bluuebunny/crossref_metadata_2025_split huggingface dataset:
A comprehensive assessment of insecticide resistance mutations in source and immigrant populations of the diamondback moth Plutella xylostella (L.)
Authors: Shen Xiu‐Jing , Cao Li‐Jun , Chen Jin‐Cui , Ma Li‐Jun , Wang Jia‐Xu , Hoffmann Ary A. , Wei Shu‐Jun 
Published: October 2022

AbstractBACKGROUNDThe diamondback moth (DBM) Plutella xylostella has developed resistance to almost all insecticides used to control it. Populations of DBM in temperate regions mainly migrate from annual breeding areas. However, the distribution pattern of insecticide resistance of DBM within the context of long‐distance migration remains unclear.RESULTSIn this study, we examined the frequency of 14 resistance mutations for 52 populations of DBM collected in 2010, 2011, 2017 and 2018 across China using a high‐throughput KASP genotyping method. Mutations L1041F and T929I conferring pyrethroid resistance, and mutations G4946E and E1338D conferring chlorantraniliprole resistance were near fixation in most populations, whereas resistant alleles of F1020S, M918I, A309V and F1845Y were uncommon or absent in most populations. Resistance allele frequencies were relatively stable among different years, although the frequency of two mutations decreased. Principal component analysis based on resistant allele frequencies separated a southern population as an outlier, whereas the immigrants clustered with other populations, congruent with the migration pattern of northern immigrants coming from the Sichuan area of southwestern China. Most resistant mutations deviated from Hardy–Weinberg equilibrium due to a lower than expected frequency of heterozygotes. The deviation index of heterozygosity for resistant alleles was significantly higher than the index obtained from single nucleotide polymorphisms across the genome. These findings suggest heterogeneous selection pressures on resistant mutations.CONCLUSIONOur results provide a picture of resistant mutation patterns in DBM shaped by insecticide usage and migration of this pest, and highlight the widespread distribution of resistance alleles in DBM. © 2022 Society of Chemical Industry.
Techniques and Survey for 3D Modeling of Touristic Caves: Valdemino Case
Authors: Pisoni Isabella Nicole , Cina Alberto , Grasso Nives , Maschio Paolo 
Published: October 2022

AbstractNowadays, touristic caves are a relevant topic among topographical and geological studies. Modern techniques allow to elaborate 3D models with high accuracy and precision. Anyway, underground surveys are always delicate to perform, due to narrow and difficult to reach environments. In this paper, we show a case study, “Valdemino” cave, that involved the utilization of different point cloud acquisition methods: UAV, TLS, SLAM. The first purpose was to obtain 3D models of outdoor and indoor environments with a medium and high accuracy. These models were used to calculate the thickness of the rock between surface and cave’s roof and will be used for further studies, taking part in the PRIN 2017 project, concerning the impact of the tourist on show caves. The second purpose was to discuss about the feasibility and precision of the different survey methods, when studying a cave. The results showed how SLAM technology is enough accurate for speleological purposes, if compared with the more accurate TLS method. It is precise, maneuverable, easy to use and it allowed to get into environments that TLS can’t reach, such as non-touristic areas.
Multi-platform, Multi-scale and Multi-temporal 4D Glacier Monitoring. The Rutor Glacier Case Study
Authors: Macelloni Myrta Maria , Corte Elisabetta , Ajmar Andrea , Cina Alberto , Giulio Tonolo Fabio , Maschio Paolo Felice , Pisoni Isabella Nicole 
Published: October 2022

AbstractAt present most alpine glaciers are not in equilibrium with the current climate, as a result they are undergoing a dramatic mass loss. Monitoring glacial variations is crucial to assess the consequences of climate change on the territory. In this work different geomatics techniques are exploited to measure and monitor the Rutor glacier over the years. In this study two different techniques were adopted to generate 3 digital surface models (DSMs): aerial and satellite photogrammetry. Two photogrammetric aerial surveys were carried out: at the end of the hydrological year 2019/20 and at the end of the following hydrological year. Additionally, a very high-resolution satellite stereo pair, acquired by the Pléiades-1A platform in 2017, was processed to assess whether satellite images can be applied to extract the 3D surface of the Rutor glacier. In order to evaluate the Rutor glacier mass-balance throughout the years several reference points were positioned and measured before the 2021 aerial flight. Thanks to the presence of the materialized points the 2021 model is considered as the ‘Reference Model’ against which subsequent models can be compared for glacier analysis. This model was validated by means of a comparison with the authoritative Regional DSM based on LiDAR surveys. In alpine glaciers, the positioning of artificial square cross target in time invariant areas is crucial to enable a multitemporal 4D analysis. The use of very high-resolution satellite imagery allows large areas to be mapped in 3D, but with lower accuracies proportionally decreasing with respect to slope and exposure.
Small Schwarzschild de Sitter black holes, quantum extremal surfaces and islands
Authors: Goswami Kaberi , Narayan K. 
Published: October 2022

