bluuebunny/crossref_metadata_2025 huggingface dataset:
New Cell Lines Derived from European Tick Species
Authors: Bell-Sakyi Lesley , Hartley Catherine S. , Khoo Jing Jing , Forth Jan Hendrik , Palomar Ana M. , Makepeace Benjamin L.
Published: May 2022

Tick cell lines are important tools for research on ticks and the pathogens they transmit. Here, we report the establishment of ten new cell lines from European ticks of the genera Argas, Dermacentor, Hyalomma, Ixodes and Rhipicephalus originating from Germany and Spain. For each cell line, the method used to generate the primary culture, a morphological description of the cells and species confirmation by sequencing of the partial 16S rRNA gene are presented. Further molecular analysis of the two new Ixodes ricinus cell lines and three existing cell lines of the same species revealed genetic variation between cell lines derived from ticks collected in the same or nearby locations. Collectively, these new cell lines will support research into a wide range of viral, bacterial and protozoal tick-borne diseases prevalent in Europe.
Non-Coding RNAs in Rheumatoid Arthritis: Implications for Biomarker Discovery
Authors: Castañeda-Delgado Julio Enrique , Macias-Segura Noé , Ramos-Remus Cesar
Published: May 2022

Recent advances in gene expression analysis techniques and increased access to technologies such as microarrays, qPCR arrays, and next-generation sequencing, in the last decade, have led to increased awareness of the complexity of the inflammatory responses that lead to pathology. This finding is also the case for rheumatic diseases, importantly and specifically, rheumatoid arthritis (RA). The coincidence in major genetic and epigenetic regulatory events leading to RA’s inflammatory state is now well-recognized. Research groups have characterized the gene expression profile of early RA patients and identified a group of miRNAs that is particularly abundant in the early stages of the disease and miRNAs associated with treatment responses. In this perspective, we summarize the current state of RNA-based biomarker discovery and the context of technology adoption/implementation due to the COVID-19 pandemic. These advances have great potential for clinical application and could provide preclinical disease detection, follow-up, treatment targets, and biomarkers for treatment response monitoring.
Biological and Pharmacological Properties of Carbon Monoxide: A General Overview
Authors: Bilska-Wilkosz Anna , Górny Magdalena , Iciek Małgorzata
Published: May 2022

Carbon monoxide (CO) is one of the most common causes of inhalation poisoning worldwide. However, it is also well known that CO is produced endogenously in the heme degradation reaction catalyzed by heme oxygenase (HO) enzymes. HO catalyzes the degradation of heme to equimolar quantities of CO, iron ions (Fe2+), and biliverdin. Three oxygen molecules (O2) and the electrons provided by NADPH-dependent cytochrome P450 reductase are used in the reaction. HO enzymes comprise three distinct isozymes: the inducible form, heme oxygenase-1 (HO-1); the constitutively expressed isozyme, heme oxygenase-2 (HO-2); and heme oxygenase-3 (HO-3), which is ubiquitously expressed but possesses low catalytic activity. According to some authors, HO-3 is rather a pseudogene originating from the HO-2 transcript, and it has only been identified in rats. Therefore, cellular HO activity is provided by two major isoforms—the inducible HO-1 and the constitutively expressed HO-2. For many years, endogenously generated CO was treated as a by-product of metabolism without any serious physiological or biochemical significance, while exogenous CO was considered only as an extremely toxic gas with lethal effects. Research in recent years has proven that endogenous and exogenous CO (which may be surprising, given public perceptions) acts not only as an agent that affects many intracellular pathways, but also as a therapeutic molecule. Hence, the modulation of the HO/CO system may be one option for a potential therapeutic strategy. Another option is the administration of CO by exogenous inhalation. As alternatives to gas administration, compounds known as CO-releasing molecules (CORMs) can be administered, since they can safely release CO in the body. The aim of this article is to provide a brief overview of the physiological and biochemical properties of CO and its therapeutic potential.
In Silico, In Vitro, and Pharmacokinetic Studies of UBMC-4, a Potential Novel Compound for Treating against Trypanosoma cruzi
Authors: Bustamante Christian , Díez-Mejía Andrés Felipe , Arbeláez Natalia , Soares Maurilio José , Robledo Sara M. , Ochoa Rodrigo , Varela-M. Rubén E. , Marín-Villa Marcel
Published: May 2022

