Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparative Transcriptomic Analysis Provides Insight into the Domestication and Improvement of Pear (P. pyrifolia) Fruit1[OPEN]

Genes associated with stone cell formation, fruit size, and sugar content underwent directional selection during pear domestication and improvement, which contributed to drastic changes of cultivated pears. Knowledge of the genetic changes that occurred during the domestication and improvement of perennial trees at the RNA level is limited. Here, we used RNA sequencing analysis to compare representative sets of wild, landrace, and improved accessions of pear (Pyrus pyrifolia) to gain insight into the genetic changes associated with domestication and improvement. A close population relationship and similar nucleotide diversity was observed between the wild and landrace groups, whereas the improved group had substantially reduced nucleotide diversity. A total of 11.13 Mb of genome sequence was identified as bearing the signature of selective sweeps that occurred during pear domestication, whereas a distinct and smaller set of genomic regions (4.04 Mb) was identified as being associated with subsequent improvement efforts. The expression diversity of selected genes exhibited a 20.89% reduction from the wild group to the landrace group, but a 23.13% recovery was observed from the landrace to the improved group, showing a distinctly different pattern with variation of sequence diversity. Module-trait association analysis identified 16 distinct coexpression modules, six of which were highly associated with important fruit traits. The candidate trait-linked differentially expressed genes associated with stone cell formation, fruit size, and sugar content were identified in the selected regions, and many of these could also be mapped to the previously reported quantitative trait loci. Thus, our study reveals the specific pattern of domestication and improvement of perennial trees at the transcriptome level, and provides valuable genetic sources of fruit traits that could contribute to pear breeding and improvement.
EFFECT OF BLOOD TRANSFUSIONS AND NON -TRANSFUSION ON SERUM FERRITIN LEVELS OF PATIENTS WITH SICKLE CELL DISEASE ATTENDING THE PAEDIATRIC HAEMATOLOGY CLINIC OF THE UNIVERSITY OF BENIN TEACHING HOSPITAL

The need for recurrent blood transfusion is thought to be protective against iron deficiency in children affected by sickle cell disease. However, the subject has not received sufficient attention in Nigeria. The objective of the study was to assess the iron status of transfused and non transfused sickle cell disease children aged 1-18 years who are in steady state, using serum ferritin levels. In this cross -sectional study, 100 children with sickle cell disease aged 1-18years attending the Paediatric Haematology OutPatient Clinic were recruited consecutively. The subjects were in steady state and had not received blood transfusion in the last 3 months. Their iron status was determined using serum ferritin levels. Serum ferritin levels of <25ng/ ml was used to establish the presence of low iron stores. A patient with low mean corpuscular volume for age together with low serum ferritin (<25ng/ml) was considered to have iron deficiency anemia (IDA). Fifty four (54%) of the 100 subjects had received blood transfusion. The lowest mean serum ferritin value of 34± 36.1ng/ml was seen amongst subjects who had never received blood transfusion in the past. The prevalence of iron deficiency was 35.2% and 60.1% in transfused and non transfused SCD children respectively. The prevalence rates of iron deficiency anemia (IDA) were 14.8% and 30.4% respectively in transfused and non transfused SCD children. The prevalence of iron deficiency increased with the duration of blood transfusion. 20.8% of those who had received blood transfusion less than a year prior to the study were iron deficient while 85.7% of those who received blood more than 5 years prior to the study were deficient. This difference was statistically significant. Iron deficiency and iron deficiency anemia were seen in transfused and non transfused SCD children but the prevalence was higher in the non-transfused group. Transfusion given more than 5 years ago, was not protective against the presence of iron deficiency.
GASC: Genre-Aware Semantic Change for Ancient Greek

