Improved Finite Element Model Updating of a Highway Viaduct Using Acceleration and Strain Data.

Most finite element model updating (FEMU) studies on bridges are acceleration-based due to their lower cost and ease of use compared to strain- or displacement-based methods, which entail costly experiments and traffic disruptions. This leads to a scarcity of comprehensive studies incorporating strain measurements. This study employed the strain- and acceleration-based FEMU analyses performed on a more than 50-year-old multi-span concrete highway viaduct. Mid-span strains under heavy vehicles were considered for the strain-based FEMU, and frequencies and mode shapes for the acceleration-based FEMU. The analyses were performed separately for up to three variables, representing Young's modulus adjustment factors for different groups of structural elements. FEMU studies considered residual minimisation and the error-domain model falsification (EDMF) methodology. The residual minimisation utilised four different single-objective optimisations focusing on strains, frequencies, and mode shapes. Strain- and frequency-based FEMU analyses resulted in an approximately 20% increase in the overall superstructure's design stiffness. This study shows the benefits of the intuitive EDMF over residual minimisation for FEMU, where information gained from the strain data, in addition to the acceleration data, manifests more sensible updated variables. EDMF finally resulted in a 25-50% overestimated design stiffness of internal main girders.

Use of the instrumental inequalities in simulated mendelian randomization analyses with coarsened exposures.

Mendelian randomization (MR) requires strong unverifiable assumptions to estimate causal effects. However, for categorical exposures, the MR assumptions can be falsified using a method known as the instrumental inequalities. To apply the instrumental inequalities to a continuous exposure, investigators must coarsen the exposure, a process which can itself violate the MR conditions. Violations of the instrumental inequalities for an MR model with a coarsened exposure might therefore reflect the effect of coarsening rather than other sources of bias. We aim to evaluate how exposure coarsening affects the ability of the instrumental inequalities to detect bias in MR models with multiple proposed instruments under various causal structures. To do so, we simulated data mirroring existing studies of the effect of alcohol consumption on cardiovascular disease under a variety of exposure-outcome effects in which the MR assumptions were met for a continuous exposure. We categorized the exposure based on subject matter knowledge or the observed data distribution and applied the instrumental inequalities to MR models for the effects of the coarsened exposure. In simulations of multiple binary instruments, the instrumental inequalities did not detect bias under any magnitude of exposure outcome effect when the exposure was coarsened into more than 2 categories. However, in simulations of both single and multiple proposed instruments, the instrumental inequalities were violated in some scenarios when the exposure was dichotomized. The results of these simulations suggest that the instrumental inequalities are largely insensitive to bias due to exposure coarsening with greater than 2 categories, and could be used with coarsened exposures to evaluate the required assumptions in applied MR studies, even when the underlying exposure is truly continuous.

Toward a clearer understanding of what works to reduce gun violence: the role of falsification strategies.

Strong epidemiologic evidence from ecologic and individual-level studies in the United States supports the claim that access to firearms substantially increases the risk of dying by suicide, homicide, and firearm accidents. Less certain is how well particular interventions work to prevent these deaths and other firearm-related harms. Given the limits of existing data to study firearm violence, and the infeasibility of conducting randomized trials of firearm access, it is important to do the best we can with the data we already have. We argue that falsification strategies are a critical - yet underutilized - component of any such analytic approach. The falsification strategies we focus on are versions of "negative controls" analyses in which we expect an analysis should yield a null causal effect, and thus where not obtaining a null effect estimate raises questions about the assumptions underlying causal interpretation of a study's findings. We illustrate the saliency of this issue today with examples drawn from studies published within the last five years in leading peer-reviewed journals. Collecting rich, high-quality data always takes time, urgent as the need may be. On the other hand, doing better with the data we already have can start right now.

Popperian ecology is a delusion.

