Miracle-dz/UniFAR-FTUs huggingface dataset:
Coupling Matrix-Based Co-Design of Filter-Oscillators

This letter presents a methodology of designing integrated filter-oscillators using the coupling matrix technique. The $N + 4$ coupling matrix is developed for the first time to describe the filter-oscillator topology. Accordingly, the corresponding group delay, loop gain, loop phase, and complex quality factor of the feedback filter can be calculated using the matrix. This helps rapidly predict oscillating frequencies at group delay or complex quality factor peak frequencies to achieve lower phase noise. Moreover, since the transistor and the transmission line (TL) entries are incorporated in the coupling matrix, the physical geometries can be directly determined, resulting in improved design efficiency. Two third-order filter-oscillators are implemented at 2.91 GHz (group delay peak) and 3.15 GHz (complex quality factor peak) frequencies, respectively. The developed filter-oscillators are measured with −121 and −145 dBc/Hz phase noise at 1-MHz offset frequency, validating this coupling matrix-based co-design approach.
An Exact Solution to a Quaternion Matrix Equation with an Application

In this paper, we establish the solvability conditions and the formula of the general solution to a Sylvester-like quaternion matrix equation. As an application, we give some necessary and sufficient conditions for a system of quaternion matrix equations to be consistent, and present an expression of the general solution of the system when it is solvable. We present an algorithm and an example to illustrate the main results of this paper. The findings of this paper generalize the known results in the literature.
Sputum Galactomannan Has Utility in the Diagnosis of Chronic Pulmonary Aspergillosis

Diagnosis of pulmonary aspergillosis (PA), a fungal disease caused by Aspergillus species, is challenging since symptoms are unspecific. The galactomannan (antigen secreted by Aspergillus species) test in bronchoalveolar lavage (BAL) fluid is a valuable diagnostic adjunct test in the diagnosis of PA. However, BAL collection is invasive and may not be suitable to severely ill patients. Sputum is non-invasive, easily collected, and lung specific and may be an alternative to BAL. The aim of this research was to retrospectively evaluate the utility of sputum galactomannan in the diagnosis of pulmonary aspergillosis in patients with chronic respiratory diseases and to estimate the sputum galactomannan cut-off value. We collected data from patients with clinical suspicion of pulmonary aspergillosis who had sputum galactomannan, culture, and Aspergillus IgG tests performed within four weeks. Sputum galactomannan was validated against the clinical diagnosis of aspergillosis, Aspergillus culture, and Aspergillus IgG tests. In total, 218 patients met inclusion criteria. Overall, sputum GM showed satisfactory agreement with clinical diagnosis of aspergillosis, Aspergillus culture, and Aspergillus IgG. When a receiver operating characteristic curve was constructed using Aspergillus culture/IgG and clinical diagnosis, the same cut-off (CO) of 0.71 (AUC: 0.83; CI: 0.69–0.86, p < 0.001) was determined. Against clinical diagnosis, sputum GM gave sensitivity and specificity of 70% and 71%, respectively. Sensitivity of 77% and specificity of 78% were found when sputum GM was evaluated against Aspergillus culture/IgG. In conclusion, this study showed that sputum galactomannan antigen testing has utility in the diagnosis of chronic forms of pulmonary aspergillosis and further prospective validation is indicated.
Transfer learning and gated recurrent unit based epileptic seizure detection method

Automatic seizure detection system can greatly reduce the burden of manual diagnosis on epilepsy. In this paper, an epileptic seizure detection method is proposed based on transfer learning of VGGNet-16 and gated recurrent unit network. Evaluated on CHB-MIT EEG dataset, the proposed detection method achieved an average sensitivity of 90.12%, an average specificity of 96.32% and an average accuracy rate of 96.31%. A comparative experiment based on the transfer learning of Resnet50 further demonstrates the good performance of VGGNet-16 in seizure detection
Biosynthesis of Aurodox, a Type III Secretion System Inhibitor from Streptomyces goldiniensis

