Deterministic End-to-End Transmission to Optimize the Network Efficiency and Quality of Service: A Paradigm Shift in 6G

Toward end-to-end mobile service provision with optimized network efficiency and quality of service, tremendous efforts have been devoted in upgrading mobile applications, transport and internet networks, and wireless communication networks for many years. However, the inherent loose coordination between different layers in the end-to-end communication networks leads to unreliable data transmission with uncontrollable packet delay and packet error rate, and a terrible waste of network resources incurred for data re-transmission. In an attempt to shed some lights on how to tackle these challenges, design methodologies and some solutions for deterministic end-to-end transmission for 6G and beyond are presented, which will bring a paradigm shift to the end-to-end wireless communication networks.Comment: 5 pages, 2 figure

The archaeal ATPase PINA interacts with the helicase Hjm via its carboxyl terminal KH domain remodeling and processing replication fork and Holliday junction.

PINA is a novel ATPase and DNA helicase highly conserved in Archaea, the third domain of life. The PINA from Sulfolobus islandicus (SisPINA) forms a hexameric ring in crystal and solution. The protein is able to promote Holliday junction (HJ) migration and physically and functionally interacts with Hjc, the HJ specific endonuclease. Here, we show that SisPINA has direct physical interaction with Hjm (Hel308a), a helicase presumably targeting replication forks. In vitro biochemical analysis revealed that Hjm, Hjc, and SisPINA are able to coordinate HJ migration and cleavage in a concerted way. Deletion of the carboxyl 13 amino acid residues impaired the interaction between SisPINA and Hjm. Crystal structure analysis showed that the carboxyl 70 amino acid residues fold into a type II KH domain which, in other proteins, functions in binding RNA or ssDNA. The KH domain not only mediates the interactions of PINA with Hjm and Hjc but also regulates the hexameric assembly of PINA. Our results collectively suggest that SisPINA, Hjm and Hjc work together to function in replication fork regression, HJ formation and HJ cleavage

On the Dual Attack of LWE Schemes in the Presence of Hints

Combining theoretical-based traditional attack method with practical-based side-channel attack method provides more accurate security estimations for post-quantum cryptosystems. In CRYPTO 2020, Dachman-Soled et al. integrated hints from side-channel information to the primal attack against LWE schemes. This paper develops a general Fourier analytic framework to work with the dual attack in the presence of hints. Distinguishers that depend on specific geometric properties related to hints are established. The Fourier transform of discretized multivariate conditional Gaussian distribution on $\mathbb{Z}_q^d$ is carefully computed and estimated, some geometric characteristics of the resulting distinguisher are explored and a new model of dual attack is proposed. In our framework, an adversary performs the BKZ algorithm directly in a projected lattice to find short projection components, and then recovers them by MLLL algorithm to make a distinction. This method relies on a reasonable assumption and is backed up by naturally formed mathematical arguments. The improvements and the assumption are validated by experiments. For examples, for a Kyber768 instance, with 200 hints, the blocksize can be reduced by at least 188 and the time complexity can be reduced by a factor of greater than $2^{55}$. After adding 300 hints to a FireSaber instance, even in the worst case, the blocksize drops from 819 to 542, and the cost drops from $2^{255.61}$ to $2^{174.72}$

Multi-task Learning-based CSI Feedback Design in Multiple Scenarios

For frequency division duplex systems, the essential downlink channel state information (CSI) feedback includes the links of compression, feedback, decompression and reconstruction to reduce the feedback overhead. One efficient CSI feedback method is the Auto-Encoder (AE) structure based on deep learning, yet facing problems in actual deployments, such as selecting the deployment mode when deploying in a cell with multiple complex scenarios. Rather than designing an AE network with huge complexity to deal with CSI of all scenarios, a more realistic mode is to divide the CSI dataset by region/scenario and use multiple relatively simple AE networks to handle subregions' CSI. However, both require high memory capacity for user equipment (UE) and are not suitable for low-level devices. In this paper, we propose a new user-friendly-designed framework based on the latter multi-tasking mode. Via Multi-Task Learning, our framework, Single-encoder-to-Multiple-decoders (S-to-M), designs the multiple independent AEs into a joint architecture: a shared encoder corresponds to multiple task-specific decoders. We also complete our framework with GateNet as a classifier to enable the base station autonomously select the right task-specific decoder corresponding to the subregion. Experiments on the simulating multi-scenario CSI dataset demonstrate our proposed S-to-M's advantages over the other benchmark modes, i.e., significantly reducing the model complexity and the UE's memory consumptionComment: 31 pages, 13 figures, 10 Table

Video-assisted thoracic bronchial sleeve lobectomy with bronchoplasty for treatment of lung cancer confined to a single lung lobe: a case series of Chinese patients

