bluuebunny/crossref_metadata_2025_split huggingface dataset:
Multiple linear regression models to simulate spore yields of Bacillus amyloliquefaciens BS13 through optimization of medium composition
Authors: Kamoun Fakher , Weekers Frederic , Ayed Rayda Ben , Mechri Sondes , Jabeur Fadoua , Thonart Philippe , Jaouadi Bassem 
Published: January 2022

AbstractBacillus amyloliquefaciens is a food spoilage spore‐forming bacterium. Its spores are useful for multiple biotechnological applications. Nevertheless, few reports are available regarding the achievement of a high cell density and good sporulation effectiveness under fermentation conditions. Therefore, the current study was designed to optimize a low‐cost fermentation medium allowing the highest sporulation yield by B. amyloliquefaciens strain BS13. Our data revealed that tryptone and starch were the best carbon and energy sources. In addition, two nitrogen sources namely, corn steep liquor (CSL) and yeast extract (YE), allowed a significant enhancement of spore production and they were both retained for further optimization. A combination of CaCl2, MgSO4, and MnSO4 showed a positive impact on spores’ production. The composition of the optimized medium was (in g/L); tryptone 3, starch 15, CSL 13.5, YE 1.5, CaCl2 0.1, MgSO4·7H2O 0.012, and MnSO4·7H2O 0.0012. Such medium was further validated in a 400‐L fermentor. The spore yield by B. amyloliquefaciens strain BS13 was enhanced from 3.0 × 1010 spores/mL under flask culture conditions to 6.2 × 1010 spores/mL when cultures were performed on large scale. Therefore, strain BS13 spore preparation could be proposed as a promising probiotic and a biocontrol agent useful for plants, animals, and humans.
Induced effect of Ca2+ and Al3+ on chaetominine synthesis by Aspergillus fumigatus CY018 under submerged fermentation
Authors: Liu Changqing , Chen Tianwen , Chen Jijie , Zhou Yuxuan , Deng Lina , Feng Gongneng , Gao Jian , Liang Huixing 
Published: January 2022

AbstractChaetominine (CHA), an alkaloid with a biological activity obtained from Aspergillus fumigatus CY018, has strong anticancer activity against the human leukemia cells. However, its physiological and biochemical research is limited by CHA yield in the liquid‐state fermentation, which is a problem that urgently needs effective biological solution. In this work, Ca2+ and Al3+ were found to have a strong promoting effect on CHA production after multiple metal ions screening. Then, the addition condition of Ca2+ and Al3+ was, respectively, optimized CHA production and dry cell weight. The intermediate metabolites were increased with coaddition of Ca2+ and Al3+. The activities of key enzymes of DAHPs, AroAs, and TrpCs in the CHA biosynthesis pathway were improved by 3.58‐, 3.60‐, and 3.34‐fold, respectively. Meanwhile, the transcription level of laeA, dahp, cs, and trpC was upregulated by 3.22‐, 12.65‐, 5.58‐, and 6.99‐fold, respectively, by coaddition of Ca2+ and Al3+. Additionally, the fermentation strategy was successfully scaled up to a 5‐L bioreactor, in which CHA production could attain 75.6 mg/L at 336 h. This work demonstrated that Ca2+ and Al3+ coaddition was an effective strategy for increasing CHA production, and the information obtained might be useful in the fermentation of filamentous fungi with the addition of metal ions.
Information processing in tax decisions: a MouselabWEB study on the deterrence model of income tax evasion
Authors: Kogler Christoph , Olsen Jerome , Müller Martin , Kirchler Erich 
Published: January 2022

