Frequency Analysis Research Articles

Investigating the antioxidant potential and mechanism of a hydrazide bioactive component of garlic: insights from density functional theory calculations, drug-likeness and molecular docking studies.

Glutathione remains one of the most efficient antioxidant compounds in living systems, and the biological abilities of hydrazides have been well documented in literature. This study highlights the phytochemical constituents of garlic and the separation of the bioactive benzoic acid, 4-chloro- 1-(4-methoxyphenyl) hydrazide (BA4C) using gas chromatography-mass spectroscopy (GC-MS) technique. Preliminary phytochemical screening reveals the presence of alkaloids, saponins, flavonoids, tannins, terpenoids, steroids and phenols. Computationally, compound BA4C was optimized using the B3LYP/aug-cc-PVDZ DFT method. Spectroscopic studies of the compound involved analysis of the vibrational FT-IR frequencies and the modes of vibrations. Frontier molecular orbitals analysis records an energy gap of 4.3391eV; NBO studies reveal that the compound has strong perturbation energies of 246kcal/mol and 269kcal/mol among its intramolecular interactions such as *C12 - C13 to *C14 - C15 and *C11 - C16 to *C14 - C15, respectively. According to the visualization of non-covalent interactions, steric repulsions were observed at the core of the phenyl and benzene rings. However, other regions of the compound depict a significant balance of forces between steric repulsions and van der Waals forces. To significantly deduce the reducing power of compound BA4C, electrons were found to be highly localized at the methoxy and hydrazide moieties significantly implying their propensity to donate electrons to oxidized systems. Furthermore, ADMET analysis reveals that the compound has two hydrogen donors. Most significantly, the compound binds to NADPH dehydrogenase (5V4P) and glutathione reductase (1XAN) with binding energies of - 6.0kcal/mol and - 8.0kcal/mol showing considerable favourable binding feasibility as well as forming plural hydrogen bonds with the amino acid residues. Notably, BA4C was bonded at the active site of 1XAN, which implies the ability of the compound for the reduction of oxidized glutathione.

Factors affecting the quality of mathematics teaching and learning of high school students in the 4th grade in Savannakhet province

The purpose of this research is to examine the factors that affect the quality of learning and teaching mathematics of 4th grade students in Savannakhet province. The sample group included the 4th grade students and natural science teachers with a total number of 434. The data was analyzed by SPSS program and Microsoft Excel to calculate frequency, percentage, standard deviation, CV and content analysis. The results of the research are as follows: The results of the analysis of the factors that affect the quality of teaching mathematics the most according to the students' ideas are curriculum by average value of 3.58, which means that the curriculum is suitable with the current learning standards at a low level, followed by the factors of teachers and family with an average 3.57 and 3.52 respectively. The results of the analysis of the factors that affect the quality of teaching mathematics according to the teachers' ideas in general are at good levels and when considering each aspect, it is found that the factor that affect the most is the teacher with an average of 3.82, followed by the curriculum and teaching aids with an average of 3.81 and 3.80 respectively. The results of the analysis of teachers' and students' opinions toward the improvement of the quality of mathematics teaching are: paying more attention to study of students covering 28.65%; teaching methods consistently with the current situations, covering 15.63%, giving opportunities for students to participate in learning more covering 15.71%, and organizing a program to promote those who are good at learning and help weak students covering 12 .50% respectively.

Maximizing Profitability and Occupancy: An Optimal Pricing Strategy for Airbnb Hosts Using Regression Techniques and Natural Language Processing

In the competitive landscape of Airbnb hosting, optimizing pricing strategies for properties is a complex challenge that requires revenue maximization with high occupancy rates. This research aimed to introduce a solution that leverages big data and machine learning techniques to help hosts improve their property’s market performance. Our primary goal was to introduce a solution that can augment property owners’ understanding of their property’s market value within their urban context, thereby optimizing both the utilization and profitability of their listings. We employed a multi-faceted approach with diverse models, including support vector regression, XGBoost, and neural networks, to analyze the influence of factors such as location, host attributes, and guest reviews on a listing’s financial performance. To further refine our predictive models, we integrated natural language processing techniques for in-depth listing review analysis, focusing on term frequency-inverse document frequency (TF-IDF), bag-of-words, and aspect-based sentiment analysis. Integrating such techniques allowed for in-depth listing review analysis, providing nuanced insights into guest preferences and satisfaction. Our findings demonstrated that AirBnB hosts can effectively utilize both state-of-the-art and traditional machine learning algorithms to better understand customer needs and preferences, more accurately assess their listings’ market value, and focus on the importance of dynamic pricing strategies. By adopting this data-driven approach, hosts can achieve a balance between maintaining competitive pricing and ensuring high occupancy rates. This method not only enhances revenue potential but also contributes to improved guest satisfaction and the growing field of data-driven decisions in the sharing economy, specially tailored to the challenges of short-term rentals.

