bluuebunny/crossref_metadata_2025 huggingface dataset:
Nutrition in palliative care: issues, perceptions and opportunities to improve care for patients
Authors: Holdoway Anne
Published: November 2022

Dietary advice, the provision of timely nutritional support and the alleviation of diet-related issues, should be an essential component of a holistic approach to palliative and end-of-life care, adjusted to account for the stage in the patient's journey, including prognosis. With an ageing population and increasing numbers of people living with not just one life-limiting disease but several, the dietary management of these patients is becoming more complex. This article considers the issues patients and families experience, how nurses can play a key role in identifying and alleviating nutrition- and diet-related issues in palliative care, including the use of tools to screen, assess and guide nutrition conversations and interventions. The content of the article is mostly drawn from the literature relating to palliative cancer care, knowledge derived from stakeholder engagement, clinical observations in a dietetic role in a hospice setting and qualitative research on the role of diet in palliative care as perceived by patients, carers, and health professionals.
Ratio fluorescence sensor based on CD/Cu-MOFs for detection of Hg2+
Authors: Hou Jingzhou , Zhang Ya , Ming Fanglin , Hong Yiyihui , Liu Huan , He Qiang , Hou Changjun , Huo Danqun
Published: November 2022

Trace detection of toxic heavy metals is a very important and difficult problem in several areas: convenience, sensitivity, and reliability. Herein, we develop an innovative fluorescence resonance energy transfer (FRET)-based ratio fluorescence sensor for the detection of heavy metal mercury ion (

H
g

2
+

). The sensing platform is composed of coumarin derivatives (CDs) and a copper metal-organic framework (Cu-MOF) named CD/Cu-MOF. The constructed CD/Cu-MOFs ratio fluorescence sensor exhibits dual emission peaks at 430 and 505 nm under the single excitation wavelength of 330 nm. With the addition of

H
g

2
+

, the fluorescence intensity of the system at 430 nm gradually increased, and the fluorescence intensity at 505 nm remained stable, resulting in a change in the fluorescence ratio. There is a good logarithmic relationship between the

H
g

2
+

concentration in the range from

2

×

10

−
8

to 0.001 nM and the ratio of the fluorescence emission intensity of the system (

F

430

/

F

505

) (

R

2

=

0.9901

), and its calculated detection limit is

3.76

×

10

−
9

n
M

. In addition, the CD/Cu-MOFs ratio fluorescence sensor has achieved a good recovery rate of standard addition in the actual food sample recovery experiment, which provides an effective method for the detection of

H
g

2
+

in food samples.
Open-source, highly efficient, post-acquisition synchronization for 4D dual-contrast imaging of the mouse embryonic heart over development with optical coherence tomography
Authors: Faubert Andre C. , Larina Irina V. , Wang Shang
Published: November 2022

Dynamic imaging of the beating embryonic heart in 3D is critical for understanding cardiac development and defects. Optical coherence tomography (OCT) plays an important role in embryonic heart imaging with its unique imaging scale and label-free contrasts. In particular, 4D (3D + time) OCT imaging enabled biomechanical analysis of the developing heart in various animal models. While ultrafast OCT systems allow for direct volumetric imaging of the beating heart, the imaging speed remains limited, leading to an image quality inferior to that produced by post-acquisition synchronization. As OCT systems become increasingly available to a wide range of biomedical researchers, a more accessible 4D reconstruction method is required to enable the broader application of OCT in the dynamic, volumetric assessment of embryonic heartbeat. Here, we report an open-source, highly efficient, post-acquisition synchronization method for 4D cardiodynamic and hemodynamic imaging of the mouse embryonic heart. Relying on the difference between images to characterize heart wall movements, the method provides good sensitivity to the cardiac activity when aligning heartbeat phases, even at early stages when the heart wall occupies only a small number of pixels. The method works with a densely sampled single 3D data acquisition, which, unlike the B-M scans required by other methods, is readily available in most commercial OCT systems. Compared with an existing approach for the mouse embryonic heart, this method shows superior reconstruction quality. We present the robustness of the method through results from different embryos with distinct heart rates, ranging from 1.24 Hz to 2.13 Hz. Since the alignment process operates on a 1D signal, the method has a high efficiency, featuring sub-second alignment time while utilizing ∼100% of the original image files. This allows us to achieve repeated, dual-contrast imaging of mouse embryonic heart development. This new, open-source method could facilitate research using OCT to study early cardiogenesis.
THz broadband and dual-channel perfect absorbers based on patterned graphene and vanadium dioxide metamaterials
Authors: Zhuo Shanshan , Liu Zhimin , Zhou Fengqi , Qin Yipeng , Luo Xin , Ji Cheng , Yang Guangxin , Yang Ruihan , Xie Yadong
Published: November 2022

