Miracle-dz/UniFAR-FTUs huggingface dataset:
Role of Strain Elastography and Shear-Wave Elastography in a Multiparametric Clinical Approach to Indeterminate Cytology Thyroid Nodules

Background In thyroid nodules with indeterminate cytology, further clinical assessment aimed at ruling out malignancy is often mandatory. Ancillary imaging techniques and genetic mutation analysis can improve the risk stratification of such lesions, thereby facilitating the clinician’s decision to undertaken surgery or simple follow-up. The aim of this study was to evaluate the diagnostic performance of shear-wave elastography (SW), strain elastography (ELX 2/1), conventional ultrasound (US), contrast-enhanced ultrasound (CEUS), and BRAF V600E mutation analysis in the aforementioned lesions. Material/Methods We enrolled 81 patients, each with 1 indeterminate-cytology thyroid nodule. Thyroid function, thyroperoxidase antibodies and calcitonin were known in each case. SW, ELX 2/1, US, CEUS, and BRAF mutation analysis were subsequently performed, followed by a second FNAB. If the lesion was not downgraded to benign, surgery was recommended and histological reports collected. Results There were 28 nodules (34%) that proved benign on the second FNAB; 38 nodules (47%) underwent surgery (17 benign, 21 malignant), and 15 nodules (19%) refused surgery. The only techniques related to histological outcome were US (AUC=0,766), ELX 2/1 (AUC=0.701), and BRAF analysis (AUC=0.762). ELX 2/1 and SW reports were not correlated with each other (P=0.45). A scoring system taking into account all the variables considered performed better than the single variables alone (AUC=0.831). Conclusions In indeterminate-cytology thyroid lesions, repeating FNAB can avoid unnecessary surgery. ELX 2/1 seems to perform better than SW in distinguishing malignancy; these techniques could, however, be complementary in describing such lesions. A multiparametric approach appears the most accurate in predicting nodule histology.
Rigor and reproducibility in genetic research on eating disorders

OBJECTIVE We explored both within-method and between-method rigor and reproducibility in the field of eating disorders genetics. METHOD We present critical evaluation and commentary on component methods of genetic research (family studies, twin studies, molecular genetic studies) and discuss both successful and unsuccessful efforts in the field. RESULTS Eating disorders genetics has had a number of robust results that converge across component methodologies. Familial aggregation of eating disorders, twin-based heritability estimates of eating disorders, and genome-wide association studies (GWAS) all point toward a substantial role for genetics in eating disorders etiology and support the premise that genes do not act alone. Candidate gene and linkage studies have been less informative historically. DISCUSSION The eating disorders field has entered the GWAS era with studies of anorexia nervosa. Continued growth of sample sizes is essential for rigorous discovery of actionable variation. Molecular genetic studies of bulimia nervosa, binge-eating disorder, and other eating disorders are virtually nonexistent and lag seriously behind other major psychiatric disorders. Expanded efforts are necessary to reveal the fundamental biology of eating disorders, inform clinical practice, and deliver new therapeutic targets.
Challenges of Context and Time in Reinforcement Learning: Introducing Space Fortress as a Benchmark

Research in deep reinforcement learning (RL) has coalesced around improving performance on benchmarks like the Arcade Learning Environment. However, these benchmarks conspicuously miss important characteristics like abrupt context-dependent shifts in strategy and temporal sensitivity that are often present in real-world domains. As a result, RL research has not focused on these challenges, resulting in algorithms which do not understand critical changes in context, and have little notion of real world time. To tackle this issue, this paper introduces the game of Space Fortress as a RL benchmark which incorporates these characteristics. We show that existing state-of-the-art RL algorithms are unable to learn to play the Space Fortress game. We then confirm that this poor performance is due to the RL algorithms' context insensitivity and reward sparsity. We also identify independent axes along which to vary context and temporal sensitivity, allowing Space Fortress to be used as a testbed for understanding both characteristics in combination and also in isolation. We release Space Fortress as an open-source Gym environment.
Impact of hydration status on haemodynamics, effects of acute blood pressure‐lowering treatment, and prognosis after stroke