The lack of therapeutic alternatives for the treatment of Chagas disease, a neglected disease, drives the discovery of new drugs with trypanocidal activity. Consequently, we conducted in vitro studies using UBMC-4, a potential Trypanosoma cruzi AKT-like pleckstrin homology (PH) domain inhibitory compound found using bioinformatics tools. The half effective concentration (EC50) on intracellular amastigotes was determined at 1.85 ± 1 μM showing low cytotoxicity (LC50) > 40 μM on human cell lines tested. In order to study the lethal effect caused by the compound on epimastigotes, morphological changes were assessed by scanning and transmission electron microscopy. Progressive alterations such as flagellum inactivation, cell size reduction, nuclear structure alteration, condensation of chromatin towards the nuclear periphery, vacuole formation, and mitochondrial swelling with kinetoplast integrity loss were evidenced. In addition, apoptosis-like markers in T. cruzi were assessed by flow cytometry, demonstrating that the effect of UBMC-4 on T. cruzi AKT-like kinase reduced the tolerance to nutritional stress-triggered, apoptosis-like events, including DNA fragmentation, mitochondrial damage, and loss of plasma membrane integrity. After this, UBMC-4 was formulated for oral administration and pharmacokinetics were analyzed in a mouse model. Finally, upon oral administration of 200 mg/kg in mice, we found that a UBMC-4 plasma concentration remaining in circulation beyond 24 h after administration is well described by the two-compartment model. We conclude that UBMC-4 has an effective trypanocidal activity in vitro at low concentrations and this effect is evident in T. cruzi cell structures. In mice, UBMC-4 was well absorbed and reached plasma concentrations higher than the EC50, showing features that would aid in developing a new drug to treat Chagas disease.
Intracranial Aneurysm Rupture after SARS-CoV2 Infection: Case Report and Review of Literature
Authors: Khan Dilaware , Naderi Soheil , Ahmadi Mostafa , Ghorbani Askar , Cornelius Jan Frederick , Hänggi Daniel , Muhammad Sajjad
Published: May 2022

Background: SARS-CoV virus infection results in a dysbalanced and severe inflammatory response with hypercytokinemia and immunodepression. Viral infection triggers systemic inflammation and the virus itself can potentially cause vascular damage, including blood–brain barrier (BBB) disruption and alterations in the coagulation system, which may result in cardiovascular and neurovascular events. Here, we review the literature and present a case of COVID-19 infection leading to an aneurysmal subarachnoid haemorrhage (aSAH). Case Description: A 61-year-old woman presented with dyspnea, cough, and fever. She had a history of hypertension and was overweight with a body mass-index of 34. There was no history of subarachnoid hemorrhage in the family. Due to low oxygen saturation (89%) she was admitted into ICU. A chest CT showed a typical picture of COVID-19 pneumonia. The PCR-based test of an oropharyngeal swab was COVID-19-positive. In addition to oxygen support she was prescribed with favipiravir and hydroxychloroquine. She experienced a sudden headache and lost consciousness on the second day. Computer tomography (CT) with CT-angiography revealed a subarachnoid haemorrhage in the basal cisterns from a ruptured anterior communicating artery aneurysm. The aneurysm was clipped microsurgically through a left-sided standard pterional approach and the patient was admitted again to the intensive care unit for further intensive medical treatment. Post-operatively, the patient showed slight motor dysphasia. No other neurological deficits. Conclusion: Systemic inflammation and ventilator support-associated blood pressure fluctuations may trigger aneurysmal subarachnoid haemorrhage secondary to COVID-19 infection. COVID-19 infection could be considered as one of the possible risk factors leading to instability and rupture of intracranial aneurysm.
A Tunable Resolution Grating Monochromator and the Quest for Transform Limited Pulses
Authors: Nicolas Josep , Cocco Daniele
Published: May 2022

A variable resolution, transform limited monochromator is designed for the Free Electron Laser (FEL) source of LCLS. It provides monochromatic beam in the 250–1500 eV range, delivering the beam on the second floor of the LCLS experimental Hall. One major requirement for this monochromator is to provide, as close as possible, monochromatic transform limited pulses for time-resolved experiments. The theory and the limit of using classical diffraction scheme to monochromatize Soft X-ray beam, while preserving the pulse length, will be presented, together with the optical scheme of this versatile monochromator design.
Deterministic Entanglement Swapping with Hybrid Discrete- and Continuous-Variable Systems
Authors: Yang Shou-Bang , Ning Wen , Zheng Ri-Hua , Yang Zhen-Biao , Zheng Shi-Biao
Published: May 2022

The study of entanglement between discrete and continuous variables is an important theoretical and experimental topic in quantum information processing, for which entanglement swapping is one of the interesting elements. Entanglement swapping allows two particles without interacting with each other in any way, to form an entangled state by the action of another pair of entangled particles. In this paper, we propose an experimentally feasible scheme to realize deterministic entanglement swapping in the hybrid system with discrete and continuous variables. The process is achieved by preparing two pairs of entangled states, each is formed by a qubit and two quasi-orthogonal coherent state elements of a cavity, performing a Bell-state analysis through nonlocal operations on the continuous variable states of the two cavities, and projecting the two qubits into a maximally entangled state. The present scheme may be applied to other physical systems sustaining such hybrid discrete and continuous forms, providing a typical paradigm for entanglement manipulation through deterministic swapping operations.
Improving the Phenolic Content of Tempranillo Grapes by Sustainable Strategies in the Vineyard
Authors: Valdés M. Esperanza , Talaverano M. Inmaculada , Moreno Daniel , Uriarte David , Mancha Luis , Vilanova Mar
Published: May 2022