During the last 50 years, a group of ecologists has repeatedly used Popper's falsificationism in normative claims concerning how research in ecology should be conducted and/or how ecology should be corrected. Other ecologists seem to be dissatisfied with these criticisms. Nevertheless, they have not provided systematic analyses of how and why the Popperian criticisms of ecology fail. I have two aims in this article First, I show how so-called Popperian ecologists have not only failed to use but have misused - if not abused - Popper in their criticisms of ecology. That is, the Popperian criticisms of ecology lack the justification the critics claim it has. Second, I claim that Popper's falsificationism is an unsuitable philosophy of science for ecology. In other words, ecology should not be criticized nor evaluated from the Popperian perspective in the first place.

Using the global randomization test as a Mendelian randomization falsification test for the exclusion restriction assumption.

Mendelian randomization may give biased causal estimates if the instrument affects the outcome not solely via the exposure of interest (violating the exclusion restriction assumption). We demonstrate use of a global randomization test as a falsification test for the exclusion restriction assumption. Using simulations, we explored the statistical power of the randomization test to detect an association between a genetic instrument and a covariate set due to (a) selection bias or (b) horizontal pleiotropy, compared to three approaches examining associations with individual covariates: (i) Bonferroni correction for the number of covariates, (ii) correction for the effective number of independent covariates, and (iii) an r2 permutation-based approach. We conducted proof-of-principle analyses in UK Biobank, using CRP as the exposure and coronary heart disease (CHD) as the outcome. In simulations, power of the randomization test was higher than the other approaches for detecting selection bias when the correlation between the covariates was low (r2 < 0.1), and at least as powerful as the other approaches across all simulated horizontal pleiotropy scenarios. In our applied example, we found strong evidence of selection bias using all approaches (e.g., global randomization test p < 0.002). We identified 51 of the 58 CRP genetic variants as horizontally pleiotropic, and estimated effects of CRP on CHD attenuated somewhat to the null when excluding these from the genetic risk score (OR = 0.96 [95% CI: 0.92, 1.00] versus 0.97 [95% CI: 0.90, 1.05] per 1-unit higher log CRP levels). The global randomization test can be a useful addition to the MR researcher's toolkit.

Indirect reciprocity with abductive reasoning.

Indirect reciprocity is a reputational mechanism through which cooperative behavior can be promoted amongst a group of individuals. However, in order for this mechanism to effectively do so, cheating must be appropriately punished and cooperating appropriately rewarded. Errors in assessments and actions can hinder this process. In such a setting, individuals might try to reason about evidence to assign reputations given the possibility of errors. Here, we consider a well-established theory of reasoning used to combine evidence, abductive reasoning, as a possible means by which such errors can be circumvented. Specifically, we use Dempster-Shafer theory to model individuals who account for possible errors by combining information about their beliefs about the status of the population and the errors rates and then choose the simplest scenario that could explain their observations in the context of these beliefs. We investigate the effectiveness of abductive reasoning at promoting cooperation for five social norms: Scoring, Shunning, Simple Standing, Staying, and Stern Judging. We find that, generally, abductive reasoning can outperform non-reasoning models at ameliorating the effects of the aforementioned challenges and promote higher levels of cooperation under low-error conditions. However, for high-error conditions, we find that abductive reasoning can undermine cooperation. Furthermore, we also find that a degree of bias towards believing previously held reputations can help sustain cooperation.

Darwin's feathers: Eco-evolutionary biology, predictions and policy.

The scientific community is often asked to predict the future state of the environment and, to do so, the structure (biodiversity) and the functions (ecosystem functioning) of the investigated systems must be described and understood. In his "handful of feathers" metaphor, Charles Darwin explained the difference between simple and predictable systems, obeying definite laws, and complex (and unpredictable) systems, featured by innumerable components and interactions among them. In order not to waste efforts in impossible enterprises, it is crucial to ascertain if accurate predictions are possible in a given domain, and to what extent they might be reliable. Since ecology and evolution (together forming "natural history") deal with complex historical systems that are extremely sensitive to initial conditions and to contingencies or 'black swans', it is inherently impossible to accurately predict their future states. Notwithstanding this impossibility, policy makers are asking the community of ecological and evolutionary biologists to predict the future. The struggle for funding induces many supposed naturalists to do so, also because other types of scientists (from engineers to modellers) are keen to sell predictions (usually in form of solutions) to policy makers that are willing to pay for them. This paper is a plea for bio-ecological realism. The "mission" of ecologists and evolutionary biologists (natural historians) is not to predict the future state of inherently unpredictable systems, but to convince policy makers that we must live with uncertainties. Natural history, however, can provide knowledge-based wisdom to face the uncertainties about the future. Natural historians produce scenarios that are of great help in figuring out how to manage our relationship with the rest of nature.

