bluuebunny/crossref_metadata_2025 huggingface dataset:
Approximate time–energy uncertainty relationship from the fixed-energy sum over paths approach
Authors: Malgieri Massimiliano , Zuccarini Giacomo , Onorato Pasquale
Published: May 2022

In this article, we show how an approximate time–energy uncertainty relationship of the form Δ EΔ t ≃ ℏ can be derived in the context of the fixed-energy sum over paths approach to quantum bound systems. The relationship connects the indeterminacy Δ t on the travel time of the quantum object to the width Δ E of the resonance in the approximate Green function corresponding to an allowed value of energy. The mathematical origin of the relationship is to be tracked to the Fourier transform relationship between the time propagator and energy-dependent Green function; however, the core of the derivation does not use advanced mathematics, may be carried out using mostly graphical and geometrical methods, and may provide insight to students on the meaning and origin of the time–energy uncertainty relationship. Our work may contribute to close a gap by which the time–energy relationship is most often taught with insufficient explanation at elementary level.
Strain rate effect on tensile strength of glass fiber-reinforced polymers
Authors: Wang Wenjie , Mo Zonglai , Chouw Nawawi , Jayaraman Krishnan
Published: May 2022

This study presents the tensile properties of glass fiber-reinforced polymer (GFRP) composites under dynamic loadings. The dynamic tensile tests were performed via a high-speed servo-hydraulic testing machine with a velocity ranging from 1 m/s to 15 m/s, corresponding to a strain rate range between 4.9 s−1 and 93.7 s−1. The effects of the strain rate on the tensile strength and dynamic increase factor (DIF) were considered. The results showed that the tensile strength and DIF of GFRP increased with the strain rate. The failure pattern of GFRP was discussed via a group of high-speed camera images. The results of this research can provide useful information for future construction, e.g., protective structures under extreme impacts.
Molecular Motors–Nature’s Efficiency at Work
Authors: Teizer Winfried
Published: May 2022

Nature has generated sophisticated and very efficient molecular motors, employed for nanoscale transport at the intracellular level. As a complementary tool to nanofluidics, these motors have been envisioned for nanotechnological devices. In order to pave the way for such applications, a thorough understanding of the mechanisms governing these motors is needed. Because of the complexity of their in vivo functions, this understanding is best acquired in vitro, where functional parameters can independently be controlled. I will report on work in my group that studies and harnesses the transport properties of molecular motors on functionalized structures of reduced dimensionality such as carbon nanotubes, 1 lithographically designed electrodes, 2 microwires, 3 loops 4 and swarms. 5 In addition, I will show results that demonstrate the potential of this work for biomedical advances. 6
ESPSim: An Efficient Scalable Power Grid Simulator Based on Parallel Algebraic Multigrid
Authors: Li Chunqiao , An Chengtao , Yang Fan , Zeng Xuan
Published: May 2022

Fast verification for the extremely large-scale power grid is demanding as CMOS technology advances consistently. In this work, we propose ESPSim, an efficient scalable power grid simulator based on a parallel smoothed aggregation-based algebraic multigrid technique. ESPSim has the ability to do fast DC and transient analysis through MPI and adaptive timestep control mechanism. Thanks to the smoother applied on the prolongation operator, ESPSim copes well with the convergence rate on extremely large-scale power grid transient analysis. Extensive experiments are conducted with a variety of serial/parallel solvers. The runtime of ESPSim is linear with case size. With 16 processors, 1,000 timesteps transient analysis of 63.4M nodes can be completed in 22.1 min. Over 22× speedup compared to the well-known direct solver Cholmod is observed.
Timed Automata as a Formalism for Expressing Security: A Survey on Theory and Practice
Authors: Arcile Johan , André Étienne
Published: May 2022

Timed automata are a common formalism for the verification of concurrent systems subject to timing constraints. They extend finite-state automata with clocks, that constrain the system behavior in locations, and to take transitions. While timed automata were originally designed for
safety
(in the wide sense of correctness w.r.t. a formal property), they were progressively used in a number of works to guarantee
security
properties. In this work, we review works studying security properties for timed automata over the past two decades. We notably review theoretical works, with a particular focus on opacity, as well as more practical works, with a particular focus on attack trees and their extensions. We derive main conclusions concerning open perspectives, as well as tool support.
Personal, Not Real: Manufactured Housing Insecurity, Real Property, and the Law
Authors: Sullivan Esther
Published: May 2022

Manufactured homes provide a critical source of affordable housing and are the primary source of low-income homeownership in the United States. Yet manufactured housing (MH) is both socially stigmatized and spatially marginalized, which translates to significant inequalities for MH residents. The law figures centrally into how MH is perceived and how it is located, segregated, and financed differently from other housing. This review explores how the law has treated MH with legal hybridity, as personal property similar to an automobile rather than real property like other forms of housing. This core legal distinction structures an array of zoning, financing, and policy provisions that together create a gulf between the opportunities available to conventional owners and renters and those available to residents of MH. I explore existing research on the outcomes of this disparate legal treatment to offer an agenda for future research on a broader range of housing insecurities.
The influence of longitudinal muscle fascicle growth on mechanical function
Authors: Hinks Avery , Franchi Martino V. , Power Geoffrey A.
Published: May 2022

