The nestin-expressing and non-expressing neurons in rat basal forebrain display different electrophysiological properties and project to hippocampus

<p>Abstract</p> <p>Background</p> <p>Nestin-immunoreactive (nestin-ir) neurons have been identified in the medial septal/diagonal band complex (MS/DBB) of adult rat and human, but the significance of nestin expression in functional neurons is not clear. This study investigated electrophysiological properties and neurochemical phenotypes of nestin-expressing (nestin+) neurons using whole-cell recording combined with single-cell RT-PCR to explore the significance of nestin expression in functional MS/DBB neurons. The retrograde labelling and immunofluorescence were used to investigate the nestin+ neuron related circuit in the septo-hippocampal pathway.</p> <p>Results</p> <p>The results of single-cell RT-PCR showed that 87.5% (35/40) of nestin+ cells expressed choline acetyltransferase mRNA (ChAT+), only 44.3% (35/79) of ChAT+ cells expressed nestin mRNA. Furthermore, none of the nestin+ cells expressed glutamic acid decarboxylases 67 (GAD₆₇) or vesicular glutamate transporters (VGLUT) mRNA. All of the recorded nestin+ cells were excitable and demonstrated slow-firing properties, which were distinctive from those of GAD₆₇or VGLUT mRNA-positive neurons. These results show that the MS/DBB cholinergic neurons could be divided into nestin-expressing cholinergic neurons (NEChs) and nestin non-expressing cholinergic neurons (NNChs). Interestingly, NEChs had higher excitability and received stronger spontaneous excitatory synaptic inputs than NNChs. Retrograde labelling combined with choline acetyltransferase and nestin immunofluorescence showed that both of the NEChs and NNChs projected to hippocampus.</p> <p>Conclusions</p> <p>These results suggest that there are two parallel cholinergic septo-hippocampal pathways that may have different functions. The significance of nestin expressing in functional neurons has been discussed.</p

Assessing slope forest effect on flood process caused by a short-duration storm in a small catchment

Land use has significant impact on the hydrologic and hydraulic processes in a catchment. This work applies a hydrodynamic based numerical model to quantitatively investigate the land use effect on the flood patterns under various rainfall and terrain conditions in an ideal V-shaped catchment and a realistic catchment, indicating the land use could considerably affect the rainfall-flood process and such effect varies with the catchment terrain, land use scenario and the rainfall events. The rainfall-flood process is less sensitive for the side slope than the channel slope. For a channel slope lower than the critical value in this work, the forest located in the middle of the catchment slope could most effectively attenuate the flood peak. When the channel slope is higher than the critical one, forest located in the downstream of the catchment could most significantly mitigate the peak discharge. Moreover, the attenuation effect becomes more obvious as the rainfall becomes heavier. The fragmentation of vegetation does not reduce the flood peak in a more obvious way, compared with the integral vegetation patterns with the same area proportion. The research can help more reasonably guide the land use plan related to flood risk

Application of improved YOLOv7-based sugarcane stem node recognition algorithm in complex environments

IntroductionSugarcane stem node detection is one of the key functions of a small intelligent sugarcane harvesting robot, but the accuracy of sugarcane stem node detection is severely degraded in complex field environments when the sugarcane is in the shadow of confusing backgrounds and other objects.MethodsTo address the problem of low accuracy of sugarcane arise node detection in complex environments, this paper proposes an improved sugarcane stem node detection model based on YOLOv7. First, the SimAM (A Simple Parameter-Free Attention Module for Convolutional Neural Networks) attention mechanism is added to solve the problem of feature loss due to the loss of image global context information in the convolution process, which improves the detection accuracy of the model in the case of image blurring; Second, the Deformable convolution Network is used to replace some of the traditional convolution layers in the original YOLOv7. Finally, a new bounding box regression loss function WIoU Loss is introduced to solve the problem of unbalanced sample quality, improve the model robustness and generalization ability, and accelerate the convergence speed of the network.ResultsThe experimental results show that the mAP of the improved algorithm model is 94.53% and the F1 value is 92.41, which are 3.43% and 2.21 respectively compared with the YOLOv7 model, and compared with the mAP of the SOTA method which is 94.1%, an improvement of 0.43% is achieved, which effectively improves the detection performance of the target detection model.DiscussionThis study provides a theoretical basis and technical support for the development of a small intelligent sugarcane harvesting robot, and may also provide a reference for the detection of other types of crops in similar environments

