Miracle-dz/UniFAR-FTUs huggingface dataset:
Highly reflective Fiber Bragg Gratings in active fibers for fiber-integrated multi-mode resonators

In single-mode fiber lasers, power scaling is typically limited by effects such as stimulated Raman-scattering and transverse mode instabilities. However, in highly multi-mode fibers, these two effects are usually negligible due to the high number of transverse modes and therefore, higher optical powers can be achieved. To further decrease the complexity, increase the robustness and reliability of multi-mode fiber resonators, we develop highly reflective multi mode Fiber Bragg Gratings (FBGs) in active doped fibers, which is challenging e.g. due to the required homogeneity of the FBG within the fiber. Here, we present a proof of concept of a fiber-integrated multi-mode resonator using a highly reflective multi-mode FBG for spectral stabilization in a fiber with a rectangular core of 20 x 60 µm² and a numerical aperture of 0.1. More than 60 modes can be guided within this fiber, which can result in a homogeneous near-field beam profile. In our experimental verification, we build up a fiber resonator and achieve an optical-optical efficiency of 50 % and stable wavelength operation at 1072 nm. 10 % of the power is emitted as ASE at a wavelength of 1030 nm, which can be removed by using longer fiber lengths to further improve the efficiency. Approximately 12 % of the signal power is propagating through the HR-FBG, which leads to an FBG-reflectivity of 70-80 % based on our simulations. As a next step, we plan to transfer the HR-FBG concept to round-core XLMA-fibers to improve our earlier demonstrated setups and realize full in-fiber multimode resonators.
Low repetition rate mode-locked Yb:CALGO laser with a White cell configuration and sub-100 fs pulses

We have demonstrated a diode-pumped Yb:CALGO laser operating at 13.85 MHz repetition rate with high pulse energy and high peak power. The laser delivered 750 mW of output power at 21 W of incident pump power. The shortest pulses obtained were 73 fs using a 15% output coupler. The corresponding pulse energy was 54 nJ and the peak power was 744 kW. A White cell configuration was used to extend the laser cavity. To the best of our knowledge, this is the first ever femtosecond laser operated with a White cell configuration.
Research on Operation Cockpit Technologies of Complicated Power System

To meet the ever growing demand for the ability to control large-scale power systems,a brand new conceptual model of the next generation system,named operation smart system(OS2),is proposed.The top-level application of OS2is designed as the power system operation cockpit(POC). The concept and design of POC are described first,and the related technologies of key performance indicator(KPI)system design,panoramic modeling,remote calling of the user interface,and the smart gateway are then discussed in detail.Pilot applications demonstrate the feasibility of the design and technologies.
Structure Optimization of the Pressing Block Tooth in Underwater Skirt Pile Gripper of Offshore Oil Platform

Underwater skirt pile gripper is a kind of hydraulic gripper.It is widely applied to the construction of offshore oil platform.Tjhe platform is supported by pressing block teeth.Optimal design based on finite element analysis was introduced into the structure of pressing block tooth for underwater skirt pile gripper.The optimal design model was built and calculated by ANSYS.The result of optimal design was gained,and compared to the theoretical calculation result.It was revealed that the application of optimal design process based on finite element analysis was useful in the pressing block tooth of underwater skirt pile gripper design.The structure charoctenstics and force status of the optimal design were improved,and the engineering demands were well satisfied.
Remote Monitoring of Chronic Critically Ill Patients after Hospital Discharge: A Systematic Review

