Miracle-dz/UniFAR-FTUs huggingface dataset:
NMT’s wonderland where people turn into rabbits : a study on the comprehensibility of newly invented words in NMT output

Machine translation (MT) quality has improved enormously since the arrival of neural machine translation (NMT). The most noticeable improvement compared to statistical MT systems is the increased grammaticality and ﬂuency of the produced MT output. At the lexical level, the quality of NMT systems is less promising. New types of lexical mistakes appear in NMT output, such as the occurrence of non-existing words, i.e. words that are not part of the vocabulary of the target language and were thus invented by the NMT system. For MT use cases in which readers only have access to the MT output without the source text, such non-existing words can aﬀect comprehension as the intended source meaning may not be recovered. To investigate if and to what extent non-existing words in English-to-Dutch NMT output impair comprehension, an experiment was set up in SurveyMonkey. Eighty-six participants were given 15 non-existing words (5 single words and 10 noun compounds) and were either asked to describe the meaning of these words or to select the correct meaning from a predeﬁned list. The words were presented either in isolation or in sentence context. Participants were asked to indicate how conﬁdent they were about their answer. Results show that non-existing words indeed impair comprehension as in 60% of the cases the participants gave a wrong answer. Sentence context had a positive impact and made it easier for the participants to determine the meaning of the non-existing word. Participants were also more conﬁdent about their answer when the words were presented in sentence context.
Molecular Dynamics Modeling of Crack Propagation

The study is focused on the application of different approaches for initial crack propagation angle determination. Copper plate with the central crack under complex mechanical stresses (Mode I and Mode II loading) is studied by extensive molecular dynamics simulations using EAM potential. In addition, the complete Williams expansion for the crack tip fields containing higher-order terms is used. Crack propagation angle is obtained by 1) multi-parameter fracture mechanics approach based on three fracture mechanics criteria, MTS, maximum tangential strain and SED; 2) atomistic modeling for mixed-mode loading of plane medium with the central crack. From our simulations we can derive crack propagation directions and crack angles. MD calculations were run for three different values of the mixity parameter: 0.4, 0.5 and 0.6. Calculated values of crack angles were -51:5 deg, -46:6 deg and -42:2 deg accordingly. All the fracture criteria tested give similar values of crack growth angle for different values of the mixity parameter. It is shown that initial crack propagation angles given by both approaches are very close, especially when higher order terms of Williams series expansion for stress/displacement field description are taken into account. Thus, one can conclude that the criteria of classical continuum mechanics MTS and SED can give satisfactory predictions for crack initiation direction. Crack propagation direction angles given by conventional fracture mechanics reasonably agree with the angles obtained from molecular dynamics simulations.
The Cloud-resolving model Radar SIMulator (CR-SIM) Version 3.3: description and applications of a virtual observatory

Abstract. Ground-based observatories use multisensor observations to characterize cloud and precipitation properties. One of the challenges is how to design strategies to best use these observations to understand these properties and evaluate weather and climate models. This paper introduces the Cloud-resolving model Radar SIMulator (CR-SIM), which uses output from high-resolution cloud-resolving models (CRMs) to emulate multiwavelength, zenith-pointing, and scanning radar observables and multisensor (radar and lidar) products. CR-SIM allows for direct comparison between an atmospheric model simulation and remote-sensing products using a forward-modeling framework consistent with the microphysical assumptions used in the atmospheric model. CR-SIM has the flexibility to easily incorporate additional microphysical modules, such as microphysical schemes and scattering calculations, and expand the applications to simulate multisensor retrieval products. In this paper, we present several applications of CR-SIM for evaluating the representativeness of cloud microphysics and dynamics in a CRM, quantifying uncertainties in radar–lidar integrated cloud products and multi-Doppler wind retrievals, and optimizing radar sampling strategy using observing system simulation experiments. These applications demonstrate CR-SIM as a virtual observatory operator on high-resolution model output for a consistent comparison between model results and observations to aid interpretation of the differences and improve understanding of the representativeness errors due to the sampling limitations of the ground-based measurements. CR-SIM is licensed under the GNU GPL package and both the software and the user guide are publicly available to the scientific community.
An Exploratory Study of Single and Coupled Lesbian Mothers' Experiences with Social Support

