bluuebunny/crossref_metadata_2025_split huggingface dataset:
A report on the chloroplast genome of Melia dubia Cav. (Sapindales: Meliaceae), a potential agroforestry species
Authors: Samji Aghila , Eashwarlal Komal , Shanmugavel Senthilkumar , Kumar K. Santhosh , Warrier Rekha R 
Published: April 2022

Abstract
Background: Melia dubia Cav. is a fast-growing plywood species gaining popularity due to high economic returns. This study aimed to assemble and annotate the chloroplast (cp) genome of M.dubia and compare it with previously published cp genomes within the Meliaceae family. Methods and Results: The chloroplast genome was constructed by the de novo and reference-based assembly of paired-end reads generated by long-read sequencing of genomic DNA. The cp genome, sized 171,956 bp, comprised a typical angiosperm quadripartite structure. The large single-copy (LSC) region of 76,055 bp and a small single-copy (SSC) region of 18,693 bp, covers 55% of the genome. The pair of inverted repeats (IRA and IRB) of 38,604 bp each (covering 45% of the genome). We identified unique genes (112), including protein-coding genes (79), tRNA (29) and 4 rRNA genes. Phylogenetic analysis using complete cp genomes of 11 species from Meliaceae revealed that M. dubia and M. azedarach hared a sister clade. Comparative analysis using cp genome of M.dubia , M.azedarach and Azadirachta indica revealed a high sequence similarity ( >70%). Five intergenic regions were highly conserved among the three cp genomes. The gene trnG-UCC at LSC region was found to be more divergent in M.dubia and M.azedarach while it shows complete conservation within M.dubia and A.indica. Conclusions: The available levels of taxonomic expertise and clarity in species delineation within the Melia genus is low. The information generated provides scope for identifying new barcodes which increases the discriminatory power of the species within the genus beyond morphological identification.
Image Modification Using Deep Neural Cellular Automata
Authors: Gore Kaushal , Kothari Sanskar , Kamtalwar Saurav , Kokate Chinmay , Soman Koustubh 
Published: April 2022

Abstract
Abstract — Art Style Transfer is part of the rapidly growing AI Art community of recent times. Pioneered by Gatys et al, this class of methods makes it possible to convey styles, textures, patterns, and more. to a target image. The expressive masking feature of mainframe vision models such as VGG19 is used as a lossy function. The method of performing this transformation takes many forms, from the original method that directly optimizes the image pixels to more recent forms that form the CNN form to create a generic transport network. The method presented in this article is similar to more recent methods, but takes advantage of a new class of deep learning methods, deep neural automation. This new method provides the ability to convert any image into a target type that, like the CNN method mentioned previously, uses the same automatic data update rules over and over again. This paper contains how to use NCAs to transform images. also contains the Gatys et. al. type style transfer and the other a OpenAI CLIP based version where a prompt can be given to train NCAs to perform that transformation.
Application of Artificial Intelligence in static Formation temperature estimation
Authors: AL-FAKIH ABDULRAHMAN , Kaka SanLinn 
Published: April 2022

Abstract
This study presents a new model to predict the static formation temperature at multiple oil fields using multiple machine learning algorithms. Results are compared with the real obtained temperatures from two wells. The model developed in this study uses Python and Matlab to predict static formation temperature according to several machine learning algorithms including artificial neural networks, fuzzy logic, k-nearest neighbors, and random forest algorithms. Also, we used well-known analytical methods called line-source-Horner and spherical & radial heat-flow (SRF). The following are the key findings: Using well-known analytical methods, we estimated formation hole temperatures, our results demonstrated that The Horner approach overestimates the static temperature of the formation., but the SRF method gives more accurate temperatures. Using Python and MATLAB programming languages, based on machine learning models, we developed a novel model for forecasting static formation temperature., examined the modeling data and outcomes, and found that Random Forest (RF), Fuzzy logic (FL), and K-nearest neighbors (KNN) outperformed Artificial Neural Network (ANN). Therefore, the performance of the proposed model for estimating the static well temperature achieved an error percentage of AAPE 0.003% and R2 is 0.99%. The findings generated by the unique new model computation and the measured test data are substantially matched when compared to computed data and observed temperature data. The novelty of this newly developed AI model is that it will serve as a practical and inexpensive tool for SFT determination in geothermal and petroleum wells.
Keywords: Static Formation temperature; artificial intelligence; predicting the static formation temperature at multiple oil fields; Honor method; SRF method
Cross-resistance between macrocyclic lactones in populations of Rhipicephalus microplus in Brazil’s semiarid region
Authors: Ferreira Larissa Claudino , Lima Estefany Ferreira , Silva Ana Luzia Peixoto , Oliveira Clarisse Silva Menezes , Filho Geraldo Moreira Silva , Sousa Luana Carneiro , Klafke Guilherme Marcondes , Feitosa Thais Ferreira , Vilela Vinícius Longo Ribeiro 
Published: April 2022

