Miracle-dz/UniFAR-FTUs huggingface dataset:
Erratum: “Post-T Tauri Stars in the Nearest OB Association” (AJ, 124, 1670 [2002])

A few typos in Mamajek, Meyer, & Liebert (2002, AJ, 124, 1670) have been corrected in this erratum (including two stellar misidentifications and an incorrect power in the units of a slope). The most significant is the correction of a sign error in the published polynomial conversion between Tycho and Johnson-Cousins (B-V) colors.
Hour-Ahead Optimization Strategy for Shared Energy Storage of Renewable Energy Power Stations to Provide Frequency Regulation Service

With the rapid growth of intermittent renewable energy sources, it is critical to ensure that renewable power generators have the capability to perform primary frequency response (PFR). This paper proposes a framework for using a shared battery energy storage system (BESS) to undertake the PFR obligations for multiple wind and photovoltaic (PV) power plants and provide commercial automatic generation control (AGC) service in the ancillary service market at the same time. Furthermore, an optimal bidding strategy in the hour-ahead energy and ancillary service markets is proposed to maximize the BESS' benefits, considering frequency regulation performance, battery degradation cost, and the state of charge (SoC) limits. The optimization model is first built as a chance-constrained optimization problem and then transformed into mixed-integer quadratically constrained programming using Wasserstein metric-based distributionally robust optimization technique. Simulation results show that the proposed optimal bidding strategy and solution method can effectively take advantage of a BESS to perform PFR and provide AGC services simultaneously and improve its economic benefits.
Competition, Integration, or Complementation? Exploring Dock-Based Bike-Sharing in New York City

The bike-sharing system has advanced urban transportation by solving “the last mile problem,” enabling riders to better connect to public transit. There has been a paucity of knowledge, however, regarding the relationship between bike-sharing and public transit. In this article, we solicit one year of bike trip data comprising approximately 17 million trips from Citi Bike, the largest dock-based bike-sharing system in New York City. Then, we derive six bike usage clusters based on three clustering variables: the start trips, end trips, and station empty status. Finally, we propose three relationships between bike-sharing and public transit: competition, integration, and complementation. The result demonstrates that bike-sharing can largely compete with public transit in New York City. A significant portion of bike-sharing trips are more time-intensive than their public transit alternatives. The article concludes that this competition exists due to riders’ preferences for lower costs and flexibility over savings in travel time, which helps to improve transportation equity for socioeconomically disadvantaged populations. Thus, in New York City, bike-sharing primarily fulfills the need for low-cost and flexible travel rather than solving “the last mile problem. ” This revelation provides new insights into the roles of bike-sharing in urban transportation.
Electronic health records and blockchain interoperability requirements: a scoping review

Abstract Objective The purpose of this study was to conduct a scoping review of publications that explored blockchain technology in the context of interoperability and challenges of electronic health record (EHR) implementations. We synthesize the literature regarding standards and security, specifically regulation, regulatory operability, and conformance to standards. We review open practitioner questions that were not addressed in the studies as directions for further research. Materials and Methods We conducted a literature search in the OVID databases (Medline and Embase) on terms blockchain, implementation, interoperability, EHRs, security, and standards. The search resulted in 152 nonduplicate, peer-reviewed manuscripts, of which 15 were relevant to our objective and included for synthesis. Results Based on the search results, we analyzed the adoption of blockchain technology in the healthcare systems and challenges to EHR implementation of blockchain. From the synthesized research, we categorized and reported compelling factors of blockchain for EHR integration using current knowledge on blockchain research standardization and architectural challenges. Discussion Our research showed promise in implementing blockchain technology associated with EHRs, especially with Health Information Exchanges. The studies relevant for both EHR (n = 5) and blockchain (n = 10) reported compelling factors and limitations of the architecture. Security (n = 4) and interoperability (n = 4) features were reported as compelling requirements with lingering challenges. Standardization literature (n = 3) reported implementation challenges. Conclusion This study shows promise in implementing blockchain technology within EHR systems. The adoption is increasing; however, multiple implementation challenges remain from architectural perspectives (eg, scalability and performance), to security challenges (eg, legal requirements), and standard perspectives including patient-matching problems.
Prevention Is the Best Intervention: Proactive Strategies for Supporting Students Who Engage in Escalated Behaviors

