Experimental study on propagation and attenuation regularity of landslide surge

On the basis of landslide surge model test by adopting generalized simulation of waterways, this paper, for the first time, established a four-dimensional mathematical model between wave height transmissibility rate and the initial wave height, water depth, azimuth angle as well as propagation distance through utilizing the method of tensor space mapping. Using the new model, we proposed an empirical wave field covering all areas of the channel including the attenuation area within the width of a landslide mass, the straight channel attenuation area outside the width of the landslide mass, the curved channel attenuation area and the after-curve attenuation area, which comprehensively reflects the progressive changes of surge wave factors. The transmissibility of wave height and propagation distance are in a bivariate negative exponential distribution, and the wave height gradually reduces and the attenuation also slows down as the propagation distance increases; wave height transmissibility rate, azimuth and propagation distance are in a trivariate negative exponential distribution, the attenuation of the wave height in the straight channel within the width of the landslide mass was the slowest, followed by that of wave in the straight channel outside the width of the landslide mass, and the attenuation of the wave height in the curved channel is the greatest. This empirical wave field was based on test data, scientifically abstracted the general regularity of the propagation and attenuation of landslide surge, which can be applied to similar analyses and forecasts on landslide surge and can scientifically and accurately determine the damage range of landslide surge

Recent Advance in the Relationship between Excitatory Amino Acid Transporters and Parkinson’s Disease

Parkinson’s disease (PD) is the most common movement disorder disease in the elderly and is characterized by degeneration of dopamine neurons and formation of Lewy bodies. Glutamate is the major excitatory neurotransmitter in the central nervous system (CNS). If glutamate is not removed promptly in the synaptic cleft, it will excessively stimulate the glutamate receptors and induce excitotoxic effects on the CNS. With lack of extracellular enzyme to decompose glutamate, glutamate uptake in the synaptic cleft is mainly achieved by the excitatory amino acid transporters (EAATs, also known as high-affinity glutamate transporters). Current studies have confirmed that decreased expression and function of EAATs appear in PD animal models. Moreover, single unilateral administration of EAATs inhibitor in the substantia nigra mimics several PD features and this is a solid evidence supporting that decreased EAATs contribute to the process of PD. Drugs or treatments promoting the expression and function of EAATs are shown to attenuate dopamine neurons death in the substantia nigra and striatum, ameliorate the behavior disorder, and improve cognitive abilities in PD animal models. EAATs are potential effective drug targets in treatment of PD and thus study of relationship between EAATs and PD has predominant medical significance currently

XL3M: A Training-free Framework for LLM Length Extension Based on Segment-wise Inference

Length generalization failure problem, namely the large language model (LLM) fails to generalize to texts longer than its maximum training length, greatly restricts the application of LLM in the scenarios with streaming long inputs. To address this problem, the existing methods either require substantial costs or introduce precision loss. In this paper, we empirically find that the accuracy of the LLM's prediction is highly correlated to its certainty. Based on this, we propose an efficient training free framework, named XL3M (it means extra-long large language model), which enables the LLMs trained on short sequences to reason extremely long sequence without any further training or fine-tuning. Under the XL3M framework, the input context will be firstly decomposed into multiple short sub-contexts, where each sub-context contains an independent segment and a common ``question'' which is a few tokens from the end of the original context. Then XL3M gives a method to measure the relevance between each segment and the ``question'', and constructs a concise key context by splicing all the relevant segments in chronological order. The key context is further used instead of the original context to complete the inference task. Evaluations on comprehensive benchmarks show the superiority of XL3M. Using our framework, a Llama2-7B model is able to reason 20M long sequences on an 8-card Huawei Ascend 910B NPU machine with 64GB memory per card.Comment: 11 pages, 5 figure

Wnt3a protects SH-SY5Y cells against 6-hydroxydopamine toxicity by restoration of mitochondria function

