Miracle-dz/UniFAR-FTUs huggingface dataset:
MM-Narrator: Narrating Long-form Videos with Multimodal In-Context Learning

We present MM-Narrator, a novel system leveraging GPT-4 with multimodal in-context learning for the generation of audio descriptions (AD). Unlike previous methods that primarily focused on downstream fine-tuning with short video clips, MM-Narrator excels in generating precise audio descriptions for videos of extensive lengths, even beyond hours, in an autoregressive manner. This capability is made possible by the proposed memory-augmented generation process, which effectively utilizes both the short-term textual context and long-term visual memory through an efficient register-and-recall mechanism. These contextual memories compile pertinent past information, including storylines and character identities, ensuring an accurate tracking and depicting of story-coherent and character-centric audio descriptions. Maintaining the training-free design of MM-Narrator, we further propose a complexity-based demonstration selection strategy to largely enhance its multi-step reasoning capability via few-shot multimodal in-context learning (MM-ICL). Experimental results on MAD-eval dataset demonstrate that MM-Narrator consistently outperforms both the existing fine-tuning-based approaches and LLM-based approaches in most scenarios, as measured by standard evaluation metrics. Additionally, we introduce the first segment-based evaluator for recurrent text generation. Empowered by GPT-4, this evaluator comprehensively reasons and marks AD generation performance in various extendable dimensions.
Robust network formation with biological applications

We provide new results on the structure of optimal transportation networks obtained as minimizers of an energy cost functional consisting of a kinetic (pumping) and material (metabolic) cost terms, constrained by a local mass conservation law. In particular, we prove that every tree (i.e., graph without loops) represents a local minimizer of the energy with concave metabolic cost. For the linear metabolic cost, we prove that the set of minimizers contains a loop-free structure. Moreover, we enrich the energy functional such that it accounts also for robustness of the network, measured in terms of the Fiedler number of the graph with edge weights given by their conductivities. We examine fundamental properties of the modified functional, in particular, its convexity and differentiability. We provide analytical insights into the new model by considering two simple examples. Subsequently, we employ the projected subgradient method to find global minimizers of the modified functional numerically. We then present two numerical examples, illustrating how the optimal graph's structure and energy expenditure depend on the required robustness of the network.
The Effects of Different Fatigue Types on Action Anticipation and Physical Performance in High-level Volleyball Players

This study examined the effects of different fatigue types on action anticipation and physical performance in high-level volleyball players. Twenty-four participants underwent four counterbalanced conditions: 60-min of cycling at 60% peak power output, 60-min Stroop task, 60-min cycling at 60% peak power output with Stroop task and 60-min neutral documentary to induce physical fatigue (PF), mental fatigue (MF), dual fatigue (DF) and control group (CG), respectively. Action anticipation (anticipation test and visual search test) and physical performance (countermovement jump, T-test, and spike test) were conducted at baseline, immediately after (Post1), and 40-min after fatigue intervention (Post2). DF and PF led to significantly lower jump height, T-test completion time, and spiking speed at Post1 and Post2 compared with CG and MF. Compared with PF, DF led to a significant decline in jumping, agility, and spiking performance at Post1 and decreased jumping performance at Post2. MF significantly decreased reaction time in the anticipation test at Post1 compared with CG. Reaction times in the visual search test were significantly lower with DF and MF at Post2 compared with CG. PF led to a greater decline in physical performance and this was exacerbated in DF, yet anticipation performance remained lesser impact.
Spatio‐temporal variation of the tidal triggering effect on earthquake occurrence associated with the 1982 South Tonga earthquake of Mw 7.5

We observed a clear tidal triggering effect on earthquakes closely related to the occurrence of the 1982 South Tonga earthquake (Mw 7.5) by precisely measuring the correlation between the earth tide and earthquake occurrence using 385 shallow earthquakes of reverse‐fault type in the Tonga‐Kermadec subduction zone. The result of statistical analysis indicates that the tidal effect, having been predominant for the normal stress on the fault plane, concentrated in and near the future focal area for several years preceding the South Tonga earthquake. The high correlation disappeared after the earthquake. The frequency distribution of phase angles for the pre‐event period exhibited a peak at the phase angle where the tidal normal stress is at its maximum to accelerate the fault slip, which indicates that the observed high correlation is not a statistical chance but physically reasonable.
Simplest Model of Nervous System. II. Evolutionary Optimization

