Preset Levels Research Articles

Safety Risk Analysis of Urban Viaduct Construction Based on Dynamic Weight

The safety risk analysis of urban elevated bridge construction is an important management method to reduce the loss of safety accidents, and it has significant scientific research value and engineering application value. Therefore, this study proposes a novel analysis method to address these challenges. Firstly, this paper constructs a Work Breakdown Structure (WBS)–Risk Breakdown Structure (RBS) matrix for the safety risk of urban elevated bridge construction in order to achieve a comprehensive and complete identification of the indicator system. Then, a combination of static weights and dynamic weights calculation methods is developed. The static weights are obtained using the analytic hierarchy process, while the dynamic weights are obtained based on the relationship between the dynamic scores of construction safety risk indicators in different construction stages and the preset evaluation levels. Finally, a case study of the Longlingshan elevated bridge project in Wuhan, China, is conducted to validate the feasibility of the proposed model and its potential application in projects. The case analysis for the first time reveals that with the progress of construction, the weights of each indicator continuously change, and the secondary indicators related to environmental factors, such as extreme high-temperature weather, undergo the greatest changes. A comparison of different dynamic weight calculation methods is conducted to highlight the advancement of the proposed model. The research findings of this paper will provide new insights and guidance for improving the construction safety of urban elevated bridge projects.

Examination of an Image Identification System for Agricultural Machines Based on Machine Vision

As computer and mechanical automation technologies advance, machine vision-based non-destructive testing technology finds use in a multitude of domains. Non-destructive testing technologies can be used on apple sorting equipment to decrease apple damage while simultaneously increasing sorting efficiency. As a result, the apple sorting machine’s image identification system now incorporates machine vision technology. The automatic classification of apple grades is accomplished by gathering, processing, extracting, and computing the contour features of apple photographs using preset sorting levels. The automatic control system then sorts apples of different grades to designated locations, thus achieving the automation of apple sorting. Tests were run on the sorting machine’s image recognition system to confirm the solution’s viability. The outcomes demonstrate that the sorting machine can effectively classify fruit automatically based on their perimeter, which is important for fruit sorting automation.

Measuring the significance of higher-order dependency in networks

Higher-order networks (HONs), which go beyond the limitations of pairwise relation modeling by graphs, capture higher-order dependencies involving three or more components for various systems. As the number of potential higher-order dependencies increases exponentially with both network size and the order of dependency, it is of particular importance for HON models to balance their representation power against model complexity. In this study, we propose a method, significant k-order dependencies mining (SkDM), based on hypothesis testing and the Markov chain Monte Carlo (MCMC), to identify significant higher-order dependencies in real systems. Through synthetic clickstreams with elaborately designed higher-order dependencies, SkDM shows a powerful ability to correctly identify all significant dependencies at preset significance levels of α={0}{.01, 0}{.05, 0}{.10} , performing as the only method, in comparison to the state of the arts, that can robustly maintain the Type I error rate, and without generating any Type II error across all the experimental settings. We further apply the SkDM method to various empirical networks, including journal citations, air traffic, and email communications. Empirical results show that among those tested networks, only 6.03%, 1.47%, and 1.28% of all potential dependencies are of statistical significance ( α={0}{.01} ). The proposed SkDM method, therefore, provides an efficient tool for higher-order network analysis tasks at reduced computational complexity.

How can complacency mold managerial decisions? The role of perceptions in strategic decision-making

This paper addresses how managers react to attainment discrepancies in their firms’ performance. Scholars have generally argued that only when performance drops below a predetermined aspiration level firms present a search and change behavior in order to fix this dropping performance. In particular, prior research assumes that organizations compare their performance against preset aspiration levels proceeding from their peers’ performance or their own performance in prior years when determining the urgency of engaging in organizational change. However, empirical evidence on this issue is ambiguous and inconclusive. We tackle this puzzle by studying the executives’ complacency (or cognitive interpretations) with objective results of the firm to determine when the company will decide to change and the magnitude of those changes. Using a sample of 137 medium-sized firms, we do find that the combination of objective results with the managerial perception of them, allows us to obtain a better understanding of the performance feedback literature. Thus, organizational change will be (only) enhanced in front of low managerial levels of complacency with organizational results, disregarding the sign of the objective performance feedback obtained by the firm. Moreover, in our research, we go one step further in analyzing several executives’ characteristics that may affect this managerial complacency.

