedure is optimized, and then, based on this optimized calibration number, thermal compensation is performed, which is necessary for environments with large temperature variations, since calibration parameters change at different temperatures. The calibration procedures and algorithms were experimentally validated on marketed accelerometers. Based on the optimized calibration method, the calibrated results have been obtained nearly 100 times improvement. Thermal drift calibration experiments on the triaxial accelerometer show that the thermal compensation scheme in this paper can effectively reduce drift in the temperature range of -40°C to 60°C. The temperature drifts of x- and y-axes are reduced from -13.2 and 11.8 mg to -0.9 and -1.1 mg, respectively. The z-axis temperature drift is reduced from -17.9 to 1.8 mg. We have conducted various experiments on the proposed calibration method and demonstrated its capacity to calibrate the sensor frame error model (SFEM) parameters. Therefore, the MEMS sensors calibrated in this paper have certain engineering application values for tilt measurement.

We communicate the theoretical results in the study of utilizing the quantum phenomena in optical current for quantum computation in the context of high precision voltage measurements. These results can be used around computation by quantum sampling and quantum communication as the basis for further research and physical implementations. We propose a Main Optical Setup (MOS) for such computation which allows to make a superstructure to implement specific computations and algorithms. To create MOS we used the nonlinear units (e.g., beta- barium borate crystal), arranged in series, powered with pulsed laser pump, and ended with the beam splitter to generate the output state of a number of entangled photon pairs. The computation is made by propagation of entanglement with beam splitters applied crossword and adjustable phase shifters that are tools for parameter steering. We show how to implement the series of cosine-based components on the example of two-component case. The results opens a broad area for future research in the area of building quantum optimizer using the quantum sampling methods and in the area of high precision temporal measurement of voltage, which is the important process for building high-fidelity devices.

A method for measuring the mechanical parameters of viscoelastic polymers by nanoindentation technology was proposed and verified. Through the mechanical response of load-displacement curves at different loading rates, then creep compliances and relaxation modulus were fitted. Polyimide thin film was employed in this research and experiments for five different loading rates were conducted. The fitting load-displacement loading curves obtained by the inversion method were identical to the experimental curves at five different loading rates，confirming the validity of the method. Moreover, with the loading rates increased，the fitting curves were more consistent commensurately with the nanoindentation experiment. DMA experiments were tested, and the generalized Kelvin/ Maxwell model were used for fitting experiment data. Results from DMA tests generally agree well with data from nanoindentation method, thereby verifying the feasibility of the method. The Prony series obtained by the two methods were used to simulate the creep experiments, which further verified the method.

Aiming at the defects of low precision and time cumulative error, an external wireless signal weighted centroid localization algorithm aided inertial positioning method is designed in this paper. According to the signal strength of each anchor node received at the test point, the distance between the anchor node and the anchor node is obtained by using the attenuation model of the wireless signal. Three anchor nodes are used to measure the distance between the anchor node and the measured point. We can obtain the area to be measured according to the actual situation, the position of the measured point is obtained by the weighted centroid localization algorithm and a combined model of wireless signal aided inertial navigation system is established. The simulation results show that the method can greatly improve the positioning accuracy and restrain the divergence of the longitude error and latitude error.

Refractive index measurements have been an important task for a long time because that index plays an essential role in describing the optical properties of a material. Many methods have been developed to perform that task. Some of them use interferometry to achieve high precision, however these configurations are complicated. Some measure the critical angle using simple structures, but the accuracy is not satisfactory because it is difficult to judge the exact critical angle with intensity variations. Here we propose several new schemes based on measuring the polarization change in the total internal reflection. The proposed method has the merits of simple structure and easy incident angle determination that gives the maximum phase change. Additionally, it is possible to find the material dispersion by measuring the wavelength dependence of the polarization ellipticity. Some useful formulas relating the refractive index with the maximum phase change are obtained. This work can provide valuable alternatives for index measurement.

