How widespread use of generative AI for images and video can affect the environment and the science of ecology.

Generative artificial intelligence (AI) models will have broad impacts on society including the scientific enterprise; ecology and environmental science will be no exception. Here, we discuss the potential opportunities and risks of advanced generative AI for visual material (images and video) for the science of ecology and the environment itself. There are clearly opportunities for positive impacts, related to improved communication, for example; we also see possibilities for ecological research to benefit from generative AI (e.g., image gap filling, biodiversity surveys, and improved citizen science). However, there are also risks, threatening to undermine the credibility of our science, mostly related to actions of bad actors, for example in terms of spreading fake information or committing fraud. Risks need to be mitigated at the level of government regulatory measures, but we also highlight what can be done right now, including discussing issues with the next generation of ecologists and transforming towards radically open science workflows.

Fraud in Genetic Testing: Swindling the System.

PURPOSE: Healthcare fraud comprises a sizable portion of United States healthcare expenditure and inflicts undue burden on payors, patients, and the healthcare system overall. The genetic testing industry is rapidly growing which propagates opportunities for healthcare fraud. Although federal organizations have highlighted it as an issue, there is limited research exploring genetic testing fraud. METHODS: A retrospective review of federal websites, news articles, and a legal database resulted in 42 cases of fraud involving outpatient genetic testing published between February 2019 and December 2023. These cases were analyzed for themes via inductive conventional content analysis. RESULTS: Themes of fraudulent activity included submission of fraudulent claims, kickback or bribe payments, minimal or no contact with patients for which testing was ordered, inappropriate billing and documentation practices, and further actions to conceal fraud. Repercussions imposed on defendants included monetary penalty, imprisonment, business restrictions, and seizure of property. CONCLUSION: High rates of medically inappropriate testing in fraud cases highlight the value of genetics experts in ordering or reviewing claims for genetic testing. Examining fraudulent activity in genetic testing can help providers identify and report fraud, and provide awareness of optimal healthcare allocation in the genetic testing industry.

Food profiling goes green: Sustainable analysis strategies for food authentication.

Omics technologies, such as genomics, proteomics, metabolomics, isotopolomics, and metallomics, are important tools for analytical verification of food authenticity. However, in many cases, their application requires the use of high-resolution technological platforms as well as careful consideration of sample collection, storage, preparation and, in particular, extraction. In this overview, the individual steps and disciplines are explained against the background of the term "Green Chemistry," and the various instrumental procedures for the respective omics disciplines are discussed. Furthermore, new approaches and developments are presented on how such analyses can be made sustainable in the future.

Should a gamete bank verify the non-medical information provided by a donor?

Over the years, cases of fraud have been discovered where donors have been lying about their characteristics. The question raised by such cases is what the responsibility of the gamete bank is for the non-medical information provided by the donor. The problem is that extended donor profiles contain a large amount of information about different aspects of the donor's life and that not all this information can be verified or is worth verifying. Two cases are scrutinized in more detail: education and criminal record. The proposed solution is to split the donor information into a verified and a non-verified part with the non-verified part falling under the responsibility of the donor. The question of what information should be included in the verified part of the donor profile is still open.

Advancing data honesty in experimental biology.

The ease with which scientific data, particularly certain types of raw data in experimental biology, can be fabricated without trace begs urgent attention. This is thought to be a widespread problem across the academic world, where published results are the major currency, incentivizing publication of (usually positive) results at the cost of lax scientific rigor and even fraudulent data. Although solutions to improve data sharing and methodological transparency are increasingly being implemented, the inability to detect dishonesty within raw data remains an inherent flaw in the way in which we judge research. We therefore propose that one solution would be the development of a non-modifiable raw data format that could be published alongside scientific results; a format that would enable data authentication from the earliest stages of experimental data collection. A further extension of this tool could allow changes to the initial original version to be tracked, so every reviewer and reader could follow the logical footsteps of the author and detect unintentional errors or intentional manipulations of the data. Were such a tool to be developed, we would not advocate its use as a prerequisite for journal submission; rather, we envisage that authors would be given the option to provide such authentication. Only authors who did not manipulate or fabricate their data can provide the original data without risking discovery, so the mere choice to do so already increases their credibility (much like 'honest signaling' in animals). We strongly believe that such a tool would enhance data honesty and encourage more reliable science.

