Miracle-dz/UniFAR-FTUs huggingface dataset:
A New Constructive Algorithm for Architectural and Functional Adaptation of Artificial Neural Networks

The generalization ability of artificial neural networks (ANNs) is greatly dependent on their architectures. Constructive algorithms provide an attractive automatic way of determining a near-optimal ANN architecture for a given problem. Several such algorithms have been proposed in the literature and shown their effectiveness. This paper presents a new constructive algorithm (NCA) in automatically determining ANN architectures. Unlike most previous studies on determining ANN architectures, NCA puts emphasis on architectural adaptation and functional adaptation in its architecture determination process. It uses a constructive approach to determine the number of hidden layers in an ANN and of neurons in each hidden layer. To achieve functional adaptation, NCA trains hidden neurons in the ANN by using different training sets that were created by employing a similar concept used in the boosting algorithm. The purpose of using different training sets is to encourage hidden neurons to learn different parts or aspects of the training data so that the ANN can learn the whole training data in a better way. In this paper, the convergence and computational issues of NCA are analytically studied. The computational complexity of NCA is found to be O(W times Pt times tau), where W is the number of weights in the ANN, Pt is the number of training examples, and tau is the number of training epochs. This complexity has the same order as what the backpropagation learning algorithm requires for training a fixed ANN architecture. A set of eight classification and two approximation benchmark problems was used to evaluate the performance of NCA. The experimental results show that NCA can produce ANN architectures with fewer hidden neurons and better generalization ability compared to existing constructive and nonconstructive algorithms.
Na 1 Dependence and the Role of Glutamate Receptors and Na 1 Channels in Ion Fluxes During Hypoxia of Rat Hippocampal Slices

Na 1 dependence and the role of glutamate receptors and Na 1 channels in ion ﬂuxes during hypoxia of rat hippocampal slices. J Neurophysiol 84: 1869–1880, 2000. Spreading depression (SD) as well as hypoxia-induced SD-like depolarization in forebrain gray matter are characterized by near complete depolarization of neurons. The biophysical mechanism of the depolarization is not known. Earlier we reported that simultaneous pharmacological blockade of all known major Na 1 and Ca 2 1 channels prevents hypoxic SD. We now recorded extracellular voltage, Na 1 , and K 1 concentrations and the intracellular potential of individual CA1 pyramidal neurons during hyp- oxia of rat hippocampal tissue slices after substituting Na 1 in the bath by an impermeant cation, or in the presence of channel blocking drugs applied individually and in combination. Reducing extracellular Na 1 concentration [Na 1 ] o to 90 mM postponed the hypoxia-induced extracellular DC-potential deﬂection ( D V o ) and reduced its amplitude, and it also postponed the SD-like depolarization of neurons. After lowering [Na 1 ] o to 25 mM, SD-like D V o became very small, indicating that an inﬂux of Na 1 is required for SD; inﬂux of Ca 2 1 ions alone is not sufﬁcient. We then asked whether the SD-related Na 1 current ﬂows through glutamate-controlled and/or through voltage-gated Na 1 channels. Administration of either the non- N -methyl- D -aspartate (NMDA) receptor antagonist 6,7-dinitroquinoxaline-2,3-dione (DNQX), or the NMDA receptor antagonist ( 6 )-3-(2-carboxypiperazin-4-yl)-propyl-1-phosphonic acid (CPP) postponed the hypoxic D V o and depressed its amplitude but the effect of the combined administration of these two drugs was not greater than that of either alone. During the early phase of hypoxia, before SD onset, [K 1 ] o increased faster and reached a much higher level in the presence of glutamate antagonists than in their ab- sence. The [K 1 ] o level reached at the height of hypoxic SD was, how- ever, not affected. When TTX was added to DNQX and CPP, SD was prevented in half the trials. When SD did occur, it was greatly delayed, yet eventually neurons depolarized to the same extent as in normal solution. The SD-related sudden drop in [Na 1 ] o was depressed by only 19% in the presence of the three drugs, indicating that Na 1 can ﬂow into cells through pathways other than ionotropic glutamate receptors and TTX-sensitive Na 1 channels. We conclude that, when they are functional, glutamate-receptor-mediated and voltage-gated Na 1 currents are the major generators of the self-regenerative rapid depolarization, but in their absence other pathways can sometimes take their place. The ﬁnal level of SD-like depolarization is determined by positive feedback and not by the number of channels available. A schematic ﬂow chart of the events generating hypoxic SD is discussed.
Can one use total variation prior for edge-preserving Bayesian inversion?

