A finite-difference method for the one-dimensional time-dependent schrödinger equation on unbounded domain

AbstractA finite-difference scheme is proposed for the one-dimensional time-dependent Schrödinger equation. We introduce an artificial boundary condition to reduce the original problem into an initial-boundary value problem in a finite-computational domain, and then construct a finite-difference scheme by the method of reduction of order to solve this reduced problem. This scheme has been proved to be uniquely solvable, unconditionally stable, and convergent. Some numerical examples are given to show the effectiveness of the scheme

Gender Differences in Giving Motivations for Bequest Donors and Non-Donors

This study explores gender differences in the inclusion of a charitable provision in one’s will. We found that overall among representative samples of households polled in different regions of the U.S., gender is not a statistically significant predictor of the intent to leave a charitable bequest, after controlling for other factors, such as age, income, and marital status.Made possible by an Association of Fundraising Professionals (AFP) research grant supported by Legacy Leader

Emerging Synergies Between Large Language Models and Machine Learning in Ecommerce Recommendations

With the boom of e-commerce and web applications, recommender systems have become an important part of our daily lives, providing personalized recommendations based on the user's preferences. Although deep neural networks (DNNs) have made significant progress in improving recommendation systems by simulating the interaction between users and items and incorporating their textual information, these DNN-based approaches still have some limitations, such as the difficulty of effectively understanding users' interests and capturing textual information. It is not possible to generalize to different seen/unseen recommendation scenarios and reason about their predictions. At the same time, the emergence of large language models (LLMs), represented by ChatGPT and GPT-4, has revolutionized the fields of natural language processing (NLP) and artificial intelligence (AI) due to their superior capabilities in the basic tasks of language understanding and generation, and their impressive generalization and reasoning capabilities. As a result, recent research has sought to harness the power of LLM to improve recommendation systems. Given the rapid development of this research direction in the field of recommendation systems, there is an urgent need for a systematic review of existing LLM-driven recommendation systems for researchers and practitioners in related fields to gain insight into. More specifically, we first introduced a representative approach to learning user and item representations using LLM as a feature encoder. We then reviewed the latest advances in LLMs techniques for collaborative filtering enhanced recommendation systems from the three paradigms of pre-training, fine-tuning, and prompting. Finally, we had a comprehensive discussion on the future direction of this emerging field

Adaptive absorbing boundary conditions for Schrodinger-type equations: application to nonlinear and multi-dimensional problems

We propose an adaptive approach in picking the wave-number parameter of absorbing boundary conditions for Schr\"{o}dinger-type equations. Based on the Gabor transform which captures local frequency information in the vicinity of artificial boundaries, the parameter is determined by an energy-weighted method and yields a quasi-optimal absorbing boundary conditions. It is shown that this approach can minimize reflected waves even when the wave function is composed of waves with different group velocities. We also extend the split local absorbing boundary (SLAB) method [Z. Xu and H. Han, {\it Phys. Rev. E}, 74(2006), pp. 037704] to problems in multidimensional nonlinear cases by coupling the adaptive approach. Numerical examples of nonlinear Schr\"{o}dinger equations in one- and two dimensions are presented to demonstrate the properties of the discussed absorbing boundary conditions.Comment: 18 pages; 12 figures. A short movie for the 2D NLS equation with absorbing boundary conditions can be downloaded at http://home.ustc.edu.cn/~xuzl/movie.avi. To appear in Journal of Computational Physic

Enterocyte STAT5 promotes mucosal wound healing via suppression of myosin light chain kinase-mediated loss of barrier function and inflammation

