Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploring The Role of Employees Impediments in Determining The Employees Performance

The employees’ performance is the building block for the organizations to attain competitive edge over the competitors in the contemporary competitive situations. The organizations including the higher institutions, are direly needed to focus on employees’ performance if these institutions are serious in reflecting their desired standing. However, there are certain impediments associated with the employees’ performance among which the job burnout, absenteeism, commitment and motivation are foremost. This study aimed at probing these impediments towards employees’ performance in the context of higher education. The data was collected from teaching faculty from higher institutions of KP, Pakistan. The results have provided enough evidence in deciding relationships between employees’ impediments and employees’ performance. Some recommendations have been offered to the policymakers to cater these impediments to achieve the desired standards. Some suggestions have also been providing to future researchers to examine these variables in other contexts by using some mediators to obtained better results.
X-Chromosome Inactivation and Related Diseases

X-chromosome inactivation (XCI) is the form of dosage compensation in mammalian female cells to balance X-linked gene expression levels of the two sexes. Many diseases are related to XCI due to inactivation escape and skewing, and the symptoms and severity of these diseases also largely depend on the status of XCI. They can be divided into 3 types: X-linked diseases, diseases that are affected by XCI escape, and X-chromosome aneuploidy. Here, we review representative diseases in terms of their definition, symptoms, and XCI's role in the pathogenesis of these diseases.
Evaluation and Mitigation of Racial Bias in Clinical Machine Learning Models: Scoping Review

Background Racial bias is a key concern regarding the development, validation, and implementation of machine learning (ML) models in clinical settings. Despite the potential of bias to propagate health disparities, racial bias in clinical ML has yet to be thoroughly examined and best practices for bias mitigation remain unclear. Objective Our objective was to perform a scoping review to characterize the methods by which the racial bias of ML has been assessed and describe strategies that may be used to enhance algorithmic fairness in clinical ML. Methods A scoping review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) Extension for Scoping Reviews. A literature search using PubMed, Scopus, and Embase databases, as well as Google Scholar, identified 635 records, of which 12 studies were included. Results Applications of ML were varied and involved diagnosis, outcome prediction, and clinical score prediction performed on data sets including images, diagnostic studies, clinical text, and clinical variables. Of the 12 studies, 1 (8%) described a model in routine clinical use, 2 (17%) examined prospectively validated clinical models, and the remaining 9 (75%) described internally validated models. In addition, 8 (67%) studies concluded that racial bias was present, 2 (17%) concluded that it was not, and 2 (17%) assessed the implementation of bias mitigation strategies without comparison to a baseline model. Fairness metrics used to assess algorithmic racial bias were inconsistent. The most commonly observed metrics were equal opportunity difference (5/12, 42%), accuracy (4/12, 25%), and disparate impact (2/12, 17%). All 8 (67%) studies that implemented methods for mitigation of racial bias successfully increased fairness, as measured by the authors’ chosen metrics. Preprocessing methods of bias mitigation were most commonly used across all studies that implemented them. Conclusions The broad scope of medical ML applications and potential patient harms demand an increased emphasis on evaluation and mitigation of racial bias in clinical ML. However, the adoption of algorithmic fairness principles in medicine remains inconsistent and is limited by poor data availability and ML model reporting. We recommend that researchers and journal editors emphasize standardized reporting and data availability in medical ML studies to improve transparency and facilitate evaluation for racial bias.
Design of integrated broadband vanadium dioxide hybrid plasmonic modulator

