bluuebunny/crossref_metadata_2025 huggingface dataset:
Does Anatomical Contextual Information Improve 3D U-Net-Based Brain Tumor Segmentation?
Authors: Tampu Iulian Emil , Haj-Hosseini Neda , Eklund Anders
Published: June 2021

Effective, robust, and automatic tools for brain tumor segmentation are needed for the extraction of information useful in treatment planning. Recently, convolutional neural networks have shown remarkable performance in the identification of tumor regions in magnetic resonance (MR) images. Context-aware artificial intelligence is an emerging concept for the development of deep learning applications for computer-aided medical image analysis. A large portion of the current research is devoted to the development of new network architectures to improve segmentation accuracy by using context-aware mechanisms. In this work, it is investigated whether or not the addition of contextual information from the brain anatomy in the form of white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF) masks and probability maps improves U-Net-based brain tumor segmentation. The BraTS2020 dataset was used to train and test two standard 3D U-Net (nnU-Net) models that, in addition to the conventional MR image modalities, used the anatomical contextual information as extra channels in the form of binary masks (CIM) or probability maps (CIP). For comparison, a baseline model (BLM) that only used the conventional MR image modalities was also trained. The impact of adding contextual information was investigated in terms of overall segmentation accuracy, model training time, domain generalization, and compensation for fewer MR modalities available for each subject. Median (mean) Dice scores of 90.2 (81.9), 90.2 (81.9), and 90.0 (82.1) were obtained on the official BraTS2020 validation dataset (125 subjects) for BLM, CIM, and CIP, respectively. Results show that there is no statistically significant difference when comparing Dice scores between the baseline model and the contextual information models (p > 0.05), even when comparing performances for high and low grade tumors independently. In a few low grade cases where improvement was seen, the number of false positives was reduced. Moreover, no improvements were found when considering model training time or domain generalization. Only in the case of compensation for fewer MR modalities available for each subject did the addition of anatomical contextual information significantly improve (p < 0.05) the segmentation of the whole tumor. In conclusion, there is no overall significant improvement in segmentation performance when using anatomical contextual information in the form of either binary WM, GM, and CSF masks or probability maps as extra channels.
COVID-19 Antibody Detecting Rapid Diagnostic Tests Show High Cross-Reactivity When Challenged with Pre-Pandemic Malaria, Schistosomiasis and Dengue Samples
Authors: Vanroye Fien , Bossche Dorien Van den , Brosius Isabel , Tack Bieke , Esbroeck Marjan Van , Jacobs Jan
Published: June 2021

COVID-19 Antibody Detecting Rapid Diagnostic Tests (COVID-19 Ab RDTs) are the preferred tool for SARS-CoV-2 seroprevalence studies, particularly in low- and middle-income countries. The present study challenged COVID-19 Ab RDTs with pre-pandemic samples of patients exposed to tropical pathogens. A retrospective study was performed on archived serum (n = 94) and EDTA whole blood (n = 126) samples obtained during 2010–2018 from 196 travelers with malaria (n = 170), schistosomiasis (n = 25) and dengue (n = 25). COVID-19 Ab RDTs were selected based on regulatory approval status, independent evaluation results and detecting antigens. Among 13 COVID-19 Ab RDT products, overall cross-reactivity was 18.5%; cross-reactivity for malaria, schistosomiasis and dengue was 20.3%, 18.1% and 7.5%, respectively. Cross-reactivity for current and recent malaria, malaria antibodies, Plasmodium species and parasite densities was similar. Cross-reactivity among the different RDT products ranged from 2.7% to 48.9% (median value 14.5%). IgM represented 67.9% of cross-reactive test lines. Cross-reactivity was not associated with detecting antigens, patient categories or disease (sub)groups, except for schistosomiasis (two products with ≥60% cross-reactivity). The high cross-reactivity for malaria, schistosomiasis and—to a lesser extent—dengue calls for risk mitigation when using COVID-19 Ab RDTs in co-endemic regions.
Variational Message Passing and Local Constraint Manipulation in Factor Graphs
Authors: Şenöz İsmail , van de Laar Thijs , Bagaev Dmitry , de Vries Bert de
Published: June 2021

Accurate evaluation of Bayesian model evidence for a given data set is a fundamental problem in model development. Since evidence evaluations are usually intractable, in practice variational free energy (VFE) minimization provides an attractive alternative, as the VFE is an upper bound on negative model log-evidence (NLE). In order to improve tractability of the VFE, it is common to manipulate the constraints in the search space for the posterior distribution of the latent variables. Unfortunately, constraint manipulation may also lead to a less accurate estimate of the NLE. Thus, constraint manipulation implies an engineering trade-off between tractability and accuracy of model evidence estimation. In this paper, we develop a unifying account of constraint manipulation for variational inference in models that can be represented by a (Forney-style) factor graph, for which we identify the Bethe Free Energy as an approximation to the VFE. We derive well-known message passing algorithms from first principles, as the result of minimizing the constrained Bethe Free Energy (BFE). The proposed method supports evaluation of the BFE in factor graphs for model scoring and development of new message passing-based inference algorithms that potentially improve evidence estimation accuracy.
The Carnot Cycle, Reversibility and Entropy
Authors: Sands David
Published: June 2021

