Significant Coefficient Of Determination Research Articles

Comparative biomonitoring of airborne potentially toxic elements using mosses (Hypnum cupressiforme, Brachythecium spp.) and lichen (Evernia prunastri) over remote areas.

The selection of the appropriate biomonitor species is a crucial criterion for biomonitoring on a broad spatial scale. Mosses Hypnum cupressiforme and Brachythecium spp. and lichen Evernia prunastri were sampled at 22 remote sites over Serbia aiming interspecies comparison of their bioconcentration capacities. The concentration of 16 potentially toxic elements (PTEs), Al, Ba, Cd, Co, Cr, Cu, Fe, Hg, Mn, Ni, P, Pb, S, Sr, V, and Zn, was measured in the samples. Between the co-located mosses, linear regression analysis (type II) showed significant determination coefficients only for a couple of the elements (Cd and S), while for H. cupressiforme vs. lichen, significant regression lines were obtained for a broader set of elements (Ba, Cd, Fe, Hg, Mn, Ni, Sr). The ratio of the PTEs in the mosses discovered higher concentrations in H. cupressiforme than in another moss at some sites and vice versa at other sites. According to the PTE ratios, H. cupressiforme accumulated much more element content than the lichen, but followed a similar spatial pattern. In addition, principal component analysis (PCA) pointed out a different grouping of the PTEs depending on the species tested. The poor correlation of the moss-moss data is perhaps because several species of the genus Brachythecium were sampled, which possibly influenced the average genus accumulation capacity. In addition, morphological features of the mosses (concave vs. flat leaflets, creeping vs. cushiony life form) presumably delegate differences in PTE accumulation. To conclude, it should be careful with using more biomonitor species, even of the same genus, within the same study.

Digital Voices in Early Days: Analysing Local Government Social Media Approaches to Risk Communication during the Initial Stages of the COVID-19 Pandemic in Indonesia

This study evaluates the communication strategies utilised by local governmental bodies in Indonesia concerning the risk communication associated with the COVID-19 pandemic. Furthermore, an analysis is conducted on the impact of these communication approaches in promoting public engagement. In this study, we collected a dataset consisting of 1,577 tweets that originated from five different local governments in Indonesia. This dataset was obtained using web crawling techniques and was intended to be used for content analysis purposes. The findings of this study demonstrate that local governments employ a diverse range of risk communication strategies. This encompasses the distribution of medical knowledge, protocols for maintaining health, frequent reports on the COVID-19 status in different areas, governmental measures, initiatives for public education, community engagement endeavours, information about accessible assistance, enforcement of regulations, provision of emotional assistance, and promotion of collaborative efforts. The findings of this research demonstrate that some forms of content, such as narratives or testimonies from individuals who have recovered from COVID-19 or medical experts, public awareness campaigns related to COVID-19, and interactive quizzes or activities, have a significant coefficient of determination. This discovery implies that the material above has generated substantial attention and involvement from the general public. Keywords: COVID-19, risk communication, social media, Indonesia, communication strategies.

The impact of vehicle parameters on road PM10 vehicle resuspended emissions: A case in South African low-income settlement

About 70% of the roads in low-income settlements are unpaved and close (≤15m) to residents, thus a major source of ambientand indoor PM10 concentrations. International studies have suggested that decreasing vehicle speed and managing vehicle type onpaved or unpaved roads can reduce vehicle dust emissions. These mitigation strategies should be examined before being adoptedand gazetted into South African air quality management plans. This study aimed to characterise roads and traffic, emphasisingdetermining the impact of vehicle type on PM10 emissions. GIS was used to determine the proportion of paved and unpaved roads. Atraffic counter was used to monitor vehicles and to determine traffic composition, diurnal cycles, and average speed per road type.Field campaigns (summer; 6 days; 15 hrs per day) were carried out in Bokamoso to monitor PM10 concentration usinga TSI DustTrak DRX® real-time optical aerosol counter. The Box Model method quantifies vehicle PM10 emission factors for heavy-duty, medium-duty, and motor vehicles. About 0.88 km of road within Bokamoso is paved with a daily traffic volume of >2000, and 3.6 km is unpaved with >250 daily traffic volume. Paved road heavy-duty vehicle non-exhaust PM10 emissions reported a positive medium to strong coefficient of determination to vehicle speed increase with a coefficient of determination of 0.59. Even though there is a positive coefficient of determination between heavy-duty vehicle non-exhaust PM10 emission factors and speed on unpaved roads, it is weak (0.2) due to low and less variable vehicle speed. Motor vehicle paved and unpaved road non-exhaust emission factors showed no significant coefficient of determination with increased vehicle speed. Paved road non-exhaust emission factors were not significantly variable with vehicle type. They ranged between an average of 0.15-0.18 g/km/h, with motor vehicles reporting an average of 0.18 g/km/h while heavy-duty vehicles reported an average of 0.15 g/km/h. On the contrary, unpaved road non-exhaust traffic PM10 emissions ranged between 0.16-0.3 g/km/h. The emission factors presented may be used to model vehicle traffic emissions, improve on-road vehicle dust emissions impact assessment and as a guide when deciding on local applicable road dust mitigation strategies