This paper proposes a novel and perfect absorber based on patterned graphene and vanadium dioxide hybrid metamaterial, which can not only achieve wide-band perfect absorption and dual-channel absorption in the terahertz band, but also realize their conversion by adjusting the temperature to control the metallic or insulating phase of VO2. Firstly, the absorption spectrum of the proposed structure is analyzed without graphene, where the absorption can reach as high as 100% at one frequency point (f = 5.956 THz) when VO2 is in the metal phase. What merits attention is that the addition of graphene above the structure enhances the almost 100% absorption from one frequency point (f = 5.956 THz) to a wide frequency band, in which the broadband width records 1.683 THz. Secondly, when VO2 is the insulating phase, the absorption of the metamaterial structure with graphene outperforms better, and two high absorption peaks are formed, logging 100% and 90.7% at f3 = 5.545 THz and f4 = 7.684 THz, respectively. Lastly, the adjustment of the Fermi level of graphene from 0.8 eV to 1.1 eV incurs an obvious blueshift of the absorption spectra, where an asynchronous optical switch can be achieved at f
K
1 = 5.782 THz and f
K
2 = 6.898 THz. Besides, the absorber exhibits polarization sensitivity at f3 = 5.545 THz, and polarization insensitivity at f4 = 7.684 THz with the shift in the polarization angle of incident light from 0° to 90°. Accordingly, this paper gives insights into the new method that increases the high absorption width, as well as the great potential in the multifunctional modulator.
Analog-to-spike encoding and time-efficient RF signal processing with photonic neurons
Authors: Ma Bowen , Zhang Junfeng , Zhao Yang , Zou Weiwen
Published: November 2022

The radio-frequency (RF) signal processing in real time is indispensable for advanced information systems, such as radar and communications. However, the latency performance of conventional processing paradigm is worsened by high-speed analog-to-digital conversion (ADC) generating massive data, and computation-intensive digital processing. Here, we propose to encode and process RF signals harnessing photonic spiking response in fully-analog domain. The dependence of photonic analog-to-spike encoding on threshold level and time constant is theoretically and experimentally investigated. For two classes of waveforms from real RF devices, the photonic spiking neuron exhibits distinct distributions of encoded spike numbers. In a waveform classification task, the photonic-spiking-based scheme achieves an accuracy of 92%, comparable to the K-nearest neighbor (KNN) digital algorithm for 94%, and the processing latency is reduced approximately from 0.7 s (code running time on a CPU platform) to 80 ns (light transmission delay) by more than one million times. It is anticipated that the asynchronous-encoding, and binary-output nature of photonic spiking response could pave the way to real-time RF signal processing.
Mechanical artifacts in optical projection tomography: classification and automatic calibration
Authors: Liu Yan , Dong Jonathan , Pham Thanh-an , Marelli François , Unser Michael
Published: November 2022