Epithelial myosin light chain kinase (MLCK)-dependent barrier dysfunction contributes to the pathogenesis of inflammatory bowel diseases (IBD). We reported that epithelial GM-CSF–STAT5 signalling is essential for intestinal homeostatic response to gut injury. However, mechanism, redundancy by STAT5 or cell types involved remained foggy. We here generated intestinal epithelial cell (IEC)-specific STAT5 knockout mice, these mice exhibited a delayed mucosal wound healing and dysfunctional intestinal barrier characterized by elevated levels of NF-κB activation and MLCK, and a reduction of zonula occludens expression in IECs. Deletion of MLCK restored intestinal barrier function in STAT5 knockout mice, and facilitated mucosal wound healing. Consistently, knockdown of stat5 in IEC monolayers led to increased NF-κB DNA binding to MLCK promoter, myosin light chain phosphorylation and tight junction (TJ) permeability, which were potentiated by administration of tumour necrosis factor-α (TNF-α), and prevented by concurrent NF-κB knockdown. Collectively, enterocyte STAT5 signalling protects against TJ barrier dysfunction and promotes intestinal mucosal wound healing via an interaction with NF-κB to suppress MLCK. Targeting IEC STAT5 signalling may be a novel therapeutic approach for treating intestinal barrier dysfunction in IBD

GlanceVAD: Exploring Glance Supervision for Label-efficient Video Anomaly Detection

In recent years, video anomaly detection has been extensively investigated in both unsupervised and weakly supervised settings to alleviate costly temporal labeling. Despite significant progress, these methods still suffer from unsatisfactory results such as numerous false alarms, primarily due to the absence of precise temporal anomaly annotation. In this paper, we present a novel labeling paradigm, termed "glance annotation", to achieve a better balance between anomaly detection accuracy and annotation cost. Specifically, glance annotation is a random frame within each abnormal event, which can be easily accessed and is cost-effective. To assess its effectiveness, we manually annotate the glance annotations for two standard video anomaly detection datasets: UCF-Crime and XD-Violence. Additionally, we propose a customized GlanceVAD method, that leverages gaussian kernels as the basic unit to compose the temporal anomaly distribution, enabling the learning of diverse and robust anomaly representations from the glance annotations. Through comprehensive analysis and experiments, we verify that the proposed labeling paradigm can achieve an excellent trade-off between annotation cost and model performance. Extensive experimental results also demonstrate the effectiveness of our GlanceVAD approach, which significantly outperforms existing advanced unsupervised and weakly supervised methods. Code and annotations will be publicly available at https://github.com/pipixin321/GlanceVAD.Comment: 21 page

Rapid assessment of early biophysical changes in K562 cells during apoptosis determined using dielectrophoresis

Apoptosis, or programmed cell death, is a vital cellular process responsible for causing cells to self-terminate at the end of their useful life. Abrogation of this process is commonly linked to cancer, and rapid detection of apoptosis in vitro is vital to the discovery of new anti-cancer drugs. In this paper, we describe the application of the electrical phenomenon dielectrophoresis for detecting apoptosis at very early stages after drug induction, on the basis of changes in electrophysiological properties. Our studies have revealed that K562 (human myelogenous leukemia) cells show a persistent elevation in the cytoplasmic conductivity occurring as early as 30 minutes following exposure to staurosporine. This method therefore allows a far more rapid detection method than existing biochemical marker methods

An integrated software for virus community sequencing data analysis

BACKGROUND: A virus community is the spectrum of viral strains populating an infected host, which plays a key role in pathogenesis and therapy response in viral infectious diseases. However automatic and dedicated pipeline for interpreting virus community sequencing data has not been developed yet.RESULTS: We developed Quasispecies Analysis Package (QAP), an integrated software platform to address the problems associated with making biological interpretations from massive viral population sequencing data. QAP provides quantitative insight into virus ecology by first introducing the definition "virus OTU" and supports a wide range of viral community analyses and results visualizations. Various forms of QAP were developed in consideration of broader users, including a command line, a graphical user interface and a web server. Utilities of QAP were thoroughly evaluated with high-throughput sequencing data from hepatitis B virus, hepatitis C virus, influenza virus and human immunodeficiency virus, and the results showed highly accurate viral quasispecies characteristics related to biological phenotypes.CONCLUSIONS: QAP provides a complete solution for virus community high throughput sequencing data analysis, and it would facilitate the easy analysis of virus quasispecies in clinical applications.</p

More Than Just Statics: Static and Temporal Dynamic Changes in Intrinsic Brain Activity in Unilateral Temporal Lobe Epilepsy

