Demonstrating nonlocality induced teleportation through Majorana bound states in a semiconductor nanowire

It was predicted by Tewari [Phys. Rev. Lett. {\bf 100}, 027001 (2008)] that a teleportationlike electron transfer phenomenon is one of the novel consequences of the existence of Majorana fermion, because of the inherently nonlocal nature. In this work we consider a concrete realization and measurement scheme for this interesting behavior, based on a setup consisting of a pair of quantum dots which are tunnel-coupled to a semiconductor nanowire and are jointly measured by two point-contact detectors. We analyze the teleportation dynamics in the presence of measurement backaction and discuss how the teleportation events can be identified from the current trajectories of strong response detectors.Comment: 5 pages, 3 figure

Deep Image Harmonization

Compositing is one of the most common operations in photo editing. To generate realistic composites, the appearances of foreground and background need to be adjusted to make them compatible. Previous approaches to harmonize composites have focused on learning statistical relationships between hand-crafted appearance features of the foreground and background, which is unreliable especially when the contents in the two layers are vastly different. In this work, we propose an end-to-end deep convolutional neural network for image harmonization, which can capture both the context and semantic information of the composite images during harmonization. We also introduce an efficient way to collect large-scale and high-quality training data that can facilitate the training process. Experiments on the synthesized dataset and real composite images show that the proposed network outperforms previous state-of-the-art methods

Mechanisms Of Intrinsic Epileptogenesis In Human Gelastic Seizures With Hypothalamic Hamartoma

Human hypothalamic hamartoma (HH) is a rare developmental malformation often characterized by gelastic seizures, which are refractory to medical therapy. Ictal EEG recordings from the HH have demonstrated that the epileptic source of gelastic seizures lies within the HH lesion itself. Recent advances in surgical techniques targeting HH have led to dramatic improvements in seizure control, which further supports the hypothesis that gelastic seizures originate within the HH. However, the basic cellular and molecular mechanisms of epileptogenesis in this subcortical lesion are poorly understood. Since 2003, Barrow Neurological Institute has maintained a multidisciplinary clinical program to evaluate and treat patients with HH. This program has provided a unique opportunity to investigate the basic mechanisms of epileptogenesis using surgically resected HH tissue. The first report on the electrophysiological properties of HH neurons was published in 2005. Since then, ongoing research has provided additional insights into the mechanisms by which HH generate seizure activity. In this review, we summarize this progress and propose a cellular model that suggests that GABA-mediated excitation contributes to epileptogenesis in HH lesions

Text Is All You Need: Learning Language Representations for Sequential Recommendation

Sequential recommendation aims to model dynamic user behavior from historical interactions. Existing methods rely on either explicit item IDs or general textual features for sequence modeling to understand user preferences. While promising, these approaches still struggle to model cold-start items or transfer knowledge to new datasets. In this paper, we propose to model user preferences and item features as language representations that can be generalized to new items and datasets. To this end, we present a novel framework, named Recformer, which effectively learns language representations for sequential recommendation. Specifically, we propose to formulate an item as a "sentence" (word sequence) by flattening item key-value attributes described by text so that an item sequence for a user becomes a sequence of sentences. For recommendation, Recformer is trained to understand the "sentence" sequence and retrieve the next "sentence". To encode item sequences, we design a bi-directional Transformer similar to the model Longformer but with different embedding layers for sequential recommendation. For effective representation learning, we propose novel pretraining and finetuning methods which combine language understanding and recommendation tasks. Therefore, Recformer can effectively recommend the next item based on language representations. Extensive experiments conducted on six datasets demonstrate the effectiveness of Recformer for sequential recommendation, especially in low-resource and cold-start settings.Comment: accepted to KDD 202

Expression of the apoptosis-related genes BCL-2 and BAD in human breast carcinoma and their associated relationship with chemosensitivity

