Miracle-dz/UniFAR-FTUs huggingface dataset:
Leading University Change: A Case Study of Meaning-Making and Implementing Online Learning Quality Standards

ABSTRACT This case study reports the collaborative meaning-making process and strategies for organizational change used by a diverse leadership team at a regional comprehensive university. The purpose of the study was to engage in continuous learning and improvement by producing knowledge for informing action; that is, to learn from analyzing the first phase of implementation in order to continue to improve, understand, and perhaps adjust in order to contribute to institutional change. Initiated by outcomes from a 2017 regional accreditation review and the recent development of a Global Campus, administrators, faculty, and instructional design and technology staff were charged with developing standards for quality university distance education. This study addresses lived experiences in the story of institutional change by reporting critical events, tensions, and turning points experienced by the leadership team relative to a change framework applied to distance education in a higher education setting. Over a two-year period (2018–2020), the team piloted, communicated, and refined plans as they began implementing the first of four phases in their quality assurance plan, including assessing 751 course syllabi for entry-level design standards. Findings indicate the process of enacting change also began shifting the culture of the university for purposes of quality assurance, consistency, and shared understandings of rigor. In this article, the team describes and discusses their framework using Kotter’s Change Model, their process, and their outcomes related to organizational change in higher education. Discussion addresses starting points for other higher education stakeholders involved in pursuing quality distance education.
MUSIC LOCALIZATION OF LOW-FREQUENCY ELECTROMAGNETIC SOURCES

In this work we apply the MUSIC algorithm to localize low-frequency (< MHz) electromagnetic sources, especially the magnetic dipoles (current loops), by measuring the magnetic field distributions around the sources. Both the locations and orientations of the incoherent multiple magnetic dipoles are estimated efficiently by searching for the local maxima of a MUSIC cost function with interpolation over the 3-d volume of interest. With simulations we evaluate the performance as well as the accuracy of the MUSIC algorithm.
Fuzzy optimization techniques applied to the design of a digital BLDC servo drive

This paper presents a novel design approach by applying fuzzy optimization techniques to design a digital brushless DC servomotor drive. The system specifications and design variables are firstly specified. The servo responses are then fed back to evaluate the overall system performances, which are expressed as cost functions with respect to the design variables. According to the cost functions and specifications, each design variable can be properly tuned toward the optimal value by using the proposed fuzzy optimization techniques. Besides, once the optimum design is achieved, the proposed fuzzy optimization strategy can perform as an intelligent controller for online gain adaptation with different loading conditions. Simulation and experimental results indicate that the servo control parameters can be optimized to achieve minimum cost under large uncertain load variations.
Gallium nitride MEMS resonators

As a wide band-gap semiconductor, with large breakdown fields and saturation velocities, Gallium Nitride (GaN) has been increasingly used in high-power, high-frequency electronics and monolithic microwave integrated circuits (MMICs). At the same time, GaN also has excellent electromechanical properties, such as high acoustic velocities and low elastic losses. Together with a strong piezoelectric coupling, these qualities make GaN ideal for RF MEMS resonators. Hence, GaN technology offers a platform for the seamless integration of low-loss, piezoelectric RF MEMS resonators with high power, high frequency electronics. Monolithic integration of MEMS resonators with ICs would lead to reduced parasitics and matching constraints, enabling high-purity clocks and frequency-selective filters for signal processing and high-frequency wireless communications. This thesis highlights the physics and resonator design considerations that must be taken into account in a monolithically integrated solution. We then show devices that achieve the highest frequency-quality factor product in GaN resonators to date (1.56 x 1013). We also highlight several unique transduction mechanisms enabled by this technology, such as the ability to use the 2D electron gas (2DEG) channel of High Electron Mobility Transistors (HEMTs) as an electrode for transduction. This enables a unique out-of-line switching capability which allowed us to demonstrate the first DC switchable solid-state piezoelectric resonator. Finally, we discuss the benefits of using active HEMT sensing of the mechanical signal when scaling to GHz frequencies, which enabled the highest frequency lithographically defined resonance reported to date in GaN (3.5 GHz). These demonstrated features show high potential for low-loss, reconfigurable systems for wireless communications. Thesis Supervisor: Dana Weinstein Title: Associate Professor Thesis Supervisor: Pablo Jarillo-Herrero Title: Associate Professor
Comparison of Long-term Human Precision-cut Lung Slice Culture Methodology and Response to Challenge: An Argument for Standardisation

