bluuebunny/crossref_metadata_2025 huggingface dataset:
Biochar development from thermal TGA studies of individual food waste vegetables and their blended systems
Authors: Elkhalifa Samar , Parthasarathy Prakash , Mackey Hamish R. , Al-Ansari Tareq , Elhassan Omar , Mansour Said , McKay Gordon
Published: February 2022

The amount of food waste that is generated all over the world is enormous. As food wastes are rich in nutrients and organics, they serve as a potential source for the generation of many value-added commodities and energy. In most countries, food wastes are predominately dumped in open lands or incinerated, along with other combustible materials such as municipal solid wastes, for the possible extraction of energy. However, these two modes of food wastes disposal are encountering more and more environmental, technical, and economical challenges. More recently, it has been realized that food wastes can be transformed into energy and value-added products, such as horticultural biochars, using thermochemical technologies such as pyrolysis and gasification. In the current research work, three selected food items, carrots, cucumbers, and tomatoes, have been studied using thermogravimetric analysis. The biochar analysis involves one single food item (carrot), one binary mixture (carrot + cucumber), and one ternary blend of carrot, cucumber, and tomato. Two heating rates were used in order to perform kinetic modeling studies using the Arrhenius and Coats-Redfern models. Since the production of the pyrolysis gases—for energy and chemicals production—is of major economic significance regarding the overall process viability, the TGA syngas for a single component, binary component and tertiary component systems were analyzed by TGA coupled mass spectrometry. The results of the gas analysis indicate an increase in hydrogen generation due to blending the food wastes.
Computational intelligence in processing of speech acoustics: a survey
Authors: Singh Amitoj , Kaur Navkiran , Kukreja Vinay , Kadyan Virender , Kumar Munish
Published: February 2022

Speech recognition of a language is a key area in the field of pattern recognition. This paper presents a comprehensive survey on the speech recognition techniques for non-Indian and Indian languages, and compiled some of the computational models used for processing speech acoustics. An immense number of frameworks are available for speech processing and recognition for languages persisting around the globe. However, a limited number of automatic speech recognition systems are available for commercial use. The gap between the languages being spoken around the globe and the technical support available to these languages are very few. This paper examined major challenges for speech recognition for different languages. Analysis of the literature shows that lack of standard databases availability of minority languages hinder the research recognition research across the globe. When compared with non-Indian languages, the research on speech recognition of Indian languages (except Hindi) has not achieved the expected milestone yet. Combination of MFCC and DNN–HMM classifier is most commonly used system for developing ASR minority languages, whereas in some of the majority languages, researchers are using much advance algorithms of DNN. It has also been observed that the research in this field is quite thin and still more research needs to be carried out, particularly in the case of minority languages.
Effective and scalable legal judgment recommendation using pre-learned word embedding
Authors: Dhanani Jenish , Mehta Rupa , Rana Dipti
Published: February 2022

Legal professionals strongly demand an automatic and convenient legal document recommendation system (LDRS) to identify similar judgments for preparing the advantageous and strategic arguments in the Court. Doc2Vec excellently learns semantically rich embedding (i.e., vector) space from the textual information of judgment corpus. During Doc2Vec learning, the practice of prior domain-specific knowledge can potentially enhance the embedding representation. This research thus proposes a pre-learned word embedding based LDRS (P-LDRS) that learns the Doc2Vec embedding using Legal domain-specific pre-learned word embedding possessing the Legal semantic knowledge. However, learning the judgment embedding from existing substantial Legal documents turns out to be a scalability issue for Doc2Vec. The proposed P-LDRS also provides additional functionality to learn the judgment embedding distributedly over the cluster of computing nodes using frameworks like MapReduce and Spark to address the scalability issue. The empirical analysis is performed with a non-distributed and a distributed variant of the proposed P-LDRS to validate the effectiveness and scalability. Experiment results showcase that proposed non-distributed P-LDRS perform significantly better than traditional Doc2Vec based LDRS with an Accuracy of 0.88, F1-Score of 0.82 and MCC Score of 0.73. They also demonstrate that the proposed distributed P-LDRS improves the time efficiency and achieves stable Accuracy of $$\approx $$
≈
0.88, F1-Score of $$\approx $$
≈
0.83 and MCC Score of $$\approx $$
≈
0.72, with an increasing number of nodes.
An iterative approach to unsupervised outlier detection using ensemble method and distance-based data filtering
Authors: Chakraborty Bodhan , Chaterjee Agneet , Malakar Samir , Sarkar Ram
Published: February 2022

Outlier or anomaly detection is the process through which datum/data with different properties from the rest of the data is/are identified. Their importance lies in their use in various domains such as fraud detection, network intrusion detection, and spam filtering. In this paper, we introduce a new outlier detection algorithm based on an ensemble method and distance-based data filtering with an iterative approach to detect outliers in unlabeled data. The ensemble method is used to cluster the unlabeled data and to filter out potential isolated outliers from the same by iteratively using a cluster membership threshold until the Dunn index score for clustering is maximized. The distance-based data filtering, on the other hand, removes the potential outlier clusters from the post-clustered data based on a distance threshold using the Euclidean distance measure of each data point from the majority cluster as the filtering factor. The performance of our algorithm is evaluated by applying it to 10 real-world machine learning datasets. Finally, we compare the results of our algorithm to various supervised and unsupervised outlier detection algorithms using Precision@n and F-score evaluation metrics.
A consensus building model in group decision making with non-reciprocal fuzzy preference relations
Authors: Liu Fang , Liu Tong , Chen Ya-Ru
Published: February 2022