<p>Abstract</p> <p>Objective</p> <p>To evaluate the expression of BCL-2 and BAD genes in tissues of breast carcinoma and investigate the relationship between the expression of BCL-2 and BAD in breast cancer cells with chemosensitivity.</p> <p>Methods</p> <p>Immunohistochemical technique was used to detect the expression of BCL-2, BAD in 10 normal breast tissues, 10 breast fibroadenoma tissues, 40 youth human breast carcinoma tissues, 40 menopause human breast carcinoma tissues. And to detect the expression of ER, PR in 80 human breast carcinoma tissues. 20 Surgical samples of breast cancer, diagnosed by pathology, were obtained from The First Affiliated Hospital of Chongqing Medical University. The cancer sample cells were cultured separately in the incubator at 37°C, 5% CO₂in vitro. The rate of inhibition of cancer cells in 4 kinds of anticancer drugs-- Epirubicin Adriamycin (EADM),5-Fluorouracil (5-Fu), Navelbine(NVB) and Diaminedichloroplatinum (DDP), were assayed by MTT method.</p> <p>Results</p> <p>The expression of BCL-2, BAD genes in young human breast carcinoma tissues were lower than that in menopause human breast carcinoma tissues (<b><it>P </it>< 0.05</b>). There was a negative correlation between the positive expression rate of BCL-2 and histologic grade or the lymph node metastasis (<b><it>P </it>< 0.05</b>). There was a positive correlation between the expression rates of BCL-2 and of ER, PR (<b><it>P </it>< 0.05</b>). The expression of BAD had no relationship with the expression of ER, PR, histologic grade and the lymph node metastasis(<b><it>P </it>= <it>NS</it></b>). Sensitivity rates of 20 breast cancer cells in 0.1 × PPC within 48 h in vitro were 30% EADM,20% 5-Fu,45% NVB and 25% DDP. Respectively, the rate of inhibition of EADM,5- Fu, NVB and DDP were significantly higher in the BCL-2 negative cancer cells than in the BCL-2 positive cancer cells. A negative correlation was found between expression of BCL-2 and chemosensitivity for all the 4 anticancer drugs. The inhibition rates of EADM and NVB were significantly lower in the BAD negative cancer cells than in the BAD positive cancer cells. A positive correlation was found between expression of BAD and chemosensitivity for Epirubicin.</p> <p>Conclusion</p> <p>The expression of BCL-2 and BAD can be used as prognosis factors of breast cancer. Detection of the BCL-2 protein expression level, particularly, combined with the detection of the expression of BCL-2 and BAD as well as ER and PR were helpful in confirming the prognosis of breast carcinoma. The combined detection of BCL-2 and BAD may be markers for predicting the responses to anticancer drugs.</p

Mitochondrial BNIP3 upregulation precedes endonuclease G translocation in hippocampal neuronal death following oxygen-glucose deprivation

<p>Abstract</p> <p>Background</p> <p>Caspase-independent apoptotic pathways are suggested as a mechanism for the delayed neuronal death following ischemic insult. However, the underlying signalling mechanisms are largely unknown. Recent studies imply the involvement of several mitochondrial proteins, including endonuclease G (EndoG) and Bcl-2/adenovirus E1B 19 kDa-interacting protein (BNIP3), in the pathway of non-neuronal cells.</p> <p>Results</p> <p>In this report, using western blot analysis and immunocytochemistry, we found that EndoG upregulates and translocates from mitochondria to nucleus in a time-dependent manner in cultured hippocampal neurons following oxygen-glucose deprivation (OGD). Moreover, the translocation of EndoG occurs hours before the observable nuclear pyknosis. Importantly, the mitochondrial upregulation of BNIP3 precedes the translocation of EndoG. Forced expression of BNIP3 increases the nuclear translocation of EndoG and neuronal death while knockdown of BNIP3 decreases the OGD-induced nuclear translocation of EndoG and neuronal death.</p> <p>Conclusion</p> <p>These results suggest that BNIP3 and EndoG play important roles in hippocampal neuronal apoptosis following ischemia, and mitochondrial BNIP3 is a signal protein upstream of EndoG that can induce neuronal death.</p

RF-Net: An End-to-End Image Matching Network based on Receptive Field

This paper proposes a new end-to-end trainable matching network based on receptive field, RF-Net, to compute sparse correspondence between images. Building end-to-end trainable matching framework is desirable and challenging. The very recent approach, LF-Net, successfully embeds the entire feature extraction pipeline into a jointly trainable pipeline, and produces the state-of-the-art matching results. This paper introduces two modifications to the structure of LF-Net. First, we propose to construct receptive feature maps, which lead to more effective keypoint detection. Second, we introduce a general loss function term, neighbor mask, to facilitate training patch selection. This results in improved stability in descriptor training. We trained RF-Net on the open dataset HPatches, and compared it with other methods on multiple benchmark datasets. Experiments show that RF-Net outperforms existing state-of-the-art methods.Comment: 9 pages, 6 figure