Abstract
Rhipicephalus microplus, also known as the cattle tick, is the parasite with the greatest impact on cattle in Brazil. The most common method for controlling this tick is the application of synthetic chemical acaricides, especially ivermectin, which belongs to the group of macrocyclic lactones (MLs). However, because ivermectin is widely used, there is concern about the development of cross-resistance within this chemical class. Thus, engorged females were collected from farms with a history of resistance to ivermectin, which was the only one among the MLs that was used as an anthelmintic drug. Using the larval immersion test (LIT) technique, bioassays were performed with ivermectin, moxidectin and eprinomectin on populations of R. microplus from the semiarid region of the states of Paraíba and Ceará. Epidemiological questionnaires were applied to collect information about tick control management. All the evaluated populations showed cross-resistance between ivermectin and moxidectin, but only one population showed cross-resistance between ivermectin and eprinomectin. Weekly or monthly administration of injectable 1% ivermectin on farms was reported. It was concluded that the frequent use of ivermectin may lead to the development of cross-resistance to moxidectin. For eprinomectin, despite the structural similarity, cross-resistance was not observed in three tick populations.
Osteosarcoma transcriptome data exploration reveals STC2 as a novel risk indicator in disease progression
Authors: Wang Ziyue , Zeng Zixin , Gao Feng , Gui Ziwei , Du Juan , Shen Ningning , Shang Yangwei , Yang Zhiqing , Shang Lifang , Wei Rong , Ma Wenxia , Wang Chen 
Published: April 2022

Abstract
Background Osteosarcoma has been the most common primary bone malignant tumor in children and adolescents. Despite the considerable improvement in the understanding of genetic events attributing to the rapid development of molecular pathology, the current information is still lacking considering the comprehensive and highly heterogeneous nature of osteosarcoma. The study is to identify more potential responsible genes during the development of osteosarcoma, thus identifying promising gene indicators and aiding more precise interpretation of the disease. Methods Firstly, from GEO database, osteosarcoma transcriptome microarrays were used to screen the abnormally expressed genes (AEGS) in cancer comparing to normal bone samples, followed by GO/KEGG interpretation, risk score assessment and survival analysis of the genes to select a credible key gene. Further, the basic physicochemical properties, predicted cellular location, gene expression in human cancers, association with clinical pathological features and the potential signaling pathways involved in the key gene’s regulation on osteosarcoma development were preliminary explored. Results A total of 24430 genes were identified to express abnormally in osteosarcoma versus normal bone samples, and the genes were classified into four groups based on the difference level, further genes interpretation indicated that the high abnormal level (>8 fold) genes were mainly located extracellular and related to matrix structural constituent regulation. Meanwhile, module function analysis of the 67 high abnormal level (>8 fold) AEGS revealed a 22-gene containing extracellular matrix regulation associated hub gene cluster. Further survival analysis of the 22 genes revealed that STC2 was an independent prognosis indicator in osteosarcoma. Moreover, after the validation of changed expression of STC2 in cancer vs normal tissues using local hospital osteosarcoma samples by IHC experiment, the gene’s physicochemical property revealed STC2 as a cellular stable and hydrophilic protein, and the gene’s association with osteosarcoma clinical pathological parameters, expression in pan-cancers and the probable biological functions and signaling pathways it involved were explored. Conclusions Using multiple bioinformatic analysis and local hospital samples validation, we revealed the aberrant gain of expression of STC2 in osteosarcoma, which associated statistical significantly with patients survival, and the gene’s clinical features and potential biological functions were also explored. Although the results shall provide inspiring insights into further understanding of the disease, further experiments and detailed rigorous clinical trials are needed to reveal its potential drug-target role in clinical medical use.
A new species of Desmodesmus sp. from high altitude area was discovered and its isolated, purification, amplification culture and species identification were studied
Authors: Wang Jinhu , Zhang Qiangying , Chen Naijiang , Chen Junyu , Zhou Jinna , Li Jing , Wei Yanli , Bu Duo 
Published: April 2022

