Miracle-dz/UniFAR-FTUs huggingface dataset:
Contextual Density Ratio for Language Model Biasing of Sequence to Sequence ASR Systems

End-2-end (E2E) models have become increasingly popular in some ASR tasks because of their performance and advantages. These E2E models directly approximate the posterior distribution of tokens given the acoustic inputs. Consequently, the E2E systems implicitly deﬁne a language model (LM) over the output tokens, which makes the exploitation of independently trained language models less straightforward than in conventional ASR systems. This makes it difﬁcult to dynamically adapt E2E ASR system to contextual proﬁles for better recognizing special words such as named entities. In this work, we propose a contextual density ratio approach for both training a contextual aware E2E model and adapting the language model to named entities. We apply the aforementioned technique to an E2E ASR system, which transcribes doctor and patient con-versations, for better adapting the E2E system to the names in the conversations. Our proposed technique achieves a relative improvement of up to 46.5% on the names over an E2E baseline without degrading the overall recognition accuracy of the whole test set. Moreover, it also surpasses a contextual shallow fusion baseline by 22.1 % relative.
Terrestrial Water Storage Anomalies Emphasize Interannual Variations in Global Mean Sea Level During 1997–1998 and 2015–2016 El Niño Events

Interannual variations in global mean sea level (GMSL) closely correlate with the evolution of El Niño‐Southern Oscillation. However, GMSL differences occur in extreme El Niños; for example, in the 2015–2016 and 1997–1998 El Niños, the peak GMSL during the mature stage of the former (9.00 mm) is almost 2.5 times higher than the latter (3.72 mm). Analyses from satellite and reanalysis data sets show that the disparity in GMSL is primarily due to barystatic (ocean mass) changes. We find that the 2015–2016 event developed not purely as an Eastern Pacific El Niño event but with Central Pacific (CP) El Niño forcing. CP El Niños contribute to a stronger negative anomaly of global terrestrial water storage and subsequent higher barystatic heights. Our results suggest that the mechanism of hydrology‐related interannual variations of GMSL should be further emphasized, as more CP El Niño events are projected to occur.
Cognitive interest as a key indicator of adolescent personality development

The research objective is to show new possibilities for understanding cognitive interest as one of the indicators of personality development. Based on a systematic analysis, the authors clarified the content of the category of “cognitive interest”. A conceptual model of the dialectic of interest in knowledge was proposed. The principles that are the foundation of the process of its learning were revealed. On this ground, educational technology was developed. Long-term observations of the subjects of the educational process, conducted by the authors, allowed determining the dialectical connections of cognitive interest with thinking, attention, memory, speech, and emotions. The pro-posed model of the dialectic of interest in knowledge is conceptual, since based on it, the process of raising interest is built as a didactically thought-out system for managing children’s development, contributing to their personal growth, one of the components of which is educational technology.
A study on the bacterial isolates from blood cultures of a tertiary care hospital

Blood stream infections are the most important and common cause of morbidity and mortality in tertiary care hospitals. Since the results are usually not available promptly a knowledge of epidemiologic and antimicrobial susceptibility pattern of blood pathogens is life saving and very useful for early treatment and recovery of patients. The aim of this study is to describe the epidemiological, bacterial profile and antimicrobial resistance pattern of bloodstream infections in a tertiary care centre.A prospective cross-sectional study was done on seven hundred and eight blood samples collected over a period of six months in the Microbiology laboratory. Blood samples collected under aseptic conditions were cultured by aerobic culture method. Identification of bacterial isolates were done using standard bacteriologic and biochemical testing methods and antibiotic sensitivity testing done by Kirby - Bauer disc diffusion method.Bacteria was isolated in 201 (28.3%) samples with highest rates among newborns 84(41.8%). The most frequent isolates were 111 (55.2%) followed by 49 (24.4%). Results showed high susceptibilities of CoNS 111 (100%) to Vancomycin, Linezolid and 51 (98%) to Meropenem. This study highlights the common prevalent bacteriological agents in bacteremia, their antibiotic susceptibility & resistance patterns. and multi drug resistant were the leading causes of septicaemia in our hospital with Vancomycin, Linezolid and Carbapenems the effective antibiotics against these pathogens respectively.
Practical Challenges of High-Power IGBT’s I-V Curve Measurement and Its Importance in Reliability Analysis