Wine phenolics are of considerable interest due to their implication in the organoleptic appreciation of wines and due to their bioactive functions as antioxidants. In this work, the effects of sustainable strategies in the vineyard, regulated deficit irrigation treatments (RDI) and crop load level (CL) on Tempranillo grape phenolics over two seasons was studied. Rainfed (T), early (EDI) and late (LDI) regulated deficit irrigation was applied. Cluster thinning (TH) and control (C) without cluster removal were also applied under each irrigation treatment. The effect of CL remained independent of RDI for all compounds, except for phenolic acids. The RDI influence on the grape skin phenolic profile was higher than CL in the dry season (2009); however, in 2010, the effect of CL was greater. In 2009, a tendency to increase anthocyanin and hydroxycinnamic acid content in grape skins was registered in EDI with respect to T. However, significant decreases in hydroxycinnamic and flavanol compounds were found in LDI. In 2010, the wettest year, CL increased all phenolic families’ content. Thus, it can be concluded that the effects of RDI and cluster thinning treatments depend on the family of compounds considered and the meteorological conditions of the year.
Nickel Toxicity Interferes with NO3−/NH4+ Uptake and Nitrogen Metabolic Enzyme Activity in Rice (Oryza sativa L.)
Authors: Rizwan Muhammad , Usman Kamal , Alsafran Mohammed , Jabri Hareb Al , Samreen Tayyaba , Saleem Muhammad Hamzah , Tu Shuxin
Published: May 2022

The excessive use of nickel (Ni) in manufacturing and various industries has made Ni a serious pollutant in the past few decades. As a micronutrient, Ni is crucial for plant growth at low concentrations, but at higher concentrations, it can hamper growth. We evaluated the effects of Ni concentrations on nitrate (NO3−) and ammonium (NH4+) concentrations, and nitrogen metabolism enzyme activity in rice seedlings grown in hydroponic systems, using different Ni concentrations. A Ni concentration of 200 μM significantly decreased the NO3− concentration in rice leaves, as well as the activities of nitrate reductase (NR), nitrite reductase (NiR), glutamine synthetase (GS), and glutamate synthetase (GOGAT), respectively, when compared to the control. By contrast, the NH4+ concentration and glutamate dehydrogenase (GDH) activity both increased markedly by 48% and 46%, respectively, compared with the control. Furthermore, the activity of most active aminotransferases, including glutamic pyruvic transaminase (GPT) and glutamic oxaloacetic transaminase (GOT), was inhibited by 48% and 36%, respectively, in comparison with the control. The results indicate that Ni toxicity causes the enzymes involved in N assimilation to desynchronize, ultimately negatively impacting the overall plant growth.
Development and Application of the New Integrated Equipment and Process of the Nine-Steam-Nine-Bask Method in the Processing of Polygonatum cyrtonema
Authors: Liu Jun , Zhang Zhentao , Huai Xiulan , Wei Yongxing , Zhu Jizhou , Li Xiaoqiong , Xu Peng , Ijabadeniyi Oluwatosin Ademola
Published: May 2022

As a traditional processing method, the Nine-Steam-Nine-Bask method has been widely used in the special processing of Chinese medicinal materials. With the highly integrated design and innovation of infiltrating equipment, steaming equipment, drying equipment, and other equipment, a new type of integrated equipment for the Nine-Steam-Nine-Bask method was finally developed and successfully applied in Polygonatum cyrtonema processing. Moreover, seven new processes were explored. The longer the steaming time was, the more steaming and drying cycles, the lower the product recovery rate and the higher the energy consumption. The higher the steaming pressure was, the lower the product recovery rate, the higher the energy consumption and the shorter the drying time. The longer the drying time was, the lower the product recovery rate and polysaccharide content, and the higher the energy consumption. The best new process was XGY1, which had the highest overall score. The steaming process was the most time-consuming and energy-intensive production process, followed by the drying process. The obtained results can provide knowledgeable guidance for the further optimization of the integrated equipment of the Nine-Steam-Nine-Bask method and the development and application of technology for processing characteristic Chinese medicinal materials.
Cooling Crystallization with Complex Temperature Profiles on a Quasi-Continuous and Modular Plant
Authors: Höving Stefan , Oldach Bastian , Kockmann Norbert
Published: May 2022

Volatile markets and increasing demands for quality and fast availability of specialty chemical products have motivated the rise of small-scale, integrated, and modular continuous processing plants. As a significant unit operation used for product isolation and purification, cooling crystallization is part of this trend. Here, the small-scale and integrated quasi-continuous filter belt crystallizer (QCFBC) combines cooling crystallization, solid-liquid separation, and drying on a single apparatus. This contribution shows the general working principle, different operation modes, and possibilities of temperature control with the modular setup. For precise temperature control in cooling crystallization, Peltier elements show promising results in a systematic study of different operation parameters. Sucrose/water was used as a model substance system. The results confirm that seed crystal properties are the most important parameter in crystallization processes. Additionally, an oscillating temperature profile has a narrowing effect on the crystal size distribution (CSD). The integrated, small-scale, and modular setup of the QCFBC offers high degrees of flexibility, process control, and adaptability to cope with future market demands.
Hydrothermal Pretreatment of Wheat Straw—Evaluating the Effect of Substrate Disintegration on the Digestibility in Anaerobic Digestion
Authors: Zerback Timo , Schumacher Britt , Weinrich Sören , Hülsemann Benedikt , Nelles Michael
Published: May 2022