Skeletal muscle has the remarkable ability to remodel and adapt, such as the increase in serial sarcomere number (SSN) or fascicle length (FL) observed after overstretching a muscle. This type of remodeling is termed longitudinal muscle fascicle growth, and its impact on biomechanical function has been of interest since the 1960s due to its clinical applications in muscle strain injury, muscle spasticity, and sarcopenia. Despite simplified hypotheses on how longitudinal muscle fascicle growth might influence mechanical function, existing literature presents conflicting results partly due to a breadth of methodologies. The purpose of this review is to outline what is currently known about the influence of longitudinal muscle fascicle growth on mechanical function and suggest future directions to address current knowledge gaps and methodological limitations. Various interventions indicate longitudinal muscle fascicle growth can increase the optimal muscle length for active force, but whether the whole force-length relationship widens has been less investigated. Future research should also explore the ability for longitudinal fascicle growth to broaden the torque-angle relationship’s plateau region, and the relation to increased force during shortening. Without a concurrent increase in intramuscular collagen, longitudinal muscle fascicle growth also reduces passive tension at long muscle lengths; further research is required to understand whether this translates to increased joint range of motion. Finally, some evidence suggests longitudinal fascicle growth can increase maximum shortening velocity and peak isotonic power; however, there has yet to be direct assessment of these measures in a neurologically intact model of longitudinal muscle fascicle growth.
Thermal Storage for the Analysis of Hybrid Energy Systems Based on Geothermal and Solar Power
Authors: Aravind K. U. , Mekala N. Muthu , Muthuraju N. P. , Soni N. B. , Al-Ammar Essam A. , Seikh A. H. , Siddique M. H. , Christopher David
Published: May 2022

Thermal degradation of geothermal energy occurs even during the duration of geothermal energy facilities. The enormity and efficiency of thermal energy available for electric transformation, as well as plant performance and power production, are both affected by the decrease in geofluid heat. Additionally, due to the generally increased turbine exhaust temperatures, the efficiency of geothermal energy based upon air-cooled organic Rankine cycle devices (ORCs) degrades considerably at hot room temperatures. A newly designed Geothermal-Concentrator Solar Power (GEO-CSP) station is simulated in this work, which allows for greater geothermal power use and enhances the effectiveness of the geothermal ORC system over the power plant’s lifespan. The geothermal fluid entering the ORC’s heating element is heated using the sun’s radiation. The CSP facility is fitted with a thermal energy storing unit that stores excess energy from the sun accessible throughout the day and releases it at nighttime whenever the energy system’s performance is better. When the storage facility is included in the concentrator CSP technology, the incremental yearly energy generation from solar increases by 19 percent, from 5.3 percent to 6.3 percent, similar to the geothermal-only plant. As a result, adding a TES unit to the hybrid unit could be quite beneficial.
Surgical Selection of T1 Stage Renal Tumor Resection Based on Imaging MAP Score under Smart Medical Care
Authors: Zong Hongtao , Xia Qiang , Zhang Liansheng , Zhu Jin
Published: May 2022

Smart medical uses the medical information platform and the current technological means to enable the process of sharing information between medical staff and medical equipment. The combination of current technology and the medical field has become the norm. In the future, more artificial intelligence technologies will be integrated into the medical field to promote the development of medical care. At present, the information on the Internet is very large and complex, and general search engines often do not have knowledge in certain professional fields and can only perform shallow keyword searches. Therefore, it is difficult to meet people’s medical diagnosis needs, and smart medical care can solve these needs. Medical imaging refers to the technology or process of obtaining internal tissue images of a certain part of the human body for medical research, including medical imaging systems and medical image processing. Medical image processing refers to the further processing of the obtained images, the purpose of which is either to restore the original image that was not clear enough or to highlight some characteristic information in the image. The purpose of this paper is to study the research on the selection of T1 stage renal tumor resection based on the imaging MAP score under smart medical care. It is hoped that through smart medicine and medical imaging technology, it can help renal tumor resection, reduce the sequelae of renal tumor resection, and promote the development of medical services. This paper proposes applying natural language processing technology to the medical field, creating an intelligent diagnosis assistance system, and using the existing medical record data to realize the corresponding medical assistance functions. It studies the class imbalance problem prevalent in medical datasets and provides better solutions through ensemble learning techniques to improve classifier performance when the number of positive and negative samples is unbalanced. The experimental results in this paper show that the creatinine of patients undergoing renal tumor resection combined with smart medicine and imaging technology is stable at 75 mol/L, while the creatinine is stable at 71 mol/L in other methods. It shows that the postoperative effect of smart medical treatment and imaging technology is better.
Efficient Liver Segmentation from Computed Tomography Images Using Deep Learning
Authors: Ahmad Mubashir , Qadri Syed Furqan , Ashraf M. Usman , Subhi Khalid , Khan Salabat , Zareen Syeda Shamaila , Qadri Salman
Published: May 2022

