State Capacity and COVID-19: Targeted versus Population-Wide Restrictions.

CONTEXT: During the COVID-19 pandemic, governments varied in their implementation of social distancing rules. Some governments were able to target their social distancing requirements toward specific segments of the population, whereas others had to resort to more indiscriminate applications. This article will argue that state capacity crucially affected the manner in which social distancing rules were applied. METHODS: Using data from the Oxford COVID-19 Government Response Tracker, the author performed a series of ordered logistic regressions to examine whether state capacity increased the likelihood of more targeted applications of each social distancing rule. FINDINGS: Given the same level of infectivity, more capable states were indeed more likely to resort to targeted applications of each social distancing restriction. Interestingly, the size of state capacity's effect varied by the type of restriction. State capacity had a stronger influence on face-covering requirements and private-gathering restrictions than it had on school closures, workplace closures, and stay-at-home orders. CONCLUSIONS: The way in which social distancing rules are applied is endogenous to state capacity. Effective governance is a precursor to more targeted and nuanced applications of social distancing rules.

Relationship Between Coronavirus Disease 2019 Vaccination Rates and Rare But Potentially Fatal Adverse Events: A Regression Discontinuity Analysis of Western Countries.

BACKGROUND: Owing to limited experience with the new vaccine platforms, discussion of vaccine safety is inevitable. However, media coverage of adverse events of special interest could influence the vaccination rate; thus, evaluating the outcomes of adverse events of special interest influencing vaccine administration is crucial. METHODS: We conducted regression discontinuity in time analysis to calculate the local average treatment effect (LATE) using datasets from Our World in Data and Johns Hopkins University Center for Systems Science and Engineering. For the United States, the United Kingdom, and Europe, the cutoff points were April 23rd and June 23rd, April 7th, and the 14th week of 2021, respectively. RESULTS: The LATE of the Advisory Committee on Immunization Practices (ACIP) meeting held on April 23rd was -0.249 for all vaccines, -0.133 (-0.189 to -0.076) for Pfizer, -0.064 (-0.115 to -0.012) for Moderna, and -0.038 (-0.047 to -0.030) for Johnson & Johnson. Discontinuities were observed for all three types of vaccines in the United States. The June 23rd meeting of the ACIP (mRNA vaccines and myocarditis) did not convene any discontinuities. Furthermore, there was no significant drop in the weekly average vaccination rates in Europe following the European Medicines Agency (EMA) statement on April 7th. Conversely, there was a significant drop in the first-dose vaccination rates in the United Kingdom related to the EMA report. The first-dose vaccination rate for all vaccines changed by -0.104 (-0.176 to -0.032). CONCLUSION: Although monitoring and reporting of adverse events of special interest are important, a careful approach towards public announcements is warranted.

MFA-net: Object detection for complex X-ray cargo and baggage security imagery.

Deep convolutional networks have been developed to detect prohibited items for automated inspection of X-ray screening systems in the transport security system. To our knowledge, the existing frameworks were developed to recognize threats using only baggage security X-ray scans. Therefore, the detection accuracy in other domains of security X-ray scans, such as cargo X-ray scans, cannot be ensured. We propose an object detection method for efficiently detecting contraband items in both cargo and baggage for X-ray security scans. The proposed network, MFA-net, consists of three plug-and-play modules, including the multiscale dilated convolutional module, fusion feature pyramid network, and auxiliary point detection head. First, the multiscale dilated convolutional module converts the standard convolution of the detector backbone to a conditional convolution by aggregating the features from multiple dilated convolutions using dynamic feature selection to overcome the object-scale variant issue. Second, the fusion feature pyramid network combines the proposed attention and fusion modules to enhance multiscale object recognition and alleviate the object and occlusion problem. Third, the auxiliary point detection head adopts an auxiliary head to predict the new keypoints of the bounding box to emphasize the localizability without requiring further ground-truth information. We tested the performance of the MFA-net on two large-scale X-ray security image datasets from different domains: a Security Inspection X-ray (SIXray) dataset in the baggage domain and our dataset, named CargoX, in the cargo domain. Moreover, MFA-net outperformed state-of-the-art object detectors in both domains. Thus, adopting the proposed modules can further increase the detection capability of the current object detectors on X-ray security images.

Multichannel Acoustic Spectroscopy of the Human Body for Inviolable Biometric Authentication.

