bluuebunny/crossref_metadata_2025 huggingface dataset:
Dietary Concentrate Supplementation Alters Serum Metabolic Profiles Related to Energy and Amino Acid Metabolism in Grazing Simmental Heifers
Authors: Chen Hao , Wang Chunjie , Huasai Simujide , Chen Aorigele
Published: October 2021

Supplementation plays a vital role in the growth performance of grazing heifers. We investigated the effects of maize-based concentrate supplementation on the serum metabolome in grazing heifers. Twenty-four 7-month-old heifers (211.65 ± 4.25 kg BW) were randomly divided into a supplement (SUP) group and a control (CON) group. The results indicated that concentrate supplementation increased the final body weight (BW) of grazing heifers, and the average daily gain (ADG) was 61.5% (P = 0.011) higher in the SUP group than in the CON group. Serum concentrations of total protein (TP), triglyceride (TG), and leptin were higher in the SUP group than in the CON group (p < 0.05). Supplementation increased serum metabolites and amino acids and markedly altered glucose, lipid, and protein metabolism, which contributed to the heifer growth. Furthermore, by multivariate analysis, 45 serum metabolites were identified as significantly different between the two groups. Enrichment analysis revealed that arginine biosynthesis and tryptophan metabolism as well as glycerophospholipid metabolism were significantly enriched between the two groups. We concluded that the growth potential of heifers could be improved by maize-based concentrate supplementation, and the main biological pathways affected were those related to energy and amino acid metabolism.
Severe Inhibition of Long-Chain Acyl-CoA Enoylhydratase (EC 4.2.1.74) in a Newborn Foal Suffering From Atypical Myopathy
Authors: Sander Johannes , Terhardt Michael , Janzen Nils
Published: October 2021

In horses, congenital defects of energy production from long-chain fatty acids have not been described so far. In contrast, inhibition of fatty acid degradation caused by the toxins hypoglycin A and methylenecyclopropylglycine from various maple species are observed frequently. These non-proteinogenic aminoacids are passed on placentally to fetuses or with collostrum or milk to newborn foals. Nevertheless, newborn foals become very rarely symptomatic. Vertical transmission apparently is not sufficient to induce clinical disease without a particular genetic constellation being present. One of these rare cases was investigated here using samples from a mare and her foal. Intoxication by hypoglycin A and methylenecyclopropylglycine is also of interest to human pathology, because these toxins have caused fatal poisonings after consumption of certain fruits many times, especially in children. Maple toxins, their metabolites and some short-chain acyl compounds were quantified by ultrahigh-pressure liquid chromatography/tandem mass spectrometry. An comprehensive spectrum of long-chain acylcarnitines was prepared using electrospray ionization tandem mass spectrometry. Organic acids and acylglycines were determined by gas chromatography mass spectrometry. For evaluation, results of other horses poisoned by maple material as well as unaffected control animals were used. In the serum of the foal, hypoglycin A was detected at a low concentration only. Toxin metabolites reached <3.5% of the mean of a comparison group of horses suffering from atypical myopathy. The spectrum of acylcarnitines indicated enzyme inhibition in short-chain and medium-chain regions typical of acer poisoning, but the measured concentrations did not exceed those previously found in clinically healthy animals after maple consumption. The values were not sufficient to explain the clinical symptoms. In contrast, a remarkably strong enrichment of tetradecenoylcarnitine and hexadecenoylcarnitine was observed. This proves a blockade of the long-chain enoyl-CoA hydratase (EC 4.2.1.74). Vertical transfer of maple toxins to a newborn foal is sufficient for induction of clinical disease only if there is an additional specific reactivity to the active toxins. This was found here in an inhibition of long-chain enoyl-CoA hydratase. Isolated dysfunction of this enzyme has not yet been reported in any species. Further studies are necessary to prove a specific genetic defect.
Evaluation of Features Generated by a High-End Low-Cost Electrical Smart Meter
Authors: Koutroumpina Christina , Sioutas Spyros , Koutroubinas Stelios , Tsichlas Kostas
Published: October 2021

The problem of energy disaggregation is the separation of an aggregate energy signal into the consumption of individual appliances in a household. This is useful, since the goal of energy efficiency at the household level can be achieved through energy-saving policies towards changing the behavior of the consumers. This requires as a prerequisite to be able to measure the energy consumption at the appliance level. The purpose of this study is to present some initial results towards this goal by making heavy use of the characteristics of a particular din-rail meter, which is provided by Meazon S.A. Our thinking is that meter-specific energy disaggregation solutions may yield better results than general-purpose methods, especially for sophisticated meters. This meter has a 50 Hz sampling rate over 3 different lines and provides a rather rich set of measurements with respect to the extracted features. In this paper we aim at evaluating the set of features generated by the smart meter. To this end, we use well-known supervised machine learning models and test their effectiveness on certain appliances when selecting specific subsets of features. Three algorithms are used for this purpose: the Decision Tree Classifier, the Random Forest Classifier, and the Multilayer Perceptron Classifier. Our experimental study shows that by using a specific set of features one can enhance the classification performance of these algorithms.
Screening of Swiss Pig Herds for Hepatitis E Virus: A Pilot Study
Authors: Lienhard Julia , Vonlanthen-Specker Isabelle , Sidler Xaver , Bachofen Claudia
Published: October 2021

