bluuebunny/crossref_metadata_2025 huggingface dataset:
Miniaturized BDS Anti-jamming Antenna Research
Authors: Dong Yanchen , Xue Yulei , Liu Shijie , Dai Peipei , Wang Sen , Xing Jianping
Published: February 2022

At present, BeiDou-3 Navigation Satellite System (BDS) was officially commissioned, and BDS is widely used in military and civil terminal types of equipment, including missiles, warships, satellites, ships, aircraft, unmanned bicycles, intelligent transportation, etc. In view of the fact that the navigation signal has easily interfered in the process of practical application, this paper designs a 5-array anti-jamming miniaturized antenna with a volume of only 110mm*110mm. The four surrounding BDS-B3 frequency elements are used for anti-interference processing, and the middle BDS-B1 element is used to receive BDS-B1 frequency signals directly, and the final BDS-B3 and BDS-B1 signals after anti-interference processing are controlled by RF switch for final output to improve navigation accuracy and reduce power consumption when there is no interference. Finally, the RF circuit of the antijamming array antenna is studied. By analyzing the key parameters such as noise coefficient, gain and IMD3 ( Third Order Intermodulation ), the design scheme of high performance antijamming RF circuit is determined.
Automatic Recognition Method of Broken Transmission Line Defect Image Based on Deep Transfer Learning
Authors: Zhou Yaoxiang , Sun Hongdi , Liu Changlong , Zhang Jiaming , Zhu Zhenbo , Tang Bin
Published: February 2022

The material of ACSR in transmission line is prone to local damage, which leads to broken strand defect and reducing power consumption safety. Therefore, an automatic recognition method of broken strand defect image of transmission line based on deep transfer learning is designed to improve the automatic recognition effect of broken strand defect image. The multi-scale algorithm is used to enhance the image. In the feature extraction part of the depth transfer learning framework in the confusion domain, the multi-source domain transfer and dual flow fusion algorithm are used to extract the features of the enhanced image, and the Euclidean distance between the feature vector and the template image feature vector is used to correct the image features; using the corrected image feature training network propagated to the automatic defect recognition part and the domain classification part, the loss function and back propagation algorithm are used to reduce the loss of feature extraction and automatic defect recognition part, and the optimal results of automatic defect recognition and domain classification are obtained. The experimental results show that the method can enhance the image effectively with high definition. At different image angles, the recognition accuracy of this method is as high as 0.96, which has better automatic recognition effect of defect image.
Network-on-Chip hardware Trojan detection platform based on machine learning
Authors: Yao Jiaqi , Zhang Ying , Xin Chen
Published: February 2022

The extensive use of the Network-on-Chip (NoC) architecture makes it vulnerable to malicious attacks by hardware Trojans, especially Denial of Service (DoS) attack. To address this issue, this paper proposes a general NoC hardware Trojan detection platform based on machine learning. The platform establishes a security detection module including traffic feature tracking unit, feature registration unit, change point detection unit, and random forest detection unit, to accomplish the traffic-related hardware Trojan detection. The live-lock and fault routing Trojans are inserted in the proposed platform, then the simulation results verify the effectiveness of platform function and show its superiority to other existing detection schemes.
A Rotating Object Detection Method Based on Anchor-Free in Remote Sensing Scene Images
Authors: Yuan Zhengwu , Kou Sijia , Tang Qiao , Xu Fapeng
Published: February 2022

The core of the object detection task is to be able to accurately classify and regress the object position. The current two-stage algorithm based on convolutional neural networks has achieved good results in horizontal box detection, but the effect in rotating bounding box detection is limited, and the anchor-based detection algorithm has problems, such as complicated hyper-parameter design and imbalance between positive and negative samples. In order to better solve the above problems, the model in this paper adopts a single-stage anchor-free method, uses the high resolution network(HRNet) to obtain the high-resolution feature map of cross fusion, and uses a rotating Gaussian kernel for predicting center point, which can increase the number of positive samples at the center point, simultaneously realize the improvement of detection accuracy and speed. Experimental results on HRSC2016 and DOTA datasets, which demostrates that our method exceed the state-of-art models, and indicates the effectiveness of the proposed methods.
Multi-scale residual network-based image restoration
Authors: Yang Liu , You Fucheng
Published: February 2022

All Image restoration technology has undergone extensive research. For image degradation, inverse filtering was proposed in the last century. Then Helstrom proposed a Wiener filtering algorithm. In recent years, the convolutional neural network has promoted the further development of image restoration technology. The coarse-to-fine multi-scale residual network Multiscale Deblur Net (MDN) used in this paper is stable in operation, simple in structure, and easy to train. It has a good deblurring ability for motion-blurred images by testing in the GO_PRO dataset.
Underwater Image Saliency Detection Via Attention-based Mechanism
Authors: Liu Lidan , Yu Weiwei
Published: February 2022

Due to complex lighting circumstances and other factors, visual saliency recognition of underwater images is not as good as visual saliency detection models that function well on land when applied to underwater environments. The dearth of large-scale annotated underwater picture datasets has further hindered the development of visual saliency detection in underwater images. we propose an attention-based approach for underwater image saliency detection to address this issue. The backbone network is pre-trained using both land and underwater image datasets, which effectively solves the problem of fewer datasets. After that, a residual refinement module incorporating a channel-space attention mechanism is merged, the model as a whole is trained end-to-end using underwater image datasets, and the model accuracy is experimentally tested. The experimental results in three underwater image datasets show that our method is better than several other methods in the mainstream evaluation indicators of the saliency detection.
Research on intelligent peak-cutting and valley-filling charging and swapping mode based on potential game theory
Authors: Hu Lanxin , Yue Feiyang
Published: February 2022

