Miracle-dz/UniFAR-FTUs huggingface dataset:
Formal Language Theory Meets Modern NLP

NLP is deeply intertwined with the formal study of language, both conceptually and historically. Arguably, this connection goes all the way back to Chomsky's Syntactic Structures in 1957. It also still holds true today, with a strand of recent works building formal analysis of modern neural networks methods in terms of formal languages. In this document, I aim to explain background about formal languages as they relate to this recent work. I will by necessity ignore large parts of the rich history of this field, instead focusing on concepts connecting to modern deep learning-based NLP.
Mutation of daf‐2 extends lifespan via tissue‐specific effectors that suppress distinct life‐limiting pathologies

In aging Caenorhabditis elegans, as in higher organisms, there is more than one cause of death. C. elegans exhibit early death with a swollen, infected pharynx (P death), and later death with pharyngeal atrophy (p death). Interventions that alter lifespan can differentially affect frequency and timing of each type of death, generating complex survival curve shapes. Here, we use mortality deconvolution analysis to investigate how reduction of insulin/IGF‐1 signaling (IIS), which increases lifespan (the Age phenotype), affects different forms of death. All daf‐2 insulin/IGF‐1 receptor mutants exhibit increased lifespan in the p subpopulation (p Age), while pleiotropic class 2 daf‐2 mutants show an additional marked reduction in P death frequency. The latter is promoted by pharyngeal expression of the IIS‐regulated DAF‐16 FOXO transcription factor, and at higher temperature by reduced pharyngeal pumping rate. Pharyngeal DAF‐16 also promotes p Age in class 2 daf‐2 mutants, revealing a previously unknown role for the pharynx in the regulation of aging. Necropsy analysis of daf‐2 interactions with the daf‐12 steroid receptor implies that previously described opposing effects of daf‐12 on daf‐2 longevity are attributable to internal hatching of larvae, rather than complex interactions between insulin/IGF‐1 and steroid signaling. These findings support the view that wild‐type IIS acts through multiple distinct mechanisms which promote different life‐limiting pathologies, each of which contribute to late‐life mortality. This study further demonstrates the utility of mortality deconvolution analysis to better understand the genetics of lifespan.
Versatile nonlinear-optical materials based on mesomorphic metal alkanoates: design, properties, and applications

Metal alkanoates combine simple chemical structures and a versatility of condensed states of matter they exhibit. Solid crystals, plastic crystals, lyotropic and thermotropic ionic liquid crystals, liquids, mesomorphic glasses, and Langmuir–Blodgett films are just a few examples. Liquid crystal phases of metal alkanoates are the most intriguing because they represent a non-conventional class of materials known as ionic metallomesogens. Structural, thermal, and transport properties of mesomorphic metal alkanoates are well documented and reviewed. On the contrary, the optical and nonlinear-optical properties of these materials are very poorly understood. The situation has changed rapidly during the last decade. Advances in the design of mesomorphic glasses stable at room temperatures have launched a new era of research in the field of photonic and optoelectronic materials based on mesomorphic metal alkanoates. This manuscript reviews recent developments in the field of optical and nonlinear-optical materials based on mesomorphic metal alkanoates.
Prakriti Analysis of COVID 19 Patients: An Observational Study.

Rationale & Objective The concept of Prakriti is unique to Ayurveda, which is used for deciding the preventive and curative strategy to be adopted in the treatment of patients. It is the total of anatomical, physiological, and psychological domains of an individual. The diseases often manifest by susceptibility that depends upon Prakriti of individuals. COVID 19 is a new disease, where the status of the susceptibility of its victim in terms of Prakriti is not known. This study has been undertaken to determine the Prakriti of COVID 19 positive patients. Method The validated instrument CCRAS Prakriti assessment scale has been applied to the COVID 19 positive patients admitted between 16 May 2020 to 10 June 2020 at COVID hospital. Result Data of 117 patients aged 10 to 80 years have been analyzed. The ratio of male-female patients was 1.8:1. Most patients belonged to Vata-KaphaPrakriti (27%). Individuals with their Prakriti found in order of frequency were Pitta-Kapha (21%), Kapha (20%), Vata (13%), Vata-Pitta (11%), Sama (4%) and Pitta (3%). Conclusion Patients with Vata-Kapha, Pitta-Kapha, and Kapha dominant Prakriti have been found more in COVID19. The treatment strategies can be accordingly decided in respect of each patient.
Realistic High-Resolution Body Computed Tomography Image Synthesis by Using Progressive Growing Generative Adversarial Network: Visual Turing Test

