Miracle-dz/UniFAR-FTUs huggingface dataset:
Chinese causal event extraction using causality‐associated graph neural network

Causal event extraction (CEE) aims to identify and extract cause‐effect event pairs from texts, which is a fundamental task in natural language processing. Recent research treat CEE as a sequence labeling problem. However, the linguistic complexity and ambiguity of textual description results in the low accuracy of extractors. To address the above issues, considering the prior knowledge like the causal network constructed based on the causal indicators, which can represent information transition between cause and effect, may helpful for CEE. In this article, we propose causality‐associated graph neural network to incorporate in‐domain knowledge by taking important causal words into account. External causal knowledge is modeled as causal associated graph (CAG). Then we use graph neural networks (GNN) to capture the complex relationship of intraevent mentions and interevent causality in a sentence based on the relationship obtained from CAG. Finally, sentence sequence and prior causal knowledge of GNN embedding are fed into multiscaled convolution and bidirectional long short‐term memory networks. Experimental results on two datasets show that our method outperforms the state‐of‐the‐art baseline.
General relativistic magnetohydrodynamic dynamo in thick accretion disks: fully nonlinear simulations

The recent imaging of the M87 black hole at millimeter wavelengths by the Event Horizon Telescope (EHT) collaboration has triggered a renewed interest in numerical models for the accretion of magnetized plasma in the regime of general relativistic magnetohydrodynamics (GRMHD). Here non-ideal simulations, including both the resistive effects and, above all, the mean-field dynamo action due to sub-scale, unresolved turbulence, are applied for the first time to such systems in the fully nonlinear regime. Combined with the differential rotation of the disk, the dynamo process is able to produce an exponential growth of any initial seed magnetic field up to the values required to explain the observations, when the instability tends to saturate even in the absence of artificial quenching effects. Before reaching the final saturation stage we observe a secondary regime of exponential growing, where the magnetic field increases more slowly due to accretion, which is modifying the underlying equilibrium. By varying the dynamo coefficient we obtain different growth rates, though the field seems to saturate at approximately the same level, at least for the limited range of parameters explored here, providing substantial values for the MAD parameter for magnetized accretion. For reasonable values of the central mass density and the commonly employed recipes for synchrotron emission by relativistically hot electrons, our model is able to reproduce naturally the observed flux of Sgr A*, the next target for EHT.
Language processing in glioma patients: speed or accuracy as a sensitive measure?

ABSTRACT Background Glioma (brain tumour) patients can suffer from mild linguistic and non-linguistic cognitive problems when the glioma is localised in an eloquent brain area. Word-finding problems are among the most frequently reported complaints. However, mild problems are difficult to measure with standard language tests because they are generally designed for more severe aphasic patients. Aims The aim of the present study was to investigate whether word-finding problems reported by patients with a glioma can be objectified with a standard object naming test, and a linguistic processing speed test. In addition, we examined whether word-finding problems and linguistic processing speed are related to non-verbal cognitive abilities. Methods & Procedures We tested glioma patients (N=36) as part of their standard pre-treatment clinical work-up. Word-finding problems were identified by a clinical linguist during the anamnesis. Linguistic processing speed was assessed with a newly designed sentence judgment test (SJT) as part of the Diagnostic Instrument for Mild Aphasia (DIMA), lexical retrieval with the Boston Naming Test (BNT), presence of aphasia with a Token Test (TT), and non-verbal processing with the Trail Making Test A and B (TMT). Test performances of glioma patients were compared to those of healthy control participants (N=35). Outcomes & Results The results show that many glioma patients (58%) report word-finding problems; these complaints were in only half of the cases supported by deviant scores on the BNT. Moreover, the presence of reported word-finding problems did not correlate with the BNT scores. However, word-finding problems were significantly correlated with reaction times on the SJT and the TMT. Although there were no significant differences between the patient and control group on the SJT, a subgroup of patients with a glioma in the frontal lobe of the language-dominant hemisphere was slower on the SJT. Finally, performance on the SJT and TMT were significantly correlated in the patient group but not in the control group. Conclusions Linguistic processing speed appears to be an important factor in explaining reported word-finding problems. Moreover, the overlap between speed of language processing and non-verbal processing indicates that patients may rely on more domain-general cognitive abilities as compared to healthy participants. The variability observed between patients emphasises the need for tailored neuro-linguistic assessments including an extensive anamnesis regarding language problems in clinical work-up.
Loss tolerant quantum state tomography by number-resolving measurements without approximate displacements

