Miracle-dz/UniFAR-FTUs huggingface dataset:
Performance Optimization of Constant Speed - Small Horizontal Axis Wind Turbine for Wind Energy Development in Malaysia

Though Malaysia is blessed with a lot of natural resources, still it mainly depends on fossil-fuels for electricity generation. Due to this dependency, among the different polluting agencies, the electric power sector ranks second in the country’s statistics. So as to reduce the pollution from them and to reduce the dependency on the depleting fossil-fuels, Malaysia is very keen on promoting renewable energy based electricity generation. Following the Government’s renewable energy policy and subsidies, several renewable energy attempts were made and only the solar PV energy systems have had a good start; however, the continued development from the start is questionable because of the high capital cost involved and the unattractive energy conversion efficiency. Few attempts on the proven, cost-effective wind energy systems were carried out and the net outcome is not encouraging due to the low-speed scenario in Malaysia. As per a few successful studies on wind speed assessments, there are attractive sites for wind turbine based electricity generation not with high speed higher capacity turbines, but at low speed small capacity wind turbines. To promote wind energy in Malaysia and to attract global investors, this research aims at low capacity wind turbines suitable for low wind regimes as in the Malaysian context. The proposed constant speed-small horizontal axis wind turbines exhibited encouraging values of annual energy production, power coefficient and capacity factors promising a successful start of wind energy in Malaysia.
Bio¢lm formation by asymptomatic and virulent urinary tract infectiousEscherichiacoli strains

Escherichia coli is the most common organism associated with asymptomatic bacteriuria (ABU) in humans. In contrast to uropathogenic E. coli (UPEC) that cause symptomatic urinary tract infection, very little is known about the mechanisms by which these strains colonize the urinary tract. Here, we have investigated the bioﬁlm-forming capacity on abiotic surfaces of groups of ABU strains and UPEC strains in human urine. We found that there is a strong bias; ABU strains were signiﬁcantly better bioﬁlm formers than UPEC strains. Our data suggest that bioﬁlm formation in urinary tract infectious E. coli seems to be associated with ABU strains and appears to be an important strategy used by these strains for persistence in this high-ﬂow environment.
High frequency scattering from trihedral corner reflectors and other benchmark targets: SBR versus experiment

A general method for calculating the radar cross section (RCS) from a three-dimensional target is described. The target is first constructed by using a solid-geometry-modeling computer-aided design (CAD) package. Following the shooting and bouncing ray (SBR) method, a very dense grid of rays is launched from the incident direction toward the target. Each ray is traced according to the geometrical optics theory including the effect of ray tube divergence, polarization, and material reflection coefficient. At the point where the ray exits the target, a physical optics-type integration is performed to obtain the scattered far fields. This method is tested using several simple examples involving interaction among plates, cylinders, and spheres. The theoretical results are generally in good agreement with measured data. >
Transcription factor localization dynamics and DNA binding drive distinct promoter interpretations

Environmental information may be encoded in the temporal dynamics of transcription factor (TF) activation and subsequently decoded by gene promoters to enact stimulus-specific gene expression programs. Previous studies of this behavior focused on the encoding and decoding of information in TF nuclear localization dynamics, yet cells control the activity of TFs in myriad ways, including by regulating their ability to bind DNA. Here, we use light-controlled mutants of the yeast TF Msn2 as a model system to investigate how promoter decoding of TF localization dynamics is affected by changes in the ability of the TF to bind DNA. We find that yeast promoters directly decode the light-controlled localization dynamics of Msn2 and that the effects of changing Msn2 affinity on that decoding behavior are highly promoter dependent, illustrating how cells could potentially regulate TF localization dynamics and DNA binding in concert for improved control of gene expression.
Influenza virus transcription and progeny production are poorly correlated in single cells

The ultimate success of a viral infection at the cellular level is determined by the number of progeny virions produced. However, most single-cell studies of infection quantify the expression of viral transcripts and proteins, rather than the amount of progeny virions released from infected cells. Here we overcome this limitation by simultaneously measuring transcription and progeny production from single influenza-virus-infected cells by embedding nucleotide barcodes in the viral genome. We find that viral transcription and progeny production are poorly correlated in single cells. The cells that transcribe the most viral mRNA do not produce the most viral progeny, and often represent aberrant infections that fail to express the influenza NS gene. However, only some of the discrepancy between transcription and progeny production can be explained by viral gene absence or mutations: there is also a wide range of progeny production among cells infected by complete unmutated virions. Overall, our results show that viral transcription is a relatively poor predictor of an infected cell’s contribution to the progeny population.
Optimization of two‐step batch processes and the method of compensation for random error

This paper considers the problem of the optimal setting of controllable variables in two‐step processes with quality constraints. The optimal setting minimizes the cost and satisfies quality constraints defined for the final output. The main emphasis is given to processes where it is possible to make intermediate measurements after the first processing step and to utilize these measurements before the control variables in the second step are set. Optimization based on this method of compensation for random error can yield substantially lower cost than does optimization based on a strategy where all variables are fixed before the process starts. An example of application of the method is taken from the food industry. Copyright © 2012 John Wiley & Sons, Ltd.
Conscription and Military Service: Do They Result in Future Violent and Nonviolent Incarcerations and Recidivism?