Accelerating scientific progress through Bayesian adversarial collaboration.

Adversarial collaboration has been championed as the gold standard for resolving scientific disputes but has gained relatively limited traction in neuroscience and allied fields. In this perspective, we argue that adversarial collaborative research has been stymied by an overly restrictive concern with the falsification of scientific theories. We advocate instead for a more expansive view that frames adversarial collaboration in terms of Bayesian belief updating, model comparison, and evidence accumulation. This framework broadens the scope of adversarial collaboration to accommodate a wide range of informative (but not necessarily definitive) studies while affording the requisite formal tools to guide experimental design and data analysis in the adversarial setting. We provide worked examples that demonstrate how these tools can be deployed to score theoretical models in terms of a common metric of evidence, thereby furnishing a means of tracking the amount of empirical support garnered by competing theories over time.

Misconduct in Biomedical Research: A Meta-Analysis and Systematic Review.

Aims and Objectives: This study aimed to assess the nature and prevalence of misconduct in self and nonself-reported biomedical research. Materials and Methods: A detailed review of previously conducted studies was conducted through PubMed Central, PubMed, and Google Scholar using MeSH terms: "scientific misconduct," "Publications," "plagiarism," and "authorship," and keywords: scientific misconduct, gift authorship, ghost authorship, and duplicate publication. MeSH terms and keywords were searched in combinations using Boolean operators "AND" and "OR." Of 7771 articles that appeared in the search, 107 were selected for inspection. The articles were screened for their quality and inclusion criteria. Finally, 16 articles were selected for meta-analysis. Data analysis was conducted using an Open-Source, Open Meta Analyst, statistical software using the package "metaphor." Results: Plagiarism, data fabrication, and falsification were prevalent in most articles reviewed. The prevalence of research misconduct for plagiarism was 4.2% for self-reported and 27.9% for nonself-reported studies. Data fabrication was 4.5% in self-reported and 21.7% in nonself-reported studies. Data falsification was 9.7% in self-reported and 33.4% in nonself-reported studies, with significant heterogeneity. Conclusion: This meta-analysis gives a pooled estimate of the misconduct in research done in biomedical fields such as medicine, dental, pharmacy, and others across the world. We found that there is an alarming rate of misconduct in recent nonself-reported studies, and they were higher than that in the self-reported studies.

Concepts and Reasoning: a Conceptual Review and Analysis of Logical Issues in Empirical Social Science Research.

A substantial number of social science studies have shown a lack of conceptual clarity, inadequate understanding of the nature of the empirical research approaches, and undue preference for deduction, which have caused much confusion, created paradigmatic incommensurability, and impeded scientific advancement. This study, through conceptual review and analysis of canonical discussions of concepts and the reasoning approaches of deduction and induction and their applications in social science theorization by philosophers and social scientists, is purported to unveil the logical nature of empirical research and examine the legitimacy of the preference of deduction among social scientists. The findings note that conceptual clarity as the foundation of social science research, exchange, and replication can be achieved through interdisciplinary stress of conceptual analyses to establish universal measurements and that the primacy of deduction in social sciences needs to concede to or be balanced with induction for new knowledge, more discoveries, and scientific advancement. The study recommends that institutions and researchers of social sciences invest more in conceptual analysis and inductive research through collaboration and separate efforts.

CRIMINAL OFFENCES RELATED TO ILLICIT TRAFFICKING IN FALSIFIED MEDICINES: INVESTIGATION PROBLEMS.

