806 research outputs found
sj-docx-1-npx-10.1177_1934578X231168481 - Supplemental material for Volatile Components and Biological Activities of <i>n</i>-Hexane Extract From Rhizomes of <i>Homalomena cochinchinensis</i>
No full textSupplemental material, sj-docx-1-npx-10.1177_1934578X231168481 for Volatile Components and Biological Activities of n-Hexane Extract From Rhizomes of Homalomena cochinchinensis by Linh Thuy Khanh Nguyen, Phu Quynh Dinh Nguyen, Nghia Ai Thi Doan, Chau Bao Hoai Nguyen, Tuan Quoc Doan, Linh Thuy Thi Tran, Hoai Thi Nguyen and Duc Viet Ho in Natural Product Communications</p
Random matrices and random boxes
No full textThis thesis concerns two questions on random structures: the semi-circular law for adjacency matrix of regular random graph and the piercing number for random boxes. Random matrices: We proved in full generality the semi-circular law for random d-regular graph model in the case d tends to infinity as n does. Our result complements the McKay law [19], which applied for the case d is an absolute constant. Random boxes. Take n random boxes with axis-parallel edges inside the unit cube [0; 1][superscript]d, the piercing number is the minimum number of points needed to pierce all boxes. Using hypergraph setting, we was able to prove a near sharp estimation for the piercing number. This thesis is based on two papers by the author [31] and [30] (joint work with Van Vu and Ke Wang).Ph.D.Includes bibliographical referencesIncludes vitaby Linh V. Tra
Interview with Mai-Linh Hong
No full textMai-Linh Hong is a Vietnamese American woman, she was born in Vietnam and grew up near Washington D.C. Hong is an author, editor, and Assistant Professor of Literature at UC Merced. Prior to joining the Auntie Sewing Squad, she ran an Etsy shop and its proceeds went to anti-racist and feminist organizations. As an Auntie, she actively donates masks but is also currently co-editing the Auntie Sewing Squad’s new book.https://digitalcommons.csumb.edu/auntiesewing_interviews/1040/thumbnail.jp
Back to the Future: Mathematical Predictions //VAC 112
No full textSujata Bhandari, Predicting Loan Default using Logistic Regression
Anh Doan, Statistics and Machine Learning: Regression and Forecasting
Linh T. Pham, Implementation of Binomial and Black-Scholes Option Pricing Models in Python to Predict Amazon European Option Premiums
Marella Fernandez, Social Factors Contributing to Academic Success: A Statistical Analysis
Moderator: Dr. Molly Lync
sj-docx-1-npx-10.1177_1934578X231175263 - Supplemental material for Phytochemical Composition and Bioactivities of Essential Oils from Rhizomes of <i>Homalomena pendula</i> and <i>Homalomena cochinchinensis</i>
No full textSupplemental material, sj-docx-1-npx-10.1177_1934578X231175263 for Phytochemical Composition and Bioactivities of Essential Oils from Rhizomes of Homalomena pendula and Homalomena cochinchinensis by Linh Thuy Khanh Nguyen, Tuan Quoc Doan and
Phu Quynh Dinh Nguyen, Chau Bao Hoai Nguyen, Linh Thuy Thi Tran, Thi Van Anh Tran, Hoai Thi Nguyen, Duc Viet Ho in Natural Product Communications</p
Heterogeneity in behavioural response to pricing policies in the transition from motorcycles to private cars in motorcycle-based societies
No full textPricing instruments are widely seen as an effective tool for reducing the travel demand for private vehicles. In contrast to developed countries, the design of pricing policies in certain developing countries is more challenging, owing to the mixed use of private cars and motorcycles. This study argues for the existence of a transitional group of motorcycle users who will switch to being car users. An investigation of the behavioural responses to a pricing policy from private car users and motorcycle users is implemented in Ho Chi Minh City, Vietnam. A propensity score-matching technique is used to identify the transitional group. The results regarding the mode choice models for various pricing policies show similar responses between the transitional motorcycle users and car users. Such characteristics of the transitional group imply that ignorance of travellers' heterogeneity may cause significant bias, especially when modelling pricing policies.This research was financed by the Special Research Fund of Hasselt University.
