bluuebunny/crossref_metadata_2025_split huggingface dataset:
Exceptional warming over the Barents area
Authors: Isaksen Ketil , Nordli Øyvind , Ivanov Boris , Køltzow Morten A. Ø. , Aaboe Signe , Gjelten Herdis M. , Mezghani Abdelkader , Eastwood Steinar , Førland Eirik , Benestad Rasmus E. , Hanssen-Bauer Inger , Brækkan Ragnar , Sviashchennikov Pavel , Demin Valery , Revina Anastasiia , Karandasheva Tatiana 
Published: June 2022

AbstractIn recent decades, surface air temperature (SAT) data from Global reanalyses points to maximum warming over the northern Barents area. However, a scarcity of observations hampers the confidence of reanalyses in this Arctic hotspot region. Here, we study the warming over the past 20–40 years based on new available SAT observations and a quality controlled comprehensive SAT dataset from the northern archipelagos in the Barents Sea. We identify a statistically significant record-high annual warming of up to 2.7 °C per decade, with a maximum in autumn of up to 4.0 °C per decade. Our results are compared with the most recent global and Arctic regional reanalysis data sets, as well as remote sensing data records of sea ice concentration (SIC), sea surface temperature (SST) and high-resolution ice charts. The warming pattern is primarily consistent with reductions in sea ice cover and confirms the general spatial and temporal patterns represented by reanalyses. However, our findings suggest even a stronger rate of warming and SIC-SAT relation than was known in this region until now.
Sofosbuvir-based direct-acting antivirals and changes in cholesterol and low density lipoprotein-cholesterol
Authors: Wang Yi-Kai , Wang Ying-Wen , Lu Chia-Ling , Huang Yi-Hsiang , Hou Ming-Chih , Chang Yuh-Lih , Lee Wei-Ping , Lan Keng-Hsin 
Published: June 2022

AbstractWorsened lipid profiles were observed in chronic hepatitis C (CHC) patients during direct-acting antivirals (DAAs) treatment, among which combination drugs confounded the effect of individual ingredient on lipid. Tenofovir alafenamide (TAF) also worsened lipid profiles in HIV patients. Structural similarity between sofosbuvir (SOF) and TAF prompted us to investigate rapid increase in total cholesterol (TC) and low-density lipoprotein cholesterol (LDL-C) in CHC patients treated with SOF-based DAAs. A retrospective study was performed to analyze 487 CHC patients receiving DAAs with SVR12. Relative risks on elevating TC and LDL-C were analyzed by logistic regression to determine SOF-based over non-SOF-based regimens. TC or LDL-C levels at baseline, week-4 and SVR12 were compared by Wilcoxon matched-pairs signed rank test. Week 4 or SVR12 to baseline ratios of serum TC or LDL-C between regimens were compared by Mann–Whitney's test. 487 patients were treated with Harvoni (SOF-based, 206 patients), Epclusa (SOF-based, 124 patients), Maviret (non-SOF-based, 122 patients), or Zepatier (non-SOF-based, 35 patients). At week 4 during drug treatment, Harvoni, Epclusa, and Maviret induced statistically significant elevation of TC and LDL-C, but Zepatier did not. SOF-based regimens had 2.72-fold higher relative risk (RR) causing 10% elevation of TC (95% CI 1.84–4.02, p < 0.001) and 2.04-fold higher RR causing 10% elevation of LDL-C (95% CI 1.39–3.01, p < 0.001) than non-SOF-based DAAs. SOF-based DAAs were associated with significantly larger amplitude of increases in TC and LDL-C than non-SOF-based DAAs during the initial 4 weeks of treatment, but the increases were not sustained to SVR12.
Machine learning for comprehensive prediction of high risk for Alzheimer’s disease based on chromatic pupilloperimetry
Authors: Lustig-Barzelay Yael , Sher Ifat , Sharvit-Ginon Inbal , Feldman Yael , Mrejen Michael , Dallasheh Shada , Livny Abigail , Schnaider Beeri Michal , Weller Aron , Ravona-Springer Ramit , Rotenstreich Ygal 
Published: June 2022

