bluuebunny/crossref_metadata_2025 huggingface dataset:
A Prediction Method of Seedling Transplanting Time with DCNN-LSTM Based on the Attention Mechanism
Authors: Zhu Huaji , Liu Chang , Wu Huarui
Published: June 2022

To improve the production efficiency and reduce the labor cost of seedling operations, cabbage was selected as the research subject, and a novel approach based on the attention mechanism combining the deep convolutional neural network (DCNN) and long short-term memory (LSTM) is proposed. First, the cabbage growth data and environmental monitoring data were normalized, and input samples were obtained by sliding the time window. Then, the DCNN and the LSTM were used to extract the spatial feature information and temporal correlation of the samples, respectively. At the same time, the attention mechanism was used to set the weight coefficients of different feature information and highlight the role of the main features of the sample in the model, thereby improving the prediction accuracy. By analyzing the experimental data collected by the Shandong Seedling Plant, the DCNN-LSTM method based on the proposed attention mechanism achieved good prediction results, providing experience for the engineering application of decision-making regarding seedling transplanting time. The experimental data showed that the mean absolute error, root-mean-square error, mean absolute percentage error, and symmetric mean absolute percentage error of the prediction results of this method were 0.356, 0.507, 0.157, and 0.082, respectively. Compared with the CNN, LSTM, LSTM-Attention and CNN-LSTM models, this model showed higher prediction accuracy.
Identification of Maize Rf4-Restorer Lines and Development of a CAPS Marker for Rf4
Authors: Liu Yongming , Zhang Ling , Liu Xiaowei , Zhang Peng , Zhao Zhuofan , Yi Hongyang , Cao Moju
Published: June 2022

Rf4 is one of the dominant restorer genes for maize C-type cytoplasmic male sterility (CMS-C), which has significant value in hybrid maize seed production. However, the highly complex fertility restoration mechanism of CMS-C makes it difficult to screen Rf4-restorer lines, and insufficient Rf4-restorer lines limit its use in current agricultural production. To search for Rf4-restorer lines, in this study, the genotypes of eighteen inbred maize lines at the Rf4 locus were analyzed based on the male fertility investigation of hybrid F1, the genetic analysis of F2 populations, molecular marker mapping, allelic tests, and Rf4 genomic sequence analysis. Our results indicated that of the eighteen maize inbred lines, ten were able to completely rescue CMS-C line CHuangzaosi (CHZS) male sterility. A genetic analysis showed that DAN598, PHT77, 78551S, and LH212Ht only contained one dominant restorer gene each, and the molecular-marker mapping indicated that their restorer genes were located at the short arm of chromosome 8. The allelic testing of the fertility of the restorer (Rf) demonstrated that the restorer gene of twelve inbred lines, including DAN598, PHT77, 78551S, and LH212Ht, was allelic to one restorer gene of A619. Furthermore, the genomic sequence alignment of Rf4 revealed that there were two different amino acids in the coding sequence between the A619 (Rf4Rf4) restorer lines and four CMS-C lines (rf4rf4). For the crucial S1596 site variation (TTT/TAC), DAN598, PHT77, 78551S, and LH212Ht shared the same bases (TTT) with A619 and encoded phenylalanine, while the four CMS-C sterile lines had the TAC and encoded tyrosine. Our results revealed that these tester lines, DAN598, PHT77, 78551S, and LH212Ht, were the Rf4-restorer lines. Additionally, derived from the sequence variants of Rf4, 39 possible Rf4-restorer lines from 129 inbred maize lines were detected. Furthermore, we developed a Cleaved Amplified Polymorphism Sequences (CAPS) marker based on the S1596 variations. The PCR amplification product of S1596 (TAC) was digested by the TatI endonuclease into two bands with sizes of ~260 bp and ~100 bp. In comparison, when S1596 was TTT, the PCR product could not be digested. In conclusion, in this study, we identified various Rf4-restorer lines for maize CMS-C and developed a molecular marker for Rf4. The reported results will contribute to the popularization and application of Rf4 in hybrid maize-seed production.
Evaluation of Pedotransfer Functions for Estimating Soil Water Retention Curve of Ap Horizon Soils for Various Soil Series of Reclaimed Tidal Flat Soil
Authors: Lee Kyo-Suk , Lee Dong-Sung , Jung Hyun-Gyu , Lee Sang-Phil , Ryu Jin-Hee , Choi Woo-Jung , Yang Jae-Eui , Chung Doug-Young
Published: June 2022

This investigation was to evaluate the applicability and prediction accuracy of pedotransfer function (PTF) to estimate the water retention curves of Ap horizon soils for five soil series which cannot be directly used to cultivate upland crops other than rice because of their high salinity. Soil water retention curves (SWRCs) were obtained from 150 undisturbed soil samples collected from the Ap horizons of which soil textures were grouped into sandy loam with high contents of sand (>60%) and low clay contents (<10%) and silt loam with relatively high silt content (>60%) and low sand content (<10%). Soil-water retention characteristics between 0 to −50 kPa and −50 to −1500 kPa were measured using the sandbox, kaolin-plate, and pressure chamber methods, respectively. The SWRCs were also estimated by Rawls and Brakensiek PTF (RB-PTF). The measured SWRCs of sandy loam and silt loam were compared against those obtained from RB-PTF. The SWRCs estimated with the modeled data closely fit the measured data of sandy loam and silt loam although saturated volume water content (θs) and residual volume water content (θr) of RB-PTF were higher than those of the measured mean for both soil textures. The air entry point (α) and the steepness of the water-retention curve (n) were higher in sandy loam than those of silt loam. SWRCS estimated by the RB-PTF yielded the best fit of all soil samples from the five series, whereas the MBE values less than zero indicate that θv measured at the water potentials is under-predicted. The r2 values greater than 0.9 for sandy loam and silt loam represent RB-PTF and are suitable for predicting SWRCs in RTFS because the measured data points do not vary around the estimated regression line.
Development of Retrotransposon-Based Molecular Markers for Characterization of Persea americana (Avocado) Cultivars and Horticultural Races
Authors: Carracedo Mario González , Alonso Samuel Bello , Cabrera Rahil Salomé Brito , Jiménez-Arias David , Pérez Pérez José Antonio
Published: June 2022