As non-animal alternatives gain acceptance, a need for harmonised testing strategies has emerged. Arguably the most physiologically-relevant model for assessing potential respiratory toxicants, that based on human precision-cut lung slices (hPCLS) has been utilised in many laboratories, but a variety of culture methodologies are employed. In this pilot study, combinations of three different hPCLS culture methods (dynamic organ roller culture (DOC), air–liquid interface (ALI) and submersion) and various media (based on E-199, DMEM/F12 and RPMI-1640) were compared. The hPCLS were assessed in terms of their viability and responsiveness to challenge. The endpoints selected to compare the medium–method (M–M) combinations, which included histological features and viability, were evaluated at day 14 (D14) and day 28 (D28); protein and adenylate kinase (AK) content, and cytokine response to immunostimulants (lipopolysaccharide (LPS) at 5 μg/ml; polyinosinic:polycytidylic acid (Poly I:C) at 15 μg/ml) were evaluated at D28 only. Based on the set of endpoints assessed at D28, it was clear that certain culture conditions significantly affected the hPCLS, with the tissue retaining more of its native features and functionality (in terms of cytokine response) in some of the M–M combinations tested more than others. This pilot study indicates that the use of appropriate M–M combinations can help maintain the health and functional responses of hPCLS, and highlights the need for the standardisation of culture conditions in order to facilitate effective inter-laboratory comparisons and encourage greater acceptance by the regulatory community.
Multi-objective generation dispatch using bi-criterion global optimisation

This paper proposes a bi-criterion global optimisation approach to determine the most appropriate generation dispatch solution taking into account the fuel cost, the environmental cost and the requirement of the operation security of power networks. The approach is based on the simulated annealing technique and the formation of a bi-criterion objective function. Its effectiveness is demonstrated through an example, in which the sample test system is a 3-area interconnected and longitudinal system.
Capital structure, stock exchanges in Chile: 2007 to 2016

PurposeThe article consists of analyzing the behavior of the determinants of the capital structure of Chilean companies between 2007 and 2016. The objective of this study was achieved through a typology of research based on bibliographic, documentary, exploratory and explanatory, considering annual financial reports from Economática in the chosen period.Design/methodology/approachAs this is a research study with a quantitative approach, the statistical tools used were descriptive analysis, Pearson correlation, variance inflation factor (VIF) and panel regression.FindingsThe results show that Chilean companies (240) have higher and costly long-term debt. These companies have high averages in current liquidity, return to shareholders, growth in sales and assets and market-to-book (MTB). Long-term debt was highlighted with an explanatory power of 85%. Current liquidity was highlighted as being significant in most of the indebtedness proposed in the survey, failing to register brands like this in expensive short-term and long-term indebtedness. It is noticed that flip flops companies are more prone to the pecking order theory (POT). The gap occupied by this study is linked to research involving South American countries, especially the Chilean market, and the determinants of the capital structure.Originality/valueAs future research, it is suggested to include other types of variables related to indebtedness and the same action for its determinants, in addition to the speed technique of adjusting corporate debts.
Coping with the ‘double bind’ through vlogging: pandemic digital citizenship of Chinese international students