Segmentation of a liver in computed tomography (CT) images is an important step toward quantitative biomarkers for a computer-aided decision support system and precise medical diagnosis. To overcome the difficulties that come across the liver segmentation that are affected by fuzzy boundaries, stacked autoencoder (SAE) is applied to learn the most discriminative features of the liver among other tissues in abdominal images. In this paper, we propose a patch-based deep learning method for the segmentation of a liver from CT images using SAE. Unlike the traditional machine learning methods, instead of anticipating pixel by pixel learning, our algorithm utilizes the patches to learn the representations and identify the liver area. We preprocessed the whole dataset to get the enhanced images and converted each image into many overlapping patches. These patches are given as input to SAE for unsupervised feature learning. Finally, the learned features with labels of the images are fine tuned, and the classification is performed to develop the probability map in a supervised way. Experimental results demonstrate that our proposed algorithm shows satisfactory results on test images. Our method achieved a 96.47% dice similarity coefficient (DSC), which is better than other methods in the same domain.
Removal of Reactive Red 120 in a Batch Technique Using Seaweed‐Based Biochar: A Response Surface Methodology Approach
Authors: Ravindiran Gokulan , Gaddam Kalyani , Sunil Killi
Published: May 2022

The elimination of Reactive Red 120 (RR120) from synthetic solution using biochar generated from Ulva prolifera was investigated. The process parameters sorbent dose (A), pH (B), initial dye concentration (C), and temperatures (D) were optimized using response surface methodology (RSM). To estimate the removal effectiveness of dye with the best 27 trails, the Box‐Behnken method (blocked) was utilised. Analysis of variance (ANOVA), main effect plot, interaction plot, and surface plot were used to establish the significance of the model, and the confidence level of the model was set at 95%. To maximise the objective, the RSM optimizer was utilised with a desirability of 1. Furthermore, the batch investigation was supplemented by isotherm models, kinetic models, and thermodynamic analyses to understand the adsorption mechanism.
Effects of Dietary Tuna Viscera Hydrolysate Supplementation on Growth, Intestinal Mucosal Response, and Resistance to Streptococcus iniae Infection in Pompano (Trachinotus blochii)
Authors: Pham Hung Duc , Siddik Muhammad A. B. , Le Hoang Minh , Ngo Manh Van , Nguyen Minh Van , Francis David
Published: May 2022

The effects of tuna viscera hydrolysate (TVH) on juvenile pompano Trachinotus blochii, growth performance, nutritional response, intestinal and liver health, and resistance to Streptococcus iniae were investigated in this study. Five isonitrogenous and isocaloric diets (protein 46.0%, lipid 10.0%) were formulated in which TVH was added to replace fishmeal protein at levels of 0 (control), 30, 60, 90, and 120 g kg-1, labelled as TVH0, TVH05, TVH10, TVH15, and TVH20, respectively. Triplicate groups of pompano were fed the respective diets for ten weeks. The results showed that fish fed diets containing TVH10 produced significantly higher final body weight and specific growth rate in comparison to the fishmeal control (

P
<
0.05

). Dietary TVH did not produce any effect on feed utilisation, somatic indices, and proximate composition of juvenile pompano (

P
>
0.05

). While most amino acids were unchanged by the dietary inclusion of TVH, phenylalanine and valine levels were significantly lower in the fish fed TVH20 diet compared to the control. Fish fed the TVH20 diet had significantly lowered total serum protein compared to the TVH10 treatment, whereas other biochemical parameters in the blood did not show any difference among treatments. The intestinal histology indicated a significant increase in goblet cell numbers in fish fed TVH10 diet. Fish fed diet supplemented with TVH showed the highest disease resistance against Streptococcus iniae after 14 days of challenge. Based on a quadratic regression between final body weight and dietary TVH levels, the optimum TVH was calculated to be 10% or 60.0 g kg-1 for maximum growth performance when fed to pompano.
Evaluation of Bacterial Cellulose Dressing versus Vaseline Gauze in Partial Thickness Burn Wounds and Skin Graft Donor Sites: A Two-Center Randomized Controlled Clinical Study
Authors: Pan Xuanliang , Han Chunmao , Chen Guoxian , Fan Youfen
Published: May 2022

Objective. Bacterial cellulose (BC) dressing, which can maintain a moist environment and prevent the invasion of pathogens, has become a competitive dressing material for burn wound treatment. This study was conducted to evaluate the treatment efficacy of a novel China-made BC dressing for the treatment of second-degree burn wounds and skin graft donor sites. Methods. 212 patients with second-degree burn wounds or skin graft donor sites were enrolled from two research centers. They were randomly assigned to the BC dressing group (study group) or the Vaseline gauze (VG) dressing group (control group). Wound conditions were assessed before and after treatment. Dressings were changed according to the condition of the wound bed. Healing rate and healing time were recorded as primary endpoints to evaluate the efficacy of BC dressing against VG dressing. Erythema, swelling, exudation, bleeding, subeschar purulence, and pain were assessed as secondary endpoints. Results. 207 participants completed the trial and their wounds all healed within 28 days. The average healing times for superficial and deep secondary burn wounds and skin graft donor sites in the BC group were 8.12, 15.77, and 10.55 days, respectively. In the VG group, the average healing times for superficial and deep secondary burn wounds and skin graft donor sites were 9.30, 15.27, and 11.19 days, respectively. The healing time of superficial burn wounds in the BC group was statistically shorter than that in the VG group. There was no difference in the frequency of dressing changing between two groups. The BC dressing showed equal efficacy with the VG dressing at all secondary endpoints. Conclusion. The novel BC dressing could be used for the management of second-degree burn wounds and skin graft donor sites. With a shorter healing time in superficial secondary burn wound than that of the VG dressing, the BC dressing showed noninferiority in the treatment of superficial and deep secondary burn wounds and skin graft donor sites versus the VG dressing. This study is registered with the Chinese Clinical Trial Registry (registry number: ChiCTR1800014377 (http://www.chictr.org.cn)).
Levetiracetam Attenuates the Spinal Cord Injury Induced by Acute Trauma via Suppressing the Expression of Perforin
Authors: Xia Hong , Huang Jiaqiang , Liu Jian , Zhang Hua , Chen Dawei , Zhang Wen , Zhou Xianghong , Wei Zhouyang , Liu Zhaoxiang
Published: May 2022

