Miracle-dz/UniFAR-FTUs huggingface dataset:
The Cell Cycle Browser: an interactive tool for visualizing, simulating, and perturbing cell cycle progression

SUMMARY The cell cycle is driven by precise temporal coordination among many molecular activities. To understand and explore this process, we developed the Cell Cycle Browser (CCB), an interactive web interface based on real-time reporter data collected in proliferating human cells. This tool facilitates visualizing, simulating, and predicting the outcomes of perturbing cell cycle parameters. Time-series traces from individual cells can be combined to build a multi-layered timeline of molecular activities. Users can simulate the cell cycle using computational models that capture the dynamics of molecular activities and phase transitions. By adjusting individual expression levels and strengths of molecular relationships, users can predict effects on the cell cycle. Virtual assays, such as growth curves and flow cytometry, provide familiar outputs to compare cell cycle behaviors for data and simulations. The CCB serves to unify our understanding of cell cycle dynamics and provides a platform for generating hypotheses through virtual experiments. HIGHLIGHTS Users can stack and align single-cell traces for different molecular reporters Computational models with adjustable parameters simulate cell cycle progression Virtual growth curves and flow cytometry assays predict cell cycle behaviors
High-Gain Antipodal Vivaldi Antenna Surrounded by Dielectric for Wideband Applications

In this communication, an antipodal Vivaldi antenna surrounded by dielectric (AVA-SD) is proposed for wideband applications such as microwave and millimeter-wave imaging, see-through walls, and radio astronomy. The main features of the proposed AVA-SD are wideband high gain, high front-to-back ratio, corrected the E-plane tilt of beam at wide bandwidth, narrow half-power beamwidth, and low sidelobe and cross-polarization levels. A prototype of the proposed AVA-SD is fabricated, and its performance is simulated and measured demonstrating operating frequency bandwidth from 5 to 50 GHz. The designed AVA-SD has overall size of <inline-formula> <tex-math notation="LaTeX">$31.6\times110$ </tex-math></inline-formula> mm<sup>2</sup>.
A Data Imputation Model in Phasor Measurement Units Based on Bagged Averaging of Multiple Linear Regression

Synchrophasor data from the phasor measurement unit (PMU) indicate the health of the electrical system. However, the PMU performance relies entirely on a supported communication network. The existing communication approaches do not guarantee the error-free channel for the PMU network. Meanwhile, the mean or median approaches are commonly used to impute the missing value. These methods, however, fail to recover some valuable frequency events. In this paper, we first proved the multiple linear regression features in many synchronized frequency data streams in the short-time window. Then, we proposed the Bagged Averaging of Multiple Linear Regression model, which handles and fulfills the missing values in synchronized frequency data measurement fast and efficiently. This technique was based on the ensemble learning by bootstrapping and averaging many multiple linear regressions to predict the missing values. Various experiments on the synchronized frequency measurement data from the Texas synchrophasor network have demonstrated the effectiveness of our proposed approach in recovering the missing frequency events. Our proposed approach guarantees the performance of real-time wide area monitoring system applications, such as frequency analysis or stability monitoring and trending.
A Full Ka-Band Power Amplifier With 32.9% PAE and 15.3-dBm Power in 65-nm CMOS

This paper presents a CMOS broadband millimeter wave power amplifier (PA) based on magnetically coupled resonator (MCR) matching network. The MCR matching network is analyzed theoretically. Design method for MCR-based broadband PA is proposed. For the PA’s output matching network, the inductance ratio should be equal to the load/source resistance ratio to achieve broadband impedance transformation. And the coupling coefficient (<inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula>) of the MCR can be determined from the no gain ripple condition. Fabricated in 65-nm CMOS process, the PA chip achieves 32.9% peak power added efficiency, 15.3-dBm saturated output power (<inline-formula> <tex-math notation="LaTeX">$P_{\mathrm {sat}}$ </tex-math></inline-formula>), and 12.9-dBm output 1-dB compression point (<inline-formula> <tex-math notation="LaTeX">$P_{\mathrm {1\,dB}}$ </tex-math></inline-formula>). The fractional bandwidth of the PA is 63.3% from 21.6 to 41.6 GHz, which covers the full Ka-band (26.5 to 40 GHz).
The Bidirectional Relationship Between Obstructive Sleep Apnea and Metabolic Disease

