Miracle-dz/UniFAR-FTUs huggingface dataset:
Variant- and Vaccination-Specific Alternative Splicing Profiles in SARS-CoV-2 Infections

The COVID-19 pandemic, caused by the coronavirus SARS-CoV-2, and its subsequent variants has underscored the importance of understanding the host-viral molecular interactions to devise effective therapeutic strategies. A significant aspect of these interactions is the role of alternative splicing in modulating host responses and viral replication mechanisms. Our study sought to delineate the patterns of alternative splicing of RNAs from immune cells across different SARS-CoV-2 variants and vaccination statuses, utilizing a robust dataset of 190 RNA-seq samples from our previous studies, encompassing an average of 212 million reads per sample. We identified a dynamic alteration in alternative splicing and genes related to RNA splicing were highly deactivated in COVID-19 patients and showed variant- and vaccination-specific expression profiles. Overall, Omicron-infected patients exhibited a gene expression profile akin to healthy controls, unlike the Alpha or Beta variants. However, significantly, we found identified a subset of infected individuals, most pronounced in vaccinated patients infected with Omicron variant, that exhibited a specific dynamic in their alternative splicing patterns that was not widely shared amongst the other groups. Our findings underscore the complex interplay between SARS-CoV-2 variants, vaccination-induced immune responses, and alternative splicing, emphasizing the necessity for further investigations into these molecular cross-talks to foster deeper understanding and guide strategic therapeutic development.
Salt-dependent self-association of trinucleotide repeat RNA sequences

Low complexity repeat RNA sequences self-associate by homotypic interactions to form condensates. Using simulations of a coarse grained Single-Interaction Site model for (CAG)n (n = 30 and 31), we show that the salt-dependent free energy gap, ∆GS, between the ground (perfect hairpin) and the excited state (slipped hairpin (SH) with one CAG overhang) of monomer (n even) is the primary factor that determines the rates and yield of self-assembly. For odd n, the SH ground state free energy (GS) is used to predict self-association kinetics. As the monovalent salt concentration, CS, increases ∆GS and GS increases, which in turn decreases the self-association rates. In contrast, ∆GS for scrambled sequences, with the same length and sequence composition as (CAG)31 but with higher complexity, is larger which greatly suppresses the propensities to aggregate. Although demonstrated explicitly for (CAG)30 and (CAG)31 polymers, the finding that there is an inverse correlation between CS-dependent ∆GS or GS and RNA aggregation is general. Our predictions are amenable to experimental tests.
Tracking the misallocation and reallocation of spatial attention towards auditory stimuli

Completely ignoring a salient distractor presented concurrently with a target is difficult and sometimes attention is involuntarily attracted to the distractor’s location (attentional capture). Employing the N2ac component as a marker of attention allocation towards sounds, in this study we investigate the spatio-temporal dynamics of auditory attention across two experiments. Human participants (male and female) performed an auditory search task, where the target was accompanied by a distractor in 2/3rd of the trials. For a distractor more salient than target (Exp. 1), we observe not only a distractor N2ac (indicating attentional capture), but the full chain of attentional dynamics implied by the notion of attentional capture, namely: (a) the distractor captures attention before the target is attended, (b) allocation of attention to the target is delayed by distractor presence, and (c) the target is attended after the distractor. Conversely, for a distractor less salient than the target (Exp. 2), although behavioral interference was present, no attentional capture was observed. Together, these findings reveal two types of spatial-attentional dynamics in the auditory modality (distraction with and without attentional capture). Significance Statement Oftentimes, we find it hard to ignore the location of a salient sound that distracts us from our current tasks. Although, a common everyday experience, little is known about how spatial distraction unfolds at the neural level in the auditory modality. Using electrophysiological markers of attention allocations, we report comprehensive evidence of spatial attentional capture by a salient auditory distractor, indicating that attention is first misallocated to the distractor and only afterwards reallocated towards the target. Similar patterns were observed earlier only in vision and their discovery in the auditory modality indicates towards the existence of domain-general spatial attentional dynamics consistent across sensory modalities. Finally, we demonstrate that only a distractor more salient than the target reliably captures attention.
Sex and heredity are determinants of oral oxycodone self-administration in 36 Inbred Rat Strains: correlations with behavioral tests of anxiety and novelty-seeking