The increasing demand for renewable energy sources and demand-oriented electricity provision makes anaerobic digestion (AD) one of the most promising technologies. In addition to energy crops, the use of lignocellulosic residual and waste materials from agriculture is becoming increasingly important. However, AD of such feedstocks is often associated with difficulties due to the high content of lignocellulose and its microbial persistence. In the present work, the effect of hydrothermal pretreatment (HTP) on the digestibility of wheat straw is investigated and evaluated. Under different HTP temperatures (160–180 °C) and retention times (15–45 min), a significant increase in biomethane potential (BMP) can be observed in all cases. The highest BMP (309.64 mL CH4 g−1 volatile solid (VS) is achieved after pretreatment at 160 °C for 45 min, which corresponds to an increase of 19% of untreated wheat straw. The results of a multiple linear regression model show that the solubilization of organic materials is influenced by temperature and time. Furthermore, using two different first-order kinetic models, an enhancement of AD rate during hydrolysis due to pretreatment is observed. However, the increasing intensity of pretreatment conditions is accompanied by a decreasing trend in the conversion of intermediates to methane.
Green Extraction of Date Palm Fruits via Ultrasonic-Assisted Approach: Optimizations and Antioxidant Enrichments
Authors: Mohamed Hisham , Al-Hajhoj Mohamed , Al-Saikhan Mohamed , Alqahtani Nashi , Zayed Mohammad , Moawad Mahmoud , Alsenaien Waleed , Mohamed Maged E.
Published: May 2022

Background: Green extraction involves using green solvents, such as water, to reduce energy consumption, avoid health and environmental hazards and induce the quality and quantity of the extract. Date palm fruits are a vital source of food and medicinal activities, as they contain a high diversity of phytochemicals, mainly phenolic and flavonoid compounds. The main aim of this study is to investigate the use of water as a green solvent, when assisted by different ultrasonic frequencies, in the extraction of four different cultivars of date palm fruits, by evaluating the phenolic and flavonoid composition as well as the antioxidant capacity of the extract. Methods: Four date palm fruits’ cultivars (Agwa, Anbarah, Khalas, and Reziz) were extracted using conventional methods (by water and ethanol) and by ultrasonic means, using two frequencies, 28 and 40 kHz, and applying temperatures (30, 45, and 60 °C), also measuring extraction times (20, 40, 60 min.). Response surface methodology was used for the statistical analysis, applying three factors (temperature, time, and ultrasonic frequency), four responses (total phenolic content, total flavonoid content, FRAP, and ABTS), and four cultivars (categories). Results: Conventional water extraction obtained minimal phenolic and flavonoid compounds (up to 52% of ethanol extraction). This percent improved to reach 60% when heat was utilized. The application of ultrasonic frequencies significantly enhanced the extraction of phenolics/flavonoids and the antioxidant ability of the extract to nearly 90% and 80%, respectively. The use of 40 kHz ultrasonic power managed to extract more phenolic and flavonoid components; however, the antioxidant capacities of the extract were less than when the 28 kHz power was utilized. Agwa and Khalas demonstrated themselves to be the best cultivars for ultrasonic-assisted extraction, depending on the results of the optimized responses. Conclusion: This study could be implemented in the industry to produce date palm fruits’ enriched extracts with phenolic and flavonoid components and/or antioxidants.
Production, Optimization, and Partial Purification of Alkali-Thermotolerant Proteases from Newly Isolated Bacillus subtilis S1 and Bacillus amyloliquefaciens KSM12
Authors: Hashmi Sidra , Iqbal Sajid , Ahmed Iftikhar , Janjua Hussnain Ahmed
Published: May 2022

Proteases that can remain active under extreme conditions such as high temperature, pH, and salt concentration are widely applicable in the commercial sector. The majority of the proteases are rendered useless under harsh conditions in industries. Therefore, there is a need to search for new proteases that can tolerate and function in harsh conditions, thus improving their commercial value. In this study, 142 bacterial isolates were isolated from diverse alkaline soil habitats. The two highest protease-producing bacterial isolates were identified as Bacillus subtilis S1 and Bacillus amyloliquefaciens KSM12, respectively, based on 16S rRNA sequencing. Optimal protease production was detected at pH 8, 37 °C, 48 h, 5% (w/v) NaCl for Bacillus subtilis S1 (99.8 U/mL) and pH 9, 37 °C, 72 h, 10% (w/v) NaCl for Bacillus amyloliquefaciens KSM12 (94.6 U/mL). The molecular weight of these partially purified proteases was then assessed on SDS-PAGE (17 kDa for Bacillus subtilis S1 and 65 kDa for Bacillus amyloliquefaciens KSM12), respectively. The maximum protease activity for Bacillus subtilis S1 was detected at pH 8, 40 °C, and for Bacillus amyloliquefaciens KSM12 at pH 9, 60 °C. These results suggest that the proteases secreted by Bacillus subtilis S1 and Bacillus amyloliquefaciens KSM12 are suitable for industries working in a highly alkaline environment.
Experimental Research on Oil–Water Flow Imaging in Near-Horizontal Well Using Single-Probe Multi-Position Measurement Fluid Imager
Authors: Liu Junfeng , Shi Shoubo , Chen Hang
Published: May 2022

