Miracle-dz/UniFAR-FTUs huggingface dataset:
ICF and perception of functioning according to children/adolescents in follow-up with speech/language disorders

ABSTRACT Purpose To characterize changes in the functioning aspects, in the perception of children and adolescents with speech and language disorders under speech-language follow-up, using the ICF. Methods Descriptive, analytical and longitudinal research, with a qualitative and quantitative approach, whose sample consisted of 60 children and adolescents: 30 with speech and language disorders and 30 with typical speech and language development. Data collection was carried out in two moments: beginning of the research and six months later. A semi-structured questionnaire was administered to the participants, and a medical records analysis was performed. From these data, functioning was classified using he ICF categories. The Wilcoxon test and thematic content analysis were used to compare the interviews. Results The use of ICF allowed characterizing changes resulting from speech-language follow-up. Participants with speech and language disorders presented a decrease in the magnitude of the qualifiers in the categories: articulation and fluency, social relationships, daily activities, engagement in play, people's attitude barriers, and how to handle stress. Conclusion The findings show changes in components of Body Functions, Activities and Participation, and the influence of Environmental Factors after speech-language follow-up, in the perception of the studied group, which brings relevant subsidies for a greater understanding of functioning and therapeutic intervention. The use of the ICF enabled the longitudinal analysis in a biopsychosocial approach, contemplating, in addition to biological aspects, the social impact of speech and language disorders in the lives of these children and adolescents.
Large- and Small-Signal Modeling Derived Loss Optimal Power Loop Decoupling Mechanism of TAB Converter

This article presents a precisely synthesized full order as well as reduced order continuous time large signal and small signal model of a hybrid phase-duty controlled triple-active bridge (TAB) converter based on higher order harmonic frequency inclusive averaging model. Such model helps to accurately predict the steady state circuit parameters such as inductor current, average output voltage, output voltage ripple etc. that in turn can be used to formulate the loss minimized optimal phase-duty modulation strategy for a TAB. Further, the derived full order small signal model can specifically model the high frequency dynamics of the converter which are neglected in the reduced order modeling. Moreover, in order to facilitate decoupled power flow in a TAB, a decoupler network is formulated based on meticulously modeled converter plant considering higher order harmonics of the bridge voltages into calculation. Finally, a controller-based decoupled power management strategy is proposed in this study that decouples the TAB control loops and facilitates faster transient performance with two independent PI controllers. An 800 W TAB converter proof-of-concept is designed, fabricated, and tested to verify the established modeling techniques and the proposed controller decoupling action. With the implementation of the decoupled control under an 80% load transient at the 2nd output port, the experimental results show 30% improvement in overshoot compared to the fundamental harmonic based decoupling method.
Salient feature extraction for hyperspectral image classification

ABSTRACT Hyperspectral image (HSI) classification has been a vibrant area of research in recent years. In this letter, a salient feature extraction method is designed to improve the HSI classification performance. First, three consecutive bands of HSI are decomposed into several elements in order to better extract salient feature. Second, two measures of contrast that rate the uniqueness and the spatial distribution of these elements are computed. Thirdly, two measures of contrast are combined to form the saliency value of an element. The final saliency of a pixel is formed by a weighted linear combination of its surrounding elements saliency. Finally, three band sliding window is used over the spectral dimension of HSI and salient features extracted from each three adjacent bands are stacked to form the final features. The important characteristic of the proposed approach is that both local spatial information and global spatial information are taken into account in the process of feature extraction. Experimental results on two real HSI datasets demonstrate that the designed feature extraction method could improve the classification performance.
Group Fairness in Set Packing Problems

Kidney exchange programs (KEPs) typically seek to match incompatible patient-donor pairs based on a utilitarian objective where the number or overall quality of transplants is maximized---implicitly penalizing certain classes of difficult to match (e.g., highly-sensitized) patients. Prioritizing the welfare of highly-sensitized (hard-to-match) patients has been studied as a natural \textit{fairness} criterion. We formulate the KEP problem as $k$-set packing with a probabilistic group fairness notion of proportionality fairness---namely, fair $k$-set packing (\f{}). In this work we propose algorithms that take arbitrary proportionality vectors (i.e., policy-informed demands of how to prioritize different groups) and return a probabilistically fair solution with provable guarantees. Our main contributions are randomized algorithms as well as hardness results for \f{} variants. Additionally, the tools we introduce serve to audit the price of fairness involved in prioritizing different groups in realistic KEPs and other $k$-set packing applications. We conclude with experiments on synthetic and realistic kidney exchange \textsc{FairSP} instances.
Water-Soluble Alkali Lignin as a Natural Radical Scavenger and Anticancer Alternative

