Senior year = 高三

Film Director: Zhou Hao (周浩) Film Release Year: 2005https://commons.ln.edu.hk/ccs_worksheet/1008/thumbnail.jp

GPER-induced signaling is essential for the survival of breast cancer stem cells.

G protein-coupled estrogen receptor-1 (GPER), a member of the G protein-coupled receptor (GPCR) superfamily, mediates estrogen-induced proliferation of normal and malignant breast epithelial cells. However, its role in breast cancer stem cells (BCSCs) remains unclear. Here we showed greater expression of GPER in BCSCs than non-BCSCs of three patient-derived xenografts of ER- /PR+ breast cancers. GPER silencing reduced stemness features of BCSCs as reflected by reduced mammosphere forming capacity in vitro, and tumor growth in vivo with decreased BCSC populations. Comparative phosphoproteomics revealed greater GPER-mediated PKA/BAD signaling in BCSCs. Activation of GPER by its ligands, including tamoxifen (TMX), induced phosphorylation of PKA and BAD-Ser118 to sustain BCSC characteristics. Transfection with a dominant-negative mutant BAD (Ser118Ala) led to reduced cell survival. Taken together, GPER and its downstream signaling play a key role in maintaining the stemness of BCSCs, suggesting that GPER is a potential therapeutic target for eradicating BCSCs

Large shift current via in-gap and charge-neutral exciton excitations in BN nanotubes and single BN layer

We perform {\it ab initio} many-body calculations to investigate the exciton shift current in small diameter zigzag BN nanotubes and also single BN sheet, using the GW plus Bethe-Salpeter equation (GW-BSE) method with the newly developed efficient algorithms. Our GW-BSE calculations reveal a giant in-gap peak in the shift current spectrum in all the studied BN systems due to the excitation of the A exciton. The peak value of the excitonic shift current is more than three times larger than that of the quasiparticle shift current, and is attributed to the gigantic enhancement of the optical dipole matrix element by the A exciton resonance. The effective exciton shift current conductivity is nearly ten times larger than the largest shift conductivity observed in ferroelectric semiconductors. Importantly, the direction of the shift current in the BN nanotubes is found to be independent of the tube chirality ($n,0$) (or diameter), contrary to the simple rule of $sgn(J_\text{shift})=\text{mod}(n,3)$ predicted by previous model Hamiltonian studies. Finally, our {\it ab initio} calculations also show that the exciton excitation energies decrease significantly with the decreasing diameter due to the curvature-induced orbital rehybridization in small diameter zigzag BN nanotubes.Comment: 12 pages, 8 figures and 2 table

Acupuncture for the Treatment of Opiate Addiction

Acupuncture is an accepted treatment worldwide for various clinical conditions, and the effects of acupuncture on opiate addiction have been investigated in many clinical trials. The present review systematically analyzed data from randomized clinical trials published in Chinese and English since 1970. We found that the majority agreed on the efficacy of acupuncture as a strategy for the treatment of opiate addiction. However, some of the methods in several included trials have been criticized for their poor quality. This review summarizes the quality of the study design, the types of acupuncture applied, the commonly selected acupoints or sites of the body, the effectiveness of the treatment, and the possible mechanism underlying the effectiveness of acupuncture in these trials

eHint: An Efficient Protocol for Uploading Small-Size IoT Data

IoT (Internet of Things) has attracted a lot of attention recently. IoT devices need to report their data or status to base stations at various frequencies. The IoT communications observed by a base station normally exhibit the following characteristics: (1) massively connected, (2) lightly loaded per packet, and (3) periodical or at least mostly predictable. The current design principals of communication networks, when applied to IoT scenarios, however, do not fit well to these requirements. When a large number of devices contend to send small packets, the signaling overhead is not cost-effective. To address this problem, our previous work [1] proposes the Hint protocol, which is slot-based and schedule- oriented for uploading IoT devices' data. In this work, we extend [1] to support data transmissions for multiple resource blocks. We assume that the uplink payloads from IoT devices are small, each taking very few slots (or resource blocks), but devices are massive. The main idea is to "encode" information in a tiny broadcast that allows each device to "decode" its transmission slots, thus significantly reducing transmission overheads and contention overheads. Our simulation results verify that the protocol can significantly increase channel utilization compared with traditional schemes

Multi-Slot Allocation Protocols for Massive IoT Devices with Small-Size Uploading Data

The emergence of Internet of Things applications introduces new challenges such as massive connectivity and small data transmission. In traditional data transmission protocols, an ID (i.e., IP address or MAC address) is usually included in a packet so that its receiver is able to know who sent the packet. However, this introduces the big head-small body problem for light payload. To address this problem, the Hint protocols have been proposed. The main idea is to 'encode' information in a tiny broadcast Hint message that allows devices to 'decode' their transmission slots. Thus, it can significantly reduce transmission and contention overheads. In this letter, we extend eHint to support multi-slot data transmissions. Several efficient protocols are proposed. Our simulation results validate that the protocols can significantly increase the number of successfully transmitted devices, channel utilization, and payload of transmitted devices compared with eHint

How to Reduce Unexpected eMBMS Session Disconnection: Design and Performance Analysis

In 3GPP eMBMS, sometimes sessions will be disconnected unexpectedly due to the miss of session keys. Although rekeying can prevent old users from getting multicast data, it also causes authorized users to miss subsequent data if they miss the key update messages. Thus, re-authentication is needed to obtain lost keys from KMM. We point out this problem in our previous work 1. In this paper, we further propose a new KeySet algorithm, which can pre-issue a number of keys to users when they join eMBMS. The advantage is that a user can still decode multicast data even if it misses some key updates tentatively. However, the cost is that allowing some old users to freely enjoying multicast for some time. In this paper, we quantify the tradeoff and derive the optimal case

T5lephone: Bridging Speech and Text Self-supervised Models for Spoken Language Understanding via Phoneme level T5

In Spoken language understanding (SLU), a natural solution is concatenating pre-trained speech models (e.g. HuBERT) and pretrained language models (PLM, e.g. T5). Most previous works use pretrained language models with subword-based tokenization. However, the granularity of input units affects the alignment of speech model outputs and language model inputs, and PLM with character-based tokenization is underexplored. In this work, we conduct extensive studies on how PLMs with different tokenization strategies affect spoken language understanding task including spoken question answering (SQA) and speech translation (ST). We further extend the idea to create T5lephone(pronounced as telephone), a variant of T5 that is pretrained using phonemicized text. We initialize T5lephone with existing PLMs to pretrain it using relatively lightweight computational resources. We reached state-of-the-art on NMSQA, and the T5lephone model exceeds T5 with other types of units on end-to-end SQA and ST