bluuebunny/crossref_metadata_2025 huggingface dataset:
Simultaneous Analysis of Nine Volatile Phenols in Smoked Meat Products Using an Gas Chromatography-Tandem Mass Spectrometry
Authors: LI Jun , WANG Zhen , LAI Fei , SHU MeiCheng , SONG Lei , HE ZhiLin
Published: July 2022

A sensitive method for the determination of nine volatile phenols in smoked meat products samples has been developed using Gas Chromatography-Tandem Mass Spectrometry(GC-MS/MS). Smoked meat sample was extracted with soaking in 0.1 mol/L sodium hydroxide solution for 12 hours.The extracting solution was acidified by injecting the excess CO2 gas and then purified using sodium chloride and acetonitrile. Good linearities (R2>0.9908) were acquired for the analytes. The limit of detection and quantification were 5–15 μg kg-1 for all the nine target compounds. The recoveries were 81.6–92.0% and the relative standard deviations values were lower than 8.2% at three spiked levels (50, 200 and 1000 μg kg-1 ). The results indicated that the method was employed for the determination of volatile phenolic compounds in smoked meat because of its accuracy, speediness, high-efficiency and inexpensiveness.
Projection of Meteorological Drought under a Changing Climate in the Urmia Lake Basin, Iran
Authors: Chelan Bagher Shirmohammadi , Rostami Maryam , Moosavi Vahid , Varamesh Saeid , Semiromi Majid Taie
Published: July 2022

Arid and semi-arid regions are more susceptible to climate change impacts, leading to recurrent and sustained meteorological droughts as a natural hazard. Therefore, this study is established to assess the meteorological drought characteristics in the Urmia Lake Basin under a changing climate in Iran. To that end, General Circulation Models (GCMs) were evaluated using observed and Global Precipitation Climatology Centre (GPCC) datasets. Then, the selected GCMs were applied to project drought conditions until 2046 under Representative Concentration Pathway 2.6 and 8.5 (RCP2.6 and RCP8.5). Afterward, we developed eight combined scenarios (A1, A2, A3, A4, B1, B2, B3, and B4) to assess future drought characteristics. Ultimately, the Standardized Precipitation Index (SPI) was calculated using the Drought Indices Package (DIP) for the historic (1985–2015) and future (2016–2046) periods under two temporal scales, namely the medium-term (SPI-6) and long-term (SPI-18). According to the results, precipitation is expected to increase from 16.3–34% while the northeast and south parts of the basin will be affected by future drought effects. The projected SPI-18 under RCP8.5 indicated that the basin will suffer from the most severe and long-standing meteorological drought, anticipated to happen around 2045–2046 (A4 scenario). The increase was projected for severe low-frequency drought events in A4 (long-term) and, B1 and A3 (medium-term) scenarios. While, in most cases, the decrease was shown for the high-frequency with less intensity drought events mainly in medium-term assessment.
New strategy for silicon supply through fertigation in sugarcane integrating the pre-sprouted seedling phase and field cultivation
Authors: Silva José Lucas Farias , Prado Renato Mello , Alves Thayane Leonel , Lata-Tenesaca Luis Felipe , Soares Mariana Bomfim
Published: July 2022

Adopting a Si supply strategy can amplify sugarcane response. Thus, this study aimed to verify whether Si supply in the pre-sprouted seedling (PSS) formation phase would have an effect after field transplanting similar to Si supply only in the field phase (via foliar spraying or fertigation), and whether Si supply in the PSS formation phase associated with Si fertigation after transplanting can potentiate or amplify Si benefits. Two experiments were conducted. In experiment I, PSS were grown in nursery without Si (Control) and with Si. Experiment II was conducted in the field on Eutrustox with the following treatments: no Si supply (Control); Si supplied during the PSS formation phase; Si supplied through foliar spraying in the field; Si supplied through fertigation in the field; and Si supplied in the PSS formation phase and during field development. Silicon use in both crop phases benefited sugarcane by increasing photosynthetic pigment content and the antioxidative defense system. The innovation of Si management to be supplied via fertigation integrated in both crop phases (PSS and in the field) optimizes the element use by increasing the crop's productivity and sustainability.
Development of Python Application for Automated Geomatics Data Processing, Analysis, and Visualisation
Authors: Ugwuanyi Ifeanyi A. , Anejionu Obinna C.D.
Published: July 2022

Emerging technologies have led to the rapid generation of vast quantities of field data by geomatics professionals. However, these raw field data cannot be directly utilised unless they undergo rigorous processing (using complex mathematical models e.g. - reductions, adjustments, and computations) to convert them to meaningful information. These operations are often repetitive. Despite global advancement in automated data processing, most surveyors in developing countries such as Nigeria still deploy manual surveying computation techniques for their day-to-day data processing and analysis needs. Hence, the development of cost effective and easy-to-use automated applications based on the existing models is highly relevant, to ease operations requiring repeated processes. This study developed a Python-based geomatics application “Survey Companion” that can streamline the processing of survey field data into meaningful spatial information. To achieve these, python codes were written for the processing of data from key geomatics operations such as traverse and levelling networks, resection, intersection, and bathymetric operations as well as area computation. It is expected that this application will greatly improve survey operations in developing countries as well as increase the speed of data processing, thereby reducing overall project costs.
m6A RNA Methylation Regulator-Based Signature for Prognostic Prediction and its Potential Immunological Role in Uterine Corpus Endometrial Carcinoma
Authors: Fang Fang , Wang Peipei , Huang Haoyu , Ye Mingquan , Liu Xiaocen , Li Qingqing
Published: July 2022

