bluuebunny/crossref_metadata_2025_split huggingface dataset:
Toxicity of malathion during Senegalese sole,Solea senegalensislarval development and metamorphosis: Histopathological disorders and effects on type B esterases andCYP1Aenzymatic systems
Authors: Ortiz‐Delgado Juan Bosco , Funes Victoria , Albendín Gemma , Scala Emanuele , Sarasquete Carmen 
Published: June 2021

AbstractThe toxicity of malathion toSolea senegalensiswas studied in a static renewal bioassay during its first month of larval life (between 4 and 30 dph). Through the use of different biomarkers and biochemical, cellular and molecular approaches (inhibition of cholinesterases [ChEs], changes in cytochrome P450‐1A [CYP1A] and the study of histopathological alterations), the effects of three concentrations of malathion (1.56, 3.12, and 6.25 μg/L) have been analyzed. In subacute exposure, malathion inhibited cholinesterase activities (AChE, BChE, CbE) in a dose‐ and time‐dependent manner, ranging the inhibition percentage from 20% to 90%. However, the expression levels of CYP1A and AChE transcripts or proteins were not modified. Additionally, exposure to malathion provoked histopathological alterations in several organ systems of Senegalese sole in a time‐ and dose dependent way, namely disruption of parenchymal architecture in the liver, epithelial desquamation, pyknotic nuclei and steatosis in the intestine, disorganization of supporting cartilage, and sings of hyperplasia and hypertrophy in the gills and degeneration of the epithelial cells from the renal tubules. Malathion exposure also provoked strong disorganization of cardiac fibers from the heart. The findings provide evidence that exposure to sublethal concentrations of malathion that provoked serious injury to the fishS.senegalensis, were below the expected environmental concentrations reported in many other ecosystems and different fish species,revealing a higher sensitivity for Solea senegalensis to malathion exposure, thus reinforcing its use as sentinel species for environmental pollution in coastal and estuarine environments.
Effects of lead exposure on the activation of microglia in mice fed with high‐fat diets
Authors: Wu Lei , Li Shuang , Pang Shulan , Zhang Bo , Wang Jierui , He Bin , Lv Linyi , Wang Weixuan , Zhao Na , Zhang Yanshu 
Published: June 2021

AbstractLead (Pb) exposure can cause central nervous system (CNS) damage. The process of Pb neurotoxicity is accompanied by the microglia activation. In addition, microglia activation was observed under the intervention of high‐fat diets (HFD). This study was designed to investigate the effect of Pb on the cognitive function of mice with HFD, with focus on the microglia activation in brain. Male C57BL/6J mice, 8 weeks of age, were randomly divided into control, HFD, Pb, and HFD + Pb groups. The results showed that HFD following Pb exposure could exacerbate the learning and memory impairment in mice. Pb exposure could promote microglia activation and increase the expression of M1 microglia marker and decrease the expression of M2 microglia marker in the hippocampus of mice with HFD. Our finding suggested that Pb exposure may aggravate CNS damage by promoting M1 polarization and inhibiting M2 polarization of hippocampal microglia in HFD mice.
Volatility and dynamic dependence modeling: Review, applications, and financial risk management
Authors: So Mike K. P. , Chu Amanda M. Y. , Lo Cliff C. Y. , Ip Chun Yin 
Published: June 2021

AbstractSince the introduction of ARCH models close to 40 years ago, a wide range of models for volatility estimation and prediction have been developed and integrated into asset allocation, financial derivative pricing, and financial risk management. Research has also been very active in extending volatility modeling to dependence modeling and in developing our understanding of risk and uncertainty in financial systems. This paper presents a review on the statistical modeling on volatility and dynamic dependence of financial returns. In addition, we present a real data example using a time‐varying copula model to estimate the dynamic dependence of stock returns. Research on volatility and dynamic dependence modeling will continue to encounter statistical and computational challenges; it is necessary to persist in dealing with the 3H (high dimension, high frequency, high complexity) paradigm in modeling.This article is categorized under:Statistical Learning and Exploratory Methods of the Data Sciences > Modeling MethodsStatistical Models > Nonlinear ModelsData: Types and Structure > Time Series, Stochastic Processes, and Functional Data
Speech Recognition: B
Authors: Walrand Jean 
Published: June 2021