AbstractCurrently there are no reliable biomarkers for early detection of Alzheimer's disease (AD) at the preclinical stage. This study assessed the pupil light reflex (PLR) for focal red and blue light stimuli in central and peripheral retina in 125 cognitively normal middle age subjects (45–71 years old) at high risk for AD due to a family history of the disease (FH+), and 61 age-similar subjects with no family history of AD (FH−) using Chromatic Pupilloperimetry coupled with Machine Learning (ML). All subjects had normal ophthalmic assessment, and normal retinal and optic nerve thickness by optical coherence tomography. No significant differences were observed between groups in cognitive function and volumetric brain MRI. Chromatic pupilloperimetry-based ML models were highly discriminative in differentiating subjects with and without AD family history, using transient PLR for focal red (primarily cone-mediated), and dim blue (primarily rod-mediated) light stimuli. Features associated with transient pupil response latency (PRL) achieved Area Under the Curve Receiver Operating Characteristic (AUC-ROC) of 0.90 ± 0.051 (left-eye) and 0.87 ± 0.048 (right-eye). Parameters associated with the contraction arm of the rod and cone-mediated PLR were more discriminative compared to parameters associated with the relaxation arm and melanopsin-mediated PLR. Significantly shorter PRL for dim blue light was measured in the FH+ group in two test targets in the temporal visual field in right eye that had highest relative weight in the ML algorithm (mean ± standard error, SE 0.449 s ± 0.007 s vs. 0.478 s ± 0.010 s, p = 0.038). Taken together our study suggests that subtle focal changes in pupil contraction latency may be detected in subjects at high risk to develop AD, decades before the onset of AD clinical symptoms. The dendrites of melanopsin containing retinal ganglion cells may be affected very early at the preclinical stages of AD.
Predicting ecological impacts of the invasive brush-clawed shore crab under environmental change
Authors: Theurich Nora , Briski Elizabeta , Cuthbert Ross N. 
Published: June 2022

AbstractGlobally, the number of invasive non-indigenous species is continually rising, representing a major driver of biodiversity declines and a growing socio-economic burden.Hemigrapsus takanoi, the Japanese brush-clawed shore crab, is a highly successful invader in European seas. However, the ecological consequences of this invasion have remained unexamined under environmental changes—such as climatic warming and desalination, which are projected in the Baltic Sea—impeding impact prediction and management. Recently, the comparative functional response (resource use across resource densities) has been pioneered as a reliable approach to quantify and predict the ecological impacts of invasive non-indigenous species under environmental contexts. This study investigated the functional response ofH. takanoifactorially between different crab sexes and under environmental conditions predicted for the Baltic Sea in the contexts of climate warming (16 and 22 °C) and desalination (15 and 10), towards blue musselMytilus edulisprey provided at different densities.Hemigrapsus takanoidisplayed a potentially population-destabilising Type II functional response (i.e. inversely-density dependent) towards mussel prey under all environmental conditions, characterised by high feeding rates at low prey densities that could extirpate prey populations—notwithstanding high in-field abundances ofM. edulis. Males exhibited higher feeding rates than females under all environmental conditions. Higher temperatures reduced the feeding rate of maleH. takanoi, but did not affect the feeding rate of females. Salinity did not have a clear effect on feeding rates for either sex. These results provide insights into interactions between biological invasions and climate change, with future warming potentially lessening the impacts of this rapidly spreading marine invader, depending on the underlying population demographics and abundances.
Small-molecule metabolome identifies potential therapeutic targets against COVID-19
Authors: Bennet Sean , Kaufmann Martin , Takami Kaede , Sjaarda Calvin , Douchant Katya , Moslinger Emily , Wong Henry , Reed David E. , Ellis Anne K. , Vanner Stephen , Colautti Robert I. , Sheth Prameet M. 
Published: June 2022