The spinal cord injury (SCI) is one of the major reasons causing the motor dysfunctions of the patients. At present, few therapeutic strategies can effectively improve the symptom of SCI. Levetiracetam has been confirmed to alleviate the injury of nerve cells, while its functions in SCI remains unclear. In this study, C57BL/6J mice were used to establish SCI models to observe the effect of levetiracetam on SCI. The mice were fed with 180 mg/kg levetiracetam when suffering from SCI, and Basso mouse score (BMS) and CatWalk-assisted gait analysis were used to observe the motor functions of the mice. Nissl staining and TUNEL staining were used to observe the injury of nerve cells. The abundance of inflammatory factors was measured by ELISA. The permeability of blood-spinal cord barrier (BSCB) in mice was detected with macrophage infiltration analysis. Moreover, the abundance of perforin in the tissues was detected by western blot. The results showed that the SCI mice treated with levetiracetam exhibited lighter motor dysfunction compared with the mice treated with saline. Levetiracetam can effectively reduce the inflammatory reactions and alleviate apoptosis of the nerve cells. Moreover, levetiracetam remarkably decreased the BSCB permeability of SCI mice. Besides, it was also found that levetiracetam can significantly inhibit the expression of perforin. In conclusion, this study suggests that levetiracetam can attenuate the injury of BSCB to block the progression of SCI via suppressing the expression of perforin.
The Use of BP Neural Network Algorithm and Natural Language Processing in the Impact of Social Audit on Enterprise Innovation Ability
Authors: Wang Jie , Wang Xiaomei , Wen Haili
Published: May 2022

At present, there are still some problems in the document management of enterprise innovation projects, such as non-standard management, lagging update, chaotic content, insufficient information, and insufficient application. There is still a lack of effective methods to evaluate the financing ability of enterprises. To solve the above problems, high technology expertise (HNTE) is taken as the research objects. Firstly, the relationship between social audit and enterprise technological innovation is analyzed, and on this basis, combined with natural language processing (NLP), an extraction method of project document information is proposed. Secondly, the evaluation index system of enterprise financing ability is constructed based on Back Propagation Neural Network (BPNN), and the technology innovation audit system of HNTEs. Finally, combined with the actual content, the proposed document audit method is evaluated. The results show that: the average accuracy rate of the NLP-based innovation project document audit method is 91.36%, the average recall rate is 96.34%, and the average F statistical value is 95.34%. Among them, the recall rate and F statistical value are about 2.3% and 1.4% higher than manual processing, respectively. The recall rate and F value are obviously better than those of manual processing methods, and the processing time of single document based on NLP is only 87.5 s. The processing time is nearly 50 times lower than that of manual processing, which greatly improves the processing efficiency of document information. The corresponding test results of each index selected based on the evaluation of enterprise financing ability are all below 0.1, which meets the requirements of consistency. The evaluation results of BPNN model on enterprise financing ability are highly consistent with the target value, and the prediction error is controlled within 0.02, which can provide more accurate prediction results. This research obtains a more accurate prediction model of enterprise financing ability evaluation, which provides technical support for social auditing and the innovation and development of enterprise technology, and provides a feasible route for the development of BPNN in the financial field.
Sustainability Assessment of Electricity Generation Development under the Implementation of Support Policies with Endogenous Financial Resources Using a Hybrid Decision Support Model
Authors: Dianat Fateme , Khodakarami Vahid , Shakouri Ganjavi Hamed , Hosseini Seyed-Hossein
Published: May 2022

Sustainable electricity development is one of the requirements for achieving sustainable development in global communities. However, due to barriers, especially in less developed countries, there is little incentive to invest in the development of sustainable electricity technologies. Therefore, there should be a change in market mechanisms, and broad support policies have to be implemented for the sustainable development of electricity. In the long run, these policies must lead to the sustainable development of energy systems. To evaluate the efficiency and effects of the proposed support policies on the sustainability of electricity generation development, this study intends to analyze the multiple and complex dimensions of the problem using a hybrid decision support model. Moreover, by defining an indicator to assess the electricity generation expansion sustainability, this study assists policymakers in making logical decisions about sustainable support programs for the electricity development based on the characteristics of the electricity market of each country. Despite uncertainties in the electricity market, simulations show that the results of this hybrid model have approximately 88% conformance with historical data. Consequently, the model can evaluate the sustainability of the system under the implementation of the proposed support programs and compare them to select the most effective one. The results show that by assuming a competitive market and rational behavior and implementing support programs with endogenous financial resources, the installed renewable capacity can be improved by up to 70.4% compared with the direct subsidy policies. Regardless of the financial burden of policies (e.g., direct subsidies) and the possibility of facing a budget deficit, these programs can be up to 79.2% more effective in the sustainability of the energy system compared with the direct subsidy policy.
Numerical Investigation of Impact Characteristics of Rigid Retaining Wall for Blocking Landslides: A Case Study of the Shum Wan Road Landslide
Authors: Fan Yunyun , Zhang Feng , Liu Ying , Ma Dongyang
Published: May 2022

