Plan View Research Articles

Improved Visualization of Oral Microbial Consortia.

Bacteria on the tongue dorsum (TD) form consortia tens to hundreds of microns in diameter organized around a core of epithelial cells. Whole-mount preparations have been instrumental in revealing their organization and specific microbial associations. However, their thickness and intricate 3-dimensional complexity present challenges for a comprehensive spatial analysis. To overcome these challenges, we employed a complementary approach: embedding in hydrophilic plastic followed by sectioning and postsectioning labeling. Samples were labeled by hybridization with multiplexed fluorescent oligonucleotide probes and visualized by spectral imaging and linear unmixing. Application of this strategy to TD biofilms improved the visualization of bacteria that were difficult to resolve in whole-mount imaging. Actinomyces, previously detected as patches, became resolved at the single-cell level. The filamentous taxa Leptotrichia and Lachnospiraceae, located at the core of the consortium, were regularly visualized whereas previously they were rarely detected when using whole mounts. Streptococcus salivarius, heterogeneously detected in whole mounts, were regularly and homogenously observed. Two-dimensional images provide valuable information about the organization of bacterial biofilms. However, they offer only a single plane of view for objects that can extend to hundreds of microns in thickness, and information obtained from such images may not always reflect the complexity of a 3-dimensional object. We combined serial physical sectioning with optical sectioning to facilitate the 3-dimensional reconstruction of consortia, spanning over 100 µm in thickness. Our work showcases the use of hydrophilic plastic embedding and sectioning for examining the structure of TD biofilms through spectral imaging fluorescence in situ hybridization. The result was improved visualization of important members of the human oral microbiome. This technique serves as a complementary method to the previously employed whole-mount analysis, offering its own set of advantages and limitations. Addressing the spatial complexity of bacterial consortia demands a multifaceted approach for a comprehensive and effective analysis.

Place and Independence Are Formed by Moving Furniture

In contemporary architectural design, a noticeable trend emerges in the meticulous planning of common areas, with an emphasis on fostering the free movements of users within these areas. It is important to consider the architectural elements that influence user behavior in these environments. Previous studies have delved into the relationship between architecture and user activity, often through questionnaires and activity surveys conducted in arbitrary spaces. However, such data are discontinuous and only capture a portion of the space. Therefore, in this study, continuous and extensive recordings were performed in an arbitrary space using a video camera to capture the entirety of the area. Consequently, we were able to comprehend the relationship between architecture and people’s activities and observe the formation of user autonomy through their decisions to rearrange furniture. Furthermore, an “Open Pose” system was used to detect people and generate a user stay distribution chart. This was achieved by converting it into a plan view using perspective projection transformation, thereby obtaining objective data automatically. Consequently, we verified the feasibility of conducting visually comprehensible processing using tools like “Open Pose”, which was used in one segment of the experiment.

A complementary approach for neocortical cytoarchitecture inspection with cellular resolution imaging at whole brain scale

Cytoarchitecture, the organization of cells within organs and tissues, serves as a crucial anatomical foundation for the delineation of various regions. It enables the segmentation of the cortex into distinct areas with unique structural and functional characteristics. While traditional 2D atlases have focused on cytoarchitectonic mapping of cortical regions through individual sections, the intricate cortical gyri and sulci demands a 3D perspective for unambiguous interpretation. In this study, we employed fluorescent micro-optical sectioning tomography to acquire architectural datasets of the entire macaque brain at a resolution of 0.65 μm × 0.65 μm × 3 μm. With these volumetric data, the cortical laminar textures were remarkably presented in appropriate view planes. Additionally, we established a stereo coordinate system to represent the cytoarchitectonic information as surface-based tomograms. Utilizing these cytoarchitectonic features, we were able to three-dimensionally parcel the macaque cortex into multiple regions exhibiting contrasting architectural patterns. The whole-brain analysis was also conducted on mice that clearly revealed the presence of barrel cortex and reflected biological reasonability of this method. Leveraging these high-resolution continuous datasets, our method offers a robust tool for exploring the organizational logic and pathological mechanisms of the brain’s 3D anatomical structure.

