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Measuring subregional economic activity: missing frequencies and missing mata
No full textBayesian mixed-frequency vector autoregressions (MF-VARs) are commonly used to produce timely and high-frequency estimates of low-frequency variables. A typical application uses quarterly data on output, for a given country, and monthly indicator data to produce monthly estimates of national output. But, when working at subnational levels, data limitations preclude the use of standard MF-VARs. The frequency mismatch is more complicated, key variables can have missing data, and release delays can be substantial. In this chapter, we develop a novel MF-VAR that addresses all these issues and use it to produce historical estimates of subregional output growth in the UK. The model combines information in the annual subregional data (when available) with data from the UK regions and the UK as a whole. The model is estimated using variational Bayesian methods with shrinkage priors, reflecting the “big data” setup. We use our model to produce a new database of quarterly estimates of subregional GVA growth back to the 1960s, that importantly, because the MF-VAR imposes temporal and cross-sectional restrictions, is consistent with those official data that do exist. We illustrate the use of these new estimates by showing how they can be used to characterize the considerable heterogeneity in subregional business cycle dynamics in the UK and contribute to our understanding of regional economic resilience
Chemisorption and physisorption of alcohols on iron(III) oxide-terminated surfaces from nonpolar solvents.
Get PDFThe adsorption isotherm of alkanols at the haematite|hydrocarbon interface should reflect both chemisorption (chemically bonded fraction) and physisorption (hydrogen bonded fraction). Quartz crystal microbalance (QCM) and X-ray photoelectron spectroscopy (XPS) have been used for characterization of Fe O |hydrocarbon interfaces with absorbed alcohol. A range of Fe O -terminated surfaces, alkanols, hydrocarbons and temperatures have been investigated. A chemisorption-physisorption Langmuir model (CPL) has been developed to interpret the data. All data show simultaneous physisorption and chemisorption of the alcohol. The CPL analysis reveals variability of the surface chemistry from one sample to another - different fractions of surface sites have been determined for Fe O -coated crystals, Fe O powder, stainless steel-coated crystals etc. However, for a given surface, the fraction of chemisorption sites is stable - it does not change with the alcohol, and changes only slightly with the solvent. The physisorbed alcohol molecules assume configuration normal to the surface, while the chemisorbed molecules assume configuration that is either parallel (high homologues) or normal (low homologues). A transition from normal to parallel orientation has been observed at hexyl. The effects from branching of the alcohol are captured well by CPL. The temperature has been shown to alter both the strength of the physisorption and the fraction of available chemisorption sites
Rotational Speed Measurement of a Metallic Rotor through Electret-assisted Electrostatic Sensing
No full textThe rotational speed monitoring of rotating machinery is required in many industrial processes. Electret marker tracking provides a new approach to improving the performance of electrostatic sensors in rotational speed measurement of metallic rotors. This paper proposes a technique for monitoring the rotational speed of a metallic rotor using an electrostatic sensing system with electret markers on the rotor. The impact of the geometric shape, size, number, and arrangement of electret markers on the sensing characteristics of the sensor are analysed through numerical simulation, leading to the optimisation of the design of the markers. Experimental tests were conducted with a metallic rotor with attached markers made from five types of material, including fluorinated ethylene propylene (FEP), polytetrafluoroethylene (PTFE), polyimide (PI), polyethylene terephthalate (PET), and polyvinyl chloride (PVC). The performance of the measurement system is assessed in terms of accuracy, reliability, and rangeability. Experimental results indicate that, FEP electret exhibits superior charge affinity as markers than the other materials. The lower end of the measurement range is as low as 1 rpm (revolution per minute). The measurement system yields a relative error within ±3% over the range of 1 to 3000 rpm with a repeatability of 4.8%. While ensuring the minimum measurable speed (1 rpm), the upper limit of the distance between the rotor surface and the electrodes is 4 mm
Criminalisation and Control: Mediterranean Maritime Search and Rescue Workers’ Perceptions of Uses of Law
Get PDFThis article, based on qualitative research of 22 search and rescue (SAR) activists who save migrant lives at sea, examines perceptions of these activists on measures used to criminalise and control them and their organisations. Recognising the law in this area as contested between the impressions of civic society humanitarian activists and state authorities, it analyses how SAR activists perceive how the law is used to disrupt their work. This article examines not only how the law is developed by government, but it will be argued, utilising the theory of critical legal pluralism, that state officials create law in their encounters with SAR activists and their vessels. This article is therefore significant in demonstrating how state officials can create law for nefarious purposes, which has relevance not only to immigration and maritime law, but to other areas of controversial or contested activity
Self‑Bias and Self‑Related Mentalizing are Unaltered in Adolescents with Autism
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The self is a multidimensional concept that can be represented at a pre-reflective (first-order) level, at a deeper, reflective level (second-order), or even at a meta-level (representing one’s own thoughts, i.e. self-related mentalizing). Since self-related processing and mentalizing are crucial for social cognition, both constructs have been researched in individuals with autism, who experience persistent socio-communicative difficulties. Some studies suggested autism-related reductions of the self-bias, i.e. tendency to preferentially process self-related content; while others observed a decreased ability to mentalize on one’s own thoughts in autism. However, prior research examined distinct levels of self-related processing in isolation, in the context of separate studies.
