Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimizing the Cloud Resources, Bandwidth and Deployment Costs in Multi-Providers Network Function Virtualization Environment

The introduction of network function virtualization (NFV) leads to a new business model in which the Telecommunication Service Provider needs to rent cloud resources to infrastructure provider (InP) at prices as low as possible. Lowest prices can be achieved if the cloud resources can be rented in advance by allocating long-term virtual machines (VM). This is in contrast with the short-term VMs that are rented on demand and have higher costs. For this reason, we propose a proactive solution in which the cloud resource rent is planned in advance based on peak traffic knowledge. We illustrate the problem of determining the cloud resources in cloud infrastructures managed by different InPs and so as to minimize the sum of cloud resource, bandwidth and deployment costs. We formulate an integer linear problem (ILP) and due to its complexity, we introduce an efficient heuristic approach allowing for a remarkable computational complexity reduction. We compare our solution to a reactive solution in which the cloud resources are rented on demand and dimensioned according to the current traffic. Though the proposed proactive solution needs more cloud and bandwidth resources due to its peak allocation, its total resources cost may be lower than the one achieved when a reactive solution is applied. That is a consequence of the higher cost of short-term VMs. For instance, when a reactive solution is applied with traffic variation times of ten minutes, our proactive solution allows for lower total costs when the long-term VM rent is lower than the short-term VM one by 33%.
Resilience, condom use self-efficacy, internalized homophobia, and condomless anal sex among black men who have sex with men, New York City

Background Black men who have sex with men, who account for less than 1% of the U.S. population, account for approximately 25% of new HIV infections annually. Condomless anal sex contributes to HIV infection among black men who have sex with men. The capacity to recover quickly from difficulties (resilience) may be protective against condomless anal sex, but has been understudied among black men who have sex with men. Psychosocial factors related to resilience, i.e., condom use self-efficacy and internalized homophobia, may also affect condomless anal sex. We assessed the association between resilience, condom use self-efficacy, internalized homophobia and condomless anal sex among black men who have sex with men. Methods Data are from a 2010–2011 study examining condomless anal sex (past 60 days) among black men who have sex with men in New York City. Validated scales assessed resilience (theoretical range = 0–100), condom use self-efficacy (theoretical range = 27–135), and internalized homophobia (theoretical range = 9–36). We described continuous variables using median and interquartile range (IQR). Univariable and multivariable Poisson regression models assuming a robust variance estimator were used to compute unadjusted and adjusted prevalence ratios, respectively, and their corresponding 95% confidence intervals (CI). Adjusted prevalence ratios (aPR) examined the association of resilience, condom use self-efficacy, and internalized homophobia with condomless anal sex, while controlling for potential confounders (e.g., having >1 sex partner). Results The median resilience score within our sample (N = 228) was 75 (IQR = 66–83). Many black men who have sex with men reported condomless anal sex (55.7%) and >1 sex partner (58.8%). Decreased condomless anal sex was associated with increased levels of condom use self-efficacy (aPR: 0.94 per 10-point increase in condom use self-efficacy score; CI: 0.90–0.97; p-value: 0.001). Condomless anal sex was not associated with resilience or internalized homophobia. Conclusions Within this sample of black men who have sex with men, condomless anal sex was prevalent. Greater resilience was not protective against condomless anal sex. Interventions that support condom use are warranted for black men who have sex with men.
Liver Sinusoidal Endothelial Cells Promote the Expansion of Human Cord Blood Hematopoietic Stem and Progenitor Cells