Tomographic Planning of Dental Implants Using a Smartphone: Linear Measurements and Implant Selection-A Cross-Sectional Study.

This study assessed the accuracy of linear measurements and dental implant selection performed in a smartphone application compared to a computer software. Forty-four DICOM files from partially edentulous patients in the posterior region of the mandible were evaluated by three trained and calibrated examiners. Images were analyzed using three visualization methods: cross-sectional view (CScr) and coronal (CSco) plane using the CS 3D Imaging software, and coronal (DRco) plane using the DroidRender smartphone application. For the purpose of standardization, measurements of bone width and height were taken in the edentulous posterior region of the mandible, 10 mm posterior to the mental foramen. Dental implant selection was made according to Straumann® Standard implant catalog 2022/2023. Linear measurements were compared using the ANOVA test for repeated measurements and implant selection was compared using the Friedman test. Statistical analysis was performed using the SPSS software, considering a significance level of 5%. Linear measurements showed a statistically significant difference for bone width (p = 0.030), but not for height (p = 0.685). The choice of implant was not influenced by the visualization method (p = 0.614). It is possible to suggest the use of smartphone applications as an additional diagnostic tool for DICOM evaluation and dental implant planning in the posterior region of the mandible. Smartphone applications allow an assessment not limited to 2D images or to static environments. Therefore, information exchange and diagnostic opinion in emergency situations may be facilitated.

Methodology and accuracy evaluation of global calibration for Multi-Line-Scan camera system in rail transit tunnel

Vision-based inspection techniques have improved the efficiency of tunnel inspection. This paper presents a rail transit tunnel multi-line-scan camera inspection system that requires global calibration to obtain the spatial relationships among all line-scan cameras, which is crucial for tunnel panoramic image mosaicking and 3D reconstruction. A flexible global calibration method is proposed, a hybrid calibration target is designed that includes triangular patterns based on the cross-ratio(CR) invariance principle and target holes. Establishing a virtual target field and using coplanarity as a constraint to refit a new view plane and globally optimizing the initial coordinates, which would ensure the calibration accuracy. In addition, an accuracy evaluation method based on CR triangles is proposed to assess the calibration results. The experimental results demonstrate the feasibility and reliability of the proposed calibration method and that the developed accuracy evaluation method is feasible compared with the traditional reprojection error method.

Stepping Up Recovery: Integrating Patient-reported Outcome Measures and Wearable Technology for Rehabilitation Following Knee Arthroplasty.

Improvement after knee arthroplasty (KA) is often measured using patient-reported outcome measures (PROMs). However, PROMs are limited due to their subjectivity. Therefore, wearable technology is becoming commonly utilized to objectively assess physical activity and function. We assessed the correlation between PROMs and step/stair flight counts in total (TKA) and partial knee arthroplasty (PKA) patients.Analysis of a multicenter, prospective, longitudinal cohort study investigating the collection of average daily step and stair flight counts, was performed. Subjects (N = 1,844 TKA patients and N = 489 PKA patients) completed the Knee Injury and Osteoarthritis Outcome Score for Joint Replacement (KOOS JR) and provided numerical rating scale pain scores pre- and postoperatively. Only patients who reported living in a multilevel home environment (N = 896 TKA patients and N = 258 PKA patients) were included in analysis of stair flight counts. Pearson correlation coefficients were calculated to determine correlations between variables.Among TKA patients, pain scores demonstrated a negative correlation to mean step counts at preoperative (r = -0.14, p < 0.0001) and 1-month follow-up (r = -0.14, p < 0.0001). Similar negative correlations were true for pain and stair flight counts at preoperative (r = -0.16, p < 0.0001) and 1-month follow-up (r = -0.11, p = 0.006). KOOS JR scores demonstrated weak positive correlations with mean step counts at preoperative (r = 0.19, p < 0.0001) and 1-month postoperative (r = 0.17, p < 0.0001). Similar positive correlations were true for KOOS JR scores and stair flight counts preoperatively (r = 0.13, p = 0.0002) and at 1-month postoperatively (r = 0.10, p = 0.0048). For PKA patients, correlations between pain and KOOS JR with step/stair counts demonstrated similar directionality.Given the correlation between wearable-generated data and PROMs, wearable technology may be beneficial in evaluating patient outcomes following KA. By combining subjective feedback with the objective data, health care providers can gain a holistic view of patients' progress and tailor treatment plans accordingly.

