Miracle-dz/UniFAR-FTUs huggingface dataset:
On the Energy Efficiency of MIMO Hybrid Beamforming for Millimeter-Wave Systems With Nonlinear Power Amplifiers

Multiple-input multiple-output (MIMO) millimeter-wave (mm-wave) systems are vulnerable to hardware impairments due to operating at high frequencies and employing a large number of radio-frequency hardware components. In particular, nonlinear power amplifiers (PAs) employed at the transmitter distort the signal when operated close to saturation due to energy efficiency considerations. In this paper, we study the performance of an MIMO mm-wave hybrid beamforming scheme in the presence of nonlinear PAs. First, we develop a statistical model for the transmitted signal in such systems and show that the spatial direction of the inband distortion is shaped by the beamforming filter. This suggests that even in the large antenna regime, where narrow beams can be steered toward the receiver, the impact of nonlinear PAs should not be ignored. Then, by employing a realistic power consumption model for the PAs, we investigate the tradeoff between spectral and energy efficiency in such systems. Our results show that increasing the transmit power level when the number of transmit antennas grows large can be counter-effective in terms of energy efficiency. Furthermore, using numerical simulation, we show that when the transmit power is large, analog beamforming leads to higher spectral and energy efficiency compared to digital and hybrid beamforming schemes.
Tumor-associated macrophages in human breast cancer produce new monocyte attracting and pro-angiogenic factor YKL-39 indicative for increased metastasis after neoadjuvant chemotherapy

ABSTRACT In breast cancer, the tumor microenvironment plays a critical role in the tumor progression and responses to therapy. Tumor-associated macrophages (TAMs) are major innate immune cells in tumor microenvironment that regulate intratumoral immunity and angiogenesis by secretion of cytokines, growth factors as well as chitinase-like proteins (CLPs), that combine properties of cytokines and growth factors. YKL-39 is a chitinase-like protein found in human and absent in rodents, and its expression in TAMs and role in breast cancer progression was not studied to date. Here for the first time we demonstrate that YKL-39 is expressed on TAMs, predominantly positive for stabilin-1, but not by malignant cells or other stromal cells in human breast cancer. TGF-beta in combination with IL-4, but not IL-4 alone was responsible of the stimulation of the production of YKL-39 in human primary macrophages. Mechanistically, stabilin-1 directly interacted with YKL-39 and acted as sorting receptor for targeting YKL-39 into the secretory pathway. Functionally, purified YKL-39 acted as a strong chemotactic factor for primary human monocytes, and induced angiogenesis in vitro. Elevated levels of YKL-39 expression in tumors after neoadjuvant chemotherapy (NAC) were predictive for increased risk of distant metastasis and for poor response to NAC in patients with nonspecific invasive breast carcinoma. Our findings suggest YKL-39 as a novel therapeutic target, and blocking of its activity can be combined with NAC in order to reduce the risk of metastasis in breast cancer patients.
Experimental Trypanosoma evansi infection in donkeys : hematological , biochemical and histopathological changes

Five adult donkeys were experimentally infected with Brazilian strain of Trypanosoma evansi originally isolated from a naturally infected dog to study the hematological biochemical and histopathological alterations during the evolution of the disease. The course of the experimental infection was followed up to 145 days. Hematological analyses of the infected donkeys revealed a marked decline in hemoglobin, packed-cell volume, and erythrocyte count. Anemia was observed after successive peaks of parasitemia. Biochemical analyses showed increased levels of icterus index, serum globulins and decreased serum albumin and glucose values. All infected donkeys revealed enlargement of spleen and its white pulp, enlargement of mediastinal lymph nodes and lungs congestion. The main histopathological features consisted of meningoencephalitis. Demyelination in some areas of the cerebellum pediculus and neuropil vacuolization were observed. This study showed that donkeys infected with a Brazilian strain of T. evansi developed a chronic disease.
Multi-level Hybrid Cache: Impact and Feasibility