Landslides pose a serious threat to the downstream infrastructure and personnel safety. For situations where the location of possible landslides is difficult to determine, or the potential landslides areas are widely distributed and scattered, passive protective structural measures need to be adopted to relieve the threat of landslides. Taking the Shum Wan Road landslide as an example, the discrete element method was used to reproduce and analyze the landslide movement. On this basis, this study conducts a further numerical investigation on the impact characteristics of the rigid retaining wall used to block landslides. The results show that the numerical back analysis can well represent the evolution of the landslide, and the numerical results are in good agreement with the actual situation, thus confirming its correctness and effectiveness. Under the condition of setting a rigid retaining wall, the landslide can be effectively blocked and form a final deposition behind the retaining wall. The impact on the rigid retaining wall varies with time, and the distribution of the impact in space is also uneven. Through the statistical analysis of the contact forces on the retaining wall, the distributions of static and peak stresses on the retaining wall can be obtained. Compared with the static stability, the spatial distribution of dynamic impact is more difficult to predict, especially the area of the peak impact has a significant influence on the design. Numerical investigation can efficiently and reliably provide abundant information of static stress and dynamic impact on the rigid retaining wall, which can provide important reference for the optimal design of the rigid retaining wall structure.
Simultaneous Load Identification Method Based on Hybrid Features and Genetic Algorithm for Nonintrusive Load Monitoring
Authors: Yi Shu-Hui , Wang Jian , Liu Jun-Jie
Published: May 2022

Nonintrusive load monitoring (NILM) is a widely accepted technology to conduct load monitoring. Many effective methods have been established to make NILM more practical. However, the focus of current methods is mainly on the identification accuracy and efficiency of single load under the individual appliance operated independently, which have limited support for the identification problem under multiple appliances operated simultaneously. Therefore, a simultaneous identification method is proposed to efficiently identify the total load under multiple appliances operated simultaneously in this paper. The proposed identification method mainly consists of three parts: hybrid features extraction, simultaneous identification optimization model construction, and frequency-weighting-factor-based genetic algorithm (FWF-GA). Firstly, the hybrid feature model, which integrates the features of active power, reactive power, and harmonic magnitude, is constructed by hybrid features extraction. Secondly, the simultaneous identification optimization model is constructed by employing the features of active and reactive power. Thirdly, the developed FWF-GA is used to solve the simultaneous identification optimization problem. In FWF-GA, the relative errors of active power, reactive power, and the frequency-weighting factor of harmonic magnitude are used to evaluate the fitness of an individual. Finally, a NILM practice to identify household appliances is used to demonstrate the validity of the proposed method.
Prediction of Ultimate Antifloating Force of Bored Piles in Urban Road Crossing Overpass
Authors: Minxia Zhang , Kaijun Fan , Shengrong Liao , Ping Xu , Jinwei Li , Chen Chen
Published: May 2022

As an effective antifloating measurement in underpass engineering, uplift piles have been widely employed in the antifloating design of underground structures, such as basements, underground roads, and underground shopping malls. For the purpose of studying the antifloating behavior of bored piles and predicting the uplift bearing capacity in underpass engineering, the on-site pull-out tests of bored piles are carried out in laboratory. Besides, the MMF growth curve model, the ordinary hyperbolic model, and the exponential model are employed to fit and predict the ultimate bearing capacity of the measured uplift load and uplift displacement data of three test piles, respectively. The research results indicate that three test piles meet the stability requirements of antibuoyant bearing capacity, and the pull-up load-displacement curves of test piles are gentle and steep. Meanwhile, the fitting accuracy of the pull-displacement curve is high; specifically, the correlation coefficient is above 0.98619, and the average value is 0.99134, thereby verifying that the fitting effect of MMF growth curve model is better than those of the hyperbolic model and the exponential model. Therefore, the MMF growth curve model proposed in this paper not only describes the fitting of the uplift load-uplift displacement curve of uplift piles accurately but also predicts the ultimate bearing capacity of test piles. The research results provide an important reference for the antifloating behavior of bored piles in underpass engineering.
Novel Hidden Bit Location Method towards JPEG Steganography
Authors: Pan Binmin , Qiao Tong , Li Jiaming , Chen Yiyang , Yang Chunfang
Published: May 2022

Image steganalysis has been widely studied, most of which can only complete the binary task of identifying the existence of hidden bits in an inquiry image. Currently, although some algorithms have been proposed to locate hidden bits, most of them mainly focus on the spatial domain, while usually ignoring the study of locating secret bits hidden in DCT domain for JPEG image. To address that challengeable problem, in this paper, towards two classical steganographic algorithms JSteg and F5, hiding bits in DCT domain, we propose a novel payload location method. The principal step of payload location is to estimate the cover image. We novelly propose to assign the different weights to the DCT coefficient residual in virtue of the texture of regions measured by the local variance, leading to the remarkable improvement of location results. Compared with the state of the art, the numerical experiments empirically verify that our proposed location method achieves the superior performance. In particular, when locating hidden bits in JSteg steganographic images with quality factor of 95 at the payload 0.1, the accuracy of location is remarkably improved from 46.18% to 90.22%.
Hostile Takeover: Tregs Expand in IFNγ-Rich AML Microenvironment
Authors: Ferrell P. Brent , Kordasti Shahram
Published: May 2022

The unexpected higher level of IFNγ in a subset of patients with acute myeloid leukemia (AML; IFNγhigh) upregulates immunosuppressive genes in mesenchymal stem cells (MSC) and expands regulatory T cells through IDO1 overexpression. IDO1 and IFNG gene expression was positively correlated and required both leukemia cells and MSCs, as IFNγhigh cells were not able to induce Tregs alone.

