Miracle-dz/UniFAR-FTUs huggingface dataset:
Dual-Band CMOS Down-Conversion Mixer Adopting Band-Switchable Transformer

In this brief, a dual-band complementary metal–oxide–semiconductor (CMOS) down-conversion mixer is presented, which supports the fifth-generation new radio frequency bands of 26–30 GHz and 37–40 GHz. In the proposed design, the transformer-based inductance adjustment techniques are utilized to handle dual-band radio frequency and local oscillator (LO) signals for performance optimization. The proposed design is fabricated using a 65-nm CMOS process. With an identical LO power of +5 dBm, the implemented down-conversion mixer attains conversion gains of 7.1 dB and 5.1 dB, noise figures of 9.6 dB and 11.4 dB, input 1-dB compression points of–14.7 dBm and–11 dBm, and input third-order intercept points of–5.1 dBm and–1.95 dBm for 28 and 39 GHz frequency bands, respectively. The implemented design consumes the current of 6.2 mA with a 1-V supply.
RamanSPy: An open-source Python package for integrative Raman spectroscopy data analysis

Raman spectroscopy is a non-destructive and label-free chemical analysis technique, which plays a key role in the analysis and discovery cycle of various branches of science. Nonetheless, progress in Raman spectroscopic analysis is still impeded by the lack of software, methodological and data standardisation, and the ensuing fragmentation and lack of reproducibility of analysis workflows thereof. To address these issues, we introduce RamanSPy, an open-source Python package for Raman spectroscopic research and analysis. RamanSPy provides a comprehensive library of ready-to-use tools for spectroscopic analysis, which streamlines day-to-day tasks, integrative analyses, as well as novel research and algorithmic development. RamanSPy is modular and open source, not tied to a particular technology or data format, and can be readily interfaced with the burgeoning ecosystem for data science, statistical analysis and machine learning in Python.
Considerations on Testing Secondary Endpoints in Group Sequential Design

ABSTRACT In the fixed sample size design, when the null hypothesis for the primary endpoint is rejected at trial completion, secondary endpoints sometimes are tested at the full alpha level in a prespecified hierarchical order, and this strategy strongly controls the overall Type I error rate. However, in a group sequential setting, this hierarchical testing strategy may not control the overall Type I error rate for the secondary endpoints in the strong sense. Thus, when there is one interim analysis, there are proposals for an alpha spending function for testing secondary endpoints. Motivated by a Phase 3 oncology trial, we explored whether there is a less stringent approach to control the Type I error rate for testing one or more secondary endpoints in a prespecified order for the settings where there are more than one interim analysis.
The role of innate lymphoid cells in chronic rhinosinusitis in children

Natural lymphoid cells belong to the cells of the innate immune system. Their main role is to regulate the immune response to infectious and non-infectious inflammatory stimuli. They play a key role in the etiology of chronic rhinosinusitis (CRS) due to their ability to react quickly and shape the cytokine microenvironment. The development of CRS in children demonstrates the interaction between dysbiosis and the inflammatory response of the respiratory mucosa.
AGS Gastric Cells: Antioxidant Activity and Metabolic Effects of Phenolic Extracts from Different Monocultivar Virgin Olive Oils

The effects of the phenolic compounds of extra virgin olive oil (EVOO) on AGS cells have never been studied so far, which is the aim of this study. The profiles of the main phenolic components in EVOOs, mainly secoiridoid compounds derived from the transformation of oleuropein during the olive milling process, were evaluated and compared. Oils of different origins were evaluated aiming at verifying whether chemical differences in the phenolic composition of the dry extracts played a role in the metabolism and in maintaining the cellular redox state of AGS cells. The following key enzymes of some metabolic pathways were studied: lactate dehydrogenase, enolase, pyruvate kinase, glucose 6-phosphate dehydrogenase, citrate synthase, 3-Hydroxyacyl-CoA dehydrogenase and hexokinase. As confirmed through PCA analysis, pretreatments with the dry extracts of EVOOs at different concentrations appeared to be able to counteract the enzymatic activity alterations due to oxidative stress induced by H2O2 1 mM and 2 mM. The studied phytocomplexes showed the ability to protect AGS cells from oxidative damage and the secoiridoid derivatives from both oleuropein and ligstroside contributed to the observed effects. The results suggested that EVOOs with medium to high concentrations of phenols can exert this protection.
Asymptotic analysis of boundary-effect on strength of concrete