With the continuous increase in the proportion of renewable energy represented by wind and light in the power grid in recent years, on the one hand, the energy structure of the existing power grid has been directly optimized, and on the other hand, the full utilization of renewable clean energy can also reduce traditional power generation. The pollution caused by the industry to the environment. As an indispensable infrastructure for electric vehicles, charging and swapping stations, after being connected to a distributed micro-grid, can play a role in reducing peaks and valleys, promoting the consumption of new energy, and saving costs through reasonable configuration. The analysis of calculation examples shows that the intelligent charging and swapping system model based on the potential game theory proposed in this paper can effectively reduce the operating cost and user cost of the swap station, and effectively improve the level of wind and solar consumption, and achieve the level of smoothing the grid curve and peak-shaving and valley-filling. Purpose has important practical significance and engineering value.
Short-Term Wind Speed Interval Prediction using LUBE based Quasi-Recurrent Neural Network
Authors: Saeed Adnan , Li Chaoshun , Gan Zhenhao
Published: February 2022

Accurate wind speed forecasting is an extremely difficult task and therefore less accurate forecasts may sometimes make the power systems vulnerable. Interval predictions on the other hand may help in maximizing the usage of integrated wind energy, as well as to reduce the adverse effects of the uncertainties introduced by the random fluctuations of wind, to the power systems. In this paper, we propose a novel wind speed interval prediction model by integrating lower upper bound estimation method (LUBE) into a quasi-recurrent neural network (QRNN). LUBE is a non-differentiable loss function requiring usage of meta-heuristic optimization techniques for training the model. By incorporating two objective functions, we proposed a new form of LUBE, using which the network can be trained with conventional stochastic gradient descent. The proposed model is evaluated for eight different datasets distributed among two wind fields. Results obtained from the computational experiments reveals that the proposed method generated narrow intervals with high coverage which helps it in achieving an improvement of 33% in coverage width criterion over the traditional models.
Monthly-scale runoff forecast model based on PSO-SVR
Authors: Qiao Guangchao , Yang Mingxiang , Zeng Xiaoling
Published: February 2022

The current methods used in the Lubbog reservoir runoff forecast generally have shortcomings such as low forecast accuracy and low stability. Aiming at these problems, this paper constructs a PSO-SVR mid-and-long term forecast model, and it uses the particle swarm optimization algorithm (PSO) to find the penalty coefficient C, the insensitivity coefficient ε and the gamma parameter of the Gaussian radial basis kernel function of the support vector regression machine (SVR). The results demonstrates that the average relative errors of the PSO-SVR forecast model is relatively small, which are all within a reasonable range; the qualification rates for most monthly forecasts are above 80%. Experimental results indicate that compared with multiple regression analysis, the PSO-SVR model has a higher forecast accuracy, a stronger stability, and a higher credibility. It has a certain practical value and provides a reference for related research.
Short-term load forecasting based on improved manta ray algorithm to optimize neural network
Authors: Hao Gang , Xianyu Jianchuan
Published: February 2022

Accurate short-term load forecasting can reduce the shutdown reserve and rotating reserve of generator units, which directly affects the safety, stability and economic benefits of power grid. Aiming at the shortcomings of sensitive initial value and easy to fall into local optimization of BP neural network, a load forecasting method based on improved manta ray algorithm to optimize BP neural network is proposed. The location update formula of manta ray foraging is improved through Levy flight strategy, the local and global search performance of the algorithm is balanced, its ability to jump out of the local optimization is enhanced, the weight and threshold of BP network are optimized, and the optimization model for short-term load forecasting is established. The results show that the prediction accuracy and convergence speed of the improved prediction model have been greatly improved. It has engineering practical value.
A new algorithm for precise location of power cable fault based on zero phase filter
Authors: Zhang Xiaojun , Zhang Bo , Wu Suzhou , Li Chao , Lei Zeyang
Published: February 2022

In order to improve the fault location accuracy of power cables, the two-side method is used for fault location. The main factors affecting the cable fault accuracy of the double-ended fault location method are the wave speed of traveling waves transmitted in the cable and the time difference between the traveling waves arriving at the monitoring equipment. In fact, traveling wave signals with different frequencies propagate at different wave speeds, and the use of fixed wave speeds for positioning calculations will inevitably cause positioning errors. First, the center frequency spectrum method is used to calculate the wave speed, and different wave speeds are used for different types of cables, so as to reduce the positioning error caused by the wave speed. Then, the devices on both sides use high-precision GPS to synchronize the time to reduce the natural error. For the time difference between the detected traveling waves reaching the devices on both sides, the triangle algorithm can be used to find the starting point for time difference calculation, thereby constructing a new cable fault location algorithm. Finally, a large number of PSCAD simulations and field discharge tests of cable grounding were carried out. The simulation results and test results verified the feasibility and superiority of this algorithm.
An anti-outlier robust clock compensated algorithm for wireless network
Authors: Chen Kai , Chen Xin , Gao Xiang
Published: February 2022