Seasonal Evolution of Stable Thermal Stratification in Central Area of Lake Ladoga

The complete climatic courses of the parameters of stable thermal stratification for the central part of Lake Ladoga, the largest European lake, are presented on the basis of empirical relationships, taking into account the physical processes governing water temperature variations. For the first time, the seasonal cycle of the surface water temperature, the temperature and the depth of the thermocline, and the hypolimnion temperature are calculated using the vertical profiles of the temperature obtained from the central area of Lake Ladoga. Temperature data are used for the period of in situ observations from 1897 to the present. The proposed functional forms of the temporal temperature cycle and the course of thermocline’s boundaries deepening are useful for examination and simulation of the heat vertical transport from air to water. Approximation curves for the parameters of heating and cooling periods were developed with high significant determination coefficients. Time dependencies of the climatic rates of change in water temperature and the depth of the thermocline boundaries were determined from the onset of stable stratification to its dissipation. The highest rate of water temperature change in the heating stage takes place in late June–early July, which at the water surface, is 0.32 °C/day, while in the thermocline layer, it is 0.18 °C/day. The peak velocity during the cooling stage at the surface occurs in late August–early September and is 0.14 °C/day, whereas in the thermocline, it is 0.08 °C/day and takes place between September and early October. During the period of heating, the deepening parameters of the thermocline layer do not fluctuate very much, only within the range of 0.1–0.3 m/day. During the cooling period, under the influence of free convection, rates increase drastically. The maximum rates of deepening during the period of full autumn mixing reach 1.8 m/day. When the autumn overturn occurs, the epilimnion thickness equals the bottom depth, and the bottom temperature reaches its maximum during the annual cycle. Climatic norms of the stratification parameters against which it is necessary to assess climate change are calculated.

Pengaruh Trait Big Five Personality dan Dukungan Sosial Terhadap Flourishing Mahasiswa Menjalani Perkuliahan Selama Masa Pandemi