Optical projection tomography (OPT) is a powerful tool for biomedical studies. It achieves 3D visualization of mesoscopic biological samples with high spatial resolution using conventional tomographic-reconstruction algorithms. However, various artifacts degrade the quality of the reconstructed images due to experimental imperfections in the OPT instruments. While many efforts have been made to characterize and correct for these artifacts, they focus on one specific type of artifacts, whereas a comprehensive catalog of all sorts of mechanical artifacts does not currently exist. In this work, we systematically document many mechanical artifacts. We rely on a 3D description of the imaging system that uses a set of angular and translational parameters. We provide a catalog of artifacts. It lists their cause, resulting effects, and existing correction methods. Then, we introduce an automatic calibration algorithm that is able to recover the unknown system parameters fed into the final 3D iterative reconstruction algorithm for a distortion-free volumetric image. Simulations with beads data and experimental results on a fluorescent textile fiber confirm that our algorithm successfully removes miscalibration artifacts in the reconstruction.
Pendulum-type light beams
Authors: Jia Junhui , Lin Haolin , Liao Yixuan , Li Zhen , Chen Zhenqiang , Fu Shenhe
Published: November 2022

Nondiffracting and shape-preserving light beams have been extensively studied and were shown to exhibit intriguing wave phenomena, which led to applications including particle manipulation, curved plasma channel generation, and optical superresolution. However, these beams are generated by caustics, i.e., conical superposition of waves. As a result, they tend to propagate along a straight line or accelerate in a plane [(1

+

1)D], and tailoring their propagation trajectories in a higher dimension [(2

+

1]D] is challenging. Here we report both theoretically and experimentally a class of nondiffracting solutions to the paraxial wave equation perturbed by harmonic potential. We demonstrate that the initial wave packets of light can be engineered to accelerate along an arbitrary trajectory centered on an elliptic or a circular orbit in a (2

+

1)D configuration, while maintaining their phase and polarization structures during propagation. Such particle-like features manifested by orbital movements can be attributed to the centripetal force of the underlying potential. We name such oscillating wave packets as pendulum-type beams. We suggest the concept can be generalized to other waves such as quantum waves, matter waves, and acoustic waves, opening possibilities for the study and applications of the pendulum-type wave packet in a wide range, e.g., it may be utilized in the field of laser scanning technology.
Is aggregated surveillance data a reliable method for constructing tuberculosis care cascades? A secondary data analysis from Uganda
Authors: White Elizabeth B. , Hernández-Ramírez Raúl U. , Majwala Robert Kaos , Nalugwa Talemwa , Reza Tania , Cattamanchi Adithya , Katamba Achilles , Davis J. Lucian
Published: November 2022

To accelerate tuberculosis (TB) control and elimination, reliable data is needed to improve the quality of TB care. We assessed agreement between a surveillance dataset routinely collected for Uganda’s national TB program and a high-fidelity dataset collected from the same source documents for a research study from 32 health facilities in 2017 and 2019 for six measurements: 1) Smear-positive and 2) GeneXpert-positive diagnoses, 3) bacteriologically confirmed and 4) clinically diagnosed treatment initiations, and the number of people initiating TB treatment who were also 5) living with HIV or 6) taking antiretroviral therapy. We measured agreement as the average difference between the two methods, expressed as the average ratio of the surveillance counts to the research data counts, its 95% limits of agreement (LOA), and the concordance correlation coefficient. We used linear mixed models to investigate whether agreement changed over time or was associated with facility characteristics. We found good overall agreement with some variation in the expected facility-level agreement for the number of smear positive diagnoses (average ratio [95% LOA]: 1.04 [0.38–2.82]; CCC: 0.78), bacteriologically confirmed treatment initiations (1.07 [0.67–1.70]; 0.82), and people living with HIV (1.11 [0.51–2.41]; 0.82). Agreement was poor for Xpert positives, with surveillance data undercounting relative to research data (0.45 [0.099–2.07]; 0.36). Although surveillance data overcounted relative to research data for clinically diagnosed treatment initiations (1.52 [0.71–3.26]) and number of people taking antiretroviral therapy (1.71 [0.71–4.12]), their agreement as assessed by CCC was not poor (0.82 and 0.62, respectively). Average agreement was similar across study years for all six measurements, but facility-level agreement varied from year to year and was not explained by facility characteristics. In conclusion, the agreement of TB surveillance data with high-fidelity research data was highly variable across measurements and facilities. To advance the use of routine TB data as a quality improvement tool, future research should elucidate and address reasons for variability in its quality.
Participation of young women in sexual and reproductive health decision-making in Malawi: Local realities versus global rhetoric
Authors: Wigle Jannah M. , Paul Stewart , Birn Anne-Emanuelle , Gladstone Brenda , Kalolo Monica , Banda Lumbani , Braitstein Paula
Published: November 2022