Enterohemorrhagic Escherichia coli (EHEC) is a significant global pathogen for which traditional antibiotic treatment is not recommended. Aurodox inhibits the ability of EHEC to establish infection in the host gut through the specific targeting of the type III secretion system while circumventing the induction of toxin production associated with traditional antibiotics. ABSTRACT The global increase in antimicrobial-resistant infections means that there is a need to develop new antimicrobial molecules and strategies to combat the issue. Aurodox is a linear polyketide natural product that is produced by Streptomyces goldiniensis, yet little is known about aurodox biosynthesis or the nature of the biosynthetic gene cluster (BGC) that encodes its production. To gain a deeper understanding of aurodox biosynthesis by S. goldiniensis, the whole genome of the organism was sequenced, revealing the presence of an 87 kb hybrid polyketide synthase/non-ribosomal peptide synthetase (PKS/NRPS) BGC. The aurodox BGC shares significant homology with the kirromycin BGC from S. collinus Tϋ 365. However, the genetic organization of the BGC differs significantly. The candidate aurodox gene cluster was cloned and expressed in a heterologous host to demonstrate that it was responsible for aurodox biosynthesis and disruption of the primary PKS gene (aurAI) abolished aurodox production. These data supported a model whereby the initial core biosynthetic reactions involved in aurodox biosynthesis followed that of kirromycin. Cloning aurM* from S. goldiniensis and expressing this in the kirromycin producer S. collinus Tϋ 365 enabled methylation of the pyridone group, suggesting this is the last step in biosynthesis. This methylation step is also sufficient to confer the unique type III secretion system inhibitory properties to aurodox. IMPORTANCE Enterohemorrhagic Escherichia coli (EHEC) is a significant global pathogen for which traditional antibiotic treatment is not recommended. Aurodox inhibits the ability of EHEC to establish infection in the host gut through the specific targeting of the type III secretion system while circumventing the induction of toxin production associated with traditional antibiotics. These properties suggest aurodox could be a promising anti-virulence compound for EHEC, which merits further investigation. Here, we characterized the aurodox biosynthetic gene cluster from Streptomyces goldiniensis and established the key enzymatic steps of aurodox biosynthesis that give rise to the unique anti-virulence activity. These data provide the basis for future chemical and genetic approaches to produce aurodox derivatives with increased efficacy and the potential to engineer novel elfamycins.
Optimization of Multi-Core Accelerator Performance Based on Accurate Performance Estimation

Multicore accelerators have emerged to efficiently execute recent applications with complex computational dimensions. Compared to a single-core accelerator, a multicore accelerator handles a larger amount of communication and computation simultaneously. Since the conventional performance estimation algorithm tailored to single-core accelerators cannot estimate the performance of multicore accelerators accurately, we propose a novel performance estimation algorithm for a multicore accelerator. The proposed algorithm predicts a dynamic communication bandwidth of each direct memory access controller (DMAC) based on the runtime state of DMACs, making it possible to estimate the communication amounts handled by DMACs accurately by taking into account the temporal intervals. The proposed algorithm is evaluated for convolutional neural networks and wireless communications. The experimental results using a pre-register transfer level (RTL) simulator shows that the proposed algorithm can estimate the performance of a multicore accelerator with the estimation error of up to 2.8%, regardless of the system communication bandwidth. These results were also verified by the hardware implementations on Xilinx ZYNQ. In addition, the proposed algorithm is used to explore a design space of accelerator core dimensions, and the resulting optimal core dimension provides performance gains of 10.8% and 31.2%, compared to the conventional multicore accelerator and single-core accelerator, respectively. The source code is available on the GitHub repository: https://github.com/SDL-KU/OptAccTile.
Constitutively active STAT5b feminizes mouse liver gene expression

STAT5 is an essential transcriptional regulator of the sex-biased actions of growth hormone (GH) in the liver. Delivery of constitutively active STAT5 (STAT5CA) to male mouse liver using an engineered adeno-associated virus with high tropism for the liver is shown to induce widespread feminization of the liver, with extensive induction of female-biased genes and repression of male-biased genes, largely mimicking results obtained when male mice are given GH as a continuous infusion. Many of the gene expression changes observed were associated with STAT5 binding to liver chromatin, supporting the proposed direct role of persistently active STAT5 in continuous GH-induced liver feminization. The feminizing effects of STAT5CA were dose-dependent; moreover, at higher levels, overexpression of STAT5CA resulted in some histopathology not seen in continuous GH-infused male liver, including hepatocyte hyperplasia and distorted liver architecture. These findings establish that the persistent activation of STAT5 by GH that characterizes female liver is by itself sufficient to account for the female-biased expression of a majority of female-biased genes. Moreover, histological changes seen when STAT5CA is overexpressed highlight the importance of carefully evaluating such effects before considering such STAT5 derivatives for therapeutic use in treating liver disease.
Lidar and Radar Enable the Next Generation of Dairy Cattle Feeding

HighlightsDevelopments in automatized feeding lead to farms being locked industrial production sites.LiDAR and Radar facilitate driverless feed mixers by covering navigation and safety aspects.External safety of driverless vehicles can be compensated with optical, acoustical and organizational measures.Abstract. Present automatic feeding systems (AFS) for dairy cattle are predominantly machines with additional external structures, e.g., bus bars and guide rails. In order to achieve complete automation of the feeding process, future AFS must be adaptable to different types of farm structures. Technologies such as LiDAR (Light Detection and Ranging) and Radar (Radio Detection and Ranging) enable free navigation of self-propelled feed mixer wagons and make important contributions to personal protection and collision avoidance. This enables the feed mixer to reach silo systems independently, remove feed and present it at the feed table. Using a self-propelled mixer feeder, both LiDAR and Radar are comparatively analyzed in a practical series of tests under farm conditions. Research into the legal framework and an exemplary risk assessment lay the conceptual basis for future automatic feeding systems. The aim of this consideration is to derive a coordinated concept for the areas of navigation and collision protection in an automatic feeding system for next-generation dairy cattle. Keywords: AFS, AGV, Automation, Dairy, Feeding, Laser, LiDAR, Radar.
Fast Solution of High Stochastic Dimensional EM Problems Using Proper Orthogonal Decomposition

