Sampling Area Research Articles

Single-frame double-grating interferometry with two inherent-phase-shifted interferograms

In this work, we introduce a novel self-referencing, common-path, double-grating interferometry method for studying slowly varying phase samples. Two plane wave diffraction orders of the gratings, namely (0,+1) and (+1,0), with a certain phase difference, interfere with each other in a single frame. When a phase sample is applied in the middle of the impinging beam, two simultaneous inherent phase-shifted interferograms are generated on either side of the interference pattern. In one interferogram, the sample phase is added to (0,+1), while in the second one, the sample phase is added to (+1,0). Consequently, the phase of the first interferogram increases by the amount of the sample phase, while in the second interferogram, it decreases by the same amount. Without a phase sample, both interferograms have uniform intensity and value since the two interfering beams have the same phase difference in both patterns. We observe that the intensity changes in the two interferograms due to the phase sample, depending on the initial phase difference between the two interfering beams, can be equal or unequal, and in certain circumstances, they can be even complementary. We introduce a specific phase difference between the interfering orders by precisely controlling the separation between two diffraction gratings. This allows us to extract the sample's phase information from the resulting pair of interferograms. This setup enables us to obtain the sample phase without applying an additional phase shift(s) between the interfering beams. The method was applied to a thermal lens induced in a nonlinear liquid sample containing absorbent nanoparticles. The proposed method is characterized by its simplicity, accuracy, and insensitivity to vibrations, making it well-suited for analyzing dynamic samples with millimeter scales, such as nearly transparent organisms. The theory, simulations, and experimental results presented in this paper are found to be consistent. Unlike conventional methods, our approach does not necessarily require a reference interferogram. Additionally, when the absolute value of phase changes over the sample area and time is less than π, the raw phase pattern precisely matches the reconstructed phase pattern of the sample, eliminating the need for a phase-reconstructing algorithm. The phase pattern can be accurately calculated from the interferograms using an arcsine function without needing a fast Fourier transform. Compared to Fourier-based methods, the phase extraction process for each frame in our approach is 60 times faster. As a result, this technique operates in real-time for |φ(x, y;t) | < π.

Sex-based Differences in Fatty Acids and Macro Elements Composition in Garfish, European Barracuda and Anglerfish from Aegean Sea, Türkiye

Background: Fish, owing to its nutritional attributes, serves as a pivotal component of a wholesome diet. The constituents found in fish, specifically macroelements and polyunsaturated fatty acids (PUFA), play a crucial role in promoting human health. This study investigates the fatty acid profiles and macro element contents of economically significant fish species, including garfish (Belone belone), European barracuda (Sphyraena sphyraena) and anglerfish (Lophius piscatorius), with a specific focus on gender-based differences. The research addresses a notable gap in existing literature, providing a comprehensive evaluation of the nutritional quality of these species. Methods: In February 2023, marine fish species, were obtained from the Aegean Sea located between the western and southwestern shores of Türkiye and the eastern shores of Greece. A total of fifteen samples, representing each fish species and gender within the sampling area, were collected for the analysis of fatty acids and macro elements. Result: The findings of this study indicate that, regardless of fish species and gender, the major fatty acids in the SFAs, MUFAs and PUFAs classes were palmitic (C16:0), oleic (C18:1n-9) and DHA (C22:6n-3), respectively. The examined species in this study exhibit average macro element levels. While PUFA, EPA and DHA values meet target levels of content for human health and quality food consumption, achieving these levels minimally implies that the studied species lack a rich fatty acid profile compared to those in prior research. Nonetheless, it is concluded that monitoring seasonal variations is essential for a comprehensive understanding of their fatty acid composition.