ABSTRACT:Employing nonparametric bounds, we examine the effect of military service on incarceration outcomes using the Vietnam draft lotteries as a possibly invalid instrumental variable for military service. The draft is allowed to have a direct effect on the outcomes independently of military service, disposing of the exclusion restriction. We find: (i) suggestive but not strong statistical evidence that the direct effect of the draft increases the incarceration rate for violent offenses for a particular cohort of draft avoiders and (ii) military service increases the incarceration rate for violent and nonviolent crimes of white volunteers and veterans in certain birth cohorts.
New particle searches at Tevatron (II)

Various recent results of new particle searches at the Fermilab Tevatron are presented. No evidence is found for supersymmetric particles (chargino, gluino), leptoquark bosons and heavy gauge bosons in {ital p{anti P}} collisions at {radical}s = 1.8 TeV. Excluded mass regions for each particle are determined.
"Animal Welfare and Environmental Ethics: Reconciling Competing Values"

Abstract:In this discussion I revisit the animal welfare-environmental ethics debate, including a recent argument by Ian Campbell in this journal, that its underlying values are incommensurable at the level of principle, making them hard to reconcile, even in practice. By relying on the geocentric framework of William Lynn and the capabilities approach of Martha Nussbaum, as well as a place-specific example of wild horse protection policies, I argue that it is possible to balance these competing values. In light of the pervasive presence of non-native animals, as well as habitat loss and other threats to self-sustaining ecosystems, binary choices are fast becoming anachronistic. Case-by-case analyses are necessary in order to assess how to grant equitable consideration to complex claims.
Unified Framework of Dimensionality Reduction and Text Categorisation

Text classification (categorization) is a supervised learning task that assigns text documents to pre-defined classes of documents. It is used to organize and manage the collection of text documents available in digital form. To accomplish the task, support vector machine (SVM) is regarded as the suitable classifier for any kind of applications. Though SVM’s computational complexity is independent of number of dimensions, still high dimensionality poses the problem of ‘curse of dimensionality’ that can be solved effectively by the process of Dimension Reduction (DR). This work contemplates on developing a framework for dimensionality reduction and text classification. A comparative analysis of the classification accuracies using two approaches viz., text classification with dimensionality reduction and text classification without dimensionality reduction completes the scope of the paper. It also evaluates the efficiency of various dimensionality reduction techniques to include one of the most coherent methods in the framework
Bernstein type inequality for a class of dependent random matrices

In this paper we obtain a Bernstein type inequality for the sum of self-adjoint centered and geometrically absolutely regular random matrices with bounded largest eigenvalue. This inequality can be viewed as an extension to the matrix setting of the Bernstein-type inequality obtained by Merlev\`ede et al. (2009) in the context of real-valued bounded random variables that are geometrically absolutely regular. The proofs rely on decoupling the Laplace transform of a sum on a Cantor-like set of random matrices.
Bayesian Analysis of Weak Form Polynomial Reduced Rank Structures in VEC Models

The main goal of the paper is the Bayesian analysis of weak form polynomial serial correlation common features together with cointegration. In the VEC model the serial correlation common feature leads to an additional reduced rank restriction imposed on the model parameters. After the introduction and discussion of the model, the methods will be illustrated with an empirical investigation of the price-wage nexus in the Polish economy. Additionally, consequences of imposing such additional short-run restrictions for permanent-transitory decomposition will be discussed.
TM Scattering by a Shallow Elliptical-Shaped Cavity

In this letter, the problem of electromagnetic scattering by a shallow elliptical-shaped cavity in a perfect electric conductor plane is considered. We propose an efficient modal approach based on the region-matching technique that can calculate scattered fields without the use of the Mathieu functions. By enforcing boundary conditions at a semicircular auxiliary border, a system of linear equations is constructed. The results obtained by this method are compared with those provided by the method of moment. Finally, the effect of the shape of the cavity on the scattering signature is investigated.
Measuring Design Simplicity