Although high blood pressure (BP) is common in acute stroke and associated with poor outcome, the Efficacy of Nitric Oxide in Stroke (ENOS) trial showed no beneficial effect of antihypertensive treatment in this situation. Antihypertensive agents have accentuated effects in dehydrated patients. We assessed the impact of dehydration on haemodynamics, the effects of antihypertensive treatment, and prognosis in the ENOS trial.
Adaptive growth changes in the liver remnant are affected by the size of hepatectomy in rats

In this study we investigated the dynamics of hepatocyte hyperplasia and hypertrophy in rats subjected to increasing sizes of partial hepatectomy (PH). A total of 104 rats were randomized according to the size of PH. On postoperative days (PODs) 1, 3 and 5, blood was drawn and the remnant liver removed for stereological analysis. Liver parameters and regeneration rate were significantly affected by size of PH. On POD 1, hepatocyte volumes had increased significantly in all PH groups. On POD 3, all groups showed hepatocyte volumes approximating baseline. On POD 5, hepatocyte volumes were significantly lower in PH (90) than in baseline, sham and PH (30) rats. Increasing hepatocyte proliferation was not observed following PH (30). Following PH (70), cell proliferation was significantly elevated on PODs 1 and 3, and following PH (90) on PODs 3 and 5. In conclusion, general hypertrophy of hepatocytes after different size of PH was followed by hepatocyte proliferation only in the liver remnant of PH (70) and PH (90).
Large Scale Learning with Kreĭn Kernels

We extend the Nystr\"om method for low-rank approximation of positive definite Mercer kernels to approximation of indefinite kernel matrices. Our result is the first derivation of the approach that does not require the positive definiteness of the kernel function. Building on this result, we then devise highly scalable methods for learning in reproducing kernel Kre\u{\i}n spaces. The main motivation for our work comes from problems with structured representations (e.g., graphs, strings, time-series), where it is relatively easy to devise a pairwise (dis)similarity function based on intuition/knowledge of a domain expert. Such pairwise functions are typically not positive definite and it is often well beyond the expertise of practitioners to verify this condition. The proposed large scale approaches for learning in reproducing kernel Kre\u{\i}n spaces provide principled and theoretically well-founded means to tackle this class of problems. The effectiveness of the approaches is evaluated empirically using kernels defined on structured and vectorial data representations.
Character-Aware Decoder for Neural Machine Translation

Standard neural machine translation (NMT) systems operate primarily on words, ignoring lower-level patterns of morphology. We present a character-aware decoder for NMT that can simultaneously work with both word-level and subword-level sequences which is designed to capture such patterns. We achieve character-awareness by augmenting both the softmax and embedding layers of an attention-based encoder-decoder network with convolutional neural networks that operate on spelling of a word (or subword). While character-aware embeddings have been successfully used in the source-side, we find that mixing character-aware embeddings with standard embeddings is crucial in the target-side. Furthermore, we show that a simple approximate softmax layer can be used for large target-side vocabularies which would otherwise require prohibitively large memory. We experiment on the TED multi-target dataset, translating English into 14 typologically diverse languages. We find that in this low-resource setting, the character-aware decoder provides consistent improvements over word-level and subword-level counterparts with BLEU score gains of up to +3.37.
Changes in Care After Implementing a Multifaceted Intervention to Improve Preventive Cardiology Practice in Rheumatoid Arthritis

Rheumatoid arthritis (RA) increases cardiovascular disease (CVD) risk. However, CVD risk factor identification and treatment is often inadequate. The authors implemented a multifaceted rheumatology practice intervention to improve CVD risk factor measurement, assessment, and management. The intervention included clinician education, point-of-care decision support, feedback, and care management. The authors measured quality indicators from electronic health records and assessed impact with interrupted time series. Following the intervention, more RA patients had all major CVD risk factors assessed (53% vs 72.2%), and the rate of increase was greater during the intervention period than baseline (difference of 0.74% per month, P = .0016). Moderate- or high-intensity statin prescribing increased (21.6% to 28.2%), but the rate of change was not different from baseline. Several other quality measures did not increase. Although CVD risk factor assessment improved, the intervention did not affect risk factor management and control. Other strategies are needed to optimize CVD prevention in RA.
Molecular genetic alterations in thyroid transcription factor 1–negative lung adenocarcinoma in cytology specimens: A subset with aggressive behavior and a poor prognosis