Poaceascoma zborayi sp. nov. and Agrorhizomyces patris gen. et spec. nov. – Two novel dark septate endophytes colonizing wheat (Triticum aestivum) roots from a cropland in Hungary

In this study, we investigated two distinct new phylogenetic lineages of root-colonizing dark septate endophytic fungi colonizing wheat (Triticum aestivum) roots from a long-term agricultural experimental site in Hungary. According to four-locus (internal transcribed spacer, partial large and small subunit regions of nuclear ribosomal DNA, and partial translation elongation factor 1-alpha) phylogenetic analyses, the isolates belong to the Lentitheciaceae and Didymosphaeriaceae of the Pleosporales (Dothideomycetes). We studied the morphology and culture characteristics of the strains. We carried out in vitro resynthesis pot experiments with their original hosts and found no overall negative effect of the inoculation with different isolates of the new taxa. One of the lineages belonged to the genus Poaceascoma (Lentitheciaceae) and represented a novel species described here as Poaceascoma zborayi. We could describe conidia-like structures from this species. Isolates of the other lineage represented a monotypic novel genus in the Didymosphaeriaceae. Accordingly, the new genus, Agrorhizomyces, represented by the species A. patris, is introduced. Sterile, globose structures resembling immature sporocarps were detected. Sequence similarity searches indicated that P. zborayi might be widely distributed, while no sequence similar to A. patris was found outside the sampling area.

Conceptual design of a macromolecular diffractometer for the Jülich high brilliance source.

In this work, a concept for a neutron diffractometer for high-resolution macromolecular structures has been developed within the Jülich High Brilliance Neutron Source (HBS) project. The SELENE optics are adapted to the requirements of the instrument to achieve a tunable low background neutron beam at mm2 scale sample area. With the optimized guide geometry, a low background neutron beam can be achieved at the small sample area with tunable divergence and size. For the 1 × 1mm2 sample, a flux of 1.10 × 107 n/s/cm2 for 0.38° divergence is calculated in the 2-4Å wavelength range, which is about 84.6% of the flux at MaNDi of the high-power spallation source SNS at ORNL. Virtual neutron scattering experiments have been performed to demonstrate the instrument's capabilities for studies of mm scale samples with large unit cells. Results of Vitesse simulations indicate that unit cell sizes of up to 200Å are possible to be resolved with the proposed instrument.

Estimation of Oil Palm Tree Quantity Using Oil Palm Ecognition and SAGA GIS Based on UAV Imagery (Case Study: Dumai, Riau)

Abstract Oil palm is a plantation commodity in Indonesia that drives the growth of the national economy. The growth of oil palm is rapidly expanding every year, thus requiring efficient land monitoring strategies. Tree counting is one technique used to monitor current conditions in vast plantation areas. Utilizing UAV technology in agricultural mapping is the best option as a tool for capturing high-resolution aerial photos. The objective of this research is to automatically count the number of oil palm trees by comparing two methods and algorithms. GEOBIA (Geography-Based Image Analysis) and Deep Learning classification are methods used for automatic object counting. In this study, high-resolution aerial photo data was utilized, making object detection much more feasible. The research applied the Template Matching and Watershed Segmentation algorithm models in a sample area of 32.5 hectares divided into two blocks: Unknown-2 and E-1. It can be concluded that both methods, with their respective algorithm models, are sufficiently relevant for use in the automatic counting process of oil palm trees. This is evidenced by the accuracy test error values, which are not more than 15%, indicating that the counted oil palm tree results can be used for further data analysis.

Large‐Scale Lensless Microscopy with Fast Acquisition and Region‐Wise Focusing

AbstractLensless microscopy provides a wide field of view (FOV) determined by the image sensor size, allowing visualization of large sample areas. Coupled with advanced and even pixel super‐resolution phase retrieval algorithms, it can achieve resolutions up to the sub‐micron level, enabling both large‐FOV and high‐resolution imaging. However, high‐throughput lensless imaging encounters challenges in rapid data acquisition and large‐scale phase retrieval. Furthermore, when examining biological samples over a large FOV, focal plane inconsistencies often emerge among distinct regions. This study introduces a fast acquisition and efficient reconstruction method for coherent lensless imaging. Multiple measurements are manually modulated using an axial translation stage and sequentially captured by an image sensor, requiring no hardware synchronization. Optical parameter calibration, region‐wise auto‐focusing, and region‐wise phase retrieval algorithms are integrated to establish a general parallel computing framework for rapid, efficient, and high‐throughput lensless imaging. Experimental results demonstrate a 7.4 mm × 5.5 mm FOV and 1.38 µm half‐pitch resolution imaging of human skin and lung tumor sections with region‐wise focusing, requiring ≈0.5‐s acquisition time and 17‐s reconstruction time. By incorporating pixel super‐resolution, a 0.98 µm half‐pitch resolution is achieved in full‐FOV peripheral blood smears without additional data required, advantageous for discerning hollow shapes and segmenting blood cells.

