Density Patterns Research Articles

Chemical mechanical polishing for indium bond pad damascene processing

We investigated chemical mechanical polishing (CMP) of indium, with the goal of obtaining indium bond pads for later cryo-3D integration of quantum computing-related chips, through bonding between these bond pads and indium bumps. Higher removal rates were obtained with soft CMP pads than with hard pads. The latter led to deep scratching, while this effect was much more limited for soft pad CMP. On patterned wafers, indium is cleared well in structured areas using soft pad CMP, leading to relatively high-quality indium surfaces inside bond pads, although corrosion might be of some concern. Pattern density uniformity was an important factor for within-die deviation in indium clearing time. Dishing was much more limited than in earlier work on indium polishing, while surface roughness was also found to be relatively limited. The obtained indium damascene bond pads may be suitable for 3D die-to-die and wafer-to-wafer bonding through indium pad-to-bump bonding.

EVALUATION OF CLOUD TO GROUND FLASH DENSITY OF 150 KV TRANSMISSION LINE BETWEEN PARIT BARU SUBSTATION AND SENGGIRING SUBSTATIO

SUTT is a high voltage overhead line with a power of 70 kV - 150 kV to distribute electric power from the generating center to the substation or from substation to substation. The purpose of this study was to obtain modeling of lightning strike density on the 150 kV transmission line between Parit Baru substation and Senggiring substation using geostatistical approaches, namely IDW methods (Inverse Distance Weighted). In identifying the level of vulnerability to lightning strikes, Cloud to Ground lightning event data (2018–2020) is used. The aim of this research is to obtain the density pattern of lightning strikes on the 150 kV transmission line between the Parit Baru substation and the Senggiring substation. The process in ArcGIS 10.8 software aims to obtain lightning strike density and display the results of the lightning strike density map. Based on the results of data processing for 3 years, the highest density of lightning strikes occurred in 2019 in Segedong District at 54.52 strikes/km². Meanwhile, the lowest density of lightning strikes occurred in 2018 in East Mempawah District, amounting to 2.86 strikes/km². Based on the lightning strike density map per grid on the 150 kV transmission line between Parit Baru substation and Senggiring substation for 3 years, the results obtained for the highest lightning strike were 36 strikes/km² while for the lowest strike it was 1 strike/km². From this research, it was found that there were 15 transmission towers that passed a high density of lightning strikes with a strike range of 25–36 strikes/km² and the highest lightning strike occurred at tower number 31, number 30, and number 29, amounted to 36 strikes/km².

Comparison of Measured and Calculated Porosity Parameters of Woven Fabrics to Results Obtained with Image Analysis.

Porosity, the measure of the open spaces within a fabric structure, is a decisive factor in the performance of textiles. It influences breathability, permeability to liquids or gases, and suitability for various industries such as apparel, medical, and technical textiles. This study compares classical porosity calculation methods with non-destructive image analysis for 24 woven fabric samples that differ in density and weave pattern. Factors such as fabric density, weave pattern, illumination conditions, magnification, and the influence of the Otsu and Yen threshold algorithms were considered. The multifactor ANOVA statistical analysis shows that fabric density and weave pattern significantly influence porosity, with illumination playing an important role, while the threshold algorithm has a minor influence. A strong correlation is found between the actual fabric porosity and the results of the image analysis, except for double-sided illumination (reflective and transmissive), where the correlation is weakest. This comprehensive investigation provides valuable insights into the reliability of different porosity assessment approaches, which is essential for applications in various textile industries.

