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LowMC is a family of block ciphers proposed by Albrecht et al. at EUROCRYPT 2015, which is tailored specifically for FHE and MPC applications. At ToSC 2018, a difference enumeration attack was given for the cryptanalysis of low-data instances of full LowMCv2 with few applied S-boxes per round. Recently at CRYPTO 2021, an efficient algebraic technique was proposed to attack 4-round LowMC adopting a full S-box layer. Following these works, we present a new difference enumeration attack framework, which is based on our new observations on the LowMC S-box, to analyze LowMC instances with a full S-box layer. As a result, with only 3 chosen plaintexts, we can attack 4-round LowMC instances which adopt a full S-box layer with block size of 129, 192, and 255 bits, respectively. We show that all these attacks have either a lower time complexity or a higher success probability than those reported in the CRYPTO paper.

Purpose After adequate surgical resection, early-stage oral tongue cancer patients can harbor a low risk of local recurrence but remain at risk of regional recurrence. Oral tongue avoidance during adjuvant radiation therapy is an attractive potential treatment strategy to mitigate treatment toxicity. We sought to quantify the dosimetric advantages of this approach and hypothesized that intensity-modulated proton therapy (IMPT) may further reduce organs at risk doses compared with intensity-modulated radiation therapy (IMRT). Materials and Methods Five patients with oral tongue cancer treated with postoperative radiation therapy from August 2020 to September 2021 were retrospectively reviewed. Novel clinical target volume contours, excluding the oral tongue, were generated while maintaining coverage of bilateral at-risk lymph nodes. Comparison IMRT (X) and IMPT (PBT) plans were generated using standard treatment volumes (control) and avoidance volumes (study) (n = 4 plans/patient). Dosimetric variables for organs at risk were compared using the paired t test. Results The prescribed dose was 60 Gy in 30 fractions. D95% clinical target volume coverage was similar between X and PBT plans for both control and study clinical target volumes. Comparing control with study plans, both X (58.9 Gy vs 38.3 Gy, P = .007) and PBT (60.2 Gy vs 26.1 Gy, P < .001) decreased the oral cavity dosemean. The pharyngeal constrictor dosemean was also reduced (P< .003). There was no difference between control and study plans for larynx (P = .19), parotid (P = .11), or mandible dose (P = .59). For study plans, PBT significantly reduced oral cavity dosemean (38.3 Gy vs 26.1 Gy, P = .007) and parotid dosemean (23.3 Gy vs 19.3 Gy, P = .03) compared with X. For control plans, there was no difference in oral cavity dosemean using PBT compared with X, but PBT did improve the parotid dosemean (26.6 Gy vs 19.7 Gy, P = .02). Conclusion This study quantifies the feasibility and dosimetric advantages of oral tongue avoidance while still treating the at-risk lymph nodes for oral tongue cancer. The dosimetric difference between PBT and X was most prominent with an oral tongue–avoidance strategy.

Sulfur hexafluoride (SF6) is the most potent greenhouse gas (GHG), and its atmospheric abundance, albeit small, has been increasing rapidly. Although SF6 is used to assess atmospheric transport modeling and its emissions influence the climate for millennia, SF6 emission magnitudes and distributions have substantial uncertainties. In this study, we used NOAA's ground-based and airborne measurements of SF6 to estimate SF6 emissions from the United States between 2007 and 2018. Our results suggest a substantial decline of US SF6 emissions, a trend also reported in the US Environmental Protection Agency's (EPA) national inventory submitted under the United Nations Framework Convention on Climate Change (UNFCCC), implying that US mitigation efforts have had some success. However, the magnitudes of annual emissions derived from atmospheric observations are 40 %–250 % higher than the EPA's national inventory and substantially lower than the Emissions Database for Global Atmospheric Research (EDGAR) inventory. The regional discrepancies between the atmosphere-based estimate and EPA's inventory suggest that emissions from electric power transmission and distribution (ETD) facilities and an SF6 production plant that did not or does not report to the EPA may be underestimated in the national inventory. Furthermore, the atmosphere-based estimates show higher emissions of SF6 in winter than in summer. These enhanced wintertime emissions may result from increased maintenance of ETD equipment in southern states and increased leakage through aging brittle seals in ETD in northern states during winter. The results of this study demonstrate the success of past US SF6 emission mitigations and suggest that substantial additional emission reductions might be achieved through efforts to minimize emissions during servicing or through improving sealing materials in ETD.

