Miracle-dz/UniFAR-FTUs huggingface dataset:
DaGAN++: Depth-Aware Generative Adversarial Network for Talking Head Video Generation

Predominant techniques on talking head generation largely depend on 2D information, including facial appearances and motions from input face images. Nevertheless, dense 3D facial geometry, such as pixel-wise depth, plays a critical role in constructing accurate 3D facial structures and suppressing complex background noises for generation. However, dense 3D annotations for facial videos is prohibitively costly to obtain. In this work, firstly, we present a novel self-supervised method for learning dense 3D facial geometry (i.e., depth) from face videos, without requiring camera parameters and 3D geometry annotations in training. We further propose a strategy to learn pixel-level uncertainties to perceive more reliable rigid-motion pixels for geometry learning. Secondly, we design an effective geometry-guided facial keypoint estimation module, providing accurate keypoints for generating motion fields. Lastly, we develop a 3D-aware cross-modal (i.e., appearance and depth) attention mechanism, which can be applied to each generation layer, to capture facial geometries in a coarse-to-fine manner. Extensive experiments are conducted on three challenging benchmarks (i.e., VoxCeleb1, VoxCeleb2, and HDTF). The results demonstrate that our proposed framework can generate highly realistic-looking reenacted talking videos, with new state-of-the-art performances established on these benchmarks. The codes and trained models are publicly available on the GitHub project page.
Hippocampal motor memory network reorganization depends on familiarity, not time

There is debate as to whether a time-dependent transformation of the episodic-like memory network is observed for nonepisodic tasks, including procedural motor memory. To determine how motor memory networks reorganize with time and practice, mice performed a motor task in a straight alley maze for 1 d (recent), 20 d of continuous training (continuous), or testing 20 d after the original training (remote), and then regional c-Fos expression was assessed. Elevated hippocampal c-Fos accompanied remote, but not continuous, motor task retrieval after 20 d, suggesting that the hippocampus remains engaged for nonhabitual remote motor memory retrieval.
Dynamic, sex‐ and diet‐specific pleiotropism in the PAC1 receptor‐mediated regulation of arcuate proopiomelanocortin and Neuropeptide Y/Agouti related peptide neuronal excitability by anorexigenic ventromedial nucleus PACAP neurons

This study furthers the investigation of how pituitary adenylate cyclase activating polypeptide (PACAP) and the PAC1 receptor (PAC1R) regulate the homeostatic energy balance circuitry. We hypothesized that apoptotic ablation of PACAP neurones in the hypothalamic ventromedial nucleus (VMN) would affect both energy intake and energy expenditure. We also hypothesized that selective PAC1R knockdown would impair the PACAP‐induced excitation in anorexigenic proopiomelanocortin (POMC) neurones and inhibition of orexigenic neuropeptide Y (NPY)/agouti‐related peptide (AgRP) neurones in the hypothalamic arcuate nucleus (ARC). The results show CASPASE‐3‐induced ablation of VMN PACAP neurones leads to increased energy intake and meal frequency as well as decreased energy expenditure in lean animals. The effects were more robust in obese males, whereas we saw the opposite effects in obese females. We then utilized visualized whole‐cell patch clamp recordings in hypothalamic slices. PAC1R knockdown in POMC neurones diminishes the PACAP‐induced depolarization, increase in firing, decreases in energy intake and meal size, as well as increases in CO2 production and O2 consumption. Similarly, the lack of expression of the PAC1R in NPY/AgRP neurones greatly attenuates the PACAP‐induced hyperpolarization, suppression of firing, decreases in energy intake and meal frequency, as well as increases in energy expenditure. The PACAP response in NPY/AgRP neurones switched from predominantly inhibitory to excitatory in fasted animals. Finally, the anorexigenic effect of PACAP was potentiated when oestradiol was injected into the ARC in ovariectomized females. This study demonstrates the critical role of anorexigenic VMN PACAP neurones and the PAC1R in exciting POMC and inhibiting NPY/AgRP neurons to control homeostatic feeding.
When Age Tips the Balance: a Dual Mechanism Affecting Hemispheric Specialization for Language