Background: Over the past few decades, critical care has seen many advancements. These advancements resulted in a considerable increase in the prevalence of chronically critically ill patients requiring prolonged medical care, which led to a massive increase in healthcare utilization. Methods: We performed a search for suitable articles using PubMed and Google Scholar from the inception of these databases to 15 May 2021. Results: Thirty-four articles were included in the review and analyzed. We described the following characteristics and problems with chronic critically ill patient management: the patient population, remote monitoring, the monitoring of physiological parameters in chronic critically ill patients, the anatomical location of sensors, the barriers to implementation, and the main technology-related issues. The main challenges in the management of these patients are (1) the shortage of caretakers, (2) the periodicity of vital function monitoring (e.g., episodic measuring of blood pressure leads to missing important critical events such as hypertension, hypotension, and hypoxia), and (3) failure to catch and manage critical physiological events at the right time, which can result in poor outcomes. Conclusions: The prevalence of critically ill patients is expected to grow. Technical solutions can greatly assist medical personnel and caregivers. Wearable devices can be used to monitor blood pressure, heart rate, pulse, respiratory rate, blood oxygen saturation, metabolism, and central nervous system function. The most important points that should be addressed in future studies are the performance of the remote monitoring systems, safety, clinical and economic outcomes, as well as the acceptance of the devices by patients, caretakers, and healthcare professionals.
Let’s Talk With Developers, Not About Developers: A Review of Automatic Program Repair Research

Automatic program repair (APR) offers significant potential for automating some coding tasks. Using APR could reduce the high costs historically associated with fixing code faults and deliver significant benefits to software engineering. Adopting APR could also have profound implications for software developers’ daily activities, transforming their work practices. To realise the benefits of APR it is vital that we consider how developers feel about APR and the impact APR may have on developers’ work. Developing APR tools without consideration of the developer is likely to undermine the success of APR deployment. In this paper, we critically review how developers are considered in APR research by analysing how human factors are treated in 260 studies from Monperrus’s Living Review of APR. Over half of the 260 studies in our review were motivated by a problem faced by developers (e.g., the difficulty associated with fixing faults). Despite these human-oriented motivations, fewer than 7% of the 260 studies included a human study. We looked in detail at these human studies and found their quality mixed (for example, one human study was based on input from only one developer). Our results suggest that software developers are often talked about in APR studies, but are rarely talked with. A more comprehensive and reliable understanding of developer human factors in relation to APR is needed. Without this understanding, it will be difficult to develop APR tools and techniques which integrate effectively into developers’ workflows. We recommend a future research agenda to advance the study of human factors in APR.
Soft Adversarial Training Can Retain Natural Accuracy

Adversarial training for neural networks has been in the limelight in recent years. The advancement in neural network architectures over the last decade has led to signiﬁcant improvement in their performance. It sparked an interest in their deployment for real-time applications. This process initiated the need to understand the vulnerability of these models to adversarial attacks. It is instrumental in designing models that are robust against adversaries. Recent works have proposed novel techniques to counter the adversaries, most often sacriﬁcing natural accuracy. Most suggest training with an adversarial version of the inputs, constantly moving away from the original distribution. The focus of our work is to use abstract certiﬁcation to extract a subset of inputs for (hence we call it ’soft’) adversarial training. We propose a training framework that can retain natural accuracy without sacriﬁcing robustness in a constrained setting. Our framework speciﬁcally targets moder-ately critical applications which require a reasonable bal-ance between robustness and accuracy. The results testify to the idea of soft adversarial training for the defense against adversarial attacks. At last, we propose the scope of future work for further improvement of this framework.
Evaluating the X-ray-Shielding Performance of Graphene-Oxide-Coated Nanocomposite Fabric

Exposure to ionizing radiation (IR) during diagnostic medical procedures brings certain risks, especially when experiencing recurrent exposures. The fabrication of nano-based composites, doped with different nanoparticles, have been suggested as effective shielding materials to replace conventional lead-based ones in material sciences and nanotechnology. In this study, commercially available fabrics, used to produce scrubs and gowns for clinical staff, are modified utilizing graphene oxide (GO) nanoparticles using a layer-by-layer (LBL) technique. GO was obtained from graphite through environmentally friendly technology by using a modified–improved Hummers’ method without NaNO3. Lightweight, flexible, air- and water-permeable shielding materials are produced that are wearable in all-day clinical practice. The nanoparticles are kept to a minimum at 1 wt%; however, utilizing the LBL technique they are distributed evenly along the fibers of the fabrics to achieve as much shielding effect as possible. The evaluation of samples is accomplished by simulating real-time routine clinical procedures and the radiographic programs and devices used daily. The GO-coated nanocomposite fabrics demonstrated promising results for X-ray shielding.
Supervisory Fuzzy Control of DSP-Based Pendubot