Methods
In this investigation, we directly compared self-bias, self- and other-related mentalizing within the same sample of adolescents with and without autism, to identify which of these are altered in this condition. Thirty adolescents with autism and 26 age- and IQ-matched controls performed a visual search task (first-order self-bias), a trait adjectives task (second-order self-bias), a feeling-of-knowing task (self-related mentalizing) and the Frith-Happé animations task (other-related mentalizing). Parents also completed two questionnaires (i.e. SRS, SCQ) assessing the adolescent’s degree of autism traits.
Results
Our findings replicated previous research showing reduced other-related mentalizing in autism. However, we did not find any difference between adolescents with and without autism in terms of first- or second-order self-bias, nor in the ability to mentalize on one’s own thoughts.
Conclusion
In line with recent investigations, our results do not support earlier claims of altered self-related information processing in autism
Piloting a minimum data set for older people living in care homes in England: a developmental study
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We developed a prototype minimum data set (MDS) for English care homes, assessing feasibility of extracting data directly from digital care records (DCRs) with linkage to health and social care data.
Methods
Through stakeholder development workshops, literature reviews, surveys and public consultation, we developed an aspirational MDS. We identified ways to extract this from existing sources, including DCRs and routine health and social care datasets. To address gaps, we added validated measures of delirium, cognitive impairment, functional independence and quality of life to DCR software. Following routine health and social care data linkage to DCRs, we compared variables recorded across multiple data sources, using a hierarchical approach to reduce missingness where appropriate. We reported proportions of missingness, mean and standard deviation (SD) or frequencies (%) for all variables.
Results
We recruited 996 residents from 45 care homes in three English Integrated Care Systems. 727 residents had data included in the MDS. Additional data were well completed (<35% missingness at wave 1). Competition for staff time, staff attrition and software-related implementation issues contributed to missing DCR data. Following data linkage and combining variables where appropriate, missingness was reduced (≤4% where applicable).
Discussion
Integration of health and social care is predicated on access to data and interoperability. Despite governance challenges we safely linked care home DCRs to statutory health and social care datasets to create a viable prototype MDS for English care homes. We identified issues around data quality, governance, data plurality and data completion essential to MDS implementation going forward
Assessing the Silent Frontlines: Exploring the Impact of DDoS Hacktivism in the Russo-Ukrainian War
Get PDFThis study assessed the impact and effectiveness of Distributed Denial of Service (DDoS) attacks during a period of about four months of the Russo-Ukrainian war, by observing the exchanges between the opposing sides. The data collection phase took place between the 28th of November 2022 and the 15th of April 2023. In total, we monitored 1,257 websites and web applications targeted in the conflict, with 633 targeted by pro-Russian and 624 by pro-Ukrainian entities. Only a small fraction (1.27%) of the targets remained unaffected, whereas 30.63% faced complete shutdowns. When considering the extent of the attacks conducted by the belligerents in the war, the attacks by pro-Russian entities showed a slightly more successful overall impact, with 36.18% of their targets were taken down, compared to 25.00% on the opposite side. Businesses demonstrated greater resilience against DDoS attacks compared to governmental and educational institutions. An in-depth analysis revealed significant differences in target categories, despite both sides primarily targeting businesses. Our findings regarding the usage of DDoS protection services among the 1,257 analysed targets showed that only 13.37% used such services. Among these minority of users, 70.24% had protection from the beginning of our analysis, while 29.76% adopted it only after experiencing attacks. We also looked into the use of geolocation-based access policies on websites targeted by pro-Ukrainian entities. Our findings indicated that most of these websites do not implement geolocation-based access restrictions. To an extent, such restrictions could have been useful for preventing some unsophisticated attacks. Surprisingly, only a small percentage (4.50%) restricted access to solely Russian addresses, while a fraction (12.56%) seemed to implement adaptive access policies in response to cyberattacks. Lastly, and quite surprisingly for us, we discovered that a significant number of targets on the Russian side were using anti-DDoS services and technology provided by countries that have for a long time imposed economic and commercial sanctions on Russia. This may or may not be strictly illegal, but it is without question against the spirit of these sanctions