Group decision making (GDM) is a wisdom extracting process where a group of decision makers (DMs) could reach a consensus on the optimal solution to the choice problem with a finite set of alternatives. This paper reports a consensus model in GDM, where the opinions of experts are expressed as fuzzy preference relations (FPRs) without additively reciprocal property to cope with the existing uncertainty. The concept of non-reciprocal fuzzy preference relations (NrFPRs) is proposed to capture the considered situation. A novel additive consistency index is constructed to quantify the inconsistency degree of NrFPRs using the relationship of two column/row vectors. An optimization model is constructed, where a new fitness function is proposed by considering the consistency degrees of NrFPRs and the consensus level of a group of experts. A novel concept of acceptable consensus standard is proposed to characterize the acceptance of the consensus process. The particle swarm optimization (PSO) algorithm is utilized to solve the constructed optimization problem. As compared to the existing models, numerical results show that the proposed model can be used to effectively reach an optimal solution to a GDM problem with NrFPRs.
The Book You Need to Read to Write the Book You Want to Write
Authors: Burton Sarah , Poster Jem
Published: February 2022

Have you ever wanted to write a novel or short story but didn't know where to start? If so, this is the book for you. It's the book for anyone, in fact, who wants to write to their full potential. Practical and jargon-free, rejecting prescriptive templates and formulae, it's a storehouse of ideas and advice on a range of relevant subjects, from boosting self-motivation and confidence to approaching agents and publishers. Drawing on the authors' extensive experience as successful writers and inspiring teachers, it will guide you through such essentials as the interplay of memory and imagination; plotting your story; the creation of convincing characters; the uses of description; the pleasures and pitfalls of research; and the editing process. The book's primary aim is simple: to help its readers to become better writers.
Populism and Antitrust
Authors: Bernatt Maciej
Published: February 2022

Competition law is designed to promote a consumer-friendly economy, but for the law to work in practice, competition agencies - and the courts who oversee them - must enforce it effectively and impartially. Today, however, the rule of populist governments is challenging the foundations of competition law in unprecedented ways. In this comprehensive work, Maciej Bernatt analyses these challenges and describes how populist governments have influenced national and regional (EU) competition law systems. Using empirical findings from Poland and Hungary, Bernatt proposes a new theoretical framework that will allow the illiberal influence of populism on competition law systems to be better measured and understood. Populism and Antitrust will be of interest not only to antitrust and constitutional law scholars, but also to those concerned about the future of liberal democracy and free markets.
Copyright Exhaustion
Authors: Mezei Péter
Published: February 2022

In the Second Edition of Copyright Exhaustion, copyright scholar Péter Mezei offers an expanded examination of copyright exhaustion, including its historical development, theoretical framework, practical applications, and policy considerations. He includes updated case law and statutory developments for the first-sale doctrine in the United States and in the European Union, covering both analogue and digital applications with an eye toward scrutinizing the common rejection of exhaustion in the resale of digital subject matter including computer programs, sound recordings, audiovisual works, and e-books. He advocates for a digital first-sale doctrine that would offer legal consistency to copyright law and a technologically feasible framework for content producers and consumers.
CYP4CJ6-mediated resistance to two neonicotinoid insecticides in Sitobion miscanthi (Takahashi)
Authors: Hu Gui-Lei , Lu Liu-Yang , Li Ya-She , Su Xu , Dong Wen-Yang , Zhang Bai-Zhong , Liu Run-Qiang , Shi Ming-Wang , Wang Hong-Liang , Chen Xi-Ling
Published: February 2022

The wheat aphid Sitobion miscanthi (CWA) is an important harmful pest in wheat fields. Insecticide application is the main method to effectively control wheat aphids. However, CWA has developed resistance to some insecticides due to its extensive application, and understanding resistance mechanisms is crucial for the management of CWA. In our study, a new P450 gene, CYP4CJ6, was identified from CWA and showed a positive response to imidacloprid and thiamethoxam. Transcription of CYP4CJ6 was significantly induced by both imidacloprid and thiamethoxam, and overexpression of CYP4CJ6 in the imidacloprid-resistant strain was also observed. The sensitivity of CWA to these two insecticides was increased after the knockdown of CYP4CJ6. These results indicated that CYP4CJ6 could be associated with CWA resistance to imidacloprid and thiamethoxam. Subsequently, the posttranscriptional regulatory mechanism was assessed, and miR-316 was confirmed to participate in the posttranscriptional regulation of CYP4CJ6. These results are crucial for clarifying the roles of P450 in the resistance of CWA to insecticides.
Comparison of different sample-based motion planning methods in redundant robotic manipulators
Authors: Shahabi Mehdi , Ghariblu Hashem , Beschi Manuel
Published: February 2022

