bluuebunny/crossref_metadata_2025_split huggingface dataset:
Interaction of Docetaxel with Phosphatidylcholine Membranes: A Combined Experimental and Computational Study
Authors: Aranda Elisa , Teruel José A. , Ortiz Antonio , Pérez-Cárceles María Dolores , Aranda Francisco J. 
Published: February 2022

AbstractThe antineoplastic drug Docetaxel is a second generation taxane which is used against a great variety of cancers. The drug is highly lipophilic and produces a great array of severe toxic effects that limit its therapeutic effectiveness. The study of the interaction between Docetaxel and membranes is very scarce, however, it is required in order to get clues in relation with its function, mechanism of toxicity and possibilities of new formulations. Using phosphatidylcholine biomimetic membranes, we examine the interaction of Docetaxel with the phospholipid bilayer combining an experimental study, employing a series of biophysical techniques like Differential Scanning Calorimetry, X-Ray Diffraction and Infrared Spectroscopy, and a Molecular Dynamics simulation. Our experimental results indicated that Docetaxel incorporated into DPPC bilayer perturbing the gel to liquid crystalline phase transition and giving rise to immiscibility when the amount of the drug is increased. The drug promotes the gel ripple phase, increasing the bilayer thickness in the fluid phase, and is also able to alter the hydrogen-bonding interactions in the interfacial region of the bilayer producing a dehydration effect. The results from computational simulation agree with the experimental ones and located the Docetaxel molecule forming small clusters in the region of the carbon 8 of the acyl chain palisade overlapping with the carbonyl region of the phospholipid. Our results support the idea that the anticancer drug is embedded into the phospholipid bilayer to a limited amount and produces structural perturbations which might affect the function of the membrane.
Graphical Abstract
Financing Pediatric Surgery: A Provider's Perspective from the Global Initiative for Children's Surgery
Authors: Ullrich Sarah J. , Tamanna Nowrin , Aziz Tasmiah Tahera , Philipo Godfrey Sama , Banu Tahmina , Ameh Emmanuel A. , Ozgediz Doruk ,   the Global Initiative for Children's Surgery
Published: February 2022

AbstractBackgroundHalf the world's population is at risk of catastrophic health expenditure (CHE, out‐of‐pocket spending of more than 10% of annual expenditure) should they require surgery. Protection against CHE is a key indicator of successful health care delivery and has been identified as a priority area by the Global Initiative for Children's Surgery (GICS). Data specific to pediatric surgical patients is limited. This study examines the financial risks for pediatric surgical patients and their families from a provider's perspective.MethodsWe surveyed GICS members about the existing financial protection mechanisms and estimated expenditures for their patients. Questions were structured based on the National Surgical, Obstetric and Anesthesia Planning Surgical Indicators and finalized based on multi‐institutional consensus between high‐income country and low‐and middle‐income country (LMIC) providers. Chi‐squared test, Fisher's exact test and student's t‐test were used as appropriate.ResultsAmong 107 respondents, 72.4% were from low income or lower‐middle income (LIC/LMIC) countries, and 55.1% were attending or consultant physicians. Families were most likely to decline surgery in LIC/LMIC due to inability to afford treatment (mean Likert = 3.77 ± 1.06). The odds of incurring CHE after children's surgery are up to 17 times greater in LIC/LMIC (P = 0.001, unadjusted OR 17.28, 95%CI 2.13–140.02). Over 50% of families of children undergoing major surgery in these settings face CHE. An estimated 5.1% of providers in LIC/LMIC and 56.2% (P < 0.001) of providers in UMIC/HIC reported that families are able to pay for their direct medical costs with the assistance available to them and were more likely to sell assets (74.4% vs. 33.3%, P = 0.005).ConclusionPatients in LMICs are at greater risk for CHE and have less financial risk protection than their HIC counterparts. Given this disparity, intervention is needed to make safe surgery affordable for children worldwide.
Harmonization of design-based mapping for spatial populations
Authors: Marcelli A. , Fattorini L. , Franceschi S. 
Published: February 2022

