Miracle-dz/UniFAR-FTUs huggingface dataset:
Semantically-enhanced pre-filtering for context-aware recommender systems

Several research works have demonstrated that if users' ratings are truly context-dependent, then Context-Aware Recommender Systems can outperform traditional recommenders. In this paper we present a novel contextual pre-filtering approach that exploits the implicit semantic similarity of contextual situations. For determining such a similarity we rely only on the available users' ratings and we deem as similar two syntactically different contextual situations that are actually influencing in a similar way the user's rating behavior. We validate the proposed approach using two contextually tagged ratings data sets showing that it outperforms a traditional pre-filtering approach and a state-of-the-art context-aware Matrix Factorization model.
Dialogue act classiﬁcation using a Bayesian approach ∗

In this work, we make a contribution to natural speech dialogue act detection. We focus our attention on the dialogue act classiﬁcation using a Bayesian approach. Our classiﬁer is tested on two corpora, the Switchboard and the Basurde tasks. A combination of a naive Bayes classi-ﬁer and n -grams is used. The impact of different smoothing methods (Laplace and Witten Bell) and n -grams in classiﬁcation are studied. With respect to the Switchboard corpus, an accuracy of 66% is achieved using a uniform naive Bayes classiﬁer, 3 -grams and Laplace smoothing to avoid zero probabilities. For the Basurde corpus, our system achieves performances similar to other methodologies we have previously tested. Through a combination of a naive Bayes classiﬁer with 2 -grams and Witten Bell smoothing we achieve the best accuracy of 89%. These results show that a Bayesian approach is well suited for these tasks.
Implementation of transparent sources in FDTD simulations

Sources can be embedded in a finite-difference time-domain (FDTD) grid in any one of several ways. Depending on the particular implementation, the embedded source corresponds physically to a hard field source (applied field), a transparent current source (impressed current), a finite-impedance voltage source, or some other physical excitation. While the implementation of any of these sources is a straightforward procedure in FDTD simulations, ensuring an accurate correspondence between the physical source and its numerical implementation is challenging. We describe the implementation of a new field source, referred to as a transparent field source, that couples the same fields into the FDTD grid as a hard field source. Unlike the hard field source, however, the transparent source does not scatter energy, i.e., the usual FDTD update equation applies to the source node. The implementation is described both in terms of a single node and in terms of an array of nodes. The latter is discussed in the context of parallel-plate waveguide excitation.
Lucentis® using Visudyne® study: determining the threshold-dose fluence of verteporfin photodynamic therapy combined with intravitreal ranibizumab for exudative macular degeneration

Purpose Combination verteporfin photodynamic therapy (vPDT) and antivascular endothelial growth factor (anti-VEGF) therapy may decrease the need for injections while maintaining visual acuity in exudative age-related macular degeneration. This pilot study was designed to determine the threshold fluence dose of vPDT (the dose required to demonstrate an effect on choroidal perfusion) combined with ranibizumab. Methods Seven patients were randomized to sham vPDT (two patients), 20% fluence vPDT (two patients), or 40% fluence vPDT (three patients) in combination with three-monthly intravitreal 0.5 mg ranibizumab injections. Intravitreal ranibizumab was reinjected if disease activity was seen on fluorescein angiography, optical coherence tomography, or clinical examination. Indocyanine green-determined choroidal hypoperfusion was graded in a masked fashion. Results Patients with 20% vPDT had mild hypoperfusion defects at seven days that resolved by week 4 (threshold dose); patients with 40% fluence vPDT had marked hypoperfusion at seven days that persisted as long as 12 months. Recruitment was stopped after limited efficacy was observed. One patient with 20% fluence vPDT lost 19 letters at one year; no other patient lost or gained >10 letters. Central retinal thickness decreased in six of seven patients, but ranibizumab injections did not decrease. Conclusion This pilot study shows that the threshold fluence dose of vPDT (when combined with ranibizumab) is approximately 20% standard fluence, and that mild and transient choroidal hypoperfusion can occur. Forty percent fluence vPDT causes a more prolonged and striking hypoperfusion. Despite hypoperfusion, no decrease in visual acuity or injections required was noted, suggesting that even higher fluence levels of vPDT may be necessary to decrease the number of anti-VEGF injections.
Structure–activity relationships of the N-terminus of calcitonin gene-related peptide: key roles of alanine-5 and threonine-6 in receptor activation

The N‐terminus of calcitonin gene‐related peptide (CGRP) is important for receptor activation, especially the disulphide‐bonded ring (residues 1–7). However, the roles of individual amino acids within this region have not been examined and so the molecular determinants of agonism are unknown. This study has examined the role of residues 1, 3–6 and 8–9, excluding Cys‐2 and Cys‐7.
Automatic prominence annotation of a German speech synthesis corpus: towards prominence-based prosody generation for unit selection synthesis