Most individuals affected in the national epidemic of oxycodone abuse began taking oral oxycodone by prescription. We studied vulnerability to oxycodone intake in a rat model of oral drug self-administration (SA), since pharmacokinetics affect abuse potential. Females (33 inbred strains) and males (26) obtained oxycodone at increasing concentrations in operant sessions (FR5; 1-16-h) followed by extinction and reinstatement. Active spout licks were greater in females than males during 4-h and 16-h sessions (p< 0.001 for all). Across all stages of oxycodone SA, intake/session was greater in females (p<0.001). Both sexes escalated intake during 16-h extended access vs 4-h sessions (p<2e-16). Intake and active licks varied greatly by strain. The heritability (h2) of active licks/4-h at increasing oxycodone dose was larger in males (h2 females: 0.30-0.39 vs. males: 0.41-0.53). Under a progressive ratio schedule, breakpoints differed by strain (p<2e-16) and by sex in some strains (p=0.018). For cue-induced reinstatement, active licks were greater in females than males (p<0.001). Behavior in naive rats was assessed using elevated plus maze (EPM), open field (OF) and novel object interaction. (NOI) tests. We correlated these behaviors with 28 parameters of oxycodone SA. EPM-defining traits were most commonly associated with SA in both sexes, whereas more OF and NOI traits were SA-associated in males. Overall, sex and heredity are major determinants of the motivation to take and seek oxycodone, which escalates during extended access. The correlation of EPM, a measure of anxiety, with multiple SA parameters indicates the influence of pleiotropic genes.
Multi-level 3D genome organization deteriorates during breast cancer progression

Breast cancer entails intricate alterations in genome organization and expression. However, how three-dimensional (3D) chromatin structure changes in the progression from a normal to a breast cancer malignant state remains unknown. To address this, we conducted an analysis combining Hi-C data with lamina-associated domains (LADs), epigenomic marks, and gene expression in an in vitro model of breast cancer progression. Our results reveal that while the fundamental properties of topologically associating domains (TADs) remain largely stable, significant changes occur in the organization of compartments and subcompartments. These changes are closely correlated with alterations in the expression of oncogenic genes. We also observe a restructuring of TAD-TAD interactions, coinciding with a loss of spatial compartmentalization and radial positioning of the 3D genome. Notably, we identify a previously unrecognized interchromosomal insertion event, wherein a locus on chromosome 8 housing the MYC oncogene is inserted into a highly active subcompartment on chromosome 10. This insertion leads to the formation of de novo enhancer contacts and activation of the oncogene, illustrating how structural variants can interact with the 3D genome to drive oncogenic states. In summary, our findings provide evidence for the degradation of genome organization at multiple scales during breast cancer progression revealing novel relationships between genome 3D structure and oncogenic processes.
Explaining the Transfer Learning Ability of a Deep Neural Networks by Means of Representations

The basis of transfer learning methods is the ability of deep neural networks to use knowledge from one domain to learn in another domain. However, another important task is the analysis and explanation of the internal representations of deep neural networks models in the process of transfer learning. Some deep models are known to be better at transferring knowledge than others. In this re-search, we apply the Centered Kernel Alignment (CKA) method to analyze the in-ternal representations of deep neural networks and propose a method to evaluate the ability of a neural network architecture to transfer knowledge based on the quantitative change in representations during the learning process. We introduce the Transfer Ability Score (TAs) measure to assess the ability of an architecture to effectively transfer learning. We test our approach using Vision Transformer (ViT-B/16) and CNN (ResNet, DenseNet) architectures in computer vision tasks in several datasets, including medical images. Our work is a contribution to the field of explainable AI and an attempt to explain the learning transfer process.
The Halloween Effect in US Sectors: Comment