Signal Separation Operator Based on Wavelet Transform for Non-Stationary Signal Decomposition

This paper develops a new frame for non-stationary signal separation, which is a combination of wavelet transform, clustering strategy and local maximum approximation. We provide a rigorous mathematical theoretical analysis and prove that the proposed algorithm can estimate instantaneous frequencies and sub-signal modes from a blind source signal. The error bounds for instantaneous frequency estimation and sub-signal recovery are provided. Numerical experiments on synthetic and real data demonstrate the effectiveness and efficiency of the proposed algorithm. Our method based on wavelet transform can be extended to other time–frequency transforms, which provides a new perspective of time–frequency analysis tools in solving the non-stationary signal separation problem.

Associations between end stage renal disease and HLA polymorphisms in the Guangxi Zhuang population

To investigate the genetic relationship between end stage renal disease (ESRD) and human leukocyte antigen (HLA) alleles in the Guangxi Zhuang population. We performed polymerase chain reaction reversed sequence-specific oligonucleotide (PCR-rSSO) in 325 patients with ESRD and genotyped the HLA-A, HLA-B, HLA-C, HLA-DRB1, and HLA-DQB1 loci. The direct counting method was used to determine the frequencies of HLA alleles, and Arlequin software (version 3.5.2.2) was used for haplotypic frequency analyses to compare the included ESRD patients with 350 healthy donors from the Guangxi Zhuang population. In our study, 120 HLA alleles, 284 HLA-A-B-DRB1 haplotypes, and 332 HLA-A-C-B-DRB1-DQB1 haplotypes were detected. We found that only A*11:01-B*15:02-DRB1*12:02 had a positive association with ESRD (P = 0.001, Pc = 0.020, OR = 3.106, 95% CI = 1.497–6.446) after Bonferroni correction; thus, individuals with this haplotype may be susceptible to ESRD. A*11:01-B*15:02-DRB1*12:02 is a potentially valuable haplotype for evaluating the risk of ESRD in the Guangxi Zhuang population.

Scaling up! Staff e-learning for a national take-home naloxone program

BackgroundA staff e-learning course was developed to prepare for scaling up a national take-home naloxone (THN) program in Norway. The aims of the study were to (a) describe participant characteristics for those that completed a THN e-learning course, (b) compare opioid overdose knowledge scores before and after e-learning course completion, and (c) to explore subsequent THN distribution by those trained.MethodsThis was a quasi-experimental pre-test, post-test longitudinal cohort study of individuals completing a THN e-learning course from April 2021 to May 2022. Frequency analyses were performed for participant characteristics and subsequent naloxone distributions at 1-week and 1-month follow-up. The opioid overdose knowledge scale (OOKS) was used to measure pre-test-post-test knowledge among participants. Wilcoxon signed-rank test was performed for comparison between pre-test and post-test. Effect size was calculated using Cohen criteria.ResultsIn total, 371 individuals were included in this study. Most were either nurses or social workers (n = 277, 75%). Participant knowledge increased by medium or large effect for all items measured. At 1-month follow-up, 15% reported naloxone distribution. During the study period, 94 naloxone kits were distributed. Major reasons for not distributing were “clients not interested”, “workplace not distributing” and “workplace in process of distributing”.ConclusionsOur findings suggest that an e-learning course is equally effective in terms of knowledge transfer as an in-person classroom setting, and may provide engagement in terms of naloxone distribution. However, our findings also emphasize the importance of clear implementation routines, including support from central coordinators to optimize the implementation process.