Abstract
We study 4-dimensional Schwarzschild de Sitter black holes in the regime where the black hole mass is small compared with the de Sitter scale. Then the de Sitter temperature is very low compared with that of the black hole and we study the black hole, approximating the ambient de Sitter space as a frozen classical background. We consider distant observers in the static diamond, far from the black hole but within the cosmological horizon. Using 2-dimensional tools, we find that the entanglement entropy of radiation exhibits linear growth in time, indicative of the information paradox for the black hole. Self-consistently including an appropriate island emerging at late times near the black hole horizon leads to a reasonable Page curve. There are close parallels with flat space Schwarzschild black holes in the regime we consider.
„Clinical variant“-Galaktosämie: Andere Länder, andere Phänotypen …
Authors: Grünert Sarah Catharina , Schumann Anke , Härtling Anton , Hörster Friederike , Spiekerkoetter Ute , Pohl Martin 
Published: October 2022

ZusammenfassungEin 2 Monate altes afrikanisches Mädchen wurde mit Gedeihstörung, Exsikkose und renalem Fanconi-Syndrom vorgestellt. Eine Hepatopathie bestand nicht, und das Neugeborenenscreening war unauffällig. Die genetische Abklärung aufgrund des Fanconi-Syndroms ergab eine „Clinical-variant“-Galaktosämie. Diese Form der Galaktosämie, die typischerweise in der afrikanischen Bevölkerung vorkommt, ist mit einer hohen Restaktivität in der Leber und somit niedrigen Galaktosemetaboliten im Blut assoziiert, sodass die Diagnose im Neugeborenenscreening verpasst werden kann. Unser Fall zeigt, dass bei Kindern mit anderem ethnischen Hintergrund andere Phänotypen genetischer Erkrankungen vorliegen können, die den etablierten Screeningmethoden entgehen können und daher bei differenzialdiagnostischen Überlegungen Beachtung finden müssen.
Host-associated and Environmental Microbiomes in an Open-Sea Mediterranean Gilthead Sea Bream Fish Farm
Authors: Quero Grazia Marina , Piredda Roberta , Basili Marco , Maricchiolo Giulia , Mirto Simone , Manini Elena , Seyfarth Anne Mette , Candela Marco , Luna Gian Marco 
Published: October 2022

Abstract

Gilthead seabream is among the most important farmed fish species in the Mediterranean Sea. Several approaches are currently applied to assure a lower impact of diseases and higher productivity, including the exploration of the fish microbiome and its manipulation as a sustainable alternative to improve aquaculture practices. Here, using 16S rRNA gene high-throughput sequencing, we explored the microbiome of farmed seabream to assess similarities and differences among microbial assemblages associated to different tissues and compare them with those in the surrounding environment. Seabream had distinct associated microbiomes according to the tissue and compared to the marine environment. The gut hosted the most diverse microbiome; different sets of dominant ASVs characterized the environmental and fish samples. The similarity between fish and environmental microbiomes was higher in seawater than sediment (up to 7.8 times), and the highest similarity (3.9%) was observed between gill and seawater, suggesting that gills are more closely interacting with the environment. We finally analyzed the potential connections occurring among microbiomes. These connections were relatively low among the host’s tissues and, in particular, between the gut and the others fish-related microbiomes; other tissues, including skin and gills, were found to be the most connected microbiomes. Our results suggest that, in mariculture, seabream microbiomes reflect only partially those in their surrounding environment and that the host is the primary driver shaping the seabream microbiome. These data provide a step forward to understand the role of the microbiome in farmed fish and farming environments, useful to enhance disease control, fish health, and environmental sustainability.
The EUSO@TurLab project in the framework of the JEM-EUSO program
Authors: Barrillon P. , Battisti M. , Belov A. , Bertaina M. , Bisconti F. , Blin-Bondil S. , Bonino R. , Capel F. , Caruso R. , Casolino M. , Contino G. , Cotto G. , Dagoret-Campagne S. , Fenu F. , Fornaro C. , Forza R. , Gorodetzky P. , Guardone N. , Jung A. , Klimov P. , Manfrin M. , Marcelli L. , Mignone M. , Miyamoto H. , Mulas R. , Onorato M. , Parizot E. , Piotrowski L. , Plebaniak Z. , Prevot G. , Szabelski J. , Suino G. , Takizawa Y. , Tibaldi P. , Vigorito C. , Youssef A. 
Published: October 2022

