bluuebunny/crossref_metadata_2025_split huggingface dataset:
Ornithopter Trajectory Optimization with Neural Networks and Random Forest
Authors: Pérez-Cutiño M. A. , Rodríguez F. , Pascual L. D. , Díaz-Báñez J. M. 
Published: May 2022

AbstractTrajectory optimization has recently been addressed to compute energy-efficient routes for ornithopter navigation, but its online application remains a challenge. To overcome the high computation time of traditional approaches, this paper proposes algorithms that recursively generate trajectories based on the output of neural networks and random forest. To this end, we create a large data set composed by energy-efficient trajectories obtained by running a competitive planner. To the best of our knowledge our proposed data set is the first one with a high number of pseudo-optimal paths for ornithopter trajectory optimization. We compare the performance of three methods to compute low-cost trajectories: two classification approaches to learn maneuvers and an alternative regression method that predicts new states. The algorithms are tested in several scenarios, including the landing case. The effectiveness and efficiency of the proposed algorithms are demonstrated through simulation, which show that the machine learning techniques can be used to compute the flight path of the ornithopter in real time, even under uncertainties such as wrong sensor readings or re-positioning of the target. Random Forest obtains the higher performance with more than 99% and 97% of accuracy in a landing and a mid-range scenario, respectively.
The Effort of Reasoning: Modelling the Inference Steps of Boundedly Rational Agents
Authors: Solaki Anthia 
Published: May 2022

AbstractIn this paper we design a new logical system to explicitly model the different deductive reasoning steps of a boundedly rational agent. We present an adequate system in line with experimental findings about an agent’s reasoning limitations and the cognitive effort that is involved. Inspired by Dynamic Epistemic Logic, we work with dynamic operators denoting explicit applications of inference rules in our logical language. Our models are supplemented by (a) impossible worlds (not closed under logical consequence), suitably structured according to the effect of inference rules, and (b) quantitative components capturing the agent’s cognitive capacity and the cognitive costs of rules with respect to certain resources (e.g. memory, time). These ingredients allow us to avoid problematic logical closure principles, while at the same time deductive reasoning is reflected in our dynamic truth clauses. We further show that our models can be reduced to awareness-like plausibility structures that validate the same formulas and we give a sound and complete axiomatization with respect to them. This approach to the agent’s internal deductive reasoning is finally combined with actions of external information.
Tunable Assembly and Magnetic Interactions in Two Cyano-bridged FeIII–CoII Bimetallic Complexes
Authors: Yao Nian-Di , Wang Xi-Lun , Wang Xiao-Qin , Liu Jun-Shen , Zheng Hui 
Published: May 2022

Abstract
Using a new semi-rigid tetradentate ligand and two cyanometalate building blocks with different steric hindrance, a Fe2Co triangular unit [(Tp)FeIII(CN)3]2CoII(bpmb)·2H2O [1; Tp = hydrotris(pyrazolyl)borate; bpmb = 1,2-bis(3-(2-pyridyl)pyrazol-1-ylmethyl)benzenes] and a Fe2Co2 square unit {[(pzTp)FeIII(CN)3]2[CoII(bpmb)]2}·[(pzTp)FeIII(CN)3]2·4H2O [2; pzTp = tetrakis(pyrazolyl)borate] were synthesized via tunable assembly. Both compounds adopt cis arrangement because of the structural distorted semi-rigid bpmb. Tetranuclear square of 2 was formed due to larger steric hindrance building block of [(pzTp)FeIII(CN)3]− compared with [(Tp)FeIII(CN)3]− in trinculear 1. Magnetic measurements show that antiferromagnetic interactions dominate in 1 and 2. The fitting results of J values suggest a positive correlation between magnetic orbitals overlap of FeIII and CoII ions and Co–N≡C bond angles.

