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This study intends to build smart water irrigation for rice farming using IoT and microcontroller devices with solar panel support. The system demonstrates the capabilities of automated irrigation by reducing physical labor through smart monitoring of the temperature, soil moisture, and humidity using multiple sensors. This study uses an agile methodology as it is suitable for reiterative operation for the development of the prototype. The mean result for the interpretation of data gathered for the systems' adaptability and flexibility is 4.32. The researchers were able to develop smart water irrigation for rice farming using IoT and microcontroller devices with solar panel support and the respondents also agreed that Smart water irrigation for rice farming using IoT and microcontroller devices with solar panel support is practical and valuable. A decision support system is recommended that can analyze data collected from IoT sensors and provide further recommendations. Based on the results, it is also suggested that future researchers use drip irrigation, instead of flood irrigation. Smart water irrigation has the potential to revolutionize agriculture, enhance environmental sustainability, and address pressing global challenges related to water resources and food security. These implications highlight the importance of continued research and innovation in this field., Comment: 14 pages, 5 figures, 1 table

As part of the federally-funded grant project "SLIDE: The School Librarian Investigation--Decline or Evolution?" this study analyzed the status of school librarian employment for almost 13,000 U.S public school districts from 2018-19 and 2020-21. The purpose of the study was to learn how the COVID-19 pandemic, which radically disrupted K-12 education, impacted the losses or gains of school librarian positions. The dataset utilized was the Common Core of Data annually collected by the National Center for Education Statistics (NCES) which consists of self-reported data from school districts. The report is based on data for public school districts in 46 states and the District of Columbia as data for California, Illinois, New York, and Utah were either unavailable or unusable for this analysis. Full-time equivalents (FTEs) of school librarian positions were compared to percentages and net numbers of district administrators, school administrators, teachers, and instructional coordinators. Additionally, other characteristics were studied--enrollment size, locale (city, suburb, town, rural), per pupil expenditures, majority race of students, and poverty based on the federal Free and Reduced-cost Meals Program--in relation to the losses or gains of school librarians. The results showed that between 2018-19 and 2020-21, the decrease in the total number of reported school librarians nationwide--more than 1,800 librarian FTEs--was about 800 FTEs greater than for the previous two-year interval. For districts in every enrollment range and every locale type, the percentage losing librarians exceeded the percentage gaining librarians. Inequities in access to school librarians most notably increased in lower-enrollment districts, those in rural areas, those serving more minority students, particularly Black students, and districts with more students living in poverty. Nationwide, school librarian FTEs decreased while other educator positions increased or remained relatively stable, suggesting that the loss of librarians may not merely be a matter of school funding. These data illustrate that, as the pandemic set in, staffing dollars were more likely to be targeted toward administrators than toward educators who have more direct contact with, and instruct, students--teachers and librarians. It is unknown whether these inequitable losses of school librarians are temporary or will become a post-COVID "new normal." [This report was co-prepared by Antioch University Seattle.]

This report was produced by "The School Librarian Investigation: Decline or Evolution?" (SLIDE), a research project funded by a Laura Bush 21st Century Librarian grant from the Institute for Museum and Library Services to Antioch University Seattle. It studied the employment status of school librarians in the United States from 2009-10 through 2018-19. The analysis examined data from all 50 states and D.C. as well as over 13,000 local school districts. The data are collected annually by the National Center for Education Statistics via its Common Core of Data program. The findings document an almost 20 percent loss of school librarians between 2010 and 2019, the most recent data available at the time. Further analysis uncovered gross inequities in access to school librarians across the U.S. Districts with more students living in poverty, more minority students, and more English language learners were less likely to have librarians than districts with fewer such students. Other notable findings: (1) Three out of 10 districts had no librarians in any of their schools; (2) More than 4.4 million students in high-poverty (50%+) districts had no librarians; (3) Almost 3.1 million students in predominantly Hispanic districts were without school librarians; (4) Almost 4.8 million students in predominantly non-white districts were without school librarians; (5) Smaller and rural districts were more likely to have no librarians than larger and suburban districts; and (6) Nine out of 10 charter school districts had no school librarians. The study questions the conventional wisdom that losses of school librarians are explained by school funding cuts. During the decade studied, employment for other types of educators increased--sometimes dramatically--while librarian employment alone declined steadily. Also, districts with the most librarians relative to schools were those that spent the most, and the least, per pupil. Stronger librarian staffing was also found in states that had staffing mandates, whether they were enforced or not, and in states that had more institutions of higher education preparing school librarians. These findings provide solid evidence of inequities nationally, by state, and based on characteristics of local districts and their student demographics. It also has implications for the future preparation of school librarians and for school districts attempting to improve educational equity for their K-12 students. [This report was co-prepared by Antioch University Seattle.]