Persea americana (avocado) represents one of the most demanded food products worldwide, with an important impact in several agronomy-based economies. The avocado is one of the most salt-sensitive and valuable crops. It is therefore necessary to use salt-tolerant varieties, such as the West Indian, for cultivation in locations with soil salinity problems, such as the Canary Islands. Therefore, characterization of avocado cultivars is in demand, as well as development of molecular tools able to easily identify the main avocado cultivars and horticultural races. In the present work, inter-Primer Binding Site (iPBS) and Inter-Retrotransposon Amplified Polymorphism (IRAP) techniques, which are based on retrotransposon with Long Terminal Repeats (LTR), have been implemented for the first time in P. americana, allowing the characterization of genetic variation among cultivars from the three main horticultural races and the identification of potential P. americana LTR sequences. The iPBS approach showed clear advantages over its technical implementation, and allowed a better delimitation of horticultural races, especially when focused on West Indian cultivars. However, both techniques generated reproducible genetic fingerprints that not only allowed genetic characterization of each cultivar analyzed, but also revealed potential molecular markers for the identification of avocado cultivars and horticultural races.
Contrasting Adaptation Mechanisms of Golden Camellia Species to Different Soil Habitats Revealed by Nutrient Characteristics
Authors: Zhu Xianliang , Tang Jianmin , Qin Huizhen , Bai Kundong , Chen Zongyou , Zou Rong , Liu Shengyuan , Yang Quanguang , Wei Xiao , Chai Shengfeng
Published: June 2022

Golden Camellia species are highly specific to certain soil environments. Most species are only native to calcareous soils in karst regions, except for a few that grow only in acidic soils. Our aim is to elucidate the adaptation mechanisms of the species of calcareous-soil golden Camellia (CSC) and acidic-soil golden Camellia (ASC) to habitat soils through plant–soil nutrient characteristics and their relationships. We investigated 30 indices for soils and plants. Compared with ASC, CSC had more fertile soil, while their plant tissues exhibited stronger Ca, P, and Mn and weaker K storage, which may be important mechanisms for adapting to habitat soils. However, ASC showed a higher biological absorption coefficient (BAC) for nutrients, which may contribute to the adaptation of ASC to relatively barren acidic soils. Both CSC and ASC showed much higher BAC and accumulation of Ca than other nutrients. We also found that the concentrations of nutrients in the different tissues varied considerably between species. Correlation analysis revealed 135 significant relationships between the 30 indices, with the soil pH and soil Ca levels being the most important factors influencing the nutrient uptake network. This information helps in understanding the adaptation mechanisms of karst plants to habitat soils.
Self-Medication as an Important Risk Factor for Antibiotic Resistance: A Multi-Institutional Survey among Students
Authors: Zeb Shah , Mushtaq Mariam , Ahmad Muneeb , Saleem Waqas , Rabaan Ali A. , Naqvi Bibi Salma Zahid , Garout Mohammed , Aljeldah Mohammed , Al Shammari Basim R. , Al Faraj Nehad J. , Al-Zaki Nisreen A. , Al Marshood Mona J. , Al Saffar Thuria Y. , Alsultan Khadija A. , Al-Ahmed Shamsah H. , Alestad Jeehan H. , Naveed Muhammad , Ahmed Naveed
Published: June 2022

Self-medication is an important issue, especially in developing countries. Self-medication is the concept in which individuals use medicine to ease and manage their minor illnesses. The current survey was designed to conduct interviews at different universities based on the availability of the students from August 2021 to October 2021 in Hazara region of Khyber Pakhtunkhwa (KPK), Pakistan. Overall, 1250 questionnaires were distributed to students from various departments. Students of microbiology (n = 305, 24.4%) and agriculture 236 (n = 18.8%) were the most elevated members in this study, while other participants were from medical lab technology (n = 118, 9.4%), chemistry (n = 103, 8.2%), food science (n = 92, 7.3%), business administration (n = 83, 6.6%), sociology (n = 78, 6.2%), math/physics (n = 6, 14.8%), Pak study (n = 58, 4.6%), English (n = 47, 3.7%), and psychology (n = 19, 1.5%). Students working towards their Bachelor numbered (n = 913, 73.0%), Master (minor) numbered (n = 80, 6.4%), Master (major) numbered (n = 221, 17.6%), and Doctorate numbered (n = 36, 2.8%). The age group of participants was majorly 20–25 years (61.0%), while others belonged to the age groups 25–30 years (20.6%), 30–35 years (9.8%), and 35–40 years (8.4%). The mean and standard deviation of daily practices of self-medication were observed (M = 416.667, SD = 1,026,108.667) and p = 0.002. The mean and standard deviation of daily practices of antibiotic knowledge was (M = 431.5, SD = 1,615,917) and p = 0.002. Antimicrobial agents were leading over others with 631 (50.4%), followed by anti-inflammatory with 331 (26.4%), multivitamins with 142 (11.3%), gynecological purpose with 59 (4.7%), and analgesic with 72 (5.7%), while the lowest frequency rate was observed against herbal remedies with 15 (1.2%). The results of the current study concluded that students practiced self-medication for reasons such as convenience to obtain these medications from cheap sources and to avoid the fee of a physician. They searched for the medicine on social media platforms and purchased it blindly from the pharmacy without any prescription from a physician.
Novel Organoselenium Redox Modulators with Potential Anticancer, Antimicrobial, and Antioxidant Activities
Authors: Sak Marwa , Al-Faiyz Yasair , Elsawy Hany , Shaaban Saad
Published: June 2022

