Miracle-dz/UniFAR-FTUs huggingface dataset:
Insights for the Partitioning of Ecosystem Evaporation and Transpiration in Short‐Statured Croplands

Reducing water losses in agriculture needs a solid understanding of when evaporation (E) losses occur and how much water is used through crop transpiration (T). Partitioning ecosystem T is however challenging, and even more so when it comes to short‐statured crops, where many standard methods lead to inaccurate measurements. In this study, we combined biometeorological measurements with a Soil‐Plant‐Atmosphere Crop (SPA‐Crop) model to estimate T and E at a Swiss cropland over two crop seasons with winter cereals. We compared our results with two data‐driven approaches: The Transpiration Estimation Algorithm (TEA) and the underlying Water Use Efficiency (uWUE). Despite large differences in the productivity of both years, the T to evapotranspiration (ET) ratio had relatively similar seasonal and diurnal dynamics, and averaged to 0.72 and 0.73. Our measurements combined with a SPA‐Crop model provided T estimates similar to the TEA method, while the uWUE method produced systematically lower T even when the soil and leaves were dry. T was strongly related to the leaf area index, but additionally varied due to climatic conditions. The most important climatic drivers controlling T were found to be the photosynthetic photon flux density (R2 = 0.84 and 0.87), and vapor pressure deficit (R2 = 0.86 and 0.70). Our results suggest that site‐specific studies can help establish T/ET ratios, as well as identify dominant climatic drivers, which could then be used to partition T from reliable ET measurements. Moreover, our results suggest that the TEA method is a suitable tool for ET partitioning in short‐statured croplands.
Human Responses to the Thermal Comfort in Air-Conditioned Building: A Climate Chamber Study

One of the challenges for engineers in designing comfort indoor environments is merging the need of energy savings and thermal comfort of the occupants. However, to assess complex heterogeneous environments created by novel building systems, there is a need for choosing more sophisticated and precise tools. There are many best ways to evaluate thermal comfort, at the same time the most cost and time-consuming one, various modelling tools are widely used. In this paper, we present a human climate chamber as a methodology for indoor environmental research, to predict the thermal comfort. Along with presenting this methodology, the human climate chamber was demonstrated on ﬁve supply temperature representing the indoor environment such as conditions for which thermal sensation was predicted with satisfactory accuracy. Based on the presented results, the overall thermal sensation on the body will be influenced mainly by those body segments that have a greatest thermal sensation under different condition's environment (supply temperature). The overall thermal comfort will follow the warmest environment (26 oC and 29 oC) and the coldest in a cool environment (19 oC and 23 oC). Furthermore, the overall thermal comfort will closely follow the parts of the body that feel the most uncomfortable in a cool or warm environment. The study found that supply temperature at the 23 oC indicates that the PMV is comfortable. The value of PMV in a supply temperature set at 23 oC is 0.26. This study contributes to the body knowledge of thermal comfort towards human in the building.
Screen-printed capacitive pressure sensors with high sensitivity and accuracy on flexible substrates

Printable elastic conductors promise large-area stretchable sensor/actuator networks for healthcare, wearables and robotics, among other areas. Force pressure sensors are one of their most attractive applications, although their large-area integration has been limited by difficulties in their processability or bendability and their use by their insufficient sensitivity or stability. In this work, we present a flexible screen-printed capacitive pressure sensor, able to be modularly integrated in large-area systems thanks to the substrate flexibility, bending within itself capability and not only at its intersections, and cuttability, allowing a range of modifications in size and shape for complex structures. We built the sensors with a microstructured dielectric, whose hill radii were tuned (between 125 and 375 µm) until obtaining a measurement range of five orders of magnitude, with a logarithm sensitivity above 20% dB−1 at the maximum pressure peak of 750 kPa and of 80% kPa−1 at the lowest test value of 0.5 kPa. These results went along completely with the theoretical model that we also developed. Besides, while smaller pillars showed a significant hysteresis for decreasing pressures, we observed how large hills performed with a small hysteresis of down to 3%, way ahead of the published sensors to the best of our knowledge.
Comparison of generator topologies for direct-drive wind turbines including structural mass

In direct-drive wind turbines, the generator outer diameter and cost must be reduced substantially to allow a higher penetration of direct-drive wind-turbines on the market. In this paper, different generator topologies are investigated. A comparison is carried out, on the basis of 60 different machine prototypes built or designed by numerous authors. Data for those machines is found in the scientific literature. The comparison is based on torque density and cost/torque. Only the machines active material is considered.
PICU Survivorship: Factors Affecting Feasibility and Cohort Retention in a Long-Term Outcomes Study