Abstract
Plateau microalgae play a key role in maintaining water quality in these lakes and rivers on the Qinghai-Tibet plateau. Plateau microalgae have wide application prospects in environmental purification, biotechnology, medicine and cosmetics, food industry and renewable energy. In order to get the high biomass of microalgae that exist in nature, microalgae with the largest biomass was screened from natural water samples by filtration, preculture and plate scribing separation. Microalgae with the largest biomass was screened from natural water samples by filtering first, pre-culturing and agar plate scribing separation. Identified by 18S rRNA as Desmodesmus sp. and constructed an neighbor-joining phylogenetic tree based on 18S rRNA sequences; Further studies have been made on the light-absorbing properties of plateau Desmodesmus sp.. The characteristic absorption peak of Desmodesmus sp. on the plateau was found at 689nm in the visible region by full wavelength scanning with UV-Vis spectrophotometer. For Desmodesmus sp. which is easy to settle in the process of amplification culture. By monitoring the change trend of total nitrogen, total phosphorus, pH and electrical conductivity in algae solution system, it was determined that logarithmic phase of the growth and the best transfer time of Desmodesmus sp. were 15-20 days.
Isolation and characterization of newly Pediococcus spp. and Leuconostoc spp. with antimicrobial activity from organic meat sausages
Authors: Moslem Mina Nasiri , Ghasemi Mohammad Faezi , Amirmozafari Nour , Ranji Najmeh 
Published: April 2022

Abstract
Organic meat products are well known for their probiotic values due to the presence of probiotic lactic acid bacteria (LAB) such as Lactobacillus, Leuconostoc, Lactococcus, and Pediococcus strains. In this study, two Pediococcus spp. and three Leuconostoc spp. with antimicrobial activity were isolated from vacuum-packed organic meat sausages. All five isolates were characterized by morphological, biochemical, 16S rRNA analysis, and designated as MN-A, MN-B, MN-A2, MN-A2-1, and MN-A3. The results showed that the isolate MN-A and MN-B belonged to the strain Pediococcus acidilactici, and the MN-A2, MN-A2-1, and MN-A3 isolates were identified as Leuconostoc mesentroieds strains. Amongst the isolates, the strain MN-B showed the highest antimicrobial activity against the Micrococcus luteus PTCC 1408. The growth kinetics and antimicrobial activity of the strain MN-B against Lactobacillus casei ATCC 39392 was determined in MRS broth medium. Also, bacteriocin produced by the strains MN-B revealed antimicrobial activity against selected food-borne pathogens including, Salmonella enterica subsp. enterica serotype Typhimurium PTCC 1709, Staphylococcus aureus PTCC 1113, Listeria monocytogenes PTCC1302, and Listeria inovani PTCC 1303. Bacteriocin produced by the MN-B strain was partially purified using the adsorption-desorption method followed by dialyzes. The molecular weight of bacteriocin was about 5.0 KDa by SDS-PAGE analysis.
Conv-Transformer Architecture for Unconstrained Off-LineUrdu Handwriting Recognition
Authors: Riaz Nauman , Arbab Haziq , Maqsood Arooba , Nasir Khuzaeymah Bin , Ul-Hasan Adnan , Shafait Faisal 
Published: April 2022