Graphical Abstract
Two cis arrangement cyanometalate [Fe-Co] clusters were synthesized via tunable assembly with a new semi-rigid tetradentate ligand. The tetranuclear cluster was formed because of larger steric hindrance of pzTp. Both compounds exhibit dominant antiferromagnetic couplings. The fitting results of J values suggest a positive correlation between magnetic orbitals overlap of FeIII and CoII ions and Co–N≡C bond angles.
Weak acid leaching of uranium ore from a high carbonate uranium deposit
Authors: Chen Shifeng , Wei Xuebin , Liu Jinhui , Sun Zhanxue , Chen Gongxin , Yang Mei , Liu Yuanyuan , Wang Duo , Ma Chengcui , Kong Dexuan 
Published: May 2022

AbstractMineralogical study showed that the Yuejin uranium ore is from a low grade, high carbonate and high pyrite sandstone type uranium deposit. Uranium leaching rate, uranium speciation of leachate, leaching kinetics and precipitation analysis were investigated under the conditions of different acidity, liquid–solid ratio and H2O2 concentration. The test results showed that the weak acid leaching process can be used to develop high carbonate type uranium deposits, however, because of the high content of pyrite, other oxidants except high concentration H2O2 need to be considered.
Higher-Order Logic and Disquotational Truth
Authors: Picollo Lavinia , Schindler Thomas 
Published: May 2022

AbstractTruth predicates are widely believed to be capable of serving a certain logical or quasi-logical function. There is little consensus, however, on the exact nature of this function. We offer a series of formal results in support of the thesis that disquotational truth is a device to simulate higher-order resources in a first-order setting. More specifically, we show that any theory formulated in a higher-order language can be naturally and conservatively interpreted in a first-order theory with a disquotational truth or truth-of predicate. In the first part of the paper we focus on the relation between truth and full impredicative sentential quantification. The second part is devoted to the relation between truth-of and full impredicative predicate quantification.
[99Tc]Sestamibi bioaccumulation induces apoptosis in prostate cancer cells: an in vitro study
Authors: Urbano Nicoletta , Scimeca Manuel , Bonanno Elena , Bonfiglio Rita , Mauriello Alessandro , Schillaci Orazio 
Published: May 2022

AbstractThe main aim of this preliminary in vitro study was to evaluate both the uptake of [99Tc]Sestamibi into prostate cancer cells and the relationship among [99Tc]Sestamibi bioaccumulation, cancer cells proliferation and apoptosis. An in vitro study in which PC3 prostate cancer cell line was cultured with increasing doses of decayed sestamibi has been developed. Specifically, PC3 cells were incubated with three different concentrations of [99Tc]Sestamibi: 10 µg/mL, 1 µg/mL, and 0.1 µg/mL Expression of apoptotic caspase-3 and AIF, as well as the ultrastructure of PC3 cells, were evaluated at T0 and after 24, 48, 72, and 120 h following [99Tc]Sestamibi incubation. Data here reported showed the bioaccumulation of sestamibi in prostate cancer cells. As concern the cancer cell homeostasis, the treatment of PC3 cells with [99Tc]Sestamibi strongly influenced the cells proliferation. Indeed, a significant reduction in the number of mitosis was observed. Noteworthy, the accumulation of sestamibi in prostate cancer cells was associated with the appearance of morphological signs of apoptosis. The increase in AIF and caspase 3 expression in prostate cancer cells treated with 10 µg/mL of [99Tc]Sestamibi confirmed that this radiopharmaceutical can trigger the apoptosis. To the best of our knowledge, this preliminary study reported for the first time in vitro data about the uptake of sestamibi in prostate cancer cells. The evidence about the accumulation of sestamibi in prostate cancer cells and its role in the apoptosis process could open new clinical perspectives on the use of this radiopharmaceutical in both the diagnosis and treatment of prostate cancers.
Long Hands gesture recognition system: 2 step gesture recognition with machine learning and geometric shape analysis
Authors: Popov Pavel A. , Laganière Robert 
Published: May 2022

AbstractA two stage real-time hand gesture recognition system is presented. It combines a machine learning trained detection step with a colour processing contour shape validation step. The detection step is done with either Adaboost Cascades or Support Vector Machines using HOG features. The system achieves a low false positive rate and a sufficient true positive rate necessary for robust real-time performance. It performs well compared to MobileNets a state of the art Neural Network for mobile real-time applications.
Relation between digital tool practices in the language arts classroom and reading comprehension scores
Authors: Salmerón Ladislao , Vargas Cristina , Delgado Pablo , Baron Naomi 
Published: May 2022

