bluuebunny/crossref_metadata_2025_split huggingface dataset:
Wage returns to English language and technical skills in India: An inter-occupational disparity
Authors: P Azad , Refeque Muhammed 
Published: December 2022

Abstract
This study examines the wage returns to education, English language skills and the computer skills across various occupations in India, and analyses how the returns vary across gender, rural urban sector, age group, caste, and wage structure within each occupation. Respondents are classified into four important occupational groups such as professionals and executives, farmers and related workers, production related workers, and service-related workers. Using selectivity correction methods, the study finds that the returns to linguistic ability, computer skills and education are high for the professionals and executives and service-related workers. The study also found significant inter-occupational variation in returns to linguistic and computer skills by gender, rural/urban area, caste and across wage structure. The findings of the study also proves that the linguistic and technical skills complement the education and experience across different job categories in India. Higher returns to English skills accrue more to the educated workers across the occupations and such impacts are more in the case of professional and service sectors. The study emphasises on the importance of extending education and imparting skills to people in order to reduce the labour market discriminations as the education and skills have a profound impact on enhancing the wage earnings irrespective of the socio-demographic backgrounds of the people. The study also shows that, pursuing education and acquiring skills are real investments as they ensure better returns regardless of the job categories.
JEL Classification I 24 · I 26 · J 01 · J 24 · J 31 · J 46
Aβ43 levels determine the onset of pathological amyloid deposition
Authors: Tambini Marc D. , Yin Tao , Yesiltepe Metin , Breuillaud Lionel , Zehntner Simone P. , D'Adamio Luciano 
Published: December 2022

Abstract
Background
While most Alzheimer’s disease cases are sporadic with late onset (LOAD), ~ 2% of cases are inherited, have an early onset, and are caused by mutations in Presenilins (PSEN1/2) or Amyloid-β Precursor Protein (APP) genes (familial AD, FAD). PSEN1/2 are the catalytic component of γ-secretase, a protease that generates Aβ peptides of different length from APP. Aβ peptides are the major components of amyloid plaques, a pathological lesion that characterizes AD. Analysis of mechanisms by which PSEN1/2 and APP mutations affect Aβ peptide compositions lead to the implication of the absolute or relative increase in Aβ42 levels in amyloid-β plaques formation and AD pathogenesis. The age at onset of FAD depends on the mutation and can differ by decades, suggesting a link between age at onset of dementia and the effects of distinct FAD mutations on Aβ species profiles. It is reasonable to presume that Aβ peptide compositions that initiate amyloid pathology and disease in FAD patients can also inform about disease mechanisms driving the more common LOAD cases.
Methods
Here, to elucidate the formation of pathogenic Aβ cocktails leading to amyloid pathology, we utilized rat knock-in models of FAD carrying the Swedish APP (Apps allele) and the PSEN1 L435F (Psen1LF allele) mutations. To accommodate the possibility of differences in pathogenicity of rodent and human Aβ, these rat models are genetically engineered to express human Aβ species as both the Swedish mutant allele and the wild-type rat allele (called Apph) have been humanized in the Aβ-coding region.
Results
Analysis of the 8 possible FAD mutant permutations demonstrates correlations between mutation-driven alterations in Aβ profiles and amyloid pathology, and indicates that the CNS levels of Aβ43, rather than absolute or relative increases in Aβ42, determine the onset of pathological amyloid deposition.
Conclusions
This study corroborates the critical pathological importance of alterations in the Aβ peptides composition, helps clarifying the molecular determinants initiating amyloid pathology, and supports therapeutic interventions targeting Aβ43 to prevent, delay, or revert AD.
Models of Dental Care for People Experiencing Homelessness in the United Kingdom - A Systematic Review of the Literature.
Authors: Bradley Natalie , Heidari Ellie , Andreasson Sam , Newton Jonathon 
Published: December 2022