Individual nursery trees classification and segmentation using a point cloud-based neural network with dense connection pattern

Nurseries are used to cultivate a variety of tree species. Obtaining some specific information like the tree species, positions of crowns and trunks can enhance the efficacy of nursery management. Due to the robustness to illumination, the point cloud-based neural network models have become extensively employed in segmenting and classifying individual trees from large-scale data. However, few studies have focused on further processing the point clouds of individual trees. Therefore, D-PointNet++ (Dense PointNet++) is proposed in this paper for classifying tree species and segmenting different parts of trees (crowns, trunks, pots and supporting poles). D-PointNet++ utilizes a dense connection pattern in the feature extraction module, inspired by the architecture of DenseNet. Additionally, the proposed model uses a gating system and concatenation as fusion operations to combine point cloud features with different dimensions to improve accuracy. The point cloud data of seven different types of garden trees in the nursery was collected using a laser sensor. The experimental results demonstrate that D-PointNet++ surpasses two representative baseline methods, PointNet and PointNet++, in terms of both classification and segmentation accuracy. For the self-made nursery dataset, the classification overall accuracy (OA) and class accuracy (mAcc) of D-PointNet++ can reach 92.65% and 92.54%; the average Intersection over Union (mIoU) and mAcc can reach 89.90% and 92.18%, respectively. The proposed D-PointNet++ can provide more accurate information on each tree and is beneficial to the management of the nursery.

Iris-Based Biometric Identification Using a Combination of the Right - Left Iris Statistical Features

A combination between the information extracted for both right iris and left iris could increase the efficacy of the biometric recognition systems. In this paper, we propose a biometric identification method based on density of image patterns extracted from human iris images and the combination and comparison of the right iris and the left iris characteristics. The density of the patters approach for processed images can be a new biometric feature used to implement a biometric recognition system with high performance when a small feature dimension is used. In this way, we can maximize the retention of the effective biometric information. The experiments were conducted on the MMU Iris Database containing 225 images of the left eye and 225 images of the right eye. Two morphological Top-hat and Hit or Miss transforms were implemented to find out the particular pattern of pixels. They allow for the enhancement of detail in images. Then, a statistical feature extraction technique is employed to derive the density of the patterns in morphological transformed images. To assess the density of the patterns differences between the right and left iris data groups, the Pearson’s correlation coefficient (PCC) is computed. We reported very good results with a PCC of 0.6164 (strong and positive correlation) for Top-hat morphological operation whilst the Hit or Miss transform returns a PCC of 0.0127 so there is no relationship between the density of the patterns in the right and left irises.

Air assistance and spray volumes on the coverage, droplet density, and spray deposition in melon plants

This study aimed to evaluate the influence of air assistance on the coverage, droplet density, and deposition of the mixture volume applied to melon plants. The experiment was conducted in a completely randomized design set up in a 4 x 4 x 2 factorial arrangement referring to four spray nozzles (AVI 110-02, TT 110-02, AVI 110-03, and TT 110-03), four mixture volumes (140, 200, 300, and 400 L ha-1), and two application techniques (with and without air assistance), at a constant working pressure of 300 kPa. Deposition analysis was performed by using a bright blue dye, and the coverage pattern and droplet density were analyzed using water-sensitive paper tags attached to the adaxial and abaxial surfaces of the leaf blade of melon plants. Air assistance in the spray boom improved the deposition of the mixture sprayed on melon leaves only when using nozzle TT 110-02, whereas nozzles TT 110-03, AVI 110-02, and AVI 110-03 were not influenced by air assistance. Coverage and spray deposition on the adaxial leaf surface increased with the mixture volume applied for all nozzles. The technique using water-sensitive tags is not efficient to evaluate droplet density when working with high spray volumes.

Imaging Characteristics of Clear Cell Papillary Renal Cell Carcinoma: Identifying the Sheep in Wolf's Clothing.