Aging leads to neuroadaptations, often reducing specificity in functional brain responses. However, the extent to which functional specialization of brain hemispheres in the Language-and-Memory Network regions changes with adulthood remains unclear. In a cohort of healthy adults, we provide evidence that aging is linked to shifts in the cortical organization’s lateralization, unveiling two age-related asymmetry patterns. The first pattern indicates a lateralization shift in language regions, with aging rendering language functions more bilateral. The second pattern reveals increased specialization in memory regions within the left hemisphere as we age. Manifesting around midlife, these shifts correlate with declines in language production performance. Our findings offer new insights into how functional brain asymmetries impact language proficiency and underscore brain plasticity in aging, providing a dynamic view of the aging brain’s functional architecture.
Four minutes of capacitive and resistive electric transfer therapy increased jump performance

ABSTRACT Capacitive and resistive electric transfer (CRET) therapy can improve flexibility and increase muscle activity and may be useful as a warm-up technique. This study examined the effects of short-time CRET on jump performance. Thirty healthy men (age range, 20–40 years) were randomly divided into passive (n = 15) and active (n = 15) warm-up groups. The participants and statisticians were blinded to the participant allocation. The passive warm-up group underwent 4 min of CRET therapy on their posterior lower legs. The active warm-up group performed stretching and jogging for 4 min. Calf muscle temperature and rebound jump (RJ) index were measured before and after the intervention. The mean (± standard deviation) muscle temperature increased by 2.0 ± 0.5°C and 1.4 ± 0.6°C in the passive and active warm-up groups, respectively (p < 0.05). RJ index increased significantly in both groups (p < 0.05). Therefore, passive warm-up using CRET may help avoid energy loss while increasing the muscle temperature in a short time when compared with traditional active warm-up techniques. Plain Language Summary Capacitive and resistive electric transfer (CRET) is a device with deep thermal effect. CRET therapy can improve flexibility and increase muscle activity and may be useful as a warm-up technique. This study examined the effects of short-time CRET on jump performance. Thirty healthy men (age range, 20–40 years) were randomly divided into passive (n=15) and active (n=15) warm-up groups. The passive warm-up group underwent 4min of CRET therapy on their calf. The active warm-up group performed stretching and jogging for 4min. Calf muscle temperature and jump performance were measured before and after the intervention. The mean (± standard deviation) muscle temperature increased by 2.0±0.5°C and 1.4±0.6°C in the passive and active warm-up groups, respectively (p<0.05). Jump performance increased significantly in both groups (p<0.05). Therefore, passive warm-up using CRET may help avoid energy loss while increasing the muscle temperature in a short time when compared with traditional active warm-up techniques.
Pop-Stack Operators for Torsion Classes and Cambrian Lattices

The pop-stack operator of a finite lattice $L$ is the map $\mathrm{pop}^{\downarrow}_L\colon L\to L$ that sends each element $x\in L$ to the meet of $\{x\}\cup\text{cov}_L(x)$, where $\text{cov}_L(x)$ is the set of elements covered by $x$ in $L$. We study several properties of the pop-stack operator of $\mathrm{tors}\Lambda$, the lattice of torsion classes of a $\tau$-tilting finite algebra $\Lambda$ over a field $K$. We describe the pop-stack operator in terms of certain mutations of 2-term simple-minded collections. This allows us to describe preimages of a given torsion class under the pop-stack operator. We then specialize our attention to Cambrian lattices of a finite irreducible Coxeter group $W$. Using tools from representation theory, we provide simple Coxeter-theoretic and lattice-theoretic descriptions of the image of the pop-stack operator of a Cambrian lattice (which can be stated without representation theory). When specialized to a bipartite Cambrian lattice of type A, this result settles a conjecture of Choi and Sun. We also settle a related enumerative conjecture of Defant and Williams. When $L$ is an arbitrary lattice quotient of the weak order on $W$, we prove that the maximum size of a forward orbit under the pop-stack operator of $L$ is at most the Coxeter number of $W$; when $L$ is a Cambrian lattice, we provide an explicit construction to show that this maximum forward orbit size is actually equal to the Coxeter number.
Difference in tissue temperature change between two cryoballoons