The human-readable simplicity with which the CSV format was devised, together with the absence of a standard that strictly defines this format, has allowed the proliferation of several variants in the dialects with which these files are written. The latter has meant that the exchange of information between data management systems, or between countries and regions, requires human intervention during the data mining and cleansing process. This has led to the development of various computational tools that aim to accurately determine the dialects of CSV files, in order to avoid data loss at data loading stage in a given system. However, the dialect detection is a complex problem and current systems have limitations or make assumptions that need to be improved and/or extended. This paper proposes a method for determining CSV file dialects through table uniformity, a statistical approach based on table consistency and records dispersion measurement along with the detection of data type over each field. The new method has a 100\% accuracy on a dataset with 148 CSV files composed of samples coming from a data load testing framework and some others added as verification of the parsing routines. In tests on truly messy data, the proposed solution outperforms the state-of-the-art tool by achieving an improvement of about 10\% in the accuracy with which dialects are detected. Furthermore, the proposed method is accurate enough to determine dialects by reading only ten records, requiring more data to disambiguate those cases where the first records do not contain the necessary information to conclude with a dialect determination.

Accurately estimating the pose of spacecraft is indispensable for space applications. However, such targets are generally non-cooperative, i.e., no markers are mounted on it and no parts for operation. Therefore, the detection and measurement of a non-cooperative target is very challenging. Stereovision sensors are important solutions in the near field. In this paper, a rectangular natural feature recognition and pose measurement method for non-cooperative spacecraft is proposed. Solar panels or the bodies of spacecraft are selected as detection objects and their image features are captured by stereo vision. These rectangle features are then reconstructed in 3D Cartesian space through parallelogram fitting on the image planes of two cameras. The vertexes are used to calculate the center position of the rectangle and the direction of the fixed coordinate system to solve the pose and attitude of the non-cooperative target. An experimental system is built to validate the effectiveness of the algorithm. The experimental results show that the average position measurement error of the algorithm is about 10mm and the average attitude measurement error is less than 1°. The results show that the proposed method has high accuracy and efficiency.

Bayesian nonlinear mixed effects models for data in the form of continuous, repeated measurements from a population, also known as Bayesian hierarchical nonlinear models, are a popular platform for analysis when interest focuses on individual specific characteristics and relevant uncertainty quantification. Due to the limitation of computational power, this framework was relatively dormant until the late 1980s, but in recent years, the statistical research community saw vigorous development of new methodological and computational techniques for these models, the emergence of software, and wide application of the models in numerous industrial and academic fields. This article presents an overview of the formulation, interpretation, and implementation of Bayesian nonlinear mixed effects models and surveys recent advances and applications.

Ammonia (NH3), the most prevalent alkaline gas in the atmosphere, plays a significant role in PM2.5 formation, atmospheric chemistry, and new particle formation. This paper reviews quantification of [NH3] through measurements, satellite-remote-sensing, and modeling reported in over 500 publications towards synthesizing current knowledge of [NH3], focusing on spatiotemporal variations, controlling processes, and quantification issues. Most measurements are through regional passive sampler networks. [NH3] hotspots are typically over agricultural regions like the Midwest US and North China Plain, with elevated concentrations reaching monthly averages of 20 and 74 ppbv, respectively. Topographical effects dramatically increase [NH3] over the Indo-Gangetic Plains, North India and San Joaquin Valley, US. Measurements are sparse over oceans, where [NH3] ≈ few tens of ppbv, variations of which can affect aerosol formation. Satellite-remote-sensing (AIRS, CrIS, IASI, TANSO-FTS, TES) provides global [NH3] quantification in the column and at surface since 2002. Modeling is crucial for improving understanding of NH3 chemistry and transport, its spatiotemporal variations, source apportionment, exploring physicochemical mechanisms, and predicting future scenarios. GEOS-Chem (global) and FRAME (UK) models are commonly applied for this. A synergistic approach of measurements↔satellite-inference↔modeling is needed towards improved understanding of atmospheric ammonia, of concern from the standpoint of human health and the ecosystem.