The Carnot cycle and the attendant notions of reversibility and entropy are examined. It is shown how the modern view of these concepts still corresponds to the ideas Clausius laid down in the nineteenth century. As such, they reflect the outmoded idea, current at the time, that heat is motion. It is shown how this view of heat led Clausius to develop the entropy of a body based on the work that could be performed in a reversible process rather than the work that is actually performed in an irreversible process. In consequence, Clausius built into entropy a conflict with energy conservation, which is concerned with actual changes in energy. In this paper, reversibility and irreversibility are investigated by means of a macroscopic formulation of internal mechanisms of damping based on rate equations for the distribution of energy within a gas. It is shown that work processes involving a step change in external pressure, however small, are intrinsically irreversible. However, under idealised conditions of zero damping the gas inside a piston expands and traces out a trajectory through the space of equilibrium states. Therefore, the entropy change due to heat flow from the reservoir matches the entropy change of the equilibrium states. This trajectory can be traced out in reverse as the piston reverses direction, but if the external conditions are adjusted appropriately, the gas can be made to trace out a Carnot cycle in P-V space. The cycle is dynamic as opposed to quasi-static as the piston has kinetic energy equal in difference to the work performed internally and externally.
Selecting a Model for Forecasting
Authors: Castle Jennifer L. , Doornik Jurgen A. , Hendry David F.
Published: June 2021

We investigate forecasting in models that condition on variables for which future values are unknown. We consider the role of the significance level because it guides the binary decisions whether to include or exclude variables. The analysis is extended by allowing for a structural break, either in the first forecast period or just before. Theoretical results are derived for a three-variable static model, but generalized to include dynamics and many more variables in the simulation experiment. The results show that the trade-off for selecting variables in forecasting models in a stationary world, namely that variables should be retained if their noncentralities exceed unity, still applies in settings with structural breaks. This provides support for model selection at looser than conventional settings, albeit with many additional features explaining the forecast performance, and with the caveat that retaining irrelevant variables that are subject to location shifts can worsen forecast performance.
Dimensioning an FPGA for Real-Time Implementation of State of the Art Neural Network-Based HPA Predistorter
Authors: Louliej Abdelhamid , Jabrane Younes , Jiménez Víctor P. Gil , Guilloud Frédéric
Published: June 2021

Orthogonal Frequency Division Multiplexing (OFDM) is one of the key modulations for current and novel broadband communications standards. For example, Multi-band Orthogonal Frequency Division Multiplexing (MB-OFDM) is an excellent choice for the ECMA-368 Ultra Wideband (UWB) wireless communication standard. Nevertheless, the high Peak to Average Power Ratio (PAPR) of MB-OFDM UWB signals reduces the power efficiency of the key element in mobile devices, the High Power Amplifier (HPA), due to non-linear distortion, known as the non-linear saturation of the HPA. In order to deal with this limiting problem, a new and efficient pre-distorter scheme using a Neural Networks (NN) is proposed and also implemented on Field Programmable Gate Array (FPGA). This solution based on the pre-distortion concept of HPA non-linearities offers a good trade-off between complexity and performance. Some tests and validation have been conducted on the two types of HPA: Travelling Wave Tube Amplifiers (TWTA) and Solid State Power Amplifiers (SSPA). The results show that the proposed pre-distorter design presents low complexity and low error rate. Indeed, the implemented architecture uses 10% of DSP (Digital Signal Processing) blocks and 1% of LUTs (Look up Table) in case of SSPA, whereas it only uses 1% of LUTs in case of TWTA. In addition, it allows us to conclude that advanced machine learning techniques can be efficiently implemented in hardware with the adequate design.
An Overview of Machine Learning-Based Energy-Efficient Routing Algorithms in Wireless Sensor Networks
Authors: Ding Qianao , Zhu Rongbo , Liu Hao , Ma Maode
Published: June 2021

Machine learning (ML) technology has shown its unique advantages in many fields and has excellent performance in many applications, such as image recognition, speech recognition, recommendation systems, and natural language processing. Recently, the applicability of ML in wireless sensor networks (WSNs) has attracted much attention. As resources are limited in WSNs, identifying how to improve resource utilization and achieve power-efficient load balancing is becoming a critical issue in WSNs. Traditional green routing algorithms aim to achieve this by reducing energy consumption and prolonging network lifetime through optimized routing schemes in WSNs. However, there are usually problems such as poor flexibility, a single consideration factor, and a reliance on accurate mathematical models. ML techniques can quickly adapt to environmental changes and integrate multiple factors for routing decisions, which provides new ideas for intelligent energy-efficient routing algorithms in WSNs. In this paper, we survey and propose a theoretical hypothetic model formulation of ML as an effective method for creating a power-efficient green routing model that can overcome the limitations of traditional green routing methods. In addition, the study also provides an overview of past, present, and future progress in green routing schemes in WSNs. The contents of this paper will appeal to a wide range of audiences interested in ML-based WSNs.
A Pipeline-TDC-Based CMOS Temperature Sensor with a 48 fJ·K2 Resolution FoM
Authors: Cai Zhikuang , Wang Ze , Zhang Wenjing , Wang Xin , Wang Zixuan
Published: June 2021