Novel organic selenides were developed in good yields (up to 91%), and their chemical entities were confirmed by IR, MS, and 1H- and 13C-NMR spectroscopy. Their anticancer and antimicrobial properties were estimated against different human cancer (MCF-7 and HepG2) and healthy (WI-38) cell lines, as well as several microbial strains (Escherichia coli, Staphylococcus aureus, and Candida albicans). Furthermore, the 2,2-diphenyl-1-picrylhydrazyl (DPPH) and 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) bioassays were used for the estimation of the antioxidant activities. Generally, cytotoxicity results were more pronounced against the MCF-7 cells than HepG2 cells. Compound 2-((4-((1-hydroxynaphthalen-2-yl)diazenyl)phenyl)selanyl)-N-phenylacetamide (9) was the most cytotoxic, even more than doxorubicin, with IC50 of 3.27 ± 0.2 against 4.17 ± 0.2 µM and twelve-times more selective, respectively. Interestingly, compound 9 exhibited similar antimicrobial potential to reference antibacterial and antifungal drugs and comparable antioxidant activity to vitamin C. These results point to selective cytotoxicity against MCF-7 cells and interesting antimicrobial and antioxidant properties of some newly synthesized organic selenides, which in turn needs further in vitro studies.
Metabolomics-Based Profiling, Antioxidant Power, and Uropathogenic Bacterial Anti-Adhesion Activity of SP4TM, a Formulation with a High Content of Type-A Proanthocyanidins
Authors: Mannino Giuseppe , Maffei Massimo E.
Published: June 2022

Flavonoids and proanthocyanidins (PACs) have been the subject of intense scientific investigations, both for their antioxidant properties and anti-adhesion activity against uropathogenic bacteria. We investigated the metabolomics and antioxidant capacity of SP4TM, a patent-pending formulation based on a mixture of plant extracts with a high content of bioactive PACs and other polyphenols. The total content of polyphenols (885.51 ± 14.19 mg/g), flavonoids (135.52 ± 8.98 mg/g), anthocyanins (54.84 ± 2.97 mg/g), and PACs (379.43 ± 12.44 mg/g) was quantified using UV-Vis assays. Use of HPLC-ESI-MS/MS revealed the presence of 5 flavanols (100.77 ± 3.90 mg g−1 d.wt), 11 flavonols (59.96 ± 1.83 mg g−1 d.wt), and 8 anthocyanins (46.96 ± 1.59 mg g−1 d.wt), whereas MALDI-TOF MS showed that SP4TM contains PACs with one or more type-A interflavan bonds at each degree of polymerization. Regarding antioxidant properties, LUCS technology on HepG2 cells evidenced the ability of SP4TM to neutralize intracellular free radicals, inhibit membrane lipid peroxidation, quench H2O2, and reduce free radicals mainly through chelating mechanism, as demonstrated by a higher FRAP value (2643.28 ± 39.86 mmol/g) compared with ABTS (139.92 ± 6.16 mmol/g) and DPPH (89.51 ± 3.91 mmol/g). Finally, the SP4TM type-A PAC content strongly prevented bacterial adhesion of P-fimbriated uropathogenic Escherichia coli (0.23 mg/mL). In conclusion, SP4TM has a strong antioxidant capacity involving multitarget mechanisms and is a potential supplement to fight urinary tract infections due to its ability to inhibit uropathogenic E. coli adhesion.
Empirical Modeling and Optimization by Active Central Composite Rotatable Design: Brilliant Red HE-3B Dye Biosorption onto Residual Yeast Biomass-Based Biosorbents
Authors: Zaharia Carmen , Suteu Daniela
Published: June 2022

(1) Introduction: Natural polymers can be successfully used as a matrix to immobilize residual yeast-based biomass in a form that is easy to handle and can be used as biosorbent capable of removing persistent polluting species from different aqueous systems such as reactive azo dyes. (2) Experimental: Two types of new biosorbents were prepared based on residual Saccharomyces pastorianus yeast biomass immobilized in sodium alginate (using two different practice techniques) and studied in the biosorption process of reactive Brilliant Red HE-3B dye using certain experimental planning matrices according to the active central composite rotatable design of 23 order. The experimental data obtained under certain selected working conditions were processed considering the influence of three independent variables (biosorbent concentration—X1, initial dye concentration—X2 and biosorption time—X3) onto the dependent variable (Y = f(X1,X2,X3)) expressing the performance of reactive dye biosorption onto the new prepared biosorbents (i.e., dye removal degree, %). (3) Results: Two mathematical models were proposed for each prepared biosorbent. The maximum dye removal was 52.878% (Y1) when 18 g/L biosorbent 1 (micro-encapsulated form) was applied in 70 mg/L dye-containing solution for at least 8 h, and 75.338% (Y2) for 22.109 g/L biosorbent 2 (immobilized form) in 48.49 mg/L dye-containing solution for at least 8.799 h. (4) Discussion: The optimal values achieved for the two tested biosorbents were compared, and we investigated the possibility of using this residual biomass as a biosorbent for the reactive dye removal, supported by the experimental results with the recommended variation domains of each influencing variable. The results are sufficient to permit performing dye removal higher than 50% (biosorbent 1) or 70% (biosorbent 2), working with more than 18–22 g/L biosorbent after at least 8 h (as an exchange at work). (5) Conclusions: The proposed models are in good agreement with the experimental data and permit the prediction of dye biosorption behavior onto the experimental variation domain of each independent variable.
Challenges of Using Blockchain in the Education Sector: A Literature Review
Authors: Mohammad Abdulghafour , Vargas Sergio
Published: June 2022