Storage class memories, including flash, has been attracting much attention as promising candidates fitting into in today's enterprise storage systems. In particular, since the cost and performance characteristics of flash are in-between those of DRAM and hard disks, it has been considered by many studies as an secondary caching layer underneath main memory cache. However, there has been a lack of studies of correlation and interdependency between DRAM and flash caching. This paper views this problem as a special form of multi-level caching, and tries to understand the benefits of this multi-level hybrid cache hierarchy. We reveal that significant costs could be saved by using Flash to reduce the size of DRAM cache, while maintaing the same performance. We also discuss design challenges of using flash in the caching hierarchy and present potential solutions.
A Di-D-Fructose Dianhydride-Enriched Caramel Modulates Pig Fecal Microbiota Composition

A correlation has been previously described between bifidobacteria counts before and after the use of a dietary additive in human studies. However, to our knowledge no information on this topic has yet been reported in animals, and no information exists either on similar possible correlations of bacterial groups other than bifidobacteria. The potential prebiotic effects of di-D-fructose dianhydride (DFA)-enriched caramels have been previously reported in laboratory animals, poultry and pigs. In the present work, twelve growing male castrated pigs (41.8 ± 1.9 kg mean BW) were fed in succession on a control (no additive) or DFA-enriched caramel (20 g/kg) containing diets. Another group of 10 pigs (38.0 ± 3.7 kg mean BW) fed on a control diet without any additive was used as negative control. Bacterial log10 number of copies of the 16S rRNA gene was determined in fecal samples by using qPCR. Increased (P10 number of copies were determined in fecal samples of pigs fed on the caramel containing diet compared with non-caramel controls. In addition, for all bacterial groups studied microbiological values co-variated with initial counts and, except for enterobacteria, variations in the fecal bacterial numbers after caramel supplementation correlated (P< 0.05) with the fecal numbers before supplementation. In conclusion, the supplementation of pig diets with DFA-enriched caramels induced significant increases in the fecal number of copies of bacterial groups regarded as beneficial, and variations in the fecal number of copies correlated with the initial fecal number of copies.
A 14-ENOB Delta-Sigma-Based Readout Architecture for ECoG Recording Systems

This paper presents a delta-sigma based readout architecture targeting electrocortical recording in brain stimulation applications. The proposed architecture can accurately record a peak input signal up to 240 mV in a power-efficient manner without saturating or employing offset rejection techniques. The readout architecture consists of a delta-sigma modulator with an embedded analog front-end. The proposed architecture achieves a total harmonic distortion of −95 dB by employing a current-steering DAC and a multi-bit quantizer implemented as a tracking ADC. A system prototype is implemented in a <inline-formula> <tex-math notation="LaTeX">$0.18~\mu \text{m}$ </tex-math></inline-formula> CMOS triple-well process and has a total power consumption of <inline-formula> <tex-math notation="LaTeX">$54~\mu \text{W}$ </tex-math></inline-formula>. Measurement results, across 10 packaged samples, show approximately 14-ENOB over a 300Hz bandwidth with an input referred noise of <inline-formula> <tex-math notation="LaTeX">$5.23~\mu \text{V}_{\text {rms}}$ </tex-math></inline-formula>, power-supply/common-mode rejection ratio of 100 dB/98 dB and an input impedance larger than 94 <inline-formula> <tex-math notation="LaTeX">$\text{M}\Omega $ </tex-math></inline-formula>.
Linear Groups Definable in o-Minimal Structures☆

We study subgroups G of GL(n, R) definable in o-minimal expansions M = (R, +, · ,…) of a real closed field R. We prove several results such as: (a) G can be defined using just the field structure on R together with, if necessary, power functions, or an exponential function definable in M. (b) If G has no infinite, normal, definable abelian subgroup, then G is semialgebraic. We also characterize the definably simple groups definable in o-minimal structures as those groups elementarily equivalent to simple Lie groups, and we give a proof of the Kneser–Tits conjecture for real closed fields.
Microbial Community Structure and Associations During a Marine Dinoflagellate Bloom

