Miracle-dz/UniFAR-FTUs huggingface dataset:
A Robust Algorithm to Identify the Test Stimulus in Histogram-Based A/D Converter Testing

Traditional testing of analog-to-digital converters (ADCs) with automatic test equipment is time-consuming and expensive, and a built-in self-test (BIST) can be one solution to this problem. Most of the proposed BIST routines require a well-known test stimulus which is much more linear than the device under test. A stimulus error identification and removal (SEIR) method that does not require a high-linearity stimulus has been proposed recently, and it is evident that reliable test results could be achieved with a stimulus linearity lower than the required measurement accuracy. This paper presents a simple and easy-to-implement calculation algorithm for use with the stimulus-identification method, particularly for BIST purposes. Simulations demonstrate that the integral-nonlinearity measuring accuracy of the SEIR method with the new calculation algorithm is 1 least significant bit for 14-b ADCs, even though the linearity of the test stimulus is only 7 b. The SEIR method and the new simpler calculation algorithm can reduce the hardware resources required for ADC BIST.
Tele‐assessment of Psoriasis Area and Severity Index: A study of the accuracy of digital image capture

Background: The implementation of remote Psoriasis Area and Severity Index (PASI) determinations would greatly enhance the delivery of specialist dermatological care to patients with severe psoriasis unable to attend face‐to‐face dermatological consultations. Here we investigate the feasibility of the remote determination of PASI scores by comparing the results of face‐to‐face with digital image assessment.
AID ALLOCATION PRACTICE: COMPARING DONORS AND ERAS

Focusing on seven bilateral donors over a 25 year period, the paper answers 4 questions related to aid allocation practice. Questions one and two examine allocation differences between donors and time periods. Questions three and four relate to changes in poverty and policy selectivity. To answer these questions a formal approach is used to quantify the effects of four factors that influence aid allocation: poverty, policy, proximity and population. The results reaffirm findings of large donor heterogeneity and the role of non-development influences. However, they dispute recent findings of large or growing policy sensitivity.
The Emergence of a 'Language' in an Evolving Population of Neural Networks

The evolution of language implies the parallel evolution of an ability to respond appropriately to signals (language understanding) and an ability to produce the appropriate signals in the appropriate circumstances (language production). When linguistic signals are produced to inform other individuals, individuals that respond appropriately to these signals may increase their reproductive chances but it is less clear what the reproductive advantage is for the language producers. We present simulations in which populations of neural networks living in an environment evolve a simple language with an informative function. Signals are produced to help other individuals categorize edible and poisonous mushrooms, in order to decide whether to approach or avoid encountered mushrooms. Language production, while not under direct evolutionary pressure, evolves as a byproduct of the independently evolving perceptual ability to categorize mushrooms.
Prayas at EmoInt 2017: An Ensemble of Deep Neural Architectures for Emotion Intensity Prediction in Tweets

The paper describes the best performing system for EmoInt - a shared task to predict the intensity of emotions in tweets. Intensity is a real valued score, between 0 and 1. The emotions are classified as - anger, fear, joy and sadness. We apply three different deep neural network based models, which approach the problem from essentially different directions. Our final performance quantified by an average pearson correlation score of 74.7 and an average spearman correlation score of 73.5 is obtained using an ensemble of the three models. We outperform the baseline model of the shared task by 9.9% and 9.4% pearson and spearman correlation scores respectively.
The “potential” face of absorptive capacity. An empirical investigation for an area of 3 European countries

This paper draws on the multi-dimensional characterization of absorptive capacity (AC) to empirically investigate the antecedents and the effects of its “potential” dimension (PAC): i.e., the firm’s capacity of acquiring and assimilating external knowledge, as distinguished from its “realized” transformation and exploitation (RAC). Based on a sample of about 10,500 firms for an area of 3 EU countries (Italy, Germany and Spain) we find that the firm’s reliance on external knowledge in general increases its PAC, and that this effect is magnified by the internal shocks the firm faces. However, both these effects find relevant exceptions when different kinds of external sources are considered, at different kinds of distance from the absorbing firm. Unexpectedly, social integration mechanisms in the firm makes PAC less, rather than more, inductive of innovation outcomes. On the contrary, the human capital of the firm has a positive moderating role on the PAC effects. A possible trade-off in the exploitation of the externally assimilated knowledge is suggested.
Enumerating singular curves on surfaces