Patients with thyroid transcription factor 1 (TTF1)–negative pulmonary adenocarcinoma (ADC) have been reported to have a worse prognosis and to lack epidermal growth factor receptor (EGFR) mutations. This study describes a series of cytology specimens from patients with clinically confirmed pulmonary carcinoma negative for TTF1.
The Extraction of Emotional and Attribute Words in Perspective Sentences

The article focuses on the research on the classification criteria of emotional words and attribute words. Firstly, the semantic similarity and its representative method based on distance, the Euclidean distance calculation method and the cosine distance calculation method are introduced. Based on this, a comparison experiment of semantic similarity between emotional words and attribute words based on Euclidean distance and cosine distance was carried out. According to the experimental results, a method for determining the classification criteria of emotional words and attribute words based on the distribution rules of words and cosine distances was proposed.
Appetite during the second and third trimesters mediates the impact of prenatal environmental tobacco smoke exposure on symmetric full-term low birth weight

Abstract Objective: To examine the relationship of prenatal environmental tobacco smoke (ETS) exposure and full-term low birth weight (FT-LBW) when taking anthropometric proportionality into consideration, and explore whether appetite mediates their association. Study design: We conducted a case-control study among pregnant women at two Women and Children’s Hospitals in Guangdong, China. Information was collected through interview and medical records review. A series of logistic and linear regressions were used to examine the relationships of prenatal ETS exposure, appetite, and FT-LBW. Results: After adjusting for the potential confounders, prenatal ETS exposure was significantly negatively associated with FT-LBW (OR: 1.83, 95%CI: 1.35–2.48) and negatively correlated with maternal appetite in second and third trimester during pregnancy (β: −0.11, standard error: 0.03). Moreover, mediation analysis illustrated that maternal appetite partially mediated 12.00% of their relationship. However, subgroup analysis showed that prenatal ETS exposure was linked to higher risk of symmetric FT-LBW (OR: 2.26, 95%CI: 1.56–3.26) but not asymmetric FT-LBW. And maternal appetite explained only 6.45% of their relationship. Conclusions: Maternal prenatal ETS exposure increased risk of having symmetric FT-LBW infant, and appetite might mediate their relationship partially. This study emphasizes the importance of sample homogeneity and stresses the needs to improve the public awareness of the harmful effects of ETS.
Effect of the wetland environment on particulate matter and dry deposition

ABSTRACT In Beijing, particulate matter (PM) in the atmosphere, especially PM2.5 and PM10, have attracted public attention because of its adverse effects. A series of studies have investigated the sources and spatial–temporal variation of PM. Wetland has been reported to own the capacity of resolving air problem. To examine the characteristics of the particulate matter in wetlands, the diurnal variation of PM2.5 and PM10 concentrations with respect to two heights (i.e. 1.5 and 10 m, respectively) and three meteorological factors (i.e. wind speed, temperature, and relative humidity, respectively) was monitored in the Cuihu National Wetland Park in Beijing, and the dry deposition velocity and flux were analysed using the above-mentioned data. Results indicated that (1) As for diurnal variation, the PM concentration constantly decreased at 07:00–16:00 and gradually increased at 16:00–18:00. The maximum instantaneous concentration was observed at 07:00–10:00, while the minimum instantaneous concentration was observed at 13:00–16:00. (2) The annual concentration variation of PM followed the order of dry period > wet period > normal period. (3) The particulate concentrations at 10 m were always greater than those at 1.5 m. (4) The PM concentration was positively correlated to the relative humidity and negatively correlated to the temperature. Wind speed exhibited a complex effect on PM concentration. (5) The regulation of dry deposition efficiency followed the order of spring > winter > summer. (6) Wind speed strongly and positively affected the dry deposition velocity of PM10. The effects of temperature and relative humidity on dry deposition were uncertain. GRAPHICAL ABSTRACT
HC-Net: Memory-based Incremental Dual-Network System for Continual learning