We introduce a quantum state tomography technique to reconstruct the density matrix of an arbitrary quantum state by experimentally determining the Wigner function overlap, or the fidelity, between the unknown state and a set of tomographically complete coherent states. Each fidelity is determined by a parity measurement from number-resolving statistics on only a single mode of the output field after an interference between each probing coherent state and the unknown state. We demonstrate that the state can be accurately reconstructed following an arbitrary well-calibrated loss, and that this reconstruction is robust to noise. Unlike conventional continuous variable state tomography methods, our method utilizes computationally efficient semidefinite programming (SDP).
Variability in Anthropogenic Underwater Noise Due to Bathymetry and Sound Speed Characteristics

Oceanic acoustic environments are dynamic, shaped by the spatiotemporal variability in transmission losses and sound propagation pathways of natural and human-derived noise sources. Here we used recordings of an experimental noise source combined with transmission loss modeling to investigate changes in the received levels of vessel noise over space and time as a result of natural water column variability. Recordings were made in the Juan de Fuca Strait, on the west coast of Vancouver Island, a biologically productive coastal region that hosts several cetacean species. Significant variability in noise levels was observed due to changing water masses, tied to seasonal temperature variation and, on a finer scale, tidal movements. Comparisons of interpreted received noise levels through the water column indicated that vessel noise recorded by bottom-stationed monitoring devices might not accurately represent those received by whales in near-surface waters. Vertical and temporal differences of 3–5 dB were commonly observed in both the recorded and modeled data. This has implications in estimating the success of noise mitigation measures, and our understanding of the change in sound fields experienced by target species for conservation.
Analysis of an Inhomogeneous Circularly Polarized Hollow Dielectric Resonator Antenna Using Perturbation Theory

The perturbation approach is presented here for the first time for the analysis of an inhomogeneous circularly polarized rectangular dielectric resonator (DR) antenna (DRA). The inhomogeneous permittivity is created by perturbing a rectangle-shaped region of different material inside the rectangular dielectric resonator antenna (RDRA). The orthogonal degenerate modes with a phase difference of TE111x, and TE111y, are excited simultaneously for achieving circular polarization. A simple expression for the calculation of the resonant frequency and optimal axial ratio point for a circularly polarized (CP) inhomogeneous RDRA is presented here. Theoretical results obtained from the proposed theory are compared with theoretical, simulated, and experimental data available in the literature. The proposed analysis results show optimal axial ratio point calculations within a 1% range of the simulated and experimental data, which is better than the previous transverse transmission line reported method, having an error of approximately 4%. The advantages, accuracy, and simplicity of perturbation theory for DR are discussed in detail. The proposed theory can be easily extended for higher order modes and other shapes of material perturbation and anisotropic DRAs. The proposed technique will help in incorporation of the perturbation in the DR so that CP radiation can be obtained in an easy way.
Barley Variety Identification by iPhone Images and Deep Learning

Abstract The quality of barley seeds determines the quality and flavor aspects of malts and beers, and the purity of barley seeds is one of the primary considerations in the malting process. Visual discrimination between barley varieties is difficult and requires a barley specialist with intensive experience and years of training. Therefore, computational and automatic methods are in great demand to efficiently and effectively evaluate barley seed purity among different varieties. By using digital images, this research work developed a novel, automated, deep learning-based approach to accurately classify barley seeds. It implemented and compared different artificial neural networks for the classification problem based on the shape, color, and texture attributes of the barley seed. Data augmentation and transfer learning strategies were integrated into the deep convolutional networks to maximize the model’s performance and accuracy. The results demonstrate the feasibility and effectiveness of automatic classification of barley seeds with high validation accuracy and test accuracies at 95.71% and 95.70%, respectively.
A Novel Low-Profile Circularly Polarized Diversity Patch Antenna With Extremely Small Spacing, Reduced Size, and Low Mutual Coupling

