Miracle-dz/UniFAR-FTUs huggingface dataset:
Hydrogen peroxide activates APE1/Ref-1 via NF-κB and Parkin: a role in liver cancer resistance to oxidative stress

Abstract Cancer cells exhibit an altered redox balance and aberrant redox signaling due to genetic, metabolic, and microenvironment-associated reprogramming. Persistently elevated levels of reactive oxygen species (ROS) contribute to many aspects of tumor development and progression. Emerging studies demonstrated the vital role of apurinic/apyrimidinic endonuclease 1 or reduction/oxidation (redox) factor 1(APE1/Ref-1) in the oxidative stress response and survival of cancer cells. APE1/Ref-1 is a multifunctional enzyme involved in the DNA damage response and functions as a redox regulator of transcription factors. We herein demonstrated that basal hydrogen peroxide (H2O2) and APE1/Ref-1 expression levels were markedly higher in cancer cell lines than in non-cancerous cells. Elevated APE1/Ref-1 levels were associated with shorter survival in liver cancer patients. Mechanistically, we showed that H2O2 activated nuclear factor-κB (NF-κB). RelA/p65 inhibited the expression of the E3 ubiquitin ligase Parkin, possibly by interfering with ATF4 activity. Parkin was responsible for the ubiquitination and proteasomal degradation of APE1/Ref-1; therefore, the H2O2-induced suppression of Parkin expression increased APE1/Ref-1 levels. The probability of survival was lower in liver cancer patients with low Parkin and high RelA expression levels. Additionally, Parkin and RelA expression levels negatively and positively correlated with APE1/Ref-1 levels, respectively, in the TCGA liver cancer cohort. We concluded that increases in APE1/Ref-1 via the NF-κB and Parkin pathways are critical for cancer cell survival under oxidative stress. The present results show the potential of the NF-κB-Parkin-APE1/Ref-1 axis as a prognostic factor and therapeutic strategy to eradicate liver cancer.
A comparison of sampling and testing approaches for the surveillance of SARS-CoV-2 in farmed American mink

Surveillance for SARS-CoV-2 in American mink (Neovison vison) is a global priority because outbreaks on mink farms have potential consequences for animal and public health. Surveillance programs often focus on screening natural mortalities; however, significant knowledge gaps remain regarding sampling and testing approaches. Using 76 mink from 3 naturally infected farms in British Columbia, Canada, we compared the performance of 2 reverse-transcription real-time PCR (RT-rtPCR) targets (the envelope [E] and RNA-dependent RNA polymerase [RdRp] genes) as well as serology. We also compared RT-rtPCR and sequencing results from nasopharyngeal, oropharyngeal, skin, and rectal swabs, as well as nasopharyngeal samples collected using swabs and interdental brushes. We found that infected mink were generally RT-rtPCR–positive on all samples; however, Ct values differed significantly among sample types (nasopharyngeal < oropharyngeal < skin < rectal). There was no difference in the results of nasopharyngeal samples collected using swabs or interdental brushes. For most mink (89.4%), qualitative (i.e., positive vs. negative) serology and RT-rtPCR results were concordant. However, mink were positive on RT-rtPCR and negative on serology and vice versa, and there was no significant correlation between Ct values on RT-rtPCR and percent inhibition on serology. Both the E and RdRp targets were detectable in all sample types, albeit with a small difference in Ct values. Although SARS-CoV-2 RNA can be detected in multiple sample types, passive surveillance programs in mink should focus on multiple target RT-rtPCR testing of nasopharyngeal samples in combination with serology.
An Analysis of Multigenerational Issues of Generation X and Y Employees in Small- and Medium-Sized Enterprises in Thailand: The Moderation Effect of Age Groups on Person–Environment Fit and Turnover Intention