This paper gives a simple and natural control technique to realize swing-up and balance control of a DSP-based pendubot. The switch control is utilized for the integrated controller. The backwards and forwards energy pumping method is used to swing up the pendulum. The proof of this method is provided in this paper. The supervisory fuzzy controller is exploited to stabilize the equilibrium position. The supervisory fuzzy controller includes the fuzzy stabilizing controller and fuzzy target angle tuner. The backwards and forwards energy pumping method and the supervisory fuzzy target angle tuner are the main contributions of this paper. The experimental results show the feasibility of this method.
Aflatoxin Reduction and Retardation of Aflatoxin Production by Microorganisms in Doenjang during a One-Year Fermentation

Meju, a raw material for doenjang preparation, is highly vulnerable to aflatoxin-producing fungi. The aim of this study was to evaluate the effect of a one-year fermentation on aflatoxins and aflatoxin-producing fungi in doenjang spiked with aflatoxins B1, G1, B2, and G2 and inoculated with toxigenic Aspergillus flavus. A significant reduction in aflatoxins was observed after a year of fermentation, measuring 92.58%, 100%, 98.69%, and 100% of B1, G1, B2, and G2, respectively. After a year of fermentation, 6.95 ± 3.64 µg/kg of total aflatoxin was detected, which represents a 97.88% reduction in the total aflatoxin compared with the initial value (328.83 ± 36.60 µg/kg). Several aflatoxin-degrading fungi (Aspergillus versicolor, Cladosporium subcinereum, Aspergillus ochraceus) and bacteria (Bacillus albus, Bacillus velezensis) isolated from doenjang were identified as the major contributors to the reduction of aflatoxin. Furthermore, it was observed that most of the aflatoxin contamination in doenjang occurred during the meju stage, and this stage was found to be most susceptible to A. flavus contamination and growth. These findings reveal that native microorganisms mediate aflatoxin clean-up in doenjang during fermentation and support the use of such microorganisms as a starter culture for the preparation of aflatoxin-free doenjang.
Reflective practice as a threshold concept in the development of pedagogical content knowledge

The acquisition of Pedagogical Content Knowledge (PCK) necessarily requires an integration of knowledge about the content one is teaching with an understanding of appropriate underpinning pedagogic theories and good practice. Experienced colleagues in higher education (HE), who did not have the benefit of a taught course to develop their teaching practice, sometimes only encounter pedagogic literature when they are required to reflect on their practice and take an evidence-informed approach for the purposes of a formal professional recognition. Traditionally, many academics have prioritised the development of their subject expertise and engaged in CPD relevant to their discipline over the development of their teaching expertise (Parsons et al., 2012). Therefore, when they are required to engage with pedagogic literature it can at times prove challenging (Loads, 2013). For teaching practitioners working within HE, successful engagement in professional development relating to teaching, learning and assessment is a prerequisite of the UK Professional Standards Framework for teaching and supporting learning (UKPSF). The UKPSF is used by HE providers in the UK, and increasingly internationally, to benchmark their CPD offer, signal a commitment to teaching and learning, and recognise individuals contribution to student learning and teaching (Spowart et al., 2020). It also provides a common language and descriptions of dimensions of good practice for HE teaching and learning (Hibbert & Semler, 2016). The UKPSF is hosted by Advance HE 1 who accredit CPD provision against the standard, in the form of either taught courses such as Postgraduate Certificates, or institutional schemes that recognise experiential learning. Professional recognition achieved through either of these routes is in the form of an appropriate category of fellowship of the Higher Education Academy.
The Effects of Enteral Nutrition on the Intestinal Environment in Patients in a Persistent Vegetative State