This paper examines the practical challenges of simplified setups aimed at achieving high-power IGBTs’ IC–VCE curve. The slope of this I–V curve (which is defined as on-resistance RCE) and the point where the VCE–VGE curve visibly bends (threshold gate voltage) can be suitable failure precursor parameters to determine an IGBT’s health condition. A simplified/affordable design for these specific measurements can be used for in-situ condition monitoring or field testing of switching devices. First, the possible I–V curve measurement methods are discussed in detail in order to prevent self-heating. The selected design includes two IGBTs in which the high-side IGBT was the device under test (DUT) with a constant gate voltage (VGE) of 15 V. Then, the low-side IGBT was switched by a short pulse (50 μs) to impose a high-current pulse on the DUT. The VCE–VGE curve was also extracted as an important failure-precursor indicator. In the next stage, a power-cycling test was performed, and the impact of degradation on the IGBT was analyzed by these measurement methods. The results show that after 18,000 thermal cycles, a visible shift in I–V curve can be seen. The internal resistance increased by 13%, while the initial collector-emitter voltage and voltage at the knee point in the VCE–VGE curve slightly changed. It is likely that in our case, during the performed power-cycling test and aging process, the bond wires were most affected, but this hypothesis needs further investigation.
Optimisation of absorption power cycle for generator temperatures 60–210°C with LiBr water as a working fluid

ABSTRACT In this work, the absorption power cycle (APC) and reheated absorption power cycle (RHAPC) have been optimised based on the LiBr concentration in the generator and absorber for a wide range of operating temperatures of the generator and absorber. The mathematical model and simulation of the APC and RHAPC are done by using the highly accurate thermodynamic correlations available in the literature. Sensitivity analysis of the exergy and thermal efficiency of the power cycle has been done for operating parameters such as LiBr concentration and the generator temperature. This technique will be helpful to choose an optimised operating parameter for designing the power cycle for practical applications. For APC, the highest thermal efficiency is 19.91% and for RHAPC, it is 29.5%. Economic analysis has been performed for APC and RHAPC operating at optimised operating conditions. GRAPHICAL ABSTRACT
Daily River Water Temperature Prediction: A Comparison between Neural Network and Stochastic Techniques

The temperature of river water (TRW) is an important factor in river ecosystem predictions. This study aims to compare two different types of numerical model for predicting daily TRW in the Warta River basin in Poland. The implemented models were of the stochastic type—Autoregressive (AR), Moving Average (MA), Autoregressive Moving Average (ARMA) and Autoregressive Integrated Moving Average (ARIMA)—and the artificial intelligence (AI) type—Adaptive Neuro Fuzzy Inference System (ANFIS), Radial Basis Function (RBF) and Group Method of Data Handling (GMDH). The ANFIS and RBF models had the most fitted outputs and the AR, ARMA and ARIMA patterns were the most accurate ones. The results showed that both of the model types can significantly present suitable predictions. The stochastic models have somewhat less error with respect to both the highest and lowest TRW deciles than the AIs and were found to be better for prediction studies, with the GMDH complex model in some cases reaching Root Mean Square Error (RMSE) = 0.619 °C and Nash-Sutcliff coefficient (NS) = 0.992, while the AR(2) simple linear model with just two inputs was partially able to achieve better results (RMSE = 0.606 °C and NS = 0.994). Due to these promising outcomes, it is suggested that this work be extended to other catchment areas to extend and generalize the results.
Study of Microstructural and Mechanical Properties of Al/SiC/TiO2 Hybrid Nanocomposites Developed by Microwave Sintering