Multigenerational employees can evidently impact human resource management practices in terms of effective employee retention. Arguably, a high turnover intention of young employees can hinder a company’s human resource development, while a high volume of retirement of senior employees can create a skill deficit and even a labor management dilemma. This study explored how a supportive work environment can retain employees of different age groups in Thailand’s small- and medium-sized enterprises (SMEs), particularly Generation X and Y. It modeled a supportive work environment that impacts the behaviors of Generation X and Y employees, taking into consideration the relationship among factors such as person–job fit, person–group fit, person–supervisor fit, person–organization fit, person–environment fit, and turnover intention. This paper statistically analyzed a set of data drawn from an attentive survey of a total of 400 employees of SMEs in 4 populous provinces in Thailand using structural equation modeling (SEM) and multigroup analysis (MGA) with the moderation effect of generations. This paper then found that person–job fit, person–group fit, person–supervisor fit, person–organization fit, person–environment fit, and turnover intention can influence an employee’s intention to remain in his/her job. Additionally, the relationship manipulation among the aforementioned variables might influence Generation X and Y employees differently. Under the circumstances, supervisory support with less group involvement may encourage the retention of Generation Y employees, whereas a sufficient focus on job suitability could improve the retention of Generation X employees.
A Novel Ethyl Formate Fumigation Strategy for Managing Yellow Tea Thrips (Scirtothrips dorsalis) in Greenhouse Cultivated Mangoes and Post-Harvest Fruits

Simple Summary Climate change, along with increased demand for tropical fruits like mangoes, has led to an increase in greenhouse cultivation in South Korea, raising the risk of yellow tea thrips infestations. Our study explored ethyl formate fumigation as a safe, effective alternative to traditional pesticides in mango greenhouse cultivation and post-harvest storage. This novel fumigation method was successfully able to manage thrips without harming mango trees or fruits, offering an environmentally friendly pest management approach benefiting both farmers and consumers. Abstract The effects of climate change and shifting consumer preferences for tropical/subtropical mango fruits have accelerated their greenhouse cultivation in South Korea, which has consequently exacerbated the risk of unexpected or exotic insect pest outbreaks. This study used the pest risk analysis (PRA) of greenhouse-cultivated mangoes provided by the Animal & Plant Quarantine Agency in Korea to evaluate the potential of ethyl formate (EF) fumigation as a new pest management strategy against the yellow tea thrips (Scirtothrips dorsalis), which is considered a surrogate pest in the thrips group according to the PRA. The efficacy and phytotoxicity of EF were evaluated in greenhouse-cultivated mango tree (Irwin variety) and post-harvest mango fruit scenarios. EF efficacy ranged from 6.25 to 6.89 g∙h/m³ for lethal concentration time (LCt)50 and from 17.10 to 18.18 g∙h/m³ for LCt99, indicating similar efficacy across both scenarios. Application of 10 g/m³ EF for 4 h at 23 °C could effectively control S. dorsalis (100% mortality) without causing phytotoxic damage to the greenhouse-cultivated mango trees, while post-harvest mango fruit fumigation with 15 g/m³ EF for 4 h at 10 °C showed potential for complete disinfestation of S. dorsalis without compromising fruit quality.
Prenatal ultrasound for the diagnosis of the agenesis of corpus callosum: a meta-analysis

Abstract Background Prenatal ultrasound has been regularly used as the screening tool for agenesis of corpus callosum (ACC) of the fetuses, which were mainly suspected on the basis of indirect signs rather than the visualization of the CC. However, the diagnostic accuracy of prenatal ultrasound for ACC, compared to the gold standard of postmortem diagnosis or postnatal images, is still unknown. This meta-analysis was performed to comprehensively evaluate the efficacy of prenatal ultrasound for the diagnosis of ACC. Methods Studies evaluating the diagnostic accuracy of prenatal ultrasound for ACC compared to postmortem diagnosis or postnatal images were retrieved by searching PubMed, Embase, and Web of Science databases. Pooled sensitivity and specificity were calculated with a random-effects model. The diagnostic accuracy was measured by summarized area under the receiver operating characteristic (AUC) curve. Results Twelve studies involving 544 fetuses with suspected anomalies of central nervous system were included, and 143 of them were with validated diagnosis of ACC. Pooled results showed that prenatal ultrasound has satisfying diagnostic efficacy for ACC, with the pooled sensitivity, specificity, positive and negative likelihood ratios of 0.72 (95% confidence interval [CI]: 0.39–0.91), 0.98 (95% CI: 0.79–1.00), 43.73 (95% CI: 3.42–558.74, and 0.29 (95% CI: 0.11–0.74), respectively. The pooled AUC was 0.94 (95% CI: 0.92–0.96), suggesting good diagnostic performance of prenatal ultrasound. Subgroup analysis according to the prenatal ultrasound procedures showed a better diagnostic efficacy of neurosonography than that of regular ultrasound screening (sensitivity: 0.84 versus 0.57, specificity: 0.98 versus 0.89, and AUC: 0.97 versus 0.78). Conclusions Prenatal ultrasound, particularly for the neurosonography, confers satisfying efficacy for the diagnosis of ACC.
Treatment of Uncomplicated Type B Aortic Dissection: Optimal Medical Therapy vs TEVAR + Optimal Medical Therapy