Empirically, this study aims to look at the Effect of Big Five Personality Traits and Social Support on Flourishing Students Undergoing Lectures During the Pandemic Period. The population in this study were 150 students and 150 students were the sample where the sample was taken using random sampling. Data collection techniques, namely questionnaires and documentation, data analysis was carried out by multiple regression, hypothesis testing t test, F test, and determination test. The results showed that the main effect of each of the Big Five dimensions of Personality and Social Support p: (1) a. There is a significant positive effect between Extraversion and Flourishing personality types as seen from the significance value where the coefficient tx2ay = 9.529 with p = 0.000, means p <0.05, (2) b. There is no significant positive effect on Agreeableness Fluorishing, where the coefficient tx2by 1.165 with p=0.282, means p> 0.05, (3) c. There is a significant positive influence between Counsicientiousness and flourishing personality types where the coefficient tx2cy = 10.099 with p = 0.000, means p <0.05, (4) d. There is no significant positive effect between Nerotic and Fluorishing personality types, where the coefficient of tx2dy is 0.896 with p = 0.372, meaning p>0.05, (5) e. There is no significant positive effect between Openness to experience and Fluorishing personality types, where the tx2ey coefficient is 0.098 with p = 0.922, meaning p> 0.05. Social support has a significant positive effect on Floursihing where the value of the coefficient tx1y = 8.161 with p = 0.000 means p <0.05. For the Interaction effect, (1).a there is a significant influence of social support and personality type a (Extraversion) simultaneously on Fluorishing where the coefficient F = 45.410; with p = 0.000 means p < 0.050. (2) b. There is significant effect of social support and personality type b (Agreebleness) simultaneously on Fluorishing where the coefficient F = 34.853; with p = 0.000 means p < 0.050. (3) c. There is a significant influence of social support and personality type c (Counscientiousness) simultaneously on Fluorishing where the coefficient F = 78.855; with p = 0.000 means p < 0.050. (4) d. There is a significant effect of social support and personality type d (Nerotic) simultaneously on Fluorishing where the coefficient F = 33,497; with p = 0.000 means p < 0.050. (5) e. There is a significant effect of social support and personality type e (Opennes to experience) simultaneously on Fluorishing where the coefficient F = 33.080; with p = 0.000 means p < 0.050.Of the Big Five Personality and Social Support variables, only the Counsicientiousness and Extraversion dimensions have the most significant determination coefficient values, where Counsicientiousness (R2) = 0.518 or 51.80%, while Extraversion (R2) = 0.382 or 38, 20% (2) Thus it can be concluded that of the five dimensions of Big Five Personality there are two dimensions that have a significant influence, namely Counsicientiousness and Extraversion between Big Five Personality and Social support with Flourishing in third semester students of the law faculty of North Sumatra University in undergoing college during their tenure pandemic.

Investigation into shrinkage of stretchable denim fabric and its consumption in marker making by varying drying temperatures

This investigation was carried out to minimize Cotton and Cotton–polyester stretchable denim fabrics consumption for garment development through marker making. It was achieved by controlling fabric shrinkage by reducing drying temperature after washing in fixed processing time, without compromising properties of denim; Tensile strength, Stretch (growth and recovery at constant and cyclic loading) and colour strength (K/S) of required shade. warp faced 3x1 and 2x1 denim containing elastin were constructed and then washed using same recipe as per industrial practice however drying temperatures were set at 50oC, 60oC and 70oC, separately. After measuring shrinkage and evaluating tensile strength, Stretch, Growth and recovery at constant and cyclic loading and colour strength (K/S) using standard test methods; trouser marker layout was developed by employing Gerber technology to investigate fabrics consumption. The obtained shrinkage % demonstrated a significant coefficient of determination (R2=0.9931) against drying temperatures. Relation of tensile strength, colour strength and growth were insignificant however stretch, growth and recovery at static and cyclic loading were significantly affected by changing temperatures. Average shrinkage % of stretchable denim fabric was 1.71% in warp and 8.24% in weft at 50oC. It increased to 12.05% in weft at 60oC however remained same in warp while against 70oC it was 1.82% in warp and 14.08% in weft. 10 minutes drying time was kept same for selected drying temperatures. It was found that fabric consumption reduced to 1.25 m per trouser from 1.32 m per trouser by setting drying temperature at 50oC. Present research work provides guideline to denim industries to process stretchable denim at lower drying temperature i.e., 50oC because it not only reduced consumption of elastin containing denim fabric, but it also makes process cost effective as well as environmentally friendly.

Bond strength analysis of post-installed rebar with chemical adhesive in concrete mixed with marble powder and glass fiber

This study investigates the impact of marble powder as a part of fine aggregate and the addition of glass fiber on the bond strength of concrete and deformed high-strength post-installed steel rebars using the epoxy chemical as an adhesive. Five marble dust powder (MDP) substitution percentages (i.e. 0%, 10%, 20%, 30%, and 35%) and the addition of glass fiber (i.e. 0.5%, 1%, and 1.5%) were used. The performance of deformed high-strength post-installed rebars in conventional concrete and concrete modified with 35% marble powder and 1% glass fiber was examined here utilizing pull-out tests on a total of 96 specimens. To examine the bond behaviors of deformed high-strength post-installed rebars at the epoxy–conventional concrete interface and epoxy-modified concrete with MDP and glass fiber interface, test criteria included concrete compressive strength, anchorage depth of rebar into concrete, rebar diameter, and concrete cover to rebar diameter ratio. For post-installed high-strength deformed rebar, bond stress–slip relationships were determined, examined, and subsequently compared with prior work and readily available codes. It was found that none of the specimens exhibited pull-out failure and that the majority of them displayed concrete splitting, concrete rapture, or rebar rapture failure. This suggests that epoxy resins are particularly successful as bonding agents to retrofit concrete structures at the steel–concrete contact. A closed-form equation for predicting the bond strength for post-installed high-strength deformed rebar was also created using regression analyses on the experimental data. With a significant coefficient of determination (R2 = 0.85) the observed predicted bond strengths and the test data were quite similar.