Several phytochemicals, which display antioxidant activity and inhibit cancer cell phenotypes, could be used for cancer treatment and prevention. Lignin, as a part of plant biomass, is the second most abundant natural biopolymer worldwide, and represents approximately 30% of the total organic carbon content of the biosphere. Historically, lignin-based products have been viewed as waste materials of limited industrial usefulness, but modern technologies highlight the applicability of lignin in a variety of industrial branches, including biomedicine. The aims of our preliminary study were to compare the antioxidant properties of water-soluble alkali lignin solutions, before and after UV-B irradiation, as well as to clarify their effect on colon cancer cell viability (Colon 26), applied at low (tolerable) concentrations. The results showed a high antioxidant capacity of lignin solutions, compared to a water-soluble control antioxidant standard (Trolox) and remarkable radical scavenging activity was observed after their UV-B irradiation. Diminishment of cell viability as well as inhibition of the proliferative activity of the colon cancer cell line with an increase in alkali lignin concentrations were observed. Our results confirmed that, due to its biodegradable and biocompatible nature, lignin could be a potential agent for cancer therapy, especially in nanomedicine as a drug delivery system.
Poultry Consumption and Human Cardiometabolic Health-Related Outcomes: A Narrative Review

Poultry meats, in particular chicken, have high rates of consumption globally. Poultry is the most consumed type of meat in the United States (US), with chicken being the most common type of poultry consumed. The amounts of chicken and total poultry consumed in the US have more than tripled over the last six decades. This narrative review describes nutritional profiles of commonly consumed chicken/poultry products, consumption trends, and dietary recommendations in the US. Overviews of the scientific literature pertaining to associations between, and effects of consuming chicken/poultry on, body weight and body composition, cardiovascular disease (CVD), and type II diabetes mellitus (T2DM) are provided. Limited evidence from randomized controlled trials indicates the consumption of lean unprocessed chicken as a primary dietary protein source has either beneficial or neutral effects on body weight and body composition and risk factors for CVD and T2DM. Apparently, zero randomized controlled feeding trials have specifically assessed the effects of consuming processed chicken/poultry on these health outcomes. Evidence from observational studies is less consistent, likely due to confounding factors such as a lack of a description of and distinctions among types of chicken/poultry products, amounts consumed, and cooking and preservation methods. New experimental and observational research on the impacts of consuming chicken/poultry, especially processed versions, on cardiometabolic health is sorely needed.
Development and Calibration of a Low Cost Wireless Camera Sensor Network

In camera sensor network research, physical camera sensor network platforms with low power and low cost are needed for testing and validating algorithms. It is also necessary that the camera nodes be calibrated precisely. In this work, we first develop and evaluate a low power and low cost wireless camera sensor network platform. The camera sensor nodes in this platform transmit a grayscale image over a wireless channel to a master control station. Then we propose a simple, lightweight algorithm to perform distributed calibration of the camera sensor nodes. The camera sensor nodes use their imaging abilities in collaboration with a cooperative moving target to determine their own positions and orientations. The proposed algorithm requires simple arithmetic calculations and hence it can be realized on low power processors. This calibration algorithm has been implemented and evaluated on the developed physical camera sensor network platform.
A General Matrix Variable Optimization Framework for MIMO Assisted Wireless Communications

Complex matrix derivatives play an important role in matrix optimization, since they form a theoretical basis for the Karush-Kuhn-Tucker (KKT) conditions associated with matrix variables. We commence with a comprehensive discussion of complex matrix derivatives. First, some fundamental conclusions are presented for deriving the optimal structures of matrix variables from complex matrix derivatives. Then, some restrictions are imposed on complex matrix derivatives for ensuring that the resultant first order equations in the KKT conditions exploit symmetric properties. Accordingly, a specific family of symmetric matrix equations is proposed and their properties are unveiled. Using these symmetric matrix equations, the optimal structures of matrix variables are directly available, and thereby the original optimization problems can be significantly simplified. In addition, we take into account the positive semidefinite constraints imposed on matrix variables. In order to accommodate the positive semidefinitness of matrix variables, we introduce a matrix transformation technique by leveraging the symmetric matrix equations, which can dramatically simplify the KKT conditions based analysis albeit at the expense of destroying convexity. Moreover, this matrix transformation technique is valuable in practice, since it offers a more efficient means of computing the optimal solution based on the optimal structures derived directly from the KKT conditions.
Fairness via Group Contribution Matching

