Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluating the use of machine learning in endometrial cancer: a systematic review

Objective To review the literature on machine learning in endometrial cancer, report the most commonly used algorithms, and compare performance with traditional prediction models. Methods This is a systematic review of the literature from January 1985 to March 2021 on the use of machine learning in endometrial cancer. An extensive search of electronic databases was conducted. Four independent reviewers screened studies initially by title then full text. Quality was assessed using the MINORS (Methodological Index for Non-Randomized Studies) criteria. P values were derived using the Pearson’s Χ2 test in JMP 15.0. Results Among 4295 articles screened, 30 studies on machine learning in endometrial cancer were included. The most frequent applications were in patient datasets (33.3%, n=10), pre-operative diagnostics (30%, n=9), genomics (23.3%, n=7), and serum biomarkers (13.3%, n=4). The most commonly used models were neural networks (n=10, 33.3%) and support vector machine (n=6, 20%). The number of publications on machine learning in endometrial cancer increased from 1 in 2010 to 29 in 2021.Eight studies compared machine learning with traditional statistics. Among patient dataset studies, two machine learning models (20%) performed similarly to logistic regression (accuracy: 0.85 vs 0.82, p=0.16). Machine learning algorithms performed similarly to detect endometrial cancer based on MRI (accuracy: 0.87 vs 0.82, p=0.24) while outperforming traditional methods in predicting extra-uterine disease in one serum biomarker study (accuracy: 0.81 vs 0.61). For survival outcomes, one study compared machine learning with Kaplan-Meier and reported no difference in concordance index (83.8% vs 83.1%). Conclusion Although machine learning is an innovative and emerging technology, performance is similar to that of traditional regression models in endometrial cancer. More studies are needed to assess its role in endometrial cancer. PROSPERO registration number CRD42021269565.
FPGA-based Deep Learning Inference Accelerators: Where Are We Standing?

Recently, artificial intelligence applications have become part of almost all emerging technologies around us. Neural networks, in particular, have shown significant advantages and have been widely adopted over other approaches in machine learning. In this context, high processing power is deemed a fundamental challenge and a persistent requirement. Recent solutions facing such a challenge deploy hardware platforms to provide high computing performance for neural networks and deep learning algorithms. This direction is also rapidly taking over the market. Here, FPGAs occupy the middle ground regarding flexibility, reconfigurability, and efficiency compared to general-purpose CPUs, GPUs, on one side, and manufactured ASICs on the other. FPGA-based accelerators exploit the features of FPGAs to increase the computing performance for specific algorithms and algorithm features. Filling a gap, we provide holistic benchmarking criteria and optimization techniques that work across several classes of deep learning implementations. This article summarizes the current state of deep learning hardware acceleration: More than 120 FPGA-based neural network accelerator designs are presented and evaluated based on a matrix of performance and acceleration criteria, and corresponding optimization techniques are presented and discussed. In addition, the evaluation criteria and optimization techniques are demonstrated by benchmarking ResNet-2 and LSTM-based accelerators.
Does empathy lead to creativity? A simulation-based investigation on the role of team trait empathy on nominal group concept generation and early concept screening

Abstract Research on empathy has been surging in popularity in the engineering design community since empathy is known to help designers develop a deeper understanding of the users’ needs. Because of this, the design community has become more invested in devising and assessing empathic design activities. However, research on empathy has been primarily limited to individuals, meaning we do not know how it impacts team performance, particularly in the concept generation and selection stages of the design process. Specifically, it is unknown how the empathic composition of teams, defined here as the average (elevation) and standard deviation (diversity) of team members’ empathy, would impact design outcomes during nominal group concept generation and early concept screening. Therefore, the goal of the current study is to investigate the impact of team empathy on nominal group concept generation and early concept screening in an engineering design student project. This was accomplished through a computational simulation of 13,482 teams of non-interacting brainstorming individuals generated by a statistical bootstrapping technique. This simulation drew upon a design repository of 806 ideas generated by first-year engineering students. The main findings from the study indicated that the impact of the elevation and diversity of different components of team empathy varied depending upon the specific design outcome (number of ideas, overall creativity, elegance, usefulness, uniqueness) and design stage (concept generation and concept screening). The results from this study can be used to guide team formation in engineering design.
Repeatability of adaptation in sunflowers: genomic regions harbouring inversions also drive adaptation in species lacking an inversion