Estimation of non-discrete physical quantities from indirect linear measurements is considered. Bayesian solution of such an inverse problem involves discretizing the problem and expressing available a priori information in the form of a prior distribution in a finite-dimensional space. Since a priori information is independent of the measurement, the discretization of the unknown quantity can be arbitrarily fine regardless of the number of measurements. The main result is that Bayesian conditional mean estimates for total variation prior distribution are not edge-preserving with very fine discretizations of the model space. Theoretical findings are illustrated by a numerical example with computer simulated data.
Neural Transformation Machine: A New Architecture for Sequence-to-Sequence Learning

We propose Neural Transformation Machine (NTram), a novel architecture for sequence-to-sequence learning, which performs the task through a series of nonlinear transformations from the representation of the input sequence (e.g., a Chinese sentence) to the final output sequence (e.g., translation to English). Inspired by the recent Neural Turing Machines [8], we store the intermediate representations in stacked layers of memories, and use read-write operations on the memories to realize the nonlinear transformations of those representations. Those transformations are designed in advance but the parameters are learned from data. Through layer-by-layer transformations, NTram can model complicated relations necessary for applications such as machine translation between distant languages. The architecture can be trained with normal back-propagation on parallel texts, and the learning can be easily scaled up to a large corpus. NTram is broad enough to subsume the state-of-the-art neural translation model in [2] as its special case, while significantly improves upon the model with its deeper architecture. Remarkably, NTram, being purely neural network-based, can achieve performance comparable to the traditional phrase-based machine translation system (Moses) with a small vocabulary and a modest parameter size.
Challenging discourses of aspiration: The role of expectations and attainment in access to higher education

© 2018 British Educational Research Association Raising the proportion of young people from disadvantaged backgrounds progressing to higher education has been a key policy objective for successive governments in the UK since the late 1990s. Often this has been conceptualised as a problem with their ‘aspirations’, with the solution being seen as the provision of ‘aspiration-raising’ activities to promote higher education to those thought to have the potential to progress. Recent large-scale studies cast strong doubt on this hypothesis by demonstrating that aspirations are not generally low, that different social groups have similar levels of aspiration and that school attainment accounts for nearly all the differences in participation rates between social groups. This article draws on data from a national project exploring efforts to widen participation across two generations of practitioner-managers in England, focusing on their conceptualisations of the field and their constructions of ‘successful’ activities. It uses the lens of ‘possible selves’ (Markus & Nurius,) to argue that too much policy emphasis has been placed on the aspirations of young people, rather than either their academic attainment or their expectations, which are shaped by the normative expectations of the adults surrounding them. In addition, the more expansive concepts of widening participation that were present a decade ago have become less common, with a shift towards activities with a clear role in institutional recruitment rather than social transformation. The article concludes with alternative suggestions for policy and practice.
An implementation of radiative transfer in the cosmological simulation code gadget

We present a novel numerical implementation of radiative transfer in the cosmological smoothed particle hydrodynamics (SPH) simulation code gadget. It is based on a fast, robust and photon-conserving integration scheme where the radiation transport problem is approximated in terms of moments of the transfer equation and by using a variable Eddington tensor as a closure relation, following the Optically Thin Variable Eddington Tensor suggestion of Gnedin & Abel. We derive a suitable anisotropic diffusion operator for use in the SPH discretization of the local photon transport, and we combine this with an implicit solver that guarantees robustness and photon conservation. This entails a matrix inversion problem of a huge, sparsely populated matrix that is distributed in memory in our parallel code. We solve this task iteratively with a conjugate gradient scheme. Finally, to model photon sink processes we consider ionization and recombination processes of hydrogen, which is represented with a chemical network that is evolved with an implicit time integration scheme. We present several tests of our implementation, including single and multiple sources in static uniform density fields with and without temperature evolution, shadowing by a dense clump and multiple sources in a static cosmological density field. All tests agree quite well with analytical computations or with predictions from other radiative transfer codes, except for shadowing. However, unlike most other radiative transfer codes presently in use for studying re-ionization, our new method can be used on-the-fly during dynamical cosmological simulation, allowing simultaneous treatments of galaxy formation and the re-ionization process of the Universe.
Active Learning to Improve Self-Confidence and Decision-Making Skills Through the Use of Hotel Simulation

ABSTRACT This study evaluated the use of hotel simulation learning and how it promotes users’ confidence as a decision-making tool. Given the challenges of preparing students for the service industry, it enables them to make hypothetical decisions based on real-life scenarios. The perceived learning experience can enhance students’ critical thinking ability to manipulate different operational strategies. Data were collected from 202 students who attended hospitality management programs in Switzerland, the United States, and the United Kingdom. A series of regression analyses were conducted to test how confident the students were in their ability to make decisions. This article compares perceived self-confidence and the development of decision-making skills between undergraduate and postgraduate students. The students improved their confidence and thus their decision-making skills relating to day-to-day operations. In addition, confidence was more effectively valued as a relevant norm among undergraduate than postgraduate students in developing critical and analytical decision skills.
The Effects of Aerobic Training and Blood Flow Restriction Training on the Stride Length and Balance of Women with Multiple Sclerosis