Sustainable solution of sewing thread attributes on seam pucker

Bending rigidity magnitude of sewing thread provides a sustainable solution on the appearance of single needle lock stitched lightweight woven fabrics which are prone to pucker. Comparison of sewing thread bending rigidity with thread count, thread diameter, thread cyclic recovery and their resultant implication in the single lock stitched assemblies were given less consideration for the prediction and reduction of seam pucker severity. The resultant implication of physical and mechanical properties of sewing thread with rising trend of static thread tension magnitude at lock stitched sewing machine has significant impact on lightweight lock stitched fabric assemblies to predict and elude seam pucker. The present research is focused to investigate impact of the thread bending rigidity on count, diameter and cyclic recovery at 4th cycle of four cores spun sewing threads. The study concluded that sewing thread bending rigidity has high coefficient of determination of sewing thread; diameter (R2 =0.81), count (R2 =0.73) and cyclic recovery (R2 =0.77). Single needle 400 lock stitched samples of two cores spun sewing threads (t2 and t4) were prepared with ten plain weave lightweight woven fabric samples prone to pucker at four different static needle thread tensions. It is also established that combined effect of sewing thread static tension and cyclic recovery at sewing machine has significant coefficient of determination (R2>0.85 at low static thread tension and R2>0.73 at very high static thread tension) to predict and elude seam pucker severity. Research finding provides a sustainable solution to select the fine count sewing thread attuned with lightweight woven fabrics prone to pucker severity. It was observed that the Fine count sewing thread has lowest bending rigidity and 4th cyclic recovery magnitudes (R2 close to 1) to reduce or predict pucker severity for prone to pucker plain weave lightweight woven fabrics at minimum static thread tension (25gf ) on single needle lock stitched sewing machine (R2>0.81).

PRELIMINARY RESULTS REGARDING THE OPTIMAL SEED RATES OF SOME WINTER WHEAT VARIETIES

Before to extended on large surfaces, the new wheat varieties need to be examinate to finding their requirements regarding technological components, like planting density. In accord with this demand, during the agricultural year 2021 – 2022 were tested at Oradea, in north-west of Romania, our news registered varieties Dacic and Biharia, beside of other 23 Romanian or foreign varieties of wheat, at seven seeding rates:200, 300, 400, 500, 600, 700 and 800 seeds/m2. Statistical processing of the yield and wheat features were dan by usual correlation (Pearson), Spearman rank correlations, the calculations of linear and quadratic equations of correlations between grain yield and seeding rate and calculation of linear, quadratic, exponential and logarithmic trend between the same characters, the trend of the most significant determination coefficient being utilised in graphical transpositions. Some genotypes (Voinic, Bogdana, Dacic, Cezara and Crisana) have their best ranks of yield at low densities while other (Gabrio, Consecvent, Anapurna and Abundent) at the greatest ones. Taking in consideration the average of ranks, the genotype Consecvent has the best average position, followed by Gabrio, Abundent, Bogdana and Voinic. These five genotypes have a good capability to adjust their yields components to vary densities of plants. At low densities (200, 300, 400 and 500 germinal seeds/m2), the genotypes yield ranks are comparable but at high densities (more than six hundred seeds/m2), the ranks are stronger effected by density. Every genotype has an optimum seed density, depending on its capacity to tolerate or no high density: Crisana- 500 seed/m2, Biharia- 600 seed/m2, Consecvent- 600 to 700 seed/m2, Anapurna- 800 seed/m2, etc. Some varieties, like Voinic, have a pour response to seeding rate, they yielded well even at small density, being able to compensate the reduced density by tillering capacity, number of grains/spikes, better test weight and bigger grain size.

