Miracle-dz/UniFAR-FTUs huggingface dataset:
Dual-Memory Multi-Modal Learning for Continual Spoken Keyword Spotting with Confidence Selection and Diversity Enhancement

Enabling continual learning (CL) from an ever-changing environment is highly valuable, but it poses significant challenges for spoken keyword spotting (KWS), which simultaneously deals with both variability in acoustic characteristics of speech signals and catastrophic forgetting issues. In this paper, we pro-pose a novel framework for replay-based CL in KWS that uses a Dual-Memory Multi-Modal ( DM3 ) structure to enhance generalizability and robustness. Our approach leverages short-term and long-term models to learn near-term and long-term knowledge in an adaptive manner with a dual-memory structure, while also exploiting the consistency of multiple speech perturbations to improve the robustness with a multi-modal structure. Additionally, we introduce a class-balanced selection strategy that uses confidence scores to sort training samples. Experiments demonstrate the effectiveness of our method over competitive baselines in class incremental learning and domain incremental learning KWS settings.
Analysis of drying kinetic of brewer´s spent grains: effect of the temperature on the physical properties and the content of bioactive compounds

Background: Brewer´s spent grain (BSG) is a biomass by-product generated in large volumes during industrial beer production. BSG has become a growing environmental problem, as most breweries discard it inappropriately, negatively impacting the environment. Alternatives for the exploitation of this by-product have consisted of elaborating food supplements for farm animals, obtaining biofuels, developing adsorbents, and obtaining substances for the food industry. However, the high moisture content in BSG (approximately 70%), poses a significant challenge in exploring various reuse alternatives. Therefore, the implementation of a pre-drying process becomes essential. Objective: This study aimed to analyze the BSG drying kinetics at different temperatures and the effect of the drying temperature on the physical properties and the content of bioactive compounds. Methods: BSG samples were dried at different temperatures (50, 60, 70, 80, 90, and 105°C) and analyzed for their moisture ratio, water activity, total polyphenol content (TPC), and DPPH (1,1-diphenyl-2-picrylhydrazil) radical scavenging activity. Also, four kinetics models were fitted to the drying data. Results: It was determined that the effective diffusivity was between 5.23x10-10 (m2/s) and 2.49x10-09 (m2/s), and the value of the activation energy was 28.05 kJ/mol. In addition, it was found that the content of phenolic compounds (1.27±0.120 mg gallic acid equivalents /g) and the DPPH radical scavenging activity (0.21±0.015 mg gallic acid equivalents /g) were not significantly affected by the variation in the drying temperatures studied. Conclusions: From an operational point of view, the most suitable temperature for the drying process of BSG was 105°C since it would allow to reach shorter drying times, and the TPC was not affected markedly by the range of temperature studied.
Lost Worlds: Locating submerged archaeological sites in southeast Alaska

Synthesis and interpretation of archaeologically documented land-use patterns and ethnographic data are used to identify and model where people chose to live, hunt, and gather prehistorically. This project tests the hypothesis that the archaeological record of SE Alaska extends to areas of the continental shelf that were submerged by postPleistocene sea level rise beginning around 10,600 cal years BP (9,400 14 C years). Digital elevation models (DEM) and sea-level curve for southeastern Alaska are used to create time slices between 16,000 to 10,500 cal BP. The variables (slope, aspect, distance from paleo-stream, paleo-lakes, paleo-coastlines, and known archaeological sites, and coastal sinuosity) included in the predictive model are incorporated in model identifying high potential areas for archeological sites. This model has been used to delineate survey areas for underwater archaeological surveys during two fields and will be used for two more field season.
Independent Predictors of Repeat Emergency Room Presentations: Insights from a Cohort of 1066 Consecutive Patients with Non-Cardiac Chest Pain Generating 4770 Repeat Presentations

