Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimal annuitization post-retirement with labor income

Evidence shows that the labor participation rate of retirement age cohorts is non-negligible, and it is a widespread phenomenon globally. In the United States, the labor force participation rate for workers age 75 and older is projected to be over 10 percent by 2026 as reported by the Bureau of Labor Statistics. The prevalence of post-retirement work changes existing considerations of optimal annuitization, a research question further complicated by novel factors such as post-retirement labor rates, wage rates, and capacity or willingness to work. To our knowledge, this poses a practical and theoretical problem not previously investigated in actuarial literature. In this paper, we study the problem of post-retirement annuitization with extra labor income in the framework of stochastic control, optimal stopping, and expected utility maximization. The utility functions are of the Cobb-Douglas type. The martingale methodology and duality techniques are employed to obtain closed-form solutions for the dual and primal problems. The effect of labor income is investigated by exploiting the explicit solutions and Monte-Carlo simulation. The latter reveals that the optimal annuitization time is strongly linear with respect to the initial wealth, with or without labor income. When it comes to optimal annuitization, we find that the wage and labor rates may play opposite roles. However, their impact is mediated by the leverage ratio.
Generalized Strategic Classification and the Case of Aligned Incentives

Strategic classification studies learning in settings where self-interested users can strategically modify their features to obtain favorable predictive outcomes. A key working assumption, however, is that"favorable"always means"positive"; this may be appropriate in some applications (e.g., loan approval), but reduces to a fairly narrow view of what user interests can be. In this work we argue for a broader perspective on what accounts for strategic user behavior, and propose and study a flexible model of generalized strategic classification. Our generalized model subsumes most current models but includes other novel settings; among these, we identify and target one intriguing sub-class of problems in which the interests of users and the system are aligned. This setting reveals a surprising fact: that standard max-margin losses are ill-suited for strategic inputs. Returning to our fully generalized model, we propose a novel max-margin framework for strategic learning that is practical and effective, and which we analyze theoretically. We conclude with a set of experiments that empirically demonstrate the utility of our approach.
Generating Training Data with Language Models: Towards Zero-Shot Language Understanding

Pretrained language models (PLMs) have demonstrated remarkable performance in various natural language processing tasks: Unidirectional PLMs (e.g., GPT) are well known for their superior text generation capabilities; bidirectional PLMs (e.g., BERT) have been the prominent choice for natural language understanding (NLU) tasks. While both types of models have achieved promising few-shot learning performance, their potential for zero-shot learning has been underexplored. In this paper, we present a simple approach that uses both types of PLMs for fully zero-shot learning of NLU tasks without requiring any task-specific data: A unidirectional PLM generates class-conditioned texts guided by prompts, which are used as the training data for fine-tuning a bidirectional PLM. With quality training data selected based on the generation probability and regularization techniques (label smoothing and temporal ensembling) applied to the fine-tuning stage for better generalization and stability, our approach demonstrates strong performance across seven classification tasks of the GLUE benchmark (e.g., 72.3/73.8 on MNLI-m/mm and 92.8 on SST-2), significantly outperforming zero-shot prompting methods and achieving even comparable results to strong few-shot approaches using 32 training samples per class.
Log-based Anomaly Detection with Deep Learning: How Far Are We?

Software-intensive systems produce logs for troubleshooting pur-poses. Recently, many deep learning models have been proposed to automatically detect system anomalies based on log data. These models typically claim very high detection accuracy. For example, most models report an F-measure greater than 0.9 on the commonly-used HDFS dataset. To achieve a profound understanding of how far we are from solving the problem of log-based anomaly detection, in this paper, we conduct an in-depth analysis of five state-of-the-art deep learning-based models for detecting system anomalies on four public log datasets. Our experiments focus on several aspects of model evaluation, including training data selection, data grouping, class distribution, data noise, and early detection ability. Our re-sults point out that all these aspects have significant impact on the evaluation, and that all the studied models do not always work well. The problem of log-based anomaly detection has not been solved yet. Based on our findings, we also suggest possible future work.
Performance of BeBe, a proposed dedicated beam-beam monitoring detector for the MPD-NICA experiment at JINR

