Medical Dialogue Generation via Dual Flow Modeling

Medical dialogue systems (MDS) aim to provide patients with medical services, such as diagnosis and prescription. Since most patients cannot precisely describe their symptoms, dialogue understanding is challenging for MDS. Previous studies mainly addressed this by extracting the mentioned medical entities as critical dialogue history information. In this work, we argue that it is also essential to capture the transitions of the medical entities and the doctor's dialogue acts in each turn, as they help the understanding of how the dialogue flows and enhance the prediction of the entities and dialogue acts to be adopted in the following turn. Correspondingly, we propose a Dual Flow enhanced Medical (DFMed) dialogue generation framework. It extracts the medical entities and dialogue acts used in the dialogue history and models their transitions with an entity-centric graph flow and a sequential act flow, respectively. We employ two sequential models to encode them and devise an interweaving component to enhance their interactions. Experiments on two datasets demonstrate that our method exceeds baselines in both automatic and manual evaluations.Comment: Accepted as Findings of ACL 202

RECAP: Towards Precise Radiology Report Generation via Dynamic Disease Progression Reasoning

Automating radiology report generation can significantly alleviate radiologists' workloads. Previous research has primarily focused on realizing highly concise observations while neglecting the precise attributes that determine the severity of diseases (e.g., small pleural effusion). Since incorrect attributes will lead to imprecise radiology reports, strengthening the generation process with precise attribute modeling becomes necessary. Additionally, the temporal information contained in the historical records, which is crucial in evaluating a patient's current condition (e.g., heart size is unchanged), has also been largely disregarded. To address these issues, we propose RECAP, which generates precise and accurate radiology reports via dynamic disease progression reasoning. Specifically, RECAP first predicts the observations and progressions (i.e., spatiotemporal information) given two consecutive radiographs. It then combines the historical records, spatiotemporal information, and radiographs for report generation, where a disease progression graph and dynamic progression reasoning mechanism are devised to accurately select the attributes of each observation and progression. Extensive experiments on two publicly available datasets demonstrate the effectiveness of our model.Comment: Accepted by Findings of EMNLP 202

The History, Mechanism, and Clinical Application of Auricular Therapy in Traditional Chinese Medicine

Auricular therapy includes acupuncture, electroacupuncture, acupressure, lasering, cauterization, moxibustion, and bloodletting in the auricle. For 2500 years, people have employed auricular therapy for treating diseases, but the methods have been limited to bloodletting and cauterization. Only after 1957, the international scientific community became aware that the map of the ear resembles an inverted fetus, its introduction has led to auricular acupuncture (AA) becoming a more systemic approach, and, following the identification and standardization of more precise points, AA has been employed in clinical applications. The mechanisms of AA are considered to have a close relationship with the autonomic nervous system, the neuroendocrine system, neuroimmunological factors, neuroinflammation, and neural reflex, as well as antioxidation. Auricular therapy has been applied, for example, for pain relief, for the treatment of epilepsy, anxiety, and obesity, and for improving sleep quality. However, the mechanisms and evidence for auricular therapy warrant further study

Plant Species Diversity along a Precipitation Gradient in Temperate Grasslands of China and Mongolia

Variations in species diversity can be linked to several ecological gradients (Huston 1994). Plant functional type is characterized by an adaption of plants to certain ecological conditions (Galan de Mera et al. 1999). In addition, patterns of species richness along an environmental gradient might be more interpretable by considering both species richness of different functional types and total species richness (Pausas and Austin 2001). Water availability generally signifies total precipitation available to support plant growth (Adler and Levine 2007), and its temporal distribution is the main driver of species composition and species diversity in arid and semi-arid environments (Shmida and Wilson 1985; Kutiel et al. 2000). Therefore, understanding how precipitation influences species diversity at a spatial scale will be critical for predicting the impacts of altered precipitation on vegetation patterns. This study aimed to examine the vegetation response to a spatial precipitation gradient in temperature grassland in China and Mongolia

Probing flavor changing interactions in hadron collisions

The subprocess $gg \to t\bar{c}+\bar{t}c$ in the two-Higgs-doublet model with flavor-changing scalar couplings is examined at the one loop level. With perturbative QCD factorization theorem, the corresponding cross sections for hadron-hadron collisions are computed numerically. The results are applicable to the whole mass range of the weakly coupled Higgs bosons. In case we could efficiently exclude the severe backgrounds of the $t\bar{c}(\bar{t}c)$ production signal, probing the flavor-changing top-charm-scalar vertex at hadron colliders would be very promising and accessible experimentally.Comment: LaTex file, 14 pages, 8 EPS figure

Cloning and selection of reference genes for gene expression studies in Ananas comosus

Full length mRNA sequences of Ac-β-actin and Ac-gapdh, and partial mRNA sequences of Ac-18SrRNA and Ac-ubiquitin were cloned from pineapple in this study. The four genes were tested as housekeeping genes in three experimental sets. GeNorm and NormFinder analysis revealed that β-actin was the most appropriate reference gene for qPCR analysis of callus under induction conditions and in different tissue types, meanwhile, 18SrRNA was the most stable reference gene during organ development. Gapdh was the most unstable gene in all tested experimental sets. Transcript level analysis result of AcSERK1 in stressed callus normalized by β-actin and 18SrRNA further confirmed that reference genes selected in this study were suitable for transcript level analysis of pineapple. The expression pattern of AcSERK1 during somatic embryogenesis normalized by β-actin coincided with the cytological features of calluses during somatic embryogenesis. These results will enable more accurate and reliable normalization of qPCR results for transcription analysis in pineapple. Keywords: Reference genes, qPCR, pineapple, geNorm, NormFinder African Journal of Biotechnology Vol. 11(29), pp. 7424-7433, 10 April, 201