AbstractThe highly influential Allingham and Sandmo model of income tax evasion assumes that taxpayers are driven by utility maximization, choosing evasion over compliance if it yields a higher expected profit. We test the main assumptions of this so‐called deterrence approach considering both compliance decisions and the process of information acquisition using MouselabWEB. In an incentivized experiment, 109 participants made 24 compliance decisions with varying information presented for four within‐subject factors (the four central model parameters: income, tax rate, audit probability, and fine level). Additionally, explicit expected value information was indicated in one of two conditions. The results reveal that participants attended to all relevant information, a prerequisite for expected value‐like calculations. As predicted by the deterrence model, choices were clearly influenced by audit probability and fine level. Against the model assumptions, the presented parameters were not integrated adequately, indicated by a non‐monotonic increase of evasion with rising expected rate of return from evasion. Additionally, more transitions between information necessary for calculating expected values did not result in higher model conformity, just as presenting explicit information on expected values. We conclude that deterrence information clearly influences tax compliance decisions in our setting but observed deviations from the deterrence model can be attributed to failures to properly integrate all relevant parameters.
A versatile enrichment of functionalized calixarene as a facile sensor for amino acids
Authors: Parikh Jaymin , Bhatt Keyur , Modi Krunal , Patel Nihal , Desai Ajay , Kumar Sandeep , Mohan Brij 
Published: January 2022

AbstractAmino acids are the most important part of the human biological system due to their role in living processes. The role of amino acids stretches beyond their traditional role as a building block for proteins, and deficiency of amino acids could lead to decreased immunity, digestive problems, depression, fertility issues, lower mental alertness, slowed growth in children, and many other health issues. The acute detection of amino acids is necessary to determine the human health domain. Here, in this review, we summarize and study the calixarenes as complexes that are of immeasurable value and their utilization for amino acid detection. Key factors such as noncovalent forces, limit of detection, and the supramolecular chemistry of calixarenes with amino acids have been well described. This study presents the most recent efforts made towards the development of potential and highly efficient calixarene‐based sensors for the detection of amino acids.
Fading bioluminescence of the tropical Atlantic Ocean
Authors: Piontkovski Sergey A. , Serikova Irina M. 
Published: January 2022

AbstractBioluminescence intensity acts as the indicator of the functional state of a plankton community. Data on bioluminescence intensity, zooplankton biomass, and chlorophyll a from the expeditions to the tropical and subtropical Atlantic Ocean were analyzed. The regression models implied a ~10‐fold decline of bioluminescence intensity [bioluminescence potential (BP)] and zooplankton biomass for the 46 year time range from 1970 to 2016. The correlation was low between chlorophyll a (the indicator of phytoplankton biomass) and BP, but it was significant for the zooplankton biomass BP annual time series. The decline of BP was associated with the decreasing abundance of bioluminescent zooplankton, and increasing global warming‐driven temperature.
Determination of multiple active constituents in Da‐Huang‐Xiao‐Shi decoction using HPLC–LTQ–Orbitrap mass spectrometry: Application in comparing the differences in the formula and its constituent herbs
Authors: Li Hongyu , Jin Jingyi , Xue Haoyu , Li Yuanyuan , Wang Tianming , Shi Rong , Ma Yueming 
Published: January 2022

AbstractDa‐Huang‐Xiao‐Shi decoction (DHXSD) is a traditional Chinese medicine formula and is used to treat cholestasis. In this study, we developed a reliable and comprehensive HPLC coupled with a linear ion trap–Orbitrap mass spectrometry method for the separation and determination of 21 components including six alkaloids, five anthraquinones, three tannins, three terpenes, two iridoid glycosides, one organic acid and one flavonoid in DHXSD. A C18 column was eluted using a gradient mobile phase at a flow rate of 1 ml/min. Detection was operated with an electrospray ionization source in positive and negative ion modes using selective ion monitoring. The calibration curves for all analytes showed good linearity (r > 0.9901), and the inter‐ and intra‐day precision did not exceed 4.98%. The recovery, repeatability and stability were also within the acceptable limits. The method was successfully applied to determine multiple active constituents in DHXSD and its constituent herbs. Compared with Da Huang, the total contents of the five anthraquinones were significantly higher in DHXSD. However, the changes in the components from Zhi Zi/Huang Bo were complicated in DHXSD. The study could serve as a fundamental reference for establishing comprehensive DHXSD quality control measures and be helpful to understand some compatibility laws of DHXSD.
A neural signature for combined action observation and motor imagery? An fNIRS study into prefrontal activation, automatic imitation, and self–other perceptions
Authors: Emerson Jonathan R. , Scott Matthew W. , van Schaik Paul , Butcher Natalie , Kenny Ryan P. W. , Eaves Daniel L. 
Published: January 2022