A new size effect model is presented, which deals with the specimen boundary influence on the strength of concrete measured from the maximum load tests. The new boundary effect model shows that the size independent tensile strength and fracture toughness (and then the specific fracture energy) of concrete-like quasi-brittle composites can be conveniently determined from the simple maximum load tests. The common size effect observed using geometrically similar specimens is only a special case of the specimen boundary effect on fracture properties of concrete. The difference and similarity between the current boundary effect model and the common size effect models are discussed and illustrated with concrete results measured from four different sets of geometrically similar specimens. It is shown that the asymptotic analysis of the large plate with a small edge crack, for which the front specimen boundary rather than the specimen size needs to be considered, provides the solution to all the quasi-brittle fracture transition curves, or the size effect.
Intelligent Modeling for Batch Polymerization Reactors with Unknown Inputs

While system identification methods have developed rapidly, modeling the process of batch polymerization reactors still poses challenges. Therefore, designing an intelligent modeling approach for these reactors is important. This paper focuses on identifying actual models for batch polymerization reactors, proposing a novel recursive approach based on the expectation-maximization algorithm. The proposed method pays special attention to unknown inputs (UIs), which may represent modeling errors or process faults. To estimate the UIs of the model, the recursive expectation-maximization (EM) technique is used. The proposed algorithm consists of two steps: the E-step and the M-step. In the E-step, a Q-function is recursively computed based on the maximum likelihood framework, using the UI estimates from the previous time step. The Kalman filter is utilized to calculate the estimates of the states using the measurements from sensor data. In the M-step, analytical solutions for the UIs are found through local optimization of the recursive Q-function. To demonstrate the effectiveness of the proposed algorithm, a practical application of modeling batch polymerization reactors is presented. The performance of the proposed recursive EM algorithm is compared to that of the augmented state Kalman filter (ASKF) using root mean squared errors (RMSEs). The RMSEs obtained from the proposed method are at least 6.52% lower than those from the ASKF method, indicating superior performance.
A Numerical Investigation of the Potential Effects of Aerosol-Induced Warming and Updraft Width and Slope on Updraft Intensity in Deep Convective Clouds

AbstractThe effects of aerosol perturbations on deep convective clouds have received considerable attention in the recent literature, especially from a modeling perspective. The published responses in precipitation amount and updraft strength vary in both sign and magnitude and may be the result of different models and parameterizations. Here, a simple numerical framework is employed to determine the potential effects of warming both below the freezing level (warm invigoration) and above the freezing level (mixed-phase invigoration) due to increased aerosol loading. The role of updraft width and slope in the same framework is also examined, highlighting the relative importance of each factor on the resulting updraft strength. The results show that the potential effects of warm invigoration are 2–3 times larger than for mixed-phase invigoration. However, a relatively small response in updraft velocity to warming is found, especially in comparison with the predicted changes in updraft velocity due to small .
Compliance to modification of risk factors for recurrent myocardial infarction in the long term of the disease: a randomized study