Background Generative adversarial network (GAN)–based synthetic images can be viable solutions to current supervised deep learning challenges. However, generating highly realistic images is a prerequisite for these approaches. Objective The aim of this study was to investigate and validate the unsupervised synthesis of highly realistic body computed tomography (CT) images by using a progressive growing GAN (PGGAN) trained to learn the probability distribution of normal data. Methods We trained the PGGAN by using 11,755 body CT scans. Ten radiologists (4 radiologists with <5 years of experience [Group I], 4 radiologists with 5-10 years of experience [Group II], and 2 radiologists with >10 years of experience [Group III]) evaluated the results in a binary approach by using an independent validation set of 300 images (150 real and 150 synthetic) to judge the authenticity of each image. Results The mean accuracy of the 10 readers in the entire image set was higher than random guessing (1781/3000, 59.4% vs 1500/3000, 50.0%, respectively; P<.001). However, in terms of identifying synthetic images as fake, there was no significant difference in the specificity between the visual Turing test and random guessing (779/1500, 51.9% vs 750/1500, 50.0%, respectively; P=.29). The accuracy between the 3 reader groups with different experience levels was not significantly different (Group I, 696/1200, 58.0%; Group II, 726/1200, 60.5%; and Group III, 359/600, 59.8%; P=.36). Interreader agreements were poor (κ=0.11) for the entire image set. In subgroup analysis, the discrepancies between real and synthetic CT images occurred mainly in the thoracoabdominal junction and in the anatomical details. Conclusions The GAN can synthesize highly realistic high-resolution body CT images that are indistinguishable from real images; however, it has limitations in generating body images of the thoracoabdominal junction and lacks accuracy in the anatomical details.
Increased Risk of High-grade Cervical Neoplasia in Women with Inflammatory Bowel Disease: A Case-controlled Cohort Study

Abstract Background and Aims Women with inflammatory bowel disease [IBD] may be at higher risk for cervical intraepithelial neoplasia [CIN]. However, data are conflicting. The aim of this study was to assess the risk of high-grade dysplasia and cancer [CIN2+] in IBD women and identify risk factors. Methods Clinical data from adult IBD women in a multicentre Dutch IBD prospective cohort [PSI] from 2007 onwards were linked to cervical cytology and histology records from the Dutch nationwide cytology and pathology database [PALGA], from 2000 to 2016. Patients were frequency-matched 1:4 to a general population cohort. Standardised detection rates [SDR] were calculated for CIN2+. Longitudinal data were assessed to calculate CIN2+ risk during follow-up using incidence rate ratios [IRR] and risk factors were identified in multivariable analysis. Results Cervical records were available from 2098 IBD women [77%] and 8379 in the matched cohort; median follow-up was 13 years. CIN2+ detection rate was higher in the IBD cohort than in the matched cohort (SDR 1.27, 95% confidence interval [CI] 1.05–1.52). Women with IBD had an increased risk of CIN2+ [IRR 1.66, 95% CI 1.21–2.25] and persistent or recurrent CIN during follow-up (odds ratio [OR] 1.89, 95% CI 1.06–3.38). Risk factors for CIN2+ in IBD women were smoking and disease location (ileocolonic [L3] or upper gastrointestinal [GI] [L4]). CIN2+ risk was not associated with exposure to immunosuppressants. Conclusions Women with IBD are at increased risk for CIN2+ lesions. These results underline the importance of human papillomavirus [HPV] vaccination and adherence to cervical cancer screening guidelines in IBD women, regardless of exposure to immunosuppressants.
miR‐17‐3p promotes the proliferation of multiple myeloma cells by downregulating P21 expression through LMLN inhibition

