Miracle-dz/UniFAR-FTUs huggingface dataset:
Common and differential acoustic representation of interpersonal and tactile iconic perception of Mandarin vowels

Many have found that sound sequences can convey various domains of meaning, yet the mechanisms underlying such apparent associations between particular sound sequences and meanings in speech are underexplored. The study aimed to examine the common and different acoustic cues crucial for tactile and social sound symbolism based on the vowels in Mandarin. With the full spectrum of vowels tested, the study provided rich sound variations to demonstrate the role of multiple acoustic cues in encoding different meanings at the same time. Forty native Chinese listened to vowel sequences and rated on the interpersonal (e.g., encouraging-authoritative) and tactile (e.g., light-heavy) attributes based on these sounds. Acoustic analysis was performed on the vowel sequences and XGBoost algorithm was further applied to simulate tactile/social perception. The results showed that duration and pitch are two features crucial for representing both tactile and social sound symbolism. The second formant and nasality of vowels are specifically important for tactile representation while the third formant is fundamental for social representation. Machine learning models can achieve an above-chance performance using limited yet important acoustic features of vowels. Findings of this study have implications for multi-modal speech perception and iconic sound-meaning mappings in Mandarin.
What Drives Salespeople's Performance? the Role of Organizational Attributes and the Moderating Effect of Experience

The mobile telecommunications services industry has a high level of instability as a result of shifting market conditions, persistent market problems, and changing market demand. As a result, marketers need to take their customers' preferences into account. With these considerations in mind, the goal of this study is to determine how the characteristics associated with the mobile communication services industry are presented to salesperson performance and how this influences sales personnel. Primary and secondary data sources were used in the investigation. In this study, we used a structured questionnaire, with 1 indicating strongly disagree and 5 indicating strongly agree. The data was analysed using both inferential and descriptive statistics. In Bangladesh, where the characteristics of mobile service providers are well documented, speculative data on elements influencing salespeople's performance was used. Structural Equation Modeling was utilised to identify impact factors connected to salesperson performance. Data was collected from active salesmen using a convenient sampling method. According to this study, just two parameters, external motivation and salespeople's political abilities, have a significant effect on predicting salespeople's effectiveness in mobile telecommunications in Bangladesh. As a result, business executives should take more initiative to improve their enterprises' performance, as this would benefit both salespeople and their organisations.
Aggregation rate as a function of soil organic matter in heavy clayey Ferralsols

: Heavy clayey Ferralsols are known for their high capacity to form water-stable macroaggregates. However, little is known about how different size classes of macroaggregates exchange mass with increasing organic matter content. This study aimed to characterize and detail aggregation dynamics with increasing organic matter content in these soils. Profiles of three heavy clayey Ferralsols were sampled to isolate the role of organic matter on the stability of aggregates. In this sampling scenario, a conceptual model was established to calculate the aggregation rate of different size classes of water-stable aggregates. This approach allowed the establishment of a critical value for classifying microaggregates in the studied soils (≤0.50 mm) based on their behavior as “building blocks” for macroaggregates when organic matter content is increased. In surface soil layers, where organic matter is higher, most dynamics are expected to happen between macroaggregates classes because free microaggregates are scarce. Consequently, it is important to subdivide macroaggregates into different size classes when evaluating their stability. Quantifying macroaggregates as a single class (e.g., >0.25 or >0.50 mm) was insufficient in representing the macroaggregation dynamics in heavy clayey Ferralsols.
A Machine Learning Approach for School Dropout Prediction in Brazil

School dropout is a problem that impacts many socio-economic aspects, including inequality. Dropout prediction algorithms can help remediate this problem, although several past attempts in the literature did so using small datasets. This paper brings forward an experimental approach of machine learning for school dropout prediction in Brazilian schools. The data used for this study was first retrieved from the academic systems of a group of Brazilian private schools, which was later enriched with socio-economic data extracted from governmental sources. Using the dataset to train different types of classifiers, we obtained up to 95.2% precision rates when predicting dropout at different year and educational stages, thus allowing schools to plan and apply retention strategies.
Class-Aware Distribution Alignment based Unsupervised Domain Adaptation for Speaker Verification