Obstructive sleep apnea (OSA) is a common sleep disorder, effecting 17% of the total population and 40–70% of the obese population (1, 2). Multiple studies have identified OSA as a critical risk factor for the development of obesity, diabetes, and cardiovascular diseases (3–5). Moreover, emerging evidence indicates that metabolic disorders can exacerbate OSA, creating a bidirectional relationship between OSA and metabolic physiology. In this review, we explore the relationship between glycemic control, insulin, and leptin as both contributing factors and products of OSA. We conclude that while insulin and leptin action may contribute to the development of OSA, further research is required to determine the mechanistic actions and relative contributions independent of body weight. In addition to increasing our understanding of the etiology, further research into the physiological mechanisms underlying OSA can lead to the development of improved treatment options for individuals with OSA.
A New SOLT Calibration Method for Leaky On-Wafer Measurements Using a 10-Term Error Model

We present a new short-open-load-thru (SOLT) calibration method for on-wafer S-parameter measurements. The new calibration method is based on a 10-term error model which is a simplified version of the 16-term error model. Compared with the latter, the former ignores all signal leakages except the ones between the probes. Experimental results show that this is valid for modern vector network analyzers. The advantage of using this 10-term error model is that the exact values of all error terms can be obtained by using the same calibration standards as the conventional SOLT method. This avoids not only the singularity problem with approximate methods, such as least squares, but also the usage of additional calibration standards. In this paper, we first demonstrate how the 10-term error model is developed, and then, the experimental verification of the theory is given. Finally, a practical application of the error model using a 10-dB attenuator from 140 to 220 GHz is presented. Compared with the conventional SOLT calibration method without crosstalk corrections, the new method shows approximately 1-dB improvement in the transmission coefficients of the attenuator at 220 GHz.
Microglia Response During Parkinson’s Disease: Alpha-Synuclein Intervention

The discovery of the central role played by the protein alpha-synuclein in Parkinson’s disease and other Lewy body brain disorders has had a great relevance in the understanding of the degenerative process occurring in these diseases. In addition, during the last two decades, the evidence suggesting an immune response in Parkinson’s disease patients have multiplied. The role of the immune system in the disease is supported by data from genetic studies and patients, as well as from laboratory animal models and cell cultures. In the immune response, the microglia, the immune cell of the brain, will have a determinant role. Interestingly, alpha-synuclein is suggested to have a central function not only in the neuronal events occurring in Parkinson’s disease, but also in the immune response during the disease. Numerous studies have shown that alpha-synuclein can act directly on immune cells, such as microglia in brain, initiating a sterile response that will have consequences for the neuronal health and that could also translate in a peripheral immune response. In parallel, microglia should also act clearing alpha-synuclein thus avoiding an overabundance of the protein, which is crucial to the disease progression. Therefore, the microglia response in each moment will have significant consequences for the neuronal fate. Here we will review the literature addressing the microglia response in Parkinson’s disease with an especial focus on the protein alpha-synuclein. We will also reflect upon the limitations of the studies carried so far and in the therapeutic possibilities opened based on these recent findings.
Structural hierarchy confers error tolerance in biological materials

Significance Structural hierarchy is ubiquitous in nature and an emerging trend in engineered materials. Despite their many virtues, hierarchical materials also add complexity and dramatically increase the opportunities for random errors in assembly. Nonetheless, highly hierarchical tissues have evolved many times in diverse lineages; this prevalence suggests a common source of mechanical robustness. In this work, we introduce a tractable, model hierarchical lattice with controllable attributes on each length scale. We find, contrary to intuition, that adding additional levels of structure actually reduces the relative variation in mechanical properties, despite an increase in assembly errors. This finding informs our understanding of the emergence of hierarchically structured biological materials, while also offering a practical heuristic in materials design. Structural hierarchy, in which materials possess distinct features on multiple length scales, is ubiquitous in nature. Diverse biological materials, such as bone, cellulose, and muscle, have as many as 10 hierarchical levels. Structural hierarchy confers many mechanical advantages, including improved toughness and economy of material. However, it also presents a problem: Each hierarchical level adds a new source of assembly errors and substantially increases the information required for proper assembly. This seems to conflict with the prevalence of naturally occurring hierarchical structures, suggesting that a common mechanical source of hierarchical robustness may exist. However, our ability to identify such a unifying phenomenon is limited by the lack of a general mechanical framework for structures exhibiting organization on disparate length scales. Here, we use simulations to substantiate a generalized model for the tensile stiffness of hierarchical filamentous networks with a nested, dilute triangular lattice structure. Following seminal work by Maxwell and others on criteria for stiff frames, we extend the concept of connectivity in network mechanics and find a similar dependence of material stiffness upon each hierarchical level. Using this model, we find that stiffness becomes less sensitive to errors in assembly with additional levels of hierarchy; although surprising, we show that this result is analytically predictable from first principles and thus potentially model independent. More broadly, this work helps account for the success of hierarchical, filamentous materials in biology and materials design and offers a heuristic for ensuring that desired material properties are achieved within the required tolerance.
Caprellid amphipods (Caprella spp.) are vulnerable to both physiological and habitat-mediated effects of ocean acidification