The Multipurpose Detector (MPD) is an experimental array, currently under construction, designed to study the nuclear matter created during the collisions that will be provided by the Nuclotron-based Ion Collider fAcility (NICA) at JINR. The MPD-NICA experiment consists of a typical array of particle detectors as those used to study heavy-ion collisions at LHC and RHIC. To increase the trigger capabilities of MPD for stage 2 of NICA operation, a detector constituted by two arrays of 80 plastic scintillator cells each located symmetrically at opposite sides of the interaction point of MPD is proposed (BeBe). Based on Monte Carlo simulations, a discussion of the potential physics performance of BeBe detector is given for triggering tasks and for the resolution in the determination of the event plane reaction and the centrality of the collisions at NICA. Also, laboratory measurements to estimate the time resolution of individual BeBe cells prototypes are presented. It is shown that a time resolution between 0.47 and 1.39 ns can be reached depending on the number of photosensors employed to collect the scintillation photons. The BeBe detector will be complementary to FFD and FHCAL forward detectors.
Methodology to Assess Quality, Presence, Empathy, Attitude, and Attention in 360-degree Videos for Immersive Communications

This paper proposes a methodology to assess video quality, spatial and social presence, empathy, attitude, and attention in 360-degree videos for immersive communications. The methodology is validated in an experiment which simulates an immersive communication environment where participants attend three conversations of different genre (everyday conversation, educational, and discussion) and from actor and observer acquisition perspectives. We consider three experimental conditions: (A) visualizing and rating the perceptual quality of contents in a Head-Mounted Display (HMD), (B) visualizing the contents in an HMD, and (C) visualizing the contents in an HMD where participants can see their hands and take notes. In all conditions participants visualize the same 360-degree videos, designed and acquired in the context of international experiences. Fifty-four participants were evenly distributed among A, B, and C conditions taking into account their international experience backgrounds (working or studying in a foreign country), obtaining a balanced and diverse sample of participants. In this paper, video quality is evaluated with Single-Stimulus Discrete Quality Evaluation (SSDQE) methodology. Spatial and social presence are evaluated with questionnaires adapted from the literature. Initial empathy is assessed with Interpersonal Reactivity Index (IRI) and a questionnaire is designed to evaluate the attitude after the visualization of each video. Attention is evaluated with three questions about the conversations of the contents that had pass/fail answers. The results from the subjective test validate the proposed methodology in immersive communications, showing that video quality experiments can be adapted to conditions imposed by experiments focused on the evaluation of socioemotional features in terms of contents of long-duration, different acquisition perspectives, and genre. In addition, the positive results related to the sense of social and spatial presence imply that technology can be relevant in the analyzed use case. Other main result is that the acquisition perspective greatly influences social presence. Finally, the annotated dataset, Student Experiences Around the World dataset (SEAW-dataset), obtained from the experiment is made publicly available for the research community.
Innovative Randomized Phase I Study and Dosing Regimen Selection to Accelerate and Inform Pivotal COVID‐19 Trial of Nirmatrelvir

Coronavirus disease 2019 (COVID‐19) is a continued leading cause of hospitalization and death. Safe, efficacious COVID‐19 antivirals are needed urgently. Nirmatrelvir (PF‐07321332), the first orally bioavailable, severe acute respiratory syndrome‐coronavirus 2 (SARS‐CoV‐2) Mpro inhibitor against the coronaviridae family, has demonstrated potent preclinical antiviral activity and benign safety profile. We report safety, tolerability, and pharmacokinetic data of nirmatrelvir with and without ritonavir as a pharmacokinetic enhancer, from an accelerated randomized, double‐blind, placebo‐controlled, phase I study. Two interleaving single‐ascending dose (SAD) cohorts were evaluated in a three‐period crossover. Multiple‐ascending dose (MAD) with nirmatrelvir/ritonavir twice daily (b.i.d.) dosing was evaluated over 10 days in five parallel cohorts. Safety was assessed, including in a supratherapeutic exposure cohort. Dose and dosing regimen for clinical efficacy evaluation in phase II/III clinical trials were supported by integrating modeling and simulations of SAD/MAD data with nonclinical data and a quantitative systems pharmacology model (QSP). In SAD, MAD, and supratherapeutic exposure cohorts, nirmatrelvir/ritonavir was safe and well‐tolerated. Nirmatrelvir exposure and half‐life were considerably increased by ritonavir, enabling selection of nirmatrelvir/ritonavir dose and regimen for phase II/III trials (300/100 mg b.i.d.), to achieve concentrations continuously above those required for 90% inhibition of viral replication in vitro. The QSP model suggested that a 5‐day regimen would significantly decrease viral load in SARS‐CoV‐2‐infected patients which may prevent development of severe disease, hospitalization, and death. In conclusion, an innovative and seamless trial design expedited establishment of phase I safety and pharmacokinetics of nirmatrelvir/ritonavir, enabling high confidence in phase II/III dose selection and accelerated pivotal trials’ initiation (NCT04756531).
Effects of an Alphasatellite on the Life Cycle of the Nanovirus Faba Bean Necrotic Yellows Virus

