Miracle-dz/UniFAR-FTUs huggingface dataset:
Research Online Research Online Enhancing target speech based on nonlinear soft masking using a Enhancing target speech based on nonlinear soft masking using a single acoustic vector sensor single acoustic vector sensor

Abstract Enhancing speech captured by distant microphones is a challenging task. In this study, we investigate the multichannel signal properties of the single acoustic vector sensor (AVS) to obtain the inter-sensor data ratio (ISDR) model in the time-frequency (TF) domain. Then, the monotone functions describing the relationship between the ISDRs and the direction of arrival (DOA) of the target speaker are derived. For the target speech enhancement (SE) task, the DOA of the target speaker is given, and the ISDRs are calculated. Hence, the TF components dominated by the target speech are extracted with high probability using the established monotone functions, and then, a nonlinear soft mask of the target speech is generated. As a result, a masking-based speech enhancement method is developed, which is termed the AVS-SMASK method. Extensive experiments with simulated data and recorded data have been carried out to validate the effectiveness of our proposed AVS-SMASK method in terms of suppressing spatial speech interferences and reducing the adverse impact of the additive background noise while maintaining less speech distortion. Moreover, our AVS-SMASK method is computationally inexpensive, and the AVS is of a small physical size. These merits are favorable to many applications, such as robot auditory systems. Abstract: Enhancing speech captured by distant microphones is a challenging task. In this study, we investigate the multichannel signal properties of the single acoustic vector sensor (AVS) to obtain the inter-sensor data ratio (ISDR) model in the time-frequency (TF) domain. Then, the monotone functions describing the relationship between the ISDRs and the direction of arrival (DOA) of the target speaker are derived. For the target speech enhancement (SE) task, the DOA of the target speaker is given, and the ISDRs are calculated. Hence, the TF components dominated by the target speech are extracted with high probability using the established monotone functions, and then, a nonlinear soft mask of the target speech is generated. As a result, a masking-based speech enhancement method is developed, which is termed the AVS-SMASK method. Extensive experiments with simulated data and recorded data have been carried out to validate the effectiveness of our proposed AVS-SMASK method in terms of suppressing spatial speech interferences and reducing the adverse impact of the additive background noise while maintaining less speech distortion. Moreover, our AVS-SMASK method is computationally inexpensive, and the AVS is of a small physical size. These merits are favorable to many applications, such as robot auditory systems.
Current Distortion Optimization for Electrical Drives at Low Switching Frequencies

This work addresses an optimization problem for electrical drives at low switching frequencies. Two approaches are developed and compared in this dissertation. The first one is an offline current distortion optimization algorithm that has advantages in terms of problem formulation and calculation times. The second approach is an online optimization based on stator flux predictions. Finally, the performance of both approaches is analyzed and compared through experimental results for a 5-level Flying Capacitor converter. However, the algorithms can be applied to any other topology with any voltage levels.
Challenges for Product Development of Orthopedic Implants

The paper represents the complete product development activities and challenges in orthopedic implants. The need for patient comfort and ease of surgeon’s skills in implant placement enhance the challenges for the development of accurate in geometry and orientation with the help of medical devices or fixtures. The aim is to reduce operating time with preplan surgery with minimum risk and also with minimum cost. All these processes are done more effectively with the help of advanced computing technology.
Tests of Significance in Theory and Practice

The best (most widely) received theory for tests of significance is that due largely to Fisher. Embellished with Neyman's mathematics, Fisher's theory is very well received. But Fisher's logic is not consistent with Bayes' theorem. And Bayes' theorem is beyond reproach. Thus, Fisher's logic is deficient. However, in practice, there is often some redress. Indeed, sometimes Fisher's level of significance P coincides mathematically with the posterior probability of the null hypothesis, i.e. P=p(hOIE), where E is the sample event (evidence). More generally, a good Fisherian tends intuitively (although certainly not inevitably) toward the inference he would make if he employed Bayes' theorem with explicit subjective priors. In effect, he is almost Bayesian. 1 In theory
Wilson’s functional equation for vector and matrix functions

We determine the general solution of the functional equation f(x + y) + f(x y) = A(y)f(x) (xy E G), where G is a 2-divisible abelian group, f is a vector-valued function and A is a matrix-valued function. Using this result we solve the scalar equation f(x + y) + f(x-y) = g1(x)hl(y) + g2(x)h2(Y) (xy E G), which contains as special cases, among others, the d'Alembert and Wilson equations and the parallelogram law.
AN EFFICIENT METHOD TO AUTOMATE POTHOLE DETECTION IN ROAD SURFACE USING IOT