Optimal Medical Therapy (OMT) has been the accepted mode of treatment for uncomplicated Type B Aortic Dissection (uTBAD). There is growing evidence that despite the short-term benefits of OMT, patients suffer deleterious consequences in the long-term with OMT alone. Thoracic Endovascular Aortic Repair (TEVAR) along with OMT has emerged as an alternative option for patients with uTBAD. This study evaluates the available literature for TEVAR + OMT as an alternative to OMT for treatment of uTBAD. In addition, issues related to TEVAR as a treatment for uTBAD are discussed.
Patent Ownership Fragmentation and Market Value: An Empirical Analysis

Patent ownership Fragmentation following the U.S. pro-patent shifts has built overlapping intellectual property rights or patent thickets. This has made the use of others’ innovations costlier due to transaction costs, licensing fees, and hold-up. Using panel data on 2,441 public U.S. manufacturing firms for 1976–2002, I find that patent thickets lower firms’ expected profit and their market value. I also find that firms with a large patent portfolio experience a smaller effect, likely because stronger bargaining position lowers the hold-up likelihood. There is no systematic time effect from patent thickets on firms’ market value with a large patent portfolio size.
Soft-Hard Event Engineering in Ultrarelativistic Heavy Ion Collisions

Event-by-event hydrodynamic simulations are combined with a generic energy loss model to show that: (i) high $p_T >10$ GeV azimuthal asymmetry in mid-central collisions is well described by a linear response given as $v^{\rm high}_{2}(p_T> 10 \;{\rm GeV})=\chi^{\rm high}_{2}(p_T) \varepsilon_{2}$ where $\varepsilon_{2}$ is the initial elliptic eccentricity that fluctuates from event to event and $\chi^{high}_{2}(p_T)$ is approximately independent of the event by event fluctuations of bulk (low $p_T < 2\; {\rm GeV}$) elliptic flow, (ii) the high $p_T$ $\pi^0$ nuclear modification observables $R_{AA}$, $v^{high}_2$, and $v^{high}_3$ are found to be compatible with available LHC data. Soft-Hard Event Engineering (SHEE) makes it possible to extract $\chi^{\rm high}_2(p_T)$ from sub-classes ${\cal C}^s$ of data on $v^{\rm high}_2(p_T; {\cal C}^s)$ selected not only by bins of centrality but also by bins of bulk elliptic flow far from the average to test different models of energy loss.
Relationship between Permeability and Structure of CO2-Assisted Polymer Compression Products

Membrane filters were fabricated from polyethylene terephthalate nonwoven fabrics with an average fiber diameter of 8 μm using the CO2-assisted polymer compression method. The filters were subjected to a liquid permeability test and structural analysis was performed using X-ray computed tomography to evaluate the tortuosity, pore size distribution, and percentage of open pores. Based on the results, filter tortuosity was proposed to be a function of porosity. Pore size estimated from the permeability test and X-ray computed tomography were in rough agreement. The ratio of open pores to all pores was as high as 98.5%, even at a porosity of 0.21. This may be due to the process of exhausting trapped high-pressure CO2 after molding. For filter applications, a high open-pore ratio is desirable since it means that many pores are involved in the fluid flow. The CO2-assisted polymer compression method was found to be suitable for the production of porous materials for filters.
Tight and Compact Sample Average Approximation for Joint Chance-Constrained Problems with Applications to Optimal Power Flow

