bluuebunny/crossref_metadata_2025 huggingface dataset:
Foster Kennedy Syndrome (FKS): A Case Report
Authors: Musa Mutali , Aluyi-Osa Gladness , Zeppieri Marco
Published: July 2022

(1) Background: Foster Kennedy syndrome (FKS) is an ophthalmological condition characterized by an insidious reduction in vision in one eye, accompanied by clinically significant papilledema in the fellow eye. The unilateral loss of vision and optic atrophy is due to compressive optic atrophy, which causes elevated intracranial pressure that leads to swelling in the fellow eye. The risk factors for FKS include the presence of mass lesions in radiographic imaging, female gender, and increased body mass index. Differential diagnoses of FKS include tumors and pseudotumor of the frontal lobe and cranial meninges. (2) Methods: We present two cases of FKS diagnosed in February 2021 and December 2021. (3) Results: A 52-year-old male with a history of poor vision in one eye after trauma complained of constant headache. Ocular examination revealed disc pallor in his right eye with disc edema in the contralateral eye. The patient was sent for computerized tomography (CT) and placed on oral prednisolone tablets. The CT scan confirmed the diagnosis of FKS. A 30-year-old female presented to the emergency department for poor vision in her left eye and headache on the left side. Medication included dexamethasone, chloramphenicol, timolol eyedrops, furosemide, and anti-oxidant tablets dispensed from a previous private eye clinic. Ophthalmoscopy showed disc pallor with 0.1 cupping and arteriolar attenuation in both eyes with macular hemorrhages in her left eye. Bilateral papilledema secondary to raised intracranial hyper-tension was suspected. CT scans showed an intracranial mass. (4) Conclusions: These two cases show the importance of ocular examination in the diagnosis of serious systemic conditions. A concise case history, extensive ocular workup, and cranial imaging with magnetic resonance imaging and/or CT scans are indicative of patients showing acute visual loss and retro-orbital pain, which can give rise to the diagnosis of sight-threatening, permanent and fatal conditions, such as FKS. Non-surgical treatments include oral steroidal therapy, radiotherapy, and chemotherapy; however, neurosurgery is normally required.
Advanced Materials for Electrochemical Energy Conversion and Storage
Authors: Dang Jingshuang , Zhong Ruyi
Published: July 2022

With the massive consumption of traditional fossil resources, environmental issues such as air pollution and greenhouse gas emissions have motivated a transition towards clean and sustainable energy sources capable of meeting the increasing energy demands of our modern society [...]
Mathematical Modeling: Global Stability Analysis of Super Spreading Transmission of Respiratory Syncytial Virus (RSV) Disease
Authors: Sungchasit Rattiya , Tang I-Ming , Pongsumpun Puntani
Published: July 2022

In this paper, a model for the transmission of respiratory syncytial virus (RSV) in a constant human population in which there exist super spreading infected individuals (who infect many people during a single encounter) is considered. It has been observed in the epidemiological data for the diseases caused by this virus that there are cases where some individuals are super-spreaders of the virus. We formulate a simply SEIrIsR (susceptible–exposed–regular infected–super-spreading infected–recovered) mathematical model to describe the dynamics of the transmission of this disease. The proposed model is analyzed using the standard stability method by using Routh-Hurwitz criteria. We obtain the basic reproductive number (R0) using the next generation method. We establish that when R0<1, the disease-free state is locally asymptotically stable and the disease endemic state is unstable. The reverse is true when R0>1, the disease endemic state becomes the locally asymptotically stable state and the disease-free state becomes unstable. It is also established that the two equilibrium states are globally asymptotically stable. The numerical simulations show how the dynamics of the disease change as values of the parameters in the SEIrIsR are varied.
Breast Cancer Patients: Who Would Benefit from Neoadjuvant Chemotherapies?
Authors: Yao Liqin , Jia Gang , Lu Lingeng , Ma Wenxue
Published: July 2022

Neoadjuvant chemotherapy (NACT) was developed with the aims of shrinking tumors or stopping cancer cells from spreading before surgery. Unfortunately, not all breast cancer patients will benefit from NACT, and thus, patients must weigh the risks and benefits of treatment prior to the initiation of therapy. Currently, the data for predicting the efficacy of NACT is limited. Molecular testing, such as Oncotype DX, MammaPrint, and Curebest 95GC, have been developed to assist which breast cancer patients will benefit from the treatment. Patients with an increased level of Human Leukocyte Antigen-DR isotype, tumor-infiltrating lymphocytes, Fizzy-related protein homolog, and a decreased level of tumor-associated macrophages appear to benefit most from NACT.
Surgery for Pituitary Tumor Apoplexy Is Associated with Rapid Headache and Cranial Nerve Improvement
Authors: Cross Kevin A. , Desai Rupen , Vellimana Ananth , Liu Yupeng , Rich Keith , Zipfel Gregory , Dacey Ralph , Chicoine Michael , Klatt-Cromwell Cristine , McJunkin Jonathan , Pipkorn Patrik , Schneider John S. , Silverstein Julie , Kim Albert H.
Published: July 2022