Strategies for preventing the escalation of problematic student behavior in inclusive school settings are detailed. These strategies include utilizing proactive behavioral interventions, implementing function-based behavioral interventions that address root causes of escalated student behaviors, and teaching and reinforcing socially acceptable alternatives to escalated student behaviors. Each strategy is described in practical detail using case study vignettes about students who engage in escalated behaviors within inclusive school settings.
The CinQASE Model: Design to Practice Individual & Collaborative Critical Thinking Skill in Learning

This study is a preliminary study in the process of developing the Collaborative in Questioning, Analyzing, Synthesizing and Evaluating (CinQASE) learning model in improving individual critical thinking skills (InCT) and collaborative critical thinking skills (CCT). Research methods in developing this model include needs analysis, literature review, and field survey in the form of descriptive analysis. The results show that this innovation can survive as a theoretical basis for developing the CinQASE learning model. This is the basis for continuous research related to the development of learning models for learning physics in schools. The syntax of the CINQASE learning model includes (1) Orientation problem, (2) Individual Work, (3) Collaborative Thinking Teamwork, (4) Discussion Class, (5) Evaluation and Feedback. The implications of the CinQASE learning model make it one of the learning models that can improve individual critical thinking skills (InCT) and collaborative critical thinking skills (CCT).
Toward the Development of GE11-Based Radioligands for Imaging of Epidermal Growth Factor Receptor-Positive Tumors

The epidermal growth factor receptor (EGFR) is closely associated with tumor development and progression and thus an important target structure for imaging and therapy of various tumors. As a result of its important role in malignancies of various origins and the fact that antibody-based compounds targeting the EGFR have significant drawbacks in terms of in vivo pharmacokinetics, several attempts have been made within the last five years to develop peptide-based EGFR-specific radioligands based on the GE11 scaffold. However, none of these approaches have shown convincing results so far, which has been proposed to be attributed to different potential challenges associated with the GE11 lead structure: first, an aggregation of radiolabeled peptides, which might prevent their interaction with their target receptor, or second, a relatively low affinity of monomeric GE11, necessitating its conversion into a multimeric or polymeric form to achieve adequate EGFR-targeting properties. In the present work, we investigated if these aforementioned points are indeed critical and if the EGFR-targeting ability of GE11 can be improved by choosing an appropriate hydrophilic molecular design or a peptide multimer system to obtain a promising radiopeptide for the visualization of EGFR-overexpressing malignancies by positron emission tomography (PET). For this purpose, we developed several monovalent 68Ga-labeled GE11-based agents, a peptide homodimer and a homotetramer to overcome the challenges associated with GE11. The developed ligands were successfully labeled with 68Ga3+ in high radiochemical yields of ≥97% and molar activities of 41–104 GBq/μmol. The resulting radiotracers presented logD(7.4) values between −2.17 ± 0.21 and −3.79 ± 0.04 as well as a good stability in human serum with serum half-lives of 112 to 217 min for the monovalent radiopeptides and 84 and 62 min for the GE11 homodimer and homotetramer, respectively. In the following in vitro studies, none of the 68Ga-labeled radiopeptides demonstrated a considerable EGF receptor-specific uptake in EGFR-positive A431 cells. Moreover, none of the agents was able to displace [125I]I-EGF from the EGFR in competitive displacement assays in the same cell line in concentrations of up to 1 mM, whereas the endogenous receptor ligand hEGF demonstrated a high affinity of 15.2 ± 3.3 nM. These results indicate that it is not the aggregation of the GE11 sequence that seems to be the factor limiting the usefulness of the peptide as basis for radiotracer design but the limited affinity of monovalent and small homomultivalent GE11-based radiotracers to the EGFR. This highlights that the development of small-molecule GE11-based radioligands is not promising.
Micromagnetic simulation of spin wave propagation in a ferromagnetic film with different thicknesses