In this paper, we tackle the resolution of chance-constrained problems reformulated via sample average approximation. The resulting data-driven deterministic reformulation takes the form of a large-scale mixed-integer program (MIP) cursed with Big-Ms. We introduce an exact resolution method for the MIP that combines the addition of a set of valid inequalities to tighten the linear relaxation bound with coefficient strengthening and constraint screening algorithms to improve its Big-Ms and considerably reduce its size. The proposed valid inequalities are based on the notion of k-envelopes and can be computed off-line using polynomial-time algorithms and added to the MIP program all at once. Furthermore, they are equally useful to boost the strengthening of the Big-Ms and the screening rate of superfluous constraints. We apply our procedures to a probabilistically constrained version of the DC optimal power flow problem with uncertain demand. The chance constraint requires that the probability of violating any of the power system’s constraints be lower than some positive threshold. In a series of numerical experiments that involve five power systems of different size, we show the efficiency of the proposed methodology and compare it with some of the best performing convex inner approximations currently available in the literature. History: Accepted by Andrea Lodi, Area Editor for Design & Analysis of Algorithms – Discrete. Funding: This work was supported in part by the European Research Council under the EU Horizon 2020 research and innovation program [Grant 755705], in part by the Spanish Ministry of Science and Innovation [Grant AEI/10.13039/501100011033] through project PID2020-115460GB-I00, and in part by the Junta de Andalucía and the European Regional Development Fund through the research project P20_00153. Á. Porras is also financially supported by the Spanish Ministry of Science, Innovation and Universities through the University Teacher Training Program with fellowship number FPU19/03053. Supplemental Material: The online supplement is available at https://doi.org/10.1287/ijoc.2022. 0302 .
Taylor columns and inertial-like waves in a three-dimensional odd viscous liquid

Abstract Odd viscous liquids are endowed with an intrinsic mechanism that tends to restore a displaced particle back to its original position. Since the odd viscous stress does not dissipate energy, inertial oscillations and inertial-like waves can become prominent in such a liquid. In this paper, we show that an odd viscous liquid in three dimensions may give rise to such axially symmetric waves and also to plane-polarized waves. We assume tacitly that an anisotropy axis giving rise to odd viscous effects has already been established, and proceed to investigate the effects of odd viscosity on fluid flow behaviour. Numerical simulations of the full Navier–Stokes equations show the existence of inertial-like waves downstream of a body that moves slowly along the axis of an odd viscous liquid filled cylinder. The wavelength of the numerically determined oscillations agrees well with the developed theoretical framework. When odd viscosity is the dominant effect in steady motions, a modified Taylor–Proudman theorem leads to the existence of Taylor columns inside such a liquid. Formation of the Taylor column can be understood as a consequence of helicity segregation and energy transfer along the cylinder axis at group velocity, by the accompanying inertial-like waves, whenever the reflection symmetry of the system is lost. A number of Taylor column characteristics known from rigidly rotating liquids are recovered here for a non-rotating odd viscous liquid. These include counter-rotating swirling liquid flow above and below a body moving slowly along the anisotropy axis. Thus in steady motions, odd viscosity acts to suppress variations of liquid velocity in a direction parallel to the anisotropy axis, inhibiting vortex stretching and vortex twisting. In unsteady and nonlinear motions, odd viscosity enhances the vorticity along the same axis, thus affecting both vortex stretching and vortex twisting.
GroundNLQ @ Ego4D Natural Language Queries Challenge 2023

In this report, we present our champion solution for Ego4D Natural Language Queries (NLQ) Challenge in CVPR 2023. Essentially, to accurately ground in a video, an effective egocentric feature extractor and a powerful grounding model are required. Motivated by this, we leverage a two-stage pre-training strategy to train egocentric feature extractors and the grounding model on video narrations, and further fine-tune the model on annotated data. In addition, we introduce a novel grounding model GroundNLQ, which employs a multi-modal multi-scale grounding module for effective video and text fusion and various temporal intervals, especially for long videos. On the blind test set, GroundNLQ achieves 25.67 and 18.18 for R1@IoU=0.3 and R1@IoU=0.5, respectively, and surpasses all other teams by a noticeable margin. Our code will be released at\url{https://github.com/houzhijian/GroundNLQ}.
Hyper-parameter Adaptation of Conformer ASR Systems for Elderly and Dysarthric Speech Recognition