The main objective of a motion planning algorithm is to find a collision-free path in the workspace of a robotic manipulator in a point-to-point motion. Among the various motion planning methods available, sample-based motion planning algorithms are easy to use, quick and powerful in redundant robotic systems applications. In this study, different sampling-based motion planning algorithms are employed to select the most appropriate method for efficient collision-free motion planning. As a case study, finding a collision-free robotic displacement for welding a main pipe with other intersecting pipes and joints is considered. The robotic manipulator employed in this study has seven degrees of freedom, where six degrees are related to the manipulator joints and one degree is related to its base linear movement suspended from ceiling. Five criteria, time, path length, path time, path smoothness and process time are used to evaluate the efficiency of different sample-based motion planning algorithms. Finally, a smaller set of more efficient algorithms are introduced based on the defined efficiency evaluation criteria.
LANGUAGE EXPERIENCE AND BILINGUAL CHILDREN’S HERITAGE LANGUAGE LEARNING
Authors: Sun He , Waschl Nicolette , Veera Roodra
Published: February 2022

Both language input and output are important to child language learners’ heritage language development. Nevertheless, existing studies mainly focus on language input, leaving the significance of language output underexplored. The current study assessed 201 kindergarteners’ Mandarin skills (i.e., receptive vocabulary, receptive grammar, and verbal fluency) in Singapore, and investigated the influence of children’s Mandarin experience, and specifically output, on these Mandarin skills. The results based on multilevel models reveal that children’s Mandarin experience plays a crucial role in the three Mandarin skills, after controlling for children’s gender, language aptitude, and English proficiency. Specifically, children’s onset age of Mandarin speaking and the number of places where they used Mandarin alone significantly predict all the Mandarin skills.
Impact of Ocean Heat Transport on Arctic Sea Ice Variability in the GFDL CM2‐O Model Suite
Authors: Decuypère Marine , Tremblay L. Bruno , Dufour Carolina O.
Published: February 2022

The impact of horizontal resolution on meridional Ocean Heat Transport (OHT) and sea ice in the Arctic is investigated using the GFDL CM2‐O climate model suite (1°, 1/4°, and 1/10°) in both preindustrial control and climate change simulations. Results show an increase in OHT associated to a decrease in sea ice extent (SIE) in the Arctic on interannual and decadal timescales. This link, however, is not monotonic with spatial resolution. While OHT increases and SIE decreases from the Low to the Medium resolution, the reverse is true from the Medium to the High resolution. Differences in OHT and SIE between the three model configurations mostly arise from the preindustrial state. As the spatial resolution increases, the Irminger Current is favored at the expense of the North Atlantic Drift. This rerouting of water to the Western side of Greenland results in less heat delivered to the Arctic in the High‐resolution configuration than in its Medium counterpart. As a result, the Medium‐resolution configuration is in best agreement with observed SIE and Atlantic OHT. Concurrent with the change in the partitioning in volume is a change in deep convection centers from the Greenland‐Irminger‐Norwegian Seas in the Low resolution to the Labrador Sea in the Medium and High resolutions. Results suggest a coupling between OHT into the Arctic and deep convection in the North Atlantic.
Representation of Leaf‐to‐Canopy Radiative Transfer Processes Improves Simulation of Far‐Red Solar‐Induced Chlorophyll Fluorescence in the Community Land Model Version 5
Authors: Li Rong , Lombardozzi Danica , Shi Mingjie , Frankenberg Christian , Parazoo Nicholas C. , Köhler Philipp , Yi Koong , Guan Kaiyu , Yang Xi
Published: February 2022

Recent advances in satellite observations of solar‐induced chlorophyll fluorescence (SIF) provide a new opportunity to constrain the simulation of terrestrial gross primary productivity (GPP). Accurate representation of the processes driving SIF emission and its radiative transfer to remote sensing sensors is an essential prerequisite for data assimilation. Recently, SIF simulations have been incorporated into several land surface models, but the scaling of SIF from leaf‐level to canopy‐level is usually not well‐represented. Here, we incorporate the simulation of far‐red SIF observed at nadir into the Community Land Model version 5 (CLM5). Leaf‐level fluorescence yield was simulated by a parametric simplification of the Soil Canopy‐Observation of Photosynthesis and Energy fluxes model (SCOPE). And an efficient and accurate method based on escape probability is developed to scale SIF from leaf‐level to top‐of‐canopy while taking clumping and the radiative transfer processes into account. SIF simulated by CLM5 and SCOPE agreed well at sites except one in needleleaf forest (R2 > 0.91, root‐mean‐square error <0.19 W⋅m−2⋅sr−1⋅μm−1), and captured the day‐to‐day variation of tower‐measured SIF at temperate forest sites (R2 > 0.68). At the global scale, simulated SIF generally captured the spatial and seasonal patterns of satellite‐observed SIF. Factors including the fluorescence emission model, clumping, bidirectional effect, and leaf optical properties had considerable impacts on SIF simulation, and the discrepancies between simulate d and observed SIF varied with plant functional type. By improving the representation of radiative transfer for SIF simulation, our model allows better comparisons between simulated and observed SIF toward constraining GPP simulations.
Dynamic network impairments underlie cognitive fluctuations in Lewy body dementia
Authors: Matar Elie , Ehgoetz Martens Kaylena A. , Phillips Joseph R. , Wainstein Gabriel , Halliday Glenda M. , Lewis Simon J. G. , Shine James M.
Published: February 2022