AbstractIntroductionResearch indicates that both observed and imagined actions can be represented in the brain as two parallel sensorimotor representations. One proposal is that higher order cognitive processes would align these two hypothetical action simulations.MethodsWe investigated this hypothesis using an automatic imitation paradigm, with functional near‐infrared spectroscopy recordings over the prefrontal cortex during different motor simulation states. On each trial, participants (n = 14) observed a picture of a rhythmical action (instructed action) followed by a distractor movie showing the same or different action. Participants then executed the instructed action. Distractor actions were manipulated to be fast or slow, and instructions were manipulated during distractor presentation: action observation (AO), combined action observation and motor imagery (AO+MI) and observe to imitate (intentional imitation). A pure motor imagery (MI) condition was also included.ResultsKinematic analyses showed that although distractor speed effects were significant under all instructions (shorter mean cycle times in execution for fast compared to slow trials), this imitation bias was significantly stronger for combined AO+MI than both AO and MI, and stronger for intentional imitation than the other three automatic imitation conditions. In the left prefrontal cortex, cerebral oxygenation was significantly greater for combined AO+MI than all other instructions. Participants reported that their representation of the self overlapped with the observed model significantly more during AO+MI than AO.ConclusionLeft prefrontal activation may therefore be a neural signature of AO+MI, supporting attentional switching between concurrent representations of self (MI, top‐down) and other (AO, bottom‐up) to increase imitation and perceived closeness.
Frailty and malnutrition as influential drivers of outcomes after aortic valve replacement
Authors: Upadhyay Ankit , Jneid Hani 
Published: January 2022

Key Points
Frailty and malnutrition share common pathophysiologic pathways as evidenced by similar hormonal disturbances and cardiac biomarker abnormalities.
Multiple assessment tools exist to measure frailty and malnutrition in patients undergoing aortic valve replacement (AVR). In the current single‐center study, the fried frailty phenotype frailty score and the Mini Nutritional Assessment–Long Form nutrition scale appear to have the strongest association with 1‐year all‐cause mortality in those patients.
Objective assessment of frailty and nutritional status should be added to conventional surgical risk scores in all patients undergoing AVR, and incorporated in the multidisciplinary heart team deliberations and the shared decision‐making process with patients.
Surgical bailout after transcatheter aortic valve replacement: Hospital procedural volume matters!
Authors: Okuya Yoshiyuki , Moussa Issam D. 
Published: January 2022

Key Points
Surgical bailout after transcatheter aortic valve replacement (TAVR) has diminished overtime to less than 1%; however, it is still associated with very high mortality rate even at very high volume hospitals.
The frequency of surgical bailout after TAVR is related to annual hospital procedural volume. An annual hospital volume >200 procedures is associated with <0.5% incidence of surgical bailout.
These findings ought to trigger a discussion regarding the necessity for surgical standby for TAVR procedures at high volume hospitals.
Prolonged dual antiplatelet therapy in selected patients with acute coronary syndrome
Authors: Spirito Alessandro , Mehran Roxana 
Published: January 2022

Key Points
It is crucial to identify patients with an increased bleeding or ischemic risk that may benefit from a tailored antiplatelet regimen.
This study confirmed the benefit of a prolonged DAPT (≥12 months) in reducing ischemic events without bleeding harm in a real world East Asian population presenting with acute coronary syndrome and additional clinical and angiographic high‐risk features.
An alternative approach, consisting of a prolonged P2Y12 monotherapy, is under investigation in this patient subset.
Oxidation of Methane to Methanol by Water Over Cu/SSZ‐13: Impact of Cu Loading and Formation of Active Sites
Authors: Zhang Hailong , Lv Jianhang , Zhang Zhun , Du Congcong , Wang Shuai , Lin Jingdong , Wan Shaolong , Wang Yong , Xiong Haifeng 
Published: January 2022