Specific features of the human body, such as fingerprint, iris, and face, are extensively used in biometric authentication. Conversely, the internal structure and material features of the body have not been explored extensively in biometrics. Bioacoustics technology is suitable for extracting information about the internal structure and biological and material characteristics of the human body. Herein, we report a biometric authentication method that enables multichannel bioacoustic signal acquisition with a systematic approach to study the effects of selectively distilled frequency features, increasing the number of sensing channels with respect to multiple fingers. The accuracy of identity recognition according to the number of sensing channels and the number of selectively chosen frequency features was evaluated using exhaustive combination searches and forward-feature selection. The technique was applied to test the accuracy of machine learning classification using 5,232 datasets from 54 subjects. By optimizing the scanning frequency and sensing channels, our method achieved an accuracy of 99.62%, which is comparable to existing biometric methods. Overall, the proposed biometric method not only provides an unbreakable, inviolable biometric but also can be applied anywhere in the body and can substantially broaden the use of biometrics by enabling continuous identity recognition on various body parts for biometric identity authentication.

Identity Recognition Based on Bioacoustics of Human Body.

Current biometrics rely on images obtained from the structural information of physiological characteristics, which is inherently a fatal problem of being vulnerable to spoofing. Here, we studied personal identification using the frequency-domain information based on human body vibration. We developed a bioacoustic frequency spectroscopy system and applied it to the fingers to obtain information on the anatomy, biomechanics, and biomaterial properties of the tissues. As a result, modulated microvibrations propagated through our body could capture a unique spectral trait of a person and the biomechanical transfer characteristics persisted for two months and resulted in 97.16% accuracy of identity authentication in 41 subjects. Ultimately, our method not only eliminates the practical means of creating fake copies of the relevant characteristics but also provides reliable features.

Effectiveness of Penalties for Lockdown Violations During the COVID-19 Pandemic in Germany.

Objectives. To investigate whether the imposition of fines can mitigate the spread of COVID-19.Methods. We used quasi-experimental difference-in-difference models. On March 20, 2020, Bavaria introduced fines as high as €25 000 (US $28 186) against citizens in violation of the Bundesland's (federal state's) lockdown policy. Its neighboring Bundesländer (federal states), on the other hand, were slow to impose such clear restrictions. By comparing 38 Landkreise (counties) alongside Bavaria's border from March 15 to May 11 using data from the Robert Koch Institute, we produced for each Landkreis its (1) time-dependent reproduction numbers (Rt) and (2) growth rates in confirmed cases.Results. The demographics of the Landkreise were similar enough to allow for difference-in-difference analyses. Landkreise that introduced fines on March 20 reduced the Rt by a further 0.32 (95% confidence interval [CI] = -0.46, -0.18; P < .001) and decreased the growth rate in confirmed cases by an additional 6 percentage points (95% CI = -0.11, -0.02; P = .005) compared with the control group.Conclusions. Imposing fines may slow down the spread of COVID-19.Public Health Implications. Lockdowns may work better when governments introduce penalties against those who ignore them.

Decrease in interpretation time for both novice and experienced readers using a concurrent computer-aided detection system for digital breast tomosynthesis.

OBJECTIVES: To compare the diagnostic performance and interpretation time of digital breast tomosynthesis (DBT) for both novice and experienced readers with and without using a computer-aided detection (CAD) system for concurrent read. METHODS: CAD system was developed for concurrent read in DBT interpretation. In this observer performance study, we used an enriched sample of 100 DBT cases including 70 with and 30 without breast cancers. Image interpretation was performed by four radiologists with different experience levels (two experienced and two novice). Each reader completed two reading sessions (at a minimum 2-month interval), once with and once without CAD. Three different rating scales were used to record each reader's interpretation. Reader performance with and without CAD was reported and compared for each radiologist. Reading time for each case was also recorded. RESULTS: Average area under the receiver operating characteristic curve values for BI-RADS scale on using CAD were 0.778 and 0.776 without using CAD, demonstrating no statistically significant differences. Results were consistent when the probability of malignancy and percentage probability of malignancy scales were used. Reading times per case were 72.07 s and 62.03 s (SD, 37.54 s vs 34.38 s) without and with CAD, respectively. The average difference in reading time on using CAD was a statistically significant decrease of 10.04 ± 1.85 s, providing 14% decrease in time. The time-reducing effect was consistently observed in both novice and experienced readers. CONCLUSION: DBT combined with CAD reduced interpretation time without diagnostic performance loss to novice and experienced readers. KEY POINTS: • The use of a concurrent DBT-CAD system shortened interpretation time. • The shortened interpretation time with DBT-CAD did not come at a cost to diagnostic performance to novice or experienced readers. • The concurrent DBT-CAD system improved the efficiency of DBT interpretation.

Fully automated nipple detection in digital breast tomosynthesis.