Alphasatellites are circular single-stranded DNA molecules frequently found in association with natural isolates of nanoviruses and some geminiviruses, the two ssDNA plant-infecting virus families. While the implications of alphasatellite presence in geminivirus infections are relatively well documented, comparable studies on alphasatellites associated with nanoviruses are not available. ABSTRACT Nanoviruses are plant viruses with a multipartite single-stranded DNA (ssDNA) genome. Alphasatellites are commonly associated with nanovirus infections, but their putative impact on their helper viruses is unknown. In this study, we investigated the role of subterranean clover stunt alphasatellite 1 (here named SCSA 1) on various important traits of Faba bean necrotic yellows virus (FBNYV) in its host plant Vicia faba and aphid vector Acyrthosiphon pisum, including disease symptoms, viral accumulation, and viral transmission. The results indicate that SCSA 1 does not affect the severity of symptoms nor overall FBNYV accumulation in V. faba, but it does change the relative amounts of its different genomic segments. Moreover, the association of SCSA 1 with FBNYV increases the rate of plant-to-plant transmission by a process seemingly unrelated to the simple increase of viral accumulation in the vector. These results represent the first study on the impact of an alphasatellite on the biology of its helper nanovirus. They suggest that SCSA 1 may benefit FBNYV, but the genericity of this conclusion is discussed and questioned. IMPORTANCE Alphasatellites are circular single-stranded DNA molecules frequently found in association with natural isolates of nanoviruses and some geminiviruses, the two ssDNA plant-infecting virus families. While the implications of alphasatellite presence in geminivirus infections are relatively well documented, comparable studies on alphasatellites associated with nanoviruses are not available. Here, we confirm that subterranean clover stunt alphasatellite 1 affects different traits of its helper nanovirus, Faba bean necrotic yellows virus, both in the host plant and aphid vector. We show that the frequencies of the virus segments change in the presence of alphasatellite, in both the plant and the vector. We also confirm that although within-plant virus load and symptoms are not affected by alphasatellite, the presence of alphasatellite decreases within-aphid virus load but significantly increases virus transmission rate, and thus it may confer a possible evolutionary advantage for the helper virus.
Novel Humanized Peripheral Blood Mononuclear Cell Mouse Model with Delayed Onset of Graft-versus-Host Disease for Preclinical HIV Research

