Annals of the New York Academy of Sciences最新文献

The rapid expansion of digital media has sparked significant concerns regarding the swift dissemination and potential misuse of forged video content. Existing forgery detection technologies primarily focus on simple forgeries and are still evolving, resulting in a critical gap in the detection of multilevel forgeries, where one forgery is layered over another. This paper presents an innovative framework designed to address this challenge by extracting intricate features from forged frames using attention-augmented convolutional neural networks (AACNNs). A U-Net-based CycleGAN is employed to accurately localize forged regions, enabling a comprehensive analysis that identifies both two- and three-level forgeries by leveraging AACNN's local and global attention mechanisms. To enhance robustness and accuracy, we integrate a model-agnostic meta-learning approach. Our meticulously curated custom dataset, which represents complex forgery scenarios, underpins the effectiveness of our framework. In a 10-shot scenario, the AACNN backbone achieved an impressive accuracy of 98.2%, alongside a sensitivity of 96.3%, specificity of 97.6%, and an F1-score of 96.8%. These results represent a significant advancement in the accuracy and reliability of sophisticated video forgery detection.

The superiority of ferrofluid pumps in the fields of biomedical, life science, energy, and power research has been experimentally demonstrated. However, the mechanisms underlying the morphological transformations of ferrofluid fusion and separation during pump driving are not completely understood. To bridge the gap between the theory and practical applications of ferrofluid pumps, we employed optical methods to record the dynamic morphological transformation of rotating and fixed ferrofluids under different magnetic field polarities, magnetic field distributions, and ferrofluid mass fractions. The magnetic field polarity causes dynamic differences in the fusion-separation process of the ferrofluid but does not affect the volume segmentation of the ferrofluid, which depends on the ratio of the magnetic field intensities. When this ratio deviates from one, the morphology of ferrofluid changes, reducing the pumping efficiency. Compared to external environmental factors, the mass fraction does not change the morphology of the ferrofluid. However, high mass fractions lead to wall-clinging of the ferrofluid, and low mass fractions induce bubbles, both of which detrimentally affect the pumping performance. This study reveals the properties of ferrofluid and the effects of external environmental conditions on the morphological transformation of ferrofluid, providing references for optimizing ferrofluid pumps.

This study aims to establish a cost basis for biologics manufacturers and policymakers by quantifying the price and time required to bring a biosimilar from the lab to market. For efficient implementation of a cost-based policy, especially for life-saving medicines like biosimilars, it is imperative to establish a benchmark for the cost involved in biosimilar development. In this holistic and multiple-case study, stage-wise cost estimates of biosimilar development were obtained for microbial and mammalian systems. The investigation of six biopharmaceutical companies based in India concluded that biosimilar development through the microbial system costs ∼18 million USD and ∼21 million USD for the mammalian system. Additionally, 45–50 million USD is required as a one-time capital investment. Further, US/EU authorization can cost ∼25 million USD per product. Clinical studies are the most expensive and account for 60%–70% of total development cost. The presented information can serve as a basis for implementing cost-based pricing in countries like India and reimbursement policies for biosimilars under Medicare Part B in the United States.

This study provides a comprehensive review of the literature on climate risk insurance modeling to identify lessons learned and knowledge gaps to be addressed by future research. These models are increasingly relevant due to the rising losses attributable to climate change. Insurance models estimate risk for different perils and simulate risk-related parameters for insurance schemes, such as premiums and deductibles. Most forward-looking models indicate that climate change and socioeconomic developments highly exacerbate future risk and increase insurance premiums. Various studies recommend charging risk-based premiums to incentivize adaptation efforts that limit this increase in climate risks. Other findings point toward introducing public–private insurance to cope with climate change and enhance risk spreading by introducing insurance purchase requirements or insurance products that cover multiple climate risks. Gaps that we identify in this literature include an underrepresentation of insurance assessments for developing countries and for hazards other than flooding. Additionally, we note a lack of research into insurance for non-agricultural commercial sectors. Furthermore, less than half of the studies take a forward-looking approach by incorporating climate change scenarios, and an even smaller percentage consider socioeconomic development scenarios. This limitation shows that current methods require additional development for assessing the effects of future climate risk on insurance. We recommend that future research develops such forward-looking models, considers using a more refined spatial scale, broadens geographical and hazard coverage, and includes the commercial sector.

Wax deposition in constant-temperature transportation of waxy oil with high pour points poses a significant challenge for the oil industry. The demand for efficient methods to solve wax deposition has gained attention. To elucidate the impact of emulsion-based wax inhibitors on the performance of crude oils with varying wax content at low temperatures, experiments, rheological analyses, and microscopic analyses were conducted to study their pour point regulation, low-temperature flow improvement, wax prevention effectiveness, and wax crystallization behavior. The results indicate that emulsion-based wax inhibitors significantly reduce the pour point of crude oil, especially for high-wax-content oil, while for low-wax-content oil, the pour point only decreased by 3°C. By penetrating and dispersing wax crystals, the inhibitor reduced the viscosity of crude oil at low temperatures, enhancing its flowability. At 28°C, crude oil transitioned from a shear-thinning non-Newtonian fluid to a Newtonian fluid at wax inhibitor dosages of 500−750 ppm. At 1000 ppm, the wax prevention rate for high-wax-content oil reached 87.5%, but the effect plateaued beyond this concentration. Additionally, the wax prevention and removal mechanism of the emulsion-based wax inhibitors is discussed. This study confirms that emulsion-based wax inhibitors significantly enhance the low-temperature processability of crude oil, offering a viable strategy for the conveyance and refinement in cold climates.