Abstract
Background
People who experience homelessness have poor oral health and face significant barriers to accessing care. Recommendations have been outlined for health services to address their needs - termed Inclusion Health.
The Smile4Life report recommended dentistry for this group should have three ‘tiers’ of service: emergencies, ad hoc treatments and routine care. In primary care, other medical services have developed into two models of care. They are either mainstream practices that offer care with enhanced services for people who experience homelessness, or an integrated model where specialist services bridge the gap between primary and secondary care.
There is little understanding of how Inclusion Oral Health recommendations have been implemented across dental settings; particularly across different geographies and within the different stages of homelessness.
Aims
Describe and compare dental services that exist for people who experience homelessness in the UK.
Methods
Two medline searches were performed in October 2020 to assess the models of dental care for people who experience homelessness in the UK, including rough sleepers, the hidden homeless, travellers, sex workers and vulnerable migrants.
Results
The search resulted in nine dental services which were dedicated to treating people who experience homelessness. The majority did not explore the specific definitions of homelessness and only one service cared for gypsies and travellers.
There were a mixture of models of care, including using blended approaches such as different sites and appointment types to flex to the needs of their population.
Conclusion
Many services that are dedicated to treat people who experience homelessness in the UK are based in the Community Dental Services which allows for flexible models of care due to sporadic patient attendance, high treatment requirements and complex needs.
More research is required to determine how other settings can accommodate these patients as well as understanding how more rural populations access dental care.
Generating Direct Current Electricity from Dripping or Flowing Ionic Water
Authors: Luo Jikui , Kuang Haoze , Huang Shuyi , Zhang Kaihang , Cai Xinyu , Wang Haobin , Zhang Chi , Chen Jinkai , Li Yubo , Wang Xiaozhi , Jin Hao , Dong Shurong , Yang Zongyin , Hasan Tawfique , Wang Zhong Lin 
Published: December 2022

Abstract
Generation of electricity from flowing salt water is extremely attractive as the resources are abundant and green. We propose a generator to harvest DC electricity from flowing ionic solution. The device consists of a substrate with fixed surface charges, a top electrode and a bottom electrode separated with a distance. The electrostatic field originated from the surface charges separates charges of opposite polarities in the solution, while the flow directs the charges to different electrodes in a closed circuit. By utilizing ultrahigh charge density of ferroelectric substrate and ionic solution, the device produces pulsed DC output for droplets and constant current for continuous flow. The output could be greatly enhanced by using substrates with high surface charge densities and high ion concentration solutions. It could also be scaled up by connecting the devices in series or parallel. This work provides a new strategy to harvest low hydrodynamic energy from sea.
Natural Language Processing based Obtaining Information in Pathology Report of Breast Cancer: Single-Institution Study
Authors: Park Phillip , Choi Yeonho , Han Na Young , Hwang Juyeon , Chae Gyeong Min , Kim Minkyung , Chae Heejung , Yoo Chong Woo , Choi Kui Son , Kim Hyun-Jin 
Published: December 2022

Abstract
Background: In 2018, breast cancer was the second most common cancer worldwide. Pathology reports provide important information for optimal treatment decision making.
Objective: To elucidate the deployment of deep learning data extraction methods for pathology reports in a single institute, we investigated the performance of methods between regular expression and natural language processing (NLP) in terms of accuracy.
Methods: This was compared to the bidirectional encoder representations from transformers (BERT) model using specific vocabulary such as BERT-basic, BioBERT, and ClinicalBERT. A total of 1,215 pathology reports were used to build annotated data to develop an extraction algorithm for pathology reports. K-fold cross-validation was used to verify the performance of BioBERT and ClinicalBERT, pre-trained in the BERT model.
Results: Among them, BioBERT emerged as a highly accurate (0.99901) data parsing model based on by k-fold validation. The parsing method using the NLP model could obtain data with higher overall accuracy than the existing method using regular expressions.
Conclusions: Our results showed that BioBERT has high accuracy in pathology reports, and that the NLP model can obtain data with a higher overall accuracy than regular expressions. Taken together, our findings suggest that the process of obtaining information from pathology reports should include NLP using BioBERT.
Marker-free quantification of progenitor population reveals incipient cell fate commitments
Authors: He Xionglei , Deng Shanjun , Gong Han , Zhang Di , Liu Li 
Published: December 2022

