bluuebunny/crossref_metadata_2025_split huggingface dataset:
Bubble–bitumen detachment in a flowing water channel
Authors: Zhou Joe Z. 
Published: April 2022

AbstractEffect of water flow velocity (≤3 m/s) on bubbles detaching from bitumen was examined in a water channel at room temperature. The results showed different behaviours of bubble–bitumen detachment for different sizes of bubbles. With increasing water flow speed, a larger bubble (>0.15–0.2 cm) underwent the following steps before detaching from the bitumen layer: deformation; neck formation; the bubble broke up from the neck, with the top portion sheared away, leaving the bottom portion as a small bubble stuck to bitumen; and then, the small bubble detached from the bitumen and was carried away by further increasing water flow. Smaller bubbles (<0.1–0.15 cm) detached from bitumen after deformation without breaking up, with increasing water flow. An empirical correlation between the size of bubbles detaching from bitumen with water flow velocity/shear rate was established. At a flow velocity of 3 m/s, only bubbles smaller than 250–300 μm might be able to stay attached to bitumen, or a shear rate higher than 2500 s−1 is needed to detach a 250–300 μm bubble from bitumen.
Inductive effect and hyperconjugation in radical chain reactions – new learning opportunity to work out key concepts of organic chemistry
Authors: Zimmermann Marc , Domke Dennis , Schween Michael 
Published: April 2022

AbstractIn diesem Beitrag wird eine Lerngelegenheit zur experimentellen Untersuchung von radikalischen Photobromierungsreaktionen vorgestellt. Die Experimente sind als Fallvergleiche konstitutionsisomerer Reaktanten inszeniert und erlauben in der präsentierten Form die Erarbeitung des induktiven Effekts bzw. des Konzepts Hyperkonjugation, die zu den Kernkonzepten der organischen Chemie gehören. Mit unterschiedlichen Beobachtungsmethoden (Verschwinden der Bromfarbe in den Reaktionslösungen sowie Nachweis von pH‐Wert‐Änderungen, Änderungen des elektrischen Leitwerts und Bromid‐Nachweisreaktionen in Testlösungen) eignen sich diese Reaktionen in der Verflechtung von Experiment und Theorie, um grundlegende mechanistische Aspekte radikalischer Substitutionsreaktionen zu untersuchen. Dazu gehören insbesondere die Energetik sowie die Regioselektivität. Zudem sind die Fallvergleiche so angelegt, dass Lernende zwischen relevanten und irrelevanten äußeren Strukturmerkmalen unterscheiden lernen.
Pleomorphic liposarcoma: A clinicopathologic study of 20 FNA cases
Authors: Wakely Paul E. , Wangsiricharoen Sintawat , Ali Syed Z. 
Published: April 2022

BACKGROUNDPleomorphic liposarcoma (PLPS) is the least common but most aggressive of all forms of liposarcoma (LPS). Its diagnosis relies on the recognition of pleomorphic lipoblasts (PLBs), whose numbers vary considerably. Because few large fine‐needle aspiration (FNA) biopsy studies exist, the authors review their experience with PLPS.METHODSThe authors’ cytopathology files were searched for PLPS with histopathologic verification. FNA biopsy smears were performed via standard techniques.RESULTSTwenty cases from 20 patients (male/female ratio, 2.3/1; age range, 22‐77 years; mean age, 58 years) met the inclusion criteria. All had tissue confirmation. Biopsy sites included the following: thigh (11 [55%]), upper extremity (4 [20%]), axilla (2 [10%]), neck (1 [5%]), chest wall (1 [5%]), and mediastinum (1 [5%]). Aspirates were from primary (17 [85%]), locally recurrent (2 [10%]), and metastatic neoplasms (1 [5%]). The FNA diagnoses were PLPS (10 [50%]), myxofibrosarcoma (4 [20%]), LPS (2 [10%]), sarcoma (2 [10%]), and high‐grade malignant neoplasm (2 [10%]). Smears showed thick cell clusters and dissociated single forms. Pleomorphic, epithelioid, and bizarre cell/nuclear shapes were common. PLBs were absent, rare, or unnoticed in 45%. In 25%, smears dominated by myxoid stroma were diagnosed as high‐grade myxofibrosarcoma or myxoid LPS. Ancillary testing performed in 5 cases had limited diagnostic efficacy.CONCLUSIONSFNA biopsy of PLPS, although able to successfully recognize malignancy, suffers from a sampling bias due to an inability to capture or recognize PLBs in a significant proportion of cases secondary to the heterogeneous composition of this neoplasm.;
Malware detection based on multi‐objective convolution restricted Boltzmann machine model and constraint‐dividing crossover strategy algorithm
Authors: Cui Zhihua , Zhao Yaru , Liu Hao , Wang Ling , Fan Wenhui 
Published: April 2022