This study aimed to describe the characteristics of computed tomography (CT) and magnetic resonance imaging (MRI) of clear cell papillary renal cell carcinoma (CCPRCC). This retrospective study comprised 27 patients diagnosed with 29 tumors of CCPRCC. The study was approved by the Medical Ethics Committee and the requirement for the informed consent was waived. The inclusion criteria stipulated pathology-confirmed CCPRCCs with at least one preoperative imaging examination, including CT or MRI. Two experienced radiologists independently analyzed the imaging characteristics, including size, location, growth mode, morphology, texture, density, and enhancement pattern. Paired t-test was used to compare differences in CT Hounsfield unit values and apparent diffusion coefficient (ADC) imaging between the tumor and the renal cortex. The mean age of the 27 patients was 57.0 ± 14.2 years. Nineteen patients underwent CT, while 12 underwent MRI (There are 4 patients underwent not only CT but also MRI). Among the cases, 26 (96%) were single, and 1 (4%) was multiple, consisting of three lesions. Out of the 29 tumors, 15 (52%) were located in the left kidney and 14 (48%) in the right kidney. The mean tumor diameter was 3.3 ± 1.7 cm. Furthermore, 19 (66%), 3 (10%), and 7 (24%) tumors were solid, cystic, mixed solid, and cystic type, respectively. The growth mode was endogenous and exogenous in 8 (28%) and 21 (72%) tumors, respectively. The tumor shape was irregular and round in 5 (17%) and 24 (83%) tumors, respectively. The CT value of the tumor was approximately 33.2 ± 9.8 HU, which was not significantly different from that of the renal cortex(31.1 ± 6.3HU)(p = 0.343). Furthermore, 7 (24%), 12 (41%), and 3 (10%) had calcification, cystic degeneration, and hemorrhage, respectively. In 12 tumors, hypointense and hyperintense were predominant on T1 and T2-weighted images, respectively. The tumor capsule was found at the edge of 12 tumors. The average ADC value of the tumor (1.54 ± 0.74 × 10-3 mm2/s) and that of the renal cortex(1.68 ± 0.63×10-3mm2 /s) was not statistically significantly different (p = 0.260). The enhancement scanning revealed "wash-in and wash-out" enhancement in 19 (68%) tumors, continuous or progressive enhancement in 6 (21%) tumors, and enhanced cystic wall and central separation in 3 (11%) tumors. CCPRCC occurs more likely in middle-aged and elderly individuals, and the tumor is prone to cystic degeneration, with rare bleeding and calcification, and no obvious limitation on MRI diffusion-weighted imaging, which enhancement form performs as mainly "wash-in and washout," but the final diagnosis depends on histopathology.

Optimizing 3D printed diamond lattice structure and investigating the influence of process parameters on their mechanical integrity using nature-inspired machine learning algorithms

This research investigates the effect of process parameters on the mechanical integrity of 3D-printed Polylactic Acid (PLA+) lattice structures, with a focus on diamond lattice configurations. Adhering to ASTM D695 standards, the study employs compression testing to analyze the impact of various factors, including layer height, infill pattern, cell size, and infill density. The printing process utilizes the Ultimaker Cura Fused Deposition Modelling method, ensuring accuracy and uniformity in sample production. Mechanical properties were assessed using a Universal Testing Machine, highlighting the influence of the studied parameters on compressive strength and specific energy absorption (SEA). Innovatively, this study integrates nature-inspired machine-learning algorithms for hyperparameter tuning. Particle Swarm Optimization (PSO) is employed to optimize the settings of Random Forest and XGBoost models, enhancing their predictive capabilities. Results indicate that XGBoost, fine-tuned with PSO, slightly outperforms its counterpart in predicting key mechanical properties. Furthermore, feature significance assessments reveal cell size as a critical factor for compressive strength. This research not only provides a comprehensive analysis of mechanical properties in 3D-printed structures but also introduces a novel approach to applying nature-inspired algorithms for machine learning optimization in additive manufacturing.