Blockchain is one of the latest innovations that is increasingly attracting the attention of various stakeholders in different fields, including the education sector. This is primarily due to its attractive features, such as decentralization, transparency, traceability, security, and reliability. Despite its advantages, blockchain still faces several challenges, and the acceptance rate of this technology is still low. Thus, the purpose of this study was to conduct a review of published articles that have discussed the challenges of adopting blockchain in the education sector. The review contained scientific papers published from 2017 to 2022 and, from the screened records, 32 articles were analyzed in full-text form. In this review, 14 challenges were reported and classified, based on the technology-organization-environment (TOE) framework. In addition, this review showed that organizational and environmental barriers received little attention in the literature, compared to technological barriers.
Sensing Hydrogen Seeps in the Subsurface for Natural Hydrogen Exploration
Authors: Mainson Mederic , Heath Charles , Pejcic Bobby , Frery Emanuelle
Published: June 2022

The recent detection of natural hydrogen seeps in sedimentary basin settings has triggered significant interest in the exploration of this promising resource. If large economical resources exist and can be extracted from the sub-surface, this would provide an opportunity for natural hydrogen to contribute to the non-carbon-based energy mix. The detection and exploration of hydrogen gas in the sub-surface is a significant challenge that requires costly drilling, sophisticated instrumentation, and reliable analytical/sampling methods. Here, we propose the application of a commercial-based sensor that can be used to detect and monitor low levels of hydrogen gas emissions from geological environments. The sensitivity, selectivity (K > 1000), and stability (<1 ppm/day) of the sensor was evaluated under various conditions to determine its suitability for geological field monitoring. Calibration tests showed that the hydrogen readings from the sensor were within ±20% of the expected values. We propose that chemical sensing is a simple and feasible method for understanding natural hydrogen seeps that emanate from geological systems and formations. However, we recommend using this sensor as part of a complete geological survey that incorporates an understanding of the geology along with complementary techniques that provide information on the rock properties.
Novel Vision Transformer–Based Bi-LSTM Model for LU/LC Prediction—Javadi Hills, India
Authors: Mohanrajan Sam Navin , Loganathan Agilandeeswari
Published: June 2022

Continuous monitoring and observing of the earth’s environment has become interactive research in the field of remote sensing. Many researchers have provided the Land Use/Land Cover information for the past, present, and future for their study areas around the world. This research work builds the Novel Vision Transformer–based Bidirectional long-short term memory model for predicting the Land Use/Land Cover Changes by using the LISS-III and Landsat bands for the forest- and non-forest-covered regions of Javadi Hills, India. The proposed Vision Transformer model achieves a good classification accuracy, with an average of 98.76%. The impact of the Land Surface Temperature map and the Land Use/Land Cover classification map provides good validation results, with an average accuracy of 98.38%, during the process of bidirectional long short-term memory–based prediction analysis. The authors also introduced an application-based explanation of the predicted results through the Google Earth Engine platform of Google Cloud so that the predicted results will be more informative and trustworthy to the urban planners and forest department to take proper actions in the protection of the environment.
Design and Implementation of an Explainable Bidirectional LSTM Model Based on Transition System Approach for Cooperative AI-Workers
Authors: Yang Minyeol , Moon Junhyung , Yang Seowon , Oh Hyungsuk , Lee Soojin , Kim Yoonkyum , Jeong Jongpil
Published: June 2022

Recently, interest in the Cyber-Physical System (CPS) has been increasing in the manufacturing industry environment. Various manufacturing intelligence studies are being conducted to enable faster decision-making through various reliable indicators collected from the manufacturing process. Artificial intelligence (AI) and Machine Learning (ML) have advanced enough to give various possibilities of predicting manufacturing time, which can help implement CPS in manufacturing environments, but it is difficult to secure reliability because it is difficult to understand how AI works, and although it can offer good results, it is often not applied to industries. In this paper, Bidirectional Long Short Term Memory (BI-LSTM) is used to predict process execution time, which is an indicator that can be used as a basis for CPS in the manufacturing process, and the Shapley Additive Explanations (SHAP) algorithm is used to explain how artificial intelligence works. The experimental results of this paper, applying manufacturing data, prove that the results derived from SHAP are effective for workers and AI to collaborate.
Multifilters-Based Unsupervised Method for Retinal Blood Vessel Segmentation
Authors: Muzammil Nayab , Shah Syed Ayaz Ali , Shahzad Aamir , Khan Muhammad Amir , Ghoniem Rania M.
Published: June 2022