BackgroundUterine corpus endometrial carcinoma (UCEC) is the most common female pelvic malignancy worldwide. N6-methyladenosine (m6A) plays an important role in various cellular responses, especially in cancer progression. However, the correlation between prognostic UCEC and m6A RNA methylation regulators remains unclear. MethodsWe used The Cancer Genome Atlas (TCGA) to provide a gene signature that could improve the prognostic evaluation of UCEC patients according to the distinct genetic trait of m6A RNA methylation regulators from a bioinformatics perspective. After comparing UCEC subgroups with different genetic profiles of m6A regulators, we identified 71 differentially expressed genes associated with overall survival (OS) and generated a nine-gene signature through least absolute shrinkage and selection operator (LASSO) Cox regression analysis. Finally, we used in vitro tumor cell experiments and immune correlation analysis to verify the function of each gene in the proposed gene signature.ResultsTime-dependent receiver operating characteristic (ROC) curves revealed that the proposed gene signature could predict the outcome of UCEC patients accurately. We found that CDKN2A mainly acted from the perspective of tumor cells, while COL4A4, PXDN, TIGIT, CHODL, LMO3, KCNJ12, and L1CAM might play a role in UCEC from an immunological point of view.ConclusionsFrom an epigenetics perspective, the m6A RNA methylation regulator-based gene signature can predict the prognosis of UCEC patients and immune therapeutic efficacy.
Consolidation quantitative analysis on cultivated land fragmentation and its terrain gradient effect in mountainous areas of southwest China: A case study of Caotangxi watershed in the Three Gorges Reservoir Area
Authors: Yang Yongfeng , Li Ruikang
Published: July 2022

Cultivated land fragmentation (CLF) has become the main obstacle restricting rural revitalization and agricultural modernization management in China, especially in southwest mountainous areas. And it’s of great significance to investigate the spatial-temporal evolution law of cultivated land as well as to facilitate regional food security and land management. Taking widely used areas of the Caotangxi River watershed as examples, based on landscape pattern principle, this paper constructs an evaluation system of CLF by landscape metrics. We firstly analyzed the temporal and spatial characteristics of cultivated landscape through the method of cultivated landscape gradient, calculated the value of CLF to reveal its evolution and spatial characteristics, explored the topographic gradient effects of CLF, and further summarized its modes. The results show that the area where arable land is concentrated are often comparatively crushed and distributed in the plain areas along the river banks. CLF in watersheds presented the overall improvement trend by the influence of natural conditions and China’s ecological policies. The overall level of CLF in the watershed is low during the whole study period, and the spatial evolution is uneven. The CLF displays pronounced regional divergence patterns in space, and the value of CLF is comparatively high in terrain Grade 2 and 3, which is the pivotal area for alleviating the fragmentation in the subsequent work. These findings imply that the differences of characteristics of CLF with terrain gradient must be considered in the formulation of targeted policies for land consolidation in the watershed.
Prediction of soil-water thresholds for plant responses
Authors: Chi ChunMing
Published: July 2022

Background It is well known that there is a soil water content threshold (θTHR) for plant growth and physiological processes. It is very import to obtain the θTHR for agriculture water management . However the measurement of θTHR needs specialized and expensive equipment. The θTHR can also be considered as the soil water content of capillary break (θCB). The θTHR can be calculated based on soil water retention curve. But the obtainment of soil water retention curve is time-consuming. Therefore, a simple and rapid prediction of θTHR is the focus of this study. Aims The θTHR can be predicted by estimating the θCB since the θTHR is generally regarded as the θCB. Whether the θCB can be estimated by simple soil parameters such as field capacity (θFC) and soil bulk density (Db)? Is the estimated θCB equal to the measured θTHR? Which of soil or plant is the major factor affecting the θTHR?Methods An formula of B was proposed to estimate θCB. Eight soils from six literature were used to calculate values of θCB. Theses estimated θCB were compared with 16 measured values of θTHR for 12 plant species in the eight soils. The variation in the θTHR and fraction of transpirable soil water (FTSW) with different plant species in the same soil and the same plant species in different soils were analyzed to compare effects of θCB and plant species on θTHR. Results The values of estimated θCB were nearly equal to those of measured θTHR. Highly significant (adjR2=0.9993,p<0.001) linear relationship was found between estimated θCB and measured θTHR with slope of 0.9938 and fixed y intercept of zero. In addition, the values of θTHR for different plant species were close to the same θCB in a soil. The θTHR values for the same plant species were different if θCB were different. Thus, the θTHR varied only with the θCB but not with the plant species. But the threshold FTSW varied due to plant species, not soil. Conclusions The estimated θCB can be considered equal to the measured θTHR. It is the θCB but not the plant that affects majorly the θTHR. Therefore, the θTHR can be predicted simply and quickly based on the estimation of θCB from θFC and Db.
Identification of mutations in SARS-CoV-2 PCR primer regions
Authors: Mentes Anikó , Papp Krisztián , Visontai Dávid , Stéger József , Group VEO Technical Working , Csabai István , Medgyes-Horváth Anna , Pipek Orsolya Anna
Published: July 2022