Hydrological and hydrodynamic modelling for flood management: A case study of the Yamuna River Basin in Delhi

Study regionYamuna River (Delhi), India. Study focusThe anthropogenic activities within the vicinity of the floodplain reduce the river's margin and subsequently alter the magnitude of the river's flow. The encroachment of riverbeds leads to waterlogging and flooding in urban areas, thereby causing damage to property, human life, etc. It necessitates a comprehensive study of the floodplain and changes in its proximity such as encroachment of floodplains to carry out any further activities with certainty. This study employs a two-dimensional model to simulate the Yamuna River's (YR) hydrodynamic characteristics, focusing on India's Delhi region. New hydrological insightsSimulated flood flows are employed to evaluate floods of once in 10, 20, 25, and 30-year return periods using the flood frequency analysis for 1951–2013. The model validation results indicated that the model could mimic the flood depth in YR. Simulation results revealed that the floodplain's encroachment had increased the severity of the floods. The increase in the extremeness of flooding events, i.e., from once in a 10-year return period to a 30-year return period event, is expected to increase the areas at risk of floods by 12 %. The model also offers a potential platform for evaluating other alternatives, such as further encroachment, for a business-as-usual scenario or for restoring the Yamuna floodplains. With such a comprehensive perspective, floodplains' role enhances river basin resilience to climate and anthropogenic changes and increases flood safety.

The Difference between Traditional Magnetic Stimulation and Microcoil Stimulation: Threshold and the Electric Field Gradient

This paper considers the threshold value of the activating function needed for stimulation in traditional magnetic stimulation and microcoil stimulation. Two analyses of excitation have been studied: spatial frequency analysis and active membrane analysis using the Hodgkin−Huxley model. The activating function depends on the spatial distribution of the electric field gradient in the active membrane analysis and the spatial frequency in the spatial frequency analysis. Both analyses show that a microcoil (tens of microns in size) has a higher threshold than a traditional coil (tens of millimeters in size) when the spatial frequency is large or the spatial extent of the activating function is small. Consequently, the stimulation threshold for a microcoil is much higher than that for a conventional coil.

FOPDT model and CHR method based control of flywheel energy storage integrated microgrid

The main causes of frequency instability or oscillations in islanded microgrids are unstable load and varying power output from distributed generating units (DGUs). An important challenge for islanded microgrid systems powered by renewable energy is maintaining frequency stability. To address this issue, a proportional integral derivative (PID) controller is designed in this article. Firstly, islanded microgrid model is constructed by incorporating various DGUs and flywheel energy storage system (FESS). Further, considering first order transfer function of FESS and DGUs, a linearized transfer function is obtained. This transfer function is further approximated into first order plus time delay (FOPTD) form to design PID control strategy, which is efficient and easy to analyze. PID parameters are evaluated using the Chien-Hrones-Reswick (CHR) method for set point tracking and load disturbance rejection for 0% and 20% overshoot. The CHR method for load disturbance rejection for 20% overshoot emerges as the preferred choice over other discussed tuning methods. The effectiveness of the discussed method is demonstrated through frequency analysis and transient responses and also validated through real time simulations. Moreover, tabulated data presenting tuning parameters, time domain specifications and comparative frequency plots, support the validity of the proposed tuning method for PID control design of the presented islanded model.

Microfluctuations in Capillary Lumens Independent of Pericyte Lining Density in the Anesthetized Mouse Cortex.

This study aimed to examine the spatiotemporal coherence of capillary lumen fluctuations in relation to spatial variations in the pericyte lining in the cortex of anesthetized mice. Two-photon microscopic angiography data (previously published) were reanalyzed, and spatial variations in capillary diameter fluctuations at rest and in capillary lining with vascular mural cells were measured along capillary centerlines. Relatively large diameters of the capillaries (5.5 μm) coincided with a dense pericyte lining, while small capillaries (4.3 μm) had a sparse pericyte lining. Temporal variations had a frequency of about 0.1 Hz with an amplitude of 0.5 μm, which were negatively correlated with pericyte lining density. Spatial frequency analysis further revealed a common pattern of spatial variations in capillary diameter and pericyte lining, but temporal variations differed. The temporal variations in capillary lumens were locally distinct from those in neighboring locations, suggesting intrinsic fluctuations independent of the pericyte lining. Capillary lumens in the brain exhibit slow microfluctuations that are independent of pericyte lining. These microfluctuations could affect the distribution of flowing blood cells and may be important for homogenizing their distribution in capillary networks.