Aluminum hybrid metal matrix nanocomposites (Al/SiC/TiO2) were synthesized through a microwave-assisted powder metallurgy process, and their evolved microstructure and mechanical properties were investigated. The Al/SiC/TiO2 hybrid nanocomposites were prepared by reinforcing aluminum (Al) matrix with a fixed amount of silicon carbide (SiC) nanoparticles (5 wt.%) and varying concentrations of titanium dioxide (TiO2) nanoparticles (3, 6, and 9 wt.%). The morphology results revealeda uniform distribution of SiC and TiO2 reinforcements in the aluminum matrix. An increase in the hardness and compressive strength of the Al/SiC/TiO2 hybrid nanocomposites was noticed with the increasein TiO2 nanoparticles. The Al/SiC/TiO2 hybrid nanocomposites that had an optimum amount of TiO2 nanoparticles (9 wt.%) showcased the best mechanical properties, with maximum increments of approximately 124%, 90%, and 23% of microhardness (83 ± 3 HV), respectively, yield strength (139 ± 8 MPa), and ultimate compression strength (375 ± 6 MPa) as compared to that of pure Al matrix. The Al/SiC/TiO2 hybrid nanocomposites exhibited the shear mode of fracture during their deformation process.
An Electrically Controlled Pattern- and Polarization-Reconfigurable Cylindrical Dielectric Resonator Antenna

A pattern- and polarization-reconfigurable dielectric resonator antenna (DRA) is presented. It deploys a conventional cylindrical dielectric resonator (DR) with a new switchable feeding network. The feeding network has four slots that are etched in the ground. By tuning the phase distributions in these slots, three DR modes (the TM01δ and two degenerated HEM113 modes) are excited. The former has an omnidirectional radiation pattern, whereas the latter two have boresight patterns with orthogonal polarizations (x- and y-polarization). By tuning the height-to-radius ratio, these modes can be designed to operate at the same frequency, thus enabling both the pattern and polarization reconfigurability. A prototype of the reconfigurable DRA working in 2.4 GHz is fabricated and measured to verify ideas. Reasonable agreement between measurements and simulations is obtained. Our design provides both pattern and polarization reconfigurability, with good efficiency in the band of interest.
Hydrological Responses of Watershed to Historical and Future Land Use Land Cover Change Dynamics of Nashe Watershed, Ethiopia

Land use land cover (LULC) change is the crucial driving force that affects the hydrological processes of a watershed. The changes of LULC have an important influence and are the main factor for monitoring the water balances. The assessment of LULC change is indispensable for sustainable development of land and water resources. Understanding the watershed responses to environmental changes and impacts of LULC classes on hydrological components is vigorous for planning water resources, land resource utilization, and hydrological balance sustaining. In this study, LULC effects on hydrological parameters of the Nashe watershed, Blue Nile River Basin are investigated. For this, historical and future LULC change scenarios in the Nashe watershed are implemented into a calibrated Soil and Water Assessment Tool (SWAT) model. Five LULC scenarios have been developed that represent baseline, current, and future periods corresponding to the map of 1990, 2005, 2019, 2035, and 2050. The predicted increase of agricultural and urban land by decreasing mainly forest land will lead till 2035 to an increase of 2.33% in surface runoff and a decline in ground water flow, lateral flow, and evapotranspiration. Between 2035 and 2050, a gradual increase of grass land and range land could mitigate the undesired tendency. The applied combination of LULC prognosis with process-based hydrologic modeling provide valuable data about the current and future understanding of variation in hydrological parameters and assist concerned bodies to improve land and water management in formulating approaches to minimize the conceivable increment of surface runoff.
Quantification of Oil Fractions of Deep-Fried Wheat Dough and Batter Enriched with Oat and Wheat Bran

This study investigated oil distribution in two types of deep-fried dough products with two moisture levels (65 and 100 wt. %), two bran types (oat and wheat bran), and five bran concentrations (5–20%). The total oil content of fried products was categorised as surface oil (SO), penetrated surface oil (PSO), and structural oil (STO) using a spectrophotometric method. Moisture loss reduced ( p < 0.05 ) from 23.35% in the control to 15.19% fried batter (FB) and to 20% oat bran (OB), while a reverse trend was observed in the fried dough. Reduction of total oil from 0.43 g/g in the control to 0.38 g/g at 20% OB and 8% wheat bran (WB) was observed. At 15% OB and 20% WB, total fat reduced from 0.41 g/g in the control to 0.26 g/g of fried dough (FD). The trend STO < SO < PSO was observed in FD, while FB followed a SO < STO < PSO trend. This investigation indicated that oil uptake reduction in fried dough products is achievable through ingredient modifications. The method of oil distribution measurement used herein can be applied to other thick deep-fried food systems in the assessment of product quality.
Can Deep Models Help a Robot to Tune Its Controller? A Step Closer to Self-Tuning Model Predictive Controllers