AbstractConcerns about the negative effects of digitalization on students’ reading comprehension, empirically backed by recent meta-analyses, question the efficacy of digital tools in the language arts classroom. By analyzing data from 4 and 8th grade US students from NAEP 2017, we aimed to test the generalization of the negative association between screens use and reading comprehension test scores within language arts classrooms, and to identify teachers’ practices to support comprehension, which could reduce such a negative relationship. We used data from 149,400 4th grade and 144,900 8th grade students to predict their reading comprehension scores based on their frequency of use of digital devices in the language arts class, as well as on the specific learning activities performed with such devices. Results revealed that amount of daily use of digital devices was negatively related to scores on a reading comprehension test. In addition, teachers’ uses of digital tools to support students’ reading comprehension showed positive relations for student use of digital devices for reading projects, and negative relations for activities addressing specific reading skills, such as building and practicing vocabulary. We discuss these results in light of our current understanding of the effects of digitalization on reading.
3D map reconstruction using a monocular camera for smart cities
Authors: Hu Yuxi , Fu Taimeng , Niu Guanchong , Liu Zixiao , Pun Man-On 
Published: May 2022

AbstractLarge-scale high-resolution three-dimensional (3D) maps play a vital role in the development of smart cities. In this work, a novel deep learning-based multi-view-stereo method is proposed for reconstructing the 3D maps in large-scale urban environments by exploiting a monocular camera. Compared with other existing works, the proposed method can perform 3D depth estimation more efficiently in terms of computational complexity and graphics processing unit memory usage. As a result, the proposed method can practically perform depth estimation for each pixel before generating 3D maps for even large-scale scenes. Extensive experiments on the well-known DTU dataset and real-life data collected on our campus confirm the good performance of the proposed method.
Metabotyping the Welsh population of badgers based on thoracic fluid
Authors: Scott-Baumann James , Pizzey Richard , Beckmann Manfred , Villarreal-Ramos Bernardo , King Jonathan , Hopkins Beverley , Rooke David , Hewinson Glyn , Mur Luis A. J. 
Published: May 2022

Abstract
Introduction
The European badger (Meles meles) is a known wildlife reservoir for bovine tuberculosis (bTB) and a better understanding of the epidemiology of bTB in this wildlife species is required for disease control in both wild and farmed animals. Flow infusion electrospray—high-resolution mass spectrometry (FIE-HRMS) may potentially identify novel metabolite biomarkers based on which new, rapid, and sensitive point of care tests for bTB infection could be developed.

Objectives
In this foundational study, we engaged on assessing the baseline metabolomic variation in the non-bTB infected badger population (“metabotyping”) across Wales.

Methods
FIE-HRMS was applied on thoracic fluid samples obtained by post-mortem of bTB negative badgers (n = 285) which were part of the Welsh Government ‘All Wales Badger Found Dead’ study.

Results
Using principal component analysis and partial least squares—discriminant analyses, the major sources of variation were linked to sex, and to a much lesser extent age, as indicated by tooth wear. Within the female population, variation was seen between lactating and non-lactating individuals. No significant variation linked to the presence of bite wounds, obvious lymphatic lesions or geographical region of origin was observed.

Conclusion
Future metabolomic work when making comparisons between bTB infected and non-infected badger samples will only need be sex-matched and could focus on males only, to avoid lactation bias.
Computation for Latent Variable Model Estimation: A Unified Stochastic Proximal Framework
Authors: Zhang Siliang , Chen Yunxiao 
Published: May 2022

AbstractLatent variable models have been playing a central role in psychometrics and related fields. In many modern applications, the inference based on latent variable models involves one or several of the following features: (1) the presence of many latent variables, (2) the observed and latent variables being continuous, discrete, or a combination of both, (3) constraints on parameters, and (4) penalties on parameters to impose model parsimony. The estimation often involves maximizing an objective function based on a marginal likelihood/pseudo-likelihood, possibly with constraints and/or penalties on parameters. Solving this optimization problem is highly non-trivial, due to the complexities brought by the features mentioned above. Although several efficient algorithms have been proposed, there lacks a unified computational framework that takes all these features into account. In this paper, we fill the gap. Specifically, we provide a unified formulation for the optimization problem and then propose a quasi-Newton stochastic proximal algorithm. Theoretical properties of the proposed algorithms are established. The computational efficiency and robustness are shown by simulation studies under various settings for latent variable model estimation.
Impact of tissue properties on time-dependent alterations in apparent diffusion coefficient: a phantom study using oscillating-gradient spin-echo and pulsed-gradient spin-echo sequences
Authors: Ichikawa Kazushige , Taoka Toshiaki , Ozaki Masanori , Sakai Mayuko , Yamaguchi Hiroshi , Naganawa Shinji 
Published: May 2022

Abstract
Purpose
The purpose of this study was to investigate whether the changes in apparent diffusion coefficients (ADCs) due to differences in diffusion time reflect tissue properties in actual measurements of phantoms.