Financial support in data collection: Ho Chi Minh City Institute for Development Studies (HIDS)
Author contribution: The authors confirm contribution to the paper as follows: study concept and design: Hoang Thuy Linh, Nguyen Hoang Tung, Vu Anh Tuan, Muhammad Adnan, and Tom Bellemans; data preparation, analysis, and interpretation of results: Hoang Thuy Linh; draft manuscript preparation: Hoang Thuy Linh, Nguyen Hoang Tung, and Muhammad Adnan. All authors reviewed the results and approved the final version of the manuscript
sj-docx-1-npx-10.1177_1934578X231191636 - Supplemental material for New Sesterterpenoid from the Marine Fungus <i>Penicillium oxalicum</i> M893
No full textSupplemental material, sj-docx-1-npx-10.1177_1934578X231191636 for New Sesterterpenoid from the Marine Fungus Penicillium oxalicum M893 by Thi Hoang Anh Nguyen, Thi Quynh Do, Thuy Linh Nguyen and
Hong Minh Le Thi, Mai Anh Nguyen, Brian T Murphy,
Thanh Xuan Dam, Doan Thi Mai Huong, Pham Van Cuong in Natural Product Communications</p
Recognition of breast cancer from heterogeneous ultrasound images: A multi-level deep learning approach
No full textBreast ultrasound is a medical imaging technique that employs sound waves to produce breast images, and it has been primarily used to diagnose breast cancer and other related issues. With various machine learning algorithms being applied, many applications have shown promising results and demonstrated outstanding efficiency in giving doctors early accurate diagnoses. By investigating existing state-of-the-art approaches to breast lesion detection, given ConvNeXt-Small architecture as an example, we observe that although they bring a satisfactory performance in classification, their ability to detect small lesions is limited. Therefore, there is still room for improving the performance of DL-based approaches. In this paper, we present a practical Deep Learning-based solution for breast lesion detection, using DetectoRS with Gaussian Receptive Field-based Label Assignment (RFLA) and SegFormer-B4 for recognizing and segmenting small breast lesions, including malignant tumors. Our proposed solution involves three distinct models: ConvNeXt-Small for classification, Swin-Base combined with DetectoRS and RFLA for object detection, and SegFormer-B4 for segmentation. Each model is tailored specifically to address its respective task in breast cancer detection and analysis. The proposed approach has been evaluated on diverse ultrasound datasets. Our deep learning model achieves an Average Precision of 0.270 for small objects (AP_S), and records the highest mean Intersection over Union at 81.55%. The results show that the proposed model outperforms various well-established baselines. We suppose that our method can be integrated into computer-aided diagnosis systems to assist physicians in their clinical activities
Fluid flux in fractured rock of the Alpine fault hanging-wall determined from temperature logs in the DFDP-2B borehole, New Zealand
No full textSixteen temperature logs were acquired during breaks in drilling of the 893m-deep DFDP-2B borehole, which is in the Alpine Fault hanging-wall. The logs record various states of temperature recovery after thermal disturbances induced by mud circulation. The long-wavelength temperature signal in each log was estimated using a sixth-order polynomial, and residual (reduced) temperature logs were analyzed by fitting discrete template wavelets defined by depth, amplitude, and width parameters. Almost two hundred wavelets are correlated between multiple logs. Anomalies generally have amplitudes <1°C, and downhole widths <20m. The largest amplitudes are found in the first day after mud circulation stops, but many anomalies persist with similar amplitude for up to 15 days. Our models show that thermal and hydraulic diffusive processes are dominant during the first few days of re-equilibration after mud circulation stops, and fluid advection of heat in the surrounding rock produces temperature anomalies that may persist for several weeks. Models indicate that the fluid flux normal to the borehole within fractured zones is of order 10−7 to 10−6 m s−1, which is 2–3 orders of magnitude higher than the regional flux. Our approach could be applied more widely to boreholes, as it uses the thermal re-equilibration phase to derive useful information about the surrounding rock mass and its fluid flow regime.</p
Determination of stress state in deep subsea formation by combination of hydraulic fracturing in situ test and core analysis: A case study in the IODP Expedition 319
No full text[1] In situ test of hydraulic fracturing (HF) provides the only way to observe in situ stress magnitudes directly. The maximum and minimum horizontal stresses, SHmax and Shmin, are determined from critical borehole pressures, i.e., the reopening pressure Pr and the shut-in pressure Ps, etc, observed during the test. However, there is inevitably a discrepancy between actual and measured values of the critical pressures, and this discrepancy is very significant for Pr. For effective measurement of Pr, it is necessary for the fracturing system to have a sufficiently small compliance. A diagnostic procedure to evaluate whether the compliance of the employed fracturing system is appropriate for SHmax determination from Pr was developed. Furthermore, a new method for stress measurement not restricted by the system compliance and Pr is herein proposed. In this method, the magnitudes and orientations of SHmax and Shmin are determined from (i) the cross-sectional shape of a core sample and (ii) Ps obtained by the HF test performed near the core depth. These ideas were applied for stress measurement in a central region of the Kumano fore-arc basin at a water depth of 2054?m using a 1.6?km riser hole drilled in the Integrated Ocean Drilling Program (IODP) Expedition 319. As a result, the stress decoupling through a boundary at 1285?m below seafloor was detected. The boundary separates new upper layers and old lower ones with an age gap of ~1.8?Ma, which is possibly the accretionary prism. The stress state in the lower layers is consistent with that observed in the outer edge of accretionary prism
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