대구 경북지역 병원종사자의 직무스트레스가 직무만족도에 미치는 영향에서 자아탄력성의 매개효과

Objectives The purpose of this study is to verify the mediating effect of ego resilience in the relationship between job stress and job satisfaction of hospital workers in the Daegu and Gyeongbuk regions. Methods An online survey was conducted targeting hospital workers working in the Daegu and Gyeongbuk regions from October 8, 2023 to October 15, 2023, and 86 copies were used in the final statistical analysis. The collected data were subjected to reliability analysis, frequency analysis, descriptive statistical analysis, multivariate normal distribution verification, correlation analysis, and regression analysis using SPSS V27.0, and the Sobel Test was performed to verify statistical significance. Results First, job stress of hospital workers in the Daegu and Gyeongbuk regions was found to have a significant negative effect on job satisfaction and ego resilience, and ego resilience was found to have a positive effect on job satisfaction. Second, ego resilience was found to mediate the relationship between job stress and job satisfaction among hospital workers in the Daegu and Gyeongbuk regions. Conclusions Through the results of this study, the relationship between job stress, job satisfaction, and ego resilience of hospital workers in the Daegu and Gyeongbuk regions was verified, and the relationship between major variables was confirmed theoretically and empirically, and key variables that affect hospital workers' job satisfaction were confirmed. It is meaningful in that it can provide basic data for early screening of hospital workers with low levels of job satisfaction and effective intervention by uncovering these factors. It is also significant in that it provided implications for the development of counseling and education programs related to job stress and ego resilience that can increase the job satisfaction of hospital workers in the Daegu and Gyeongbuk regions.

키워드 네트워크 분석을 활용한 인공지능 융합 영재교육 연구 동향 분석

Objectives The purpose of this study is to analyze trends in artificial intelligence convergence gifted education in elementary and middle schools that have been studied with a focus on artificial intelligence, and to derive important issues, topics, trends, and trends in related research. Methods Research trends were analyzed for 75 literatures related to artificial intelligence and artificial intelligence convergence gifted education research and education programs. Analysis data was collected through Academic Research Information Service (RISS). The collected data was refined using Excel and text, and major keywords were identified, analyzed, and visualized through frequency analysis and keyword network analysis. CONCOR cluster analysis was used to determine the centrality of keywords. Results First, since 2017, research on artificial intelligence convergence gifted education has been steadily expanding in terms of content and methods. Second, the results of frequency analysis of the main keywords in research related to artificial intelligence convergence gifted education showed ‘artificial intelligence’, ‘artificial intelligence education’, ‘gifted education’, ‘computational thinking ability’, and ‘machine learning’.Third, as a result of TF-IDF weight analysis, ‘artificial intelligence’, ‘artificial intelligence education’, ‘gifted education’, ‘computational thinking ability’, ‘science gifted’, ‘artificial intelligence education program’, and ‘information gifted’ were found. In general, it was similar to the results of the frequency analysis of major keywords, but it was confirmed that there was a difference in the rankings. Keywords with relatively high weight compared to their frequency of occurrence are ‘science gifted’, ‘creativity’, and ‘artificial intelligence education program’.Fourth, through semantic network and CONCOR analysis, it can be confirmed that artificial intelligence convergence gifted education research is being conducted focusing on ‘educational content’, ‘educational effect’, ‘teaching method’, and ‘educational target’. Conclusions This study derived the main topics and flows of research based on the results of keyword network analysis of domestic artificial intelligence convergence gifted education-related research.

문제중심학습(PBL) 교수법을 적용한 수업이 간호대학생의 자기주도 학습능력과 의사소통능력, 학업적 자기효능감에 미치는 효과

Objectives The purpose of this study was to examine the effects of flipped learning teaching and learning method on self-directed learning ability, communication ability, and academic self-efficacy of nursing college students. Methods The subjects of this study were nursing students at S University in Jeonnam, and the data collection period was from September 6, 2023 to December 6, 2023.,The collected data were analyzed by frequency analysis, reliability analysis, descriptive statistical analysis, correlation analysis, and paired t-test using SPSS Windows 20.0 Program. Results It was confirmed that the flipped learning method applied class had statistically significant effects on self-directed learning ability, communication ability, and academic self-efficacy of nursing college students.,Also, as a result of analyzing sub-areas of each variable, it was found that there was a significant effect in the recognition ability, learning strategy, learning activity, learning evaluation, interpersonal skills, confidence of academic self-efficacy, self-regulation efficacy, and preference of task difficulty. Conclusions This study is significant in that it verified the effectiveness by applying the problem-based learning teaching method that has recently emerged to the curriculum, and in the future, it is expected that this teaching and learning method will be applied to the curriculum in consideration of various environments and students' levels, and extensive research will be needed to confirm the effectiveness and to add various variables.