This exploratory interview study reveals ten lesbian mothers’ experiences with different forms of social support. Ten lesbian mothers, five single and five who were part of couples, all with young children and living in southern Ontario, discussed their experiences with emotional, instrumental, and informational support from family, friends and neighbours, the LGBTQ (lesbian, gay, bisexual, transgender, queer/questioning) community, support groups, day cares and schools, health care providers, and online and print resources. Most women had largely positive experiences with family and friends but experienced more variability in the other domains. The mothers’ perceptions of potential support sources’ acceptance of diversity and efforts at inclusivity particularly influenced their willingness to access organized forms of support. The single lesbian mothers’ experiences differed from the coupled lesbian mothers’, although there was overlap. Organizations, service providers, and authors providing assistance and information to prospective and current parents are encouraged to continue to increase their awareness of and efforts at including all families.
Nested Learning For Multi-Granular Tasks

Standard deep neural networks (DNNs) are commonly trained in an end-to-end fashion for specific tasks such as object recognition, face identification, or character recognition, among many examples. This specificity often leads to overconfident models that generalize poorly to samples that are not from the original training distribution. Moreover, such standard DNNs do not allow to leverage information from heterogeneously annotated training data, where for example, labels may be provided with different levels of granularity. Furthermore, DNNs do not produce results with simultaneous different levels of confidence for different levels of detail, they are most commonly an all or nothing approach. To address these challenges, we introduce the concept of nested learning: how to obtain a hierarchical representation of the input such that a coarse label can be extracted first, and sequentially refine this representation, if the sample permits, to obtain successively refined predictions, all of them with the corresponding confidence. We explicitly enforce this behavior by creating a sequence of nested information bottlenecks. Looking at the problem of nested learning from an information theory perspective, we design a network topology with two important properties. First, a sequence of low dimensional (nested) feature embeddings are enforced. Then we show how the explicit combination of nested outputs can improve both the robustness and the accuracy of finer predictions. Experimental results on Cifar-10, Cifar-100, MNIST, Fashion-MNIST, Dbpedia, and Plantvillage demonstrate that nested learning outperforms the same network trained in the standard end-to-end fashion.
Enabling Online Initiatives: The Role of Teaching and Learning Center Leaders at Small, Private Colleges.

As online learning continues to grow and became an integral component of many higher education institutions, the role of leadership in guiding those online learning initiatives differs from institution to institution. This paper explores the experiences of leaders in centers for teaching and learning who have a role in online learning leadership at small, private colleges. With online learning being just one of my many roles for leaders, a phenomenological study was used to fully understand the perceptions of leaders in leading online initiatives. Findings from the voices of those leaders can inform approaches for other leaders in online learning.
Response to referees' comments

This article lays out the fundamentals of data assimilation as used in biogeochemistry. It demonstrates that all of the methods in widespread use within the field are special cases of the underlying Bayesian formalism. Methods differ in the assumptions they make and information they provide on the probability distributions used in Bayesian calculations. It thus provides a basis for comparison and choice among these methods. It also provides a standardised notation for the various quantities used in the field. 5
Activity-based profiling of cullin-RING ligase networks by conformation-specific probes

The cullin-RING E3 ligase (CRL) network comprises over 300 unique complexes that switch from inactive to activated conformations upon site-specific cullin modification by the ubiquitin-like protein NEDD8. Assessing cellular repertoires of activated CRL complexes is critical for understanding eukaryotic regulation. However, probes surveying networks controlled by site-specific ubiquitin-like protein modifications are lacking. We report development of a synthetic antibody recognizing the active conformation of a NEDD8-linked cullin. We established a pipeline probing cellular networks of activated CUL1-, CUL2-, CUL3- and CUL4-containing CRLs, revealing the CRL complexes responding to stimuli. Profiling several cell types showed their baseline neddylated CRL repertoires vary, prime efficiency of targeted protein degradation, and are differentially rewired across distinct primary cell activation pathways. Thus, conformation-specific probes can permit nonenzymatic activity-based profiling across a system of numerous multiprotein complexes, which in the case of neddylated CRLs reveals widespread regulation and could facilitate development of degrader drugs.
Deep learning for population size history inference: design, comparison and combination with approximate Bayesian computation