This paper describes work directed towards the development of a syllable prominence-based prosody generation functionality for a German unit selection speech synthesis system. A general concept for syllable prominence-based prosody generation in unit selection synthesis is proposed. As a first step towards its implementation, an automated syllable prominence annotation procedure based on acoustic analyses has been performed on the BOSS speech corpus. The prominence labeling has been evaluated against an existing annotation of lexical stress levels and manual prominence labeling on a subset of the corpus. We discuss methods and results and give an outlook on further implementation steps.
Pervasive information through constant personal projection: the ambient mobile pervasive display (AMP-D)

The vision of pervasive ambient information displays which show relevant information has not yet come true. One of the main reasons is the limited number of available displays in the environment which is a fundamental requirement of the original vision. We introduce the concept of an Ambient Mobile Pervasive Display AMP-D which is a wearable projector system that constantly projects an ambient information display in front of the user. The floor display provides serendipitous access to public and personal information. The display is combined with a projected display on the user's hand, forming a continuous interaction space that is controlled by hand gestures. The paper introduces this novel device concept, discusses its interaction design, and explores its advantages through various implemented application examples. Furthermore, we present the AMP-D prototype which illustrates the involved challenges concerning hardware, sensing, and visualization.
1-bit Compressive Data Gathering for Wireless Sensor Networks

Compressive sensing (CS) has been widely used in wireless sensor networks for the purpose of reducing the data gathering communication overhead in recent years. In this paper, we firstly apply 1-bit compressive sensing to wireless sensor networks to further reduce the communication overhead that each sensor needs to send. Furthermore, we propose a novel blind 1-bit CS reconstruction algorithm which outperforms other state-of-the-art blind 1-bit CS reconstruction algorithms under the settings of WSN. Experimental results on real sensor datasets demonstrate the efficiency of our method.
The Effects of Interdependence and Cooperative Behaviors on Buyer’s Satisfaction in the Semiconductor Component Supply Chain

The semiconductor industry is characterized by extreme competition in price and product features. Firms need to acquire or exchange resources with their supplier or buyer partners to stay at the leading edge of technology. Cooperation between buyers and suppliers is important and power is the mechanism that can explain the cooperative behaviors. This study aims to investigate how the power structure between the buyer and supplier influences the extent of suppliers’ cooperative behaviors, and the effects of these on buyer satisfaction with the buyer-supplier relationship. Opinions from firms in semiconductor manufacturing supply chain were used to investigate the proposed model. It is found that mutual interdependence between a supplier and its buyer can enhance cooperative behaviors and power asymmetry hurt firms’ investment in cooperative behaviors. Suggestions are then provided to semiconductor supply chain members based on the findings of this work.
PET SFCM image segmentation for alzheimer’s disease

Medical images are known to capture the human body in both anatomical and functional view. These images are interpreted with expert domain for clinical analysis. Here, the selection of image sample plays a fundamental role. However, doctors need to manually obtain this process. But, in order to get similarity between the samples automation is definitely required as it reduces the computation time. So, the automation process should be knowledge based to get better results. This paper highlights the knowledge based automation of medical image sample analysis. It presents a significant assessment of PET – SFCM approach for the segmentation of functional medical images which is considered as the value of neighboring pixels in spatial correlation. Here, the proposed method is used to apply the decision support strategy to identify the effective samples from the huge data collection. The proposed algorithm is implemented in Matlab 7.0. The obtained results were analyzed and compared with other two clustering approaches known as K-Means and Fuzzy C-Means. The resultant images encourage the identification and an evaluation of treatment response in a set of oncological constraints.
Critical analysis of India's National Mission on Medicinal Plants (NMMP) in providing access to quality botanical drugs to improve public health

Drugs play an important role in improving health of the population. Medicinal plants help in addressing the health issues of a large section of the population – especially the low and middle-income people. However, there are some concerns about the supply, efficacy and safety in using them. This study reviews India's major initiative toward medicinal plants namely, the National Mission on Medicinal Plants to meet medicinal plants challenges. The study analyzed the mission's probable shortcomings due to its design and operational details. This study used “content analysis” approach for analysis of mission's publicly available documents, viz. “Operational guidelines” and its two amendments. The study identified prevalent 28 shortcomings in the original document related to clarity of the document; accountability, transparency and stakeholders' representation. These challenges were partially addressed in two amendments, which indicate persistence of shortcomings in design and operational details. The mission can help in improving and strengthening the Ayurveda, Yoga, Unani, Siddha and Homeopathy program by addressing those shortcomings.
Genetics and phenotypes of RPE65 mutations in inherited retinal degeneration.