Hepatitis E virus (HEV) is an important cause of acute hepatitis in humans worldwide. In industrialised countries, most infections are caused by the zoonotic genotype 3. The main reservoir was found in pigs, with fattening pigs as the main shedders. The aim of this study was to establish a screening tool to detect HEV in pig farms. HEV-positive samples were sequenced using Sanger sequencing. First, different sample materials, including floor swabs, slurry, dust swabs and faeces were tested for HEV. Floor swabs turned out to give the best results and, in the form of sock swabs, were used for the screening of Swiss pig herds. A total of 138 pig farms were tested, with a focus on fattening pigs. Overall, 81 farms (58.8%) were HEV positive. Most sequences belonged to subtype 3h, in which they formed a specific cluster (Swiss cluster). In addition, subtype 3l and two unassigned sequences were detected. As a conclusion, sock swabs were found to be a helpful tool to screen pig herds for HEV and establish a sequence collection that may enable molecular epidemiology and support outbreak investigation and prevention.
DeepFMD: Computational Analysis for Malaria Detection in Blood-Smear Images Using Deep-Learning Features
Authors: Abubakar Aliyu , Ajuji Mohammed , Yahya Ibrahim Usman
Published: October 2021

Malaria is one of the most infectious diseases in the world, particularly in developing continents such as Africa and Asia. Due to the high number of cases and lack of sufficient diagnostic facilities and experienced medical personnel, there is a need for advanced diagnostic procedures to complement existing methods. For this reason, this study proposes the use of machine-learning models to detect the malaria parasite in blood-smear images. Six different features—VGG16, VGG19, ResNet50, ResNet101, DenseNet121, and DenseNet201 models—were extracted. Then Decision Tree, Support Vector Machine, Naïve Bayes, and K-Nearest Neighbour classifiers were trained using these six features. Extensive performance analysis is presented in terms of precision, recall, f-1score, accuracy, and computational time. The results showed that automating the process can effectively detect the malaria parasite in blood samples with an accuracy of over 94% with less complexity than the previous approaches found in the literature.
The Role of Heat Flux in an Idealised Firebreak Built in Surface and Crown Fires
Authors: Khan Nazmul , Moinuddin Khalid
Published: October 2021

The disruptions to wildland fires, such as firebreaks, roads and rivers, can limit the spread of wildfire propagating through surface or crown fire. A large forest can be separated into different zones by carefully constructing firebreaks through modification of vegetation in firebreak regions. However, the wildland fire behaviour can be unpredictable due to the presence of either wind- or buoyancy-driven flow in the fire. In this study, we aim to test the efficacy of an idealised firebreak constructed by unburned vegetation. The physics-based large eddy simulation (LES) simulation is conducted using Wildland–urban interface Fire Dynamic Simulator (WFDS). We have carefully chosen different wind velocities with low to high values, 2.5~12.5 m/s, so the different fire behaviours can be studied. The behaviour of surface fire is studied by Australian grassland vegetation, while the crown fire is represented by placing cone-shaped trees with grass underneath. With varying velocity and vegetation, four values of firebreak widths (Lc), ranging from 5~20 m, is tested for successful break distance needed for the firebreak. For each failure or successful firebreak width, we have assessed the characteristics of fire intensity, mechanism of heat transfer, heat flux, and surface temperature. It was found that with the inclusion of forest trees, the heat release rate (HRR) increased substantially due to greater amount of fuel involved. The non-dimensional Byram’s convective number (NC) was calculated, which justifies simulated heat flux and fire characteristics. For each case, HRR, total heat fluxes, total preheat flux, total preheat radiation and convective heat flux, surface temperature and fire propagation mode are presented in the details. Some threshold heat flux was observed on the far side of the firebreak and further studies are needed to identify them conclusively.
Dynamic Characteristics of the Circulation and Diurnal Spatial Cycle of Outgoing Longwave Radiation in the Different Phases of the Madden–Julian Oscillation during the Formation of the South Atlantic Convergence Zone
Authors: Viana Liviany P. , Manco Jhonatan A. A. , Herdies Dirceu Luis
Published: October 2021

In this work, we verified the formation of the South Atlantic Convergence Zone (SACZ) during the active, unfavorable, and transition phases of the Madden–Julian Oscillation (MJO), as well as the diurnal spatial variability in the estimated Outgoing Longwave Radiation (OLR) data. The real-time multivariate index (RMM) and the composites of meteorological variables were used, along with the temporal average of the estimated OLR data. All the different patterns for the average period of SACZ showed classic behavior: well-organized and with meteorological variables in phases throughout the troposphere. However, some differences were evident in the organization of each phase of the MJO: at 200 hPa, the Bolivian High (BH) was more flattened during the active phase pattern than in the unfavorable and transition phases, being wider and with a wavier trough embedded in the western flow; at medium levels, the subtropical highs appeared more defined and with a very wide trough; the trough supported the frontal systems on the surface and, together with the subtropical highs, concentrated all the moisture in this layer. In the OLR dataset, the formation of the Coast Squall Line (CSL) occurred during SACZ events in the active phase and MJO transition, whereas in the unfavorable phase, this system was not observed.
Preparing Datasets of Surface Roughness for Constructing Big Data from the Context of Smart Manufacturing and Cognitive Computing
Authors: Fattahi Saman , Okamoto Takuya , Ura Sharifu
Published: October 2021