BACKGROUND AND OBJECTIVE: We propose a nipple detection algorithm for use with digital breast tomosynthesis (DBT) images. DBT images have been developed to overcome the weaknesses of 2D mammograms for denser breasts by providing 3D breast images. The nipple location acts as an invaluable landmark in DBT images for aligning the right and left breasts and describing the relative location of any existing lesions. METHODS: Nipples may be visible or invisible in a breast image, and therefore a nipple detection method must be able to detect the nipples for both cases. The detection method for visible nipples based on their shape is simple and highly efficient. However, it is difficult to detect invisible nipples because they do not have a prominent shape. Fibroglandular tissue in a breast is anatomically connected with the nipple. Thus, the nipple location can be detected by analyzing the location of such tissue. In this paper, we propose a method for detecting the location of both visible and invisible nipples using fibroglandular tissue and changes in the breast area. RESULTS: Our algorithm was applied to 138 DBT images, and its nipple detection accuracy was evaluated based on the mean Euclidean distance. The results indicate that our proposed method achieves a mean Euclidean distance of 3.10±2.58mm. CONCLUSIONS: The nipple location can be a very important piece of information in the process of a DBT image registration. This paper presents a method for the automatic nipple detection in a DBT image. The extracted nipple location plays an essential role in classifying any existing lesions and comparing both the right and left breasts. Thus, the proposed method can help with computer-aided detection for a more efficient DBT image analysis.

Three-Dimensional Computer-Aided Detection of Microcalcification Clusters in Digital Breast Tomosynthesis.

We propose computer-aided detection (CADe) algorithm for microcalcification (MC) clusters in reconstructed digital breast tomosynthesis (DBT) images. The algorithm consists of prescreening, MC detection, clustering, and false-positive (FP) reduction steps. The DBT images containing the MC-like objects were enhanced by a multiscale Hessian-based three-dimensional (3D) objectness response function and a connected-component segmentation method was applied to extract the cluster seed objects as potential clustering centers of MCs. Secondly, a signal-to-noise ratio (SNR) enhanced image was also generated to detect the individual MC candidates and prescreen the MC-like objects. Each cluster seed candidate was prescreened by counting neighboring individual MC candidates nearby the cluster seed object according to several microcalcification clustering criteria. As a second step, we introduced bounding boxes for the accepted seed candidate, clustered all the overlapping cubes, and examined. After the FP reduction step, the average number of FPs per case was estimated to be 2.47 per DBT volume with a sensitivity of 83.3%.

Magnetic resonance imaging spectrum of solid pseudopapillary neoplasm of the pancreas.

OBJECTIVE: To describe the magnetic resonance imaging spectrum of solid pseudopapillary tumors (SPTs), with an emphasis on solid SPTs. METHODS: Thirty-two patients with proven SPTs with preoperative magnetic resonance were included. The SPTs were classified into 3 types: solid, cystic, and mixed; and 2 radiologists analyzed the images regarding the morphologic features and enhancement pattern. RESULTS: Of 11 solid SPTs, 9 SPTs (81.8%) were less than 3 cm. Alternatively, of the 18 mixed SPTs and 3 cystic SPTs, 15 SPTs (71.4%) were larger than 3 cm. The predominant imaging features were homogeneous hypoenhancement with a gradually incremental enhancement pattern showing a sharp margin without hemorrhage, whereas those of the mixed SPTs were heterogeneous enhancement showing a sharp margin with internal hemorrhage. CONCLUSION: Solid SPTs frequently present as small, well-defined tumors with a gradual enhancement and without hemorrhage or necrosis, and with features that differ from those of mixed or cystic SPTs.

Resveratrol suppresses tumor progression via the regulation of indoleamine 2,3-dioxygenase.

This study showed the potential of resveratrol to inhibit the expression and activity of interferon-γ (IFN-γ)-induced indoleamine 2,3-dioxygenase (IDO) in bone marrow-derived dendritic cells (BMDCs). The mechanism of suppression was associated with the activity of Janus kinase/signal transducers and activators of transcription (JAK/STAT) and protein kinase Cδ (PKCδ). In addition, resveratrol-mediated IDO suppression in IFN-γ-stimulated BMDCs appears to play a pivotal role in anti-tumor activity through the regulation of CD8(+) T cell polarization and cytotoxic T lymphocyte (CTL) activity. Systemic administration of resveratrol suppressed tumor growth in EG7 thymoma-bearing mice in an IDO-dependent manner. Taken together, resveratrol not only regulates immune response through the regulation of IDO in a JAK/STAT1- and PKCδ-dependent manner, but also modulates the IDO-mediated immune tolerance in EG7 thymoma.