Our understanding of longitudinal outcomes of Pediatric Intensive Care Unit (PICU) survivors is limited by the heterogeneity of follow-up intervals, populations, and outcomes assessed. We sought to demonstrate (1) the feasibility of longitudinal multidimensional outcome assessment and (2) methods to promote cohort retention. The objective of this presented study was to provide details of follow-up methodology in a PICU survivor cohort and not to present the outcomes at long-term follow-up for this cohort. We enrolled 152 children aged 0 to 17 years admitted to the PICU in a prospective longitudinal cohort study. We examined resource utilization, family impact of critical illness, and neurodevelopment using the PICU Outcomes Portfolio (POP) Survey which included a study-specific survey and validated tools: 1. Functional Status Scale, 2. Pediatric Evaluation of Disability Inventory Computer Adaptive Test, 3. Pediatric Quality of Life Inventory, 4. Strengths and Difficulties Questionnaire, and 5. Vanderbilt Assessment Scales for Attention Deficit-Hyperactivity Disorder. POP Survey completion rates were 89%, 78%, and 84% at 1, 3, and 6 months. Follow-up rates at 1, 2, and 3 years were 80%, 55%, and 43%. Implementing a longitudinal multidimensional outcome portfolio for PICU survivors is feasible within an urban, tertiary-care, academic hospital. Our attrition after one year demonstrates the long-term follow-up challenges in this population. Our findings inform ongoing efforts to implement core outcome sets after pediatric critical illness.
Hybrid Optimization-Based Structural Design of Deep Q Network With Feature Selection Algorithm for Medical Data Classification

In the area of medical informatics, the medical data classification is considered a complicated job. However, accurate classification of medical data is a complex task. Therefore, a robust and effective hybrid optimization-based deep learning method for classifying the medical data is developed in this research. The input data is pre-processed using data normalization method. Then, the features are selected using the proposed Henry Sea Lion Optimization (HSLnO), which is the combination of Henry Gas Solubility Optimization (HGSO), and Sea Lion Optimization (SLnO). The classification process is achieved using a optimized Deep Q Network (DQN). The DQN is optimized using the proposed Shuffled Shepherd Whale optimization Algorithm (SSWOA). The proposed SSWOA is developed by the integration of the Shuffled Shepherd Optimization Algorithm (SSOA), and Whale Optimization Algorithm (WOA). The developed technique achieves better performance of testing accuracy, sensitivity, and specificity with values of 95.413%, 95.645%, and 95.364%, respectively.
SPARSE DATA CLASSIFIER BASED ON FIRST-PAST-THE-POST VOTING SYSTEM

A point of interest (POI) is a general term for objects that describe places from the real world. The concept of POI matching (i.e., determining whether two sets of attributes represent the same location) is not a trivial challenge due to the large variety of data sources. The representations of POIs may vary depending on the basis of how they are stored. A manual comparison of objects is not achievable in real time; therefore, there are multiple solutions for automatic merging. However, there is no yet the efficient solution solves the missing of the attributes. In this paper, we propose a multi-layered hybrid classifier that is composed of machine-learning and deep-learning techniques and supported by a first-past-the-post voting system. We examined different weights for the constituencies that were taken into consideration during a majority (or super-majority) decision. As a result, we achieved slightly higher accuracy than the best current model (random forest), which also is based on voting.
Nutritional Support with Omega-3 Fatty Acids in Burn Patients: A Systematic Review with Meta-Analysis of Randomized Controlled Trials

Background: In burn patients, the profound effect of nutritional support on improved wound healing and a reduced rate of hospitalization and mortality has been documented. Fish oil as a primary source of omega-3 fatty acids in nutritional support may attenuate the inflammatory response and enhance immune function; however, unclear effects on the improvement of clinical outcomes in burn patients remain. Methods: The systematic literature review was conducted by searching the electronic databases: Cochrane Library, PubMed, ScienceDirect, and Scopus to assess the randomized controlled trials of nutritional support with omega-3 fatty acids compared to control diets in patients that presented with burns from any causes. Results: Seven trials were included in this meta-analysis. We found no significant differences in length of stay (LOS) (p = 0.59), mortality (p = 0.86), ventilation days (p = 0.16), gastrointestinal complications—e.g., constipation and diarrhea (p = 0.73)—or infectious complications—e.g., pneumonia and sepsis (p = 0.22)—between the omega-3-fatty-acid-receiving group and the control/other diets group. Conclusions: We did not find a benefit of omega-3 support in reducing the various complications, mortality and LOS in burn patients. Further studies are necessary to find the effect of nutritional support with omega-3 fatty acids over low-fat diets in this population.
Algorithm of probabilistic assessment of fully-mechanized longwall downtime