Electromagnetic (EM) systems are prone to parameter variations and their impact help in predictive analysis. In this letter, proper orthogonal decomposition is proposed as a fast uncertainty quantification method, which can efficiently handle a large number of stochastic parameters, without any restriction on the levels of variations. The performance of the approach is evaluated in a frequency domain stochastic EM problem employing vector finite element method and having permittivity variations. The computational time increases by only 15% even with a fivefold increase in the stochastic variables.
A Deep Learning Accelerator Based on a Streaming Architecture for Binary Neural Networks

Deep neural networks (DNNs) have played an increasingly important role in various areas such as computer vision and voice recognition. While training and validation become gradually feasible with high-end general-purpose processors such as graphical processor units (GPU), high throughput inferences in embedded hardware platforms with low hardware resources and power consumption efficiency are still challenging. Binarized neural networks (BNNs) are emerging as a promising method to overcome these challenges by reducing bit widths of DNN data representations with many optimal prior solutions. However, accuracy degradation is a considerable problem of the BNN, compared to the same architecture with full precision, while the binary neural networks still contain significant redundancy for optimization. In this paper, to address the limitations, we implement a streaming accelerator architecture with three optimization techniques: pipelining-unrolling for streaming each layer, weight reuse for parallel computation, and MAC (multiplication-accumulation) compression. Our method first constructs streaming architecture by pipelining-unrolling method to maximize throughput. Next, the weight reuse method with the K-mean cluster is applied to reduce the complexity of the popcount operation. Finally, MAC compression reduces hardware resources used for remaining computation on MAC operations. The implemented hardware accelerator integrated into a state-of-the-art field programable gate array (FPGA) provides the maximum performance of the classification at 1531k frames per second with 98.4% accuracy for the MNIST dataset and 205K frame per second with 80.2% accuracy for the Cifar-10 dataset. Besides, the proposed design’s ratio FPS/LUTs is approximately 57 (MNIST) and 0.707 (Cifar-10), which is much lower than the state-of-the-art design with a comparable throughput and inference accuracy.
Two minds of credit professionals: accrual vs. cash accounting information

: To explore in what ways and what elements of financial statement information is important for credit practitioners, we employ a survey method to obtain new evidence. We ask if there is evidence on the existence of two different types of views to accounting information, namely accrual accounting and cash accounting emphasis. The two views come out robustly throughout our analysis, and they are consistently linked both to credit professional’s experience, and task complexity. We infer our evidence to be consistent with the explanations for co-existence of differential information preferences advanced in behavioral accounting literature related to individuals’ cognitive constraints in use of accounting information. We discuss the implications of our results for credit professionals, accounting standard setters, and researchers.
Hemostatic Dysfunction in Dogs Naturally Infected with Angiostrongylus vasorum—A Narrative Review

This narrative review aims to describe Angiostrongylus vasorum-induced hemostatic dysfunction of dogs with emphasis on clinical and laboratory findings as well as potential therapeutic strategies for the bleeding patient. Canine angiostrongylosis (CA) is a disease with potentially high morbidity and mortality in endemic areas and with fatal outcome often associated with either severe respiratory compromise, pulmonary hypertension and right-sided heart failure, or hemostatic dysfunction with severe bleeding. The most common signs of hemorrhage are hematomas, petecchiation, ecchymoses, oral mucosal membrane bleeding and scleral bleeding, while intracranial and pulmonary hemorrhage are among the most severe. The pathophysiological mechanisms underlying hemostatic dysfunction in these patients are presently researched. While the larval effect on platelets remains unknown, the parasite appears to induce dysregulation of hemostatic proteins, with studies suggesting a mixture of pro-coagulant protein consumption and hyperfibrinolysis. Importantly, not all dogs display the same hemostatic abnormalities. Consequently, characterizing the hemostatic state of the individual patient is necessary, but has proven difficult with traditional coagulation tests. Global viscoelastic testing shows promise, but has limited availability in general practice. Treatment of A. vasorum-infected dogs with hemostatic dysfunction relies on anthelmintic treatment as well as therapy directed at the individual dog’s specific hemostatic alterations.
Tamer: A Sandbox for Facilitating and Automating IoT Malware Analysis with Techniques to Elicit Malicious Behavior