Ocean acidification (OA) is one of the most significant threats to marine life, and is predicted to drive important changes in marine communities. Although OA impacts will be the sum of direct effects mediated by alterations of physiological rates and indirect effects mediated by shifts in species interactions and biogenic habitat provision, direct and indirect effects are rarely considered together for any given species. Here, we assess the potential direct and indirect effects of OA on a ubiquitous group of crustaceans: caprellid amphipods (Caprella laeviuscula and Caprella mutica). Direct physiological effects were assessed by measuring caprellid heart rate in response to acidification in the laboratory. Indirect effects were explored by quantifying caprellid habitat dependence on the hydroid Obelia dichotoma, which has been shown to be less abundant under experimental acidification. We found that OA resulted in elevated caprellid heart rates, suggestive of increased metabolic demand. We also found a strong, positive association between caprellid population size and the availability of OA-vulnerable O. dichotoma, suggesting that future losses of biogenic habitat may be an important indirect effect of OA on caprellids. For species such as caprellid amphipods, which have strong associations with biogenic habitat, a consideration of only direct or indirect effects could potentially misestimate the full impact of ocean acidification.
Posttraumatic Stress Disorder in Patients with Heavy Alcohol Consumption and Alcoholic Hepatitis

BACKGROUND Lifetime prevalence of posttraumatic stress disorder (PTSD) in the general population is reported to be 6.8%. Individuals with alcohol dependence and substance abuse have high prevalence of PTSD. However, the prevalence of PTSD in heavy drinkers with alcoholic hepatitis (AH) is not known.The study's aim was to determine the prevalence of PTSD in heavy drinkers with and without AH. METHODS We screened for PTSD using the Primary Care-PTSD questionnaire among heavy drinkers with (n = 115) and without (n = 64) AH participating in a multicenter observational study in which participants were followed up to 12 months following their enrollment. RESULTS The prevalence of PTSD in heavy drinkers with AH was 34% and was not different from heavy drinking controls without liver disease (34%). In the entire group screened for PTSD, the presence of PTSD was associated with higher alcohol consumption as reported by average drinks per last 30 days and average grams of alcohol consumed per day (p = 0.047 for both tests), but not associated with relapse of heavy drinking or mortality. Similarly, patients with AH and PTSD did not have higher relapse rate or higher mortality compared to patients with AH but no PTSD. CONCLUSIONS Compared to previously reported prevalence in general population, heavy drinking individuals with or without AH have significantly higher prevalence of PTSD. However, PTSD was not associated with higher relapse rate or higher mortality in this population.
High-Level Reliability Evaluation of Reconfiguration-Based Fault Tolerance Techniques

Field Programmable Gate Arrays (FPGAs) offer very efficient fault-tolerance strategies based on partial reconfiguration. These strategies use dedicated spare resources at different levels to replace faulty elements. A method to determine if the targeted level of reliability can be obtained is then required. In this paper, we generalize the reliability estimation formulas for the state-of-the-art fault tolerance techniques based on partial reconfiguration. We use those formulas to estimate the bounds of the different techniques in terms of reliability level and bitstream overhead. This work makes possible to evaluate early in the design-flow the achievable mission time for a given number of faults per time unit. Thanks to its generality, our approach can be derived for future new partial reconfiguration approaches.
Bayesian Semiparametric Multivariate Density Deconvolution

ABSTRACT We consider the problem of multivariate density deconvolution when interest lies in estimating the distribution of a vector valued random variable X but precise measurements on X are not available, observations being contaminated by measurement errors U. The existing sparse literature on the problem assumes the density of the measurement errors to be completely known. We propose robust Bayesian semiparametric multivariate deconvolution approaches when the measurement error density of U is not known but replicated proxies are available for at least some individuals. Additionally, we allow the variability of U to depend on the associated unobserved values of X through unknown relationships, which also automatically includes the case of multivariate multiplicative measurement errors. Basic properties of finite mixture models, multivariate normal kernels, and exchangeable priors are exploited in novel ways to meet modeling and computational challenges. Theoretical results showing the flexibility of the proposed methods in capturing a wide variety of data-generating processes are provided. We illustrate the efficiency of the proposed methods in recovering the density of X through simulation experiments. The methodology is applied to estimate the joint consumption pattern of different dietary components from contaminated 24 h recalls. Supplementary materials for this article are available online.
Calculate joint probability distribution of steady directed cyclic graph with local data and domain casual knowledge