Word meaning changes over time, depending on linguistic and extra-linguistic factors. Associating a word’s correct meaning in its historical context is a central challenge in diachronic research, and is relevant to a range of NLP tasks, including information retrieval and semantic search in historical texts. Bayesian models for semantic change have emerged as a powerful tool to address this challenge, providing explicit and interpretable representations of semantic change phenomena. However, while corpora typically come with rich metadata, existing models are limited by their inability to exploit contextual information (such as text genre) beyond the document time-stamp. This is particularly critical in the case of ancient languages, where lack of data and long diachronic span make it harder to draw a clear distinction between polysemy (the fact that a word has several senses) and semantic change (the process of acquiring, losing, or changing senses), and current systems perform poorly on these languages. We develop GASC, a dynamic semantic change model that leverages categorical metadata about the texts’ genre to boost inference and uncover the evolution of meanings in Ancient Greek corpora. In a new evaluation framework, our model achieves improved predictive performance compared to the state of the art.
Keeping Up With The Joneses? An Exploration Through Intragenerational Mobility and Occupational Employment Risk

Motivated by Albert Hirschman's tunnel e ect parable, this study examines the long-term intra-generational mobility in wage rates for young Baby Boomers and estimates the e ect of occupational employment risk (OER) on unemployment duration hazards and wage loss upon re-employment. The ndings suggest that the degree of long-term mobility in wages declined over time from 1989 to 2009, and mobility was not enough to counterbalance the long-term distributional e ects of rising earnings inequality. Individuals in high-risk OER occupations as de ned by industrial specialization of occupations were less likely to end unemployment spells and were more likely to experience wage loss upon re-employment compared to individuals in low-risk OER occupations. OER's e ect on the probability of wage loss was especially high for those workers who were displaced and changed their occupation, even after controlling for a wide range of covariates including the unemployment rate, ability, length of unemployment spell and various human-capital indicators. ∗International Business School, Brandeis University, 415 South St. MS 032, MA 02453, USA. Email: spanday@brandeis.edu. I am grateful to Catherine L. Mann for her invaluable guidance and support. I would like to thank Juan Contreras and Ignez Tristao for sharing quantitative programing codes related to the NLSY dataset from their related work. All errors are my own. Usual disclaimer applies.
Information and Communication Technology, the Income Distribution, and Occupational Choice

A key feature of Information and Communication Technologies (ICT) is that they may increase the scale of operation for workers in some occupations. We model the scale of operation as the limit up to which the production technology displays increasing returns to scale. We then explore the implications of this feature of ICT for the income distribution as well as individual’s occupational choices. We find that an ICT-induced increase in the scale of operation for workers within an occupation intensifies competition between the workers. This drives the lowest-ability workers out of the occupation, reduces the earnings of the next lowest-ability workers and raises the overall log income gap within the occupation. We compare these effects with those produced by more traditional technological changes that increase the quantity of output per unit of time. Lastly, we test the theoretical results with U.S. data and find support for the predictions. JEL: J24, J31, O30, D33
General cognitive but not mathematic abilities predict very preterm and healthy term born adults’ wealth

Objective Very preterm (<32 weeks gestation; VP) and/or very low birth weight (<1500g; VLBW) children often have cognitive and mathematic difficulties. It is unknown whether VP/VLBW children’s frequent mathematic problems significantly add to the burden of negative life-course consequences over and above effects of more general cognitive deficits. Our aim was to determine whether negative consequences of VP/VLBW versus healthy term birth on adult wealth are mediated by mathematic abilities in childhood, or rather explained by more general cognitive abilities. Methods 193 VP/VLBW and 217 healthy term comparison participants were studied prospectively from birth to adulthood as part of a geographically defined study in Bavaria (South Germany). Mathematic and general cognitive abilities were assessed at 8 years with standardized tests; wealth information was assessed at 26 years with a structured interview and summarized into a comprehensive index score. All scores were z-standardized. Results At 8 years, VP/VLBW (n = 193, 52.3% male) had lower mathematic and general cognitive abilities than healthy term comparison children (n = 217, 47.0% male). At 26 years, VP/VLBW had accumulated significantly lower overall wealth than term born comparison adults (-0.57 (1.08) versus -0.01 (1.00), mean difference 0.56 [0.36–0.77], p < . 001). Structural equation modeling confirmed that VP/VLBW birth (β = -.13, p = .022) and childhood IQ (β = .24, p < .001) both directly predicted adult wealth, but math did not (β = .05, p = .413). Analyses were controlled for small-for-gestational-age (SGA) birth, child sex, and family socioeconomic status. Conclusion This longitudinal study from birth to adulthood shows that VP/VLBW survivors’ general cognitive rather than specific mathematic problems explain their diminished life-course success. These findings are important in order to design effective interventions at school age that reduce the burden of prematurity for those individuals who were born at highest neonatal risk.
Selected Predictors of the Importance Attached to Salt Content Information on the Food Packaging (a Study among Polish Consumers)