Background and importance: Chest pain (CP) is one of the most frequent presentations to the emergency department (ED), a large proportion of which is non-cardiac chest pain (NCCP). Repeat attendances to ED are common and impose considerable burden to overstretched departments. Objective: Our aim was to determine drivers for repeat ED presentations using NCCP as the primary cause of index presentation. Design, setting and participants: This was a retrospective cohort study of 1066 consecutive presentations with NCCP to a major urban hospital ED in North England. Index of Multiple Deprivation (IMD), a postcode-derived validated index of deprivation, was computed. Charlson comorbidity index (CCI) was determined by reference to known comorbidity variables. Repeat presentation to ED to any national hospital was determined by a national linked database (population 53.5 million). Independent predictors of ED representation were computed using logistic regression analysis. Results: Median age was 43 (IQR 28–59), and 50.8% were male. Furthermore, 27.8%, 8.1% and 3.8% suffered from chronic obstructive pulmonary disease (COPD), hypertension and diabetes mellitus, respectively. The most frequent diagnoses, using ICD-10 coding, were non-cardiac chest pain (55.1%), followed by respiratory conditions (14.7%). One-year incidence of adjudicated myocardial infarction, urgent or emergency coronary revascularisation and all-cause death was 0.6%, 2% and 5.3%, respectively. There was a total of 4770 ED repeat presentations 1 year prior to or following index presentation with NCCP in this cohort. Independent (multivariate) predictors for frequent re-presentation (defined as ≥2 representations) were a history of COPD (OR [odds ratio] 2.06, p = 0.001), previous MI (OR3.6, p = 0.020) and a Charlson comorbidity index ≥1 (OR 1.51, p = 0.030). The frequency of previous MI was low as only 3% had sustained a previous MI. Conclusions: This analysis indicates that COPD and complex health care needs (represented by high CCI), but not socio-economic deprivation, should be health policy targets for lessening repeat ED presentations. What is already known on this topic: Repeat presentations with non-ischaemic chest pain are common, placing a considerable burden on emergency departments. What this study adds: COPD and complex health care needs, denoted by Charlson comorbidity index, are implicated as drivers for repeat presentation to accident and emergency department. Socio-economic deprivation was not an independent predictor of re-presentation. How might this study affect research, practice, or policy: Community-based support for COPD and complex health care needs may reduce frequency of ED attendance.
EmotiEffNets for Facial Processing in Video-based Valence-Arousal Prediction, Expression Classification and Action Unit Detection

In this article, the pre-trained convolutional networks from the EmotiEffNet family for frame-level feature extraction are used for downstream emotion analysis tasks from the fifth Affective Behavior Analysis in-the-wild (ABAW) competition. In particular, we propose an ensemble of a multi-layered perceptron and the LightAutoML-based classifier. The post-processing by smoothing the results for sequential frames is implemented. Experimental results for the large-scale Aff-Wild2 database demonstrate that our model is much better than the baseline facial processing using VGGFace And ResNet. For example, our macro-averaged F1-scores of facial expression recognition and action unit detection on the testing set are 11-13% greater. Moreover, the concordance correlation coefficients for valence/arousal estimation are up to 30% higher when compared to the baseline.
The Firm Balance Sheet Channel of Uncertainty Shocks

Following spikes in aggregate uncertainty, firm-level physical capital drops along with salient liquidity buildup and deleveraging. Conventional macro-finance models treating corporate cash holding as net debt fail to capture the observed liquidity buildup when reproducing deleveraging, leaving an important adjustment margin unexplained. This paper embeds empirically-consistent corporate cash-holding motives into a workhorse macrofinance model of borrowing constraints, which provides a unified explanation for the observed balance-sheet transmission of uncertainty shocks. In the model, building up liquid assets allows firms to preserve internal funds for debt repayment and growth opportunities, thereby addressing both the downside risk and the upside potential triggered by heightened uncertainty. In the calibrated model consistent with firm-level behavior, (i). uncertainty shocks generate sharp and persistent drops in aggregate output that align well with data patterns, and (ii). debt relief programs are powerful in stabilizing uncertaintydriven recessions since it not only directly lowers firms’ debt burdens but also indirectly reduce firms’ elevated cash demand for debt repayment. In sharp contrast, models failing to account for corporate liquidity choice generate counterfactual output responses to uncertainty shocks and underestimate the stabilizing effects of debt relief. JEL Classificantion: D22, E22, E44, G32
Effect of Portland Cement on Mechanical and Durability Properties of Geopolymer Concrete at Ambient Temperature