Bipolar magnetic semiconductor and spin Seebeck effects in 2H-NbSe2 monolayers.

A sulfonic acid-functionalized zirconium-based coordination catalyst (Zr-BDC-S60) containing Zr4+–O2− pairs and –SO3H groups showed satisfactory catalytic activity and stability for the one-pot reductive etherification of HMF to BIPMF.

The growth of the Internet of Things makes it possible to share information on risky vehicles openly and freely. How to create dynamic knowledge graphs of continually changing risky vehicles has emerged as a crucial technology for identifying risky vehicles, as well as a research hotspot in both artificial intelligence and field knowledge graphs. The node information of the risky vehicle knowledge graph is not rich, and the graph structure plays a major role in its dynamic changes. The paper presents a fusion algorithm based on relational graph convolutional network (R-GCN) and Long Short-Term Memory (LSTM) to build the dynamic knowledge graph of risky vehicles and conducts a comparative experiment on the link prediction task. The results showed that the fusion algorithm based on R-GCN and LSTM had better performance than the other methods such as GCN, DynGEM, ROLAND, and RE-GCN, with the MAP value of 0.2746 and the MRR value of 0.1075. To further verify the proposed algorithm, classification experiments are carried out on the risky vehicle dataset. Accuracy, precision, recall, and F-values were used as heat-tolerance evaluation indexes in classification experiments, the values were 0.667, 0.034, 0.422, and 0.52 respectively.

A sulfonated zirconium–carbon coordination catalyst (Zr-GC-SO3H-1.0), containing Zr4+–O2− pairs and –SO3H groups, showed excellent catalytic activity, stability and universality for the synthesis of various biomass-derived furanic diethers.

Nowadays, composite materials are widely used in high-strength and low-weight parts, such as airborne structures, military equipment, sports devices, etc. Since most of the serpentine pipe parts have the requirement of one-piece forming and high strength, the material of serpentine pipe parts is still mainly metal. However, the parts cannot easily separate from the metal molds after autoclave curing is always a difficult problem in the manufacturing process, which results in failed products. The autoclave process is often long and expensive. Therefore, improving its manufacturing yield rate is very important. To solve this problem, this study employs a ceramic lost foam mold to replace the metal mold used in the autoclave process. By adjusting parameters of autoclave in different experiments and experienced several failed experiments, workable manufacturing processes and parameters are finally obtained such that the composite material made serpentine pipe parts are successfully produced. This paper detailed the causes of failed products and corresponding solutions. Moreover, the current study executed process reproducibility experiments to verify the reproducibility of the proposed method. All experiments have been performed in a real workshop.

Manageable thermal expansion (MTE) of metal trifluorides can be achieved by introducing local structure distortion (LSD) in the negative thermal expansion ScF

Electrocatalyzed urea-assisted wastewater splitting is a promising approach for sustainable hydrogen production. However, the lack of cost-efficient electrocatalysts hinders its practical application. Herein, bimetal phosphide (NiCoP

Aging is accompanied by muscle loss. In older adults with cancer sarcopenia (OACS), systemic inflammation, reduced food intake, and reduced physical activity led to a poor prognosis. This study was to investigate the prognostic ability of the inflammatory Geriatric Nutritional Risk Index (GNRI), which combines patient's inflammation, diet status, and physical activity status to predict overall survival of OACS.This prospective multi-center study enrolled 637 OACS, with an average age of 72.78 ± 5.98 years, of which 408 (64.1%) were males. We constructed the Inflammatory Functional Prognostic Index (IFPI) of OACS based on inflammatory GNRI scores, reduced food intake, and reduced physical activity. According to the IFPI, OACS was divided into high-, moderate-, and low-risk groups. Univariate and multivariate survival analyses analyzed the prognostic ability of the clinical parameters.Compared with OACS with a high GNRI score, the 1-, 3-, and 5-year hazard ratios (95% confidence interval) of OACS with a low GNRI score was 1.816 (1.076-3.063), 1.678 (1.118-2.518), and 1.627 (1.101-2.407), respectively. This result was consistent with that of the calibration curve. The subgroup analysis showed that the low GNRI score had a significant positive relation with patients with gastrointestinal cancer (PThe GNRI score was a short-term and long-term inflammatory prognostic indicator for OACS. The IFPI score could improve patient survival prediction.