Due to the constantly increasing number of mutations in the SARS-CoV-2 genome, concerns have emerged over the possibility of decreased diagnostic accuracy of reverse transcription-polymerase chain reaction (RT-PCR), the gold standard diagnostic test for SARS-CoV-2. We propose an analysis pipeline to discover genomic variations overlapping the target regions of commonly used PCR primer sets. We provide the list of these mutations in a publicly available format based on a dataset of more than 600,000 SARS-CoV-2 samples. Our approach distinguishes among mutations possibly having a damaging impact on PCR efficiency and ones anticipated to be neutral in this sense. Samples are categorized as „prone to misclassification” vs. „likely to be correctly detected” by a given PCR primer set based on the estimated effect of mutations present. Samples susceptible to misclassification are always present at a daily rate of 2% or lower, while the daily ratio of samples having a slight chance of misclassification with a particular primer set can reach 90%. As different variant strains may temporarily gain dominance in the worldwide SARS-CoV-2 viral population, the efficiency of a particular PCR primer set may change over time, therefore constant monitoring of variations in primer target regions is highly recommended.
Collapse assessment of high-rise reinforced concrete building under chloride induced pitting corrosion subjected to near-field and far-field ground motions
Authors: Jafary Amirhossein , Zaherbin Pouria , Ghanoonibagha Mohammad , Shayanfar Mohsenali
Published: July 2022

Reinforced concrete structures are vulnerable to corrosion considering its influences on the performance of the structure during the possible earthquakes. Corrosion mostly occurs due to two main reasons: chloride and carbon dioxide penetration into the concrete that leads to the chemical reaction between them and concrete compositions. Chloride diffusion into the concrete brings about rebar pitting, while carbonation-induced corrosion causes uniform corrosion of rebars. In the present study, chloride-induced corrosion was investigated. In this regard, the Haselton 20-story reinforced concrete model was chosen. At first, corrosion initiation time was determined by probabilistic Monte-Carlo Simulation methods for three water to cement ratios of 0.4, 0.45, and 0.5. Next, the effects of corrosion on the mechanical properties of the steel and the concrete were taken into account by using equations available in the literature. Seismic performance of corroded structure was evaluated by conducting Non-linear static and incremental dynamic analysis (IDA). FEMA p695 far-field and near-field ground motions were selected for dynamic analysis. The reduction of overstrength and ductility over 40 years after corrosion initiation was calculated. The results showed that ductility was more affected by corrosion rather than overstrength. The probabilities of the structure being at the four damage states of slight, moderate, extensive, and complete damage were estimated based on fragility curves obtained from IDA. It was observed that ten years after initiation of corrosion there is only a slight difference in the probability of damage states and after that considerable distinction was observed, especially in water to cement ratio of 0.5. Moreover, it was seen that exceeding selected damage states under non-pulse-like near field ground motions is more likely.
Spatio-temporal monitoring of droughts in Iran using remote-sensing indices
Authors: Pouyan Soheila , Bordbar Mojgan , Ravichandran Venkatesh , Tiefenbacher John P. , Pourghasemi Hamid Reza
Published: July 2022

This study monitored spatially drought in Iran country using distance measurement indicators. Five drought indicators measured from 2016 to 2020 were used: temperature condition index (TCI), vegetation condition index (VCI), vegetation health index (VHI), precipitation condition index (PCI), and standardized precipitation index (SPI). The TCI revealed that the largest percentage of the region classified as “severe drought” occurred in 2020. The VCI indicated that the largest portion of the country (73.30%) experiencing “moderate drought” occurred in 2018. The VHI indicated that vegetation stress increased throughout the region, and areas of severe and moderate drought reached their greatest extents in the mentioned years. Although significant droughts have occurred primarily in the central, eastern, and southeastern parts of Iran, mild droughts have occurred in northern Iran as well. The PCI indicated that rainfall amounts have diminished in most of the country during the period of study. The SPI showed that northern Iran received heavy rain, and was the only region classified as “extremely wet.” Most of the rest of Iran were “moderately dry.” The analysis of the VHI index for agricultural plants showed that 27.71% of Iran's agricultural regions experienced “critical drought” conditions, this included the provinces of Razavi Khorasan, Hamadan, and Khozestan. The study can provide a baseline for the selection of the most useful drought-monitoring indicators and can enable a deeper understanding of drought in arid and semi-arid regions.
Low preoperative serum fibrinogen level is associated with postoperative acute kidney injury in patients with in acute aortic dissection
Authors: Guan Xinliang , Li Lei , Jiang Wenjian , Gong Ming , Li Haiyang , Wang Xiaolong , Liu Yuyong , Zhang Hongjia
Published: July 2022