Pituitary tumor apoplexy (PTA) classically comprises sudden-onset headache, loss of vision, ophthalmoparesis, and decreased consciousness. It typically results from hemorrhage and/or infarction within a pituitary adenoma. Presentation is heterologous, and optimal management is debated. The time course of recovery of cranial nerve deficits (CNDs) and headaches is not well established. In this study, a retrospective series of consecutive patients with PTA managed at a single academic institution over a 22-year period is presented. Headaches at the time of surgery were more severe in the early and subacute surgical cohort and improved significantly within 72 h postoperatively (p < 0.01). At one year, 90% of CNDs affecting cranial nerves (CNs) 3, 4, and 6 had recovered, with no differences between early (<4 d), subacute (4–14 d), and delayed (>14 d) time-to-surgery cohorts. Remarkably, half recovered within three days. In total, 56% of CN2 deficits recovered, with the early surgery cohort including more severe deficits and recovering at a lower rate (p = 0.01). No correlation of time-to-surgery and rapidity of recovery of CNDs was observed (p = 0.65, 0.72). Surgery for PTA is associated with rapid recovery of CNDs in the early, subacute, and delayed time frames, and with rapid headache improvement in the early and subacute time frames in 50% or more of patients.
Immune-Related LncRNAs to Construct a Prognosis Risk-Assessment Model for Gastric Cancer
Authors: Zhi Shilin , Yang Bin , Zhou Shengning , Tan Jianan , Zhong Guangyu , Han Fanghai
Published: July 2022

Background: Gastric cancer is a prevalent cause of tumor death. Tumor immunotherapy aims to reshape the specific immunity to tumors in order to kill the tumor. LncRNAs play a pivotal role in regulating the tumor immune microenvironment. Herein, immune-related lncRNAs were used to establish a prognosis risk-assessment model for gastric cancer and provide personalized predictions while providing insights and targets for gastric cancer treatment to enhance patient prognosis. Methods: Gastric adenocarcinoma transcriptome and clinical data were acquired from the The Cancer Genome Atlas (TCGA) database to screen the immune-related lncRNAs. Then, LASSO COX regression was utilized to construct the prognosis risk-assessment model. Afterward, the reliability of the model was evaluated the relationship between immune infiltration, clinical characteristics, and the model was analyzed. Results: We identified 13 lncRNAs and constructed the prognosis assessment model. According to the median risk score of the training set, the patients were assigned to different risk groups. Overall survival time was shorter in the high-risk group. In the high-risk group, higher infiltration of mono-macrophages, dendritic cells, CD4+ T cells, and CD8+ T cells was observed. Moreover, the model was positively related to tumor metastasis. Conclusion: The prognosis risk-assessment model developed in this research can effectively predict the prognosis of gastric cancer patients. This tool is expected to be further applied to clinics in the future, thus providing a novel target for immunotherapy in gastric cancer patients.
Super-Resolution Images Methodology Applied to UAV Datasets to Road Pavement Monitoring
Authors: Inzerillo Laura , Acuto Francesco , Di Mino Gaetano , Uddin Mohammed Zeeshan
Published: July 2022

The increasingly widespread use of smartphones as real cameras on drones has allowed an ever-greater development of several algorithms to improve the image’s refinement. Although the latest generations of drone cameras let the user achieve high resolution images, the large number of pixels to be processed and the acquisitions from multiple lengths for stereo-view often fail to guarantee satisfactory results. In particular, high flight altitudes strongly impact the accuracy, and result in images which are undefined or blurry. This is not acceptable in the field of road pavement monitoring. In that case, the conventional algorithms used for the image resolution conversion, such as the bilinear interpolation algorithm, do not allow high frequency information to be retrieved from an undefined capture. This aspect is felt more strongly when using the recorded images to build a 3D scenario, since its geometric accuracy is greater when the resolution of the photos is higher. Super-Resolution algorithms (SRa) are utilized when registering multiple low-resolution images to interpolate sub-pixel information The aim of this work is to assess, at high flight altitudes, the geometric precision of a 3D model by using the the Morpho Super-Resolution™ algorithm for a road pavement distress monitoring case study.
Analysis of Mixing Processes of LPG Gases in Tanks When Transporting by Sea
Authors: Morozyuk Larisa , Kosoy Boris , Sokolovska-Yefymenko Viktoriia , Ierin Volodymyr
Published: July 2022

The present study is an analysis of the processes in the components of the LPG (propane/butane) reliquefaction plant under the conditions of co-mingling in tanks when transporting by sea. For the analysis, the monitoring data of an LPG cargo operation have been used. An energy analysis of the mixture-based reliquefaction plant has been performed. The characteristics of the mixture in the tanks, the operating conditions of the reliquefaction plant, and the performance of the system have been considered. The method of equivalence has been applied for thermodynamic analysis. The result of the substitution of actual processes with equivalent ones allows for the accomplishment of the parameters control of each working fluid within the mixture as a pure working fluid. It is shown that the low-boiling component determines the operating parameters of the entire reliquefaction plant. The method of equivalence and visualization of the processes within the LPG as a mixture using the thermodynamic diagrams of pure working fluids is recommended to shorten the path to set up the appropriate reliquefaction plant management strategy. The energy analysis performed using the method of equivalent cycles has been validated with the existing reliquefaction plant characteristics. The inaccuracies are in the limit of 4%.
Structural Compressed Panel VAR with Stochastic Volatility: A Robust Bayesian Model Averaging Procedure
Authors: Pacifico Antonio
Published: July 2022