We enumerate the singular algebraic curves in a complete linear system on a smooth projective surface. The system must be suitably ample in a rather precise sense. The curves may have up to eight nodes, or a triple point of a given type and up to three nodes. The curves must also pass through appropriately many general points. The number of curves is given by a universal polynomial in four basic Chern numbers. To justify the enumeration, we make a rudimentary classification of the types of singularities using Enriques diagrams, obtaining results like Arnold's. We show that the curves in question do, in fact, appear with multiplicity 1 using the versal deformation space, Shustin's codimension formula, and Gotzmann's regularity theorem. Finally, we relate our work to Vainsencher's work with up to seven nodes.
An Intelligent Fuzzy Logic Controller for Maximum Power Capture of Point Absorbers

This article presents an intelligent fuzzy logic controller (FLC) for controlling single-body heaving wave energy converter (WEC) or what is widely known as “Point Absorber”. The controller aims at maximizing the energy captured from the sea waves. The power take-off (PTO) limitations are addressed implicitly in the fuzzy inference system (FIS) framework. In order to enhance the WEC power capturing bandwidth and make it less susceptible to wave environment irregularities and the system parametric uncertainties, the controller is built to have a self-configurable capability. This also eliminates the need to repeatedly run in-situ tuning procedure of the fuzzy controller or switch between several controllers based on the operating conditions. The fuzzy membership functions (MFs) are optimally tuned using particle swarm optimization (PSO) algorithm. To alleviate the computational burden associated with performing on-line optimization, the fuzzy controller is tuned at a rate significantly lower than the system sampling time. The suggested PSO-FLC has shown promising results compared with the fixed structure fuzzy logic controller (FS-FLC) and other passive control strategies. Several computer simulations were carried out to evaluate the controller effectiveness by applying different sea-states and analyzing the resultant WEC dynamics.
Robust stability analysis of discrete-time systems with parametric and switching uncertainties

Robust stability analysis is investigated for discrete-time linear systems with rational dependency with respect to polytopic type uncertainties. Two type of uncertainties are considered: constant parametric uncertainties and time-varying switching uncertainties. Results are in LMI formalism and proofs involve parameter-dependent, quadratic in the state, Lyapunov functions. The new proposed conditions are shown to extend and merge two important existing results. Conservatism reduction is tackled via a model augmentation technique. Numerical complexity is contained by exploiting the structure of the models with respect to the uncertainties.
The Pollution Haven Hypothesis: A Geographic Economy Model in a Comparative Study

Although based on theoretical foundations, the pollution haven hypothesis has never been clearly proven empirically. In this study, we re-examine this hypothesis by a fresh take on both its theoretical and empirical aspects. While applying a geographic economy model on French firm-level data, we confirm the hypothesis for the global sample. Through sensitivity analysis, we validate it for Central and Eastern European countries, emerging and high-income OECD countries, but not for the major part of the Commonwealth of Independent States countries. Finally, we show that the pollution haven hypothesis is confirmed in the strongest manner for emerging economies.
Immaturity in puberty and negative attitudes toward reproductive health among Indonesian adolescents

