Secondary Factor Research Articles

Map-aiding of the additional secondary factors isosurface by the spline approximation method as a condition of improving the e-Loran observations accuracy

The benefit of the Loran ground-based radio navigation system as an alternative to global navigation satellite systems is argued. The motivation of searching for a duplicate variant is caused by the necessity to ensure the reliability of positioning as a subject of countering spoofing and jamming risks when implementing the concept of cybernetic awareness on water transport. Hypothetically, the possibility of using e-Loran on the Northern Sea Route as a backup navigation system is considered. The experience of operating pilot projects of the enhanced Loran in the issue of the predicted potential of positioning accuracy is analyzed. The optimal method of compensation for the system error of geolocation based on the use of additional secondary factors is investigated. Taking into account the principle of the d-Loran functional, based on comparing the measured values of the radio signal passage delay with published analogues for transmitting clarifications to marine consumers, the necessity of using integrity as a criterion for a confidence assessment of the navigation information processing reliability has been determined. A critical analysis of the attempts effectiveness to use the linear interpolation method to calculate intermediate representative values of the delay in the radio signal transmission in order to simulate the map of additional secondary factors is performed. The hypothesis of the prospects for the isosurface corrections synthesis based on B-spline approximation is put forward. The South Korean experiment of synthesizing a chart of additional secondary factors with measured indicators of the radio signal propagation time delay in nanoseconds from the Pohang transmitting station has been repeated at the correct algorithmic level. In order to demonstrate the practical feasibility of the spline algorithm, a computer visualization of a cartographic fragment of additional secondary factors of Yongil Bay is performed. It is suggested that three-dimensional representation of the additional secondary factor for situational perception by the Officer on watch of map-aided correction as a process in alternative positioning in order to increase the reliability of location control through visual evaluation of proper use of corrections of the e-Loran differential variant. The prospect of using the developed package of applied Pascal-programs with implementations on display-type monitors as intellectual support for decision-making by the navigator in a posteriori assessment of the observation accuracy due to the visual representation of the correction field is noted.

Lactate in breast cancer cells is associated with evasion of hypoxia-induced cell cycle arrest and adverse patient outcome.

Tumor hypoxia is a common microenvironmental factor in breast cancers, resulting in stabilization of Hypoxia-Inducible Factor 1 (HIF-1), the master regulator of hypoxic response in cells. Metabolic adaptation by HIF-1 results in inhibition of citric acid cycle, causing accumulation of lactate in large concentrations in hypoxic cancers. Lactate can therefore serve as a secondary microenvironmental factor influencing cellular response to hypoxia. Presence of lactate can alter the hypoxic response of breast cancers in many ways, sometimes in opposite manners. Lactate stabilizes HIF-1 in oxidative condition, as well as destabilizes HIF-1 in hypoxia, increases cellular acidification, and mitigates HIF-1-driven inhibition of cellular respiration. We therefore tested the effect of lactate in MDA-MB-231 under hypoxia, finding that lactate can activate pathways associated with DNA replication, and cell cycling, as well as tissue morphogenesis associated with invasive processes. Using a bioengineered nano-patterned stromal invasion assay, we also confirmed that high lactate and induced HIF-1α gene overexpression can synergistically promote MDA-MB-231 dissemination and stromal trespass. Furthermore, using The Cancer Genome Atlas, we also surprisingly found that lactate in hypoxia promotes gene expression signatures prognosticating low survival in breast cancer patients. Our work documents that lactate accumulation contributes to increased heterogeneity in breast cancer gene expression promoting cancer growth and reducing patient survival.

Implementation of a GEOAI model to assess the impact of agricultural land on the spatial distribution of PM2.5 concentration