Sustainability Standards in Pediatric Anesthesia: Quality Initiative to Reduce Costly Environmentally Harmful Volatile Anesthetics

Background: The emission and entrapment of greenhouse gases (GHG) inside the atmosphere is one of the leading causes of global warming. Commonly administered anesthetics have global warming potential up to 2,000 times greater than carbon dioxide. This Quality Improvement (QI) initiative aimed to develop a set of sustainability standards to reduce volatile anesthetic GHG emissions and costs at a children’s hospital. Methods: In January 2020, the QI project team implemented education sessions for clinical staff on the environmental impact of volatile anesthetics, bedside clinical reminders, resource guides on sustainable anesthesia practices, preset low-flow gas levels on anesthesia machines, relocated and reduced the number of available vaporizers, and implemented policies to standardize clinical practice. Using hospital pharmacy purchase order data between 2018 and 2022, GHG emissions and costs from three commonly used volatile anesthetics (Isoflurane, Sevoflurane, and Desflurane) were compared using metric ton carbon dioxide equivalents. Results: During 3 years, GHG emissions from volatile anesthetics were significantly reduced by 77%, with most of the reduction attributed to the reduced use and eventual elimination of Desflurane. Purchase costs were also significantly reduced during this period by 41%. Conclusions: This QI project successfully decreased GHG emissions over 3 years by simultaneously reducing the use of costly and environmentally harmful volatile anesthetic, Desflurane, and increasing the use of low-flow anesthesia. This study addresses our anesthesia practices and healthcare system’s impact on the pediatric population and proposes simple interventions to mitigate the negative consequences of current practices.

The role of personality differences in achieving organisational productivity

Purpose: This study examines the role of personality differences in organizational productivity. Specifically, the study examined the level of acceptance of individual differences, ascertained how individuals relate to each other to attain preset productivity levels and assessed how personality differences translate into organizational productivity. Research methodology: Using a quantitative research approach and case study design, data were collected from 190 employees through simple random sampling. Data were analyzed using descriptive statistics from IBM SPSS Statistics 24 and are presented in the tables. Results: The results showed a high level of acceptance of individual differences, even though leaders mostly failed to adjust to employee differences. It was also found that, although leaders did not invest in employee relations programs, personality differences positively affected organizational productivity. The findings also reveal that employees are creative in managing resources and materials for production, explaining the significant influence of personality differences on productivity. Limitations: The data were analyzed using descriptive statistics only. Therefore, no inferences can be made. This study was limited to the employees of the Ghana Meteorological Agency. Contribution: Organizational leaders need to become more tolerant of individual employee differences, as this goes a long way to improve organizational productivity. Future studies should consider other industries in which the workforce is more diverse. Novelty: This study highlighted the role of personality differences in achieving organizational productivity with evidence from the Ghana Meteorological Agency.

A Digital Controller for Reactivity Monitoring and Power Control

This paper introduces a controller unit for reactivity monitoring and automatic power control that was designed and constructed for the 500 kW Dalat Nuclear Research Reactor (DNRR). For power control and reactivity calculations, frequency signals from neutron measurement channels of starting and working ranges of the reactor are used. Two abovementioned independent functions were combined in an Artix-7 FPGA board for determining reactivity values by solving the point reactor kinetics equations with six delayed neutron groups and for stabilizing the reactor power at preset levels by determining the unbalance voltage signal to control the automatic control rod. With real-time calculations, the newly developed controller can monitor the reactor reactivity and control the reactor power online. The developed controller unit’s reactivity measuring and power stabilizing capabilities were assessed using the DNRR in normal operation and assumed emergency conditions and compared with those of the preexisting imported BNO-102R1 module of the DNRR control and protection system, known as ASUZ-14R. The results of the experiments show that the produced FPGA-based unit and the BNO-102R1 unit have the same technical characteristics and features, with the disparities being less than 5% and 1%, respectively, in reactivity measurement and power stabilization. The experimental data of reactivity measurements by the FPGA-based unit and the calculation results were also compared and found that the relative deviations between those are also less than 10%. The developed controller unit is capable of carrying out a variety of training and operational experiments on the DNRR.