Clock synchronization technology plays an important role in wireless networks, and the improvement of clock synchronization precision has always been the goal pursued by research. This paper introduces a clock compensation technology in wireless networks, which solves two main problems influencing clock accuracy in current clock synchronization technology: time-varying clock frequency deviation and interference from outliers. In this paper, the linear regression algorithm with local weighting and least square sum estimation is used to solve the above problems. Simulation results show that the algorithm has higher clock synchronization accuracy than other algorithms, and the clock synchronization error is significantly lower than the non-robust regression algorithm when there are outliers, proving that this method can effectively resist the influence of outliers on clock synchronization accuracy.
High-Resolution Representation Learning for Human Pose Estimation based on Transformer
Authors: Fu Dengyu , Wu Wei
Published: February 2022

Human pose estimation requires accurate coordinate values for the prediction of human joints, which requires a high-resolution representation to effectively improve accuracy. For some difficult joint prediction tasks, it is not only necessary to look at the characteristics of the joint points themselves, but also to make judgments in combination with the context of the whole image. Generally, the resolution will be reduced when the context information is obtained. In this process, it will inevitably lose some spatial information and make the prediction inaccurate. In this paper, we propose a high-resolution human pose estimation network based on Transformer to reduce the impact of spatial information loss on keypoints estimation. In detail, we use low-level convolution neural network to extract low-level semantics from the image, and then the Transformer is used to capture the image context to further predict the key points of the human body, obtain the high-resolution representation. The experiments show that our network can accurately predict the positions of keypoints, we achieve state-of-art results on the COCO keypoint detection dataset.
Research on the Methods to Improve RFSS Accuracy
Authors: Yuan Qingze
Published: February 2022

RFSS is a common test method in the research and development of radar guidance systems, which overcomes the problem of the large cost of the field test to a certain extent. With the development of radar technology, the evaluation of hardware in the loop RF simulation error needs to be more accurate. This paper summarizes the current research, mainly focusing on simulation error analysis, near-field error and near-field correction, expansion of simulation object and suppression of simulation error. At present, most studies focus on azimuth error and pitch error respectively, but do not take into account the correlation of the errors in these two different angle domains. Or only the root mean square of the amplitude of the two-dimensional angle error is considered, without considering the directional distribution of the angle error.
Aptamer-functionalized targeted siRNA delivery system for tumor immunotherapy
Authors: Lv Haiyin , Wang Tengfei , Ma Fanshu , Zhang Kunchi , Gao Tian , Pei Renjun , Zhang Ye
Published: February 2022

Programmed death ligand 1 (PD-L1) overexpressed on the surface of tumor cells is one of the reasons for tumor immune escape. Reducing PD-L1 expression has been proved to be an effective strategy to facilitate immune system activation and inhibit tumor progression. RNA interference (RNAi) is a promising technology for gene regulation in tumor therapy. In this study, we constructed a targeted siRNA delivery system NPs@apt to transfect PD-L1 siRNA into human non-small-cell lung carcinoma cell line (A549) for inhibiting tumor immune evasion. NPs@apt was prepared by compressing PD-L1 siRNA with cationic Lipofectamine 2000, fusing with erythrocyte membrane-derived nanovesicles, and further modifying with targeting AS1411 aptamer. The introduction of erythrocyte membrane endowed the siRNA delivery system with lower cytotoxicity and the ability to escape from the phagocytosis of macrophages. The stability of NPs@apt and the protection to loaded siRNA were confirmed. In vitro studies after NPs@apt treatment demonstrated that PD-L1 siRNA was selectively delivered into A549 cells, and further resulted in PD-L1 gene knockdown, T cell activation and tumor cell growth inhibition. This study offered an alternative strategy for specific siRNA transfection for improving anti-tumor immunity.
Projected risks associated with heat stress in the UK Climate Projections (UKCP18)
Authors: Kennedy-Asser Alan T , Owen Gwilym , Griffith Gareth J , Andrews Oliver , Lo Y T Eunice , Mitchell Dann M , Jenkins Katie , Warren Rachel F
Published: February 2022

Summer heat extremes in the UK pose a risk to health (amongst other sectors) and this is exacerbated by localised socio-economic factors that contribute to vulnerability. Here, regional climate model simulations from the UK Climate Projections are used to assess how different elements of extreme heat will vary across the UK in the future under global mean surface temperature warming levels of +1.5 °C, +2.0 °C and +3.0 °C above pre-industrial. Heat stress metrics incorporating daily maximum and minimum temperature, temperature variability and vapour pressure are included. These show qualitatively similar spatial patterns for the recent past, with the most pronounced heat hazards found in south-eastern regions of the UK. Projected heat hazard changes across the UK are not homogeneous, with southern regions (e.g. Greater London, South East) showing greater increases in maximum temperatures and northern regions (e.g. Scotland and Northern Ireland) showing greater increases in humidity. With +3.0 °C warming, the relative change in combined heat hazards is found to be greatest in the south-western UK, however, in absolute terms, south-eastern regions will still experience the greatest hazards. When combined with socio-economic factors, hotspots of high heat stress risk emerge in parts of London, the Midlands and eastern England along with southern and eastern coastal regions. Weighting of different heat risk factors is subjective and to this end we have developed and made available an interactive app which allows users to assess sensitivities and uncertainties in the projected UK heat risk.
Single step method for two-frame phase-shifting interferometry with unknown phase shift
Authors: López-Álvarez Yadira F , Muñoz-Maciel Jesús , Peña-Lecona Francisco G , Duran-Rámirez Víctor M
Published: February 2022