Cognitive fluctuations are a characteristic and distressing disturbance of attention and consciousness seen in patients with Dementia with Lewy bodies and Parkinson’s disease dementia. It has been proposed that fluctuations result from disruption of key neuromodulatory systems supporting states of attention and wakefulness which are normally characterised by temporally variable and highly integrated functional network architectures. In this study, patients with DLB (n = 25) and age-matched controls (n = 49) were assessed using dynamic resting state fMRI. A dynamic network signature of reduced temporal variability and integration was identified in DLB patients compared to controls. Reduced temporal variability correlated significantly with fluctuation-related measures using a sustained attention task. A less integrated (more segregated) functional network architecture was seen in DLB patients compared to the control group, with regions of reduced integration observed across dorsal and ventral attention, sensorimotor, visual, cingulo-opercular and cingulo-parietal networks. Reduced network integration correlated positively with subjective and objective measures of fluctuations. Regions of reduced integration and unstable regional assignments significantly matched areas of expression of specific classes of noradrenergic and cholinergic receptors across the cerebral cortex. Correlating topological measures with maps of neurotransmitter/neuromodulator receptor gene expression, we found that regions of reduced integration and unstable modular assignments correlated significantly with the pattern of expression of subclasses of noradrenergic and cholinergic receptors across the cerebral cortex. Altogether, these findings demonstrate that cognitive fluctuations are associated with an imaging signature of dynamic network impairment linked to specific neurotransmitters/neuromodulators within the ascending arousal system, highlighting novel potential diagnostic and therapeutic approaches for this troubling symptom.
BCG-induced trained immunity enhances acellular pertussis vaccination responses in an explorative randomized clinical trial
Authors: Gillard Joshua , Blok Bastiaan A. , Garza Daniel R. , Venkatasubramanian Prashanna Balaji , Simonetti Elles , Eleveld Marc J. , Berbers Guy A. M. , van Gageldonk Pieter G. M. , Joosten Irma , de Groot Ronald , de Bree L. Charlotte J. , van Crevel Reinout , de Jonge Marien I. , Huynen Martijn A. , Netea Mihai G. , Diavatopoulos Dimitri A.
Published: February 2022

Acellular pertussis (aP) booster vaccines are central to pertussis immunization programs, although their effectiveness varies. The Bacille Calmette-Guérin (BCG) vaccine is a prototype inducer of trained immunity, which enhances immune responses to subsequent infections or vaccinations. While previous clinical studies have demonstrated that trained immunity can protect against heterologous infections, its effect on aP vaccines in humans is unknown. We conducted a clinical study in order to determine the immunological effects of trained immunity on pertussis vaccination. Healthy female volunteers were randomly assigned to either receive BCG followed by a booster dose of tetanus-diphteria-pertussis inactivated polio vaccine (Tdap-IPV) 3 months later (BCG-trained), BCG + Tdap-IPV concurrently, or Tdap-IPV followed by BCG 3 months later. Primary outcomes were pertussis-specific humoral, T- and B-cell responses and were quantified at baseline of Tdap-IPV vaccination and 2 weeks thereafter. As a secondary outcome in the BCG-trained cohort, ex vivo leukocyte responses were measured in response to unrelated stimuli before and after BCG vaccination. BCG vaccination 3 months prior to, but not concurrent with, Tdap-IPV improves pertussis-specific Th1-cell and humoral responses, and also increases total memory B cell responses. These responses were correlated with enhanced IL-6 and IL-1β production at the baseline of Tdap-IPV vaccination in the BCG-trained cohort. Our study demonstrates that prior BCG vaccination potentiates immune responses to pertussis vaccines and that biomarkers of trained immunity are the most reliable correlates of those responses.
The significance of ErbB2/3 in the conversion of induced pluripotent stem cells into cancer stem cells
Authors: Hassan Ghmkin , Zahra Maram H. , Seno Akimasa , Seno Masaharu
Published: February 2022

Cancer stem cells (CSCs) are suggested to be responsible for drug resistance and aggressive phenotypes of tumors. Mechanisms of CSC induction are still under investigation. Our lab has established a novel method to generate CSCs from iPSCs under a cancerous microenvironment mimicked by the conditioned medium (CM) of cancer-derived cells. Here, we analyzed the transcriptome of CSCs, which were converted from iPSCs with CM from pancreatic ductal adenocarcinoma cells. The differentially expressed genes were identified and used to explore pathway enrichment. From the comparison of the CSCs with iPSCs, genes with elevated expression were related to the ErbB2/3 signaling pathway. Inhibition of either ErbB2 with lapatinib as a tyrosine kinase inhibitor or ErbB3 with TX1-85-1 or siRNAs arrested cell proliferation, inhibited the in vitro tumorigenicity, and lead to loss of stemness in the converting cells. The self-renewal and tube formation abilities of cells were also abolished while CD24 and Oct3/4 levels were reduced, and the MAPK pathway was overactivated. This study shows a potential involvement of the ErbB2/ErbB3 pathway in CSC generation and could lead to new insight into the mechanism of tumorigenesis and the way of cancer prevention.
Morpho-physiological adaptations of Leptocylindrus aporus and L. hargravesii to phosphate limitation in the northern Adriatic
Authors: Kužat Nataša , Marić Pfannkuchen Daniela , Smodlaka Tanković Mirta , Baričević Ana , Ivančić Ingrid , Vrana Ivna , Gašparović Blaženka , Pfannkuchen Martin
Published: February 2022