Cord blood (CB) is an attractive source of hematopoietic stem cells (HSCs) for hematopoietic cell transplantation. However, its application remains limited due to the low number of HSCs/progenitors in a single CB unit and its notoriously difficulty in expanding ex vivo. Here, we demonstrated that the human fetal liver sinusoidal endothelial cells engineered to constitutively express the adenoviral E4orf1 gene (hFLSECs-E4orf1) is capable of efficient expansion ex vivo for human CB hematopoietic stem and progenitor cells (HSPCs). Coculture of CD34+ hCB cells with hFLSECs-E4orf1 resulted in generation of substantially more total nucleated cells, CD34+CD38− and CD34+ CD38−CD90+ HSPCs in comparison with that of cytokines alone after 14 days. The multilineage differentiation potential of the expanded hematopoietic cells in coculture condition, as assessed by in vitro colony formation, was also significantly heightened. The CD34+ hCB cells amplified on hFLSECs-E4orf1 were capable of engraftment in vivo. Furthermore, hFLSECs-E4orf1 highly expressed hematopoiesis related growth factor and Notch receptors. Accordingly, the CD34+ hCB cells amplified on hFLSECs-E4orf1 exhibited Notch signaling activation. Taken together, our findings indicated that FLSECs may potentially be the crucial component of the microenvironment to support recapitulation of embryonic HSC amplification in vitro and allow identification of new growth factors responsible for collective regulation of hematopoiesis.
The Utility of a Convolutional Neural Network for Generating a Myelin Volume Index Map from Rapid Simultaneous Relaxometry Imaging

Purpose: A current algorithm to obtain a synthetic myelin volume fraction map (SyMVF) from rapid simultaneous relaxometry imaging (RSRI) has a potential problem, that it does not incorporate information from surrounding pixels. The purpose of this study was to develop a method that utilizes a convolutional neural network (CNN) to overcome this problem. Methods: RSRI and magnetization transfer images from 20 healthy volunteers were included. A CNN was trained to reconstruct RSRI-related metric maps into a myelin volume-related index (generated myelin volume index: GenMVI) map using the MVI map calculated from magnetization transfer images (MTMVI) as reference. The SyMVF and GenMVI maps were statistically compared by testing how well they correlated with the MTMVI map. The correlations were evaluated based on: (i) averaged values obtained from 164 atlas-based ROIs, and (ii) pixel-based comparison for ROIs defined in four different tissue types (cortical and subcortical gray matter, white matter, and whole brain). Results: For atlas-based ROIs, the overall correlation with the MTMVI map was higher for the GenMVI map than for the SyMVF map. In the pixel-based comparison, correlation with the MTMVI map was stronger for the GenMVI map than for the SyMVF map, and the difference in the distribution for the volunteers was significant (Wilcoxon sign-rank test, P < 0.001) in all tissue types. Conclusion: The proposed method is useful, as it can incorporate more specific information about local tissue properties than the existing method. However, clinical validation is necessary.
Meta-analysis of naturalistic developmental behavioral interventions for young children with autism spectrum disorder

Naturalistic developmental behavioral intervention is an emerging class of interventions for young children with autism spectrum disorder. The present article is a meta-analysis of outcomes of group-design studies (n = 27) testing interventions using naturalistic developmental behavioral intervention strategies. Small, significant positive effects of naturalistic developmental behavioral intervention were found for expressive language (g = 0.32), reduction in symptoms of autism spectrum disorder (g = −0.38), and play skills (g = 0.23). Larger effects were found for social engagement (g = 0.65) and overall cognitive development (g = 0.48). A marginal effect was found for joint attention (g = 0.14) and receptive language (g = 0.28). For joint attention, improvement was moderated by hours of professional involvement. Evidence of publication and reporting bias was present for language outcomes. This meta-analysis grows the evidence base for naturalistic developmental behavioral interventions, particularly in the key areas of social engagement and cognition.
Electrophysiological Evidence for Top-Down Lexical Influences on Early Speech Perception

An unresolved issue in speech perception concerns whether top-down linguistic information influences perceptual responses. We addressed this issue using the event-related-potential technique in two experiments that measured cross-modal sequential-semantic priming effects on the auditory N1, an index of acoustic-cue encoding. Participants heard auditory targets (e.g., “potatoes”) following associated visual primes (e.g., “MASHED”), neutral visual primes (e.g., “FACE”), or a visual mask (e.g., “XXXX”). Auditory targets began with voiced (/b/, /d/, /g/) or voiceless (/p/, /t/, /k/) stop consonants, an acoustic difference known to yield differences in N1 amplitude. In Experiment 1 (N = 21), semantic context modulated responses to upcoming targets, with smaller N1 amplitudes for semantic associates. In Experiment 2 (N = 29), semantic context changed how listeners encoded sounds: Ambiguous voice-onset times were encoded similarly to the voicing end point elicited by semantic associates. These results are consistent with an interactive model of spoken-word recognition that includes top-down effects on early perception.
Inside the black box: permanent vs transitory components and economic fundamentals

