bluuebunny/crossref_metadata_2025_split huggingface dataset:
Removal of yttrium from rare-earth wastewater by Serratia marcescens: biosorption optimization and mechanisms studies
Authors: Liang Chang-li , Shen Ji-li 
Published: March 2022

AbstractThe discharge of yttrium containing wastewater is a potential risk to human health. Although biosorption is a promising method to remove yttrium from wastewater, whereas the application of it is limited due to the lack of efficient biosorbents. In this study, the removal of yttrium from wastewater using Serratia marcescens as a biosorbent was conducted. The effects of six parameters including pH (2–5.5), initial yttrium concentration (10–110 mg/L), biosorbent dosage (0.1–0.5 g/L), biosorption time (10–700 min), stirring speed (50–300 rpm) and temperature (20–60 °C) were evaluated. The main parameters were optimized using response surface methodology. The results showed that the adsorption capacity reached 123.65 mg/g at the optimized conditions. The biosorption mechanism was revealed based on a combined analysis using field emission transmission electron microscope-energy dispersion spectrum, Fourier transform infrared spectrophotometer, and X-ray photoelectron spectroscopy. These results revealed that the hydroxyl, carboxyl, and amino groups were the adsorption functional groups for yttrium ions. Biosorption of yttrium by S. marcescens is under the combination of ion exchange, electrostatic attraction and complexation. These findings indicated that S. marcescens can be used as an efficient biosorbent to remove yttrium from wastewater. In addition, its adsorption capacity can be further improved by the enhancement of adsorption functional groups on the surface through chemical modification.
A study on Ti-doped Fe3O4 anode for Li ion battery using machine learning, electrochemical and distribution function of relaxation times (DFRTs) analyses
Authors: Chi Po-Wei , Paul Tanmoy , Su Yu-Hsuan , Su Kai-Han , Su Cherng-Yuh , Wu Phillip M. , Wang Sea-Fue , Wu Maw-Kuen 
Published: March 2022

AbstractAmong many transition-metal oxides, Fe3O4 anode based lithium ion batteries (LIBs) have been well-investigated because of their high energy and high capacity. Iron is known for elemental abundance and is relatively environmentally friendly as well contains with low toxicity. However, LIBs based on Fe3O4 suffer from particle aggregation during charge–discharge processes that affects the cycling performance. This study conjectures that iron agglomeration and material performance could be affected by dopant choice, and improvements are sought with Fe3O4 nanoparticles doped with 0.2% Ti. The electrochemical measurements show a stable specific capacity of 450 mAh g−1 at 0.1 C rate for at least 100 cycles in Ti doped Fe3O4. The stability in discharge capacity for Ti doped Fe3O4 is achieved, arising from good electronic conductivity and stability in microstructure and crystal structure, which has been further confirmed by density functional theory (DFT) calculation. Detailed distribution function of relaxation times (DFRTs) analyses based on the impedance spectra reveal two different types of Li ion transport phenomena, which are closely related with the electron density difference near the two Fe-sites. Detailed analyses on EIS measurements using DFRTs for Ti doped Fe3O4 indicate that improvement in interfacial charge transfer processes between electrode and Li metal along with an intermediate lithiated phase helps to enhance the electrochemical performance.
Ultrafast neuromorphic photonic image processing with a VCSEL neuron
Authors: Robertson Joshua , Kirkland Paul , Alanis Juan Arturo , Hejda Matěj , Bueno Julián , Di Caterina Gaetano , Hurtado Antonio 
Published: March 2022

AbstractThe ever-increasing demand for artificial intelligence (AI) systems is underlining a significant requirement for new, AI-optimised hardware. Neuromorphic (brain-like) processors are one highly-promising solution, with photonic-enabled realizations receiving increasing attention. Among these, approaches based upon vertical cavity surface emitting lasers (VCSELs) are attracting interest given their favourable attributes and mature technology. Here, we demonstrate a hardware-friendly neuromorphic photonic spike processor, using a single VCSEL, for all-optical image edge-feature detection. This exploits the ability of a VCSEL-based photonic neuron to integrate temporally-encoded pixel data at high speed; and fire fast (100 ps-long) optical spikes upon detecting desired image features. Furthermore, the photonic system is combined with a software-implemented spiking neural network yielding a full platform for complex image classification tasks. This work therefore highlights the potential of VCSEL-based platforms for novel, ultrafast, all-optical neuromorphic processors interfacing with current computation and communication systems for use in future light-enabled AI and computer vision functionalities.
Calibration and validation of the Angstrom–Prescott model in solar radiation estimation using optimization algorithms
Authors: Banihashemi Dehkordi Seyedeh Nafiseh , Bakhtiari Bahram , Qaderi Kourosh , Ahmadi Mohammad Mehdi 
Published: March 2022