The Ninth Visual Object Tracking VOT2021 Challenge Results

acceptedVersionPeer reviewe

Changes in the Main Physicochemical Properties and Electrochemical Fingerprints in the Production of Sea Buckthorn Juice by Pectinase Treatment

Enzymatic hydrolysis using pectinase is critical for producing high-yield and quality sea buckthorn juice. This study determined the optimal temperature, time, and enzyme dosage combinations to guide manufacturers. A temperature of 60 °C, hydrolysis time of 3 h, and 0.3% enzyme dosage gave 64.1% juice yield—25% higher than without enzymes. Furthermore, monitoring physicochemical properties reveals enzyme impacts on composition. Higher dosages increase soluble solids up to 15% and soluble fiber content by 35% through cell wall breakdown. However, excessive amounts over 0.3% decrease yields. Pectin concentration also declines dose-dependently, falling by 91% at 0.4%, improving juice stability but needing modulation to retain viscosity. Electrochemical fingerprinting successfully differentiates process conditions, offering a rapid quality control tool. Its potential for commercial inline use during enzymatic treatment requires exploration. Overall, connecting optimized parameters to measured effects provides actionable insights for manufacturers to boost yields, determine enzyme impacts on nutrition/functionality, and introduce novel process analytical technology. Further investigations of health properties using these conditions could expand sea buckthorn juice functionality

Dynamic Simulation on Deflagration of LNG Spill

The deflagration characteristics of premixed LNG vapour-air mixtures with different mixing ratios were quantitatively and qualitatively investigated by using CFD (computational fluid dynamics) method. The CFD model was initially established based on theoretical analysis and then validated by a lab-scale deflagration experiment. The flame propagation behaviour, pressure-time history, and flame speed were compared with the experimental data, upon which a good agreement was achieved. A large-scale deflagration fire during LNG bunkering process was conducted using the model to investigate the flame development and overpressure effects. Mesh independence and time scale were tested in order to obtain the suitable grid resolution and time step. Deflagration cases with two different LNG vapour volume fractions, i.e., 10.4% and 15.0%, were simulated and compared. The one with a volume fraction of 10.4% which was around stoichiometric mixing ratio had the highest flame propagating speed. High flame velocity observed in the simulation was coupled with the thin flame front where overpressure occurred. The CFD model could capture the main features of deflagration combustion and account for LNG fire hazard which could provide an in-depth insight when dealing with complicated cases

Hazardous Consequence Dynamic Simulation and Risk Analysis of LNG Spill on Water for Ship-to-Ship Bunkering

The inland transportation of LNG (liquefied natural gas) by small and medium scale carriers has been acknowledged as an innovated way in the main rivers of China, and the safety issues for LNG bunkering practices have been highly concerned. The significant hazards related with LNG ship-to-ship bunkering could involve LNG vapour dispersion, LNG pool fire and deflagration. LNG vapour initially behaves as a denser-than-air vapour cloud and then is dissipated in surrounding environment. LNG pool fire occurs when bulk LNG releasing on water and encountering ignition source, which could cause thermal radiation damage to the surrounding properties and people. If the dispersed vapour cloud reaches the flammable limits and is ignited, deflagration could occur, as well as flash fire or explosion. The present study aims to capture the feature of these hazards and analyse the potential hazardous area by applying computational fluid dynamics analysis. The pool fire is investigated in order to obtain the thermal radiant flux and temperature and the material effectiveness on both LNG tanker and cargo vessel. The ship side water curtain, which is commonly used to prevent material stress cracking in case of LNG leaking, is considered to mitigate the radiation hazard. In combining with hazardous consequence simulation, a QRA (quantitative risk assessment) was performed to evaluate both individual and social risks of the LNG waterway transportation, with consideration of the crews and social environment at the ship to ship bunkering place. The Pearl River Estuary (PRE) area, which is located at the Southern China Sea coast, was taken as a study case to perform the QRA analysis