Environmental concerns have prompted researchers to focus on the development of alternative building materials like geopolymer concrete. However, their implementation requires curing beyond 60°C, which limits their application on building sites. This study aims to design a geopolymer concrete at room temperature (30 ± 5°C) in a laboratory in Burkina Faso using a metakaolin-based geopolymer binder activated by an alkaline solution of NaOH and natural aggregates. Portland cement type CEM I 42.5 was used by mass substitution (0 to 25%) of metakaolin to promote curing at ambient temperature. The samples were cured for 7 to 28 days and characterized for physical, mechanical, and durability properties. The results showed that the incorporation of 0 to 20% cement significantly improved the compressive strength from 9.9 to 30.5 MPa and the tensile strength from 1.2 to 2.2 MPa. However, Portland cement has various effects on the durability of geopolymer concrete. It reduces the porosity accessible by water from 15 to 13% and decreases the resistance to acid attack by increasing the mass loss from 2 to 7%. This confirms that common concrete types C20/25 or C25/30 can be casted using geopolymer concrete on the sites in Burkina Faso once their durability is confirmed. Doi: 10.28991/CEJ-2023-09-07-04 Full Text: PDF
Perception of Incomplete Voicing Neutralization of Obstruents in Tohoku Japanese

Intervocalic voicing neutralization has been generally accepted as a peculiar feature of Tohoku dialects. The present paper reports the results of perception experiments on this phenomenon. Natural and resynthesized stimuli spoken by Tohoku speakers were presented to both Tohoku and Tokyo listeners in a series of online experiments. A comparison between these two listener groups reveals that, for Tohoku listeners whose perception was biased by the voicing neutralization in their phonology, the boundary between voiced and voiceless tokens was more blurred compared to Tokyo listeners whose phonology had no such neutralization. These results suggest that neutralization can be bidirectional: i.e., voiced tokens become less voiced and voiceless tokens become less voiceless in contrast to the traditional view of neutralization which assumes a unidirectional process where one category remains intact and the other category merges with the former.
Enhancing New Intent Discovery via Robust Neighbor-based Contrastive Learning

New intent discovery (NID) has become a hot topic for dialogue system, which aims to discover the Out-Of-Domain in-tents from conversation corpus and classify these utterances correctly. Existing methods usually focus on learning compact representations of utterances, and leverage the clustering algorithm to generate new intents. Inspired by the recent progress of contrastive learning, in this work, we propose a novel neighbor-based contrastive learning (NCL) model to obtain clustering-friendly representations for utterances. Specifically, to enhance the robustness of NCL, on the one hand, we pick out diverse samples as positive pairs by considering both the anchor neighborhood and nearby neighborhood. On the other hand, we also devise a boundary distance constraint to avoid introducing noisy samples when extending the positives via neighbors. Extensive experiments are conducted on three public NID datasets and the results demonstrate the competitiveness and effectiveness of our proposed approach.
Network Momentum across Asset Classes