Enteral nutrition (EN) is a rational approach to providing nutritional intake via the intestines in patients who are unable to tolerate parenteral nutrition. We conducted a preliminary study to investigate the effects of EN on the intestinal environment in 10 patients in a persistent vegetative state (PVS) (n = 5 each in the EN and EN with probiotics; Clostridium butyricum MIYAIRI 588) groups compared with 10 healthy controls. The results of 16S amplicon sequencing of the intestinal microbiota showed that EN led to dysbiosis with a decrease in α-diversity and an obvious change in β-diversity. A particularly significant decrease was seen in useful intestinal bacteria such as Bifidobacterium and butyrate-producing bacteria. Analysis of intestinal metabolites also supported these results, showing significant decreases in butyric and pyruvic acid after EN. Although C. butyricum MIYAIRI 588 improved some intestinal metabolites that were decreased after EN, it did not improve the dysbiosis of the intestinal microbiota. These findings indicate that EN causes dysbiosis of the intestinal microbiota and an imbalance in some intestinal metabolites in patients in a PVS. Moreover, although C. butyricum MIYAIRI 588 improved the imbalance of some intestinal metabolites after EN, it did not prevent dysbiosis of the intestinal microbiota.
Aggregation and spatio-temporal dynamics of fruit flies (Diptera, Tephritidae) in papaya orchards associated with different area delimitations in Brazil

We investigated aggregation patterns in three fruit fly species economically important in Brazil, namely Ceratitis capitata, Anastrepha fraterculus, and A. obliqua. The study was carried out in a buffer zone and two neighbourhoods by comparing two-time series associated with the management strategy of fruit flies (systems approach). The abundance of these three species significantly decreased over the years with a negative binomial regression model describing the relationship between abundance and time in the entire area, buffer zone, and their neighbourhoods. In addition, the negative binomial model was also well fitted to the frequency distribution data of fruit flies in all analyzed scenarios. Anastrepha obliqua showed the highest aggregation degree, considering both the entire area and time series. A. fraterculus exhibited the lowest aggregation level, and C. capitata showed an intermediate degree. The buffer zone exhibited the highest aggregation degree for all species, and neighbourhood 2 exhibited the lowest aggregation degree. The aggregation degree was higher in the time series impacted by the systems approach than the series in the first years of its implementation.
AnimaChaotic: AI-based Automatic Conversion of Children's Stories to Animated 3D Videos

Stories are an effective and entertaining way of teaching children about real-life experiences in an engaging way. Although many children’s stories are supplemented with graphical illustrations, having animated 3D video illustrations can effectively boost the learning process, especially for visual learners. However, producing animated 3D videos is a hard, expensive, and time-consuming process, so there is a need to automate this process. In this paper, we introduce AnimaChaotic, a story visualization system designed to automatically convert children’s short stories to animated 3D videos by leveraging Artificial Intelligence (AI) and computer graphics. Our Natural Language Processing (NLP) pipeline extracts visualizable information from the story such as actors and actions. Then, our object positioning algorithm determines the initial positions of the objects in the scene. Finally, the system animates the scene using different techniques including AI behaviors. A quantitative analysis of our system demonstrates a high precision and recall in extracting visualizable information. It also shows that our system outperforms existing solutions in terms of static scene generation. A qualitative analysis of the system shows that its output is visually acceptable and outperforms similar solutions.
Deep neural architectures for dialect classification with single frequency filtering and zero-time windowing feature representations.