PURPOSE To characterize the spectrum of RPE65 mutations present in 453 patients with retinal dystrophy with an interest in understanding the range of functional deficits attributable to sequence variants in this gene. METHODS The 14 exons of RPE65 were amplified by polymerase chain reaction (PCR) from patients' DNA and analyzed for sequence changes by single-strand conformation polymorphism (SSCP) and direct sequencing. Haplotype analysis was performed using RPE65 intragenic polymorphisms. Patients were examined clinically and with visual function tests. RESULTS Twenty-one different disease-associated DNA sequence changes predicting missense or nonsense point mutations, insertions, deletions, and splice site defects in RPE65 were identified in 20 patients in homozygous or compound heterozygous form. In one patient, paternal uniparental isodisomy (UPD) of chromosome 1 resulted in homozygosity for a probable functional null allele. Eight of the disease-associated mutations (Y79H, E95Q, E102X, D167Y, 669delCA, IVS7+4a-->g, G436V, and G528V) and one mutation likely to be associated with disease (IVS6+5g-->a) have not been reported previously. The most commonly occurring sequence variant identified in the patients studied was the IVS1+5g-->a mutation, accounting for 9 of 40 (22.5%) total disease alleles. This splice site mutation, as well as R91W, the most common missense mutation, exists on at least two different genetic backgrounds. The phenotype resulting from RPE65 mutations appears to be relatively uniform and independent of mutation class, suggesting that most missense mutations (15 of 40 disease alleles [37.5%]) result in loss of function. At young ages, this group of patients has somewhat better subjective visual capacity than is typically associated with Leber congenital amaurosis (LCA) type I, with a number of patients retaining some useful visual function beyond the second decade of life. CONCLUSIONS RPE65 mutations account for a significant percentage (11.4%) of disease alleles in patients with early-onset retinal degeneration. The identification and characterization of patients with RPE65 mutations is likely to represent an important resource for future trials of rational therapies for retinal degeneration.
How the Electoral College Influences Campaigns and Policy: The Probability of Being Florida

This paper analyzes how US presidential candidates should allocate resources across states to maximize the probability of winning the election, by developing and estimating a probabilistic-voting model of political competition under the Electoral College system. Actual campaigns act in close agreement with the model. There is a 0.9 correlation between equilibrium and actual presidential campaign visits across states, both in 2000 and 2004. The paper shows how presidential candidate attention is affected by the states' number of electoral votes, forecasted state-election outcomes, and forecast uncertainty. It also analyzes the effects of a direct national popular vote for president.
How to trim a MST: A 2-Approximation algorithm for minimum cost-tree cover

The minimum cost-tree cover problem is to compute a minimum cost-tree T in a given connected graph G with costs on the edges, such that the vertices spanned by T form a vertex cover for G. The problem is supposed to occur in applications of vertex cover and in edge-dominating sets when additional connectivity is required for solutions. Whereas a linear-time 2-approximation algorithm for the unweighted case has been known for quite a while, the best approximation ratio known for the weighted case is 3. Moreover, the 3-approximation algorithms for such cases are far from practical due to their inefficiency. In this article we present a fast, purely combinatorial 2-approximation algorithm for the minimum cost-tree cover problem. It constructs a good approximate solution by trimming some leaves within a minimum spanning tree (MST); and, to determine which leaves to trim, it uses both the primal-dual schema and an instance layering technique adapted from the local ratio method.
POSITION DETERMINATION USING LANDMARK LOCALIZATION FOR A MOBILE ROBOT

An artificial landmark-based, automatic navigation system was developed for a small-scale field robot. Several low-cost sensing techniques were involved in the system to detect surroundings and determine the position of the moving robot. Several tests were conducted to evaluate the accuracy of linear distance and angular displacement using dead-reckoning with a gyro-correction, overall performance of the gyroscope used, and effectiveness of an artificial-landmark-based automatic navigation. The accuracy of the position determination methods based on dead-reckoning only, dead-reckoning with a gyro-correction, and laser-range-finder (LRF)-based methods was tested, analyzed, and compared, respectively. The results of the automatic navigation tests showed that LRF-based position estimation was much more accurate when compared to the dead-reckoning and dead-reckoning with gyroscope correction approaches. It had the ability to navigate the testing robot with a high accuracy.
Analysis of Speaker Adaptation Algorithms for HMM-Based Speech Synthesis and a Constrained SMAPLR Adaptation Algorithm