It is desired to obtain the joint probability distribution (JPD) over a set of random variables with local data, so as to avoid the hard work to collect statistical data in the scale of all variables. A lot of work has been done when all variables are in a known directed acyclic graph (DAG). However, steady directed cyclic graphs (DCGs) may be involved when we simply combine modules containing local data together, where a module is composed of a child variable and its parent variables. So far, the physical and statistical meaning of steady DCGs remain unclear and unsolved. This paper illustrates the physical and statistical meaning of steady DCGs, and presents a method to calculate the JPD with local data, given that all variables are in a known single-valued Dynamic Uncertain Causality Graph (S-DUCG), and thus defines a new Bayesian Network with steady DCGs. The so-called single-valued means that only the causes of the true state of a variable are specified, while the false state is the complement of the true state.
Kibo: An Open-Source Fixed-Point Tool-kit for Training and Inference in FPGA-Based Deep Learning Networks

Field-Programmable Gate Arrays (FPGAs) have become an essential component of the deep learning landscape, providing a balance between flexibility, customization, and efficiency. One of the key optimizations afforded by FPGA technology is the ability to customize the bit width of fixed-point weights and activations within deep learning networks. In this paper, we present an open-source tool-kit which allows a researcher to investigate different fixed-point representations and saturating arithmetic operations in Python. The tool-kit over-rides arithmetic and comparison functions commonly used in deep learning structures, allowing a researcher to quickly evaluate the impact of alternative numeric representations. Compared to higher-level frameworks such as Tensorflow or PyTorch, a much wider set of numeric precisions can be modeled. Unlike lower-level C-synthesis tools, our tool-kit is written in Python providing the ability to much more rapidly explore architectural alternatives. Our framework is open-source and is available on-line.
Changes in socioeconomic position among individuals with mental disorders during the economic recession in Portugal: a follow-up of the National Mental Health Survey

Abstract Aims Portugal was one of the European countries most affected by the period of economic recession initiated in 2008. Social inequalities are likely to widen during such periods and disproportionately affect people with mental disorders. The present study aims to compare self-reported changes in indicators of socioeconomic position during the economic recession in Portugal among people with and without mental disorders in the beginning of this period. Three dimensions were assessed, namely employment situation, experiences of financial hardship and subjective social status. Methods Data from the World Mental Health Survey Initiative Portugal (2008/2009) and from the National Mental Health Survey Follow-up (2015/2016) were used (n = 911). Multinomial and logistic recession models were performed to examine the association between the presence of any 12-month mood or anxiety mental disorder in 2008/2009 and indicators of socioeconomic position in 2015/2016. All analyses were adjusted for gender, age, presence of any physical disorder and education at the baseline. Results Participants that had any mental disorder in the beginning of the economic recession reported 2.20 (95% CI 1.31–3.71; P < 0.01) higher odds of financial hardship related to daily life in 2015/2016, when compared with those without any mental disorder, after adjusting for age, gender, education and presence of any physical disorder. The results may also suggest a pattern of increased socioeconomic disadvantage among people with prior mental disorder, despite not reaching statistical significance. Conclusions The results of this study suggest that the economic recession may have contributed to wider social inequalities between people with and without mental disorders. Policies to support these individuals, such as access to treatment and alleviation of financial hardship, should be a priority in times of economic downturn.
Does Online Comprehension Monitoring Make a Unique Contribution to Reading Comprehension in Beginning Readers? Evidence from eye movements

ABSTRACT The goal of this study was to investigate the nature of online comprehension monitoring, its predictors, and its relation to reading comprehension. Questions were concerned with (a) beginning readers’ sensitivity to inconsistencies, (b) predictors of online comprehension monitoring, and (c) the relation of online comprehension monitoring to reading comprehension over and above word reading and listening comprehension. Using eye tracking technology, online comprehension monitoring was measured as the amount of time spent rereading target implausible words and looking back at surrounding contexts. Results from 319 second graders revealed that children spent greater time fixating on inconsistent than consistent words and engaged in more frequent lookbacks. Comprehension monitoring was explained by both word reading and listening comprehension. However, comprehension monitoring did not uniquely predict reading comprehension after accounting for word reading and listening comprehension. These results provide insight into the nature of comprehension monitoring and its role in reading comprehension for beginning readers.
Nanocircuits for a Bio-Implantable System in EEG Signal Acquisitions

Bio-implantable circuits always raise interest because it is already the frontier of overcoming different deficiencies of human body physiological limitations and impairments. They allow, on one hand the operating mode of internal organs, and the contact with outside, at the other hand, thanks to wired and/or wireless architectures. EEG (Electroencephalogram) signals are an example of a topic where scientists and researchers have been working to use them for preventing general and specific pathologies regarding namely central nervous system and other physiological aspects. This paper illustrates preliminary results of nanocircuits used for a bio-implantable neuro-case encompassing circuits useful for signal processing and measurement.