Despite the global prioritization of addressing adolescent girls’ and young women’s sexual and reproductive health (SRH) and participatory rights, little research has examined their lived experiences in shaping their engagement in SRH decision-making processes in the global South. Further, few studies have explored how structural and societal factors influence their agency and participation. This critical and focused ethnography, informed by postcolonial feminist and difference-centred citizenship theories, conducted in Malawi (2017–2018) elicited perspectives of youth and key informants to help address these knowledge gaps. Our findings show that the effective implementation and uptake of global discourse on participation and gender equity is hindered by inadequate consideration of girls’ and young women’s local political, cultural and social realities. Many girls and young women demonstrate passion to participate in SRH policymaking as agents of change. However, patriarchal and gerontocratic political and social structures/institutions, and gendered and adultist norms and practices limit their active and meaningful participation in SRH decision-making. In addition, donors’ roles in SRH policymaking and their prioritization of the “girl child” highlight an enduring postcolonial power over agenda-setting processes. Understanding young people’s experiences of gendered participation and scrutinizing underlying systemic forces are critical steps toward realizing young women’s SRH and participatory rights.
The Five Canadas of Climate Change: Using audience segmentation to inform communication on climate policy
Authors: Martel-Morin Marjolaine , Lachapelle Erick
Published: November 2022

This study examines how unique audience segments within the Canadian population think and act toward climate change, and explores whether and how the level of audience engagement moderates the effect of various messages on support for climate policy. Drawing on a random probability sample of Canadian residents (N = 1207) conducted in October 2017, we first identify and describe five distinct audiences that vary in their attitudes, perceptions and behaviours with respect to climate change: the Alarmed (25%), Concerned (45%), Disengaged (5%), Doubtful (17%) and Dismissive (8%). We then explore how each segment responds to different messages about carbon pricing in Canada. We find that messages alluding to earmarking (i.e., “Invest in solutions”) or leveling the playing field for alternative energy sources (i.e., “Relative price”) increase support for a higher carbon price among the population as a whole. However, these messages decreased support for carbon pricing among more engaged audiences (e.g., Alarmed) when a low carbon price was specified to the respondent. Meanwhile, the “Relative price” is the only message that increased policy support among less engaged audiences–the Concerned and the Doubtful. In addition to highlighting the importance of tailoring and targeting messages for differently engaged segments, these results suggest that communicating around the specific consequences of carbon taxes for the prices of some goods may be a fruitful way to enhance support for carbon taxes among relatively less engaged audiences.
Authenticating coins of the ‘Roman emperor’ Sponsian
Authors: Pearson Paul N. , Botticelli Michela , Ericsson Jesper , Olender Jacek , Spruženiece Liene
Published: November 2022

The ‘Roman emperor’ Sponsian is known only from an assemblage of coins allegedly found in Transylvania (Romania) in 1713. They are very unlike regular Roman coins in style and manufacture, with various enigmatic features including bungled legends and historically mixed motifs, and have long been dismissed as poorly made forgeries. Here we present non-destructive imaging and spectroscopic results that show features indicative of authenticity. Deep micro-abrasion patterns suggest extensive circulation-wear. Superficial patches of soil minerals bound by authigenic cement and overlain by oxidation products indicate a history of prolonged burial then exhumation. These observations force a re-evaluation of Sponsian as a historical personage. Combining evidence from the coins with the historical record, we suggest he was most likely an army commander in the isolated Roman Province of Dacia during the military crisis of the 260s CE, and that his crudely manufactured coins supported a functioning monetary economy that persisted locally for an appreciable period.
Projections of adult skills and the effect of COVID-19
Authors: Özdemir Caner , Reiter Claudia , Yildiz Dilek , Goujon Anne
Published: November 2022