We investigate the concept of network momentum, a novel trading signal derived from momentum spillover across assets. Initially observed within the confines of pairwise economic and fundamental ties, such as the stock-bond connection of the same company and stocks linked through supply-demand chains, momentum spillover implies a propagation of momentum risk premium from one asset to another. The similarity of momentum risk premium, exemplified by co-movement patterns, has been spotted across multiple asset classes including commodities, equities, bonds and currencies. However, studying the network effect of momentum spillover across these classes has been challenging due to a lack of readily available common characteristics or economic ties beyond the company level. In this paper, we explore the interconnections of momentum features across a diverse range of 64 continuous future contracts spanning these four classes. We utilise a linear and interpretable graph learning model with minimal assumptions to reveal the intricacies of the momentum spillover network. By leveraging the learned networks, we construct a network momentum strategy that exhibits a Sharpe ratio of 1.5 and an annual return of 22%, after volatility scaling, from 2000 to 2022. This paper pioneers the examination of momentum spillover across multiple asset classes using only pricing data, presents a multi-asset investment strategy based on network momentum, and underscores the effectiveness of this strategy through robust empirical analysis.
Clinical and pathogenetic mechanisms of formation of fetal growth retardation

Fetal growth retardation (FGR) is a major cause of child morbidity and mortality, and is also an important medical and social problem due to a wide range of pregnancy complications and negative outcomes in the postnatal period. The results of recent studies indicate that chronic arterial hypertension causes a number of pathological changes in a pregnant woman’s organism, in particular, it increases the risk of FGR.The wide knowledge about the pathogenesis of placental dysfunction and FGR allow to establish that the development of these pathologies is primarily caused by the changes in uterine and placental blood circulation, which leads to metabolic disorders. The important etiological reasons for FGR also include social and biological factors, the influence of narcotic substances, insufficient nutrition, alcohol abuse, tobacco smoking, as well as the use of coumarin or derivatives. The mother’s older age is also a risk factor for the FGR development.Over the past decades, both clinical and experimental studies have established that FGR, caused by the influence of the unfavorable environment of the uterus, is a risk factor for the development of hypertension, as well as various diseases in adults. There are a lot of evidences that support the association of FGR with an increased risk of hypertension in adults, but the mechanisms underlying these processes remain unclear. Both clinical and basic scientific studies have confirmed the theory of intrauterine programming of arterial hypertension in adults. That is why many countries have developed programs for the prevention of FGR. Scientific researches indicate a close relationship between social adaptation and the birth of children with low body weight.The absence of indices decrease in perinatal morbidity and mortality by FGR shows the difficulties caused by polyetiological factors and certain pathogenetic mechanisms of the mentioned complication. Today, the search for an effective pathogenetically based therapy of this pathology continues, which indicates the need for further researches, and the development and implementation of approaches to the prevention of FGR will improve the perinatal putcomes.
Durational and Non-durational Correlates of Lexical and Derived Geminates in Arabic

This paper reports on the phonetic and phonological patterns of gemination in Tripolitanian Libyan Arabic (TLA). While previous studies on Arabic gemination have either focused on lexical geminates or reported results on data that contains both lexical and derived geminates, without investigating its effect on the phonetic output, the present study investigates the effect of the phonological status of a geminate on the phonetic realization. Several measurements were obtained including target segments duration, RMS amplitude and F1, F2 and F3 for the target consonants. Preliminary results suggest that the acoustic distinction between singleton and geminate consonants in TLA is dependent mainly on durational correlates. There was no evidence of differences in RMS amplitude between singleton and geminate consonants of any type. F1, F2 and F3 frequencies are found to show similar patterns for singleton and geminate types for all sounds, suggesting no gestural effects of gemination in TLA.
A Mixed-Methods Study of Women’s Empowerment through Physical Activities: Relationships with Self-Efficacy and Physical Activity Levels