Existing speaker verification (SV) systems usually suffer from significant performance degradation when applied to a new domain that lies outside the training distribution. Given the unlabeled target-domain dataset, most Unsupervised Domain Adaptation (UDA) methods aim to minimize the distribution divergence between different domains. However, global distribution alignment strategies fail to consider latent speaker label information and can hardly guarantee the feature discriminative capability in target domain. In this paper, we pro-pose a novel UDA approach called WBDA (Within-class and Between-class Distribution Alignment), which aims to transfer the class-aware information ( i.e. , within-and between-class distributions) learned from the well-labeled source-domain, to the unlabeled target-domain. Motivated by the recent progress of self-supervised contrastive learning, positive and negative pairs are constructed separately for source and target domains, from which the within-and between-class distribution can be estimated. And the SV system can then be learned by jointly optimizing the cross-domain class-aware distribution discrepancy loss and source-domain classification loss in an end-to-end manner. Evaluations on NIST SRE16 and SRE18 achieve a relative performance improvement of about 43.7% and 26.2% over the baseline in terms of Equal Error Rate (EER) separately, significantly outperforming the previous adaption methods based on global distribution alignment
Development and Validation of a Nomogram Model for Predicting the Risk of Readmission in Patients with Heart Failure with Reduced Ejection Fraction within 1 Year

The high incidence of readmission for patients with reduced ejection fraction heart failure (HFrEF) can seriously affect the prognosis. In this study, we aimed to build a simple predictive model to predict the risk of heart failure (HF) readmission in patients with HFrEF within one year of discharge from the hospital. This retrospective study enrolled patients with HFrEF evaluated in the Heart Failure Center of the Affiliated Hospital of Xuzhou Medical University from January 2018 to December 2020. The patients were allocated into the readmission or nonreadmission group, according to whether HF readmission occurred within 1 year of hospital discharge. Subsequently, all patients were randomly divided into training and validation sets in a 7 : 3 ratio. A nomogram was established according to the results of univariate and multivariate logistic regression analysis. Finally, the area under the receiver operating characteristic curve (AUC-ROC), calibration plot, and decision curve analysis (DCA) were used to validate the nomogram. Independent risk factors for HF readmission of patients with HFrEF within 1 year of hospital discharge were as follows: age, body mass index, systolic blood pressure, diabetes mellitus, left ventricular ejection fraction, and angiotensin receptor-neprilysin inhibitors. The AUC-ROC of the training and validation sets were 0.833 (95% confidence interval (CI): 0.793-0.866) and 0.794 (95% CI: 0.727-0.852), respectively, which have an excellent distinguishing ability. The predicted and observed values of the calibration curve also showed good consistency. DCA also confirmed that the nomogram had good clinical value. In conclusion, we constructed an accurate and straightforward nomogram model for predicting the 1-year HF readmission risk in patients with HFrEF. This nomogram can guide early clinical intervention and improve patient prognosis.
Integrating Discrete Word-Level Style Variations into Non-Autoregressive Acoustic Models for Speech Synthesis

This paper presents a method of integrating word-level style variations (WSVs) into non-autoregressive acoustic models for speech synthesis. WSVs are discrete latent representations extracted from the acoustic features of words, which have been proposed in our previous work to improve the naturalness of the Tacotron2 model. In this paper, we integrate WSVs into FastSpeech2, a non-autoregressive acoustic model. In the WSV extractor, a Gumbel-Sigmoid activation function is introduced for WSV representation and is compared with the original Gumbel-Softmax activation by experiments. The WSV predictor utilizes the word embeddings provided by BERT and has a non-autoregressive structure to be compatible with FastSpeech2. Experimental results show that our proposed method with the Gumbel-Sigmoid activation achieved better objective performance on F0 prediction than the FastSpeech2 baseline and the method using the Gumbel-Softmax activation. The subjective performance of our proposed models was also significantly better than the FastSpeech2 baseline.
Motion Planning for the Three Wheel Mobile Robot using the Reachable Set Computation under Constraints

Abstract In this paper, an off-line motion planning algorithm for the three wheel mobile robot based on backward reachability is proposed. We formulate a strategy to compute the backward reachability sets of a non linear dynamic system using level set method. The level set method is a computational tool which can be applied to a general class of target reaching/ hitting problems. The set of states from which the target set can be reached is represented as the zero level set of the viscosity solution of a time dependent Hamilton- Jacobi-Isaacs (HJI) partial differential equation (PDE). We demonstrate this method by applying it to the three wheel mobile robot, to ensure that the mobile robot reaches a certain target area by avoiding obstacles while still being in the safe reachability set.
Interactive Co-Learning with Cross-Modal Transformer for Audio-Visual Emotion Recognition

This paper proposes a novel modeling method for audio-visual emotion recognition. Since human emotions are expressed multi-modally, jointly capturing audio and visual cues is a potentially promising approach. In conventional multi-modal modeling methods, a recognition model was trained from an audio-visual paired dataset so as to only enhance audio-visual emotion recognition performance. However, it fails to estimate emotions from single-modal inputs, which indicates they are degraded by overfitting the combinations of the individual modal features. Our supposition is that the ideal form of the emotion recognition is to accurately perform both audio-visual multi-modal processing and single-modal processing with a single model. This is expected to promote utilization of individual modal knowledge for improving audio-visual emotion recognition. Therefore, our proposed method employs a cross-modal transformer model that enables different types of inputs to be handled. In addition, we introduce a novel training method named interactive co-learning; it allows the model to learn knowledge from both and either of the modals. Experiments on a multi-label emotion recognition task demonstrate the effectiveness of the proposed method.
The Effect of Fundamental Factors on Corporate Social Responsibility in Property and Real Estate Companies in ISSI 2016-2020