청소년의 일상스트레스 요인이 행복감에 미치는 영향: 분노대처방식의 매개효과

Objectives This study aimed to examine the relationships between daily stress factors (parents, economy, grades, school, peers, and appearance) perceived by adolescents and verify the mediating effect of anger coping styles in the relationship between daily stress factors and happiness. Methods The participants were 468 adolescents attending middle and high schools in the Gwangju and Jeonnam regions. This study conducted frequency analysis, reliability test, and correlation analysis using the SPSS WIN 23.0 program and examined the mediating effect using Process Macro Model 4. Results The findings revealed that daily stress factors (parents, grades, school, peers, appearance, and economy) affected adolescents’ happiness. Secondly, parental, academic, school, and economy-related stress influenced anger coping styles. Thirdly, anger coping styles mediated the relationship between daily stress and happiness. Specifically, economic stress showed a full mediating effect, while parentak, academic, and school-related stress had a partial mediating effect. However, peer and appearance-related stress had no mediating effect. Conclusions These results confirm that daily stress factors influence both happiness and anger coping styles among adolescents, with economic, parental, academic, and school-related stress factors showing mediating effects. Thus, this study emphasized the importance of addressing and intervening in stress factors affecting adolescents and discussed suggestions for future studies.

청소년의 건강행태와 먹방⋅쿡방 시청이 비만에 미치는 영향: 제18차 청소년건강행태조사 자료를 활용하여

Objectives The purpose of this study was to determine the relationship between adolescents' health behaviors and obesity and their viewing of mukbangs and cooking shows. Methods This study used data from the 18th Youth Health Behavior Survey conducted in 2022, and a total of 51,850 participants were analyzed by reflecting stratification variables, clustering variables, and weights according to the Korean Centers for Disease Control and Prevention's guidelines for composite sample analysis. Composite frequency analysis and composite crosstabulation analysis(Rao-Scott χ2-test) were conducted, and composite logistic regression analysis was performed to analyze the influencing factors. Results The results showed that adolescents' gender, grade level, subjective economic status, breakfast skipping, fruit consumption, fast food consumption, vegetable consumption, late-night snacking, days of physical activity of 60 minutes or more per day during the week, days of strength training during the week, and frequency of watching mukbangs and cooking shows were significantly associated with obesity. Conclusions In order to prevent obesity in teenagers, it is necessary to provide appropriate education and various programs so that people can enjoy watching mukbang and cooking show videos and manage the effects on their own.

Effect of Densah Burs on Primary and Secondary Stability of Immediately Loaded Implants in Addition to Crestal Bone Loss and Gingival Probing Depth - An Evaluative Study.

Osseodensification (OD) compaction increases primary stability by leaving the residual bone particles in the osteotomy site, which in turn act as an autograft.[1] Condensing the bone trabeculae through OD has demonstrated to have a potentiating influence on secondary stability.[2]. A split-mouth study was conducted in 40 patients to determine the effect of OD on implant success rate in terms of primary and secondary stability in situations including immediate loading of implants placed in low-density bone, which was tested using resonance frequency analysis (RFA) at the interval of 0, 6th month. In order to assess the implant success rate, gingival probing depth and crestal bone loss (CBL) around the implant were also assessed at baseline and 6 months. With respect to primary stability, at baseline, the mean RFA of Densah burs is 71.6 ± 9.5 and of conventional drills is 67.6 ± 10.4. The mean stability of Densah burs is significantly higher than conventional drills, both at baseline and after 6 months as well. CBL, at baseline, the mean CBL of Densah burs is 0.58 ± 0.11 and of conventional drills is 0.64 ± 0.12. The mean CBL of Densah burs is significantly lower than that of conventional drills for both. The implant stability values found in the present study were remarkable when compared between OD and conventional osteotomy techniques. Decreased loss of bone at the crest probing depth also aided in the increased success rate.

