Miracle-dz/UniFAR-FTUs huggingface dataset:
Recommending based on rating frequencies

Since the development of the comparably simple neighborhood-based methods in the 1990s, a plethora of techniques has been developed to improve various aspects of collaborative filtering recommender systems like predictive accuracy, scalability to large problem instances or the capability to deal with sparse data sets. Many of the recent algorithms rely on sophisticated methods which are based, for instance, on matrix factorization techniques or advanced probabilistic models and/or require a computationally intensive model-building phase. In this work, we evaluate the accuracy of a new and extremely simple prediction method (RF-Rec) that uses the user's and the item's most frequent rating value to make a rating prediction. The evaluation on three standard test data sets shows that the accuracy of the algorithm is on a par with the standard collaborative filtering algorithms on dense data sets and outperforms them on sparse rating databases. At the same time, the algorithm's implementation is trivial, has a high prediction coverage, requires no complex offline pre-processing or model-building phase and can generate predictions in constant time.
Who is Afraid of Political Instability?

An unstable macroeconomic environment is often regarded as detrimental to economic growth. Among the sources contributing to such instability, much of the blame has been assigned to political issues. This paper empirically tests for a causal and negative long-run relationship between political instability and economic growth but finds no such relationship. Sensitivity analysis, however, indicates that there is indeed a short-run negative relationship and, that in the long-run and ignoring institutional factors, the group of African countries is the driving force. In other words, we suspect that excluding the African countries from their samples, results of a negative relation between SPI and growth would founder.
Effect of incorporation of walnut cake (Juglans regia) in concentrate mixture on degradation of dry matter, organic matter and production of microbial biomass in vitro in goat

Aim: This study was carried out to investigate the effect of incorporation of different level of walnut cake in concentrate mixture on in vitro dry matter degradation in order to determine its level of supplementation in ruminant ration. Materials and Methods: Walnut cake was used @ 0, 10, 15, 20, 25 and 30% level to formulate an iso-nitrogenous concentrate mixtures and designated as T1, T2, T3, T4, T5 and T6 respectively. The different formulae of concentrate mixtures were used for in vitro gas production studies using goat rumen liquor with wheat straw in 40:60 ratio. Proximate composition, fiber fractionation and calcium and phosphrous content of walnut cake were estimated. Result: The per cent IVDMD value of T1 and T2 diets was 68.42 ± 1.20 and 67.25 ± 1.37 respectively which was found highest (P<0.05) T3, T4, T5 and T6. Similar trend was also found for TDOM and MBP. Inclusion of walnut cake at 10% level in the concentrate mixture does not affect in vitro dry matter digestibility (IVDMD), truly degradable organic matter (TDOM, mg/200 mg DM), total gas production, microbial biomass production (MBP) and efficiency of microbial biomass production (EMP). Conclusion: It is concluded that walnut cake incorporation up to 10% level in the iso -nitrogenous concentrate mixture has no any negative effect on in vitro digestibility of dry matter (DM), TDOM, MBP, EMP and total gas production in goat.
Estimation of optimal PDE-based denoising in the SNR sense

This paper is concerned with finding the best partial differential equation-based denoising process, out of a set of possible ones. We focus on either finding the proper weight of the fidelity term in the energy minimization formulation or on determining the optimal stopping time of a nonlinear diffusion process. A necessary condition for achieving maximal SNR is stated, based on the covariance of the noise and the residual part. We provide two practical alternatives for estimating this condition by observing that the filtering of the image and the noise can be approximated by a decoupling technique, with respect to the weight or time parameters. Our automatic algorithm obtains quite accurate results on a variety of synthetic and natural images, including piecewise smooth and textured ones. We assume that the statistics of the noise were previously estimated. No a priori knowledge regarding the characteristics of the clean image is required. A theoretical analysis is carried out, where several SNR performance bounds are established for the optimal strategy and for a widely used method, wherein the variance of the residual part equals the variance of the noise
Dept. for Speech, Music and Hearing Quarterly Progress and Status Report Speech/music Discrimination Using Discrete Hidden Markov Models Speech/music Discrimination Using Discrete Hidden Markov Models

A speech/music discrimination system using discrete Hidden Markov Models has been designed. The system has been evaluated using separate training, development and test databases. The discrimination ability was examined using different features and feature combinations and results are presented as error rate on the development and test databases. Features were chosen from knowledge about the speech signal. Adding the zero crossing rate, autocorrelation function and spectral gravity features to cepstrum coefficients helped to improve the discrimination result, while the cepstrum features were found to be more robust. The impact of the model size on the Speech/Music discrimination result was especially evaluated. Different compositions of the database were also explored, with and without a good match. The best result on a mismatched situation, 2.3% error rate on test data, was achieved with 2x13 LFCC (13 Cepstrum coefficients and first time differentials), using 24 states and 96 symbols. In the matched situation, the best result on test data was achieved using a combination of all features extracted (47-dimensional), yielding 1% error rate or just below, at the optimal model size, 20-24 states and 48-54 symbols. These tests used a 1-second decision window size. By using transcribed speech files it was also possible to compare the state assignment with the uttered phoneme for each segment. Investigating these results showed that the assigned states from the Viterbi search in a 3-state HMM, could be considered as phoneme classes
Gait Angle Prediction for Lower Limb Orthotics and Prostheses Using an EMG Signal and Neural Networks