Brain MRI sequence and view plane identification using deep learning.

Brain magnetic resonance imaging (MRI) scans are available in a wide variety of sequences, view planes, and magnet strengths. A necessary preprocessing step for any automated diagnosis is to identify the MRI sequence, view plane, and magnet strength of the acquired image. Automatic identification of the MRI sequence can be useful in labeling massive online datasets used by data scientists in the design and development of computer aided diagnosis (CAD) tools. This paper presents a deep learning (DL) approach for brain MRI sequence and view plane identification using scans of different data types as input. A 12-class classification system is presented for commonly used MRI scans, including T1, T2-weighted, proton density (PD), fluid attenuated inversion recovery (FLAIR) sequences in axial, coronal and sagittal view planes. Multiple online publicly available datasets have been used to train the system, with multiple infrastructures. MobileNet-v2 offers an adequate performance accuracy of 99.76% with unprocessed MRI scans and a comparable accuracy with skull-stripped scans and has been deployed in a tool for public use. The tool has been tested on unseen data from online and hospital sources with a satisfactory performance accuracy of 99.84 and 86.49%, respectively.

Autonomous fetal morphology scan: deep learning + clustering merger – the second pair of eyes behind the doctor

The main cause of fetal death, of infant morbidity or mortality during childhood years is attributed to congenital anomalies. They can be detected through a fetal morphology scan. An experienced sonographer (with more than 2000 performed scans) has the detection rate of congenital anomalies around 52%. The rates go down in the case of a junior sonographer, that has the detection rate of 32.5%. One viable solution to improve these performances is to use Artificial Intelligence. The first step in a fetal morphology scan is represented by the differentiation process between the view planes of the fetus, followed by a segmentation of the internal organs in each view plane. This study presents an Artificial Intelligence empowered decision support system that can label anatomical organs using a merger between deep learning and clustering techniques, followed by an organ segmentation with YOLO8. Our framework was tested on a fetal morphology image dataset that regards the fetal abdomen. The experimental results show that the system can correctly label the view plane and the corresponding organs on real-time ultrasound movies.Trial registrationThe study is registered under the name “Pattern recognition and Anomaly Detection in fetal morphology using Deep Learning and Statistical Learning (PARADISE)”, project number 101PCE/2022, project code PN-III-P4-PCE-2021–0057. Trial registration: ClinicalTrials.gov, unique identifying number NCT05738954, date of registration 02.11.2023.

A Review on Recent Deep Learning-Based Semantic Segmentation for Urban Greenness Measurement.

Accurate urban green space (UGS) measurement has become crucial for landscape analysis. This paper reviews the recent technological breakthroughs in deep learning (DL)-based semantic segmentation, emphasizing efficient landscape analysis, and integrating greenness measurements. It explores quantitative greenness measures applied through semantic segmentation, categorized into the plan view- and the perspective view-based methods, like the Land Class Classification (LCC) with green objects and the Green View Index (GVI) based on street photographs. This review navigates from traditional to modern DL-based semantic segmentation models, illuminating the evolution of the urban greenness measures and segmentation tasks for advanced landscape analysis. It also presents the typical performance metrics and explores public datasets for constructing these measures. The results show that accurate (semantic) segmentation is inevitable not only for fine-grained greenness measures but also for the qualitative evaluation of landscape analyses for planning amidst the incomplete explainability of the DL model. Also, the unsupervised domain adaptation (UDA) in aerial images is addressed to overcome the scale changes and lack of labeled data for fine-grained greenness measures. This review contributes to helping researchers understand the recent breakthroughs in DL-based segmentation technology for challenging topics in UGS research.