For the past decades, simulation-based likelihood-free inference methods have enabled researchers to address numerous population genetics problems. As the richness and amount of simulated and real genetic data keep increasing, the field has a strong opportunity to tackle tasks that current methods hardly solve. However, high data dimensionality forces most methods to summarize large genomic datasets into a relatively small number of handcrafted features (summary statistics). Here we propose an alternative to summary statistics, based on the automatic extraction of relevant information using deep learning techniques. Specifically, we design artificial neural networks (ANNs) that take as input single nucleotide polymorphic sites (SNPs) found in individuals sampled from a single population and infer the past effective population size history. First, we provide guidelines to construct artificial neural networks that comply with the intrinsic properties of SNP data such as invariance to permutation of haplotypes, long scale interactions between SNPs and variable genomic length. Thanks to a Bayesian hyperparameter optimization procedure, we evaluate the performance of multiple networks and compare them to well established methods like Approximate Bayesian Computation (ABC). Even without the expert knowledge of summary statistics, our approach compares fairly well to an ABC based on handcrafted features. Furthermore we show that combining deep learning and ABC can improve performance while taking advantage of both frameworks. Finally, we apply our approach to reconstruct the effective population size history of cattle breed populations.
Separation or Integration of Sequential Arrays in VWM Depends On the interval Between Them

The visual information could be stored in either the active state or the passive state for a short time in visual working memory (VWM). Catering to the dynamic nature of visual world, we explored how the temporally dynamic input was stored in VWM by employing sequentially presented arrays rather than static arrays in which all items are presented simultaneously, and the contralateral delay activity (CDA), an electrophysiological measure was used to identify whether the memory items had been transferred into the passive state. In the current study, participants were instructed to encode two sequential arrays and retrieve them respectively, with two conditions of interval across the two arrays: 400ms and 800ms. These results provided strong evidence that two sequential arrays could be stored in VWM by forming two state-separated images if the interval between them was long enough, or by becoming an integration if the interval was relatively short. This conclusion was valid only when the participants encountered the task for the first time. Once participants have formed their mindset, they would apply the same memory mode to the subsequently extended or shortened interval condition. Therefore, the finding indicated that the extended interval could allow the storage transformation for the leading array, separated from the trailing array stored in the active state. Thus we proposed that the interval between two memory arrays influenced whether participants stored the two sequential arrays as parts of a single extended event or two independent episodes.
A 5-GS/s 7.2-ENOB Time-Interleaved VCO-Based ADC Achieving 30.5 fJ/cs

This article presents an eight-channel time-interleaved voltage-controlled oscillator (VCO)-based analog-to-digital converter (ADC), achieving 7.2 effective number of bits (ENOBs) at 5 GS/s in 28-nm CMOS. A high-speed ring oscillator with feedforward cross-coupling and a shared tail transistor is combined with an asynchronous counter in order to improve the resolution while minimizing the power consumption. Asynchronous double sampling is used to enable reliable sampling of the asynchronous counter state. On-chip digital calibration is used to compensate for channel mismatch and nonlinear distortion, and sampling time mismatch is corrected using tunable clock delays. With a total power consumption of just 22.7 mW, it achieves a Walden figure-of-merit (FOM) of 30.5 fJ/cs.
Neutron Activation Analysis as a tool to Determine Concentration of Selected Metals in Table Salt Mined from Benya Lagoon, Ghana