See related article by Corradi et al., p. 3141
GAS6-AXL Inhibition by AVB-500 Overcomes Resistance to Paclitaxel in Endometrial Cancer by Decreasing Tumor Cell Glycolysis
Authors: Bruce Shaina F. , Cho Kevin , Noia Hollie , Lomonosova Elena , Stock Elizabeth C. , Oplt Alyssa , Blachut Barbara , Mullen Mary M. , Kuroki Lindsay M. , Hagemann Andrea R. , McCourt Carolyn K. , Thaker Premal H. , Khabele Dineo , Powell Matthew A. , Mutch David G. , Shriver Leah P. , Patti Gary J. , Fuh Katherine C.
Published: May 2022

Chemotherapy is often ineffective in advanced-stage and aggressive histologic subtypes of endometrial cancer. Overexpression of the receptor tyrosine kinase AXL has been found to be associated with therapeutic resistance, metastasis, and poor prognosis. However, the mechanism of how inhibition of AXL improves response to chemotherapy is still largely unknown. Thus, we aimed to determine whether treatment with AVB-500, a selective inhibitor of GAS6-AXL, improves endometrial cancer cell sensitivity to chemotherapy particularly through metabolic changes. We found that both GAS6 and AXL expression were higher by immunohistochemistry in patient tumors with a poor response to chemotherapy compared with tumors with a good response to chemotherapy. We showed that chemotherapy-resistant endometrial cancer cells (ARK1, uterine serous carcinoma and PUC198, grade 3 endometrioid adenocarcinoma) had improved sensitivity and synergy with paclitaxel and carboplatin when treated in combination with AVB-500. We also found that in vivo intraperitoneal models with ARK1 and PUC198 cells had decreased tumor burden when treated with AVB-500 + paclitaxel compared with paclitaxel alone. Treatment with AVB-500 + paclitaxel decreased AKT signaling, which resulted in a decrease in basal glycolysis. Finally, multiple glycolytic metabolites were lower in the tumors treated with AVB-500 + paclitaxel than in tumors treated with paclitaxel alone. Our study provides strong preclinical rationale for combining AVB-500 with paclitaxel in aggressive endometrial cancer models.
Território, doenças negligenciadas e ação de agentes comunitários e de combate a endemias
Authors: García Gabriela Soledad Márdero , Souza Eliana Amorim de , Araújo Vigna Maria de , Macedo Mariana Sousa Santos , Andrade Rosélly Mascarenhas Amaral de , Ferreira Paulo Rogers da Silva , Guimarães Maria Cristina Soares , Silva José Alexandre Menezes da , Ramos Júnior Alberto Novaes
Published: May 2022

OBJETIVO Caracterizar conhecimentos, práticas e experiência profissional de agentes comunitários de saúde (ACS) e agentes de controle de endemias (ACE) sobre hanseníase e doença de Chagas (DC), durante participação em oficina de formação integrada no projeto IntegraDTNs-Bahia. MÉTODOS Estudo de caso descritivo e exploratório, envolvendo comunitários de saúde e agentes de controle de endemias, participantes de oficina de formação sobre o papel compartilhado desses profissionais no processo de vigilância e atenção à saúde. Projeto desenvolvido nos municípios de Anagé, Tremedal e Vitória da Conquista, no Sudoeste do Estado da Bahia, 2019–2020. Aplicou-se instrumento específico prévio com questões relativas a conhecimentos e práticas de vigilância e atenção para hanseníase e doença de Chagas. Análise descritiva dos dados, além de consolidação da análise léxica. RESULTADOS Do total de 135 participantes (107 ACS e 28 ACE), 80,7% deles atuam há pelo menos 12 anos, sem participação prévia em processos de formação conjunta. Apenas 17,9% dos agentes de controle de endemias relataram ter participado de capacitações sobre hanseníase e nenhum informou desenvolver ações específicas de controle da doença. Para a doença de Chagas, 36,4% dos agentes comunitários de saúde participaram de capacitações há mais de uma década, enquanto para 60,7% dos agentes de controle de endemias a última capacitação foi realizada nos últimos cinco anos. O desenvolvimento de ações educativas para a doença de Chagas foi mais frequente para agentes de controle de endemias (64,3%). Quando perguntados sobre formas de reconhecimento das doenças, a palavra “manchas na pele” foi a mais relatada (38 vezes) para hanseníase e, para a doença de Chagas, a palavra “não sei” (17 vezes). CONCLUSÃO Os processos de atuação de agentes comunitários de saúde e agentes de controle de endemias em realidades endêmicas para hanseníase e doença de Chagas no interior da Bahia revelaram-se desintegrados nos territórios. Para essas doenças, reforça-se o distanciamento entre ações de vigilância e de atenção à saúde, inclusive nos processos de capacitação. Reitera-se a importância de ações inovadoras de educação permanentes e integradas para promover de fato mudanças nas práticas.
Satisfação dos cuidadores e dos idosos usuários do Programa Melhor em Casa
Authors: Silva Natália Romana Gomes da , Gurgel Junior Garibaldi Dantas , Sá Domício Aurelio de , Silva Vanessa de Lima , Moreira Rafael da Silveira
Published: May 2022