A novel low-profile circularly polarized (CP) diversity patch antenna with extremely small edge-to-edge distance, reduced size, and low mutual coupling is proposed under dual modes. Initially, the single microstrip patch antenna (MPA) is theoretically investigated by using characteristic mode analysis. It demonstrates that a large number of radiative modes, i.e., CM1 to CM7, are excited for the traditional MPA. By selecting its quarter patch configuration with shorting pins, only a few modes, i.e., CM2 and CM7, could be resonated for the quarter patch antenna (QPA). Meanwhile, their nonbroadside radiated fields could be transformed into the broadside radiation. Particularly, the polarizations of CM2 and CM7 are maintained orthogonally with each other. Next, a linear slot is etched on the patch to reduce the magnitude ratio between <inline-formula> <tex-math notation="LaTeX">$\vert E_{\mathrm {\theta }}\vert $ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$\vert E_{\varphi }\vert $ </tex-math></inline-formula> components. After that, the resonant frequency of CM7 is moved closely to that of CM2 for nearby 90° phase difference. With these arrangements, the compact CP performance is acquired by combining its CM2 and CM7. Furthermore, a pair of QPAs with CP diversity is deeply studied. The results prove that the antenna has successfully acquired both of left-handed CP (LHCP) and right-handed CP (RHCP) performances at dual ports. Moreover, the low mutual coupling between them is generated under extremely small spacing. In final, the proposed antenna is fabricated and tested. Both of LHCP and RHCP patterns are formed of around 4.785 GHz. Besides, the proposed antenna occupies the small overall volume <inline-formula> <tex-math notation="LaTeX">$0.023\lambda _{\mathrm {g}}^{3}$ </tex-math></inline-formula> (<inline-formula> <tex-math notation="LaTeX">$\lambda _{\mathrm {g}}$ </tex-math></inline-formula> is the guided wavelength), that is only half of the traditional patch (<inline-formula> <tex-math notation="LaTeX">$0.045\lambda _{\mathrm {g}}^{3}$ </tex-math></inline-formula>), and maintains the isolation as high as about 24 dB under extremely small distance (0.3 mm).
Implementasi Sistem Monitoring Suhu dan Kelembapan Ruangan Penyimpanan Obat Berbasis Internet Of Things (IoT) di Puskesmas Kecamatan Taman Sari Jakarta Barat

Hal paling mudah untuk menentukan suatu ruangan sehat atau tidak adalah dengan mengetahui suhu dan tingkat kelembapan ruangan tersebut. Menurut CPOB, produk farmasi (obat) harus disimpan pada suhu dan kelembapan tertentu untuk mengurangi dan mencegah risiko degradasi obat yang akan merusak kualitas dan keamanan obat. Tujuan dari penelitian ini untuk mampu membuat dan merancang sistem monitoring suhu dan kelembapan ruangan penyimpanan obat berbasis Internet of Things (IoT) memantau suhu dan kelembapan ruangan penyimpanan obat dengan standar suhu tidak melebihi dari 25°C dan kelembapan tidak melebihi dari 60%. Oleh sebab itu, perlu dilakukan monitoring suhu dan kelembapan ruangan yang dapat dilakukan setiap saat. Metodologi yang digunakan adalah dengan metode pengumpulan data dengan metode literatur dan observasi. Berdasarkan hal tersebut, dibuatlah rancang bangun suatu alat yang dapat mengkontrol suhu dan kelembapan ruangan gudang obat farmasi berbasis Internet of Things agar dapat dipantau suhu dan kelembapan dari mana saja dan kapan saja. Kelebihan dari WeMosD1 ESP8266, alat ini dapat mendeteksi suhu dan kelembapan udara suatu objek hanya membuka alamat website atau aplikasi yang sudah terhubung dengan jaringan dan juga menghasilkan suhu dan kelembapan dengan cepat. Cara penggunaannya hanya dihubungkan ke internet melalui website ataupun aplikasi dan ruangan akan diukur suhu dan kelembapannya, maka akan ditampilkan suhu dan kelembapannya.
Graphene Supported Metal Oxide for Non-Enzymatic H2O2 Sensing