This paper improves the existing literature on the shrinkage of high dimensional model and parameter spaces through Bayesian priors and Markov Chains algorithms. A hierarchical semiparametric Bayes approach is developed to overtake limits and misspecificity involved in compressed regression models. Methodologically, a multicountry large structural Panel Vector Autoregression is compressed through a robust model averaging to select the best subset across all possible combinations of predictors, where robust stands for the use of mixtures of proper conjugate priors. Concerning dynamic analysis, volatility changes and conditional density forecasts are addressed ensuring accurate predictive performance and capability. An empirical and simulated experiment are developed to highlight and discuss the functioning of the estimating procedure and forecasting accuracy.
Learning to Plan by Learning to Reflect?—Exploring Relations between Professional Knowledge, Reflection Skills, and Planning Skills of Preservice Physics Teachers in a One-Semester Field Experience
Authors: Vogelsang Christoph , Kulgemeyer Christoph , Riese Josef
Published: July 2022

Following concepts describing lesson planning as a form of anticipatory reflection, preservice physics teachers’ reflection skills are assumed to be positively connected with their planning skills. However, empirical evidence on this is scarce. To explore how relations between these specific skills change over the course of a field experience controlling for influences of professional knowledge, we conduct a pre-post field study with N = 95 preservice physics teachers in a one-semester field experience. Content knowledge (CK) and pedagogical content knowledge (PCK) (paper-and-pencil tests), and reflection and planning skills (standardized performance assessments) were assessed before and after the field experience. Path analyses revealed almost no influence of reflection skills on planning skills. Reflections skills did not contribute to preservice teachers planning skills beyond knowledge, indicating both constructs might represent rather independent abilities. The results show the need for further development of models describing the development of teachers’ professional knowledge and skills in academic teacher education and for the development of concepts for a better integration of reflection and lesson planning in field experiences.
Adversarial Attack and Defense Strategies of Speaker Recognition Systems: A Survey
Authors: Tan Hao , Wang Le , Zhang Huan , Zhang Junjian , Shafiq Muhammad , Gu Zhaoquan
Published: July 2022

Speaker recognition is a task that identifies the speaker from multiple audios. Recently, advances in deep learning have considerably boosted the development of speech signal processing techniques. Speaker or speech recognition has been widely adopted in such applications as smart locks, smart vehicle-mounted systems, and financial services. However, deep neural network-based speaker recognition systems (SRSs) are susceptible to adversarial attacks, which fool the system to make wrong decisions by small perturbations, and this has drawn the attention of researchers to the security of SRSs. Unfortunately, there is no systematic review work in this domain. In this work, we conduct a comprehensive survey to fill this gap, which includes the development of SRSs, adversarial attacks and defenses against SRSs. Specifically, we first introduce the mainstream frameworks of SRSs and some commonly used datasets. Then, from the perspectives of adversarial example generation and evaluation, we introduce different attack tasks, the prior knowledge of attacks, perturbation objects, perturbation constraints, and attack effect evaluation indicators. Next, we focus on some effective defense strategies, including adversarial training, attack detection, and input refactoring against existing attacks, and analyze their strengths and weaknesses in terms of fidelity and robustness. Finally, we discuss the challenges posed by audio adversarial examples in SRSs and some valuable research topics in the future.
Anomaly Detection for SCADA System Security Based on Unsupervised Learning and Function Codes Analysis in the DNP3 Protocol
Authors: Altaha Mustafa , Hong Sugwon
Published: July 2022

An Intrusion Detection System (IDS) is a tool used primarily for security monitoring, which is one of the security strategies for Supervisory Control and Data Acquisition (SCADA) systems. Distributed Network Protocol version 3 (DNP3) is the predominant SCADA protocol in the energy sector. In this paper, we have developed an effective and flexible IDS for DNP3 networks, observing that most critical operations in DNP3 systems are utilized based on the function codes in DNP3 application messages, and that exploitation of those function codes enables attackers to manipulate the system operation. Our proposed anomaly-detection method deals with possible attacks that can bypass any rule-based deep packet inspection once attackers take over servers in the system. First, we generated datasets that reflected DNP3 traffic characteristics observed in real-world power grid substations for a reasonably long time. Next, we extracted input features that consisted of the occurrences of function codes per TCP connection, along with TCP characteristics. We then used an unsupervised deep learning model (Autoencoder) to learn the normal behavior of DNP3 traffic based on function code patterns. We called our approach FC-AE-IDS (Function Code Autoencoder IDS). The evaluation of the proposed method was carried out on three different datasets, to prove its accuracy and effectiveness. To evaluate the effectiveness of our proposed method, we performed various experiments that resulted in more than 95% detection accuracy for all considered attack scenarios that are mentioned in this study. We compared our approach to an IDS that is based on traditional features, to show the effectiveness of our approach.
Bearing Fault Diagnosis Based on Stochastic Resonance and Improved Whale Optimization Algorithm
Authors: Huang Weichao , Zhang Ganggang , Jiao Shangbin , Wang Jing
Published: July 2022