This single-blind randomized crossover study aimed to explore the effectiveness of virtual reality–based music attention training (VR-MAT) on cognitive function and examine its potential as a cognitive assessment tool in people with acquired brain injury (ABI). Overall, 24 participants with cognitive impairment secondary to a first-ever ABI underwent VR-MAT and conventional cognitive training (CCT) 3 months after onset. This was performed in two 4-week phases, over 8 weeks. During VR-MAT, participants engaged in attention training through a four-level virtual drumming program designed to enhance various attentional aspects. In contrast, during CCT, participants underwent structured conventional training, including card sorting and computerized training. Neuropsychological evaluations were performed preintervention, during the fourth and eighth weeks, and post-intervention using tests to evaluate attention and executive function, along with global neuropsychological assessments. In the VR-MAT group, significant differences were observed between pre- and post-intervention in the trail making test-black and white version B (p = 0.009) and version B–A (p = 0.018) and clinical dementia rating-sum of boxes (p = 0.035). In the CCT group, significant differences were observed in spatial working memory (p = 0.005) and the mini-mental state examination scores (p = 0.003). VR-MAT is an effective cognitive intervention that is particularly beneficial for improving attention in people with ABI.

Brain imaging studies have reported that the neural deficits of congenital amusia in non-tonal language speakers are mainly in the connectivity between the auditory cortex and the inferior frontal gyrus (IFG) in the right hemisphere. However, the relationship between the functional connectivity (FC) in these regions and the music perception ability of amusia in tonal language speakers remains unclear. In this study, we investigated the FC characteristics of amusia in Mandarin speakers in resting-state functional magnetic resonance imaging data by voxel-wise connectivity analyses with seeds in left and right Heschl's gyri (HG) and region of interest (ROI)-to-ROI connectivity analyses. Our findings indicate increased connectivity between right HG and bilateral posterior superior temporal gyrus, as determined by voxel-wise connectivity analyses in amusia. Conversely, reduced connectivity was observed between bilateral HG and bilateral IFG (orbital part) as assessed through ROI-to-ROI connectivity analyses in amusia when compared to controls. Moreover, the music perception scores of amusia in Mandarin speakers were associated with diminished connectivity between the left HG and the right IFG. This study furnishes direct evidence for the link between music perception deficits and the aberrant frontotemporal connectivity of congenital amusia in tonal language speakers in resting state.

This paper presents a novel hybrid approach for the probabilistic reconstruction of meteorological fields based on the combined use of the analogue method (AM) and deep autoencoders (AEs). The AE–AM algorithm trains a deep AE in the predictor fields, which the encoder filters towards a compressed space of reduced dimensionality. The AM is then applied in this latent space to find similar situations (analogues) in the historical record, from which the target field can be reconstructed. The AE–AM is compared to the classical AM, in which flow analogues are explicitly searched in the fully resolved field of the predictor, which may contain useless information for the reconstruction. We evaluate the performance of these two approaches in reconstructing the daily maximum temperature (target) from sea-level pressure fields (predictor) recorded during eight major European heat waves of the 1950–2010 period. We show that the proposed AE–AM approach outperforms the standard AM algorithm in reconstructing the magnitude and spatial pattern of the considered heat wave events. The improvement ranges from 7% to 22% in skill score, depending on the heat wave analyzed, demonstrating the potential added value of the hybrid method.

Nano Al₃Ti-TiB₂-AlN-TiN/Al inoculant ribbons containing a large number of evenly distributed nanoparticles, such as Al₃Ti (sized about 300 nm), TiB₂ (sized about 100 nm), AlN (sized about 150 nm), and TiN (sized about 200 nm), were prepared by vacuum rapid quenching furnace to refine AlZnMgCu alloys. The nano Al₃Ti-TiB₂-AlN-TiN/Al inoculant ribbons showed an excellent inoculant effect, which modified the dendrite crystals to equiaxed crystals and refined the grains from 122 ± 4 µm to 36 ± 5 µm by the addition of 0.3 wt% nano Al₃Ti-TiB₂-AlN-TiN/Al inoculant ribbons. In addition to nano Al₃Ti and TiB₂ particles, nano AlN and TiN particles also have a certain orientation relationship with α-Al, which suggests that these particles possess nucleation potency to α-Al. After inoculation with 0.3% nano Al₃Ti-TiB₂-AlN-TiN/Al inoculant ribbons, the ultimate tensile strength, yield strength, and average microhardness of the AlZnMgCu alloys increased from 246 MPa, 79 MPa, and 112 HV to 319 MPa, 100 MPa, and 136 HV, or by 29.7%, 26.6% and 21.4%, respectively.