Anthropogenic Activities Generate High-Refractory Black Carbon along the Yangtze River Continuum

12 pages, 7 figuresCombustion-driven particulate black carbon (PBC) is a crucial slow-cycling pool in the organic carbon flux from rivers to oceans. Since the refractoriness of PBC stems from the association of non-homologous char and soot, the composition and source of char and soot must be considered when investigating riverine PBC. Samples along the Yangtze River continuum during different hydrological periods were collected in this study to investigate the association and asynchronous combustion drive of char and soot in PBC. The results revealed that PBC in the Yangtze River, with higher refractory nature, accounts for 13.73 ± 6.89% of particulate organic carbon, and soot occupies 37.53 ± 11.00% of PBC. The preponderant contribution of fossil fuel combustion to soot (92.57 ± 3.20%) compared to char (27.55 ± 5.92%), suggested that fossil fuel combustion is a crucial driver for PBC with high soot percentage. Redundancy analysis and structural equation modeling confirmed that the fossil fuel energy used by anthropogenic activities promoting soot is the crucial reason for high-refractory PBC. We estimated that the Yangtze River transported 0.15–0.23 Tg of soot and 0.15–0.25 Tg of char to the ocean annually, and the export of large higher refractory PBC to the ocean can form a long-term sink and prolong the residence time of terrigenous carbonThis study was supported by grants from the National Natural Science Foundation of China (nos. 42277214, 42207256, and 41971286), major programs of the National Social Science Foundation of China (grant nos. 22&ZD136), the Special Science and Technology Innovation Program for Carbon Peak and Carbon Neutralization of Jiangsu Province (grant no. BE2022612)Peer reviewe

Qwen Technical Report

Large language models (LLMs) have revolutionized the field of artificial intelligence, enabling natural language processing tasks that were previously thought to be exclusive to humans. In this work, we introduce Qwen, the first installment of our large language model series. Qwen is a comprehensive language model series that encompasses distinct models with varying parameter counts. It includes Qwen, the base pretrained language models, and Qwen-Chat, the chat models finetuned with human alignment techniques. The base language models consistently demonstrate superior performance across a multitude of downstream tasks, and the chat models, particularly those trained using Reinforcement Learning from Human Feedback (RLHF), are highly competitive. The chat models possess advanced tool-use and planning capabilities for creating agent applications, showcasing impressive performance even when compared to bigger models on complex tasks like utilizing a code interpreter. Furthermore, we have developed coding-specialized models, Code-Qwen and Code-Qwen-Chat, as well as mathematics-focused models, Math-Qwen-Chat, which are built upon base language models. These models demonstrate significantly improved performance in comparison with open-source models, and slightly fall behind the proprietary models.Comment: 59 pages, 5 figure

Dimensionality Reduction in Stochastic Complex Dynamical Networks

Complex systems are ubiquitous in nature and engineering, but their analysis and control are hampered by their high dimensionality and the influence of various factors on their dynamics. Dimensionality reduction aims to find a low-dimensional representation of the complex system that preserves its essential features and reveals its underlying mechanisms and long-term dynamics. However, most existing methods for dimensionality reduction assume deterministic systems, while many real-world systems exhibit stochasticity. Here, we develop a general analytical framework for dimensionality reduction of stochastic complex dynamical networks that can map a high-dimensional system with stochastic terms to a low-dimensional effective system with a single effective state variable and few effective parameters. The effective parameters are those that determine the network's dynamical behavior and are associated with specific system states. The effective equation is a low-dimensional representation of the original stochastic complex dynamical network that preserves its essential dynamical features. The framework also allows us to analyze the dynamic behavior and potential convergence of the stochastic complex dynamical network by using the standard deviation of the effective equation.Comment: 11 pages, 2 figure

The Limiting Sequence and Proper Ratio of Lysine, Methionine and Threonine for Calves Fed Milk Replacers Containing Soy Protein

The limiting sequence and relative ratio of lysine (Lys), methionine (Met), and threonine (Thr) for calves about 2 mo of age fed milk replacers (MR) containing soy protein are not clearly defined. The objective of the study was to investigate the effect of supplementing MR containing 22% CP, half from soy protein concentrate (SPC, 40.56% CP, flour) and half from whey proteins, with Lys, Met, and Thr to estimate amino acid (AA) sequence and their relative ratio for calves about 2 mo of age. A method of partial deduction of AA was adopted. Twenty-four newborn calves (half males and half females, 40.7±0.9 kg of BW) were fed 1 of 4 MR diets for 56 d (n = 6/diet). The diets were supplemented with all (positive control) or with 2 of the 3 AAs: Lys, Met and Thr, (i.e., PC (22% CP, 2.34% Lys, 0.72% Met and 1.80% Thr), PC-Lys (22% CP, 1.64% Lys, 0.72% Met and 1.80% Thr), PC-Met (22% CP, 2.34% Lys, 0.50% Met and 1.80% Thr), and PC-Thr (22% CP, 2.34% Lys, 0.72% Met and 1.26% Thr)). Calves were fed thrice daily; starter (20% CP, 1.03% Lys, 0.30% Met and 0.69% Thr), hay (3.23% CP, 0.29% Lys, 0.12% Met and 0.23% Thr) and water were offered free choice. Starter and hay were only offered beginning on d 36 (after 5 wk) and d 43 (after 6 wk), respectively. BW, body size and blood samples measures were taken every two weeks. Three-day total collection of feed refusals, feces, and urine were recorded starting at d 33 and d 54 of age, respectively. From the results, the limiting sequence and relative ratio between the 3 AAs in calves with different diet structures were calculated. The limiting sequence of the 3 AAs were ranked as Lys, Met and Thr; the proper ratio was 100:29:70 for MR-only diet and 100:30:60 for diets consisted of MR, starter and hay. Nitrogen digestion and utilization and nutrient digestibility were negatively affected by AA deletion treatments. From the evidence of this experiment, it did not appear that the AA limiting sequence was selectively altered by differences in diet structures such as would be encountered in practice. The relative ratio between the 3 AAs varied with the offer of starter and hay to calves, and the average ratio was 100:29.5:65 for calves during 2 to 10 wk of age