AbstractOnline learning algorithms update their estimates as additional observations are made. Section 12.1 explains a simple example: online linear regression. The stochastic gradient projection algorithm is a general technique to update estimates based on additional observations; it is widely used in machine learning. Section 12.2 presents the theory behind that algorithm. When analyzing large amounts of data, one faces the problems of identifying the most relevant data and of how to use efficiently the available data. Section 12.3 explains three examples of how these questions are addressed: the LASSO algorithm, compressed sensing, and the matrix completion problem. Section 12.4 discusses deep neural networks for which the stochastic gradient projection algorithm is easy to implement.
Route Planning: A
Authors: Walrand Jean 
Published: June 2021

AbstractThis chapter is concerned with making successive decisions in the presence of uncertainty. The decisions affect the cost at each step but also the “state” of the system. We start with a simple example: choosing a route with uncertain travel times. We then examine a more general model: controlling a Markov chain.Section 13.1 presents a model of route section when the travel times are random. Section 13.2 shows one formulation where one plans the trip long in advance. Section 13.3 explains how the problem changes if one is able to adjust the route based on real-time information. That section introduces the main ideas of stochastic dynamic programming. Section 13.4 discusses a generalization of the route planning problem: a Markov decision problem. Section 13.5 solves the problem when the horizon is infinite.
Digital Link—B
Authors: Walrand Jean 
Published: June 2021

AbstractChapter 7 explained the detection and hypothesis testing problems, Huffman codes and the situation where errors are independent and Gaussian. In this chapter, we prove the optimality of the Huffman code in Sect. 8.1 and the Neyman–Pearson Theorem in Sect. 8.2. Section 8.3 discusses the theory of jointly Gaussian random variables that is used to analyze the modulation schemes of Sect. 7.5 . Section 8.4 uses the results on jointly Gaussian random variables to explain hypothesis tests that arise when analyzing data. That section discusses the chi-squared test and the F-test. Section 8.5 is devoted to the LDPC codes that are widely used in high-speed communication links. These codes augment a group of bits to be transmitted over a noisy channel with additional bits computed from those in the group. When it receives the bits, when the augmented bits are not consistent, the receiver attempts to determine the bits that are most likely to have been corrupted by noise.
Tracking—A
Authors: Walrand Jean 
Published: June 2021

AbstractThis chapter explains how to estimate an unobserved random variable or vector from available observations. This problem arises in many examples, as illustrated in Sect. 9.1. The basic problem is defined in Sect. 9.2. One commonly used approach is the linear least squares estimate explained in Sect. 9.3. A related notion is the linear regression covered in Sect. 9.4. Section 9.5 comments on the problem of overfitting. Sections 9.6 and 9.7 explain the minimum means squares estimate that may be a nonlinear function of the observations and the remarkable fact that it is linear for jointly Gaussian random variables. Section 9.8 is devoted to the Kalman filter, which is a recursive algorithm for calculating the linear least squares estimate of the state of a system given previous observations.
Searching for elusive dark sectors with terrestrial and celestial observations
Authors: Contino Roberto , Max Kevin , Mishra Rashmish K. 
Published: June 2021

Abstract
We consider the possible existence of a SM-neutral and light dark sector coupled to the visible sector through irrelevant portal interactions. Scenarios of this kind are motivated by dark matter and arise in various extensions of the Standard Model. We characterize the dark dynamics in terms of one ultraviolet scale Λuv, at which the exchange of heavy mediator fields generates the portal operators, and by one infrared scale ΛIR, setting the mass gap. At energies ΛIR « E « Λuv the dark sector behaves like a conformal field theory and its phenomenology can be studied model independently. We derive the constraints set on this scenario by high- and low-energy laboratory experiments and by astrophysical observations. Our results are conservative and serve as a minimum requirement that must be fulfilled by the broad class of models satisfying our assumptions, of which we give several examples. The experimental constraints are derived in a manner consistent with the validity of the effective field theory used to define the portal interactions. We find that high-energy colliders give the strongest bounds and exclude UV scales up to a few TeV, but only in specific ranges of the IR scale. The picture emerging from current searches can be taken as a starting point to design a future experimental strategy with broader sensitivity.
Double layered solutions to the extended Fisher–Kolmogorov P.D.E.
Authors: Smyrnelis Panayotis 
Published: June 2021