The northern Adriatic is highly productive and shallow area characterized by numerous spatio-temporal gradients (e.g. nutrients, salinity, temperature). It is strongly influenced by numerous freshwater inputs, mainly from Po river. Its current systems as well as Po river, generates gradients of phosphate availability with an expressed N/P imbalance and phosphate limitation. A number of recent studies characterized these gradients as major factors affecting abundance and composition of microphytoplankton communities. Focus of this study is on two Leptocylindrus species, Leptocylindrus aporus (F.W. French & Hargraves) D. Nanjappa & A. Zingone 2013 and Leptocylindrus hargravesii D. Nanjappa & A. Zingone 2013. Species belonging to Leptocylindrus genus are frequently observed and have high abundances and also high contributions to the microphytoplankton community in this area. We focused on their morphological and physiological responses to phosphate limitation in situ and also performed in vitro experiments. In this study we report data on species specific growth rates under phosphorus (P) deplete and P rich conditions, localization and characteristics of alkaline phosphate activity, phosphate uptake rates as well as their morphological differences in P deplete versus P rich conditions. Our in vitro experiments showed that both Leptocylindrus species morphologically reacted similarly to phosphorus depletion and showed significantly elongated pervalvar axis in P depleted conditions if compared to P rich conditions. Also average chain lengths increased when in P depleted conditions. Two previously mentioned adaptations indicate their tendency to increase cellular surface areas available for alkaline phosphatase. Chlorophyll fluorescence of both species significantly decreased in P depleted medium. Although both species morphologically reacted similarly, our experiment demonstrated significant differences in physiological reactions to P depleted conditions.
Towards machine learning aided real-time range imaging in proton therapy
Authors: Lerendegui-Marco Jorge , Balibrea-Correa Javier , Babiano-Suárez Víctor , Ladarescu Ion , Domingo-Pardo César
Published: February 2022

Compton imaging represents a promising technique for range verification in proton therapy treatments. In this work, we report on the advantageous aspects of the i-TED detector for proton-range monitoring, based on the results of the first Monte Carlo study of its applicability to this field. i-TED is an array of Compton cameras, that have been specifically designed for neutron-capture nuclear physics experiments, which are characterized by $$\gamma $$
γ
-ray energies spanning up to 5–6 MeV, rather low $$\gamma $$
γ
-ray emission yields and very intense neutron induced $$\gamma $$
γ
-ray backgrounds. Our developments to cope with these three aspects are concomitant with those required in the field of hadron therapy, especially in terms of high efficiency for real-time monitoring, low sensitivity to neutron backgrounds and reliable performance at the high $$\gamma $$
γ
-ray energies. We find that signal-to-background ratios can be appreciably improved with i-TED thanks to its light-weight design and the low neutron-capture cross sections of its LaCl$$_{3}$$

3

crystals, when compared to other similar systems based on LYSO, CdZnTe or LaBr$$_{3}$$

3

. Its high time-resolution (CRT $$\sim $$
∼
 500 ps) represents an additional advantage for background suppression when operated in pulsed HT mode. Each i-TED Compton module features two detection planes of very large LaCl$$_{3}$$

3

monolithic crystals, thereby achieving a high efficiency in coincidence of 0.2% for a point-like 1 MeV $$\gamma $$
γ
-ray source at 5 cm distance. This leads to sufficient statistics for reliable image reconstruction with an array of four i-TED detectors assuming clinical intensities of 10$$^{8}$$

8

protons per treatment point. The use of a two-plane design instead of three-planes has been preferred owing to the higher attainable efficiency for double time-coincidences than for threefold events. The loss of full-energy events for high energy $$\gamma $$
γ
-rays is compensated by means of machine-learning based algorithms, which allow one to enhance the signal-to-total ratio up to a factor of 2.
Low voltage optical fiber positioner robot based on minimum inductance hollow cup motors
Authors: Guo Shaoxiong , Zhai Chao , Bi Songlin
Published: February 2022

With the further transformation of The Large Sky Area Multi-Object Fiber Spectroscopic Telescope, the new generation of fiber positioner robot chooses a 4 mm hollow cup motor with minimum phase inductance. Because the load of the fiber positioner robot is constant and the inertia of the motor is very small, an open loop positioning control method based on Space Vector Pulse Width Modulation is proposed, and the specific open loop parameters are directly tuned by relevant experimental strategies. The critical factors of the open loop driving mode are discussed in detail from four aspects: subdivision, fundamental frequency, wave generation mode and peak current. Based on the actual fiber positioner robot, the hardware driver and assessment platform are built. The positioning tests show that the method proposed is practical and effective, and meets the precision positioning demand of the new generation optical fiber positioner robot.
Solubilization of cuprous oxide in water using biosurfactant extracts from corn steep liquor: a comparative study
Authors: López-Prieto A. , Moldes A. B. , Cruz J. M. , Pérez-Cid B.
Published: February 2022