To obtain local flow velocity and holdup for oil–water in a near-horizontal well, array probes were adopted in the cross section of the wellbore. In this study, a fluid flow imaging logging tool called the single-probe multi-position measurement fluid imager (SPFI) was developed, which consisted of only a single turbine flowmeter and a single capacitance holdup probe. Most importantly, it could collect local velocity and holdup information at different locations along the vertical direction of the wellbore diameter. Firstly, in the large-diameter multi-phase flow simulation test loop, the instrument was placed at five different positions along the wellbore cross section to perform simulated measurements in different wellbore deviation angles and oil–water flowrates. Secondly, the experiment data was analyzed, and the experiment flow pattern chart, instrument response coefficient, and rule of the instrument response were obtained. At the same time, the calculation methods of local holdup and local velocity were derived. Thirdly, by combining the interpolation algorithm, velocity imaging and holdup imaging were implemented, and the stratified flow model was used to calculate the flowrate of each phase. Finally, this study provides technology support for production profile data interpretation using the fluid flow imaging tool for oil–water in a near-horizontal well.
Lightweight Design and Experimental Study of Ceramic Composite Armor
Authors: Chen Jianmei , Zeng Yihui , Liang Xiaopeng , Hou Yanbin , Wang Yunliang , Sun Zhenqi , Cui Shuwan
Published: May 2022

Ceramic/fiber composite armor is a hot research topic of bulletproof equipment. The lightweight design of ceramic materials and structures has attracted much attention. In this work, in the light of the remarkable performance of ceramic against elastic and oblique penetration, a novel honeycomb ceramic panel with a hexagonal prism and spherical body was designed. The splicing ceramic/fiber composite plate was bonded with a PE plate. The splicing ceramic/fiber composite was prepared, and the target test of the composite was conducted. The results show that the bulletproof performance of the hexagonal prism spherical crown ceramic/fiber composite plate is better than that of the conventional ceramic/fiber composite plate of the same thickness. The honeycomb spherical crown structure of the ceramic surface can convert the nominal forward penetration into the actual oblique penetration. This surface structure provides an effective lightweight design of ceramic/fiber composite armor.
Zero Liquid Discharge System for the Tannery Industry—An Overview of Sustainable Approaches
Authors: Ricky Rajamanickam , Shanthakumar Subramanian , Ganapathy Ganapathy Pattukandan , Chiampo Fulvia
Published: May 2022

The tannery industry is characterized by the consumption of a large quantity of water, around 30–40 m3 for processing 1000 kg of hide or skin. This amount becomes wastewater, containing about 300 kg of different chemicals, mainly refractory organic compounds, with high chemical oxygen demand (COD), total dissolved salts (TDS), chromium, and evolution of toxic gases, such as ammonia and sulfides, etc. The remaining tanning chemicals are released as effluent having high resistance against biological degradation, becoming a serious environmental issue. Usually, end-of-pipe treatment is not sufficient to meet the concerns of environmental issues. In terms of cleaner production options, the redesigning of the existing effluent treatment procedures with alternate or additional treatment techniques, which “supports resource recovery with no added chemicals”, is expected to give a sustainable solution for the management of toxic effluent. The Zero Liquid Discharge (ZLD) system serves to ensure zero water emission, as well as treatment facilities by recycling, recovery, and reuse of the treated wastewater using advanced cleanup technology. The international scenario shows the implementation of ZLD thanks to pressure from regulatory agencies. The ZLD system consists of a pre-treatment system with conventional physicochemical treatment, tertiary treatment, softening of the treated effluent, reverse osmosis (RO) treatment for desalination, and thermal evaporation of the saline reject from RO to separate the salts. By adopting this system, water consumption is reduced. Moreover, ZLD also becomes effective in disaster mitigation in areas where the tannery industry is a strong economic actor. With this review, we aim to give an outlook of the current framework.
Multivariate Analysis of Geological Data for Regional Studies of Geodiversity
Authors: Erikstad Lars , Bakkestuen Vegar , Dahl Rolv , Arntsen Mari Lie , Margreth Annina , Angvik Tine Larsen , Wickström Linda
Published: May 2022

In Norway, a landscape map exists which gives the opportunity to collect data in landscape units for further analysis. This study covers parts of Norway and Sweden, so the landscape map was extended into Sweden to form a unified landscape structure. A collection of geological and terrain data within landscape units can serve as a tool to describe the geodiversity profile of the units, study their geographical distribution and analyse similarities and dissimilarities between them. We collected geological and terrain data for an area covering large parts of southern Norway and Sweden. The data were collected as attributes in landscape polygons. The data were then analysed using multivariate techniques (Principle component analyses) where the first four axes of variation were definable. The first axis is a terrain axis, the second a bedrock unit axis, the third a bedrock diversity axis and the fourth a soil/sediment axis. In total, the four gradients answer for 54.9% of the total variation in the material. Links are found between the terrain data and geological units, but these links are relatively weak. The four gradients represent a step-less model of the geodiversity profile of the landscape areas but are dependent on the quality and scale of the input data. Norwegian and Swedish data had to be harmonised in order to be analysed together; however, because of this they ended up having a coarser resolution than desired, both spatially and scientifically. The stepless model was clustered to form 16 geodiversity profile groups for easy comparison and regional overview. The procedure can serve as a baseline for more detailed and field-based studies of geodiversity profiles, and give the opportunity to make analytical maps through simple overlay techniques and to compare areas with each other with respect to their geodiversity profile. This can be carried out both alone and in a wider landscape setting.
Enhancement of the ESSENZ Method and Application in a Case Study on Batteries
Authors: Pelzeter Julia , Bach Vanessa , Henßler Martin , Ruhland Klaus , Finkbeiner Matthias
Published: May 2022