The discovery of two-dimensional carbonaceous crystal by Andre Geim and Konstatin Novoselov in 2004 at the University of Manchester opened new paths in various fields around the world [1]. Graphene attracted the researchers around the globe owing to its unique features such as high surface area, high electric conductivity, high flexibility and many more which lead to the announcement of Noble prize in 2010 to its discovers [1]. Graphene serves as an excellent support to host various metal oxides. Graphene offers its massive surface to anchor metal oxides along with preventing the agglomeration of the metal oxide nanoparticles during their assembly in the process of forming the composite [2]. Even the small deviation on the surface of the graphene layer causes significant change in electric conductivity which makes the developed material extremely sensitive to their environment and thus elevating the electrochemical performance of the prepared composites [3]. These two properties make graphene a highly dependable candidate as a support for the active materials in the H2O2 sensing.
Progress on the Stereoselective Synthesis of Chiral Molecules Based on Metal-Catalyzed Dynamic Kinetic Resolution of Alcohols with Lipases

Metal/lipase-combo catalyzed dynamic kinetic resolution (DKR) of racemic chiral alcohols is a general and practical process to obtain the corresponding enantiopure esters R with quantitative conversion. The use of known Ru-catalysts as well as newly developed homogeneous and heterogeneous metal catalysts (Fe, V) contributed to make the DKR process more sustainable and to expand the substrate scope of the reaction. In addition to classical substrates, challenging allylic alcohols, tertiary alcohols, C1-and C2-symmetric biaryl diols turned out to be competent substrates. Synthetic utility further emerged from the integration of this methodology into cascade reactions leading to linear/cyclic chiral molecules with high ee through the formation of multiple bonds, in a one-pot procedure.
Phoenix: Towards Persistently Secure, Recoverable, and NVM Friendly Tree of Counters

Emerging Non-Volatile Memories (NVMs) bring a unique challenge to the security community, namely persistent security. As NVM-based memories are expected to restore their data after recovery, the security metadata must be recovered as well. However, persisting all affected security metadata on each memory write would significantly degrade performance and exacerbate the write endurance problem. Moreover, recovery time can increase significantly (up to hours for practical memory sizes) when security metadata are not updated strictly. Counter trees are used in state-of-the-art commercial secure processors, e.g., Intel's Safe Guard Extension (SGX). Counter trees have a unique challenge due to the inability to recover the whole tree from leaves. Thus, to ensure recoverability, all updates to the tree must be persisted, which can be tens of additional writes on each write. The state-of-art scheme, Anubis, enables recoverability but incurs an additional write per cache eviction, i.e., reduces lifetime to approximately half. Additionally, Anubis degrades performance significantly in many cases. In this paper, we propose Phoenix, a practical novel scheme which relies on elegantly reproducing the cache content before a crash, however with minimal overheads. Our evaluation results show that Phoenix reduces persisting security metadata overhead writes from 87\% extra writes (for Anubis) to less than write-back compared to an encrypted system without recovery, thus improving the NVM lifetime by 2x. Overall Phoenix performance is better than the baseline, unlike Anubis which adds 7.9\% (max of 35\%) performance overhead.
Stage at cancer diagnosis during the COVID-19 pandemic in western Washington state.