In this paper, we project Skills in Literacy Adjusted Mean Years of Schooling (SLAMYS) for the working age population in 45 countries and quinquennial time periods until 2050 according to various population scenarios. Moreover, we integrate the effect of school closures due to the COVID-19 pandemic on these projections. Adult skills are projected using the cohort components method. They can help in assessing the potential consequences of the recent trends for the adult population, particularly the workforce, whose skills are essential for the jobs contributing to economic growth and development outlooks. Our projections are novel as they take into account both the amount of schooling and quality of education and also consider the changes in adult skills through lifetime. Projections show that the adult skills gap between countries in the Global North and countries in the Global South will likely continue to exist by 2050, even under very optimistic assumptions–but may widen or narrow depending on the demographic development trajectories specific to each country. Moreover, the loss of learning due to school closures during the COVID-19 pandemic further exacerbates inequalities between countries. Particularly, in countries where schools have been closed for a prolonged period of time and the infrastructure for effective online schooling is lacking, the skills of cohorts who were in school during the pandemic have been severely affected. The fact that the duration of school closures has been longer in many low- and middle-income countries is a serious concern for achieving global human capital equality. The impact of the COVID-19 pandemic is projected to erase decades-long gains in adult skills for affected cohorts unless policies to mitigate learning loss are implemented immediately.
Throughput screening of Bacillus subtilis strains that abundantly secrete surfactin in vitro identifies effective probiotic candidates
Authors: Lee Dongho , Oh Taehoon , Kang Bongseok , Ahn Jong Seok , Cho Yangrae
Published: November 2022

Since the prohibition of antibiotics as animal growth promoters, demand for effective probiotic strains has steadily increased. The goal is to maintain productivity and mitigate environmental concerns in the livestock industry. There are many probiotic animal-diet supplements available, over 2,000 products in the Republic of Korea alone, with little explanation about the desirable properties of each probiotic strain. The purpose of this study was to describe the underlying logic and methods used to select two novel strains of probiotic candidates. To economically screen these candidates, the abundance of surfactin secreted was used as an in vitro marker. We used a modified oil-misting method to screen ~2,000 spore-forming bacteria for novel strains of Bacillus subtilis. Of these, 18 strains were initially selected based on the semiquantitative criterion that they secreted more surfactin than B. subtilis ATCC21322 on Luria-Berani (LB) agar plates. The whole genome sequence was determined for two of the 18 strains to verify their identity. A phylogeny of 1,162 orthologous genes, genome contents, and genome organization confirmed them as novel strains. The surfactin profiles produced by these two strains consisted of at least four isoforms similar to standard surfactin and enhanced cellulase activities up to 50%. Four fractionated individual isoforms of surfactin suppressed inflammation induced by lipopolysaccharides. The half-maximal inhibitory concentration (IC50) was about 20 μM for each isoform. Both selected strains were susceptible to seven important antibiotics. Our results implied that an abundant secretion of surfactin was a useful biomarker in vitro and could be utilized for mining probiotic candidates through high-throughput screening of environmental samples.
INTERNATIONAL DIVERSIFICATION STRATEGIES AND THEIR EFFECTS ON THE PERFORMANCE OF COMPANIES LISTED ON B3
Authors: Pereira Júnior Aloisio , Pereira Vinícius
Published: November 2022