With a growing awareness of the impact of resource exploitation, issues such as mine site certification and recyclate use in products come to the fore. These aspects are incorporated into the ESSENZ method which assesses resource criticality. Moreover, the method is enhanced by addressing further shortcomings and considering the SCARCE method. The resultant so-called ESSENZ+ method is tested in a case study on batteries involving a data update concerning the characterization factors of eight raw materials. The comparison of the results, using the original ESSENZ versus the updated ESSENZ+ characterization factors, shows significant changes regarding the demand growth (an increase of four times due to the inclusion of future trends) and price fluctuations (an increase of fourteen times due to a data update). The impact of the introduction of the aspects of mine site certification and recyclate use are examined via sensitivity analyses showing a reduced supply risk, yet to different extents in the different categories. A comparison of nickel-manganese-cobalt (NMC) batteries with different NMC ratios shows a decreasing supply risk per kWh, along with technological advancement, due to lower material requirements and smaller cobalt shares. ESSENZ+ enables users to include relevant developments in their assessment such as increasing mine site certifications and recyclate use.
The Dynamics of Chromatin Accessibility Prompted by Butyrate-Induced Chromatin Modification in Bovine Cells
Authors: Boschiero Clarissa , Gao Yahui , Liu Mei , Baldwin Ransom L. , Ma Li , Li Cong-Jun , Liu George E.
Published: May 2022

Butyrate is produced by microbe fermentation in the rumen, and its supplementation results in rumen development. Butyrate-induced experiments are valuable in studying nutrient metabolism, cell growth, and functional genomics. This study aimed to characterize accessible chromatin regions and the dynamics of genomic accessibility prompted by butyrate-induced histone modifications in bovine cells. An average of 117,569 accessible chromatin regions were identified for all samples, and 21,347 differentially accessible regions (DARs) for butyrate. Most of the DARs were in distal intergenic regions, introns, and promoters. Gene ontology enrichment resulted in important terms related to the digestive system, regulation of epithelial cells, and cell adhesion. Ingenuity Pathway Analysis (IPA) identified critical networks (e.g., digestive system development, cell morphology and assembly, and cell cycle); canonical pathways (e.g., TGFβ, Integrin-linked kinase, and epithelial adherens junction); and upstream regulators (e.g., TGFβ1, FOS, JUNB, ATF3, and KLFs). Co-expression analysis further showcased the TGFβ and Integrin-linked kinase (ILK)-signaling pathways, which play roles in rumen development through cellular adhesions. This study is the first to provide a genome-wide characterization of differential, open chromatin regions for bovine cells by butyrate-induced treatment. These results provide valuable information for future studies of the butyrate functions in cattle gastrointestinal tract development.
Research on an Improved Segmentation Recognition Algorithm of Overlapping Agaricus bisporus
Authors: Yang Shuzhen , Ni Bowen , Du Wanhe , Yu Tao
Published: May 2022

The accurate identification of overlapping Agaricus bisporus in a factory environment is one of the challenges faced by automated picking. In order to better segment the complex adhesion between Agaricus bisporus, this paper proposes a segmentation recognition algorithm for overlapping Agaricus bisporus. This algorithm calculates the global gradient threshold and divides the image according to the image edge gradient feature to obtain the binary image. Then, the binary image is filtered and morphologically processed, and the contour of the overlapping Agaricus bisporus area is obtained by edge detection in the Canny operator, the convex hull and concave area are extracted for polygon simplification, and the vertices are extracted using Harris corner detection to determine the segmentation point. After dividing the contour fragments by the dividing point, the branch definition algorithm is used to merge and group all the contours of the same Agaricus bisporus. Finally, the least squares ellipse fitting algorithm and the minimum distance circle fitting algorithm are used to reconstruct the outline of Agaricus bisporus, and the demand information of Agaricus bisporus picking is obtained. The experimental results show that this method can effectively overcome the influence of uneven illumination during image acquisition and be more adaptive to complex planting environments. The recognition rate of Agaricus bisporus in overlapping situations is more than 96%, and the average coordinate deviation rate of the algorithm is less than 1.59%.
Applied Machine Learning in Industry 4.0: Case-Study Research in Predictive Models for Black Carbon Emissions
Authors: Rubio-Loyola Javier , Paul-Fils Wolph Ronald Shwagger
Published: May 2022