Fairness issues in Deep Learning models have recently received increasing attention due to their significant societal impact. Although methods for mitigating unfairness are constantly proposed, little research has been conducted to understand how discrimination and bias develop during the standard training process. In this study, we propose analyzing the contribution of each subgroup (i.e., a group of data with the same sensitive attribute) in the training process to understand the cause of such bias development process. We propose a gradient-based metric to assess training subgroup contribution disparity, showing that unequal contributions from different subgroups are one source of such unfairness. One way to balance the contribution of each subgroup is through oversampling, which ensures that an equal number of samples are drawn from each subgroup during each training iteration. However, we have found that even with a balanced number of samples, the contribution of each group remains unequal, resulting in unfairness under the oversampling strategy. To address the above issues, we propose an easy but effective group contribution matching (GCM) method to match the contribution of each subgroup. Our experiments show that our GCM effectively improves fairness and outperforms other methods significantly.
The influence of macrofauna on intertidal sediment stability and biogeochemical properties

Macrofauna are known to have a significant effect on intertidal sediment stability and biogeochemical properties. A series of manipulative in situ mudflat studies at Breydon Water, Great Yarmouth, UK investigated the effect of biodiversity on selected biogeochemical sedimentary properties related to mudflat sediment stability including the sediment erosion threshold and relative erosion rate, microphytobenthos biomass and health, sediment particle size and size distribution, sediment water content, chlorophyll a and b concentration, and colloidal carbohydrate concentration. Mudflat sediment macrofaunal biomass was removed using cryo-defaunation and the abundances of three common mudflat species Hediste diversicolor, Hydrobia ulvae and Corophium volutator manipulated to examine different aspects of macrofaunal biodiversity including species identity, density, biomass distribution, and richness. An additional laboratory study enabled two and three dimensional high resolution visualisation of fluid and particle mixing as a result of organism sediment bioturbation. Species identity was found to have a significant effect on sediment properties. The three species have distinct bioturbatory actions with consequences for sediment stability. In some circumstances a single organism was found to have as great an effect on selected ecosystem processes as a whole community. Variations in species density significantly changed the effect of the species on the measured sedimentary processes. Species richness effects were negatively interactive, with species mixtures underyielding in comparison to their monoculture counterparts. Changes in species biomass distribution and richness resulted in significant context dependent changes to sediment properties, moderated by inter- and intraspecific interactions. Species were also observed to exhibit a functional abundance threshold, below which they did not contribute significantly to ecosystem processes. Temporal and spatial variability observed in the experiments emphasised the potential of environmental and abiotic factors to also influence ecosystem processes. Investigating these subtle aspects of biodiversity will be key in the determination of the relationship between biodiversity and ecosystem processes.
LTE-Powered BLE-to-WiFi Backscattering Chip Toward Single-Device Interrogation RFID-Like Systems

This letter presents a backscattering chip that is powered via LTE signals and reflects an incident reverse-whitened Bluetooth low energy (BLE) tone-like advertisement packet into a reradiated single-side-band (SSB) 802.11 b WiFi packet at a configurable WiFi channel location, all toward enabling an RFID-like single-device interrogation system. The chip includes an RF energy harvester, a WiFi wake-up receiver, an intermediate frequency (IF) ring oscillator whose frequency is calibrated with a successive-approximation-register (SAR) frequency-lock-loop (FLL), and a QPSK SSB backscatter modulator. Implemented in 65-nm CMOS, the chip consumes 4.5-<inline-formula> <tex-math notation="LaTeX">$\mu \text{W}$ </tex-math></inline-formula> power in wake-up mode and 11 to <inline-formula> <tex-math notation="LaTeX">$45~\mu \text{W}$ </tex-math></inline-formula> power in backscatter mode, with on-chip ring oscillator frequencies ranging from 33 to 253 MHz in order to support eight different BLE-to-WiFi backscatter schemes. Wireless measurement showed that the chip can be charged to 1 V before backscattering within 1 s on a 1-<inline-formula> <tex-math notation="LaTeX">$\mu \text{F}$ </tex-math></inline-formula> off-chip storage capacitor up to a 50-cm distance.
Dynamic Transcriptional Landscape of Mycobacterium smegmatis under Cold Stress