In this work the chemical characterization (elemental analysis and the content of phospholipids) and surface-active properties of two biosurfactants (BS) extracted with both chloroform or ethyl acetate from corn steep liquor were compared. The phospholipids content for the BS extracted with chloroform (BS1) was considerably higher (8.15%) than that obtained for the BS extracted with ethyl acetate (BS2), 0.11%. When comparing the FTIR spectra of the two BS studied in this work with the spectrum of the commercial surfactant lecithin, a greater similarity (75%) was observed with the spectrum of the BS1. The biosurfactant extract (BS2) provided the most favorable conditions for the solubilization of cuprous oxide (Cu-Ox) in water (12.54% of copper dissolved), in comparison with BS1. The results achieved were considerably better than those obtained with chemical surfactants (Tween 80, SDS and CTAB) on solubilizing Cu-Ox, resulting in the latter cases on percentages of Cu dissolved always lower than 0.21%. In addition, a factorial design was performed obtaining the optimum conditions to solubilize Cu-Ox, where the maximum water solubility of Cu-Ox (13.17%) was achieved using 3.93 g/L of BS2 with a contact time of 19.86 min and using a concentration of Cu-Ox of 1.96 g/L. Thus, the BS2 extract could have a promising future as solubilizing agent in the formulation of more sustainable Cu-Ox based pesticides. Moreover, it was confirmed that the presence of phospholipids prevents the solubilization of copper-based pesticides in water.
Onset of Late Cretaceous diversification in Europe’s freshwater gastropod fauna links to global climatic and biotic events
Authors: Neubauer Thomas A. , Harzhauser Mathias
Published: February 2022

The Mesozoic rise of the European freshwater gastropod fauna is still poorly understood. Compared to the well documented Cenozoic history, little is known about the patterns and processes underlying the early diversification preceding their extinction crisis at the K–Pg boundary. We assess what is probably a first pulse of diversification of the Cenozoic-type fauna in the Late Cretaceous along with the potential abiotic and biotic controls for shifts in species diversification. We find strong support that the increase in the speciation rate in the Santonian (~ 85 Myr ago) is linked to a global sea level rise, which caused extensive flooding of continental areas and the formation of vast brackish-water ecosystems. The following decline of the speciation rate coincides with a rise in diversity and reflects increasing interspecific competition. The peak in the speciation rate postdates the Cenomanian–Turonian Thermal Maximum, which probably limited the potential for diversification among freshwater gastropods due to ecological constraints. The peak coincides moreover with the end phase of the Cretaceous Terrestrial Revolution, which sparked the radiation of angiosperms. The expansion and diversification of flowering plants, being an important food source for freshwater gastropods today, could have formed a necessary basis for gastropod diversification.
Settling moths are the vital component of pollination in Himalayan ecosystem of North-East India, pollen transfer network approach revealed
Authors: Singh Navneet , Lenka Rajesh , Chatterjee Pallab , Mitra Dipayan
Published: February 2022

Majority of the pollination related studies are based on the diurnal pollinators, and the nocturnal pollinators received less scientific attention. We reveal the significance of settling moths in pollination of angiosperm families in Himalayan ecosystem of North-East India. The refined and novel method of pollen extraction from the proboscides provides a more robust assessment of the pollen carrying capacity. The study is based on one of the largest data sets (140 pollen transporter moth species (PTMS)), with interpretation based on seasonal as well as altitudinal data. In the present study about 65% moths (91 species) carried sufficient quantities of pollen grains to be considered as potential pollinators (PPMS). Teliphasa sp. (Crambidae) and Cuculia sp. (Noctuidae) are found to carry the highest quantity of pollen. We found pollen grains of 21 plant families and the abundant pollen are from Betulaceae, Fabaceae, Rosaceae and Ericaceae. Species composition of PTMS and PPMS in pre-monsoon, monsoon, and post-monsoon revealed the dominance of Geometridae. Maximum diversity of PTMS and PPMS is found from 2000 to 2500 m altitude. The nocturnal pollen transfer network matrices exhibited high degree of selectivity (H2ʹ = 0.86).
Non-parametric multiple inputs prediction model for magnetic field dependent complex modulus of magnetorheological elastomer
Authors: Saharuddin Kasma Diana , Ariff Mohd Hatta Mohammed , Bahiuddin Irfan , Ubaidillah Ubaidillah , Mazlan Saiful Amri , Aziz Siti Aishah Abdul , Nazmi Nurhazimah , Fatah Abdul Yasser Abdul , Shapiai Mohd Ibrahim
Published: February 2022

