Miracle-dz/UniFAR-FTUs huggingface dataset:
Navigating postgraduate research during the COVID-19 pandemic: A scoping review

Background The worldwide coronavirus disease 2019 (COVID-19) pandemic compelled higher education institutions and postgraduate students (master’s and PhD) to rethink their research designs, as alert level restrictions affected data collection. Objectives To identify and map out the breadth of evidence available on the challenges and opportunities for conducting postgraduate research during the COVID-19 pandemic. Method A scoping review was conducted in CINAHL, MEDLINE (EBSCO), SCOPUS and PubMed databases. The authors independently began by screening the titles, the abstracts and full texts. Duplications were removed during the title and abstract screening by exporting them into EndNote. Results The search identified 463 documents, and 12 were included in the final review. The documents were studies commentaries, letters (n = 1) from India and guidelines from countries across the globe. The common themes that were reported on the challenges of conducting postgraduate research were the inability to collect data, the digital divide and changes in study designs. Conclusion The review reports on the opportunities and challenges in conducting postgraduate research during the COVID-19 pandemic. Despite the limited evidence on the opportunities of conducting postgraduate research, most postgraduate research stalled because of COVID-19 restrictions. There is a need for more literature to explore further postgraduate research opportunities during COVID-19 and beyond. Contribution The focus on the challenges and opportunities in conducting postgraduate research during the COVID-19 pandemic may assist in the development of strategies needed to mitigate the effects of this and future pandemics.
A progression of pre-service teachers towards deep curricular knowledge (the Pieces model in Open Source Tutorials)

, we aim to equip our pre-service teachers (PSTs) with “curricular knowledge” about instructional materials, knowledge about the “theory” underlying the curriculum and the reasons behind particular choices such as conceptual flow, use of individual vs. group work, and so on. This study presents two case studies grounded in of our attempts to teach nuanced curricular knowledge about differences between two fairly similar sets of curricular modules. Our analysis centers on two Masters of Science (MS) students who had various experiences involving Open Source Tutorials (OSTs), guided worksheets developed by the University of Maryland. A theoretically nuanced (and hence deep) component of curricular knowledge regarding OSTs is that they are based upon the “Knowledge in Pieces” (in contrast to a “Misconceptions” or unspecified) model of student ideas. The Pieces model maintains that student ideas are not always robustly intact and inherently incorrect cognitive structures, but rather, that student ideas are often temporary coherences of thought assembled from finer-grained pieces of knowledge that can productively be drawn upon and refined in instruction. In our courses, PSTs read research literature about OSTs, conduct mock lessons using existing OSTs, improve existing OSTs, design and teach their own OSTs to real students, and reflect upon the process to further improve the curriculum. Our analysis focuses upon case studies of Brock and Saki, MS students at our institutions. In addition to one-on-one interviews with these PSTs, we will draw upon data from in-class observations and written coursework to discuss how PSTs progressed in their understanding of nuanced curricular knowledge about OSTs and
A Macroeconomic Perspective on Education and Inequality

Useiden taloustieteilijoiden seka politiikan tekijoiden esittaman vaitteen mukaan tehokkuutta ja tasa-arvoa ei voida sovittaa yhteen. Taloudellista tehokuutta on katsottu voitavan edistaa eriarvoisuutta kasvattamalla. Taman perinteisen nakemyksen keskeisin perustelu on ajatus, etta eriarvoisuuden lisays kasvattaa koulutuksen yksityisia seka yhteiskunnallisia tuottoja, ja lisaksi parantaa yksiloiden halua ponnistella elintasonsa hyvaksi. Markkinamekanismiin tukeutumalla voidaan saavuttaa koulutusinvestointien tehokas taso. Taman nakemyksen mukaan koulutuksen tukeminen tulonjakotarkoituksessa aiheuttaa vaaristymia ja nain ollen haittaa taloudellista tehokkuutta ja kasvua. Tama kirjoitus tarkastelee tata perinteista nakemysta sen tietamyksen valossa, jota viimeaikainen teoreettinen ja empiirinen tutkimus on aiheesta sanonut. Suppean katsauksen yleisjohtopaatos on, etta eriarvoisuuden ja talouskasvun valinen yhteys ei ole suinkaan selva. Epaselvyytta on myos taustalla olevista mekanismeista. Yksi asia on kuitenkin kiistaton. Tuore empiirinen todistusaineisto on kyseenalaistanut perinteisen nakemyksen, jonka mukaan eriarvoisuuden lisayksella on myonteinen vaikutus talouskasvuun ja etta koulutuksen julkisen tuen muodossa tapahtuvat tulonsiirrot haittaavat kasvua.
Characteristic Modes Analysis of Aperiodic Arrays Using Entire Domain Basis Function Method With Adaptive Cross Approximation Algorithm