This project was funded by The Directorate of Research, Innovation and Consultancy (DRIC) and the Management of the University of Cape Coast. It was sponsored as a Group-led Research involving researchers from the Department of Physics during the third call for proposals for Research Support Grants (RSGs) in 2018 Abstract Table salt is essential for life and if it contains metal impurities, it can affect the people that consume it. The Komenda Edina Eguafo Abrem municipality makes salt by evaporating brine from the Benya Lagoon. Benya lagoon is a lagoon known to be polluted due to various anthropogenic activities within its environs. The concentration of eight metals, Arsenic (As), Cadmium (Cd), Manganese (Mn) Lead (Pb), Aluminium (Al), Copper (Cu), Magnesium (Mg), and Vanadium (V) have been determined in salt mined using water from the Benya lagoon. Salt samples were selected from five fixed-sampling stations and the concentrations of the metals determined using Neutron Activation Analysis. The ranges of the measured concentrations in the salts are as follows: 161.04-632.63 mg/kg for Al, 0.001-0.004 mg/kg for As, 1.50-2.70 mg/kg for Mg, 49.14-3883.00 mg/kg for Mg, 17.24-110.96 mg/kg for Mn, and 2.85-7.10 mg/kg for V. An assessment according to the metal concentration marked Mg as the most abundant, whiles Cd and Pb the least being 0.001 mg/kg at all the five stations. Principal Component Analysis also established Mg to be the most abundant metal, and used to identify two major clusters; Group 1 (stations 4 and 5) and Group 2 (stations 1, 2 and 3). Group 2 recorded higher intensities of Mg. Using Pearson's correlation coefficient, significant correlations were drawn between Al and Mg (r = - 0.862), Mg and Mn (r = 0.863) and Mn and V (r = 0.735), indicating the same or similar source inputs for each pair. Comparison with Codex Standard for Food Grade Salt showed that concentration values recorded for Al, Mg and Mn were above recommended limits. The contamination factor (C F ) and degree of contamination (C D ) confirmed this level of contamination for Al, Mg and Mn for all the five Stations, with Station 2 recording the highest Degree of Contamination. the least and corroborated salt from station 2 as most contaminated considering the combined toxicity at each station. Using an average daily salt intake of 6,000 mg, the mean daily intake of the elements when one consumes salt mined from the Benya lagoon was found to be above each element’s Upper Tolerable Limit of its Recommended Dietary Allowable for the various Life Stage Groups. The associated Hazard Index suggests the probability of adverse effects when consumed. High standard deviation values for Al and Mn indicated the non-uniform spatial distribution of the individual metal contaminates at the various stations. Keywords: Benya Lagoon; salt; heavy metal; contamination factor; degree of contamination, neutron activation analysis; recommended daily allowance, GHARR-1 DOI : 10.7176/CMR/11-8-06 Publication date :October 31 st 2019
Numerical Methods in Calculating Eigenvalues: Case Studies in Stability of Euler Columns

A comparative analysis of well renowned “Shooting Method” with another numerical method “Complementary Functions Method” (CFM) is presented for calculating eigenvalue (λ). Contrary to the shooting method hit and trial approach, CFM exploits the properties of linear ordinary differential equation (LODE). In the case of linear eigenvalue Boundary value Problem (BVP), CFM generates an algebraic equation system with one unknown “λ” and, alone root finding method is sufficient to give required eigenvalue. However, the Shooting Method create a system of algebraic equations containing two unknowns “λ” and “missing initial conditions”, that demands an additional numerical technique along with root finding method. These radical differences between two approaches, sets the basis for this comparative investigation. As a case study in Linear Elastic Stability, different cases of Euler columns are investigated by finding eigenvalues for each case numerically, under both methods. Comparison is performed on the basis of results accuracy and cost effectiveness for both numerical techniques while solving linear stability problems.
Sosyal Bilgiler Öğretmen Adaylarının Öğretmenlik Mesleğine Yönelik Tutumlarının İncelenmesi