A procedure to recover the phase from two interferograms with unknown phase step is proposed. A least-square approach is used to solve simultaneously for the illumination background and the introduced phase shift in a local window. This allows to calculate the interferogram phase of the pixel at the center of the window with the standard arc-tangent formula. This process is carried out sequentially across the interferogram field until all pixels are recovered. The proposed scheme is fast and robust, and unlike others methods eliminates the need to implement prior steps of background suppression or interferogram normalization. The developed procedure may be used in problematic environments where vibrations or other disturbances difficult to acquire a full set of phase shifted interferograms with constants phase shifts. The developed procedure is validated in real and simulated data with good results.
Graphdiyne based GDY/CuI/NiO parallel double S-scheme heterojunction for efficient photocatalytic hydrogen evolution
Authors: Jin Zhiliang , Wang Xiangyi , Hao Xuqiang , Wang Guorong , Guo Xin , Wang Kai
Published: February 2022

As a new kind of two-dimensional (2D) layered carbon allotrope, graphdiyne (GDY) is rarely studied in the application field of photocatalytic hydrogen production. In addition, the efficient construction of photocatalyst heterostructure is a promising strategy to improve the yield of hydrogen production from photocatalytic split of water. Therefore, it is an excellent method to construct heterostructure photocatalytic system by introducing GDY into semiconductor photocatalytic materials. Herein, it is an excellent method to construct heterostructure photocatalytic system by introducing the cuprous iodide based 2D layered carbon allotrope (GDY) into metallic oxide semiconductor (NiO). Thus, a ternary hybrid photocatalyst (GDY/CuI/NiO) was prepared by in situ ultrasonic agitation method. X-ray diffraction, SEM, transmission electron microscope and x-ray photoelectron spectroscopy results showed that NiO nanosheets were successfully adsorbed by GDY/CuI. In addition, the composite catalyst (GDY/CuI/NiO) showed excellent photocatalytic performance, which performed a high hydrogen production activity of 5955 μmol g−1 and good stability in the 20 h hydrogen production experiment. Amorphous GDY provides more active sites for the process of hydrogen evolution in this photocatalytic system. Most importantly, the construction of S-scheme heterojunction promotes electron transfer and plays an important role in enhancing the hydrogen production activity. These findings provide new ideas for realizing efficient solar hydrogen production system.
Vaccine efficacy at a point in time
Authors: Follmann Dean A , Fay Michael P
Published: February 2022

Vaccine trials are generally designed to assess efficacy on clinical disease. The vaccine effect on infection, while important both as a proxy for transmission and to describe a vaccine’s entire effects, requires frequent (e.g., twice a week) longitudinal sampling to capture all infections. Such sampling may not always be feasible. A logistically easy approach is to collect a sample to test for infection at a regularly scheduled visit. Such point or cross-sectional sampling does not permit estimation of classic vaccine efficacy on infection, as long duration infections are sampled with higher probability. Building on work by Rinta-Kokko and others (2009) and Lipsitch and Kahn (2021), we evaluate proxies of the vaccine effect on transmission at a point in time; the vaccine efficacy on prevalent infection and on prevalent viral load, VE$_{\rm PI}$ and VE$_{\rm PVL}$, respectively. Longer infections with higher viral loads should have more transmission potential and prevalent vaccine efficacy naturally captures this aspect. We demonstrate how these parameters obtain from an underlying proportional hazards model for infection and allow for waning efficacy on infection, duration, and viral load. We estimate these parameters based on regression models with either repeated cross-sectional sampling or frequent longitudinal sampling. We evaluate the methods by simulation and analyze a phase III vaccine trial with polymerase chain reaction (PCR) cross-sectional sampling for subclinical infection.
Diffusion microstructure imaging in progressive supranuclear palsy: reduced axonal volumes in the superior cerebellar peduncles, dentato-rubro-thalamic tracts, ventromedial thalami, and frontomesial white matter
Authors: Rau Alexander , Jost Wolfgang H , Demerath Theo , Kellner Elias , Reisert Marco , Urbach Horst
Published: February 2022

Differentiating between Parkinson’s disease (PD) and atypical Parkinson syndromes such as progressive supranuclear palsy (PSP), multiple system atrophy (MSA), and corticobasal degeneration is challenging. Diffusion microstructure imaging (DMI) was analyzed in patients with clinically suspected atypical Parkinson syndromes and healthy controls. In an exploration cohort, the spatial distribution of PSP-related changes of DMI parameters were evaluated in a voxel-wise analysis and a region-of-interest (ROI)-based approach was established. The diagnostic performance was subsequently tested in an independent validation cohort. In the exploration cohort, 53 PSP patients were compared to a pooled comparison group of 19 patients with PD, 26 patients with MSA, 7 patients with corticobasal syndrome, and 25 healthy controls. PSP patients showed widespread axonal loss in the superior cerebellar peduncles, the dentato-rubro-thalamic tracts, the thalami and the frontal white matter (each P < 0.001). In the validation cohort consisting of 12 patients with PSP vs. 13 patients with other movement disorders, the accuracy of this ROI-based approach for identifying the PSP was highest in the thalamus and the frontal white matter (accuracy 0.96 each). This DMI approach can identify PSP patients on an individual level in a collective with suspected atypical Parkinson syndromes and allows further insight on microstructural alterations in vivo.
Altered prefrontal signaling during inhibitory control in a salient drug context in cocaine use disorder
Authors: Ceceli Ahmet O , Parvaz Muhammad A , King Sarah , Schafer Matthew , Malaker Pias , Sharma Akarsh , Alia-Klein Nelly , Goldstein Rita Z
Published: February 2022