ABSTRACT The article examines the vlogging practices of Chinese international students during the COVID-19 pandemic and their positive roles in coping with the double bind. By doing thematic analysis of the content of vlog videos generated by Chinese international students on both Chinese and English audio-visual platforms, we identify three overarching themes of their vlogging stories: ‘everyday personal experience sharing’, ‘vlogger-generated citizen journalism’ and ‘producing counternarratives’. We argue that Chinese international students creatively practice ‘actualizing digital citizenship’ through dual vlogging. Their vlogging implies a strong sense of civic engagement, connectivity and empowerment, and is conducive to the self-resilience of the affected group as well as their identity and solidarity building in the crisis. Our research advocates for a shift of digital citizenship studies to recognize the flexible, individualized and loosely networked ‘actualizing digital citizenship’ practice. We also call attention to take the everyday digital practices of the international students seriously to understand their concerns, needs and resilience in the uncertain and difficult times in order to better support this vulnerable cohort.
A bibliometric study of lean supply chain management research: 1996–2020

Lean Supply Chain Management is an emerging research field in Operations Management that is attracting growing attention from researchers and practitioners. This paper aims to present a comprehensive analysis of the Lean Supply Chain Management literature to understand the influence, basic research characteristics, interrelationships, and productivity of the research in this field. The present study uses BibExcel and VOSviewer software to conduct thorough bibliometric and network analyses of 715 papers published in the Web of Science database over the period 1996-2020. The use of bibliometric methods has enabled the identification of current and emerging research clusters to detect some key research topics, interrelations, and collaboration patterns. Moreover, this analysis has enabled to draw numerous conclusions and propose a roadmap for future research in the field. This paper, therefore, provides some new insights not previously evaluated in other reviews of Lean Supply Chain Management that can help researchers to understand the evolution of research trends through a proposed classification of the literature on this topic.
Electronically tunable all-pole low-pass leapfrog ladder filter with operational transconductance amplifier

A general theory of the synthesis of all-pole low-pass filters using only operational transconductance amplifiers and capacitors with the leapfrog design method is presented. Especially the possibility of a simple method for tuning the cut-off frequency will be shown. An estimation of the worst-case sensitivity and a comparison of theory and experiment will complete the paper.
Piper: Multidimensional Planner for DNN Parallelization

The rapid increase in sizes of state-of-the-art DNN models, and consequently the increase in the compute and memory requirements of model training, has led to the development of many execution schemes such as data parallelism, pipeline model parallelism, tensor (intra-layer) model parallelism, and various memory-saving optimizations. However, no prior work has tackled the highly complex problem of optimally partitioning the DNN computation graph across many accelerators while combining all these parallelism modes and optimizations. In this work, we introduce Piper, an efﬁcient optimization algorithm for this problem that is based on a two-level dynamic programming approach. Our two-level approach is driven by the insight that being given tensor-parallelization techniques for individual layers (e.g., Megatron-LM’s splits for transformer layers) signiﬁcantly reduces the search space and makes the global problem tractable, compared to considering tensor-parallel conﬁgurations for the entire DNN operator graph.
Predictive Control of the Radiant Floor Heating System in Apartment Buildings

Abstract The objective of this study is to improve the control performance of the radiant floor heating system in apart-ment buildings. For this, predictive control, which is simple and also compatible with the existing system, is suggested, and its performance is evaluated. The control system of radiant floor heating should be easily adapted to thermal mass characteristics and building load variations without complication in real application. In this study, predictive control using the ANN (Artificial Neural Network) model is proposed and the possibility of this predictive control is investigated through experimental research. The results show that the performance of this predictive control is better than that of the current 2-position on/off control. Through the dynamic simulation analysis of the thermal mass model using a computer for the multi zones of a real apartment building, the adaptability of the predictive control to several load variations and thermal characteristics is evaluated.
Crew Factors in Flight Operations XII: A Survey of Sleep Quantity and Quality in On-Board Crew Rest Facilities