Materials and methods
Various n-alkane phantoms and sucrose/collagen phantoms with various collagen densities were set up with and without polyvinyl alcohol (PVA) foam with an average pore diameter of 300 μm. Thus, n-alkanes or sucrose/collagen represented substrate viscosity and the presence of PVA foam represented tissue structure with septum. Diffusion-weighted images with various diffusion times (7.71–60 ms) were acquired using pulsed-gradient spin-echo (PGSE) and oscillating-gradient spin-echo (OGSE) sequences. The ADCs of the phantoms with and without PVA foam were calculated.

Results
The ADCs of some of the phantoms without PVA decreased with diffusion times decreased. In the n-alkane phantoms, only C8H18 showed significantly different ADCs depending on the use of PVA foam in the OGSE sequence. On the other hand, sucrose/collagen phantoms showed significant differences according to diffusion time. The ADCs of the phantoms decreased as the molecular size of the n-alkanes or collagen density of the sucrose/collagen phantom increased. Compared to phantoms without PVA foam, the ADC of the phantoms with PVA foam decreased as the diffusion time increased.

Conclusion
Changes in ADCs due to differences in diffusion time reflect tissue properties in actual measurements of phantoms. These changes in ADCs can be used for tissue characterization in vivo.
The role of perceptions and social norms in shaping women’s fertility preferences: a case study from Ethiopia
Authors: Rodrigues Patrícia , Manlosa Aisa O. , Fischer Joern , Schultner Jannik , Hanspach Jan , Senbeta Feyera , Dorresteijn Ine 
Published: May 2022

AbstractThe population–environment–food nexus is a sustainability challenge for the Global South, and for Africa in particular, where rapid human population growth typically overlaps with high levels of food insecurity and environmental degradation. In this context, it is important to understand the reasons driving high fertility in these regions. Here, we examined possible determinants of women’s fertility preferences in rural southwestern Ethiopia. Using a survey tool (n = 120), we assessed women’s perceptions of four key environmental stressors, namely food insecurity, environmental degradation, human population growth, and land scarcity. Through statistical modelling we tested whether there was a relationship between perceptions of future trends in these stressors and women’s fertility preferences; expressed as their desired number of children and use of family planning methods. This analysis was complemented by a qualitative content analysis of the survey’s open-ended questions, to contextualize and interpret the quantitative data. Our quantitative results indicated that perceptions of future trends in key stressors had little effect on fertility preferences of respondents, with the exception of perceptions of human population growth. Our qualitative data suggested that this may be due to the influence of social-cultural norms and religion, decision-making with the husband, as well as a perceived utilitarian value of children. These findings have important implications for the development of interventions to slow down human population growth. Our findings suggest the need to look beyond improved physical access to family planning, and develop a new suite of deliberative approaches that engage with social norms, religion, and gender equity.
A Combined Powder Metallurgical Approach to Process Gamma-TiAl with Composite Structure
Authors: Gao R. , Peng H. , Guo H. , Chen B. 
Published: May 2022

Abstract
Gamma-TiAl (> 99 pct) sample with composite structural design was fabricated by a combined powder metallurgical approach of the SEBM capsule and HIP. Selective electron beam melting (SEBM) was used to create the pre-sintered powder bed, composite structure and the capsule, followed by hot isostatic pressing (HIP) at 1250 °C. A mixture of plasma rotating electrode (PREP) and gas atomization (AA) processed powders, with the respective higher (49.66 at. pct) and lower Al (47.61 at. pct) concentrations, was employed successfully to track the transition from powder to bulk sample, providing enriched information to elucidate the microstructure formation mechanism. The selective melting created composite structure consisted of the fine equiaxed γ-grains, while the rest of the powder bed that had been subjected to preheat only and then HIP was characterized by the triple microstructure. Formation mechanisms of such unique microstructure, consisting of primarily the coarse γ-grains and fine γ-grains with the previous particle boundaries (PPBs), were correlated to the Al concentration. The Al-rich powder was transformed into the coarse γ-grains, while the Al-depleted powder was responsible for the fine γ-grains with the PPBs. This finding suggests that the detrimental PPBs can be eliminated by increasing the Al concentration in the nascent powder. In the post-heat treated condition (1350 °C), no PPBs was found, suggesting that heat treatment is beneficial by eliminating the PPBs. For the designed composite structures, there was evidence to suggest desired distribution of the hard and soft regions, with the fine γ-grains associated with the composite structure being responsible for the high hardness region.
The Inverse and Conventional Magnetocaloric Effects in Ni0.4Cu0.2Zn0.4Fe2-xDyxO4 Nanoferrites Over an Extraordinary Temperature Range
Authors: Hamad Mahmoud A. , Alamri Hatem R. 
Published: May 2022