Currently, there is no cure or vaccine for HIV infection; thus, continued research is needed to end the HIV pandemic. While many animal models are used in HIV research, none is used more than the humanized mouse model. ABSTRACT Humanized mouse models are based on the engraftment of human cells in immunodeficient mouse strains, most notably the NSG strain. Most used models have a major limitation in common, the development of graft-versus-host disease (GVHD). GVHD not only introduces variabilities into the research data but also leads to animal welfare concerns. A new mouse strain, B6.129S-Rag2tm1Fwa CD47tm1Fpl Il2rgtm1Wjl/J, which lacks Rag1, IL2rg, and CD47 (triple knockout [TKO]), is resistant to GVHD development. We transplanted TKO mice with human peripheral blood mononuclear cells (PBMCs) to establish a new humanized PBMC (hu-PBMC) mouse model. A cohort of these mice was infected with HIV-1 and monitored for plasma HIV viremia and CD4+ T cell depletion. The onset and progression of GVHD were monitored by clinical signs. This study demonstrates that TKO mice transplanted with human PBMCs support engraftment of human immune cells in primary and secondary lymphoid tissues, rectum, and brain. Moreover, the TKO hu-PBMC model supports HIV-1 infection via the intraperitoneal, rectal, or vaginal route, as confirmed by robust plasma HIV viremia and CD4+ T cell depletion. Lastly, TKO mice showed a delayed onset of GVHD clinical signs (∼24 days) and exhibited significant decreases in plasma levels of tumor necrosis factor beta (TNF-β). Based on these results, the TKO hu-PBMC mouse model not only supports humanization and HIV-1 infection but also has a delayed onset of GVHD development, making this model a valuable tool in HIV research. IMPORTANCE Currently, there is no cure or vaccine for HIV infection; thus, continued research is needed to end the HIV pandemic. While many animal models are used in HIV research, none is used more than the humanized mouse model. A major limitation with current humanized mouse models is the development of graft-versus-host disease (GVHD). Here, we describe a novel humanized-PBMC mouse model that has a delayed onset GVHD development and supports and models HIV infection comparably to well-established humanized mouse models.
App based education programme to reduce salt intake (AppSalt) in schoolchildren and their families in China: parallel, cluster randomised controlled trial

Abstract Objective To determine whether a smartphone application based education programme can lower salt intake in schoolchildren and their families. Design Parallel, cluster randomised controlled trial, with schools randomly assigned to either intervention or control group (1:1). Setting 54 primary schools from three provinces in northern, central, and southern China, from 15 September 2018 to 27 December 2019. Participants 592 children (308 (52.0%) boys; mean age 8.58 (standard deviation 0.41) years) in grade 3 of primary school (about 11 children per school) and 1184 adult family members (551 (46.5%) men; mean age 45.80 (12.87) years). Intervention Children in the intervention group were taught, with support of the app, about salt reduction and assigned homework to encourage their families to participate in activities to reduce salt consumption. Main outcome measures Primary outcome was the difference in salt intake change (measured by 24 hour urinary sodium excretion) at 12 month follow-up, between the intervention and control groups. Results After baseline assessment, 297 children and 594 adult family members (from 27 schools) were allocated to the intervention group, and 295 children and 590 adult family members (from 27 schools) were allocated to the control group. During the trial, 27 (4.6%) children and 112 (9.5%) adults were lost to follow-up, owing to children having moved to another school or adults unable to attend follow-up assessments. The remaining 287 children and 546 adults (from 27 schools) in the intervention group and 278 children and 526 adults (from 27 schools) in the control group completed the 12 month follow-up assessment. Mean salt intake at baseline was 5.5 g/day (standard deviation 1.9) in children and 10.0 g/day (3.5) in adults in the intervention group, and 5.6 g/day (2.1) in children and 10.0 g/day (3.6) in adults in the control group. During the study, salt intake of the children increased in both intervention and control groups but to a lesser extent in the intervention group (mean effect of intervention after adjusting for confounding factors −0.25 g/day, 95% confidence interval −0.61 to 0.12, P=0.18). In adults, salt intake decreased in both intervention and control groups but to a greater extent in the intervention group (mean effect −0.82 g/day, −1.24 to −0.40, P<0.001). The mean effect on systolic blood pressure was −0.76 mm Hg (−2.37 to 0.86, P=0.36) in children and −1.64 mm Hg (−3.01 to −0.27, P=0.02) in adults. Conclusions The app based education programme delivered through primary school, using a child-to-parent approach, was effective in lowering salt intake and systolic blood pressure in adults, but the effects were not significant in children. Although this novel approach could potentially be scaled up to larger populations, the programme needs further strengthening to reduce salt intake across the whole population, including schoolchildren. Trial registration Chinese Clinical Trial Registry ChiCTR1800017553.
Spatial and temporal characteristics of harmful algal blooms in Zhejiang Province waters during 1933–2018