In this work, we build upon a simple model of a primitive nervous system presented in a prior companion paper. Within this model, we formulate and solve an optimization problem, aiming to mirror the process of evolutionary optimization of the nervous system. The formally derived predictions include the emergence of sharp peaks of neural activity (‘spikes’), an increasing sensory sensitivity to external signals and a dramatic reduction in the cost of the functioning of the nervous system due to evolutionary optimization. Our work implies that we may be able to make general predictions about the behavior and characteristics of the nervous system irrespective of specific molecular mechanisms or evolutionary trajectories. It also underscores the potential utility of evolutionary optimization as a key principle in mathematical modeling of the nervous system and offers examples of analytical derivations possible in this field. Though grounded in a simple model, our findings offer a novel perspective, merging theoretical frameworks from nonequilibrium statistical physics with evolutionary principles. This perspective may guide more comprehensive inquiries into the intricate nature of neural networks.
Temporal stability of sex ratio distorter prevalence in natural populations of the isopod Armadillidium vulgare

In the terrestrial isopod Armadillidium vulgare, many females produce progenies with female-biased sex ratios due to two feminizing sex ratio distorters (SRD): Wolbachia endosymbionts and a nuclear non-mendelian locus called the f element. To investigate the potential impact of these SRD on the evolution of sex determination, we analyzed their temporal distribution in 6 A. vulgare populations sampled up to 6 times over 12 years, for a total of 29 time points. SRD distribution was heterogeneous among populations despite their close geographic locations, so that when one SRD was frequent in a population, the other SRD was rare. In contrast with spatial heterogeneity, our results overall did not reveal substantial temporal variability in SRD prevalence within populations, suggesting equilibria in SRD evolutionary dynamics may have been reached or nearly so. SRD temporal stability was also reflected in mitochondrial and nuclear variation, with two exceptions. One population was affected by anthropogenic alteration at the sampling spot between the earliest and second time points, likely explaining a rapid shift in genetic composition. However, subsequent global stability suggested that population dynamics equilibrium may be reached in a few generations. In another population, a Wolbachia strain replacement coincided with changes in mitochondrial composition but no change in nuclear composition, thus constituting a typical example of mitochondrial sweep caused by endosymbiont rise in frequency. Rare incongruence between Wolbachia strains and mitochondrial haplotypes further highlighted the occurrence of intraspecific horizontal transmission, making it a biologically relevant parameter for Wolbachia evolutionary dynamics in A. vulgare.
Investigating impacts of marine sponge derived mycothiazole and its acetylated derivative on mitochondrial function and aging

Small molecule inhibitors of the mitochondrial electron transport chain (ETC) hold significant promise to provide valuable insights to the field of mitochondrial research and aging biology. In this study, we investigated two molecules: mycothiazole (MTZ) - from the marine sponge C. mycofijiensis and its more stable semisynthetic analog 8-O-acetylmycothiazole (8-OAc) as potent and selective chemical probes based on their high efficiency to inhibit ETC complex I function. Similar to rotenone (Rote), a widely used ETC complex I inhibitor, these two molecules showed cytotoxicity to cancer cells but strikingly demonstrate a lack of toxicity to non-cancer cells, a highly beneficial feature in the development of anti-cancer therapeutics. Furthermore, in vivo experiments with these small molecules utilizing C.elegans model demonstrate their unexplored potential to investigate aging studies. We observed that both molecules have the ability to induce a mitochondria-specific unfolded protein response (UPRMT) pathway, that extends lifespan of worms when applied in their adult stage. Interestingly, we also found that these two molecules employ different pathways to extend lifespan in worms. Whereas MTZ utilize the transcription factors ATFS-1 and HSF-1, which are involved in the UPRMT and heat shock response (HSR) pathways respectively, 8-OAc only required HSF-1 and not ATFS-1 to mediate its effects. This observation underscores the value of applying stable, potent, and selective next generation chemical probes to elucidate an important insight into the functional roles of various protein subunits of ETC complexes and their regulatory mechanisms associated with aging.
Biomolecular condensates in fungi are tuned to function at specific temperatures

Temperature can impact every reaction and molecular interaction essential to a cell. For organisms that cannot regulate their own temperature, a major challenge is how to adapt to temperatures that fluctuate unpredictability and on variable timescales. Biomolecular condensation offers a possible mechanism for encoding temperature-responsiveness and robustness into cell biochemistry and organization. To explore this idea, we examined temperature adaptation in a filamentous-growing fungus called Ashbya gossypii that engages biomolecular condensates containing the RNA-binding protein Whi3 to regulate mitosis and morphogenesis. We collected wild isolates of Ashbya that originate in different climates and found that mitotic asynchrony and polarized growth, which are known to be controlled by the condensation of Whi3, are temperature sensitive. Sequence analysis in the wild strains revealed changes to specific domains within Whi3 known to be important in condensate formation. Using an in vitro condensate reconstitution assay we found that temperature impacts the relative abundance of protein to RNA within condensates and that this directly impacts the material properties of the droplets. Finally, we found that exchanging Whi3 genes between warm and cold isolates was sufficient to rescue some, but not all, condensate-related phenotypes. Together these data demonstrate that material properties of Whi3 condensates are temperature sensitive, that these properties are important for function, and that sequence optimizes properties for a given climate.
Microencapsulation of mesenchymal stromal cells in covalent alginate hydrogels for cell therapy