Commercial lower limb prostheses or orthotics help patients achieve a normal life. However, patients who use such aids need prolonged training to achieve a normal gait, and their fatigability increases. To improve patient comfort, this study proposed a method of predicting gait angle using neural networks and EMG signals. Experimental results using our method show that the absolute average error of the estimated gait angles is 0.25°. This performance data used reference input from a controller for the lower limb orthotic or prosthesis controllers while the patients were walking. Increasing numbers of patients are being paralyzed or are having lower limbs amputated following industrial and traffic accidents. Many investigators and companies have developed orthotics and prostheses for such patients. Commercial lower limb prostheses or orthotics help give these patients a normal life. However, patients who use such aids need prolonged training to achieve a normal gait. As there is a difference between a normal gait and the gait with an orthotic or prosthesis, a patient's fatigability increases. To solve this problem, optimum control should be achieved based on a patient's gait. Previous research on the optimal control of patient gait posture focused on predicting the exact posture angle of the lower limb with the orthotic or prosthesis. Recently, Chan et al. used an electromyographic (EMG) classification for prosthesis control. However, this method cannot predict the posture angles of a prosthesis because it only uses a logical scheme to determine "flexion" and "extension" from the EMG signals (1). Therefore, we propose a technique for predicting the posture angles of patients' orthotics or prostheses for a single lower limb. We assumed that the gait properties of the normal lower limb equal those of the injured lower limb. The method consists of two steps that predict knee angles in the normal lower limb and the posture angles for the orthotic or prosthesis based on the predicted angle of the knee. First, the knee angle during a patient's gait is predicted using the two-channel surface EMG signals for the one normal lower limb. In the second step, the angles of the orthotic or prosthesis are predicted using the predicted knee angle for the normal lower limb. In this study, the predictor used an artificial neural network. The performance of the predictor was evaluated in simulations and experiments. The experimental results using the proposed method showed that the reference input signal could be used to control the lower limb orthotic and prosthesis to give the patient a smooth gait.
Time-based arrival management concept with mixed FMS equipage

This paper describes a trade study on a time-based arrival management concept designed to maximize the success rate of Continuous Descent Operations (CDO) in high-density traffic. The concept assumes a mixed fleet with three types of onboard 4D guidance and control capabilities. Specifically, the airplanes in this concept are provided with flight management systems (FMS) which encompass either Required Time of Arrival (RTA), or an experimental continuous 4D guidance method called CDA-MP, or no 4D capability at all. The concept is supported by existing arrival management systems that strategically sequence the traffic to the runway and a set of meter fixes and issues meet-time advisories to the meter fixes. Automation advisories include single speed and path stretching instructions. Fast-time simulation experiments were conducted using ELASTic, a traffic simulation capability being developed at Boeing that emphasizes on detailed FMS and accurate trajectory modeling. The operational performance of the concept was evaluated for a representative traffic scenario for Atlanta International Airport. Results indicated that the concept has the potential of achieving 80% of uninterrupted CDO flights to the meter fixes with 4D unequipped aircraft for the evaluated scenario and modeling assumptions. With onboard 4D guidance, CDO success increased by around 10%. When mixing 4D guided flights with speed advised flights, the majority of the aircraft needs to be equipped with a 4D guidance capability before similar operational benefits can be achieved. The effect of tuning the arrival management system with delay absorption in the terminal area and by introducing spacing buffers at the meter fixes was also evaluated and proven to be of value to CDO success, flight delay and fuel consumption.
Combating (Child) Human Trafficking: Building Capacity

The presentation/paper focuses on the challenges and necessity of building capacity at local, national, and international levels with a focus of how to more effectively combat trafficking in human beings (THB). Insight from several of initiatives are shared with the aim of illustrating how to capitalize on the vast number of opportunities that already exist at these levels and how they might be coordinated to enable collaborative work in an informed and dynamic manner to combat human trafficking. Information from several recent research projects that focus on some of these same issues is also incorporated into this paper. El articulo se centra en los desafios de la lucha contra el trafico de personas y en la necesidad de aumentar la capacidad para ser mas eficaces en ese sentido, local, nacional e internacionalmente. Nos hacemos eco de la vision de varias iniciativas, con el fin de ilustrar como capitalizar el gran numero de oportunidades que ya existen en los ambitos citados, y la forma en que se podrian coordinar para posibilitar la colaboracion de una manera informada y dinamica para combatir la trata de personas. Tambien se incluye en el articulo informacion emanada de diversos proyectos recientes de investigacion sobre el tema que nos ocupa. Available from: https://doi.org/10.35295/osls.iisl/0000-0000-0000-0921
ROS-Induced JNK and p38 Signaling Is Required for Unpaired Cytokine Activation during Drosophila Regeneration