BACKGROUND: Wnt/β-catenin signal has been reported to exert cytoprotective effects in cellular models of several diseases, including Parkinson’s disease (PD). This study aimed to investigate the neuroprotective effects of actived Wnt/β-catenin signal by Wnt3a on SH-SY5Y cells treated with 6-hydroxydopamine (6-OHDA). METHODS: Wnt3a-conditioned medium (Wnt3a-CM) was used to intervene dopaminegic SH-SY5Y cells treated with 6-OHDA. Cell toxicity was determined by cell viability and lactate dehydrogenase leakage (LDH) assay. The mitochondria function was measured by the mitochondrial membrane potential, while oxidative stress was monitored with intracellular reactive oxygen species (ROS). Western blot analysis was used to detect the expression of GSK3β, β-catenin as well as Akt. RESULTS: Our results showed that 100 μM 6-OHDA treated for 24 h significantly decreased cell viability and mitochondrial transmembrane potential, reduced the level of β-catenin and p-Akt, increased LDH leakage, ROS production and the ratio of p-GSK3β (Tyr216) to p-GSK3β (Ser9). However, Wnt3a-conditioned medium reversing SH-SY5Y cells against 6-OHDA-induced neurotoxicity by reversing these changes. CONCLUSIONS: Activating of Wnt/β-catenin pathway by Wnt3a-CM attenuated 6-OHDA-induced neurotoxicity significantly, which related to the inhibition of oxidative stress and maintenance of normal mitochondrial function

The biomarkers of immune dysregulation and inflammation response in Parkinson disease

Parkinson’s disease (PD) is referring to the multi-systemic α-synucleinopathy with Lewy bodies deposited in midbrain. In ageing, the environmental and genetic factors work together and overactive major histocompatibility complex pathway to regulate immune reactions in central nerve system which resulting in neural degeneration, especially in dopaminergic neurons. As a series of biomarkers, the human leukocyte antigen genes with its related proteomics play cortical roles on the antigen presentation of major histocompatibility complex molecules to stimulate the differentiation of T lymphocytes and i-proteasome activities under their immune response to the PD-related environmental alteration and genetic variation. Furthermore, dopaminergic drugs change the biological characteristic of T lymphatic cells, affect the α-synuclein presentation pathway, and inhibit T lymphatic cells to release cytotoxicity in PD development. Taking together, the serum inflammatory factors and blood T cells are involved in the immune dysregulation of PD and inspected as the potential clinic biomarkers for PD prediction

Acupuncture Modulates the Cerebello-Thalamo-Cortical Circuit and Cognitive Brain Regions in Patients of Parkinson's Disease With Tremor

Objective: To investigate the effect of acupuncture on Parkinson's disease (PD) patients with tremor and its potential neuromechanism by functional magnetic resonance imaging (fMRI).Methods: Forty-one PD patients with tremor were randomly assigned to true acupuncture group (TAG, n = 14), sham acupuncture group (SAG, n = 14) and waiting group (WG, n = 13). All patients received levodopa for 12 weeks. Patients in TAG were acupunctured on DU20, GB20, and the Chorea-Tremor Controlled Zone, and patients in SAG accepted sham acupuncture, while patients in WG received no acupuncture treatment until 12 weeks after the course was ended. The UPDRS II and III subscales, and fMRI scans of the patients' brains were obtained before and after the treatment course. UPDRS II and III scores were analyzed by SPSS, while the degree centrality (DC), regional homogeneity (ReHo) and amplitude low-frequency fluctuation (ALFF) were determined by REST.Results: Acupuncture improved the UPDRS II and III scores in PD patients with tremor without placebo effect, only in tremor score. Acupuncture had specific effects on the cerebrocerebellar pathways as shown by the decreased DC and ReHo and increased ALFF values, and nonspecific effects on the spinocerebellar pathways as shown by the increased ReHo and ALFF values (P < 0.05, AlphaSim corrected). Increased ReHo values were observed within the thalamus and motor cortex of the PD patients (P < 0.05, AlphaSim corrected). In addition, the default mode network (DMN), visual areas and insula were activated by the acupuncture with increased DC, ReHo and/or ALFF, while the prefrontal cortex (PFC) presented a significant decrease in ReHo and ALFF values after acupuncture (P < 0.05, AlphaSim corrected).Conclusions: The cerebellum, thalamus and motor cortex, which are connected to the cerebello-thalamo-cortical (CTC) circuit, were modulated by the acupuncture stimulation to alleviate the PD tremor. The regulation of neural activity within the cognitive brain regions (the DMN, visual areas, insula and PFC) together with CTC circuit may contributes to enhancing movement and improving patients' daily life activities