This paper aims to identify selected antecedents of the importance attached to salt content information (ISCI) placed on food labels, on the basis of a representative survey of 1051 Polish consumers. The study was conducted with the use of the CAWI (Computer Assisted Web Interviews) method in 2018. Quota sampling was applied with reference to the following five criteria: sex, age, education, place of living (urban and rural areas), and region. In a multiple regression model, ISCI depends on the respondent’s: sex, age, evaluation of the quantity of nutrition claims, importance attached to nutrition claims, willingness to pay a price premium for products with nutrition claims, attention paid to health and nutrition claims, agreeing with the opinion that unreliable nutrition claims are a serious problem, evaluation of healthiness of one’s diet, self-rated knowledge about healthy nutrition, buying organic food, and reading front-of-package (FOP) labels during and after the purchase. The strongest effects on the importance attached to salt content information on the food packaging were displayed by the importance of nutrition claims, attention paid to nutrition and health claims, respondent’s age, FOP label reading at home, and agreeing that the use of unreliable nutrition claims is a serious problem.
Classifying Breast Cancer Subtypes Using Multiple Kernel Learning Based on Omics Data

It is very significant to explore the intrinsic differences in breast cancer subtypes. These intrinsic differences are closely related to clinical diagnosis and designation of treatment plans. With the accumulation of biological and medicine datasets, there are many different omics data that can be viewed in different aspects. Combining these multiple omics data can improve the accuracy of prediction. Meanwhile; there are also many different databases available for us to download different types of omics data. In this article, we use estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) to define breast cancer subtypes and classify any two breast cancer subtypes using SMO-MKL algorithm. We collected mRNA data, methylation data and copy number variation (CNV) data from TCGA to classify breast cancer subtypes. Multiple Kernel Learning (MKL) is employed to use these omics data distinctly. The result of using three omics data with multiple kernels is better than that of using single omics data with multiple kernels. Furthermore; these significant genes and pathways discovered in the feature selection process are also analyzed. In experiments; the proposed method outperforms other state-of-the-art methods and has abundant biological interpretations.
Uncertainty Aware Learning from Demonstrations in Multiple Contexts using Bayesian Neural Networks

Diversity of environments is a key challenge that causes learned robotic controllers to fail due to the discrepancies between the training and evaluation conditions. Training from demonstrations in various conditions can mitigate—but not completely prevent—such failures. Learned controllers such as neural networks typically do not have a notion of uncertainty that allows to diagnose an offset between training and testing conditions, and potentially intervene. In this work, we propose to use Bayesian Neural Networks, which have such a notion of uncertainty. We show that uncertainty can be leveraged to consistently detect situations in high-dimensional simulated and real robotic domains in which the performance of the learned controller would be sub-par. Also, we show that such an uncertainty based solution allows making an informed decision about when to invoke a fallback strategy. One fallback strategy is to request more data. We empirically show that providing data only when requested results in increased data-efficiency.
Automatic Pulmonary Nodule Detection Applying Deep Learning or Machine Learning Algorithms to the LIDC-IDRI Database: A Systematic Review

