Miracle-dz/UniFAR-FTUs huggingface dataset:
Phytochemical and Gas Chromatography-Mass Spectrometry Analysis of Chenopodium album and Stellaria media

The current study was designed to conduct the physicochemical, phytochemical and gas chromatographymass spectrometry analysis of Chenopodium album and Stellaria media L. Methanolic extract of dried leaves of Chenopodium album and Stellaria media was prepared and subsequently fractionated using different solvents like hexane, chloroform, ethyl acetate. Obtained plant fractions were analyzed for the presence of different secondary metabolites using phytochemical screening methods. Further, total phenolic content, total flavonoid content and total alkaloid content in different plant fractions were also estimated employing Ultraviolet-visible spectrophotometric methods. Results of phytochemical analysis revealed the presence of different secondary metabolites including flavonoids, phenols, alkaloids, tannins, glycosides and saponin. Further, gas chromatography-mass spectrometry analysis indicated presence of total 30 and 31 phytoconstituents in hexane and ethyl acetate fractions of methanolic extract of Chenopodium album respectively whereas chloroform and ethyl acetate fractions of methanolic extract of Stellaria media showed presence of total 33 and 35 phytoconstituents respectively. Gas chromatography-mass spectrometry chromatogram showed abundance of polyphenolic compounds (85 % Phenol-2,4-bis(1,1-dimethylethyl), phosphite (3:1) in hexane fractions of Chenopodium album, long-chain fatty acids (51 % hexadecanoic acid, methyl ester in chloroform fractions of Chenopodium album), higher alkanes (66 % Octasiloxane1,1,3,3,5,5,7,7,9,9,11,11,13,13,15,15-hexadecamethyl in ethyl acetate fractions of Chenopodium album ). Outcome of the study would certainly assist the investigators to explore these plants and to identify and develop new leads for the treatment of different pathological conditions.
AC 2007-1241: DRAMATIZING ENGINEERING EDUCATION: THE PERFORMANCE OF TEAMWORK

Abstract Engineering education is now characterized by innovative approaches to instruction. Collaboration between (often disparate) disciplines is becoming increasingly common to meet the educational needs of engineering undergraduates. ABET’s EC 2000 has shifted the focus from technical educational outcomes to encompass professional educational outcomes, including the ability to communicate and function effectively on multidisciplinary teams. As a result, greater emphasis is placed on teaching students the teamwork principles and associated communication competencies necessary for a healthy and productive team experience. Interestingly, teamwork pedagogy has not occupied a prominent position in the engineering education literature, despite this emphasis on teaming in the classroom and industry. The purpose of this paper is to highlight one specific, innovative approach to teaming instruction that requires collaboration from faculty in three different disciplines, namely, communication, drama, and engineering. Representatives from each department work with undergraduate engineering students to teach them team dynamics through writing of vignettes appropriate for the particular curriculum, and through performance, employing a range of techniques such as role-play, role switching, alter-egoing, etc. A description of this educational approach is provided, followed by a summary of students’ reactions to the instruction. Finally, faculty members’ reflect on their experience working as part of a multidisciplinary team and offer recommendations for implementation.
A Lightweight Detection Model for SAR Aircraft in a Complex Environment

Recently, deep learning has been widely used in synthetic aperture radar (SAR) aircraft detection. However, the complex environment of the airport—consider the boarding bridges, for instance—greatly interferes with aircraft detection. Besides, the detection speed is also an important indicator in practical applications. To alleviate these problems, we propose a lightweight detection model (LDM), mainly including a reuse block (RB) and an information correction block (ICB) based on the Yolov3 framework. The RB module helps the neural network extract rich aircraft features by aggregating multi-layer information. While the RB module brings more effective information, there is also redundant and useless information aggregated by the reuse block, which is harmful to detection precision. Therefore, to accurately extract more aircraft features, we propose an ICB module combining scattering mechanism characteristics by extracting the gray features and enhancing spatial information, which helps suppress interference in a complex environment and redundant information. Finally, we conducted a series of experiments on the SAR aircraft detection dataset (SAR-ADD). The average precision was 0.6954, which is superior to the precision values achieved by other methods. In addition, the average detection time of LDM was only 6.38 ms, making it much faster than other methods.
More compact ferrite circulator junctions with predicted performance

The analysis of two novel types of three-port junction circulator is discussed in detail, and, neglecting losses, graphs of the predicted performance of specific theoretical designs are shown. The first type of circulator is based on a ferrite ring, and it is shown that by appropriately selecting the ratio of the inner/outer radius of the ring the need for transformers can be eliminated. The second type is based on a three-port ferrite disk with two ports positioned 60 away from a middle port. This provides a more compact layout and a design for 94 GHz is presented. >
Objective hand measurement of materials used for disposable diapers