OBJECTIVE: The aim: Formulate recommendations for improving the efficiency of detection and investigation of trafficking in falsified medicines, application of criminal¬istics knowledge. To analise the contemporary condition and the latest trends in combating this type of crimes and to justify the need for creation of a complex criminalistic methodic investigation. PATIENTS AND METHODS: Materials and methods: Аnalysis of the applicable laws governing trade in medical products in Ukraine; judgments of courts of Ukraine for the period from 2013 to 2022; results of generalization of 128 criminal proceedings; active employee survey results (205 respondents) etc. Over the course of the present research, we have used general scientific and specialised research methods. RESULTS: Results and Conclusions: Increasing the effectiveness of combating the illegal circulation of falsified falsified medicines is a complex problem that encompasses a whole system of directions, requiring the combined efforts of international bodies and organizations, various scientists. One of the priority directions for the introduction of an effective mechanism for combating the distribution of falsified medicines is the development of a complex criminalistic methodic investigation.

SALE OF FALSIFIED MEDICINES VIA THE INTERNET IN UKRAINE: PROBLEMS OF DETECTION AND COUNTERACTION.

OBJECTIVE: The aim: The purpose of the article is to identify and analyze problematic theoretical and practical aspects related to the sale of counterfeit medicines via the Internet and measures to counteract the spread of their counterfeit products, as well as to search for evidence-based ways to improve the regulatory and legal mechanism that regulates the activities of the pharmaceutical business in Ukraine. PATIENTS AND METHODS: Materials and methods: The research based by the analysis of international acts, conventions and national legislation of Ukraine in the sphere of trade medi¬cines via the Internet, scientific achievements in this area. Methodologically, this work is based on the system of methods, scientific approaches, techniques and principles with the help of which the realization of the research aim is carried out. There have been applied universal, general scientific and special legal methods. CONCLUSION: Conclusions: Analyzed the legal regulation of online sales of medicines. Made the conclusion about necessity implementation of projects to create forensic records which have shown their effectiveness in the fight against counterfeit medicines in European countries.

Una Revisión de los tipos de Fraude Científico más Frecuentes / A Review of the most frequent types of Scientific Fraud

La presión que existe hoy por publicar ha llevado a que muchos investigadores cometan malas conductas científicas, siendo el fraude la más grave de todas. Este ocurre en forma de fabricación, falsificación, plagio, problemas de autoría, manipulación de imágenes y publicaciones redundantes. El fraude científico se define como una tergiversación deliberada por parte de alguien que conoce la verdad. En la historia de la humanidad se han conocido importantes casos de fraude científico, dentro de ellos se pueden destacar: el hombre de Piltdown, caso Shinichi Fujimura, el escándalo de las vacunas, caso Pearce, el caso Yoshitaka Fujii, entre otros. Con el objetivo de neutralizar el fraude, se han desarrollado diferentes estrategias dirigidas a detectarlo, dentro de ellas encontramos: evaluación mediante pares evaluadores, programas de Conducta de Investigación Responsable (RCR), regulaciones que la misma comunidad científica realiza, donde encontramos la fundación PubPeer y el blog For Better Science. Del mismo modo, se han impuesto diferentes medidas para contrarrestar el fraude, tales como: transparencia de las presiones y oportunidades, disponibilidad pública de los datos que sustentan la hipótesis y denuncia pública de los fraudes científicos. El impacto de un fraude trae consecuencias importantes para la ciencia, estudiar a partir de información falsa o errónea conlleva a un gran retroceso en los avances científicos del mundo actual. Es responsabilidad de cada uno ser consciente de lo que se escribe y lo que se lee, ya que como se sabe, esa es la única manera de combatirlo. Como investigadores somos responsables de actuar éticamente en nuestras investigaciones y tener conocimiento de las medidas que existen hoy para detectar y combatir el fraude científico.