Background Cryoballoon ablation, especially Arctic Front Advance Pro (AFA-Pro) (Medtronic, Minneapolis, Minnesota, USA), has been widely recognised as a standard approach to atrial fibrillation (AF). Recently, Boston Scientific has released a novel cryoballoon system (POLARx). Despite comparable acute clinical outcomes of these two cryoballoons, the recent study reported a higher complication rate, especially for phrenic nerve palsy, with POLARx. However, their impact on biological tissue remains unclear. Objective The purpose of our study is to evaluate temperature change of biological tissue during cryoablation of each cryoballoon using a porcine experimental model. Method A tissue-based pulmonary vein model was constructed from porcine myocardial tissue and placed on a stage designed to simulate pulmonary vein anatomy and venous flow. Controlled cryoablations of AFA-Pro and POLARx were performed in this model to evaluate the tissue temperature. A temperature sensor was set behind the muscle and cryoballoon ablation was performed after confirming the occlusion of pulmonary vein with cryoballoon. Results The mean tissue nadir temperature during cryoablation with AFA-Pro was −41.5°C±4.9°C, while the mean tissue nadir temperature during cryoablation with POLARx was −58.4°C±5.9°C (p<0.001). The mean balloon nadir temperature during cryoablation with AFA-Pro was −54.6°C±2.6°C and the mean balloon nadir temperature during cryoablation with POLARx was −64.7°C±3.8°C (p<0.001). Conclusion POLARx could freeze the biological tissue more strongly than AFA-Pro.
AVID: Any-Length Video Inpainting with Diffusion Model

Recent advances in diffusion models have successfully enabled text-guided image inpainting. While it seems straightforward to extend such editing capability into the video domain, there have been fewer works regarding text-guided video inpainting. Given a video, a masked region at its initial frame, and an editing prompt, it requires a model to do infilling at each frame following the editing guidance while keeping the out-of-mask region intact. There are three main challenges in text-guided video inpainting: ($i$) temporal consistency of the edited video, ($ii$) supporting different inpainting types at different structural fidelity levels, and ($iii$) dealing with variable video length. To address these challenges, we introduce Any-Length Video Inpainting with Diffusion Model, dubbed as AVID. At its core, our model is equipped with effective motion modules and adjustable structure guidance, for fixed-length video inpainting. Building on top of that, we propose a novel Temporal MultiDiffusion sampling pipeline with a middle-frame attention guidance mechanism, facilitating the generation of videos with any desired duration. Our comprehensive experiments show our model can robustly deal with various inpainting types at different video duration ranges, with high quality. More visualization results are made publicly available at https://zhang-zx.github. io/AVID/ .
Quality by design approach in the formulation of vaginal tablet of fluconazole solid dispersion

Abstract Vaginal Candidiasis had caused quite frequent gynecological medical consultations. Fluconazole is an antifungal drug that has poor solubility that hinders dissolution and antifungal activity. The study aimed to formulate the sustained release vaginal tablet of Fluconazole solid dispersion through the Design of Experiment approach to guarantee no compromise with the quality. In the first step, Plackett Burman Design was employed for the preliminary screening of the essential factors that would affect the tablet’s property. The significant factors were used further in applying the 32 factorial design and the responses were studied. The drug release, bioadhesive strength and swelling index were taken as the responses and considered as the vital critical quality attributes of the vaginal tablet. The design space was determined through the contour and response surface plots. The tablet was prepared within the design space with the drug release (99.97±0.1%), bioadhesive strength (1671.62±43.23 dynes/cm2), and swelling index (342.47±5 %) that suggested the values lie within the quality target product profile determined previously. The antifungal activity against C. albicans resulted in a larger inhibition zone for the solid dispersion-based tablet (51±3 mm) than the plain drug-based tablet (36±2 mm). GRAPHICAL ABSTRACT
Multimorbidity in African ancestry populations: a scoping review