Many aircraft operated on long-haul commercial airline flights are equipped with on-board crew rest facilities, or bunks, to allow crewmembers to rest during the flight. The primary objectives of this study were to gather data on how the bunks were used, the quantity and quality of sleep obtained by flight crewmembers in the facilities, and the factors that affected their sleep. A retrospective survey comprising 54 questions of varied format addressed demographics, home sleep habits, and bunk sleep habits. Crewmembers from three airlines with long-haul fleets carrying augmented crews consisting of B747-100/200, B747-400, and MD-11 aircraft equipped with bunks returned a total of 1404 completed surveys (a 37% response rate). Crewmembers from the three carriers were comparable demographically, although one carrier had older, more experienced flight crewmembers. Each group, on average, rated themselves as "good" or "very good" sleepers at home, and all groups obtained about the same average amount of sleep each night. Most were able to sleep in the bunks, and about two thirds indicated that these rest opportunities benefited their subsequent flight deck alertness and performance. Comfort, environment, and physiology (e.g., being ready for sleep) were identified as factors that most promoted sleep. Factors cited as interfering with sleep included random noise, thoughts, heat, and the need to use the bathroom. These factors, in turn, suggest potential improvements to bunk facilities and their use. Ratings of the three aircraft types suggested differences among facilities. Bunks in the MD-11 were rated significantly better than either of the B747 types, and the B747-400 bunks received better ratings than did the older, B747-100/200 facilities.
Mediterranean climate change projections from CMIP 5 and CMIP 6

The Mediterranean has been identified as a climate change hotspot due to increased warming trends and precipitation decline. To estimate the impacts of the ongoing climate change on the region, projections of various CMIP5 and CMIP6 experiments and scenarios are compared. The changes in temperature and precipitation for the 21st century are studied under scenarios RCP2.6/SSP1-2.6, RCP4.5/SSP2-4.5 and RCP8.5/SSP5-8.5 as well as the high resolution HighResMIP experiments. Additionally, to give robust estimates of projected changes a model weighting scheme is applied, accounting for historical performance and inter-independence of the multi-member multi-model ensembles. Results indicate a significant and robust warming over the Mediterranean during the 21st century over all the ensembles and experiments. Nevertheless, the amplified Mediterranean warming with respect to the global average is only found for summer. Projected changes vary between CMIP5 and CMIP6, with the latter projecting a stronger warming. In contrast to temperature, precipitation changes show a higher level of uncertainty and spatial heterogeneity. However, for the high emission scenario, a robust decline in precipitation is projected for large parts of the region during summer. Results applying the model weighting scheme indicate reductions in CMIP6 and increases in CMIP5 warming trends, making the differences between the two ensembles smaller.
KEYWEXT: A Multilingual Keyword Extraction Service based on Word Embeddings

: Contextual Advertising utilizes the content a user is seeing to understand their interest in real-time to serve relevant advertising. A good representation of this context is the ﬁrst step to achieve a more precise selection of suitable ad-vertisements that is relevant to the content. We present the description of the SEEDTAG’s keywords extractor system demonstration: KEYWEXT. It uses state-of-the-art multilingual BERT-based positional embeddings to help contextualize advertising campaigns by retrieving those n − grams that best represent the content of the document. This leads to more relevant advertising while being respectful with the user.
Comparative study of autonomous path-following vehicle control via model predictive control and linear quadratic control