A study on the accuracy of a new fluorescent detection method for vaginal fungi

Abstract Background To investigate the positive rate and clinical applicability of liquid—based fungal method for detecting of vaginal fungi. We collect the secretions from the posterior vaginal fornix and the vaginal wall of 198 patients with clinically suspected fungi vaginitis patients for study. Methods The vaginal fungi of vaginal discharge were detected by fluorescence method, i.e., by liquid—based thin-layer fungi fluorescence morphology staining detection kit (liquid—based fungal method), saline smear method and fungal culture method. Results The positive rate of liquid-based fungal method, saline smear method was 50%, 25.75% respectively. The positive rate of liquid-based fungal method were 50%. The true positive rate of liquid-based fungal method (87.85%) was higher than that of saline smear method (45.79%, P < 0.001), which was easy to miss diagnosis. Moreover, the Kappa (K) of liquid-based fungal method was 0.81, and P < 0.01, which was statistically significant, indicating that the consistency of the two detection methods is good. Of the eight common symptoms of fungal vaginitis, the positive symptom coincidence rate of liquid-based fungal method was consistent with that of fungal culture method. It was also easier to see fungi under a microscope than with saline smear method. Conclusion The liquid-based fungal method has a high positive coincidence rate and accuracy in the detection of vaginal fungi, and it is convenient to operate and implement steps. Therefore, it may be applied in clinical practice. Or a combination of several detection methods can be used

RPT: relational pre-trained transformer is almost all you need towards democratizing data preparation

Can AI help automate human-easy but computer-hard data preparation tasks that burden data scientists, practitioners, and crowd workers? We answer this question by presenting RPT, a denoising autoencoder for tuple-to-X models (" X " could be tuple, token, label, JSON, and so on). RPT is pre-trained for a tuple-to-tuple model by corrupting the input tuple and then learning a model to reconstruct the original tuple. It adopts a Transformer-based neural translation architecture that consists of a bidirectional encoder (similar to BERT) and a left-to-right autoregressive decoder (similar to GPT), leading to a generalization of both BERT and GPT. The pre-trained RPT can already support several common data preparation tasks such as data cleaning, auto-completion and schema matching. Better still, RPT can be fine-tuned on a wide range of data preparation tasks, such as value normalization, data transformation, data annotation, etc. To complement RPT, we also discuss several appealing techniques such as collaborative training and few-shot learning for entity resolution, and few-shot learning and NLP question-answering for information extraction. In addition, we identify a series of research opportunities to advance the field of data preparation. </jats:p

Development and Validation of a Tunable Diode Laser Absorption Spectroscopy System for Hot Gas Flow and Small-Scale Flame Measurement

TDLAS (tunable diode laser absorption spectroscopy) is an important gas analysis method that can be employed to obtain characteristic parameters non-invasively by the infrared absorption spectra of tracer molecules such as CH4, H2O and O2. In this study, a portable H2O-based TDLAS system with a dual optical path was developed with the aim of assessing the combustion characteristics of flammable gases. Firstly, a calculation method of gas characteristics including temperature and velocity combining absorption spectra and a HITRAN database was provided. Secondly, to calibrate and validate this TDLAS system precisely, a pressure vessel and a shock tube were introduced innovatively to generate static or steady flow fields with preset constant temperatures, pressures, or velocities. Static tests within environment pressures up to 2 MPa and steady flow field tests with temperatures up to 1600 K and flow velocities up to 950 m/s were performed for verification. It was proved that this system can provide an accurate values for high temperature and velocity gas flows. Finally, an experimental investigation of CH4/air flames was conducted to test the effectiveness of the system when applied to small diffusion flames. This TDLAS system gave satisfactory flame temperature and velocity data owing to the dual optical path design and high frequency scanning, which compensated for scale effects and pulsation of the flame. This work demonstrates a valuable new approach to thermal hazard analysis in specific environments

A study of mechanical optimization strategy for cardiac resynchronization therapy based on an electromechanical model

An optimal electrode position and interventricular (VV) delay in cardiac resynchronization therapy (CRT) improves its success. However, the precise quantification of cardiac dyssynchrony and magnitude of resynchronization achieved by biventricular (BiV) pacing therapy with mechanical optimization strategies based on computational models remain scant. The maximum circumferential uniformity ratio estimate (CURE) was used here as mechanical optimization index, which was automatically computed for 6 different electrode positions based on a three-dimensional electromechanical canine model of heart failure (HF) caused by complete left bundle branch block (CLBBB). VV delay timing was adjusted accordingly. The heart excitation propagation was simulated with a monodomain model. The quantification of mechanical intra-and interventricular asynchrony was then investigated with eight-node isoparametric element method. The results showed that (i) the optimal pacing location from maximal CURE of 0.8516 was found at the left ventricle (LV) lateral wall near the equator site with a VV delay of 60 ms, in accordance with current clinical studies, (ii) compared with electrical optimization strategy of E-RMS, the LV synchronous contraction and the hemodynamics improved more with mechanical optimization strategy. Therefore, measures of mechanical dyssynchrony improve the sensitivity and specificity of predicting responders more. The model was subject to validation in future clinical studies