Participation in empowering physical activities may increase self-efficacy and facilitate long-term engagement. This explanatory sequential mixed-methods study examined the relationship between physical activity empowerment, exercise self-efficacy, and engagement. Midwestern women (N = 147) aged 18–65, 90% white, completed an online cross-sectional survey that captured exercise engagement and self-efficacy for exercise. Participants entered up to five types of physical activities and ranked them from most to least empowering. Physical activities were coded by training type for statistical comparisons using independent t-tests. After survey completion, seventeen women completed a 30 min, 8-question semi-structured interview. Women ranked resistance training as the most empowering physical activity type (38%), followed by running (14%). Total and moderate-to-vigorous physical activity and self-efficacy for exercise scores did not vary between women empowered by cardiorespiratory or resistance training (i.e., total physical activity t(136) = 1.13, p = 0.11; moderate-to-vigorous physical activity t(136) = 2.42, p = 0.06; and self-efficacy for exercise t(136) = 0.66, p = 0.07). Themes identified from the interviews included: (1) women’s physical activity participation barriers are gender-centric, (2) physical activity participation benefits extend beyond physical health, (3) some exercise types are more empowering than others, and (4) empowerment and enjoyment are closely related. Exploring empowerment in exercise may reveal mechanisms to facilitate exercise self-efficacy and engagement in physical activity.
Reliability of Mechanical and EMG Variables Assessed During Concentric Bench Press Exercise Against Different Submaximal Loads

Purpose: To analyze the intrasession reliability of different kinetic, kinematic and surface electromyography (EMG) variables obtained during concentric phase of the bench press exercise against four different submaximal loads: 50%, 60%, 70% and 80% 1RM. Methods: Twelve physical active men performed four testing sessions (one with each load magnitude) in a random order and separated by a time period of 3-4 days. In each session, participants were required to perform 3 sets of 2 repetitions each (3-min interset rests). The fastest repetition of each set was considered for subsequent reliability analysis. All data were analyzed using the intraclass correlation coefficient (ICC) and the coefficient of variation (CV). Results: Variables related to force, velocity, power and acceleration presented high reliability scores (ICC: 0.920-0.997, CV: 1.22-8.87%) against all load magnitudes used. The maximal rate of force development (MRFD) showed a high reproducibility, whereas the time taken to achieve the MRFD, time needed to attain different fractions of peak force and RFD quantify in different time bands (0-25, 0-50, 0-75ms) resulted in low to high relative reliability (ICC: 0.550-0.978) and moderate to poor absolute reliability (CV: 11.60-52.68%). Absolute (CV: 3.59-57.52%) and relative (ICC: 0.703-0.995) reproducibility for EMG variables related to signal amplitude and frequency of the power spectrum was fair to good, independent of load magnitude used and muscle assessed. Conclusion: Overall, these results suggest that the reliability of the mechanical and EMG measures varied depending on the variable used to assess the performance during a concentric BP exercise.
FTA-net: A Frequency and Time Attention Network for Speech Depression Detection

Depression is one of the most common mental diseases nowadays, which seriously affects the health of individuals. Some researchers have shown an association between the level of depression and speech features in individuals, so a lot of automatic speech-based depression detection systems have been proposed. A number of studies utilized convolutional neural network (CNN) to realize the speech depression detection. However, most of these studies did not take into account that different frequencies and time steps in the speech spectrum features contribute unequally to the detection of depression. In order to extract more significant and distinctive features, this paper proposes an effective frequency-time attention (FTA) module for CNN, which is based on squeeze and excitation operations and can emphasize the time steps and frequencies associated with depression. Experimental results based on the AVEC 2013 and AVEC 2014 benchmarks demonstrate the effectiveness of our proposed method.
Female Leadership and Workplace Climate

Using data from over 2,000 professionals in 24 large corporations, we show that female leaders shape the relational culture in the workplace diﬀerently than male leaders. Males form homophilic professional ties under male leadership, but female leadership disrupts this pattern, creating a less segregated workplace. Female leaders are more likely to establish professional support links with their subordinates. Under female leadership, female employees are less likely to quit their jobs but no more likely to get promoted. Our results suggest that increasing female presence in leadership positions may be an eﬀective way to mitigate toxic relational culture in the workplace.