145 Background: The COVID-19 pandemic disrupted medical care, including routine cancer screening for breast, colorectal, lung and cervical cancers. We aimed to investigate the impact of the pandemic on stage at diagnosis for cancer patients. Methods: Using data from the Washington State SEER records we compared AJCC stage for patients diagnosed with cancer in 2017-2019 to 2020 for two time periods, March to June (initial pandemic months) and July to December (later pandemic months). Patients were included if they were age 18+, diagnosed with a solid tumor, and not diagnosed at autopsy. Results: In the early phase of the pandemic, March – June 2020, there was a shift to cancers being diagnosed at a later stage compared to the same time period in 2017-2019 (Stage III: 13.5% to 14.9%, Stage IV: 16.2% to 19.7%). There was also a decrease in cancer diagnoses for cancers that are often detected through routine screening. As a percentage of all cancer diagnoses, both melanoma (13.2% to 9.8%) and colon cancer diagnoses (7.2% to. 6.7%) decreased during the early pandemic. In the later phase of the pandemic, July to December 2020, the stage at diagnosis showed an indication of returning to pre-pandemic levels with an increase in the proportion of early stage cancers (In situ: 16.6% to 19.3%, Stage I: 38.8% to 41.1%). Stage at diagnosis trends varied by tumor type. For colorectal cancer, the overall number of diagnoses decreased during the initial pandemic months. Stage I diagnoses decreased and Stage IV cancer diagnoses increased in both early and late stages of the pandemic. Conclusions: In Washington State, the COVID-19 pandemic had an impact on stage at diagnosis potentially caused by delays or interruptions in medical care. Additional studies are needed to understand how this shift in stage at diagnosis impacted treatment and outcomes for patients.
Maximizing treatment benefits in type 2 diabetes by affordable oral anti diabetes agents in India

Diabetes mellitus (DM) is a global epidemic with number of cases rising exponentially with each decade. What makes it more concerning is its association with numerous complications like cardiovascular diseases, end-stage renal disease, neuropathy, and retinopathy. In India, the management of this disease mainly involves out‑of‑pocket expense and contributes to catastrophic health expenditure and distress financing. Thus, the need of the hour is to make oral anti diabetes agents (OADs) affordable and accessible so that maximum number of patients can avail treatment benefits in diabetes care. This review article focuses on the currently available low cost OADs such as sulfonylureas, metformin, thiazolidinediones, alpha glucosidase inhibitors, dipeptidyl-peptidase 4 (DPP4) inhibitors and sodium-glucose co-transporter-2 (SGLT2) inhibitors explaining their efficacy and safety from recent clinical evidence and those going off patent and becoming much affordable in their generic form. This information will help family physicians make rational choices for their type 2 DM (T2DM) patients.
Asteroid Photometry from the Transiting Exoplanet Survey Satellite: A Pilot Study

The Transiting Exoplanet Survey Satellite (TESS) searches for planets transiting bright and nearby stars using high-cadence, large-scale photometric observations. Full frame images provided by the TESS mission include a large number of serendipitously observed main-belt asteroids (MBAs). Due to the cadence of the published full frame images, we are sensitive to periods as long as of order tens of days, a region of phase space that is generally not accessible through traditional observing. This work represents a much less biased measurement of the period distribution in this period range. We have derived rotation periods for 300 MBAs and have partial lightcurves for a further 7277 asteroids, including 43 with periods of P > 100 hr; this large number of slow rotators is predicted by theory. Of these slow rotators we find none requiring significant internal strength to resist rotational reshaping. We find our derived rotation periods to be in excellent agreement with results in the Lightcurve Database for the 55 targets that overlap. Over the nominal two-year lifetime of the mission, we expect the detection of around 85,000 unique asteroids with rotation period solutions for around 6000 asteroids. We project that the systematic analysis of the entire TESS data set will increase the number of known slow-rotating asteroids (period > 100 hr) by a factor of 10. Comparing our new period determinations with previous measurements in the literature, we find that the rotation period of asteroid (2320) Blarney has decreased by at least 20% over the past decade, potentially due to surface activity or subcatastrophic collisions.