The pressure to publish today has led many researchers to commit scientific misconduct, fraud being the most serious of all. This occurs in the form of fabrication, falsification, plagiarism, authorship problems, image manipulation, and redundant posting. Scientific fraud is defined as deliberate misrepresentation by someone who knows the truth. In the history of humanity, important cases of scientific fraud have been known, among them the following can be highlighted: the Piltdown man, the Shinichi Fujimura case, the vaccine scandal, the Pearce case, the Yoshitaka Fujii case, among others. In order to neutralize fraud, different strategies have been developed to detect it, among them we find: evaluation by peer reviewers, Responsible Research Conduct (RCR) programs, regulations that the scientific community itself carries out, where we find the PubPeer Foundation and the For Better Science blog. Similarly, different measures have been imposed to counteract fraud, such as: transparency of pressures and opportunities, public availability of the data that support the hypothesis, and public denunciation of scientific fraud. The impact of a fraud has important consequences for science, studying from false or wrong information leads to a great setback in scientific advances in the world today. It is the responsibility of each one to be aware of what is written and what is read, since as is known, that is the only way to combat it. As researchers we are responsible for acting ethically in our research and being aware of the measures that exist today to detect and combat scientific fraud.

Falsification of the instrumental variable conditions in Mendelian randomization studies in the UK Biobank.

Mendelian randomization (MR) is an increasingly popular approach to estimating causal effects. Although the assumptions underlying MR cannot be verified, they imply certain constraints, the instrumental inequalities, which can be used to falsify the MR conditions. However, the instrumental inequalities are rarely applied in MR. We aimed to explore whether the instrumental inequalities could detect violations of the MR conditions in case studies analyzing the effect of commonly studied exposures on coronary artery disease risk.Using 1077 single nucleotide polymorphisms (SNPs), we applied the instrumental inequalities to MR models for the effects of vitamin D concentration, alcohol consumption, C-reactive protein (CRP), triglycerides, high-density lipoprotein (HDL) cholesterol, and low-density lipoprotein (LDL) cholesterol on coronary artery disease in the UK Biobank. For their relevant exposure, we applied the instrumental inequalities to MR models proposing each SNP as an instrument individually, and to MR models proposing unweighted allele scores as an instrument. We did not identify any violations of the MR assumptions when proposing each SNP as an instrument individually. When proposing allele scores as instruments, we detected violations of the MR assumptions for 5 of 6 exposures.Within our setting, this suggests the instrumental inequalities can be useful for identifying violations of the MR conditions when proposing multiple SNPs as instruments, but may be less useful in determining which SNPs are not instruments. This work demonstrates how incorporating the instrumental inequalities into MR analyses can help researchers to identify and mitigate potential bias.

Systemic Obstacles to Addressing Research Misconduct in Higher Education: A Case Study.

Several widely publicized incidents of academic research misconduct, combined with the politicization of the role of science in public health and policy discourse (e.g., COVID, immunizations) threaten to undermine faith in the integrity of empirical research. Researchers often maintain that peer-review and study replication allow the field to self-police and self-correct; however, stark disparities between official reports of academic research misconduct and self-reports of academic researchers, specifically with regard to data fabrication, belie this argument. Further, systemic imperatives in academic settings often incentivize institutional responses that focus on minimizing reputational harm rather than the impact of fabricated data on the integrity of extant and future research.

Counterfeit medicines: relevance, consequences and strategies to combat the global crisis

Abstract Counterfeiting of medicines, also known as "falsification" or "adulteration", is the process in which the identity, origin, or history of genuine medicines are intentionally modified. Currently, counterfeit medicines are a global crisis that affects and is mostly caused by developing countries in Asia, Africa and Latin America. These countries lack strict law enforcement against this practice and have low-income populations with medicinal needs. Lately, the crisis has escalated, impacting developed countries as well, e.g., the US and the EU, mainly via the Internet. Despite this extension, some current laws aim to control and minimize the crisis' magnitude. Falsification of medicines maintains an illegitimate supply chain that is connected to the legitimate one, both of which are extremely complex, making such falsification difficult to control. Furthermore, political and economic causes are related to the crisis' hasty growth, causing serious consequences for individuals and public health, as well as for the economy of different countries. Recently, organizations, technologies and initiatives have been created to overcome the situation. Nevertheless, the development of more effective measures that could aggregate all the existing strategies into a large functioning network could help prevent the acquisition of counterfeit medicines and create awareness among the general population.