Bacterial adaptation to cold stress requires wide transcriptional reprogramming. However, the knowledge of molecular mechanisms underlying the cold stress response of mycobacteria is limited. We conducted comparative transcriptomic analysis of Mycobacterium smegmatis subjected to cold shock. The growth of M. smegmatis cultivated at 37 °C was arrested just after exposure to cold (acclimation phase) but later (by 24 h) was resumed at a much slower rate (adaptation phase). Transcriptomic analyses revealed distinct gene expression patterns corresponding to the two phases. During the acclimation phase, differential expression was observed for genes associated with cell wall remodeling, starvation response, and osmotic pressure stress, in parallel with global changes in the expression of transcription factors and the downregulation of ribosomal genes, suggesting an energy-saving strategy to support survival. At the adaptation phase, the expression profiles were recovered, indicating restoration of the processes repressed earlier. Comparison of transcriptional responses in M. smegmatis with those in other bacteria revealed unique adaptation strategies developed by mycobacteria. Our findings shed light on the molecular mechanisms underlying M. smegmatis survival under cold stress. Further research should clarify whether the discovered transcriptional mechanisms exist in other mycobacterial species, including pathogenic Mycobacterium tuberculosis, which could be important for transmission control.
Changes in Tree Swallow Phenology Due to Climate Change in Alaska

Ecological effects of climate change are beginning to be seen across the globe. In avian species, these effects often manifest in earlier breeding dates. Tree swallows in the temperate zones of North America advanced their laying date by nine days between 1959 and 1991. However tree swallows in more arctic regions, where climate change is occurring more rapidly, have not yet been studied. Additionally, two important climate variables, wind and precipitation, have been largely ignored in climate change studies to date. I used tree swallow nest records from Fairbanks, Alaska to examine how climate change is affecting these birds in the northern part of their range. To provide a more comprehensive view on how tree swallows are being affected by climate change, I looked at effects from wind and precipitation in addition to temperature. I found an advance in laying date and a decrease in incubation time, resulting in a greater advance in hatch date, associated with increasing temperatures and decreasing wind
The temporal event-based model: Learning event timelines in progressive diseases

Abstract Timelines of events, such as symptom appearance or a change in biomarker value, provide powerful signatures that characterise progressive diseases. Understanding and predicting the timing of events is important for clinical trials targeting individuals early in the disease course when putative treatments are likely to have the strongest effect. However, previous models of disease progression cannot estimate the time between events and provide only an ordering in which they change. Here, we introduce the temporal event-based model (TEBM), a new probabilistic model for inferring timelines of biomarker events from sparse and irregularly sampled datasets. We demonstrate the power of the TEBM in two neurodegenerative conditions: Alzheimer’s disease (AD) and Huntington’s disease (HD). In both diseases, the TEBM not only recapitulates current understanding of event orderings but also provides unique new ranges of timescales between consecutive events. We reproduce and validate these findings using external datasets in both diseases. We also demonstrate that the TEBM improves over current models; provides unique stratification capabilities; and enriches simulated clinical trials to achieve a power of 80% with less than half the cohort size compared with random selection. The application of the TEBM naturally extends to a wide range of progressive conditions.
Relationship between eating patterns and emotional distress, and perceived quality of life in women with polycystic ovarian syndrome.

INTRODUCTION AND OBJECTIVE Polycystic Ovary Syndrome (PCOS) is a prevalent endocrine disorder with numerous hormonal, metabolic, and reproductive manifestations. Because of the variety of adverse consequences associated with the condition, women with PCOS suffer emotional distress, resulting in reduced health-related quality of life. Similar to other chronic conditions, eating patterns have been shown effective in impacting the quality of life of PCOS patients. Therefore, lifestyle modifications are recommended as a first-line therapy for PCOS, before prescribing any pharmaceutical management of the PCOS. The aim of the study was to investigate the relationship between dietary patterns, emotional distress, and perceived quality of life in women with diagnosed PCOS. MATERIAL AND METHODS The cross-sectional study included 130 women with PCOS aged 18 - 60 years from the Polish population. The respondents were asked to complete a self-administered questionnaire developed for the purpose of the study, inspired by the Food Frequency Questionnaire (FFQ), Polycystic Ovary Syndrome Health-Related Quality of Life Questionnaire (PCOSQ), Three-Factor Eating Questionnaire (TFEQ-R18), and the Eating attitude questionnaire (Eat-26). RESULTS Respondents were found to experience emotional distress regardless of how healthy their diet. Nonetheless, the results showed that women who followed a healthier eating pattern had lower occurrence of experiencing mood swings, and less often felt triggered in the social context. The group did not show a tendency to over-eat, gain weight, or binge eating. CONCLUSIONS Healthier eating habits, besides providing advantages in weight management, may mitigate symptoms of emotional distress and improve the quality of life in women with PCOS.