Automated, high temporal resolution mechanics measurements during incubation of contractile tissues

Muscle tissue mechanics and contractility measurements have a great advantage over cultured cell level experiments as their mechanical and contractile properties are much closer to in vivo tissue properties. However, tissue level experiments cannot be combined with incubation with the same time resolution and consistency as cell culture studies. Here we present a system in which contractile tissues can be incubated for days while intermittently being tested for their mechanical and contractile properties. A two-chamber system was developed with control of temperature in the outer chamber and CO2 and humidity control in the inner, sterile chamber. Incubation medium, to which biologically active components may be added, is reused after each mechanics test to preserve both added and released components. Mechanics and contractility are measured in a different medium to which, through a high accuracy syringe pump, up to 6 different agonists in a 100-fold dose range can be added. The whole system can be operated through fully automated protocols from a personal computer. Testing data shows accurate maintenance of temperature, CO2 and relative humidity at pre-set levels. Equine trachealis smooth muscle tissues tested in the system showed no signs of infection after 72 h with incubation medium replacement every 24 h. Methacholine dosing and electrical field stimulation every 4 h showed consistent responses. In conclusion, the developed system is a great improvement on the manual incubation techniques being used thus far, improving on time resolution, repeatability and robustness, while reducing contamination risk and tissue damage from repeated handling.

Uptight responses between clenching and forearm raising with factors of visual feedback and maintenance effort in healthy young women: An experimental study on factorial design

BackgroundTo achieve different central preset force levels requires various fine-tuning efforts and may elicit different uptight responses. The mandibular lever system has a distinct regularity in the fine-tuning function of the upper limbs. The purpose of the present study was to detect whether the uptight responses elicited from motivating clenching differ from those induced by motivating forearm raising at different force levels.MethodsTwenty-five healthy females were enrolled in this study. The target was low, medium, and maximum force levels with or without visual feedback and/or maintenance effort. Surface electromyographic (SEMG) activity was recorded from the bilateral anterior temporalis and masseter or left biceps brachii muscle (BicL), and the T-Scan III System synchronously recorded the sensitive force values. The uptight responses and task difficulties were recorded for occlusal and left forearm lifting tasks using a unique visual analogue scale.ResultsThe highest uptight response value was achieved at a low clenching force level with visual feedback requiring no maintenance effort but at a maximum forearm-raising force level with visual feedback and maintenance effort. The SEMG activities of both jaw-closing muscles and BicL were associated with the central preset force level (P < 0.001). However, the maintenance effort only increased the jaw-closing muscles’ SEMG activity at the maximal force level (P < 0.001).ConclusionsClenching at the central preset lower force level with visual feedback is prone to elicit a higher degree of uptight response. The constant need for a low-intensity bite can have a negative effect on an individual's mood.

Impact of the Initial Phase Composition of Alloys on the Effects Manifested by Yield Sites That Occur on Sheet Aluminum Alloys Subjected to Impact-Oscillatory Loading

The impact of the initial phase composition of alloys was evaluated, in particular, the content of Cu, Mn, and Mg in aluminum alloys D16ChATW, 2024-T351 and aluminum alloy T, which in its physical and mechanical characteristics is close to alloy 6013. The impact was evaluated on the effects manifested by yield sites that occur on aluminum alloys that were subject to the dynamic non-equilibrium processes (DNPs) at the expense of impact-oscillatory loading of different intensities under conditions of static tensioning, The one-time DNP, to which the investigated aluminum alloys were subjected at the pre-set levels of elastic strain followed by static tensioning, was found to cause yield sites formation. This is due to self-organization of the alloy structure, which contributes to alloy plasticization. The initial phase alloys composition impact on the yield sites, which occurs when impulse energy of a different intensity is applied to the alloys, was analyzed. The specimens from the aluminum alloys undergoing DNPs of the same level were compared. This made it possible to conclude that alloys D16ChATW and 2024-T351, which have a higher content of Cu, Mn, and Mg, have longer yield sites upon subsequent static tensioning. On the basis of the experimental results, in particular, physical studies, the authors derived a physical and mathematical model of the yield sites that appear after DNPs.