AbstractMalicious code, which is used to threaten network security, has been improved by many methods and strategies. However, the use of unreasonable deep learning models and single‐objective algorithms often affects the accuracy of data classification. Moreover, as an optimization problem, the existence of low‐quality datasets (imbalanced datasets) constrains the training effect of neural network models. Therefore, it is a big challenge to effectively design data processing methods and suitable training models. To enhance the robustness of the model and obtain better data classification results, it is essential to develop an efficient training model and strategy. To resolve this problem, a novel multi‐objective convolution restricted Boltzmann machine (CRBM) model based on the spatial pyramid pooling strategy is proposed to identify images and classify data in this study. Moreover, a fast nondominated sorting genetic algorithm based on the constraint‐dividing crossover strategy (CDCS‐NSGA‐II) is designed to optimize the imbalance datasets of the malware families. Extensive experimental results show that the multi‐objective CRBM model designed in this study combined with the CDCS‐NSGA‐II algorithm can effectively enhance the learning ability of the dataset, increase the effect of data classification and improve the robustness of the model.
Electroless Deposited Nickel Thin Films Alloyed with Thorium
Authors: Schapiro Ilan , Shandalov Michael , Maman Nitzan , Ezersky Vladimir , Golan Yuval , Yahel Eyal 
Published: April 2022

AbstractNi thin films alloyed with 232Th are obtained using electroless bath deposition by optimization of solution composition and deposition temperature. X‐ray photoelectron spectroscopy and transmission electron microscopy (TEM) indicate a fairly homogenous distribution of 232Th, with considerable amounts of incorporated oxygen. TEM confirms the presence of crystalline films with low concentrations of nickel phosphide precipitates for both non‐alloyed Ni and Ni─Th films.
Multi‐output, multi‐level, multi‐gate design using non‐linear programming
Authors: Dimopoulos A. C. , Pavlatos C. , Papakonstantinou G. 
Published: April 2022

SummaryThe conventional methodology of logic circuits design is by using logic gates. Thus, most of the minimization algorithms concern a limited set of gates (complete sets), like sum of products, exclusive‐or sum of products, NAND gates, NOR gates, and so forth. In this paper, a method is proposed for minimizing multi‐output Boolean functions using any kind of two‐input gates although it can easily be extended to multi‐input gates. The method is based on non‐linear mixed integer programming. Our methodology was tested against others proposed in the literature showing that it can achieve the same or better results in all cases. The contribution of this work can be summarized in the following: (i) it is the only approach to guarantee minimality to the problem of multi‐output, multi‐level, multi‐gate design, (ii) it is general and flexible and can solve design problems with any predefined gates and gate topology, (iii) it is a novel approach which may be adopted easily to solve other kinds of logic design problems, and (iv) incompletely specified Boolean functions are accepted, in contrary to other methods.
Flow rule‐based routing protocol management system in software‐defined IoT sensor network for IoT applications
Authors: Kumar Karunanithi Praveen , Sivanesan Perumal 
Published: April 2022

SummaryIn this article, a software‐defined (SDN)‐based Internet of things (IoT) sensor network (S‐ISN) architecture is proposed to fulfill the IoT applications in real time. The proposed system's architecture contains three planes, namely, data plane, control plane, and application plane, to enrich SDN in IoT applications. An IoT application‐based SDN controller is designed exclusively with two management rules—IoT application device management and IoT application‐based topology management. IoT application device management engages in controlling the functions of physical devices that lie on the data plane—path formation of the sensor (proactive, reactive, and hybrid) and reporting scheme management (query, time, and event) of the IoT sensor node. Likewise, IoT application topology management facilitates controlling network topology‐related issues using network structure management (data, location, group, and hierarchical) and next‐hop selection management (broadcast, location, and probabilistic) of the IoT sensor network. The above said management policies are achieved in real time to meet the applications of IoT. Hence, this S‐ISN scheme focuses on IoT application‐related issues with great flexibility in real time. Experimental results show that the network metrics have been improved by the proposed approach as compared with existing methods.
Analytical approaches for evaluating passive acoustic monitoring data: A case study of avian vocalizations
Authors: Symes Laurel B. , Kittelberger Kyle D. , Stone Sophia M. , Holmes Richard T. , Jones Jessica S. , Castaneda Ruvalcaba Itzel P. , Webster Michael S. , Ayres Matthew P. 
Published: April 2022