With increasing demands in all-optical signal processing functions such as switching and modulating in integrated photonic-electronic circuits, plasmonic modulators are getting lots of attentions. In this paper, we present a novel design of hybrid plasmonic modulator based on insulator-metal phase transition in vanadium dioxide (VO2). The device consists of two silicon tapers and a metal-VO2-insulator-silicon hybrid plasmonic structure that are inserted into a strip silicon waveguide, with 120 nm x 800 nm modulating section within 450 nm x 2 μm device footprint. By taking advantages of the large refractive index contrast between the metal and semiconductor phase of VO2, the proposed modulator achieves a high modulation depth of 14.852 dB with a low insertion loss of 1.804 dB. Moreover, we have systematically analyzed the geometry dependence of the device and the influence of broadband light on modulation performances. Considering the effects of seed layer in VO2 deposition process, we have also studied the modulating performances using different dielectric layers. Our design can be practically fabricated, and a complete process flow is provided. We believe this work has great values in promoting the industrial process of silicon photonics in the fields of optical communication and data storage.
The relationship between postnatal hypoglycemia and umbilical artery Doppler ultrasonography in neonates with intrauterine growth restriction: A longitudinal follow-up study

Abstract Background Intrauterine growth restriction (IUGR) refers to fetuses with an estimated ultrasonography weight below the 10% percentile. Hypoglycemia is a major concern in neonates with IUGR. Objective To investigate the relationship between umbilical artery (UA) Doppler ultrasonography and neonate hypoglycemia and IUGR. Materials and Methods This was a longitudinal follow-up study consisting of 114 neonates (gestational age of 28-40 wk) born with IUGR in the third trimester of pregnancy at Shahid Sadoughi Hospital, Yazd, Iran between May 2016 and October 2017. The neonates were assigned into three subgroups of normal UA Doppler, absent end-diastolic flow (EDF) in UA Doppler, and reverse EDF in UA Doppler. The blood glucose of the neonates was checked one, two, three, six, 12, 24 and 48 hr after birth, and the neonates were placed in the hypoglycemia or euglycemia groups according to guidelines. Results Out of the 114 neonates included in the study, 75 (65.8%) had normal UA Doppler, 29 (25.4%) had absent EDF in UA Doppler, and 10 (8.8%) had reverse EDF in UA Doppler. There was a significant difference in the mean blood glucose in the first hr between the normal UA Doppler group and the reverse EDF in UA Doppler group (p < 0.01). Conclusion Postnatal hypoglycemia in neonates with IUGR is associated with the result of UA Doppler ultrasonography during pregnancy.
Application of Russian Language Phonemics to Generate Macedonian Speech Recognition Model Using Sphinx

Speech-recognition provides possibilities for improved user experience and new level of features in various applications. Although there are widely available open-source and proprietary systems for speech recognition and synthesis for the more widely used languages, there are no available and robust enough systems for the Macedonian language. Building a speech recognition system requires a lot of high-quality recordings, which is expensive operation. To overcome this issue we propose applying some background knowledge and using existing speech synthesis engines to train speech recognition system. Since the Macedonian language belongs to the group of Slavic languages, there are many similarities between them. In this paper we apply this fact to generate a speech synthesis module for the Macedonian language based on the Russian language model. Furthermore, we use the speech synthesis module to build a speech recognition module using the CMUSphinx Toolkit. Finally the results are presented and they conﬁrm that a system with substantial quality can be built without the need of manual recordings in the speciﬁc language.
A Predictive Study Between Anxiety and Fear of COVID-19 With Psychological Behavior Response: The Mediation Role of Perceived Stress

Objective Despite the abundance of studies linking fear and anxiety to COVID-19, there are limited studies that examine how these elements impact psychological behavioral responses, especially in Iran. The aim of this study was to investigate the relationship between anxiety and fear of COVID-19 with psychological behavior response, whether this relationship is mediated by role of perceived stress among Iranian population during the COVID-19 pandemic. Methods A predictive cross-sectional study was used to investigate the relationships between COVID-19 anxiety syndrome, fear of COVID-19 with psychological behavioral responses due to the pandemic, and the mediating role of the COVID-19 perceived stress in these relationships. Results The current study revealed that during the COVID-19 pandemic, fear and anxiety of COVID-19 can influence the psychological behavioral responses of individuals; however, this can be explained through perceived stress. Conclusion As such, the current study points out that the individuals who perceived high stress due to COVID-19 were more likely to comply with guidelines, which has given new insight into this field. The current study findings are applicable for health policymakers in order to help them in understanding human behavior for developing health promotion programs and also for fostering resilience among the general population.
A method for representation of space non-cooperative target attitude based on point cloud data