The application of matching pursuit spectral blueing in post-stack seismic frequency enhancement

The calculation of the spectral blueing operator in the traditional spectral blueing method has singularity, which leads to poor performance in post-stack seimic frequency expansion. To this end, a frequency spreading technique based on matching pursuit (MP) and spectral blueing is proposed. Through time–frequency analysis processing, it is shown that the seismic signal extracted by matching tracking method has good stability and higher resolution. The specific process of the method in this paper firstly uses the matching tracking method to accurately divide the post-stack seismic data into multiple frequency-division seismic bodies; then, in the process of calculating the spectral blueing ization operators for each frequency band, the weighting idea is used to calculate the weights of the optimized spectral blueing ization operators for each frequency band based on the differences in energy in different frequency bands; finally, the optimized spectral blueing operator is convolved with seismic reflection coefficients to obtain high-resolution seismic data. The actual test results of poststack seismic data have proven that the frequency raising method proposed in this paper is superior to the traditional spectral blueing ization algorithm, greatly improving the high-frequency component information of poststack seismic data. After frequency extension, there are more seismic events and higher resolution. Finally, the practicability and rationality of the seismic data after frequency extraction are verified by a series of operations such as attribute extraction, well seismic calibration and inversion.

Analysis of the Mechanism Underlying Radiotherapy Resistance Caused by Oligodendroglia Cells in Glioblastoma by Applying the Single-cell RNA Sequencing Technology.

Glioblastoma (GBM) is an aggressive malignancy. The inherent resistance of GBM to radiotherapy poses great challenges for clinical treatment. The primary objective of this study is to explore the molecular mechanisms of radiotherapy resistance in GBM and identify the key influencing factors that contribute to this phenomenon. The single-cell RNA sequencing (scRNA-seq) data of GBM were downloaded from the Gene Expression Omnibus (GEO) database. Cells were clustered using the Seurat R package, and the clusters were annotated using the CellMarker database. Pseudotime analysis was conducted using Monocle2. Marker scores were calculated based on the RNA-seq data of GBM from the UCSC database, and the enrichment of Hallmark gene sets was measured with the AUCell package. Furthermore, the most frequently mutated genes were identified using the simple nucleotide variation data from The Cancer Genome Atlas (TCGA) applying the maftools package. This study identified two oligodendrocyte subsets (ODC3 and ODC4) as radiotherapy-resistant groups in GBM. Enrichment and Pseudotime analysis revealed that the inflammatory response and immune activation pathways were enriched in ODC3, while the cell division and interferon response pathways were enriched in ODC4. The enrichment scores of hallmark gene sets further confirmed that ODC3 and ODC4 subpopulations developed radiotherapy resistance via distinct molecular mechanisms. Analysis of gene mutation frequencies showed that TP53 exhibited the most significant change in mutation frequency, indicating that it was an important risk factor involved in radiotherapy resistance in GBM. We identified two ODC subpopulations that exhibited resistance to radiotherapy, providing a new perspective and potential targets for personalized treatment strategies for GBM.

Characterization and depositional pattern of the modern pollen and non-pollen palynomorphs in Pobitora Wildlife Sanctuary, India and its implications to palaeoecology and palaeoherbivory analysis

ABSTRACT This study documents the depositional pattern of modern pollen and fungal spores in relation to the different vegetation types and wildlife activities in Pobitora Wildlife Sanctuary located in northeast India. The pollen data accurately matches the extant vegetation types and provides additional evidence on the representation and relative abundance of the major pollen taxa in the pollen assemblages. Forest habitat is characterized by the abundance of Bombax, Lagerstroemia, Barringtonia, and Albizia pollen in the pollen assemblage. The swamp habitat is characterized by a Cyperaceae, Onagraceae, Nymphaea, and Potamogeton the grassland habitat characterized by the dominance of non-cereal (Poaceae), Asteroideae, Cyperaceae, and Bombax pollen in the pollen assemblage. Among fungal spores, coprophilous fungal spores were observed and identified. Their presence varies in relation to the different vegetation types and level of wildlife activity in each habitat in the wildlife sanctuary. Rhododendron pollen in the palynoassemblages is indicative of seasonal flooding during periods of high rainfall in and around the study areas. Principal Component Analysis (PCA) applied to the quantified data obtained from the pollen frequency analyses revealed a significant variation that distinguished the three different vegetation types in the Pobitora Wildlife Sanctuary. This modern pollen and fungal spore data serves as a reliable baseline for the reconstruction of the palaeoecology and palaeoherbivory in the Pobitora Wildlife Sanctuary and to correlate the types of vegetation present in other parts of the tropical region of Indo-Burma.

Deep Learning Method for Post-earthquake Damage Assessment of Frame Structures Based on Time–Frequency Analysis and CGAN

Deep Learning Method for Post-earthquake Damage Assessment of Frame Structures Based on Time–Frequency Analysis and CGAN