In smart manufacturing, human-cyber-physical systems host digital twins and IoT-based networks. The networks weave manufacturing enablers such as CNC machine tools, robots, CAD/CAM systems, process planning systems, enterprise resource planning systems, and human resources. The twins work as the brains of the enablers; that is, the twins supply the required knowledge and help enablers solve problems autonomously in real-time. Since surface roughness is a major concern of all manufacturing processes, twins to solve surface roughness-relevant problems are needed. The twins must machine-learn the required knowledge from the relevant datasets available in big data. Therefore, preparing surface roughness-relevant datasets to be included in the human-cyber-physical system-friendly big data is a critical issue. However, preparing such datasets is a challenge due to the lack of a steadfast procedure. This study sheds some light on this issue. A state-of-the-art method is proposed to prepare the said datasets for surface roughness, wherein each dataset consists of four segments: semantic annotation, roughness model, simulation algorithm, and simulation system. These segments provide input information for digital twins’ input, modeling, simulation, and validation modules. The semantic annotation segment boils down to a concept map. A human- and machine-readable concept map is thus developed where the information of other segments (roughness model, simulation algorithm, and simulation system) is integrated. The delay map of surface roughness profile heights plays a pivotal role in the proposed dataset preparation method. The successful preparation of datasets of surface roughness underlying milling, turning, grinding, electric discharge machining, and polishing shows the efficacy of the proposed method. The method will be extended to the manufacturing processes in the next phase of this study.
Hypoxic Incubation Conditions for Optimized Manufacture of Tenocyte-Based Active Pharmaceutical Ingredients of Homologous Standardized Transplant Products in Tendon Regenerative Medicine
Authors: Jeannerat Annick , Peneveyre Cédric , Armand Florence , Chiappe Diego , Hamelin Romain , Scaletta Corinne , Hirt-Burri Nathalie , de Buys Roessingh Anthony , Raffoul Wassim , Applegate Lee Ann , Laurent Alexis
Published: October 2021

Human fetal progenitor tenocytes (hFPT) produced in defined cell bank systems have recently been characterized and qualified as potential therapeutic cell sources in tendon regenerative medicine. In view of further developing the manufacture processes of such cell-based active pharmaceutical ingredients (API), the effects of hypoxic in vitro culture expansion on key cellular characteristics or process parameters were evaluated. To this end, multiple aspects were comparatively assessed in normoxic incubation (i.e., 5% CO2 and 21% O2, standard conditions) or in hypoxic incubation (i.e., 5% CO2 and 2% O2, optimized conditions). Experimentally investigated parameters and endpoints included cellular proliferation, cellular morphology and size distribution, cell surface marker panels, cell susceptibility toward adipogenic and osteogenic induction, while relative protein expression levels were analyzed by quantitative mass spectrometry. The results outlined conserved critical cellular characteristics (i.e., cell surface marker panels, cellular phenotype under chemical induction) and modified key cellular parameters (i.e., cell size distribution, endpoint cell yields, matrix protein contents) potentially procuring tangible benefits for next-generation cell manufacturing workflows. Specific proteomic analyses further shed some light on the cellular effects of hypoxia, potentially orienting further hFPT processing for cell-based, cell-free API manufacture. Overall, this study indicated that hypoxic incubation impacts specific hFPT key properties while preserving critical quality attributes (i.e., as compared to normoxic incubation), enabling efficient manufacture of tenocyte-based APIs for homologous standardized transplant products.
Multimodal Imaging-Based Potential Visualization of the Tumor Microenvironment in Bone Metastasis
Authors: Moon Jang Bae , Yoo Su Woong , Lee Changho , Kim Dong-Yeon , Pyo Ayoung , Kwon Seong Young
Published: October 2021

Bone metastasis (BM) is the most common malignant bone tumor and a significant cause of morbidity and mortality for patients with cancer. Compared to other metastatic organs, bone has unique characteristics in terms of the tumor microenvironment (TME). Precise assessments of the TME in BM could be an important step for developing an optimized management plan for patient care. Imaging approaches for BM have several advantages, such as biopsy not being required, multiple site evaluation, and serial assessment in the same sites. Owing to the developments of new imaging tracers or imaging modalities, bone TME could be visualized using multimodal imaging techniques. In this review, we describe the BM pathophysiology, diagnostic principles of major imaging modalities, and clinically available imaging modalities to visualize the TME in BM. We also discuss how the interactions between various factors affecting the TME could be visualized using multimodal imaging techniques.
Squaraine-Based Optical Sensors: Designer Toolbox for Exploring Ionic and Molecular Recognitions
Authors: Ta Daniel D. , Dzyuba Sergei V.
Published: October 2021