The objective hand measurement of the materials used for disposable diapers has been looked into, with consideration given to aspects of both dermatitis and comfort. The subjective hand of the commercially produced diapers both at the leg gatherings and at the center was assessed by mothers and female students. The mechanical and surface parameters of the diapers were measured with the KES‐FB system. The equations that connect the material properties to the subjective hand were obtained by using the stepwise block‐regression analysis method. It became clear that the hand of diapers could be predicted from the physical parameters, for which the calculated error was within the range of the standard deviation of the subjective hand value of each diaper. In a dry condition, it is expected that the hand of diapers could be satisfactorily evaluated by using only the surface and compression parameters.
The SPUR adherence profiling tool: preliminary results of algorithm development

Abstract Objective The SPUR (Social, Psychological, Usage, and Rational) Adherence Profiling Tool is a recently developed adaptive instrument for measuring key patient-level risk factors for adherence problems. This study describes the SPUR questionnaire’s psychometric refinement and evaluation. Methods Data were collected through an online survey among individuals with type 2 diabetes in the United States. 501 participants completed multiple questionnaires, including SPUR and several validated adherence measures. A Partial Credit Model (PCM) analysis was performed to evaluate the structure of the SPUR tool and verify the assumption of a single underlying latent variable reflecting adherence. Partial least-squares discriminant analyses (PLS-DA) were conducted to identify which hierarchically-defined items within each dimension needed to be answered by a given patient. Lastly, correlations were calculated between the latent trait of SPUR adherence and other patient-reported adherence measures. Results Of the 45 candidate SPUR items, 39 proved to fit well to the PCM confirming that SPUR responses reflected one underlying latent trait hypothesized as non-adherence. Correlations between the latent trait of the SPUR tool and other adherence measures were positive, statistically significant, and ranged from 0.32 to 0.48 (p-values < .0001). The person-item map showed that the items reflected well the range of adherence behaviors from perfect adherence to high levels of non-adherence. The PLS-DA results confirmed the relevance of using four meta-items as filters to open or close subsequent items from their corresponding SPUR dimensions. Conclusions The SPUR tool represents a promising new adaptive instrument for measuring adherence accurately and efficiently using the digital behavioral diagnostic tool.
Foundations for Digital Transformation: The Case of Vietnam

Research purpose: The purpose of this paper is to analyze the digitalization environment in Vietnam by investigating the foundations for digital transformation, from which enterprises can foresee the opportunities as well as challenges in the process of digital transformation. Research motivation: The motivation of this research is based on the observation that digital transformation is accomplished by a combination of people, businesses, and technology and it needs the guidance from a sound strategy, all of which are influenced by the nation’s digitalization environment. Understanding this environment plays a critical role in shaping not only the future digital transformation of industries but also the digital transformation strategies of enterprises. Research design, approach and method: This study uses data analysis and synthesis methods, with data taken from World Bank, previously published studies, as well as Government’s official statistical data… Main findings:
Elastic Multibody Models of Transport Aircraft High-Lift Mechanisms

DOI: 10.2514/1.37583 In development of transport aircraft high-lift systems, the application of commercial simulation tools is widely used. This paper provides a short overview of parametric modeling of the mechanisms of the high-lift system of a transport aircraft as an elastic multibody system. Elastic mechanical components are modeled by means of the method of finite elements. The high-lift mechanisms comprise the leading-edge devices (droop nose, slats) and thetrailing-edgedevices(flaps). Aftergivingsomedetailsofthetheoreticalbackgroundofelasticmultibodysystems, the specificmodels of the high-lift mechanisms are described. Simulation results of representative parameter studies demonstrate the application of the model. Some failure cases are also investigated in addition to an operating load case. Nomenclature D = deformation tensor F = force F = load vector f = modal load vector G = constraint matrix g = residuals of implicit constraints K = stiffness matrix M = mass matrix N = modal matrix q = modal coordinates � q = eigenvector q � = Craig–Bampton coordinates r = position vector u = physical displacement vector v = velocity vector � = Euler angles " = strain vector � = eigenvalue � = reaction force coordinates � = stress vector � = modal matrix ! = angular velocity vector
Deviation Point Curriculum Learning for Trajectory Outlier Detection in Cooperative Intelligent Transport Systems