Scarcity and quality risks for future global urban water supply

ContextSupply of freshwater to the world’s cities is increasingly affected by human pressures and climate change. Understanding the effects of human pressures and climate change on global urban water scarcity and quality risks in an integrated way is important.ObjectivesThe objective of this study is to assess the scarcity and quality risks to water security for 304 large cities (population > 1 million) across the world for 2015 and 2050.MethodsWe assessed the water scarcity according to water demand and availability, and evaluated the quality of water supply in terms of the population density, cropland fertilization, and landscape patterns in source watersheds. In addition, the impacts of human pressures and climate change on urban water risks were quantified using contribution analysis.ResultsWe found that about 90% of these cities faced water risks in 2015. The number of cities facing quality risk was about three times the number of cities facing scarcity risk, and nearly a quarter faced dual risks. From 2015 to 2050, 88.8–99.7% of cities were projected to face rising water risks with about one-third facing dual risks by 2050. Increase in water demand was the main cause of rising scarcity risk; growth in population and crop fertilization in source watersheds were the main reasons for rising quality risk.ConclusionsThere is an urgent need to promote landscape conservation of urban water source areas, implement sustainable urban water planning and governance, improve water supply infrastructure, and refine ecological compensation regimes to achieve global urban water security.

Global distribution of surface soil organic carbon in urban greenspaces

Urban greenspaces continue to grow with global urbanization. The global distribution and stock of soil organic carbon (SOC) in urban greenspaces remain largely undescribed and missing in global carbon (C) budgets. Here, we synthesize data of 420 observations from 257 cities in 52 countries to evaluate the global pattern of surface SOC density (0–20 cm depth) in urban greenspaces. Surface SOC density in urban greenspaces increases significantly at higher latitudes and decreases significantly with higher mean annual temperature, stronger temperature and precipitation seasonality, as well as lower urban greenness index. By mapping surface SOC density using a random forest model, we estimate an average SOC density of 55.2 (51.9–58.6) Mg C ha−1 and a SOC stock of 1.46 (1.37–1.54) Pg C in global urban greenspaces. Our findings present a comprehensive assessment of SOC in global urban greenspaces and provide a baseline for future urban soil C assessment under continuing urbanization.

A Comparison Study of Edge Line Estimation Algorithms for Dimensional Quality Assessment of Precast Concrete Slabs

Point cloud data-based edge line extraction is an important task for accurate geometrical inspection of precast concrete (PC) elements in the construction industry. Although a few edge extraction algorithms have been developed so far based on point cloud data, little attention has been paid on which edge extraction algorithm performs the best in terms of edge estimation accuracy. To tackle the research gap, this study aims to evaluate currently available edge extraction algorithms in order to determine optimal algorithm for precise geometrical inspection of PC elements. To do this, simulated scan points are first generated and used for algorithm performance analysis using a geometrical model and a measurement noise modeling that determine the coordinates of simulated scan points. For validation of the simulation approach, comparison tests with experimental data are performed and the results show that the simulation approach has a high similarity of more than 90% compared to experimental data in terms of the number of scan points, scan pattern, and scan density, proving the effectiveness of the simulation-based evaluation method. In addition, it shows that a least square regression (LSR) algorithm provides the best performance with an edge extraction accuracy of 1.56 and 2.71 mm for simulated and experimental scan points, respectively. The contributions of this study are (1) development of the geometrical model and noise modeling based on actual scan data and (2) validation of simulated-based evaluation method on the lab-scale PC slabs.

Spatial Optimization and Temporal Changes in the Ecological Network: A Case Study of Wanning City, China

Ecological networks serve as vital tools for safeguarding biodiversity and ensuring regional ecological stability. This study, conducted in Wanning City, employs minimum-area threshold analysis to pinpoint crucial ecological sources while extracting potential ecological corridors using the minimum cumulative resistance model. Our investigation delves into the ecological network’s elements and structural transformations within Wanning City, spanning the period from 2000 to 2020, and assesses the priorities for ecological network preservation. The findings of our research reveal noteworthy spatial disparities in the distribution of ecological sources across Wanning City. Furthermore, the ecological corridors display sparse patterns in the north and denser patterns in the south. Over the two decades from 2000 to 2020, Wanning’s ecological resources exhibited a discernible trend of contraction and fragmentation, accompanied by an uneven spatial distribution. The average path length of the ecological corridors has increased, indicative of reduced biological flow efficiency. Correspondingly, the structural accessibility of the ecological network has decreased, signifying a decline in landscape connectivity. Based on our analysis, we propose an ecological protection and restoration framework denoted as “One Belt, Four Sources, Eight districts, multiple corridors, and multiple points”. Therefore, with the Shangxi–Jianling, Liulianling, Nanlin, and Jiexin nature reserves as the core area, and Houan Town, Damao Town, Changfeng Town, and Liji Town as the key restoration areas, we have proposed an ecological protection and restoration pattern.