Air pollution is considered one of the major environmental risks to health worldwide. Researchers are making significant efforts to study it, thanks to state-of-art technologies in data collection and processing, and to mitigate its effect. In this context, while a lot is known about the role of urbanization, industries, and transport, the impact of agricultural activities on the spatial distribution of pollution is less studied, despite knowledge about emissions suggest it is not a secondary factor. Therefore, the aim of this study was to assess this impact, and to compare it with that of traditional polluting sources, harvesting the capabilities of GEOAI (Geomatics and Earth Observation Artificial Intelligence). The analysis targeted the highly polluted territory of Lombardy, Italy, considering fine particulate matter (PM2.5). PM2.5 data were obtained from the Copernicus-Atmosphere-Monitoring-Service and processed to infer time-invariant spatial parameters (frequency, intensity and exposure) of concentration across the whole period. An ensemble architecture was implemented, with three blocks: correlation-based features selection, Multiscale-Geographically-Weighted-Regression for spatial enhancement, and a final random forest classifier. Finally, the SHapley Additive exPlanation algorithm was applied to compute the relevance of the different land-use classes on the model. The impact of land-use classes was found significantly higher compared to other published models, showing that the insignificant correlations found in the literature are probably due to an unfit experimental setup. The impact of agricultural activities on the spatial distribution of PM2.5 concentration was comparable to the other considered sources, even when focusing only on the most densely inhabited urban areas. In particular, the agriculture's contribution resulted in pollution spikes rather than in a baseline increase. These results allow to state that public policymakers should consider also agricultural activities for evidence-based decision-making about pollution mitigation.

An Empirical Analysis of Local Governments’ Support for College Students’ Innovation and Entrepreneurship

In order to improve the results of college students' innovation and entrepreneurship, local governments need to analyze from the perspectives of support policies, financial support, innovation model guidance and government-enterprise cooperation. Therefore, this paper proposes several assumptions. There is a positive correlation between government financial support and entrepreneurship rate, and whether government-enterprise cooperation, model guidance and financial support are the main influencing factors of college students' innovation and entrepreneurship support. The results showed that the innovation model was the indirect factor of college students' innovation and entrepreneurship, with an impact of 0.63, the government-enterprise cooperation was a secondary factor, and the influence was 0.89, the impact of policy and financial support on college innovation and entrepreneurship was a short-term impact, the government support policy was a long-term impact, and the school-enterprise cooperation was an intermediary factor. Therefore, local governments should strengthen early financial support and introduce support policies to promote the development of college students' innovation and entrepreneurship and ensure the effect of innovation and entrepreneurship.

Abstract TP124: Evaluating Secondary Stroke Prevention Following Discharge From a Community Hospital

Background: Having major effects on both morbidity and mortality, stroke has become a large health burden worldwide. This disease state not only is the second leading cause of death; but also leaves about half of survivors chronically disabled. The 2021 AHA guidelines state that the risk of a recurrent stroke can be mitigated with appropriate secondary stroke prevention. The success of these interventions following discharge from the hospital largely lies in the hands of both the primary care physician and the patient. The goal of this investigation is to determine patient and provider compliance with risk factor modification and drug therapy within 3 months of hospitalization for acute ischemic stroke or transient ischemic attack. Methods: This quality improvement project is a single-center, retrospective chart review of the current secondary stroke prevention procedures exercised at a community hospital within a large healthcare system. This project has received Institutional Review Board approval. To be included, subject were required to have established primary care within the health system, discharged home following admission, and a final principle diagnosis of acute ischemic or transient ischemic event. The primary outcome assessed the percentage of patients that received a follow-up visit with a primary care provider within 30 days of hospital discharge. Additionally, this investigation also assessed modifiable risk factor management for secondary ischemic stroke prophylaxis. Results: Of the 97 patients that met inclusion criteria, 49 of them received a follow-up visit with a primary care provider within 30 days of hospital discharge (50.5%). In regards to secondary outcomes, all outcomes assessed showed to achieve appropriate clinical follow-up except for management of hypertension. It was reported that of the 49 patients, twenty-seven were reported to have controlled blood pressure at follow-up (55%). Conclusions: Results from the primary outcome of this quality improvement project highlighted the need for additional intervention to establish primary care prior to hospital discharge. Additionally this evaluation also highlighted further need for management of hypertension as a modifiable secondary risk factor.

Exogenous applications of brassinosteroids promote secondary xylem differentiation in Eucalyptus grandis.