The pose measurement of space non-cooperative targets is a key technology for approaching, flying around, and manipulating space targets. This paper presents a method for the attitude representation of non-cooperative targets in space based on laser point cloud data, and demonstrates the effectiveness and practically of the method from the basic principles , the ability of the method to characterize targets’ attitude, and the anti-noise performance of the method to resist measurement noise of point cloud. This attitude characterization method realizes the extraction and concise from massive point cloud data of space non-cooperative targets to attitude information, and lays a foundation for the subsequent intelligent, stable, and real-time pose measurement.
How Can We Address Professional Isolation Among Traditionally Underrepresented Students? The Importance of Peer Mentorship

Abstract Professional isolation is a perennial problem among academics, but it is especially common among traditionally underrepresented students who lack the social networks that could provide them support. One way to forge stronger social networks among traditionally underrepresented students is through peer mentorship. Underrepresented graduate students often serve as mentors to underrepresented undergraduate students. Senior underrepresented graduate students in turn provide mentorship to their more junior counterparts. The forms of peer mentorship provided are invaluable because they have experience overcoming many of the same challenges as their less experienced counterparts. In this reflection essay we, a group of graduate students from traditionally underrepresented communities, draw on our lived experiences to discuss how professional isolation among underrepresented students can be overcome by participating in peer mentorship programs.
Dual EKF-based State and Parameter Estimator for a LiFePO4 Battery Cell

This work presents the design of a dual extended Kalman filter (EKF) as a state/parameter estimator suitable for adaptive state-of-charge (SoC) estimation of an automotive lithium–iron–phosphate (LiFePO₄) cell. The design of both estimators is based on an experimentally identified, lumped-parameter equivalent battery electrical circuit model. In the proposed estimation scheme, the parameter estimator has been used to adapt the SoC EKF-based estimator, which may be sensitive to nonlinear map errors of battery parameters. A suitable weighting scheme has also been proposed to achieve a smooth transition between the parameter estimator-based adaptation and internal model within the SoC estimator. The effectiveness of the proposed SoC and parameter estimators, as well as the combined dual estimator, has been verified through computer simulations on the developed battery model subject to New European Driving Cycle (NEDC) related operating regimes.
A Simple-To-Use Nomogram for Predicting Early Death in Metastatic Renal Cell Carcinoma: A Population-Based Study

Background Metastatic renal cell carcinoma (mRCC) is usually considered to have a poor prognosis, which has a high risk of early death (≤3 months). Our aim was to developed a predictive nomogram for early death of mRCC. Methods The SEER database was accessed to obtain the related information of 6,005 mRCC patients between 2010 and 2015. They were randomly divided into primary cohort and validation cohort in radio of 7:3. The optimal cut-off point regarding age at diagnosis and tumor size were identified by the X-tile analysis. Univariate and multivariate logistic regression models were applied to determine significant independent risk factors contributed to early death. A practical nomogram was constructed and then verified by using calibration plots, receiver operating characteristics (ROCs) curve, and decision curve analysis (DCA). Results There were 6,005 patients with mRCC included in the predictive model, where 1,816 patients went through early death (death within ≤3 months of diagnosis), and among them 1,687 patients died of mRCC. Based on 11 significant risk factors, including age, grade, N-stage, histologic type, metastatic sites (bone, lung, liver and brain) and treatments (surgery, radiation, and chemotherapy), a practical nomogram was developed. The model's excellent effectiveness, discrimination and clinical practicality were proved by the AUC value, calibration plots and DCA, respectively. Conclusions The nomogram may play a major part in distinguishing the early death of mRCC patients, which can assist clinicians in individualized medicine.
Experimental investigation on laser in-situ assisted ultra-precision cutting of fused silica

