bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Light Weight Depthwise Separable Layer Optimized CNN Architecture for Object-Based Forgery Detection in Surveillance Videos
Authors: Sandhya  , Kashyap Abhishek 
Published: January 2024

AbstractThe present era is at the peak of technological advancement in image and video processing techniques, with user-friendly accessible tools/techniques. This immersive technology development makes video forensics enormously challenging. Specifically, the passive approaches to object-based forgeries in videos are crucial for legal and judicial matters. Hence, to ensure the integrity of the videos, a scientific, statistical and passive investigation of videos is required to maintain the spatial and temporal information content. This paper aims to develop a passive approach for digging out the forgery traces by applying the motion residue windowing technique for object removal forgery in surveillance videos. The novel max averaging windowing techniques improve visual imprints of the object removal forgery in the videos from the existing methods in the literature. A deep learning approach is the next step for achieving forgery detection in surveillance videos. The proposed lightweight depth-separable layer-optimized CNN has fast execution speed, optimized in terms of parameters without compromising the desired accuracy. This network is trained at a frame level with 98.60% testing accuracy, followed by a pipeline architecture of the proposed model for detection of forgery at video level with 99.01% accuracy. The suggested model works better than current models regarding post-processing operations, compression rates, forged video detection accuracy, precision, recall and F1 score.
Bank lending policies and monetary policy: some lessons from the negative interest era
Authors: Arce Oscar , García-Posada Miguel , Mayordomo Sergio , Ongena Steven 
Published: January 2024

Abstract
What is the long-term impact of negative interest rates on bank lending? To answer this question, we construct a unique summary measure of negative rate exposure by individual banks based on exclusive survey data and banks’ balance sheets and couple it with the credit register of Spain and firms’ balance sheets to identify this impact on the supply of credit to firms. We find that only when deposit rates reached the zero lower bound did affected banks (relative to non-affected banks) decrease their supply, especially when undercapitalized and lending to risky firms. The adverse effects of the negative rates on banks’ intermediation capacity only took place after a protracted period of time.
Does information reduce interpersonal violence? Evidence from prisons
Authors: Szekely Aron 
Published: January 2024

Abstract
Why does interpersonal violence erupt? A key source is conflict over resources and a little-studied mechanism for solving such cases concerns the availability of credible information about individuals’ abilities and willingness to use force. Its core prediction is that when such credible information abounds, the outcome of a potential struggle can be anticipated and thus there is no need to fight. I test this prediction using a nationally representative survey of male prisoners (Ninmates = 10,768, Nfacilities = 207) incarcerated in US state correctional facilities. I also make two methodologically orientated contributions. First, recent research highlights the important consequences that data analysis choices can have in determining quantitative findings. To overcome this, I draw on multiverse analysis and specification curve analysis to map out the key analytical decisions I make and run 262,144 plausible regression models. By doing so, I classify associations that are robust, mixed, or entirely frail according to analytic decisions and find partial support for the informational mechanism of interpersonal violence. Second, in contrast to much quantitative prison research, which uses only official or institutionally punished assaults data, I compare self-recognized fights to self-reported institutionally punished fights and highlight key differences.
Cannabis for chronic pain: cardiovascular safety in a nationwide Danish study
Authors: Holt Anders , Nouhravesh Nina , Strange Jarl E , Kinnberg Nielsen Sebastian , Schjerning Anne-Marie , Vibe Rasmussen Peter , Torp-Pedersen Christian , Gislason Gunnar H , Schou Morten , McGettigan Patricia , Lamberts Morten 
Published: January 2024

Abstract

Background and Aims
A rising number of countries allow physicians to treat chronic pain with medical cannabis. However, recreational cannabis use has been linked with cardiovascular side effects, necessitating investigations concerning the safety of prescribed medical cannabis.

Methods
Using nationwide Danish registers, patients with chronic pain initiating first-time treatment with medical cannabis during 2018–21 were identified and matched 1:5 to corresponding control patients on age, sex, chronic pain diagnosis, and concomitant use of other pain medication. The absolute risks of first-time arrhythmia (atrial fibrillation/flutter, conduction disorders, paroxysmal tachycardias, and ventricular arrhythmias) and acute coronary syndrome were reported comparing medical cannabis use with no use.