The aim of this study was to provide an overview of the literature available on machine learning (ML) algorithms applied to the Lung Image Database Consortium Image Collection (LIDC-IDRI) database as a tool for the optimization of detecting lung nodules in thoracic CT scans. This systematic review was compiled according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Only original research articles concerning algorithms applied to the LIDC-IDRI database were included. The initial search yielded 1972 publications after removing duplicates, and 41 of these articles were included in this study. The articles were divided into two subcategories describing their overall architecture. The majority of feature-based algorithms achieved an accuracy >90% compared to the deep learning (DL) algorithms that achieved an accuracy in the range of 82.2%–97.6%. In conclusion, ML and DL algorithms are able to detect lung nodules with a high level of accuracy, sensitivity, and specificity using ML, when applied to an annotated archive of CT scans of the lung. However, there is no consensus on the method applied to determine the efficiency of ML algorithms.
c-Jun/Ap-1 is upregulated in an Ang II-induced abdominal aortic aneurysm formation model and mediates Chop expression in mouse aortic smooth muscle cells

Abdominal aortic aneurysm (AAA) is an asymptomatic, potentially lethal disease whose ruptures have a high mortality rate. An effective pharmacological approach to decrease expansion or prevent the rupture of AAAs in humans remains lacking. Previous studies have suggested that activator protein 1 (c-Jun/AP-1) and C/EBP homologous protein (Chop) are involved in the development of AAA. The purpose of the present study was to investigate whether c-Jun/AP-1 mediates Chop overexpression in AAA. c-Jun/AP-1 and Chop protein levels were determined in an angiotensin II (Ang II)-induced AAA model using apolipoprotein E-deficient mice. Additionally, mouse aortic smooth muscle cells (MOVAS cell line) were treated with Ang II. Apoptosis was evaluated via TUNEL assay, MOVAS cell migration ability was assessed by monolayer wound healing assay and the levels of c-Jun/AP-1 and Chop were determined by western blotting, immunofluorescence and immunocytochemical assays. Following c-Jun silencing using c-Jun-specific small interfering (si)RNA, Chop expression was evaluated. Furthermore, chromatin immunoprecipitation (ChIP) was used to investigate whether c-Jun/Ap-1 binds directly to the DNA damage-inducible transcript 3 protein (Ddit3) promoter. It was observed that c-Jun/AP-1 and Chop were synchronously overexpressed in Ang II-induced AAA and Ang II-treated cells, and that apoptosis and migration were induced by Ang II. In addition, Chop was suppressed when c-Jun was silenced by targeted siRNA. Notably, the ChIP assay demonstrated that the DNA fragments pulled down by primary antibodies against c-Jun/Ap-1 were able to be amplified by (Ddit3) promoter-specific primers. c-Jun/AP-1 may therefore mediate Chop expression in MOVAS cells via Ddit3. These results suggested that c-Jun/AP-1 may be a novel target for AAA therapy.
3D Printing of Polycaprolactone–Polyaniline Electroactive Scaffolds for Bone Tissue Engineering

Electrostimulation and electroactive scaffolds can positively influence and guide cellular behaviour and thus has been garnering interest as a key tissue engineering strategy. The development of conducting polymers such as polyaniline enables the fabrication of conductive polymeric composite scaffolds. In this study, we report on the initial development of a polycaprolactone scaffold incorporating different weight loadings of a polyaniline microparticle filler. The scaffolds are fabricated using screw-assisted extrusion-based 3D printing and are characterised for their morphological, mechanical, conductivity, and preliminary biological properties. The conductivity of the polycaprolactone scaffolds increases with the inclusion of polyaniline. The in vitro cytocompatibility of the scaffolds was assessed using human adipose-derived stem cells to determine cell viability and proliferation up to 21 days. A cytotoxicity threshold was reached at 1% wt. polyaniline loading. Scaffolds with 0.1% wt. polyaniline showed suitable compressive strength (6.45 ± 0.16 MPa) and conductivity (2.46 ± 0.65 × 10−4 S/cm) for bone tissue engineering applications and demonstrated the highest cell viability at day 1 (88%) with cytocompatibility for up to 21 days in cell culture.
Bayesian general multivariate latent variable modeling of longitudinal item response data