Fundus imaging is one of the crucial methods that help ophthalmologists for diagnosing the various eye diseases in modern medicine. An accurate vessel segmentation method can be a convenient tool to foresee and analyze fatal diseases, including hypertension or diabetes, which damage the retinal vessel’s appearance. This work suggests an unsupervised approach for vessels segmentation out of retinal images. The proposed method includes multiple steps. Firstly, from the colored retinal image, green channel is extracted and preprocessed utilizing Contrast Limited Histogram Equalization as well as Fuzzy Histogram Based Equalization for contrast enhancement. To expel geometrical articles (macula, optic disk) and noise, top-hat morphological operations are used. On the resulted enhanced image, matched filter and Gabor wavelet filter are applied, and the outputs from both is added to extract vessels pixels. The resulting image with the now noticeable blood vessel is binarized using human visual system (HVS). A final image of segmented blood vessel is obtained by applying post-processing. The suggested method is assessed on two public datasets (DRIVE and STARE) and showed comparable results with regard to sensitivity, specificity and accuracy. The results we achieved with respect to sensitivity, specificity together with accuracy on DRIVE database are 0.7271, 0.9798 and 0.9573, and on STARE database these are 0.7164, 0.9760, and 0.9560, respectively, in less than 3.17 s on average per image.
Privacy-Preserving and Explainable AI in Industrial Applications
Authors: Ogrezeanu Iulian , Vizitiu Anamaria , Ciușdel Costin , Puiu Andrei , Coman Simona , Boldișor Cristian , Itu Alina , Demeter Robert , Moldoveanu Florin , Suciu Constantin , Itu Lucian
Published: June 2022

The industrial environment has gone through the fourth revolution, also called “Industry 4.0”, where the main aspect is digitalization. Each device employed in an industrial process is connected to a network called the industrial Internet of things (IIOT). With IIOT manufacturers being capable of tracking every device, it has become easier to prevent or quickly solve failures. Specifically, the large amount of available data has allowed the use of artificial intelligence (AI) algorithms to improve industrial applications in many ways (e.g., failure detection, process optimization, and abnormality detection). Although data are abundant, their access has raised problems due to privacy concerns of manufacturers. Censoring sensitive information is not a desired approach because it negatively impacts the AI performance. To increase trust, there is also the need to understand how AI algorithms make choices, i.e., to no longer regard them as black boxes. This paper focuses on recent advancements related to the challenges mentioned above, discusses the industrial impact of proposed solutions, and identifies challenges for future research. It also presents examples related to privacy-preserving and explainable AI solutions, and comments on the interaction between the identified challenges in the conclusions.
A Novel Broad Echo State Network for Time Series Prediction: Cascade of Mapping Nodes and Optimization of Enhancement Layer
Authors: Liu Wen-Jie , Bai Yu-Ting , Jin Xue-Bo , Kong Jian-Lei , Su Ting-Li
Published: June 2022

Time series prediction is crucial for advanced control and management of complex systems, while the actual data are usually highly nonlinear and nonstationary. A novel broad echo state network is proposed herein for the prediction problem of complex time series data. Firstly, the framework of the broad echo state network with cascade of mapping nodes (CMBESN) is designed by embedding the echo state network units into the broad learning system. Secondly, the number of enhancement layer nodes of the CMBESN is determined by proposing an incremental algorithm. It can obtain the optimal network structure parameters. Meanwhile, an optimization method is proposed based on the nonstationary statistic metrics to determine the enhancement layer. Finally, experiments are conducted both on the simulated and actual datasets. The results show that the proposed CMBESN and its optimization have good prediction capability for nonstationary time series data.
Prebiotic Isomaltooligosaccharide Provides an Advantageous Fitness to the Probiotic Bacillus subtilis CU1
Authors: Villéger Romain , Pinault Emilie , Vuillier-Devillers Karine , Grenier Karine , Landolt Cornelia , Ropartz David , Sol Vincent , Urdaci Maria C. , Bressollier Philippe , Ouk Tan-Sothéa
Published: June 2022

Bacillus subtilis CU1 is a probiotic strain with beneficial effects on immune health in elderly subjects and diarrhea. Commercialized under spore form, new strategies to improve the germination, fitness and beneficial effects of the probiotic once in the gut have to be explored. For this purpose, functional food ingredients, such as isomaltooligosaccharides (IMOSs), could improve the fitness of Bacillus probiotics. IMOSs are composed of α(1 → 6)- and α(1 → 4)-linked oligosaccharides and are partially indigestible. Dietary IMOSs stimulate beneficial members of intestinal microbiota, but the effect of a combination of IMOSs with probiotics, such as B. subtilis CU1, is unknown. In this study, we evaluate the potential effect of IMOSs in B. subtilis CU1 and identify the metabolic pathways involved. The biochemical analysis of the commercial IMOSs highlights a degree of polymerization (DP) comprised between 1 and 29. The metabolism of IMOSs in CU1 was attributed to an α-glucosidase, secreted in the extracellular compartment one hundred times more than with glucose, and which seems to hydrolyze high DP IMOSs into shorter oligosaccharides (DP1, DP2 and DP3) in the culture medium. Proteomic analysis of CU1 after growth on IMOSs showed a reshaping of B. subtilis CU1 metabolism and functions, associated with a decreased production of lactic acid and acetic acid by two times. Moreover, we show for the first time that IMOSs could improve the germination of a Bacillus probiotic in the presence of bile salts in vitro, with an 8 h reduced lag-time when compared to a glucose substrate. Moreover, bacterial concentration (CFU/mL) was increased by about 1 log in IMOS liquid cultures after 48 h when compared to glucose. In conclusion, the use of IMOSs in association with probiotic B. subtilis CU1 in a synbiotic product could improve the fitness and benefits of the probiotic.
High-Efficiency Conversion of Bread Residues to Ethanol and Edible Biomass Using Filamentous Fungi at High Solids Loading: A Biorefinery Approach
Authors: Kawa-Rygielska Joanna , Pietrzak Witold , Lennartsson Patrik R.
Published: June 2022