Automatic recognition of disordered and elderly speech remains highly challenging tasks to date due to data scarcity. Parameter fine-tuning is often used to exploit the large quantities of non-aged and healthy speech pre-trained models, while neural architecture hyper-parameters are set using expert knowledge and remain unchanged. This paper investigates hyper-parameter adaptation for Conformer ASR systems that are pre-trained on the Librispeech corpus before being domain adapted to the DementiaBank elderly and UASpeech dysarthric speech datasets. Experimental results suggest that hyper-parameter adaptation produced word error rate (WER) reductions of 0.45% and 0.67% over parameter-only fine-tuning on DBank and UASpeech tasks respectively. An intuitive correlation is found between the performance improvements by hyper-parameter domain adaptation and the relative utterance length ratio between the source and target domain data.
Towards Sybil Resilience in Decentralized Learning

Federated learning is a privacy-enforcing machine learning technology but suffers from limited scalability. This limitation mostly originates from the internet connection and memory capacity of the central parameter server, and the complexity of the model aggregation function. Decentralized learning has recently been emerging as a promising alternative to federated learning. This novel technology eliminates the need for a central parameter server by decentralizing the model aggregation across all participating nodes. Numerous studies have been conducted on improving the resilience of federated learning against poisoning and Sybil attacks, whereas the resilience of decentralized learning remains largely unstudied. This research gap serves as the main motivator for this study, in which our objective is to improve the Sybil poisoning resilience of decentralized learning. We present SybilWall, an innovative algorithm focused on increasing the resilience of decentralized learning against targeted Sybil poisoning attacks. By combining a Sybil-resistant aggregation function based on similarity between Sybils with a novel probabilistic gossiping mechanism, we establish a new benchmark for scalable, Sybil-resilient decentralized learning. A comprehensive empirical evaluation demonstrated that SybilWall outperforms existing state-of-the-art solutions designed for federated learning scenarios and is the only algorithm to obtain consistent accuracy over a range of adversarial attack scenarios. We also found SybilWall to diminish the utility of creating many Sybils, as our evaluations demonstrate a higher success rate among adversaries employing fewer Sybils. Finally, we suggest a number of possible improvements to SybilWall and highlight promising future research directions.
Value of Information in Games with Multiple Strategic Information Providers

In the classical communication setting multiple senders having access to the same source of information and transmitting it over channel(s) to a receiver in general leads to a decrease in estimation error at the receiver as compared with the single sender case. However, if the objectives of the information providers are different from that of the estimator, this might result in interesting strategic interactions and outcomes. In this work, we consider a hierarchical signaling game between multiple senders (information designers) and a single receiver (decision maker) each having their own, possibly misaligned, objectives. The senders lead the game by committing to individual information disclosure policies simultaneously, within the framework of a non-cooperative Nash game among themselves. This is followed by the receiver's action decision. With Gaussian information structure and quadratic objectives (which depend on underlying state and receiver's action) for all the players, we show that in general the equilibrium is not unique. We hence identify a set of equilibria and further show that linear noiseless policies can achieve a minimal element of this set. Additionally, we show that competition among the senders is beneficial to the receiver, as compared with cooperation among the senders. Further, we extend our analysis to a dynamic signaling game of finite horizon with Markovian information evolution. We show that linear memoryless policies can achieve equilibrium in this dynamic game. We also consider an extension to a game with multiple receivers having coupled objectives. We provide algorithms to compute the equilibrium strategies in all these cases. Finally, via extensive simulations, we analyze the effects of multiple senders in varying degrees of alignment among their objectives.
Identifying Socially Disruptive Policies

Social disruption occurs when a policy creates or destroys many network connections between agents. It is a costly side effect of many interventions and so a growing empirical literature recommends measuring and accounting for social disruption when evaluating the welfare impact of a policy. However, there is currently little work characterizing what can actually be learned about social disruption from data in practice. In this paper, we consider the problem of identifying social disruption in a research design that is popular in the literature. We provide two sets of identification results. First, we show that social disruption is not generally point identified, but informative bounds can be constructed using the eigenvalues of the network adjacency matrices observed by the researcher. Second, we show that point identification follows from a theoretically motivated monotonicity condition, and we derive a closed form representation. We apply our methods in two empirical illustrations and find large policy effects that otherwise might be missed by alternatives in the literature.