Quantitative Assessment of Acetabular Defects in Revision Hip Arthroplasty Based on 3D Modeling: The Area Increase Ratio (AIR) Method.

The most common classifications for acetabular bone defects are based on radiographic two-dimensional imaging, with low reliability and reproducibility. With the rise of modern processing techniques based on 3D modelling, methodologies for the volumetric quantification of acetabular bone loss are available. Our study aims to describe a new methodology for the quantitative assessment of acetabular defects based on 3D modelling, focused on surface analysis of the integrity of the main anatomical structures of the acetabulum represented by four corresponding sectors (posterior, superior, anterior, and medial). The defect entity is measured as the area increase ratio (AIR) detected in all the sectors analyzed on three planes of view (frontal, sagittal, and axial) compared to healthy hemipelvises. The analysis was performed on 3D models from the CT-scan of six exemplary specimens with a unilateral pathological hemipelvis. The AIR between the native and the pathological hemipelvis was calculated for each sector, for a total of 48 analyses (range, +0.93-+171.35%). An AIR of >50% were found in 22/48 (45.8%) sectors and affected mostly the posterior, medial, and superior sectors (20/22, 90.9%). Qualitative analysis showed consistency between the data and the morphological features of the defects. Further studies with larger samples are needed to validate the methodology and potentially develop a new classification scheme.

Planar defects in α-Ga2O3 thin films produced by HVPE

The defect structure of α-phase gallium oxide thin films was investigated using transmission electron microscopy (TEM). Epitaxial Ga2O3 films were grown via halide vapor-phase epitaxy on c-plane sapphire substrates. TEM analysis revealed a high density of extended planar defects within the films, primarily located along prismatic planes of {112¯0} type. Displacement vectors were determined using the invisibility criterion for stacking faults. The study encompassed both planar and cross-sectional views of the films. It is hypothesized that these defects form due to the motion of edge partial dislocations with the 13⟨11¯00⟩ Burgers vector. Various mechanisms of their formation have been explored.

COASTAL TERRITORY AND COASTAL ZONE: DEFINITION, CHARACTERISTICS, URBAN DEVELOPMENT

The purpose of this publication is to define the terms «coastal territory» and «coastal zone» from the point of view of their urban planning use, because the current legislative documents, normative sources, scientific articles, which raise the problems of development and preservation of coastal territories, do not give their clear interpretation. As a natural phenomenon, the river and its coastal territory are an interdependent river ecosystem, which is a complex dynamic complex with paradynamic connections, where the exchange of substances, energy, and information takes place. The general boundary and configuration of the coastal territory is determined according to the maximum value of the influence of the river, taking into account its engineering and geological, microclimatic and spatial planning criteria. From the point of view of urban planning, the coastal area is a natural reserve of the urban fabric, which has a favorable potential for the formation of coastal zones in order to create a comfortable and safe urban environment. The coastal zone is a part of the coastal territory and water area with regulated and unregulated economic activity, the functional purpose of which is the organization of a favorable environment for the life of the population in the zone of influence of the reservoir. Almost all coastal areas are favorable for urban development - the difference exists in the degree of complexity and cost of urban development of coastal areas, their transformation into coastal zones. The urban planning assessment of the coastal zone for the organization of a favorable and comfortable environment for people's stay here is a complex of engineering-geological, architectural-compositional, sanitary-ecological and economic assessments. The choice of techniques for the development of the coastal zone should be based on the principles of the formation of an expressive architectural and planning development, improvement of the urban microclimate, the formation of convenient public space and landscaped and recreational areas. It is unacceptable to build up the coastal zone with capital structures of the industrial area, with the exception of water management facilities, and the laying of transit main streets here. The functional purpose of coastal zones may change over time. An assessment of the natural factors of coastal areas in relation to the degree of favorability of urban development of coastal areas and an assessment of coastal landscapes in relation to their functional purpose is given. It is noted that the main defining features of the coastal area, among many factors, are the geomorphological structure and microclimate. The transformation of Kyiv's Dnieper embankment has been traced: starting from the 5th century, after passing through 4 main periods of formation due to the arrangement and beautification of the coastal zone, the Podil embankment today has lost its function as a public space. The transformation of the coastal zone of Kyiv into a center of limited elite housing and a transport corridor is an impoverishment of the life of the city, the loss of an important urban area. The development of coastal areas, as a natural potential in cities, should be carried out within the limits of current legislation and taking into account environmental norms to create a favorable urban environment.