Abstract
Quantifying the number of progenitor cells that founder an organ, tissue or cell population is of fundamental value for understanding the development and homeostasis of a multicellular organism. Previous efforts rely on marker genes that are specifically expressed in progenitors. The strategy is, however, hindered often by the lack of ideal markers. By exploring the cell phylogenetic tree that records the cell division history during development, we here describe a general statistical method able to quantify the progenitors of any tissues or cell populations defined in an organism without progenitor-specific markers. The method, termed as targeting coalescent analysis (TCA), computes for all cells of a tissue the average coalescent rate at the monophyletic clades of the target tissue, the inverse of which then measures the progenitor number of the tissue. Both theoretical deduction and computer simulations supported the underlying logics of TCA, which was then validated by empirical data of nematodes, fruit fly and mouse, all with required cell phylogenetic trees. We further showed that TCA can be used to identify lineage-specific gene expression upregulations during embryogenesis, revealing incipient cell fate commitments in mouse embryos.
The Curious Case of the Structural Phase Transition in SnSe: Insights from Neutron Total Scattering
Authors: Jiang Bo , Neu Jennifer , Olds Daniel , Kimber Simon , Page Katharine , Siegrist Theo 
Published: December 2022

Abstract
At elevated temperatures SnSe is reported to undergo a structural transition from the low symmetry orthorhombic GeS-type to a higher symmetry orthorhombic TlI-type. Although increasing symmetry should likewise increase lattice thermal conductivity, many experiments on single crystals and polycrystalline materials indicate that this is not the case 1,2. Here we present temperature dependent analysis of time-of-flight (TOF) neutron total scattering data in combination with theoretical modeling to probe the local to long-range evolution of the structure. We report that while SnSe is well characterized on average within the high symmetry space group above the transition, over length scales of a few unit cells SnSe remains better characterized in the low symmetry GeS-type space group. Our finding from robust modeling provides further insight into the curious case of a dynamic order-disorder phase transition in SnSe, a model consistent with the soft-phonon picture of the high thermoelectric power above the phase transition.
Assessment of Genomic Prediction Strategies after Animal Genome-Wide Association Study
Authors: Wang Jiabo , Peng Wei , Chen Li , Kangzhu Yixi , Zhong Jincheng 
Published: December 2022

Abstract
Background
The detection of candidate variants with interesting traits is a major goal of a genome-wide association study (GWAS). GWAS-associated markers are considered candidate functional loci regarding animal and plant breeding and can serve to predict and treat human genetic diseases. Significant selected markers are functionally validated via molecular biology experiments or statistically validated by genomic prediction (GP) in an individual population. GWAS in a whole population used for GP causes an overprediction regarding accuracy. However, whether this overprediction exists in any traits with different genetic architectures remains unknown, while the extent of the difference between overprediction and actual prediction is also undetermined. The lack of whole key genetic information and linear dependence ubiquity can make perfect prediction of traits of interest impossible. A stable and adaptable prediction method for multiple genetic architectures is thus essential.
Results
We used a public dataset to present the accuracy bias in a cross-validation population with different genetic architectures and developed an approach termed “marker-assisted best linear unbiased prediction (MABLUP),” with removed linear dependence to improve the prediction accuracy for complex traits with genetic architectures. The MABLUP showed better prediction accuracy than other methods for traits under the control of few quantitative trait nucleotides (QTNs) and similar prediction accuracy to the best-known methods for traits under many QTNs.
Conclusions
The reasonable design of GP in the cross-validation after animal GWAS can be used to present actual potential breeding ability of detected significant markers. The MABLUP is a more stable and accurate GP method for more complex genetic traits.
Synchronization of Coupled Fractional-order Reaction–Diffusion Neural Networks under Markovian Switching Topologies via Quantized Control
Authors: Liu Fengyi , Yang Yongqing , Hao Rixu , Zhang Lingzhong 
Published: December 2022