Abstract

The interface between field biology and technology is energizing the collection of vast quantities of environmental data. Passive acoustic monitoring, the use of unattended recording devices to capture environmental sound, is an example where technological advances have facilitated an influx of data that routinely exceeds the capacity for analysis. Computational advances, particularly the integration of machine learning approaches, will support data extraction efforts. However, the analysis and interpretation of these data will require parallel growth in conceptual and technical approaches for data analysis. Here, we use a large hand‐annotated dataset to showcase analysis approaches that will become increasingly useful as datasets grow and data extraction can be partially automated.

We propose and demonstrate seven technical approaches for analyzing bioacoustic data. These include the following: (1) generating species lists and descriptions of vocal variation, (2) assessing how abiotic factors (e.g., rain and wind) impact vocalization rates, (3) testing for differences in community vocalization activity across sites and habitat types, (4) quantifying the phenology of vocal activity, (5) testing for spatiotemporal correlations in vocalizations within species, (6) among species, and (7) using rarefaction analysis to quantify diversity and optimize bioacoustic sampling.

To demonstrate these approaches, we sampled in 2016 and 2018 and used hand annotations of 129,866 bird vocalizations from two forests in New Hampshire, USA, including sites in the Hubbard Brook Experiment Forest where bioacoustic data could be integrated with more than 50 years of observer‐based avian studies. Acoustic monitoring revealed differences in community patterns in vocalization activity between forests of different ages, as well as between nearby similar watersheds. Of numerous environmental variables that were evaluated, background noise was most clearly related to vocalization rates. The songbird community included one cluster of species where vocalization rates declined as ambient noise increased and another cluster where vocalization rates declined over the nesting season. In some common species, the number of vocalizations produced per day was correlated at scales of up to 15 km. Rarefaction analyses showed that adding sampling sites increased species detections more than adding sampling days.

Although our analyses used hand‐annotated data, the methods will extend readily to large‐scale automated detection of vocalization events. Such data are likely to become increasingly available as autonomous recording units become more advanced, affordable, and power efficient. Passive acoustic monitoring with human or automated identification at the species level offers growing potential to complement observer‐based studies of avian ecology.
Chromosome‐level genome assembly for the horned‐gall aphid provides insights into interactions between gall‐making insect and its host plant
Authors: Wei Hong‐Yuan , Ye Yu‐Xuan , Huang Hai‐Jian , Chen Ming‐Shun , Yang Zi‐Xiang , Chen Xiao‐Ming , Zhang Chuan‐Xi 
Published: April 2022

AbstractThe aphid Schlechtendalia chinensis is an economically important insect that can induce horned galls, which are valuable for the medicinal and chemical industries. Up to now, more than twenty aphid genomes have been reported. Most of the sequenced genomes are derived from free‐living aphids. Here, we generated a high‐quality genome assembly from a galling aphid. The final genome assembly is 271.52 Mb, representing one of the smallest sequenced genomes of aphids. The genome assembly is based on contig and scaffold N50 values of the genome sequence are 3.77 Mb and 20.41 Mb, respectively. Nine‐seven percent of the assembled sequences was anchored onto 13 chromosomes. Based on BUSCO analysis, the assembly involved 96.9% of conserved arthropod and 98.5% of the conserved Hemiptera single‐copy orthologous genes. A total of 14,089 protein‐coding genes were predicted. Phylogenetic analysis revealed that S. chinensis diverged from the common ancestor of Eriosoma lanigerum approximately 57 million years ago (MYA). In addition, 35 genes encoding salivary gland proteins showed differentially when S. chinensis forms a gall, suggesting they have potential roles in gall formation and plant defense suppression. Taken together, this high‐quality S. chinensis genome assembly and annotation provide a solid genetic foundation for future research to reveal the mechanism of gall formation and to explore the interaction between aphids and their host plants.
Comparative study on gut microbiota in three Anura frogs from a mountain stream
Authors: Chen Zhuo , Chen Jun‐Qiong , Liu Yao , Zhang Jie , Chen Xiao‐Hong , Qu Yan‐Fu 
Published: April 2022