This study introduces a novel platform to predict complex modulus variables as a function of the applied magnetic field and other imperative variables using machine learning. The complex modulus prediction of magnetorheological (MR) elastomers is a challenging process, attributable to the material’s highly nonlinear nature. This problem becomes apparent when considering various possible fabrication parameters. Furthermore, traditional parametric modeling methods are limited when applied to solve larger-scale cases involving large databases. Consequently, the application of non-parametric modeling such as machine learning has gained increasing attraction in recent years. Therefore, this work proposes a data-driven approach for predicting multiple input-dependent complex moduli using feedforward neural networks. Besides excitation frequency and magnetic flux density as operating conditions, the inputs consider compositions and curing conditions represented by magnetic particle weight percentage and the curing magnetic field, respectively. Extreme learning machines and artificial neural networks were used to train the models. The simulation results obtained at various curing conditions and other inputs confirm that the predicted complex modulus has high accuracy with an R2 of about 0.997, as compared to the experimental results. Furthermore, the predicted complex modulus pattern and magnetorheological effect agree with the experimental data using both the learned and unlearned data.
Host-trailing satellite flight behaviour is associated with greater investment in peripheral visual sensory system in miltogrammine flies
Authors: Polidori Carlo , Piwczynski Marcin , Ronchetti Federico , Johnston Nikolas P. , Szpila Krzysztof
Published: February 2022

Insect sensory systems are the subjects of different selective pressures that shape their morphology. In many species of the flesh fly subfamily Miltogramminae (Diptera: Sarcophagidae) that are kleptoparasitic on bees and wasps, females perch on objects close to the host nests and, once a returning host is detected, they follow it in flight at a fixed distance behind until reaching the nest. We hypothesized that such satellite (SAT) flight behaviour, which implies a finely coordinated trailing flight, is associated with an improved visual system, compared to species adopting other, non-satellite (NON-SAT) strategies. After looking at body size and common ancestry, we found that SAT species have a greater number of ommatidia and a greater eye surface area when compared to NON-SAT species. Ommatidium area is only affected by body size, suggesting that selection changes disproportionately (relative to body size variation) the number of ommatidia and as a consequence the eye area, instead of ommatidium size. SAT species also tend to have larger ocelli, but their role in host-finding was less clear. This suggests that SAT species may have a higher visual acuity by increasing ommatidia number, as well as better stability during flight and motion perception through larger ocelli. Interestingly, antennal length was significantly reduced in SAT species, and ommatidia number negatively correlated with antennal length. While this finding does not imply a selection pressure of improved antennal sensory system in species adopting NON-SAT strategies, it suggests an inverse resource (i.e. a single imaginal disc) allocation between eyes and antennae in this fly subfamily.
Isolation of rhizosheath and analysis of microbial community structure around roots of Stipa grandis
Authors: Zhu Ai-Min , Wu Qian , Liu Hai-Li , Sun Hai-Lian , Han Guo-Dong
Published: February 2022

Root zone microbial structure is particularly complex in plants with rhizosheaths, and greater understanding of the rhizosheath may play an important role in the future development of sustainable agricultural practices. However, one important reason to focus study on rhizosheath microbial structure is that there is no definite method for rhizosheath separation. The aim of this study was to explore rhizosheath isolation methods and the diversity characteristics of microorganisms around the rhizosphere. In this study, we isolated the rhizosheath of Stipa grandis, a dominant species in desert steppe, and the microorganisms in the roots, root epidermis, rhizosheath and rhizosphere soil were extracted and sequenced by 16S rRNA and ITS. The alpha diversity index of bacteria in Stipa grandis rhizosphere soil was the greatest, followed by rhizosheath, and the alpha diversity index of endophytic bacteria in root system was the smallest. The alpha diversity index of fungi in the rhizosheath and rhizosphere soil were significantly higher than that in the root epidermis and root system. There were significant differences in bacterial community structure between the root epidermis, endophytic bacteria, rhizosheath and rhizosphere soil. Unlike bacterial community structure, the community structure of fungi in the root epidermis was similar that of endophytic fungi, but significantly different from those in rhizosheath and rhizosphere soil. This study demonstrated a feasible method for separating plant rhizosheath and root epidermis. We suggest that the root epidermis can act as the interface between the host plant root and the external soil environment. We will have to re-examine the biological and ecological significance of rhizosheath and microorganisms in rhizosheath, as well as the mechanism explaining the close relationship of the rhizosheath and the plant root epidermis. This study provides theoretical and technical guidance for the isolation of the plant rhizosheath and the study of microorganisms in plant rhizosheath.
Improved fixation stability for repairing pedicle screw loosening using a modified cement filling technique in porcine vertebrae
Authors: Hsieh Ming-Kai , Li Yun-Da , Li Yu-Chen , Liu Mu-Yi , Tsai Tsung-Ting , Lai Po-Liang , Tai Ching-Lung
Published: February 2022