67-LB: Factor Structure and Effects of Illness Perception on Depression and Anxiety in Patients with Diabetes

Objective: Illness perception represents how a patient perceives his or her health and illness. The Brief Illness Perception Scale (BIPQ; Broadbent et al. 2006) is often used to assess illness perception. However, the factor structure of the BIPQ is inconsistent across studies. The present study aimed to confirm the factor structure of the BIPQ in diabetic patients and to examine its impact on depression and anxiety. Methods: Patients with diabetes (N = 340, type 1: 39. type 2; 296, others: 5) provided demographic and clinical information and completed the Japanese version of the BIPQ, the Patient Health Questionnaire-9, and the Generalized Anxiety Disorder -7. This research was conducted with the approval of Waseda University's Ethics Review Committee on Human Studies (Accreditation Number: 2021-351). Results: We eliminated one item on the timeline because of the ceiling effect. Then, we conducted an exploratory factor analysis and adopted a two-factor structure. Moreover, a confirmatory factor analysis with the same two-factor structure indicated the sufficient model fit (GFI = .93, AGFI = .86, CFI = .87) Furthermore, from multiple regression analyses, assessed the effects of "Impact on daily life" and "Sense of control", the two factors we named, on depression and anxiety indicated a significant coefficient of determination (R 2 = .31, p < .001, R 2 = .30, p < .001). Additionally, the Impact on daily life (β = .36, p < .01, β = .29, p < .01) and the Sense of control (β = - .29, p < .001, β = -.23, p < .001) had significant effects on depression and anxiety. Conclusion: The results supported the two-factor structure of the BIPQ, similar to that for cancer survivors (Hata et al., 2020), even though we eliminated one item. Illness perception in patients with diabetes consists of the impact of the disease on their daily lives and their sense of control over diabetes and its symptoms. Improving these perceptions would reduce depression and anxiety. Disclosure E. Tajima: None. K. Hata: None. S. Suzuki: None. Funding Japan Society for the Promotion of Science (19J22933)

Application of the novel manta-ray foraging algorithm to optimize acidic peptidase production in solid-state fermentation using binary agro-industrial waste

Peptidases, which constitute about 20% of the global enzyme market, have found applications in detergent, food and pharmaceutical industries, and could be produced on a large scale using low-cost agro-industrial waste. An acidophilic Bacillus cereus strain produced acidic peptidase on binary-agro-industrial waste comprising yam peels and fish processing waste at pH 4.5 with high catalytic activity. A five-variable central composite rotatable design of a response surface methodology was used to model bioprocess conditions for improved peptidase production in solid-state fermentation. Data generated was leveraged as the basis for applying the novel Manta-ray foraging optimization-linked feed-forward artificial neural network to predict bioprocess conditions optimally. Results obtained from the optimization experiments revealed a significant coefficient of determination of 0.9885 with low-performance error. The bioprocess predicted a peptidase activity of 1035.32 U/mL under optimized conditions set as 54.8 g/100 g yam peels, 23.85 g/100 g fish waste, 0.31 g/100 g CaCl2, 47.54% (v/w) moisture content, and pH 2. Peptidase activity was improved 5-fold, and was stable for 240 min between pH 2.5 and 3.5. Michaelis-Menten kinetics revealed a Km of 0.119 mM and a catalytic efficiency of 45462.19 mM−1 min−1. The bioprocess holds promise for sustainable enzyme-driven applications.

Connections between spatially distant primary language regions strengthen with age during infancy, as revealed by resting-state fNIRS