AbstractThe Angstrom–Prescott (A–P) model is widely suggested for estimating solar radiation (Rs) in areas without measured or deficiency of data. The aim of this research was calibration and validation of the coefficients of the A–P model at six meteorological stations across arid and semi-arid regions of Iran. This model has improved by adding the air temperature and relative humidity terms. Besides, the coefficients of the A–P model and improved models have calibrated using some optimization algorithms including Harmony Search (HS) and Shuffled Complex Evolution (SCE). Performance indices, i.e., Root Mean Square Error (RMSE), Mean Bias Error, and coefficient of determination (R2) have used to analyze the models ability in estimating Rs. The results indicated that the performance of the A–P model had more precision and less error than improved models in all the stations. In addition, the best results have obtained for the A–P model with the SCE algorithm. The RMSE varies between 0.82 and 2.67 MJ m−2 day−1for the A–P model with the SCE algorithm in the calibration phase. In the SCE algorithm, the values of RMSE had decreased about 4% and 7% for Mashhad and Kerman stations in the calibration phase compared to the HS algorithm, respectively.
A green protocol for the electrochemical synthesis of a fluorescent dye with antibacterial activity from imipramine oxidation
Authors: Souri Zahra , Masoudi Khoram Mahmood , Nematollahi Davood , Mazloum-Ardakani Mohammad , Alizadeh Hojjat 
Published: March 2022

AbstractElectrochemical oxidation of imipramine (IMP) has been studied in aqueous solutions by cyclic voltammetry and controlled-potential coulometry techniques. Our voltammetric results show a complex behavior for oxidation of IMP at different pH values. In this study, we focused our attention on the electrochemical oxidation of IMP at a pH of about 5. Under these conditions, our results show that the oxidation of IMP leads to the formation of a unique dimer of IMP (DIMP). The structure of synthesized dimer is fully characterized by UV–visible, FTIR,1H NMR,13C NMR and mass spectrometry techniques. It seems that the first step in the oxidation of IMP is the cleavage of the alkyl group (formation of IMPH). After this, a domino oxidation-hydroxylation-dimerization-oxidation reaction, converts IMPH to (E)-10,10′,11,11′-tetrahydro-[2,2′-bidibenzo[b,f]azepinylidene]-1,1′(5H,5′H)-dione (DIMP). The synthesis of DIMP is performed in an aqueous solution under mild conditions, without the need for any catalyst or oxidant. Based on our electrochemical findings as well as the identification of the final product, a possible reaction mechanism for IMP oxidation has been proposed. Conjugated double bonds in the DIMP structure cause the compound to become colored with sufficient fluorescence activity (excitation wave-length 535 nm and emission wave-length 625 nm). Moreover, DIMP has been evaluated for in vitro antibacterial. The antibacterial tests indicated that DIMP showed good antibacterial performance against all examined gram-positive and gram-negative bacteria (Staphylococcus aureus, Bacillus cereus, Escherichia coliandShigella sonnei).
Weakly supervised end-to-end artificial intelligence in gastrointestinal endoscopy
Authors: Buendgens Lukas , Cifci Didem , Ghaffari Laleh Narmin , van Treeck Marko , Koenen Maria T. , Zimmermann Henning W. , Herbold Till , Lux Thomas Joachim , Hann Alexander , Trautwein Christian , Kather Jakob Nikolas 
Published: March 2022