Brassinosteroids (BRs) play many pivotal roles in plant growth and development, especially in cell elongation and vascular development. Although its biosynthetic and signal transduction pathway have been well characterized in model plants, their biological roles in Eucalyptus grandis, a major hardwood tree providing fiber and energy worldwide, remain unclear. Here, we treated E. grandis plantlets with 24-epibrassinolide (EBL), the most active BR and/or BR biosynthesis inhibitor brassinazole. We recorded the plant growth and analyzed the cell structure of the root and stem with histochemical methods; then, we performed a secondary growth, BR synthesis, and signaling-related gene expression analysis. The results showed that the BRs dramatically increased the shoot length and diameter, and the exogenous BR increased the xylem area of the stem and root. In this process, EgrBRI1, EgrBZR1, and EgrBZR2 expression were induced by the BR treatment, and the expressions of HD-ZIPIII and cellulose synthase genes were also altered. To further verify the effect of BRs in secondary xylem development in Eucalyptus, we used six-month-old plants as the material and directly applied EBL to the xylem and cambium of the vertical stems. The xylem area, fiber cell length, and cell numbers showed considerable increases. Several key BR-signaling genes, secondary xylem development-related transcription factor genes, and cellulose and lignin biosynthetic genes were also considerably altered. Thus, BR had regulatory roles in secondary xylem development and differentiation via the BR-signaling pathway in this woody plant.

What is the primary culprit that causes the "Doomsday Glacier" in Antarctica?

Antarctica, situated in the southernmost part of the earth is surrounded by the Southern Ocean. It has an extremely important role in tuning global climate, both because of its geographic location, and its giant ice mass, that comprises ~90% of the world's ice. In the past decades, the Thwaites Glacier in the Amundsen Sea of West Antarctica is undergoing the fastest recession in the region. The ice loss in Thwaites Glacier is currently responsible for roughly four percent of the global sea-level rise, which has been attributed to climate change and ocean warming. Due to the continuous collapsing and melting of Thwaites Glacier and the severe threat to humans, scientists gave it a terrifying name "Doomsday Glacier". With increasingly geological and geophysical studies conducted in West Antarctica, geothermal heat flux has been discovered to play a vital role in icesheet retreating. The rapidly retreating Thwaites and Pope glaciers are underlain by areas of largely elevated geothermal heat flow, which relates to the tectonic and magmatic history of the West Antarctic Rift System in this region, suggesting that this area is coupled to the dynamics of the underlying lithosphere. The collapsing and melting of the West Antarctic glaciers are without doubt a realistic and complex issue. From the current geological surveys, the heat flux of the crust of West Antarctica appears to be accelerating, coupled with frequent earthquakes and volcanoes. Geothermal features such as hot water lakes, thermal rivers, and giant ice caves beneath the glaciers have been continuously discovered. Therefore, it is reasonable to speculate that geothermal effects play a significant role in modifying the vast ice masses, causing glacier sliding, cracking, collapsing, and ultimately melting, and create conditions for a warming climate to melt West Antarctic glaciers. Many studies also suggest that warm ocean water is intruding beneath the glaciers across the grounding line, leading to melting of glacier bottom, which has been generally considered to be associated with human-emitted greenhouse gases, but it is thought here not to be a primary factor for glacier melting, but most likely a secondary factor. It is believed that primary and secondary factors, Milankovitch orbits, black body radiation, solar activities, human activities, and other factors are all interconnected to form a feedback loop between the glacier base and the ocean, or even a positive feedback loop, which further accelerates the collapsing and melting of the west Antarctic glaciers

Evaluation of Parametric Tropical Cyclone Surface Winds over the Eastern Australian Region