An energy-efficient temperature sensor is important for temperature monitoring in Biomedical Internet-of-things (BIoT) applications. This article presents a time-domain temperature sensor with a pipeline time-to-digital converter (TDC). A programmable-gain time amplifier (PGTA) with high linearity and wide linear range is proposed to improve the resolution of the sensor and to reduce the chip area. The conversion time of the sensor is reduced by the fast TDC that only needs ~26 ns/conversion, which means the sensor is suitable for BIoT applications that commonly use duty cycling mode. Fabricated in a 40 nm standard CMOS technology, the sensor consumes 7.6 μA at a 0.6 V supply and achieves a resolution of 90 mK and a sensitivity of 0.62%/°C in a 1.3 μs conversion time. This translates into a resolution figure-of-merit of 48 fJ·K2. The sensor achieves an inaccuracy of 0.39 °C from −20 °C to 80 °C after two-point calibration. Duty cycling the sensor results in an even lower average power: ~18.6 nW at 10 conversions/s.
P4-KBR: A Key-Based Routing System for P4-Programmable Networks
Authors: Manzanares-Lopez Pilar , Muñoz-Gea Juan Pedro , Malgosa-Sanahuja Josemaria
Published: June 2021

Software-defined networking (SDN) architecture has provided well-known advantages in terms of network programmability, initially offering a standard, open, and vendor-agnostic interface (e.g., OpenFlow) to instruct the forwarding behavior of network devices from different vendors. However, in the last few years, data plane programmability has emerged as a promising approach to extend the network management allowing the definition and programming of customized and non-standardized protocols, as well as specific packet processing pipelines. In this paper, we propose an in-network key-based routing protocol called P4-KBR, in which end-points (hosts, contents or services) are identified by virtual identifiers (keys) instead of IP addresses, and where P4 network elements are programmed to be able to route the packets adequately. The proposal was implemented and evaluated using bmv2 P4 switches, verifying how data plane programmability offers a powerful tool to overcome continuing challenges that appear in SDN networks.
A Compressed Sensing Recovery Algorithm Based on Support Set Selection
Authors: Liang Wandi , Wang Zixiong , Lu Guangyu , Jiang Yang
Published: June 2021

The theory of compressed sensing (CS) has shown tremendous potential in many fields, especially in the signal processing area, due to its utility in recovering unknown signals with far lower sampling rates than the Nyquist frequency. In this paper, we present a novel, optimized recovery algorithm named supp-BPDN. The proposed algorithm executes a step of selecting and recording the support set of original signals before using the traditional recovery algorithm mostly used in signal processing called basis pursuit denoising (BPDN). We proved mathematically that even in a noise-affected CS system, the probability of selecting the support set of signals still approaches 1, which means supp-BPDN can maintain good performance in systems in which noise exists. Recovery results are demonstrated to verify the effectiveness and superiority of supp-BPDN. Besides, we set up a photonic-enabled CS system realizing the reconstruction of a two-tone signal with a peak frequency of 350 MHz through a 200 MHz analog-to-digital converter (ADC) and a signal with a peak frequency of 1 GHz by a 500 MHz ADC. Similarly, supp-BPDN showed better reconstruction results than BPDN.
Health-Conscious Optimization of Long-Term Operation for Hybrid PEMFC Ship Propulsion Systems
Authors: Dall’Armi Chiara , Pivetta Davide , Taccani Rodolfo
Published: June 2021

The need to decarbonize the shipping sector is leading to a growing interest in fuel cell-based propulsion systems. While Polymer Electrolyte Membrane Fuel Cells (PEMFC) represent one of the most promising and mature technologies for onboard implementation, they are still prone to remarkable degradation. The same problem is also affecting Lithium-ion batteries (LIB), which are usually coupled with PEMFC in hybrid powertrains. By including the combined degradation effects in an optimization strategy, the best compromise between costs and PEMFC/LIB lifetime could be determined. However, this is still a challenging yet crucial aspect, rarely addressed in the literature and rarely yet explored. To fill this gap, a health-conscious optimization is here proposed for the long-term minimization of costs and PEMFC/LIB degradation. Results show that a holistic multi-objective optimization allows a 185% increase of PEMFC/LIB lifetime with respect to a fuel-consumption-minimization-only approach. With the progressive ageing of PEMFC/LIB, the hybrid propulsion system modifies the energy management strategy to limit the increase of the daily operation cost. Comparing the optimization results at the beginning and the end of the plant lifetime, daily operation costs are increased by 73% and hydrogen consumption by 29%. The proposed methodology is believed to be a useful tool, able to give insights into the effective costs involved in the long-term operation of this new type of propulsion system.
Global-Local Heat Demand Development for the Energy Transition Time Frame Up to 2050
Authors: Keiner Dominik , Barbosa Larissa D.S.N.S. , Bogdanov Dmitrii , Aghahosseini Arman , Gulagi Ashish , Oyewo Solomon , Child Michael , Khalili Siavash , Breyer Christian
Published: June 2021