BACKGROUND: Temporal lobe epilepsy (TLE) is the most prevalent refractory focal epilepsy and is more likely accompanied by cognitive impairment. The fully understanding of the neuronal activity underlying TLE is of great significance. OBJECTIVE: This study aimed to comprehensively explore the potential brain activity abnormalities affected by TLE and detect whether the changes were associated with cognition. METHODS: Six static intrinsic brain activity (IBA) indicators [amplitude of low-frequency fluctuation (ALFF), fractional ALFF (fALFF), regional homogeneity (ReHo), degree centrality (DC), global signal correlation (GSCorr), and voxel-mirrored homotopic connectivity (VMHC)] and their corresponding dynamic indicators, such as dynamic ALFF (dALFF), dynamic fALFF (dfALFF), dynamic ReHo (dReHo), dynamic DC (dDC), dynamic VMHC (dVMHC), and dynamic GSCorr (dGSCorr), in 57 patients with unilateral TLE and 42 healthy volunteers were compared. Correlation analyses were also performed between these indicators in areas displaying group differences and cognitive function, epilepsy duration, and severity. RESULTS: Marked overlap was present among the abnormal brain regions detected using various static and dynamic indicators, primarily including increased ALFF/dALFF/fALFF in the bilateral medial temporal lobe and thalamus, decreased ALFF/dALFF/fALFF in the frontal lobe contralateral to the epileptogenic side, decreased fALFF, ReHo, dReHo, DC, dDC, GSCorr, dGSCorr, and VMHC in the temporal neocortex ipsilateral to the epileptogenic foci, decreased dReHo, dDC, dGSCorr, and dVMHC in the occipital lobe, and increased ALFF, fALFF, dfALFF, ReHo, and DC in the supplementary motor area ipsilateral to the epileptogenic foci. Furthermore, most IBA indicators in the abnormal brain region significantly correlated with the duration of epilepsy and several cognitive scale scores ( CONCLUSION: The combined application of static and dynamic IBA indicators could comprehensively reveal more real abnormal neuronal activity and the impairment and compensatory mechanisms of cognitive function in TLE. Moreover, it might help in the lateralization of epileptogenic foci and exploration of the transmission and inhibition pathways of epileptic activity

Alterations in Static and Dynamic Regional Homogeneity in Mesial Temporal Lobe Epilepsy With and Without Initial Precipitating Injury

Objectives Initial precipitating injury (IPI) such as febrile convulsion and intracranial infection will increase the susceptibility to epilepsy. It is still unknown if the functional deficits differ between mesial temporal lobe epilepsy with IPI (mTLE-IPI) and without IPI (mTLE-NO). Methods We recruited 25 mTLE-IPI patients, 35 mTLE-NO patients and 33 healthy controls (HC). Static regional homogeneity (sReHo) and dynamic regional homogeneity (dReHo) were then adopted to estimate the alterations of local neuronal activity. One-way analysis of variance was used to analyze the differences between the three groups in sReHo and dReHo. Then the results were utilized as masks for further between-group comparisons. Besides, correlation analyses were carried out to detect the potential relationships between abnormal regional homogeneity indicators and clinical characteristics. Results When compared with HC, the bilateral thalamus and the visual cortex in mTLE-IPI patients showed an increase in both sReHo and variability of dReHo. Besides, mTLE-IPI patients exhibited decreased sReHo in the right cerebellum crus1/crus2, inferior parietal lobule and temporal neocortex. mTLE-NO patients showed decreased sReHo and variability of dReHo in the bilateral temporal neocortex compared with HC. Increased sReHo and variability of dReHo were found in the bilateral visual cortex when mTLE-IPI patients was compared with mTLE-NO patients, as well as increased variability of dReHo in the left thalamus and decreased sReHo in the right dorsolateral prefrontal cortex. Additionally, we discovered a negative correlation between the national hospital seizure severity scale testing score and sReHo in the right cerebellum crus1 in mTLE-IPI patients. Conclusion According to the aforementioned findings, both mTLE-IPI and mTLE-NO patients had significant anomalies in local neuronal activity, although the functional deficits were much severer in mTLE-IPI patients. The use of sReHo and dReHo may provide a novel insight into the impact of the presence of IPI on the development of mTLE