Objectives Multimorbidity (MM) is a growing concern linked to poor outcomes and higher healthcare costs. While most MM research targets European ancestry populations, the prevalence and patterns in African ancestry groups remain underexplored. This study aimed to identify and summarise the available literature on MM in populations with African ancestry, on the continent, and in the diaspora. Design A scoping review was conducted in five databases (PubMed, Web of Science, Scopus, Science Direct and JSTOR) in July 2022. Studies were selected based on predefined criteria, with data extraction focusing on methodology and findings. Descriptive statistics summarised the data, and a narrative synthesis highlighted key themes. Results Of the 232 publications on MM in African-ancestry groups from 2010 to June 2022—113 examined continental African populations, 100 the diaspora and 19 both. Findings revealed diverse MM patterns within and beyond continental Africa. Cardiovascular and metabolic diseases are predominant in both groups (80% continental and 70% diaspora). Infectious diseases featured more in continental studies (58% continental and 16% diaspora). Although many papers did not specifically address these features, as in previous studies, older age, being women and having a lower socioeconomic status were associated with a higher prevalence of MM, with important exceptions. Research gaps identified included limited data on African-ancestry individuals, inadequate representation, under-represented disease groups, non-standardised methodologies, the need for innovative data strategies, and insufficient translational research. Conclusion The growing global MM prevalence is mirrored in African-ancestry populations. Recognising the unique contexts of African-ancestry populations is essential when addressing the burden of MM. This review emphasises the need for additional research to guide and enhance healthcare approaches for African-ancestry populations, regardless of their geographic location.
GInRec: A Gated Architecture for Inductive Recommendation using Knowledge Graphs

We have witnessed increasing interest in exploiting KGs to integrate contextual knowledge in recommender systems in addition to user-item interactions, e.g., ratings. Yet, most methods are transductive, i.e., they represent instances seen during training as low-dimensionality vectors but cannot do so for unseen instances. Hence, they require heavy retraining every time new items or users are added. Conversely, inductive methods promise to solve these issues. KGs enhance inductive recommendation by offering information on item-entity relationships, whereas existing inductive methods rely purely on interactions, which makes recommendations for users with few interactions sub-optimal and even impossible for new items. In this work, we investigate the actual ability of inductive methods exploiting both the structure and the data represented by KGs. Hence, we propose GInRec, a state-of-the-art method that uses a graph neural network with relation-specific gates and a KG to provide better recommendations for new users and items than related inductive methods. As a result, we re-evaluate state-of-the-art methods, identify better evaluation protocols, highlight unwarranted conclusions from previous proposals, and showcase a novel, stronger architecture for this task. The source code is available at: https://github.com/theisjendal/kars2023-recommendation-framework.
Safety and efficacy of e-cigarettes in those with atherosclerotic disease: a review

Smoking cessation is the most effective intervention to reduce mortality in patients with established atherosclerotic cardiovascular disease (ASCVD), with ‘e-cigarettes’ becoming an increasingly used intervention to achieve smoking cessation. The current review aims to summarise the current evidence base for their efficacy and safety in the ASCVD cohort. A search of the PUBMED and MEDLINE databases using the terms ‘e-cigarette’, ‘cessation’, ‘safety’ and ‘efficacy’ since 2012 yielded 706 results. Both observational and experimental studies were included, while those with an unavailable full text, non-English or duplicates were excluded, yielding 78 relevant articles, with 13 subsequent additional articles included from a search of reference lists, for a total of 91 included papers. E-cigarette vapour contains many known pro-atherosclerotic substances and has been demonstrated to potentiate traditional atherosclerotic mechanisms. While e-cigarettes may be more effective in promoting smoking cessation in the general population over a medium term (>6 months), when compared with nicotine replacement therapy (NRT), few studies specifically examined those with ASCVD, despite the latter having a higher baseline quit rate (52% vs 2%). Most studies compare e-cigarettes with NRT alone and do not include pharmacotherapy, which may be more effective in the ASCVD cohort. The single randomised controlled trial addressing the research question favoured traditional methods. Those that successfully quit smoking using e-cigarettes are more likely to continue to use the intervention at 1 year (90% vs 9%). Conflicting advice exists regarding the utilisation of e-cigarettes for smoking cessation. E-cigarettes may be inferior to standard care for smoking cessation in those with ASCVD, and their use is likely to promote the key drivers of the atherosclerotic process already active in this cohort.
A deep knowledge tracing model based on multi-head self-attention mechanism