Lipid profiles in the cerebrospinal fluid of rats with 6-hydroxydopamine-induced lesions as a model of Parkinson’s disease

BackgroundParkinson’s disease (PD) is a progressive neurodegenerative disease with characteristic pathological abnormalities, including the loss of dopaminergic (DA) neurons, a dopamine-depleted striatum, and microglial activation. Lipid accumulation exhibits a close relationship with these pathologies in PD.MethodsHere, 6-hydroxydopamine (6-OHDA) was used to construct a rat model of PD, and the lipid profile in cerebrospinal fluid (CSF) obtained from model rats was analyzed using lipidomic approaches.ResultsEstablishment of this PD model was confirmed by apomorphine-induced rotation behaviors, loss of DA neurons, depletion of dopamine in the striatum, and microglial activation after 6-OHDA-induced lesion generation. Unsupervised and supervised methods were employed for lipid analysis. A total of 172 lipid species were identified in CSF and subsequently classified into 18 lipid families. Lipid families, including eicosanoids, triglyceride (TG), cholesterol ester (CE), and free fatty acid (FFA), and 11 lipid species exhibited significantly altered profiles 2 weeks after 6-OHDA administration, and significant changes in eicosanoids, TG, CE, CAR, and three lipid species were noted 5 weeks after 6-OHDA administration. During the period of 6-OHDA-induced lesion formation, the lipid families and species showed concentration fluctuations related to the recovery of behavior and nigrostriatal abnormalities. Correlation analysis showed that the levels of eicosanoids, CE, TG families, and TG (16:0_20:0_18:1) exhibited positive relationships with apomorphine-induced rotation behaviors and negative relationships with tyrosine hydroxylase (TH) expression in the midbrain.ConclusionThese results revealed that non-progressive nigrostriatal degeneration induced by 6-OHDA promotes the expression of an impairment-related lipidomic signature in CSF, and the level of eicosanoids, CE, TG families, and TG (16:0_20:0_18:1) in CSF may reveal pathological changes in the midbrain after 6-OHDA insult

Formal Feature Identification of Vernacular Architecture Based on Deep Learning—A Case Study of Jiangsu Province, China

As an important sustainable architecture, vernacular architecture plays a significant role in influencing both regional architecture and contemporary architecture. Vernacular architecture is the traditional and natural way of building that involves necessary changes and continuous adjustments. The formal characteristics of vernacular architecture are accumulated in the process of sustainable development. However, most of the research methods on vernacular architecture and its formal features are mainly based on qualitative analysis. It is therefore necessary to complement this with scientific and quantitative means. Based on the object detection technique, this paper proposes a quantitative model that can effectively recognize and detect the formal features of architecture. First, the Chinese traditional architecture image dataset (CTAID) is constructed, and the model is trained. Each image has the formal features of “deep eave”, “zheng wen”, “gable” and “long window” marked by experts. Then, to accurately identify the formal features of vernacular architecture in Jiangsu Province, the Jiangsu traditional vernacular architecture image dataset (JTVAID) is created as the object dataset. This dataset contains images of vernacular architecture from three different regions: northern, central, and southern Jiangsu. After that, the object dataset is used to predict the architectural characteristics of different regions in Jiangsu Province. Combined with the test results, it can be seen that there are differences in the architectural characteristics of the northern, middle, and southern Jiangsu. Among them, the “deep eave”, “zheng wen”, “gable”, and “long window” features of the vernacular architecture in southern Jiangsu are very outstanding. Compared with middle Jiangsu, northern Jiangsu has obvious features of “zheng wen” and “gable”, with recognition rates of 45.8% and 27.5%, respectively. The features of “deep eave” and “long windows” are more prominent in middle Jiangsu, with recognition rates of 50.9% and 73.5%, respectively. In addition, architectural images of contemporary vernacular architecture practice projects in the Jiangsu region are selected and they are inputted into the AOD R-CNN model proposed in this paper. The results obtained can effectively identify the feature style of Jiangsu vernacular architecture. The deep-learning-based approach proposed in this study can be used to identify vernacular architecture form features. It can also be used as an effective method for assessing territorial features in the sustainable development of vernacular architecture