Ferromagnetic transition in a one-dimensional spin-orbit-coupled metal and its mapping to a critical point in smectic liquid crystals

We study the quantum phase transition between a paramagnetic and ferromagnetic metal in the presence of Rashba spin-orbit coupling in one dimension. Using bosonization, we analyze the transition by means of renormalization group, controlled by an $\varepsilon$-expansion around the upper critical dimension of two. We show that the presence of Rashba spin-orbit coupling allows for a new nonlinear term in the bosonized action, which generically leads to a fluctuation driven first-order transition. We further demonstrate that the Euclidean action of this system maps onto a classical smectic-A -- C phase transition in a magnetic field in two dimensions. We show that the smectic transition is second-order and is controlled by a new critical point.Comment: 16 pages, 4 figures, 1 tabl

The Impact Of Young Unlicensed Driving On Passenger Restraint Use: Concern For Risk Spillover Effect?

Background: Despite recent prevention gains, motor vehicle crashes continue to be the leading cause of death for US adolescents and young adults. Many of these deaths involve young unlicensed drivers that are more likely to be in fatal crashes and to engage in high-risk driving behaviors like impaired driving, speeding, and driving unrestrained. In a crash context, the influence of these high-risk behaviors may spillover to adversely affect passenger safety restraint use. Objective: To examine the effect of young unlicensed drivers on safety restraint use and mortality of their passengers. Methods. A cross-sectional analysis of the National Highway Traffic Safety Administration\u27s Fatality Analysis Reporting System from years 1996-2008 was conducted. Fatal crashes involving unlicensed drivers (15-24 yrs) and their passengers (15-24 yrs) were included. Multivariate logistic regression with generalized estimating equations were undertaken to assess the relationship between unlicensed driving and passenger restraint use, controlling for established predictors of restraint use, including driver restraint use, passenger gender, alcohol use, number of occupants, crash year, and crash location (rural vs. urban). Results: 102,092 passengers were involved in fatal crashes nationally from 1996-2008 with 64,803 unique drivers. 6,732 (10.51%) were never licensed drivers and 5,603(8.8%) were drivers with suspended, revoked, or expired licenses. Rates of unlicensed driving ranged from 17.7% to 25.1% and increased over time. While passengers in fatal crashes averaged 40.9% restraint use, passengers of never and invalidly licensed drivers had a further decreased odds of wearing a safety restraint (OR 0.73, 95% CI 0.69-0.77, p\u3c0.001) and (OR 0.84, 95% CI 0.79-0.90, p\u3c0.001). Other factors related to passenger restraint use were driver restraint use (OR 15.40, 95% CI 14.71-16.11, p\u3c0.001), being a front- seated passenger (OR 3.61, 95% CI 3.47-3.74, p\u3c0.001), rural crash location (OR 0.71, 95% CI 0.68-0.74, p\u3c0.001), and driver alcohol use (OR 0.74, 95% CI 0.70-0.77, p\u3c0.001). Conclusions: We found a strong inverse correlation between unlicensed driving and passenger restraint use, suggesting a significant risk spillover effect. Unlicensed driving was involved in a disproportionate and increasing number of fatal crashes and plays a detrimental role in the lifesaving safety behaviors of their passengers. Unlicensed driving not only puts the driver and public at risk, but may also diminish passengers\u27 ability to mitigate risk in a crash context. Our findings highlight an alarming peer influence between unlicensed drivers and passengers that has considerable implications for US highway safety and the public\u27s health. Further in-depth study in this area can guide the development of targeted countermeasures and traffic safety programs

Episodic neurologic disorders: syndromes, genes, and mechanisms.

Many neurologic diseases cause discrete episodic impairment in contrast with progressive deterioration. The symptoms of these episodic disorders exhibit striking variety. Herein we review what is known of the phenotypes, genetics, and pathophysiology of episodic neurologic disorders. Of these, most are genetically complex, with unknown or polygenic inheritance. In contrast, a fascinating panoply of episodic disorders exhibit Mendelian inheritance. We classify episodic Mendelian disorders according to the primary neuroanatomical location affected: skeletal muscle, cardiac muscle, neuromuscular junction, peripheral nerve, or central nervous system (CNS). Most known Mendelian mutations alter genes that encode membrane-bound ion channels. These mutations cause ion channel dysfunction, which ultimately leads to altered membrane excitability as manifested by episodic disease. Other Mendelian disease genes encode proteins essential for ion channel trafficking or stability. These observations have cemented the channelopathy paradigm, in which episodic disorders are conceptualized as disorders of ion channels. However, we expand on this paradigm to propose that dysfunction at the synaptic and neuronal circuit levels may underlie some episodic neurologic entities

CDC: Convolutional-De-Convolutional Networks for Precise Temporal Action Localization in Untrimmed Videos