BACKGROUND: The outcomes of video-assisted thoracic bronchial sleeve lobectomy (VABSL), a minimally invasive video-assisted thoracoscopic (VATS) lobectomy, are mostly unknown in Chinese patients. OBJECTIVES: To investigate operative and postoperative outcomes of VABSL in a cases series of Chinese patients with lung cancer. METHODS: Retrospective study of 9 patients (male:female 8:1; mean age 59.4 ± 17.6 years, ranging 21–79 years) diagnosed with lung cancer of a single lobe, treated with VABSL between March 2009 and November 2011, and followed up for at least 2 months (mean follow-up: 14.17 ± 12.91 months). Operative outcomes (tumor size, operation time, estimated blood loss and blood transfusion), postoperative outcomes (intensive care unit [ICU] stay, hospitalization length and pathological tumor stage), death, tumor recurrence and safety were assessed. RESULTS: Patients were diagnosed with carcinoid cancer (11.1%), squamous carcinoma (66.7%) or small cell carcinoma (22.2%), affecting the right (77.8%) or left (22.2%) lung lobes in the upper (55.6%), middle (11.1%) or lower (33.3%) regions. TNM stages were T2 (88.9%) or T3 (11.1%); N0 (66.7%), N1 (11.1%) or N2 (22.2%); and M0 (100%). No patient required conversion to thoracotomy. Mean tumor size, operation time and blood loss were 2.50 ± 0.75 cm, 203 ± 20 min and 390 ± 206 ml, respectively. Patients were treated in the ICU for 18.7 ± 0.7 hours, and overall hospitalization duration was 20.8 ± 2.0 days. No deaths, recurrences or severe complications were reported. CONCLUSIONS: VABSL surgery is safe and effective for treatment of lung cancer by experienced physicians, warranting wider implementation of VABSL and VATS training in China

Dynamics of American Giving: Descriptive Evidence

Almost all of the scientific literature on charitable giving is implicitly based on a static paradigm which posits there are non-donors who never give and donors who habitually give year-in/year-out to a specific charitable purpose. This article presents evidence that charitable giving is not static, but dynamic: Few Americans never give, and among Americans that donate the majority are switchers—giving in some years but not others or switching from one charitable purpose to another. The implications are that a static perspective is misleading, and research questions should place more emphasis on the time dimension of charitable giving

Prompt-enhanced Hierarchical Transformer Elevating Cardiopulmonary Resuscitation Instruction via Temporal Action Segmentation

The vast majority of people who suffer unexpected cardiac arrest are performed cardiopulmonary resuscitation (CPR) by passersby in a desperate attempt to restore life, but endeavors turn out to be fruitless on account of disqualification. Fortunately, many pieces of research manifest that disciplined training will help to elevate the success rate of resuscitation, which constantly desires a seamless combination of novel techniques to yield further advancement. To this end, we collect a custom CPR video dataset in which trainees make efforts to behave resuscitation on mannequins independently in adherence to approved guidelines, thereby devising an auxiliary toolbox to assist supervision and rectification of intermediate potential issues via modern deep learning methodologies. Our research empirically views this problem as a temporal action segmentation (TAS) task in computer vision, which aims to segment an untrimmed video at a frame-wise level. Here, we propose a Prompt-enhanced hierarchical Transformer (PhiTrans) that integrates three indispensable modules, including a textual prompt-based Video Features Extractor (VFE), a transformer-based Action Segmentation Executor (ASE), and a regression-based Prediction Refinement Calibrator (PRC). The backbone of the model preferentially derives from applications in three approved public datasets (GTEA, 50Salads, and Breakfast) collected for TAS tasks, which accounts for the excavation of the segmentation pipeline on the CPR dataset. In general, we unprecedentedly probe into a feasible pipeline that genuinely elevates the CPR instruction qualification via action segmentation in conjunction with cutting-edge deep learning techniques. Associated experiments advocate our implementation with multiple metrics surpassing 91.0%.Comment: Transformer for Cardiopulmonary Resuscitatio

The effect of celecoxib on tumor growth in ovarian cancer cells and a genetically engineered mouse model of serous ovarian cancer

Our objective was to evaluate the effect of the COX-2 inhibitor, celecoxib, on (1) proliferation and apoptosis in human ovarian cancer cell lines and primary cultures of ovarian cancer cells, and (2) inhibition of tumor growth in a genetically engineered mouse model of serous ovarian cancer under obese and non-obese conditions. Celecoxib inhibited cell proliferation in three ovarian cancer cell lines and five primary cultures of human ovarian cancer after 72 hours of exposure. Treatment with celecoxib resulted in G1 cell cycle arrest, induction of apoptosis, inhibition of cellular adhesion and invasion and reduction of expression of hTERT mRNA and COX-2 protein in all of the ovarian cancer cell lines. In the KpB mice fed a high fat diet (obese) and treated with celecoxib, tumor weight decreased by 66% when compared with control animals. Among KpB mice fed a low fat diet (non-obese), tumor weight decreased by 46% after treatment with celecoxib. In the ovarian tumors from obese and non-obese KpB mice, treatment with celecoxib as compared to control resulted in decreased proliferation, increased apoptosis and reduced COX-2 and MMP9 protein expression, as assessed by immunohistochemistry. Celecoxib strongly decreased the serum level of VEGF and blood vessel density in the tumors from the KpB ovarian cancer mouse model under obese and non-obese conditions. This work suggests that celecoxib may be a novel chemotherapeutic agent for ovarian cancer prevention and treatment and be potentially beneficial in both obese and non-obese women