Miracle-dz/UniFAR-FTUs huggingface dataset:
Neural Transduction of Letter Position Dyslexia using an Anagram Matrix Representation

Research on analyzing reading patterns of dyslectic children has mainly been driven by classifying dyslexia types offline. We contend that a framework to remedy reading errors inline is more far-reaching and will help to further advance our understanding of this impairment. In this paper, we propose a simple and intuitive neural model to reinstate migrating words that transpire in letter position dyslexia, a visual analysis deficit to the encoding of character order within a word. Introduced by the anagram matrix representation of an input verse, the novelty of our work lies in the expansion from one to a two dimensional context window for training. This warrants words that only differ in the disposition of letters to remain interpreted semantically similar in the embedding space. Subject to the apparent constraints of the self-attention transformer architecture, our model achieved a unigram BLEU score of 40.6 on our reconstructed dataset of the Shakespeare sonnets.
Conservation genetics in the new molecular age

Molecular techniques can be used to address questions of conservation significance. At the individual level, these questions concern how kinship affects reproduction, group structure, dispersal, and cooperation which leads to social group assembly rules such that populations can be genetically managed and restored. Furthermore, inbreeding can now be measured at the individual level in natural populations, and, in combination with field studies, can be used to assess fitness declines that might require active management to arrest. We discuss genetic units for conservation and attempt to integrate data on phenotype and the environment into an evaluation that includes genetic data. To a limited extent, genetic surveys can now include genes that may influence fitness, as well as those not under selection. We discuss the use of animal and plant remains to monitor current populations and to determine directly the demographic changes that have occurred in the past.
Isozyme profiles associated with the hypersensitive response of Chenopodium foetidum to plum pox virus infection

Isozyme profiles of esterases (E.C. 3.1.1.1), glutamate oxaloacetate transaminase (E.C. 2.6.1.1) and peroxidases (E.C. 1.11.1.7) have been determined in healthy tissues of Chenopodium foetidum as well as their modifications during leaf development. The effect of plum pox virus infection on the isozyme profiles has also been studied. Virus-induced necrotic lesions displayed a peroxidase (POX) pattern that has not been found in any other tissue of the plant so far analyzed. The pattern was similar to that of old yellow leaves, except that POX-B, which was detected in the necrotic lesions, has not been detected in any developmental stage of healthy leaves. Changes in the peroxidase profile seem to begin early during infection, even before necrosis is visible. We suggest that senescence is established at necrotic lesions extending from there to the rest of the infected leaf affecting the peroxidase isozyme pattern. However, other changes, which induce POX-B, must also take place at necrotic lesions. These do not extend to the rest of the infected leaves. Plum pox virus infection has less effect on the glutamate oxaloacetate transaminase and esterase isozyme patterns, inducing an almost normal senescence pattern.
Biomarker-driven phase 2 umbrella trial study for patients with recurrent small cell lung cancer failing platinum-based chemotherapy.