Globally, the heat sector has a major share in energy consumption and carbon emission footprint. To provide reliable mitigation options for space heating, domestic hot water, industrial process heat and biomass for cooking for the energy transition time frame up to the year 2050, energy system modeling relies on a comprehensive and detailed heat demand database in high spatial resolution, which is not available. This study overcomes this hurdle and provides a global heat demand database for the mentioned heat demand types and in a resolution of 145 mesoscale regions up to the year 2050 based on the current heat demand and detailed elaboration of parameters influencing the future heat demand. Additionally, heat demand profiles for 145 mesoscale regions are provided. This research finds the total global heat demand will increase from about 45,400 TWhth in 2012 up to about 56,600 TWhth in 2050. The efficiency measures in buildings lead to a peak of space heating demand in around 2035, strong growth in standards of living leads to a steady rise of domestic hot water consumption, and a positive trend for the worldwide economic development induces a growing demand for industrial process heat, counterbalanced by the efficiency gain in already industrialised countries. For the case of biomass for cooking, a phase-out path until 2050 is presented. Literature research revealed a lack of consensus on future heat demand. This research intends to facilitate a more differentiated discussion on heat demand projections.
Soil Diversity and Key Functional Characteristics of Yakutsk City: Largest Urbanized Cryogenic World’s Ecosystem
Authors: Polyakov Vyacheslav , Nizamutdinov Timur , Abakumov Evgeny , Morgun Eugeniya
Published: June 2021

Urban soils are the most vulnerable component of the current terrestrial ecosystem. Due to the anthropogenic influence, various pollutants can accumulate in the soils and have a negative effect on the health of citizens. As a result of the degradation of permafrost landscapes, the disappearance of a number of natural ecosystems, as well as urban areas, is possible. In the course of the development of thermokarst processes, problems arise in the urban environment with the destruction of urban buildings and a decrease in agricultural areas. The ecosystem of Yakutsk city is located in the valley of the Lena River and represents the largest urbanized terrestrial biotope, located in the permafrost-affected bioclimatic and geogenic conditions. This work represents relevant datasets on the physico-chemical, toxicological and agrochemical state of soil cover components in various functional zones of the city. An 3excess of the maximum threshold levels for Zn was noted in the area of active mining within the city borders. From the data obtained of pollution state, the most polluted zone of Yakutsk city is the quarry complex located in relative proximity to the city. In other studied areas of the city, there is no excess of permissible threshold levels for trace elements. According to agrochemical analysis, in Yakutsk city, there is a relatively low content of available agrochemical elements in comparison with other cities located in the permafrost-affected zone.
Modeling of Water Generation from Air Using Anhydrous Salts
Authors: Sibie Shereen K. , El-Amin Mohamed F. , Sun Shuyu
Published: June 2021

The atmosphere contains 3400 trillion gallons of water vapor, which would be enough to cover the entire Earth with a one-inch layer of water. As air humidity is available everywhere, it acts as an abundant renewable water reservoir, known as atmospheric water. The efficiency of an atmospheric water harvesting system depends on the sorption capacities of water-based absorption materials. Using anhydrous salts is an efficient process in capturing and delivering water from ambient air, especially under a condition of low relative humidity, as low as 15%. Many water-scarce countries, like Saudi Arabia, receive high annual solar radiation and have relatively high humidity levels. This study is focused on the simulation and modeling of the water absorption capacities of three anhydrous salts under different relative humidity environments: copper chloride (CuCl2), copper sulfate (CuSO4), and magnesium sulfate (MgSO4), to produce atmospheric drinking water in water-scarce regions. By using a mathematical model to simulate water absorption, this study attempts to compare and model the results of the current computed model with the laboratory experimental results under static and dynamic relative humidities. This paper also proposes a prototype of a system to produce atmospheric water using these anhydrous salts. A sensitivity analysis was also undertaken on these three selected salts to determine how the uniformity of their stratified structures, thicknesses, and porosities as applied in the mathematical model influence the results.
Cascade-Type Pole-Zero Cancellation Output Voltage Regulator for DC/DC Boost Converters
Authors: You Sung Hyun , Bonn Koo , Kim Dong Soo , Kim Seok-Kyoon
Published: June 2021

This paper presents a novel output voltage regulator in the cascade structure under the consideration of both the parameter and load uncertainties. It leads to the first-order closed-loop inner and outer loop dynamics in the low-pass filter form by the pole-zero cancellation through the active damping injection, which is the main contribution of this study. Moreover, it is proved that the active damping injection level determines the disturbance rejection capability of the closed-loop system. A 3-kW DC/DC boost converter confirms the actual advantages from these two contributions.
Valorization of Lignin Side-Streams into Polyols and Rigid Polyurethane Foams—A Contribution to the Pulp and Paper Industry Biorefinery
Authors: Pinto João A. , Fernandes Isabel P. , Pinto Virginia D. , Gomes Elson , Oliveira Cátia F. , C. R. Pinto Paula C. R. , Mesquita Luís M. R. , Piloto Paulo A. G. , Rodrigues Alírio E. , Barreiro Maria-Filomena
Published: June 2021