Investigation of the role of distances from liquid crystal monomer (LCM) factories on distribution of LCMs in surface soil samples

Liquid crystal monomers (LCMs), which are commonly used in electronic device screens, have attracted attention as a potential class of emerging organic pollutants with persistent, bioaccumulative, and toxic (PBT) properties. This study involved the collection of 54 surface soil samples around one LC industrial park at increasing spatial distances within 1 km, 1–3 km, and 3–5 km from the center of the LC industrial park. Our observations revealed the presence of LCMs in 46 of 54 surface soil samples examined. Of the 39 target LCMs, 36 were identified, comprising 14 non-fluorinated and 22 fluorinated LCMs. Nine LCMs were detected at frequencies exceeding 20%, with 3bcHdFB exhibiting the highest detection frequency of 59% in the soil samples. The total LCM concentrations across the 46 sampling locations varied from 0.0072 to 17.24 ng/g dw, with the highest total concentrations at sampling sites within 1 km of the liquid crystal plant, suggesting that manufacturing processes may be a potential source for LCM release into the environment. Differences were observed in the LCM contamination patterns among the three sampling areas. Additionally, we observed a decrease in the median LCM concentration with increasing distance from the center of the LC industrial park. However, no statistically significant differences (p > 0.05) in LCM concentrations were observed across the three distances assessed in this study. This may be owing to the limited variety of target compounds analyzed and the limited number of soil samples. Our results emphasize that further studies on the emissions and pollution characteristics of LCMs during production are warranted.

Effects of calcium-to-silicon ratio on the properties of fly ash-based tobermorite and its removal performance of Zn2+ and Mn2.

The effects of calcium-to-silicon ratio on the properties of fly ash (FA)-based tobermorite and its removal performance of Zn2+ and Mn2+ were studied. The calcium-to-silicon ratio had a significant effect on the structural properties of the tobermorite samples. The specific surface area, pore volume, and average pore size of mesoporous tobermorite samples with different calcium-to-silicon ratios (0.8TOB, 1.2TOB, and 1.6TOB) were much larger than those of FA, and those of 1.2TOB were the largest, which were 53.29 m2/g, 0.448 cm3/g, and 30.50 nm, respectively. The removal efficiencies of Zn2+ and Mn2+ by 1.2TOB were 84.19% and 47.67%, respectively, which were much higher than those of 0.8TOB (60.62% and 42.41%), 1.6TOB (46.69% and 24.31%), and FA (4.13% and 6.95%). The adsorption of Zn2+ and Mn2+ by 0.8TOB, 1.2TOB, and 1.6TOB was corresponding to the pseudo-second-order kinetic model and Langmuir isotherm model. Particularly, 1.2 TOB showed the highest maximum adsorption capacities of Zn2+ and Mn2+ calculated from the Langmuir model, which were 129.70 mg/g and 82.09 mg/g, respectively. Moreover, the adsorption mechanisms might be due to the combination with -OH and the interlayer adsorption of the samples. This research provides new insight into the fly ash-based adsorbents towards Zn2+ and Mn2+ in wastewater.

Hyperspectral remote sensing of forage stoichiometric ratios in the senescent stage of alpine grasslands