Upon apoptotic stimuli, epithelial cells compensate the gaps left by dead cells by activating proliferation. This has led to the proposal that dying cells signal to surrounding living cells to maintain homeostasis. Although the nature of these signals is not clear, reactive oxygen species (ROS) could act as a signaling mechanism as they can trigger pro-inflammatory responses to protect epithelia from environmental insults. Whether ROS emerge from dead cells and what is the genetic response triggered by ROS is pivotal to understand regeneration of Drosophila imaginal discs. We genetically induced cell death in wing imaginal discs, monitored the production of ROS and analyzed the signals required for repair. We found that cell death generates a burst of ROS that propagate to the nearby surviving cells. Propagated ROS activate p38 and induce tolerable levels of JNK. The activation of JNK and p38 results in the expression of the cytokines Unpaired (Upd), which triggers the JAK/STAT signaling pathway required for regeneration. Our findings demonstrate that this ROS/JNK/p38/Upd stress responsive module restores tissue homeostasis. This module is not only activated after cell death induction but also after physical damage and reveals one of the earliest responses for imaginal disc regeneration.
Responses of insect pests, pathogens, and invasive plant species to climate change in the forests of northeastern North America: what can we predict?

Climate models project that by 2100, the northeastern US and eastern Canada will warm by approximately 3- 5 8C, with increased winter precipitation. These changes will affect trees directly and also indirectly through effects on ''nuisance'' species, such as insect pests, pathogens, and invasive plants. We review how basic ecological principles can be used to predict nuisance species' responses to climate change and how this is likely to impact northeastern forests. We then examine in detail the potential responses of two pest species (hemlock woolly adelgid (Adelges tsugae Annand) and forest tent caterpillar (Malacosoma disstria Hubner)), two pathogens (armillaria root rot (Armillaria spp.) and beech bark disease (Cryptococcus fagisuga Lind. + Neonectria spp.)), and two invasive plant species (glossy buckthorn (Frangula alnus Mill.) and oriental bittersweet (Celastrus orbiculatus Thunb.)). Several of these species are likely to have stronger or more widespread effects on forest composition and structure under the projected climate. However, uncertainty pervades our predictions because we lack adequate data on the species and because some species depend on complex, incompletely understood, unstable relationships. While targeted research will increase our confidence in making predictions, some un-
Is this a wampimuk? Cross-modal mapping between distributional semantics and the visual world

Following up on recent work on establishing a mapping between vector-based semantic embeddings of words and the visual representations of the corresponding objects from natural images, we first present a simple approach to cross-modal vector-based semantics for the task of zero-shot learning, in which an image of a previously unseen object is mapped to a linguistic representation denoting its word. We then introduce fast mapping, a challenging and more cognitively plausible variant of the zero-shot task, in which the learner is exposed to new objects and the corresponding words in very limited linguistic contexts. By combining prior linguistic and visual knowledge acquired about words and their objects, as well as exploiting the limited new evidence available, the learner must learn to associate new objects with words. Our results on this task pave the way to realistic simulations of how children or robots could use existing knowledge to bootstrap grounded semantic knowledge about new concepts.
Bone Marrow Aspirate in the Treatment of Chondral Injuries

The ability of mesenchymal stem cells (MSCs) to transdifferentiate into a desired cell lineage has captured the imagination of scientists and clinicians alike. The limited ability for chondrocytes to regenerate in chondral injuries has raised the concept of using MSCs to help regenerate and repair damaged tissue. The expansion of cells in a laboratory setting to be delivered back to the patient is too costly for clinical use in the present tough economic climate. This process is slow with due to the complexity of trying to imitate the natural environment and biological stimulation of chondral cell replication and proliferation. Bone marrow aspirate concentrate (BMAC) has the potential to provide an easily accessible and readily available source of MSCs with key growth factors that can be used in treating chondral injuries. This review summarizes the underlying basic science of MSCs and the therapeutic potential of BMAC.
Reliability of the new environmental paradigm for analysing the environmental attitudes of Senegalese pupils in the context of conservation education projects