Objective: Acute kidney injury (AKI) after cardiac surgery is associated with serious complication and high risk of mortality. The relationship between hemostatic system and the prognosis of patients with acute type A aortic dissection (ATAAD) has not been evaluated. The purpose of this study was to investigate the association between preoperative serum fibrinogen level and risk of postoperative AKI in patients with ATAAD. Methods: A total of 172 consecutive patients undergoing urgent aortic arch surgery for ATAAD between April 2020 and December 2021 were identified from Beijing Anzhen Hospital aortic surgery database. The primary outcome was postoperative AKI as defined by the Kidney Disease Improving Global Outcomes (KDIGO) criteria. The univariate and multivariate logistic regression analysis was done to assess the independent predictors of risk for postoperative AKI. Receiver operating characteristic (ROC) curve was generated to evaluate the predictive probabilities of risk factors for AKI.Results: In our study, 51.2% (88/172) patients developed postoperative AKI. Multivariate logistic regression analysis identified low preoperative serum fibrinogen level (OR, 1.492; 95% CI, 1.023 to 2.476; p = 0.021) and increased body mass index (BMI) (OR, 1.153; 95% CI, 1.003 to 1.327; p = 0.046) as independent predictors of postoperative AKI in patients with ATAAD. A mixed effect analysis of variance modeling revealed that obese patients with low preoperative serum fibrinogen level had higher incidence of postoperative AKI (p = 0.04). The ROC curve indicated that low preoperative serum fibrinogen level was a significant predictor of AKI [area under the curve (AUC), 0.771; p < 0.001].Conclusions: Low preoperative serum fibrinogen level and obesity were associated with the risk of postoperative AKI in patients with ATAAD. These data suggested that low preoperative serum fibrinogen level was preferred marker for predicting the postoperative AKI, especially in obese patients with ATAAD.
Betting on Forests and Soils to Reach Net Zero
Authors: Smith Harry , Vaughan Naomi E. , Forster Johanna
Published: July 2022

The deployment of Carbon Dioxide Removal (CDR) is essential to reach global and national net-zero emissions targets, but little attention has been paid to their practical deployment by countries. Here we conducted a systematic analysis of CDR in 41 national climate strategies submitted to the UNFCCC. We show that enhancing forest and soil carbon sinks are most advocated (40/41) within strategies but only quantified in 12. Residual emissions in 2050 are only quantified in 19/41 strategies and most of these use forests to reach national net-zero targets. Strategies that quantify residual emissions and assess CDR identify national constraints (e.g., wildfire risks for forests and geology for CO2 storage) and highlight the need for international collaboration. Our analysis also identifies that net-zero targets are often poorly described and, in some cases, misleading. Together these findings underline the need for the UNFCCC to urgently strengthen national reporting requirements for 2050.
Deep Learning Eliminates Massive Dust Storms from Images of Tianwen-1
Authors: Li Hongyu , Li Jia , ren xin , Xu Long
Published: July 2022

Dust storms may remarkably degrade the imaging quality of Martian orbiters and delay the progress of mapping the global topography and geomorphology. To address this issue, this paper presents an approach that reuses the image dehazing knowledge obtained on Earth to resolve the dust-removal problem on Mars. In this approach, we collect remote-sensing images captured by Tianwen-1 and manually select hundreds of clean and dusty images. Inspired by the haze formation process on Earth, we formulate a similar visual degradation process on clean images and synthesize dusty images sharing a similar feature distribution with realistic dusty images. These realistic clean and synthetic dusty image pairs are used to train a deep model that inherently encodes dust irrelevant features and decodes them into dust-free images. Qualitative and quantitative results show that dust storms can be effectively eliminated by the proposed approach, leading to obviously improved topographical and geomorphological details of Mars.
GWNN-HF : Beyond assortativity in Graph Wavelet Neural Network
Authors: Huang BinFeng , Zheng WenJie , Qian Fulan , Zhao Shu , Chen Jie , Zhang Yanping
Published: July 2022

Graph wavelet neural network exerts a powerful learning ability in the assortative network where most of adjacent nodes have the same label as the target node. However, it doesn't perform well in the disassortative network where most of adjacent nodes have different label than the target node. So graph wavelet neural network cannot extract the most useful information based on different types of networks. On the one hand, as a low-pass filter, graph wavelet neural network only obtains the commonality of the same label nodes, it is not capable of obtaining the difference of different label nodes. On the other hand, graph wavelet neural network only aggregates neighbor nodes so that it can't obtain information of nodes which have similar feature with the target node and are far from the target node. To solve the above problems, we propose the GWNN-HF model, which can effectively adapt to different types of networks and get a better node representation. Specifically speaking, firstly, we design low-pass filter and high-pass filter convolution kernels to get low-pass and high-pass signals and then use adaptive fusion method to fuse them, which effectively get commonality of same label nodes and difference of different label nodes. Secondly, we use the Relaxed Minimum-Spanning Tree algorithm to construct a feature correlation graph and use an attention mechanism to fuse the original graph and feature correlation graph representation. Extensive experiments on benchmark datasets clearly indicates that GWNN-HF behaves better than the state-of-the-art GNNs.
Improving the Value and Efficiency of Healthcare Services by Integrated Data Envelopment Analysis and Organizational Structure Design
Authors: Barros Oscar , Diaz Jorge
Published: July 2022