Purpose: to study the relationship between awareness and commitment to modifying risk factors for recurrent myocardial infarction in a long period of the disease. Material & Methods: to study the awareness of risk factors and adherence to secondary prevention of myocardial infarction (MI), a representative sample was created. Of 912 patients treated for myocardial infarction, 333 patients were randomized, taking into account proportional distribution in the population by age (under 65 and over 65 years) and gender. The average age of patients was 62.5±9.8 years: 70,27% of men and 29,73% of women. Patients' awareness of risk factors, the use of preventive measures and adherence to treatment were assessed on the basis of a questionnaire. Statistical processing of the obtained material was carried out using the statistical program STATISTICA 12.5 (StatSoft.Inc). Results are presented as mean and standard deviation (M±s), number of options (n). To compare the qualitative characteristics (frequency tables), the χ2 test and Fisher's exact test were used. All participants were informed about the aims of the study and gave written consent to participate in the study. Results: low awareness (Aw) and commitment (Cm) to the modification of such risk factors for recurrent infarction in a long period of the disease as: reduced fat intake Aw 16,52%, Cm 19,4%; regular consumption of vegetables and fruits Aw 11,41%, Cm 9,7%; smoking cessation Aw 15,92%, Cm 11,04%; decrease in alcohol consumption Aw 16,52%, Cm 10,70%; increased physical activity Aw 14,41%, Cm 12,37%; weight loss with its excess Aw 3,0%, Cm 2,34%; avoidance of stress Aw 28,53%, Cm 18,06%. Although the vast majority of patients received appropriate recommendations from the doctor. Conclusions: low awareness of the possibility of modifying heart disease risk factors is associated with the failure to implement such non-pharmacological measures in secondary prevention after MI: decrease in fat intake (χ2=65,12; p=0,000) and regular consumption of vegetables and fruits (F p=0,000), unwillingness to quit smoking (F p=0,000) and decrease in alcohol consumption (F p=0,000), unwillingness to increase physical activity (χ2=17,61; p=0,000) and reduce weight in case of its excess (F p=0,015), avoiding stress (χ2=27,42; p=0,000).
Neuropathic pain has sex-specific effects on oxycodone seeking and drug-seeking ensembles in the dorsomedial prefrontal cortex

Approximately 50 million Americans suffer from chronic pain, and opioids are commonly prescribed for such individuals. Unfortunately, nearly a quarter of chronic pain patients have reported misusing their prescription. We are investigating the effect of chronic pain on drug-seeking behavior at the neuronal level. Repeated drug-seeking is associated with reactivation of an ensemble of neurons sparsely scattered throughout the dorsomedial prefrontal cortex (dmPFC). Prior research has demonstrated that chronic pain increases intrinsic excitability of dmPFC neurons, which may increase the likelihood of reactivation during drug seeking. We tested the hypothesis that chronic pain would increase oxycodone seeking behavior, and that the pain state would differentially increase intrinsic excitability in dmPFC drug seeking ensemble neurons. TetTag mice self-administered intravenous oxycodone. After 7 days of forced abstinence, a drug seeking session (extinction conditions) was performed and the ensemble was tagged. Mice received spared nerve injury (SNI) to induce chronic pain during the period between a first and second seeking session, and we measured persistence of seeking between the two sessions to determine if the SNI exacerbated seeking. Following the second seeking session we performed electrophysiology on individual neurons within the dmPFC to assess intrinsic excitability of the drug-seeking ensemble and non-ensemble neurons. We found significant sex differences in the effect of SNI on oxycodone seeking and electrophysiology, such that the induction of chronic pain could modulate seeking behavior in mice that have previously self-administered oxycodone prior to injury. Highlights Oxycodone seeking was higher in females following SNI that came after the 10-day SA timeline. An increase in intrinsic excitability was detected among non-ensemble neurons from female mice that received SNI, and this correlated with an increase in seeking behavior.
Leveraging Permutation Testing to Assess Confidence in Positive-Unlabeled Learning Applied to High-Dimensional Biological Datasets

Background Compared to traditional supervised machine learning approaches employing fully labeled samples, positive-unlabeled (PU) learning techniques aim to classify “unlabeled” samples based on a smaller proportion of known positive examples. This more challenging modeling goal reflects many real-world scenarios in which negative examples are not available, posing direct challenges to defining prediction accuracy robustness. While several studies have evaluated predictions learned from only definitive positive examples, few have investigated whether correct classification of a high proportion of known positives (KP) samples from among unlabeled samples can act as a surrogate to indicate a performance. Results In this study, we report a novel methodology combining multiple established PU learning-based strategies to evaluate the potential of KP samples to accurately classify unlabeled samples without using “ground truth” positive and negative labels for validation. To address model robustness, we report the first application of permutation test in PU learning. Multivariate synthetic datasets and real-world high-dimensional benchmark datasets were employed to validate the proposed pipeline with varied underlying ground truth class label compositions among the unlabeled set and different proportions of KP examples. Comparisons between model performance with actual and permutated labels could be used to distinguish reliable from unreliable models. Conclusions Like in fully supervised machine learning, permutation testing offers a means to set a baseline “no-information rate” benchmark in the context of semi-supervised PU learning inference tasks against which model performance can be compared.
Opportunities for Legislative Influence? Latinos and Committee Participation in the U.S. Congress