: As malware poses a signiﬁcant threat to IoT devices, the technology to combat IoT malware, like sandbox, has not received enough attention. The majority of efforts in existing researches have focused on x86-ﬂavored binaries that are not used for IoT devices. In fact, we have witnessed that many samples of IoT malware that can be observed in the wild are ARM binaries. In this paper, we propose a novel sandbox for analyzing Linux malware including IoT malware. Our sandbox system, called Tamer, supports dynamic analysis for ARM binaries and has some features to automate and facilitate IoT malware analysis, like the automated interaction mechanism and the fake network environment for dynamic analysis. In addition, our system adopts features, like dynamic binary instrumentation and virtual machine introspection, which may allow retrieving further insights from malware. With the dataset of real-world malware, we demonstrated that our sandbox system can analyze IoT malware which is speciﬁcally designed for infecting IoT devices. Through an analysis experiment on a large number of IoT malware samples, we demonstrate a possibility that our system could facilitate a large scale analysis in an automated manner and retrieve further insights from IoT malware.
Types and Aspects of Front-of-Package Labeling Preferred by Parents: Insights for Policy Making in China

The WHO recommends front-of-package labeling (FOPL) to help parents make healthier food choices for their children. But which type of FOPL resonates with parents in China? We performed a cross-sectional study to investigate parental preferences for five widely used formats of FOPL. A multi-stage cluster sampling method was applied to selected parents of students in primary and secondary schools in six provinces and municipalities from July 2020 to March 2021. A close-ended questionnaire was used to collect demographic information, parents’ preferences for five FOPL in three dimensions, perceptions of the importance of nutrients labeled on FOPL, and prepackaged foods that need FOPL most. Chi-square tests were used to examine the characteristics among five groups. The results showed that multiple traffic lights (MTL) was preferred by parents, followed by warning labels. Parents thought the most needed nutrients to label were sugar, salt, and total fat. The top three prepackaged foods to label were “baked food”, “milk and dairy products” and “sugar-sweetened beverages”. Our findings indicate that nutrient-specific FOPL formats with interpretive aids were preferred by Chinese parents. These new findings can help inform the planning and implementation of FOPL in China and help Chinese parents make healthier food choices.
Visualization of human optic nerve and tract by diffusion tensor mapping and degree of neuropathy

Diffusion-weighted magnetic resonance imaging of the human optic nerve and tract is technically difficult because of its small size, the inherent strong signal generated by the surrounding fat and the cerebrospinal fluid, and due to eddy current-induced distortions and subject movement artifacts. In addition, the effects of the bone channel through which the optic nerve passes, and the proximity of blood vessels, muscles and tendons are generally unknown. Furthermore, the limited technical capabilities of the scanners and the minimization of acquisition times result in poor quality diffusion-weighted images. It is challenging for current tractography methods to accurately track optic pathway fibers that correspond to known anatomy and to produce a reasonable fraction of decussating fibers. Despite these technical limitations and low image resolution, here we show how to visualize the optic nerve and tract and quantify nerve atrophy. Our visualization method based on the analysis of the diffusion tensor shows marked differences between a healthy male subject and a male subject with progressive optic nerve neuropathy, differences that are otherwise not visible on standard morphological images or scalar diffusion maps. Importantly, our method provides a quantification of the degree of optic nerve atrophy in a systematic way.
Method of Diamond-Like Coatings Obtaining

The article is devoted to the method of obtaining a diamond-like coating on a silicon substrate by laser ablation of a glassy carbon target in a vacuum. The presented technology makes it possible to achieve the synthesis of wear-resistant thin-film coatings with a thickness of about 200 nm. The diagnostics of the obtained coating was carried out using probe microscopy, the chemical and phase composition was estimated by the Raman spectra.
Coexisting with the Life of Patients with Hemodialysis: Qualitative Meta-Synthesis Study of Life of Caregivers of Patients with Hemodialysis

As the number of patients with hemodialysis (HD) continues to increase, so too does the number of people depending on caregivers. There is need to pay attention to the lives of caregivers of patients with HD, where sacrifices are forced. This study systematically reviewed and synthesized qualitative studies that explored the experiences of caregivers caring for patients with HD using the meta-synthesis method. We searched literature using four databases (i.e., PubMed, Excerpta Medica dataBASE, Cumulated Index to Nursing and Allied Health Literature, and Web of Science), and finally ten publications were selected. Four themes and nine subtopics were derived from analyzing and synthesizing the research results. The synthesized themes were: “bearing the burden of life as a caregiver,” “reconstructing life to maintain hemodialysis”, “the fading of caregiver’s own life,” and “effort to relieve the burden. ” The results of this study can contribute to the development of interventional studies to improve the quality of life of HD patients. These studies provide an integrated and in-depth perspective on the experiences of caregivers who care for HD patients.