The characteristic modes of the aperiodic arrays are analyzed by combining the entire domain basis function method with the adaptive cross approximation (ACA) algorithm. The array cells are identical. The entire domain basis functions defined on the array cells are obtained by analyzing the characteristic modes of the reference cell firstly. Then, the generalized eigenvalue equation whose size is smaller than the conventional one can be obtained. After solving the equation, the characteristic modes of the whole array can be analyzed. Calculation of the matrices is very time-consuming. To speed up the computation, the ACA algorithm is applied. Several numerical examples are performed. The accuracy and computational efficiency of the proposed technique are validated by simulation results.
Evaluation of Al-Ishaqi Irrigation Project: A Case Study Eastern Canal of the Project

An evaluation the performance of the irrigation system for the Al-Ishaqi irrigation project for the Eastern Canal was conducted to identify management strategies that can be used to improve the operation and performance of the irrigation system. The study area is located in Salah al-Din G.0overnorate, Iraq. The field work included determining the moisture content of the soil before and after irrigation, measuring the inflow of the field to find the depth of the applied water, field monitoring, and measuring the depth of the root zone for each irrigation process. Field measurements showed that the average efficiency of water application for the two fields (A, and B) are 59.81% and 38.6%, respectively. The results of the efficiency of water application showed that farmers use water more than the actual demand, so it was possible to increase the efficiency of field water use by controlling the quantities of water that supplied and controlling the irrigation time and water distribution within the irrigated land. The results also showed that the storage efficiency of the two fields (A, and B) ranged between (39.1% to 68.28%), and (41.80% to 79.8%), respectively. As for the efficiency of water distribution, the average distribution efficiency for fields (A) and (B) was about (99.54%) and (99.33%), respectively. The irrigation efficiency evaluation done in the Al-Ishaqi Irrigation Project revealed that farmers utilize more water than is required, resulting in a substantial amount of water being lost in the fields observed in this research owing to inefficient use. If the current scenario continues, groundwater levels would undoubtedly rise, putting the irrigation system's long-term viability in jeopardy.
Can Teacher Case Study Research be Participatory? Critical Reflections on the Approach Adopted for an English Language Teacher Expertise Study in India

C ase study research is a well-established, widely recognised methodology that enables us to understand phenomena of interest in social sciences through a range of data collection means, often com-bined (Flyvbjerg, 2011). 1 As such, it is recognised by scholars working across the paradigm continuum – from interpretivist (e.g
Regulating the p53 Tumor Suppressor Network at PML Biomolecular Condensates