Food authenticity and the interactions with human health and climate change.

Food authenticity and fraud, as well as the interest in food traceability have become a topic of increasing interest not only for consumers but also for the research community and the food manufacturing industry. Food authenticity and fraud are becoming prevalent in both the food supply and value chains since ancient times where different issues (e.g., food spoilage during shipment and storage, mixing decay foods with fresh products) has resulted in foods that influence consumers health. The effect of climate change on the quality of food ingredients and products could also have the potential to influence food authenticity. However, this issue has not been considered. This article focused on the interactions between consumer health and the potential effects of climate change on food authenticity and fraud. The role of technology and development of risk management tools to mitigate these issues are also discussed. Where applicable papers that underline the links between the interactions of climate change, human health and food fraud were referenced.

A review of the emerging technologies and systems to mitigate food fraud in supply chains.

Food fraud has serious consequences including reputational damage to businesses, health and safety risks and lack of consumer confidence. New technologies targeted at ensuring food authenticity has emerged and however, the penetration and diffusion of sophisticated analytical technologies are faced with challenges in the industry. This review is focused on investigating the emerging technologies and strategies for mitigating food fraud and exploring the key barriers to their application. The review discusses three key areas of focus for food fraud mitigation that include systematic approaches, analytical techniques and package-level anti-counterfeiting technologies. A notable gap exists in converting laboratory based sophisticated technologies and tools in high-paced, live industrial applications. New frontiers such as handheld laser-induced breakdown spectroscopy (LIBS) and smart-phone spectroscopy have emerged for rapid food authentication. Multifunctional devices with hyphenating sensing mechanisms together with deep learning strategies to compare food fingerprints can be a great leap forward in the industry. Combination of different technologies such as spectroscopy and separation techniques will also be superior where quantification of adulterants are preferred. With the advancement of automation these technologies will be able to be deployed as in-line scanning devices in industrial settings to detect food fraud across multiple points in food supply chains.

Portable and miniature sensors in supply chain for food authentication: a review.

Food fraud, a pervasive issue in the global food industry, poses significant challenges to consumer health, trust, and economic stability, costing an estimated $10-15 billion annually. Therefore, there is a rising demand for developing portable and miniature sensors that facilitate food authentication throughout the supply chain. This review explores the recent advancements and applications of portable and miniature sensors, including portable/miniature near-infrared (NIR) spectroscopy, e-nose and colorimetric sensors based on nanozyme for food authentication within the supply chain. After briefly presenting the architecture and mechanism, this review discusses the application of these portable and miniature sensors in food authentication, addressing the challenges and opportunities in integrating and deploying these sensors to ensure authenticity. This review reveals the enhanced utility of portable/miniature NIR spectroscopy, e-nose, and nanozyme-based colorimetric sensors in ensuring food authenticity and enabling informed decision-making throughout the food supply chain.

Fingerprinting of Octane Rating Gasoline and its Contaminants Using Synchronous Fluorescence Spectroscopy.

Fuel fraud has proliferated due to underlying economic advantage in nearly every nation. For the purpose of detecting adulteration and providing real-time quality assurance, non-destructive oil analysis is crucial. This paper reports the simple approach for fingerprinting undiluted petroleum products including gasoline from various brands, diesel, and kerosene oil in comparison with organic solvents using synchronous fluorescence spectroscopy and hierarchical cluster analysis. Fluorescence-based successful detection of adulterated samples is demonstrated in imported RON 92 gasoline, synthetically adulterated with kerosene oil (KO) in proportions up to 70%. Compared to gasoline, kerosene oil has a lower relative poly aromatic hydrocarbons, as the amount of kerosene oil (KO) increases, the KO peak at 352 nm rises, but the gasoline's peak intensity decreases in the range of 371-500 nm. It is noteworthy that imported fuel grades RON 92 and RON 95 are comparable to each other and surprisingly clustered with RON 91 from the Attock refinery presenting concerns about quality. Similarly, the Shell website mentions that Shell V-Power is RON 99 but interestingly it clusters with retail fuel samples acquired from PSO filling stations and PSO RON 95 showing disagreement with the claim that the fuel is high octane. Another use for this technique in oil exploration was the detection of adulterants and successfully spotted methanol, ethanol, and kerosene oil in the tainted samples. These findings suggest SFS as an accurate, and low-cost testing tool for gasoline fingerprinting and contamination screening.