Abstract In this article, I look at how differences in committee participation help further explain the way Latinos are represented in Congress. I examine levels of participation in four committees in the House of Representatives for the 109th–112th Congresses. I find that Latino committee members participate at greater levels when high Latino saliency legislation is considered, but overall they do not engage in greater committee activity compared to non-Latino members. I also find that a higher percentage of Latinos in a district leads to greater levels of activity among committee members, especially when considering high Latino saliency bills. The results show that Latinos receive substantive representation in committees via district composition, but that descriptive representation is relative and not absolute. These findings may speak to the continued lack of Latino institutional power and the tradeoffs Latino members must consider when deciding where and when to invest legislative effort. Furthermore, the results underscore the importance of institutional context in assessing the link between descriptive and substantive representation.
Poleward Migration of Spatial Asymmetry in Tropical Cyclone Precipitation over the Western North Pacific

Comprehensive understanding of the spatial characteristics of tropical cyclone (TC) precipitation is essential for effective socioeconomic planning and scientific research. The present study examines the spatial asymmetry in TC precipitation over the western North Pacific (WNP) concerning various factors, including latitudes, sea surface temperature (SST), TC intensity, and translation speed, based on satellite observations. The results reveal a significant poleward migration of TC precipitation asymmetry particularly above 15° N. Furthermore, the asymmetry exhibits considerable sensitivity to changes in TC center latitudes and SSTs, characterized by anticlockwise and northeastward migration, respectively. The poleward migration of TC precipitation spatial asymmetry is primarily due to the poleward decreasing SST, increasing vertical wind shear and increasing TC translation speed. These findings contribute to a comprehensive understanding of TC behavior over the WNP and provide valuable insights for disaster preparedness and mitigation efforts.
Dietary Plant Polysaccharides for Cancer Prevention: Role of Immune Cells and Gut Microbiota, Challenges and Perspectives

Dietary plant polysaccharides, one of the main sources of natural polysaccharides, possess significant cancer prevention activity and potential development value in the food and medicine fields. The anti-tumor mechanisms of plant polysaccharides are mainly elaborated from three perspectives: enhancing immunoregulation, inhibiting tumor cell growth and inhibiting tumor cell invasion and metastasis. The immune system plays a key role in cancer progression, and immunomodulation is considered a significant pathway for cancer prevention or treatment. Although much progress has been made in revealing the relationship between the cancer prevention activity of polysaccharides and immunoregulation, huge challenges are still met in the research and development of polysaccharides. Results suggest that certain polysaccharide types and glycosidic linkage forms significantly affect the biological activity of polysaccharides in immunoregulation. At present, the in vitro anti-tumor effects and immunoregulation of dietary polysaccharides are widely reported in articles; however, the anti-tumor effects and in vivo immunoregulation of dietary polysaccharides are still deserving of further investigation. In this paper, aspects of the mechanisms behind dietary polysaccharides’ cancer prevention activity achieved through immunoregulation, the role of immune cells in cancer progression, the role of the mediatory relationship between the gut microbiota and dietary polysaccharides in immunoregulation and cancer prevention are systematically summarized, with the aim of encouraging future research on the use of dietary polysaccharides for cancer prevention.
Goos–Hänchen shift for Gaussian beams impinging on monolayer-MoS2-coated surfaces