OBJETIVO Avaliar a satisfação dos cuidadores e dos idosos usuários do serviço de atenção domiciliar por meio do Programa Melhor em Casa e seus fatores associados. METÓDOS Trata-se de um estudo transversal com dados da pesquisa nacional sobre o Programa Melhor em Casa, conduzida pela Ouvidoria Geral do SUS. Foram entrevistados 5.595 cuidadores e 950 idosos. Quatro perguntas relacionadas à satisfação foram unidas para formulação da variável dependente por meio da análise de classes latentes e 13 perguntas foram utilizadas como variáveis independentes. RESULTADOS Mostraram-se satisfeitos com o serviço, 93,7% dos idosos e 90,2% dos cuidadores. Na análise múltipla, as variáveis que apresentaram associação com a satisfação foram: também ser acompanhados por uma equipe de saúde da família (idoso: OR = 4,22; p = 0,014), menor tempo entre o encaminhamento e a primeira visita (idoso: OR = 10,20; p = 0,006), (cuidador: OR = 5,84; p < 0,001), realização de exames quando havia solicitação médica (idoso: OR = 5,74; p = 0,037), (cuidador: OR = 7,41; p < 0,001), realização de consulta com especialista (cuidador: OR = 6,02; p < 0,001), ter visitas fora do horário agendado quando fosse necessário (idoso: OR = 8,09; p = 0,014), (cuidador: OR = 1,81; p = 0,015) e compreender as orientações que eram passadas pela equipe do programa (cuidador: OR = 10,61; p < 0,001). CONCLUSÕES Constatou-se que a maioria dos idosos e dos cuidadores demonstraram satisfação com o programa, havendo distinção nos aspectos associados a essa satisfação, nos quais apenas as características diretamente relacionadas ao programa influenciaram na satisfação, não ocorrendo o mesmo com as características socioeconômicas e demográficas.
Análise de tendência de mortalidade por sepse no Brasil e por regiões de 2010 a 2019
Authors: Almeida Nyara Rodrigues Conde de , Pontes Giovana Fonseca , Jacob Felipe Lima , Deprá João Victor Salvador , Porto João Pedro Pires , Lima Fernanda Rocha de , Albuquerque Mário Roberto Tavares Cardoso de
Published: May 2022

OBJETIVO Caracterizar o perfil dos pacientes internados e a tendência de mortalidade por sepse no Sistema Único de Saúde (SUS), em todo Brasil e em suas regiões separadamente, entre os anos de 2010 e 2019. MÉTODOS Estudo observacional, analítico e retrospectivo de dados secundários obtidos por consulta ao Sistema de Informação Hospitalar. Foram incluídas todas as notificações por septicemia admitidas entre 1 de janeiro de 2010 e 31 de dezembro de 2019. Utilizou-se as variáveis sociodemográficas: sexo, idade, raça, região e unidade federativa de residência. Para a análise dos dados, utilizou-se coeficiente de mortalidade e de internação, risco relativo e regressão por Joinpoints. RESULTADOS Totalizaram-se 1.044.227 casos de sepse no país, perfazendo um coeficiente de prevalência média de 51,3/100 mil habitantes. Foram registrados 463 mil óbitos por sepse, com coeficiente médio de 22,8 óbitos/100 mil habitantes. As maiores taxas ocorreram entre os idosos, de raça parda e não houve uma diferença significativa entre os sexos. A Região Sudeste foi responsável pelo maior índice de internação e óbitos. Observou-se uma tendência geral de aumento da mortalidade no período estudado. CONCLUSÃO Cabe considerar a heterogeneidade do Brasil, no que concerne às características socioeconômicas e demográficas e às diferenças de investimento em saúde e de subnotificações entre as regiões, a fim de entender o traçado epidemiológico da doença. Por fim, é necessário correlacionar esses achados com demais estudos, buscando entendimento do comportamento da doença e embasamento para políticas públicas e privadas, com intuito de diminuir a expressividade de casos e óbitos por sepse no país.
Hepatitis A and E among immigrants and refugees in Central Brazil
Authors: Costa e Silva Grazielle Rosa da , Martins Thaynara Lorrane Silva , Silva Carla de Almeida , Caetano Karlla Antonieta Amorim , Carneiro Megmar Aparecida dos Santos , Diniz e Silva Bruno Vinicius , Pacheco Leonora Rezende , Villar Livia Melo , Paula Vanessa Salete de , Martins Regina Maria Bringel , Teles Sheila Araújo
Published: May 2022