Motivated by the difficulty roboticists experience while tuning model predictive controllers (MPCs), we present an automated weight set tuning framework in this work. The enticing feature of the proposed methodology is the active exploration approach that adopts the exploration–exploitation concept at its core. Essentially, it extends the trial-and-error method by benefiting from the retrospective knowledge gained in previous trials, thereby resulting in a faster tuning procedure. Moreover, the tuning framework adopts a deep neural network (DNN)-based robot model to conduct the trials during the simulation tuning phase. Thanks to its high fidelity dynamics representation, a seamless sim-to-real transition is demonstrated. We compare the proposed approach with the customary manual tuning procedure through a user study wherein the users inadvertently apply various tuning methodologies based on their progressive experience with the robot. The results manifest that the proposed methodology provides a safe and time-saving framework over the manual tuning of MPC by resulting in flight-worthy weights in less than half the time. Moreover, this is the first work that presents a complete tuning framework extending from robot modeling to directly obtaining the flight-worthy weight sets to the best of the authors’ knowledge.
A Twisted String, Flexure Hinges Approach for Design of a Wearable Haptic Thimble

Wearable haptic devices in the shape of actuated thimbles are used to render the sense of touch in teleoperation and virtual reality scenarios. The design of similar devices has to comply with concurring requirements and constraints: lightweight and compactness, intensity and bandwidth of the rendered signals. Micro-sized motors require a mechanical reduction to increase the output force, at the cost of noise and vibrations introduced by conventional gear reducers. Here we propose a different actuation method, based on a miniaturized twisted string actuator and a flexure hinge transmission mechanism. The latter is required to transmit and transform the pulling force of the twist actuator to a pushing force of the plate in contact with the fingerpad. It achieves a lightweight and noiseless actuation in a compact mechanism. In this work, we present design guidelines of the proposed approach, optimization, and FEM analysis of the flexure hinge mechanism, implementation of the prototype, and experimental characterization of the twist actuator measuring frequency response and output force capabilities.
A tri-section substrate integrated waveguide filtering power divider with a wide stopband

In this article, a substrate integrated waveguide (SIW) power divider with tri-section filtering topology is proposed. Two TE101-mode SIW cavities and one TE102-mode SIW cavity are placed in the upper and lower substrate layers, respectively. Two vertically stacked SIW cavities are excited simultaneously by one section of SIW. The TE102-mode SIW cavity is introduced to achieve 180°- phase conversion. And then, two controllable transmission zeros and a wide stopband can be obtained. Finally, a tri-section SIW filtering power divider sample is fabricated using the printed circuit board (PCB) technology; and good agreements are achieved in the measured and simulated S-parameters.
Sharing personal experiences and online consumer engagement: A case study of Glossier

ABSTRACT Social media has become influential in the fashion and beauty marketplace where digital communication centers around consumer interests in products and brands. This case study examines how sharing of personal experiences on the digital communication platforms of the Glossier beauty brand influences consumer engagement in an online brand community. In-depth interviews of thirteen consumers of the Glossier brand and its social media channels were conducted. The qualitative method allows the researchers to capture the rich context of the consumer experience and the social reality of online community members through their own words. This case study offers insight into how social media communication, moving beyond simple product reviews, allows a direct-to-consumer brand to effectively leverage the personal experiences of their consumers as a catalyst for learning, advocating for the brand, co-developing the brand, and building consumer and brand relationships. A new perspective from Brodie et al.’sconsumer engagement model highlights key interrelated processes that evolve from the sharing of consumer experiences and adding value to building a robust brand community.
Clinical Discernment, Bone Marrow, and Molecular Diagnostics Are Equally Important to Solve the Phenotypic Mimicry among Subtypes of Myeloproliferative Neoplasms