Investigation on Energy Evolution and Storage Characteristic of CSTBD Red Sandstone during Mixed-Mode Fracture

To investigate the energy evolution and storage characteristics of the rock during the mixed-mode fracture failure, several single loading-unloading tests under preset different unloading levels were conducted on the cracked straight-through Brazilian disc (CSTBD) red-sandstone specimen with crack inclination angles of 10° and 20°. The input energy, elastic energy, and dissipated energy parameters were obtained by calculating the area integral of the load-displacement curve. Test results display that the total input energy, elastic energy, and dissipated energy of rock specimens increase in quadratic function with the increase of unloading level at different unloading levels. It was found that there are significant linear energy storage and dissipation laws of rock during the mixed-mode fracture process. The concepts of fracture energy storage coefficient (FESC) and fracture energy dissipation coefficient (FEDC) were proposed to express the energy variation of rock in the prepeak stage. Under the same loading conditions, FESC and FEDC remain unchanged regardless of crack inclination angles, indicating that the linear energy storage and dissipation laws are an inherent property of the rock. Besides, the peak fracture elastic-dissipation index W ed (the ratio of peak elastic energy to peak dissipation energy) was obtained through quantitative analysis and demonstrated its invariant feature.

Analysis of Effect of Grouser Height on Tractive Performance of Tracked Vehicle under Different Moisture Contents in Paddy Soil

Grouser height and soil moisture content have a significant effect on the tractive performance of tracked vehicles. Paddy soil has the mechanical properties of both clay soil and sandy soil and can have a wide range of water content values, and it has a considerable influence on the tractive performance of tracked agricultural machinery. To study the influence of grouser height on the tractive performance of a single-track shoe under different soil moisture contents, a three-dimensional shearing model of the single-track shoe and the contact soil was established based on the ground vehicle mechanics theory, and an experimental platform with a soil bin, sensors, and a control system was established. Six preset levels of moisture contents (7%, 12%, 17%, 22%, 27%, and 32%) of paddy soil were prepared for the research experiment. The mechanical properties of the soil with different moisture contents were obtained through the use of a direct shear test, penetration test, and compaction test. The obtained physical parameters of the soil have special characteristics that are different from typical soil. Combined with the three-dimensional model and the obtained soil parameters, the parameters of the tractive performance, such as thrust, running resistance, and traction with different moisture contents were analyzed and calculated. The test results revealed that the thrust at different grouser heights shows a regular waveform growth trend with an increase in soil moisture content. The minimum value and the maximum value of thrust were obtained at moisture contents of 7% and 12%, respectively. The curve of different grouser heights of the running resistance shows similar changes with different moisture contents. The two peak points and inflection points of the fluctuation curve are for moisture contents of 17% and 27%. The change curve of the traction is highly similar to the curve of thrust. The maximum value of the traction was found at a moisture content of 12%, and the minimum value at 22% or 27%. Under different moisture conditions, tracked vehicles with higher grousers have better tractive performances.

Multiple forward scattering reduces the measured scattering coefficient of whole blood in visible-light optical coherence tomography.

The optical properties of blood encode oxygen-dependent information. Noninvasive optical detection of these properties is increasingly desirable to extract biomarkers for tissue health. Recently, visible-light optical coherence tomography (vis-OCT) demonstrated retinal oxygen saturation (sO2) measurements by inversely measuring the oxygen-dependent absorption and scattering coefficients of whole blood. However, vis-OCT may be sensitive to optical scattering properties of whole blood, different from those reported in the literature. Incorrect assumptions of such properties can add additional uncertainties or biases to vis-OCT's sO2 model. This work investigates whole blood's scattering coefficient measured by vis-OCT. Using Monte Carlo simulation of a retinal vessel, we determined that vis-OCT almost exclusively detects multiple-scattered photons in whole blood. Meanwhile, photons mostly forward scatter in whole blood within the visible spectral range, allowing photons to maintain ballistic paths and penetrate deeply, leading to a reduction in the measured scattering coefficient. We defined a scattering scaling factor (SSF) to account for such a reduction and found that SSF varied with measurement conditions, such as numerical aperture, depth resolution, and depth selection. We further experimentally validated SSF in ex vivo blood phantoms with pre-set sO2 levels and in the human retina, both of which agreed well with our simulation.