Introduction

Drug addiction is characterized by impaired response inhibition and salience attribution (iRISA), where the salience of drug cues is postulated to overpower that of other reinforcers with a concomitant decrease in self-control. However, the neural underpinnings of the interaction between the salience of drug cues and inhibitory control in drug addiction remain unclear.

Methods

We developed a novel stop-signal functional magnetic resonance imaging task where the stop-signal reaction time (SSRT–a classical inhibitory control measure) was tested under different salience conditions (modulated by drug, food, threat, or neutral words) in individuals with cocaine use disorder (CUD; n = 26) versus demographically matched healthy control participants (n = 26).

Results

Despite similarities in drug cue-related SSRT and valence and arousal word ratings between groups, dorsolateral prefrontal cortex (dlPFC) activity was diminished during the successful inhibition of drug versus food cues in CUD and was correlated with lower frequency of recent use, lower craving, and longer abstinence (Z > 3.1, P < 0.05 corrected).

Discussion

Results suggest altered involvement of cognitive control regions (e.g. dlPFC) during inhibitory control under a drug context, relative to an alternative reinforcer, in CUD. Supporting the iRISA model, these results elucidate the direct impact of drug-related cue reactivity on the neural signature of inhibitory control in drug addiction.
The left prefrontal cortex determines relevance at encoding and governs episodic memory formation
Authors: Orth Michael , Wagnon Carole , Neumann-Dunayevska Elisabeth , Kaller Christoph Phillipp , Klöppel Stefan , Meier Beat , Henke Katharina , Peter Jessica
Published: February 2022

The role hemispheric lateralization in the prefrontal cortex plays for episodic memory formation in general, and for emotionally valenced information in particular, is debated. In a randomized, double-blind, and sham-controlled design, healthy young participants (n = 254) performed 2 runs of encoding to categorize the perceptual, semantic, or emotionally valenced (positive or negative) features of words followed by a free recall and a recognition task. To resolve competing hypotheses about the contribution of each hemisphere, we modulated left or right dorsolateral prefrontal cortex (DLPFC) activity using transcranial direct current stimulation during encoding (1 mA, 20 min). With stimulation of the left DLPFC, but not the right DLPFC, encoding and free recall performance improved particularly for words that were processed semantically. In addition, enhancing left DLPFC activity increased memory formation for positive content while reducing that for negative content. In contrast, promoting right DLPFC activity increased memory formation for negative content. The left DLPFC assesses semantic properties of new memory content at encoding and thus influences how successful new episodic memories are established. Hemispheric laterlization—more active left DLPFC and less active right DLPFC—at the encoding stage shifts the formation of memory traces in favor of positively valenced content.
A paleo-neurologic investigation of the social brain hypothesis in frontotemporal dementia
Authors: Vandenbulcke Mathieu , Van de Vliet Laura , Sun Jiaze , Huang Yun-An , Van Den Bossche Maarten J A , Sunaert Stefan , Peeters Ron , Zhu Qi , Vanduffel Wim , de Gelder Beatrice , De Winter François-Laurent , Van den Stock Jan
Published: February 2022

The social brain hypothesis posits that a disproportionate encephalization in primates enabled to adapt behavior to a social context. Also, it has been proposed that phylogenetically recent brain areas are disproportionally affected by neurodegeneration. Using structural and functional magnetic resonance imaging, the present study investigates brain–behavior associations and neural integrity of hyperspecialized and domain-general cortical social brain areas in behavioral variant frontotemporal dementia (bvFTD). The results revealed that both structure and function of hyperspecialized social areas in the middle portion of the superior temporal sulcus (STS) are compromised in bvFTD, while no deterioration was observed in domain general social areas in the posterior STS. While the structural findings adhered to an anterior–posterior gradient, the functional group differences only occurred in the hyperspecialized locations. Activity in specialized regions was associated with structural integrity of the amygdala and with social deficits in bvFTD. In conclusion, the results are in line with the paleo-neurology hypothesis positing that neurodegeneration primarily hits cortical areas showing increased specialization, but also with the compatible alternative explanation that anterior STS regions degenerate earlier, based on stronger connections to and trans-neuronal spreading from regions affected early in bvFTD.
Prevalence and Management of Sexually Transmitted Infections in Correctional Settings: A Systematic Review
Authors: Spaulding Anne C , Rabeeah Zainab , del Mar González-Montalvo Myrna , Akiyama Matthew J , Baker Brenda J , Bauer Heidi M , Gibson Brent R , Nijhawan Ank E , Parvez Farah , Wangu Zoon , Chan Philip A ,   Rollins Investigational Team on STIs in Corrections, Clausen Alyssa , Levano Samantha R , Michel Ciara , Pett Lindsay , Pluznik Jacob A , Richard Danielle , Ramanna Veena , Vega Allie
Published: February 2022