Cooperative Intelligent Transport Systems (C-ITS) are emerging in the field of transportation systems, which can be used to provide safety, sustainability, efficiency, communication and cooperation between vehicles, roadside units, and traffic command centres. With improved network structure and traffic mobility, a large amount of trajectory-based data is generated. Trajectory-based knowledge graphs help to give semantic and interconnection capabilities for intelligent transport systems. Prior works consider trajectory as the single point of deviation for the individual outliers. However, in real-world transportation systems, trajectory outliers can be seen in the groups, e.g., a group of vehicles that deviates from a single point based on the maintenance of streets in the vicinity of the intelligent transportation system. In this paper, we propose a trajectory deviation point embedding and deep clustering method for outlier detection. We first initiate network structure and nodes’ neighbours to construct a structural embedding by preserving nodes relationships. We then implement a method to learn the latent representation of deviation points in road network structures. A hierarchy multilayer graph is designed with a biased random walk to generate a set of sequences. This sequence is implemented to tune the node embeddings. After that, embedding values of the node were averaged to get the trip embedding. Finally, LSTM-based pairwise classification method is initiated to cluster the embedding with similarity-based measures. The results obtained from the experiments indicate that the proposed learning trajectory embedding captured structural identity and increased F-measure by 5.06% and 2.4% while compared with generic Node2Vec and Struct2Vec methods.
Older Adults’ Experience of an Exergaming Intervention to Improve Balance and Prevent Falls: A Nested Explanatory Qualitative Study

Falls are frequent and life-changing events for older adults worldwide. The ageing phenomenon has arrived in developing countries, which experience tensions between curative and rehabilitative services, combined with an increase in non-communicable diseases. Policies addressing issues of ageing have been poorly implemented, and there are few fall prevention initiatives. Compelling evidence from the Global North supports exercise-based interventions to improve balance and reduce fall risk in older adults. More recently, attention has focused on interactive videogaming, known as exergames, as a novel way to manage fall risk with exercise. Commercially available exergames have inherent appeal for low- and middle-income country contexts, where rehabilitation professionals and resources are scanty. The aim of this study was to explore the feasibility of a large-scale randomized control trial comparing an exergaming intervention with the gold-standard Otago Exercise Programme and a no-intervention arm. Exercise adherence was poor in both intervention arms, and this prompted a shift to mixed methodology to explore the construct of falls and participants’ experience of the exergaming intervention. Focus groups were conducted, and the results were analysed using content analysis. Whereas the results demonstrated improvements in physical outcome measures (e.g., Timed-Up-and-Go, MiniBESTest) related to balance and falls that were encouraging in both the gold-standard and exergaming intervention groups, few participants achieved optimal adherence. Attitudes toward falls and fall prevention were explored, as well as participants’ experiences of the exergaming programme. Consistent with a developing country context, participants acknowledged both intrinsic and extrinsic fall risk factors. Exergaming participants enjoyed the fun and playful aspects of the exercise programme, yet these were not sufficient to maximize adherence. The focus groups described the barriers and facilitators to participation, which included motivation. The focus groups discussed strategies to enhance participation, and these are discussed in the context of exergaming.
Population-Based Hyperparameter Tuning With Multitask Collaboration

Population-based optimization methods are widely used for hyperparameter (HP) tuning for a given specific task. In this work, we propose the population-based hyperparameter tuning with multitask collaboration (PHTMC), which is a general multitask collaborative framework with parallel and sequential phases for population-based HP tuning methods. In the parallel HP tuning phase, a shared population for all tasks is kept and the intertask relatedness is considered to both yield a better generalization ability and avoid data bias to a single task. In the sequential HP tuning phase, a surrogate model is built for each new-added task so that the metainformation from the existing tasks can be extracted and used to help the initialization for the new task. Experimental results show significant improvements in generalization abilities yielded by neural networks trained using the PHTMC and better performances achieved by multitask metalearning. Moreover, a visualization of the solution distribution and the autoencoder’s reconstruction of both the PHTMC and a single-task population-based HP tuning method is compared to analyze the property with the multitask collaboration.
Nonlinear decoupled FDTD code: phase-matching in 2D defective photonic crystal

A simple 2D finite difference time domain (FDTD) code able to describe second-harmonic generation in 1D or 2D structured materials is developed. This code is applied to a semiconductor defective photonic crystal waveguide where phase-matching is obtained by engineering the dispersion of the Bloch modes.
Impact of processing technology on DRAM sense amplifier design