Small molecule-based chromogenic and fluorogenic probes play an indispensable role in many sensing applications. Ideal optical chemosensors should provide selectivity and sensitivity towards a variety of analytes. Synthetic accessibility and attractive photophysical properties have made squaraine dyes an enticing platform for the development of chemosensors. This review highlights the versatility of modular assemblies of squaraine-based chemosensors and chemodosimeters that take advantage of the availability of various structurally and functionally diverse recognition motifs, as well as utilizing additional recognition capabilities due to the unique structural features of the squaraine ring.
Changing Admission Patterns in Pediatric Emergency Departments during the COVID-19 Pandemic in Italy Were Due to Reductions in Inappropriate Accesses
Authors: Rabbone Ivana , Tagliaferri Francesco , Carboni Elena , Crotti Beatrice , Ruggiero Jessica , Monzani Alice , Bonetti Lorenza , Soliani Martina , Bellone Simonetta , Cavalli Claudio , Scaramuzza Andrea E.
Published: October 2021

During the initial phase of the national lockdown, we found that there were sharp decreases in admissions to two pediatric emergency departments (EDs) in northern Italy (Cremona and Novara). Here we present a detailed analysis of these admission patterns and types of admissions over a longer timeframe. ED admissions data were anonymously extracted from the departmental management software. Admissions data from 2019 and 2020 were analyzed and compared separately for each ED and combined. There was a 73.2% decrease in total admissions compared with the same period in 2019. With respect to admission diagnoses, there was a significant (p < 0.001) drop in infectious (−51%), respiratory (−25.5%), and nervous systems diseases (−50%) and injuries and poisoning (−17%) but not endocrine, metabolic, neoplastic, circulatory, or musculoskeletal diseases. White codes (patients with minor injuries for whom ED medical care is not required) significantly decreased by 56.3% (p < 0.001). Even if the COVID-19 pandemic represented an enormous healthcare burden in Italy, especially during the first months of the pandemic (late February to May), the workload of pediatric EDs was significantly reduced, especially for unnecessary accesses (white codes).
Thin Al2O3 Coatings Produced by Electrochemical Method, Subjected to Thermo-Chemical Treatment
Authors: Niedźwiedź Mateusz , Skoneczny Władysław , Bara Marek , Dercz Grzegorz
Published: October 2021

The article presents the effect of the anodizing parameters, as well as the thermo-chemical treatment, of Al2O3 layers produced on an aluminum alloy on the characterization of structure, geometrical structure of the surface (SGS), the thickness of the oxide layers, the phase composition, and their microhardness. The oxide layers were produced by the method of direct current anodizing in a three-component electrolyte. Then, thermo-chemical treatment was carried out in distilled water and aqueous solutions of sodium dichromate and sodium sulphate. The anodizing parameters and compounds for the thermo-chemical treatment were selected on the basis of Hartley’s plans. The research showed the effect of anodizing parameters on the thickness of the Al2O3 layers and the increase in the thickness of the layers as a result of the thermo-chemical treatment. The research showed a significant increase in the microhardness of the layers as a result of thermo-chemical treatment and its influence on the phase composition of Al2O3 layers. A significant influence of the thermo-chemical treatment on the geometrical structure of the surface was also found.
Investigating Deep Learning Approaches on the Security Analysis of Cryptographic Algorithms
Authors: Chong Bang Yuan , Salam Iftekhar
Published: October 2021

This paper studies the use of deep learning (DL) models under a known-plaintext scenario. The goal of the models is to predict the secret key of a cipher using DL techniques. We investigate the DL techniques against different ciphers, namely, Simplified Data Encryption Standard (S-DES), Speck, Simeck and Katan. For S-DES, we examine the classification of the full key set, and the results are better than a random guess. However, we found that it is difficult to apply the same classification model beyond 2-round Speck. We also demonstrate that DL models trained under a known-plaintext scenario can successfully recover the random key of S-DES. However, the same method has been less successful when applied to modern ciphers Speck, Simeck, and Katan. The ciphers Simeck and Katan are further investigated using the DL models but with a text-based key. This application found the linear approximations between the plaintext–ciphertext pairs and the text-based key.
Prototype Development of Cross-Shaped Microphone Array System for Drone Localization Based on Delay-and-Sum Beamforming in GNSS-Denied Areas
Authors: Madokoro Hirokazu , Yamamoto Satoshi , Watanabe Kanji , Nishiguchi Masayuki , Nix Stephanie , Woo Hanwool , Sato Kazuhito
Published: October 2021

Drones equipped with a global navigation satellite system (GNSS) receiver for absolute localization provide high-precision autonomous flight and hovering. However, the GNSS signal reception sensitivity is considerably lower in areas such as those between high-rise buildings, under bridges, and in tunnels. This paper presents a drone localization method based on acoustic information using a microphone array in GNSS-denied areas. Our originally developed microphone array system comprised 32 microphones installed in a cross-shaped configuration. Using drones of two different sizes and weights, we obtained an original acoustic outdoor benchmark dataset at 24 points. The experimentally obtained results revealed that the localization error values were lower for 0∘ and ±45∘ than for ±90∘. Moreover, we demonstrated the relative accuracy for acceptable ranges of tolerance for the obtained localization error values.
An Analysis of the Operation of Distribution Networks Using Kernel Density Estimators
Authors: Kornatka Mirosław , Gawlak Anna
Published: October 2021