The goal of this study is to investigate advanced signal processing approaches [single frequency filtering (SFF) and zero-time windowing (ZTW)] with modern deep neural networks (DNNs) [convolution neural networks (CNNs), temporal convolution neural networks (TCN), time-delay neural network (TDNN), and emphasized channel attention, propagation and aggregation in TDNN (ECAPA-TDNN)] for dialect classification of major dialects of English. Previous studies indicated that SFF and ZTW methods provide higher spectro-temporal resolution. To capture the intrinsic variations in articulations among dialects, four feature representations [spectrogram (SPEC), cepstral coefficients, mel filter-bank energies, and mel-frequency cepstral coefficients (MFCCs)] are derived from SFF and ZTW methods. Experiments with and without data augmentation using CNN classifiers revealed that the proposed features performed better than baseline short-time Fourier transform (STFT)-based features on the UT-Podcast database [Hansen, J. H. , and Liu, G. (2016). "Unsupervised accent classification for deep data fusion of accent and language information," Speech Commun. 78, 19-33]. Even without data augmentation, all the proposed features showed an approximate improvement of 15%-20% (relative) over best baseline (SPEC-STFT) feature. TCN, TDNN, and ECAPA-TDNN classifiers that capture wider temporal context further improved the performance for many of the proposed and baseline features. Among all the baseline and proposed features, the best performance is achieved with single frequency filtered cepstral coefficients for TCN (81.30%), TDNN (81.53%), and ECAPA-TDNN (85.48%). An investigation of data-driven filters, instead of fixed mel-scale, improved the performance by 2.8% and 1.4% (relatively) for SPEC-STFT and SPEC-SFF, and nearly equal for SPEC-ZTW. To assist related work, we have made the code available ([Kethireddy, R., and Kadiri, S. R. (2022). "Deep neural architectures for dialect classification with single frequency filtering and zero-time windowing feature representations," https://github.com/r39ashmi/e2e_dialect (Last viewed 21 December 2021)]. ).
Phytochemicals Mediated Synthesis of AuNPs from Citrullus colocynthis and Their Characterization

Engineered nanoparticles that have distinctive targeted characteristics with high potency are modernistic technological innovations. In the modern era of research, nanotechnology has assumed critical importance due to its vast applications in all fields of science. Biologically synthesized nanoparticles using plants are an alternative to conventional methods. In the present study, Citrullus colocynthis (bitter apple) was used for the synthesis of gold nanoparticles (AuNPs). UV-Vis’s spectroscopy, XRD, SEM and FTIR were performed to confirm the formation of AuNPs. UV-Vis’s spectra showed a characteristic peak at the range of 531.5–541.5 nm. XRD peaks at 2 θ = 38°, 44°, 64° and 77°, corresponding to 111, 200, 220 and 311 planes, confirmed the crystalline nature of AuNPs. Spherical AuNPs ranged mostly between 7 and 33 nm, and were measured using SEM. The FTIR analysis confirmed the presence of phytochemicals on the surface of AuNPs. Successful synthesis of AuNPs by seed extract of Citrullus colocynthis (bitter apple) as a capping and reducing agent represents the novelty of the present study.
Control methods of active power filter

Harmonic pollution becomes more and more serious.Active power filter(APF) is an important equipment to compensate harmonic and reactive currents in power systems and its control method has a great influence on its performance.So many control methods of APF were presented.This paper introduces briefly about several control methods used by APF,covering the one-cycle control,hysteresis current control,space vector control,dead-beat control,sliding mode control,repetitive control,predicted control,fuzzy control,adaptive control,iterative learning control,passivity based control,artificial neural network control and so on.The comparison and analysis indicate their individual advantages and disadvantages.The improved ways and control methods are proposed. This project is supported by National Natural Science Foundation of China(No.60172009),Scientific Research Project of Chongqing(No.7952),and the"Chunhui Proiect" of State Education Ministry of China(No.20033589-13).
Genetic diversity of Aedes albopictus (Skuse) in Sarawak, Malaysia and other regions of the world

This study inferred the genetic diversity and dispersal pattern of Aedes albopictus, for the first time from various populations in Sarawak, the largest Malaysian state situated in northwest Borneo Island. A set of sequences of 120 Ae. albopictus from Sarawak aligned as 633 characters of the cytochrome c oxidase subunit I (COI) revealed 22 haplotypes (A1–A22), of which A1 was the most widespread haplotype. The overall haplotype and nucleotide diversities were 0.65014 and 0.00176, respectively, with no significant genetic differentiation and high gene flow (Nm = 1.07). The genetic distances among the populations ranged from 0 to 0.0227. In the global dataset, sequence alignment of Ae. albopictus from Sarawak and other regions of the world revealed 72 haplotypes. Based on uniquely shared haplotypes, Ae. albopictus in Sarawak has a close affinity with those from Southeast Asian and Oceania regions.