Abstract
Unconstrained off-line handwriting text recognition in general and for Arabic-like scripts in particular is a challenging task and is still an active researcharea. Transformer based models for English handwriting recognition have recently shown promising results.In this paper, we have explored the use of transformerarchitecture for Urdu handwriting recognition. The useof a Convolution Neural Network before a vanilla fullTransformer and using Urdu printed text-lines alongwith handwritten text lines during the training are thehighlights of the proposed work. The Convolution Layers act to reduce the spatial resolutions and compensate for the n2 complexity of transformer multi-head attention layers. Moreover, the printed text images inthe training phase help the model in learning a greaternumber of ligatures (a prominent feature of Arabiclike scripts) and a better language model. Our modelachieved state-of-the-art accuracy (CER of 5.31%) onpublicly available NUST-UHWR dataset [1].
Streamlining sporozoite isolation from mosquitoes by leveraging the dynamics of migration to the salivary glands
Authors: Pathak Ashutosh K. , Shiau Justine C. , Franke-Fayard Blandine , Shollenberger Lisa M. , Harn Donald A. , Kyle Dennis E. , Murdock Courtney C. 
Published: April 2022

Abstract
Background
Sporozoites isolated from the salivary glands of Plasmodium-infected mosquitoes are a prerequisite for several basic and pre-clinical applications. Although salivary glands are pooled to maximize sporozoite recovery, insufficient yields pose logistical and analytical hurdles; thus, predicting yields prior to isolation would be valuable. Preceding oocyst densities in the midgut is an obvious candidate, although it is unclear whether our current understanding of its relationship with sporozoite densities can be used to maximize yields.
Methods
This study presents a retrospective analysis of mosquitoes infected with two strains of the rodent-specific P. berghei. Mean oocyst densities were estimated in the midguts earlier in the infection (11–15 days post-bloodmeal), with sporozoites pooled from the salivary glands later in the infection (17–29 days). Generalized linear mixed effects models were used to determine if 1) mean oocyst densities can predict sporozoite yields from pooled salivary glands, 2) whether these densities can capture differences in rates of sporozoite invasion of salivary glands, and 3) if the interaction between oocyst densities and time could be leveraged to boost overall yields.
Results
The non-linear effect of mean oocyst densities confirmed the role of density-dependent constraints in limiting yields beyond certain oocyst densities. Irrespective of oocyst densities however, the continued invasion of salivary glands by the sporozoites boosted recoveries over time (17–29 days post-bloodmeal) for either parasite strain.
Conclusions
Sporozoite invasion of the salivary glands over time can be leveraged to maximize yields for P. berghei. In general, however, invasion of the salivary glands over time is a critical fitness determinant for all Plasmodium species (extrinsic incubation period, EIP). Thus, delaying sporozoite collection could, in principle, substantially reduce dissection effort for any parasite within the genus, although our results also recommend closer examination of how changes in sporozoites densities over time modify parasite infectivity for the next host.
TNFAIP8 in Mesenchymal Glioblastoma Correlates with Metabolic Dysfunction and Poor Prognosis
Authors: Zhang Jinsen , Zhang Zongpu , Zhang Huaichao , Xiao Xing , Fu Minjie , Feng Yuan , Wang Qijun , Hua Wei 
Published: April 2022

Abstract
TNFAIP8, a cytosolic TNF-α-inducible oncogenic molecule, plays pivotal roles in many types of cancers. However, the effect of TNFAIP8 on glioma remains elusive. In this study, we confirmed that TNFAIP8 promoted glioma viability and motility through alteration of nucleotide metabolism and tricarboxylic acid (TCA) cycle. Firstly, bioinformatic analysis indicated that TNFAIP8 expression elevated along with the WHO grade and predicted adverse prognosis in gliomas. Moreover, TNFAIP8 was enriched in gliomas with progressive genotypes, serving as an efficient indicator for mesenchymal glioma. To determine its function in glioblastoma progression, cell viability, migration and invasion were examined by loss/gain of function experiments. TNFAIP8 promoted glioma proliferation, migration, invasion and transition to mesenchymal phenotype. These findings were further confirmed in vivo. RNA sequencing and liquid chromatography-mass spectrometry (LC-MS) results showed impaired nucleotide metabolism and TCA cycle after TNFAIP8 knockdown, implying that TNFAIP8 enhanced glioblastoma progression via metabolic dysfunction. In summary, this study identified a novel oncogene in glioma with great potential for prognostic prediction and subtype identification. Alterations in metabolic process and transition towards mesenchymal subtype were supposed to be the underlying mechanisms for the oncogenic function of TNFAIP8.
Selective Electroreduction of CO2 to C2+ Biofuels using Graphitic Frustrated Lewis Pair Catalyst
Authors: Kim Hyun-Tak , Park Jaehyun , Mun Jinhong , Shin HyeonOh , Roh Deok-Ho , Kwon Junhyeok , Kim Sungtae , Lee Geunsik , Kang Seok Ju , Kwon Tae-Hyuk 
Published: April 2022