Industry 4.0 constitutes a major application domain for sensor data analytics. Industrial furnaces (IFs) are complex machines made with special thermodynamic materials and technologies used in industrial production applications that require special heat treatment cycles. One of the most critical issues while operating IFs is the emission of black carbon (EoBC), which is due to a large number of factors such as the quality and amount of fuel, furnace efficiency, technology used for the process, operation practices, type of loads and other aspects related to the process conditions or mechanical properties of fluids at furnace operation. This paper presents a methodological approach to predict EoBC during the operation of IFs with the use of predictive models of machine learning (ML). We make use of a real data set with historical operation to train ML models, and through evaluation with real data we identify the most suitable approach that best fits the characteristics of the data set and implementation constraints in real production environments. The evaluation results confirm that it is possible to predict the undesirable EoBC well in advance, by means of a predictive model. To the best of our knowledge, this paper is the first approach to detail machine-learning concepts for predicting EoBC in the IF industry.
Implementation of Omni-D Tele-Presence Robot Using Kalman Filter and Tricon Ultrasonic Sensors
Authors: Tariq Hassan , Rashid Muhammad , Javed Asfa , Riaz Muhammad Aaqib , Sinky Mohammed , Zia Muhammad Yousuf Irfan
Published: May 2022

The tele-presence robot is designed to set forth an economic solution to facilitate day-to-day normal activities in almost every field. There are several solutions to design tele-presence robots, e.g., Skype and team viewer, but it is pretty inappropriate to use Skype and extra hardware. Therefore, in this article, we have presented a robust implementation of the tele-presence robot. Our proposed omnidirectional tele-presence robot consists of (i) Tricon ultrasonic sensors, (ii) Kalman filter implementation and control, and (iii) integration of our developed WebRTC-based application with the omnidirectional tele-presence robot for video transmission. We present a new algorithm to encounter the sensor noise with the least number of sensors for the estimation of Kalman filter. We have simulated the complete model of robot in Simulink and Matlab for the tough paths and critical hurdles. The robot successfully prevents the collision and reaches the destination. The mean errors for the estimation of position and velocity are 5.77% and 2.04%. To achieve efficient and reliable video transmission, the quality factors such as resolution, encoding, average delay and throughput are resolved using the WebRTC along with the integration of the communication protocols. To protect the data transmission, we have implemented the SSL protocol and installed it on the server. We tested three different cases of video resolutions (i.e., 320×280, 820×460 and 900×590) for the performance evaluation of the video transmission. For the highest resolution, our TPR takes 3.5 ms for the encoding, and the average delay is 2.70 ms with 900 × 590 pixels.
µRA—A New Compact Easy-to-Use Raman System for All Hydrogen Isotopologues
Authors: Priester Florian , Marsteller Alexander , Niemes Simon , Tuchscherer Nancy , Welte Stefan
Published: May 2022

We have developed a new compact and cost-efficient Laser-Raman system for the simultaneous measurement of all six hydrogen isotopologues. The focus of this research was set on producing a tool that can be implemented in virtually any existing setup providing in situ process control and analytics. The “micro Raman (µRA)” system is completely fiber-coupled for an easy setup consisting of (i) a spectrometer/CCD unit, (ii) a 532 nm laser, and (iii) a commercial Raman head coupled with a newly developed, tritium-compatible all-metal sealed DN16CF flange/Raman window serving as the process interface. To simplify the operation, we developed our own software suite for instrument control, data acquisition, and data evaluation in real-time. We have given a detailed description of the system, showing the system’s capabilities in terms of the lower level of detection, and presented the results of a dedicated campaign using the accurate reference mixtures of all of the hydrogen isotopologues benchmarking µRA against two of the most sensitive Raman systems for tritium operation. Due to its modular nature, modifications that allow for the detection of various other gas species can be easily implemented.
A Review of Noninvasive Methodologies to Estimate the Blood Pressure Waveform
Authors: Athaya Tasbiraha , Choi Sunwoong
Published: May 2022

Accurate estimation of blood pressure (BP) waveforms is critical for ensuring the safety and proper care of patients in intensive care units (ICUs) and for intraoperative hemodynamic monitoring. Normal cuff-based BP measurements can only provide systolic blood pressure (SBP) and diastolic blood pressure (DBP). Alternatively, the BP waveform can be used to estimate a variety of other physiological parameters and provides additional information about the patient’s health. As a result, various techniques are being proposed for accurately estimating the BP waveforms. The purpose of this review is to summarize the current state of knowledge regarding the BP waveform, three methodologies (pressure-based, ultrasound-based, and deep-learning-based) used in noninvasive BP waveform estimation research and the feasibility of employing these strategies at home as well as in ICUs. Additionally, this article will discuss the physical concepts underlying both invasive and noninvasive BP waveform measurements. We will review historical BP waveform measurements, standard clinical procedures, and more recent innovations in noninvasive BP waveform monitoring. Although the technique has not been validated, it is expected that precise, noninvasive BP waveform estimation will be available in the near future due to its enormous potential.
Securing Fog Computing with a Decentralised User Authentication Approach Based on Blockchain
Authors: Umoren Otuekong , Singh Raman , Pervez Zeeshan , Dahal Keshav
Published: May 2022

The use of low-cost sensors in IoT over high-cost devices has been considered less expensive. However, these low-cost sensors have their own limitations such as the accuracy, quality, and reliability of the data collected. Fog computing offers solutions to those limitations; nevertheless, owning to its intrinsic distributed architecture, it faces challenges in the form of security of fog devices, secure authentication and privacy. Blockchain technology has been utilised to offer solutions for the authentication and security challenges in fog systems. This paper proposes an authentication system that utilises the characteristics and advantages of blockchain and smart contracts to authenticate users securely. The implemented system uses the email address, username, Ethereum address, password and data from a biometric reader to register and authenticate users. Experiments showed that the proposed method is secure and achieved performance improvement when compared to existing methods. The comparison of results with state-of-the-art showed that the proposed authentication system consumed up to 30% fewer resources in transaction and execution cost; however, there was an increase of up to 30% in miner fees.
A Novel Method Based on GAN Using a Segmentation Module for Oligodendroglioma Pathological Image Generation
Authors: Kweon Juwon , Yoo Jisang , Kim Seungjong , Won Jaesik , Kwon Soonchul
Published: May 2022