Bread residues represent a significant fraction of retail food wastes, becoming a severe environmental challenge and an economic loss for the food sector. They are, however, an attractive resource for bioconversion into value-added products. In this study, the edible filamentous fungi Neurospora intermedia and Aspergillus oryzae were employed for the production of bioethanol and high-protein biomass by cultivation on enzymatically liquefied bread-waste medium at 150 g/L solids. The fermentation of hydrolysate by N. intermedia resulted in the ethanol titer of 32.2 g/L and biomass yield of 19.2 g/L with ca. 45% protein. However, the fermentation ended with a considerable amount of residual fermentable sugars; therefore, the liquid medium after the first fermentation was distilled and fermented again by two fungal strains (N. intermedia and A. oryzae). The fermentations resulted in the production of additional ethanol and biomass. A. oryzae showed better performance in the production of biomass, while the other strain yielded more ethanol. The final products’ yield ranged 0.29–0.32 g EtOH/g and 0.20–0.22 g biomass/g bread waste depending on the strain used in the second fermentation. The study shows that valorization of bread residuals by fungi is a promising option for the production of biofuels and foodstuff within the circular bioeconomy approach.
Significance of Camera Pixel Error in the Calibration Process of a Robotic Vision System
Authors: Khan Mohammad Farhan , Dannoun Elham M. A. , Nofal Muaffaq M. , Mursaleen M.
Published: June 2022

Although robotic vision systems offer a promising technology solution for rapid and reconfigurable in-process 3D inspection of complex and large parts in contemporary manufacturing, measurement accuracy poses a challenge for its wide deployment. One of the key issues in adopting a robotic vision system is to understand the extent of its measurement errors which are directly correlated with the calibration process. In this paper, a possible source of practical and inherent measurement uncertainties involved in the calibration process of a robotic vision system are discussed. The system considered in this work consists of an image sensor mounted on an industrial robot manipulator with six degrees of freedom. Based on a series of experimental tests and computer simulations, the paper gives a comprehensive performance comparison of different calibration approaches and shows the impact of measurement uncertainties on the calibration process. It has been found from the error sensitivity analysis that minor uncertainties in the calibration process can significantly affect the accuracy of the robotic vision system. Further investigations suggest that inducing errors in image calibration patterns can have an adverse effect on the hand–eye calibration process compared to the angular errors in the robot joints.
Optimization and Diversification of Cryptocurrency Portfolios: A Composite Copula-Based Approach
Authors: Tenkam Herve M. , Mba Jules C. , Mwambi Sutene M.
Published: June 2022

This paper focuses on the selection and optimisation of a cryptoasset portfolio, using the K-means clustering algorithm and GARCH C-Vine copula model combined with the differential evolution algorithm. This integrated approach allows the construction of a diversified portfolio of eight cryptocurrencies and determines an optimal allocation strategy making it possible to minimize the conditional value-at-risk of the portfolio and maximise the return. Our results show that stablecoins such as True-USD are negatively correlated to the other cryptoassets in the portfolio and could therefore be a safe haven for crypto-investors during market turmoil. Our findings are in line with previous studies exhibiting stablecoins as potential diversifiers.
Incorporating Ecological Constraints into the Simulations of Tropical Urban Growth Boundaries: A Case Study of Sanya City on Hainan Island, China
Authors: Han Nianlong , Hu Ke , Yu Miao , Jia Peihong , Zhang Yiqing
Published: June 2022

The rapid expansion of cities in tropical regions has triggered a series of problems such as the destruction of rare natural resources and decreases in the environmental resource carrying capacity and ecological security, which seriously threaten the sustainable development of tropical cities. In this study, the city of Sanya, Hainan, China, is taken as an example. A bottom-line ecological security pattern is constructed based on the remote sensing ecological index (RSEI) and the patch-generating land use simulation (PLUS) for urban growth boundary (UGB) delineation. The results show that Sanya has a good ecological background, but the overall ecological quality decreased from 2014 to 2018 due to the expansion of construction in hot spot areas. Under the natural growth scenario, the urban built-up area in Sanya in 2030 will be 73.81% greater than in 2018, mainly occupying a large amount of agricultural and ecological space, and urban expansion will not be effectively suppressed. Delineation of the UGBs combined with the ecological constraints can effectively protect the regional ecological security and control the urban sprawl, which is relatively consistent with the current planning. The results of this study demonstrate that the RSEI-PLUS-based UGB delineation perspective has a high scientific and applicability, and they provide a reference for the coordinated ecological–economic sustainable development of ecologically fragile cities in tropical areas.
Application of Tungsten-Oxide-Based Electrochromic Devices for Supercapacitors
Authors: Li Muyun , Yan Haoyang , Ning Honglong , Li Xinglin , Zhong Jinyao , Fu Xiao , Qiu Tian , Luo Dongxiang , Yao Rihui , Peng Junbiao
Published: June 2022