AbstractWe construct double layered solutions to the extended Fisher–Kolmogorov P.D.E., under the assumption that the set of minimal heteroclinics of the corresponding O.D.E. satisfies a separation condition. The aim of our work is to provide for the extended Fisher–Kolmogorov equation, the first examples of two-dimensional minimal solutions, since these solutions play a crucial role in phase transition models, and are closely related to the De Giorgi conjecture.
Root formation and metallurgical challenges in laser beam and laser-arc hybrid welding of thick structural steel
Authors: Bunaziv Ivan , Dørum Cato , Nielsen Steen Erik , Suikkanen Pasi , Ren Xiaobo , Nyhus Bård , Eriksson Magnus , Akselsen Odd M. 
Published: June 2021

AbstractSingle-pass laser beam welding (LBW) of steel components with wall thickness of > 10 mm is of high interest due to enhanced productivity. Deep penetration LBW provides excessive hardness and certain quality issues such as root humping in flat position, which is associated with disability of surface tension to sustain melt dropout. High hardness is associated with fast cooling rates and shortage of filler wire transportation to the root of the fusion zone. Use of laser-arc hybrid welding (LAHW) can promote acicular ferrite by adding filler metal and additional heat input from the arc. However, LAHW may promote humping and adjustment of many parameters is required hindering its application. In this work, a 16 kW disk laser was used in butt welding of 12 mm and 15 mm thick plates with different bevelling geometries. Root humping occurred within a wide range of process parameters providing narrow process window. Twelve millimeter thick plates were successfully welded with a single-pass technique providing good quality of root by using zero air gap regardless bevelling geometry. Welding of 15 mm plates was more challenging, and the process was sensitive even with a slight parameter change. Improved results were achieved with application of small air gap. Acceptable hardness in both weld metal and heat affected zone (< 290 HV) was achieved for both plate thicknesses providing good toughness of minimum 27 J at −50°C.
Some conditional reliability properties of k-out-of-n system composed of different types of components with discrete independent lifetimes
Authors: Jasiński Krzysztof 
Published: June 2021

AbstractIn this paper, we study reliability properties of k-out-of-n system consisting of l$$(1\le l\le n)$$

(
1
≤
l
≤
n
)

different types of components with discrete, independent lifetimes. We obtain some conditional survival functions of lifetime of a used system. Next, we use them to calculate two conditional failure probabilities of k-out-of-n systems and show that they are equal to unconditional failure probability of a k-out-of-$$(n-r)$$

(
n
-
r
)

system, $$r<n-k+1$$

r
<
n
-
k
+
1

. These results are extended versions of the respective ones existing in the literature.
Dominant and global dimension of blocks of quantised Schur algebras
Authors: Fang Ming , Hu Wei , Koenig Steffen 
Published: June 2021

AbstractGroup algebras of symmetric groups and their Hecke algebras are in Schur-Weyl duality with classical and quantised Schur algebras, respectively. Two homological dimensions, the dominant dimension and the global dimension, of the indecomposable summands (blocks) of these Schur algebras S(n, r) and $$S_q(n,r)$$

S
q

(
n
,
r
)

with $$n \geqslant r$$

n
⩾
r

are determined explicitly, using a result on derived invariance in Fang, Hu and Koenig (J Reine Angew Math 770:59–85, 2021).
Feasibility study on the use of elemental profiles to authenticate aromatic rice: the case of Basmati and Thai rice
Authors: Dumitrascu Catalina , Fiamegos Yiannis , de la Calle Guntiñas Maria Beatriz 
Published: June 2021