Any non-stationary series can be decomposed into permanent (or "trend") and transitory (or "cycle") components. Typically some atheoretic pre-filtering procedure is applied to extract the permanent component. This paper argues that analysis of the fundamental underlying stationary economic processes should instead be central to this process. This argument is not, in itself new, since the links between multivariate Beveridge-Nelson trends and cointegration have been known for some time. But, despite the early work of King et al. (1991), there have been relatively few applications of the approach, possibly due to the perceived deficiencies of Beveridge-Nelson trends as derived from univariate representations, and a lack of transparency. We present an alternative derivation, whereby transitory components can be derived explicitly as a weighting of observable stationary processes, that have clear economic interpretations. We illustrate with two examples: from Garratt et al’s (2003) model of the UK economy; and from Robertson and Wright’s (2002) model of the US stock market.
CD4+CXCR5+PD-1+ T Follicular Helper Cells Play a Pivotal Role in the Development of Rheumatoid Arthritis

Background T follicular helper (Tfh) cells are a subgroup of activated CD4+ T cells in the germinal centers of secondary lymphoid organs, they play critical roles in the development of many chronic autoimmune inflammatory diseases. The aim of this study was to investigate whether circulating Tfh cells contribute to the development of rheumatoid arthritis (RA). Material/Methods Thirty patients fulfilled the diagnosis criteria that was established by the American College of Rheumatology and 30 healthy controls were recruited. The frequency of Tfh cells in patients and collagen-induced arthritis (CIA) in DBA/1J mice were analyzed by flow cytometry. The serum IL-21 level was examined by enzyme-linked immunosorbent assay (ELISA). The mRNA expression of Blimp-1 and Bcl-6 were detected by qRT-PCR. Results RA patients had more CD4+PD-1+CXCR5+ Tfh cells in peripheral blood compared with healthy controls, and CIA in DBA/1J mice showed similar results. Higher mRNA expression of Bcl-6 and lower Blimp-1 mRNA expression were observed in patients with RA compared to healthy controls, and the expression level of IL-21 was higher in RA patients, which was also seen in CIA mice. Furthermore, the spleen CD4+ICOS+CXCR5+ Tfh cells in CIA mice show significantly higher frequency than that in the control mice. The percentage of CD4+PD-1+CXCR5+ Tfh cells was correlated positively with the values of erythrocyte sedimentation rate (ESR) (r=0.968, P<0.001), rheumatoid factor (RF) (r=0.962, P<0.001), C-reactive protein (CRP) (r=0.953, P<0.001), and anti-cyclic citrullinated peptide antibodies (ACPA) (r=0.966, P<0.001), and the level of serum interleukin (IL)-21 in RA patients showed positive correlation with ESR (r=0.982, P<0.001), RF (r=0.959, P<0.001), CRP (r=0.951, P<0.001), and ACPA (r=0.971, P<0.001) as well. Conclusions The activated Tfh cells in the peripheral blood may be responsible for the development of RA.
Thermophiles; or, the Modern Prometheus: The Importance of Extreme Microorganisms for Understanding and Applying Extracellular Electron Transfer