This study aims to analyze the fundamental factors of property and real estate companies in 2016-2020 in the Indonesian sharia stock index (ISSI), which consists of liquidity (CR), profitability (ROA), company size (CR), leverage (DER) influential or whether or not to corporate social responsibility (CSR). In this study, panel data analysis was used to find the best model, namely the Common Effect Model (CEM), Fixed Effect Model (FEM), Random Effect Model (REM) with purposive sampling method in order to obtain data in accordance with predetermined categories with data originating from 15 selected property and real estate companies that report corporate social responsibility and financial summary in the annual report and sustainability report that have been registered with ISSI in the 2016-2020 period. The results of this study simultaneously show that all independent variables, namely firm size (SIZE), profitability (ROA), liquidity (CR), leverage (DER) have a significant influence on CSR. Meanwhile, partially the firm size variable has a positive and significant effect on CSR and the leverage, profitability and liquidity variables do not have a positive and significant effect on CSR.
A Brief Overview of Soviet and Russian Military Map Symbology and Terms

ABSTRACT Soviet and Russian military maps may comprise any combination of over 1,000 map symbols and 3,000 Russian terms. These symbols and terms identify tangible aspects such as locations, unit/equipment type and numbers, but some symbols, and groupings of symbols, can also denote more subjective aspects such as movement over time, types of manoeuvres, relationship to the surrounding environment and other activities or conditions. Unlike Russian topographic maps that have a well-documented symbology system, there has been little study of Soviet/Russian military map symbology and terms. This paper offers a brief overview of the topic and discusses a few examples.
Enroll-Aware Attentive Statistics Pooling for Target Speaker Verification

The well-developed robust speaker verification system can remove the environment noise and retain speaker information automatically. However, when the uttering voice is disturbed by another interfering speaker’s voice, the speaker verification system usually cannot selectively extract only the target speaker’s information. Some works have been done by introducing a speech separation network to separate the target speaker’s speech in advance. However, adding a speech separation network for speaker verification task could be redundant. Here, we proposed enroll-aware attentive statistic pooling (EA-ASP) layer to help the speaker verification system extract specific speaker’s information. To evaluate the system, we simulate the multi-speaker evaluation data based on Voxceleb1 data. The results show that our proposed EA-ASP can outperform the baseline system by a large margin and achieved ∼ 50% relative Equal Error Rate (EER) reduction.
EFFECT OF SOFT TQM PRACTICES ON JOB SATISFACTION AND ORGANIZATIONAL COMMITMENT OF HEALTHCARE PROFESSIONALS

This study aims to measure the effect of soft TQM practices on job satisfaction and organizational commitment of healthcare professionals. Data were collected from three ISO 9000:2008 certified hospitals located in two northern cities of Pakistan. Out of 800 self-administered questionnaires distributed to doctors and nurses, 530 filled questionnaires were returned. Results were drawn by applying reliability, correlation, and linear regression analyses. Study proves that soft TQM practices exert a positive effect on organizational commitment and job satisfaction of healthcare professionals. However, the study fails to find any significant impact of top management commitment, leadership, and customer focus on job satisfaction. Contrary to previous work, the study proves the negative effect of customer focus on organizational commitment. Hospital administration should be committed to successfully implement the TQM practices for the improvement of organizational commitment and job satisfaction of healthcare professionals. This study can be considered as a pioneer work that examined the relationship of TQM practices with job satisfaction and organizational commitment of healthcare professionals in Pakistan.
Voicing decision based on phonemes classification and spectral moments for whisper-to-speech conversion

Cordectomized or laryngectomized patients recover the ability to speak thanks to devices able to produce a natural-sounding voice source in real time. However, constant voicing can impair the naturalness and intelligibility of recon-structed speech. Voicing decision, consisting in identifying whether an uttered phone should be voiced or not, is investigated here as an automatic process in the context of whisper-to-speech (W2S) conversion systems. Whereas state-of-the-art approaches apply DNN techniques on high-dimensional acoustic features, we seek here a low-resource alternative approach for a perceptually-meaningful mapping between acoustic features and voicing decision, suitable for real-time applications. Our method first classifies whisper signal frames into phoneme classes based on their spectral centroid and spread, and then discriminates voiced phonemes from their unvoiced counterpart based on class-dependent spectral centroid thresholds. We compared our method to a simpler approach using a single centroid threshold on several databases of annotated whispers in both single-speaker and multi-speaker training setups. While both approaches reach voicing accuracy higher than 91%, the proposed method allows to avoid some systematic voicing decision errors, which may allow users to learn to adapt their speech in real-time to compensate for remaining voicing errors.
INSTITUTIONAL COMPLEXITY OF HR PRACTICES: CHALLENGES FOR SUSTAINABLE BUSINESS