Simple Summary The cell nucleus is organized into different sub-nuclear compartments to control specific cellular processes, including PML nuclear bodies (NBs), also termed PML biomolecular condensates. PML-NBs form multi-protein complexes that are highly responsive to cellular stress, and regulate cell fate decisions in response to genome damage. By concentrating proteins that directly control the activity of the tumor suppressor p53, PML biocondensates guide the cellular response either towards induction of cell death or senescence through altering p53 modifications. In this review, we discuss the molecular mechanisms controlling PML condensate formation, and how they impact the regulation of p53 activity, and propose a list of promising candidate proteins that may contribute to the regulation of p53 at PML biomolecular condensates. Abstract By forming specific functional entities, nuclear biomolecular condensates play an important function in guiding biological processes. PML biomolecular condensates, also known as PML nuclear bodies (NBs), are macro-molecular sub-nuclear organelles involved in central biological processes, including anti-viral response and cell fate control upon genotoxic stress. PML condensate formation is stimulated upon cellular stress, and relies on protein–protein interactions establishing a PML protein meshwork capable of recruiting the tumor suppressor p53, along with numerous modifiers of p53, thus balancing p53 posttranslational modifications and activity. This stress-regulated process appears to be controlled by liquid–liquid phase separation (LLPS), which may facilitate regulated protein-unmixing of p53 and its regulators into PML nuclear condensates. In this review, we summarize and discuss the molecular mechanisms underlying PML nuclear condensate formation, and how these impact the biological function of p53 in driving the cell death and senescence responses. In addition, by using an in silico approach, we identify 299 proteins which share PML and p53 as binding partners, thus representing novel candidate proteins controlling p53 function and cell fate decision-making at the level of PML nuclear biocondensates.
Vibration based fault diagnostics in a wind turbine planetary gearbox using machine learning

To reduce wind turbine operations and maintenance costs, we present a machine learning framework for early damage detection in gearboxes based on the cyclostationary and kurtogram analysis of sensor data. The application focus is fault diagnostics in gearboxes under varying load conditions, particularly turbulent wind. Faults in the gearbox rotating components can leave their signatures in vibrations signals measured by accelerometers. We analyze data stemming from a simulated vibration response of a 5 MW multibody wind turbine model in a healthy and damaged scenarios and under different wind conditions. With cyclostationary and kurtogram analysis applied on acquired sensor data, we generate two types of 2D maps that highlight signatures related to the fault damage. Using these maps, convolutional neural networks are trained to identify faults, including those of small magnitude, in test data with a high accuracy. Benchmark test cases inspired by an NREL study are tested and faults successfully detected.
Conditional instability of the first kind upside-down. [in stratocumulus clouds]

Abstract It is shown that entrainment leads to the generation of turbulence kinetic energy in a stratocumulus layer when the virtual temperature jump at the cloud top is weaker than a critical value. The critical value increases as the relative humidity of the air above cloud top decreases. This result is interpreted as a criterion for the instability of the layer cloud to penetrative downdrafts. The role of the instability in determining the subtropical and tropical distributions of boundary-layer cloudiness is assessed.
Hmo1 Protein Affects the Nucleosome Structure and Supports the Nucleosome Reorganization Activity of Yeast FACT

Yeast Hmo1 is a high mobility group B (HMGB) protein that participates in the transcription of ribosomal protein genes and rDNA, and also stimulates the activities of some ATP-dependent remodelers. Hmo1 binds both DNA and nucleosomes and has been proposed to be a functional yeast analog of mammalian linker histones. We used EMSA and single particle Förster resonance energy transfer (spFRET) microscopy to characterize the effects of Hmo1 on nucleosomes alone and with the histone chaperone FACT. Hmo1 induced a significant increase in the distance between the DNA gyres across the nucleosomal core, and also caused the separation of linker segments. This was opposite to the effect of the linker histone H1, which enhanced the proximity of linkers. Similar to Nhp6, another HMGB factor, Hmo1, was able to support large-scale, ATP-independent, reversible unfolding of nucleosomes by FACT in the spFRET assay and partially support FACT function in vivo. However, unlike Hmo1, Nhp6 alone does not affect nucleosome structure. These results suggest physiological roles for Hmo1 that are distinct from Nhp6 and possibly from other HMGB factors and linker histones, such as H1.
Internet of things implementation and analysis of fuzzy Tsukamoto in prototype irrigation of rice