Senescence is an important phenological stage in the life cycle of grassland plants, and estimating grass senescence in alpine grasslands is particularly crucial for animal husbandry and grazing the utilization of grassland resources for grazing. However, the application of proximal sensing technologies to capture the variations in forage growth parameters in the senescent stage, especially regarding some key stoichiometric ratios, still faces challenges associated with indiscernible spectral properties and indeterminate absorption and reflectance features. The present study aims to demonstrate the potential and effectiveness of applying hyperspectral data to assess the forage carbon-nitrogen (C:N) ratio and calcium-phosphorus (Ca:P) ratio during the senescent stage (September to November). A progressive variable dimensionality reduction strategy based on a genetic algorithm (GA) and hybrid optimization method (ant optimization colony (ACO) and extreme learning machine (ELM)) coupled with multiple linear and nonlinear statistical methods is applied to develop C:N ratio and Ca:P ratio estimation models via combination with data from 205 sample sites collected from six field campaigns (2016–2019) on the eastern Tibetan Plateau. The results show that the important spectral bands favorable for forage C:N ratio and Ca:P ratio retrieval are generally in the red and shortwave infrared (SWIR) regions, and the proposed model presents satisfactory performance in the estimation of the forage C:N ratio (V-R2 = 0.81, V-RMSE = 6.44) and Ca:P ratio (V-R2 = 0.64, V-RMSE = 2.54) during senescence. Moreover, the model can effectively overcome the spatial differences among sampling areas and perform optimally in capturing the variations in the forage C:N ratio and Ca:P ratio in the early and middle stages of senescence. Overall, our study demonstrates that it is feasible and promising to estimate these stoichiometric ratios using hyperspectral feature bands during grass senescence at the canopy level, with potential applications that may further enhance the monitoring of forage quality and quantity.

Bioaccumulation of heavy metals in Capoeta tinca fish and health risk assessment

The This study evaluates the potential human health risks associated with five heavy metals (Zn, Pb, Cu, Cd, and Cr) in Capoeta tinca fish. It assesses the heavy metal burden in the muscle, gill, and liver tissues of C. tinca, and estimates the potential health risks for consumers by employing estimated daily intake (EDI) and standard hazard ratios (THQ) related to heavy metal consumption. Fish and water samples were taken from three different Regions as Sincan Brook (Sivas–Hafik), Habeş Brook (Sivas–Zara), and Tozanlı Brook (Sivas–Hafik), Turkey. The heavy metal concentrations in the brook water were found to be higher than the established safe for safety threshold in all the sampling points. Besides that, the values were observed to be lower than the allowed limits. Considering the fish tissues, the Pb, Cd, and Cr concentrations were found to be higher than the safe limits predicted by WHO. The findings indicate that the liver of C. tinca fish exhibited the highest accumulation of heavy metals across all sampling areas. The highest heavy metal concentrations found in fish muscles were found to be (Cu) 2.51 ± 0.91 μg·g-1, (Cr) 0.45 ± 0.03 μg·g-1, (Cd) 0.88 ± 0.04 μg·g-1, (Pb) 2.04 ± 0.03 μg·g-1, and (Zn) 13.12 ± 1.08 μg·g-1. The descending order of heavy metal accumulation in gills was found to be Zn > Cu >Pb > Cd > Cr. Moreover, for each heavy metal, the Bio–concentration factor (BCF) index, Acceptable Daily Intake, EDI, and THQ (<1) values were found to be lower than the limits set in the international standards, indicating that no elements posing a threat to public health were encountered, thus not posing a short–term risk.

Precipitation data merging via machine learning: Revisiting conceptual and technical aspects

The development of accurate precipitation products of high spatio-temporal coverage is crucial for a wide range of applications. In this context, precipitation data merging (PDM), which entails the blending of satellite-based estimates with ground-based measurements, holds a prominent position, while currently there is an increasing trend in the deployment of machine learning (ML) algorithms in such endeavors. In the light of recent advances in the field, this work discusses key aspects of the PDM problem associated with: a) the conceptual formulation of the problem, that is closely related to the training of ML models and their predictive capacity, b) the selection of products fused, that is associated with the latency of final product and operational applicability of the method, c) the efficiency of single-step and two-step merging approaches, with the former one treating the problem via only regression algorithms, and the latter one via the combined use of classification and regression algorithms. By formulating PDM as a spatio-temporal prediction problem, we define and assess two different training strategies for the ML models, termed as full and per time step strategy, which entail the building of a single or several ML models, respectively. Furthermore, the performance of the full training strategy, which allows the development of predictions in both spatial and temporal dimensions, is assessed in the context of single-step and two-step merging. In each of the three scenarios, three popular ensemble tree-based ML algorithms are employed, i.e., the random forest, gradient boosting and extreme gradient boosting algorithm, resulting in nine merged products. To provide empirical evidence, we employ a datacube composed by ground-based daily precipitation observations, satellite-based and reanalysis estimates, as well as auxiliary covariates, from 1009 uniformly distributed cells (representative of a sampling area of 25 × 25 km), over four countries around the world (Australia, USA, India and Italy). The large-scale experiment indicates that: (i) full training strategy is a competitive alternative to the per time step strategy, since it enables the development of methods with improved accuracy, with respect to performance metrics and reproduction of statistics, but also with higher predictive capability and operational applicability, (ii) two-step merging enables a much better reproduction of precipitation occurrence characteristics, as reflected in the improvement of relevant categorical metrics, the reproduction of probability and autocorrelation coefficient, (iii) no significant difference was noticed in the performance of different ML algorithms.

