The current and potential applications of Ambient Mass Spectrometry in detecting food fraud

AbstractThe adulteration of food has received substantial amounts of media attention in the last few years, with events such as the European horsemeat scandal in 2013 sending shockwaves through society. Almost all cases are motivated by the pursuit of profits and are often aided by long and complex supply chains. In the past few years, the rapid growth of ambient mass spectrometry (AMS) has been remarkable, with over thirty different ambient ionisation techniques available. Due to the increasing concerns of the food industry and regulators worldwide, AMS is now being utilised to investigate whether or not it can generate results which are faster yet comparable to those of conventional techniques. This article reviews some aspects of the adulteration of food and its impact on the economy and the public's health, the background to ambient mass spectrometry and the studies that have been undertaken to detect food adulteration using this technology

A comprehensive strategy to detect the fraudulent adulteration of herbs: The oregano approach

AbstractFraud in the global food supply chain is becoming increasingly common due to the huge profits associated with this type of criminal activity. Food commodities and ingredients that are expensive and are part of complex supply chains are particularly vulnerable. Both herbs and spices fit these criteria perfectly and yet strategies to detect fraudulent adulteration are still far from robust. An FT-IR screening method coupled to data analysis using chemometrics and a second method using LC-HRMS were developed, with the latter detecting commonly used adulterants by biomarker identification. The two tier testing strategy was applied to 78 samples obtained from a variety of retail and on-line sources. There was 100% agreement between the two tests that over 24% of all samples tested had some form of adulterants present. The innovative strategy devised could potentially be used for testing the global supply chains for fraud in many different forms of herbs

Self-Consistent Asset Pricing Models

We discuss the foundations of factor or regression models in the light of the self-consistency condition that the market portfolio (and more generally the risk factors) is (are) constituted of the assets whose returns it is (they are) supposed to explain. As already reported in several articles, self-consistency implies correlations between the return disturbances. As a consequence, the alpha's and beta's of the factor model are unobservable. Self-consistency leads to renormalized beta's with zero effective alpha's, which are observable with standard OLS regressions. Analytical derivations and numerical simulations show that, for arbitrary choices of the proxy which are different from the true market portfolio, a modified linear regression holds with a non-zero value $\alpha_i$ at the origin between an asset $i$'s return and the proxy's return. Self-consistency also introduces ``orthogonality'' and ``normality'' conditions linking the beta's, alpha's (as well as the residuals) and the weights of the proxy portfolio. Two diagnostics based on these orthogonality and normality conditions are implemented on a basket of 323 assets which have been components of the S&P500 in the period from Jan. 1990 to Feb. 2005. These two diagnostics show interesting departures from dynamical self-consistency starting about 2 years before the end of the Internet bubble. Finally, the factor decomposition with the self-consistency condition derives a risk-factor decomposition in the multi-factor case which is identical to the principal components analysis (PCA), thus providing a direct link between model-driven and data-driven constructions of risk factors.Comment: 36 pages with 8 figures. large version with 6 appendices for the Proceedings of the 5th International Conference APFS (Applications of Physics in Financial Analysis), June 29-July 1, 2006, Torin

Interpreting Neural Networks through the Polytope Lens

Mechanistic interpretability aims to explain what a neural network has learned at a nuts-and-bolts level. What are the fundamental primitives of neural network representations? Previous mechanistic descriptions have used individual neurons or their linear combinations to understand the representations a network has learned. But there are clues that neurons and their linear combinations are not the correct fundamental units of description: directions cannot describe how neural networks use nonlinearities to structure their representations. Moreover, many instances of individual neurons and their combinations are polysemantic (i.e. they have multiple unrelated meanings). Polysemanticity makes interpreting the network in terms of neurons or directions challenging since we can no longer assign a specific feature to a neural unit. In order to find a basic unit of description that does not suffer from these problems, we zoom in beyond just directions to study the way that piecewise linear activation functions (such as ReLU) partition the activation space into numerous discrete polytopes. We call this perspective the polytope lens. The polytope lens makes concrete predictions about the behavior of neural networks, which we evaluate through experiments on both convolutional image classifiers and language models. Specifically, we show that polytopes can be used to identify monosemantic regions of activation space (while directions are not in general monosemantic) and that the density of polytope boundaries reflect semantic boundaries. We also outline a vision for what mechanistic interpretability might look like through the polytope lens.Comment: 22/11/22 initial uploa

European Working Time Directive and doctors' health: a systematic review of the available epidemiological evidence

Objective: To summarise the available scientific evidence on the health effects of exposure to working beyond the limit number of hours established by the European Working Time Directive (EWTD) on physicians. Design: A systematic literature search was conducted in PubMed and EMBASE. Study selection, quality appraisal and data extraction were carried out by independent pairs of researchers using pre-established criteria. Setting: Physicians of any medical, surgical or community specialty, working in any possible setting (hospitals, primary healthcare, etc), as well as trainees, residents, junior house officers or postgraduate interns, were included. Participants: The total number of participants was 14 338. Primary and secondary outcome measures: Health effects classified under the International Classification of Diseases (ICD-10). Results: Over 3000 citations and 110 full articles were reviewed. From these, 11 studies of high or intermediate quality carried out in North America, Europe and Japan met the inclusion criteria. Six studies included medical residents, junior doctors or house officers and the five others included medical specialists or consultants, medical, dental, and general practitioners and hospital physicians. Evidence of an association was found between percutaneous injuries and road traffic accidents with extended long working hours (LWH)/days or very LWH/weeks. The evidence was insufficient for mood disorders and general health. No studies on other health outcomes were identified. Conclusions: LWH could increase the risk of percutaneous injuries and road traffic accidents, and possibly other incidents at work through the same pathway. While associations are clear, the existing evidence does not allow for an established causal or ‘dose–response’ relationship between LWH and incidents at work, or for a threshold number of extended hours above which there is a significantly higher risk and the hours physicians could work and remain safe and healthy. Policymakers should consider safety issues when working on relaxing EWTD for doctors