Results
Among 1.88 million patients with chronic pain (46% musculoskeletal, 11% cancer, 13% neurological, and 30% unspecified pain), 5391 patients claimed a prescription of medical cannabis [63.2% women, median age: 59 (inter-quartile range 48–70) years] and were compared with 26 941 control patients of equal sex- and age composition. Arrhythmia was observed in 42 and 107 individuals, respectively, within 180 days. Medical cannabis use was associated with an elevated risk of new-onset arrhythmia {180-day absolute risk: 0.8% [95% confidence interval (CI) 0.6%–1.1%]} compared with no use [180-day absolute risk: 0.4% (95% CI 0.3%–0.5%)]: a risk ratio of 2.07 (95% CI 1.34–2.80) and a 1-year risk ratio of 1.36 (95% CI 1.00–1.73). No significant association was found for acute coronary syndrome [180-day risk ratio: 1.20 (95% CI 0.35–2.04)].

Conclusions
In patients with chronic pain, the use of prescribed medical cannabis was associated with an elevated risk of new-onset arrhythmia compared with no use—most pronounced in the 180 days following the initiation of treatment.
Toward greater realism in inclusive fitness models: the case of caste fate conflict in insect societies
Authors: Ferreira Helena Mendes , Alves Denise Araujo , Cool Lloyd , Oi Cintia Akemi , Oliveira Ricardo Caliari , Wenseleers Tom 
Published: January 2024

Abstract
In the field of social evolution, inclusive fitness theory has been successful in making a wide range of qualitative predictions on expected patterns of cooperation and conflict. Nevertheless, outside of sex ratio theory, inclusive fitness models that make accurate quantitative predictions remain relatively rare. Past models dealing with caste fate conflict in insect societies, for example, successfully predicted that if female larvae can control their own caste fate, an excess should opt to selfishly develop as queens. Available models, however, were unable to accurately predict levels of queen production observed in Melipona bees—a genus of stingless bees where caste is self-determined—as empirically observed levels of queen production are approximately two times lower than the theoretically predicted ones. Here, we show that this discrepancy can be resolved by explicitly deriving the colony-level cost of queen overproduction from a dynamic model of colony growth, requiring the incorporation of parameters of colony growth and demography, such as the per-capita rate at which new brood cells are built and provisioned, the percentage of the queen’s eggs that are female, costs linked with worker reproduction and worker mortality. Our revised model predicts queen overproduction to more severely impact colony productivity, resulting in an evolutionarily stable strategy that is approximately half that of the original model, and is shown to accurately predict actual levels of queen overproduction observed in different Melipona species. Altogether, this shows how inclusive fitness models can provide accurate quantitative predictions, provided that costs and benefits are modeled in sufficient detail and are measured precisely.
Modeling a new taper curve and form factor of tree branches using terrestrial laser scanning
Authors: Bazezew Muluken N , Fehrmann Lutz , Kleinn Christoph , Nölke Nils 
Published: January 2024