Does the choice of proxy for stock market development matter? This paper suggests that the growth effect of stock market development is sensitive to the choice of proxy and using alternative financial development indicators have practically no influence on the results. We found that using either the stock market capitalization to GDP ratio or the stock market returns; have a positive and significant effect on growth. However, we cannot make same conclusion when one uses either the ratio of total value of trades on the major stock exchanges to GDP or stock market turnover ratio to proxy for stock market development as the coefficient on these variables were found to be statistically insignificant. The indexes extracted from principal component analysis confirm the sensitivity of the effect to the choice of proxy. This finding suggest that stock market development is a conceptual terms, thus, representing it with single indicators make it impossible to identify which stock market development indicators have a significant positive growth effects.

Vitamin D plays an essential role in embryogenesis and the course of intra- and postnatal periods and is crucially involved in the functioning of the mother-placenta-fetus system. Low quantity of Vitamin D during pregnancy can lead to the elevated risk for preeclampsia occurence. Despite the numerous studies on the association of Vitamin D deficiency and preeclampsia development, the current research on this theme is contradictory. In this review we summarize and analyze study data on the effects of vitamin D deficiency and supplementation on pregnancy, labor, fetal and neonatal outcomes.

Formula feeding, as an alternative to breastfeeding, offers benefits such as convenience and consistent nutrition. Among the drawbacks of formula feeding, however, is potential dilution or concentration errors in the of formula during preparation that may lead to infant health issues. The present study aimed to investigate the accuracy of caregiver measurements as they prepared infant formula under multiple conditions, compared with manufacturer specifications. A diverse sample of caregivers (N = 84) participated in this cross-over experimental study. Participants hand-scooped infant formula powder and poured water to prepare 4oz and 7oz feedings, using both a standardized set of infant formula products and participants’ own products. Linear mixed effects models were used to estimate fixed effects of target amount (4oz versus 7oz) and products (participant versus researcher) on mean absolute percent error (MAPE) of measurement. Across all conditions MAPE was significantly greater for measuring powder than for water (9.0% vs. 4.4%; p&lt;0.001) with a combined powder and water MAPE at 13.0%. Greater measurement error was associated with the odd-sized 7oz preparation and participants’ own products. We observed considerable variability and substantial error during infant formula preparation, particularly for hand-scooping of powder, which tended toward higher values than the theoretical gold standard.

(1)Background: Early-age concrete shrinkage induces stress that impact the cost and service life of concrete pavements. (2)Methods: In this study, strain measurements of field slabs were conducted and a methodology was presented that independently derived autogenous, drying, and thermal shrinkages in the initial stages of concrete placement. Total strain was measured according to five different environmental conditions and shrinkage strain was calculated for each condition. (3)Results: By measuring the strain of the slab and the specimen, the drying shrinkage strain was measured to be approximately 54% better than that by the conventional non-stressed cylinder method because it was possible to measure the drying shrinkage strain at the surface rather than in the middle part of the slab along its depth direction. When the water-to-cement ratio increased (35→40%), there was a considerable reduction (317με→82με) of autogenous shrinkage strain for the concrete at 28 days of age. Furthermore, calculation of stress-dependent strain allowed the presentation of more intuitive and accurate results. (4)Conclusion: As the measurement of independent shrinkage occurrence is possible, the consequent calculated result of the stress-dependent strain acting on real slabs will facilitate improvement in the construction quality, reduction in the development of defects in the concrete structure, and increase in the service life.

The aim of the study is to obtain a more complete picture of the blood plasma melatonin concentration in the donkey species. To this purpose sampling and statistical processing were carried out in such a way that allowed to establish the annual and daily rhythm. Based on human observations, according to the hypothesis of the authors, the blood plasma melatonin concentration of pregnant individuals rises during late gestational period, before parturition. To confirm this, the melatonin concentration of pregnant and non-pregnant mares was monitored and compared. In regard to the circannual rhythm, the significantly lowest midnight melatonin value (27.67 pg/ml) is typical for the summer solstice. Under consideration of circadian changes, a significantly strongest melatonin production (45.16 pg/ml) can be observed on the night of the winter solstice (p &lt; 0.001). Considering the gestational age, the blood plasma melatonin concentration (around 38 pg/ml) does not change as pregnancy progresses (p = 0.136). The results obtained in the study population of the domestic ass usefully expand the little knowledge previously gathered about the development of blood plasma melatonin concentration of this species.