The Treatment of People with Mental Illness in the Criminal Justice System: The Example of Oneida County, New York

This publication is two-fold: an executive summary and the report itself. The executive summary provides a general overview of the larger report, on the criminalization of the mentally ill. It begins by summarizing three case studies from the report that concern the intersection of mental health issues and the criminal justice system in Oneida County in New York State. It then provides a brief historical overview of mental health issues and the criminal justice system before going on to discuss the current best practices in addressing the criminalization of the mentally ill, including law-enforcement mechanisms, mental health courts, and reintegration programs. Next, the paper identifies the shortcomings of these practices and the lack of organizational and financial capacity that hobbles concerned stakeholders from effectively tackling the issue. The paper concludes by proposing a general program for immediate action on local and national scales

Rabies virus matrix protein interplay with eIF3, new insights into rabies virus pathogenesis

Viral proteins are frequently multifunctional to accommodate the high density of information encoded in viral genomes. Matrix (M) protein of negative-stranded RNA viruses such as Rhabdoviridae is one such example. Its primary function is virus assembly/budding but it is also involved in the switch from viral transcription to replication and the concomitant down regulation of host gene expression. In this study we undertook a search for potential rabies virus (RV) M protein's cellular partners. In a yeast two-hybrid screen the eIF3h subunit was identified as an M-interacting cellular factor, and the interaction was validated by co-immunoprecipitation and surface plasmon resonance assays. Upon expression in mammalian cell cultures, RV M protein was localized in early small ribosomal subunit fractions. Further, M protein added in trans inhibited in vitro translation on mRNA encompassing classical (Kozak-like) 5′-UTRs. Interestingly, translation of hepatitis C virus IRES-containing mRNA, which recruits eIF3 via a different noncanonical mechanism, was unaffected. Together, the data suggest that, as a complement to its functions in virus assembly/budding and regulation of viral transcription, RV M protein plays a role in inhibiting translation in virus-infected cells through a protein–protein interaction with the cellular translation machinery

A Prototype Virginia Ground Station Network

This paper provides a detailed technical description of a prototype ground station network, the Virginia Ground Station Network (VGSN), developed for the Virginia Cubesat Constellation (VCC) mission. Virginia Tech (VT), University of Virginia (UVA), and Old Dominion University (ODU) have each constructed ground stations to communicate with their respective VCC spacecraft. Initially, each university was responsible for commanding its own spacecraft via its own ground station. As the mission progressed, it was decided to network the ground stations and operations centers together to provide backup communications capability for the overall mission. The NASA Wallops Flight Facility (WFF) UHF smallsat ground station was also included in this network. Implementing the VGSN led to the establishment of successful communications with UVA’s Libertas spacecraft via the VT Ground Station (VTGS), demonstrating the utility of collaboration and of the VGSN. This paper provides a technical overview of the VGSN, details concerning signal processing requirements for the mission, a discussion concerning the radio regulatory process as applied to the VCC mission, and plans for future upgrades of the network to continue to support Virginia (and partner institution) small satellite missions

Mortality in Pharmacologically Treated Older Adults with Diabetes: The Cardiovascular Health Study, 1989–2001

BACKGROUND: Diabetes mellitus (DM) confers an increased risk of mortality in young and middle-aged individuals and in women. It is uncertain, however, whether excess DM mortality continues beyond age 75 years, is related to type of hypoglycemic therapy, and whether women continue to be disproportionately affected by DM into older age. METHODS AND FINDINGS: From the Cardiovascular Health Study, a prospective study of 5,888 adults, we examined 5,372 participants aged 65 y or above without DM (91.2%), 322 with DM treated with oral hypoglycemic agents (OHGAs) (5.5%), and 194 with DM treated with insulin (3.3%). Participants were followed (1989–2001) for total, cardiovascular disease (CVD), coronary heart disease (CHD), and non-CVD/noncancer mortality. Compared with non-DM participants, those treated with OHGAs or insulin had adjusted hazard ratios (HRs) for total mortality of 1.33 (95% confidence interval [CI], 1.10 to 1.62) and 2.04 (95% CI, 1.62 to 2.57); CVD mortality, 1.99 (95% CI, 1.54 to 2.57) and 2.16 (95% CI, 1.54 to 3.03); CHD mortality, 2.47 (95% CI, 1.89 to 3.24) and 2.75 (95% CI, 1.95 to 3.87); and infectious and renal mortality, 1.35 (95% CI, 0.70 to 2.59) and 6.55 (95% CI, 4.18 to 10.26), respectively. The interaction of age (65–74 y versus ≥75 y) with DM was not significant. Women treated with OHGAs had a similar HR for total mortality to men, but a higher HR when treated with insulin. CONCLUSIONS: DM mortality risk remains high among older adults in the current era of medical care. Mortality risk and type of mortality differ between OHGA and insulin treatment. Women treated with insulin therapy have an especially high mortality risk. Given the high absolute CVD mortality in older people, those with DM warrant aggressive CVD risk factor reduction