Local adaptation commonly involves alleles of large effect, which experience fitness advantages when in positive linkage disequilibrium (LD). Because segregating inversions suppress recombination and facilitate the maintenance of LD between locally adapted loci, they are also commonly found to be associated with adaptive divergence. However, it is unclear what fraction of an adaptive response can be attributed to inversions and alleles of large effect, and whether the loci within an inversion could still drive adaptation in the absence of its recombination-suppressing effect. Here, we use genome-wide association studies to explore patterns of local adaptation in three species of sunflower: Helianthus annuus, H. argophyllus, and H. petiolaris, which each harbour a large number of species-specific inversions. We find evidence of significant genome-wide repeatability in signatures of association to phenotypes and environments, which are particularly enriched within regions of the genome harbouring an inversion in one species. This shows that while inversions may facilitate local adaptation, at least some of the loci can still harbour mutations that make substantial contributions without the benefit of recombination suppression in species lacking a segregating inversion. While a large number of genomic regions show evidence of repeated adaptation, most of the strongest signatures of association still tend to be species-specific, indicating substantial genotypic redundancy for local adaptation in these species.
Empirical Analysis of Beam Search Curse and Search Errors with Model Errors in Neural Machine Translation

Beam search is the most popular decoding method for Neural Machine Translation (NMT) and is still a strong baseline compared with the newly proposed sampling-based methods. To better understand beam search, we investigate its two well-recognized issues, beam search curse and search errors, at the sentence level. We find that only less than 30% of sentences in the test set experience these issues. Meanwhile, there is a related phenomenon. For the majority of sentences, their gold references have lower probabilities than the predictions from beam search. We also test with different levels of model errors including a special test using training samples and models without regularization. We find that these phenomena still exist even for a model with an accuracy of 95% although they are mitigated. These findings show that it is not promising to improve beam search by seeking higher probabilities in searching and further reducing its search errors. The relationship between the quality and the probability of predictions at the sentence level in our results provides useful information to find new ways to improve NMT.
How can machine translation help generate Arab melodic improvisation?

This article presents a system to generate Arab music improvisation using machine translation. To reach this goal, we developed a machine translation model to translate a vocal improvisation into an automatic instrumental oud (Arab lute) response. Given the melodic and non-metric musical form, it was necessary to develop efficient textual representations for classical machine translation models to be as successful as NLP applications. We experimented with SMT and NMT to train our parallel corpus (Vocal to Instrumental) of 6991 sentences. The best model was then used to generate improvisation by iteratively translating thThis article presents a system to generate Arab music improvisation using machine translation (MT). To reach this goal, we developed a MT model to translate a vocal improvisation into an automatic instrumental oud (Arab lute) response. Given the melodic and non-metric musical form, it was necessary to develop efficient textual representations in order for classical MT models to be as successful as in common NLP applications. We experimented with Statistical and Neural MT to train our parallel corpus (Vocal to Instrument) of 6991 sentences. The best model was then used to generate improvisation by iteratively translating the translations of the most common patterns of each maqām (n-grams), producing elaborated variations conditioned to listener feedback. We constructed a dataset of 717 instrumental improvisations to extract their n-grams. Objective evaluation of MT was conducted at two levels: a sentence-level evaluation using the BLEU metric, and a higher level evaluation using musically informed metrics. Objective measures were consistent with one another. Subjective evaluations by experts from the maqām music tradition were promising, and a useful reference for understanding objective results.e translations of the most common patterns of each maqām (n-grams), producing elaborated variations conditioned to listener feedback. We constructed a dataset of 717 instrumental improvisations to extract their n-grams. Objective evaluation of machine translation was conducted at two levels: a sentence-level evaluation using the BLEU metric, and a higher level evaluation using musically informed metrics. Objective measures were consistent with one another. Subjective evaluations by experts from the maqām music tradition were promising, and a useful reference for understanding objective results.
Insights into Digit Evolution from a Fate Map Study of the Forearm

The cellular and genetic networks which contribute to the development of the zeugopod, (radius and ulna of the forearm, tibia and fibula of the leg) are not well understood, although these bones are susceptible to loss in congenital human syndromes and to the action of teratogens such as thalidomide. Using a new fate mapping approach in transgenic chickens, we show that there is a small contribution of SHH expressing cells to the posterior ulna, posterior carpals and digit 3. We establish that while the majority of the ulna develops in response to paracrine SHH signaling in both the chicken and mouse, there are differences in the contribution of SHH expressing cells to other tissues of the zeugopod between these two species as well as between the chicken ulna and fibula. This is evidence that although zeugopod bones are clearly homologous according to the fossil record, the zeugopod bones of the wing and leg are formed by subtly different signalling and patterning events during embryonic development, which can be used to understand the shaping of the bird wing skeleton during the evolution of powered flight.
Toxoplasma gondii actin filaments are tuned for rapid disassembly and turnover