AbstractThe magnetocaloric effect (MCE) of Ni0.4Cu0.2Zn0.4Fe2-xDyxO4 (x = 0.02, 0.03, and 0.04) nanoferrites is simulated using a phenomenological model. The analysis indicates that the MCE of Ni0.4Cu0.2Zn0.4Fe2-xDyxO4 nanoferrites is strongly influenced by Dy content in both conventional and inverse MCE. For conventional MCE, the full-width at half-maximum ($$\delta {\text{T}}_{{{\text{FWHM}}}}$$

δ

T
FWHM

) has significant values, ranging between 200 K and 258 K for Ni0.4Cu0.2Zn0.4Fe2-xDyxO4 nanoferrites. However, for inverse MCE, $$\delta {\text{T}}_{{{\text{FWHM}}}}$$

δ

T
FWHM

ranges between 25 and 55 K. The MCE of the Ni0.4Cu0.2Zn0.4Fe2-xDyxO4 system covers an extensive temperature range and is a particularly interesting prospect for nitrogen and hydrogen liquefaction.
From growth goals to proactive organizational resilience: first evidence in women-led and non-women-led Italian wineries
Authors: Casprini Elena , Pucci Tommaso , Zanni Lorenzo 
Published: May 2022

AbstractIn a fast-changing world, characterized by evenly unexpected challenges and shocks, being resilient is a crucial aspect for every organization. Drawing from the goal setting theory and the double standards of competence perspective, this study aims at understanding the antecedents of organizational proactive resilience. More precisely, it looks at the impact of quantitative and qualitative organizational growth goals on proactive resilience, distinguishing between women-led and non-women-led firms. Based on a unique sample of 167 Italian wineries (67 women-led and 100 non-women-led), this paper tests this theoretical model using path analysis techniques. The wine sector is a particularly interesting context to study the phenomenon due to its exposure to natural disasters, new consumers’ behaviours that are requiring firms to continuously innovate and differentiate in a traditionally low-tech sector, but also changes happening at wineries’ management level. In fact, the sector has been traditionally male dominated, but women are increasingly taking the lead. The findings indicate that growth goals differently contribute to proactive organizational resilience, but their effects vary in women- and non-women-led businesses. Specifically, these results suggest that in women-led wineries, proactive organizational resilience depends on quantitative growth goals while in non-women-led wineries businesses this depends on qualitative growth goals.
Imaging-Guided Treatment for Cardiac Amyloidosis
Authors: Ioannou Adam , Patel Rishi , Gillmore Julian D. , Fontana Marianna 
Published: May 2022

Abstract
Purpose of Review
This review will explore the role of cardiac imaging in guiding treatment in the two most commonly encountered subtypes of cardiac amyloidosis (immunoglobulin light-chain amyloidosis [AL] and transthyretin amyloidosis [ATTR]).

Recent Findings
Advances in multi-parametric cardiac imaging involving a combination of bone scintigraphy, echocardiography and cardiac magnetic resonance imaging have resulted in earlier diagnosis and initiation of treatment, while the evolution of techniques such as longitudinal strain and extracellular volume quantification allow clinicians to track individuals’ response to treatment. Imaging developments have led to a deeper understanding of the disease process and treatment mechanisms, which in combination result in improved patient outcomes.

Summary
The rapidly expanding treatment regimens for cardiac amyloidosis have led to an even greater reliance on cardiac imaging to help establish an accurate diagnosis, monitor treatment response and aid the adjustment of treatment strategies accordingly.