With the development of information technology, the digital image processing has the characteristics of strong permeability, large use of action and good comprehensive benefits. A road maintenance pothole detection is one of the important tasks. A road surface modelling or road image analysis is generally come from computer vision approaches. However, these two categories were always used independently. Furthermore, the accuracy of the pothole detection is not satisfactory. These challenges promote the development of a better application to detect potholes, cracks using the digital image processing like segmentation, extraction, recognition, and morphology from the images of road surface by using image processing. We are proposing an application system with efficient digital image processing techniques to improve the accuracy and consistency of obtaining accurate shapes of potholes and topologies, etc. The successful detection accuracy is around 98.7% and the overall pixel-level accuracy is approximately 99.6%. By using the digital image processing techniques, the detected potholes and cracks are updated to the web server by using IOT device.
Statistical Approach to Quantum Field Theory: An Introduction

Introduction. - Path Integrals in Quantum and Statistical Mechanics. - High-Dimensional Integrals. - Monte-Carlo Simulations in Quantum Mechanics. - Scalar Fields at Zero and Finite Temperature. - Classical Spin Models: An Introduction. - Mean Field Approximation. - Transfer Matrices, Correlation Inequalities and Roots of Partition Functions. - High-Temperature and Low-Temperature Expansions. - Peierls Argument and Duality Transformations. - Renormalization Group on the Lattice. - Functional Renormalization Group. - Lattice Gauge Theories. - Two-dimensional Lattice Gauge Theories and Group Integrals. - Fermions on a Lattice. - Index.
PENGUKURAN EFEKTIFITAS SISTEM INFORMASI

After implementation of IS, required post-implementation review to determine the effectiveness of IS used by looking the influence between variables in measuring the effectiveness of IS. The results of tests performed for variables F Test System Quality, Information Quality and Service Quality to variable Use had no significant effect, while for the t test is performed, the variable does not affect Service Quality significantly Variable on Use. F test on the variable System Quality, Information Quality and Service Quality of Variable User Satisfaction while obtaining significant results for the t test performed, the variable Service Quality variables had no significant effect on User Satisfaction. While the measurements for the F test between the variables System Quality, Information Quality, Service Quality, Use and User Satisfaction variables have a significant Net Benefits among all variables, the t test conducted prove the variable Service Quality no significant effect on the variable Net Benefits Keywords: Efektifitas Sistem Informasi, System Quality, Information Quality, Service Quality, Use, User Satisfaction, Net Benefits
Investment under Up-and Downstream Uncertainty ?

We empirically and theoretically show that uncertainty’s impact on firms’ investment decisions depends on its source in the supply-chain. A real-option model with time-to-build predicts that only upstream uncertainty suppresses firms’ economic activity, since upstream uncertainty from suppliers affects firms in the shorter-run, while downstream uncertainty from customers affects the longer-run. Using production-network data, we provide micro-level evidence that upstream (downstream) uncertainty is negatively (positively) related to firm-level investment and valuations, as predicted theoretically. At the macrolevel, these two uncertainties oppositely predict aggregate consumption, output, and investment growth. Lastly, COVID-19-induced uncertainty is predominantly downstream, which need not hinder economic recovery. JEL classification: E32, D81, D50, L14, G11, G12
Origin of Interfacial Charges of Al2o3/Si and Al2o3/Gan Heterogeneous Heterostructures

Al 2 O 3 is a broadly employed dielectric and significant interfacial charges occur at Al 2 O 3 /semiconductor interfaces. However, the charge origin is often unclear that severely impacts device engineering and design. Al 2 O 3 /Si and Al 2 O 3 /GaN are two of the most common heterogeneous heterostructures (H2s) for many crucial devices including GaN transistors and Si solar cells. While negative charges are extensively observed in Al 2 O 3 /Si, positive charges exist in Al 2 O 3 /GaN, both of which are not well understood. In this study, we performed in-depth interfacial studies of the Al 2 O 3 /Si and Al 2 O 3 /GaN H2s to clarify the origin of the interfacial charges. Stoichiometry deviations were found at the interfaces of the two H2s where Al surpasses O for Al 2 O 3 /GaN, whereas O dominates at the Al 2 O 3 /Si interface. Therefore, we propose that the different interfacial charges are caused by nonstoichiometry atomic ratios of Al 2 O 3 at the interface. The study indicates the important role of the semiconductor surface on the device performance, provide a deep understanding on the origin of interfacial charges at the insulator-semiconductor interfaces.
Correlating IgG Levels with Neutralising Antibody Levels to Indicate Clinical Protection in Healthcare Workers at Risk during a Measles Outbreak