AbstractRespiratory viruses are transmitted and acquired via the nasal mucosa, and thereby may influence the nasal metabolome composed of biochemical products produced by both host cells and microbes. Studies of the nasal metabolome demonstrate virus-specific changes that sometimes correlate with viral load and disease severity. Here, we evaluate the nasopharyngeal metabolome of COVID-19 infected individuals and report several small molecules that may be used as potential therapeutic targets. Specimens were tested by qRT-PCR with target primers for three viruses: Influenza A (INFA), respiratory syncytial virus (RSV), and SARS-CoV-2, along with unaffected controls. The nasopharyngeal metabolome was characterized using an LC–MS/MS-based screening kit capable of quantifying 141 analytes. A machine learning model identified 28 discriminating analytes and correctly categorized patients with a viral infection with an accuracy of 96% (R2 = 0.771, Q2 = 0.72). A second model identified 5 analytes to differentiate COVID19-infected patients from those with INFA or RSV with an accuracy of 85% (R2 = 0.442, Q2 = 0.301). Specifically, Lysophosphatidylcholines-a-C18:2 (LysoPCaC18:2) concentration was significantly increased in COVID19 patients (P < 0.0001), whereas beta-hydroxybutyric acid, Methionine sulfoxide, succinic acid, and carnosine concentrations were significantly decreased (P < 0.0001). This study demonstrates that COVID19 infection results in a unique nasopharyngeal metabolomic signature with carnosine and LysoPCaC18:2 as potential therapeutic targets.
Ceramides are early responders in metabolic syndrome development in rhesus monkeys
Authors: Smith Alex B. , Schill Jonah P. , Gordillo Ruth , Gustafson Grace E. , Rhoads Timothy W. , Burhans Maggie S. , Broman Aimee T. , Colman Ricki J. , Scherer Philipp E. , Anderson Rozalyn M. 
Published: June 2022

AbstractMetabolic syndrome increases risk of complicating co-morbidities. Current clinical indicators reflect established metabolic impairment, preventing earlier intervention strategies. Here we show that circulating sphingolipids are altered in the very early stages of insulin resistance development. The study involved 16 paired overweight but healthy monkeys, one-half of which spontaneously developed metabolic syndrome over the course of 2 years. Importantly, animals did not differ in adiposity and were euglycemic throughout the study period. Using mass spectrometry, circulating sphingolipids, including ceramides and sphingomyelins, were detected and quantified for healthy and impaired animals at both time points. At time of diagnosis, several ceramides were significantly different between healthy and impaired animals. Correlation analysis revealed differences in the interactions among ceramides in impaired animals at diagnosis and pre-diagnosis when animals were clinically indistinguishable from controls. Furthermore, correlations between ceramides and early-stage markers of insulin resistance, diacylglycerols and non-esterified fatty acids, were distinct for healthy and impaired states. Regression analysis identifies coordinated changes in lipid handling across lipid classes as animals progress from healthy to insulin resistant. Correlations between ceramides and the adipose-derived adipokine adiponectin were apparent in healthy animals but not in the metabolically impaired animals, even in advance of loss in insulin sensitivity. These data suggest that circulating ceramides are clinically relevant in identifying disease risk independent of differences in adiposity, and may be important in devising preventative strategies.
A pilot meta-analysis on self-reported efficacy of neurofeedback for adolescents and adults with ADHD
Authors: Fan Hsin-Yi , Sun Cheuk-Kwan , Cheng Yu-Shian , Chung Weilun , Tzang Ruu‐Fen , Chiu Hsien‐Jane , Ho Chun-Ning , Hung Kuo-Chuan 
Published: June 2022