Abstract Background: Complex factors influence adolescents’ attitudes. Secondary sexual development and emotional changes are markers of puberty and affect attitudes toward reproductive health (RH). This is especially evident in the society and culture of Indonesia. This study examined the presence of immaturity at puberty and factors associated with negative attitudes toward RH among Indonesian adolescents. Methods: We conducted a cross-sectional study with 1040 students (aged 11–16 years) selected using multistage random cluster sampling. Data were collected using a self-administered questionnaire that included the illustrative questionnaire for interview surveys with young people and the pubertal development scale (PDS), modified in accordance with the Indonesian context. Data analysis used descriptive and comparative statistics and logistic regression analyses. Results: Immature pubertal development was higher in boys [22.7%, 95% confidence interval (CI): 14.7%–30.7%] than girls (18.4%, 95% CI: 11%–25.7%). However, negative attitudes were higher in girls (40.6%, 95% CI: 34.3%–46.8%) than boys (37.1%, 95% CI: 29.9%–44.7%). Factors associated with negative attitudes toward RH in both boys and girls were age, RH communication with parents, and pubertal development. Smoking was an additional factor in boys, whereas living in an urban area was an additional factor in girls. High knowledge about RH was associated with less negative attitudes toward RH in both boys and girls. Conclusion: Immaturity and factors that influence negative attitudes toward RH should be explored during puberty. Improving knowledge about RH may help to prevent negative attitudes toward RH, especially for girls in urban areas and boys with smoking habits.
Mindfulness Meditation and Cognitive Behavioral Therapy Intervention Reduces Pain Severity and Sensitivity in Opioid-Treated Chronic Low Back Pain: Pilot Findings from a Randomized Controlled Trial.

OBJECTIVE To assess benefits of mindfulness meditation and cognitive behavioral therapy (CBT)-based intervention for opioid-treated chronic low back pain (CLBP). DESIGN 26-week parallel-arm pilot randomized controlled trial (Intervention and Usual Care versus Usual Care alone). SETTING Outpatient. SUBJECTS Adults with CLBP, prescribed ≥30 mg/day of morphine-equivalent dose (MED) for at least 3 months. METHODS The intervention comprised eight weekly group sessions (meditation and CLBP-specific CBT components) and 30 minutes/day, 6 days/week of at-home practice. Outcome measures were collected at baseline, 8, and 26 weeks: primary-pain severity (Brief Pain Inventory) and function/disability (Oswestry Disability Index); secondary-pain acceptance, opioid dose, pain sensitivity to thermal stimuli, and serum pain-sensitive biomarkers (Interferon-γ; Tumor Necrosis Factor-α; Interleukins 1ß and 6; C-reactive Protein). RESULTS Thirty-five (21 experimental, 14 control) participants were enrolled and completed the study. They were 51.8 ± 9.7 years old, 80% female, with severe CLBP-related disability (66.7 ± 11.4), moderate pain severity (5.8 ± 1.4), and taking 148.3 ± 129.2 mg/day of MED. Results of the intention-to-treat analysis showed that, compared with controls, the meditation-CBT group reduced pain severity ratings during the study (P = 0.045), with between-group difference in score change reaching 1 point at 26 weeks (95% Confidence Interval: 0.2,1.9; Cohen's d = 0.86), and decreased pain sensitivity to thermal stimuli (P < 0.05), without adverse events. Exploratory analyses suggested a relationship between the extent of meditation practice and the magnitude of intervention benefits. CONCLUSIONS Meditation-CBT intervention reduced pain severity and sensitivity to experimental thermal pain stimuli in patients with opioid-treated CLBP.
A cross-sectional survey to assess the effect of socioeconomic status on the oral hygiene habits

Background: It is widely accepted that there are socioeconomic inequalities in oral health. A socioeconomic gradient is found in a range of clinical and self-reported oral health outcomes. Aim: The present study was conducted to assess the differences in oral hygiene practices among patients from different socioeconomic status (SES) visiting the Outpatient Department of the Sudha Rustagi College of Dental Sciences. Materials and Methods: A cross-sectional survey was conducted from June to October 2014 to assess the effect of SES on the oral hygiene habits. The questionnaire included the questions related to the demographic profile and assessment of the oral hygiene habits of the study population. Results: Toothbrush and toothpaste were being used significantly (P < 0.05) more by lower middle class (84.4%) and upper middle class (100.0%). A significantly higher frequency of cleaning teeth (twice a day) was reported among the lower middle class (17.2%) and upper middle class (21.5%). The majority (34.3%) of the study population changed their toothbrush once in 3 months. The cleaning of tongue was reported by patients belonging to the upper middle (62.0%), lower middle (52.1%), and upper lower class (30.0%). The use of tongue cleaner was reported to be significantly (P < 0.05) more among upper middle (10.1%) class patients. A significantly higher number of patients from the lower class (81.3%) never visited a dentist. Conclusion: The oral hygiene practices of the patients from upper and lower middle class was found to be satisfactory whereas it was poor among patients belonging to lower and upper lower class.
Transmission from photoreceptors to ganglion cells in turtle retina