Multiple myeloma (MM), a hematological malignancy, has a poor prognosis and requires an invasive procedure. Reports have implicated miRNAs in the diagnosis, treatment and prognosis of hematological malignancies. In our study, we evaluated the expression profiles of miR‐17‐3p in plasma and bone marrow mononuclear cells of monoclonal gammopathy of undetermined significance (MGUS) and MM patients and healthy subjects. The results showed that the plasma and mononuclear cell expression levels of miR‐17‐3p in MM patients were higher than those in MGUS patients and normal controls. In addition, the expression of miR‐17‐3p was positively correlated with diagnostic indexes, such as marrow plasma cell abundance and serum M protein level, and positively correlated with the International Staging System stage of the disease. Receiver operating characteristic curve analysis suggested that miR‐17‐3p might be a diagnostic index of MM. Moreover, miR‐17‐3p regulated cell proliferation, apoptosis and the cell cycle through P21 in MM cell lines and promoted MM tumor growth in vivo. Furthermore, we predicted and verified LMLN as a functional downstream target gene of miR‐17‐3p. Negatively regulated by miR‐17‐3p, LMLN inhibits MM cell growth, exerting a tumor suppressive function through P21. Taken together, our data identify miR‐17‐3p as a promising diagnostic biomarker for MM in the clinic and unveil a new miR‐17‐3p‐LMLN‐P21 axis in MM progression.
Size Distribution and Source Apportionment of Airborne Metallic Elements in Nanjing, China

In order to investigate the temporal and spatial variations and the size distribution of atmospheric particulate matter and associated airborne elements, atmospheric particulate matter (TSP, PM2.5 and size-segregated aerosol particles) were collected monthly for one year from the traditional central district and suburbs of Nanjing, China. Source identification of airborne elements in PM2.5 was carried out using multivariate statistical analysis. The annual mass concentrations ranged from 49.4 µg/m 3 to 391 µg/m 3 , with a mean of 135 µg/m 3 for TSP and from 20.4 µg/m 3 to 200 µg/m 3 with a mean of 80.5 µg/m 3 for PM2.5. The distribution of annual size-segregated aerosol particles showed a bimodal pattern of coarse and fine particle fractions. Spatial and seasonal variations of elemental composition in atmospheric particulates were observed. The major elements (A1, Ca, Fe, Mg, Na and Mn) were mainly distributed in coarse fractions, while toxic elements, such as As, Cd, Pb and Zn, were significantly enriched in the fine fractions. The enrichment factor indicated anthropogenic inputs of As, Cu, Ni, Pb and Zn in the TSP and PM2.5 examined in this work. Four potential sources for PM2.5 were identified by principal component analysis. The source contributions calculated using absolute principal component scores were 37.5% for the first component, 34.1% for the second, 9.0% for the third and 19.8% for the fourth. The Na/Cr/Cu component identified by principal component analysis was divided into Na/Cr and Cu groups using R-mode cluster analysis of PM2.5, and the Ti in the fourth component was assigned to Cluster 2, indicating a statistical difference in airborne metallic elements. The results of the investigation of element composition, size distribution, and source apportionment carried out in this work can help to better understand and manage the effects of these aerosols on health and air quality.
Reframing social categorization as latent structure learning for understanding political behaviour

Affiliating with political parties, voting and building coalitions all contribute to the functioning of our political systems. One core component of this is social categorization—being able to recognize others as fellow in-group members or members of the out-group. Without this capacity, we would be unable to coordinate with in-group members or avoid out-group members. Past research in social psychology and cognitive neuroscience examining social categorization has suggested that one way to identify in-group members may be to directly compute the similarity between oneself and the target (dyadic similarity). This model, however, does not account for the fact that the group membership brought to bear is context-dependent. This review argues that a more comprehensive understanding of how we build representations of social categories (and the subsequent impact on our behaviours) must first expand our conceptualization of social categorization beyond simple dyadic similarity. Furthermore, a generalizable account of social categorization must also provide domain-general, quantitative predictions for us to test hypotheses about social categorization. Here, we introduce an alternative model—one in which we infer latent groups of people through latent structure learning. We examine experimental evidence for this account and discuss potential implications for understanding the political mind. This article is part of the theme issue ‘The political brain: neurocognitive and computational mechanisms’.
Corrections of political misinformation: no evidence for an effect of partisan worldview in a US convenience sample