Determining accurate PM2.5 pollution concentrations and understanding their dynamic patterns is crucial for scientifically informed air pollution control strategies. Traditional reliance on linear correlation coefficients for ascertaining PM2.5 related factors only uncovers superficial relationships. Moreover, the invariance of conventional prediction models restricts their accuracy. To enhance the precision of PM2.5 concentration prediction, this study introduces a novel integrated model that leverages feature selection and a clustering algorithm. Comprising three components - feature selection, clustering, and integrated prediction, the model first employs the non-dominated sorting Genetic Algorithm (NSGA-III) to identify the most impactful features affecting PM2.5 concentration within air pollutants and meteorological factors. This step offers more valuable feature data for subsequent modules. The model then adopts a two-layer clustering method (SOM+K-means) to analyze the multifaceted irregularity within the dataset. Finally, the model establishes the Extreme Learning Machine (ELM) weak learner for each classification, integrating multiple weak learners using the Adaboost algorithm to obtain a comprehensive prediction model. Through feature correlation enhancement, data irregularity exploration, and model adaptability improvement, the proposed model significantly enhances the overall prediction performance. Data sourced from 12 Beijing-based monitoring sites in 2016 were utilized for an empirical study, and the model's results compared with five other predictive models. The outcomes demonstrate that the proposed model significantly heightens prediction accuracy, offering useful insights and potential for broadened application to multifactor correlation concentration prediction methodologies for other pollutants.

In the field of embedded systems, energy efficiency is a critical requirement, particularly for battery-powered devices. RISC-V processors have gained popularity due to their flexibility and open-source nature, making them an attractive choice for embedded applications. However, not all RISC-V processors are equally energy-efficient, and it is important to evaluate their performance in specific use cases. This paper evaluates the energy consumption and resource utilization of a new RISC-V processor, RisCO2, and four existing processors - Zero-riscy, Micro-riscy, Ri5cy, and CV32E40P - in a signal demodulation application for NDIR CO2 sensors. The processors were implemented in the PULPino SoC and synthesized using Vivado IDE. The processor named RisCO2 is based on the RV32E_Zfinx instruction set and was designed from scratch by the authors specifically for low-power signal processing applications such as signal demodulation in CO2 NDIR sensors. The other processors are Ri5cy, Micro-riscy, and Zero-riscy, developed by the PULP Platform team, and CV32E40P (derived from Ri5cy) from the OpenHW Group, all of them widely used in the RISC-V community. Our experiments showed that RisCO2 had the lowest energy consumption among the five processors, with a 53.5% reduction in energy consumption compared to CV32E40P and a 94.8% reduction compared to Micro-riscy. Additionally, RisCO2 had the lowest FPGA resource utilization compared to the best-performing processors, CV32E40P and Ri5cy, with a 46.1% and a 59% reduction in LUTs, respectively. Our findings suggest that RisCO2 is a highly energy-efficient RISC-V processor for NDIR CO2 sensors that require signal demodulation. The results also highlight the importance of evaluating processors in specific use cases to identify the most energy-efficient option. This paper provides valuable insights for designers of energy-efficient embedded systems using RISC-V processors.

This study aimed to quantify the extent of heavy metal, non-metal and metalloid level of Campomanesia adamantium pulp obtained from area crossed by road of the high large vehicle traffic and intensive agriculture modern farm, and for monitoring the health risks associated with pulp human consumption. For this purpose, three spots located between this area, ripe fruits were collected in roadside, bush and margin-farm. Pulp samples were digested by microwave-assisted equipment, and mineral elements were quantified by ICP OES. The mineral elements average demonstrated no statistical difference observed between this pulp (p > 0.05). The heavy metals and metalloid concentrations that exceeded FAO/WHO standards are ordered Pb > As > Mo > Co > Ni > Mn > Cr. Therefore, among these metalloid and heavy metals, As, Pb and Cr were found higher in farm-margin > roadside > bush (1.5 × 10^-3, 1.1 × 10^-3 and 6.2 × 10^-4) respectively. Therefore, As is the most important metalloid with higher levels in farm-margin, roadside and bush (1.5 × 10^-3, 1.1 × 10^-3 and 6.2 × 10^-4 > 10^-6–10^-4 and 3.33, 2.30 and 1.34 > 1) respectively, to total cancer risk and hazard quotient, if 100 g daily of pulp are consumed.