Approximately four billion years ago, the first microorganisms to thrive on earth were anaerobic chemoautotrophic thermophiles, a specific group of extremophiles that survive and operate at temperatures ∼50 – 125°C and do not use molecular oxygen (O2) for respiration. Instead, these microorganisms performed respiration via dissimilatory metal reduction by transferring their electrons extracellularly to insoluble electron acceptors. Genetic evidence suggests that Gram-positive thermophilic bacteria capable of extracellular electron transfer (EET) are positioned close to the root of the Bacteria kingdom on the tree of life. On the contrary, EET in Gram-negative mesophilic bacteria is a relatively new phenomenon that is evolutionarily distinct from Gram-positive bacteria. This suggests that EET evolved separately in Gram-positive thermophiles and Gram-negative mesophiles, and that EET in these bacterial types is a result of a convergent evolutionary process leading to homoplasy. Thus, the study of dissimilatory metal reducing thermophiles provides a glimpse into some of Earth’s earliest forms of respiration. This will provide new insights for understanding biogeochemistry and the development of early Earth in addition to providing unique avenues for exploration and discovery in astrobiology. Lastly, the physiological composition of Gram-positive thermophiles, coupled with the kinetic and thermodynamic consequences of surviving at elevated temperatures, makes them ideal candidates for developing new mathematical models and designing innovative next-generation biotechnologies. KEY CONCEPTS Anaerobe: organism that does not require oxygen for growth. Chemoautotroph: organism that obtains energy by oxidizing inorganic electron donors. Convergent Evolution: process in which organisms which are not closely related independently evolve similar traits due to adapting to similar ecological niches and/or environments. Dissimilatory Metal Reduction: reduction of a metal or metalloid that uses electrons from oxidized organic or inorganic electron donors. Exoelectrogen: microorganism that performs dissimilatory metal reduction via extracellular electron transfer. Extremophiles: organisms that thrive in physical or geochemical conditions that are considered detrimental to most life on Earth. Homoplasy: a character shared by a set of species that is not shared by a common ancestor Non-synonymous Substitutions (Ka): a substitution of a nucleotide that changes a codon sequence resulting in a change in the amino acid sequence of a protein. Synonymous Substitutions (Ks): a substitution of a nucleotide that may change a codon sequence, but results in no change in the amino acid sequence of a protein. Thermophiles: a specific group of extremophiles that survive and operate at temperatures ∼50–125°C.
Can cognitive leisure activity prevent cognitive decline in older adults? A systematic review of intervention studies

The aims of this systematic review were to investigate what kind of cognitive leisure activities have been used in intervention studies targeting older adults, and whether these activities improve cognitive function or inhibit cognitive decline. Based on the PRISMA declaration, we searched keywords using three electronic databases: PubMed, PsycINFO and PsycARTICLES. Intervention studies involving cognitive leisure activities with cognitive assessments set as outcomes were included. We regarded cognitive leisure activities as activities for enjoyment or well‐being that cause intellectual stimulation (e.g. reading, playing board games). To investigate the influence of each activity on cognitive domains, multicomponent programs (e.g. combined music and art) were excluded. In total, 20 studies were included in the evaluation. Consequently, intervention studies related to arts, writing, board games, reading, handicrafts, a crossword puzzle and learning computer skills were identified. Of the 20 studies, 13 showed improvement in some cognitive domain. In 12 of these 13 studies, the intervention effects were not observed in a specific cognitive domain; rather, the intervention effects were observed across multiple cognitive domains and on working memory. The results of the present review suggest that cognitive function in older adults can be improved through cognitive leisure activity interventions. Activities related to learning new skills, that cause strong intellectual stimulation and that include communication elements were considered particularly effective tools. However, as the number of studies is small, more high‐quality research needs to be accumulated. Geriatr Gerontol Int 2019; 19: 469–482.
Energy-Efficient Resource Allocation in Multi-Cell OFDMA Systems with Limited Backhaul Capacity

We study resource allocation for energy-efficient communication in multi-cell orthogonal frequency division multiple access (OFDMA) downlink networks with cooperative base stations (BSs). We formulate the resource allocation problem for joint BS zero-forcing beamforming (ZFBF) transmission as a non-convex optimization problem which takes into account the circuit power consumption, the limited backhaul capacity, and the minimum required data rate. We transform the considered problem in fractional form into an equivalent optimization problem in subtractive form, which enables the derivation of an efficient iterative resource allocation algorithm. In each iteration, a low-complexity suboptimal semi-orthogonal user selection policy is computed. Besides, by using the concept of perturbation function, we show that in the considered systems under some general conditions, the duality gap with respect to the power optimization variables is zero despite the non-convexity of the primal problem. Thus, dual decomposition can be used in each iteration to derive an efficient closed-form power allocation solution for maximization of the energy efficiency of data transmission (bit/Joule delivered to the users). Simulation results illustrate that the proposed iterative resource allocation algorithm converges in a small number of iterations, and unveil the trade-off between energy efficiency, network capacity, and backhaul capacity: (1) In the low transmit power regime, an algorithm which achieves the maximum spectral efficiency may also achieve the maximum energy efficiency; (2) a high spectral efficiency does not necessarily result in a high energy efficiency; (3) spectral efficiency is always limited by the backhaul capacity; (4) energy efficiency increases with the backhaul capacity only until the maximum energy efficiency is achieved.
A Soft-Pruning Method Applied During Training of Spiking Neural Networks for In-memory Computing Applications