Efficiency in the operation of distribution networks is one of the commonly recognised goals of the Smart Grid aspect. Novel approaches are needed to assess the level of energy loss and reliability in electricity distribution. Transmission of electricity in the power system is invariably accompanied by certain physical phenomena and random events causing losses. Identifying areas where excessive energy losses or excessive grid failure occur is a key element for energy companies in resource management. The study presented in the article is based on data obtained from distribution system operators concerning 41 distribution regions in Poland for a period of 5 years. The first part of the article presents an analysis of the distribution of values for the introduced energy density and energy losses in the lines of medium- and low-voltage networks and in transformers supplying the low-voltage network. The second part of the article presents the assessment of the network reliability of the same distribution regions based on analysis of the distributions of System Average Interruption Duration Index (SAIDI) and System Average Interruption Frequency Index (SAIFI) values for planned and unplanned outages. Data analysis is performed by non-parametric methods by means of kernel estimators.
Overview of Possibilities of Solar Floating Photovoltaic Systems in the OffShore Industry
Authors: Vo Thi Thu Em , Ko Hyeyoung , Huh Junho , Park Namje
Published: October 2021

The demand for energy has rapidly grown around the world. Solar floating photovoltaic (FPV) systems are an efficient solution to solve the issues from nonrenewable energy sources, such as reduction of CO2 emission, limitation of global warming, environmentally friendly, a great innovation in sustainable aquaculture, and a new ecofriendly technique, along with reducing production costs, especially regarding the scarcity of habitable land. A large number of installation projects using FPV technology have been operated in water bodies such as lakes and dams/reservoirs. However, deployment of FPV offshore is still limited because of the existing characteristics of marine/sea environments that are different from onshore, such as wind loads and wave loads. Despite these difficulties, there are several projects that have been installed in some countries and gained many significant achievements. It opened possibilities to apply FPV systems offshore worldwide. In this review, we present a brief overview of FPV systems both onshore and offshore, analyze advantages and disadvantages of offshore FPV systems, and provide an overview of their future.
Research on Test and Logging Data Quality Classification for Gas–Water Identification
Authors: Xiang Zehou , Li Kesai , Deng Hucheng , Liu Yan , He Jianhua , Zhang Xiaoju , He Xianhong
Published: October 2021

Tight sandstone oil and gas reservoirs are widely distributed, rich in resources, with a bright prospect for exploration and development in China. Due to multiple evolutions of the structure and sedimentary system, the gas–water distribution laws are complicated in tight sandstone gas reservoirs in the northern Ordos area. It is difficult to identify gas and water layers in the study area. In addition, in the development and production, various factors, such as the failure of the instrument, the difference in construction parameters (injected sand volume, flowback rate), poor test results, and multi-layer joint testing lead to unreliable gas test results. Then, the inaccurate logging responses will be screened by unreliable gas test results for different types of fluids. It is hard to make high-precision fluid logging identification charts or models. Therefore, this article combines gas logging, well logging, testing and other data to research the test and logging data quality classification. Firstly, we select reliable standard samples through the initial gas test results. Secondly, we analyze the four main factors which affect the inaccuracy of gas test results. Thirdly, according to these factors, the flowback rate and the sand volume are determined as the main parameters. Then, we establish a recognition chart of injected sand volume/gas–water ratio. Finally, we proposed an evaluation method for testing quality classification. It provides a test basis for the subsequent identification of gas and water through the second logging interpretation. It also provides a theoretical basis for the exploration and evaluation of tight oil and gas reservoirs.
Biocrude Oil Production by Integrating Microalgae Polyculture and Wastewater Treatment: Novel Proposal on the Use of Deep Water-Depth Polyculture of Mixotrophic Microalgae
Authors: Watanabe Makoto M. , Isdepsky Andreas
Published: October 2021

Microalgae have attracted significant attention worldwide as one of the most promising feedstock fossil fuel alternatives. However, there are a few challenges for algal fuels to compete with fossil fuels that need to be addressed. Therefore, this study reviews the R&D status of microalgae-based polyculture and biocrude oil production, along with wastewater treatment. Mixotrophic algae are free to some extent from light restrictions using organic matter and have the ability to grow well even in deep water-depth cultivation. It is proposed that integrating the mixotrophic microalgae polyculture and wastewater treatment process is the most promising and harmonizing means to simultaneously increase capacities of microalgae biomass production and wastewater treatment with a low land footprint and high robustness to perturbations. A large amount of mixotrophic algae biomass is harvested, concentrated, and dewatered by combining highly efficient sedimentation through flocculation and energy efficient filtration, which reduce the carbon footprint for algae fuel production and coincide with the subsequent hydrothermal liquefaction (HTL) conversion. HTL products are obtained with a relatively low carbon footprint and separated into biocrude oil, solid, aqueous, and gas fractions. Algae biomass feedstock-based HTL conversion has a high biocrude oil yield and quality available for existing oil refineries; it also has a bioavailability of the recycled nitrogen and phosphorus from the aqueous phase of algae community HTL. The HTL biocrude oil represents higher sustainability than conventional liquid fuels and other biofuels for the combination of greenhouse gas (GHG) and energy return on investment (EROI). Deep water-depth polyculture of mixotrophic microalgae using sewage has a high potential to produce sustainable biocrude oil within the land area of existing sewage treatment plants in Japan to fulfill imported crude oil.
Biomass Clusterization from a Regional Perspective: The Case of Lithuania
Authors: Svazas Mantas , Navickas Valentinas , Bilan Yuriy , Nakonieczny Joanna , Spankova Jana
Published: October 2021