Temporal action localization is an important yet challenging problem. Given a long, untrimmed video consisting of multiple action instances and complex background contents, we need not only to recognize their action categories, but also to localize the start time and end time of each instance. Many state-of-the-art systems use segment-level classifiers to select and rank proposal segments of pre-determined boundaries. However, a desirable model should move beyond segment-level and make dense predictions at a fine granularity in time to determine precise temporal boundaries. To this end, we design a novel Convolutional-De-Convolutional (CDC) network that places CDC filters on top of 3D ConvNets, which have been shown to be effective for abstracting action semantics but reduce the temporal length of the input data. The proposed CDC filter performs the required temporal upsampling and spatial downsampling operations simultaneously to predict actions at the frame-level granularity. It is unique in jointly modeling action semantics in space-time and fine-grained temporal dynamics. We train the CDC network in an end-to-end manner efficiently. Our model not only achieves superior performance in detecting actions in every frame, but also significantly boosts the precision of localizing temporal boundaries. Finally, the CDC network demonstrates a very high efficiency with the ability to process 500 frames per second on a single GPU server. We will update the camera-ready version and publish the source codes online soon.Comment: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 201

Positron emission tomography imaging of endometrial cancer using engineered anti-EMP2 antibody fragments.

PurposeAs imaging of the cell surface tetraspan protein epithelial membrane protein-2 (EMP2) expression in malignant tumors may provide important prognostic and predictive diagnostic information, the goal of this study is to determine if antibody fragments to EMP2 may be useful for imaging EMP2 positive tumors.ProceduresThe normal tissue distribution of EMP2 protein expression was evaluated by immunohistochemistry and found to be discretely expressed in both mouse and human tissues. To detect EMP2 in tumors, a recombinant human anti-EMP2 minibody (scFv-hinge-C(H)3 dimer; 80 kDa) was designed to recognize a common epitope in mice and humans and characterized. In human tumor cell lines, the antibody binding induced EMP2 internalization and degradation, prompting the need for a residualizing imaging strategy. Following conjugation to DOTA (1,4,7,10-tetraazacyclododecane-N,N',N',N'″-tetraacetic acid), the minibody was radiolabeled with (64)Cu (t (1/2) = 12.7 h) and evaluated in mice as a positron emission tomography (PET) imaging agent for human EMP2-expressing endometrial tumor xenografts.ResultsThe residualizing agent, (64)Cu-DOTA anti-EMP2 minibody, achieved high uptake in endometrial cancer xenografts overexpressing EMP2 (10.2 ± 2.6, percent injected dose per gram (%ID/g) ± SD) with moderate uptake in wild-type HEC1A tumors (6.0 ± 0.1). In both cases, precise tumor delineation was observed from the PET images. In contrast, low uptake was observed with anti-EMP2 minibodies in EMP2-negative tumors (1.9 ± 0.5).ConclusionsThis new immune-PET agent may be useful for preclinical assessment of anti-EMP2 targeting in vivo. It may also have value for imaging of tumor localization and therapeutic response in patients with EMP2-positive malignancies

Fintech in the time of COVID-19: Technological adoption during crises

We document the effects of the COVID-19 pandemic on digital finance and fintech adoption. Drawing on mobile application data from a globally representative sample, we find that the spread of COVID- 19 and related government lockdowns led to a sizeable increase in the rate of finance app downloads. We then analyze factors that may have driven this effect on the demand-side and better understand the “winners” from this digital acceleration on the supply-side. Our overall results suggest that traditional incumbents saw the largest growth in their digital offerings during the initial period, but that "BigTech" companies and newer fintech providers ultimately outperformed them over time. Finally, we drill-down further on the adoption of fintech apps pertaining to both the asset and liability side of the traditional bank balance sheet, to explore the implications that the accelerated trends in digitization may have for the future landscape of financial intermediation

Preparing fertile ground: How does the quality of business environments affect MSE growth?

We study how the quality of local business environments help explain growth outcomes of micro and small enterprise microfinance clients by drawing on long-term nationwide administrative data and a policy shock in Cambodia. The staggered launch of Special Economic Zones, which we link to positive shocks to the business environment on both the demand side and supply side, leads to significantly increased employment in MSEs located in these SEZs, compared to enterprises in contextually similar districts but that are unexposed to an SEZ. Key channels explaining the improved growth outcomes include expanded access to external markets for the enterprises’ goods and services, more dynamic labour environments, and improved credit terms and conditions. To broaden the relevance of our findings, we combine data from prominent empirical studies on microfinance and demonstrate how related business conditions from the enterprise growth literature help explain differences in client business outcomes found in their results. Policy implications are that a key segment of microfinance borrowers can significantly benefit from opportunities provided by local business environments and that governments and lenders can play active roles in facilitating improved outcomes for their MSEs