OBJECTIVE To estimate the prevalence of hepatitis A virus (HAV) and hepatitis E virus (HEV) among immigrants and refugees in Goiás, Central Brazil. METHODS Overall, 355 individuals were interviewed, and blood samples were tested for anti-HAV and anti-HEV IgG. Anti-HEV-positive samples were similarly tested for HEV RNA. RESULTS All participants were from Latin American countries, most of whom, young adult males. The overall anti-HAV IgG prevalence was 87.4% (95%CI: 83.5–90.4), of whom 94.9%, 75.6%, and 60% were from Haiti, Venezuela, and other Latin American countries, respectively (p < 0.001). Age above 19 years and more than 36 months residing in Brazil were associated with a higher prevalence of previous HAV and HEV infection, respectively. Of the children eligible for HAV vaccination according to the National Immunization Program, only eight (44%) had been vaccinated. The overall anti-HEV IgG prevalence was 6.5% (95%CI: 4.4–9.5). All anti-HEV IgG-positive individuals were Haitians, including a child born in Brazil. HEV RNA was detected in two of the anti-HEV IgG-positive samples. CONCLUSION The survey detected a high prevalence of anti-HAV and anti-HEV IgG among immigrants and refugees, and active HEV infection among some Haitian participants. Prevention measures are urgently required to interrupt enteric virus transmission in this emergent and vulnerable population.
Extreme-Right Violence in the Portuguese Transition to Democracy
Authors: Marchi Riccardo , da Silva Raquel
Published: May 2022

The Exército de Libertação de Portugal [ELP; Portugal’s Liberation Army] was one of the most infamous clandestine organizations active during the Portuguese transition to democracy, bringing together far-right militants from the deposed authoritarian regime. This organization has been considered the most dangerous terrorist group fighting for the restoration of Estado Novo’s regime. This article aims to challenge this statement, recurrently defended by international historiography, through an in-depth case study of the ELP, which is assessed in its genesis, structuring, ideological identity, strategy and operative capacity, permeability to repression, and dissolution. This study is based on a qualitative methodology triangulating data dispersed in the existing scientific and journalistic literature with data collected, unprecedently, in private archives and through face-to-face interviews with former ELP militants. Therefore, this paper is of importance to scholarship on the Portuguese transition to democracy, but also on the role of the extreme right in other post-authoritarian contexts, and on political violence in processes of democratization.
Tropical Cyclone Track Prediction with an Encoding-to-Forecasting Deep Learning Model
Authors: Dong Pingping , Lian Jie , Yu Hui , Pan Jianguo , Zhang Yuping , Chen Guomin
Published: May 2022

Recently, with the accumulation of remote sensing data, the traditional tropical cyclone (TC) track prediction methods (e.g., dynamic methods and statistical methods) have limitations in prediction efficiency and accuracy when dealing with a large amount of data. However, deep learning methods begin to show their advantages to capture the complex spatiotemporal features in high-dimensional data. The task of TC track prediction based on remote sensing images can be formulated as a spatiotemporal sequence-to-sequence problem. Therefore, a novel encoding-to-forecasting model with convolutional long short-term memory (ConvLSTM) and spatial attention network (SAN-EFSModel) was proposed to predict TC tracks in this paper, which can fully extract the long-term spatial and temporal features. The proposed model was evaluated on the real remote sensing images in the western North Pacific Ocean to forecast 24-h TC tracks. Compared with ECMWF-HRES model and NCEP-GFS model, the proposed method has a better prediction accuracy in the testing set with an average position error about 30 km less. Compared with the deep learning methods, the proposed method also has the best performance.

Significance Statement

Tropical cyclones have a great impact on human life and natural environment due to their high frequency of occurrence, heavy degree of harm, wide impact range, and long disaster chain. In this article, we propose an encoding-to-forecasting model with convolutional long short-term memory (ConvLSTM) and spatial attention network (SAN-EFSModel) to predict tropical cyclone tracks, in which the SAN module and the convolution module of ConvLSTM have the ability to extract spatial features, and the long short-term memory (LSTM) module of ConvLSTM can extract temporal features from remote sensing images and tropical cyclone tracks. The results show that the average position error (APE) of our proposed method has about 30% improvement in a 24-h forecast compared with prevailing numerical weather prediction models.
Aspirin Use as a Risk Factor for Marginal Ulceration in Roux-en-Y Gastric Bypass Patients: A Meta-Analysis of 24,770 Patients
Authors: Portela Ray C. , Sharma Ishna , Vahibe Ahmet , Hassan Omer , Spaniolas Konstantinos , Dayyeh Barham Abu , Clapp Benjamin , Ghanem Omar M.
Published: May 2022

Background

Roux-en-Y gastric bypass (RYGB) is a recognized, safe bariatric procedure with minimal complications. Marginal ulceration, however, remains a challenging problem with an incidence of 8-12%. While chronic NSAID use is an established risk factor for ulcer formation, aspirin use itself as a cause for marginal ulceration is still unclear. We aim to compare the rates of marginal ulceration in RYGB with and without aspirin use.

Methods

PubMed, ScienceDirect, Cochrane, Web of Science, and Google Scholar were searched for articles between 2008 and 2021 by two independent reviewers using the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA). The risk of bias was assessed using Newcastle-Ottawa Scale. Meta-analysis was conducted using a fixed-effect model.

Results

From 5324 studies screened, we included 3 studies. Two studies had a low risk of bias, and the other one presented a high risk of bias on the Newcastle-Ottawa Scale. We included 24,770 patients, 1911 with aspirin use and 22,859 without aspirin use. After the meta-analysis, patients who used aspirin had a significantly higher marginal ulceration rate than those who did not (OR = 1.33 [95% CI 1.08 to 1.63], P < .002; I2 = 39%).

Conclusions

Aspirin use is associated with increased rates of marginal ulceration after RYGB.