The first time ever someone described how the better organization and functionality of systems can be linked to Simplicity was, in 1870, Claude Bernard (Gene, 2007). However Simplicity, as commonly understood, is not an easy thing to describe, much less to comprehend. What is taken as Simplicity is an undetermined number of concepts to explain what supposedly Simplicity is. The result is a great dispersion that cannot afford reasoning. Some have been able to reduce the given conditions for the existence of Simplicity to ten concepts designated as laws (Maeda, 2006). However we cannot consider it as a definition to describe “simplicity” because such multiplicity is just and only descriptive. If we ought to have a classic image of
Investigation Physiological signal collection before and after symptom onset

The study of Investigation Physiological signal collection before and after symptom onset includes sorting and observing the collected data, and using software rendering to map the data to make the data easier to observe after visualization. The data that needs to be mapped include the monitoring of electrocardiogram (ECG), cardiac impedance (ICG), respiratory rate (RESP), blood oxygen saturation (SPO2) of the study case, and finally the interpretation of the data.
Rigorous optimization recipes for sparse and low rank inverse problems with applications in data sciences

Many natural and man-made signals can be described as having a few degrees of freedom relative to their size due to natural parameterizations or constraints; examples include bandlimited signals, collections of signals observed from multiple viewpoints in a network-of-sensors, and per-flow traffic measurements of the Internet. Low-dimensional models (LDMs) mathematically capture the inherent structure of such signals via combinatorial and geometric data models, such as sparsity, unions-of-subspaces, low-rankness, manifolds, and mixtures of factor analyzers, and are emerging to revolutionize the way we treat inverse problems (e.g., signal recovery, parameter estimation, or structure learning) from dimensionality-reduced or incomplete data. Assuming our problem resides in a LDM space, in this thesis we investigate how to integrate such models in convex and non-convex optimization algorithms for significant gains in computational complexity. We mostly focus on two LDMs: $(i)$ sparsity and $(ii)$ low-rankness. We study trade-offs and their implications to develop efficient and provable optimization algorithms, and--more importantly--to exploit convex and combinatorial optimization that can enable cross-pollination of decades of research in both.
Low-Power Optimization Design of CMOS Phase-Locked Loop for WiFi-6E Applications

A low-power and low-voltage phase-locked loop (PLL) designed for the WiFi-6E system is presented. Several short-channel circuit techniques are used to achieve the low current dissipation of 3.1mA while saving 41.5% power consumption compared to the traditional PLL. The proposed PLL is implemented in TSMC 0.18-µm CMOS process and 1V supply voltage. The simulated phase noise of VCO is -116.5 dBc/Hz at a 1-MHz offset frequency from 6.48 GHz oscillation frequency. The locking time is shorter than 1. 3µs with a voltage ripple of 1.4mV.
Geometry-Based Clustering Characteristics for Outdoor Measurements at 28–30 GHz

This letter presents an analysis of channel characteristics for an outdoor scenario at the frequency band of 28–30 GHz. A geometry-based clustering algorithm is proposed to group the measured multipath components (MPCs) from the interaction points on the surrounding walls or objects according to ray-tracing three-dimensional (3-D) simulations, giving results that are more physically interpretable than the traditional clustering algorithms. The cluster-level characteristics at 15 positions along a predefined route covering both line-of-sight (LoS) and non-LoS (NLoS) scenarios are investigated. Moreover, power contributions of MPCs with multiple bounces (up to seven bounces in NLoS scenario) from the interaction objects are also investigated.
Using Machine Learning video analysis in the design process of Virtual Reality curation

This research provides users with a new design tool for professional designers to create virtual exhibition spaces. The system recognizes the input video through machine learning and assists the user to automatically generate design auxiliary content in the process. Finally, through VR somatosensory interaction, designers can quickly and effectively create high-quality virtual exhibition venues without writing programs.
iCare: An Intelligent System for Remote Cardiac Monitoring in Smart Healthcare

Heart disease poses a great threat to the health of an individual and even leads to sudden cardiac death, and hence a ubiquitous and portable tool for early detection and warning is of significant value. Benefiting from the speedy advance of sensor technology, artificial intelligence, and internet of things, we have developed an intelligent system that can remotely collect heart sounds, process the signals, and predict common cardiac diseases with the trained machine learning model. In this study, we detail our designed smart stethoscope and show the system architecture and its components. Besides, initial results demonstrate its power.
Technology and public interests

Since the inception of human history, people have embraced technologies, from stone axes to plows. Later, the wave of social and technological modernization unleashed by the Industrial Revolution swept the world into the contemporary era. Today, humans are confronting ever more overwhelming technologies. Social and technical discourse on and debates about new technologies with mass popularity or economic ramifications abound.
A Primary-Side Method for Ultrafast Determination of Mutual Coupling Coefficient in Milliseconds for Wireless Power Transfer Systems