AbstractComposition and diversity in gut microbiota are impacted by a wide variety of factors. The similarity of gut microbiota in related or sympatric species has been gaining recent traction. Here, 16S rRNA gene sequencing technology was employed to study the gut microbiota of three sympatric frog species, namely Odorrana tormota, O. graminea, and Amolops wuyiensis. In these three frog species, the most abundant phylum was Proteobacteria, followed by Bacteroidetes, Verrucomicrobia, and Firmicutes. The most abundant family was Burkholderiaceae in three species. The most dominant genera were Burkholderia, Caballeronia, and Paraburkholderia with the highest relative abundance in O. tormota, O. graminea, and A. wuyiensis, respectively. No differences were observed in alpha diversity indexes among the three frog species. However, bacterial similarity of gut microbiota was significantly different between O. tormota and A. wuyiensis and between O. graminea and A. wuyiensis. Metabolism‐related gene function was predominantly enriched in the gut microbiota of the three evaluated frog species. From these findings, that the relative abundance of the gut microbiota and predicted gene functions differed in three species, we conclude that there were significant differences in the gut microbiota of the three species. Similar alpha diversity and interspecific bacterial similarity in the gut might be related to bacterial transmission among the three Anura frogs evaluated in this study.
Phylogeography using mitogenomes: A rare Dipodidae, Sicista betulina, in North‐western Europe
Authors: Andersen Liselotte Wesley , Jacobsen Magnus W. , Frydenberg Jane , Møller Julie Dahl , Jensen Thomas Secher 
Published: April 2022

AbstractRepeated climatic and vegetation changes during the Pleistocene have shaped biodiversity in Northern Europe including Denmark. The Northern Birch Mouse (Sicista betulina) was one of the first small rodent species to colonize Denmark after the Late Glacial Maximum. This study analyses complete mitochondrial genomes and two nuclear genes of the Northern Birch Mouse to investigate the phylogeographical pattern in North‐western Europe and test whether the species colonized Denmark through several colonization events. The latter was prompt by (i) the present‐day distinct northern and southern Danish distribution and (ii) the subfossil record of Northern Birch Mouse, supporting early Weichselian colonization. Samples from Denmark, Norway, Sweden, Russia, Latvia, Estonia, and Slovakia were included. Mitogenomes were obtained from 54 individuals, all representing unique mitogenomes supporting high genetic variation. Bayesian phylogenetic analysis identified two distinct evolutionary linages in Northern Europe diverging within the Elster glaciation period. The results of the two nuclear genomes showed lower genetic differentiation but supported the same evolutionary history. This suggests an allopatric origin of the clades followed by secondary contact. Individuals from southern Denmark were only found in one clade, while individuals from other areas, including northern Denmark, were represented in both clades. Nevertheless, we found no evidence for repeated colonization's explaining the observed fragmented distribution of the species today. The results indicated that the mitogenome pattern of the Northern Birch Mouse population in southern Denmark was either (i) due to the population being founded from northern Denmark, (ii) a result of climatic and anthropogenic effects reducing population size increasing genetic drift or (iii) caused by sampling bias.
N‐Alkylated Analogues of Indolylthio Glycosides as Glycosyl Donors with Enhanced Activation Profile
Authors: Shrestha Ganesh , Panza Matteo , Singh Yashapal , Stine Keith J. , Demchenko Alexei V. 
Published: April 2022

AbstractWhile studying indolylthio glycosides, previously we determined their activation profile that required large excess of activators. This drawback was partially addressed in the present study of N‐alkylated SInR derivatives. The activation process was studied by NMR and the increased understanding of the mechanism led to a discovery of different activation pathways taking place with SIn versus SInR derivatives. Also investigated was orthogonality of the SInR leaving groups versus thioglycosides and selective activation of thioimidates over SInR glycosides.
Assessment of microbial activity by CO2 production during heating oil storage
Authors: Surger Maximilian J. , Blank Lars M. 
Published: April 2022