Sustainable Development Goals (SDGs) are important phenomena in public administration and many reforms have been introduced in Pakistan to ensure the achievement of SDGs committed by the political leaders. This study targets SGD 11 that relates to sustainable urban development through effective municipal corporations. For this purpose, the study explores the HR practices of public organizations operating under the Lahore Municipal Corporation and explains the institutional complexity of these practices. This complexity arises from the lack of implementation of new HR practices that are at odds with the prevailing bureaucratic logic. The study supports the argument of the institutional logic perspective that multiple institutional logics co-exist in organizations resulting in contrasting and contradictory practices.
Impact of the Figures of Merit (FoMs) Definitions on the Variability in Nanowire TFET: NEGF Simulation Study

In this article, we investigate the effect of variability in p-type nanowire tunnel FET (TFET) using quantum mechanical transport simulations. The simulations have been carried out using the Nano Electronics Simulation Software (NESS) from the University of Glasgow. Random discrete dopants (RDDs) and work-function variations (WFV) have been investigated in the simulations. Our statistical simulations reveal that key figures of merit (FoMs) such as the current variability generally decrease as the gate voltage decreases, the threshold voltage variability increases as the threshold current increases, and the dependences of these FoM variabilities on criteria become stronger with the switch characteristic ameliorated. Furthermore, it is interesting to find that the band offset in heterostructure can more or less alleviate the current variability, especially around the OFF-state.
Correlation of Body Composition and Coordination of Specific Footballers’ Position among Professional Football Players

The game of football is a competitive team sport that requires an essential component of motor fitness, body composition, psychological, technical, and tactical components for enhanced performance. This study assessed the correlation of body composition and coordination of specific footballers’ positions among professional football players. This study utilised a correlational research design. Participants in this study comprised twenty-nine (29) football players who play for a professional team in Nigeria. There were 12 forwards, 6 midfielders, 4 goalkeepers, and 7 defenders among the participants. The participants’ hand-eye coordination was evaluated using the alternate hand wall toss test. The beurer diagnostic scale was used to measure the participants’ body fat percentage and muscle mass. Results were analysed using pearson’s product moment correlation and linear regression. The level of significance was set at p < 0.05. A significant positive moderate correlation was observed between muscle mass and coordination among forwards (r = 0.550, p = 0.044). There was no significant correlation between muscle mass and coordination among defenders, midfielders, and goalkeepers. Likewise, there was no significant correlation between body fat percentage and coordination among football players in all the playing positions. The hand-eye coordination of forwards is significantly correlated with their muscle mass. In other words, a forward’s muscle mass affects their degree of hand-eye coordination. Therefore, football regulatory bodies and trainers could utilise the muscle mass of forwards to predict their hand-eye coordination ability. This finding should be considered by the coaches and governing bodies of football teams before designating players to playing positions in the game of football. Furthermore, there is a need for training programs specifically designed to monitor and enhance the muscle mass of forwards in a football team in order to enhance hand-eye coordination.
Mandarin Tone Sandhi Realization: Evidence from Large Speech Corpora

There has been a long-standing debate on the acoustical difference between second tone and sandhi third tone in Mandarin Chinese. Except [1], most of the studies focus on the tonal realization in carefully controlled speech, and the relationship between demographic features and tonal realization has not been addressed by existing studies using large-scale speech data. In this paper, we investigate the tonal realization in three large speech corpora of Mandarin Chinese, which contain around 2,300 speakers from different regions of China. The relation between demographic factors (e.g., gender, age, and place of origin) and tonal realization is addressed. The results show that even though the sandhi third tone is close to the second tone in terms of acoustic features, it still displays significant differences in large data. We also report some demographic influences on tonal realization, including age, gender, and places of origin.
The effect of enhanced variability after performance stabilization through constant practice

There is a controversy about the benefits of variable practice on motor learning. This study aimed to analyze the effect of variable practice after the learner stabilized their performance. Thirty-two healthy adults performed a computer-simulated discrete accuracy task in which they had to release a virtual ball to try to hit a target. After a pre-test, the participants were distributed into three training groups: constant practice, variable practice and a group that started practicing in constant conditions, and when their performance stabilized, changed to variable practice. The participants performed 44 sets of 10 repetitions of the task. A post-test and two retention tests were carried out. Variable practice did not show a significant improvement compared to constant practice. Variable practice did not show higher benefits even when performance was stabilized through constant practice, but its effects seem to be modulated by the initial variability of the learners.