The problem of increasing the load on a long fully-mechanized longwall has several aspects, one of which is the improvement of efficiency in using available stoping equipment due to the increase in coefficient of the machine operating time of a shearer and other mining machines that form an integral part of the longwall set of equipment. The task of predicting the reliability indicators of stoping equipment is solved by the statistical evaluation of parameters of downtime exponential distribution and failure recovery. It is more difficult to solve the problems of downtime accounting in case of accidents in the face workings and, despite the statistical data on accidents in mine workings, no solution has been found to date. The authors have proposed a variant of probability assessment of workings caving using Poisson distribution and the duration of their restoration using normal distribution. The above results confirm the possibility of implementing the approach proposed by the authors.
THE IMPACT OF COMPUTERIZED EXAM FEATURES, EFFECTIVE EXAM IMPLEMENTATION, TOWARD STUDENT SATISFACTION

This paper intends to examine in detail the relationship between computerized exam features and effective exam implementation toward student satisfaction. The main goal is to examine the synergistic relationships which impacting student satisfaction after they using a computerized standardization exam in the college setting. Design/methodology/approach –an initial exploratory analysis was conducted methodically to confirm the proposed model through a structural equation modeling approach. The computerized exam features (especially, clear wording instruction and exam rulebook) had high effects on student satisfaction. Secondly, Effective Exam implementation (especially, efficient effort, time and cost) also impacted student satisfaction. Thirdly, the statistical testing result confirmed a joint impact of computerized exam features and effective exam implementation toward student satisfaction. The conceptual model has been validated to understand the role of both variables toward student satisfaction. However, there is lack of empirical validation and generalization of the model into wider scope due to limited time of research and a small number of the participant which suggest future research.
The Architects and Architecture of Knowledge: The Formation and Circulation of Social Identities in Higher Education Research

In this dissertation, I explore the construction and reproduction of social identities (race, ethnicity, sexual orientation, and gender identity) in educational policy and research. Framed through a Foucauldian genealogy of knowledge-making practices, I focus on the discourses of social identities embedded in the (re)production of data in educational research. Drawing from sociohistorical methods and bibliometrics, I examine three distinct, yet interrelated, domains. First, I explore the construction of datasets used in postsecondary research, including a federal dataset (the Integrated Postsecondary Education Data System) and a private nationally-representative survey of students (The Freshman Survey). Secondly, I consider the uses of data emerging from these databases by examining 21,069 peer-reviewed articles published in eleven journals of educational research. Lastly, I examine the discursive practices of of social identities in the context of a specific postsecondary institution (East University, a pseudonym), where I connect administrators’ perspectives on demographic data collection practices with emerging federal standards. Findings suggest that there is a need for increased critical data literacy to understand the points of convergence between the conceptual framing of race/ethnicity and sexual orientation/gender identity. I suggest a need for more coalitional politics in the production of educational research as a strategy to enhance how social identities are understood in contemporary educational research. Degree Type Dissertation Degree Name Doctor of Philosophy (PhD) Graduate Group Education This dissertation is available at ScholarlyCommons: https://repository.upenn. edu/edissertations/2205 First Advisor Marybeth Gasman
USAARL NUH-60FS Acoustic Characterization

Abstract : The United States Army Aeromedical Research Laboratory (USAARL) Auditory Protection and Performance Division (APPD) previously acoustically characterized the Black Hawk flight simulator (NUH-60FS). Since that characterization, the NUH-60FS underwent upgrades and modifications, leading to the possibility that the previous characterization may no longer be accurate. Measurements of the NUH-60FS examined the base speakers and higher-level speakers at five different noise-level settings. The base speakers yielded lower levels across the third octave band levels from 31.5 Hertz (Hz) to 8000 Hz, while the higher-level speakers had some levels lower and some levels higher. For the pilot seats, research participants should wear hearing protection for levels greater than one with the base speakers and for all levels with the higher-level speakers while the flight simulator is in operation. For the two rear positions, the levels change to greater than three for the base speakers and greater than one for higher-level speakers.
A Novel Discontinuous Modulation Strategy With Reduced Common-Mode Voltage and Removed DC Offset on Neutral-Point Voltage for Neutral-Point-Clamped Three-Level Converter