Abstract The New Environmental Paradigm scale for children was developed and validated in Western nations but has seldom been applied in non-western countries. The aim of the current study is to examine the scale’s validity for schoolchildren in Senegal. The study was conducted in three regions of Senegal in November and December 2015, and a total 782 schoolchildren with an average age of 13 years participated. We used Cronbach’s alpha and confirmatory factor analysis to assess the consistency of the scale. The principal component analysis was used to reveal the different potential dimensions of our data-set. Given the low internal consistency of the scale and the unexpected responses to certain items, the scale seems to be rather unreliable for the investigated population. This difference could be caused by specific cultural features encompassing strong religious beliefs, different understandings of the place of humankind in nature, and weak awareness of humans’ impact on the natural world.
Between God and self: exploring the attachment to God and authenticity/inauthenticity tendencies of South African Christian youths

ABSTRACT The paper explores the relationship between attachment to God (AG) and authenticity/inauthenticity among Christian youths in relation to a range of socio-demographic variables. Cross-sectional data were collected from 100 South African Christian youths using measures of AG and authenticity/inauthenticity. The correlation results reveal that feelings of insecurity in terms of having anxiety in a relationship with God is positively related to self-alienation (feeling out of touch with oneself) and accepting external influences (conforming to the standards and expectations of others), but negatively correlated to authentic living (being in tune with one’s self). Feelings of insecurity in terms of avoidant God-attachment was also related to self-alienation. In addition, demographic differences were observed for gender and church denomination. These results suggest that insecurity with God may either be linked to feelings of authenticity or self-estrangement among Christian youths and have broad implications, both for clinical usage and further cross-cultural research.
On the Lengths, Colors, and Ages of 18 Face-on Bars

Along with a brief analysis we present data obtained from BVRI and Ks images of a sample of 19 galaxies (18 barred and 1 unbarred), which will be further explored in a future paper. We measured the lengths and colors of the bars, created color maps, and estimated global color gradients. Applying a method developed in a companion paper, we could distinguish for seven galaxies in our sample those whose bars have been recently formed from the ones with already evolved bars. We estimated an average difference in the optical colors between young and evolved bars that may be translated to an age difference of the order of 10 Gyr, meaning that bars may be, at least in some cases, long-standing structures. Moreover, our results show that, on average, evolved bars are longer than young bars. This seems to indicate that, during its evolution, a bar grows longer by capturing stars from the disk, in agreement with recent numerical and analytical results. Although the statistical significance of these results is low, and further studies are needed to confirm them, we discuss the implications from our results on the possibility of bars being a recurrent phenomenon. We also present isophotal contours for all our images as well as radial profiles of relevant photometric and geometric parameters.
Dietary overlap between sympatric Mexican spotted and great horned owls in Arizona

We estimated diet composition of sympatric Mexican spotted (Strix occidentalis lucida, n = 7 pairs of owls) and great horned owls (Bubo virginianus, n = 4 pairs) in ponderosa pine (Pinus ponderosa) - Gambel oak (Quercus gambelii) forest, northern Arizona. Both species preyed on mammals, birds, and insects; great horned owls also ate lizards. Mammals dominated the diet of both species. Mammals comprised 63 and 62% of all prey items identified in diets of spotted and great horned owls, respectively, and 94 and 95% of prey biomass. Both species primarily preyed on a few groups of small mammals. Observed overlap in diet composition between species (0.95) was greater than expected based on null models of diet overlap, and the size range of prey taken overlapped entirely. Mean prey mass was similar for both species (great horned owl, 47.0 ± 7.4 g [SE], n = 94 items; spotted owl, 40.1 ± 1.8 g, n = 1,125 items). Great horned owls consumed larger proportions of diurnally active prey than spotted owls, which primarily consumed nocturnally active mammals. Our results, coupled with a previous analysis showing that these owls foraged in the same general areas (Ganey and others 1997), suggests that they could compete for food resources, which are assumed to be limiting in at least some years. They may minimize the potential for resource competition, however, by concentrating foraging activities in different habitats (Ganey and others 1997) and by foraging at different times, when different suites of prey species are active.
Genetic association between COPD and polymorphisms in TNF, ADRB2 and EPHX1

There is evidence of a hereditary component in chronic obstructive pulmonary disease (COPD). A number of genetic association studies have been performed to find susceptibility genes of COPD. The current authors performed a case–control, genetic-association study and a meta-analysis of 16 studies, involving seven polymorphisms in three well-studied genes: microsomal epoxide hydroxylase (EPHX1); tumour necrosis factor; and β2-adrenoreceptor. A total of 492 Caucasian smokers and former smokers were recruited from hospital databases and population cohort studies. In the present study, a protective effect of the EPHX1 Tyr113His polymorphism was found (homozygous odds ratio (OR) 0.5). In the meta-analysis, homozygotes for this single nucleotide polymorphism (SNP) also had a pooled OR of 0.5. The same effect has been found in several lung cancer studies. Effects for other candidate SNPs were weak or statistically insignificant, and probable genotyping error was common. In conclusion, the present data and meta-analysis support a role for microsomal epoxide hydroxylase in the aetiology of chronic obstructive pulmonary disease.