Asymmetrical Microfracture Density Across an Active Thrust Fault: Evidence from the Longmen Shan Fault, Eastern Tibet

Abstract Microfracture density in fault damage zones can reflect spatial variability that decays in intensity as a function of distance from the fault, which is crucial in understanding the mechanical, seismological, and fluid-flow properties of the fault system. However, few studies explored the characteristics of fracture density between the two sides of active dip-slip faults due to rare field observations. Here, we measured and modeled microfractures across an active thrust fault associated with the 2008 Mw 7.9 Wenchuan earthquake in the Longmen Shan, eastern Tibetan Plateau. The results showed that the microfracture density at the Qingping site developed more intensely in the hanging wall than in the footwall for an exposed thrust fault, indicating an asymmetrical pattern. The hidden thrust fault at the Jushui site showed that microfractures developed more intensely in vertical planes in the hanging wall than in the footwall, whereas microfractures developed similarly in horizontal planes within the two sides, indicating a quasiasymmetrical pattern. Comparing the data at the two sites with computational modeling, we suggest that fault geometry might exert a first-order control of the asymmetrical microfracture density pattern, which is helpful for revealing different deformational behaviors of rock masses in the fault damage zones and better understanding the hanging-wall effect for evaluating seismic hazards on active thrust faults.

The Automatic Context Measurement Tool (ACMT) to Compile Participant-Specific Built and Social Environment Measures for Health Research: Development and Usability Study.

The environment shapes health behaviors and outcomes. Studies exploring this influence have been limited to research groups with the geographic information systems expertise required to develop built and social environment measures (eg, groups that include a researcher with geographic information system expertise). The goal of this study was to develop an open-source, user-friendly, and privacy-preserving tool for conveniently linking built, social, and natural environmental variables to study participant addresses. We built the automatic context measurement tool (ACMT). The ACMT comprises two components: (1) a geocoder, which identifies a latitude and longitude given an address (currently limited to the United States), and (2) a context measure assembler, which computes measures from publicly available data sources linked to a latitude and longitude. ACMT users access both of these components using an RStudio/RShiny-based web interface that is hosted within a Docker container, which runs on a local computer and keeps user data stored in local to protect sensitive data. We illustrate ACMT with 2 use cases: one comparing population density patterns within several major US cities, and one identifying correlates of cannabis licensure status in Washington State. In the population density analysis, we created a line plot showing the population density (x-axis) in relation to distance from the center of the city (y-axis, using city hall location as a proxy) for Seattle, Los Angeles, Chicago, New York City, Nashville, Houston, and Boston with the distances being 1000, 2000, 3000, 4000, and 5000 m. We found the population density tended to decrease as distance from city hall increased except for Nashville and Houston, 2 cities that are notably more sprawling than the others. New York City had a significantly higher population density than the others. We also observed that Los Angeles and Seattle had similarly low population densities within up to 2500 m of City Hall. In the cannabis licensure status analysis, we gathered neighborhood measures such as age, sex, commute time, and education. We found the strongest predictive characteristic of cannabis license approval to be the count of female children aged 5 to 9 years and the proportion of females aged 62 to 64 years who were not in the labor force. However, after accounting for Bonferroni error correction, none of the measures were significantly associated with cannabis retail license approval status. The ACMT can be used to compile environmental measures to study the influence of environmental context on population health. The portable and flexible nature of ACMT makes it optimal for neighborhood study research seeking to attribute environmental data to specific locations within the United States.