In this paper, a novel discontinuous pulsewidth modulation (DPWM) modulation strategy for a neutral-point-clamped (NPC) three-level converter (TLC) is proposed to reduce the switching loss, reduce common-mode voltage (CMV), and remove dc offset from the neutral-point (NP) voltage simultaneously, which is named as RCMV_DPWM. Based on the space vector diagram with reduced CMV, all clamping modes under RCMV_DPWM are revealed. Then, the NP voltage is controlled by selecting proper clamping mode. The realization of RCMV_DPWM is also discussed. Moreover, the performances of RCMV_DPWM are analyzed and compared with other PWM strategies in term of the NP voltage ripple, switching loss, and waveform quality. Finally, the feasibility and superiority of RCMV_DPWM are verified by experiments.
Stop and Think! Exploring the Role of News Truth Discernment, Information Literacy, and Impulsivity in the Effect of Critical Thinking Recommendations on Trust in Fake Covid-19 News

Covid-19-related fake news widely circulates on social media. This is problematic as people commonly do not process information on social media in a very critical manner. Also, when people encounter particular online content several times this tends to increase the content’s trustworthiness, sometimes irrespective of the accuracy of the provided information. Our study aims to explore whether, how, and for whom a simple critical thinking recommendation added to a social media newsfeed can aid people to better discern true news from fake news and reduce their trust in fake news. In an online experiment, 220 participants were exposed to a Twitter newsfeed with true and fake Covid-19-related news messages, either with or without critical thinking recommendations. The findings showed that participants who were exposed to the recommendations showed less trust in fake news messages, which was mediated by an increased accuracy in news truth discernment. Results showed no significant moderating effects of information literacy and impulsivity characteristics. Overall, the findings of this study are promising as this scalable, low-cost intervention might potentially help combat the effects of fake news on social media.
Comparison between t-SNE and cosine similarity for LIGO glitches analysis

The first direct detection of gravitational waves brought not just another proof of Einstein’s theory of general relativity but also different questions about the discovery, and new branches of scientific studies have arisen. The Advanced Laser Interferometer Gravitational-Wave Observatory (LIGO), the experiment that performed such detections, has two observatories, one in Hanford-WA and another in Livingston-LA, and operates as a Michelson–Morley interferometer with 4 km-long arms. Each observatory can measure variations in its arm lengths which are 10 000 times smaller than a proton diameter. Because LIGO has such a high sensitivity to length changes, many noise sources such as environmental effects, instrumental misbehavior, and human activities may also interfere. Studying these local intrusions, which we generically call glitches, remains a big challenge for LIGO Scientific Collaboration since they can mimic gravitational waves, polluting the data and decreasing the statistical significance of a signal. This paper compares two methods of glitch classification for nine classes by using glitchgrams. A glitchgram is constructed using only Omicron triggers and represents an event in the time, frequency, and signal-to-noise ratio space. The first method uses the cosine similarity, and the second uses support vector machine (SVM) from an application of t-distributed stochastic neighbor embedding, an unsupervised machine learning technique. The results from each method are compared with Gravity Spy classifications.
Distributional Policies and Social Cohesion in a High-Unemployment Setting

The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent.
Wordle for Central Bankers: Separating Impact of Words and Actions Under High Inflation– The Case of Turkey

ABSTRACT This paper investigates the effectiveness of monetary policy in Turkey, i.e. a developing country with high inflation, through its impact on the local currency denominated sovereign yield curve. Employing a two-factor, market-based methodology and introducing a new dataset, the study calculates the surprise factor for both actions (monetary policy surprise) and words (communication surprise). Checking their impacts separately, the study finds evidence that the communication provided by the Central Bank of Turkey through Monetary Policy Committee Statements help to extend the impact of the monetary policy to the long end of the yield curve, even during periods of high inflation.
Control Techniques for Grid Forming Inverters: A Comparative Analysis

As renewable power generation is increasingly integrated with the grid, challenges arising from the removal of synchronous generation are being highlighted in research and in practice. The reduction of grid inertia due to large scale integration of inverter-based resources (IBR) has impacts on system strength and grid stability during transient events. Grid-Forming (GFM) inverters are gaining popularity for their ability to replicate the dynamics of synchronous generation. Serving as a voltage source coupled through a reactance, GFM inverters can regulate the voltage and frequency in a similar fashion to a bulk synchronous generator and are able to complete black start operations as well as operate independently, setting the grid frequency and voltage. There are several GFM control methods, three of which are implemented and analysed in this paper; droop control, dispatchable virtual oscillator (dVOC) and matching control. The MATLAB simulation results of each control method under steady state, and dynamic conditions under grid disturbances and faults in the DC and AC side of the converter is presented together with their comparative analysis.