ScQ cloud quantum computation for generating Greenberger-Horne-Zeilinger states of up to 10 qubits

We introduce an online for public quantum computation platform, named as ScQ, based on a 1D array of 10-qubit superconducting processor. Single qubit rotation gates can be performed on each qubit. Controlled-NOT (CNOT) gates between nearest-neighbor sites on the 1D array of 10 qubits are available. We show online preparation and verification of Greenberger-Horne-Zeilinger (GHZ) states of up to 10 qubits by this platform, for all possible blocks of qubits in the chain. Both graphic interface and the quantum assembly language methods are presented to achieve the above tasks, which rely on a parameter scanning feature implemented on ScQ. Performance of this quantum computation platform, such as fidelities of the logic gates and details of the superconducting device, are presented

Deep learning driven diagnosis of malignant soft tissue tumors based on dual-modal ultrasound images and clinical indexes

BackgroundSoft tissue tumors (STTs) are benign or malignant superficial neoplasms arising from soft tissues throughout the body with versatile pathological types. Although Ultrasonography (US) is one of the most common imaging tools to diagnose malignant STTs, it still has several drawbacks in STT diagnosis that need improving.ObjectivesThe study aims to establish this deep learning (DL) driven Artificial intelligence (AI) system for predicting malignant STTs based on US images and clinical indexes of the patients.MethodsWe retrospectively enrolled 271 malignant and 462 benign masses to build the AI system using 5-fold validation. A prospective dataset of 44 malignant masses and 101 benign masses was used to validate the accuracy of system. A multi-data fusion convolutional neural network, named ultrasound clinical soft tissue tumor net (UC-STTNet), was developed to combine gray scale and color Doppler US images and clinic features for malignant STTs diagnosis. Six radiologists (R1-R6) with three experience levels were invited for reader study.ResultsThe AI system achieved an area under receiver operating curve (AUC) value of 0.89 in the retrospective dataset. The diagnostic performance of the AI system was higher than that of one of the senior radiologists (AUC of AI vs R2: 0.89 vs. 0.84, p=0.022) and all of the intermediate and junior radiologists (AUC of AI vs R3, R4, R5, R6: 0.89 vs 0.75, 0.81, 0.80, 0.63; p <0.01). The AI system also achieved an AUC of 0.85 in the prospective dataset. With the assistance of the system, the diagnostic performances and inter-observer agreement of the radiologists was improved (AUC of R3, R5, R6: 0.75 to 0.83, 0.80 to 0.85, 0.63 to 0.69; p<0.01).ConclusionThe AI system could be a useful tool in diagnosing malignant STTs, and could also help radiologists improve diagnostic performance

A simulation study on the measurement of D0-D0bar mixing parameter y at BES-III

We established a method on measuring the \dzdzb mixing parameter $y$ for BESIII experiment at the BEPCII $e^+e^-$ collider. In this method, the doubly tagged $\psi(3770) \to D^0 \overline{D^0}$ events, with one $D$ decays to CP-eigenstates and the other $D$ decays semileptonically, are used to reconstruct the signals. Since this analysis requires good $e/\pi$ separation, a likelihood approach, which combines the $dE/dx$, time of flight and the electromagnetic shower detectors information, is used for particle identification. We estimate the sensitivity of the measurement of $y$ to be 0.007 based on a $20fb^{-1}$ fully simulated MC sample.Comment: 6 pages, 7 figure

Longitudinal Genomic Evolution of Conventional Papillary Thyroid Cancer With Brain Metastasis

BackgroundBrain metastasis is extremely rare but predicts dismal prognosis in papillary thyroid cancer (PTC). Dynamic evaluation of stepwise metastatic lesions was barely conducted to identify the longitudinal genomic evolution of brain metastasis in PTC.MethodChronologically resected specimen was analyzed by whole exome sequencing, including four metastatic lymph nodes (lyn 1–4) and brain metastasis lesion (BM). Phylogenetic tree was reconstructed to infer the metastatic pattern and the potential functional mutations.ResultsContrasting with lyn1, ipsilateral metastatic lesions (lyn2–4 and BM) with shared biallelic mutations of TSC2 indicated different genetic originations from multifocal tumors. Lyn 3/4, particularly lyn4 exhibited high genetic similarity with BM. Besides the similar mutational compositions and signatures, shared functional mutations (CDK4R24C, TP53R342*) were observed in lyn3/4 and BM. Frequencies of these mutations gradually increase along with the metastasis progression. Consistently, TP53 knockout and CDK4R24C introduction in PTC cells significantly decreased radioiodine uptake and increased metastatic ability.ConclusionGenomic mutations in CDK4 and TP53 during the tumor evolution may contribute to the lymph node and brain metastasis of PTC

Informing the Design of Privacy-Empowering Tools for the Connected Home

Connected devices in the home represent a potentially grave new privacy threat due to their unfettered access to the most personal spaces in people's lives. Prior work has shown that despite concerns about such devices, people often lack sufficient awareness, understanding, or means of taking effective action. To explore the potential for new tools that support such needs directly we developed Aretha, a privacy assistant technology probe that combines a network disaggregator, personal tutor, and firewall, to empower end-users with both the knowledge and mechanisms to control disclosures from their homes. We deployed Aretha in three households over six weeks, with the aim of understanding how this combination of capabilities might enable users to gain awareness of data disclosures by their devices, form educated privacy preferences, and to block unwanted data flows. The probe, with its novel affordances-and its limitations-prompted users to co-adapt, finding new control mechanisms and suggesting new approaches to address the challenge of regaining privacy in the connected home.Comment: 10 pages, 2 figures. To appear in the Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (CHI '20

Transcriptional activation of the Axl and PDGFR-α by c-Met through a ras- and Src-independent mechanism in human bladder cancer

<p>Abstract</p> <p>Background</p> <p>A cross-talk between different receptor tyrosine kinases (RTKs) plays an important role in the pathogenesis of human cancers.</p> <p>Methods</p> <p>Both NIH-Met5 and T24-Met3 cell lines harboring an inducible human c-Met gene were established. C-Met-related RTKs were screened by RTK microarray analysis. The cross-talk of RTKs was demonstrated by Western blotting and confirmed by small interfering RNA (siRNA) silencing, followed by elucidation of the underlying mechanism. The impact of this cross-talk on biological function was demonstrated by Trans-well migration assay. Finally, the potential clinical importance was examined in a cohort of 65 cases of locally advanced and metastatic bladder cancer patients.</p> <p>Results</p> <p>A positive association of Axl or platelet-derived growth factor receptor-alpha (PDGFR-α) with c-Met expression was demonstrated at translational level, and confirmed by specific siRNA knock-down. The transactivation of c-Met on Axl or PDGFR-α <it>in vitro </it>was through a <it>ras</it>- and Src-independent activation of mitogen-activated protein kinase/extracellular signal-regulated kinase (MEK/ERK) pathway. In human bladder cancer, co-expression of these RTKs was associated with poor patient survival (<it>p </it>< 0.05), and overexpression of c-Met/Axl/PDGFR-α or c-Met alone showed the most significant correlation with poor survival (<it>p </it>< 0.01).</p> <p>Conclusions</p> <p>In addition to c-Met, the cross-talk with Axl and/or PDGFR-α also contributes to the progression of human bladder cancer. Evaluation of Axl and PDGFR-α expression status may identify a subset of c-Met-positive bladder cancer patients who may require co-targeting therapy.</p