Genome-wide egg hunt: Unhiding candidate genes for egg component traits in layers of an F2 resource population
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Certain features in eggs (including the weight of the yolk, albumen, and eggshell) are important economically for poultry breeding and production. This study aimed to establish if there are genes (and, more specifically, variants of genes) that are associated with these traits. To this end, we scanned the genomes of 142 hens phenotyped in different periods of laying; these hens had previously been obtained by crossing breeds with contrasting characteristics. We found a total of 33 gene variants that were associated with yolk weight at 18–28 weeks of age (we called these “YW1”). We found 87 that were associated with thick albumen weight at 18–28 weeks of age (TAW1) and 29–42 weeks of age (TAW2). Finally, four variants were associated with eggshell weight at 18–28 weeks of age (ESW1).These 124 variants were in 53 genes, of which we prioritized 7 genes on the basis that at least 2 variants were found in them. These genes, and the variants that they contain, are potential genetic markers for describing egg weight parameters and their components for the breeding of chickens and possibly other poultry. Using these molecular tools, egg production can be improved significantly through genetic selection.
Abstract
Egg components, including weight of yolk, albumen, and eggshell, are economically important traits in poultry breeding and production, and we thus conducted a genome-wide association study (GWAS) for them. We used an F2 resource population of hens (n = 142) in different periods of laying, obtained by crossing breeds with contrasting phenotypes, and then genotyped them using the Illumina Chicken 60K iSelect BeadChip. Significant associations were found between 33 single nucleotide polymorphisms (SNPs) and yolk weight at 18–28 weeks of age (YW1). Eighty-seven SNPs were associated with thick albumen weight at 18–28 (TAW1) and 29–42 (TAW2) weeks of age. Four SNPs were associated with eggshell weight at 18–28 weeks of age (ESW1). Fifty-three candidate genes were identified in the positions of these SNPs, and seven prioritized candidate genes (PGCs) were revealed in regions where 2–4 SNPs associated with the studied traits were localized. These were as follows: SYTL5 (YW1, TAW1), FRY (TAW1), GABRG3 (YW1, TAW1), ALDH1A3 (YW1), VCL (YW1), HYDIN (YW1), and TIMP4 (TAW1). Allelic variants at the ALDH1A3, VCL, HYDIN, FRY, and TIMP4 loci were associated with higher YW1 and TAW1. These SNPs and PGCs are potential genetic markers for characterizing egg weight parameters and their components in chicken breeding to achieve egg production improvements
The male primary sex ratio bias in goose eggs early in the laying season: a pilot study
Get PDFIn bird eggs, the theoretical expectation of a primary sex ratio (at conception) of 50:50 males/females often fails to materialize. Using PCR technology for sex verification in this pilot study, we evaluated the primary sex ratio of 128 fertilized domestic goose eggs (Anser anser) early in the laying season. Over 24 consecutive days of egg collection, 37% more males were found (58% males vs. 42% females). This male-biased trend gradually declined over the period, but an excess of males was still observed. Among the factors for predicting the male sex ratio bias in a particular goose was the egg weight, i.e., heavier eggs tended towards a male phenotype. The embryo sex of the first egg laid and the egg weight change dynamics over the laying period were also noted. The correlation between actual and predicted data was calculated, taking into account three parameters, and found to be 0.724. To explain the effect of an implicit random/non-random process more adequately, we introduced the concept of biased randomness. As well as being of academic interest, research on sex ratio bias is crucial for goose breeding/reproduction programs and important as a step towards understanding the physiological mechanisms that underly sex ratio bias in these animals
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