Machine learning (ML) is a subfield of Artificial intelligence (AI), and its applications in radiology are growing at an ever-accelerating rate. The most studied ML application is the automated interpretation of images. However, natural language processing (NLP), which can be combined with ML for text interpretation tasks, also has many potential applications in radiology. One such application is automation of radiology protocolling, which involves interpreting a clinical radiology referral and selecting the appropriate imaging technique. It is an essential task which ensures that the correct imaging is performed. However, the time that a radiologist must dedicate to protocolling could otherwise be spent reporting, communicating with referrers, or teaching. To date, there have been few publications in which ML models were developed that use clinical text to automate protocol selection. This article reviews the existing literature in this field. A systematic assessment of the published models is performed with reference to best practices suggested by machine learning convention. Progress towards implementing automated protocolling in a clinical setting is discussed., Comment: 7 figures

We have studied the laser induced ultrafast quenching of Gd 4f magnetic order in ferrimagnetic Co100-xGdx alloys to highlight the role of the inter-atomic exchange coupling. We have taken advantage of the ultrashort soft X-ray pulses deliver by the femtoslicing beamline at the BESSY II synchrotron radiation source at the Helmholtz-Zentrum Berlin to perform element- and time-resolved X-ray Magnetic Circular Dichroism spectroscopy.Our results show that the laser induced quenching of Gd 4f magnetic order occurs on very different time-scales for the Co72Gd28, the Co77Gd23 and the Co79Gd21 alloys. Most of the magnetic moment losses occur within the first picosecond (ps) while the electron distribution is strongly out of equilibrium. After the equilibration of the electrons and lattice temperatures (t > 1 ps), the magnetic losses occur on slower rates that depend on the alloy composition: increasing the Co composition speeds up the demagnetization of Gd 4f sublattice. The strength of the inter-atomic exchange coupling which depends on composition, determines the efficiency of the angular momentum flow from the Gd 4f spin towards the lattice. Our results are in qualitative agreements with the predictions of the microscopic three temperatures model for ferrimagnetic alloys., Comment: 8 pages, 6 figures

A survey of all 50 states and District of Columbia was conducted in Fall 2020 to gain background information to inform an Institute of Museum and Library Services (IMLS) grant project called SLIDE: The School Librarian Investigation--Decline or Evolution? As part of the grant, a school library leader, some in a state government/agency position or in a state school library association, agreed to participate in the grant as a "State Intermediary" to help share project findings and assist with providing state-level information. The responses, collected via Survey Monkey, were gathered to provide context to the findings of the SLIDE study's analysis of the National Center for Education Statistics (NCES) library staffing data and to inform planned interviews of school district leaders who make staffing decisions. The project is directed by Debra E. Kachel with principal investigator Keith Curry Lance, administered through Antioch University Seattle. More information about the SLIDE project can be found at https://libslide.org.