AbstractSelf-reported effectiveness of electroencephalogram-based neurofeedback (EEG-NF) against the core symptoms of attention-deficit hyperactivity disorder (ADHD) in adolescents/adults remains unclear. We searched PubMed, Embase, ClinicalKey, Cochrane CENTRAL, ScienceDirect, Web of Science, and ClinicalTrials.gov from inception to August 2021 for randomized clinical trials (RCTs) of EEG-NF with self-reported ADHD symptom ratings. Comparators included participants on waitlist/treatment as usual (TAU) or receiving other interventions. Of the 279 participants (mean age = 23.48; range: 6–60) in five eligible RCTs, 183 received EEG-NF treatment. Forest plot demonstrated no difference in inattention (SMD = −0.11, 95% CI −0.39–0.18, p = 0.46), total score (SMD = −0.08, 95% CI −0.36–0.2, p = 0.56), and hyperactivity/impulsivity (SMD = 0.01, 95% CI −0.23–0.25, p = 0.91) between EEG-NF and comparison groups. Nevertheless, compared with waitlist/TAU, EEG-NF showed better improvement in inattention (SMD = −0.48, 95% CI −0.9–−0.06, p = 0.03) but not hyperactivity/impulsivity (SMD = −0.03, 95% CI −0.45–0.38, p = 0.87). Follow-up 6–12 months demonstrated no difference in inattention (SMD = −0.01, 95% CI −0.41–0.38, p = 0.94), total score (SMD = 0.22, 95% CI −0.08–0.52, p = 0.15), and hyperactivity/impulsivity (SMD = −0.01, 95% CI −0.27–0.26, p = 0.96) between the two groups. Dropout rate also showed no difference (RR = 1.05, 95% CI 0.82–1.33, p = 0.72). Our results support EEG-NF for improving inattention in adolescents/young adults, although its effectiveness against hyperactivity/impulsivity remains inconclusive.
An integrative pan-cancer analysis of molecular characteristics and oncogenic role of mitochondrial creatine kinase 1A (CKMT1A) in human tumors
Authors: Yang Mengjie , Liu Shuna , Xiong Yue , Zhao Jingxin , Deng Wenbin 
Published: June 2022

AbstractIn recent years, several studies have suggested that mitochondrial creatine kinase 1A (CKMT1A) plays a key role in various cancer types. However, there is still a lack of systematic understanding of the contribution of CKMT1A in different types of cancer. Therefore, this study aims to explore the potential role of CKMT1A in human tumors. Firstly, we evaluated the expression level of CKMT1A in 33 types of tumors. Secondly, we used the GEPIA2 and Kaplan–Meier plotter to explore the relationship between CKMT1A expression and survival prognosis. Furthermore, the genetic alterations of CKMT1A were analyzed by the cBioPortal web. In addition, we performed immune infiltration analysis and gene enrichment pathway analysis. CKMT1A was highly expressed in most types of cancers and there was a significant correlation between CKMT1A expression and the prognosis of patients for certain tumors. Non-Small Cell Lung Cancer cases with altered CKMT1A showed a poorer overall survival. CKMT1A expression was negatively correlated with the infiltration of cancer-associated fibroblasts in most tumors. We also found that its expression was negatively associated with CD8+ T-cell infiltration in several tumors. Furthermore, enrichment analysis revealed that “Glycolysis/ Gluconeogenesis” and “metabolic pathways” functions were involved in the functional mechanism of CKMT1A. Taken together, our studies will provide a relatively clear and integrative understanding of the role of CKMT1A across different tumors. All these findings will lay a solid foundation for further molecular assays of CKMT1A in tumorigenesis and provide the rationale for developing novel therapeutic strategies.
HollowBox: An anchor‐free UAV detection method
Authors: Liu Shanliang , Qu Jingyi , Wu Renbiao 
Published: June 2022

AbstractUnmanned aerial vehicles (UAV) “black flight” incidents cause serious security risks and economic losses to airports. Additionally, existing UAV detection methods are mainly radar technology at airports. Whereas, it is unable to correctly identify the number of UAVs and visualise their size, which undoubtedly poses a serious security risk. Accordingly, an anchor‐free UAV detection method HollowBox is proposed to supplement radar detection equipment for the airport “black flight” problem. It is inspired by the FoveaBox object detection method, the object detection feature layers are reset and the allocation ratio of positive and negative samples in the training phase are redefined, the HollowBox UAV detection is proposed according to the multi‐size characteristics. Extensive experiments show that, the approach achieves 90.1% AP, 6% false detection rate and 17.2 FPS inference speed, which accomplished a satisfactory performance, as verified by the real‐shot data collected of an airport in Tianjin. This work is of great significance for the application in airport UAV detection.
RAG‐Net: ResNet‐50 attention gate network for accurate iris segmentation
Authors: Wei Yinyin , Zeng Aijun , Zhang Xiangyang , Huang Huijie 
Published: June 2022