How to provide individualized instruction and personalized teaching for students and effectively track their knowledge status in a targeted manner is a key concern in the field of education. The target of Knowledge Tracing (KT) is to use the learner's behavior in historical learning activities to model the students' educational process and forecast the future performance of students. Recently, self-attention has been used several times in the KT field. Traditional models have the problem of losing information under long sequence data. Inspired by Transformer, in this paper, we present a deep knowledge tracing model (MA-DKT) based on the multi-head self-attention mechanism, which employs the LSTM model combined with the multi-head self-attention mechanism to implement a deep knowledge tracing model that is able to catch the data characteristics of the students at different temporal scales. Our model works well on publicly available datasets and achieves some improvement in AUC.
ARID HYDROLOGICAL MODELING AT WADI ALAQIQ, MADINAH, SAUDI ARABIA

Madinah is one of the urban centers that have experienced several devastating floods during the past 50 years. The objectives of this study are to estimate the flood hydrograph and peak discharge in the Wadi Alaqiq in Madinah and its major sub-catchments based on daily rainfall distribution. Daily annual maximum records are chosen for rainfall distribution in the study area. Wadi Alaqiq is located in the western part of the Madinah city and consists of five major sub-catchments, namely, Aqiq, Ruwawah, Reem, Al-Yutmah and Annaqi. The HEC-HMS and modified Talbot models are applied to estimate design flood for various average recurrence intervals (ARI). The analysis involves two stages, where stage one is concerned with modeling of the Wadi Alaqiq sub-catchment and comparison of the peak flow values obtained by previous studies and empirical formulae based on rainfall distribution analysis. In the second stage, the HEC-HMS is run separately for the five sub-catchments of Wadi Alaqiq. The model parameter values are then used to simulate for 25-year, 50-year and 100-year flood hydrographs. The HEC-HMS model is used to analyze the hydrologic behaviour of the wadi catchments. Initial and constant rate loss method is used to determine the hydrologic loss and the excess rainfall was transformed using the Clark’s Unit Hydrograph. The peak flow simulations are very close with reported values and those derived by modified Talbot. Also, the peak discharges are applied to model discharges from the HEC-HMS and modified Talbot equations of the five sub-catchments for a set of selected return periods. The direct runoff ratio for Madinah region in wadis Al-Yutmah, Annaqi, Aqiq, Reem and Ruwawah ranged from 25% to 28% of the total rainfall. This is due to topography condition, wadi catchment area and the use of predicted maximum daily rainfall results. The model results are reasonable for rainfall-runoff application and can be used for wadi corridor management in arid region.
Imaging Urban Hidden Faults with Ambient Noise Recorded by Dense Seismic Arrays

The identification of preexisting near-surface faults represents a piece of crucial information needed to correctly assess the seismic hazard of any area. The mapping of these structures is particularly challenging in densely populated and heavily urbanized areas. We use ambient seismic noise recorded by a dense array in Seal Beach, California, to image shallow fault lines via a reflected surface-wave analysis. Our results highlight the presence of previously unknown shallow faults that correlate remarkably well with shallow seismicity and active survey images.
When Your Language Model Cannot Even Do Determiners Right: Probing for Anti-Presuppositions and the Maximize Presupposition! Principle

The increasing interest in probing the linguistic capabilities of large language models (LLMs) has long reached the area of semantics and pragmatics, including the phenomenon of presuppositions. In this study, we investigate a phenomenon that, however, has not yet been investigated, i.e., the phenomenon of anti-presupposition and the principle that accounts for it, the Maximize Presupposition! principle (MP! ). Through an experimental investigation using psycholinguistic data and four open-source BERT model variants, we explore how language models handle different anti-presuppositions and whether they apply the MP! principle in their predictions. Further, we examine whether fine-tuning with Natural Language Inference data impacts adherence to the MP! principle. Our findings reveal that LLMs tend to replicate context-based n-grams rather than follow the MP! principle, with fine-tuning not enhancing their adherence. Notably, our results further indicate a striking difficulty of LLMs to correctly predict determiners, in relatively simple linguistic contexts.