Admissions to jails and prisons in the United States number 10 million yearly; persons entering locked correctional facilities have high prevalence of sexually transmitted infections (STIs). These individuals come disproportionately from communities of color, with lower access to care and prevention, compared with the United States as a whole. Following PRISMA guidelines, the authors present results of a systematic review of literature published since 2012 on STIs in US jails, prisons, Immigration and Customs Enforcement detention centers, and juvenile facilities. This updates an earlier review of STIs in short-term facilities. This current review contributed to new recommendations in the Centers for Disease Control and Prevention 2021 treatment guidelines for STIs, advising screening for Trichomonas in women entering correctional facilities. The current review also synthesizes recommendations on screening: in particular, opt-out testing is superior to opt-in protocols. Carceral interventions—managing diagnosed cases and preventing new infections from occurring (eg, by initiating human immunodeficiency virus preexposure prophylaxis before release)—can counteract structural racism in healthcare.
Inequities in coronavirus disease 2019 (COVID-19) Vaccination Rates Among Adolescents in Massachusetts: A Cross-sectional Study
Authors: Gao David X , Fisher Lloyd D , Miller Donald R , Geller Alan C
Published: February 2022

Background

The coronavirus disease 2019 (COVID-19) pandemic has disproportionately affected more socioeconomically disadvantaged persons and areas. We sought to determine how certain sociodemographic factors were correlated to adolescents’ COVID-19 vaccination rates in towns and cities (“communities”) in the Commonwealth of Massachusetts.

Methods

Data on COVID-19 vaccination rates were obtained over a 20-week period from 30 March 2021 to 10 August 2021. Communities’ adolescent (ages 12–19) vaccination rates were compared across quintiles of community-level income, COVID-19 case rate, and proportion of non-Hispanic Black or Hispanic individuals. Other variables included population density and earlier COVID-19 vaccination rates of adolescents and adults, averaged from 30 March to 11 May to determine their effects on vaccination rates on 10 August. Linear and logistic regression was used to estimate individual effects of variables on adolescent vaccination rates.

Results

Higher median household income, lower proportion of Black or Hispanic individuals, higher early adolescent COVID-19 vaccination rates, and higher early adult COVID-19 vaccination rates were associated with higher later adolescent COVID-19 vaccination rates. Income per $10 000 (adjusted odds ratio [aOR] = 1.01 [95% confidence interval [CI] = 1.01–1.02]), proportion of Hispanic individuals (aOR = 1.33 [95% CI: 1.13–1.56]), early adolescent COVID-19 vaccination rates (aOR = 5.28 [95% CI: 4.67–5.96]), and early adult COVID-19 vaccination rates (aOR = 2.31 [95% CI: 2.02–2.64]) were associated with higher adolescent COVID-19 vaccination on 10 August, whereas proportion of Black individuals approached significance (aOR = 1.26 [95% CI: .98–1.61]).

Conclusions

Vaccination efforts for adolescents in Massachusetts should focus on boosting vaccination rates early in communities with the lowest incomes and greatest proportion of Hispanic individuals and consider targeting communities with a greater proportion of Black individuals.
Self-Assessed Severity as a Determinant of Coronavirus Disease 2019 Symptom Specificity: A Longitudinal Cohort Study
Authors: Bershteyn Anna , Dahl Angela M , Dong Tracy Q , Deming Meagan E , Celum Connie L , Chu Helen Y , Kottkamp Angelica C , Greninger Alexander L , Hoffman Risa M , Jerome Keith R , Johnston Christine M , Kissinger Patricia J , Landovitz Raphael J , Laufer Miriam K , Luk Alfred , Neuzil Kathleen M , Paasche-Orlow Michael K , Pitts Robert A , Schwartz Mark D , Stankiewicz Karita Helen C , Thorpe Lorna E , Wald Anna , Zheng Crystal Y , Wener Mark H , Barnabas Ruanne V , Brown Elizabeth R
Published: February 2022

Coronavirus disease 2019 symptom definitions rarely include symptom severity. We collected daily nasal swab samples and symptom diaries from contacts of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) case patients. Requiring ≥1 moderate or severe symptom reduced sensitivity to predict SARS-CoV-2 shedding from 60.0% (95% confidence interval [CI], 52.9%−66.7%) to 31.5% (95% CI, 25.7%− 38.0%) but increased specificity from 77.5% (95% CI, 75.3%−79.5%) to 93.8% (95% CI, 92.7%−94.8%).
Focusdata: Foreign Policy through Language and Sentiment
Authors: Fisher Scott , Klein Graig R , Codjo Juste
Published: February 2022

Countries routinely translate official statements and state media articles from native languages to English. Over time, these articles provide a window into what each government is trying to portray to the world. The FOCUSdata Project provides years’ worth of text and language sentiment ratings for hundreds of thousands of articles from state media and ministry of foreign affairs’ websites from North Korea, China, Russia, and Iran. Information is an important foreign policy tool and national security strategists analyze how it influences the attitudes and behaviors of foreign audiences. This article introduces the FOCUSdata Project and shows how the sentiment data provide unique abilities to analyze Russia's and Iran's reactions to US policies and events and NGO human rights campaigns. Evaluating countries’ official narratives improves understanding of government signals to outside actors, reactions to crises and foreign policy tools, and interests regarding (un)favorable developments. Governments’ sentiment provides unique explanatory power.
Generational Shifts in Young Adult Cardiovascular Health? Millennials and Generation X in the United States and England
Authors: Martinson Melissa L , Lapham Jessica , Ercin-Swearinger Hazal , Teitler Julien O , Reichman Nancy E
Published: February 2022

Objectives

To compare cardiovascular (CV) risks/conditions of Millennials (born 1981–1996) to those of Generation X (Gen X; born 1965–1980) at ages 20–34 years, across 2 countries (United States, England), by gender.