Interactions between microorganisms and algae during bloom events significantly impacts their physiology, alters ambient chemistry, and shapes ecosystem diversity. The potential role these interactions have in bloom development and decline are also of particular interest given the ecosystem impacts of algal blooms. We hypothesized that microbial community structure and succession is linked to specific bloom stages, and reflects complex interactions among taxa comprising the phycosphere environment. This investigation used pyrosequencing and correlation approaches to assess patterns and associations among bacteria, archaea, and microeukaryotes during a spring bloom of the dinoflagellate Alexandrium catenella. Within the bacterial community, Gammaproteobacteria and Bacteroidetes were predominant during the initial bloom stage, while Alphaproteobacteria, Cyanobacteria, and Actinobacteria were the most abundant taxa present during bloom onset and termination. In the archaea biosphere, methanogenic members were present during the early bloom period while the majority of species identified in the late bloom stage were ammonia-oxidizing archaea and Halobacteriales. Dinoflagellates were the major eukaryotic group present during most stages of the bloom, whereas a mixed assemblage comprising diatoms, green-algae, rotifera, and other microzooplankton were present during bloom termination. Temperature and salinity were key environmental factors associated with changes in bacterial and archaeal community structure, respectively, whereas inorganic nitrogen and inorganic phosphate were associated with eukaryotic variation. The relative contribution of environmental parameters measured during the bloom to variability among samples was 35.3%. Interaction analysis showed that Maxillopoda, Spirotrichea, Dinoflagellata, and Halobacteria were keystone taxa within the positive-correlation network, while Halobacteria, Dictyochophyceae, Mamiellophyceae, and Gammaproteobacteria were the main contributors to the negative-correlation network. The positive and negative relationships were the primary drivers of mutualist and competitive interactions that impacted algal bloom fate, respectively. Functional predictions showed that blooms enhance microbial carbohydrate and energy metabolism, and alter the sulfur cycle. Our results suggest that microbial community structure is strongly linked to bloom progression, although specific drivers of community interactions and responses are not well understood. The importance of considering biotic interactions (e.g., competition, symbiosis, and predation) when investigating the link between microbial ecological behavior and an algal bloom’s trajectory is also highlighted.
4 D Gradient Based Phase Unwrapping for PC-MR Flow Data

Introduction: 4D PC MRI has emerged as a promising approach for hemodynamic evaluation of larger vascular territories. One of the major problems associated with volumetric phase contrast MRI is the large dynamic range of velocities of interest and the potential risk of velocity aliasing in areas of higher velocities. While correcting a wrapped voxel is easily accomplished by adding or subtracting multiples of 2π, determining which voxels are wrapped is challenging. There is a large body of research on the phase unwrapping problem, spanning many different imaging modalities and generally following a path-based or least-squares cost function based algorithm [1]. Many of the path-following methods are challenged with regular PC MR data that contain noise, sharp jumps at vessel walls between static and moving spins, or undersampling artefacts in accelerated acquisitions. The vast majority of phase unwrapping algorithms operate in 2 dimensions, with some approaches for processing in 3 dimensions [2], or in the temporal dimension [3], or a combination of 2D and temporal dimension [4]. Here we demonstrate a novel phase unwrapping method that utilizes a gradient approach in 4 dimensions, space and time. Algorithm: Blood flow through a vessel is inherently continuous in space and time, so as voxel size and temporal resolution approach zero, the gradient between voxels in these directions also approach zero. As voxel size and temporal resolution increase, the gradients involved become larger and the process of differentiating normal flow patterns from those with wrapped phase values becomes more challenging.
Competing Prediction Algorithms

Prediction is a well-studied machine learning task, and prediction algorithms are core ingredients in online products and services. Despite their centrality in the competition between online companies who offer prediction-based products, the strategic use of prediction algorithms remains unexplored. The goal of this paper is to examine strategic use of prediction algorithms. We introduce a novel game-theoretic setting that is based on the PAC learning framework, where each player (aka a prediction algorithm at competition) seeks to maximize the sum of points for which it produces an accurate prediction and the others do not. We show that algorithms aiming at generalization may wittingly miss-predict some points to perform better than others on expectation. We analyze the empirical game, i.e. the game induced on a given sample, prove that it always possesses a pure Nash equilibrium, and show that every better-response learning process converges. Moreover, our learning-theoretic analysis suggests that players can, with high probability, learn an approximate pure Nash equilibrium for the whole population using a small number of samples.
PD-L1 expression is a prognostic factor in subgroups of gastric cancer patients stratified according to their levels of CD8 and FOXP3 immune markers

