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Aversive stimuli can cause hippocampal place cells to remap their firing fields, but it is not known whether remapping plays a role in storing memories of aversive experiences. Here, we addressed this question by performing in vivo calcium imaging of CA1 place cells in freely behaving rats (n = 14). Rats were first trained to prefer a short path over a long path for obtaining food reward, then trained to avoid the short path by delivering a mild footshock. Remapping was assessed by comparing place cell population vector similarity before acquisition versus after extinction of avoidance. Some rats received shock after systemic injections of the amnestic drug scopolamine at a dose (1 mg/kg) that impaired avoidance learning but spared spatial tuning and shock-evoked responses of CA1 neurons. Place cells remapped significantly more following remembered than forgotten shocks (drug-free versus scopolamine conditions); shock-induced remapping did not cause place fields to migrate toward or away from the shocked location and was similarly prevalent in cells that were responsive versus non-responsive to shocks. When rats were exposed to a neutral barrier rather than aversive shock, place cells remapped significantly less in response to the barrier. We conclude that place cell remapping occurs in response to events that are remembered rather than merely perceived and forgotten, suggesting that reorganization of hippocampal population codes may play a role in storing memories for aversive events.

Human translation always has an incomparable role in the process of English learning, especially in the promotion of English reading comprehension. This paper centers on the research problem of selecting suitable research objects, combining questionnaire surveys and test methods to obtain relevant data on artificial translation and English reading comprehension. Then, it analyzes the correlation between the dimensions of artificial translation and the effect on English reading comprehension, constructs the multiple regression model of artificial intelligence on English reading comprehension, and proposes the corresponding significance test method. The results show that the correlation coefficients between the five dimensions of human translation and English reading comprehension scores are, in descending order: accuracy (0.824) > completeness (0.636) > fitness (0.579) > fluency (0.485) > consistency (0.372), which are all significantly positively correlated with English reading scores. The regression results showed that the level of manual translation dimension explained 26.7% of the variation in reading achievement. Among the human translation dimensions, accuracy, completeness, and consistency have significant positive effects on English reading comprehension. The study suggests that human translation accuracy, completeness, and consistency can be optimized to improve English reading comprehension.

Nekrasov matrices play an important role in various scientific disciplines. The estimation of infinity norm bounds for the inverse of Nekrasov matrices brings a lot of convinces in many fields. In this paper, we introduce two new bounds for the inverse of Nekrasov matrices. The advantages of our bounds and numerical examples are also presented. [ABSTRACT FROM AUTHOR]

This study attempts to disclose the characteristics of knowledge integration in an interdisciplinary field by looking into the content aspect of knowledge.

Objective To analyze the effect and prognosis of COMP gene mutation on the treatment of carpal tunnel syndrome with ultrasound-guided dental crochet knife. Methods A total of 35 carpal tunnel syndrome patients with Cartilage oligomeric matrix protein gene mutation (COMP) who were treated in the outpatient department from June 2022 to June 2023 were selected as the control group. Another 40 patients with carpal tunnel syndrome without mutation of COMP gene who received treatment during the same period were selected as the observation group. All patients were treated with ultrasound-guided lower tooth crochet knife. The Transverse carpal ligament thickness, paresthesia score, muscle loss score and transverse carpal ligament thickness were compared between the two groups. Pisiform cross section median nerve cross section area, pisiform cross section median nerve cross section area, CSA), Anterior and posterior diameter of median nerve in cross section of uncinate bone (D), clinical efficacy and incidence of adverse events. Results After treatment, compared with observation group, paresthesia score, hand function satisfaction score, TTCL, CSA and D in control group were all increased, while muscle loss score was decreased, with statistical difference (P < 0.05). In addition, the total clinical efficiency increased significantly and the incidence of adverse effects decreased significantly in the observation group. The prognosis of carpal tunnel syndrome patients with COMP gene mutation was evaluated according to the satisfaction degree of hand function, which showed that compared with the good prognosis group, the hand function score of the poor prognosis group increased significantly, with statistical difference (P < 0.05). Before treatment, there was no significant difference in clinical manifestations between the two groups (P > 0.05). Conclusions The application of ultrasound-guided crochet in carpal tunnel syndrome patients with COMP gene mutation plays an important role in the development of carpal tunnel syndrome. [ABSTRACT FROM AUTHOR]

We introduce a new basis of quasisymmetric functions, the row-strict dual immaculate functions. We construct a cyclic, indecomposable 0-Hecke algebra module for these functions. Our row-strict immaculate functions are related to the dual immaculate functions of Berg-Bergeron-Saliola-Serrano-Zabrocki (2014-15) by the involution \psi on the ring \operatorname {QSym} of quasisymmetric functions. We give an explicit description of the effect of \psi on the associated 0-Hecke modules, via the poset induced by the 0-Hecke action on standard immaculate tableaux. This remarkable poset reveals other 0-Hecke submodules and quotient modules, often cyclic and indecomposable, notably for a row-strict analogue of the extended Schur functions studied in Assaf-Searles (2019). Like the dual immaculate function, the row-strict dual immaculate function is the generating function of a suitable set of tableaux, corresponding to a specific descent set. We give a complete combinatorial and representation-theoretic picture by constructing 0-Hecke modules for the remaining variations on descent sets, and showing that all the possible variations for generating functions of tableaux occur as characteristics of the 0-Hecke modules determined by these descent sets. [ABSTRACT FROM AUTHOR]

Applying hyperspectral remote sensing technology to the prediction of soil moisture content (SMC) during the growth stage of soybean emerges as an effective approach, imperative for advancing the development of modern precision agriculture. This investigation focuses on SMC during the flowering stage under varying nitrogen application levels and film mulching treatments. The soybean canopy's original hyperspectral data, acquired at the flowering stage, underwent 0–2-order differential transformation (with a step size of 0.5). Five spectral indices exhibiting the highest correlation with SMC were identified as optimal inputs. Three machine learning methods, namely support vector machine (SVM), random forest (RF), and back propagation neural network (BPNN), were employed to formulate the SMC prediction model. The results indicate the following: (1) The correlation between the optimal spectral index of each order, obtained after fractional differential transformation, and SMC significantly improved compared to the original hyperspectral reflectance data. The average correlation coefficient between each spectral index and SMC under the 1.5-order treatment was 0.380% higher than that of the original spectral index, with mNDI showing the highest correlation coefficient at 0.766. (2) In instances of utilizing the same modeling method with different input variables, the SMC prediction model's accuracy follows the order: 1.5 order > 2.0 order > 1.0 order > 0.5 order > original order. Conversely, with consistent input variables and a change in the modeling method, the accuracy order becomes RF > SVM > BPNN. When comprehensively assessing model evaluation indicators, the 1.5-order differential method and RF method emerge as the preferred order differential method and model construction method, respectively. The R2 for the optimal SMC estimation model in the modeling set and validation set were 0.912 and 0.792, RMSEs were 0.005 and 0.004, and MREs were 2.390% and 2.380%, respectively. This study lays the groundwork for future applications of hyperspectral remote sensing technology in developing soil moisture content estimation models for various crop growth stages and sparks discussions on enhancing the accuracy of these different soil moisture content estimation models. [ABSTRACT FROM AUTHOR]