Objetivo: A pesquisa busca verificar se o caixa moderado pelas contingências ambientais (munificência e dinamismo) medeia a relação entre diversificação internacional e desempenho das empresas brasileiras exportadoras listadas na B3.
Método: Foram analisadas empresas brasileiras exportadoras listadas na B3, no período de 2010 a 2020 e realizadas análises multivariadas com dados em painel com efeitos fixos e dinâmicos, nesse caso, utilizando-se o método System-GMM, por meio do modelo de mediação moderada proposto por Muller, Judd e Yzerbyt (2005).
Resultados: Os resultados indicam que o caixa, moderado pela instabilidade e crescimento do setor, medeia a relação entre a diversificação internacional e desempenho das empresas exportadoras da amostra. O efeito indireto da diversificação internacional no desempenho é melhor por meio de maior liquidez das empresas exportadoras em um ambiente menos instável e munificente. Os achados sugerem que os gestores de empresas exportadoras devem analisar as reservas de caixa na expansão dos negócios para o mercado externo, levando em consideração o ambiente de tarefas no qual a empresa atua.
Contribuições: O presente estudo traz contribuições para a teoria por expandir os estudos dos efeitos da diversificação internacional no desempenho das empresas, sugerindo que a liquidez tem valor estratégico na expansão dos negócios para o mercado externo. Empiricamente, traz implicações práticas importantes sobre o processo de tomada de decisão de constituição e gestão da liquidez, mostrando que os gestores de empresas exportadoras devem analisar os custos e benefícios da liquidez, observando a instabilidade e crescimento do setor para melhorarem o desempenho das empresas.
CONSUMERS' INTENTION TO USE OMNICHANNELS: SOUTH AFRICAN RETAIL STORES PERSPECTIVE
Authors:   University of the Western Cape, Matlala Ntswaki Petunia , Shumba Knowledge , Shambare Richardson
Published: November 2022

The fourth industrial revolution has transformed how we do things, including retailing and consumers' shopping habits. Multiple devices equipped with multiple screens enable consumers to compare prices before purchasing goods or services. Despite the fast pace of technological development that has provided an opportunity for a unique and satisfying experience for consumers through any touch point in the retailing industry globally, retailers in developing countries are still lagging in understanding the factors influencing omnichannel consumers' behaviour. The literature on factors influencing omnichannel use in a South African context remains inconsistent and fragmented, as most previous studies are based on consumers in European and Asian markets (Weber-Snyman & Badenhorst-Weiss, 2018). Against this backdrop, it becomes imperative to explore the factors influencing omnichannel consumers' behaviour in South Africa. The study contributes to the emerging and growing field of omnichannel retailing by identifying the factors influencing consumer behavioural intention to use omnichannel in South Africa. Consumers seek out new technology to experiment with and be the first to try it among their family and friends. A descriptive survey was conducted in Gauteng province using a questionnaire. Respondents were identified through the convenience sampling method. The study findings suggest that a consumer's intention to purchase in an omnichannel store is influenced by performance expectancy, effort expectancy and personal innovativeness. The researcher recommends that the omnichannel retailer managers properly define the values incorporated in an omnichannel store to stimulate personal innovativeness during the online shopping journey, as personal innovativeness is an essential predictor of purchase intention. It would be interesting for another researcher to replicate this study in other provinces across South Africa, specifically rural areas.
A Context-Based Multi-Scale Discriminant Model for Natural Image Inpainting
Authors: Wang Chao , Shao Mingwen , Zhang Wentao , Zhang Youcai
Published: November 2022

Image inpainting is a classical yet challenging problem in computer vison with many real-world applications. In this paper, we propose a novel method for inpainting based on Convolutional Neural Network (CNN) and Generative Adversarial Networks (GAN). By analogy with the autoencoder, a new context encoder is proposed to generate the contents of a missing image region conditioned on its surroundings. To improve the stability and efficiency, we also modify the architecture of the context encoder by introducing 1*1 convolution, as well as other improvements. In addition, a multi-scale discriminator combining with GAN is presented. During training, the reconstruction and adversarial losses are used for the global image. To generate more details, we further add a local texture loss for the missing part. Qualitative experiments show that our model performs favorably against classical methods in generating visually plausible inpainting results. Moreover, quantitative experiments substantiate the effectiveness of the proposed method in natural image inpainting.
Real-Time Fabric Defect Segmentation Based on Convolutional Neural Network
Authors: Wang Zhen , Junfeng Jing , Zhang Huanhuan , Zhao Yan
Published: November 2022

Automated visual inspection for quality control has widely-used deep convolutional neural networks (CNNs) in fabric defect detection. Most of the research on defect detection only focuses on increasing the accuracy of segmentation models with little attention to computationally efficient solutions. In this study, we propose a highly efficient deep learning-based method for pixel-level fabric defect classification algorithm based on a CNN. We started with the ShuffleNet V2 feature extractor, added five deconvolution layers as the decoder, and used a resize bilinear to produce the segmentation mask. To solve the sample imbalance problem, we used an improved loss function to guide network learning. We evaluated our model on the fabric defect data set. The proposed model outperformed the existing image segmentation models in both model efficiency and segmentation accuracy.
Automatic Recognition of Garment Illustrations Based on CNN
Authors: Hong Wenting , Liu Yongmei , Tong Weiqing , Ma Yonghao
Published: November 2022