AbstractThe EUSO@TurLab project aims at performing experiments to reproduce Earth UV emissions as seen from a low Earth orbit by the planned missions of the JEM-EUSO program. It makes use of the TurLab facility, which is a laboratory, equipped with a 5 m diameter and 1 m depth rotating tank, located at the Physics Department of the University of Turin. All the experiments are designed and performed based on simulations of the expected response of the detectors to be flown in space. In April 2016 the TUS detector and more recently in October 2019 the Mini-EUSO experiment, both part of the JEM-EUSO program, have been placed in orbit to map the UV Earth emissions. It is, therefore, now possible to compare the replicas performed at TurLab with the actual images detected in space to understand the level of fidelity in terms of reproduction of the expected signals. We show that the laboratory tests reproduce at the order of magnitude level the measurements from space in terms of spatial extension and time duration of the emitted UV light, as well as the intensity in terms of expected counts per pixel per unit time when atmospheric transient events, diffuse nightlow background light, and artificial light sources are considered. Therefore, TurLab is found to be a very useful facility for testing the acquisition logic of the detectors of the present and future missions of the JEM-EUSO program and beyond in order to reproduce atmospheric signals in the laboratory.
Hamiltonicity in power graphs of a class of abelian groups
Authors: Santiago Arguello Anahy , Montellano-Ballesteros Juan José , Stadler Peter F. 
Published: October 2022

AbstractThe undirected power graph $$\mathscr {G}(S)$$

G
(
S
)

of a semigroup S is an undirected graph with vertex set S where two vertices $$u,v\in S$$

u
,
v
∈
S

are adjacent if and only if there is a positive integer m such that $$u^{m}=v$$

u
m

=
v

or $$v^{m}=u$$

v
m

=
u

. Here, we investigate the power graphs of a class of abelian groups and answer, in this case, the question whether or not the power graph is Hamiltonian.
Mechanical and antibacterial behavior of multilayered geopolymer coatings on Ti6Al4V alloys
Authors: Rondinella Alfredo , Furlani Erika , Dell’Antone Lorenzo , Marin Elia , Boschetto Francesco , Sordetti Francesco , Lanzutti Alex , Andreatta Francesco , Fedrizzi Lorenzo , Maschio Stefano 
Published: October 2022

AbstractGeopolymers are commonly used in a wide range of applications including binders into the building industry, production of refractory elements, filtration systems, low CO2 emission applications, etc. Their production can be performed either by acidic or alkaline formulation. In the last 15 years, however, they have been proposed also in biomedical applications for bone tissue regeneration. The aim of this work is the preparation of a thin and homogeneous geopolymer coating on a Ti6Al4V alloy in order to test their futuristic application as coating of prosthetic devices made with this metal alloy. Multilayered coatings were therefore produced by mean of dip coating with the aim of verifying which formulation, acidic or alkaline maximize adhesion. The morphological and chemical characteristics of the coatings were analyzed and adhesion of geopolymers to the substrate was investigated by scratch tests. Finally, a bacterial growth test was performed to verify antibacterial properties of the coatings.
Graphical abstract
Low Noise Frequency-Domain Multiplexing of TES Bolometers Using SQUIDs at Sub-Kelvin Temperature
Authors: Elleflot T. , Suzuki A. , Arnold K. , Bebek C. , Cantor R. H. , Crowley K. T. , Groh J. , de Haan T. , Hornsby A. , Joseph J. , Lee A. T. , Liu T. , Montgomery J. , Russell M. , Yu Q. 
Published: October 2022