The usage of renewable resources has become inseparable from the further development of the world economy. To preserve a clean environment for future generations, the use of renewable resources is becoming inevitable even in less developed countries. Recently, the world is facing with challenges in securing green heat production. This situation allows the biomass energy sector to develop. Biomass extracted from waste enables to produce green energy, while contributing to the sustainable development of forestry. One of the major constraints on the usage of biomass is the complex and multifaceted supply chain involving different business subjects. Compatibility problems with different interests can be solved by operating in a cluster structure. Cluster activities allow for more efficient use of limited resources. It allows to create added value for the region and society. Due to the specificity of biomass energy, there is an opportunity to create regional business units that would involve human resources and solves long-standing social problems. The aim of the study is to show the progress of Lithuanian regions in using biomass resources for heat energy production. With the assistance of cluster analysis, it is performed based on economic, social, and environmental data of Lithuanian regions.
Microbial Contamination Survey of Environmental Fresh and Saltwater Resources of Upolu Island, Samoa
Authors: Ochsenkühn Michael A. , Fei Cong , Bayaara Odmaa , Romeo Emarosa , Amosa Patila , Idaghdour Youssef , Goldstein Gary , Bromage Timothy G. , Amin Shady A.
Published: October 2021

Analysis of microbe diversity in freshwater resources and nearshore seawater samples of Upolu Island was performed to investigate the distribution of harmful bacteria. For this, 124 samples were collected from 23 river systems, two volcanic lakes, and 45 locations inside and outside the barrier reef of Upolu Island, Samoa. Physicochemical parameters for general water quality, detection of coliform bacteria and 16S rRNA amplicon sequencing were performed on all samples. Fecal indicator bacteria (FIB) testing indicated a wide distribution of coliform bacteria in all sampled freshwater sites with evidence of fecal coliform in most locations. Importantly, evidence of coliform bacteria was found in most seawater samples inside and along the reef, apart from those samples taken ~20 km offshore. Illumina 16S rRNA amplicon sequencing of the V4 hypervariable region confirmed the presence of various types of harmful bacterial species, namely from the Enterobacteriaceae, Enterococcae, Streptococcaceae, and Vibrionacea families. By combining the sensitivity of FIB testing and next-generation sequencing, we were able to show the extent of potential contaminations in fresh and seawater samples and simultaneously identify the potential pathogenic bacterial genera present. The wide distribution of potential harmful bacteria from river runoff or direct sewage dumping has an impact on human health, leading to many skin and intestinal diseases, and is potentially detrimental to coral reef community health.
Fragmentation and Coordination of REDD+ Finance under the Paris Agreement Regime
Authors: Kim Dong-hwan , Kim Do-hun , Kim Hyun Seok , Kim Raehyun
Published: October 2021

Under the Kyoto Protocol regime, various forms of financial support have been committed to helping the implementation of reducing emissions from deforestation and forest degradation, as well as fostering conservation, the sustainable management of forests, and the enhancement of forest carbon stocks (REDD+) in developing countries. We analyzed the fragmentation of REDD+ finance and suggested methods for its coordination under the Paris Agreement regime. The fragmentation of REDD+ finance was observed, but it was lower than that of general official development assistance (ODA). However, we found that the trend of fragmentation in REDD+ financing is different from that of general ODA, with a few major donors occupying a large portion of the total size of committed REDD+ finance. Thus, it may not be appropriate to consider the fragmentation of REDD+ finance merely as an obstacle that needs to be decreased. Still, the total amount of REDD+ finance should be increased and adjusted for various donor–recipient relationships, in consideration of the REDD+ finance options in the Paris Agreement. Some REDD+ countries have made progress in national REDD+ and accomplished emission reductions. However, REDD+ finance needs to be stratified considering the progress of national REDD+. For such forms of cooperation, an information-sharing and monitoring system that collects information on ongoing REDD+ cooperation, the commitment and expenditure of REDD+ finance, and the support needs of REDD+ countries at a global level should be established. Multilateral organizations need to provide safeguarding functions for developing countries that are isolated from bilateral REDD+ finance.
Multi-Level Genetic Variation and Selection Strategy of Neolamarckia cadamba in Successive Years
Authors: Que Qingmin , Li Chunmei , Li Buye , Song Huiyun , Li Pei , Pian Ruiqi , Li Huaqing , Chen Xiaoyang , Ouyang Kunxi
Published: October 2021