Measuring the efficiency of health services using Data Envelopment Analysis is a common practice nowadays. In addition, some studies use analytical techniques to discover the variables that explain the efficiency level of such services. Nevertheless, few efficiency analyses have resulted in proposals to design organizational health care structures that provide adequate management for actually improving efficiency. Thus, to address the lack of use of Data Envelopment Analysis results in practice, this paper provides a general methodology based on the idea that measuring the efficiency of healthcare services must be complemented with their redesign to obtain potential efficiency improvements. This redesign may include healthcare processes, e.g. clinical flows, analytical techniques to advise processes, e.g. intelligent models, information technology support for processes, and new management structures to facilitate the implementation and operation of the redesigns. Such methodology was applied to a large hospital specialized in cancer to illustrate its use and the results that can be achieved. Results show that the potential cost savings of new designs are about US$ 1.0 million yearly. To generate such savings, new medical and management practices were designed with the MDs’ participation. The implementation of the practices and their continuous evaluation and innovation was possible by a new organizational structure designed for such purpose. This work shows the importance of integrating several methodologies to generate better-founded designs. This integration is lacking in health-service design research, particularly in connection with architecture, processes, and organizational structure; this paper shows that this is a promising line of application.
Metabolic score for visceral fat is associated with prediabetes: based on community-dwelling people prospective cohort study in China
Authors: Liu Guangxu , Dou Jingtao , Wang Meiping , Zuo Yingting , Lu Juming , Ji Linong , Zhan Siyan , He Yan
Published: July 2022

Purpose We aimed to evaluate the association between metabolic score for visceral fat (METS-VF) and prediabetes and to compare the predictive ability among obesity indicators.Methods A total of 4,376 participants (mean age, 55.4±7.1; male, 32.2%) with normal glucose metabolism were recruited in 2011, and were followed up in 2015. The demographic information and anthropometric measurement were collected by standardized procedures. The laboratory test was conducted in local communities. In the follow-up survey, the newly-diagnosed prediabetes incidents were collected. Logistic regression models and receiver operator characteristic curve analysis were used to evaluate the association of obesity indicators and prediabetes.Results During a median follow-up of 3.3 years, 1119 prediabetes participants were identified. After adjusting for all variables, the adjusted odds ratios for the highest, third, second versus lowest METS-VF quartile was 1.56 [95% confidence interval (CI) 1.17-2.08], 1.41 (95% CI 1.09-1.83), 1.25 (95% CI 1.02-1.58), respectively, and elevated with per 1-SD is associated with a 27 % increase in prediabetes risk (OR 1.27, 95% CI 1.17-1.38). A nonlinear relationship of METS-VF with incident prediabetes was observed (P for nonlinear=0.041). In the subgroup analysis stratified by age and sex, similar results were observed. METS-VF showed a better prediction ability for incident prediabetes (AUC 0.623, 95% CI 0.601-0.644).ConclusionMETS-VF is positively associated with the risk of prediabetes, and is a better predictor for prediabetes than all obesity indicators. It has the potential to early identify the risk of prediabetes in future clinical practices or primary health management.
A comparison between micro- and nano-structured compositionally graded layer TBCs: thermal shock and thermal cyclic fatigue behavior
Authors: Sezavar Arezoo , Sajjadi Seyed Abdolkarim , Babakhani Abolfazl , Peng Ru Lin
Published: July 2022

Thermal barrier coating (TBC) technology is used in the process of manufacturing of hot sections of turbine and diesel engines to improve the component life. Performance of micro- and nano-structured compositionally graded layer (CGL) TBCs produced by atmospheric plasma spray (APS) was investigated in thermal shock (TS) and thermal cyclic fatigue (TCF) conditions. Two groups of CGL-TBCs systems consisting of five layers: one bond coat layer with 100% NiCrAlY and four layers of NiCrAlY/YSZ in the weight ratios of 70:30, 50:50, 30:70 and 0:100 as top coat were investigated. In the micro- and nano-structured CGL-TBCs, conventional and nano-structured YSZ were used as TBC powders, respectively. TCF and TS tests were run at 900°C and continued until 1200 cycles. The results of the experimental studies on thermal cyclic behavior and microstructural evolution of micro- and nano-structured CGL-TBCs were compared and discussed. It was shown that after 1200 cycles of TS and TCF tests, no change in the phase composition of coatings is observed. Moreover, in both TS and TCF tests the signs of macroscopic damages appeared in micro CGL-TBC while no significant visible damage was seen in nano-structured one. Microscopic investigation revealed that although in both micro- and nano-structured CGL-TBCs, the integrity of underneath layers (bond coat and the other three gradient layers) up to top coat are preserved, different kinds of damage are seen in top coats. The presence of nanozones in the nano-structured CGL-TBC led to the toughening of the coatings through crack arresting techniques therefore, the nano-structured CGL-TBC showed better resistance than the micro one in the two tests.
Software testing with performance profiles clustering using unsupervised learning
Authors: Montes Vitor Silva , Braga Diego , Durães Thiago de Jesus Oliveira , Delbem Alexandre Claudio , Souza Simone Senger , Souza Paulo Sergio Lopes
Published: July 2022