ABSTRACT Current studies aiming at identifying single immune markers with prognostic value have limitations in the context of complex antitumor immunity and cancer immune evasion. Here, we show how the integration of several immune markers influences the predictions of prognosis of gastric cancer (GC) patients. We analyzed Tissue Microarray (TMA) by multiplex immunohistochemistry and measured the expression of immune checkpoint molecule PD-L1 together with antitumor CD8 T cells and immune suppressive FOXP3 Treg cells in a cohort of GC patients. Unsupervised hierarchical clustering analysis of these markers was used to define correlations between CD8 T, FOXP3 Treg and PD-L1 cell densities. We found that FOXP3 and PD-L1 densities were elevated while CD8 T cells were decreased in tumor tissues compared to their adjacent normal tissues. However, patient stratification based on each one of these markers individually did not show significant prognostic value on patient survival. Conversely, combination of the ratios of CD8/FOXP3 and CD8/PD-L1 enabled the identification of patient subgroups with different survival outcomes. As such, high densities of PD-L1 in patients with high CD8/FOXP3 and low CD8/PD-L1 ratios correlated with increased survival. Collectively, this work demonstrates the need for the integration of several immune markers to obtain more meaningful survival prognosis and patient stratification. In addition, our work provides insights into the complex tumor immune evasion and immune regulation by the tumor-infiltrating effector and suppressor cells, informing on the best use of immunotherapy options for treating patients.
Innovation in Systems of Care in Acute Phase of Ischemic Stroke. The Experience of the Catalan Stroke Programme

Stroke, and mainly ischemic stroke, is the second cause of death and disability. To confront the huge burden of this disease, innovative stroke systems of care are mandatory. This requires the development of national stroke plans to offer the best treatment to all patients eligible for reperfusion therapies. Key elements for success include a high level of organization, close cooperation with emergency medical services for prehospital assessment, an understanding of stroke singularity, the development of preassessment tools, a high level of commitment of all stroke teams at Stroke Centres, the availability of a disease-specific registry, and local government involvement to establish stroke care as a priority. In this mini review, we discuss recent evidence concerning different aspects of stroke systems of care and describe the success of the Catalan Stroke Programme as an example of innovation. In Catalonia, reperfusion treatment rates have increased in recent years and currently are among the highest in Europe (17.3% overall, 14.3% for IVT, and 6% for EVT in 2016).
Security Performance Analysis of Physical Layer over Fisher-Snedecor 𝐹 Fading Channels

In this letter, the performance analysis of physical layer security over Fisher-Snedecor $\mathcal{F}$ fading channels is investigated. In particular, the average secrecy capacity (ASC), the secure outage probability (SOP), the lower bound of the SOP (SOP$^L$), and the strictly positive secure capacity (SPSC) are derived in exact closed-from expressions. The Fisher-Snedecor $\mathcal{F}$ fading channel is a composite of multipath/shadowed fading that are represented by the Nakagami-$m$ distribution. Moreover, it provides close results to the practical measurements than the generalised $K$ ($K_G$) fading channels. To validate our analysis, the numerical results are affirmed by the Monte Carlo simulations.
Developing a product costing model to investigate and propose operational improvements-A case study of a small-sized manufacturing company Mattias Hallersbo