Abstract
Modeling branch taper curve and form factor contributes to increasing the efficiency of tree crown reconstructions: the branch taper, defined as the sequential measure of diameters along the course of the branch, is pivotal to accurately estimate key branch variables such as biomass and volume. Branch diameters or volumes have commonly been estimated from terrestrial laser scanning (TLS) based on automatized voxelization or cylinder-fitting approaches, given the whole branch length is sufficiently covered by laser reflections. The results are, however, often affected by ample variations in point cloud characteristics caused by varying point density, occlusions, and noise. As these characteristics of TLS can hardly be sufficiently controlled or eliminated in automatized techniques, we proposed a new branch taper curve model and form factor, which can be employed directly from the laser reflections and under variable point cloud characteristics. In this paper, the approach is demonstrated on primary branches using a set of TLS-derived datasets from a sample of 20 trees (six species). The results showed an R2 of 0.86 and a mean relative absolute error of 1.03 cm (29%) when validated with field-measured diameters. The approach improved the accuracy of diameter estimates for the fine branch scales (&lt;10 cm) as compared to the quantitative structural model (QSM). Our approach also allowed branch diameter estimation for a relatively larger number of manually recognized primary branches (&gt;85%) from point clouds when validated with panoramic images acquired simultaneously with laser scanning. Frequently used automatized crown reconstructions from QSM, on the other hand, were affected by gaps in the point clouds due to obstruction, with the crown-tops and finer branches being the most critical. Our approach reports mean form factors across the examined species of 0.35 and 0.49, with the diameters determined at 5% and 10% of the total branch length, respectively. Our approach may have the potential to produce branch volume information with reasonable accuracy from only knowing the length and respective diameter of each branch. Our model delivers a first approximation for the taper curve and form factor for primary branches but was developed on a relatively small set of samples. We believe that our approach holds the potential to improve the accuracy of the assessment of branch diameter and volume from TLS data. The approach may also be extended to other branch orders. This could expand the horizon for volumetric calculations and biomass estimates from non-destructive TLS proxies in tree crowns.
Inhibitory effect and mechanism of tannic acid against two starch digestive enzymes
Authors: Zhong Yuxiu , Ni Derang , Yang Yubo , Li Yuanyi , Wang Li , Tian Jinhu , Yang Fan , Ye Xingqian 
Published: January 2024

Abstract

Backgrounds
Tannic acid (TA), as a plant-derived phenolic substance, is involved in regulating the activity of starch digestive enzymes, but its underlying mechanism remains unclear.

Methods and Results
In the present study, inhibition rate and inhibition kinetics assays were performed and confirmed that TA had a strong inhibitory effect on both α-amylase and α-glucosidase with IC50 values of 0.1585 mg/mL and 0.00542 mg/mL, respectively, through a mixed inhibition mode. The secondary structures of both enzymes were confirmed to be modified by TA through circular dichroism (CD) spectra. Fluorescence quenching analysis revealed that the interaction between TA and two enzymes was a static process of pontaneous complex formation. Finally, molecular docking revealed that non-covalent bonds were the main interaction forces between TA and both enzymes.

Conclusions
Thus, TA was a promising candidate for the inhibition of starch-digesting enzymes, and the present research provided insight into postprandial glucose regulation through polyphenols.
Research on likelihood ratio evaluation method of fingerprint evidence based on parameter estimation method
Authors: Li Kang , Han Yishi , Luo Yaping 
Published: January 2024

Abstract

Fingerprints with similar morphological characteristics but from different individuals can lead to errors in individual identification, especially when dealing with large databases containing millions of fingerprints. To address this issue and enhance the accuracy of similar fingerprint identification, the use of the likelihood ratio (LR) model for quantitative evaluation of fingerprint evidence has emerged as an effective research method. In this study, the LR fingerprint evidence evaluation model was established by using mathematical statistical methods, such as parameter estimation and hypothesis testing. This involved various steps, including database construction, scoring, fitting, calculation, and visual evaluation. Under the same-source conditions, the optimal parameter methods selected by different number of minutiae are gamma and Weibull distribution, while normal, Weibull, and lognormal distributions were the fitting parameters selected for minutiae configurations. The fitting parameters selected by different number of minutiae under different-source conditions are lognormal distribution, and the parameter methods selected for different minutiae configurations include Weibull, gamma, and lognormal distributions. The results of the LR model showed increased accuracy as the number of minutiae increased, indicating strong discriminative and corrective power. However, the accuracy of the LR evaluation based on different configurations was comparatively lower. In addition, the LR models with different numbers of minutiae outperformed those with different minutiae configurations. Our study shows that the use of LR models based on parametric methods is favoured in reducing the risk of fingerprint evidence misidentification, improving the quantitative assessment methods of fingerprint evidence, and promoting fingerprint identification from experience to science.