Valorization of industrial low-value side-streams are of great interest, contributing to boosts in the circular economy. In this context, lignin side-streams of the pulp and paper industry were oxypropylated to produce biobased polyols and tested in the synthesis of rigid polyurethane (RPU) foams. E. globulus lignins, namely a lignin isolated from an industrial Kraft black liquor and depolymerized lignins obtained as by-products of an oxidation process, were used. RPU foams, synthesized with 100% lignin-based polyols and using a 1.1 NCO/OH ratio, were characterized concerning apparent density, morphology, thermal conductivity, thermal stability, and heat release rate (HRR). Foams containing the lignin-based polyols presented densities varying from 44.7 to 112.2 kg/m3 and thermal conductivity in the range of 37.2–49.0 mW/mK. For the reference foam (sample produced with 100% wt. Daltofoam TP 32015 polyol), values of 70.9 kg/m3 and 41.1 mW/mK were obtained, respectively. The achieved results point out the viability of using the generated lignin-based polyols at 100% content in RPU foams, mainly when depolymerized lignins are used. Moreover, fire retardancy was favored when the lignin-based polyols were introduced. The proposed strategies can contribute to establishing the integrated pulp and paper biorefinery concept where material synthesis (polyols and RPU foams) can be combined with chemical production (vanillin and syringaldehyde).
Privileging Electric Vehicles as an Element of Promoting Sustainable Urban Mobility—Effects on the Local Transport System in a Large Metropolis in Poland
Authors: Borowska-Stefańska Marta , Kowalski Michał , Kurzyk Paulina , Mikušová Miroslava , Wiśniewski Szymon
Published: June 2021

The main purpose of this article was to determine the impact on the equilibrium of the local transport system from privileging EVs by permitting them to use bus lanes. The study used two sets of data: information on infrastructure and traffic management; and information on the recorded road network loads and traffic volumes generated by a given shopping centre—the E. Leclerc shopping centre (an important traffic generator within the city of Łódź, Poland). These sets were then used to develop a microsimulation traffic model for the shopping centre and the associated effects on the localised transport system. The model was constructed by means of the PTV Vissim software tool. An initial simulation was conducted that formed a basis for subsequent scenarios (in total, 17 simulations were performed). On the basis of the conducted analyses, it was established that—for the researched part of the transport system—privileging the still rather uncommon battery electric vehicles (BEVs) engendered a marginal deterioration of traffic conditions. At the same time, allowing BEVs to use bus lanes within the chosen research area had no negative impact on bus journey times.
Mixed-Species Plantation Effects on Soil Biological and Chemical Quality and Tree Growth of A Former Agricultural Land
Authors: Danise Tiziana , Andriuzzi Walter S. , Battipaglia Giovanna , Certini Giacomo , Guggenberger Georg , Innangi Michele , Mastrolonardo Giovanni , Niccoli Francesco , Pelleri Francesco , Fioretto Antonietta
Published: June 2021

Tree planting on abandoned agricultural land could both restore the soil quality and increase the productivity of economically valuable woody species. Here, we assess the impact of mixed-species tree plantations on soil quality at a site in Central Italy where tree intercropping systems were established 20 years ago on a former agricultural land. These intercropping systems include two species of economic interest, Populus alba and Juglans regia, and one of three different nurse trees, i.e., Alnus cordata, Elaeagnus umbellata, both of which are N-fixing species, and Corylus avellana. We measured tree growth and compared how soil organic matter, soil extracellular enzymes, and nematodes of different feeding groups varied among the intercropping systems and relative to a conventional agricultural field. Our results indicate that tree plantation led to an increase in soil carbon and nitrogen, and enhanced enzyme activities, compared with the agricultural land. The proportion of nematode feeding groups was heterogeneous, but predators were absent from the agricultural soil. Multivariate analysis of soil properties, enzymatic activity, nematodes, and tree growth point to the importance of the presence N-fixing species, as the presence of A. cordata was linked to higher soil quality, and E. umbellata to growth of the associated valuable woody species. Our findings indicate that intercropping tree species provide a tool for both restoring fertility and improving soil quality.
A Sentiment-Aware Contextual Model for Real-Time Disaster Prediction Using Twitter Data
Authors: Song Guizhe , Huang Degen
Published: June 2021

The massive amount of data generated by social media present a unique opportunity for disaster analysis. As a leading social platform, Twitter generates over 500 million Tweets each day. Due to its real-time characteristic, more agencies employ Twitter to track disaster events to make a speedy rescue plan. However, it is challenging to build an accurate predictive model to identify disaster Tweets, which may lack sufficient context due to the length limit. In addition, disaster Tweets and regular ones can be hard to distinguish because of word ambiguity. In this paper, we propose a sentiment-aware contextual model named SentiBERT-BiLSTM-CNN for disaster detection using Tweets. The proposed learning pipeline consists of SentiBERT that can generate sentimental contextual embeddings from a Tweet, a Bidirectional long short-term memory (BiLSTM) layer with attention, and a 1D convolutional layer for local feature extraction. We conduct extensive experiments to validate certain design choices of the model and compare our model with its peers. Results show that the proposed SentiBERT-BiLSTM-CNN demonstrates superior performance in the F1 score, making it a competitive model in Tweets-based disaster prediction.
Face Recognition Using Popular Deep Net Architectures: A Brief Comparative Study
Authors: Gwyn Tony , Roy Kaushik , Atay Mustafa
Published: June 2021