AbstractAmong the thousands of existing rice varieties, aromatic rice has increasingly attracted consumer’s preference in recent years. Within aromatic rice, Basmati, cultivated in some regions in Pakistan and India, is highly demanded. Other aromatic rice, cultivated in specific regions, for instance in Thailand (commonly referred to as Jasmine Thai rice), are also highly appreciated by consumers. In this work, the elemental profiles of commercially available rice samples (17 Basmati, 11 Thai, and 7 Long Grain rice) were determined by energy-dispersive X-ray fluorescence (ED-XRF) spectroscopy. The mass fractions of P, Cl, S, K, Fe, Cu, and Zn were significantly different (95% confidence interval) between Basmati and Thai rice and between Thai and Long Grain rice; only Cl, S, and Zn were significantly different between Basmati and Long Grain rice. Multivariate evaluation of the results combining soft independent modelling by class analogy (SIMCA) and partial least square discriminant analysis (PLS-DA) allowed the correct classification (true positives) of 94.1, 85.6, and 100% of the Basmati, Long Grain, and Thai rice, respectively. The specificity (true negatives) of Basmati, Long Grain, and Thai was 94.4, 82.1, and 100%, respectively.
The ability of post-chemoradiotherapy DWI ADCmean and 18F-FDG SUVmax to predict treatment outcomes in head and neck cancer: impact of human papilloma virus oropharyngeal cancer status
Authors: Connor S. , Sit C. , Anjari M. , Lei M. , Guerrero-Urbano T. , Szyszko T. , Cook G. , Bassett P. , Goh V. 
Published: June 2021

Abstract
Objectives
To evaluate the ability of post-chemo-radiotherapy (CRT) diffusion-weighted-MRI apparent diffusion coefficient (ADCmean) and 18F-FDG PET maximum standardized uptake value (SUVmax) to predict disease-free survival (DFS) in head and neck squamous cell carcinoma (HNSCC), and to determine whether this ability is influenced by human papillomavirus oropharyngeal cancer (HPV-OPC) status.

Methods
This prospective cohort observational study included 65 participants (53 male, mean ± SD age 59.9 ± 7.9 years, 46 HPV-OPC) with stage III or IV HNSCC. Primary tumour and nodal ADCmean (pre-treatment, 6- and 12-weeks post-CRT) and SUVmax (12-weeks post-CRT) were measured. Variables were compared with 2-year DFS (independent t-test/Mann–Whitney test) and overall DFS (Cox regression), before and after accounting for HPV-OPC status. Variables were also compared between HPV-OPC and other HNSCC subgroups after stratifying for DFS.

Results
Absolute post-CRT ADCmean values predicted 2-year DFS and overall DFS for all participants (p = 0.03/0.03, 6-week node; p = 0.02/0.03 12-week primary tumour) but not in the HPV-OPC subgroup. In participants with DFS, percentage interval changes in primary tumour ADCmean at 6- and 12-weeks were higher in HPV-OPC than other HNSCC (p = 0.01, 6 weeks; p = 0.005, 12 weeks). The 12-week post-CRT SUVmax did not predict DFS.

Conclusion
Absolute post-CRT ADCmean values predicted DFS in HNSCC but not in the HPV-OPC subgroup. Amongst participants with DFS, post-CRT percentage interval changes in primary tumour ADCmean were significantly higher in HPV-OPC than in other HNSCC. Knowledge of HPV-OPC status is crucial to the clinical utilisation of post-CRT DWI-MRI for the prediction of outcomes.
Upregulation of the ErbB family by EZH2 in hepatocellular carcinoma confers resistance to FGFR inhibitor
Authors: Prawira Aldo , Le Thi Bich Uyen , Ho Rebecca Zhi Wen , Huynh Hung 
Published: June 2021

Abstract
Purpose
Hepatocellular carcinoma (HCC), the most common manifestation of liver cancer, is one of the leading causes of cancer-related mortality worldwide with limited treatment options. Infigratinib, a pan-FGFR inhibitor, has shown a potent antitumour effect in HCC. However, drug resistance is often observed in long-term treatment. In this study, we examined the potential feedback mechanism(s) leading to infigratinib and explored a combination therapy to overcome resistance in HCC.

Methods
Patient-derived xenograft (PDX) tumours were subcutaneously implanted into SCID mice and were subsequently treated with infigratinib. Tumour growth was monitored over time, and tumour samples were subjected to immunohistochemistry and Western blotting. For drug combination studies, mice were treated with infigratinib and/or varlitinib. Gene overexpression and knockdown studies were conducted to investigate the relationship between EZH2 and ErbB activity in infigratinib resistance.