Abstract Hazard studies based on thousands of synthetic tropical cyclone (TC) events require a validated model representation of the surface wind field. Here, we assess three different TC parametric vortex models with input from four along-track parameter studies of the TC size and shape, based on statistical formulation of the relationships to observed TC intensity, geographic location, and forward transition speed. The 12 model combinations are compared to in situ 10-min observed surface mean wind speeds for 10 TCs that made landfall over Queensland, Australia, which occurred over the period 2006–17. Empirical wind reduction factors to reduce gradient winds to the surface are recalculated for the more recent TCs at both offshore (ocean, small islands, reefs, and moorings) and onshore (land) locations. To improve the wind comparisons over ocean and land, a secondary reduction factor was developed based on an inland decay function. Pearson correlations for the unadjusted modeled peak wind speed from 118 instances of a TC passing a weather station sit between a range of 0.57 and 0.65 for the 12 model combinations. Using the secondary reduction factor based on the inland decay function increases the range of correlation to 0.74–0.81. Based on the assessment of the instances of peak surface wind speed correlations, bias, and root-mean-square error, along with the correlation 48 h around the peak, the top-ranked performing model combination for the region was an along-track parameter study with a double-vortex model, both previously tested for the South Pacific basin. Significance Statement When assessing tropical cyclone hazards, users are presented with several simplified parametric models to describe the surface wind field of tropical cyclones. These parametric models are used routinely for risk assessment of cyclonic winds, as well as for input to surge and wave models used in coastal hazard assessments. Differences between the models include the formulation of the parametric cyclone model, the way winds above the boundary layer are specified at the surface and along-track parameters that describe the cyclones’ size and shape. Of the 12 model combinations investigated in this study, the top-ranked performing model combination for the region was an along-track parameter equation with a double-vortex model, which were both tested previously for the South Pacific basin. Analysis is performed to show unadjusted modeled winds overestimate observed 10-min surface winds over the ocean by around 13% (median) and over land by around 73.9% (median), which is resolved in this study with a secondary empirical wind reduction factor. These findings will support future modeling of tropical cyclone winds for multiple applications, including regional risk assessment and coastal hazard studies.

Distribution, sources, contamination, and risks of toxic metals in Zijiang River, a typical tributary of the midstream of the Yangtze River in China

Excessive concentrations of toxic metals are a global threat to aquatic systems. Taking a typical tributary (Zijiang River, ZR) of the midstream of the Yangtze River as the research area, the concentration distribution and chemical fractions occurrence characteristics of five toxic metals (Cd, Cr, Cu, Pb, and Zn) were analyzed, their potential sources were explored, and their contamination and ecological risk was assessed. In the surface waters and sediments, there were high concentrations of Zn, a low concentration of Cd, and small spatial differences in concentration among the upstream, midstream, and downstream. In terms of speciation, Cd mainly existed in the acid-soluble fraction, Pb mainly existed in the reducible fraction, and Cr, Cu, and Zn mainly existed in the residue fraction. The potential sources in surface waters and sediments were determined to be industrial emissions and agricultural non-point sources through the absolute principal component scores–multiple linear regression model (APCS–MLR). Based on the assessment results of total concentration and speciation, Cd was the typical contamination element in ZR sediments. In addition, the secondary phase enrichment factor (SPEF) based on speciation underestimates the degree of Pb contamination, and the ecological risk of Zn assessed by the ratio of secondary phase and primary phase (RSP) and the risk assessment code (RAC) was higher than that of Cr, which was inconsistent with the results based on total concentrations. SOM and Al/Fe/Mn cycles in sediments influenced the geochemical behavior of toxic metals.

Multi-variable time series forecasting model based on high-order hesitant probabilistic linguistic fuzzy logical relationship

The stock market is uncertain, but its fluctuations have inherent laws. A suitable method to extract these rules from historical data is crucial for predicting future trends. However, since these rules are often disturbed by external noise, noise reduction while preserving critical internal information is necessary to improve the accuracy of fuzzy time series forecasting. In this paper, we propose a novel two-factor high-order fuzzy time series (FTS) forecasting model based on hesitant probabilistic fuzzy logical relationship (HPLR). To evaluate the performance of the model, we conduct empirical analysis using the closing price of the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) as the main factor and the opening price as the secondary factor. The proposed model shows improved prediction performance and is intelligent and interpretable in model design. In addition, we forecasted the Hang Seng Index (HSI) to further illustrate the generalizability of the model.

Study on the regional ASF prediction method based on the ordinary kriging interpolation