in a ferromagnetic film with different thicknesses Hiroshi Hata1, Takahiro Moriyama1, Kenji Tanabe1,2, Kensuke Kobayashi2, Ryo Matsumoto3, Shuichi Murakami3, Jun-ichiro Ohe4, Daichi Chiba5, and Teruo Ono1 1Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto 611-0011, Japan 2Department of Physics, Graduate School of Science, Osaka University, 1-1 Machikaneyama, Toyonaka, Osaka 560-0043, Japan 3Department of Physics, Tokyo Institute of Technology, 2-12-1 Ōokayama, Meguro-ku, Tokyo 152-8551, Japan 4Department of Physics, Toho University, 2-2-1 Miyama, Funabashi, Chiba 274-0072 Japan 5Department of Applied Physics, Faculty of Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan
Deep-Learning-Aided Wireless Video Transmission

We present DeepWiVe, the first-ever end-to-end joint source-channel coding (JSCC) video transmission scheme that leverages the power of deep neural networks (DNNs) to directly map video signals to channel symbols, combining video compression, channel coding, and modulation steps into a single neural transform. Our DNN decoder predicts residuals without distortion feedback, which improves video quality by accounting for occlusion/disocclusion and camera movements. We simultaneously train different bandwidth allocation networks for the frames to allow variable bandwidth transmission. Then, we train a bandwidth allocation network using reinforcement learning (RL) that optimizes the allocation of limited available channel bandwidth among video frames to maximize overall visual quality. Our results show that DeepWiVe can overcome the cliff-effect, which is prevalent in conventional separation-based digital communication schemes, and achieve graceful degradation with the mismatch between the estimated and actual channel qualities. DeepWiVe outperforms H.264 video compression followed by low-density parity check (LDPC) codes in all channel conditions by up to 0.0485 on average in terms of the multi-scale structural similarity index measure (MS-SSIM).
Rising temperature threatens China’s cropland

The rising demand for calories and protein together with urbanization, pose significant challenges to China’s food security. The determination of policy actions requires accurate estimates of climatic impacts on both crop yields (intensive margin) and cropland area (extensive margin). However, the analysis of the latter has been limited, especially in developing countries. Here, we assess the impact of temperature on land use in China by matching high-resolution satellite data on land use with daily weather data from 1980 to 2010. We find that extremely hot weather (daily average temperature above 30 °C) has a long-lasting effect on reducing cropland in China. Combining climate projections from 39 downscaled climate models, we predict that climate change is likely to reduce China’s cropland area by 2.09%–25.51% under IPCC’s slowest and fastest-warming scenarios by the end of this century. In addition, we find that non-irrigated land is more susceptible to rising temperatures in the short term; however, irrigated land is subject to a similar impact in the long term. This result suggests that the adaptive effect of irrigation could be limited under persistent rising in temperature.
Appendectomy and Parkinson's Disease Risk: A Meta-Analysis

The emergence of alternative methods of treating appendicitis and the fact that the gut lymphoid tissue is active (in terms of immune modulation and gut microbiota replenishment) increased the concern about the association of appendectomy with systemic diseases. The literature on the association between appendectomy and Parkinson's disease (PD) lacks the current meta-analysis aimed to assess the association between appendectomy and PD. We systematically searched PubMed, Cochrane Library, and Google Scholar for relevant articles published in the English language, the searching engine was limited to the period from January 2010 to January 2021. Studies on humans were eligible, while animal and experimental studies were excluded, the keywords used were Parkinson's disease, appendicitis, Parkinsonism, appendectomy, gut lymphoid tissue, and movement disorders with protean " AND " or " OR " . Out of the 263 references found, 39 full texts were screened, and only five studies fulfilled the inclusion and exclusion criteria, the studies included 8210081 patients and showed that no association between appendectomy and PD, odd ratio, 1.16, 95% CI, 0.92-1.46, and P-value, 0.20. Significant heterogeneity was observed between the studies included (three from the United States of America and two from Europe) and no relationship was evident between appendectomy and PD, further studies controlling for the causes of appendectomy and temporal profile of both PD and appendectomy are recommended.
Machine Learning in Pansharpening: A benchmark, from shallow to deep networks