AbstractDigital Frequency-Domain Multiplexing (DfMux) is a technique that uses MHz superconducting resonators and Superconducting Quantum Interference Device (SQUID) arrays to read out sets of transition edge sensors. DfMux has been used by several Cosmic Microwave Background experiments, including most recently POLARBEAR-2 and SPT-3 G with multiplexing factors as high as 68, and is the baseline readout technology for the planned satellite mission LiteBIRD. Here, we present recent work focused on improving DfMux readout noise, reducing parasitic impedance, and improving sensor operation. We have achieved a substantial reduction in stray impedance by integrating the sensors, resonators, and SQUID array onto a single-carrier board operated at 250 mK. This also drastically simplifies the packaging of the cryogenic components and leads to better-controlled crosstalk. We demonstrate a low readout noise level of 8.6 $$\mathrm{pA/Hz}1^{1/2}$$

pA
/
Hz

1

1
/
2

, which was made possible by operating the SQUID array at a reduced temperature and with a low dynamic impedance. This is a factor of two improvement compared to the achieved readout noise level in currently operating Cosmic Microwave Background experiments using DfMux and represents a critical step toward maturation of the technology for the next generation of instruments.
Informing the UK Muslim Community on Organ Donation: Evaluating the Effect of a National Public Health Programme by Health Professionals and Faith Leaders
Authors: Ali Omar M. E. , Gkekas Eleftherios , Ali Ahmad M. S. , Tang Tsz Yau Tiffany , Ahmed Sameer , Chowdhury Imadul , Waqar Salman , Hamed Amer , Al-Ghazal Sharif , Ahmed Saeed 
Published: October 2022

AbstractThere is a significant shortage of transplantable organs in the UK particularly from Black, Asian and Minority Ethnic (BAME) groups, of which Muslims make a large proportion. The British Islamic Medical Association (BIMA) held a nationwide series of community gatherings with the aim of describing the beliefs and attitudes to organ donation amongst British Muslims and evaluate the efficacy of a national public health programme on views and uncertainties regarding religious permissibility and willingness to register. Eight public forums were held across the UK between June 2019 and March 2020 by the British Islamic Medical Association (BIMA). A panel of experts consisting of health professionals and Imams discussed with audiences the procedures, experiences and Islamic ethico-legal rulings on organ donation. Attendees completed a self-administered questionnaire which captured demographic data along with opinions before and after the session regarding religious permissibility and willingness to register given permissibility. A total of 554 respondents across seven UK cities were included with a M:F ratio 1:1.1. Only 45 (8%) respondents were registered as organ donors. Amongst those not registered multiple justifications were detailed, foremost of which was religious uncertainty (73%). Pre-intervention results indicated 50% of respondents were unsure of the permissibility of organ donation in Islam. Of those initially unsure or against permissibility or willingness to register, 72% changed their opinion towards deeming it permissible and 60% towards a willingness to register indicating a significant change in opinion (p < 0.001). The effectiveness of our interventions suggests further education incorporating faith leaders alongside local healthcare professionals to address religious and cultural concerns can reduce uncertainty whilst improving organ donation rates among the Muslim community.
Scaling up stochastic gradient descent for non-convex optimisation
Authors: Mohamad Saad , Alamri Hamad , Bouchachia Abdelhamid 
Published: October 2022

AbstractStochastic gradient descent (SGD) is a widely adopted iterative method for optimizing differentiable objective functions. In this paper, we propose and discuss a novel approach to scale up SGD in applications involving non-convex functions and large datasets. We address the bottleneck problem arising when using both shared and distributed memory. Typically, the former is bounded by limited computation resources and bandwidth whereas the latter suffers from communication overheads. We propose a unified distributed and parallel implementation of SGD (named DPSGD) that relies on both asynchronous distribution and lock-free parallelism. By combining two strategies into a unified framework, DPSGD is able to strike a better trade-off between local computation and communication. The convergence properties of DPSGD are studied for non-convex problems such as those arising in statistical modelling and machine learning. Our theoretical analysis shows that DPSGD leads to speed-up with respect to the number of cores and number of workers while guaranteeing an asymptotic convergence rate of$$O(1/\sqrt{T})$$O(1/T)given that the number of cores is bounded by$$T^{1/4}$$T1/4and the number of workers is bounded by$$T^{1/2}$$T1/2whereTis the number of iterations. The potential gains that can be achieved by DPSGD are demonstrated empirically on a stochastic variational inference problem (Latent Dirichlet Allocation) and on a deep reinforcement learning (DRL) problem (advantage actor critic - A2C) resulting in two algorithms: DPSVI and HSA2C. Empirical results validate our theoretical findings. Comparative studies are conducted to show the performance of the proposed DPSGD against the state-of-the-art DRL algorithms.
The regulatory role of long non- coding RNAs as a novel controller of immune response against cancer cells
Authors: Mofed Dina , Omran Jihad I , Sabet Salwa , Baiomy Ahmed A , Emara Marwan , Salem Tamer Z. 
Published: October 2022