Misinformation often has a continuing effect on people's reasoning despite clear correction. One factor assumed to affect post-correction reliance on misinformation is worldview-driven motivated reasoning. For example, a recent study with an Australian undergraduate sample found that when politically situated misinformation was retracted, political partisanship influenced the effectiveness of the retraction. This worldview effect was asymmetrical, that is, particularly pronounced in politically conservative participants. However, the evidence regarding such worldview effects (and their symmetry) has been inconsistent. Thus, the present study aimed to extend previous findings by examining a sample of 429 pre-screened US participants supporting either the Democratic or Republican Party. Participants received misinformation suggesting that politicians of either party were more likely to commit embezzlement; this was or was not subsequently retracted, and participants' inferential reasoning was measured. While political worldview (i.e. partisanship) influenced the extent to which participants relied on the misinformation overall, retractions were equally effective across all conditions. There was no impact of political worldview on retraction effectiveness, let alone evidence of a backfire effect, and thus we did not replicate the asymmetry observed in the Australian-based study. This pattern emerged despite some evidence that Republicans showed a stronger emotional response than Democrats to worldview-incongruent misinformation. This article is part of the theme issue ‘The political brain: neurocognitive and computational mechanisms’.
Themed Section: COVID-19 Disease Burden Attributable to the First Wave of COVID-19 in China and the Effect of Timing on the Cost-Effectiveness of Movement Restriction Policies

Objectives: Movement restriction policies (MRPs) are effective in preventing/delaying COVID-19 transmission but are associated with high societal cost. This study aims to estimate the health burden of the first wave of COVID-19 in China and the cost-effectiveness of early versus late implementation of MRPs to inform preparation for future waves. Methods: The SEIR (susceptible, exposed, infectious, and recovered) modeling framework was adapted to simulate the health and cost outcomes of initiating MRPs at different times: rapid implementation (January 23, the real-world scenario), delayed by 1 week, delayed by 2 weeks, and delayed by 4 weeks. The end point was set as the day when newly confirmed cases reached zero. Two costing perspectives were adopted: healthcare and societal. Input data were obtained from official statistics and published literature. The primary outcomes were disability-adjusted life-years, cost, and net monetary benefit. Costs were reported in both Chinese renminbi (RMB) and US dollars (USD) at 2019 values. Results: The first wave of COVID-19 in China resulted in 38 348 disability adjusted life-years lost (95% CI 19 417-64 130) and 2639 billion RMB losses (95% CI 1347-4688). The rapid implementation strategy dominated all other delayed strategies. This conclusion was robust to all scenarios tested. At a willingness-to-pay threshold of 70 892 RMB (the national annual GDP per capita) per disability-adjusted life-year saved, the probability for the rapid implementation to be the optimal strategy was 96%. Conclusions: Early implementation of MRPs in response to COVID-19 reduced both the health burden and societal cost and thus should be used for future waves of COVID-19.
Preservice teachers’ motivation profiles, self-regulation, and affective outcomes in online learning

ABSTRACT The purpose of this study was to examine the relationship between motivation profiles and self-regulation in online students and self-regulation as a predictor of affective learning outcomes, depending on students’ motivation profiles. A total of 556 online preservice teachers participated in this study at a university in the United States of America. Cluster analyses yielded three subgroups of motivation: high, average, and low. One-way multivariate analysis of variance revealed that the degree of student self-regulation differed, depending on motivation profiles. In addition, multiple regression showed that for students with high motivation profiles, self-regulation between student and content and between student and instructor related with their affective learning outcomes, but only self-regulation between student and instructor related with affective learning outcomes for students with average and low motivation profiles. Overall, study results revealed that motivation profiles related with the online students’ self-regulation and with their affective learning outcomes as well.
Predictive coding is a consequence of energy efficiency in recurrent neural networks