Monolithic active pixel sensors (MAPS) are now well established as a technology for tracking charged particles, especially when low material budget is desirable. For such applications, sensors focus on spatial resolution and pixels with digital output or modest charge measurement ability are well suited. Within the European Union STRONG-2020 project, which focuses on experiments using hadrons, the TIIMM (Tracking and Ions Identifications with Minimal Material budget) joint research activity intends to expand granular MAPS capacity to energy-loss ({\Delta}E) measurement for ion species identification. The TIIMM prototypes are developed in the Tower Jazz 180 nm CMOS image sensor (CIS) process. The Time-Over-Threshold (ToT) method is applied to the sensor for the energy-loss measurement. The main design details and the preliminary test results from laboratory measurements of the initial TIIMM prototype are presented in this work., Comment: 4 pages

Objectives: To develop an image-based automatic deep learning method to classify cardiac MR images by sequence type and imaging plane for improved clinical post-processing efficiency. Methods: Multi-vendor cardiac MRI studies were retrospectively collected from 4 centres and 3 vendors. A two-head convolutional neural network ('CardiSort') was trained to classify 35 sequences by imaging sequence (n=17) and plane (n=10). Single vendor training (SVT) on single centre images (n=234 patients) and multi-vendor training (MVT) with multicentre images (n = 479 patients, 3 centres) was performed. Model accuracy was compared to manual ground truth labels by an expert radiologist on a hold-out test set for both SVT and MVT. External validation of MVT (MVTexternal) was performed on data from 3 previously unseen magnet systems from 2 vendors (n=80 patients). Results: High sequence and plane accuracies were observed for SVT (85.2% and 93.2% respectively), and MVT (96.5% and 98.1% respectively) on the hold-out test set. MVTexternal yielded sequence accuracy of 92.7% and plane accuracy of 93.0%. There was high accuracy for common sequences and conventional cardiac planes. Poor accuracy was observed for underrepresented classes and sequences where there was greater variability in acquisition parameters across centres, such as perfusion imaging. Conclusions: A deep learning network was developed on multivendor data to classify MRI studies into component sequences and planes, with external validation. With refinement, it has potential to improve workflow by enabling automated sequence selection, an important first step in completely automated post-processing pipelines., Comment: Published in European Radiology 2022

The evolution of chiral spin structures is studied in ferrimagnet Ta/Ir/Fe/GdFeCo/Pt multilayers as a function of temperature using scanning electron microscopy with polarization analysis (SEMPA). The GdFeCo ferrimagnet exhibits pure right-hand N\'eel-type domain wall (DW) spin textures over a large temperature range. This indicates the presence of a negative Dzyaloshinskii-Moriya interaction (DMI) that can originate from both the top Fe/Pt and the Co/Pt interfaces. From measurements of the DW width, as well as complementary magnetic characterization, the exchange stiffness as a function of temperature is ascertained. The exchange stiffness is surprisingly mostly constant, which is explained by theoretical predictions. Beyond single skyrmions, we find by direct imaging a pure N\'eel-type skyrmionium, which due to the absence of a skyrmion Hall angle is a promising topological spin structure to enable high impact potential applications in the next generation of spintronic devices.

We have investigated ultrafast quenching of the Tb4f magnetic order in Co74Tb26 alloys, induced by femtosecond hot-electrons pulses. The hot-electron pulses were produced in specific non-magnetic capping layers by infrared fs laser pulses. Our experimental results show that sub-picosecond dynamics of Tb4f magnetic moments can be induced by non-thermal and thermal hot-electrons. We further demonstrate that the demagnetization efficiencies of non-thermal and thermal hot electrons are similar. However, the characteristic demagnetization times show values of 0.35 ps for non-thermal hot-electrons excitations and 1.2 ps for thermal hot-electrons excitations. We explain this temporal elongation by the propagation time of thermal hot-electrons through the 15 nm thick CoTb film., Comment: 14 pages, 3 Figures and 1 Table