We argue that the Jacobsen and Visaltanachoti (2009) study is incomplete. Jacobsen and Visaltanachoti (2009) evaluate the Halloween effect or ‘Sell in May’-effect as documented by Bouman and Jacobsen (2002), and extend the analysis into the relative performances of sectors during the winter and summer period. First, Jacobsen and Visaltanachoti (2009) do not mention the optimism cycle hypothesis in their list of possible behavioral explanations for the well known seasonal pattern. Next, their documented sector rotation strategy looks strongly like Doeswijk (2005). By withholding a reference to Doeswijk (2005), they miss the opportunity to give a possible explanation for the seasonality in relative sector performances. Doeswijk (2005) suggests a link between the seasonal sector rotation strategy and a cycle in investors’ optimism.
Novices make more noise! But how can we listen to it?

This paper presents an extension to the approach described in [13] which was designed to help distinguish expert and novice performance easily by observing the sensor data without having to understand nor apply models to the sensor signal. The method consisted of plotting the sensor data and identifying irregularities in novice data and regularities in expert data. In this paper, we solidify the thesis that, with the help of sensors, expert performances are smoother, contain fewer irregularities, and have consistently uniform patterns than novice performances. We do so using the extended methodology on the same data set from the previous five cases in [13], namely running, bachata dance, salsa dance, tennis swings, and football penalty kicks, pointing out this assertion.
Seasonality in currents of the Rockall Channel

Though our knowledge of the circulation in this complex region is still incomplete, recent direct current measurements have identified four separate elements of the circulation which appear to undergo a seasonal variation of some sort. These are: (i) a summer-autumn maximum in the deep overflow of Norwegian Sea Deep Water across the Wyville-Thomson Ridge; (ii) an autumn minimum in the upper-ocean circulation around Rockall Bank, ascribed to Taylor Column processes; (iii) an autumn-winter maximum in the strength and breadth of the slope current along the European continental margin; (iv) a winter-spring maximum in eddy kinetic energy in the open waters of the Rockall Channel, and over the full depth range, as a function of windstress and stratification. The first three of these elements are of localised occurrence along the northern, western and eastern margins of the Channel and are described only briefly. The fourth process, encountered at a range of sites in the northeast Atlantic, is described in detail using a total data set of 68 instrument-years of direct current measurements recovered from the Rockall Channel in 1977–84. In the seasonally-varying 3–27 day ( d ) band of periods, eddy kinetic energies ( k E ) are shown to be depth-dependent in amplitude, but with little evidence of any significant phase-lag with either depth or location between the individual timeseries of k E estimates. These time-series demonstrate clearly and for the first time that the winterspring peaks in eddy kinetic energy lag the winter peaks in windstress by between 1 and 3 months. This phase-lag is explained as the cumulative result of wind forcing and eddy dissipation.
Integrating scientific and lay accounts of air pollution

The Environmental Psychology Research Unit together with the Fluids Research Centre, at the University of Surrey, UK, are investigating relationships between transport, air pollution and health. This collaborative research utilises a conceptual framework drawn from existing theories and paradigms in the field of environmental psychology, combined with analytical modelling and experimental data from fluid mechanics. The present research aims to investigate and account for actual and perceived levels of air pollution in Guildford, Surrey, with the collaboration of Guildford Borough Council. Preliminary research was carried out as a trial analysis to compare residents' spatial perceptions of air pollution in the Borough of Guildford with actual NOz data. This was then plotted spatially using a GIS (Geographical Information System). On the basis of the results a research tool was developed which would allow for a more sophisticated analysis, and for advanced comparisons to be made between actual and perceived levels of air pollution. This paper presents the development of this methodology, involving a large-scale air pollution risk perception survey, which is to be carried out in the Guildford area. Respondents will be required to complete two tasks: a self-administered questionnaire and a cognitive mapping exercise. The questionnaire will be designed to gauge information on residents' knowledge, awareness and perceptions of risks in relation to air quality. The mapping exercise requires residents to plot on maps where they perceive air pollution to be in their local area. GIS will be used to plot the perceptual spatial representations of air pollution levels together with the actual real-time air quality data, in order to detect and identify disparities.
Distance Queries over Dynamic Interval Graphs