In this paper, we analyze the effects of several factors and configuration choices encountered during training and model construction when we want to obtain better and more stable adaptation in HMM-based speech synthesis. We then propose a new adaptation algorithm called constrained structural maximum a posteriori linear regression (CSMAPLR) whose derivation is based on the knowledge obtained in this analysis and on the results of comparing several conventional adaptation algorithms. Here, we investigate six major aspects of the speaker adaptation: initial models; the amount of the training data for the initial models; the transform functions, estimation criteria, and sensitivity of several linear regression adaptation algorithms; and combination algorithms. Analyzing the effect of the initial model, we compare speaker-dependent models, gender-independent models, and the simultaneous use of the gender-dependent models to single use of the gender-dependent models. Analyzing the effect of the transform functions, we compare the transform function for only mean vectors with that for mean vectors and covariance matrices. Analyzing the effect of the estimation criteria, we compare the ML criterion with a robust estimation criterion called structural MAP. We evaluate the sensitivity of several thresholds for the piecewise linear regression algorithms and take up methods combining MAP adaptation with the linear regression algorithms. We incorporate these adaptation algorithms into our speech synthesis system and present several subjective and objective evaluation results showing the utility and effectiveness of these algorithms in speaker adaptation for HMM-based speech synthesis.
Radiation reaction for a massless charged particle

We derive effective equations of motion for a massless charged particle coupled to the dynamical electromagnetic field with regard to the radiation back reaction. It is shown that unlike the massive case, not all the divergences resulting from the self-action of the particle are Lagrangian, i.e., can be cancelled out by adding appropriate counterterms to the original action. Besides, the order of renormalized differential equations governing the effective dynamics turns out to be greater than the order of the corresponding Lorentz–Dirac equation for a massive particle. For the case of a homogeneous external field, the first radiative correction to the Lorentz equation is explicitly derived via the reduction of order procedure.
Lignocellulosic ethanol production from the recovery of stranded driftwood residues

This paper builds upon a research project funded by the Italian Ministry of Environment, and aims to recover stranded driftwood residues (SDRs), in order to transform a potential pollution and safety issue into valuable bio-resources. In particular, one of the experiments consisted of bioethanol production from lignocellulosic residues. The SDRs were gathered from the Italian coast (Abruzzo Region, Italy) after an intense storm. The biomass recalcitrance, due to its lignocellulosic structure, was reduced by a steam explosion (SE) pretreatment process. Four different pretreatment severity factors (R 0 ) were tested (LogR 0 3.65, 4.05, 4.24 and 4.64) in order to evaluate the pretreated material’s accessibility to enzymatic attack and the holocellulose (cellulose plus hemicellulose) recovery. A first enzymatic hydrolysis was performed on the pretreated materials by employing a solid/liquid (S/L) ratio of 1% (w/w) and an enzyme dosage of 30% (w enzyme/w cellulose), in order to estimate the maximum enzymatically accessible cellulose content. Since the primary goal of pretreatment and hydrolysis is to convert as much cellulose as possible into monomeric glucose and recover all the holocellulose, the two pretreated materials showing these features were selected for bioethanol production process. The pretreated materials underwent a semi-simultaneous saccharification and fermentation (SSSF). The SSSF process was performed into two lab-scale bioreactors (5 L) with an S/L ratio of 15% and an enzyme dosage of 15% for five days. The efficiency of the whole bioethanol production process was assessed as ethanol overall yields (g ethanol/100 g raw material). The best overall yield was achieved by sample BS04 (8.98 g ethanol/100 g raw material).
Associative learning increases adult neurogenesis during a critical period

Learning increases the number of immature neurons that survive and mature in the adult hippocampus. One‐week‐old cells are more likely to survive in response to learning than cells in animals that are exposed to training but do not learn. Because neurogenesis is an ongoing and overlapping process, it is possible that learning differentially affects new cells as a function of their maturity. To address this issue, we examined the effects of associative learning on the survival of cells at different stages of development. Training did not alter the number of cells that were produced during the training experience. Cells that were 1–2 weeks of age at the time of training survived after learning but cells that were younger or older did not. In contrast, cells that were produced during training were less likely to survive than cells in untrained animals. Additionally, the number of cells that were generated after learning in trained animals was not different from the number in untrained animals. Finally, survival was not increased if the memory was expressed when the cells were about 1‐week‐old. Together, these results indicate that new neurons are rescued from death by initial acquisition, not the expression or reacquisition, of an associative memory and only during a critical period. Overall, these results suggest the presence of a feedback system, which controls how many new neurons become incorporated into the adult brain in response to learning.