Solution and type curves for the seepage model of the water-bearing coalbed with leakage recharge

To analyze the effects of the leakage recharge of the aquifer on the initial dewatering of coalbed methane wells, the mathematical seepage model of water in the coalbed considering the aquifer leakage was established by using the leakage coefficient according to the unsteady seepage theory. The model was solved after Laplace transform and the Stehfest numerical reverse inversion was used to obtain the solution in right space. Then, the log-log type curves of pressure and pressure derivative were created with new combinations of parameters. Based on the natural seepage mechanism, the influence of aquifer leakage on curve shape was judged. It is found that the radial flow ends earlier as the leakage coefficient increases. Moreover, it was proposed to obtain reservoir permeability, skin factor, and leakage coefficient by using type curve matching. The type curves are useful for quantitatively evaluating the level of leakage, thereby guiding the adjustment of the following production system for CBM wells.Este estudio estableció el modelo matemático de filtración de agua en una capa carbonífera al estimar la salida acuífera con el uso del coeficiente de fuga, de acuerdo con la teoría de filtración inestable, para analizar los efectos en la recarga de pérdida de fluidos de un acuífero en el drenado inicial para pozos de gas metano.  El modelo se resolvió tras usar la transformación Laplace y la inversión numérica Stehfest para encontrar la respuesta en el lugar indicado. Luego, se creó la representación algorítmica de la presión y la presión derivativa con nuevas combinaciones de parámetros. Se evaluó la influencia de la pérdida de fluido del acuífero en la forma de la curva con base al mecanismo físico de filtración. Se estableció que el flujo radial finaliza antes de que el coeficiente de pérdida de fluido se incremente. Además, se propone el uso de la curva tipo correspondiente para obtener la permeabilidad del reservorio, el factor de daño y el coeficiente de pérdida de fluido. Las curvas tipo son útiles para evaluar cuantitativamente el nivel de la pérdida de fluido, y de esta manera guiar el ajuste de un sistema de producción consecuente para pozos de gas metano de carbón

Clinicopathological and Prognostic Characteristics of Hepatoid Adenocarcinoma of the Stomach

The present study was undertaken to clarify the association of the clinicopathological features of hepatoid adenocarcinoma (HAC) in the stomach, a special kind of carcinoma that histologically resembled hepatocellular carcinoma (HCC) and is characterized by large amounts of α-fetoprotein (AFP) in serum, with the clinical prognosis. We collected the data of the clinicopathological features and the follow-up information from a total of 31 HACs from January 2005 to December 2012 in our hospital. High lymphatic (54.8%) and distant (25.8%) metastasis rates before surgery, large proportion of advanced HACs (71.0%) at admission, short median overall survival time (6 months), and low three-year survival rate (22.6%) suggested that HAC in the stomach was an aggressive disease, resulting in a poor prognosis. And pTNM stages, immunohistochemical staining of AFP, CEA, CK7, and CK20 had statistically relation with the survival as the independent risk factors, P<0.05. Therefore, early and clear differentiation of HAC from cancerous or noncancerous conditions with AFP elevation and assessment of high risk patients by histopathology may improve the clinical prognosis

Increasing Cytosine Base Editing Scope and Efficiency With Engineered Cas9-PmCDA1 Fusions and the Modified sgRNA in Rice

Base editors that do not require double-stranded DNA cleavage or homology-directed repair enable higher efficiency and cleaner substitution of targeted single nucleotides in genomic DNA than conventional approaches. However, their broad applications are limited within the editing window of several base pairs from the canonical NGG protospacer adjacent motif (PAM) sequence. In this study, we fused the D10A nickase of several Streptococcus pyogenes Cas9 (SpCas9) variants with Petromyzon marinus cytidine deaminase 1 (PmCDA1) and uracil DNA glycosylase inhibitor (UGI) and developed two new effective PmCDA1-based cytosine base editors (pBEs), SpCas9 nickase (SpCas9n)-pBE and VQR nickase (VQRn)-pBE, which expanded the scope of genome targeting for cytosine-to-thymine (C-to-T) substitutions in rice. Four of six and 12 of 18 target sites selected randomly in SpCas9n-pBE and VQRn-pBE, respectively were base edited with frequencies of 4–90% in T0 plants. The effective deaminase window typically spanned positions 1–7 within the protospacer and the single target C showed the maximum C-to-T frequency at or near position 3, counting the end distal to PAM as position 1. In addition, the modified single guide RNA (sgRNA) improved the base editing efficiencies of VQRn-pBE with 1.3- to 7.6-fold increases compared with the native sgRNA, and targets that could not be mutated using the native sgRNA were edited successfully using the modified sgRNA. These newly developed base editors can be used to realize C-to-T substitutions and may become powerful tools for both basic scientific research and crop breeding in rice