The functional testing technique has been widely applied to reveal unknown faults in the software caused by programmer mistakes. Nevertheless, in autonomous data processing systems with highly variable inputs and outputs, such as embedded applications, data streams, and machine learning algorithms, the non-functional testing helps to reveal unknown-nontrivial faults in the deployment of software products. This paper addresses the detection of unknown code-faults by employing performance analysis as a nonfunctional requirement without predefined test cases, test oracles, or source-code analyses. The premise is that codefaults change demands for hardware resources during software execution, and a novel testing methodology can automatically detect them. This paper proposes the Tricorder testing methodology for automating workload characterization and detecting potential performance anomalies, caused by code-faults in autonomous data processing systems. Tricorder evaluates the performance profiles of hardware regarding the detection of the source code-faults. DAMICORE, a non-parametric multipurpose clustering methodology, enables Tricorder to group performance profiles of the software under testing and identify performance anomalies using non-parametric data in unsupervised learning based on Normalized Compression Distance (NCD). Tricorder reveals unknown source code faults, with no specialist to determine standards for input and output data, previous models inherent to architecture, test case creation, or workload characterization. We evaluate the capability of Tricorder in revealing faults through experiments based on three benchmarks: cryptography system, machine learning algorithm, and data stream processing server. Tricorder detects faults even under various workloads for different applications in our experiments. Tricorder helps the maintenance phase of the software development life cycle, providing additional information regarding the proper functioning of the application release before and after the updating process. This work contributes to the cost reduction of regression testing during the maintenance phase of autonomous data processing applications and can be used as a complementary testing technique.
Spike propagation by synchronization and vibrational resonance in feedforward Izhikevich neural network
Authors: Ge Mengyan
Published: July 2022

Multilayer feed − forward neuron networks (FFNs) are the basis of various machine learnings, in which the propagation of neural firing rates with respect to synchronization and vibrational resonance (VR) under white Gaussian noise and high − frequency stimulation (HFS) is important. In this study, the influences of HFS and noise on propagation about synchronous firing rate and the VR are investigated in different kinds of Izhikevich neural FFN. For ten layers excitatory Izhikevich neuron network, it is shown that synchronous firing rates appear gradually and the diverse noise intensities, synaptic weights and time constants take effects on the propagation of synchronous discharge rates. For four layers excitatory FFN, it is observed that the systemic output rates keep smaller than zero, and carries no information of weak signal by using small HFS. The VR phenomenon occurs, when the input of weak low frequency signal (LFS) and signal output keep well phase synchronization, and the LFS is amplified by increasing amplitude of HFS. In the excitatory − inhibition neural multilayer FFN, the propagation by synchronous firing rates is not well, and few inhibition neurons are keep excited. In the systemic output, the synchronization phenomenon can be observed, but not as good as in excitatory neural FFN.
A SFBEM-FEM coupling method for solving crack problems based on Erdogan fundamental solutions
Authors: Su Cheng , Cai Kemin , Xu Zhi
Published: July 2022

The boundary element method (BEM) has proven to be an efficient approach for crack analysis in fracture mechanics, while its versatility in application to crack problems of complex structures with irregular boundaries deserves further attention. In this study, to improve the applicability to complex crack analysis, a cracked superelement is first established with BEM to model the near-crack region, and the crack problem is then solved within the frame of finite element method (FEM). The stiffness matrix of the cracked superelement is formulated using the spline fictitious boundary element method (SFBEM) based on the Erdogan fundamental solutions for an infinite plane with a single crack. The proposed superelement is further incorporated into a finite element mesh to simulate the behaviour of the crack zone, and the governing equation of the crack problem is finally established and solved using the typical procedure of FEM. After obtaining the nodal displacements of the superelement, the stress intensity factors (SIFs) of crack tips can be obtained by a backward analysis with SFBEM. The accuracy and efficiency of the proposed SFBEM-FEM coupling method are demonstrated by two numerical examples involving a rectangular plate with a central crack and a square plate with 100 horizontal cracks. The present approach is further applied to the analysis of the SIFs of multiple cracks exposed in a steel anchorage box for a hanger of a suspension bridge, which indicates the merging of the cracked superelements to the commercial FEM software is computationally efficient for the analysis of complex structures with multiple cracks.
MarrowQuant 2.0: a digital pathology workflow assisting bone marrow evaluation in clinical and experimental hematology
Authors: Sarkis Rita , Burri Olivier , Royer-Chardon Claire , Schyrr Frédérica , Blum Sophie , Costanza Mariangela , Cherix Stephane , Piazzon Nathalie , Barcena Carmen , Bisig Bettina , Nardi Valentina , Sarro Rossella , Ambrosini Giovanna , Weigert Martin , Spertini Olivier , Blum Sabine , Deplancke Bart , Seitz Arne , de Leval Laurence , Naveiras Olaia
Published: July 2022