The eLoran system functions as a robust backup to the Global Navigation Satellite System (GNSS), providing substantial signal power, robust anti-jamming capabilities, and an easily maintainable ground system. Nonetheless, the propagation time delay of the system, primarily driven by the Additional Secondary Phase Factor (ASF), significantly influences the positioning accuracy. Compensating for ASF can effectively enhance the positioning performance. Traditional propagation delay theories frequently yield substantial discrepancies between the predicted and measured values in regions characterized by extended propagation distances and varying topographic features. To address this issue, we conducted ASF measurements within a selected test area using a limited number of measurement points. We employed the ordinary Kriging interpolation method to predict ASF values across the entire test area, and used cross-validation to validate our predictions. The results confirmed the accuracy and effectiveness of the Kriging interpolation algorithm in predicting ASF values within specific regions. The cross-validation demonstrated that the errors remained within acceptable ranges. Furthermore, we applied Ordinary Kriging, Inverse Distance Weighting, and Radial Basis Function Interpolation methods to evaluate the positioning accuracy of the test area before and after ASF correction. Compared to other methods, using the Ordinary Kriging interpolation algorithm for predicting ASF values resulted in a corrected positioning accuracy of up to 68.8 m at various test locations. This approach effectively resolves the challenge of low accuracy in theoretical calculations in complex environments. By utilizing ordinary Kriging interpolation, we required measurements of only a few ASF values within a specific region to create an ASF correction map, addressing the challenges related to inaccurate theoretical calculations in complex pathways and avoiding time-consuming and labor-intensive large-scale measurements. The results of this study offer valuable theoretical support for improving the accuracy of land-based navigation systems.

Life cycle assessment of apricot puree concentrate production

The key factors influencing the ecological impact of the food industry include intensive components such as waste management, logistics, energy consumption, and raw material usage. Holistically, these also offer a range of environmentally friendly improvement opportunities. The fruit juice industry needs the Life Cycle Assessment for sustainable improvements, especially for concentrated juice that requires high-energy evaporation. The study aims to conduct a cradle-to-gate Life Cycle Assessment of apricot puree concentrate production in Sultanhisar, Turkey. Open-access Agribalyse database and OpenLCA software and the ReCiPe impact assessment method have been used. The functional unit is chosen as 1 kg concentrated apricot puree transported to the retail center. The research results indicate that apricot production is the primary contributor, followed by harvested apricot transportation as the secondary factor, and evaporation as the tertiary factor to all environmental impacts approximately. Sensitivity, uncertainty, and scenario analyses are carried out. Sustainable improvement scenarios, in terms of photovoltaic utilization, result in a minor reduction in Global Warming Potential, ranging from 0.82% to 1.65%. On the contrary, logistics adjustments emphasize a significant hotspot with a reduction impact of 16.71%–19.67%.

Voltage transformer metering error state prediction method based on GA-BP algorithm

Abstract The metering accuracy of the voltage transformer is related to the normal operation of the power system, and the metering results can be optimized through the prediction of the error state. In this paper, according to the generation mechanism of the measurement error of the transformer, the maximum information coefficient is used to extract the error characteristic quantity, and the measurement perturbation model is constructed by combining the ambient temperature and the secondary load factor. Due to the specificity of the ambient temperature, a BP neural network is also used to compensate for the temperature of the perturbation model, which prepares for the improved BP neural network based on a genetic algorithm to recognize the error data. Finally, the simulated operation of the three-phase voltage transformer and the measured data of the wiring substation were utilized for validation, respectively. With the help of three-phase CVT simulation, the error change of A-phase simulated CVT amplitude information at the 4001st sampling point is 0.0962%, and the error change of phase information is -4.572′.GA-BP neural network also has high sensitivity to the difficult-to-detect asymptotic error and is able to realize the error calibration of voltage transformer.

Effect of Mycotoxins in Silage on Biogas Production.

Mycotoxins can pose a threat to biogas production as they can contaminate the feedstock used in biogas production, such as agricultural crops and other organic materials. This research study evaluated the contents of deoxynivalenol (DON), zearalenone (ZEA), fumonisin (FUM), and aflatoxin (AFL) mycotoxins in maize silage prior to it being processed in a biogas plant and in digestate produced at the end of the anaerobic digestion (AD) process. In the experiment, three samples of silage were collected from one silage warehouse: Variant 1 = low contamination, Variant 2 = medium contamination, and Variant 3 = heavy contamination, which were subjected to investigation. A significantly reduced biogas production was recorded that was proportional to the increasing contamination with molds, which was primarily due to the AD of silage caused by technologically erroneous silage treatment. The AD was connected with changes in silage composition expressed by the values of VS content, sugar content, lactic acid content, acetic acid content, and the ratio of lactic acid content to acetic acid content. The production of biogas and methane decreased with the increasing contents of NDF, ADF, CF, and lignin. The only exception was Variant 2, in which the content of ADF, CF, and lignin was lower (by 8-11%) than that in Variant 1, and only the content of NDF was higher (by 9%) than that in Variant 1. A secondary factor that also correlated with changes in the composition of the substrate was the development of undesirable organisms, which further contributed to its degradation and to the production of mycotoxins. It was also demonstrated in this study that during the AD process, the tested mycotoxins were degraded, and their content was reduced by 27-100%. Only the variant with low mold contamination showed a DON concentration increase of 27.8%.