This research raises the topic of modern technology in the field of rice fields. The problem in this research is determining the fuzzy inference system algorithm for electronic engineering. The prototype was built by Raspberry Pi and python-based to the internet of things. The objective of this research is to design a new model for the rice field monitoring/control system and display every condition based on the internet of things. So that the hypothesis of this research can answer the phenomena that occur in rice fields, including drought problems, maintained plant conditions. The test results showed that irrigation control automatically runs optimally by scheduling, automatic irrigation control of water pH degree value detection analyzed by fuzzy Tsukamoto method at Z=3.5 defuzzification value for low and high irrigation control, and Z value=1.83 for normal irrigation control. Furthermore, the scheduling of spraying liquid fertilizer obtained the results of duration for 60 min in accordance with the needs of fertilizer dose. Lastly, for monitoring data on the website successfully accessed anywhere from the use of hosting servers and domains. Finally, it can be concluded that fuzzy Tsukamoto's algorithm is appropriate to be applied to the modern rice field system.
Leveraging Spatial Patterns in Precipitation Forecasts Using Deep Learning to Support Regional Water Management

Short‐term precipitation forecasts are critical to regional water management, particularly in the Western U.S. where atmospheric rivers can be predicted reliably days in advance. However, spatial error in these forecasts may reduce their utility when the costs of false positives and negatives differ greatly. Here we investigate whether deep learning methods can leverage spatial patterns in precipitation forecasts to (a) improve the skill of predicting the occurrence of precipitation events at lead times from 1 to 14 days, and (b) balance the tradeoff between the rate of false negatives and false positives by modifying the discrimination threshold of the classifiers. This approach is demonstrated for the Sacramento River Basin, California, using the Global Ensemble Forecast System (GEFS) v2 precipitation fields as input to convolutional neural network (CNN) and multi‐layer perceptron models. Results show that the deep learning models do not significantly improve the overall skill (F1 score) relative to the ensemble mean GEFS forecast with bias‐corrected threshold. However, additional analysis of the CNN models suggests they often correct missed predictions from GEFS by compensating for spatial error at longer lead times. Additionally, the deep learning models provide the ability to adjust the rate of false positives and negatives based on the ratio of costs. Finally, analysis of the network activations (saliency) indicates spatial patterns consistent with physical understanding of atmospheric river events in this region, lending additional confidence in the ability of the method to support water management applications.
Modeling Real-World Affective and Communicative Nonverbal Vocalizations From Minimally Speaking Individuals

Nonverbal vocalizations from non- and minimally speaking individuals who speak fewer than 20 words (mv* individuals) convey important communicative and affective information. While nonverbal vocalizations that occur amidst typical speech and infant vocalizations have been studied extensively in the literature, there is limited prior work on vocalizations by mv* individuals. Our work is among the first studies of the communicative and affective information expressed in nonverbal vocalizations by mv* children and adults. We collected labeled vocalizations in real-world settings with eight mv* communicators, with communicative and affective labels provided in-the-moment by a close family member. Using evaluation strategies suitable for messy, real-world data, we show that nonverbal vocalizations can be classified by function (with 4- and 5-way classifications) with F1 scores above chance for all participants. We analyze labeling and data collection practices for each participating family, and discuss the classification results in the context of our novel real-world data collection protocol. The presented work includes results from the largest classification experiments with nonverbal vocalizations from mv* communicators to date.
The form of solutions and periodicity for some systems of third‐order rational difference equations

In this paper, we deal with the system that has solutions and the periodicity character of the following systems of rational difference equations with order three xn+1=yn−1yn−2xn±1±yn−1yn−2,yn+1=xn−1xn−2yn±1±xn−1xn−2, with initial conditions x−2,x−1,x0,y−2,y−1, and y0 that are arbitrary nonzero real numbers. Some numerical examples will be given to illustrate our results. Copyright © 2015 John Wiley & Sons, Ltd.
Epitaxially lifted-off GaAs MESFETs on InP for optoelectronic integration

Epitaxial lift-off (ELO) is a technique by which epitaxially grown layers are lifted off their growth substrate and subsequently reattached to a new one. The preprocessing approach where ELO devices and circuits on the host are fabricated before transplantation offers the advantages that (a) fully optimized devices provided by a foundry service can be combined, (b) the devices can be tested prior to transplantation, and (c) the final result is a monolithic integration. The authors present results on the transplantation of foundry MESFETs to InP, and compare their behavior and the extracted parameters for a nonlinear MESFET-model before and after transfer. <<ETX>>
Secure Content Delivery for Connected and Autonomous Trucks: A Coalition Formation Game Approach