Induced erotomania by online romance fraud - a novel form of de Clérambault's syndrome.

BACKGROUND: Although the impact of internet usage on mental health is extensively documented, there is a notable scarcity of reports in the literature concerning internet-induced erotomania. Erotomania is a rare and likely underdiagnosed delusional disorder. It is characterized by an irrational belief held by the affected persons that someone of higher socioeconomic status harbor romantic feelings toward them. Here, we describe the psychopathology of erotomanic delusion induced by online romantic fraud in a female patient. Employing this case as a focal point, we illuminate novel aspects of erotomania that warrant attention and examination. CASE PRESENTATION: We present a compelling case involving a 70-year-old married Caucasian woman diagnosed with medically controlled persistent depressive disorder for several years. The intricacies of her condition became evident as she became deeply engrossed in online profiles featuring the image of a renowned musician, inadvertently falling victim to an online romantic fraud. Subsequently, this distressing experience triggered the emergence of erotomanic delusions and a suicide attempt. The patient's history reveals an array of medical conditions and stressful life events, contributing to her vulnerability. The diagnosis of erotomanic delusional disorder, dysthymia, and mild cognitive impairment with cerebral vascular background was established. Treatment involved her previous antidepressant with low-dose risperidone, alongside supportive individual and group therapy. Her delusion showed remission four weeks later, prompting her discharge for outpatient follow-up. Although she retained some false beliefs, the intensity of the symptoms had notably diminished and her functionality improved. CONCLUSION: This case underscores the complex interplay between mental health, online activities, and the consequences of delusions, including suicidal thoughts, shedding light on the need for a comprehensive approach in addressing such challenging psychiatric scenarios.

The reliability of biomedical science: A case history of a maturing experimental field.

There is much discussion in the media and some of the scientific literature of how many of the conclusions from scientific research should be doubted. These critiques often focus on studies - typically in non-experimental spheres of biomedical and social sciences - that search large datasets for novel correlations, with a risk that inappropriate statistical evaluations might yield dubious conclusions. By contrast, results from experimental biological research can often be interpreted largely without statistical analysis. Typically: novel observation(s) are reported, and an explanatory hypothesis is offered; multiple labs undertake experiments to test the hypothesis; interpretation of the results may refute the hypothesis, support it or provoke its modification; the test/revise sequence is reiterated many times; and the field moves forward. I illustrate this experimental/non-experimental dichotomy by examining the contrasting recent histories of: (a) our remarkable and growing understanding of how several inositol-containing phospholipids contribute to the lives of eukaryote cells; and (b) the difficulty of achieving any agreed mechanistic understanding of why consuming dietary supplements of inositol is clinically beneficial in some metabolic diseases.

AI, doping and ethics: On why increasing the effectiveness of detecting doping fraud in sport may be morally wrong.

In this article, our aim is to show why increasing the effectiveness of detecting doping fraud in sport by the use of artificial intelligence (AI) may be morally wrong. The first argument in favour of this conclusion is that using AI to make a non-ideal antidoping policy even more effective can be morally wrong. Whether the increased effectiveness is morally wrong depends on whether you believe that the current antidoping system administrated by the World Anti-Doping Agency is already morally wrong. The second argument is based on the possibility of scenarios in which a more effective AI system may be morally worse than a less effective but non-AI system. We cannot, of course, conclude that the increased effectiveness of doping detection is always morally wrong. But our point is that whether the introduction of AI to increase detection of doping fraud is a moral improvement depends on the moral plausibility of the current system and the distribution of harm that will follow from false positive and false negative errors.