1. Synaptic transfer between photoreceptors and impulse‐generating cells was studied in isolated eyecups from turtles. Single red‐sensitive cones or rods were stimulated by current passed through an intracellular electrode, and impulses generated by the resulting synaptic action were recorded with an external micro‐electrode. This technique permits study of retinal transmission without the operation of the visual transduction mechanism. Antidromic stimulation of the optic nerve indicated that most of the impulse‐generating cells were ganglion cells.
Predictor: Providing fine-grained management and predictability in multi-tenant datacenter networks

Software-Defined Networking (SDN) can simplify traffic management in large-scale datacenter networks (DCNs). On one hand, it provides a robust method to address the challenge of performance interference (bandwidth sharing unfairness) in DCNs. On the other, its pragmatic implementation based on OpenFlow introduces scalability challenges, as it (a) adds latency for new flows (the controller must process hundreds of thousands of requests per second and install appropriate rules in switches); and (b) requires large flow tables in devices (DCNs can have more than 16 million distinct flows per second with different requirements and duration). To employ OpenFlow-based SDN in DCNs, recent work has proposed techniques that require hardware customization to keep up with the high dynamic traffic patterns of these networks. We make two key observations: providers do not need to control each flow individually (e.g., VM-to-VM), since they charge tenants based on the amount of resources consumed by applications; and congestion control in the intra-cloud network is expected to be proportional to the tenant's payment. Based on these insights, we introduce Predictor, a novel system for DCNs that enables fine-grained network management for providers, minimizes flow table size by controlling flows at application-layer and reduces flow setup time by proactively installing rules in switches. It also enables tenants to request and receive predictable network performance for both intra- and inter-application communication, with work-conserving bandwidth sharing. Evaluation results show that Predictor provides significant improvements against DevoFlow (reducing flow table size up to 87%) and offers predictable and guaranteed network performance for tenants.
High Prevalence of Genotypic and Phenotypic HIV‐1 Drug‐Resistant Strains Among Patients Receiving Antiretroviral Therapy in Abidjan, Côte d'lvoire

Summary: To describe prevalence of antiretroviral (ARV) drug‐resistant HIV‐1 strains among patients with a history of earlier treatment with ARV drugs in Abidjan, Côte d'Ivoire, we determined mutations that confer HIV‐1 ARV drug resistance by sequencing the viral reverse‐transcriptase and protease genes derived from plasma viral RNA of 68 individuals consecutively enrolled in the Joint United Nations Pro gram on AIDS Drug Access Initiative (UNAIDS‐DAI) with a history of earlier ARV drug treatment in Abidjan between August 1998 and April 1999. Phenotypic ARV drug resistance was assessed using a recombinant virus assay. Primary mutations associated with ARV drug resistance to at least one of the reverse‐transcriptase in hibitors or protease inhibitors were detected in 39 (57.4%) of the 68 patients. The prevalence of mutations associated with resistance to ARV drugs was: 29 (42.6%) to zidovudine, 10 (14.7%) to lamivudine, one (1.5%) to didanosine, one K103N mutation (associated with resistance to delavirdine, nevirapine, and efavirenz), one Y181C mutation (associated with resistance to delavirdine and nevirapine), two to both indi navir (M46I/L and V82A) and saquinavir (G48V and L90M), and one each to ritonavir (V82A) and nelfinavir (D30N). Phenotypic resistance to at least one nucleoside reverse transcriptase inhibitor (RTI) was seen in 25 (39.7%) patients, to nonnucleoside RTIs in 5 (8%) patients, and to protease inhibitors in 4 (6%) patients. The high prevalence we observed in this study may limit in future the effectiveness of ARV programs in the Côte d'Ivoire.
New analogues of brefeldin A from sediment-derived fungus Penicillium sp. DT-F29