AbstractCu/SSZ‐13 catalysts with different Cu loadings (1–5 wt.%) were prepared by conventional impregnation via a slow step‐dry process for the direct conversion of methane to methanol. Catalytic performance of the catalysts is found to depend on the Cu loading in both stepwise and continuous processes and 2 wt.% Cu presents the best performance. CuO nanoparticles, CuxOy clusters and monomeric [CuOH]+ species are found on Cu/SSZ‐13 based on HRTEM, HAADF‐STEM, DR UV‐vis and FTIR spectroscopies. The high coverage of CuO nanoparticles on 5 wt.% Cu/SSZ‐13 results in the loss of catalytic reactivity in spite of the existence of active CuxOy and [CuOH]+ sites. Besides, it is proposed that the formation of [Cu2O2]2+ and [Cu2O]2+ active sites involves [CuOH]+ intermediates. We further found that improved catalytic performance in cyclic stepwise process involves the re‐dispersion of CuO nanoparticles and/or large clusters as well as the re‐oxidation of Cu(I) cations from self‐reduction of [CuOH]+ species.
Colorimetric characterization of color imaging systems using a multi‐inputPSO‐BPneural network
Authors: Liu Lu , Xie Xufen , Zhang Yuncui , Cao Fan , Liang Jing , Liao Ningfang 
Published: January 2022

AbstractMost commonly used camera characterization methods do not use a deep learning‐based artificial neural network approach at present. This article proposes a colorimetric characterization method for color imaging systems based on the multi‐input particle swarm optimization backpropagation neural network. Combined with a particle swarm optimization algorithm for global search and a 19‐input vector, this method not only overcomes the effects of local extrema on the multi‐input backpropagation neural network, but also improves the accuracy of the common input backpropagation neural network. Images of a ColorChecker SG chart were collected using a Canon EOS 1000D camera for experimental verification, and the color differences were used to evaluate the characterization results. The results show that the color differences of the multi‐input particle swarm optimization backpropagation neural network (structure: 19‐7‐3) model are substantially better than those of the multi‐input backpropagation neural network (structure: 19‐7‐3) and common input backpropagation neural network (structure: 3‐4‐3) models. Its performance is close to that of the weighted nonlinear regression model. The multi‐input particle swarm optimization backpropagation neural network is hence an effective method for colorimetric characterization with good prediction accuracy.
Research on the colour preference and harmony of the two‐colour combination buildings
Authors: Li Ke‐Run , Zheng Zhi‐Qiang , Wang Pei‐Hong , Yan Wen‐Jie 
Published: January 2022

AbstractThis study used computer software to design building models with selected colour parameters based on a two‐colour pattern combination, which was then presented on a standard computer screen. Further, the two‐colour combination pattern was adopted to prepare building simulation pictures with 153 colour combinations. A total of six hues were extracted based on the Natural Colour System, and there were also 18 colour samples with different lightness and saturation degrees. The results of the study found that hue difference, lightness difference, chroma difference, and total colour difference have a significant effect on harmony. On the other hand, hue difference, chroma difference, and total colour difference have a significant effect on preference. It is worth noting that lightness difference and architectural colour preferences were negatively related. In addition, there was a high correlation between architectural colour harmony and preference.
Classification of human's activities from gesture recognition in live videos using deep learning
Authors: Khan Amjad Rehman , Saba Tanzila , Khan Muhammad Zeeshan , Fati Suliman Mohamed , Khan Muhammad Usman Ghani 
Published: January 2022