AbstractImmunotherapy has been established as a promising therapy for different cancer types. However, many patients experience primary or secondary resistance to treatment. Immune cells and anti-inflammatory factors are regulated by long noncoding RNAs (lncRNAs). In addition, lncRNAs have a role in immune resistance through antigen presentation loss or attenuation, PD-L1 upregulation, loss of T-cell activities, and activation of G-MDSCs and Tregs in the tumor environment. LncRNAs can also influence the interaction between cancer stem cells and immune cells in the tumor microenvironment, potentially resulting in cancer stem cell resistance to immunotherapy. Immunological-related lncRNAs can influence immune responses either directly by affecting neighboring protein-coding genes or indirectly by sponging miRNAs through various mechanisms. We have emphasized the role and levels of expression of lncRNAs that have been linked to immune cell formation, differentiation, and activation, which may have an influence on immunotherapy efficacy.
Learning enhanced features and inferring twice for fine-grained image classification
Authors: Nie Xuan , Chai Bosong , Wang Luyao , Liao Qiyu , Xu Min 
Published: October 2022

AbstractFine-Grained Visual Categorization (FGVC) aims to distinguish between extremely similar subordinate-level categories within the same basic-level category. Existing research has proven the great importance of the discriminative features in FGVC but ignored the contributions for correct classification from other features, and the extracted features always contain more information about the obvious regions but less about subtle regions. In this paper, firstly, a novel module named forcing module is proposed to force the network to extract more diverse features for FGVC, which generates a suppression mask based on the class activation maps to suppress the most distinguishable regions, so as to force the network to extract other secondary distinguishable features as the final features. The forcing module consists of the original branch and the forcing branch. The original branch focuses on the primary discriminative regions while the forcing branch focuses on secondary discriminative regions. Secondly, in order to solve the problem that information of small-scale distinguishable features is lost seriously after multi-layer down-sampling, according to the class activation maps of the first prediction, the object is cropped and scaled as the second input. To reduce the prediction error, the first and second prediction probabilities are fused as the final prediction result. Experimental results indicate that the proposed method not only outperforms the baseline model by a large margin (3.7%, 5.9%, 3.1% respectively) on CUB-200-2011, Stanford-Cars, and FGVC-Aircraft, but also achieves state-of-the-art performance on FGVC-Aircraft.
Semantic-aware deidentification generative adversarial networks for identity anonymization
Authors: Kim Hyeongbok , Pang Zhiqi , Zhao Lingling , Su Xiaohong , Lee Jin Suk 
Published: October 2022

AbstractPrivacy protection in the computer vision field has attracted increasing attention. Generative adversarial network-based methods have been explored for identity anonymization, but they do not take into consideration semantic information of images, which may result in unrealistic or flawed facial results. In this paper, we propose a Semantic-aware De-identification Generative Adversarial Network (SDGAN) model for identity anonymization. To retain the facial expression effectively, we extract the facial semantic image using the edge-aware graph representation network to constraint the position, shape and relationship of generated facial key features. Then the semantic image is injected into the generator together with the randomly selected identity information for de-Identification. To ensure the generation quality and realistic-looking results, we adopt the SPADE architecture to improve the generation ability of conditional GAN. Meanwhile, we design a hybrid identity discriminator composed of an image quality analysis module, a VGG-based perceptual loss function, and a contrastive identity loss to enhance both the generation quality and ID anonymization. A comparison with the state-of-the-art baselines demonstrates that our model achieves significantly improved de-identification (De-ID) performance and provides more reliable and realistic-looking generated faces. Our code and data are available on https://github.com/kimhyeongbok/SDGAN