The 2016 WHO classification integrates clinical, bone marrow (BM)-morphology, and molecular features to define disease entities. This together with the advancements in molecular detection and standardization of BM features enable an accurate diagnosis of myeloproliferative neoplasms (MPN) in the majority of patients. Diagnostic challenges remain due to phenotypic mimicry of MPN, failing specificity of BM-morphology, and the fact that phenotype-driver mutations, such as JAK2V617F, are not exclusive to a particular MPN, and their absence does not preclude any of these. We present a series of cases to illustrate themes to be considered in complex cases of MPN, such as triple-negative (TN)-MPN or MPN-unclassifiable (MPN-U). Eleven patients labelled as TN-MPN or MPN-U were included. Serum tryptase and NGS were part of a systematic/sequential multidisciplinary evaluation. Results were clustered into four categories based on diagnostic entities and/or how these diagnoses were made: (A) With expanding molecular techniques, BCR-ABL1 and karyotyping should not be missed; (B) systemic mastocytosis is underdiagnosed and often missed; (C) benign non-clonal disorders could mimic MPN; and (D) NGS could prove clonality in some “TN”-MPN cases. The prognostic/therapeutic consequences of an accurate diagnosis are immense. In TN-MPN or MPN-U cases, a multidisciplinary re-evaluation integrating molecular results, BM-morphology, and clinical judgment is crucial.
A Novel Hybrid Deep Learning Model for Detecting COVID-19-Related Rumors on Social Media Based on LSTM and Concatenated Parallel CNNs

Spreading rumors in social media is considered under cybercrimes that affect people, societies, and governments. For instance, some criminals create rumors and send them on the internet, then other people help them to spread it. Spreading rumors can be an example of cyber abuse, where rumors or lies about the victim are posted on the internet to send threatening messages or to share the victim’s personal information. During pandemics, a large amount of rumors spreads on social media very fast, which have dramatic effects on people’s health. Detecting these rumors manually by the authorities is very difficult in these open platforms. Therefore, several researchers conducted studies on utilizing intelligent methods for detecting such rumors. The detection methods can be classified mainly into machine learning-based and deep learning-based methods. The deep learning methods have comparative advantages against machine learning ones as they do not require preprocessing and feature engineering processes and their performance showed superior enhancements in many fields. Therefore, this paper aims to propose a Novel Hybrid Deep Learning Model for Detecting COVID-19-related Rumors on Social Media (LSTM–PCNN). The proposed model is based on a Long Short-Term Memory (LSTM) and Concatenated Parallel Convolutional Neural Networks (PCNN). The experiments were conducted on an ArCOV-19 dataset that included 3157 tweets; 1480 of them were rumors (46.87%) and 1677 tweets were non-rumors (53.12%). The findings of the proposed model showed a superior performance compared to other methods in terms of accuracy, recall, precision, and F-score.
OFİS ORTAMLARINDA EKRANLI ARAÇLARLA YAPILAN ÇALIŞMALARDA SAĞLIK VE GÜVENLİK ÖNLEMLERİ

Makale Tarihçesi ÖzGünümüzde çoğu insan çalışma alanı olarak ofislerde zamanının büyük bir bölümünü geçirirler. Bu nedenle ofis ortamında çalışanlar için ergonomi oldukça önem arz etmektedir. Ergonomik olarak tasarlanmış bir ofis ortamının gerek çalışan psikolojisi gerekse iş verimliliği açısından önemli olduğu bir gerçektir. Çünkü bu kavramla çalışanın daha huzur verici bir ortamda çalışması sağlanır. Genellikle ekranlı araçlarla yapılan işlerde çalışanlar uygun olmayan ofis ortamlarından dolayı ciddi sağlık ve güvenlik problemleriyle karşı karşıyadır. Bu nedenle uygun olmayan işyerlerinde çalışanlar için bir takım mesleki kas iskelet sistemi rahatsızlıkları meydana gelebilir. Bu durum hem çalışanın motivasyonunu hem de iş verimliliğini azaltır. Türkiye’de yürürlüğe giren “Ekranlı Araçlarla Çalışmalarda Sağlık ve Güvenlik Önlemleri Hakkında Yönetmelik” ile bu konunun yasal zemini hazırlanmıştır. Bu yönetmelikte yer alan hükümlere uyulan ofislerde, çalışanların sağlık ve güvenliği korunarak meydana gelebilecek iş kazası ve meslek hastalıkları önemli ölçüde azalabilecektir. Gönderim: 23.09. 2020