Training a neural network for a classification task typically assumes that the data to train are given from the beginning. However, in the real world, additional data accumulate gradually and the model requires additional training without accessing the old training data. This usually leads to the catastrophic forgetting problem which is inevitable for the traditional training methodology of neural networks. In this paper, we propose a memory-based continual learning method that is able to learn additional tasks while retaining the performance of previously learned tasks. Composed of two complementary networks, the Hippocampus-net (H-net) and the Cortex-net (C-net), our model estimates the index of the corresponding task for an input sample and utilizes a particular portion of itself with the estimated index. The C-net guarantees no degradation in the performance of the previously learned tasks and the H-net shows high confidence in finding the origin of the input sample
DRAG: Deep Reinforcement Learning Based Base Station Activation in Heterogeneous Networks

Heterogeneous Network (HetNet), where Small cell Base Stations (SBSs) are densely deployed to offload traffic from macro Base Stations (BSs), is identified as a key solution to meet the unprecedented mobile traffic demand. The high density of SBSs are designed for peak traffic hours and consume an unnecessarily large amount of energy during off-peak time. In this paper, we propose a Deep Reinforcement-Learning (DRL) based SBS activation strategy that activates the optimal subset of SBSs to significantly lower the energy consumption without compromising the quality of service. In particular, we formulate the SBS on/off switching problem into a Markov Decision Process that can be solved by Actor Critic (AC) reinforcement learning methods. To avoid prohibitively high computational and storage costs of conventional tabular-based approaches, we propose to use deep neural networks to approximate the policy and value functions in the AC approach. Moreover, to expedite the training process, we adopt a Deep Deterministic Policy Gradient (DDPG) approach together with a novel action refinement scheme. Through extensive numerical simulations, we show that the proposed scheme greatly outperforms the existing methods in terms of both energy efficiency and computational efficiency. We also show that the proposed scheme can scale to large system with polynomial complexities in both storage and computation.
Dual aortic and portal perfusion at procurement prevents ischaemic‐type biliary lesions in liver transplantation when using octogenarian donors: a retrospective cohort study

Several risk factors for ischaemic‐type biliary lesions (ITBL) after liver transplantation (LT) have been identified, but the role of portal vein perfusion at graft procurement is still unclear. This was a prospective study on double aortic and portal perfusion (DP) of liver grafts stratified by donor's decade (<60 yo; 60–69 yo; 70–79 yo and ≥80 yo) versus similar historical cohorts of primary, adult grafts procured with single aortic perfusion (SP) only. The primary study aim was to assess the role of DP on the incidence of ITBL. There was no difference in the incidence of overall biliary complications according to procurement technique for recipients of grafts <80 years. A higher incidence of ITBL was observed for patients receiving grafts ≥80 years and perfused through the aorta only (1.9 vs. 13.4%; P = 0.008). When analysing octogenarian grafts, donor male gender (HR = 6.4; P = 0.001), haemodynamic instability (HR = 4.9; P = 0.008), and type‐2 diabetes mellitus (DM2) (HR = 3.0; P = 0.03) were all independent risk factors for ITBL, while double perfusion at procurement (HR = 0.1; P = 0.04) and longer donor intensive care unit (ICU) stay (HR = 0.7; P = 0.04) were protective factors. Dual aortic and portal perfusion has the potential to reduce post‐transplant ITBL incidence for recipients of octogenarian donor grafts. Larger series are needed to confirm this preliminary experience.
A Requirement for Global Transcription Factor Lrp in Licensing Replication of Vibrio cholerae Chromosome 2