Motive perception pathways to the release of personal information to healthcare organizations.

BACKGROUND: The goal of the study is to assess the downstream effects of who requests personal information from individuals for artificial intelligence-(AI) based healthcare research purposes-be it a pharmaceutical company (as an example of a for-profit organization) or a university hospital (as an example of a not-for-profit organization)-as well as their boundary conditions on individuals' likelihood to release personal information about their health. For the latter, the study considers two dimensions: the tendency to self-disclose (which is aimed to be high so that AI applications can reach their full potential) and the tendency to falsify (which is aimed to be low so that AI applications are based on both valid and reliable data). METHODS: Across three experimental studies with Amazon Mechanical Turk workers from the U.S. (n = 204, n = 330, and n = 328, respectively), Covid-19 was used as the healthcare research context. RESULTS: University hospitals (vs. pharmaceutical companies) score higher on altruism and lower on egoism. Individuals were more willing to disclose data if they perceived that the requesting organization acts based on altruistic motives (i.e., the motives function as gate openers). Individuals were more likely to protect their data by intending to provide false information when they perceived egoistic motives to be the main driver for the organization requesting their data (i.e., the motives function as a privacy protection tool). Two moderators, namely message appeal (Study 2) and message endorser credibility (Study 3) influence the two indirect pathways of the release of personal information. CONCLUSION: The findings add to Communication Privacy Management Theory as well as Attribution Theory by suggesting motive-based pathways to the release of correct personal health data. Compared to not-for-profit organizations, for-profit organizations are particularly recommended to match their message appeal with the organizations' purposes (to provide personal benefit) and to use high-credibility endorsers in order to reduce inherent disadvantages in motive perceptions.

How failure to falsify in high-volume science contributes to the replication crisis.

The number of scientific papers published every year continues to increase, but scientific knowledge is not progressing at the same rate. Here we argue that a greater emphasis on falsification - the direct testing of strong hypotheses - would lead to faster progress by allowing well-specified hypotheses to be eliminated. We describe an example from neuroscience where there has been little work to directly test two prominent but incompatible hypotheses related to traumatic brain injury. Based on this example, we discuss how building strong hypotheses and then setting out to falsify them can bring greater precision to the clinical neurosciences, and argue that this approach could be beneficial to all areas of science.

Organophosphate insecticide poisoning with monocrotophos-induced fabricated illness in a 7-year-old girl with refractory seizures over a 4-year period.

Munchausen syndrome by proxy is a form of abuse in which an adult, usually the mother, deceives health workers by exaggerating, falsifying or directly inducing psychological or physical symptoms in the child victim for psychological gratification. In 2013, the American Academy of Pediatrics coined the term 'caregiver-fabricated illness in a child' to describe this form of child abuse. A 7-year-old girl had many encounters with health workers over a period of 4 years and presented with evolving clinical features including refractory seizures and red urine for which she was followed up as a case of acute intermittent porphyria. She was later discovered to be the victim of chronic monocrotophos organophosphate poisoning by her mother. If all medical staff who manage children are to avoid becoming inadvertent participants in medical child abuse, this case report is an important reminder that a high index of suspicion is warranted in cases which present a diagnostic dilemma and who respond unexpectedly to treatment.Abbreviations AIP: Acute intermittent porphyria; APSAC: American Professional Society on the Abuse of Children; ASM: anti-seizure medication; CFIC: caregiver-fabricated illness in a child; CT: computed tomography: DVT: deep vein thrombosis; EEG: electroencephalogram: ESR: erythrocyte sedimentation rate; HDW: high-dependency ward; ICU: intensive care unit; LFT: liver function test; MBP: Munchausen syndrome by proxy; NICU: neonatal intensive care unit; RFT: renal function test; TB: Tuberculosis; UTH-CH: University Teaching Hospitals Children's Hospital.