AbstractMicrobial activity is the driving force of the carbon cycle, including the digestion of biomass in the soil, oceans, and oil deposits. This natural diversity of microbial carbon sources poses challenges for humans. Contamination monitoring can be difficult in oil tanks and similar settings. To assess microbial activity in such industrial settings, off‐gas analysis can be employed by considering growth and non‐growth‐associated metabolic activity. In this work, we describe the monitoring of CO2 as a method for measuring microbial activity. We revealed that the CO2 signal corresponds to classical growth curves, exemplified by Pseudomonas fluorescens, Yarrowia lipolytica, and Penicillium chrysogenum. Deviations of the CO2 signal from the growth curves occurred when the yield of biomass on the substrate changed (i.e., the non‐growth‐associated metabolic activities). We monitored CO2 to track the onset of microbial contamination in an oil tank. This experimental setup was applied to determine the susceptibility of heating oil and biodiesel to microbial contamination long before the formation of problematic biofilms. In summary, the measurement of CO2 production by bacteria, yeasts, and molds allowed the permanent monitoring of microbial activity under oil storage conditions without invasive sampling.
Application of mixture design methodology for development of high antioxidant fruity functional beverage
Authors: Sahraee Samar , Ghanbarzadeh Babak , Falcone Pasquale M. 
Published: April 2022

AbstractThree red color fruit juice (pomegranate (PJ), barberry (BJ), and grape juice (GJ)) and three plant extracts (cardamom essential oil (CE), ginger extract (GE), and hibiscus solution (HS)) were used for the development of different functional beverages. Organoleptic analysis was done to detect the most acceptable fruit juice blend. The physicochemical properties of the samples including total phenols, 1,1‐diphenyl‐2‐picrylhydrazyl (DPPH) inhibition percent, anthocyanin, flavonoid, and vitamin C content of optimum fruit juice blend (60% PJ/20% BJ/20% GJ) were 121.57 µg gallic acid equivalent (GAE)/ml, 80.28%, 4.03 mg/L, 64.87 mg/100 ml, and 51.10 mg/100 ml, respectively. To determine the optimum level of extracts and essential oil (GE, CE, and HS) in fruit juice blends, the mixture design method was used and 14 runs (formulations) were obtained. In all formulations, samples containing HS had the highest content of antioxidant and active components and the statistical analysis indicated that the sample containing 0.5 CE/0.5 GE/1 HS (ml/100 ml) had the optimum content of antioxidant components. Thus, the results of this study introduce a functional drink possessing high polyphenols, antioxidants, anthocyanin, and vitamin C content.
Data‐driven treatment pathways mining for early breast cancer using cSPADE algorithm and system clustering
Authors: Yang Qing , Luo Ting , Zhang Wei , Zhong Xiaorong , He Ping , Zheng Hong 
Published: April 2022

AbstractObjectivesDue to the multidimensional, multilayered, and chronological order of the cancer data, it was challenging for us to extract treatment paths. To determine whether the cSPADE algorithm and system clustering proposed in this study can effectively identify the treatment pathways for early breast cancer.MethodsWe applied data mining technology to the electronic medical records of 6891 early breast cancer patients to mine treatment pathways. We provided a method of extracting data from EMR and performed three‐stage mining: determining the treatment stage through the cSPADE algorithm → system clustering for treatment plan extraction → cSPADE mining sequence pattern for treatment. The Kolmogorov‐Smirnov test and correlation analysis were used to cross‐validate the sequence rules of early breast cancer treatment pathways.ResultsWe unearthed 55 sequence rules for early breast cancer treatment, 3 preoperative neoadjuvant chemotherapy regimens, three postoperative chemotherapy regimens, and 2 chemotherapy regimens for patients without surgery. Through 5‐fold cross‐validation, Pearson and Spearman correlation tests were performed. At the significance level of p < 0.05, all correlation coefficients of support, confidence and lift were greater than 0.89. Using the Kolmogorov‐Smirnov test, we found no significant differences between the sequence distributions.ConclusionsWe have proved that cSPADE algorithm combined system clustering is an effective technique for identifying temporal relationships between treatment modalities, enabling hierarchical and vertical mining of breast cancer treatment models. In addition, we confirmed the robustness of the results by cross‐validation of these treatment pathway ordering rules. Through this method, the treatment path of early breast cancer patients can be revealed, and the real‐world breast cancer treatment behaviour model can be evaluated, which can provide reference for the redesign and optimization of treatment path.