Synthesis of Giant Dendritic Polyphenylenes with 366 and 546 Carbon Atoms and Their High-vacuum Electrospray Deposition

Dendritic polyphenylenes (PPs) can serve as precursors of nanographenes (NGs) if their structures represent 2D projections without overlapping benzene rings. Here, we report the synthesis of two giant dendritic PPs fulfilling this criteria with 366 and 546 carbon atoms by applying a "layer-by-layer" extension strategy. Although our initial attempts on their cyclodehydrogenation toward the corresponding NGs in solution were unsuccessful, we achieved their deposition on metal substrates under ultrahigh vacuum through the electrospray technique. Scanning probe microscopy imaging provides valuable information on the possible thermally induced partial planarization of such giant dendritic PPs on a metal surface

Data-driven optimization of brittleness index for hydraulic fracturing

Evaluation of brittleness index (BI) is a fundamental principle of a hydraulic fracturing design. A wide variety of BI calculations often baffle field engineers. The traditional value comparison may also not make the best of BI. Moreover, it is often mixed up with the fracability in field applications, thus causing concerns. We, therefore, redefine fracability as the fracturing pressure under certain rock mechanical (mainly brittleness), geological and injecting conditions to clarify the confusion. Then, we propose a data-driven workflow to optimize BIs by controlling the geological and injecting conditions. The machine learning (ML) workflow is employed to predict the fracability (fracturing pressure) based on field measurement. Three representative ML algorithms are applied to average the prediction, aiming to restrict the interference of algorithm performances. The contribution of brittleness on pressure/fracability prediction by error analysis (rather than the traditional method of BI-value comparison) is proposed as the new criterion for optimization. Six classic BI correlations (mineral-, logging- and elastic-based) are evaluated, three of which are optimized for the derivation of a new BI using the backward elimination strategy. The stress ratio (ratio of minimum and maximum horizontal principal stress), representing the geological feature, is introduced into the derived calculation based on the independent variable analysis. The reliability of the new BI is verified by error analyses using data of eight fracturing stages from seven different wells. Approximately 40%–50% of the errors are reduced based on the new BI. The differences among the performances of algorithms are also significantly restrained. The new brittleness index provides a more reliable option for evaluating the brittleness and fracability of the fracturing formation. The machine learning workflow also proposes a promising application scenario of the BI for hydraulic fracturing, which makes more efficient and broader usages of the BI compared with the traditional value comparison

Clinicopathologic Evaluation of Prognostic Factors for Squamous Cell Carcinoma of the Buccal Mucosa

BackgroundThe purpose of this research was to evaluate the prognostic significance of clinicopathologic variables on the survival rate for squamous cell carcinoma of the buccal mucosa (BMSCC). We analyzed the outcomes of surgical therapy for this aggressive cancer and compared these results with those in the literature.MethodsWe reviewed the medical charts of 172 patients treated in our institution between 1990 and 2005. There were 22 patients excluded from our studies: 20 patients with advanced tumors who received no treatment or palliative treatment, and 2 patients who had received preoperative radiotherapy (RT). The remaining 150 patients were treated with surgeries and among them, 56 patients had undergone postoperative RT. The influence of clinicopathologic factors on the survival rate was analyzed with the Kaplan-Meier method and log-rank test. Multivariate analysis was assessed with Cox's regression model.ResultsThere were 148 males and 2 females, with a mean age of 53.5 years. The prevalence rate of habitual betel quid chewing documented in charts among 113 patients was 75%. The 5-year overall survival rate and disease-specific survival rate for all patients were 64% and 69%, respectively. For patients with stages I, II, III, and IV disease, the 5-year disease-specific survival rates were 90%, 77%, 52%, and 47%, respectively (p< 0.001). According to the multivariate analysis, the pathologic staging and histologic grading of the tumor were independently the important prognostic factors affecting survival rate. There were 80 patients who developed locoregional recurrence in lymph nodes in the follow-up diagnoses. Distant metastases occurred in 14 patients, with 11 of them also having locoregional recurrence. The distant metastases were found in the lungs (8/14), T-spine (3/14), liver (2/14) and brain (1/14).ConclusionPathologic stage and histologic grade are the most important prognostic factors

Large intrinsic anomalous Hall effect in both Nb2_{2}FeB2_{2} and Ta2_{2}FeB2_{2} with collinear antiferromagnetism

It is rarely reported that collinear antiferromagnetic (AFM) metals can have anomalous Hall effect (AHE). In this letter, based on symmetry analysis and the first-principles electronic structure calculations, we predict that two existing collinear antiferromagnets Nb$_{2}$FeB$_{2}$ and Ta$_{2}$FeB$_{2}$, whose N\'eel temperatures are above room temperature, have very large AHE with anomalous Hall conductance (AHC) -100 $\Omega^{-1}$ cm$^{-1}$ and $-54\Omega^{-1}$ cm$^{-1}$, respectively. We further complete the symmetry resquirements for realizing the AHE in collinear antiferromagnetism