Polymethylmethacrylate (PMMA) has been applied clinically and biomechanically repair loose pedicle screws. Controversies have arisen over data due to uncontrolled cement properties, various locations and sizes of fenestrated holes in repair screws, irregular holes and different bone densities of specimens. In this study, the pullout strength was compared for two techniques, the modified technique to use PMMA to augment a threaded hole and the traditional technique with retrograde injection of a PMMA filling, for standard loose screws in porcine vertebrae. Both techniques provided statistically significant results for sufficiently randomized specimens and experimental procedures. The difference in the pullout strength between conical and cylindrical screws for the aforementioned cement augmentation techniques was also investigated. Twenty-four single-level fresh-frozen lumbar vertebrae from L1 to L6 were harvested from four mature pigs. A total of 0.8 ml of PMMA was retrograde injected into screw holes with a 5.5 mm diameter, followed by insertion of a 5.0 mm diameter repair screw in the traditional group (n = 12). A stiff threaded PMMA hole was created with a 4.5 mm tapping screw before insertion of repair screws in the modified group (n = 12). Two screw geometries were randomly assigned as cylindrical (n = 6) and conical (n = 6) in each group. The correlations between filling techniques, screw geometries and axial pullout strength were analyzed. An appropriate screw trajectory and insertion depth were confirmed using X-ray imaging prior to pullout testing in both groups. For a given screw geometry (cylindrical or conical), the pullout force of the modified group was significantly higher than that of the traditional group. There was no significant difference in the pullout force between the screw geometries for a given filling technique. The cement augmentation technique is far more influential than the screw outer geometry. The modified PMMA technique created a greater anchor force than the traditional method and could be an alternative for revision of pedicle screw loosening.
FTIR differentiation based on genomic DNA for species identification of Shigella isolates from stool samples
Authors: Pakbin Babak , Zolghadr Leila , Rafiei Shahnaz , Brück Wolfram Manuel , Brück Thomas B.
Published: February 2022

Shigellosis is one of the major public health concerns in developing and low-income countries caused by four species of Shigella. There is an apparent need to develop rapid, cost-effective, sensitive and specific methods for differentiation of Shigella species to be used in outbreaks and health surveillance systems. We developed a sensitive and specific Fourier-transform infrared spectroscopy (FTIR) based method followed by principal component analysis (PCA) and hierarchical clustering analysis (HCA) assays to differentiate four species of Shigella isolates from stool samples. The FTIR based method was evaluated by differentiation of 91 Shigella species from each other in clinical samples using both gold standards (culture-based and agglutination methods) and developed FTIR assay; eventually, the sensitivity and specificity of the developed method were calculated. In summary, four distinct FTIR spectra associated with four species of Shigella were obtained with wide variations in three definite regions, including 1800–1550 cm−1, 1550–1100 cm−1, and 1100–800 cm−1 distinguish these species from each other. In this study, we found the FTIR method followed by PCA analysis with specificity, sensitivity, differentiation error and correct differentiation rate values of 100, 100, 0 and 100%, respectively, for identification and differentiation of all species of the Shigella in stool samples.
Impacts of continuous and rotational cropping practices on soil chemical properties and microbial communities during peanut cultivation
Authors: Li Huying , Li Chaohui , Song Xin , Liu Yue , Gao Qixiong , Zheng Rui , Li Jintai , Zhang Pengcheng , Liu Xunli
Published: February 2022

Long-term monocultures have severely inhibited the cultivation of Chinese peanut (Arachis hypogaea L.). In this study, the effects of continuous cropping on soil chemical properties and microbial communities were investigated in peanut fields that had been in crop rotation for 10 years and in monoculture for 10 years. The results found that long-term monoculture increased the activities of available potassium, available phosphorus, available nitrogen, soil organic matter, urease, acid phosphatase and catalase; while decreasing the activity of catalase. The diversity and abundance of soil bacteria and fungi is higher under continuous peanut cultivation. At the genus level, the relative abundance of potentially beneficial microflora genera was higher in the rhizosphere soil of rotational cropping than in continuous cropping, while the opposite was true for the relative abundance of potentially pathogenic fungal genera. Principal coordinates and cluster analysis indicated that continuous cropping altered the structure of the microbial community. The results of the functional predictions showed significant differences in the functioning of the rhizosphere microbial community between continuous and rotational cropping. In conclusion, long-term continuous cropping changed the chemical properties of the soil, altered the structure and function of the soil bacterial and fungal communities in peanut rhizosphere, which to some extent reduced the relative abundance of potentially beneficial microbial genera and increased the relative abundance of potentially pathogenic fungal genera, thus increasing the potential risk of soil-borne diseases and reducing the yield and quality of peanut. Therefore, in the actual production process, attention should be paid not only to the application of chemical fertilizers, but also to crop rotation and the application of microbial fertilizers.
Structure of the stress-related LHCSR1 complex determined by an integrated computational strategy
Authors: Guarnetti Prandi Ingrid , Sláma Vladislav , Pecorilla Cristina , Cupellini Lorenzo , Mennucci Benedetta
Published: February 2022

Light-harvesting complexes (LHCs) are pigment-protein complexes whose main function is to capture sunlight and transfer the energy to reaction centers of photosystems. In response to varying light conditions, LH complexes also play photoregulation and photoprotection roles. In algae and mosses, a sub-family of LHCs, light-harvesting complex stress-related (LHCSR), is responsible for photoprotective quenching. Despite their functional and evolutionary importance, no direct structural information on LHCSRs is available that can explain their unique properties. In this work, we propose a structural model of LHCSR1 from the moss P. patens, obtained through an integrated computational strategy that combines homology modeling, molecular dynamics, and multiscale quantum chemical calculations. The model is validated by reproducing the spectral properties of LHCSR1. Our model reveals the structural specificity of LHCSR1, as compared with the CP29 LH complex, and poses the basis for understanding photoprotective quenching in mosses.