Machine learning (ML) is influencing the literature in several research fields, often through state-of-the-art approaches. In the past several years, ML has been explored for pansharpening, i.e., an image fusion technique based on the combination of a multispectral (MS) image, which is characterized by its medium/low spatial resolution, and higher-spatial-resolution panchromatic (PAN) data. Thus, ML for pansharpening represents an emerging research line that deserves further investigation. In this article, we go through some powerful and widely used ML-based approaches for pansharpening that have been recently proposed in the related literature. Eight approaches are extensively compared. Implementations of these eight methods, exploiting a common software platform and ML library, are developed for comparison purposes. The ML framework for pansharpening will be freely distributed to the scientific community. Experimental results using data acquired by five commonly used sensors for pansharpening and well-established protocols for performance assessment (both at reduced resolution and at full resolution) are shown. The ML-based approaches are compared with a benchmark consisting of classical and variational optimization (VO)-based methods. The pros and cons of each pansharpening technique, based on the training-by-examples philosophy, are reported together with a broad computational analysis. The toolbox is provided in https://github.com/liangjiandeng/DLPan-Toolbox.
Mechanisms of anti-hypertensive activity of methanol leaf extract and fractions of Persea americana Mill. (Lauraceae) in rats

Background: Persea americana has been identified to possess antihypertensive properties, but the mechanisms of these properties remain unclear. This study was thus designed to elucidate the mechanisms of anti-hypertensive activity of the extract and fractions of fresh leaf of Persea americana on hypertension induced in rats.Methods: Crude methanol leaf extract of P. americana was partitioned into n-butanol, dichloromethane, chloroform, hexane and ethyl acetate. The ethyl acetate fraction was further purified through column chromatography. Doses of the extract and column fraction were tested for contraction on rat isolated thoracic rings and for in vitro angiotensin converting enzyme inhibitory activities. The test doses were further evaluated for anti-hypertensive activities on noradrenaline- and L-NAME-induced hypertension as well as atherogenic index in hyperlipidemic rats. Effects were compared with control values via one-way analysis of variance using GraphPad® version 8.0 softwareResults: P. americana leaf methanol extract and ethyl acetate column fraction 3 reduced the contractile effect of noradrenaline significantly (p < 0.001) in the isolated thoracic aortic rings through intact endothelium-mediated mechanism(s). The test doses also exhibited in vitro angiotensin converting enzyme inhibitory activities similar to that of captopril. Additionally, ethyl acetate column fraction 3 also reduced the hypertensive effect of L-NAME- induced hypertension by 23%Conclusion: Persea americana methanol leaf extract and ethyl acetate column fraction 3 exhibited significant reductions in all the tested parameters of L-NAME and noradrenaline-induced hypertension most probably through inhibition of vascular alpha adrenoceptors, angiotensin converting enzyme and amelioration of dyslipidemia.
Distributions of failure times associated with non-homogeneous compound Poisson damage processes