- Paper withdrawn by the author - CMOS Monolithic Active Pixel Sensors for charged particle tracking are considered as technology for numerous experiments in heavy ion and particle physics. To match the requirements for those applications in terms of tolerance to non-ionizing radiation, it is being tried to deplete the sensitive volume of the, traditionally non-depleted, silicon sensors. We study the feasibility of this approach for the common case that the collection diodes of the pixel are small as compared to the pixel pitch. An analytic equation predicting the thickness of the depletion depth and the capacity of this point-like junction is introduced. We find that the predictions of this equations differs qualitatively from the usual results for flat PN junctions and that $dC/dU$-measurements are not suited to measure the depletion depth of diodes with point-like geometry. The predictions of the equation is compared with measurements on the depletion depth of CMOS sensors, which were carried out with a novel measurement protocol. It is found that the equation and the measurement results match with each other. By comparing our findings with TCAD simulations, we find that precise simulation models matches the empirical findings while simplified models overestimate the depletion depth dramatically. A potential explanation for this finding is introduced and the consequences for the design of CMOS sensors are discussed., Comment: This paper has been withdrawn by the author due to a critial error an the analytical calculations of the depletion depth. The ansatz chosen by Michael Deveaux came out to be fundamentally wrong. The observations on TCAD and the method for measuring the depletion depth in CMOS sensors with tiny diodes seem not affected by the mistake

We present an extensive study of structure, composition, electronic and magnetic properties of Ce--Pt surface intermetallic phases on Pt(111) as a function of their thickness. The sequence of structural phases appearing in low energy electron diffraction (LEED) may invariably be attributed to a single underlying intermetallic atomic lattice. Findings from both microscopic and spectroscopic methods, respectively, prove compatible with CePt$_5$ formation when their characteristic probing depth is adequately taken into account. The intermetallic film thickness serves as an effective tuning parameter which brings about characteristic variations of the Cerium valence and related properties. Soft x-ray absorption (XAS) and magnetic circular dichroism (XMCD) prove well suited to trace the changing Ce valence and to assess relevant aspects of Kondo physics in the CePt$_5$ surface intermetallic. We find characteristic Kondo scales of the order of 10$^2$ K and evidence for considerable magnetic Kondo screening of the local Ce $4f$ moments. CePt$_5$/Pt(111) and related systems therefore appear to be promising candidates for further studies of low-dimensional Kondo lattices at surfaces., Comment: 14 pages, 11 figures

Non-linear magnetization dynamics is essential for the operation of many spintronics devices. For microwave assisted switching of magnetic elements the low field regime is of particular interest. In addition a large number of experiments uses high amplitude FMR in order to generate d.c. currents via spin pumping mechanism. Here we use time resolved X-ray magnetic circular dichroism experiments to determine the number density of excited magnons in magnetically soft Ni_80Fe_20 thin films at small bias fields and large rf-excitation amplitudes. Our data shows that the common model of non-linear ferromagnetic resonance is not suitable to describe the low bias field limit. Here we derive a new model of parametric spin-wave excitation which correctly predicts threshold amplitudes and decay rates also at low bias fields. In fact a new series of critical modes with amplitude phase oscillations is found, generalizing the theory of parametric spin-wave excitation.

Due to an error this article has been annouced as a new article instead of a corrected version of article 1010.1374., Comment: This paper has been withdrawn

We follow for the first time the evolution of the spin and orbital angular momentum of a thin Ni film during ultrafast demagnetization, by means of x-ray magnetic circular dichroism. Both components decrease with a 130 +/- 40 fs time constant upon excitation with a femtosecond laser pulse. Additional x-ray absorption measurements reveal an increase in the spin-orbit interaction by 6 +/- 2 % during this process. This is the experimental demonstration quantifying the importance of spin-orbit mediated processes during the demagnetization.

We investigated the recently found superconductor LaO_{1-x}F_xFeAs by X-ray absorption spectroscopy (XAS). From a comparison of the O K-edge with LDA calculations we find good agreement and are able to explain the structure and changes of the spectra with electron doping. An important result from this edge is a limitation of the Hubbard U to values not significantly larger than 1 eV. From experimental Fe L_2,3-edge spectra and charge transfer multiplet calculations we gain further information on important physical values such as hopping parameters, the charge transfer energy Delta, and the on-site Hubbard U. Furthermore we find the system to be very covalent with a large amount of ligand holes. A shift in the chemical potential is visible in the O K- and Fe L_2,3-edge spectra which emphasizes the importance of band effects in these compounds., Comment: 4 pages, 2 figures