BACKGROUND A high percentage of small cell lung cancer (SCLC) cases harbor cell cycle-related gene mutations and RICTOR amplification. Based on underlying somatic mutations, the authors have conducted a phase 2 biomarker-driven, multiarm umbrella study. METHODS The SCLC Umbrella Korea StudiES (SUKSES) is an adaptive platform trial that undergoes continual modification according to the observed outcomes. This study included 286 patients with SCLC who failed platinum therapy and who had known genomic profiles based on a predesigned screening trial. Patients with MYC amplification or CDKN2A and TP53 co-alterations were allocated to adavosertib (SUKSES protocol C [SUKSES-C]; 7 patients) and those with RICTOR amplification were allocated to vistusertib (SUKSES-D; 4 patients). Alternatively, patients who were without any predefined biomarkers were assigned to a non-biomarker-selected arm: adavosertib (SUKSES-N1; 21 patients) or AZD2811NP (SUKSES-N3; 15 patients). RESULTS Patients in the SUKSES-C and SUKSES-N1 arms demonstrated no objective response. Three patients presented with stable disease (SD) in SUKSES-C and 6 patients in SUKSES-N1. The median progression-free survival (PFS) was 1.3 months (95% confidence interval, 0.9 months to not available) for SUKSES-C and 1.2 months (95% CI, 1.1-1.4 months) for SUKSES-N1. Patients in the SUKSES-D arm demonstrated no objective response and no SD, with a PFS of 1.2 months (95% CI, 1.0 months to not available). The SUKSES-N3 arm had 5 patients with SD and a PFS of 1.6 months (95% CI, 0.9-1.7 months), without an objective response. Grade≥3 adverse events (graded according to National Cancer Institute Common Terminology Criteria for Adverse Events [version 4.03]) were observed as follows: 3.2% in the SUKSES-C and SUKSES-N1 arms and 50.0% in the SUKSES-D arm. Target-related neutropenia (grade≥3) was observed in approximately 60.0% of patients in the AZD2811NP arm using the current dosing schedule. CONCLUSIONS To the best of the authors' knowledge, the current study is the first biomarker-driven umbrella study conducted in patients with recurrent SCLC. Although the current study demonstrated the limited clinical efficacy of monotherapy, novel biomarker approaches using other cell cycle inhibitor(s) or combinations warrant further investigation.
Towards Stream Translation: Adaptive Computation Time for Simultaneous Machine Translation

Simultaneous machine translation systems rely on a policy to schedule read and write operations in order to begin translating a source sentence before it is complete. In this paper, we demonstrate the use of Adaptive Computation Time (ACT) as an adaptive, learned policy for simultaneous machine translation using the transformer model and as a more numerically stable alternative to Monotonic Infinite Lookback Attention (MILk). We achieve state-of-the-art results in terms of latency-quality tradeoffs. We also propose a method to use our model on unsegmented input, i.e. without sentence boundaries, simulating the condition of translating output from automatic speech recognition. We present first benchmark results on this task.
Antioxidant activity of chestnut constituents: flowers, leaves, skins and fruits

In this study, the antioxidant properties of different chestnut constituents (flowers, leaves, skins and fruits) were evaluated through several biochemical assays: DPPH (2,2-diphenyl-1picrylhydrazyl) radical scavenging activity, reducing power, inhibition of β-carotene bleaching, inhibition of oxidative hemolysis in erythrocytes, induced by 2,2’-azobis(2amidinopropane)dihydrochloride (AAPH), and inhibition of lipid peroxidation in pig brain tissue through formation of thiobarbituric acid reactive substances (TBARS). These assays have been extensively studied as models for the peroxidative damage in biomembranes. For all the methods EC50 values were calculated in order to evaluate the antioxidant efficiency of each product. The phenol and flavonoid contents were also obtained and correlated to antioxidant activity. Chestnut skins revealed much better antioxidant properties, presenting much lower EC50 values, particularly for lipid peroxidation inhibition in TBARS assay. Also, the highest antioxidant contents (phenols and flavonoids) were found for this constituent. Key-words: Chestnut constituents; Antioxidants; Scavenging effects; Peroxidation and Hemolysis inhibition
Quantifying 60 Years of Gender Bias in Biomedical Research with Word Embeddings

Gender bias in biomedical research can have an adverse impact on the health of real people. For example, there is evidence that heart disease-related funded research generally focuses on men. Health disparities can form between men and at-risk groups of women (i.e., elderly and low-income) if there is not an equal number of heart disease-related studies for both genders. In this paper, we study temporal bias in biomedical research articles by measuring gender differences in word embeddings. Specifically, we address multiple questions, including, How has gender bias changed over time in biomedical research, and what health-related concepts are the most biased? Overall, we find that traditional gender stereotypes have reduced over time. However, we also find that the embeddings of many medical conditions are as biased today as they were 60 years ago (e.g., concepts related to drug addiction and body dysmorphia).
Commonsense Reasoning for Natural Language Processing