Fused silica has been widely used in precision instruments in extreme environment for its excellent properties such as high temperature resistance and thermal shock resistance. However, the brittleness and hardness nature of fused silica makes it difficult to achieve high quality surface through conventional technology. In recent years, the laser in-situ assisted machining has been proposed as a promising technique for ultra-precision machining of many brittle and hard materials. In this study, numerical simulations and cutting experiments were conducted to study the temperature field and cutting mechanism in laser in-situ assisted machining of fused silica. The cutting temperature and machined surface quality under different machine parameters were characterized. The results indicate that the assistance of laser improves the material’s ductile machinability significantly, which contributes to a higher surface quality compared to conventional machining. The depth of cut (DOC), laser power and rotation speed have a great impact on the surface quality, and surface roughness values in the order of 20 nm can be achieved under appropriate machine parameters.
Dynamics of wave vibrational motors

Dynamics of wave type vibrational motors is analyzed in the article. The vibrational motors are mechanisms transforming high frequency oscillations into directional movement. The constructions of the vibrational motors are described and mathematical models are developed. The formulas to describe the velocity of rotor movement and the acceleration are presented. The major dynamical parameters of vibrational motors are analytically defined. Wave type vibrational motors are developed at Kaunas University of Technology.
Diagnosing and distinguishing rotor eccentricity from partial demagnetisation of interior PMSM based on fluctuation of high-frequency d-axis inductance and rotor flux

An appropriate and complete mathematical modelling approach is developed for an interior permanent magnet synchronous motor (PMSM) with general eccentricity. The relationships between air-gap eccentricity and simulated inductances in different coordinate frames are analysed in depth. Then, an analytical high-frequency inductance model of the interior PMSM with rotor eccentricity is developed. Based on this model, an online diagnostic approach is proposed, which includes estimation of the high-frequency d-axis inductance and permanent magnet (PM) flux. Thus the rotor eccentricity and PM partial demagnetisation can be detected and distinguished. Experimental results validate the proposed theory and fault diagnosis approach. Finally, an effective and reliable eccentricity indicator is presented. It is shown that analysis of the essential sources of fault characteristics facilitates motor fault diagnosis.
Physicochemical and sensory characteristics of m'bahou: A traditional dish consumed in Côte d'Ivoire

M'bahou is a dish consumed in the eastern and central part of Côte d’Ivoire. This dish allows the use of senescent plantain, product relatively cheaper and often rejected on the market due to its high perishability. In this study, the nutritional properties as well as sensory characteristics (colour, shape, size, texture, general appearance, smell, aroma, taste, chewiness) of m’bahou were investigated. This dish produces, then dried had relatively low moisture (7.13%), ash (1.93%), fat (0.24%), proteins (3.07%), crude fiber (2.87%) contents and were good sources of carbohydrates (87.64%), starch (61.15%), energy (364,87 kcal/100 g), vitamin A (134.67 µg/100 g), vitamin B1 (49.57 µg/100 g) and vitamin B2 (564.87 µg/100 g). Mineral composition revealed that potassium (120.32 ± 0.21 mg /100 g dm) and calcium (85.50 ± 0.11 mg /100 g dm) was the most abundant mineral followed by sodium (55.71 ± 1.30 mg /100 g dm), phosphorus (48.10 ± 0.62 mg /100 g dm) and magnesium (46.23 ± 0.06 mg /100 g dm). For Phytochemical compounds, polyphenols (109.64 ± 7.40 mg GAE/100 g dm) were higher than phytates (50.42 ± 1.63 mg/100 g), tannins (27.01 ± 0.35 mg tannic acid/100 g), flavonoids (4.32 ± 0.38 mg quercetin/100 g). The mean scores of the sensory descriptors given by panelists for overall acceptability ranged from 6.40 ± 1.29 to 7.38 ± 1.19 on a 9-point scale, corresponding to pleasant level, so acceptable. Valorization of this dish would be more advantageous because it could contribute more to the reduction losses.
Intention to adopt Industry 4.0 technologies among small and medium
enterprises in the Malaysian dairy manufacturing industry