This article presents a systematic frequency-sweeping based method for fast and accurate determination of mutual coupling coefficient in a series–series wireless power transfer system. The novel contributions involve a sensitivity analysis to evaluate the robustness of the proposed method and an evaluation of several adaptive frequency step functions to minimize detection time with an accuracy of less than 1% error. It is found that the proposed method is the most sensitive when the frequency is swept from the lower frequency boundary in a weakly-coupled system. Several adaptive frequency step functions are evaluated and compared. A power factor reference and an adaptive frequency step function are designed in a systematic way to achieve the dual purposes of minimum detection time and high accuracy. The experimental results obtained from the hardware setups show that the mutual coupling coefficients under a range of conditions can be estimated within 7 ms and with errors typically less than 1.0%.
A Method for Classifying Road Narrowing Conditions Based on Features of Surrounding Vehicles and Piled Snow in In-vehicle Camera Videos

Piled snow on road shoulders may cause traffic congestion or traffic accidents, and can cause various problems in maintaining urban transportation. In order to maintain the effective width of roads during the winter, piled snow on the road shoulders is removed and cleared. However, the immediate observation of effective width of roads need huge effort of the road administrators. When the road is narrowed, the view changes and asphalt are hidden by snow. Snow piles on road shoulder becomes large and possible driving position of vehicles are limited. Therefore, features such as locations of surrounding vehicles and the size of piled snow is an effective feature in classifying road narrowing condition. In this paper, a novel method introducing features of surrounding vehicles and piled snow for classifying the road narrowing conditions from in-vehicle camera is proposed. Estimating road narrowing conditions can lay an environment that does not require a great deal of time or huge effort of the road administrators to gather road information.
Active Gate Driver With Turn-off Delay Control for Voltage Balancing of Series–Connected SiC MOSFETs

Connecting semiconductor switches in series is a way to increase the voltage rating of a power electronic converter. However, if two switches are directly connected without any special effort, an uneven voltage between the switches can occur due to nonidentical characteristics of them. A significant voltage imbalance may destroy the switches, and both thermal and loss imbalance also lead to the unstable system. Since a silicon carbide (SiC) metal–oxide–semiconductor field–effect transistor (mosfet) has a faster switching speed and higher voltage blocking capability than silicon (Si) devices, existing voltage balancing methods for Si devices may not be suitable. This article proposes a voltage balancing method that controls turn-off delay time of the switch by adding one bipolar junction transistor (BJT) on a gate turn-off path. Depending on the base voltage of the BJT, turn-off resistance and delay time are actively changed which mitigates the imbalance problem. The theoretical analysis of the proposed method has been discussed in detail based on the classical mosfet model. Both the simulations and experiments have been performed to verify the theory and the validity of the proposed method where the voltage imbalance is reduced from 22.4% to 3.2% as well as reducing the switching loss at the entire voltage and load conditions.
An Analysis of the Long-term Photometric Behavior of epsilon Aurigae

The lure of a 50 percent reduction in light has brought a multitude of observers and researchers to epsilon Aur every twenty-seven years, but few have paid attention to the system outside of eclipse. As early as the late 1800s, it was clear that the system undergoes some form of quasi-periodic variation outside of totality, but few considered this effect in their research until the mid-1950s. In this work we focus exclusively on the out-of-eclipse (OOE) variations seen in this system. We have digitized twenty-seven sources of historic photometry from eighty-one different observers. Two of these sources provide twenty-seven years of inter-eclipse UBV photometry which we have analyzed using modern period finding techniques. We have discovered the F-star variations are multiperiodic with at least two periods that evolve in time at delta(Period) approximately -1.5 day/year. These periods are detected when they manifest as near-sinusoidal variations at 3,200-day intervals. We discuss our work in an evolutionary context by comparing the behavior found in e Aur with bona-fide supergiant and post-AGB stars of similar spectral type. Based upon our qualitative comparison, we find the photometric behavior of the F-star in the e Aur system is more indicative of supergiant behavior. Therefore the star is more likely to be a "traditional supergiant" than a post-AGB object. We encourage continued photometric monitoring of this system to test our predictions.
Manufacturing Microfluidic Chips: Micro Milling Approach

Microfluidics are an important technology for the biomedical industry and often utilised in our daily lives. To facilitate the development of this technology, micromilling is proposed as an alternative method to conventional photo-lithography for fabricating microfluidic chips. There remains uncertainty around what the ideal milling practices are and it is therefore important to investigate the milling process as well as the optimal parameters. It is determined that the highest quality surface can be obtained at 60,000 RPM spindle speed with a 200 mm/min feed rate for PMMA, a common microfludic material. Robust data was used to verify this relationship. Recommendations are made to further refine the milling process to improve surface quality, including an example of a potential final product.