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Microplastic footprints in sharks and rays : first assessment of microplastic pollution in two cartilaginous fishes, hardnose shark and whitespotted whipray
No full textSystematic generation and evaluation of synthetic production data for industry 5.0 optimization
Full text linkExperimental study on the optimization of thermal environment and airflow organization in a ventilated underground refuge chamber using deflectors
No full textAcceptable temperature is crucial for underground refuge chamber (URC) to ensure the safety and comfort of occupants. A novel temperature control scheme combining mechanical ventilation with deflectors was proposed for URCs. In this study, the effects of ventilation rate (VR), deflector height and deflector angle on ambient temperature control performance and airflow organization of URC were investigated through orthogonal experiments. Results show that: (Ⅰ) The ambient temperature gradient of URC decreases with the increase of VR and deflector height. (Ⅱ) With VR of 350 m3/h, deflector height of 1.40 m, and deflector angle of 0°, compared to the situation without deflectors, the temperature unevenness coefficient can be effectively reduced, the head-to-foot temperature difference can meet the design standard requirements, the waste heat emissions efficiency is increased by 46.1 %, and an average decrease in ambient temperature of 2 °C (Ⅲ) The influence of various factors on the ambient temperature control performance in the URC is as follows: deflector height > VR > deflector angle
An early-warning risk signals framework to capture systematic risk in financial markets
No full textearly-warning risk signals
3. Methodology
4. Data collection
5. Results
6. Discussion
7. Conclusion
Disclosure statement
Footnotes
References
Appendixes
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Abstract
Despite extensive research on the relationship between systematic risk and expected returns, there exists limited knowledge of how early-warning risk signals could capture investors’ expectations about changes in systematic risk. Leveraging on graph theory and covariance matrices, this study proposes a novel framework to develop risk signal patterns. Our approach not only discerns high-risk periods from calmer ones but also elucidates the pivotal role of interconnections among securities as indicators of systematic risk. The findings offer actionable insights for timely portfolio management and risk management responses in periods of transitions towards higher systematic risk. Moreover, by leveraging on graph theory, regulators can take timely decisions about how much liquidity to inject into the markets during periods of uncertainty. This study contributes to the literature by establishing a novel framework on linking investors’ expectations and expected changes in systematic risk
Developmental validation of the AGCU EX-38 typing system : a comprehensive forensic tool for enhanced genetic identification
No full textThe necessity for developing the AGCU EX-38 typing system arises from the ever-increasing demand for more accurate and comprehensive forensic tools. Traditional kits with fewer STRs often fall short in complex cases requiring higher resolution. The AGCU EX-38 typing system incorporates 35 autosomal STRs, including extended CODIS loci as well as additional non-CODIS loci (D6S1043, D19S3045, D3S3045, D7S3048, D11S2368, D4S2366, D8S1132, D15S659, Penta D, Penta E, D6S447, D3S1744, D14S608, D18S535). This combination of CODIS and non-CODIS markers provides a significant advantage, particularly in complex kinship analyses such as half-sibship cases. This six-dye kit encompasses 38 loci, with a maximum amplicon size of 550 base pairs (bp), and features nine STRs within 200 bp and 14 STRs within 300 bp, offering unparalleled coverage and sensitivity. The AGCU EX-38 typing system is the only available kit on the market containing 35 autosomal STRs with six-dye chemistry, making it a unique and invaluable resource for forensic laboratories. This configuration allows for higher resolution and superior performance in cases with degraded or mixed DNA samples. In this study, we report the results of the developmental validation study, which followed the SWGDAM (Scientific Working Group on DNA Analysis Methods) guidelines. The data includes PCR-based studies, sensitivity, species specificity, stability, precision, reproducibility and repeatability, concordance, stutter, DNA mixtures, and performance on mock casework samples. The results validate the multiplex design and demonstrate the kit’s robustness, reliability, and suitability for genetic identification and population studies
StatAvg : mitigating data heterogeneity in federated learning for intrusion detection systems
Full text linkFederated learning (FL) enables devices to collaboratively build a shared machine learning (ML) or deep learning (DL) model without exposing raw data. Its privacy-preserving nature has made it popular for intrusion detection systems (IDS) in the field of cybersecurity. However, data heterogeneity across participants poses challenges for FL-based IDS. This paper proposes statistical averaging (StatAvg) method to alleviate non-independently and identically (non-iid) distributed features across local clients’ data in FL. In particular, StatAvg allows the FL clients to share their individual local data statistics with the server. These statistics include the mean and variance of each client’s feature vector. The server then aggregates this information to produce global statistics, which are shared with the clients and used for universal data normalization, i.e., common scaling of the input features by all clients. It is worth mentioning that StatAvg can seamlessly integrate with any FL aggregation strategy, as it occurs before the actual FL training process. The proposed method is evaluated against well-known baseline approaches that rely on batch and layer normalization, such as FedBN, and address the non-iid features issue in FL. Experiments were conducted using the TON-IoT and CIC-IoT-2023 datasets, which are relevant to the design of host and network IDS, respectively. The experimental results demonstrate the efficiency of StatAvg in mitigating non-iid feature distributions across the FL clients compared to the baseline methods, offering a gain in IDS accuracy ranging from 4% to 17%
Copper-chelation-induced ratiometric fluorescence response for sensitive ratiometric detection of zoledronic acid : implications for monitoring in renal impairment
No full text"We're so sorry – yes we really are" : optimal apology strategies for errant fundraising charities
Full text linkThe purpose of this paper is to determine the strengths of the influences of certain factors potentially contributing to an effective apology for a fundraising charity. Four motivational forces possibly affecting public acceptance of an apology issued by a charity are explored, i.e. persuasion knowledge activation, a viewer’s regulatory focus, trait forgiveness and scepticism regarding charity advertising. Texts for two apologies (one based on expressions of guilt, the other on expressions of shame) were created for a fictitious international aid charity, some field workers of which had engaged in child abuse. A questionnaire was distributed to a sample of 777 members of the public containing one or other of the apologies. A good match between a participant’s regulatory focus and the regulatory focus of an apology significantly improved the likelihoods of the apology being “liked” and accepted. Nevertheless, the quality of the match had no impact on a person’s inclination to donate to the organisation. Trait forgiveness and donation history significantly influenced liking and acceptance of an apology, but not inclination to donate. Although past studies have examined the roles of apologies within the communication management activities of commercial organisations, research into the effectiveness of apologies by fundraising nonprofits has been sparse. Outcomes to the present investigation offer insights into how charity managers can best apologise for a fundraising nonprofit organisation’s errant behaviour