Commonsense knowledge, such as knowing that “bumping into people annoys them” or “rain makes the road slippery”, helps humans navigate everyday situations seamlessly. Yet, endowing machines with such human-like commonsense reasoning capabilities has remained an elusive goal of artificial intelligence research for decades. In recent years, commonsense knowledge and reasoning have received renewed attention from the natural language processing (NLP) community, yielding exploratory studies in automated commonsense understanding. We organize this tutorial to provide researchers with the critical foundations and recent advances in commonsense representation and reasoning, in the hopes of casting a brighter light on this promising area of future research. In our tutorial, we will (1) outline the various types of commonsense (e.g., physical, social), and (2) discuss techniques to gather and represent commonsense knowledge, while highlighting the challenges specific to this type of knowledge (e.g., reporting bias). We will then (3) discuss the types of commonsense knowledge captured by modern NLP systems (e.g., large pretrained language models), and (4) present ways to measure systems’ commonsense reasoning abilities. We will finish with (5) a discussion of various ways in which commonsense reasoning can be used to improve performance on NLP tasks, exemplified by an (6) interactive session on integrating commonsense into a downstream task.
Towards Energy-Efficient Framework for IoT Big Data Healthcare Solutions

The aim of the Internet of things (IoT) is to bring every object (wearable sensors, healthcare sensors, cameras, home appliances, smart phones, etc.) online. These different objects generate huge data which consequently lead to the need of requirements of efficient storage and processing. Cloud computing is an emerging technology to overcome this problem. However, there are some applications (healthcare) which need to process data in real time to improve its performance and require low latency and delay. Fog computing is one of the promising solutions which facilitate healthcare domain in terms of reducing the delay multihop data communication, distributing resource demands, and promoting service flexibility. In this study, a fog-based IoT healthcare framework is proposed in order to minimize the energy consumption of the fog nodes. Experimental results reveal that the performance of the proposed framework is efficient in terms of network delay and energy usage. Furthermore, the authors discussed and suggested important services of big data infrastructure which need to be present in fog devices for the analytics of healthcare big data.
The use of otolith morphology to indicate the stock structure of common coral trout (Plectropomus leopardus) on the Great Barrier Reef, Australia

We investigated the use of otolith morphology to indicate the stock structure of an exploited serranid coral reef fish, Plectropomus leopardus, on the Great Barrier Reef (GBR), Australia. Otoliths were measured by traditional one- and two-dimensional measures (otolith length, width, area, perimeter, circularity, and rectangularity), as well as by Fourier analysis to capture the finer details of otolith shape. Variables were compared among four regions of the GBR separated by hundreds of kilometers, as well as among three reefs within each region, hundreds of meters to tens of kilometers apart. The temporal stability in otolith structure was examined by comparing two cohorts of fully recruited four-year-old P. leopardus collected two years before and two years after a significant disturbance in the southern parts of the GBR caused by a large tropical cyclone in March 1997. Results indicated the presence of at least two stocks of P. leopardus, although the structure of each stock varied depending on the cohort considered. The results highlight the importance of incorporating data from several years in studies using otolith morphology to discriminate temporary and possibly misleading signals from those that indicate persistent spatial structure in stocks. We conclude that otolith morphology can be used as an initial step to direct further research on groups of P. leopardus that have lived at least a part of their life in different environments.
Diet of the widespread insectivorous bats Eptesicus fuscus and Myotis lucifugus relative to climate and richness of bat communities

Abstract Partitioning of foraging niches of insectivorous bats likely is shaped by ecological factors such as availability of prey and competition; however, these factors are difficult to measure and there is little empirical evidence for either. We examined diet of the North American big brown bats (Eptesicus fuscus) and little brown bats (Myotis lucifugus) using published works and our own data from New England to better understand intraspecific dietary variation, and to test whether diet corresponded with climate (an indicator of availability of prey) and species richness of bat communities (a measure of potential interspecific competition). Diet of both species of bat varied with climate in a manner that generally corresponded with longitude. E. fuscus increased use of moths in regions with cool arid summers (western North America), whereas both species of bat consumed more beetles in moister summer climates associated with eastern North America. Additionally, E. fuscus consumed fewer beetles and more moths and true flies in more diverse bat communities. However, correlation between richness of bat communities and mean monthly precipitation limits interpretation of whether richness of bat communities influenced foraging beyond effects of climate alone. Results suggest diet is influenced indirectly by environmental factors that limit availability of prey. Further examination of these and other factors related to intraspecific dietary variation in insectivorous bats is warranted and likely to yield valuable ecological insight.
Improvement in Left Ventricular Ejection Fraction in Outpatients With Heart Failure With Reduced Ejection Fraction