Key points
Understanding Experiences of Caregivers of Spouses With Dementia During Caregiver Health Care Emergencies
Authors: Daddato Andrea E , Gleason Kathy S , Dollar Blythe A , McPhail Tobie E , Kraus Courtney R , Boxer Rebecca S 
Published: January 2024

Abstract

Background and Objectives
Caregivers of persons with dementia are frequently spouses. Caregiver hospitalization causes disruption to caregiving. The goal of this research was to understand the preparedness and stress trajectory of peri-caregiver hospitalization.

Research Design and Methods
Mixed methods were used. Caregivers of spouses with dementia (n = 1,000) were surveyed to determine their perceived preparedness for their own hospitalization. Journey mapping interviews (n = 18) were used to map caregivers’ experiences during 5 phases: (a) their spouse with dementia (SWD)’s dementia diagnosis; (b) their SWD’s dementia progression; (c) their own health event; (d) their own hospitalization; and (e) their own return home from the hospital.

Results
Among the 452 (45%) eligible caregiver survey respondents, 75 (17%) had experienced hospitalization in the previous 12 months and 51 (68%) hospitalizations were unexpected. Twenty-three (31%) of hospitalized caregivers indicated they did not have prior plans in place for the care of the SWD. When asked about an unexpected hospitalization in the future, 233 (52%) felt somewhat prepared and 133 (29%) felt not at all prepared. Journey mapping revealed 3 groups of caregivers: Group 1 (n = 7) rated their stress lower during their hospitalization, Group 2 (n = 7) rated their stress highest during their hospitalization, and Group 3 (n = 4) were at a sustained high-stress level.

Discussion and Implications
Many caregivers are not prepared for their own hospitalization. The stress trajectory through important phases of dementia caregiving and a caregiver’s own hospitalization is not universal. Meeting the needs of caregivers’ peri-hospitalization should be tailored to the individual caregiver.
Effect of message framing on support for a sugar-sweetened beverage tax in Australia: a cross-sectional survey analysis
Authors: Cullerton Katherine , Demeshko Anastassia , Waller Michael 
Published: January 2024

Abstract
Sugar-sweetened beverage (SSB) taxes are present in many countries with evidence that they are effective in decreasing purchases of SSBs. However, in Australia where SSB consumption per capita is high, and calls for an SSB tax are frequent, there is no SSB tax and policymakers have stated their lack of support for such a tax. We examined whether political party voting preference and sociodemographic factors affect individuals’ support for an SSB tax, and whether message framing affects this support. A nationally representative sample of 1519 Australian adults was recruited for an online experimental survey. Three persuasive frames and one control frame were randomly provided to participants and measures of agreement towards an SSB tax were assessed. Sociodemographic factors and political party preference were also captured. Message framing had minimal effect on the level of support for the tax. However, participants who received the ‘supportive of food and drink companies frame’ showed the highest positive feelings towards the tax, and participants in rural areas had higher levels of support for an SSB tax when receiving the ‘protecting teenagers’ frame. Participants who voted for conservative (right-leaning) parties and for Labour (a centre-left party) had similar levels of support towards the tax, which was considerably lower than Greens voters. Undecided voters had the lowest levels of support for the tax, and the frames had limited impact on them. These findings highlight the potential role of message framing in shaping public support for an SSB tax in Australia, particularly in the context of voting preference and sociodemographic factors.
Flowering genes identification, network analysis, and database construction for 837 plants
Authors: Wu Tong , Liu Zhuo , Yu Tong , Zhou Rong , Yang Qihang , Cao Rui , Nie Fulei , Ma Xiao , Bai Yun , Song Xiaoming 
Published: January 2024