In light of the problem of difficult model parameter selection and poor resonance effects in traditional bearing fault detection, this paper proposes a parameter-adaptive stochastic resonance algorithm based on an improved whale optimization algorithm (IWOA), which can effectively detect bearing fault signals of rotating machinery. First, the traditional WOA was improved with respect to initial solution distribution, global search ability and population diversity generalization, effectively improving the global convergence of the WOA. Then, the parameters of the bistable stochastic resonance model were optimized using the improved WOA, and adaptive adjustment of the stochastic resonance parameters was realized. Finally, the Case Western Reserve University bearing data set and the XJTU-SY bearing data set were used as fault data for the actual bearing to be tested for experimental verification. The signal-to-noise ratios of the detected fault frequencies for the above two data sets were −20.5727 and −21.1289, respectively. Among the algorithms compared, the IWOA proposed in this paper had the highest signal-to-noise ratio of the detected fault frequencies. The experimental results show that the proposed method can effectively detect a weak bearing fault signal in enhanced noise.
Hybrid Software Deployment Strategy for Complex Industrial Systems
Authors: Rajković Petar , Aleksić Dejan , Djordjević Andjelija , Janković Dragan
Published: July 2022

Complex industrial systems run the different pieces of software in several interconnected physical layers. The software update in such an environment must be performed in the shortest possible period with the lowest possible resource usage. Namely, it is critical to minimize the data traffic, decrease software downtime, and reduce the impact of the transitional stage during the update process. To meet these requirements and to unify the update process, the common software node structure along with a hybrid software deployment strategy is proposed. The hybrid strategy is defined as a combination of the existing and well-tested techniques—blue/green, canary, and feature flags. The main aim was to utilize their positive sides and to obtain a better overall effect. The approach was tested in the simulation environment, based on the realistic factory layout, and running the software related to the enterprise resource planning (ERP) level. For successful updates, the proposed hybrid deployment method reduced downtime on server nodes to less than 5% and on client nodes to a half compared with the standard approach. The volume of data traffic reduction in a configuration with sentinel nodes is reduced by one-third. The presented results look promising, especially in cases of erroneous updates when a roll back is needed, where the downtime on the server nodes is reduced to the level of 3%. Achieved results are used to define the set of recommendations that could be extended for the other software layers, followed by a discussion about further potential problems and strategy variations.
Primary Voltage and Frequency Regulation in Inverter Based Islanded Microgrids through a Model Predictive Control Approach
Authors: Mestriner Daniele , Rosini Alessandro , Xhani Iris , Bonfiglio Andrea , Procopio Renato
Published: July 2022

A frequency and voltage control strategy based on a decentralized and communication-less approach is proposed in this work and applied to Photovoltaic-Storage-Microturbine islanded Microgrids (MGs). The approach is based on the Model Predictive Control (MPC) technique. Thanks to the use of local measurements, each source can nullify the steady-state voltage and frequency errors by means of a dedicated MPC controller. Consequently, the proposed approach unifies the advantages of classic droop and master/slave controllers due to the absence of communication links among devices and due to the absence of a secondary centralized control loop.
Physics-Based Method for Generating Fully Synthetic IV Curve Training Datasets for Machine Learning Classification of PV Failures
Authors: Hopwood Michael W. , Stein Joshua S. , Braid Jennifer L. , Seigneur Hubert P.
Published: July 2022

Classification machine learning models require high-quality labeled datasets for training. Among the most useful datasets for photovoltaic array fault detection and diagnosis are module or string current-voltage (IV) curves. Unfortunately, such datasets are rarely collected due to the cost of high fidelity monitoring, and the data that is available is generally not ideal, often consisting of unbalanced classes, noisy data due to environmental conditions, and few samples. In this paper, we propose an alternate approach that utilizes physics-based simulations of string-level IV curves as a fully synthetic training corpus that is independent of the test dataset. In our example, the training corpus consists of baseline (no fault), partial soiling, and cell crack system modes. The training corpus is used to train a 1D convolutional neural network (CNN) for failure classification. The approach is validated by comparing the model’s ability to classify failures detected on a real, measured IV curve testing corpus obtained from laboratory and field experiments. Results obtained using a fully synthetic training dataset achieve identical accuracy to those obtained with use of a measured training dataset. When evaluating the measured data’s test split, a 100% accuracy was found both when using simulations or measured data as the training corpus. When evaluating all of the measured data, a 96% accuracy was found when using a fully synthetic training dataset. The use of physics-based modeling results as a training corpus for failure detection and classification has many advantages for implementation as each PV system is configured differently, and it would be nearly impossible to train using labeled measured data.
Enhancement of Anaerobic Digestion with Nanomaterials: A Mini Review
Authors: Barrena Raquel , Moral-Vico Javier , Font Xavier , Sánchez Antoni
Published: July 2022