With the ever-increasing demand for the content delivery services in autonomous vehicular networks (AVNs), caching popular contents in the edge nodes in advance is expected to reduce the transmission delay. Current works on the contents cached in connected and autonomous vehicles (CAVs) or roadside units (RSUs) are facing the problems of limited caching size and high deployment cost. In this paper, by exploiting the advantages of high caching space and flexibility of truck platoons composed of connected and autonomous trucks (CATs), we propose a secure content delivery service for CATs based on coalition formation game. Firstly, in order to protect the security and privacy of content delivery services, a differential privacy model is proposed to protect the sensitive information of CATs. Meanwhile, the differential privacy model is combined with the incentive based trust evaluation model to monitor the behaviors of CATs. In the incentive based models, CATs are encouraged to improve their trust values to obtain higher utilities and find a balance between confidence levels and utilities. Moreover, a coalition formation game is established among CATs with the same driving route, in which all CATs can maximize their utilities with the formation of several minor coalitions. Finally, we conduct extensive simulations to demonstrate the effectiveness and superiority of the proposed scheme.
Social capital and patients’ mobility in Italy

ABSTRACT Using a 10-year (2006–15) regional dataset on hospital discharges, we estimate the determinants of Italian regional outflow rates while also including three proxies for social capital: the quality of friendships, the involvement in social activities and the ratio of blood donors to the population. We find a significant push effect from the lack of social capital intended as generalized expectation of cooperative behaviour (proxied by blood donors); this does not hold true for the other two proxies of social capital. The lack of a cultural context where norms of reciprocity matter may reduce regions’ ability to retain their patients.
Suppressing vibration of structures using nonlinear single unit impact dampers via Taguchi method

This paper investigates a vibratory system that employs Hertzian contact theory in terms of free vibration. Nonlinear impact dampers are created by using a spring, mass, and viscous damper model. The model is simulated in MATLAB software using the DAS method as a proper simulation framework. The Taguchi method is used to examine the efficacy of impact dampers for controlling structural vibrations of the structure. It is demonstrated that the optimal factors obtained can effectively suppress the structure’s unwanted vibrations. The analysis of variance is also used to indicate the most influential factor of dampers to demonstrate their ability to quench vibrations.
Physics in a general length space-time geometry: Call for experimental revision of the light speed anisotropy

We present a phenomenological model for the nature in the Finsler and Randers space-time geometries. We show that the parity-odd light speed anisotropy perpendicular to the gravitational equipotential surfaces encodes the deviation from the Riemann geometry toward the Randers geometry. We utilize an asymmetrical ring resonator and propose a setup in order to directly measure this deviation. We address the constraints that the current technology will impose on the deviation should the anisotropy be measured on the Earth surface and the orbits of artificial satellites.
UTILIZATION OF MOLECULAR MARKER TECHNOLOGY IN FOXTAIL MILLET (Setaria italica (L.) P. Beauv.) BREEDING IN INDONESIA

Efforts to increase the productivity and quality of foxtail millet (Setaria italica (L.) P.Beauv. ) to supporting domestic food diversification in Indonesia can be done through plant breeding programs by assembling superior varieties. The effort to obtain superior millet varieties that are specific in accordance with farmer wishes, requires the availability of informative germplasm, which is delivered through characterization activities. The use of molecular markers is a method that now has been proven to help accelerate the introgression of major genes into elite cultivars. The use of molecular markers as a plant selection tool has been carried out with greater accuracy. Selection with molecular markers is only based on plant genetic traits and is not influenced by environmental factors, so the results are more accurate than selection based on morphology. Molecular tests have vary in the way they are implemented to obtain data, both the technique and the desired level of target data, according to the ease of implementation, availability of human resources, facilities and funds of money. The molecular markers that have been used for plant breeding of foxtail millet are RFLP, AFLP, RAPD, Transposon, SSR-Microsatelite, and ISSR.