Abstract Four new analogues of brefeldin A named 7, 7-dimethoxybrefeldin C (3), 6β-hydroxybrefeldin C (4), 4-epi-15-epi-brefeldin A (5), 4-epi-8α-hydroxy-15-epi-brefeldin C (6), together with four known analogues (1, 7−9) were isolated from a fermentation of the sediment-derived fungus Penicillium sp. DT-F29. The structures of these compounds were elucidated on the basis of extensive spectroscopic and chemical methods. In the bioactivity assays, only compounds 1 and 8 showed significant inhibitory activities against human lung adenocarcinoma cell. In addition, compound 1 was first reported for the potent ability to reactivate latent HIV with EC50 value of 0.03 μM.
Responding to the call: arts methodologies informing 21st century literacies

With the advent of digital technologies, a new adventure began. How the world works has changed, and we cannot go back. Digitally savvy children born in the digital age (i.e., DigiKids) are interacting with and responding to rich, curatable multimodal communications as part of their daily-lived experience. For DigiKids, traditional text-based literacy is of diminishing significance as they exercise a wide range of new literacy practices and capacities. Having more the mindset of the artist, they engage in the world of expression and communication, weaving together linguistic, visual, aural, gestural and spatial features to form coherent compositions. Nevertheless, national curriculae reformers, teachers and parents generally fear neglecting traditional text-based literacy skills and consequently struggle to optimise DigiKids' digitally savvy literacy practices and capacities. However, practices employed in arts methodologies (e.g. ceramics, theatre, and music) offer a key resource to conceptualise new practices beyond traditional text-based literacy, and to situate our new post-literacy (i.e. epiliteracy) theory. To navigate the transition from traditional text-based literacy to epiliteracy, the metaphor of the archetypal Hero/Heroine's Journey is used to describe, chart and comprehend the tensions, trials and transformations as we respond to the call of epiliteracy in the 21st century.
Revisiting Darwin's conundrum reveals a twist on the relationship between phylogenetic distance and invasibility

Significance The application of phylogenetics is rapidly growing in many areas of biology. In invasion biology, phylogenetic information is now being used in an attempt to understand and predict species invasions. However, there is only a weak foundation for the prevalent predictions of how the phylogenetic distance between native and nonnative species should be related to the invasion success of the nonnative species. In this paper, a mechanistic model of species interactions and evolution is used to generate a unique set of predictions. These predictions deviate significantly from those assumed previously, suggesting that current explanations of phylogenetic distance–invasion relationships must be reevaluated. More generally, the results highlight the importance of considering the details of community processes when interpreting phylogenetic patterns. A key goal of invasion biology is to identify the factors that favor species invasions. One potential indicator of invasiveness is the phylogenetic distance between a nonnative species and species in the recipient community. However, predicting invasiveness using phylogenetic information relies on an untested assumption: that both biotic resistance and facilitation weaken with increasing phylogenetic distance. We test the validity of this key assumption using a mathematical model in which a novel species is introduced into communities with varying ecological and phylogenetic relationships. Contrary to what is generally assumed, we find that biotic resistance and facilitation can either weaken or intensify with phylogenetic distance, depending on the mode of interspecific interactions (phenotype matching or phenotype differences) and the resulting evolutionary trajectory of the recipient community. Thus, we demonstrate that considering the mechanisms that drive phenotypic divergence between native and nonnative species can provide critical insight into the relationship between phylogenetic distance and invasibility.