In recent years, public high school teachers have received widespread attention from all walks of life because of their particularity, and occupational stress is also one of the key issues. Public high school teachers' widespread professional pressure will affect their own development and work efficiency, and will also have a negative impact on the development of students. This paper investigates the current situation of professional pressure of public high school teachers, and analyzes it from the aspects of teachers' professional pressure, interpersonal relationship pressure, professional burden pressure, professional development pressure, student management pressure and family pressure. The results show that teachers in public high schools generally have occupational stress. In view of this situation, we can improve from the aspects of school, society, teachers themselves and families to relieve the professional pressure of public high school teachers.

The aim of the study described here was to assess the evaluation of tissue stiffness around lesions by sound touch shear wave elastography (STE) in breast malignancy diagnosis. This was an institutional ethics committee-approved, single-center study. A total of 90 women with breast masses examined with conventional ultrasound and STE were eligible for enrollment from December 2020 to July 2021. The maximum and mean elastic values of masses, E

Global emissions of the ozone depleting gas 1,1-dichloro-1-fluoroethane (HCFC-141b, CH3CCl2F), derived from measurements of atmospheric mole fractions, have been rising between 2017–2021 despite a fall in reported production and consumption for dispersive uses. This study evaluates the possible drivers behind this renewed rise in emissions. HCFC-141b is a controlled substance under the Montreal Protocol, and its phase-out is currently underway, after a peak in reported consumption and production in developing countries (Article 5) in 2013. If reported production and consumption are correct, it suggests that the 2017–2021 rise is due to an increase in emissions from the bank when HCFC-141b containing appliances reach the end of their life, or from production of HCFC-141b not reported for dispersive uses. Regional emissions have been estimated between 2017–2020 for all regions where measurements have sufficient sensitivity to emissions. This includes the regions of northwestern Europe, east Asia, the USA and Australia, where emissions decreased by a total of 1.6 ± 3.9 Gg yr−1, compared to a mean global increase of 3.0 ± 1.2 Gg yr−1 over the same period. Collectively these regions only account for around a third of global emissions in 2020. Therefore we are not able to pinpoint the source regions or specific activities responsible for the recent global emission rise.

Yi-Lun Ge,1,&ast; Si-Yi Gong,1,&ast; Pu-Zhi Wang,1 Jia-Hui Yan,1 Wen Li,1 Jin-Ru Zhang,1 Hong Jin,1 Sheng Zhuang,1 Lei Hu,2 Chang-Wei Ding,2 Ya-Ping Yang,1 Fen Wang,3 Dan Li,4 Jing Chen,1 Cheng-Jie Mao,1,4 Ying-Chun Zhang,2 Kai Li,1 Chun-Feng Liu1,3,4 1Department of Neurology, the Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu, People’s Republic of China; 2Department of Ultrasound, the Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu, People’s Republic of China; 3Institute of Neuroscience, Soochow University, Suzhou, Jiangsu, People’s Republic of China; 4Department of Neurology, Suqian First Hospital, Suqian, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Kai Li, Department of Neurology, the Second Affiliated Hospital of Soochow University, No. 1055 Sanxiang Road, Suzhou, Jiangsu, 215004, People’s Republic of China, Tel +86-512-6778-4179, Fax +86-512-6828-4303, Email liskai@126.comPurpose: Cognitive impairment (CI) is a common but debilitating non-motor symptom in Parkinson’s disease (PD). Although cerebrovascular functions are related to cognitive performance in healthy individuals, such a relation in PD remains elusive. This study aims to assess the association between cerebrovascular function and cognitive performance in PD individuals.Patients and Methods: Two-hundred-and-one PD individuals were retrospectively included. They were subsequently divided into two groups: PD with normal cognition (PD-NC) and PD with CI (PD-CI). Cerebral hemodynamic characteristics of the middle cerebral arteries were assessed by transcranial ultrasound. The association between scores in each cognitive domain and cerebral hemodynamic parameters was further analyzed using regression analyses. Additionally, a binary logistic regression model with backward stepwise procedure was applied to build the model for discriminating CI in PD individuals. An independent dataset of additional 46 PD individuals was used further.Results: The PD-CI group showed a relatively lower end-diastolic blood flow velocity (EDV, p < 0.05) and a higher resistive index (RI, p < 0.05) compared to the PD-NC group. RI showed significant associations with the memory item score of Montreal Cognitive Assessment (p < 0.05). A model combining clinical and hemodynamic variables was established with optimal efficiency (area under the curve, AUC = 0.651). Further replication of the model in an independent dataset yielded a great consistency (AUC = 0.704).Conclusion: In our study, cerebrovascular functions were significantly associated with the cognitive performance in PD individuals, especially with the memory task. The established model was effective in identifying CI in PD individuals, which might be a potentially useful tool to screen the cognitive decline in PD individuals at an early stage of the disease. Further studies with larger sample sizes in different populations are warranted.Keywords: Parkinson’s disease, cognitive impairment, transcranial ultrasound, resistive index