The rapid transmission of measles poses a great challenge for measles elimination. Thus, rapid testing is required to screen the health status in the population during measles outbreaks. A pseudotype-based virus neutralisation assay was used to measure neutralising antibody titres in serum samples collected from healthcare workers in Sheffield during the measles outbreak in 2016. Vesicular stomatitis virus (VSV) pseudotypes bearing the haemagglutinin and fusion glycoproteins of measles virus (MeV) and carrying a luciferase marker gene were prepared; the neutralising antibody titre was defined as the dilution resulting in 90% reduction in luciferase activity. Spearman’s correlation coefficients between IgG titres and neutralising antibody levels ranged from 0.40 to 0.55 (p < 0.05) or from 0.71 to 0.79 (p < 0.0001) when the IgG titres were obtained using different testing kits. In addition, the currently used vaccine was observed to cross-neutralise most circulating MeV genotypes. However, the percentage of individuals being “well-protected” was lower than 95%, the target rate of vaccination coverage to eliminate measles. These results demonstrate that the level of clinical protection against measles in individuals could be inferred by IgG titre, as long as a precise correlation has been established between IgG testing and neutralisation assay; moreover, maintaining a high vaccination coverage rate is still necessary for measles elimination.
Prevalence, Predictors, and Experience of Moral Suffering in Nursing and Care Home Staff during the COVID-19 Pandemic: A Mixed-Methods Systematic Review

(1) Background: Nursing and care home staff experienced high death rates of older residents and increased occupational and psychosocial pressures during the COVID-19 pandemic. The literature has previously found this group to be at risk of developing mental health conditions, moral injury (MI), and moral distress (MD). The latter two terms refer to the perceived ethical wrongdoing which contravenes an individual’s moral beliefs and elicits adverse emotional responses. (2) Method: A systematic review was conducted to explore the prevalence, predictors, and psychological experience of MI and MD in the aforementioned population during the COVID-19 pandemic. The databases CINAHL, APA PsychINFO, APA PsychArticles, Web of Science, Medline, and Scopus were systematically searched for original research studies of all designs, published in English, with no geographical restrictions, and dating from when COVID-19 was declared a public health emergency on the 30 January 2020 to the 3 January 2022. Out of 531 studies screened for eligibility, 8 studies were selected for review. A thematic analysis was undertaken to examine the major underpinning themes. (3) Results: MI, MD, and related constructs (notably secondary traumatic stress) were evidenced to be present in staff, although most studies did not explore the prevalence or predictors. The elicited major themes were resource deficits, role challenges, communication and leadership, and emotional and psychosocial consequences. (4) Conclusions: Our findings suggest that moral injury and moral distress were likely to be present prior to COVID-19 but have been exacerbated by the pandemic. Whilst studies were generally of high quality, the dearth of quantitative studies assessing prevalence and predictors suggests a research need, enabling the exploration of causal relationships between variables. However, the implied presence of MI and MD warrants intervention developments and workplace support for nursing and care home staff.
Detergent-Free Isolation of Membrane Proteins and Strategies to Study Them in a Near-Native Membrane Environment

Atomic-resolution structural studies of membrane-associated proteins and peptides in a membrane environment are important to fully understand their biological function and the roles played by them in the pathology of many diseases. However, the complexity of the cell membrane has severely limited the application of commonly used biophysical and biochemical techniques. Recent advancements in NMR spectroscopy and cryoEM approaches and the development of novel membrane mimetics have overcome some of the major challenges in this area. For example, the development of a variety of lipid-nanodiscs has enabled stable reconstitution and structural and functional studies of membrane proteins. In particular, the ability of synthetic amphipathic polymers to isolate membrane proteins directly from the cell membrane, along with the associated membrane components such as lipids, without the use of a detergent, has opened new avenues to study the structure and function of membrane proteins using a variety of biophysical and biological approaches. This review article is focused on covering the various polymers and approaches developed and their applications for the functional reconstitution and structural investigation of membrane proteins. The unique advantages and limitations of the use of synthetic polymers are also discussed.
Software Stories Guide

Classical requirements engineering approaches [Pohl2010] and analysis and design techniques [RJB2004] do not fit agile software development. Agile software development does not aim for a complete requirements elicitation before software development starts. Instead agile software development deploys an on-site customer [Beck2000] or a product owner [TN1986] [Schwaber2004] who provides requirements on-demand. Similarly, agile software development does not aim on a complete system analysis and design before software development starts. Instead agile software development uses refactoring [FB1999] to evolve the system architecture during development. While eXtreme Programming abandons analysis and design totally, there is an urgent need for requirements, analysis, design, and modeling techniques that blend into agile software development. Such an agile design technique needs to address requirements one after the other and shall allow to proceed to analysis, design, modeling, and actual software development, early on. It shall allow to add new requirements and functionality step by step and to extend the existing system accordingly. An agile requirements, analysis, design, and modeling technique should support iterative development and refactoring towards new and changing functionality. In addition, such a technique should enable domain experts and (IT) layperson to participate in the agile development as on-site customers and product owners. At least, layperson domain experts should be able to understand the ideas and concepts underlying the software system in order to be able to judge whether their requirements are met and where the software concepts may have faults or functionality is still missing.
A Post-Traumatic Growth Perspective on PTSD: Implications for Those Who Have Served and Their Partners