Inspired from the computational efficiency of the biological brain, spiking neural networks (SNNs) emulate biological neural networks, neural codes, dynamics, and circuitry. SNNs show great potential for the implementation of unsupervised learning using in-memory computing. Here, we report an algorithmic optimization that improves energy efficiency of online learning with SNNs on emerging non-volatile memory (eNVM) devices. We develop a pruning method for SNNs by exploiting the output firing characteristics of neurons. Our pruning method can be applied during network training, which is different from previous approaches in the literature that employ pruning on already-trained networks. This approach prevents unnecessary updates of network parameters during training. This algorithmic optimization can complement the energy efficiency of eNVM technology, which offers a unique in-memory computing platform for the parallelization of neural network operations. Our SNN maintains ~90% classification accuracy on the MNIST dataset with up to ~75% pruning, significantly reducing the number of weight updates. The SNN and pruning scheme developed in this work can pave the way toward applications of eNVM based neuro-inspired systems for energy efficient online learning in low power applications.
Radar-only ego-motion estimation in difficult settings via graph matching

Radar detects stable, long-range objects under variable weather and lighting conditions, making it a reliable and versatile sensor well suited for ego-motion estimation. In this work, we propose a radar-only odometry pipeline that is highly robust to radar artifacts (e.g., speckle noise and false positives) and requires only one input parameter. We demonstrate its ability to adapt across diverse settings, from urban UK to off-road Iceland, achieving a scan matching accuracy of approximately 5.20 cm and 0.0929 deg when using GPS as ground truth (compared to visual odometry’s 5.77 cm and 0.1032 deg). We present algorithms for key point extraction and data association, framing the latter as a graph matching optimization problem, and provide an in-depth system analysis.
Developments in Transduction, Connectivity and AI/Machine Learning for Point-of-Care Testing

We review some emerging trends in transduction, connectivity and data analytics for Point-of-Care Testing (POCT) of infectious and non-communicable diseases. The patient need for POCT is described along with developments in portable diagnostics, specifically in respect of Lab-on-chip and microfluidic systems. We describe some novel electrochemical and photonic systems and the use of mobile phones in terms of hardware components and device connectivity for POCT. Developments in data analytics that are applicable for POCT are described with an overview of data structures and recent AI/Machine learning trends. The most important methodologies of machine learning, including deep learning methods, are summarised. The potential value of trends within POCT systems for clinical diagnostics within Lower Middle Income Countries (LMICs) and the Least Developed Countries (LDCs) are highlighted.
Structure and Dynamics of Ferroelectric Domains in Polycrystalline Pb(Fe1/2Nb1/2)O3

A complex domain structure with variations in the morphology is observed at ambient temperature in monoclinic Pb(Fe1/2Nb1/2)O3. Using electron microscopy and piezoresponse force microscopy, it is possible to reveal micrometre-sized wedge, lamellar-like, and irregularly shaped domains. By increasing the temperature, the domain structure persists up to 80 °C, and then starts to disappear at around 100 °C due to the proximity of the ferroelectric–paraelectric phase transition, in agreement with macroscopic dielectric measurements. In order to understand to what degree domain switching can occur in the ceramic, the mobility of the domain walls was studied at ambient temperature. The in situ poling experiment performed using piezoresponse force microscopy resulted in an almost perfectly poled area, providing evidence that all types of domains can be easily switched. By poling half an area with 20 V and the other half with −20 V, two domains separated by a straight domain wall were created, indicating that Pb(Fe1/2Nb1/2)O3 is a promising material for domain-wall engineering.