Longitudinal item response data are characterized by examinees that are assessed at different time points or measurement occasions such that time-specific measurements are nested within examinees (Singer & Andrade (2000)). Besides the usual nesting of response observations within examinees, the time-specific latent traits are also nested within examinees, see Andrade & Tavares (2006) and Andrade & Tavares (2005). In the well-known hierarchical modeling approach, the complex dependencies due to the nested structure of the data are commonly modeled by introducing random effects such that observations and latent traits are conditionally independently distributed. However, the implied compound symmetry structure is often not sufficient to model the complex time-heterogenous dependencies. Therefore, a Bayesian general multivariate item response modeling framework is proposed that accounts for the complex within-examinee latent trait dependencies. Flexible parametric covariance structures are considered to model specific withinexaminee dependencies. Furthermore, it can handle many measurement occasions, different item response functions, and different latent trait population distributions, and generalizes the modeling framework of Andrade & Tavares (2005). Due to identification rules and restricted parametric covariance structures, a conditional modeling approach is pursued to specify proper priors for the unrestricted parameters and to implement an efficient MCMC algorithm, by conditioning on baseline population parameters. The study is motivated by a large-scale longitudinal research program of the Brazilian Federal government to improve the teaching quality and general structure of schools for primary education. It is shown that the growth in math achievement can be accurately measured when accounting for complex dependencies over grades using time-heterogenous covariances structures.
Homocysteine-lowering exercise effect is greater in hyperhomocysteinemic people living with HIV: A randomized clinical trial.

Elevated concentration of homocysteine has been identified as an independent risk factor for the development of cardiovascular disease and is frequently associated with oxidative stress. Moreover, studies have shown that people living with HIV (PLHIV) present elevated concentration of homocysteine and oxidative stress compared to people without HIV. Our purpose was to describe blood homocysteine and oxidative stress markers in PLHIV and those without HIV infection, and to examine the effects of a 16-week combined training exercise program (CTE) on oxidative stress and homocysteine concentrations of PLHIV. We included 49 PLHIV (21 men, 28 women) and 33 people without HIV infection (13 men, 20 women). After baseline evaluations, 30 PLHIV were randomized to either CTE (trained group TG, n=18) or the control group (CG, n=12); CTE consisted of aerobic and strength exercise sessions during 16 weeks, three times a week. Plasma homocysteine, oxidative damage markers, folate and vitamin B12 were assessed pre- and post-training and by hyperhomocysteinemia (homocysteine≥15 µmol/L) status. At baseline, PLHIV had higher levels of homocysteine and malondialdehyde, as well as reduced circulating folate when compared to people without HIV infection. CTE resulted in a 32% reduction (p<0.05) in homocysteine concentration and a reduction in lipid hydroperoxide in PLHIV with hyperhomocysteinemia which was not observed in those without hyperhomocysteinemia. Hyperhomocysteinemic participants experienced a 5.6±3.2 µmol/L reduction in homocysteine after CTE. In summary, sixteen weeks of CTE was able to decrease elevated homocysteine concentration and enhance redox balance of PLHIV with hyperhomocysteinemia, which could improve their cardiovascular risk.
A Sliding Mode Force and Position Controller Synthesis for Series Elastic Actuators

Summary This paper deals with the robust force and position control problems of series elastic actuators (SEAs). It is shown that an SEA’s force control problem can be described by a second-order dynamic model which suffers from only matched disturbances. However, the position control dynamics of an SEA is of fourth order and includes matched and mismatched disturbances. In other words, an SEA’s position control is more complicated than its force control, particularly when disturbances are considered. A novel robust motion controller is proposed for SEAs by using disturbance observer (DOb) and sliding mode control. When the proposed robust motion controller is implemented, an SEA can precisely track desired trajectories and safely contact with an unknown and dynamic environment. The proposed motion controller does not require precise dynamic models of environments and SEAs. Therefore, it can be applied to many different advanced robotic systems such as compliant humanoids, industrial robots and exoskeletons. The validity of the proposed motion controller is experimentally verified.