Abstract
Flowering is one of the most important biological phenomena in the plant kingdom, which not only has important ecological significance, but also has substantial horticultural ornamental value. In this study, we undertook an exhaustive review of the advancements in our understanding of plant flowering genes. We delved into the identification and conducted comparative analyses of flowering genes across virtually all sequenced angiosperm plant genomes. Furthermore, we established an extensive angiosperm flowering atlas, encompassing a staggering 183 720 genes across eight pathways, along with 10 155 ABCDE mode genes, which play a pivotal role in plant flowering regulation. Through the examination of expression patterns, we unveiled the specificities of these flowering genes. An interaction network between flowering genes of the ABCDE model and their corresponding upstream genes offered a blueprint for comprehending their regulatory mechanisms. Moreover, we predicted the miRNA and target genes linked to the flowering processes of each species. To culminate our efforts, we have built a user-friendly web interface, named the Plant Flowering-time Gene Database (PFGD), accessible at http://pfgd.bio2db.com/. We firmly believe that this database will serve as a cornerstone in the global research community, facilitating the in-depth exploration of flowering genes in the plant kingdom. In summation, this pioneering endeavor represents the first comprehensive collection and comparative analysis of flowering genes in plants, offering valuable resources for the study of plant flowering genetics.
How do kernel-based sensor fusion algorithms behave under high-dimensional noise?
Authors: Ding Xiucai , Wu Hau-Tieng 
Published: January 2024

Abstract
We study the behavior of two kernel based sensor fusion algorithms, nonparametric canonical correlation analysis (NCCA) and alternating diffusion (AD), under the nonnull setting that the clean datasets collected from two sensors are modeled by a common low-dimensional manifold embedded in a high-dimensional Euclidean space and the datasets are corrupted by high-dimensional noise. We establish the asymptotic limits and convergence rates for the eigenvalues of the associated kernel matrices assuming that the sample dimension and sample size are comparably large, where NCCA and AD are conducted using the Gaussian kernel. It turns out that both the asymptotic limits and convergence rates depend on the signal-to-noise ratio (SNR) of each sensor and selected bandwidths. On one hand, we show that if NCCA and AD are directly applied to the noisy point clouds without any sanity check, it may generate artificial information that misleads scientists’ interpretation. On the other hand, we prove that if the bandwidths are selected adequately, both NCCA and AD can be made robust to high-dimensional noise when the SNRs are relatively large.
Prevalence and Phenotypic Susceptibility to Doravirine of the HIV-1 Reverse Transcriptase V106I Polymorphism in B and Non-B Subtypes
Authors: Giammarino Federica , de Salazar Adolfo , Malet Isabelle , Viñuela Laura , Fuentes Ana , Saladini Francesco , Bartolini Niccolò , Charpentier Charlotte , Lambert-Niclot Sidonie , Sterrantino Gaetana , Colao Maria Grazia , Micheli Valeria , Bertoli Ada , Fabeni Lavinia , Teyssou Elisa , Delgado Rafael , Falces-Romero Iker , Aguilera Antonio , Gomes Perpetua , Paraskevis Dimitrios , Santoro Maria M , Ceccherini-Silberstein Francesca , Marcelin Anne-Genevieve , Moreno Cristina , Zazzi Maurizio , García Federico 
Published: January 2024

Abstract

Background
Limited data are available regarding the susceptibility of the reverse transcriptase V106 polymorphism to doravirine.

Methods
Doravirine susceptibility was measured in site-directed mutants (SDMs) containing V106I, V106A, V106M, and Y188L mutations in subtype B (NL4-3, HXB2) and CRF02_AG background and in recombinant viruses with RT harboring V106I alone derived from 50 people with HIV.

Results
HIV-1 B subtype was detected in 1523 of 2705 cases. Prevalence of V106I was 3.2% in B and 2.5% in non-B subtypes, and was higher in subtype F (8.1%) and D (14.3%). Fold-changes (FC) in susceptibility for SDMs were below doravirine biological cutoff (3.0) for V106I, but not for V106A, V106M, and Y188L. Clinically derived viruses tested included 22 B (median FC, 1.2; interquartile range [IQR], 0.9–1.6) and 28 non-B subtypes (median FC, 1.8; IQR, 0.9–3.0). Nine (18%) viruses showed FC values equal or higher than the doravirine biological FC cutoff.

Conclusions
The prevalence of the HIV-1 RT V106I polymorphism in MeditRes HIV consortium remains low, but significantly more prevalent in subtypes D and F. V106I minimally decreased the susceptibility to doravirine in SDMs and most clinical isolates. Reduced susceptibility seems to occur at increased frequency in subtype F1; however, the clinical impact remains to be investigated.

Clinical Trials Registration
NCT04894357.