Sense amplifier design is critical to DRAM performance. As DRAM chip capacity has increased, different sensing schemes have been employed. The purpose of this work is to explain impacts of processing technology on DRAM sense amplifier design and to identify design strategies suitable for 64M DRAM sense amplifiers. DRAM performance and processing technology evolution are reviewed. Sense amplifier operation is examined analytically. Sense amplifiers used in 4K and higher density DRAMs are studied. 64M DRAM processing technology features and performance specifications are projected. Finally, alternative design approaches for 64M DRAM sense amplifiers are compared and evaluated. Thesis Supervisor: Charles G. Sodini Title: Associate Professor of Electrical Engineering and Computer Science Company Supervisor: Howard L. Kalter Title: Senior Technical Staff, IBM Corporation This material is based upon work supported in part under a National Science Foundation Graduate Fellowship. Acknowledgements I have completed three MIT VI-A Internship Program assignments at the IBM General Technology Division in Essex Junction, Vermont. This research was conducted during my third assignment. I am grateful to past and present members of Department A23 for their help. John Nickel served as my mentor during my first assignment, patiently teaching me CMOS circuit design. Jim Yankosky, John Barth, and John Nickel all provided invaluable computer assistance. Scott Lewis and John Fifield contributed very useful sense amplifier design insights. Chuck Drake graciously shared his computer with me. Outside of Department A23, Paul Smith supplied DRAM trend information and provided graphics software guidance. I thank Howard Kalter, my manager and thesis supervisor at IBM, for making my assignments both interesting and educational, for sharing his technical wisdom, and for reviewing drafts of this thesis. I am grateful to Charles Sodini for supervising this thesis. I thank my fiancde, Mary Condello, for helping me manage my bibliography, for proofreading this thesis, for her support and encouragement, and for enduring several long bus rides in order to visit me in Vermont. Finally, I thank my parents, Jon and Rita Gealow, for their love and support.
On a Data-Driven Approach for Detecting Disturbance in the Brazilian Savannas Using Time Series of Vegetation Indices

Remote sensing of disturbance in the savannas from Brazil is challenging, especially due to confounding effects of the vegetation phenology and natural soil exposure on the detection of clearing and fire events. In this study, we investigated the detection of disturbance over this global hotspot of biodiversity using seven vegetation indices (VIs) calculated from the Landsat time series (2017–2019) and the Continuous Change Detection and Classification (CCDC) algorithm. The selected VIs represented distinct biophysical characteristics of the savannas. We evaluated the effects of disturbance on these VIs and assessed the accuracy of CCDC-detection in 2019, considering individual VIs, ensemble VIs, and the type of disturbance (savanna clearing and fire). Finally, we analyzed the possible existence of seasonal patterns of disturbance in a study area located at the new agricultural frontier of the Cerrado biome. The results showed that the overall accuracy of CCDC detection of total disturbance ranged from 51.2% for the Green-Red Normalized Difference (GRND) to 65.9% for the Normalized Burn Ratio (NBR2). It increased to 71.2% for ensemble VIs, whose multivariate approach reduced the omission errors in the analysis when compared to the use of single VIs. For detecting events of savanna clearing and fire, the most important VIs used near-infrared and shortwave infrared reflectance bands on their formulations (NBR2, NBR, and Moisture Stress Index—MSI). The CCDC accuracy was generally higher for detecting clearing than for mapping burned areas. In contrast, the recorded date of disturbance occurrence was less precise for detecting clearing than for recording events caused by fire, especially due to the existence of some gradual processes of vegetation degradation until complete clearing. Our findings showed also the existence of a seasonal pattern of disturbance occurrence. Savanna clearing predominated in the transition from the rainy to the dry season (April to July) to open new areas for agriculture. It preceded most events of fire disturbance between August and October that occurred near the consolidated areas of agriculture and extended into the native vegetation areas. Results reinforce the importance of data-driven approaches for generating early warning alerts of disturbance in the Cerrado to be further checked in the field.
The Conceptual, Cunning, and Conclusive Experiment in Psychology

The ideal experiment in physics must be conceptual, cunning, and conclusive. Adoption of these same standards in psychology has led to experiments that are uninformative and frivolous. We explain why we believe that psychology is fundamentally incompatible with hypothesis-driven theoretical science and conclude that this erodes the logic behind recent proposals to improve psychological research, such as stricter statistical standards, preregistration, and replication. The failure of psychology is not that it is somehow insufficiently scientific but rather that it makes inordinate use of methods that are a mismatch for the aspirations of researchers in the field, at the expense of valuable empirical research.
IDENTIFICATION OF HISTORIC METHODS OF CONSTRUCTION USING DIGITAL PHOTOGRAMMETRY AND LASER SCANNING

In accordance with Article 2 of the Council of Europe Convention, for the Protection of the Architectural Heritage of Europe (Granada Convention), a National Inventory, a record of Architectural Heritage is now been undertaken by many countries in Europe. This coincides with new developments in surveying and recording techniques. This paper examines the application of automated surveying and recording techniques (integrating laser scanning, digital photogrammetry and CAD), through the recording of a case study of a 17th century streetscape based in the city of Dublin. The process results in the production not only of a record of the historic structure or artefact but also an analysis of historic construction methods, which may inform correct conservation of both structure and fabric. Automated recording and surveying techniques provide a digital image and vector record, facilitating analysis concerning many aspects of a historic structure or artefact. It is possible to abstract data relating to the original construction methods, materials and their sources and the monitoring/identification of damage and decay to objects or buildings. The paper is a collaboration of a multidisciplinary team from the Faculty of the Built Environment of the Dublin Institute of Technology and the School of Engineering Trinity College Dublin.