Osteoarthritis (OA) is the most common inflammatory joint disease and currently lacks an effective curative treatment. Intra-articular injection of mesenchymal stromal cells (MSCs) has gained attention as a relevant therapeutic approach for OA treatment due to the MSC’s ability to secrete anti-inflammatory and immunomodulatory factors. Given their limited viability post- intraarticular injection and the potential leakage of cells out of the injection site, encapsulating MSCs in hydrogels is considered a promising strategy to protect them and provide a suitable 3D microenvironment to support their biological activities. Calcium-cross-linked alginate hydrogels are commonly used for MSC encapsulation, but their long-term in vivo stability remains uncertain. On the other hand, alginate cross-linking by the strain-promoted azide- alkyne cycloaddition (SPAAC) reaction would create a network unaffected by an ionic environment. Hence, this study aimed to develop an alginate-based hydrogel cross-linked via stable and cytocompatible covalent bonds for cell encapsulation. We established for the first time the formation of covalent alginate hydrogels between two SPAAC precursors, namely alginate-BCN and alginate-N3. These hydrogels exhibited in vitro stability and enabled the diffusion of molecules of interest. We then generated alginate-based SPAAC microgels of 170 μm in mean diameter, suitable for intra-articular injection. We next encapsulated human adipose MSCs (hASCs) in these alginate-based SPAAC microgels and confirmed their cytocompatibility, with over 90 % of cells remaining viable after 14 days in culture. Finally, the microencapsulated hASCs maintained their biological properties and were able to secrete anti-inflammatory factors (IDO, PGE2, and HGF) when exposed to pro-inflammatory cytokines (TNF-α and IFN-γ). In the end, human-activated lymphocytes were cultured in contact with microencapsulated hASCs, and CD3+ T cell proliferation was quantified by flow cytometry. We demonstrated that the encapsulation process did not impair the hASC immunomodulatory activity. Overall, our findings show the potential of alginate-based SPAAC hydrogels for microencapsulating hASCs for cell therapy.
Drosophila Neuronal Glucose 6 Phosphatase is a modulator of Neuropeptide Release that regulates muscle glycogen stores via FMRFamide signaling

Neuropeptides (NPs) and their cognate receptors are critical molecular effectors of diverse physiological processes and behaviors. We recently reported of a non-canonical function of the Drosophila Glucose-6-Phosphatase (G6P) gene in a subset of neurosecretory cells in the CNS that governs systemic glucose homeostasis in food deprived flies. Here, we show that G6P expressing neurons define 7 groups of neuropeptide secreting cells, 5 in the brain and 2 in the thoracic ganglia. Using the glucose homeostasis phenotype as a screening tool, we show that one such group, located in the thoracic ganglia and expressing FMRFamide (FMRFaG6P) neuropeptides, is necessary and sufficient to maintain systemic glucose homeostasis in starved flies. We further show that the receptor for FMRFamides (FMRFaR) is one key target of G6P dependent NP signaling and essential for the build-up of glycogen stores in the jump muscle. Lastly, measurements of the Golgi apparatus of FMRFaG6P neurons and neuropeptide released into the hemolymph suggests that G6P enhances FMRFa signaling by increasing the capacity of the neurosecretory system. We propose a general model in which the main role of G6P is to counteract glycolysis in peptidergic neurons for the purpose of optimizing the intracellular environment best suited for the expansion of the Golgi apparatus, boosting release of neuropeptides, which through the activation of specific neuropeptide receptors, enhances signaling in respective target tissues.
Intersubject representational similarity analysis uncovers the impact of state anxiety on brain activation patterns in the human extrastriate cortex

The current study used functional magnetic resonance imaging (fMRI) and showed that state anxiety modulated extrastriate cortex activity in response to emotionally-charged visual images. State anxiety and neuroimaging data from 53 individuals were subjected to an intersubject representational similarity analysis (ISRSA), wherein the geometries between neural and behavioral data were compared. This analysis identified the extrastriate cortex (fusiform gyrus and area MT) to be the sole regions whose activity patterns covaried with state anxiety. Importantly, we show that this brain-behavior association is revealed when treating state anxiety data as a multidimensional response pattern, rather than a single composite score. This suggests that ISRSA using multivariate distances may be more sensitive in identifying the shared geometries between self-report questionnaires and brain imaging data. Overall, our findings demonstrate that a transient state of anxiety may influence how visual information – especially those relevant to the valence dimension – is processed in the extrastriate cortex.
Emerging practices and perspectives on Big Data analysis in economics: Bigger and better or more of the same?