Introduction: Multiple sclerosis (MS) is an autoimmune disease that causes damage to the myelin of the central nervous system. The purpose of this study was to investigate the effects of aerobic training and blood flow restriction training on the stride length and balance of women with multiple sclerosis (MS). Methods: 24 volunteer patients with disability scale of 14 (age: 37.08 ± 8.23 years; weight: 61.54 ± 8.58 kg and height: 159.5 ± 7.27 cm) were randomly divided into two groups including aerobic training group (n=12) and blood flow restriction (BFR) training group (n=12). Both groups pedaled on aqua cycle (3 sets of 6 minutes with 1 min of rest between sets and 6065% HRmax) for 6 weeks and 3 sessions in a week. To restrict the blood flow, the cuff on the upper part of the foot with a pressure of 96 ± 10 mmHg was implemented. The stride length and balance were measured by employing cameras and berg balance scale, respectively. To analyze the data, analysis of covariance (ANCOVA) and Bonferroni’s post-hoc test were used at a significant level of P <0.05. Results: The results showed that both types of training significantly increased the left step length (p< 0.05) and balance (p <0.05) in patients with multiple sclerosis, but significantly decreased the right step length (P< 0.05). Conclusion: It seems that both aerobic training and BFR training caused improvement in the balance of patients with multiple sclerosis, however, more deliberation is needed in relation to their effects on the stride length.
Molecular recognition features (MoRFs) in three domains of life.

Intrinsically disordered proteins and protein regions offer numerous advantages in the context of protein-protein interactions when compared to the structured proteins and domains. These advantages include ability to interact with multiple partners, to fold into different conformations when bound to different partners, and to undergo disorder-to-order transitions concomitant with their functional activity. Molecular recognition features (MoRFs) are widespread elements located in disordered regions that undergo disorder-to-order transition upon binding to their protein partners. We characterize abundance, composition, and functions of MoRFs and their association with the disordered regions across 868 species spread across Eukaryota, Bacteria and Archaea. We found that although disorder is substantially elevated in Eukaryota, MoRFs have similar abundance and amino acid composition across the three domains of life. The abundance of MoRFs is highly correlated with the amount of intrinsic disorder in Bacteria and Archaea but only modestly correlated in Eukaryota. Proteins with MoRFs have significantly more disorder and MoRFs are present in many disordered regions, with Eukaryota having more MoRF-free disordered regions. MoRF-containing proteins are enriched in the ribosome, nucleus, nucleolus and microtubule and are involved in translation, protein transport, protein folding, and interactions with DNAs. Our insights into the nature and function of MoRFs enhance our understanding of the mechanisms underlying the disorder-to-order transition and protein-protein recognition and interactions. The fMoRFpred method that we used to annotate MoRFs is available at http://biomine.ece. ualberta.ca/fMoRFpred/.
Governance and Bank Valuation

Which public policies and ownership structures enhance the governance of banks? This paper constructs a new database on the ownership of banks internationally and then assesses the ramifications of ownership, shareholder protection laws, and supervisory/regulatory policies on bank valuations. Except in a few countries with very strong shareholder protection laws, banks are not widely held, but rather families or the State tend to control banks. We find that (i) larger cash flow rights by the controlling owner boosts valuations, (ii) stronger shareholder protection laws increase valuations, and (iii) greater cash flow rights mitigate the adverse effects of weak shareholder protection laws on bank valuations. These results are consistent with the views that expropriation of minority shareholders is important internationally, that laws can restrain this expropriation, and concentrated cash flow rights represent an important mechanism for governing banks. Finally, the evidence does not support the view that empowering official supervisory and regulatory agencies will increase the market valuation of banks.
AI-Based Software Defect Predictors: Applications and Benefits in a Case Study

Software defect prediction aims to reduce software testing efforts by guiding testers through the defect-prone sections of software systems. Defect predictors are widely used in organizations to predict defects in order to save time and effort as an alternative to other techniques such as manual code reviews. The application of a defect prediction model in a real-life setting is difficult because it requires software metrics and defect data from past projects to predict the defect-proneness of new projects. It is, on the other hand, very practical because it is easy to apply, can detect defects using less time and reduces the testing effort. We have built a learning-based defect prediction model for a telecommunication company during a period of one year. In this study, we have briefly explained our model, presented its pay-off and described how we have implemented the model in the company. Furthermore, we have compared the performance of our model with that of another testing strategy applied in a pilot project that implemented a new process called Team Software Process (TSP). Our results show that defect predictors can be used as supportive tools during a new process implementation, predict 75% of code defects, and decrease the testing time compared with 25% of the code defects detected through more labor-intensive strategies such as code reviews and formal checklists.
Genome-wide association identifies the T gene as a novel asthma pharmacogenetic locus.