Objective. Hearing is an important sensory function that plays a key role in how children learn to speak and develop language skills. Although previous neuroimaging studies have established that much of brain network maturation happens in early childhood, our understanding of the developmental trajectory of language areas is still very limited. We hypothesized that typical development trajectory of language areas in early childhood could be established by analyzing the changes of functional connectivity in normal hearing infants at different ages using functional near-infrared spectroscopy. Approach. Resting-state data were recorded from two bilateral temporal and prefrontal regions associated with language processing by measuring the relative changes of oxy-hemoglobin (HbO) and deoxy-hemoglobin (HbR) concentrations. Connectivity was calculated using magnitude-squared coherence of channel pairs located in (a) inter-hemispheric homologous and (b) intra-hemispheric brain regions to assess connectivity between homologous regions across hemispheres and two regions of interest in the same hemisphere, respectively. Main results. A linear regression model fitted to the age vs coherence of inter-hemispheric homologous test group revealed a significant coefficient of determination for both HbO (R 2 = 0.216, p = 0.0169) and HbR (R 2 = 0.206, p = 0.0198). A significant coefficient of determination was also found for intra-hemispheric test group for HbO (R 2 = 0.237, p = 0.0117) but not for HbR (R 2 = 0.111, p = 0.0956). Significance. The findings from HbO data suggest that both inter-hemispheric homologous and intra-hemispheric connectivity between primary language regions significantly strengthen with age in the first year of life. Mapping out the developmental trajectory of primary language areas of normal hearing infants as measured by functional connectivity could potentially allow us to better understand the altered connectivity and its effects on language delays in infants with hearing impairments.

Facile and highly precise pH-value estimation using common pH paper based on machine learning techniques and supported mobile devices

Numerous scientific, health care, and industrial applications are showing increasing interest in developing optical pH sensors with low-cost, high precision that cover a wide pH range. Although serious efforts, the development of high accuracy and cost-effectiveness, remains challenging. In this perspective, we present the implementation of the machine learning technique on the common pH paper for precise pH-value estimation. Further, we develop a simple, flexible, and free precise mobile application based on a machine learning algorithm to predict the accurate pH value of a solution using an available commercial pH paper. The common light conditions were studied under different light intensities of 350, 200, and 20 Lux. The models were trained using 2689 experimental values without a special instrument control. The pH range of 1: 14 is covered by an interval of ~ 0.1 pH value. The results show a significant relationship between pH values and both the red color and green color, in contrast to the poor correlation by the blue color. The K Neighbors Regressor model improves linearity and shows a significant coefficient of determination of 0.995 combined with the lowest errors. The free, publicly accessible online and mobile application was developed and enables the highly precise estimation of the pH value as a function of the RGB color code of typical pH paper. Our findings could replace higher expensive pH instruments using handheld pH detection, and an intelligent smartphone system for everyone, even the chef in the kitchen, without the need for additional costly and time-consuming experimental work.

Load extension behavior of spun sewing threads on seam slippage

The present research is focused to develop the relationship between the seam slippage and mechanical properties of sewn fabric by considering the spun thread and fabric configuration in the stitched assembly. Plain and twill weave fabric was used for the sample development stitch with the spun thread while the sewing machine setting was kept constant to produce a balanced seam. Different stitched samples are prepared in warp and weft direction for investigation by considering superimposed, flat, and bound seam classes with multi-thread chain, lock, and cover stitches. Experiment findings highlight the optimum load of seam slippage in N at 6 mm seam opening at stitched assembly by employing mentioned seam classes and stitch types. The results showed that 189.97 N maximum load was found at 6 mm seam opening for plain weave fabric in warp direction at flat seam sample with a lock stitched while in weft direction 80.65 N minimum load at the bound seam with multi-thread chain stitch. For twill weave fabric 94.72 N minimum slippage load at a 6 mm seam opening was observed in the weft direction at the bound seam with multi-thread chain stitch while in the warp direction maximum slippage load of 200 N was reported at the superimposed, flat and bound seam with multi-thread chain, lock and cover stitches. Established findings have a significant coefficient of determination (R2 0.90) between sewing thread extension and seam slippage load at 6 mm seam opening in both directions. The present research provides the guidelines to select the spun sewing thread which was possessed the minimum extension (%) against the respective load (N) to overcome the seam slippage in the stitched garment.