Analysis of tensile behavior of Nylon-CF fabricated using material extrusion

Nylon-CF is an important thermoplastic 3D printable material that can be used to develop high-quality functional parts with slight modifications in low-cost machines like material extrusion (MEX) technology. This paper investigates the tensile behavior of Nylon-CF samples produced by material extrusion. The influence of seven process parameters is studied on response characteristics. The Taguchi design is used to investigate the effect of process parameters on Young’s modulus and yield strength of specimens fabricated as per ASTM D-638. A two-level fractional factorial design supplements the L27 design results. The results show that the layer height, infill pattern, density, and raster angle significantly affect the tensile behavior. The apparent Young’s modulus is also significantly affected by the interaction between layer height, infill pattern, and infill density.

Analysis of the thermal effect of two external parallel printed circuit board conductors set on a metal base and operating in a space vacuum on each other

Background. The need to analyze the thermal effect of two external parallel conductors is due to an increase in the density of the conductive pattern. For printed circuit boards set on a metal base and operating in the vacuum of space, this need is aggravated by the weakness of the issue's development. 
 Aim. Analysis of the mutual influence of two external parallel printed circuit board conductors set on a metal base and operating in a space vacuum on each other to identify the dependence of their temperature on the distance between them and determine the distance at which this dependence practically disappears.
 Methods. To achieve the purpose, a finite element method calculation implemented in the ANSYS program, the Steady-State Thermal module, was used. Three multilayer printed circuit boards were calculated: 4-layer, 6-layer, 8-layer. The temperature coefficient of resistance was taken into account separately, by recalculation.
 Results. Graphs of the dependence of overheating (the difference between the temperature of the printed conductor and the metal base) on the distance between the printed conductors were constructed. The approximation of the obtained results is carried out. According to the approximated dependencies, the minimum values of the distances between printed conductors are found, at which the cross influence of printed conductors practically disappears. As the thickness of the printed circuit board increases, this distance increases.
 Conclusion. The results obtained can help to assess the influence of neighboring printed conductors in the design of the boards of the onboard equipment of spacecraft.

Stomatal effects and ABA metabolism mediate differential regulation of leaf and flower cooling in tomato cultivars exposed to heat and drought stress.

Co-occurring heat and drought stresses challenge crop performance. Stomata open to promote evaporative cooling during heat stress, but close to retain water during drought stress, which resulted in complex stomatal regulation under combined heat and drought. We aimed to investigate stomatal regulation in leaves and flowers of perennial, indeterminate cultivars of tomatoes subjected to individual and combined heat and drought stress followed by a recovery period, measuring morphological, physiological, and biochemical factors involved in stomatal regulation. Under stress, stomata of leaves were predominantly affected by drought, with lower stomatal density and stomatal closing, resulting in significantly decreased photosynthesis and higher leaf temperature. Conversely, stomata in sepals seemed affected mainly by heat during stress. The differential patterns in stomatal regulation in leaves and flowers persisted into the recovery phase as contrasting patterns in stomatal density. We show that flower transpiration is regulated by temperature, but leaf transpiration is regulated by soil water availability during stress. Organ-specific patterns of stomatal development and abscisic acid metabolism mediated this phenomenon. Our results throw light on the dual role of stomata in heat and drought tolerance of vegetative and generative organs, and demonstrate the importance of considering flower surfaces in the phenotyping of stomatal reactions to stress.