Abstract
Efficient electroreduction of CO2 to multicarbon products is a complicated reaction because of the high energy barriers for CO2 activation and C–C coupling. Here, we design a graphitic frustrated Lewis pair catalyst doped with boron and nitrogen (BN-GFLP) for reducing CO2 to multicarbon products. Multicarbon (C2+) biofuels (i.e., ethanol and n-propanol) are identified as the major products with a C2+ Faradaic efficiency of 87.9% at a partial current density of −6.0 mA/cm2 (C2+ Faradaic efficiency of 70.7% at a partial current density of −10.6 mA/cm2). Furthermore, density functional theory calculations reveal that the dual binding site of FLP reduces the reaction free energies required for CO2 activation and C–C coupling. Consequently, energetically favourable CO2-reduction pathways are proposed, and selectivity for the production of ethanol and n-propanol are determined. Based on our results, we suggest a molecular design strategy for the next-generation CO2 reduction catalysts for green oceans and the atmosphere.
Ammonium recovery from agro-industrial digestate using bioelectrochemical systems
Authors: Carucci A. , Erby G. , Puggioni G. , Spiga D. , Frugoni F. , Milia S. 
Published: April 2022

Abstract
Growing food and biomass production at the global scale has determined a corresponding increase in the demand for and use of nutrients. In this study, the possibility of recovering nitrogen from agro-industrial digestate using bioelectrochemical systems was investigated: two microbial electrolysis cells (MECs) were fed with synthetic and real digestate (2.5 gNH4+-N L−1). Carbon felt and granular graphite were used as anodes in MEC-1 and MEC-2, respectively. As to synthetic wastewater, the optimal nitrogen load (NL) for MEC-1 and -2 was 1.25 and 0.75 gNH4+-N d−1, respectively. MEC-1 showed better performance in terms of NH4+-N removal efficiency (39 ± 2.5%) and recovery rate (up to 70 gNH4+-N m−2d−1), compared to MEC-2 (33 ± 4.7% and up to 30 gN m−2d−1, respectively). At the optimal hydraulic retention time, lower NH4+-N removal efficiencies and recovery rates were observed when real digestate was fed to MEC-1 (29 ± 6.6% and 60 ± 13 gNH4+-N m−2d−1, respectively) and MEC-2 (21 ± 7.9% and 10 ± 3.6 gNH4+-N m−2d−1, respectively), likely due to the higher complexity of the influent. The average energy requirements were 3.6–3.7 kWh kgNremoved−1, comparable with values previously reported in the literature and lower than conventional ammonia recovery processes. Results are promising and may reduce the need for costly and polluting processes for nitrogen synthesis.
Application of different control algorithms on a ‘home-made’ temperature control lab kit
Authors: Nguyen Nhu Tuong An , Do Vinh Quang , Pham The Thinh , Tran Nguyen Tuan 
Published: April 2022

Providing enough facilities for students to do laboratory activities is important. An existing useful kit was proposed for students learning a variety of control engineering topics. A temperature control lab kit is made from scratch using common electronics components as a replacement for the original TCLab introduced by Hedengren (Hedengren et al., 2019). Mathematical models of the system derived from theoretical and experimental methods are simulated in Matlab/Simulink to verify their accuracy to the physical kit. Different control algorithms such as: On/Off, PID, Fuzzy are then applied on the Kit as well as its mathematical models to illustrate their control feasibility. Human machine interface (HMI) is also designed using Matlab GUI allowing an operator to select a control algorithm, tune control parameters and monitor parameters of the process. Experimental results show that the derived models can reflect quite well dynamics of the physical kit with temperature deviation among them in the range of ±3°C. This confirms that the kit is well-suited for teaching different control topics such as system modelling, system identification, classical control and advanced control algorithms.