Neolamarckia cadamba (Roxb.) Bosser is a tropical evergreen broadleaf tree species that could play an important role in meeting the increasing demand for wood products. However, multi-level genetic variation and selection efficiency for growth traits in N. cadamba is poorly characterized. We therefore investigated the efficiency of early selection in N. cadamba by monitoring the height (HT), diameter at breast height (DBH), and tree volume (V) in 39 half-sib families from 11 provenances at ages 2, 3, 4, 5, and 6 years in a progeny test. Age-related trends in growth rate, genetic parameters in multi-level, efficiency of early selection, and realized gain in multi-level for growth traits were analyzed. The result showed that genetic variation among families within provenances was higher than that among provenances. The estimated individual heritability values for the growth traits ranged from 0.05 to 0.26, indicating that the variation of growth traits in N. cadamba was subject to weak or intermediate genetic control. The age–age genetic correlations for growth traits were always positive and high (0.51–0.99), and the relationships between the genetic/phenotypic correlations and the logarithm of the age ratio (LAR) were described well by linear models (R2 > 0.85, except the fitting coefficient of genetic correlation and LAR for HT was 0.35). On the basis of an early selection efficiency analysis, we found that it is the best time to perform early selection for N. cadamba at age 5 before half-rotation, and the selection efficiencies were 157.28%, 151.56%, and 127.08% for V, DBH, and HT, respectively. Higher realized gain can be obtained by selecting superior trees from superior families. These results can be expected to provide theoretical guidance and materials for breeding programs in N. cadamba and can even be a reference for breeding strategies of other fast-growing tree species.
A Comparison of Ansys Fluent and MFiX in Performing CFD-DEM Simulations of a Spouted Bed
Authors: Marchelli Filippo , Di Felice Renzo
Published: October 2021

The CFD-DEM methodology is a popular tool for the study of fluid–particle systems, and there are several programs that permit using it. In this study, we employed it to simulate a pseudo-2D spouted bed, comparing the performance of the programs Ansys Fluent and MFiX. The results are analysed and commented on in terms of both accuracy and computational efforts. Despite the similarity of the setup, MFiX seems to perform significantly better. The similarities and differences between the two programs are discussed in detail, offering useful insights to researchers regarding the selection of one over the other, depending on the application. The better suitability of the Di Felice drag model is confirmed for the device, while it is shown that the effect of the Magnus lift force may be more limited than was shown in a previous study.
Contribution of Microorganisms to Biogenic Amine Accumulation during Fish Sauce Fermentation and Screening of Novel Starters
Authors: Ma Xinxiu , Bi Jingran , Li Xinyu , Zhang Gongliang , Hao Hongshun , Hou Hongman
Published: October 2021

In this study, high-throughput sequencing and culture-dependent and HPLC methods were used to investigate the contribution and regulation of biogenic amines (BAs) by dominant microorganisms during fish sauce fermentation. The results showed that the microbial composition constantly changed with the fermentation of fish sauce. Tetragenococcus (40.65%), Lentibacillus (9.23%), Vagococcus (2.20%), Psychrobacter (1.80%), Pseudomonas (0.98%), Halomonas (0.94%) and Staphylococcus (0.16%) were the dominant microflora in fish sauce. The content of BAs gradually increased as the fermentation progressed. After 12 months of fermentation, the histamine content (55.59 mg/kg) exceeded the toxic dose recommended by the Food and Drug Administration (FDA). Correlation analysis showed that dominant microorganisms have a great contribution to the accumulation of BAs. By analyzing the BA production capacity of dominant isolates, the accumulation of BAs in fish sauce might be promoted by Tetragenococcus and Halomonas. Moreover, four strains with high BA reduction ability were screened out of 44 low BA-producing dominant strains, and their influence on BA accumulation in fermented foods was determined. Results demonstrated that Staphylococcus nepalensis 5-5 and Staphylococcus xylosus JCM 2418 might be the potential starters for BA control. The present study provided a new idea for the control of BAs in fermented foods.
Antihypertensive Peptides from Ultrafiltration and Fermentation of the Ricotta Cheese Exhausted Whey: Design and Characterization of a Functional Ricotta Cheese
Authors: Pontonio Erica , Montemurro Marco , De Gennaro Gina Valeria , Miceli Valerio , Rizzello Carlo Giuseppe
Published: October 2021