AbstractArtificial intelligence (AI) is widely used to analyze gastrointestinal (GI) endoscopy image data. AI has led to several clinically approved algorithms for polyp detection, but application of AI beyond this specific task is limited by the high cost of manual annotations. Here, we show that a weakly supervised AI can be trained on data from a clinical routine database to learn visual patterns of GI diseases without any manual labeling or annotation. We trained a deep neural network on a dataset of N = 29,506 gastroscopy and N = 18,942 colonoscopy examinations from a large endoscopy unit serving patients in Germany, the Netherlands and Belgium, using only routine diagnosis data for the 42 most common diseases. Despite a high data heterogeneity, the AI system reached a high performance for diagnosis of multiple diseases, including inflammatory, degenerative, infectious and neoplastic diseases. Specifically, a cross-validated area under the receiver operating curve (AUROC) of above 0.70 was reached for 13 diseases, and an AUROC of above 0.80 was reached for two diseases in the primary data set. In an external validation set including six disease categories, the AI system was able to significantly predict the presence of diverticulosis, candidiasis, colon and rectal cancer with AUROCs above 0.76. Reverse engineering the predictions demonstrated that plausible patterns were learned on the level of images and within images and potential confounders were identified. In summary, our study demonstrates the potential of weakly supervised AI to generate high-performing classifiers and identify clinically relevant visual patterns based on non-annotated routine image data in GI endoscopy and potentially other clinical imaging modalities.
The design of an inkjet drive waveform using machine learning
Authors: Kim Seongju , Cho Minsu , Jung Sungjune 
Published: March 2022

AbstractA drive waveform, which needs to be optimized with ink’s fluid properties, is critical to reliable inkjet printing. A generally adopted rule of thumb for its design is mostly dependent on time-consuming and repetitive manual manipulation of its parameters. This work presents a closed-loop machine learning approach to designing an optimal drive waveform for satellite-free inkjet printing at a target velocity. Each of the representative 11 model inks with different fluid properties was ink-jetted with 1100 distinct waveform designs. The high-speed images of their jetting behaviors were acquired and the big datasets of the resulting drop formation and velocity were extracted from the jetting images. Five machine learning models were examined and compared to predict the characteristics of jetting behavior. Among a variety of machine learning models, Multi-layer Perceptron affords the highest prediction accuracy. A closed-loop prediction algorithm that determined the optimal set of waveform parameters for satellite-free drop formation at a target velocity and employed the most superior learning model was established. The proposed method was confirmed through the printing of an unknown model ink with a recommended waveform.
Gabrb3 endothelial cell-specific knockout mice display abnormal blood flow, hypertension, and behavioral dysfunction
Authors: Agrud Anass , Subburaju Sivan , Goel Pranay , Ren Jun , Kumar Ashwin Srinivasan , Caldarone Barbara J. , Dai Wangde , Chavez Jesus , Fukumura Dai , Jain Rakesh K. , Kloner Robert A. , Vasudevan Anju 
Published: March 2022

AbstractOur recent studies uncovered a novel GABA signaling pathway in embryonic forebrain endothelial cells that works independently from neuronal GABA signaling and revealed that disruptions in endothelial GABAA receptor-GABA signaling from early embryonic stages can directly contribute to the origin of psychiatric disorders. In the GABAA receptor β3 subunit endothelial cell conditional knockout (Gabrb3ECKO) mice, the β3 subunit is deleted selectively from endothelial cells, therefore endothelial GABAA receptors become inactivated and dysfunctional. There is a reduction in vessel densities and increased vessel morphology in the Gabrb3ECKO telencephalon that persists in the adult neocortex. Gabrb3ECKO mice show behavioral deficits such as impaired reciprocal social interactions, communication deficits, heightened anxiety, and depression. Here, we characterize the functional changes in Gabrb3ECKO mice by evaluating cortical blood flow, examine the consequences of loss of endothelial Gabrb3 on cardiac tissue, and define more in-depth altered behaviors. Red blood cell velocity and blood flow were increased in the cortical microcirculation of the Gabrb3ECKO mice. The Gabrb3ECKO mice had a reduction in vessel densities in the heart, similar to the brain; exhibited wavy, myocardial fibers, with elongated ‘worm-like’ nuclei in their cardiac histology, and developed hypertension. Additional alterations in behavioral function were observed in the Gabrb3ECKO mice such as increased spontaneous exploratory activity and rearing in an open field, reduced short term memory, decreased ambulatory activity in CLAMS testing, and altered prepulse inhibition to startle, an important biomarker of psychiatric diseases such as schizophrenia. Our results imply that vascular Gabrb3 is a key player in the brain as well as the heart, and its loss in both organs can lead to concurrent development of psychiatric and cardiac dysfunction.
Effect of prepartum dietary energy density on beef cow energy metabolites, and birth weight and antioxidative capabilities of neonatal calves
Authors: Chen Hao , Wang Chunjie , Huasai Simujide , Chen Aorigele 
Published: March 2022