Electric Vehicle Key Technology Research in China

Electrification is regarded as the mainstream for future automobile power-train in order to cope with the impending energy and environmental problems. The technology of electric vehicle (EV), including battery powered vehicle, hybrid vehicle and fuel cell vehicle, has been investigated thoroughly for more than two decades in China. Many remarkable progresses have been achieved. In this paper, the It & D of electric vehicle technology in China are introduced. Both battery and motor development for electric vehicle application are summarized. The technology trend of electric motor drive is discussed accompanying with the introduction of the practice in electric motor drive research in Chinese Academy of Sciences

EXCITED STATE DYNAMICS IN 2-AMINOPURINE RIBONUCLEOSIDE: FROM FEMTOSECOND TO MICROSECOND TIME SCALE

Author Institution: Department of Chemistry and Center for Chemical Dynamics, Case Western Reserve University, 10900 Euclid Ave., Cleveland, Ohio 441062-aminopurine is a structural isomer of adenine that is widely used as fluorescence probe in DNA because its fluorescence lifetime and quantum yield respond sensitively to local DNA duplex conformation and neighboring microenvironment. Despite its broad utilization in biochemical and biophysical studies, there is ongoing debate about the mechanism by which fluorescence is quenched in 2-aminopurine in different solvents. Establishing the excited-state relaxation pathways that lead to fluorescence quenching is essential for a meaningful interpretation of the experimental data in terms of local structure and dynamics. In this contribution, the excited state dynamics in 2-aminopurine ribonucleoside is investigated by using broad-band transient absorption spectroscopy in different solvents. Excitation is performed at 320 nm and the spectral evolution is monitored in the spectral region from 330 nm to 700 nm. Three exponential functions are required to fit globally the transient absorption signals from femtosecond to microsecond time scale. The first lifetime is assigned to solvent relaxation dynamics in the excited singlet state. The singlet state population then bifurcates to two different decay channels. The first channel is the well-documented fluorescence emission while the second channel is assigned to intersystem crossing to the triplet manifold. The extent of participation of this nonradiative decay channel depends sensitively on the polarity and hydrogen bonding ability of the solvent. The triplet state population decays back to the ground state in hundreds of nanoseconds and is quenched by molecular oxygen. Our results unequivocally show that the excited-state dynamics in 2-aminopurine is more complex than previously thought

A Simple Electrochemical Route to Access Amorphous Co-Ni Hydroxide for Non-enzymatic Glucose Sensing

Abstract Among the numerous transition metal hydroxide materials, cobalt- and nickel-based hydroxides have been extensively studied for their excellent electrochemical performances such as non-enzymatic electrochemical sensors. Binary cobalt-nickel hydroxide has received extensive attention for its exceptionally splendid electrochemical behaviors as a promising glucose sensor material. In this work, we report the synthesis of three-dimensional amorphous Co-Ni hydroxide nanostructures with homogeneous distribution of elements via a simple and chemically clean electrochemical deposition method. The amorphous Co-Ni hydroxide, as a non-enzymatic glucose sensor material, exhibits a superior biosensing performance toward glucose detection for its superior electron transfer capability, high specific surface area, and abundant intrinsic redox couples of Ni2+/Ni3+ and Co2+/Co3+/Co4+ ions. The as-synthesized amorphous Co-Ni hydroxide holds great potential in glucose monitoring and detection as non-enzymatic glucose sensors with high sensitivity 1911.5 μA mM−1 cm−2 at low concentration, wide linear range of 0.00025–1 mM and 1–5 mM, low detection limit of 0.127 μM, super long-term stability, and excellent selectivity in 0.5 M NaOH solution

Sugarcane Stem Node Recognition in Field by Deep Learning Combining Data Expansion

The rapid and accurate identification of sugarcane stem nodes in the complex natural environment is essential for the development of intelligent sugarcane harvesters. However, traditional sugarcane stem node recognition has been mainly based on image processing and recognition technology, where the recognition accuracy is low in a complex natural environment. In this paper, an object detection algorithm based on deep learning was proposed for sugarcane stem node recognition in a complex natural environment, and the robustness and generalisation ability of the algorithm were improved by the dataset expansion method to simulate different illumination conditions. The impact of the data expansion and lighting condition in different time periods on the results of sugarcane stem nodes detection was discussed, and the superiority of YOLO v4, which performed best in the experiment, was verified by comparing it with four different deep learning algorithms, namely Faster R-CNN, SSD300, RetinaNet and YOLO v3. The comparison results showed that the AP (average precision) of the sugarcane stem nodes detected by YOLO v4 was 95.17%, which was higher than that of the other four algorithms (78.87%, 88.98%, 90.88% and 92.69%, respectively). Meanwhile, the detection speed of the YOLO v4 method was 69 f/s and exceeded the requirement of a real-time detection speed of 30 f/s. The research shows that it is a feasible method for real-time detection of sugarcane stem nodes in a complex natural environment. This research provides visual technical support for the development of intelligent sugarcane harvesters