Predicting growth potential in life expectancy at birth of the population in the Russian Federation based on scenario changes in socio-hygienic determinants using an artificial neural network

The article presents the result produced by predicting growth potential in life expectancy at birth (LEB) of the RF Population. The predictions are based on scenario changes in social and hygienic determinants (SHD) identified by using an artificial neural network (ANN). This research is vital given the existing social strategies aimed at improving the medical and demographic situation in the Russian Federation. These strategies stipulate achieving targets set within the major national and federal projects. We identified an optimal ANN structure based on a four-layer perceptron with two inner layers containing eight and three neurons accordingly. This structure is able to produce results at the highest determination coefficient (R2= 0.78). Differences between actual LEB levels and predicted ones obtained by using the suggested model did not exceed 1.1 % (or 0.8 years). We established that average LEB in the RF would reach 75.06 years (by 2024) provided that the demographic situation in the country recovers in the nearest future, LEB level reaches its values detected in 2018–2019, and SHD values grow to their preset levels according to the target scenario. Therefore, the detected growth potential amounts to 3.0 years (1095 days) against 2018. “Lifestyle-related determinants” produce the greatest effects on the growth potential in LEB by 2024 (461 days). We also identified effects produced by such SHD groups as “Sanitary-epidemiological welfare on a given territory” (212 days), “Social and demographic indicators” (196 days), “Economic indicators” (131 days), “Indicators related to public healthcare” (70 days). An indicator that shows “A share of population doing physical exercises or sports” is the most significant determinant producing the greatest effects on potential changes in LEB. If it grows up to 55.0 %, a potential growth in LEB amounts to 243.5 days. If we do not consider COVID-related processes and rely only on the trends that are being observed now when predicting changes in the demographic situation by 2030, we can expect a possible additional growth in LEB that equals 286 days. The developed algorithm for determining growth potential in population LEB can be used as an instrument for determining and ranking priority health risk factors.

Прогноз потенциала роста ожидаемой продолжительности жизни населения Российской Федерации на основе сценарного изменения социально-гигиенических детерминант с использованием искусственной нейронной сети

The article presents the result produced by predicting growth potential in life expectancy at birth (LEB) of the RF Population. The predictions are based on scenario changes in social and hygienic determinants (SHD) identified by using an artificial neural network (ANN). This research is vital given the existing social strategies aimed at improving the medical and demographic situation in the Russian Federation. These strategies stipulate achieving targets set within the major national and federal projects. We identified an optimal ANN structure based on a four-layer perceptron with two inner layers containing eight and three neurons accordingly. This structure is able to produce results at the highest determination coefficient (R2= 0.78). Differences between actual LEB levels and predicted ones obtained by using the suggested model did not exceed 1.1 % (or 0.8 years). We established that average LEB in the RF would reach 75.06 years (by 2024) provided that the demographic situation in the country recovers in the nearest future, LEB level reaches its values detected in 2018–2019, and SHD values grow to their preset levels according to the target scenario. Therefore, the detected growth potential amounts to 3.0 years (1095 days) against 2018. “Lifestyle-related determinants” produce the greatest effects on the growth potential in LEB by 2024 (461 days). We also identified effects produced by such SHD groups as “Sanitary-epidemiological welfare on a given territory” (212 days), “Social and demographic indicators” (196 days), “Economic indicators” (131 days), “Indicators related to public healthcare” (70 days). An indicator that shows “A share of population doing physical exercises or sports” is the most significant determinant producing the greatest effects on potential changes in LEB. If it grows up to 55.0 %, a potential growth in LEB amounts to 243.5 days. If we do not consider COVID-related processes and rely only on the trends that are being observed now when predicting changes in the demographic situation by 2030, we can expect a possible additional growth in LEB that equals 286 days. The developed algorithm for determining growth potential in population LEB can be used as an instrument for determining and ranking priority health risk factors.