KERAPATAN DAN KELAS KEHADIRAN JENIS EHA (CASTANOPSIS BURUANA MIQ) DI BLOK LINDUNG TAHURA NIPA-NIPA KELURAHAN PUNGGALOBA KENDARI

The Tahura Nipa-Nipa nature conservation area located in the city of Kendari has a type of Eha that is susceptible to disturbance. The research aimed to determine the density level of the Eha (Castanopsis buruana Miq) species at tree, pole, sapling and seedling level growth; knowing the presence class in the community (presence) and knowing the distribution pattern. The observation sample used the plotted path method with a sampling intensity of 1% and an entire sample area of 0.96 ha. The sample consisted of 3 transects each containing 8 plots (0.04 ha per plot), so the total sample was 24 plots. Transects were placed systematically, the distance between transects was 100 m, and the distance between plots within transects was 20 m. The results showed that the Eha tree density level was 107.29 trees/ha, the pole level was 200 trees/ha, the sapling level was 233.33 trees/ha, and the seedling level was 13229.166 trees/ha. The presence of Eha in the community at the tree, pole and seedling level is in the "Always Present" class (81%-100%). Meanwhile, the stake level and presence in the community is in the "Sometimes There" class (21%-40%). The distribution pattern of Eha at the tree level is clustered, while at the pole, sapling and seedling levels it is a regular pattern.

Impact of Mining of Marine Gastropods Habitat: Basis for Information Education Communication(IEC) for Environmental Sustainability

An alarming socio-economic and environmental impact of mining in the Municipality of Carrascal, Surigao del Sur led to this study. It is important to assess the impact of mining on marine habitats and the diversity of gastropods in the area. The collection of gastropods is done in the selected four sampling areas, which include Brgy. Adlay, Brgy. Caglayag, Brgy. Dahican, and Brgy. Gango. Based on the sampling, 228 marine gastropod species were collected, consisting of 53 genera belonging to 10 families. The findings highlight the low diversity of the marine gastropods in the study area as the diversity index is less than 1.99. In addition, the physico-chemical parameter assessment of the study area reveals conditions ranging from slightly alkaline water with low oxygen content to very warm temperatures. These conditions suggest a delicate balance in the aquatic ecosystems, which could be sensitive to changes and affect marine gastropod populations and distributions. With regards to the average concentration of nickel (mg/kg) sediments as a result of the mining activities in the study area, the atomic absorption spectrophotometry result shows that Brgy. Gango is heavily polluted in comparison to other sampling areas. Additionally, the multiple regression analysis reveals that there is a positive and significant association between the nickel concentration and the diversity of gastropods in Brgy. Gango. This could indicate that some gastropod species, specifically those that are found in areas with high nickel concentrations, have acquired tolerance to nickel pollution. However, the regression analysis reveals that in the other sampling sites, such as Brgy. Adlay and Brgy. Caglayag, the presence of nickel sediments as a result of mining activities has a negative and significant impact on the marine habitat and diversity of gastropods. The findings suggest the importance of developing an information education and communication program addressing the negative impacts of mining and promoting environmental sustainability in the research locale.