Methods

Using data from the National Health and Nutrition Examination Survey (United States) and Health Survey for England, we estimated weighted unadjusted and adjusted gender-specific proportions of CV risk factors/conditions, separately for Millennials and Generation X in each country. We also further calculated sex-specific generational differences in CV risk factor/conditions by income tercile and for individuals with normal body weight.

Results

Millennials in the United States were more obese compared to their Gen X counterparts and more likely to have diabetes risk but less likely to smoke or have high cholesterol. Millennials in England had higher diabetes risk but similar or lower rates of other CV risk/conditions compared to their Gen X counterparts. Generational changes could not be fully attributed to increases in obesity or decreases in income.

Discussion

We expected that Millennial CV risk factors/conditions would be worse than those of Gen X, particularly in the United States, because Millennials came of age during the Great Recession and a period of increasing population obesity. Millennials generally fared worse than their Gen X counterparts in terms of obesity and diabetes risk, especially in the United States, but had lower rates of smoking and high cholesterol in both countries. Secular trends of increasing obesity and decreased economic opportunities did not appear to lead to uniform generational differences in CV risk factors.
Tomato SlCER1–1 catalyzes the synthesis of wax alkanes, increasing drought tolerance and fruit storability
Authors: Wu Hongqi , Liu Le , Chen Yaofeng , Liu Tianxiang , Jiang Qinqin , Wei Zhengyang , Li Chunlian , Wang Zhonghua
Published: February 2022

Very-long-chain (VLC) alkanes are the main wax compounds of tomato fruits and leaves. ECERIFERUM1 (CER1) and ECERIFERUM3 (CER3) are the two key genes involved in VLC alkane biosynthesis in Arabidopsis thaliana. However, CER1 and CER3 homologs have not been investigated in tomato, and their exact biological functions remain unknown. We analyzed the wax profiles of tomato leaves and fruits at different growth stages and characterized the tomato CER1 and CER3 homologs. VLC alkanes were the predominant wax compounds in both leaves and fruits at all developmental stages. We identified five CER1 homologs and two CER3 homologs in tomato, which were designated SlCER1–1 to SlCER1–5 and SlCER3–1 and SlCER3–2, respectively. The genes exhibited tissue- and organ-specific expression patterns and were induced by abiotic stresses. SlCER1–1 was localized to the endoplasmic reticulum (ER), which is also the main site of wax biosynthesis. Silencing SlCER1–1 in tomato significantly reduced the amounts of n-alkanes and branched alkanes, whereas its overexpression in Arabidopsis had the opposite effect. Under drought stress, both n-alkanes and branched alkanes increased significantly in wild-type but not SlCER1–1 RNAi tomato plants. Furthermore, SlCER1–1 silencing also increased the cuticular permeability of leaves and fruits. In conclusion, SlCER1–1 is involved in wax alkane biosynthesis in tomato and plays an important role in drought tolerance and fruit storability.
Predictors of 007 triphosphate concentrations in dried blood spots in persons with hepatitis C and active drug or alcohol use
Authors: Brooks Kristina M , Castillo-Mancilla Jose R , Morrow Mary , Mawhinney Samantha , Rowan Sarah E , Wyles David , Blum Joshua , Huntley Ryan , Salah Lana , Tehrani Arya , Jimmerson Leah C , Roon Laura , Bushman Lane R , Anderson Peter L , Kiser Jennifer J
Published: February 2022

Background

Sofosbuvir is converted to its active form, 007 triphosphate (007-TP), within cells. To date, the association between treatment adherence and 007-TP in dried blood spots (DBS) and factors that influence this relationship remain unknown.

Objectives

To examine relationships between adherence and 007-TP concentrations in DBS and identify factors that influence 007-TP in DBS.

Methods

Persons with HCV or HIV/HCV coinfection and self-reported drug and/or alcohol use were randomized to one of two technology-based approaches for monitoring 12 week adherence to once-daily ledipasvir/sofosbuvir. Convenience blood samples were collected every 2 weeks during treatment. 007-TP in DBS was quantified using LC/MS and analysed using mixed-effects models.

Results

A total of 337 observations were available from 58 participants (78% male; 21% black; 22% Hispanic/Latino; 26% cirrhotic; 78% HIV-coinfected). The mean half-life of 007-TP in DBS was 142 h (95% CI 127–156) and concentrations increased by 7.3% (95% CI 2.2–12.6) for every 10% increase in between-visit adherence. Geometric mean (95% CI) 007-TP concentrations in DBS were 301 (247–368), 544 (462–639) and 647 (571–723) fmol/punch by adherence categories of ≤50%, >50 to ≤80%, and >80%. Adherence, time on therapy, increasing age and decreased estimated glomerular filtration rate were associated with higher 007-TP, whereas increased time since last dose, male sex, black race and higher BMI were associated with lower 007-TP.