In recent years, the number of articles reporting the addition of nanomaterials to enhance the process of anaerobic digestion has exponentially increased. The benefits of this addition can be observed from different aspects: an increase in biogas production, enrichment of methane in biogas, elimination of foaming problems, a more stable and robust operation, absence of inhibition problems, etc. In the literature, one of the current focuses of research on this topic is the mechanism responsible for this enhancement. In this sense, several hypotheses have been formulated, with the effect on the redox potential caused by nanoparticles probably being the most accepted, although supplementation with trace materials coming from nanomaterials and the changes in microbial populations have been also highlighted. The types of nanomaterials tested for the improvement of anaerobic digestion is today very diverse, although metallic and, especially, iron-based nanoparticles, are the most frequently used. In this paper, the abovementioned aspects are systematically reviewed. Another challenge that is treated is the lack of works reported in the continuous mode of operation, which hampers the commercial use of nanoparticles in full-scale anaerobic digesters.
A Detailed Analysis of the H.B. Robinson-2 Reactor Pressure Vessel Dosimetry Benchmark
Authors: Vuiart Romain , Brovchenko Mariya , Taforeau Julien , Dumonteil Eric
Published: July 2022

The operation of many nuclear pressurized water reactors is being extended beyond their design lifetime limit. From the perspective of possible further lifetime extension, safety requirements are a priority. Therefore, the quantification of the neutron irradiation embrittlement of the reactor pressure vessel (RPV) is an important issue, as this is a guiding parameter that influences the reactor lifetime. In this context, the Institut de Radioprotection et de Sûreté Nucléaire developed a calculation scheme for the analysis of RPV aging under neutron irradiation, named VACS (vessel aging calculation scheme). VACS couples a deterministic approach (CASMO5 and SIMULATE5) to evaluate the full-core fission neutron source term and a Monte Carlo modeling (MCNP6) approach to model the neutron attenuation from the core to sites of interest (RPV, surveillance capsules, etc.). To ensure the reliability of aging predictions, this paper describes a detailed analysis of the neutron H.B. Robinson-2 reactor pressure vessel dosimetry benchmark. The results indicate that VACS shows satisfactory accuracy when the ENDF-B/VII.1 or JEFF-3.3 nuclear data libraries are used in the attenuation calculation. However, the use of ENDF-B/VIII.0 leads to significantly worse results.
DNA Hypomethylation May Contribute to Metabolic Recovery of Frozen Wood Frog Brains
Authors: Bloskie Tighe , Storey Kenneth B.
Published: July 2022

Transcriptional suppression is characteristic of extreme stress responses, speculated to preserve energetic resources in the maintenance of hypometabolism. In recent years, epigenetic regulation has become heavily implicated in stress adaptation of many animals, including supporting freeze tolerance of the wood frog (Rana sylvatica). However, nervous tissues are frequently lacking in these multi-tissue analyses which warrants investigation. The present study examines the role of DNA methylation, a core epigenetic mechanism, in the response of wood frog brains to freezing. We use immunoblot analysis to track the relative expression of DNA methyltransferases (DNMT), methyl-CpG-binding domain (MBD) proteins and ten-eleven-translocation (TET) demethylases across the freeze-thaw cycle in R. sylvatica brain, including selected comparisons to freeze-associated sub-stresses (anoxia and dehydration). Global methyltransferase activities and 5-hmC content were also assessed. The data show coordinated evidence for DNA hypomethylation in wood frog brains during freeze-recovery through the combined roles of depressed DNMT3A/3L expression driving lowered DNMT activity and increased TET2/3 levels leading to elevated 5-hmC genomic content (p < 0.05). Raised levels of DNMT1 during high dehydration were also noteworthy. The above suggest that alleviation of transcriptionally repressive 5-mC DNA methylation is a necessary component of the wood frog freeze-thaw cycle, potentially facilitating the resumption of a normoxic transcriptional state as frogs thaw and resume normal metabolic activities.
Mapping Growth-Related Quantitative Trait Locus (QTL) in Commercial Yellow River Carp (Cyprinus carpio haematopterus) during Overwintering
Authors: Wang Lei , Zhang Lan , Chen Yuhan , Chen Junping , Zhang Meng , Yu Miao , Jiang Hongxia , Qiao Zhigang , Li Xuejun
Published: July 2022

The common carp (Cyprinus carpio) is farmed globally; as a subspecies, the Yellow River carp (C. c. haematopterus) is widely farmed in northern China. Since the Yellow River carp grows slowly in winter, it would benefit breeders to implement a breeding program targeting growth in winter. In May 2017, we established a Yellow River carp family and measured the body length, height, thickness, and weight of individuals before (October 2017) and after winter (February 2018). Based on the genetic linkage map established in our laboratory, the quantitative trait locus (QTL) mapping of these four traits led to the detection of 29 growth-related QTLs, of which 9, 7, 3, and 10 QTLs were associated with body length, height, thickness, and body weight, respectively. One consensus QTL contained seven QTLs associated with four traits. Through the two major-effect QTLs (qBL-p-1 and qBL-p-2), we screened three candidate genes (fnd3b, ghsr, and pld1), which were associated with biological activities, such as fat formation, growth, and membrane transport. These results are helpful in exploring the growth regulation mechanism and providing a reference for genetic breeding with regard to the overwintering growth of Yellow River carp.
Estimation of Flow Field in Natural Convection with Density Stratification by Local Ensemble Transform Kalman Filter
Authors: Ishigaki Masahiro , Hirose Yoshiyasu , Abe Satoshi , Nagai Toru , Watanabe Tadashi
Published: July 2022