For making full use of the discoloration function of electrochromic (EC) devices and better show the charge and discharge states of supercapacitors (SCs), electrochromic supercapacitors (ECSCs) have attracted much attention and expectations in recent years. The research progress of tungsten-oxide-based electrochromic supercapacitors (ECSCs) in recent years is reviewed in this paper. Nanostructured tungsten oxide is widely used to facilitate ion implantation/extraction and increase the porosity of the electrode. The low-dimensional nanostructured tungsten oxide was compared in four respects: material scale, electrode life, coloring efficiency, and specific capacitance. Due to the mechanics and ductility of nano-tungsten oxide electrodes, they are very suitable for the preparation of flexible ECSCs. With the application of an organic protective layer and metal nanowire conductive electrode, the device has higher coloring efficiency and a lower activation voltage. Finally, this paper indicates that in the future, WO3-based ECSCs will develop in the direction of self-supporting power supply to meet the needs of use.
Several Double Inequalities for Integer Powers of the Sinc and Sinhc Functions with Applications to the Neuman–Sándor Mean and the First Seiffert Mean
Authors: Li Wen-Hui , Shen Qi-Xia , Guo Bai-Ni
Published: June 2022

In the paper, the authors establish a general inequality for the hyperbolic functions, extend the newly-established inequality to trigonometric functions, obtain some new inequalities involving the inverse sine and inverse hyperbolic sine functions, and apply these inequalities to the Neuman–Sándor mean and the first Seiffert mean.
The Role of p16/Ki-67 Immunostaining, hTERC Amplification and Fibronectin in Predicting Cervical Cancer Progression: A Systematic Review
Authors: Voidăzan Septimiu Toader , Dianzani Caterina , Husariu Mădălina Aurelia , Geréd Bíborka , Turdean Sabin Gligore , Uzun Cosmina Cristina , Kovacs Zsolt , Rozsnyai Florin Francisc , Neagu Nicoleta
Published: June 2022

Human papillomaviruses (HPVs) are common sexually transmitted infectious agents responsible for several anogenital and head and neck cancers. Cervical cancer (CC) is the fourth leading cause of death in women with cancer. The progression of a persistent HPV infection to cancer takes 15–20 years and can be preventable through screening. Cervical cytology (Pap smear) is the standard screening test for CC and precancerous lesions. For ASC-US and ASC-H lesions, a combination of Pap smear and HR-HPV analysis is recommended as a triage step before colposcopy. However, these tests cannot predict progression to CC. For this purpose, we summarized current scientific data on the role of p16/Ki-67 immunohistostaining, telomerase and fibronectin in predicting progression to CC. p16 and p16/Ki-67 dual staining (DS) were more specific than HR-HPV DNA testing for the detection of CIN2+/CIN3+ in women with ASC-US and LSIL. Similarly, hTERC FISH analysis significantly improved the specificity and positive predictive value of HPV DNA testing in differentiating CIN2+ from CIN2 cytological samples. In conclusion, p16 IHC, p16/Ki-67 DS and hTERC FISH amplification are all valid adjunctive biomarkers which significantly increase the sensitivity and specificity of cervical dysplasia diagnosis, especially when combined with HPV DNA testing. However, considering the global socioeconomic background, we can postulate that p16 and p16/ Ki-67 IHC can be used as a next step after positive cytology for ASC-US or LSIL specimens in low-income countries, instead of HPV DNA testing. Alternatively, if HPV DNA testing is covered by insurance, p16 or p16/Ki-67 DS and HPV DNA co-testing can be performed. In middle- and high-income countries, hTERC amplification can be performed as an adjunctive test to HPV DNA testing in women with ASC-US and LSIL.
Ventricular Repolarization and Calcium Transient Show Resonant Behavior under Oscillatory Pacing Rate
Authors: Zaniboni Massimiliano
Published: June 2022

Cardiac EC coupling is triggered by rhythmic depolarizing current fronts originating from the sino-atrial node, and the way variability in rhythm is associated with variability in action potential duration (APD) and, in turn, in the variability of calcium transient amplitude (CTA) and contraction is a key determinant of beating stability. Sinusoidal-varying pacing rate is adopted here in order to establish whether APD and CTA oscillations, elicited in a human ventricular AP model (OR) under oscillatory pacing, are consistent with the dynamics of two coupled harmonic oscillators, e.g., a two-degree-of-freedom system of mass and springs (MS model). I show evidence that this is the case, and that the MS model, preliminarily fitted to OR behavior, retains key features of the physiological system, such as the dependence of APD and CTA oscillation amplitudes from average value and from beat-to-beat changes in pacing rate, and the phase relationship between them. The bi-directionality of coupling between APD and CTA makes it difficult to discriminate which one leads EC coupling dynamics under variable pacing. The MS model suggests that the calcium cycling, with its greater inertia chiefly determined by the SR calcium release, is the leading mechanism. I propose the present approach to also be relevant at the whole organ level, where the need of compact representations of electromechanical interaction, particularly in clinical practice, remains urgent.
Usefulness of the Measurement of Serum Paraoxonase-1 Arylesterase Activity in the Diagnoses of COVID-19
Authors: Gabaldó Xavier , Juanpere Màrius , Castañé Helena , Rodríguez-Tomàs Elisabet , López-Azcona Ana Felisa , Baiges-Gaya Gerard , Castro Lourdes , Valverde-Díaz Enrique , Muñoz-Blázquez Aida , Giménez-Cuenca Laura , Felipo-Balada Laura , Ballester Frederic , Pujol Isabel , Simó Josep M. , Castro Antoni , Iftimie Simona , Camps Jordi , Joven Jorge
Published: June 2022