Small and medium enterprises (SMEs) are one of the key economic growth engines which play vital roles in Malaysia’s economy. In the manufacturing sector, SMEs are considered the backbone of industrial development. Presently, the dairy manufacturing industry is one with high potential. Technology is one of the enablers that can assist companies to improve their performances. Presently, SMEs are still hesitant to embrace and adopt new technology. The fundamental objective of this study was to identify the determinants of the intention to adopt Industry 4.0 technologies among SMEs in Malaysian. Data were collected from 114 managers of Small and Medium Enterprises (SMEs) and was analysed using SPSS. The findings from multiple regression revealed that the intention of SMEs to adopt Industry 4.0 Technologies was positively influenced by perceived usefulness (PU), perceived ease of use (PEU), subjective norm (SN), perceived behaviour control (PBC) and attitude (Att). Attitude had partial mediation effects on both relationships between PU and intention. It also has relationships between PEU and intention in adopting Industry 4.0 Technologies. The paper concludes and supports the assumptions of two theories - Theory of Planned Behaviour (TPB) and Technology Acceptance Model (TAM). This study contributes to enhancing managers and higher authority of SMEs in deciding the future course of their manufacturing firms and policymakers in mapping out plans for Malaysian SMEs in the dairy manufacturing industry.
Vibration characteristics of channel steel-concrete composite girders: An experimental and numerical analysis

The broad application of steel and steel-concrete bridges has caused significant vibration and noise problems. Although the channel steel-concrete composite girder is a commonly used bridge type, the vibration transmission performance and structural optimization design (concrete deck, stiffeners, transverse connection components, etc.) from the perspective of vibration control have not been well studied. In this paper, experimental and numerical approaches are combined to investigate the dynamic properties of a steel-channel girder in the audible frequency range (20–2000 Hz). A steel-channel girder is tested via hammering. The effects of damping, stiffeners, and a concrete deck on structural vibration are evaluated using the finite element method. The experimental results indicate negligible differences in the vibration responses on a single plate, but large differences at different sections. The results are influenced by the effects of the distance and transmission path. The numerical results reveal that increasing the damping and stiffness (e.g., setting stiffeners) are both effective in reducing vibrations. Furthermore, increasing the stiffness has a more prominent effect on structural vibrations and their frequency dependence, whereas increasing the damping ratio can stably reduce structural vibrations. The simulation results indicate that installing a concrete deck is the most effective approach to vibration reduction, as it can decrease overall vibration by more than 10 dB. Vertical web stiffeners have stronger effects on vibration reduction than other stiffening countermeasures (e.g., transverse connection components and longitudinal bottom plate stiffeners).
DEDNet: an infrared and visible image fusion architecture based on dual-encoder and channel-picking/Gaussian-filtering models

DenseFuse is a new approach for infrared and visible image fusion. Considering the single encoding strategy of DenseFuse, we propose a dual-encoder DenseNet (DEDNet), which develops a heterogenous image dual-encoder and a channel picking/Gaussian filtering based fusion strategy. The proposed method includes encoding layers, fusion strategy and decoder, in which encoding layers consist of dual encoders. Since infrared and visible images have different imaging mechanisms, the dual encoders can extract the features of infrared and visible images more effectively and improve the quality of fused images. The fusion strategy based on l1-norm's channel selection and Gaussian filtering improves the structural integrity and spatial correlation of the fused features. In the DEDNet, the infrared image is input to the infrared encoder to get the infrared features while the visible image is input to the visible encoder to get the visible features. Then, the fusion strategy fuses the infrared and visible features structurally and spatially. Finally, the decoder reconstructs the fused features to obtain the fused image. Experiments show that the DEDNet achieves competitive results in both subjective and objective evaluation metrics compared with other fusion approaches.