What Self in Self-Organization? Engaging Varela's Epistemology for the Co-embodied Self

I focus on an early article by Francisco Varela, 'Not One, Not Two' (1976), to argue that his non-dualistic epistemology entails a paradigm shift towards a fundamentally co-embodied, and thus social, view of self. Varela argued that the mind–body duality could be resolved by understanding the mind as embodied. Both Varela and Evan Thompson have later elaborated on this and suggested an enactive, essentially embodied view of the self in terms of selforganized, organismic autonomy. I will argue that the enactive view of the self remains ambiguous with regards to the role of social interactions: are they constitutive for the minimal self-organization of the self or do they only play a shaping, secondary factor? I rely on Varela's epistemology in 'Not One, Not Two' to support my argument that the minimal self-organizational network that is the human self entails both individual bodily and joint co-embodied processes so that the self is already and constitutively social.

Response of Jasmine rice to different levels of irrigation and organic fertilization under SRI cultivation method

Maintaining a certain level of rice production must coincide with maintaining soil fertility, reducing pollution to the environment, and reducing water consumption. A field experiment was carried out during the 2020 summer growing season in a spot of Al-Issa county-Abbasiya district in the province of Najaf, in order to study the effect of different levels of irrigation and organic fertilizers on the growth, yield and components of the local rice variety Jasmine. The experimental plants were planted on June 17, according to the rice intensification system (SRI) method, by seedling method, at distances of 25 cm between seedlings and lines, with one seedling in the hole. Weeds were removed by hand three times. It was designed as a factorial experiment using a randomized complete block design (RCBD) with three replicates, where the irrigation levels (daily, 3 or 7 days irrigation intervals) as the main factor, while the organic fertilizers at two levels (10 and 5 ton.hˉ¹) were the secondary factor. The results showed that irrigation at 3 days intervals in clay soil mixed with the use of 10 ton.h-1 of organic fertilizers in SRI gave the highest rates of growth characteristics and yield components of Jasmine rice. In the case of irrigation and soil conditions in the study site, SRI is recommended to reduce water consumption and maintain an acceptable level of soil fertility, taking into account maintaining a level of production.

Effect of Shade Regimes and Plant Extracts on the Vegetative Growth and Yield of the Natural Sweetener Plant Stevia (Stevia rebaudiana Bertoni)

A field experiment was conducted in the fields of the College of Agricultural Engineering Sciences / University of Baghdad in the spring of 2021-2022. Stevia (sugar leaf) seedlings propagated from tissue culture method of the Spanish variety Spanti were planted in the field on the mid of March, which were previously acclimated and 6 weeks old, with the aim of studying the role of shading and spraying some plant extracts on growth and leaf yield in sugar leaf (stevia) plant. Randomized Complete Bock Design (RCBD) with three replications was used, using split plot arrangement. The experiment included two factors, the main factor includes two levels of shading, the first without shading (exposed) and the second 50% shading and they are denoted S1, S2 respectively, and the secondary factor is spraying with aqueous plant extracts of Moringa at a rate (10%) and (15%), denoted M1 and M2 respectively, and licorice extract at a rate (3%) and (6%), denoted G1 and G2 in addition to the M0G0 control treatment which was sprayed with distilled water on three dates, 15 days after establishing, 30 and 45 days from planting and measurements are taken after each spray. The results showed that S2 was significantly superior to S1 in terms of plant height (68.87 cm), and in the number of leaves branches-1 at (232.72 leaves branch-1), while S1 was significantly superior to S2 in number of branches (8.53 branches plant-1) and number of leaves (1674.80 leaves plant-1) and in leaf area (246.84 dm2 plant-1) as well as in dry weight of leaves (41.49 g plant-1). While M2 was significantly superior in plant height (65.51 cm), followed by G2 (64.55 cm) and also excelled in the number of leaves branches-1 (234.20 leaves branch-1) followed by G2 (225.65 leaves branch-1). The G2 extract also outperformed significantly in number of leaves (1358 leaves plant-1) followed by M2 (1317.50 leaves plant-1) and M1 (1309 leaves plant-1) and in dry weight of leaves (38.21 g plant-1), followed by G2 (36.30 gm plant-1), which was significantly superior in leaf area (217.30 dm2 plant-1), while in terms of number of branches, G1 treatment was superior with 6.42 branches plant-1. As for the interaction between the study factors, it showed that spraying M2 extract on exposed plants S1 gave the largest leaf area and highest dry weight for stevia plant, and also showed the same concentration M2 highest plant height and highest percentage of number of leaves branche-1 for stevia plant when sprayed on shaded plants S2 under the conditions of the central region of the country.