The development of inexpensive, fast, and reliable screening tests for COVID-19 is, as yet, an unmet need. The present study was aimed at evaluating the usefulness of serum arylesterase activity of paraoxonase-1 (PON1) measurement as a screening test in patients with different severity levels of COVID-19 infection. We included 615 COVID-19-positive patients who were classified as asymptomatic, mildly symptomatic, severely symptomatic, or fatally symptomatic. Results were compared with 50 healthy volunteers, 330 patients with cancer, and 343 with morbid obesity. Results showed PON1 activity greatly decreased in COVID-19 compared to healthy volunteers; a receiver operating characteristics plot showed a high diagnostic accuracy. The degree of COVID-19 severity did not influence PON1 levels. Our results indicated that PON1 determination was efficient for disease diagnosis, but not for prognosis. Furthermore, patients with obesity or cancer presented alterations similar to those of COVID-19 patients. As such, elevated levels of PON1 indicate the absence of COVID-19, but low levels may be present in various other chronic diseases. The assay is fast and inexpensive. We suggest that PON1 measurement could be used as an initial, high cut-off point screening method, while lower values should be confirmed with the more expensive nucleic acid amplification test.
Pathogenesis of Paradoxical Reactions Associated with Targeted Biologic Agents for Inflammatory Skin Diseases
Authors: Miyagawa Fumi
Published: June 2022

Targeted biologic agents have dramatically changed the therapeutic landscape for immune-mediated inflammatory diseases, particularly in rheumatology and dermatology. Their introduction has resulted in a paradigm shift, i.e., they produce significant clinical improvements in most patients with such diseases. Nevertheless, a variety of adverse reactions associated with these agents have been observed, including so-called paradoxical reactions (PRs), which are a new class of adverse events. PRs involve the de novo development or worsening of immune-mediated inflammatory disease during treatment with a targeted biologic agent that is commonly used to treat the idiopathic counterpart of the drug-induced reaction. In addition, the efficacy of biologic agents targeting individual cytokines and the existence of PRs to them have provided proof that cytokines are key drivers of various immune-mediated inflammatory diseases and helped researchers elucidate the molecular pathways underlying the pathophysiology of these diseases. Here, a comprehensive review of the targeted biologic agents used to treat immune-mediated inflammatory diseases, particularly psoriasis and atopic dermatitis, is provided, with a specific focus on biologic agents that inhibit cytokine signaling involving tumor necrosis factor-α, interleukin (IL)-12/23 (p40), IL-17A (and the IL-17 receptor [R]), IL-23 (p19), and the IL-4Rα, and their associated PRs. The characteristic clinical manifestations and potential immunological mechanisms of the PRs induced by these biologic agents are also reviewed.
Machine Learning Characterization of Ictal and Interictal States in EEG Aimed at Automated Seizure Detection
Authors: Zazzaro Gaetano , Pavone Luigi
Published: June 2022

Background: The development of automated seizure detection methods using EEG signals could be of great importance for the diagnosis and the monitoring of patients with epilepsy. These methods are often patient-specific and require high accuracy in detecting seizures but also very low false-positive rates. The aim of this study is to evaluate the performance of a seizure detection method using EEG signals by investigating its performance in correctly identifying seizures and in minimizing false alarms and to determine if it is generalizable to different patients. Methods: We tested the method on about two hours of preictal/ictal and about ten hours of interictal EEG recordings of one patient from the Freiburg Seizure Prediction EEG database using machine learning techniques for data mining. Then, we tested the obtained model on six other patients of the same database. Results: The method achieved very high performance in detecting seizures (close to 100% of correctly classified positive elements) with a very low false-positive rate when tested on one patient. Furthermore, the model portability or transfer analysis revealed that the method achieved good performance in one out of six patients from the same dataset. Conclusions: This result suggests a strategy to discover clusters of similar patients, for which it would be possible to train a general-purpose model for seizure detection.
Beetle Antennae Search: Using Biomimetic Foraging Behaviour of Beetles to Fool a Well-Trained Neuro-Intelligent System
Authors: Khan Ameer , Cao Xinwei , Xu Bin , Li Shuai
Published: June 2022

Deep Convolutional Neural Networks (CNNs) represent the state-of-the-art artificially intelligent computing models for image classification. The advanced cognition and pattern recognition abilities possessed by humans are ascribed to the intricate and complex neurological connection in human brains. CNNs are inspired by the neurological structure of the human brain and show performance at par with humans in image recognition and classification tasks. On the lower extreme of the neurological complexity spectrum lie small organisms such as insects and worms, with simple brain structures and limited cognition abilities, pattern recognition, and intelligent decision-making abilities. However, billions of years of evolution guided by natural selection have imparted basic survival instincts, which appear as an “intelligent behavior”. In this paper, we put forward the evidence that a simple algorithm inspired by the behavior of a beetle (an insect) can fool CNNs in image classification tasks by just perturbing a single pixel. The proposed algorithm accomplishes this in a computationally efficient manner as compared to the other adversarial attacking algorithms proposed in the literature. The novel feature of the proposed algorithm as compared to other metaheuristics approaches for fooling a neural network, is that it mimics the behavior of a single beetle and requires fewer search particles. On the contrary, other metaheuristic algorithms rely on the social or swarming behavior of the organisms, requiring a large population of search particles. We evaluated the performance of the proposed algorithm on LeNet-5 and ResNet architecture using the CIFAR-10 dataset. The results show a high success rate for the proposed algorithms. The proposed strategy raises a concern about the robustness and security aspects of artificially intelligent learning systems.