Digital pathology analysis using deep learning has been the subject of several studies. As with other medical data, pathological data are not easily obtained. Because deep learning-based image analysis requires large amounts of data, augmentation techniques are used to increase the size of pathological datasets. This study proposes a novel method for synthesizing brain tumor pathology data using a generative model. For image synthesis, we used embedding features extracted from a segmentation module in a general generative model. We also introduce a simple solution for training a segmentation model in an environment in which the masked label of the training dataset is not supplied. As a result of this experiment, the proposed method did not make great progress in quantitative metrics but showed improved results in the confusion rate of more than 70 subjects and the quality of the visual output.
Wireless Kitchen Fire Prevention System Using Electrochemical Carbon Dioxide Gas Sensor for Smart Home
Authors: Kweon Soon-Jae , Park Jeong-Ho , Park Chong-Ook , Yoo Hyung-Joun , Ha Sohmyung
Published: May 2022

This paper presents a wireless kitchen fire prevention system that can detect and notify the fire risk caused by gas stoves. The proposed system consists of two modules. The sensor module detects the concentration of carbon dioxide (CO2) near the gas stove and transmits the monitoring results wirelessly. The alarm module, which is placed in other places, receives the data and reminds the user of the stove status. The sensor module uses a cost-efficient electrochemical CO2 sensor and embeds an in situ algorithm that determines the status of the gas stove based on the measured CO2 concentration. For the wireless communication between the modules, on-off keying (OOK) is employed, thereby achieving a longer battery lifetime of the alarm module, low cost, and simple implementation. To increase the lifetime further, a wake-up function based on passive infrared (PIR) sensing is employed in the alarm module. Our system can successfully detect the on state of the stove within 40 s and the off state within 200 s. Thanks to the low-power implementation, in situ algorithm, and wake-up function, the alarm module’s expected battery lifetime is extended to about two months.
A Two-Step Approach for Classification in Alzheimer’s Disease
Authors: De Falco Ivanoe , De Pietro Giuseppe , Sannino Giovanna
Published: May 2022

The classification of images is of high importance in medicine. In this sense, Deep learning methodologies show excellent performance with regard to accuracy. The drawback of these methodologies is the fact that they are black boxes, so no explanation is given to users on the reasons underlying their choices. In the medical domain, this lack of transparency and information, typical of black box models, brings practitioners to raise concerns, and the result is a resistance to the use of deep learning tools. In order to overcome this problem, a different Machine Learning approach to image classification is used here that is based on interpretability concepts thanks to the use of an evolutionary algorithm. It relies on the application of two steps in succession. The first receives a set of images in the inut and performs image filtering on them so that a numerical data set is generated. The second is a classifier, the kernel of which is an evolutionary algorithm. This latter, at the same time, classifies and automatically extracts explicit knowledge as a set of IF–THEN rules. This method is investigated with respect to a data set of MRI brain imagery referring to Alzheimer’s disease. Namely, a two-class data set (non-demented and moderate demented) and a three-class data set (non-demented, mild demented, and moderate demented) are extracted. The methodology shows good results in terms of accuracy (100% for the best run over the two-class problem and 91.49% for the best run over the three-class one), F_score (1.0000 and 0.9149, respectively), and Matthews Correlation Coefficient (1.0000 and 0.8763, respectively). To ascertain the quality of these results, they are contrasted against those from a wide set of well-known classifiers. The outcome of this comparison is that, in both problems, the methodology achieves the best results in terms of accuracy and F_score, whereas, for the Matthews Correlation Coefficient, it has the best result over the two-class problem and the second over the three-class one.
A Unified Local–Global Feature Extraction Network for Human Gait Recognition Using Smartphone Sensors
Authors: Das Sonia , Meher Sukadev , Sahoo Upendra Kumar
Published: May 2022

Smartphone-based gait recognition has been considered a unique and promising technique for biometric-based identification. It is integrated with multiple sensors to collect inertial data while a person walks. However, captured data may be affected by several covariate factors due to variations of gait sequences such as holding loads, wearing types, shoe types, etc. Recent gait recognition approaches either work on global or local features, causing failure to handle these covariate-based features. To address these issues, a novel weighted multi-scale CNN (WMsCNN) architecture is designed to extract local to global features for boosting recognition accuracy. Specifically, a weight update sub-network (Ws) is proposed to increase or reduce the weights of features concerning their contribution to the final classification task. Thus, the sensitivity of these features toward the covariate factors decreases using the weight updated technique. Later, these features are fed to a fusion module used to produce global features for the overall classification. Extensive experiments have been conducted on four different benchmark datasets, and the demonstrated results of the proposed model are superior to other state-of-the-art deep learning approaches.