What are people's attitudes toward medical insurance fraud whistleblowers? a study from China.

PURPOSE: Medical insurance fraud has caused huge losses to countries around the world, and public reporting has become an important means to combat medical insurance fraud. The attitude of medical insurance fraud whistleblowers affects people's reporting behavior, and understanding people's attitude toward medical insurance fraud whistleblowers provides a basis for further improving the system and policy of public participation in medical insurance fund supervision. METHODS: We adopted the questionnaire method to conduct a national cross-sectional survey of the Chinese public and analyzed the data using Chi-square tests, Fisher's exact tests, and binary logistic regression models. RESULTS: A total of 837 respondents were included, and 81.8% of the population had a supportive attitude toward medical insurance fraud whistleblowers, with gender, whether they had used medical insurance reimbursement, and present life satisfaction being statistically significant (P < 0.05). CONCLUSION: The public is generally supportive of medical insurance fraud whistleblowers, and women, those who have used medical insurance for reimbursement, and those who are satisfied with their lives are more likely to be supportive of medical insurance fraud whistleblowers.

What influences the public's willingness to report health insurance fraud in familiar or unfamiliar healthcare settings? a cross-sectional study of the young and middle-aged people in China.

INTRODUCTION: Young and middle-aged people are important participants in the fight against health insurance fraud. The study aims to investigate the differences in their willingness to report health insurance fraud and the factors influencing it when it occurs in familiar or unfamiliar healthcare settings. METHODS: Data were obtained from a validated questionnaire from 828 young and middle-aged people. McNemar's test was used to compare the public's willingness to report under the two scenarios. Chi-square tests and multiple logistic regression analysis were used to analyze the determinants of individuals' willingness to report health insurance fraud in different scenarios. RESULTS: Young and middle-aged people were more likely to report health insurance fraud in a familiar healthcare setting than in an unfamiliar one (McNemar's χ²=26.51, P < 0.05). Their sense of responsibility for maintaining the security of the health insurance fund, the government's openness about fraud cases, and the perception of their ability to report had significant positive effects on the public's willingness to report in both settings (P < 0.05). In a familiar healthcare setting, the more satisfied the public is with government measures to protect whistleblowers, the more likely they are to report (OR = 1.44, P = 0.025). Those who perceive the consequences of health insurance fraud to be serious are more likely to report than those who perceive the consequences to be less serious (OR = 1.61, P = 0.042). CONCLUSION: Individuals are more likely to report health insurance fraud in familiar healthcare settings than in unfamiliar ones, in which their awareness of the severity of the consequences of health insurance fraud and their perceived risk after reporting it play an important role. The government's publicizing of fraud cases and enhancing the public's sense of responsibility and ability to maintain the safety of the health insurance fund may be a way to increase their willingness to report, regardless of whether they are familiar with the healthcare setting or not.

Unlocking food safety: a comprehensive review of South Africa's food control and safety landscape from an environmental health perspective.

Food fraud (often called fake food in South Africa) the deliberate misrepresentation or adulteration of food products for financial gain, is a growing problem in South Africa (SA) with severe public health and financial consequences for consumers and businesses. The recent public outcry against food fraud practices especially in communities that have lost loved ones due to the consumption of allegedly adulterated foodstuffs, highlights the grave danger that food fraud poses to consumers and the potential for significant reputational damage to food manufacturers. Despite the risks, food fraud often goes undetected, as perpetrators are becoming increasingly sophisticated. The precise magnitude of food fraud remains obscure, as incidents that do not cause consumer illnesses are frequently unreported and, as a result, are not investigated. Food fraud costs the global economy billion annually. This cost is borne by consumers, businesses, and the government. Food fraud can occur at any stage of the food supply chain, from production to processing to retailing or distribution. This is due in part to the limitations of current analytical methods, which are not always able to detect food fraud. This review of food fraud in SA looks at several factors that may be contributing to epidemic of food fraud, including inadequate penalties, inadequate government commitment, a complex labelling regulation, emerging threats such as e-commerce, and shortage of inspectors and laboratories. The review recommends establishing a single food control/safety authority, developing more food safety laboratories, and adopting innovative technologies to detect and prevent food fraud. SA faces a serious food fraud crises unless decisive action is taken.