Seagrass diversity in Pulau Banyak, Aceh Singkil District, Indonesia

Abstract. Erniati, Andika Y, Imanullah, Imamshadiqin, Erlangga, Rahmad, Tauladan TA, Siregar FR, Fitri A, Ritonga GH. 2023. Seagrass diversity in Pulau Banyak, Aceh Singkil District, Indonesia. Biodiversitas 24: 6621-6628. Seagrass is a high-level plant where life activities are submerged in seawater. Currently, the seagrass ecosystem is threatened with destruction and disappearance. The extent of seagrass ecosystems globally was estimated to have declined by about 58%. The solution to this problem is to balance local communities' utilization of biological resources and biodiversity maintenance. The biodiversity aspect of seagrass is key to the sustainability of seagrass ecosystems. Banyak Island is one of the sub-districts in Aceh Singkil Regency, which consists of a cluster of small islands and has rich fisheries and marine potential, one of them is seagrass, where station 1 is Balong Island, Stasion 2 is Balong Island, Stasion 3 is Lamun Island and Stasion 4 is Rago-Rago Island. This study aimed to assess the diversity of seagrass beds, including seagrass species composition, density, percentage cover, and water quality that affect the existence of seagrass ecosystems. This study used a purposive sampling method with 3 transect lines spaced 50 m perpendicular from the shoreline to the sea. Each transect line has 5 plots with a distance of 10 meters measuring 50 x 50 cm2, and the water quality parameters were measured in situ. This research found 5 seagrass species, namely T. hemprichii, C. rotundata, E. acroides, S. isoetifolium, and H. ovalis. C. rotundata is the species with the highest density on Matahari Island, but seagrass diversity is low, and no species were dominant in the groups. The results of PCA analysis showed that the environmental factors that most influenced the pattern of seagrass distribution and density were nitrate, phosphate, and substrate. The conclusion revealed that seagrass diversity on Banyak Islands is relatively low.

Forest Canopy Density Monitoring by Using Geospatial Techniques: A Study of Gadchiroli District, Maharashtra, India

Forest cover is a crucial part of the environment. It makes an essential contribution to the socio-economic and environmental welfare of the Nation. However, these forests are seriously threatened by deforestation, increased mining activity, population growth, uncontrolled urbanisation, a developing tendency of industrialisation, agricultural land purpose, shifting cultivation, effects on soil, water, and biodiversity, unsustainable forms of human activities and others. As a result, developing strategies to promote sustainable forest management, prevent desertification, prevent soil erosion, and halt environmental degradation is essential. Remote Sensing has enabled humans to observe and obtain information about the earth's surface with spatiotemporal changes. The Indian state of Maharashtra's Gadchiroli district is used as a study region. This study investigates forest canopy density and the spatiotemporal changes in forests. The geographical pattern of forest canopy density is displayed by several indices using data from Landsat 5 and Landsat 8 at 30 m spatial resolution. Try to make the study more relevant in the contemporary world. The research area's forest cover has changed through time, as shown by several multi-temporal data sets (1989 and 2019). The results revealed that between 1989 and 2019, forest canopy cover and forest density decreased. It indicated that over 30 years, 1045.51 sq. km of land had degraded. The amount of highly dense forest has decreased significantly over the research period, whereas the non-forest area has been gradually growing for the past 30 years.

Effect of Process Parameters on the Hardness of 3D-printed Thermoplastic Polyurethane that Includes Foaming Agent

Recent progress in Material Extrusion-based Additive Manufacturing (MEX) has introduced active foaming agents in filaments composition, thus allowing for the tuning, by various process parameters, the hardness and the mechanical behavior of 3D-printed parts. In case of thermoplastic polyurethane (TPU) filaments, these advances significantly broaden the range of applications, particularly in the domains of comfort and orthotics (wrist-hand orthoses, insoles), offering the dual benefits of design flexibility inherent in MEX and the comfort of lightweight and customizable structures. However, the field is still in its early stages, with only a limited number of research efforts dedicated to characterizing these novel materials. In this context, this study is focused on determining the influence of printing temperature (190�C, 220�C, 240�C), infill density (25%, 35%, 45%) and infill pattern (honeycomb, gyroid) over the hardness of cylindrical specimens made of Colorfabb varioShore TPU. A comprehensive methodology of calibration is also presented as mandatory for obtaining good quality and accurate products by establishing correlations between flow rate and printing temperatures. The findings showed that the printing temperature is the most relevant factor impacting the hardness of varioShore TPU prints. At a printing temperature of 190�C, which corresponds to less foamed prints, the honeycomb infill yielded higher hardness compared to the gyroid infill, but the difference was not significant. Also, at 220�C and 240�C, the mean values of hardness remain relatively consistent, regardless of infill density and pattern.