Evaluation of microstructure heterogeneity in INCONEL 625 thin-wall fabricated by Laser Powder Bed Fusion additive manufacturing

This study provides a thorough investigation of microstructural heterogeneity and its relationship to the mechanical properties of Inconel 625 (IN625) alloy in as-built Laser Powder Bed Fusion (LPBF) parts. Specifically, detailed high-resolution electron microscopy coupled with thermodynamic simulation, finite element analysis, and nano-hardness testing were carried out. Through the combination of these methods, a new method is proposed to develop a process-structure–property map to illustrate the complex relationship between spatial thermal conditions, microstructure, and mechanical properties in various areas of an LPBF IN625 sample. Different precipitates, including γ′′, Laves, NbC, and Al2O3 oxide were observed along the build direction from the bottom to the top layers of the LPBF part as a function of build height. The hardness value was shown to be minimum in the middle layers while attaining maximum values in the bottom (near the substrate) and top (near the surface) layers of the build’s height. The mechanism for the formation of precipitates during multi-layer additive manufacturing and the dependency of the mechanical properties on the type and distribution of these precipitates are discussed.

The Response Characteristics of Pore Volume and Specific Surface Area of Different Phases of Carbon Dioxide Injection into Anthracite Coal Pores

After the coal sample reacts with CO2, the porosity and pore volume change. Compared with dry raw coal sample, the porosity of coal after CO2 adsorption is increased. With the increase of CO2 injection pressure, the porosity of coal will gradually increase, especially when CO2 enters the supercritical phase. In terms of pore capacity of coal samples, CO2 adsorption time, CO2 adsorption pressure and CO2-H2O treatment do not show obvious regularity in the changes of pore capacity of coal samples, but in general, the increase of CO2 adsorption pressure and CO2-H2O treatment have a positive effect on the increase of pore capacity of coal samples, especially ScCO2-H2O. The mesoporous pore capacity increased by 137.1%. In terms of macro pore volume of coal sample, the change of macro pore volume after CO2 adsorption is more regular. Extending CO2 adsorption time, increasing CO2 adsorption pressure and CO2-H2O treatment all have positive effects on the increase of macro pore volume of coal sample. Under 8MPaScCO2-H2O, macro pore volume reaches a maximum of 0.016462ml/g. The increase also reached 130.4 percent. On the mesoporous specific surface area of coal sample, increasing CO2 adsorption pressure, prolongating CO2 adsorption time and CO2-H2O treatment can increase the mesoporous specific surface area of the sample. The mesoporous specific surface area of the sample at 8 MPa ScCO2-H2O is 0.631 m2/g, which reaches the maximum in this experiment, with an increase of 334.27%.

Quantitative Assessment of Morphological Changes in Lipid Droplets and Lipid-Mito Interactions with Aging in Brown Adipose.

The physical characteristics of brown adipose tissue (BAT) are defined by the presence of multilocular lipid droplets (LD) within the brown adipocytes and a high abundance of iron-containing mitochondria, which give it its characteristic color. Normal mitochondrial function is, in part, regulated by organelle-to-organelle contacts. Particularly, the contact sites that mediate mitochondria-LD interactions are thought to have various physiological roles, such as the synthesis and metabolism of lipids. Aging is associated with mitochondrial dysfunction, and previous studies show that there are changes in mitochondrial structure and proteins that modulate organelle contact sites. However, how mitochondria-LD interactions change with aging has yet to be fully clarified. Therefore, we sought to define age-related changes in LD morphology and mitochondria-lipid interactions in BAT. We examined the three-dimensional morphology of mitochondria and LDs in young (3-month) and aged (2-year) murine BAT using serial block face-scanning electron microscopy and the Amira program for segmentation, analysis, and quantification. Analysis showed reductions in LD volume, area, and perimeter in aged samples compared to young samples. Additionally, we observed changes in LD appearance and type in aged samples compared to young samples. Notably, we found differences in mitochondrial interactions with LDs, which could implicate that these contacts may be important for energetics in aging. Upon further investigation, we also found changes in mitochondrial and cristae structure for mitochondria interacting with LD lipids. Overall, these data define the nature of LD morphology and organelle-organelle contacts during aging and provide insight into LD contact site changes that interconnect biogerontology and mitochondrial functionality, metabolism, and bioactivity in aged BAT.