In the realm of computer security, the username/password standard is becoming increasingly antiquated. Usage of the same username and password across various accounts can leave a user open to potential vulnerabilities. Authentication methods of the future need to maintain the ability to provide secure access without a reduction in speed. Facial recognition technologies are quickly becoming integral parts of user security, allowing for a secondary level of user authentication. Augmenting traditional username and password security with facial biometrics has already seen impressive results; however, studying these techniques is necessary to determine how effective these methods are within various parameters. A Convolutional Neural Network (CNN) is a powerful classification approach which is often used for image identification and verification. Quite recently, CNNs have shown great promise in the area of facial image recognition. The comparative study proposed in this paper offers an in-depth analysis of several state-of-the-art deep learning based-facial recognition technologies, to determine via accuracy and other metrics which of those are most effective. In our study, VGG-16 and VGG-19 showed the highest levels of image recognition accuracy, as well as F1-Score. The most favorable configurations of CNN should be documented as an effective way to potentially augment the current username/password standard by increasing the current method’s security with additional facial biometrics.
Fruit and Agro-Industrial Waste Extracts as Potential Antimicrobials in Meat Products: A Brief Review
Authors: Gonçalves Leticia Aline , Lorenzo José M. , Trindade Marco Antonio
Published: June 2021

The use of antimicrobials in meat products is essential for maintaining microbiological stability. The reformulation by substituting synthetic additives for natural ones is an alternative to provide cleaner label products. Therefore, this work performed a literature search about extracts from fruits and agro-industrial waste with antimicrobial activity that can be applied in meat products. Jabuticaba waste extracts are excellent sources of anthocyanins with antimicrobial and pigmentation potential, capable of being applied in meat products such as fresh sausage, without compromising sensory attributes. Residue from grapes is rich in antimicrobial phytochemicals, mainly catechins, epicatechins, gallic acid and procyanidins. Extracts from different grape by-products and cultivars showed inhibition of Staphylococcus aureus, Listeria monocytogenes, Pseudomonas aeruginosa, Escherichia coli O157: H7 and other bacterial strains. Antimicrobial effects against L. monocytogenes, Bacillus cereus, S. aureus and E. coli O157: H7 were identified in Opuntia extracts. In addition, its application in hamburgers reduced (p < 0.05) aerobic mesophilic bacteria, Enterobacteriaceae and Pseudomonas sp. counts, and at a concentration of 2.5%, improved the microbiological stability of salami without causing sensory and texture changes. These data reinforce the possibility of substituting synthetic preservatives for natural versions, a growing trend that requires researching effective concentrations to maintain the sensory and technological properties.
Evaluation of Lactose Oxidase as an Enzyme-Based Antimicrobial for Control of L. monocytogenes in Fresh Cheese
Authors: Flynn Brenna , deRiancho Dana , Lawton Marie R. , Alcaine Samuel D.
Published: June 2021

Listeria monocytogenes is a ubiquitous pathogen that can cause morbidity and mortality in the elderly, immune compromised, and the fetuses of pregnant women. The intrinsic properties of fresh cheese—high water activity (aW), low salt content, and near-neutral pH—make it susceptible to L. monocytogenes contamination and growth at various points in the production process. The aim of this study was to investigate the ability of lactose oxidase (LO), a naturally derived enzyme, to inhibit the growth of L. monocytogenes in fresh cheese during various points of the production process. Lab-scale queso fresco was produced and inoculated with L. monocytogenes at final concentrations of 1 log CFU/mL and 1 CFU/100 mL. LO and LO sodium thiocyanate (TCN) combinations were incorporated into the milk or topically applied to the finished cheese product in varying concentration levels. A positive control and negative control were included for all experiments. When L. monocytogenes was inoculated into the milk used for the cheese-making process, by day 28, the positive control grew to above 7 log CFU/g, while the 0.6 g/L treatment (LO and LO + TCN) fell below the limit of detection (LOD) of 1.3 log CFU/g. In the lower inoculum, the positive control grew to above 7 log CFU/g, and the treatment groups fell below the LOD by day 21 and continued through day 28 of storage. For surface application, outgrowth occurred with the treatments in the higher inoculum, but some inhibition was observed. In the lower inoculum, the higher LO and LO-TCN concentrations (0.6 g/L) reduced L. monocytogenes counts to below the LOD, while the control grew out to above 7 log CFU/g, which is a >5 log difference between the control and the treatment. These results suggest that LO could be leveraged as an effective control for L. monocytogenes in a fresh cheese.
Silage Fermentation on Sweet Sorghum Whole Plant for Fen-Flavor Baijiu
Authors: Li Hongshen , Han Xinglin , Liu Hongrui , Hao Jianqin , Jiang Wei , Li Shizhong
Published: June 2021