Predictive coding represents a promising framework for understanding brain function. It postulates that the brain continuously inhibits predictable sensory input, ensuring a preferential processing of surprising elements. A central aspect of this view is its hierarchical connectivity, involving recurrent message passing between excitatory bottom-up signals and inhibitory top-down feedback. Here we use computational modelling to demonstrate that such architectural hard-wiring is not necessary. Rather, predictive coding is shown to emerge as a consequence of energy efficiency. When training recurrent neural networks to minimise their energy consumption while operating in predictive environments, the networks self-organise into prediction and error units with appropriate inhibitory and excitatory interconnections, and learn to inhibit predictable sensory input. Moving beyond the view of purely top-down driven predictions, we furthermore demonstrate, via virtual lesioning experiments, that networks perform predictions on two timescales: fast lateral predictions among sensory units, and slower prediction cycles that integrate evidence over time.
Mosquito Larvae (Culex spp.) Startle Responses to Vibration Stimuli

We explored startle responses of Culex spp. larvae to varying frequencies and durations of vibrations, before investigating habituation (a behavioural learning phenomenon). The startle response consists of a rapid movement to permit escape from a potentially dangerous stimulus. We used the automated Zantiks MWP_vb unit to analyse larval startle responses through the built-in live video tracking. Set within the unit’s controlled environmental chamber, we recorded distance travelled by the larvae. These results were used to optimise the vibration startle response for use in habituation studies. Repeated vibrations appeared to reduce larvae startle responses, although further analysis is required to confirm habituation. This study not only provides an insight into the learning ability of mosquito larvae, but demonstrates the ease, replicability and control conferred by the automated unit. Furthermore, this method is applicable to many other organisms and shows potential for more sophisticated environmental effect testing, such as behavioural toxicology.
Drag and oscillatory motion of freely falling cylindrical particles

The behavior of circular cylinders moving singly through water under the influence of gravity was studied with a motion picture camera over a range of particle. Reynolds number extending from 70 to 2400. The terminal velocity was determined for each particle and its drag coefficient was evaluated. At Re-greater than 300, and in some cases as low as 80, the particle acquired a secondary motion, consisting of an angular oscillation about its mean orientation and a periodic lateral deviation from its mean path of fall. A resultant dependence of the drag coefficient on particle density was found to occur. A theoretical method of predicting the period of particle oscillation was developed from consideration of variations in the location of the front-surface centre of pressure. On a etudie a L'aide d'un cine le comportement de corps cylindriques individuels en chute libre dans L'eau. Le nombre de Reynolds a varie de 70 a 2400 et on a determine pour chaque particule la vitesse terminale et evalue le coefficient de trainee. Pour des Re aussi faibles que 80, mais generalement superieurs a 300, un mouvement secondaire s'ajoute au mouvement general de la particule consistant d'une oscillation angulaire autour de L'orientation generate et d'une deviation laterale periodique de la direction generale de chute. Il en resulte alors un effet sur le coefficient de trainee de la particule. On developpe une methode theorique pour predire la periode de L'oscillation de la particule en considerant les variations de position du centre de pression sur la surface d'attaque.
ChEC-seq: a robust method to identify protein-DNA interactions genome-wide

Mittal et al. (2021; first brought to our attention in May 2019) have raised concerns regarding the Chromatin Endogenous Cleavage-sequencing (ChEC-seq) technique (Zentner et al., 2015) that may create a false impression that this method has fundamental flaws which prevent one from distinguishing between signal and noise. Although Mittal et al. focus on studies of the global co-activators SAGA, TFIID and Mediator that we were not involved in, we feel obliged to highlight here several of our own publications (Albert et al., 2019; Bruzzone et al., 2018; Hafner et al., 2018; Kubik et al., 2019; Kubik et al., 2018), as well as recent unpublished data, that employed ChEC-seq and directly addressed the observation raised by Mittal et al. that cleavage maps for various MNase fusion proteins often qualitatively resemble each other and those generated by “free” (unfused) MNase. Our studies lay out a clear path for determining sites of preferential factor localization by normalization of ChEC-seq experimental data to matched free-MNase controls. They also demonstrate the use of in vivo functional assays to assess ChEC-seq reliability and reveal examples where ChEC-seq identifies functional binding sites missed by conventional ChIP-seq analysis.