Spatiotemporal Variation in Vegetation and Its Driving Mechanisms in the Southwest Alpine Canyon Area of China

The Southwest Alpine Canyon Area (SACA), a well-known ecological vulnerability region, plays a very important role in China. Identifying the driving force of the spatial heterogeneity of vegetation and the response of interannual vegetation changes to climate change and human activities would be helpful for ecosystem management. Based on the NDVI dataset, the study analyzed the trend of NDVI change from 2000 to 2019 using the Theil–Sen trend analysis and the Mann–Kendal significance test, detected the driving forces of the spatial heterogeneity of NDVI by the means of the geographical detector, and analyzed the relative contribution of climate change and human activities to interannual NDVI changes using residual analysis model. The results showed that, in terms of the spatial distribution, the pattern of NDVI showed that it is higher in the southeast and lower in the northwest region of the SACA. Elevation was the dominant factor influencing the spatial heterogeneity of NDVI, with the explanatory power of 64%, much larger than other factors, and vegetation type, temperature, precipitation, land use type, and soil type were the main factors. In addition, the explanatory power of the dual factor interaction was higher than that of the single factor effect, which showed two kinds of interaction relationships: bivariate enhancement and nonlinear enhancement. In terms of the temporal variation, 85.59% of the study area showed an increasing trend, and only 14.41% of the area showed a decreasing trend. The main factor affecting NDVI changes was human activities, and climate change was the secondary factor, with relative contributions of 71.35% and 28.65%, respectively. The study will promote a better understanding of the complex mechanisms of vegetation changes and provide scientific recommendations for the prevention of vegetation degradation and vegetation restoration in the SACA.

The factor structure of "expectant mothers of concern" as perceived by midwives.

To clarify the factor structure of "expectant mothers of concern" for whom midwives anticipate difficulties in future childrearing. The participants were 2633 midwives working at hospitals and clinics in Japan. Data were collected using a 108-item, five-point Likert scale questionnaire about the behaviors, appearance, and family relationships of the expectant mothers of concern to the nurses. Items with a mean equal to or greater than 4.0 were selected as items considered relevant to expectant mothers of concern by midwives. Exploratory factor analysis, confirmatory factor analysis, and further secondary factor analysis were conducted. The factor structure of the expectant mothers of concern as perceived by midwives comprised seven factors, including 23 items: "Suspected of being a victim of intimate partner violence," "Uneasy feeling about the expectant mother's marital relationship," "Perception that the expectant mother is conflicted about her pregnancy," "Uneasy feeling about the expectant mother's actions/behaviors concerning her medical checkups," "Engages in physically risky actions and behaviors," "Does not appear to be able to build relationships with children," and "Makes remarks that indicate possible bonding disorder" (goodness-of-fit index = 0.910, adjusted goodness-of-fit index = 0.879, comparative fit index = 0.939, and root mean square error of approximation = 0.070). Further, a secondary factor, "Expectant mothers who must urgently be connected to support," was extracted. The elucidation of the factor structure of the expectant mothers of concern could help midwives identify expectant mothers who may face difficulties in future childrearing.

The Confluence Model of Sexual Aggression: The role of pornography as a secondary risk factor

The Confluence Model of Sexual Aggression: The role of pornography as a secondary risk factor