Targeted Single Particle Tracking with Upconverting Nanoparticles.

Single particle tracking (SPT) is a powerful technique for real-time microscopic visualization of the movement of individual biomolecules within or on the surface of living cells. However, SPT often suffers from the suboptimal performance of the photon-emitting labels used to tag the biomolecules of interest. For example, fluorescent dyes have poor photostability, while quantum dots suffer from blinking that hampers track acquisition and interpretation. Upconverting nanoparticles (UCNPs) have recently emerged as a promising anti-Stokes luminescent label for SPT. In this work, we demonstrated targeted SPT using UCNPs. For this, we synthesized 30 nm diameter doped UCNPs and coated them with amphiphilic polymers decorated with polyethylene glycol chains to make them water-dispersible and minimize their nonspecific interactions with cells. Coated UCNPs highly homogeneous in brightness (as confirmed by a single particle investigation) were functionalized by immunoglobulin E (IgE) using a biotin-streptavidin strategy. Using these IgE-UCNP SPT labels, we tracked high-affinity IgE receptors (FcεRI) on the membrane of living RBL-2H3 mast cells at 37 °C in the presence and absence of antigen and obtained good agreement with the literature. Moreover, we used the FcεRI-IgE receptor-antibody system to directly compare the performance of UCNP-based SPT labels to organic dyes (AlexaFluor647) and quantum dots (QD655). Due to their photostability as well as their backgroundless and continuous luminescence, SPT trajectories obtained with UCNP labels are no longer limited by the photophysics of the label but only by the dynamics of the system and, in particular, the movement of the label out of the field of view and/or focal plane.

3D numerical analysis of corner mechanically stabilized earth walls

ABSTRACT MSEW (Mechanically Stabilized Earth walls) has become a widely adopted and economical earth-retaining system. However, the current design standards primarily rely on a two-dimensional plane-strain approach, overlooking the critical 3D behavior and mechanisms associated with wall curves and corners. To address this gap, this research aims to enhance our comprehension of MSEW corner performance for right-angle (Sharp turns) and curved (Round off) walls by using 3D finite element modeling. A comparative study was conducted for MSEW in case of sharp turns and round off walls, in addition to examining the influence of the curve angle in the different cases with angles (internal curve angle) of 50 to 120 degrees. Based on results of comparing the right-angle wall and the curved angle (90º) wall, it is evident that the horizontal displacement of the right-angle wall is greater. For curved wall, it was observed that the value of horizontal displacement is minimal at the beginning of the curved wall and gradually increases until it reaches the maximum displacement at the mid of the curve in plan view. The geogrid strain for the right-angle wall is approximately 1.70 times of the curved wall (internal curved angle = 90°). Based on the results of difference angle of curved wall, it was concluded that the horizontal displacement values of the wall between internal curved angles 90 and 120 are quite close, but they differ significantly from 50 to 90. It was noted that, the maximum displacements for angles from 60 and 110 was occurred at approximately 0.38 H of the wall’s height from the base but, it equal to 0.50 H for angle 110 and 120. Finally, an equation of second degree can be deduced to illustrate the relationship between the maximum facing wall displacement and the wall height with the curved wall angle.