Sosyal Bilgiler ogretmen adaylarinin ogretmenlik meslegine yonelik tutumlarini incelemek amaciyla yapilan bu arastirma nicel arastirma desenlerinden tarama (survey) deseni kapsaminda yurutulmustur. Bu amacla arastirma, bir devlet universitesi egitim fakultesi 3. sinifta egitim goren 66 kadin, 80 erkek toplam 146 Sosyal Bilgiler ogretmen adayinin katilimiyla gerceklestirilmistir. Arastirmada katilimcilardan “Kisisel Bilgi Formnu” ve “Ogretmenlik Meslegi Tutum Olcegi” ile veriler elde edilmistir. Arastirma verileri SPSS 22.0 programi kullanilmis ve gerekli istatistiksel teknikler kullanilarak analiz edilmistir. Arastirmanin sonucunda Sosyal Bilgiler ogretmen adaylarinin ogretmenlik meslegine yonelik tutum puanlarinin “Katiliyorum” duzeyinde oldugu, Sosyal Bilgiler ogretmen adaylarinin ogretmenlik meslegine yonelik tutumlarinin cinsiyet ve ogrenim gordukleri sube degiskenine gore anlamli farklilik olmadigi ancak mezun olduklari lise degiskenine gore anlamli farkliligin goruldugu tespit edilmistir. Sosyal Bilgiler ogretmen adaylarinin ogretmenlik meslegine yonelik tutumlarini incelemek amaciyla yapilan bu arastirma nicel arastirma desenlerinden tarama (survey) deseni kapsaminda yurutulmustur. Bu amacla arastirma, bir devlet universitesi egitim fakultesi 3. sinifta egitim goren 66 kadin, 80 erkek toplam 146 Sosyal Bilgiler ogretmen adayinin katilimiyla gerceklestirilmistir. Arastirmada katilimcilardan “Kisisel Bilgi Formnu” ve “Ogretmenlik Meslegi Tutum Olcegi” ile veriler elde edilmistir. Arastirma verileri SPSS 22.0 programi kullanilmis ve gerekli istatistiksel teknikler kullanilarak analiz edilmistir. Arastirmanin sonucunda Sosyal Bilgiler ogretmen adaylarinin ogretmenlik meslegine yonelik tutum puanlarinin “Katiliyorum” duzeyinde oldugu, Sosyal Bilgiler ogretmen adaylarinin ogretmenlik meslegine yonelik tutumlarinin cinsiyet ve ogrenim gordukleri sube degiskenine gore anlamli farklilik olmadigi ancak mezun olduklari lise degiskenine gore anlamli farkliligin goruldugu tespit edilmistir.
Efecto del extracto acuoso foliar de moringa en la fase inicial de aclimatización de piña

Moringa oleifera Lam . leaves have several chemical constituents such as: amino acids, mineral ions, ascorbate, phytohormones and secondary metabolites. Consequently, these extracts can be used to improve growth in other plants. In addition, it is awarded antimicrobial activity against pathogens of agricultural interest. The objective of this work was to evaluate the effect of the aqueous extract obtained from moringa leaves on the morphological changes of the Ananas comosus var. comosus ‘MD-2’ plant in the initial stage of acclimatization. It was evaluated the effect of the concentration (dilutions of 1:4 and 1:8) and the immersion time (0, 24, 48 and 72 hours) in the aqueous extract of moringa previous to the acclimatization of pineapple seedlings. The aqueous extract of moringa and Previcur ® Energy LS 84 was compared in the acclimatization of pineapple seedlings. It was achieved 100 % survival with the immersion of the pineapple seedlings for 24 and 48 hours in aqueous extract diluted 1:4 and for 72 hours in aqueous extract diluted 1:8. Morphological indicators were higher with the immersion of pineapple seedlings for 72 hours in aqueous extract diluted 1:8, after 42 days in acclimatization. Significant differences weren’t observed in morphological indicators for treated plants only with Previcur ® Energy LS 84 and aqueous extract diluted 1:8. In these treatments weren’t observed visible symptoms of diseases.