ABSTRACT Harmful algal bloom (HAB) data included events caused by toxic species and non-toxic species, and was collected from red tide outbreaks in the Zhejiang Province coastal waters during 1933–2018. The geostatistical tools in Geographic Information System (GIS) were used to analyse the spatial and temporal distributions of these red tide events and map the distribution of these events in the study area. The results show that: (1) three areas had very-high frequency of red tide: Shengshan waters, Eastern waters of Zhujiajian and Nanji Islands waters. (2) The red tide occurrences exhibited significant seasonality: May is the most likely time for a red tide outbreak in Zhejiang waters. (3) Prorocentrum donghaiense occurred 182 times, Karenia mikimotoi occurred 64 times and Skeletonema costatum occurred 59 times in the total events. Prorocentrum donghaiense and Karenia mikimotoi are the algae species that are most prone to forming red tides in Zhejiang waters. This study utilized a visual approach to identify the scope, distribution and characteristics of red tide in the Zhejiang Province coastal waters over the past 85 years more fully, thus providing useful information to support the monitoring and management programme for HABs.
A highly sensitive nanobiosensor based on aptamer-conjugated graphene-decorated rhodium nanoparticles for detection of HER2-positive circulating tumor cells

Abstract Assessment of human epidermal growth factor receptor-2 (HER2) tumor marker status is an impressive factor in screening, diagnosing and monitoring breast cancer (BC). The electrochemical biosensor is a revolutionary method in cancer diagnosis, which is used in this research to detect HER2+ circulating tumor cells. The electrochemical activity, size, shape, and morphology of the synthesized nanomaterials were analyzed. The hybrid nanocomposite established by the coupling of reduced graphene oxide nanosheets (rGONs) and rhodium nanoparticles (Rh-NPs) on the surface of graphite electrode resulted in improved surface area, electrochemical activity, and biocompatibility. The graphite electrode-based aptasensor (g-aptasensor) demonstrated exceptional performance against HER2-overexpressed SKBR3 cancer cells, with a linear dynamic range of 5.0 to 10.0 × 104 cells/mL, an analytical limit of detection (LOD) as low as 1.0 cell/mL, and a limit of quantification (LOQ) of 3.0 cells/mL. The G-rich DNA aptamers can fold into an intermolecular G-quadruplex, which specifically bind to the target molecule. Consequently, the advantages of this highly efficient nanocomposite platform include broad dynamic range, high specificity, selectivity, stability, reproducibility, and low cost. These characteristics indicate that the fabricated nanobiosensor has a high potential for use in detecting and monitoring HER2 level for the care of BC patients and clinical diagnosis.
A case for co-construction with teachers in curricular reform: Introducing computer science in primary school

With the introduction of Computer Science (CS) into curricula worldwide, researchers have investigated whether CS could be introduced transversally, as a support other disciplines. Few however consider both student learning and the teachers’ perspective in their assessments. In a co-constructive approach to translational research, we collaborated with teachers, in two case studies involving two classes each, to investigate how CS content could be used transversally. More specifically, teacher inputs and student learning data were combined in a mixed methods analysis to determine whether two CS Unplugged (CSU) activities from the curriculum could be leveraged to teach disciplinary content in primary school. The findings indicated that the CSU activities could be leveraged for maths and spelling, but require validation at a larger scale. More important, though, are the takeaways of the co-constructive experience with teachers. Interestingly the benefits of co-construction went both ways. While researchers gained a deeper understanding of the effectiveness of the activities, teachers i) appreciated having detailed student learning analyses, devoid of biases and impressions, ii) changed their perspective about researchers, and iii) were open to other collaborative research initiatives which they found to be drivers of change and innovation in their practice. The way co-construction was approached also impacted the teachers’ perception of their experience. Indeed, while one study was researcher-driven and included teachers, the other was teacher-driven and included researchers. When teacher-driven, the teachers felt they had a more active role, thus reflecting more on the study design, results and implications. Provided the positive impact that co-construction may have on innovation in teacher practices, different co-construction modalities must be investigated, as well as their implications on all stakeholders, including researchers.