This study numerically analyzed the effect of composition and temperature and oxygen concentration changes on the selfignition characteristics of n-heptane/methane blended fuels in order to cope with development of alternative fuels and international environmental regulations. CHEMKIN-PRO is used as the analysis program and the LLNL model is used as the reaction model. The numerical results revealed that on autoignition and ignition delay time were sensitive to changes in fuel composition and oxygen concentration. As the methane ratio increases, OH radicals causing ignition are delayed in generation and the concentration is lowered, thus longer the ignition timing. The oxygen concentration in the mixed fuels are changed to simulate the exhaust gas recirculation and a numerical analysis in then performed. As the oxygen concentration decreases, the ignition delay time longer because the nitrogen gas acts as a thermal load in the combustion chamber.

High concentrations of Na⁺ or [Co(NH₃)₆]³⁺ can induce the B to Z conformational transition in alternating (dC-dG) oligo and polynucleotides. The use of short DNA oligomers (dC-dG)₄ and (dm⁵C-dG)₄ as models can allow a thermodynamic characterization of the transition. Both form right handed double helical structures (B-DNA) in standard phosphate buffer with 115 mM Na⁺ at 25 ^oC. However, at 2.0 M Na⁺ or 200 mM [Co(NH₃)₆]³⁺, (dm⁵C-dG)₄ assumes a left handed double helical structure (Z-DNA) while the unmethylated (dC-dG)₄ analogue remains right handed under those conditions. We have previously demonstrated that the enthalpy of the transition at 25 ^oC for either inducer can be determined using isothermal titration calorimetry (ITC) [Ferreira, J. M. & Sheardy, R. D., Biophys. J. 2006, 91, 1–7]. Here, ITC is used to investigate the linkages between temperature, water activity and DNA conformation. We found that the determined enthalpy for each titration varied linearly with temperature allowing determination of the heat capacity change (DC_p) between the initial and final states. As expected, the DC_p values were dependent upon the cation (i.e. Na⁺ vs [Co(NH₃)₆]³⁺) as well as the sequence of the DNA oligomer (i. e., methylated vs unmethylated). Osmotic stress experiments were carried out to determine the gain or loss of water by the oligomer induced by the titration. The results are discussed in terms of solvent accessible surface areas, electrostatic interactions and the role of water.

Membrane processes, such as microfiltration, ultrafiltration, and nanofiltration are increasingly used for various applications in both upstream and downstream processing. Membrane-based processes play a critical role in the field of separation/purification of biotechnological products, including protein production/purification. The possibility of using membranes to separate peptides from a chicken byproduct hydrolysate and the effect of the performed downstream processing on the DPP-IV inhibitory activity of MDCR (mechanical deboning chicken residue) has been investigated. The chicken byproduct hydrolysate was prepared by enzymatic hydrolysis followed by MF, UF, NF, and RO separation. The LC-OCD analysis confirmed that NF and RO would retain the bioactive peptides in the concentrate in comparison to MF and UF. Bioactivity was correlated with molecular weight distribution profiles and average molecular weights. Permeates after ultrafiltration showed an IC50 value of 0.75 mg/mL, comparable to other potent DPP-IV inhibitors derived from various food sources, and significantly more potent compared to the microfiltration sample, which showed an IC50 value of 1.04 mg/mL. The average molecular weight of the permeates calculated from the SEC chromatograms was 883 g/mol for UF and 1437 g/mol for MF. Of the four membranes studied, the UF membrane showed the best separation properties with respect to maximizing the yield and up-concentration of the bioactive peptides. Overall, UF was demonstrated to be a feasible technology for the removal of the undesired high molecular weight substances and up-concentration of small molecular weight bioactive peptides from chicken byproduct hydrolysate.