This paper describes a comparative study of steering and yaw moment control manoeuvres in the model predictive control and linear quadratic control approaches for path-following control of an autonomous vehicle. We present the effectiveness of the model predictive control and linear quadratic control approaches for stability control of the vehicle’s lateral position and yaw angle for different control manoeuvres: two-wheel steering, four-wheel steering and direct yaw moment control. We then propose model predictive control with a feedforward controller to minimize the tracking errors of the lateral position and the yaw angle in an active front steering manoeuvre, and these are compared with the results from linear quadratic control that has a feedforward controller. Model predictive control is designed on the basis of the simple yaw–lateral motions of a single-track vehicle with a linear tyre model (i.e. a bicycle model), which is an approximation of the more realistic model of a vehicle with double-track yaw–roll motion with a non-linear tyre model (i.e. the Pacejka model). The linear quadratic controller is designed on the basis of the same approach as adopted for the model predictive controller to achieve a fair comparison. On the basis of a given trajectory, we simulate the manoeuvre of the vehicle at a low speed, a middle speed and a high speed because load transfer effects will influence the roll dynamics especially at a high speed. We also perform simulations on low-road-friction surfaces in a double-lane-change scenario with the aim of following the desired trajectory as closely as possible while maintaining the vehicle stability. The simulation results show that model predictive control through two-wheel steering and four-wheel steering with direct yaw moment control performed better in terms of trajectory tracking at a high forward speed and low road surface variation. The proposed model predictive control with a feedforward controller is shown to be effective in minimizing the trajectory tracking errors. For all control manoeuvres, model predictive control gives a better tracking performance than linear quadratic control does. In addition, when the roll dynamics are considered, model predictive control significantly improves the vehicle stability and the trajectory along the desired path.
ANTIMICROBIAL ACTIVITY ASSAY BY TLC BIOAUTOGRAPHY OF ETHYL ACETATE EXTRACT FROM THE LEAVES OF WEDILIA TRILOBATAAGAINST PATHOGENIC BACTERIA

In present days, a search is going on for new antimicrobial agents due to the negative effects of existing antibiotics and the constant development of bacterial resistance. This study assessed the phyto chemical screening and antibacterial activities of methanol extract from the leaves of Wedilia trilobata. Methanol extract from the leaves of Wedilia trilobata has an antimicrobialactivities against 5 bacteria K. pneumoniae, E. coli, E. faecalis, S. aureus and P. Aeruginosa and it was investigated using a disc diffusion and minimum inhibitory concentration assay (MIC). Both disc diffusion and (MIC) of the extracts ranged from 5 to 20 μg/m. Results of phyto chemical screening of methanol extracts of W. trilobata showed the presence of tannins, flavonoids, terpenoids, alkaloid, poly phenols, saponins and cardiac glycosides absent. The total content of flavonoids and poly phenols in the www.ijcrt. org © 2021 IJCRT | Volume 9, Issue 6 June 2021 | ISSN: 2320-2882 IJCRT2106639 International Journal of Creative Research Thoughts (IJCRT) www.ijcrt. org f416 methanol extracts of the studied species positively correlated with their antioxidant properties . The study findings indicate that bioactive natural products from these plants may be isolated for further testing as leads in the development of new pharmaceuticals in food preservation as well as natural plant-based medicine.
Actively stabilised diode pumped Tm:YAlO laser

An actively stabilised, continuous-wave, 1.94 mum Tm:YAlO laser is presented. Optoelectronic negative feedback stabilisation is utilised to prevent relaxation-oscillation-driven spiking. The amplitude stability of the laser is found to be very robust against cavity perturbation and parasitic radiation back-reflection, making it attractive for practical applications.
MODIFICATION OF THE SSG/LRR-ω RSM FOR ADVERSE PRESSURE GRADIENTS USING TURBULENT BOUNDARY LAYER EXPERIMENTS AT HIGH Re

A modification of the SSG/LRR-ω model for turbulent boundary layers in adverse pressure gradient is presented. The modification is based on a new wall law for the mean velocity at adverse pressure gradient. The wall law is found from two new joint DLR/UniBw experiments and from the analysis of a data base from the literature. The mean velocity profile in the inner layer is found to consist of a log-law region, which is thinner than its zero pressure gradient counterpart, and a half-power law region above the log law. An empirical correlation for the wall-distance of the transition from the log-law to the half-power law is presented. Then a modification of the ω-equation to account for a half-power law behaviour of the mean velocity is described. The modified SSG/LRR-ω model is then applied to the two joint DLR/UniBw experiments. The modification leads to a reduction of the mean velocity in the inner part of the boundary layer and makes the model more susceptible for flow separation, which is in good agreement with the experimental data.