Navigating the challenges of imposter participants in online qualitative research: lessons learned from a paediatric health services study.

BACKGROUND: The growth in online qualitative research and data collection provides several advantages for health service researchers and participants, including convenience and extended geographic reach. However, these online processes can also present unexpected challenges, including instances of participant fraud or scam behaviour. This study describes an incident of participant fraud identified during online focus group discussions and interviews for a PhD health services research project on paediatric neurodevelopmental care. METHODS: We aimed to recruit carers of Australian children with neurodevelopmental disorders. Potential participants were recruited via a publicly available social media advert on Facebook offering $50 AUD compensation. Those who expressed interest via email (n = 254) were sent a pre-interview Qualtrics survey to complete. We identified imposters at an early stage via inconsistencies in their self-reported geographical location and that captured by the survey as well as recognition of suspicious actions before, during and after focus group discussions and interviews. RESULTS: Interest in participation was unexpectedly high. We determined that all potential participants were likely imposters, posing as multiple individuals and using different IP addresses across Nigeria, Australia, and the United States. In doing so, we were able to characterise several "red flags" for identifying imposter participants, particularly those posing as multiple individuals. These comprise a combination of factors including large volumes and strange timings of email responses, unlikely demographic characteristics, short or vague interviews, a preference for nonvisual participation, fixation on monetary compensation, and inconsistencies in reported geographical location. Additionally, we propose several strategies to combat this issue such as providing proof of location or eligibility during recruitment and data collection, examining email and consent form patterns, and comparing demographic data with regional statistics. CONCLUSIONS: The emergent risk of imposter participants is an important consideration for those seeking to conduct health services research using qualitative approaches in online environments. Methodological design choices intended to improve equity and access for the target population may have an unintended consequence of improving access for fraudulent actors unless appropriate risk mitigation strategies are also employed. Lessons learned from this experience are likely to be valuable for novice health service researchers involved in online focus group discussions and interviews.

No evidence for systematic voter fraud: A guide to statistical claims about the 2020 election.

After the 2020 US presidential election Donald Trump refused to concede, alleging widespread and unparalleled voter fraud. Trump's supporters deployed several statistical arguments in an attempt to cast doubt on the result. Reviewing the most prominent of these statistical claims, we conclude that none of them is even remotely convincing. The common logic behind these claims is that, if the election were fairly conducted, some feature of the observed 2020 election result would be unlikely or impossible. In each case, we find that the purportedly anomalous fact is either not a fact or not anomalous.

Automatic Recommender System of Development Platforms for Smart Contract-Based Health Care Insurance Fraud Detection Solutions: Taxonomy and Performance Evaluation.