The technology for producing bioethanol from sweet sorghum stalks by solid-state fermentation has developed rapidly in recent years, and has many similarities with traditional Chinese liquor production. However, the product from sweet sorghum stalks was lacking in volatile flavors, and the level of harmful contents were uncertain, therefore it could not be sold as liquor. In this study, the protein, fat, and tannin in the clusters and leaves of sweet sorghum were utilized to increase the content of flavor compounds in the ethanol product through the anaerobic fermentation of Saccharomyces cerevisiae. Meanwhile, the silage fermentation method was used to extend the preservation time of the raw materials and to further enhance the flavors of Fen-flavor liquor, with ethyl acetate as the characteristic flavor. The effects of different feedstock groups on ethyl acetate, ethyl lactate, methanol, acetaldehyde, acetal, fusel oil, total acid, and total ester were evaluated by analyzing the chemical composition of different parts of sweet sorghum and determined by gas chromatograph. The effect of different fermentation periods on the volatile flavor of sweet sorghum Baijiu was evaluated. The yield of the characteristic volatile flavor was increased by the extension of the fermentation time. Sweet sorghum Baijiu with a high ester content can be used as a flavoring liquor, blended with liquor with a shorter fermentation period to prepare the finished Fen-flavor Baijiu, conforming to the Chinese national standard for sale.
Brown Algae Phlorotannins: A Marine Alternative to Break the Oxidative Stress, Inflammation and Cancer Network
Authors: Catarino Marcelo D. , Amarante Sónia J. , Mateus Nuno , Silva Artur M. S. , Cardoso Susana M.
Published: June 2021

According to the WHO, cancer was responsible for an estimated 9.6 million deaths in 2018, making it the second global leading cause of death. The main risk factors that lead to the development of this disease include poor behavioral and dietary habits, such as tobacco use, alcohol use and lack of fruit and vegetable intake, or physical inactivity. In turn, it is well known that polyphenols are deeply implicated with the lower rates of cancer in populations that consume high levels of plant derived foods. In this field, phlorotannins have been under the spotlight in recent years since they have shown exceptional bioactive properties, with great interest for application in food and pharmaceutical industries. Among their multiple bioactive properties, phlorotannins have revealed the capacity to interfere with several biochemical mechanisms that regulate oxidative stress, inflammation and tumorigenesis, which are central aspects in the pathogenesis of cancer. This versatility and ability to act either directly or indirectly at different stages and mechanisms of cancer growth make these compounds highly appealing for the development of new therapeutical strategies to address this world scourge. The present manuscript revises relevant studies focusing the effects of phlorotannins to counteract the oxidative stress–inflammation network, emphasizing their potential for application in cancer prevention and/or treatment.
Effect of Informed Conditions on Sensory Expectations and Actual Perceptions: A Case of Chocolate Brownies Containing Edible-Cricket Protein
Authors: Gurdian Cristhiam E. , Torrico Damir D. , Li Bin , Tuuri Georgianna , Prinyawiwatkul Witoon
Published: June 2021

Currently, many consumers are reluctant to consume edible-cricket protein (ECP). Chocolate brownie (CB) formulations without (WO) and with (W) 6%w/w ECP (CBWO and CBW, respectively) were presented under two informed conditions: formulated without ECP (ECP−) and formulated with ECP+benefits (ECP+). CBWO− (CBWO presented with the “ECP−” claim), CBWO+ (CBWO presented with the “ECP+” claim), CBW− (CBW presented with the “ECP−” claim), and CBW+ (CBW presented with the “ECP+” claim) were evaluated by 210 consumers for expected and actual attribute liking, and after-tasting consumption and purchase intent. Multi-way ANOVA, principal component analysis, and agglomerative clustering examined liking. Cochran-Q tests compared actual-liking profiles, purchase and consumption intent. Before tasting, CBW− obtained the lowest appearance liking, flavor liking was higher for ECP− than for ECP+ for either formulation, and ECP+ decreased aroma and overall liking only for CBWO. After tasting, CBWO had higher liking than CBW (except for aroma) for either informed condition. Regardless of the formulation, ECP− and ECP+ had similar actual liking. Nevertheless, ECP+ prevented negative disconfirmation for both formulations while ECP− decreased texture liking (for CBWO) and all liking (for CBW) upon tasting. Females’ consumption intent was higher for CBWO regardless of the informed condition, but CBW+ achieved a similar purchase intent to CBWO− for both genders.
Microwave Assisted Extraction and Pressurized Liquid Extraction of Sulfated Polysaccharides from Fucus virsoides and Cystoseira barbata
Authors: Dobrinčić Ana , Pedisić Sandra , Zorić Zoran , Jurin Mladenka , Roje Marin , Čož-Rakovac Rozelindra , Dragović-Uzelac Verica
Published: June 2021