We design the first dynamic distance oracles for interval graphs, which are intersection graphs of a set of intervals on the real line, and for proper interval graphs, which are intersection graphs of a set of intervals in which no interval is properly contained in another. For proper interval graphs, we design a linear space data structure which supports distance queries (computing the distance between two query vertices) and vertex insertion or deletion in O (lg n ) worst-case time, where n is the number of vertices currently in G . Under incremental (insertion only) or decremental (deletion only) settings, we design linear space data structures that support distance queries in O (lg n ) worst-case time and vertex insertion or deletion in O (lg n ) amortized time, where n is the maximum number of vertices in the graph. Under fully dynamic settings, we design a data structure that represents an interval graph G in O ( n ) words of space to support distance queries in O ( n lg n/S ( n )) worst-case time and vertex insertion or deletion in O ( S ( n ) + lg n ) worst-case time, where n is the number of vertices currently in G and S ( n ) is an arbitrary function that satisfies S ( n ) = Ω(1) and S ( n ) = O ( n ). This implies an O ( n )-word solution with O ( √ n lg n )-time support for both distance queries and updates. All four data structures can answer shortest path queries by reporting the vertices in the shortest path between two query vertices in O (lg n ) worst-case time per vertex. We also study the hardness of supporting distance queries under updates over an intersection graph of 3D axis-aligned line segments, which generalizes our problem to 3D. Finally, we solve the problem of computing the diameter of a dynamic connected interval graph.
Fast Convolutions for Near-Convex Sequences

We develop algorithms for (min , +)- Convolution and related convolution problems such as Super Additivity Testing , Convolution 3-Sum and Minimum Consecutive Subsums which use the degree of convexity of the instance as a parameter. Assuming the min-plus conjecture (Künnemann-Paturi-Schneider, ICALP’17 and Cygan et al., ICALP’17), our results interpolate in an optimal manner between fully convex instances, which can be solved in near-linear time using Legendre transformations, and general non-convex sequences, where the trivial quadratic-time algorithm is conjectured to be best possible, up to subpolynomial factors.
Fully Softened Shear Strength for Soil Slope Stability Analyses

AbstractThe fully softened shear strengths of soils, mudstones, and shales of different plasticities and gradations were measured at low (10 and 25 kPa), intermediate (50 and 100 kPa), and high (200, 300, and 400 kPa) effective normal stresses. A torsional ring shear apparatus was used for the strength measurement. The effects of the change in nonlinearity of the fully softened shear strength envelope over the utilized normal stress ranges on slope stability analyses were investigated. An empirical correlation was developed to predict the fully softened shear strength as a function of plasticity index and a wide range of effective normal stresses. The correlation is presented as a revised version of those previously developed for a limited number of normal stresses that do not cover the range mobilized in the vast majority of reported long-term first-time landslides. A numerical expression was also introduced to allow for direct incorporation of the fully softened shear strength correlation in slope stabi.
Determinations of Fraud in Local Governments in the Province of Aceh