Although the terminology of Big Data has so far gained little traction in economics, the availability of unprecedentedly rich datasets and the need for new approaches – both epistemological and computational – to deal with them is an emerging issue for the discipline. Using interviews conducted with a cross-section of economists, this paper examines perspectives on Big Data across the discipline, the new types of data being used by researchers on economic issues, and the range of responses to this opportunity amongst economists. First, we outline the areas in which it is being used, including the prediction and ‘nowcasting’ of economic trends; mapping and predicting influence in the context of marketing; and acting as a cheaper or more accurate substitute for existing types of data such as censuses or labour market data. We then analyse the broader current and potential contributions of Big Data to economics, such as the ways in which econometric methodology is being used to shed light on questions beyond economics, how Big Data is improving or changing economic models, and the kinds of collaborations arising around Big Data between economists and other disciplines.
Halting the Solana Blockchain with Epsilon Stake

Solana is a blockchain protocol that has gained significant attention in the cryptocurrency community. This work examines Solana’s consensus protocol and its reference implementation. In this paper we try to get an understanding of the Solana protocol. However, this is not so easy because the publicly available resources are insufficient to specify the details of the protocol. More-over, the implementation has deviated in undocumented ways from the available protocol design description. Thus the consensus rules and their implied security properties remain unclear. We evaluate a number of experimental scenarios in a local Solana testnet. These tests seem to confirm our basic understanding that Solana does not fully achieve consensus. In this paper we show how a single malicious validator, once elected as leader, might be able to halt the Solana blockchain. We also observe some inconsistent behavior, which is not readily explained by any of the consensus rules we are aware of.
Mobile Banking and Financial Performance of Commercial Banks: A Case Study of Selected Commercial Banks in Uganda

:- The study concentrated on assessing the relationship between Mobile Banking and Financial Performance of the selected Commercial banks in Uganda. This was attained through assessing the relationship between mobile transaction volumes, mobile banking products, mobile banking technological investment and financial performance. This study undertaken a quantitative and non-experimental research, co-relational, cross-sectional and survey design. The target population was 120 employees and managers of three selected commercial banks that include Equity Bank, DFCU and Centenary bank from where a sample size of 92 respondents was sampled based on Morgan and Krejcie table as given by Amin, (2005) in fulfillment of attaining the research objectives of the study. Results showed that there is a significant positive relationship between mobile transaction volumes, mobile banking products, mobile banking technological investment and financial performance of Commercial banks in Uganda as this was evidenced by correlation coefficients(r) of 0.871, 0.527 and 0.525 respectively that were statistically significant since the p value (0.000) < 0.01. Based on the study findings, the researcher concludes that mobile banking deposits through the M-Banking have greatly increased the firm's revenue, increased the number of transactions done by the bank since there is increased customer convenience, increased the net profits and business for both employees and commercial bank. In addition, mobile banking technological investment has increased the productivity of the bank's employees, increased flexibility in product innovation, enhanced customer numbers, increased employee's efficiency and productivity, increased customer loyalty, reduced the overall transaction costs for both customers and the bank, reduced the administrative expenses, reduced the employees' costs, reduced the bank's expenditure in setting up new branches and further reduced on the customer queues in the banking halls. Based on the study findings, the researcher recommends that the banks should lower the transaction charges incurred by customers, reduce time taken to complete transaction and improve the quality of mobile banking services so as to motivate them use the M-banking services
Was the Eubrontes Track Maker Gregarious? Testing the Herding Hypothesis at Powder Hill Dinosaur Park, Middlefield, Connecticut

Abstract The theropod footprint taxon Eubrontes is common in Early Jurassic rocks of the Hartford Basin. Aligned Eubrontes trackways at one site in Holyoke, Massachusetts, have led to the hypothesis that the track makers were gregarious; however, trackways are not aligned at several other sites. To test the gregariousness hypothesis, we measured trackway orientations at Powder Hill Dinosaur Park in Middlefield, Connecticut, where exposed rocks were deposited in an ephemeral lake environment, and compared these orientations to those of two additional track sites from similar sedimentary facies. The Eubrontes trackways produced in the ephemeral lake environments have no preferred orientation and provide no evidence of gregarious behavior. We suggest that the alignment of tracks in Holyoke reflects behavior in response to environmental settings rather than group behavior. Trackways may be aligned next to large, permanent lakes because of shoreline-parallel travel, but random orientations characterize other habitats. This study underscores the value of examining track sites from different paleoenvironments when inferring dinosaur behavior.
An Extended Set of Haar-like Features for Rapid Object Detection

Recently Viola et al. [5] have introduced a rapid object detection scheme based on a boosted cascade of simple feature classifiers. In this paper we introduce a novel set of rotated haar-like features. These novel features significantly enrich the simple features of [5] and can also be calculated efficiently. With these new rotated features our sample face detector shows off on average a 10% lower false alarm rate at a given hit rate. We also present a novel post optimization procedure for a given boosted cascade improving on average the false alarm rate further by 12.5%.