AbstractIris segmentation is an important step in the process of iris recognition. Iris images collected under non‐cooperative conditions always contain various noise, which is a challenge for iris segmentation. Most U‐Net‐based methods have made great achievements in iris segmentation. However, this architecture lacks of focusing on target structures of varying shapes, and robustness in segmenting objects with significant shape variations. In this paper, we propose RAG‐Net: an efficient iris segmentation method based on deep learning. In contrast to many previous convolutional neural network (CNN)‐based iris segmentation methods, we adopted the attention gate (AG) mechanism and ResNet‐50 in the U‐Net architecture to improve iris segmentation accuracy, the AG module was included in the skip connection part of the RAG‐Net architecture to further identify salient feature regions and prune feature responses, which preserve only the activations relevant to the required information, and the ResNet‐50 module was used to improve the robustness of the segmentation performance. Using this model, efficient iris segmentation in a non‐cooperative environment can be realized. The proposed method was trained and evaluated using the CASIA.v4‐distance, CASIA.v4‐thousand, UBIRIS.v2, and MICHE‐I databases. From the view of the segmentation results, the proposed RAG‐Net is one of effective architecture in iris segmentation methods.
FishNet: Fish visual recognition with one stage multi‐task learning
Authors: Chen Ziwen , Cao Lijie , Wang Qihua , Cai Yu 
Published: June 2022

AbstractThe use of computer vision for fish monitoring in aquaculture fisheries has gained importance. It is crucial to obtain the object box, instance mask and landmarks of the fish to determine their status. There are well‐established methods to achieve these tasks, but running them in a serial sequence is inefficient and complex. A multi‐tasking framework is proposed that can implement the above three tasks in parallel, FishNet. Unlike other multi‐tasking frameworks that use one encoder with multiple decoders, the authors use only one encoder and one decoder to achieve multi‐tasking fusion and can be trained end‐to‐end. A multi‐task dataset for fish is produced to validate the framework. It achieved the best speed‐accuracy balance on object detection (a 95.3% box AP), instance segmentation (a 53.9% mask AP) and pose recognition (95.1% OKS AP), and reached real‐time inference speed (66.3 FPS) on the NVIDIA Tesla V100.
Multi‐model fusion approach for electromagnetic inverse scattering problems
Authors: Zhu Dong , Zhao Qiang , Yang Lixia , Bo Yong , Chen Wei 
Published: June 2022

AbstractIn this paper, a novel deep learning (DL) approach is developed to solve the electromagnetic inverse scattering (EMIS) problems. Many challenges, such as ill‐posedness, high computational cost, and strong non‐linearity, are encountered when solving the EMIS problems. To surmount these difficulties, a multi‐model fusion convolutional neural network architecture is proposed, termed here as Amplitude‐Phase scheme. To the best of our knowledge, it is the first time that the multi‐model fusion DL approach is employed to solve the EMIS problems. Amplitude data and phase data of the measured scattering data are applied to train the proposed scheme. Furthermore, we compare APs with three different training schemes, including Amplitude‐Only scheme, and Phase‐Only scheme, and Complex‐Value scheme. The performance of the proposed DL schemes has been validated by numerical simulations. The results demonstrate that the proposed multi‐model fusion approach outperforms other DL schemes in terms of accuracy and is able to achieve a better performance in reconstructing homogeneous and heterogeneous scatterers.
Extremely low speed performance research of the speed sensorless vector controlled induction motor drive system
Authors: Guo Yongbao , Wang Haixia , Su Tao 
Published: June 2022

AbstractThis paper proposes a new full‐order adaptive observer algorithm to overcome the instability of speed sensorless vector control system of induction motor at low speed, especially at extremely low speed. The algorithm consists of the improved feedback matrix algorithm and the improved speed adaptive law algorithm. By establishing an observer state error equation considering the non‐linear voltage error of the inverter and the stator resistance voltage drop, a feedback matrix was designed to reduce the effect of inverter's non‐linear voltage error and stator resistance voltage drop on speed estimation. Meanwhile, this paper improves the traditional adaptive law. The basic idea is to add compensation amount equivalent to the non‐linear voltage error, and the compensation amount is adaptive to the running speed and load to improve the motor speed estimation accuracy at low speed. Extensive experimental tests have been carried out to evaluate the performance of the proposed algorithm using a 2.2 kW induction motor experimental platform. The experimental results show that the algorithm presented in this paper can guarantee the stable operation of the motor under the rated‐load and 180% rated‐load at low, extremely low and 0 speed with good dynamic and static characteristics.