Comparative analysis of markers for H2O2-induced senescence in renal tubular cells

To address what marker(s) is/are most suitable for determining renal cell senescence, cell area, granularity, cycle shift/arrest, SA-β-Gal, SIRT1 and p16 were evaluated after inducing senescence in HK-2 cells with 0.2–0.8 mM H2O2. Only cell area and granularity concentration-dependently increased at all time-points, whereas SA-β-Gal, SIRT1 and p16 showed significant coefficient of determination (R2) at two time-points. Cell granularity had significant correlation coefficient (R) with other six, whereas SA-β-Gal had significant R with five, and cell area, SIRT1 and p16 had significant R with four others. Comparing to SA-β-Gal, other markers had significantly lower fold-changes only at 72-h with 0.8 mM H2O2, whereas p16 provided greater fold-changes at 48-h with 0.4 and 0.8 mM H2O2. Therefore, cell area, granularity, SA-β-Gal and p16 may serve as the most suitable markers for determining H2O2-induced senescence in HK-2 renal cells, whereas other markers can be also used but with inferior quantitative precision.

Organic matter composition regulates residual potential of organic carbon of the seagrass Zostera marina L. during its decomposition process in seawater

Although the seagrass Zostera marina L. (Z. marina) is expected to significantly contribute to environmental carbon dynamics, the residual potential of organic carbon (Corg) in this plant during its decomposition process in seawater remains insufficiently understood. In this study, the factors regulating this potential were examined by evaluating Z. marina decomposition in seawater and conducting a multiple regression analysis on data from the experiment as well as the original plant organic matter composition. The residual ratio during the decomposition experiment (RDEC) of carbon in Z. marina for 111 days ranged from 0.30 to 0.84 (n = 16), and the variation resulted from differences in the sampling season of this plant. Regression analysis was conducted to explain the RDEC of carbon using the RDEC of nitrogen, concentrations of carbon, nitrogen, HCl-extractable Corg and nitrogen, contributions of carbohydrate (CCAR) of total and non-structural fractions and lipid (CLIP) to carbon concentration. The RDEC of carbon was most adequately fitted using a multiple regression including three parameters, carbon concentration, CLIP, and CCAR of total carbohydrate with a significant determination coefficient. The former two parameters (carbon concentration and CLIP) have negative coefficients, indicating that these parameters correspond to bacterially available Corg in Z. marina in the regression analysis. The latter parameter (CCAR of total carbohydrate) shows a positive coefficient that indicates recalcitrant Corg in the regression. Parameters related to nitrogen were not included in the regression formula, although this element is reportedly an important parameter regulating the environmental decomposition rate of Corg. Finally, we suggested that total carbon, carbohydrate, and lipid are especially important factors to regulate the environmental residual potential of Z. marina Corg among organic components of this plant.

The Validity and Reliability of TrueDepth Camera Embedded in the Phone for Foot Measurement

There are several laser or structured-light based foot scanners available on the market, which can be used to obtain accurate 3D foot models. Compared to those 3D scanning devices, TrueDepth cameras are portable, inexpensive and easy-to-use. However, the accuracy and reliability of their 3D foot scanning remain to be confirmed. This study aimed to verify the validity and reliability of structured light TrueDepth camera integrated into the mobile phone when it is used for foot measurement. Thirteen students without any kinds of foot abnormalities or foot diseases were recruited and their feet were measured by both Infoot 3D foot scanner and mobile phone with TrueDepth camera. Three parameters were measured including foot length, foot breadth and ball girth. Subsequently, the reliability and validity of the two methods were assessed by linear regression analyses, intraclass Correlation Coefficient and Bland-Altman analysis. The foot breadth and girth circumference measurements all showed high coefficients of determination (R2>0.8) between the two methods and three measurements indicated good to excellent agreements (ICCs>0.9), although the length measurement was reported without significant coefficients of determination. Further, findings from Bland-Altman analysis demonstrated that the measurements from the TrueDepth camera had good agreements with those from Infoot and they could be used interchangeably. However, with the reconstruction algorithm updating in the near future, we could foresee the promotion in foot length measurement when using the TrueDepth camera from the phone. The TrueDepth camera utilizing structured-light and the customized application for foot measurement has fast, accurate and low-cost features and it is a convenient and economical method to obtain the foot 3D model. It can be widely applied for medical purposes and customization.