Bone marrow (BM) cellularity assessment is a crucial step in the evaluation of BM trephine biopsies for hematological and non-hematological disorders. Clinical assessment is based on a labor-intensive, semi-quantitative visual estimation of the hematopoietic and adipocytic components by hematopathologists, which does not provide quantitative information on other stromal compartments. In this study, we developed and validated MarrowQuant 2.0, an efficient user-friendly digital hematopathology workflow integrated within QuPath software which serves as BM quantifier for five mutually-exclusive compartments (bone, hematopoietic, adipocytic, interstitial/microvasculature areas, and “Other”) to derive cellularity of human BM trephine biopsies. Instance segmentation of individual adipocytes is realized via adaptation of the machine-learning-based algorithm StarDist. We calculated BM compartments and adipocyte size distributions of haematoxylin and eosin (H&E) images obtained from a total of 250 bone specimens, from control and acute myeloid leukemia or myelodysplastic patients at diagnosis or follow-up, then measured the agreement of cellularity estimates by MarrowQuant 2.0 against visual scores from four hematopathologists. The algorithm was capable of robust BM compartment segmentation with average mask accuracy of 86%, maximal for bone (99%), hematopoietic (92%) and adipocyte (98%) areas. MarrowQuant 2.0 cellularity score and hematopathologist estimations were highly correlated (R2 = 0.92–0.98, Intraclass-Correlation-Coefficient ICC = 0.98; inter-observer ICC 0.96). BM compartment segmentation quantitatively confirmed reciprocity of the hematopoietic and adipocytic compartments. MarrowQuant 2.0 performance was additionally tested for cellularity assessment of specimens prospectively collected from clinical routine diagnosis. After special consideration for the choice of the cellularity equation in specimens with expanded stroma, performance was similar in this setting (R2 = 0.86, n = 42). We thus conclude that MarrowQuant 2.0 can be applied in a clinical setting. We expect this workflow will contribute to improving the speed and ease of diagnosis in hematopathology and serve as a clinical research tool to explore novel biomarkers related to BM stromal components.
CIRM-SNN: Certainty Interval Reset Mechanism Spiking Neuron for Enabling High Accuracy Spiking Neural Network
Authors: Niu Li-Ye , Wei Ying
Published: July 2022

Spiking neural network (SNN) based on a sparse trigger and event-driven information processing has the advantages of ultra-low power consumption and hardware friendliness. As a new generation of the neural network, SNN is widely concerned. At present, the most effective way to realize deep SNN is through artificial neural network (ANN) conversion. Compared with the original ANN, the converted SNN will suffer performance loss. This paper adjusts the spike firing rate of spiking neurons to minimize the performance loss of SNN in the conversion process. We map the ANN weight to the corresponding SNN after continuous normalization, which ensures that the spike firing rate of neurons is in the normal range. We propose a certainty interval reset mechanism (CIRM), which effectively reduces the loss of membrane potential and avoids the problem of neuronal over-activation. In the experiment, we added a modulation factor (MF) to the CIRM to further adjust the spike firing rate of neurons. The accuracy of the converted SNN on CIFAR-10 is 1.026% higher than that of the original ANN. The algorithm not only realizes the lossless conversion of ANN but also reduces the network energy consumption. Our algorithm also effectively improves the accuracy of SNN (VGG-15) on CIFAR-100 and reduces the network delay. The work of this paper is of great significance for developing high-precision depth SNN.
Revealing the impact of the environment on the ginsenosides in American ginseng from three scales: bioclimatic factors, soil physicochemical properties and microbial communities
Authors: Zhang Xinke , Miao Yujing , Sun Xiao , Huang Linfang
Published: July 2022

The environment exerts a significant impact on the growth and ingredients of plants. However, comprehensive studies are limited from multiple scales to reveal the influence of environmental factors on the ginsenosides in American ginseng. Here, bioclimatic factors, soil physicochemical properties and microbial communities were integrated to uncover the important factors affecting the ginsenosides in American ginseng. The contents of ginsenosides in American ginseng from the three major producing areas in China, namely Shandong, Beijing and Jilin were significantly different. From the microbial communities perspective, there were significant differences in soil microbial communities of American ginseng from the three major producing areas by 16S rRNA and ITS amplicon sequencing. The biomarkers, namely, Burkholderia (SDS), RB41 (BJS) and Bacillus(JLS), which can distinguish three geographical regions microbial communities, were identified by LEfSe and ternary plots. The functions profile of soil microbiome communities in SDS and BJS are differed from those in JLS. RDA analyses of bioclimatic factors, soil physicochemical properties, biomarker microbiomes and main ginsenosides content in American ginseng revealed that mean diurnal temperature range were the important factors affecting the variation of ginsenosides in American ginseng, with interpretation rates of 86.2%. The validation experiment showed that the mean diurnal temperature range of 25℃/25℃considerably increased total ginsenosides content compared with 25℃ /15℃ and 25℃/5℃. These results not only provide a theoretical basis for the subsequent mining of microbial functions and the study of biological fertilizers but also the utilization of mean diurnal temperature range for cultivation of high-quality medicinal plants.
Development and validation of a questionnaire to measure the severity of pain, functional limitations, and reduction of sports ability for German-speaking patients with osteochondral lesions of the ankle (OCLA-G)
Authors: Lohrer Heinz , Wagner Stephanie , Markus Wenning , Kühle Jan , Schmal Hagen , Gollhofer Albert
Published: July 2022