The cytoskeletal protein actin plays a critical role in the pathogenicity of Toxoplasma gondii, mediating invasion and egress, cargo transport, and organelle inheritance. Advances in live cell imaging have revealed extensive filamentous actin networks in the Apicomplexan parasite, but there is conflicting data regarding the biochemical and biophysical properties of Toxoplasma actin. Here, we imaged the in vitro assembly of individual Toxoplasma actin filaments in real time, showing that native, unstabilized filaments grow tens of microns in length. Unlike skeletal muscle actin, Toxoplasma filaments intrinsically undergo rapid treadmilling due to a high critical concentration, fast monomer dissociation, and rapid nucleotide exchange. Cryo-EM structures of stabilized and unstabilized filaments show an architecture like skeletal actin, with differences in assembly contacts in the D-loop that explain the dynamic nature of the filament, likely a conserved feature of Apicomplexan actin. This work demonstrates that evolutionary changes at assembly interfaces can tune dynamic properties of actin filaments without disrupting their conserved structure.
RdDM mutants reduce histone methylation rather than DNA methylation at the paramutated maize b1 enhancer

Paramutation is the transfer of mitotically and meiotically heritable silencing information between two alleles. With paramutation at the maize booster1 (b1) locus, the low expressed B’ epiallele heritably changes the high expressed B-I epiallele into B’ with 100% frequency. This requires specific tandem repeats and multiple components of the RNA-directed DNA methylation (RdDM) pathway, including the RNA-dependent RNA polymerase (RdRP, mediator of paramutation1, MOP1), the second-largest subunit of RNA polymerase IV and V (NRP(D/E)2a, mediator of paramutation2, MOP2), and the largest subunit of RNA Polymerase IV (NRPD1, mediator of paramutation3, MOP3). Mutations in mop genes prevent paramutation and release silencing at the B’ epiallele. In this study we investigated the effect of mutations in mop1, mop2 and mop3 on chromatin structure and DNA methylation at the B’ epiallele, and especially the regulatory hepta-repeat 100 kb upstream of the b1 gene. We show that mutations in mop1 and mop3 result in decreased repressive histone modifications H3K9me2 and H3K27me2 at the hepta-repeat. Associated with this decrease are partial activation of the hepta-repeat enhancer function, formation of a multi-loop structure, and elevated b1 expression. In mop2 mutants, which do not show elevated b1 expression, H3K9me2 and H3K27me2 and a single-loop structure like in wild type B’ are retained. Surprisingly, high DNA methylation levels at the B’ hepta-repeat remains in all three mutants. Our results raise the possibility of MOP factors mediating RNA-directed histone methylation rather than RNA-directed DNA methylation at the b1 locus.
Hostility may explain the association between depressive mood and mortality: Evidence from the French GAZEL cohort study Running title: Hostility, depression and mortality

Background Depressive mood is associated with mortality. Because personality has been found to be associated with depression and mortality as well, we aimed to test whether depressive mood could predict mortality when adjusting for several measures of personality. Methods 20,625 employees of the French national gas and electricity companies gave consent to enter in the GAZEL cohort in 1989. Questionnaires were mailed in 1993 to assess depressive mood, Type A behaviour pattern, hostility, and the six personality types proposed by GrossarthMaticek & Eysenck. Vital status and date of death were obtained annually for all participants. The association between psychological variables and mortality was measured by the Relative Index of Inequality (RII) computed through Cox regression. Results 14,356 members of the GAZEL cohort (10,916 men, mean age: 49 years, 3,965 women, mean age: 46 years) completed the depressive mood scale and at least one personality scale. During a mean follow-up of 14.8 years, 687 participants had died. Depressive mood predicted mortality, even after adjustment for age, sex, education level, body mass index, alcohol consumption, and smoking [RII (95% CI) = 1.56 (1.16-2.11)]. However, this association was dramatically reduced (RII reduction: 78.9%) after further adjustment for cognitive hostility (i.e. hostile thoughts) [RII (95% CI) = 1.12 (0.80-1.57)]. Cognitive hostility was the only personality measure remaining associated with mortality after adjustment for depressive mood [RII (95% CI) = 1.97 (1.39-2.77)]. Conclusions Cognitive hostility may either confound or mediate the association between depressive mood and mortality. in se rm -0 04 64 81 3, v er si on 1 18 M ar 2 01 0
Pengaruh Brand Ambassador Terhadap Keputusan Pembelian Smartphone Oppo F3 di Samarinda