AbstractThe objective of this study was to investigate the effect of prepartum diets that differ in energy density on beef cow energy metabolites and birth weight, immunity and antioxidative capabilities of neonatal calves. On d 0 (approximately 45 d before calving), 90 multiparous Angus cows (BW = 510 ± 16 kg) were randomly allocated into 1 of 9 drylot pens (10 cows/pen). Each pen was randomly assigned to a treatment condition (three pens/treatment), the cows in each treatment were assigned randomly to receive a high-energy (HE) density diet (NEm = 1.67 Mcal/kg of DM), medium-energy (ME) density diet (NEm = 1.53 Mcal/kg of DM), or low-energy (LE) density diet (NEm = 1.36 Mcal/kg of DM). Blood samples were collected − 45, − 21, − 14, and − 7 d from calving, and plasma concentrations of cortisol, glucose, total protein, β-hydroxybutyrate (BHBA), and nonesterified fatty acids (NEFAs) were measured. After calving, the birth weights, body height, body length, thoracic girth and umbilical girth of the calves in each group were recorded, and blood samples were collected for analysis of IgG, IL-2, IL-4, IL-6, total antioxidant capacity, superoxide dismutase, glutathione peroxidase, and maleic dialdehyde levels. The amounts of feed offered and orts were recorded for individual cows 4 d/wk. The results indicated that although dry matter intake (DMI) levels did not differ among the LE, ME, and or HE groups before parturition, the group that received the HE diet had higher plasma glucose concentrations and lower prepartum blood NEFA concentrations than the other groups. Birth weight, body height, thoracic girth, and levels of IL-2, cortisol, total antioxidant capacity, and superoxide dismutase were increased in calves of the HE group compared with those of the LE group. The plasma IL-4 and serum IgG concentrations tended to be decreased in the ME group compared with the HE group, and the ME group had lower maleic dialdehyde concentrations; maleic dialdehyde levels were significantly increased in the LE group compared with the HE group. Overall, these results indicate that feeding of a low-energy diet during the last 45 d before parturition has negative effects on the growth, immunity, and antioxidative capabilities of neonatal calves. Increasing maternal energy density during late gestation may be useful to improve the energy status of cows.
Unraveling structural and conformational dynamics of DGAT1 missense nsSNPs in dairy cattle
Authors: Pathak Rajesh Kumar , Lim Byeonghwi , Park Yejee , Kim Jun-Mo 
Published: March 2022

AbstractCattle are domestic animals that have been nourishing humans for thousands of years. Milk from cattle represents a key source of high-quality protein, fat, and other nutrients. The nutritional value of milk and dairy products is closely associated with the fat content, providing up to 30% of the total fat consumed in the human diet. The fat content in cattle milk represents a major concern for the scientific community due to its association with human health. The relationship between milk fat content and diacylglycerol o-acyltransferase 1 gene (DGAT1) is well described in literature. Several studies demonstrated the difference in fat contents and other milk production traits in a wide range of cattle breeds, to be associated with missense non-synonymous single nucleotide polymorphisms (nsSNPs) of the DGAT1 gene. As a result, an nsSNPs analysis is crucial for unraveling the DGAT1 structural and conformational dynamics linked to milk fat content. DGAT1-nsSNPs are yet to be studied in terms of their structural and functional impact. Therefore, state-of-the-art computational and structural genomic methods were used to analyze five selected variants (W128R, W214R, C215G, P245R, and W459G), along with the wild type DGAT1. Significant structural and conformational changes in the variants were observed. We illustrate how single amino acid substitutions affect DGAT1 function, how this contributes to our understanding of the molecular basis of variations in DGAT1, and ultimately its impact in improving fat quality in milk.
Compatibility and synergistic interactions of fungi, Metarhizium anisopliae, and insecticide combinations against the cotton aphid, Aphis gossypii Glover (Hemiptera: Aphididae)
Authors: Nawaz Ahmad , Razzaq Fatima , Razzaq Amna , Gogi Muhammad Dildar , Fernández-Grandon G. Mandela , Tayib Muhammad , Ayub Muhammad Ahsin , Sufyan Muhammad , Shahid Muhammad Rafiq , Qayyum Mirza Abdul , Naveed Muhammad , Ijaz Anam , Arif Muhammad Jalal 
Published: March 2022