Results
Infigratinib-resistant tumours exhibited higher levels of p-ErbB2 and p-ErbB3, concomitant with an increase in EZH2 expression. Gene overexpression and knockdown studies revealed that EZH2 directly regulates the levels of p-ErbB2 and p-ErbB3 in acquired resistance to infigratinib. The addition of varlitinib effectively overcame infigratinib resistance and prolonged the antitumour response, with minimal toxicity.

Conclusion
The upregulation of the ErbB family by EZH2 appears to contribute to infigratinib resistance. The combination of infigratinib and varlitinib showed a potent antitumour effect and did not result in additional toxicity, warranting further clinical investigation.
Spectroscopy as a useful tool for the identification of changes with time in post-mortem vitreous humor for forensic toxicology purposes
Authors: Wójtowicz Anna , Mitura Agata , Wietecha-Posłuszny Renata , Kurczab Rafał , Zawadzki Marcin 
Published: June 2021

AbstractVitreous humor (VH) is an alternative biological matrix with a great advantage of longer availability for analysis due to the lack of many enzymes. The use of VH in forensic toxicology may have an added benefit, however, this application requires rapid, simple, non-destructive, and relatively portable analytical analysis methods. These requirements may be met by Fourier transform infrared spectroscopy technique (FT-IR) equipped with attenuated total reflection accessory (ATR). FT-IR spectra of vitreous humor samples, deposited on glass slides, were collected and subsequent chemometric data analysis by means of Hierarchical Cluster Analysis and Principal Component Analysis was conducted. Differences between animal and human VH samples and human VH samples stored for diverse periods of time were detected. A kinetic study of changes in the VH composition up to 2 weeks showed the distinction of FT-IR spectra collected on the 1st and 14th day of storage. In addition, data obtained for the most recent human vitreous humor samples—collected 3 and 2 years before the study, presented successful discrimination of all time points studied. The method introduced was unable to detect mephedrone addition to VH in the concentration of 10 µg/cm3.Graphic abstract
Internal field study of 21700 battery based on long-life embedded wireless temperature sensor
Authors: Yang Le , Li Na , Hu Likun , Wang Shaoqi , Wang Lin , Zhou Jiang , Song Wei-Li , Sun Lei , Pan Tai-Song , Chen Hao-Sen , Fang Daining 
Published: June 2021

AbstractThe safety of lithium-ion batteries is an essential concern where instant and accurate temperature sensing is critical. It is generally desired to put sensors inside batteries for instant sensing. However, the transmission of internal measurement outside batteries without interfering their normal state is a non-trivial task due to the harsh electrochemical environment, the particular packaging structures and the intrinsic electromagnetic shielding problems of batteries. In this work, a novel in-situ temperature sensing framework is proposed by incorporating temperature sensors with a novel signal transmission solution. The signal transmission solution uses a self-designed integrated-circuit which modulates the internal measurements outside battery via its positive pole without package breaking. Extensive experimental results validate the noninterference properties of the proposed framework. Our proposed in-situ temperature measurement by the self-designed signal modulation solution has a promising potential for in-situ battery health monitoring and thus promoting the development of smart batteries.
Graphic abstract
Dynamic maintenance model for high average-utility pattern mining with deletion operation
Authors: Wu Jimmy Ming-Tai , Teng Qian , Tayeb Shahab , Lin Jerry Chun-Wei 
Published: June 2021

AbstractThe high average-utility itemset mining (HAUIM) was established to provide a fair measure instead of genetic high-utility itemset mining (HUIM) for revealing the satisfied and interesting patterns. In practical applications, the database is dynamically changed when insertion/deletion operations are performed on databases. Several works were designed to handle the insertion process but fewer studies focused on processing the deletion process for knowledge maintenance. In this paper, we then develop a PRE-HAUI-DEL algorithm that utilizes the pre-large concept on HAUIM for handling transaction deletion in the dynamic databases. The pre-large concept is served as the buffer on HAUIM that reduces the number of database scans while the database is updated particularly in transaction deletion. Two upper-bound values are also established here to reduce the unpromising candidates early which can speed up the computational cost. From the experimental results, the designed PRE-HAUI-DEL algorithm is well performed compared to the Apriori-like model in terms of runtime, memory, and scalability in dynamic databases.