Design and Realization of Solar-powered IoT-based Flood Early Warning System with Telegram Messaging, Auto-restart Watchdog, and Power Management

A Flood is inevitable in some regions in Indonesia during rainy season. Flood can cause problems ranging from simple problem such as lightly flooded street to a complex one such as water that enters the house. For community living at river side, the flood often comes from excessive water due to rain in the upstream that outflows the river as drainage which can happen unnoticeably. An early warning system is needed to detect flood so that people who lived in a flood-prone area can be warned and be prepared to mitigate the flood. With the help of internet of things (IoT) technology, such a system can be made. In this work, an early warning system was developed using off-grid solar system as power source, ultrasonic sensor to detect water level, NodeMCU as microcontroller, and 4G modem to connect to the internet. The system uses Blynk as its IoT platform and sends alarm messages to locals using Telegram so they are vigilant. The system can detect how much the water level and categorizes it into preset alarm levels. Lab. experiments on the proposed system was performed using power from PV-module installed on the lab.’s rooftop. The system functionality works well for 3 weeks of experiments with battery voltage monitored to vary from 12 V at dawn to 13.7 V at daytime. The experiments show that the system exhibits water level measurement average relative error of 2.22% and accuracy of 97.78%. The system is also furnished with power management and auto restart self-healing functionality which were also observed to work well during the test. Measurements show that the system only consumes energy of 11.52 Wh/day which is equivalent to 8% of battery depth of discharge, hence the system can operate for 3.75 days without charging during successive rainy and cloudy days and has sufficient solar energy harvesting margin to cope with site imperfections like shading and soiling of the PV-module.

Loading-Rate Dependency of Young’s Modulus for Class I and Class II Rocks

Understanding the time-dependent behavior of rocks is important for ensuring the long-term stability of underground structures. Aspects of such a time-dependent behavior include the loading-rate dependency of Young’s modulus, strength, creep, and relaxation. In particular, the loading-rate dependency of Young’s modulus of rocks has not been fully clarified. In this study, four different types of rocks were tested, and the results were used to analyze the loading-rate dependency of Young’s modulus and explain the underlying mechanism. For all four rocks, Young’s modulus increased linearly with a tenfold increase in the loading rate. The rocks showed the same loading-rate dependency of Young’s modulus. A variable-compliance constitutive equation was proposed for the loading-rate dependency of Young’s modulus, and the calculated results agreed well with measured values. Irrecoverable and recoverable strains were separated by loading-unloading-reloading tests at preset stress levels. The constitutive equations showed that the rate of increase in Young’s modulus increased with the irrecoverable strain and decreased with increasing stress. The increase in the irrecoverable strain was delayed at high loading rates, which was concluded to be the main reason for the increase in Young’s modulus with an increasing loading rate.

Hyperspectral evidence of early-stage pine shoot beetle attack in Yunnan pine

Pine shoot beetle (PSB, Tomicus spp.) outbreaks cause widespread Yunnan pine (Pinus yunnanensis Franch) mortality in southwestern China. Early identification of PSB attacks could help forest managers mitigate the infestation before it turns into an outbreak. However, the subtle spectral changes and complex process of PSB-induced crown discoloration make the remote sensing approach difficult.This study employed a manipulated insect infestation experiment to reveal suitable monitoring indicators. Healthy Yunnan pine crowns were infested with PSB adults at different preset densities (light, moderate, and severe) using the bagging method. The crown damage parameters, physiological properties, and corresponding spectral data were systematically measured in time series. Partial least squares regression (PLSR) was used to retrieve crown chlorophylla+b (Cab) and relative water content (RWC) via band reflectance. Random forest (RF) was used to determine the optimum spectral variables capable of capturing dynamic variations in crown shoot damage ratio (SDR).Results showed that (1) after four weeks’ PSB shoot feeding attack, SDR reached saturated (26%-50%) for all damage levels, indicating a crown discoloration “switch point”. (2) A continuous decline was found in Cab and RWC at both shoot and crown levels during the whole infestation process, and the crown level decrease was smaller than the shoot level due to crown heterogeneous discoloration. (3) For PLSR retrieving crown Cab and RWC, estimation accuracy of healthy crowns could reach R2 = 0.70, RMSEcv = 14.60 mg/m2 for Cab, and R2 = 0.82, RMSEcv = 1.25% for RWC, respectively. However, PSB early attack impacted these retrieval accuracies. (4) Spectral differences were evident in the visible region (530–600 nm) and near-infrared (NIR) plateau (780–1300 nm) among the preset damage levels. Significant differences in spectral variables (AMP, CI, OSAVI, RD, and SR) were observed between healthy and moderately damaged crowns. (5) In RF modeling, the importance of spectral variables for SDR estimation varied throughout the shoot feeding process. OSAVI, CI, MSI, PSRI, and SR2 were the top indicators that were suitable for identifying SDR ranging from 5% to 50%. SDR could be estimated with an accuracy of R2 = 0.71, RMSEcv = 8.92%, after 4 weeks’ infestation. Simultaneously, with the RF model, 4 preset damage levels could be differentiated with an out-of-bag error of 14.94% and a kappa coefficient of 0.8835.In conclusion, this study mainly examined the physiological and spectral signatures of PSB early attacked crowns, and provided optimum spectral variables and models which will further help unmanned aerial vehicle (UAV) and satellite remote sensing identify PSB infestation at the early stages.