A company’s competitiveness is not only dependent on competitive prices but also on continuous cost control. This includes the ability to control and evaluate the cost of operational processes and their effect on product margins. A foundation for succeeding with such cost control, and thus enabling high competiveness, is to have precise product costing models. However, studies show that within small and medium-sized enterprises (SMEs), many companies’ product costing models lack precision. Additionally, little academic attention has been paid to product costing methods in the SMEs segment. As such, there is both an existing problem for SMEs considering the area of product costing models, as well as a lack of academic research that could work as a basis for solving that problem. This study’s purpose was to investigate the concept of product costing in SMEs. The focus was to increase knowledge of the suitability of different product costing methods in SMEs as well as how such a method can lead to improvements. The purpose was achieved by conducting a case study at a small-sized Swedish company operating as a manufacturer in the fast-moving consumer goods industry. Both qualitative and quantitative data was collected by conducting time studies, factory observations and interviews as well as from internal documents and databases. This study showed that a suitable and high-precision product costing model is best achieved by letting the characteristics of the company drive the characteristics of the model and focusing on enabling as many costs as possible to be treated as direct costs. This is in turn achieved by keeping a problem-driven approach towards the development of the product costing model. This study furthermore showed that the SMEs’ level of maturity in terms of financial health and financial functions, as well as the SMEs’ operational focus, are important factors when determining the suitability of product costing methods. Moreover, this study shows that substantial improvements can be identified based on the outcomes of suitable and precise product costing model. For the case company, the most suitable product costing model was the full cost absorption model and moreover to create two models. The outcomes of these models worked as a basis for an action plan that included a set of operational improvements, of which the most substantial were to move outsourced production and inventory in-house as well as to scale down the usage of several freight companies. Key-words: product costing, full costing, fast-moving consumer goods industry, process mapping, product costing in SMEs
Feature Engineering for Second Language Acquisition Modeling

Knowledge tracing serves as a keystone in delivering personalized education. However, few works attempted to model students’ knowledge state in the setting of Second Language Acquisition. The Duolingo Shared Task on Second Language Acquisition Modeling provides students’ trace data that we extensively analyze and engineer features from for the task of predicting whether a student will correctly solve a vocabulary exercise. Our analyses of students’ learning traces reveal that factors like exercise format and engagement impact their exercise performance to a large extent. Overall, we extracted 23 different features as input to a Gradient Tree Boosting framework, which resulted in an AUC score of between 0.80 and 0.82 on the official test set.
Works Title Biomarkers of Response to Smoking Cessation Pharmacotherapies : Progress to Date Permalink

For the past 30 years, research examining predictors of successful smoking cessation treatment response has focused primarily on clinical variables, such as levels of tobacco dependence, craving, and self-efficacy. However, recent research has begun to determine biomarkers (such as genotype, nicotine and metabolite levels, and brain imaging findings) that may have utility in predicting smoking cessation. For genotype, genes associated with nicotinic acetylcholine receptors (nAChRs) and related proteins have been found to predict response to first-line medications (e.g. nicotine replacement therapy [NRT], bupropion, or varenicline) or quitting over time without a controlled treatment trial. For nicotine and metabolite levels, function of the cytochrome P450 2A6 liver enzyme, which can be assessed with the nicotine metabolite ratio or via genotype, has been found to predict response, with slow nicotine metabolizers having less severe nicotine dependence and a greater likelihood of quitting with NRT than normal metabolizers. For brain imaging, decreased activation of brain regions associated with emotion regulation and increased connectivity in emotion regulation networks, increased responsiveness to pleasant cues, and altered activation with the Stroop effect have been found in smokers who quit with the first-line medications listed above or counseling. In addition, our group recently demonstrated that lower pre-treatment brain nAChR density is associated with a greater chance of quitting smoking with NRT or placebo. Several of these studies found that specific biomarkers may provide additional information for predicting response beyond subjective symptom or rating scale measures, thereby giving an initial indication that biomarkers may, in the future, be useful for guiding smoking cessation treatment intensity, duration, and type.
Reconfiguring Minimum Dominating Sets: The γ-Graph of a Tree

Abstract We consider γ-graphs, which are reconfiguration graphs of the minimum dominating sets of a graph G. We answer three open questions about γ- graphs of trees by providing upper bounds on the maximum degree, the diameter, and the number of minimum dominating sets. The latter gives an upper bound on the order of the γ-graph.