RATIONALE To date, most studies aimed at discovering genetic factors influencing treatment response in asthma have focused on biologic candidate genes. Genome-wide association studies (GWAS) can rapidly identify novel pharmacogenetic loci. OBJECTIVES To investigate if GWAS can identify novel pharmacogenetic loci in asthma. METHODS Using phenotypic and GWAS genotype data available through the NHLBI-funded Single-nucleotide polymorphism Health association-Asthma Resource Project, we analyzed differences in FEV(1) in response to inhaled corticosteroids in 418 white subjects with asthma. Of the 444,088 single nucleotide polymorphisms (SNPs) analyzed, the lowest 50 SNPs by P value were genotyped in an independent clinical trial population of 407 subjects with asthma. MEASUREMENTS AND MAIN RESULTS The lowest P value for the GWAS analysis was 2.09 × 10(-6). Of the 47 SNPs successfully genotyped in the replication population, three were associated under the same genetic model in the same direction, including two of the top four SNPs ranked by P value. Combined P values for these SNPs were 1.06 × 10(-5) for rs3127412 and 6.13 × 10(-6) for rs6456042. Although these two were not located within a gene, they were tightly correlated with three variants mapping to potentially functional regions within the T gene. After genotyping, each T gene variant was also associated with lung function response to inhaled corticosteroids in each of the trials associated with rs3127412 and rs6456042 in the initial GWAS analysis. On average, there was a twofold to threefold difference in FEV(1) response for those subjects homozygous for the wild-type versus mutant alleles for each T gene SNP. CONCLUSIONS Genome-wide association has identified the T gene as a novel pharmacogenetic locus for inhaled corticosteroid response in asthma.
Performance of MMSE MIMO Receivers: A Large N Analysis for Correlated Channels

Linear receivers are considered as an attractive low- complexity alternative to optimal processing for multi-antenna MIMO communications. In this paper we characterize the per- formance of MMSE MIMO receivers in the limit of large antenna numbers in the presence of channel correlations. Using the replica method, we generalize our results obtained in (1) to Kronecker- product correlated channels and calculate the asymptotic mean and variance of the mutual information of a MIMO system of parallel MMSE subchannels. The replica method allows us to use the ties between the optimal receiver mutual information and the MMSE SIR of Gaussian inputs to calculate the joint moments of the SIRs of the MMSE subchannels. Using the methodology discussed in (1) it can be shown that the mutual information converges in distribution to a Gaussian random variable. Our results agree very well with simulations even with a moderate number of antennas.
Negative Regulation of Dopamine Transporter Endocytosis by Membrane-Proximal N-Terminal Residues

The plasma membrane dopamine transporter (DAT) takes extracellular dopamine back up into dopaminergic neurons. Although the number of DATs at the cell surface is regulated by endocytosis and recycling, the molecular mechanisms that control this endocytic trafficking of DAT are not defined. To map the sequence motifs that are involved in constitutive DAT endocytosis, mutagenesis of human DAT tagged with yellow fluorescent protein (YFP) and an extracellular HA epitope was performed. Removal of the entire N terminus of DAT resulted in accumulation of the resulting DAT mutant (YFP-HA-ΔN-DAT) in early and recycling endosomes in HeLa and PAE cells, and in primary rat mesencephalic-striatal neuronal cocultures. This endosomal accumulation was due to rapid constitutive internalization of YFP-HA-ΔN-DAT by the clathrin-dependent pathway. Small deletions and multialanine substitutions in the N terminus revealed two molecular determinants within the membrane proximal residues 60–65 that are important for preventing rapid internalization of DAT. First, mutations of Arg60 or Trp63, leading to disruption of the “outward facing” DAT conformation, correlated with an increased pool of mobile DATs in the plasma membrane and accelerated constitutive internalization of the DAT mutants. Second, mutation of Lys65 also correlated with elevated endocytosis. While none of these mutations alone recapitulated the marked endocytic phenotype of YFP-HA-ΔN-DAT, simultaneous elimination of both the outward conformation of DAT and Lys65 resulted in DAT mutants that were rapidly internalized. Thus, our studies reveal a new link between DAT endocytosis and conformation-dependent uptake activity that represents a novel mode for regulating DAT function.
Phonology-based bilingual activation among different-script bilinguals?

Multilink developed by Dijkstra et al. (2018) is a computational model of monolingual and bilingual lexical access in comprehension and production. The non-selective activation of a bilingual's two languages is handled in the model by assuming that bilinguals have an integrated lexicon and that orthographic overlap between the input and the lexical representation drives lexical activation. Hence, an orthographic unit such as the letter T may activate words from multiple languages that contain the letter, resulting in simultaneous activation of multiple languages. This basic mechanism for explaining non-selective activation is similar between Multilink and its predecessors BIA and BIA+.