Supplemental Digital Content is available in the text. Background: Among patients with heart failure (HF) with reduced ejection fraction (EF), improvements in left ventricular EF (LVEF) are associated with better outcomes and remain an important treatment goal. Patient factors associated with LVEF improvement in routine clinical practice have not been clearly defined. Methods: CHAMP-HF (Change the Management of Patients with Heart Failure) is a prospective registry of outpatients with HF with reduced EF. Assessments of LVEF are recorded when performed for routine care. We analyzed patients with both baseline and ≥1 follow-up LVEF assessments to describe factors associated with LVEF improvement. Results: In CHAMP-HF, 2623 patients had a baseline and follow-up LVEF assessment. The median age was 67 (interquartile range, 58–75) years, 40% had an ischemic cardiomyopathy, and median HF duration was 2.8 years (0.7–6.8). Median LVEF was 30% (23–35), and median change on follow-up was 4% (−2 to −13); 19% of patients had a decrease in LVEF, 31% had no change, 49% had a ≥5% increase, and 34% had a ≥10% increase. In a multivariable model, the following factors were associated with ≥5% LVEF increase: shorter HF duration (odds ratio [OR], 1.21 [95% CI, 1.17–1.25]), no implantable cardioverter defibrillator (OR, 1.46 [95% CI, 1.34–1.55]), lower LVEF (OR, 1.15 [95% CI, 1.10–1.19]), nonischemic cardiomyopathy (OR, 1.24 [95% CI, 1.09–1.36]), and no coronary disease (OR, 1.20 [95% CI, 1.03–1.35]). Conclusions: In a large cohort of outpatients with chronic HF with reduced EF, improvements in LVEF were common. Common baseline cardiac characteristics identified a population that was more likely to respond over time. These data may inform clinical decision making and should be the basis for future research on myocardial recovery.
Checkpoint Reranking: An Approach to Select Better Hypothesis for Neural Machine Translation Systems

In this paper, we propose a method of re-ranking the outputs of Neural Machine Translation (NMT) systems. After the decoding process, we select a few last iteration outputs in the training process as the N-best list. After training a Neural Machine Translation (NMT) baseline system, it has been observed that these iteration outputs have an oracle score higher than baseline up to 1.01 BLEU points compared to the last iteration of the trained system.We come up with a ranking mechanism by solely focusing on the decoder’s ability to generate distinct tokens and without the usage of any language model or data. With this method, we achieved a translation improvement up to +0.16 BLEU points over baseline.We also evaluate our approach by applying the coverage penalty to the training process.In cases of moderate coverage penalty, the oracle scores are higher than the final iteration up to +0.99 BLEU points, and our algorithm gives an improvement up to +0.17 BLEU points.With excessive penalty, there is a decrease in translation quality compared to the baseline system. Still, an increase in oracle scores up to +1.30 is observed with the re-ranking algorithm giving an improvement up to +0.15 BLEU points is found in case of excessive penalty.The proposed re-ranking method is a generic one and can be extended to other language pairs as well.
Unsupervised Paraphasia Classification in Aphasic Speech

Aphasia is a speech and language disorder which results from brain damage, often characterized by word retrieval deficit (anomia) resulting in naming errors (paraphasia). Automatic paraphasia detection has many benefits for both treatment and diagnosis of Aphasia and its type. But supervised learning methods cant be properly utilized as there is a lack of aphasic speech data. In this paper, we describe our novel unsupervised method which can be implemented without the need for labeled paraphasia data. Our evaluations show that our method outperforms previous work based on supervised learning and transfer learning approaches for English. We demonstrate the utility of our method as an essential first step in developing augmentative and alternative communication (AAC) devices for patients suffering from aphasia in any language.
COX5B-Mediated Bioenergetic Alteration Regulates Tumor Growth and Migration by Modulating AMPK-UHMK1-ERK Cascade in Hepatoma