Penelitian ini bertujuan untuk mengetahui pengaruh brand ambassador yang terdiri dari varibel daya tarik, kredibilitas, dan keahlian secara parsial terhadap keputusan pembelian. Penarikan sampel dalam penelitian ini menggunakan metode non probability sampling , dengan menggunakan teknik sampling incidental . Sampel yang digunakan ialah konsumen smartphone Oppo F3 di Samarinda. Jumlah sampel yang digunakan adalah 75 responden. Metode analisis data yang digunakan adalah regresi linier berganda menggunakan SPSS versi 20. Hasil penelitian ini menunjukkan bahwa variabel brand ambassador yang terdiri dari daya tarik, kredibilitas, dan keahlian secara parsial berpengaruh positif signifikan terhadap keputusan pembelian smartphone Oppo F3 di Samarinda
Factors Affecting Software Maintenance Productivity: an Exploratory Studyl

Systems developers and researchers have long been interested in the factors that affect software development productivity. Identification of factors as either aiding or hindering productivity enables management to take steps to encourage the positive influences and to eliminate the negative ones. This research has explored the possibility of developing an estimable model of software development productivity using a frontier estimation method. The approach taken is based upon output metrics for the entire project life-cycle, and includes project quality metrics. A large number of factors potentially affecting software maintenance productivity were included in this initial investigation. The empirical analysis of a pilot data set indicated that high project quality did not necessarily reduce project productivity. Significant factors in explaining positive variations in productivity included project team capability and good system response (turnaround) time. Factors significantly associated with negative variations in productivity included lack of team application experience and high project staff loading. The use of a new structured analysis and design methodology also resulted in lower short term productivity. These preliminary results have suggested a number of new research directions and have prompted the data-site to begin a full scale data collection effort in order to validate a model of software maintenance productivity.
Chikungunya virus–associated encephalitis: A cohort study on La Réunion Island, 2005–2009

Editors' Note: Commenting on “Chikungunya virus–associated encephalitis: A cohort study on La Reunion Island, 2005–2009,” Dr. Oliveira wonders whether chikungunya virus could be responsible for the microcephaly and Guillain-Barre syndrome that are currently being linked to the Zika virus epidemic. In response, Gerardin et al., authors of the original article, reanalyzed their cohorts and did not find any association between chikungunya virus and microcephaly or other congenital malformation. Drs. Sena et al. correct authors Munger et al. about the statement in their study that “…only one study among patients with multiple sclerosis (MS) has found no association between smoking and progression,” referring to their own study that …
The Economics of Fiscal Rules and Debt Sustainability 1

Because they exert cross-border spill-over effects, fiscal policies of individual EU Member States (MS) are a common concern for the entire EU. An expansionary fiscal stance in one country raises imports from other countries, thereby stimulating their economies (Beetsma et al., 2006; Alcidi et al., 2015), but it also pushes up its public debt, magnifying solvency risk, which may spill-over to other MS or force other MS to come to financial rescue. These spill-overs provide the main rationale for the EU’s Stability and Growth Pact (SGP), with its most visible elements the 3% of GDP reference value for the deficit and the 60% reference value for the public debt. The SGP strengthens the EU Treaty’s “no-bail-out clause” by which countries or EU institutions are forbidden to bail out a country in financial difficulty. The rationale behind the clause is that a credible no-bail-out clause limits moral hazard on the side of governments. Knowing that no other party comes to the rescue, they will behave responsibly, otherwise financial markets will force them to do so. In effect, the SGP is the answer to the fear that markets cannot adequately fulfil this role, creating a risk that the no-bail-out clause will be tested, which is what has indeed happened.
Multiple Interprofessional Education Activities Delivered Longitudinally Within a Required Clinical Assessment Course

Objective. To determine if the incorporation of multiple interprofessional educational (IPE) activities delivered as a longitudinal curriculum within a required clinical assessment course changed pharmacy students’ perceptions regarding interprofessional collaboration. Design. Seventy-one third-year pharmacy students participated in Clinical Assessment, a required applications-based course with a laboratory component. Nine separate IPE activities were embedded into the course longitudinally over the semester using various active-learning strategies and simulated patients. The IPE activities required student participation from medical, nursing, and physician assistant students. Assessment. Pharmacy students completed an 18-item validated survey instrument, the Interdisciplinary Education Perception Scale (IEPS), on the first (pre-survey) and last (post-survey) day of the course. After completing the course, scores improved on 16 of 18 survey items that measured pharmacy students’ perceptions of interprofessional collaboration. Conclusion. Incorporating multiple IPE activities longitudinally into a required clinical assessment course significantly changed pharmacy students’ perceptions of interprofessional collaboration.
Globalization and the Race to the Bottom in Developing Countries: Who Really Gets Hurt?

Preface 1. Introduction 2. The race to the bottom in developing countries 3. Who really gets hurt? 4. LDC welfare states: convergence? What are the implications? 5. Globalization and the protective welfare state: case study of India 6. Globalization and the productive welfare state: case study of South Korea 7. Globalization and the dual welfare state: case study of Brazil 8. Conclusions Appendices.