Effect of fatigue on tropical wood species

Abstract The aim of present study was to create a theoretical model that allowed, with security and reliability, to obtain values of strength and stiffness to which the structural element will be submitted throughout its useful life. The effect was studied for strength and stiffness properties, and the modulus of elasticity (EM) and bending strength (fM) on static bending test were evaluated according to the increasing number of cycles of the fatigue test for the five classes of hardwoods, recommended by NBR 7190 Standard Code. A reduction in strength and stiffness properties was observed with increasing loading Ncycles applied at two frequency levels. From the multivariate regression models and the respective determination coefficients, a generic model was obtained for the set involving the five wood species, emphasizing the insertion of the apparent density as an independent variable, which allowed a greater generalization of the use of the adjustments in the estimation of the EM and fM properties, presenting significant determination coefficients, ranging between 67.89% and 70.58%.

3D Assessment of Vine Training Systems Derived from Ground-Based RGB-D Imagery

In the field of computer vision, 3D reconstruction of crops plays a crucially important role in agriculture. On-ground assessment of geometrical features of vineyards is of vital importance to generate valuable information that enables producers to take the optimum actions in terms of agricultural management. A training system of vines (Vitis vinifera L.), which involves pruning and a trellis system, results in a particular vine architecture, which is vital throughout the phenological stages. Pruning is required to maintain the vine’s health and to keep its productivity under control. The creation of 3D models of vineshoots is of crucial importance for management planning. Volume and structural information can improve pruning systems, which can increase crop yield and improve crop management. In this experiment, an RGB-D camera system, namely Kinect v2, was used to reconstruct 3D vine models, which were used to determine shoot volume on eight differentiated vineyard training systems: Lyre, GDC (Geneva Double Curtain), Y-Trellis, Pergola, Single Curtain, Smart Dyson, VSP (Vertical Shoot Positioned), and the head-trained Gobelet. The results were compared with dry biomass ground truth-values. Dense point clouds had a substantial impact on the connection between the actual biomass measurements in four of the training systems (Pergola, Curtain, Smart Dyson and VSP). For the comparison of actual dry biomass and RGB-D volume and its associated 3D points, strong linear fits were obtained. Significant coefficients of determination (R2 = 0.72 to R2 = 0.88) were observed according to the number of points connected to each training system separately, and the results revealed good correlations with actual biomass and volume values. When comparing RGB-D volume to weight, Pearson’s correlation coefficient increased to 0.92. The results reveal that the RGB-D approach is also suitable for shoot reconstruction. The research proved how an inexpensive optical sensor can be employed for rapid and reproducible 3D reconstruction of vine vegetation that can improve cultural practices such as pruning, canopy management and harvest.

Remote sensing and machine learning based framework for the assessment of spatio-temporal water quality in the Middle Ganga Basin.

Understanding the dynamics of water quality in any water body is vital for the sustainability of our water resources. Thus, investigating spatio-temporal changes of dominant water quality parameters (WQPs) in any study is indeed critical for proposing the appropriate treatment for the water bodies. Traditionally, concentrations of WQPs have been measured through intensive fieldwork. Additionally, many studies have attempted to retrieve concentrations of WQPs from satellite images using regression-based methods. However, the relationship between WQPs and satellite data is complex to be modeled accurately by using simple regression-based methods. Our study attempts to develop a machine learning model for mapping the concentrations of dominant optical and non-optical WQPs such as electrical conductivity (EC), pH, temperature (Temp), total dissolved solids (TDS), silicon dioxide (SiO2), and dissolved oxygen (DO). In this context, a remote sensing framework based on the extreme gradient boosting (XGBoost) and multi-layer perceptron (MLP) regressor with optimized hyper parameters (HPs) to quantify concentrations of different WQPs from the Landsat-8 satellite imagery is developed. We evaluated six years of satellite data stretching spatially from upstream to downstream Ankinghat to Chopan (20 stations under Central Water Commission (CWC), Middle Ganga Basin) for characterizing the trends of dominant physico-chemical WQPs across the four clusters identified in our previous study. Through the developed XGBoost and MLP regression models between measured WQPs and the reflectance of the pixels corresponding to the sampling stations, a significant coefficient of determination (R2) in the range of 0.88-0.98 for XGBoost and 0.72-0.97 for MLP were generated, with bands B1-B4 and their ratios more consistent. Indeed, these findings indicate that from a small number of in-situ measurements, we can develop reliable models to estimate the spatio-temporal variations of physico-chemical and biological WQPs. Therefore, models generated from Landsat-8 could facilitate the environmental, economic, and social management of any waterbody.