Aiming at valorizing the ricotta cheese exhausted whey (RCEW), one of the most abundant by-products from the dairy industry, a biotechnological protocol to obtain bioactive peptides with angiotensin-I-converting enzyme (ACE)—inhibitory activity was set up. The approach was based on the combination of membrane filtration and fermentation. A Lactobacillus helveticus strain selected to be used as starter for the fermentation of the ultrafiltration protein-rich retentate (R-UF) obtained from RCEW. The fermented R-UF was characterized by a high anti-ACE activity. Peptides responsible for the bioactivity were purified and identified through nano-LC–ESI–MS/MS. The sequences identified in the purified active fractions of the fermented R-UF showed partial or complete overlapping with previously reported κ-casein antihypertensive fragments. The fermented R-UF was spray-dried and used to enrich ricotta cheese at different fortification level (1 and 5% w/w). An integrated approach including the assessment of the microbiological, chemical, functional, textural, and sensory properties was used to characterize the fortified products. A significantly higher anti-ACE activity was found in the ricotta cheese fortified with fermented R-UF as compared to the control and to the samples obtained with the unfermented R-UF fraction at the same levels of fortification. In particular, a 100 g portion of the ricotta cheese produced at 5% fortification level contained circa 30 mg of bioactive peptides. The fortification led to a moderate acidification, increased hardness and chewiness, and decreased the milk odor and taste of the ricotta cheese as compared to the control, while flavor persistence and sapidity improved.
Hazard Identification Related to the Presence of Vibrio spp., Biogenic Amines, and Indole-Producing Bacteria in a Non-Filter Feeding Marine Gastropod (Tritia mutabilis) Commercialized on the Italian Market
Authors: Serratore Patrizia , Bignami Giorgia , Ostanello Fabio , Lorito Luna
Published: October 2021

Tritia mutabilis is a carrion-feeder edible marine gastropod with an open circulatory system. Therefore, biological, and chemical contaminants associated with the feed can reach all body tissues. The aim of the present study was to investigate the possible association of these characteristics with some food safety hazards. Vibrio spp. load, and the prevalence of pathogenic V. parahaemolyticus, V. vulnificus, and V. cholerae, were investigated. Moreover, biogenic amines (BAs) and indole-producing bacteria (IPB), markers of seafood decomposition, were quantified for the first time in an edible carrion-feeder. Overall, 49 batches were analyzed (38 from retail, and 11 from primary production). The Vibrio spp. load resulted of 5.64 ± 0.69 log10 CFU g−1 at retail, and 5.27 ± 0.74 at harvest but all batches resulted negative for pathogenic Vibrio. Histamine, putrescine, cadaverine, and tyramine were detected both at harvest and at the retail level. Their sum (BAs Index) showed a mean value of 50.45 and 65.83 mg Kg−1 in batches at harvest and at retail, respectively. IPB were detected at harvest and upon refrigeration for three days (T1–T3). The mean load resulted in 2.52 ± 0.85 log10 MPN g−1 at T0, 3.31 ± 1.23 at T3 in batches immediately refrigerated, and 3.22 ± 1.18 at T3 in batches previously immersed in clean seawater. Our results contribute to identifying food-borne hazards for T. mutabilis that may be related to the retention of biogenic amines and indole-producing bacteria due to carrion feeding.
Multivariate Fractal Functions in Some Complete Function Spaces and Fractional Integral of Continuous Fractal Functions
Authors: Pandey Kshitij Kumar , Viswanathan Puthan Veedu
Published: October 2021

There has been a considerable evolution of the theory of fractal interpolation function (FIF) over the last three decades. Recently, we introduced a multivariate analogue of a special class of FIFs, which is referred to as α-fractal functions, from the viewpoint of approximation theory. In the current note, we continue our study on multivariate α-fractal functions, but in the context of a few complete function spaces. For a class of fractal functions defined on a hyperrectangle Ω in the Euclidean space Rn, we derive conditions on the defining parameters so that the fractal functions are elements of some standard function spaces such as the Lebesgue spaces Lp(Ω), Sobolev spaces Wm,p(Ω), and Hölder spaces Cm,σ(Ω), which are Banach spaces. As a simple consequence, for some special choices of the parameters, we provide bounds for the Hausdorff dimension of the graph of the corresponding multivariate α-fractal function. We shall also hint at an associated notion of fractal operator that maps each multivariate function in one of these function spaces to its fractal counterpart. The latter part of this note establishes that the Riemann–Liouville fractional integral of a continuous multivariate α-fractal function is a fractal function of similar kind.
A Double-Weighted Bankruptcy Method to Allocate CO2 Emissions Permits
Authors: Moretti Stefano , Trabelsi Raja
Published: October 2021

Global warming, as a result of greenhouse gases, is exceeding the planet’s temperature stabilization capacities. Thus, greenhouse gas emissions must be reduced. We analyse a bankruptcy situation aimed at allocating emissions permits of CO2, the predominant greenhouse gas emitted by human activities. Inspired by the Constrained Equal Awards (CEA) solution for bankruptcy situations, we introduce a new allocation protocol based on the extension of the CEA solution over double-weighted bankruptcy situations, including two exogenous parameters aimed at providing a balance, in the request of emissions permits, between economic activities and the production of renewable energy. In these bi-criteria allocation problems, we focus on a computational approach to find an allocation protocol that does not prioritize any particular parameter. As an application of our method, we first consider CO2 permit allocation problems in European Union (EU) countries, using real data about the gross domestic product (GDP), the production rate of renewable energies, and countries’ ‘demands’ of CO2 emissions from 2010 to 2014. Then, we compare our approach with the CEA solution and its single-weighted extension to show the impact of using two weights over the distribution of CO2 emissions permits; we analyse the correlation between allocations of CO2 emission permits and the distribution of power within the EU Council to study the acceptability of alternative allocations.