Sulfated polysaccharide fucoidan isolated from brown algae shows a wide range of biological activities that are significantly dependent on its chemical composition, which is closely related to the applied technique and extraction parameters. Therefore, the objective of this study was to evaluate the influence of microwave assisted extraction (MAE) and pressurized liquid extraction (PLE) parameters (solvent, temperature, time, and number of cycles) on the Fucus virsoides and Cystoseira barbata polysaccharide yield (%PS) and chemical composition (total sugar, fucose, and sulfate group). The optimal MAE parameters that resulted in the highest polysaccharide extraction from F. virsoides and C. barbata were 0.1 M H2SO4 for 10 min at 80 °C, while the optimal PLE parameters were 0.1 M H2SO4, for two cycles of 15 min at 140 °C. Furthermore, the %PS, chemical structure, molecular properties, and antioxidant activity of the F. virsoides and C. barbata polysaccharide extracts obtained with MAE, PLE, and conventional extraction (CE) performed under previously determinate optimal conditions were compared. PLE resulted in a significantly higher %PS from F. virsoides, while for C. barbata, a similar yield was achieved with CE and PLE, as well as CE and MAE, for both algae. Furthermore, the polysaccharides obtained using PLE had the highest polydispersity index, fucose, and sulfate group content, and the lowest uronic acid content; however their antioxidant activity was lower.
Biosimilar Interchangeability and Emerging Treatment Strategies for Inflammatory Bowel Diseases: A Commentary
Authors: Parrish Richard H.
Published: June 2021

This commentary summarizes a collection of key references published within the last ten years, and identifies pharmacologic research directions to improve treatment access and success through greater biosimilar or “follow-on” biologic utilization combined with other targeted small molecule agents that possess unique pathophysiologic mechanisms for inflammatory bowel diseases (IBD) in adult and pediatric patients. Since they are not identical to the originator or reference biologic agent, all biosimilars are not generically equivalent. However, in the US and other countries, they are considered therapeutically interchangeable if the manufacturer has demonstrated no clinically meaningful differences from the reference product. Comparisons of different clinical initiation and switching scenarios are discussed with reference to interchangeability, immunogenicity, nocebo effect, cost effectiveness, and time courses for discontinuation rates.
Neuropathic Pain in Pancreatic Cancer: An Update of the Last Five Years
Authors: Pezzilli Raffaele
Published: June 2021

Pain is the main symptom of pancreatic cancer (pancreatic ductal adenocarcinoma, PDAC). Pain in pancreatic cancer may be visceral, somatic or neuropathic in origin. Pain is produced by tissue damage, inflammation, ductal obstruction and infiltration. Visceral nociceptive signals caused by damage to the upper abdominal viscera are carried along sympathetic fibers, which travel to the celiac plexus nerves and ganglia, which are found at the T12-L2 vertebral levels, anterolateral to the aorta near the celiac trunk. From here, the signals are transmitted through the splanchnic nerves to the T5-T12 dorsal root ganglia and then on to the higher centers of the central nervous system. Somatic and neuropathic pain may arise from tumor extension into the surrounding peritoneum, retroperitoneum and bones and, in the latter case, into the nerves, such as the lumbosacral plexus. It should also be noted that other types of pain might arise because of therapeutic interventions, such as post-chemoradiation syndromes, which cause mucositis and enteritis. Management with non-steroidal anti-inflammatory agents and narcotics was the mainstay of therapy. In recent years, celiac plexus blocks and neurolysis, as well as intrathecal therapies have been used to control severe pain, at times resulting in a decreased need for drugs, avoiding their unwanted side effects. Pain may impair the patient’s quality of life, negatively affecting patient outcome and resulting in increased psychological stress. Even after recognizing the negative effect of cancer pain on patient overall health, studies have shown that cancer pain is still undertreated. This review focuses on neuropathic pain, which is difficult to handle; thus, the most recent literature was reviewed in order to diagnose neuropathic pain and its management.
The Role of Long Non-Coding RNAs in Trophoblast Regulation in Preeclampsia and Intrauterine Growth Restriction
Authors: Monteiro Lara J. , Peñailillo Reyna , Sánchez Mario , Acuña-Gallardo Stephanie , Mönckeberg Max , Ong Judith , Choolani Mahesh , Illanes Sebastián E. , Nardocci Gino
Published: June 2021

Preeclampsia (PE) and Intrauterine Growth Restriction (IUGR) are two pregnancy-specific placental disorders with high maternal, fetal, and neonatal morbidity and mortality rates worldwide. The identification biomarkers involved in the dysregulation of PE and IUGR are fundamental for developing new strategies for early detection and management of these pregnancy pathologies. Several studies have demonstrated the importance of long non-coding RNAs (lncRNAs) as essential regulators of many biological processes in cells and tissues, and the placenta is not an exception. In this review, we summarize the importance of lncRNAs in the regulation of trophoblasts during the development of PE and IUGR, and other placental disorders.
Uncovering Signals from the Coronavirus Genome
Authors: Canessa Enrique
Published: June 2021

A signal analysis of the complete genome sequenced for coronavirus variants of concern—B.1.1.7 (Alpha), B.1.135 (Beta) and P1 (Gamma)—and coronavirus variants of interest—B.1.429–B.1.427 (Epsilon) and B.1.525 (Eta)—is presented using open GISAID data. We deal with a certain new type of finite alternating sum series having independently distributed terms associated with binary (0,1) indicators for the nucleotide bases. Our method provides additional information to conventional similarity comparisons via alignment methods and Fourier Power Spectrum approaches. It leads to uncover distinctive patterns regarding the intrinsic data organization of complete genomics sequences according to its progression along the nucleotide bases position. The present new method could be useful for the bioinformatics surveillance and dynamics of coronavirus genome variants.