We report a detailed theoretical study of the Goos–Hanchen (GH) shift for a fundamental Gaussian beam on the surface coated with monolayer (ML) molybdenum disulfide (MoS2), a promising two-dimensional transition metal dichalcogenide (2D-TMDC) and a direct band-gap semiconductor. A general model has been developed to predict the GH shifts on ML-MoS2-coated surfaces for a light beam with different wavelengths. In contrast to the conventional GH shift, which is generally observed for total internal reflection, here we predict finite spatial and angular GH shift for both partial and total internal reflection conditions. Our analysis revealed that the observation of the giant negative spatial GH shift on MoS2-coated surfaces is attributed to the surface conductivity of the MoS2 ML, something that has never been explored. Furthermore, we find that the GH shifts are dependent on the mode of polarization, the wavelength of incident beam, and the nature of surfaces. This deepens our understanding of the unusual behavior of GH shift near Brewster’s angle as well as the critical angle of incidence. We expect that our findings will lead to several new applications of MoS2 in sensors and device technology.
Development of MWCNT/Magnetite Flexible Triboelectric Sensors by Magnetic Patterning

The fabrication of low-electrical-percolation-threshold polymer composites aims to reduce the weight fraction of the conductive nanomaterial necessary to achieve a given level of electrical resistivity of the composite. The present work aimed at preparing composites based on multiwalled carbon nanotubes (MWCNTs) and magnetite particles in a polyurethane (PU) matrix to study the effect on the electrical resistance of electrodes produced under magnetic fields. Composites with 1 wt. % of MWCNT, 1 wt. % of magnetite and combinations of both were prepared and analysed. The hybrid composites combined MWCNTs and magnetite at the weight ratios of 1:1; 1:1/6; 1:1/12; and 1:1/24. The results showed that MWCNTs were responsible for the electrical conductivity of the composites since the composites with 1 wt. % magnetite were non-conductive. Combining magnetite particles with MWCNTs reduces the electrical resistance of the composite. SQUID analysis showed that MWCNTs simultaneously exhibit ferromagnetism and diamagnetism, ferromagnetism being dominant at lower magnetic fields and diamagnetism being dominant at higher fields. Conversely, magnetite particles present a ferromagnetic response much stronger than MWCNTs. Finally, optical microscopy (OM) and X-ray micro computed tomography (micro CT) identified the interaction between particles and their location inside the composite. In conclusion, the combination of magnetite and MWCNTs in a polymer composite allows for the control of the location of these particles using an external magnetic field, decreasing the electrical resistance of the electrodes produced. By adding 1 wt. % of magnetite to 1 wt. % of MWCNT (1:1), the electric resistance of the composites decreased from 9 × 104 to 5 × 103 Ω. This approach significantly improved the reproducibility of the electrode’s fabrication process, enabling the development of a triboelectric sensor using a polyurethane (PU) composite and silicone rubber (SR). Finally, the method’s bearing was demonstrated by developing an automated robotic soft grip with tendon-driven actuation controlled by the triboelectric sensor. The results indicate that magnetic patterning is a versatile and low-cost approach to manufacturing sensors for soft robotics.
Interpersonelle Psychotherapie (IPT)

Depressionen und andere psychische Störungen werden häufig durch interpersonelle Probleme (wie Konflikte, Rollenwechsel, komplizierte Trauer oder Isolation) ausgelöst oder aufrechterhalten. Die interpersonelle Psychotherapie (IPT) hat sich in vielen Studien als eine wirksame Psychotherapie für Menschen mit derartigen interpersonellen Problemen erwiesen. Dieser Beitrag gibt ein evidenzbasiertes und praxisorientiertes Update zur Wirksamkeit, Durchführung und zu Weiterentwicklungen der IPT.
Local Static Anti-Windup Design With Sign-Indefinite Quadratic Forms

This note proposes static anti-windup gains design for closed-loop linear systems with saturating inputs providing maximized non-ellipsoidal estimates of the basin of attraction. The proposed design uses sign-indefinite quadratic forms leading to locally positive definite nonquadratic Lyapunov functions. An iterative algorithm that solves the bilinear matrix conditions inherent to this problem is proposed, based on a convex-concave decomposition. A numerical application is presented to illustrate the effectiveness of the proposed method.