Conclusions

007-TP has an extended half-life in DBS and concentrations increased with adherence. Further research is needed to examine additional factors that affect 007-TP and the clinical utility of this measure.
Validation of the 3M™ Molecular Detection Assay 2 - STEC Gene Screen (stx) for the Detection of Shiga Toxin Gene (stx1 and/or stx2) in Additional Matrixes: AOAC Performance Tested MethodSM 071903
Authors: Rosauer Micki L , Barnes Christina , Silbernagel Karen M , Koch Kateland M , Thompson-Strehlow Leslie
Published: February 2022

Background

The 3M™ Molecular Detection Assay 2 - STEC Gene Screen (stx) method is based on gene amplification by the use of real-time loop-mediated isothermal amplification when used with the 3M Molecular Detection System for the rapid and specific detection of Shiga toxin gene (stx1 and/or stx2) from Shiga toxin-producing enterohemorrhagic Escherichia coli (STEC) in enriched foods.

Objective

The 3M Molecular Detection Assay 2 - STEC Gene Screen (stx) method was evaluated as a Level 2 method modification to add new matrixes to the certified claim: 25 g fresh raw ground beef (approximately 75% lean), 375 g raw beef trim (approximately 75% lean), 375 g fresh raw ground pork (approximately 70% lean), 375 g fresh raw poultry parts, and 25 g sprouts.

Methods

Matrix studies were conducted to assess the method’s performance compared to the US Department of Agriculture Food Safety and Inspection Service Microbiology Laboratory Guidebook, 5C.00 for meat and poultry, and to the US Food and Drug Administration Bacteriological Analytical Manual, Ch. 4A for sprouts, using an unpaired study design.

Results

The 3M Molecular Detection Assay 2 - STEC Gene Screen (stx) method demonstrated no significant differences between presumptive and confirmed results or between candidate and reference method results for any of the matrices tested.

Conclusion and Highlights

The data collected in these studies demonstrate that the 3M Molecular Detection Assay 2 - STEC Gene Screen (stx) is a reliable method for the rapid and specific detection of STEC in fresh raw ground beef (approximately 75% lean), fresh raw beef trim (approximately 75% lean), fresh raw ground pork (approximately 70% lean), fresh raw poultry parts, and sprouts.
Validation of the 3M™ Molecular Detection Assay 2 - STEC Gene Screen (stx and eae) for the Detection of Shiga Toxin Gene (stx1 and/or stx2) and Intimin Gene (eae): AOAC Performance Tested MethodSM 071902
Authors: Rosauer Micki L , Barnes Christina , Silbernagel Karen M , Koch Kateland M
Published: February 2022

Background

The 3M™ Molecular Detection Assay 2 - STEC Gene Screen (stx and eae) method is based on gene amplification by the use of real-time loop-mediated isothermal amplification when used with the 3M Molecular Detection System for the rapid and specific detection of Shiga toxin gene (stx1 and/or stx2) and intimin gene (eae) from Shiga toxin-producing enterohemorrhagic Escherichia coli (STEC) in enriched foods.

Objective

The 3M Molecular Detection Assay 2 - STEC Gene Screen (stx and eae) method was evaluated as a Level 2 method modification to add new matrixes to the certified claim: 25 g fresh raw ground beef (approximately 75% lean), 375 g fresh raw ground pork (approximately 70% lean), 375 g fresh raw poultry parts, and 25 g sprouts.

Methods

Matrix studies were conducted to assess the method’s performance compared to the U. S. Department of Agriculture Food Safety and Inspection Service Microbiology Laboratory Guidebook, 5C.00 for meat and poultry, and to the U. S. Food and Drug Administration Bacteriological Analytical Manual, Ch. 4A for sprouts, using an unpaired study design.

Results

The 3M Molecular Detection Assay 2 - STEC Gene Screen (stx and eae) method demonstrated no significant differences between presumptive and confirmed results or between candidate and reference method results for any of the matrixes tested.

Conclusion and Highlights

The data collected in these studies demonstrate that the 3M Molecular Detection Assay 2 - STEC Gene Screen (stx and eae) is a reliable method for the rapid and specific detection of STEC in fresh raw ground beef (approximately 75% lean), fresh raw ground pork (approximately 70% lean), fresh raw poultry parts, and sprouts.
Honoring the public trust: curbing the bane of physician sexual misconduct
Authors: Sindhu Kunal K , Schaffer Adam C , Cohen I Glenn , Allensworth Rebecca Haw , Adashi Eli Y
Published: February 2022

The Federation of State Medical Boards defines physician sexual misconduct as any ‘behavior that exploits the physician-patient relationship in a sexual way.’ Although several attempts have been made in recent years to clarify its incidence in the United States, physician sexual misconduct is almost certainly underreported. Physician sexual misconduct represents a severe and irreversible violation of the compact underlying the patient–physician relationship and can have far-reaching consequences on the lives of patients and their families. In addition, the credibility of and trust in physicians, both essential to the provision of medical care, could well erode in the eyes of the public at large if egregious cases of physician sexual misconduct are perceived as having gone unpunished. Although all physician licensees accused of sexual misconduct are entitled to the presumption of innocence and due process, complaints made by patients must be taken seriously and vigorously pursued. In this article, we discuss the ongoing challenge of physician sexual misconduct and provide recommendations to improve its reporting and curb its incidence.