For estimating thermal flow in a nuclear reactor during an accident accurately, it is important to improve the accuracy of computational fluid dynamics simulations. The temperature and flow velocity are not homogeneous and have large variations in a reactor containment vessel because of its very large volume. In addition, Kelm’s work pointed out that the influence of variations of initial and boundary conditions was important. Therefore, it is necessary to set the initial and boundary conditions taking into account the variations of these physical quantities. However, it is a difficult subject to set such complicated initial and boundary conditions. Then, we can obtain realistic initial and boundary conditions and an accurate flow field by data assimilation, and we can improve the accuracy of the simulation result. In this study, we applied data assimilation by a local ensemble transform Kalman filter to a simulation of natural convection behavior in density stratification, and we performed a twin model experiment. We succeeded in estimating the flow fields and improving the simulation accuracy by the data assimilation, even if we applied the boundary condition with error for the true condition.
Is Buying Local Less Expensive? Debunking a Myth—Assessing the Price Competitiveness of Local Food Products in Canada
Authors: Charlebois Sylvain , Hill Amy , Morrison Melanie , Vezeau Janele , Music Janet , Mayhew Kydra
Published: July 2022

It is well known that many consumers believe local foods are more expensive than comparative products coming from other markets. The aim of this study was to measure the price competitiveness of products certified by the Aliments du Québec program, a well-known program in the Canadian province of Quebec. Using machine-learning, artificial intelligence and targeted data mining, the report identifies local products and comparator products, to consider whether locally certified products are more expensive than comparative products coming from outside Quebec. Uncertified products used as comparative products come from anywhere around the world, outside of the province of Quebec. For this study, a total of more than 350,000 discrete price data points were analyzed in the Winter 2022. Local product prices were examined relative to the prices of comparator products. In total, there were 48 subcategories considered. In 70.83% of the subcategories, the local product was either as expensive (similar price) or less expensive than the comparator product. Results challenge the popular belief that local food products are often more expensive. This study also provides limitation and future research paths.
Nutritional Compositions, Phenolic Contents, and Antioxidant Potentials of Ten Original Lineage Beans in Thailand
Authors: Sahasakul Yuraporn , Aursalung Amornrat , Thangsiri Sirinapa , Wongchang Pitthaya , Sangkasa-ad Parichart , Wongpia Aphinya , Polpanit Auytin , Inthachat Woorawee , Temviriyanukul Piya , Suttisansanee Uthaiwan
Published: July 2022

Legumes and pulses are nutrient-dense foods providing a good source of protein, complex carbohydrates, fiber, vitamins, minerals, and bioactive compounds. To breed a new lineage of beans with specific nutritional and health beneficial purposes, more information on original lineage beans must be obtained. However, data concerning the nutritive compositions, total phenolic contents (TPCs), and health benefits regarding the antioxidant potentials of some original lineage beans in Thailand remain scarce, causing difficulty in decisional selection to breed a new lineage. Thus, this study aimed to examine the nutritional values (proximate compositions, vitamins, and minerals), TPCs, and antioxidant activities of ten original lineage bean cultivars in Glycine, Phaseolus, and Vigna genera from Genebank, Department of Agriculture (DOA), Thailand. The results indicated that beans in the Glycine genus potentially provided higher energy, protein, fat, and calcium contents than other genera, while the Phaseolus genus tended to provide higher carbohydrate and dietary fiber. Specifically, lima bean cultivar ‘38’ exhibited high vitamin B1, and red kidney bean cultivar ‘112’ exhibited high potassium content. Beans in the Vigna genus exhibited high TPCs and antioxidant activities. However, their nutritional compositions were markedly varied. The results of this work could support bean consumption as a feasible alternative diet and be used as a reference for future bean breeding (within the same genera) of a new lineage with particular nutritional requirements and health potentials.
Improvement of Pacific White Shrimp (Litopenaeus vannamei) Drying Characteristics and Quality Attributes by a Combination of Salting Pretreatment and Microwave
Authors: Lin Yawen , Gao Yue , Li Aiqing , Wang Lei , Ai Ziping , Xiao Hongwei , Li Jianrong , Li Xuepeng
Published: July 2022

This study investigated the effects of salting pretreatment and microwave (MW) power on drying characteristics, water distribution and quality attributes of Pacific white shrimp (Litopenaeus vannamei). With increasing salt concentration (0–8%, w/v) and MW power (300–900 W), the drying time of shrimp was shortened by 15.15–28.57%, compared with the untreated samples. Regarding the quality of dried shrimp, increasing the salt concentration and MW power increased the hardness (from 13,073.6 to 24,556.5 g), while the springiness, color parameters and astaxanthin content showed an initial decrease but a later increase trend. Low field nuclear magnetic resonance (LF-NMR) demonstrated that the T2 curve of the pretreated samples moved toward the negative x-axis and the immobilized water content decreased with increasing salt concentration. E-nose showed that volatile components were different and could be obviously distinguished at different salt concentrations and MW powers. Raman spectroscopy illustrated that the protein secondary structure of dried shrimp was altered by salting pretreatment and drying conditions, and the lowest conversion degree of α-helix to β-sheet of dried shrimp was obtained at the salt concentration of 4% (w/v) and MW power of 500 W. By comprehensively considering the drying time and quality attributes, the combination of 4% (w/v) salt and 500 W MW power was concluded as the best drying conditions for shrimp using a microwave. The results could provide an innovative combination of salt pretreatment and MW drying with suitable processing conditions for producing high-quality dried shrimp.
Improvement of Sourdough and Bread Qualities by Fermented Water of Asian Pears and Assam Tea Leaves with Co-Cultures of Lactiplantibacillus plantarum and Saccharomyces cerevisiae
Authors: Supasil Ramita , Suttisansanee Uthaiwan , Santivarangkna Chalat , Tangsuphoom Nattapol , Khemthong Chanakan , Chupeerach Chaowanee , On-nom Nattira
Published: July 2022