AbstractAphids are major pests affecting cereals, vegetables, fruit, forestry and horticultural produce. A multimodal approach may be an effective route to controlling this prolific pest. We assessed the individual and combined effect of eight insecticides and the entomopathogenic fungi,Metarhizium anisopliae(Metschin.) against the cotton aphid,Aphis gossypiiGlover (Hemiptera: Aphididae), under laboratory conditions. Six of the insecticides tested were found to be highly compatible (flonicamid, imidacloprid, nitenpyram, dinotefuran, pyriproxyfen and spirotetramat), showing positive integration with the fungus and were selected for bioassays. The combination mixtures (1:1 ratio ofM. anisopliae: insecticide) were significantly more toxic toA. gossypiithan individual treatments. Maximum mortality (91.68%) ofA. gossypiiwas recorded with combination of flonicamid andM. anisopliae(2.4 × 106 cfu/ml) 72 h after application. While minimum mortality (17.08%) was observed with the individual treatment ofM. anisopliae(2.4 × 106 cfu/ml). The insecticides revealed toxicity consistent with their compatibility withM. anisopliae,ranking for efficacy exactly as they did for compatibility. In addition, the synergy factor (SF) and co-toxicity coefficient (CTC) values indicated synergistic interactions at different time intervals. The synergistic efficacy revealed the potential of fungus-insecticide integration against sucking insect pests.
A metagenomic analysis of the bacterial microbiome of limestone, and the role of associated biofilms in the biodeterioration of heritage stone surfaces
Authors: Skipper Philip J. A. , Skipper Lynda K. , Dixon Ronald A. 
Published: March 2022

AbstractThere is growing concern surrounding the aesthetic and physical effects of microbial biofilms on heritage buildings and monuments. Carboniferous stones, such as limestone and marble, are soluble in weak acid solutions and therefore particularly vulnerable to biocorrosion. This paper aims to determine the differences and commonalities between the microbiome of physically damaged and undamaged Lincolnshire limestone, an area of research which has not been previously studied. A lack of information about the core microbiome has resulted in conflicting claims in the literature regarding the biodeteriorative potential of many microorganisms. To address this, we used metagenomics alongside traditional microbiological techniques to produce an in-depth analysis of differences between the bacterial microbiomes found on deteriorated and undamaged external limestone surfaces. We demonstrate there is a core microbiome on Lincolnshire limestone present on both damaged and undamaged surfaces. In addition to the core microbiome, significant differences were found between species isolated from undamaged compared to damaged surfaces. Isolated species were characterised for biofilm formation and biodeteriorative processes, resulting in the association of species with biodeterioration that had not been previously described. Additionally, we have identified a previously undescribed method of biofilm-associated biomechanical damage. This research adds significant new understanding to the field, aiding decision making in conservation of stone surfaces.
Transboundary aerosol transport process and its impact on aerosol-radiation-cloud feedbacks in springtime over Northeast Asia
Authors: Lee Hyo-Jung , Jo Yu-Jin , Kim Seungwoo , Kim Daecheol , Kim Jong-Min , Choi Daniel , Jo Hyun-Young , Bak Juseon , Park Shin-Young , Jeon Wonbae , Kim Cheol-Hee 
Published: March 2022

AbstractNortheast Asia has been suffering from dramatic increases of particulate matter (PM) since the late 1990s, and it still continues to undergo haze despite various abating regulations. In this study, we investigated aerosol-cloud-precipitation (ACP) interactions with the varied PM, and the impact of long-range transport (LRT) process on ACP in springtime was assessed in Northeast Asia. Our long-term (1995–2019) analysis of PM10exhibited the correlation with decreases of both sunshine duration and drizzle occurrences that can be interpreted as direct and indirect aerosol effects, while cloud cover induced by the varied PM10was found only in more than 90% cloud cover (9/10–10/10 category). The online WRF-Chem with wind-blown dust simulation indicated that cloud water was affected by secondary inorganic aerosol (SIA) formation near the surface in upwind areas dominantly, whereas, along the LRT pathway, cloud water perturbation altitudes were increased quasi-linearly toward downward between 1 and 3 km. The gas-to-particle conversion ratios of sulfur ([SO42−]/[SO2 + SO42−]) and nitrogen ([NO3−]/[NO2 + NO3−]) both remain aloft long at the same vertical levels of most perturbed cloud altitude enough to be transported over long distance in springtime. Formations of sulfate and nitrate showed different ACP interaction timing; distinctive shifts in the ratios observed at the exit (Shanghai-Yellow Sea) by nitrate, and entrance areas (Seoul-Tokyo) by sulfate along the LRT pathway, respectively, with higher ratios of 0.8 or more in springtime. Our results indicate that ACP processes have been enhanced at a LRT-related altitude with different SIA production timings that can be considered in species-specific springtime PM abatements over Northeast Asia.