The oxidative phosphorylation machinery in mitochondria, which generates the main bioenergy pool in cells, includes four enzyme complexes for electron transport and ATP synthase. Among them, the cytochrome c oxidase (COX), which constitutes the fourth complex, has been suggested as the major regulatory site. Recently, abnormalities in COX were linked to tumor progression in several cancers. However, it remains unclear whether COX and its subunits play a role in tumor progression of hepatoma. To search for the key regulatory factor(s) in COX for hepatoma development, in silico analysis using public transcriptomic database followed by validation for postoperative outcome associations using independent in-house patient cohorts was performed. In which, COX5B was highly expressed in hepatoma and associated with unfavorable postoperative prognosis. In addressing the role of COX5B in hepatoma, the loss- and gain-of-function experiments for COX5B were conducted. Consequently, COX5B expression was associated with increased hepatoma cell proliferation, migration and xenograft growth. Downstream effectors searched by cDNA microarray analysis identified UHMK1, an oncogenic protein, which manifested a positively correlated expression level of COX5B. The COX5B-mediated regulatory event on UHMK1 expression was subsequently demonstrated as bioenergetic alteration-dependent activation of AMPK in hepatoma cells. Phosphoproteomic analysis uncovered activation of ERK- and stathmin-mediated pathways downstream of UHMK1. Finally, comprehensive phenotypic assays supported the impacts of COX5B-UHMK1-ERK axis on hepatoma cell growth and migration.
PROBLEMS ON EXTREMAL PROPERTIES OF A FINITE SET OF POINTS

In 1977 I started a collection of problems in discrete geometry, distributing it and the subsequent revised versions to anyone who requested a copy. The most recent edition, “Research Problems in Discrete Geometry, 1981” (RPDG 1981) contains 68 problems; here I focus on problems from this collection that investigate extremal properties of a finite set of points. A revised version of each problem is given here to include whatever new information has become available. The designation number (# n) locates the problem in RPDG 1981.
Warming prevents the elevated CO2‐induced reduction in available soil nitrogen in a temperate, perennial grassland

Rising atmospheric carbon dioxide concentration ([CO2]) has the potential to stimulate ecosystem productivity and sink strength, reducing the effects of carbon (C) emissions on climate. In terrestrial ecosystems, increasing [CO2] can reduce soil nitrogen (N) availability to plants, preventing the stimulation of ecosystem C assimilation; a process known as progressive N limitation. Using ion exchange membranes to assess the availability of dissolved organic N, ammonium and nitrate, we found that CO2 enrichment in an Australian, temperate, perennial grassland did not increase plant productivity, but did reduce soil N availability, mostly by reducing nitrate availability. Importantly, the addition of 2 °C warming prevented this effect while warming without CO2 enrichment did not significantly affect N availability. These findings indicate that warming could play an important role in the impact of [CO2] on ecosystem N cycling, potentially overturning CO2‐induced effects in some ecosystems.
Evolutionary Multitasking for Multiobjective Optimization With Subspace Alignment and Adaptive Differential Evolution

In contrast to the traditional single-tasking evolutionary algorithms, evolutionary multitasking (EMT) travels in the search space of multiple optimization tasks simultaneously. Through sharing knowledge across the tasks, EMT is able to enhance solving the optimization tasks. However, if knowledge transfer is not properly carried out, the performance of EMT might become unsatisfactory. To address this issue and improve the quality of knowledge transfer among the tasks, a novel multiobjective EMT algorithm based on subspace alignment and self-adaptive differential evolution (DE), namely, MOMFEA-SADE, is proposed in this article. Particularly, a mapping matrix obtained by subspace learning is used to transform the search space of the population and reduce the probability of negative knowledge transfer between tasks. In addition, DE characterized by a self-adaptive trial vector generation strategy is introduced to generate promising solutions based on previous experiences. The experimental results on multiobjective multi/many-tasking optimization test suites show that MOMFEA-SADE is superior or comparable to other state-of-the-art EMT algorithms. MOMFEA-SADE also won the Competition on Evolutionary Multitask Optimization (the multitask multiobjective optimization track) within IEEE 2019 Congress on Evolutionary Computation.