Bogdanoff and Kozin, in their book (1985) define cumulative damage (CD) as the "irreversible accumulation of damage throughout life, that ultimately leads to failure" . Such damage can be manifested by corrosion, cracks, physical wear in bearing, piston rings, locks, etc. We focus attention on damage processes that occur at random times, according to some non-homogeneous Poisson process. The amount of damage that accumulates follows a specified distribution. Thus, the amount of damage at time t, is a realization of a random process {Y(t),t > 0}, where Y(t) > 0 is a non-decreasing process with Y(t) ? oo a.s. as t ? oo. A system subjected to such a damage process fails at the first instant at which Y(t) > ? i where 0 < ? < oo is a threshold specific to the system. Thus, the distribution of the failure times is a stopping time distribution. We present in the present paper the methodology of deriving these distributions. We are interested in particular in a family of non-homogeneous Poisson processes having an intensity function of the Weibull type, namely X(t) = (Xt)", 0 < ? , ? < oo. In Section 2 we specify compound non-homogeneous Poisson damage processes, and the distribution of the cumulative damage Y(t), at time t. In Section 3 we derive the density and the reliability function of failure times driven by such processes. In particular we focus attention on cumulative Weibull processes with exponentially distributed damage amount in each occurrence. We investigate and illustrate the behavior of the distribution of failure times and the hazard function. In Section 4 we develop estimators of the parameters of the failure distribution in the homogeneous case
Passively Q‐switched Tm:YAP laser with a Ti3AlC2‐based saturable absorber

In this paper, a passively Q‐switched (PQS) Tm:YAP laser was experimentally demonstrated by using a Ti3AlC2‐based saturable absorber (SA). In the PQS regime, an average output power of 2010/1575 mW with a pulse width of 266/859 ns at 130/155 kHz was achieved from a Tm:YAP laser under an output couple mirror with a transmittance (T) of 1.5%/2.5%, corresponding to an optical conversion efficiency of 9.2%/11.6%. Also, a single pulse energy of 15.5/10.2 μJ and a peak power of 58.1/11.8 W were acquired from the PQS Tm:YAP laser. As far as we know, this is the first time that a Ti3AlC2‐based SA was used for a PQS Tm:YAP laser.
Can Patients Read, Understand, and Act on Online Resources for Anterior Cruciate Ligament Surgery?

Background: Patients undergoing elective procedures often utilize online educational materials to familiarize themselves with the surgical procedure and expected postoperative recovery. While the Internet is easily accessible and ubiquitous today, the ability of patients to read, understand, and act on these materials is unknown. Purpose: To evaluate online resources about anterior cruciate ligament (ACL) surgery utilizing measures of readability, understandability, and actionability. Study Design: Cross-sectional study; Level of evidence, 4. Methods: Using the term “ACL surgery,” 2 independent searches were performed utilizing a public search engine (Google.com). Patient education materials were identified from the top 50 results. Audiovisual materials, news articles, materials intended for advertising or medical professionals, and materials unrelated to ACL surgery were excluded. Readability was quantified using the Flesch Reading Ease, Flesch-Kincaid Grade Level, Simple Measure of Gobbledygook, Coleman-Liau Index, Automated Readability Index, and Gunning Fog Index. The Patient Education Materials Assessment Tool for Printable Materials (PEMAT-P) was utilized to assess the actionability and understandability of materials. For each online source, the relationship between its Google search rank (from first to last) and its readability, understandability, and actionability was calculated utilizing the Spearman rank correlation coefficient (ρS). Results: Overall, we identified 68 unique websites, of which 39 met inclusion criteria. The mean Flesch-Kincaid Grade Level was 10.08 ± 2.34, with no website scoring at or below the 6th-grade level. Mean understandability and actionability scores were 59.18 ± 10.86 (range, 33.64-79.17) and 34.41 ± 22.31 (range, 0.00-81.67), respectively. Only 5 (12.82%) and 1 (2.56%) resource scored above the 70% adequate PEMAT-P threshold mark for understandability and actionability, respectively. Readability (lowest P value = .103), understandability (ρS = –0.13; P = .441), and actionability (ρS = 0.28; P = .096) scores were not associated with Google rank. Conclusion: Patient education materials on ACL surgery scored poorly with respect to readability, understandability, and actionability. No online resource scored at the recommended reading level of the American Medical Association or National Institutes of Health. Only 5 resources scored above the proven threshold for understandability, and only 1 resource scored above it for actionability.