AbstractThe mapping of a survey variable throughout a continuum or for finite populations of units is usually performed from a model-dependent perspective. Nevertheless, when a sample of locations/units is selected by a probabilistic sampling scheme, the complex task of modelling can be avoided by using the inverse distance weighting interpolator and deriving the properties of maps in a design-based perspective. Conditions ensuring consistency of maps can be derived mainly based on some obvious assumptions about the pattern of the survey variable throughout the study region as well from the feature of the sampling scheme adopted to select locations/units. Nevertheless, in a design-based setting the totals of the survey variable for a set of domains partitioning the study region are commonly estimated by traditional estimators such as the Horvitz–Thompson estimator in the case of finite populations or the Monte-Carlo estimator in the case of continuous populations or by related estimators exploiting the information of auxiliary variables. That necessarily gives rise to different total estimates with respect to those achieved from the resulting maps as the sum of the interpolated values within domains. To obtain non-discrepant results, a harmonization of maps is here suggested, in such a way that the resulting totals arising from maps coincide with those achieved by traditional estimation. The capacity of the harmonization procedure to maintain consistency is argued theoretically and checked by a simulation study performed on some real populations.
Building consensus and increasing self-efficacy: participatory scenarios as a tool for developing food security solutions in West Africa
Authors: Olabisi Laura Schmitt , Sidibé Amadou , Assan Elsie , Adebiyi Jelili , Totin Edmond , Thompson-Hall Mary 
Published: February 2022

AbstractFood security in West Africa is threatened by climate change, as well as demographic shifts and land constraints. Communities and policy-makers in the region need to plan for long term sustainability and food security when many conditions are highly uncertain. Participatory scenario planning has been proposed as a tool for building strategic action in the face of uncertainty. Proponents have made claims that this process can generate consensus and self-efficacy for action, but these claims have not been tested empirically. We used two parallel scenario processes in Ghana and Mali, designed with the goal of prioritizing strategic actions for food security, to gather data from participants on their views of the top challenges to food security in their region, the causes of those challenges, and actors who should be implementing solutions. The data indicate that the scenario process did promote consensus among participants on these topics, as well as self- and collective-efficacy to take action, and that these characteristics persisted past the duration of the scenario process. Agreement among local and regional actors around what actions to take to promote food security and belief that they are capable of implementing those actions are key prerequisites for planning under conditions of high uncertainty. Participatory scenario exercises are therefore a useful tool.
Selbsterfahrung in der Psychodrama Ausbildung
Authors: Fürst Jutta 
Published: February 2022

ZusammenfassungIn diesem Beitrag der Zeitschrift für Psychodrama und Soziometrie wird erörtert, dass Selbsterfahrung in der Ausbildung zur Psychodramatherapeut*in im Vergleich zur Selbsterfahrung in anderen psychotherapeutischen Ansätzen, aus historischen, philosophischen und technischen Gründen eine besondere Form hat. Der wissenschaftlichen Auseinandersetzung mit der Selbsterfahrung wurde in anderen therapeutischen Verfahren ungleich mehr Raum gegeben als im Psychodrama. Auch die Anforderungen an die Ausbildung haben sich in den letzten Jahren besonders durch die Akademisierung geändert.Aus diesen Gründen ist es mehr als sinnvoll, die Entwicklung der Selbsterfahrung als Element der Ausbildung näher zu betrachten, um aus den bisherigen Erfahrungen, Perspektiven für eine zukünftige Ausbildungsgestaltung zu erarbeiten.Der Beitrag versucht die Unterschiede sichtbar zu machen und die Entwicklung der Selbsterfahrung als Ausbildungsteil nachzuzeichnen. Dabei werden die Ziele, Wirkweise sowie Vor- und Nachteile der Selbsterfahrung in der Ausbildung beschrieben, Rückschlüsse aus den bisherigen Erfahrungen gezogen und mögliche Änderungen für die Zukunft skizziert.
Remnants, LDL, and the Quantification of Lipoprotein-Associated Risk in Atherosclerotic Cardiovascular Disease
Authors: Packard Chris J. 
Published: February 2022

Abstract

Purpose of Review
Implementation of intensive LDL cholesterol (LDL-C) lowering strategies and recognition of the role of triglyceride-rich lipoproteins (TRL) in atherosclerosis has prompted re-evaluation of the suitability of current lipid profile measurements for future clinical practice.

Recent Findings
At low concentrations of LDL-C (< 1.8 mmol/l/70 mg/dl), the Friedewald equation yields estimates with substantial negative bias. New equations provide a more accurate means of calculating LDL-C. Recent reports indicate that the increase in risk per unit increment in TRL/remnant cholesterol may be greater than that of LDL-C. Hence, specific measurement of TRL/remnant cholesterol may be of importance in determining risk. Non-HDL cholesterol and plasma apolipoprotein B have been shown in discordancy analyses to identify individuals at high risk even when LDL-C is low.

Summary
There is a need to adopt updated methods for determining LDL-C and to develop better biomarkers that more accurately reflect the abundance of TRL remnant particles.
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

Abstract
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

AbstractSpeech 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

AbstractLegal 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

AbstractOutlier 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

AbstractGroup 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.
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

AbstractThe 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

AbstractThe 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

AbstractBoth 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

AbstractThe 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.