The human pathogen, Vibrio cholerae, belongs to the 10% of bacteria in which the genome is divided. Each of its two chromosomes, like bacterial chromosomes in general, replicates from a unique origin at fixed times in the cell cycle. Chr1 initiates first, and upon duplication of a site in Chr1, crtS, Chr2 replication initiates. Recent in vivo experiments demonstrate that crtS binds the Chr2-specific initiator RctB and promotes its initiator activity by remodeling it. Compared to the well-defined RctB binding sites in the Chr2 origin, crtS is an order of magnitude longer, suggesting that other factors can bind to it. We developed an in vivo screen to identify additional crtS-binding proteins and identified the global transcription factor, Lrp, as one such protein. Studies in vivo and in vitro indicate that Lrp binds to crtS and facilitates RctB binding to crtS. Chr2 replication is severely defective in the absence of Lrp, indicative of a critical role of the transcription factor in licensing Chr2 replication. Since Lrp responds to stresses such as nutrient limitation, its interaction with RctB presumably sensitizes Chr2 replication to the physiological state of the cell.
ADM for grid CRF loss in CNN segmentation

Variants of gradient descent (GD) dominate CNN loss minimization in computer vision. But, as we show, some powerful loss functions are practically useless only due to their poor optimization by GD. In the context of weakly-supervised CNN segmentation, we present a general ADM approach to regularized losses, which are inspired by well-known MRF/CRF models in "shallow" segmentation. While GD fails on the popular nearest-neighbor Potts loss, ADM splitting with $\alpha$-expansion solver significantly improves optimization of such grid CRF losses yielding state-of-the-art training quality. Denser CRF losses become amenable to basic GD, but they produce lower quality object boundaries in agreement with known noisy performance of dense CRF inference in shallow segmentation.
Mosquito-larvicidal binary toxin receptor protein (Cqm1): crystallization and X-ray crystallographic analysis.

Cqm1 from Culex quinquefasciatus has been identified as the receptor for Lysinibacillus sphaericus binary toxin (BinAB). It is an amylomaltase that is presented on the epithelial membrane in the larval midgut through a glycosyl-phosphatidylinositol anchor. The active core of this protein (residues 23-560) was overexpressed in Escherichia coli, purified and successfully crystallized by the sitting-drop vapor-diffusion method using D-arabinose and CaCl2 as additives, as identified using high-throughput differential scanning fluorimetry analysis. X-ray diffraction data were collected to a resolution of 2.8 Å using a laboratory X-ray source. The crystals had the symmetry of space group P212121, with unit-cell parameters a = 191.3, b = 205.3, c = 59.0 Å and with four monomers in the asymmetric unit. Structure refinement is in progress. This is the first structure report for a binary toxin receptor and for a member of the GH13_17 subfamily in the CAZy database.
Mechanical incompatibility caused by modifications of multiple male genital structures using genomic introgression in Drosophila *

Mechanical incompatibility of male and female genitalia is common in animals with internal fertilization. However, our knowledge regarding the precise mechanisms is limited. One key question regards the susceptibility of the match between male and female genitalia to morphological modification. To address this issue, we generated six different second‐chromosome introgression lines possessing partially Drosophila mauritiana‐like genital morphology in multiple structures in D. simulans background. Three of the six introgression males showed elevated mobility at some stages during copulation with D. simulans females; this was assumed to be an indication of genital mismatch. Notably, one of the introgression males with D. mauritiana‐like enlarged anal plates showed occasional leakage of adhesive ejaculate on the body surface when mated with pure D. simulans females, suggesting apparent structural incompatibility in genital coupling. These observations suggested that both sexual and natural selection shape the anal plate morphology, highlighting the role of this structure as an important component of mechanical isolation. Partial replacement (introgression) by a sibling species genome can induce perturbations in genital coupling mechanics, suggesting that genital compatibility can be susceptible to subtle genomic changes at the early stages of divergence in these species.
3 Applying Deep Learning to Derivatives Valuation

The universal approximation theorem of artificial neural networks states that a forward feed network with a single hidden layer can approximate any continuous function, given a finite number of hidden units under mild constraints on the activation functions(see Hornik, 1991; Cybenko, 1989). Deep neural networks are preferred over shallow neural networks, as the later can be shown to require an exponentially larger number of hidden units (Telgarsky, 2016). This paper applies deep learning to train deep artificial neural networks to approximate derivative valuation functions using a basket option as an example. To do so it develops a Monte Carlo based sampling technique to derive appropriate training and test data sets. The paper explores a range of network geometries. The performance of the training phase and the inference phase are presented using GPU technology.