Using robots to improve indoor air quality and reduce COVID-19 exposure

Air pollution is the world’s largest environmental health risk, accounting yearly for about 8 million deaths. Most of the people spend 80% to 90% of their time indoors. Therefore, Indoor Air Quality (IAQ) has a direct impact on overall health. In this paper, a robot, equipped with sensors for measuring IAQ parameters such as temperature, relative humidity, CO2, Particulate Matters and Volatile Organic Compounds (VOC) is used to measure these parameters and compare the measured values to the pre-set permissible levels of concentrations of such parameters. If one (or more) of the measured values exceed the pre-set threshold values, the measured values are communicated to the user via a mobile application and the robot will take a corrective action by disinfecting the place using a sterilizing solution. Validation of the methodology was verified at an educational institute in Alexandria, Egypt.

Dietary supplementation of a Saccharomyces cerevisiae fermentation product attenuates exercise-induced stress markers in young horses.

Mitigation of exercise-induced stress is of key interest in determining ways to optimize performance horse health. To test the hypothesis that dietary supplementation of a Saccharomyces cerevisiae fermentation product would decrease markers of exercise-induced stress and inflammation in young horses, Quarter Horse yearlings (mean ± SD; 9 ± 1 mo) were randomly assigned to receive either no supplementation (CON; n = 8) or 21 g/d S. cerevisiae fermentation product (10.5 g/feeding twice daily; SCFP; n = 10) top-dressed on a basal diet of custom-formulated grain as well as ad libitum Coastal bermudagrass hay. After 8 wk of dietary treatments, horses underwent a 2-h submaximal exercise test (SET) on a free-stall mechanical exerciser. Serum was collected before dietary treatment supplementation (week 0), at week 8 pre-SET, and 0, 1, and 6 h post-SET and analyzed for concentrations of cortisol and serum amyloid A (SAA) by commercial enzyme-linked immunosorbent assay (ELISA) and for cytokine concentrations by commercial bead-based ELISA. Data were analyzed using linear models with repeated measures in SAS v9.4. From week 0 to 8 (pre-SET), serum cortisol decreased (P = 0.01) and SAA did not change, but neither were affected by diet. Serum concentrations of all cytokines decreased from week 0 to 8 (P ≤ 0.008), but granulocyte colony-stimulating factor (G-CSF), granulocyte-macrophage colony-stimulating factor, and interleukin-8 (IL-8) decreased to a greater extent in CON than in SCFP horses (P ≤0.003). In response to the week 8 SET, serum cortisol increased in all horses (P < 0.0001) but returned to pre-SET levels by 1 h post-SET in horses receiving SCFP. At 6 h post-SET, cortisol concentrations in CON horses returned to pre-SET concentrations, whereas cortisol declined further in SCFP horses to below pre-SET levels (P = 0.0002) and lower than CON (P = 0.003) at that time point. SAA increased at 6 h post-SET in CON (P < 0.0001) but was unchanged through 6 h in SCFP horses. All cytokines except G-CSF increased in response to the SET (P < 0.0001) but showed differing response patterns. Concentrations of IL-1β, IL-6, and tumor necrosis factor-alpha were lesser (P ≤ 0.05), and concentrations of G-CSF and IL-18 tended to be lesser (P ≤ 0.09) in SCFP compared with CON horses throughout recovery from the SET. In summary, 8 wk of dietary supplementation with 21 g/d of SCFP may mitigate cellular stress following a single, prolonged submaximal exercise bout in young horses.