Fraud refers prohibited activities undertaken by individuals both internal and external to the organization, with the aim of obtaining personal and/or collective benefits that result in an immediate disadvantage to other entities. This study aims to examine the effect of the fraud hexagon theory on fraud in Local Government. The test tool used is multiple linear regression analysis using SPSS. Participants in this study consisted of districts and cities in Aceh Province. The findings of this study show that each independent variable, specifically pressure (X1), opportunity (X2), rationalization (X3), capability (X4), arrogance (X5), and collusion (X6), has a major effect on fraud activities in the local government environment in Aceh Province. This research is expected to assess and ensure the effectiveness of risk mitigation measures in countering the various factors that contribute to the occurrence of fraudulent activities. In addition, the findings of this study can serve as additional scientific material for local government entities that intend to improve their fraud prevention strategies.
Adapting Generic Features to A Specific Task: A Large Discrepancy Knowledge Distillation for Image Anomaly Detection

Anomaly detection is a challenging task due to the lack of data on unexpected anomalies. Recent approaches using Knowledge Distillation (KD) between Teacher-Student (T-S) models have shown great potential for anomaly detection. These techniques use pre-trained models on natural images as the teacher model. However, for industrial images, defects typically occur in a small region, while the global semantics of the anomaly image remain similar to normal images. This situation results in generic features being unable to capture defects well, leading to a loss of discriminability in detecting anomalies. This paper proposes a way to improve this situation by applying learnable feature mappings to adapt the generic features for the data-specific task. Additionally, a novel angular margin loss is introduced to improve the regular training loss of knowledge distillation and ensure larger discrepancies between T-S models on anomalies. Extensive experiments show that the proposed feature mappings and angular loss can effectively improve the feature discriminability for anomaly detection and help state-of-the-art KD-based methods achieve better detection performance.
Journal Pre-proof Sleep duration moderates the associations between immune markers and corticolimbic function during stress in adolescents

Adolescence is characterized by biological changes in hormonal and circadian systems that, with concurrent psychosocial changes, result in increased sleep disturbances and stress sensitivity. Sleep disturbance has been associated with heightened stress sensitivity and elevated levels of inflammation in adults and adolescents, yet the neural correlates are unknown in adolescents. The current study investigated whether and how individual differences in peripheral immune markers (IL-6, TNF- ) related to neural response to stress in adolescents and whether these immune-brain associations were moderated by adolescents’ sleep duration. Thirty-seven adolescents (14-15 years) who met quality control criteria for fMRI reported daily sleep duration for 7 days and performed an fMRI stressor task. A subsample of 23 adolescents additionally provided blood samples that were assayed for inflammatory markers using a multiplex assay. Results revealed that average sleep duration moderated associations between TNF- and medial frontolimbic circuitry (amygdala, medial prefrontal cortex) during the stressor task such that, among adolescents who reported shorter sleep duration, higher levels of TNF- were associated with greater deactivation in those regions during stress, which was associated with greater self-reported anxiety. These findings suggest that insufficient sleep duration coupled with greater levels of peripheral inflammation may promote a neural profile characterized by alterations in frontolimbic circuitry during stress, which can exacerbate sleep disturbances and/or peripheral inflammation.
Enhancing Text-to-Video Editing with Motion Map Injection

Based on the remarkable performance of text-to-image diffusion models, text-guided video editing studies recently have been expanded. Existing video editing studies have introduced an implicit method of adding cross-frame attention to estimate inter-frame attention, resulting in temporally consistent videos. However, because these methods use models pre-trained on text-image pair data, they do not handle unique property of video: motion. When editing a video with prompts, the attention map of the prompt implying the motion of the video (e.g. ‘running’, ‘moving’) is prone to be poorly estimated, which causes inaccurate video editing. To address this problem, we propose the ‘Motion Map Injection’ (MMI) module to consider motion explicitly. The MMI module provides text-to-video (T2V) models a simple but effective way to convey motion in three steps: 1) extracting motion map, 2) calculating the similarity between the motion map and the attention map of each prompt, and 3) injecting motion map into the attention maps. Given experimental results, input video can be edited accurately with MMI module. To the best of our knowledge, our study is the first method that utilizes the motion in video for text-to-video editing. Extensive experimental results are in https://currycurry915.github. io/MMI/ .