In this paper, we investigate a damped variable-coefficient fifth-order modified Korteweg–de Vries equation for the small-amplitude surface waves in a strait or large channel of slowly-varying depth and width and non-vanishing vorticity, in which α 1 ( t ) , β ( t ) and γ ( t ) are the dispersive, dissipative and line-damping coefficients, respectively, where t is the temporal variable. Bilinear forms, bilinear Backlund transformation and multi-soliton solutions are constructed via the Hirota bilinear method under some variable-coefficient constraints. Based on those multi-soliton solutions, multi-pole, breather and hybrid solutions are derived. Effects of α 1 ( t ) , β ( t ) and γ ( t ) on the solutions are discussed analytically and graphically. For the solitons, we find that α 1 ( t ) and β ( t ) are related to the velocities and characteristic lines, and the amplitudes depend on γ ( t ) . For the multi-pole and breather solutions, α 1 ( t ) and β ( t ) influence the center trajectories of the solutions, while γ ( t ) influences the amplitudes. Hybrid solutions composed of the breathers and solitons are worked out and discussed graphically.

BACKGROUND: To use adversarial training to increase the generalizability and diagnostic accuracy of deep learning models for prostate cancer diagnosis. METHODS: This multicenter study retrospectively included 396 prostate cancer patients who underwent magnetic resonance imaging (development set, 297 patients from Shanghai Jiao Tong University Affiliated Sixth People’s Hospital and Eighth People’s Hospital; test set, 99 patients from Renmin Hospital of Wuhan University). Two binary classification deep learning models for clinically significant prostate cancer classification [PM1, pretraining Visual Geometry Group network (VGGNet)-16-based model 1; PM2, pretraining residual network (ResNet)-50-based model 2] and two multiclass classification deep learning models for prostate cancer grading (PM3, pretraining VGGNet-16-based model 3; PM4: pretraining ResNet-50-based model 4) were built using apparent diffusion coefficient and T2-weighted images. These models were then retrained with adversarial examples starting from the initial random model parameters (AM1, adversarial training VGGNet-16 model 1; AM2, adversarial training ResNet-50 model 2; AM3, adversarial training VGGNet-16 model 3; AM4, adversarial training ResNet-50 model 4, respectively). To verify whether adversarial training can improve the diagnostic model’s effectiveness, we compared the diagnostic performance of the deep learning methods before and after adversarial training. Receiver operating characteristic curve analysis was performed to evaluate significant prostate cancer classification models. Differences in areas under the curve (AUCs) were compared using Delong’s tests. The quadratic weighted kappa score was used to verify the PCa grading models. RESULTS: AM1 and AM2 had significantly higher AUCs than PM1 and PM2 in the internal validation dataset (0.84 vs. 0.89 and 0.83 vs. 0.87) and test dataset (0.73 vs. 0.86 and 0.72 vs. 0.82). AM3 and AM4 showed higher κ values than PM3 and PM4 in the internal validation dataset {0.266 [95% confidence interval (CI): 0.152–0.379] vs. 0.292 (95% CI: 0.178–0.405) and 0.254 (95% CI: 0.159–0.390) vs. 0.279 (95% CI: 0.163−0.396)} and test set [0.196 (95% CI: 0.029–0.362) vs. 0.268 (95% CI: 0.109–0.427) and 0.183 (95% CI: 0.015–0.351) vs. 0.228 (95% CI: 0.068−0.389)]. CONCLUSIONS: Using adversarial examples to train prostate cancer classification deep learning models can improve their generalizability and classification abilities.