Abstract
In this study, we investigated the synchronization of coupled fractional-order Markovian reaction–diffusion neural networks (MRDNNs) with partly unknown transition rates. The novelty of this study lies in two aspects. First, the Markovian switching model and reaction–diffusion term are incorporated into a fractional order system, which is a difficult and uncommon problem in existing studies. The synchronization problem of fractional-order MRDNNs was solved by introducing a continuous frequency distribution model of a fractional integrator. Second, a new set of sufficient synchronization conditions with low conservativeness was derived. The (extended) Wirtinger inequality and delay-partitioning technologies were used to introduce generous free parameters, thereby effectively increasing the range of solutions. Through quantized control, the channel bandwidth and communication rate were reduced. Furthermore, a
simulation was performed to illustrate the validity of the results and demonstrate the influence of fractional order and reaction–diffusion term on the synchronization rate of the system.
Understanding Gender Labour Inequality in Chile from a Multisector Perspective
Authors: Soza-Amigo Sergio , May Daniel 
Published: December 2022

Abstract
Several academic works have studied the issue of the gender gap from the perspective of wage inequality (i.e. the gender wage gap). However, little work has been done to understand the gender gap from the perspective of labour (i.e. the gender labour gap). This article contributes to the research on the gender labour gap by studying the dynamic of the female labour market across different economic sectors in two macrozones of Chile. The results revealed that the impact of economic changes on the gender labour gap is heterogeneous and complex, and the way in which companies respond to these changes in terms of female labour depends on the sector and the geographical area. That is, in some contexts, economic changes reduced the gender labour gap and in others, the same changes caused an increase in the gender gap. This suggests that policy programs aimed at reducing the gender gap should be focused on the context of a sector with the assistance of the local authority. This is because aggregate data hides the sectorial complexity and this suggests that policies at the national level that are based on aggregate data may not be effective for all sectors.
JEL: J11, J16.
Effects of energy density on the mechanical properties, residual stress and thermal-fatigue of Fe-Cr alloy fabricated by laser directed energy deposition
Authors: Yue Haitao , Lv Ning , Guo Chenguang , Zhao Lijuan , Jiang Yihan , Dai Weibing , Li Qiang , Zhang Jianzhuo 
Published: December 2022

Abstract
Aiming at the problem that AISI4340, a common material for fully mechanized coal-mining equipment, is prone to wear failure in harsh working environment. To repair damaged area and improve service performance, the high-strength Fe-Cr alloy coatings having different laser energy densities were fabricated on the AISI4340 by laser directed energy deposition. The effects of the energy densities on the tensile properties, hardness, residual stress, wear and thermal-fatigue damage were systematically studied. The models of thermal-fatigue damage and service life were established and improved, and the prediction accuracy were verified. The results indicated that with the increasing energy density, the tensile strength and Rockwell hardness increased first and then decreased, and the residual stress on the coating surface aggrandized with increasing temperature gradient. When the energy density was 35.01 J/mm2, the wear depth and wear rate were 51.8 µm and 1.91×10− 2 mm3∙N− 1∙mm− 1, and the wear resistance was increased by two times compared with the substrate. Considered the effective crack propagation and loading order, the accuracy of the service life models were improved from 65.9% and 23.1–14.6% and 6.7%, respectively. Selecting appropriate energy density is beneficial to improve the mechanical properties and decrease the thermal-fatigue damage of Fe-Cr alloy coatings.
Bulk composites from microfibrillated cellulose made into a superior mechanical–performance structural material through lignocellulose/borate cross–linking
Authors: Shen Huajie , Dong Liangzhou , Zheng Xinyuan , Jiang Yifan 
Published: December 2022