BACKGROUND: Health care insurance fraud is on the rise in many ways, such as falsifying information and hiding third-party liability. This can result in significant losses for the medical health insurance industry. Consequently, fraud detection is crucial. Currently, companies employ auditors who manually evaluate records and pinpoint fraud. However, an automated and effective method is needed to detect fraud with the continually increasing number of patients seeking health insurance. Blockchain is an emerging technology and is constantly evolving to meet business needs. With its characteristics of immutability, transparency, traceability, and smart contracts, it demonstrates its potential in the health care domain. In particular, self-executable smart contracts are essential to reduce the costs associated with traditional paradigms, which are mostly manual, while preserving privacy and building trust among health care stakeholders, including the patient and the health insurance networks. However, with the proliferation of blockchain development platform options, selecting the right one for health care insurance can be difficult. This study addressed this void and developed an automated decision map recommender system to select the most effective blockchain platform for insurance fraud detection. OBJECTIVE: This study aims to develop smart contracts for detecting health care insurance fraud efficiently. Therefore, we provided a taxonomy of fraud scenarios and implemented their detection using a blockchain platform that was suitable for health care insurance fraud detection. To automatically and efficiently select the best platform, we proposed and implemented a decision map-based recommender system. For developing the decision-map, we proposed a taxonomy of 102 blockchain platforms. METHODS: We developed smart contracts for 12 fraud scenarios that we identified in the literature. We used the top 2 blockchain platforms selected by our proposed decision-making map-based recommender system, which is tailored for health care insurance fraud. The map used our taxonomy of 102 blockchain platforms classified according to their application domains. RESULTS: The recommender system demonstrated that Hyperledger Fabric was the best blockchain platform for identifying health care insurance fraud. We validated our recommender system by comparing the performance of the top 2 platforms selected by our system. The blockchain platform taxonomy that we created revealed that 59 blockchain platforms are suitable for all application domains, 25 are suitable for financial services, and 18 are suitable for various application domains. We implemented fraud detection based on smart contracts. CONCLUSIONS: Our decision map recommender system, which was based on our proposed taxonomy of 102 platforms, automatically selected the top 2 platforms, which were Hyperledger Fabric and Neo, for the implementation of health care insurance fraud detection. Our performance evaluation of the 2 platforms indicated that Fabric surpassed Neo in all performance metrics, as depicted by our recommender system. We provided an implementation of fraud detection based on smart contracts.

Addressing Cyberscams and Acquired Brain Injury ("I Desperately Need to Know What to Do"): Qualitative Exploration of Clinicians' and Service Providers' Perspectives.

BACKGROUND: People with acquired brain injury (ABI) may be more susceptible to scams owing to postinjury cognitive and psychosocial consequences. Cyberscams result in financial loss and debilitating psychological impacts such as shame and mistrust, interference with neurorehabilitation, and reduced independence. Despite these significant consequences, there are no psychological treatments to support cyberscam survivors. There is limited evidence regarding how the current workforce is addressing post-ABI cyberscams. OBJECTIVE: This study aims to understand the perspectives and needs of clinicians and service providers in addressing post-ABI cyberscams. METHODS: Overall, 20 multidisciplinary clinicians and service providers were recruited through purposive sampling across Australia. Semistructured interviews explored post-ABI scam experiences and vulnerabilities, treatments and their efficacy, and recommendations for future cybersafety recovery interventions. Reflexive thematic analysis was used. RESULTS: In total, 8 themes encompassing a biopsychosocial understanding of scam vulnerabilities and impacts were identified: "genuine lack of awareness: cognitive-executive difficulties"; "not coping with the loss of it all"; "needing trust and connection"; "strong reactions of trusted others"; "nothing structured to do"; "financial stress and independence"; "cyberability"; and "scammer persuasion." Each theme informed clinical recommendations including the need to provide psychological and cognitive support, enhance financial and cybersafety skills, promote meaningful social engagement, and foster collaboration between families and clinical support teams. CONCLUSIONS: The multifaceted range of scam vulnerabilities and impacts highlighted the need for individualized, comprehensive, and targeted treatments using a biopsychosocial approach to enable cyberscam recovery among people with ABI. These findings will guide the development of a co-designed intervention.

Publication Ethics in the Era of Artificial Intelligence.

The application of new technologies, such as artificial intelligence (AI), to science affects the way and methodology in which research is conducted. While the responsible use of AI brings many innovations and benefits to science and humanity, its unethical use poses a serious threat to scientific integrity and literature. Even in the absence of malicious use, the Chatbot output itself, as a software application based on AI, carries the risk of containing biases, distortions, irrelevancies, misrepresentations and plagiarism. Therefore, the use of complex AI algorithms raises concerns about bias, transparency and accountability, requiring the development of new ethical rules to protect scientific integrity. Unfortunately, the development and writing of ethical codes cannot keep up with the pace of development and implementation of technology. The main purpose of this narrative review is to inform readers, authors, reviewers and editors about new approaches to publication ethics in the era of AI. It specifically focuses on tips on how to disclose the use of AI in your manuscript, how to avoid publishing entirely AI-generated text, and current standards for retraction.