Abstract Research emphasizing the negative psychosocial impacts of service-related post-traumatic stress disorder (PTSD) for military members, veterans, and their families is well established. Post-traumatic growth (PTG), positive psychological change resulting from managing adverse life events and situations, is an alternate outcome considered in research focusing on the impacts of serious illness and other life-altering circumstances on families. Little is known, however, about the processes that create and sustain PTG within military and veteran family systems. This paper will review conceptualizations of PTG and consider its relevance as a construct for analysis of outcomes related to the experiences of partners of military members and veterans living with PTSD and other operational stress injuries.
Sophisticated Batteryless Sensing

Wireless embedded sensing systems have revolutionized scientific, industrial, and consumer applications. Sensors have become a fixture in our daily lives, as well as the scientific and industrial communities by allowing continuous monitoring of people, wildlife, plants, buildings, roads and highways, pipelines, and countless other objects. Recently a new vision for sensing has emerged—known as the Internet-of-Things (IoT)—where trillions of devices invisibly sense, coordinate, and communicate to support our life and well being. However, the sheer scale of the IoT has presented serious problems for current sensing technologies— mainly, the unsustainable maintenance, ecological, and economic costs of recycling or disposing of trillions of batteries. This energy storage bottleneck has prevented massive deployments of tiny sensing devices at the edge of the IoT. This dissertation explores an alternative—leave the batteries behind, and harvest the energy required for sensing tasks from the environment the device is embedded in. These sensors can be made cheaper, smaller, and will last decades longer than their battery powered counterparts, making them a perfect fit for the requirements of the IoT. These sensors can be deployed where battery powered sensors cannot—embedded in concrete, shot into space, or even implanted in animals and people. However, these batteryless sensors may lose power at any point, with no warning, for unpredictable lengths of time. Programming, profiling, debugging, and building applications with these devices pose significant challenges. First, batteryless devices operate in unpredictable environments, where voltages vary and power failures can occur at any time—often devices are in failure for hours. Second, a device’s behavior effects the amount of energy they can harvest—meaning small changes in tasks can drastically change harvester efficiency. Third, the programming interfaces of batteryless devices are ill-defined and nonintuitive; most developers have trouble anticipating the problems inherent with an intermittent power supply. Finally, the lack of community, and a standard usable hardware platform have reduced the resources and prototyping ability of the developer. In this dissertation we present solutions to these challenges in the form of a tool for repeatable and realistic experimentation called Ekho, a reconfigurable hardware platform named Flicker, and a language and runtime for timely execution of intermittent programs called Mayfly.
Murine Central Nervous System and Bone Marrow Distribution of the Aurora A Kinase Inhibitor Alisertib: Pharmacokinetics and Exposure at the Sites of Efficacy and Toxicity

Important challenges in developing drugs that target central nervous system (CNS) tumors include overcoming barriers for CNS delivery and reducing systemic side effects. Alisertib, an aurora A kinase inhibitor, has been examined for treatment of several CNS tumors in preclinical and clinical studies. In this study, we investigated the distribution of alisertib into the CNS, the site of efficacy for brain tumors, and into the bone marrow, the site of dose-limiting toxicity leading to myelosuppression. Mechanisms influencing site-specific distribution, such as active transport mediated by the efflux proteins, p-glycoprotein (P-gp) and breast cancer resistance protein (Bcrp), were examined. Alisertib exposure to the brain in wild-type mice was less than 1% of that in the plasma, and was evenly distributed throughout various brain regions and the spinal cord. Studies using transporter knockout mice and pharmacological inhibition show that alisertib CNS distribution is influenced by P-gp, but not Bcrp. Conversely, upon systemic administration, alisertib distribution to the bone marrow occurred rapidly, was not significantly limited by efflux transporters, and reached higher concentrations than in the CNS. This study demonstrates that, given an equivalent distributional driving force exposure in plasma, the exposure of alisertib in the brain is significantly less than that in the bone marrow, suggesting that targeted delivery may be necessary to guarantee therapeutic efficacy with minimal risk for adverse events.Therefore, these data suggest that, to improve the therapeutic index when using alisertib for brain tumors, a localized regional delivery, such as convection-enhanced delivery, may be warranted. SIGNIFICANCE STATEMENT The CNS penetration of alisertib is limited with uniform distribution in various regions of the brain, and P-gp efflux is an important mechanism limiting that CNS distribution. Alisertib rapidly distributes into the bone marrow, a site of toxicity, with a greater exposure than in the CNS, a possible site of efficacy. These results suggest a need to design localized delivery strategies to improve the CNS exposure of alisertib and limit systemic toxicities in the treatment of brain tumors.