Optimization of collimator angle combined island blocking with parked gap achieves superior normal tissue sparing in SBRT planning of multiple liver lesions.

To propose an efficient collimator angle optimization method by combining island blocking (IB) and parked gap (PG) problem to reduce the radiotherapy dose for normal tissue. The reduction will be done with single-isocenter multi-lesion volumetric modulated arc therapy (VMAT) for the stereotactic body radiation therapy (SBRT) of liver cancer. A novel collimator angle optimization algorithm was developed based on the two-dimensional projection of targets on a beam's eye view (BEV) plane as a function of gantry and collimator angle. This optimization algorithm minimized the sum of the combined IB and PG (IB & PG) areas from all gantry angles for each arc. For comparison, two SBRT plans were respectively generated for each of the 20 retrospective liver cancer cases with multiple lesions. One plan was optimized using the IB & PG algorithm, and the other plan was optimized with a previously reported optimization algorithm that only considered the IB area. Plans were then evaluated and compared using typical dosimetric metrics. With the comparable target coverage, IB & PG plans had significantly lower D500cc, D700cc, mean dose (Dmean), and V15 of normal liver tissues when compared to IB plans. The median percent reductions were 3.32% to 5.36%. The D1cc, D5cc, and Dmean for duodenum and small intestine in IB & PG plans were significantly reduced in a range from 7.60% up to 16.03%. Similarly, the median integral dose was reduced by 3.73%. Furthermore, the percentage of normal liver Dmean sparing when IB & PG plans compared to IB plans, was found to be positively correlated (ρ=0.669, P=0.001) with the inter-target distance. The proposed IB & PG algorithm has been demonstrated to outperform the IB algorithm in almost all normal tissue sparing, and the magnitude of liver sparing was positively correlated with inter-target distance.

Seismic pounding of adjacent buildings considering torsional effects

This study aims to evaluate pounding effects in fixed-base models by considering torsional irregularity. For this purpose, 8 different adjacent building combinations were created by using 3-dimensional 5- and 9-story building models. In adjacent building models, the most critical situation was determined by evaluating the gap distance, different sequences of the same building models and regular or irregular plan view and if the structures are irregular, their eccentricity cases relative to each other. Nonlinear behavior of structural elements was taken into account for examine the change in the seismic behavior of structural elements due to pounding and torsion effects. The nonlinear time history analysis of the adjacent models was performed for 11 pairs of spectrum compatible ground motion recordings in the SAP2000 program. The results of 176 different analyzes show that the displacement demand, interstory drift ratio, damage ratio and torsional irregularity coefficient values tend to increase in general with the combined effects of pounding and torsion. The absolute maximum and most critical values of the relevant parameters were calculated in irregular structures with pounding where the eccentricity of buildings is in the same direction and same side. In addition, the large standard deviation of the result values according to the ground motion records indicates that care should be taken in choosing the number of ground motion records.

Analysis of neural networks for routine classification of sixteen ultrasound upper abdominal cross sections.

Abdominal ultrasound screening requires the capture of multiple standardized plane views as per clinical guidelines. Currently, the extent of adherence to such guidelines is dependent entirely on the skills of the sonographer. The use of neural network classification has the potential to better standardize captured plane views and streamline plane capture reducing the time burden on operators by combatting operator variability. A dataset consisting of 16 routine upper abdominal ultrasound scans from 64 patients was used to test the classification accuracy of 9 neural networks. These networks were tested on both a small, idealised subset of 800 samples as well as full video sweeps of the region of interest using stratified sampling and transfer learning. The highest validation accuracy attained by both GoogLeNet and InceptionV3 is 83.9% using transfer learning and the large sample set of 26,294 images. A top-2 accuracy of 95.1% was achieved using InceptionV3. Alexnet attained the highest accuracy of 79.5% (top-2 of 91.5%) for the smaller sample set of 800 images. The neural networks evaluated during this study were also successfully able to identify problematic individual cross sections such as between kidneys, with right and left kidney being accurately identified 78.6% and 89.7%, respectively. Dataset size proved a more important factor in determining accuracy than network selection with more complex neural networks providing higher accuracy as dataset size increases and simpler linear neural networks providing better results where the dataset is small.