AbstractThe automated behavior analysis is a significant problem in the examination. In the presence of invigilators and examiners, examinees use various unfair means to cheat the staff. Examinees may use different gestures like moving their head, eyes and using different suspicious objects (mobile phone, calculator) and so forth. This research is intended to automatically identify and distinguish examinees in live videos who cheat by their activities in examination hall during exams. Hence, we took the privilege of ensemble learning using deep learning‐based algorithms. The suspicious head movements and prohibited objects have been monitored using fine‐tuned Faster RCNN algorithm. At the same time, interactive use‐age of prohibited objects find out using Open‐Pose architecture. For this purpose, intersection over union (IOU) has been calculated between the region of interest (ROI) of detected objects and pose points of hands and face. To get the identity of a specific examinee, we stored the features of facial ROI after the last convolution layer and matched them at the time of testing for statistical analysis. We achieved state‐of‐the‐art results using standard evaluating measures. Moreover, for experiments, dataset of automatic examinee invigilation is available currently. So, this research also contributes toward the generation and annotation of the dataset.
Highly accurate division and square root circuits by exploiting signal correlation in stochastic computing
Authors: Wang Shaowei , Xie Guangjun , Han Jie , Zhang Yongqiang 
Published: January 2022

AbstractStochastic computing (SC) is an approximate computing paradigm using probabilities and aims at realizing circuits with low hardware cost. Basic operations (such as addition) have been comprehensively studied, whereas there are few studies on nonlinear operations (such as division and square root) in SC. In this paper, a stochastic division circuit is proposed by using maximally correlated input bitstreams to eliminate the necessity for distinguishing the divisor and dividend. Additionally, four stochastic square root circuits are designed with improved accuracy by decreasing the correlation between intermediate bitstreams via inserting delay elements. Experimental results show that both the proposed division and square root circuits achieve lower mean squared errors (MSEs) while requiring nearly the same hardware resources, compared with the state‐of‐the‐art designs. This result shows the potential in exploiting signal correlation in SC circuit design for high accuracy.
Forest phenoclusters for Argentina based on vegetation phenology and climate
Authors: Silveira Eduarda M. O. , Radeloff Volker C. , Martínez Pastur Guillermo J. , Martinuzzi Sebastián , Politi Natalia , Lizarraga Leonidas , Rivera Luis O. , Gavier‐Pizarro Gregorio I. , Yin He , Rosas Yamina M. , Calamari Noelia C. , Navarro María F. , Sica Yanina , Olah Ashley M. , Bono Julieta , Pidgeon Anna M. 
Published: January 2022

AbstractForest biodiversity conservation and species distribution modeling greatly benefit from broad‐scale forest maps depicting tree species or forest types rather than just presence and absence of forest, or coarse classifications. Ideally, such maps would stem from satellite image classification based on abundant field data for both model training and accuracy assessments, but such field data do not exist in many parts of the globe. However, different forest types and tree species differ in their vegetation phenology, offering an opportunity to map and characterize forests based on the seasonal dynamic of vegetation indices and auxiliary data. Our goal was to map and characterize forests based on both land surface phenology and climate patterns, defined here as forest phenoclusters. We applied our methodology in Argentina (2.8 million km2), which has a wide variety of forests, from rainforests to cold‐temperate forests. We calculated phenology measures after fitting a harmonic curve of the enhanced vegetation index (EVI) time series derived from 30‐m Sentinel 2 and Landsat 8 data from 2018–2019. For climate, we calculated land surface temperature (LST) from Band 10 of the thermal infrared sensor (TIRS) of Landsat 8, and precipitation from Worldclim (BIO12). We performed stratified X‐means cluster classifications followed by hierarchical clustering. The resulting clusters separated well into 54 forest phenoclusters with unique combinations of vegetation phenology and climate characteristics. The EVI 90th percentile was more important than our climate and other phenology measures in providing separability among different forest phenoclusters. Our results highlight the potential of combining remotely sensed phenology measures and climate data to improve broad‐scale forest mapping for different management and conservation goals, capturing functional rather than structural or compositional characteristics between and within tree species. Our approach results in classifications that go beyond simple forest–nonforest in areas where the lack of detailed ecological field data precludes tree species–level classifications, yet conservation needs are high. Our map of forest phenoclusters is a valuable tool for the assessment of natural resources, and the management of the environment at scales relevant for conservation actions.