Qualities of sourdough and sourdough bread using fermented water from Asian pears and Assam tea leaves with Lactiplantibacillus plantarum 299v and Saccharomyces cerevisiae TISTR 5059 as starter cultures were evaluated. Changes in the growth of lactic acid bacteria and yeast, pH, sourdough height, total phenolic contents (TPCs) and antioxidant activities detected by ORAC, FRAP and DPPH radical scavenging assays were monitored during sourdough production. Mature sourdough was achieved within 4 h after 18 h retard fermentation and used for bread production. The bread was then analyzed to determine chemical and physical properties, nutritional compositions, TPCs, antioxidant activities and sensory properties as well as shelf-life stability. Results showed that fermented water significantly promoted the growth of yeast and increased TPCs and antioxidant activities of sourdough. Compared to common sourdough bread, fermented water sourdough bread resulted in 10% lower sugar and 12% higher dietary fiber with improved consumer acceptability; TPCs and antioxidant activities also increased by 2–3 times. The fermented water sourdough bread maintained microbial quality within the standard range, with adequate TPCs after storage at room temperature for 7 days. Fermented water from Asian pears and Assam tea leaves with L. plantarum 299v and S. cerevisiae TISTR 5059 as starter cultures improved dough fermentation and bread quality.
Mythologies of Genesis and Neo-Nazi Palingenesis: Commemorating the Battle of Thermopylae in the Political Rites of the Golden Dawn
Authors: Ioannidou Eleftheria
Published: July 2022

This article examines the public commemorations of the battle of Thermopylae held by the Greek neo-Nazi party Golden Dawn in the wider context of fascist appropriations of classical antiquity. The discussion focuses on the rhetorical and cultural mechanisms involved in transforming the historical event into a fascist mythology. Drawing on methodologies of narrative analysis and performance studies, I examine the narrative patterns and ritual practices deployed in these commemorations to engross the participants in stories of genesis and rebirth. During the commemorations of Thermopylae, Golden Dawn strove to revive both the spirit of the Spartan soldiers and the ideals of Nazism. The example of GD demonstrates that the persistence of the narrative of rebirth within neo-Nazi cultures is instrumental in the resurgence of fascism. By looking at this example closely, we can conclude that commitment of neo-Nazi groups to classical antiquity invites reflection upon the role of classical traditions in Western culture.
The Effect of Lower Limb Exoskeleton Alignment on Knee Rehabilitation Efficacy
Authors: MajidiRad AmirHossein , Yihun Yimesker , Hakansson Nils , Mitchell Allyson
Published: July 2022

This study focuses on a musculoskeletal analysis of human lower extremity and associated muscle forces during different rehabilitative tasks and exoskeleton alignment models. By changing the size and orientation of the impairment levels that could be caused by the misalignment of the exoskeleton and biological knee joint, muscle stress variations were observed. This indicates an increase in force such as that generated by the Vastus lateralis muscle up to 4.3% due to a 5 mm lateral offset from an anatomically healthy knee joint location. In another setting, while a subject moved the shank through a circular trajectory using an exoskeleton support, muscle strain due to misalignment was reflected at the rectus femoris with a variation of 44%, the biceps femoris large head with 32% and the gastrocnemius muscles with 31–33% variation. These results suggest that misalignment should be taken into account while using exoskeletons with certain trajectories for knee rehabilitation purposes. Based on the shortcomings of conventional physiotherapeutic tasks, the outcome of this study can be helpful in prescribing an impactful yet convenient configuration toward a safe and promising rehabilitation process. Assessment of exoskeleton alignment during rehabilitation is important to ensure user safety with a better therapy efficacy.
Viral Infection Control in the Essential Oil-Bearing Rose Nursery: Collection Maintenance and Monitoring
Authors: Seitadzhieva Sevilia , Gulevich Alexander A. , Yegorova Natalya , Nevkrytaya Natalya , Abdurashytov Suleiman , Radchenko Lyudmila , Pashtetskiy Vladimir , Baranova Ekaterina N.
Published: July 2022