Digital Model of Plan View Pattern Control for Plate Mills Based on Machine Vision and the DBO-RBF Algorithm

Plan view pattern control (PVPC) is a highly effective means to improve the rectangularization of products and increase the yield of plate mills. By optimizing the parameters of PVPC, the effect of PVPC can be further improved. In this paper, a digital model for predicting and controlling crop patterns of plates is proposed based on the radial basis function (RBF) neural network optimized by the dung beetle optimizer (DBO) algorithm. Machine vision technology is used to obtain a digital description of the crop pattern of the rolled plates. An automatic threshold adjustment algorithm is proposed for the image processing of plate pattern photos during the rolling process. The error between the pattern data calculated through machine vision technology and the measured pattern data does not exceed 3 mm. The spread parameters of the RBF are optimized using DBO, and the digital model structure is established. The goodness of fit (R2) and the mean absolute error (MAE) are used as evaluation indicators. The results show that the digital model established based on DBO-RBF has good predictive and control performance, realizing intelligent prediction of the crop pattern of plates and the parameter optimization of PVPC. In practical applications, the crop cutting loss area of irregular deformation at the end of the plate can be reduced by 31%.

Balancing career goals and parenthood desires: results from a survey of undergraduate pre-health students at a hispanic-serving institution in Texas

Objective To examine family planning and fertility experiences and views, as well as desired parenthood timing and career plans, of diverse undergraduate pre-health students. Participants 266 pre-health undergraduate students attending a Hispanic-Serving Institution in South Texas. Methods We conducted a cross-sectional, online survey with a purposive sample of undergraduate students and analyzed data descriptively. Results Most students desired children in the future but were concerned about planning the timing of parenthood against their career training. The results highlight the need to improve both family planning and fertility knowledge, based on a high unmet need for contraceptives, low perceived knowledge about fertility/infertility treatment, and a desire to learn more about planning the timing of their career training alongside parenthood. Conclusions This study highlights potential gaps in reproductive health information and services among diverse, health-focused students needed to inform choices about the timing of their families and career training.

Applying GIS and Markov chain in establishing the land use change map and forecasting land use changes in Thach That district, Hanoi city

The study applied GIS and Markov chains to assess land use changes in the period 2015-2020 and forecast land use change trends in Thach That district, Hanoi city until 2030. Using two maps of the land use status quo map in 2015 and 2020 of Thach That district and 2 period land statistics, the research result has established a land use change map in Thach That district for the period 2015 - 2020 for 16 types of land with a land change rate of 9.63% of the total natural area. During this period, the land types that tend to increase are Perennial crop land; Special-use Forest land; Aquaculture land; Other agricultural land; Residential land; Special-use land; Land for religious establishments; Land for beliefs establishments and Specialized water surfaces with an increased rate of 0.05-2.28%. In contrast, land types with a decreasing trend are Annual crop land; Production Forest land; Protective Forest land; Cemetery land, cemetery, funeral home, crematorium; Land of rivers, streams, canals and streams; Other non-agricultural land, and Unused land which decreased at a rate of 0.02-2.34%. It is forecast that by 2030, agricultural land will have 10,271.28 hectares (accounting for 54.90%), non-agricultural land will have 8,432.22 hectares (accounting for 45.07%), unused land will have 4.76 hectares (accounting for 0.03%). Performing a T-Test (Paired two sample for Means) between the area from the forecast and the planned area until 2030 shows that ρ = 0.979 &gt; 0.05. Thus, it proves that the results of forecasting land use changes to 2030 using the Markov chain compared to the land use planning plan of Thach That district do not have too big a difference. The results of assessing land use changes and making forecasts of land change trends in the Thach That district contribute to helping policymakers have an objective view of land-use planning and economic development sustainably.