Abstract
Since the cross-linking of borates strengthens the structural connection between cells, mechanically superior structural material based on lignocellulose/borate is synthesized using a s mechanical pretreatment method and a binder free hot-pressing method. The results show that the pine lignocellulose formed a dense laminated structure after compressive force, shears, and friction forces and hot–pressing. And microfibrillated cellulose material retained the chemical composition of untreated lignocellulose and the mechanical milling processes of active hydroxyl groups formed by the condensation reaction of borate orthoester with furfural resin adhesive. The flexural strength, modulus elasticity and internal bonding strength of microfibrillated cellulose material are 5, 2.5 and 4.1higher than the untreated lignocellulose specimen, respectively. Furthermore, the thickness swelling rate was 5.66%, which are 298% lower than untreated lignocellulose specimen, indicating its excellent dimensional stability. This is mainly due to the layering and branching of pine lignocellulose during mechanical milling, which gives it more ester and hydrogen bonds, expanding the ratio to surface area and exposing more hydroxyl groups. And the formation of furfuryl alcohol occurred in the hot-pressing process, including the degradation of monosaccharides to furfural, the condensation reaction between lignin and furfural, the resinization of furfural, and the formation of hydrogen bonds. The resulting stable laminated covalent cross–linking structure and the cross–linking of nano–lignocellulose/borate ensure that the material has an excellent mechanical performance, which provides some unique strategies and theoretical guidance to design a superior mechanical–performance structural material from lignocellulose.
Dual Influence of Nano Barium Oxide on Thermal Decomposition Reaction Kinetics and Chemical Stability of cellulose nitrate
Authors: TOUIDJINE Sabri , BOULKADID Moulai Karim , TRACHE Djalal , LOUAFI Elamine , AKBI Hamdane , BELKHIRI Samir , NOURINE Manel 
Published: December 2022

Abstract
This study concerns the determination of the dual influence of nanosized barium oxide (BaO) on thermal decomposition reaction kinetics and the chemical stability of nitrocellulose. Synthetized barium oxide (BaO) nanoparticles (NPs) by the precipitation method were combined with nitrocellulose (NC). The phase, composition, morphology, and structure of the prepared barium oxide NPs and NC- based composites were characterized by X-ray powder diffraction (XRD), Fourier Transferred Infrared (FTIR) spectroscopy, RAMAN spectroscopy, helium densimetry and scanning electron microscopy (SEM). The thermal decomposition reaction kinetics of the NC- based composite were studied by differential scanning calorimetry (DSC) associated with different isoconversional kinetic approaches, namely, iterative Kissinger–Akahira–Sunose (It-KAS), iterative Flynn–Wall–Ozawa (It-FWO) and Vyazovkin’s nonlinear integral with compensation effect (VYA/CE) methods. The effect of BaO NPs on the chemical stability of NC was studied using qualitative stability tests (methyl violet and Abel tests) and quantitative stability tests (Bergmann-Junk test (BJ) and Vacuum Stability Test (VST). Also, stability tests based on microcalorimetric measurement (HFC) were carried out. The results of the thermal kinetic investigation demonstrated an enhancement in the thermal stability of nitrocellulose with the addition of nano barium oxide. The results of the stability tests indicate an improvement of the chemical stability of the pristine NC after the addition of BaO NPs.
A CNTFET-based Mixer Design for 5G Communications
Authors: Villavicencio-Avila Itza Esther , Pacheco-Sanchez Anibal , Rodriguez-Mendez Luis M. , Ramirez-Garcia Eloy 
Published: December 2022

Abstract

This article presents the design of high-frequencydown-conversion mixers using a carbon nanotube fieldeffecttransistor (CNTFET). An experimentally-calibrated semiphysicalcompact model for high-frequency CNTFET technologieshas been used. The designed mixer is proposed using atopology composed of a 90º hybrid coupler at a frequencyof 25 GHz with a coupling factor of 3 dB, a CNTFET andmicrostrip-based coupling networks. The mixer operates in theupper band for 5G communications.The RF signal is used at afrequency of 25 GHz for an intermediate frequency conversion(IF) of 1 GHz using a LO of frequency 24 GHz. The designyields a conversion gain of 20 dB whereas the RF/LO isolationis -18.9 dBm and the LO/IF isolation is -25.6 dBm with ananotube density of 40 CNT/μm. By increasing the densityof nanotubes to 100 CNT/ μm, the conversion gain and portisolation RF/LO figures of merit improve to 26 dB and -20.7dB, respectively. The mixer consumes 9.52 μW from a -1.5 V supply.