Viral diseases affecting the essential oil rose, which is a valuable object of agricultural production, may have a significant negative impact on the economic value of this crop. Hence, the study and control of potentially dangerous viruses is essential to improving the quality of cultivars of this raw plant material, to enable production of valuable derivatives. The diversity of viruses affecting Rosa L. plants manifests itself in their conditional division into those that are specific to this crop, and those that are hosted by other plants. Representatives of both groups are found in different countries, however, a low number of viruses identified have been thoroughly studied through the use of experimental methods. In particular, with regard to many viruses, the issue of their spread remains open. The viruses infecting Rosa L. plants along with other crops are described in the literature in detail, as the range of hosts they affect is rather wide and well-studied. It is also possible to single out the three most significant viruses affecting this host—Prunus necrotic ringspot virus, Apple mosaic virus and Arabis mosaic virus which individually, or collectively, cause viral diseases that manifest themselves in mosaic symptoms. The most likely mechanisms for the spread of the Rosa L. species viruses are vegetative propagation procedures and transmission by various pests. These presumptions underlie viral infection control methods, including a well-thought-out planting scheme and provision of accurate plant care, which considers plant disinfection, disease monitoring associated with diagnostics and obtaining virus-free material through biotechnology techniques.
Adherence to Mediterranean Diet and Its Association with Maternal and Newborn Outcomes
Authors: Di Renzo Laura , Marchetti Marco , Rizzo Giuseppe , Gualtieri Paola , Monsignore Diego , Dominici Francesca , Mappa Ilenia , Cavicchioni Ottavia , Aguzzoli Lorenzo , De Lorenzo Antonino ,   on behalf of the MeDAP Group
Published: July 2022

Background: Pregnancy is a crucial stage in a woman’s life and can be affected by epigenetic and environmental factors. Diet also plays a key role in gestation. This study aimed to evaluate how a greater or lesser adherence to the Mediterranean Diet (MD) influences specific parameters of mother and newborn. Methods: After delivery, the women participating in the study answered a questionnaire: demographic information; anthropometric data (pre-pregnancy weight, height, and gestational weight gain); dietary habits information (adherence to MD before and during pregnancy, using the validated Mediterranean Diet Adherence Screener (MEDAS), quality of protein intake); pregnancy information (onset of complications, cesarean/vaginal delivery, gestational age at birth, birth weight, birth length); and clinical practitioner for personalized dietary patterns during pregnancy. Results: A total of 501 respondents have been included in the study, and 135 were excluded for complications. Women who followed the advice of clinical nutritionists showed better adherence to MD (p = 0.02), and the baby’s birth weight was higher (p = 0.02). Significant differences in gestational weight gain (p < 0.01) between groups with dissimilar diet adherence were demonstrated. Conclusion: Our data demonstrate a significant relationship between adherence to MD and birthweight.
Vitamin Supplementation in Pre-Pregnancy and Pregnancy among Women—Effects and Influencing Factors in Romania
Authors: Avram Calin , Bucur Oana Maria , Zazgyva Ancuța , Avram Laura , Ruta Florina
Published: July 2022

Introduction: The aim of the study was to identify the consumption of vitamin and folic acid supplements before and during pregnancy in a group of post-partum women (Romanian, Hungarian, and Roma) from Mureș County, Romania, and the influence of socio-economic and behavioral factors on the consumption of vitamins. Materials and Methods: This cross-sectional questionnaire-based study included 1278 post-partum women (during the three days of hospitalization for birth), average age 29.5, registered for giving birth in the three hospitals in Mureș County, 2015–2016. Results: In our sample, 69.58% of the interviewed women did not use any vitamin and folic acid supplements before pregnancy, while 30.70% did not use vitamin supplements during pregnancy. The lack of vitamin supplementation during pregnancy was associated with the low birth weight (<2500 g) of newborns (OR = 2.4, 95% CI [1.6–3.8]) and birth at under 36 weeks of gestation (OR = 0.5, 95% CI [0.2–0.8]). Conclusion: The use of vitamin supplements, including folic acid, continues to be deficient among Romanian women before getting pregnant, as well as during their pregnancy. We observed a lack of vitamin supplementation for pregnant women even if they were influenced by risk factors. This highlights the importance of promoting the benefits of vitamin supplementation equally among all subjects.
Estimating the Carbon Emission of Construction Waste Recycling Using Grey Model and Life Cycle Assessment: A Case Study of Shanghai
Authors: Wang Ting , Li Kaiyi , Liu Defu , Yang Yang , Wu Dong
Published: July 2022

Great efforts have been exerted in reducing carbon emissions in design, construction and operation stages. However, little attention is paid to the quantification of carbon emissions in construction waste recycling at the end-of-life stage. This study aims to quantitatively analyze the carbon emission of construction waste in Shanghai City, PR China. A grey model is used to forecast the generation amount of construction waste, and a life cycle assessment is performed to estimate the carbon emission of construction waste. In this study, both the carbon emission of recycling activities (environmental costs), and the equivalent amount of carbon generated from alternative materials (environmental benefit) are considered. Here, recycling 1 ton (t) of construction waste in Shanghai can save 100.4 kg CO2−e. The total carbon-emission-saving potential can be increased from 0.31 million t CO2−e (2022) to 0.35 million t CO2−e (2031). The carbon emission of recycling concrete, brick, steel, wood and mortar, identified as the key components of construction waste, is investigated. This research can help to reduce carbon emissions and further achieve carbon neutrality for Shanghai City. The proposed methods can also be applied to other regions, especially when the data for construction waste are insufficient.