BackgroundThere is no patient-reported functional scale specific for osteochondral lesion of the ankle (OCLA). Therefore, the objectives of this study were to develop a questionnaire that measures symptom severity, function, and sports capacity in patients with osteochondral lesions of the ankle and to determine the psychometric properties of the tool in German language (OCLA-G). MethodsThe OCLA-G questionnaire was developed according to the COSMIN guidelines. Scalable items were generated from a literature search, based on an evaluation of 71 own OCLA patients, and from expert opinions. Following a twofold item reduction the questionnaire underwent explorative data analysis and principal component analysis. Validity and reliability were analysed in four groups of participants (40 patients with OCLA, 40 patients with other foot and ankle injuries, 40 asymptomatic athletes serving as a population at risk and 40 asymptomatic persons playing sports not at risk.Results The final OCLA-G questionnaire consists of eight and five questions to mirror activities of daily life (ADL) and sports, respectively. Excellent internal consistency (Cronbach’s α = 0.950 for the ADL subscore and 0.965 for the sport subscale, respectively) was found. Spearman's rank correlation coefficients for test-retest reliability were 0.992 for the ADL subscore and 0.999 for the sport subscale (p<0.001). The results of the exploratory and confirmatory factor analyses indicated that item difficulty was between 23.4 and 62.8. The Pearson correlation for the OCLA subscales ADL and sport was 0.853 (p<0.001). Construct validity as tested against the SF-12 questionnaire subscales (Physical and Mental component scale) were r = -0.164 to -0.663 (p<0.05). Statistically, there was no ADL and sport OCLA mean score difference between OCLA patients and patients with other foot and ankle injuries (p = 0.993 and 0.179, respectively), but both groups differed from the uninjured control groups (p < 0.001). There were no ceiling or floor effects.Conclusions The OCLA-G was successfully developed as the first patient reported and injury specific outcome scale to measure the impact of OCLA induced symptoms on activities of daily living and sport. This study provides evidence for the reliability and validity of the OCLA-G assessing patients with OCLA.
Pig waste derived capped and non-agglomerated silver nanoparticles and its effect on pathogenic bacteria and physiological responses of fish under multiple abiotic stresses
Authors: Lamare Sowa o , Krishnani K. K. , Kumar Neeraj , Pathak Madhuri , Upadhyay Ajay , Sarkar Biplab , Chadha NK
Published: July 2022

The present study elucidates the extracellular synthesis of capped silver nanoparticles (Ag-NPs) using pig processing waste, mainly the intestine in distilled water incubated with silver nitrate by dispensing with the addition of any capping agent and the advantage of avoiding the agglomeration and loss of nanosized characteristics of AgNPs. The synthesis of Ag-NPs was ascertained by a UV-VIS spectrophotometry of the incubated suspension of yellowish-brown at 410 nm. The Ag-NPs were further characterized using a High-Resolution Transmission Electron Microscope (HRTEM), which confirmed that the Ag-NPs were primarily spherical and had a size range of 5–100 with a maximum frequency fall within 5–30 nm. In addition, the Ag-NPs are characterized by Dynamic Light Scattering (DLS), which confirmed the high stability of the Ag-NPs with a zeta potential of -32 mV. Biomolecules and biological extracts of pig waste act as biogenic reducing and capping agents. Based on the zone of inhibition achieved through the agar well diffusion method, the biosynthesis Ag-NPs showed high bactericidal properties against Aeromonas hydrophila, Edwardsiella tarda, and Micrococcus luteus. The chronic toxicity analysis of the biosynthesized Ag-NPs on Pangasianodon hypophthalmus was carried out using stress biomarkers such as an antioxidant enzyme, AChE, and metabolic enzyme activity. Chronic toxicity of synthesized Ag-NPs was found to increase with increased sub-lethal ammonia concentration and temperature. The findings of this study revealed that biosynthesis of capped and non-agglomerated Ag-NPs can be undertaken by using pig wastes for their potential application in aquaculture based on the properties observed in characterization, bactericidal activity, and physiological responses of the fish.
Etiology and factors associated with urogenital fistula among women who have undergone Cesarean section in the Democratic Republic of Congo
Authors: Maroyi Raha , Moureau Madeline , Brown Heidi , Ajay Rane , Byabene Gloire , Mukwege Denis
Published: July 2022

Background
The prevalence and impact of fistulas is more common in developing countries with limited access to emergency obstetric care. As a result of fistulas, women in these settings often experience adverse psychosocial factors. The purpose of this study was to describe characteristics of Democratic Republic of Congo (DRC) women who developed urogenital fistula following Cesarean sections (CS) and to determine the characteristics associated with fistula related to obstructed labor or CS.
Methods
We abstracted data from all patients with urogenital fistula following CS who received care during a DRC outreach surgical campaign. Urogenital fistula etiology was designated as related to (1) prolonged obstructed labor; or (2) a complication of CS. Descriptive analyses characterized patients with fistula related to obstructed labor versus CS. Logistic regression identified factors associated with fistula etiology.
Results
Among 125 patients, urogenital fistula etiology was attributed to obstructed labor in 77 (62%) and complications following CS in 48 (38%). Women with a fistula attributed to obstructed labor developed the fistula at a younger age (p = .04) and had a lower parity (p = .02). Attempted delivery prior to hospital arrival was associated with an increased risk of obstetric fistula (p < .01).
Conclusion
CS are commonly performed on women who arrive at the hospital following prolonged obstructed labor and fetal demise, and account for almost 40% of urogenital fistula. Obstetric providers should assess maternal status upon arrival to prevent unnecessary CS and identify women at risk of developing a fistula.