Valor económico de los servicios ecosistémicos asociados a los corredoresfluviales atlánticos en el noroeste de la Península Ibérica

Valuing the benefits of conserving river corridors is essential to recognize the contribution of this natural capital to our well-being. This study aims to quantify the economic value of welfare improvements from the restoration of Atlantic River corridor habitats in Natura 2000 Network sites in the northwest Iberian Peninsula included in the LIFE Fluvial project. The contingent valuation method was used to estimate a discrete choice econometric model of willingness to pay for actions that protect ecosystem benefits associated with riparian forest restoration, and more than 600 residents and visitors in four major project areas were surveyed in 2021. The average willingness to pay was almost € 53 per resident and year (annual benefit to residents for the use, enjoyment and knowledge of the ecosystem services provided by these sites) and € 42 per visitor and year. By extrapolating these values to the population and visitors of the most representative sample areas we got an economic value for this type of conservation action of 4.2 million euros per year, much higher than the cost of implementing the entire project (3.03 million euros).

Problems of Anxiety among Differently Abled Children - An Academic Perspective

Differently abled children may feel sometimes confused, insecurity, anxious, disoriented, isolated, worried, rigid and less happy. These emotions fluctuate and subject to turbulent and unpredictable behavior. Stress therapy can lead to a reduction in stress, anxiety, better sleep, a strong system, improved relationships, better academic results, improved performance at work and even a better memory. The present study examines the stress and anxiety levels among the differently abled children in the selected study area and it analyzes the effectiveness of stress therapy on the anxiety levels among the differently abled children. The study further evaluates the association between the demographic variables and the anxiety level among the differently abled children.The present research study adopts Descriptive Research Design. Both primary and secondary data were utilized for drawing conclusions from the study. Interview Schedule method was employed to extract the primary data from the selected sample respondents. The sampling area selected for the study was Krishna District of Andhra Pradesh. The sample size comprises 140 sample respondents. The nature of the sample was that of the physically challenged children with different disabilities studying at different special schools in the study area. Statistical tools like percentages, mean, standard deviation, t-test and chi-square test were applied in order to draw the inferences from the study data. The study concludes that there exists a significant difference between the pre and post stress therapy anxiety levels among the differently abled children and there exists a significant association between the demographic variables and the anxiety levels of the differently abled children. The study further concludes that the stress therapy and other practices of stress management are very helpful for reducing the anxiety and stress levels among the differently abled children especially in the perspectives of academic aspects.

DCSN: Focusing on hard samples mining in small-sample fault diagnosis of marine engine

Fault samples of marine engine are extremely scarce, and there are unavoidably some hard samples with small inter-class differences, which pose a serious challenge to fault diagnosis of marine engines. This paper proposes a deep metric learning method, namely deep concentric Siamese network (DCSN), to apply strong forces to hard samples towards their corresponding correct distribution areas under small-sample conditions. First, DCSN is committed to learn discriminative information from limited fault samples through a carefully designed metric learning strategy. Then, DCSN distinguishes hard samples using inner and outer boundaries, and applies strong forces to them, making the deep model more focusing on the correct classification of hard samples. Third, DCSN shrinks the distribution area of intra-class samples, which improves intra-class compactness and inter-class separability. Finally, the experimental results on the marine engine fault dataset show that the proposed DCSN yields higher diagnostic performance compared to the considered competitive methods.

HYGROSCOPIC WATER CONTENT AS AN INDICATOR OF SOIL DISPERSITY:THERMODYNAMIC BASIS AND EXPERIMENTAL VERIFICATION

The adsorption properties of dispersed systems are determined by their surface energy, therefore the indicators of hygroscopy (adsorbed water content) and dispersity (specific surface area of the solid phase) of soils and sediments are in close mutual correlation. This well-known empirical fact received a new fundamental interpretation based on the theory of disjoining water pressure according to Deryagin in the form of a thermodynamic equation connecting the specific surface area, hygroscopic water content of soil samples and the relative humidity of the air in the laboratory room. The theoretical equation allowed us to substantiate the methodology for quantifying the hydrophilic specific surface area of soil samples based on widespread data on their hygroscopy. A comparison of the new method with the standard BET-analysis of the specific surface area, as well as with the previously proposed physically based method for its determining by the slope of thermodynamic water retention curves, showed their statistically reliable agreement in a wide range of estimated specific surface area values from 5 to 340 m2×g-1 for soil samples of different genesis and texture.