In the process of garment production, obtaining and identifying garment illustrations, transforming them into the required information, and then implementing the information into automated production can improve the production efficiency to a great extent. However, the research on recognition of garment illustration and pattern image is mostly based on category classification, but very little on the identification of parts and details. The Inception module in the GoogleNet Inception and its improvement development models enhance parameter utilization, accelerate computation, and have no special requirements for hardware. The Mask R-CNN, a convolutional neural network, is a modified model from based on Faster R-CNN for instance splitting tasks. Based on these two models, this paper proposes a method to identify garment illustrations using a self-built database. The experimental results show that this method outperforms the related algorithms.
Single Image Self-Learning Super-Resolution with Robust Matrix Regression
Authors: Jian Zhang , Tengteng Xu , Jianjun Qian , Xiao Yuchen , Zhang Heng , Li Hongran , Li Cunhua
Published: November 2022

The similarity measure plays the key role in the self-learning framework for single image super-resolution. This paper involves matrix regression with properties of robustness and two-dimensional structure to measure the similarity between image blocks and enhance the effect of super-resolution. Specifically, we use the minimal nuclear norm of representation error as a criterion, and the alternating direction method of multipliers (ADMM) to calculate the similarity between high- and low-resolution image blocks. Evaluation on several images with different interference and experimental results of super-resolution images clearly demonstrate the advantages of our proposed method in visual robustness and super-resolution effects.
Fabric Defect Detection Using Deep Convolution Neural Network
Authors: Fan Junjun , Wong Wai Keung , Wen Jiajun , Gao Can , Mo Dongmei , Lai Zhihui
Published: November 2022

Fabric defect detection plays an increasingly important role in the industrial automation application for fabric production, but how to detect defects rapidly and accurately is still challenging. In this study, we propose a powerful fabric defect detection method using a hybrid of convolutional neural network (CNN) and variational autoencoder (VAE). The convolutional layers are used for extracting fabric image pattern features and the variational autoencoder is used for modeling the latent characteristics and inferring a reconstruction. The defect positions can be detected by the differences between the original image and the reconstruction image. The proposed method is validated on public patterned fabric datasets. The experimental results demonstrate that the proposed model can achieve outstanding performance in both image level and pixel level defect detection.
Jointly Linear Embedding via L2,1-Norm for Dimensionality Reduction
Authors: Cui Jinrong , Wen Jiajun , Ye Jun , Lian Junjian , Liu Xin
Published: November 2022

In this study, we present a novel dimensionality reduction method called Jointly Linear Embedding (JLE). Unlike previous methods such as Neighborhood Preserving Embedding (NPE), in which local neighborhood information is preserved during the dimensionality reduction procedure, JLE aims to preserve the sparse reconstructive relationship of the original data by taking the merits of jointly sparse learning based on L2,1-norm. In the framework of JLE, the sparse weight matrix can reflect the intrinsic geometric structures of the original data and inherit the ability of discriminant analysis. By solving the L2,1-norm regularized objective function, the optimal projections, which are invariant to rotations and robust to outliers, can be obtained by JLE. Extensive experiments on visual recognition and fabric defect classification datasets demonstrate the superiority of the proposed L2,1-norm regularized learning method compared with the state-of-the-art methods.
Investigation of Self-Adaptive Breathable Nano-TiO2/PU Membrane with Water Vapor Transmission
Authors: Yang Qun , Liang Qi , Wang Liming
Published: November 2022

Wearable materials with thermal management and self-adaptive breathability have attracted increasing attention. In this study, nano-TiO2/polyurethane (PU) membranes were prepared via casting. Properties of fabricated nano-TiO2/ PU membranes were characterized systematically by Scanning Electron Microscope (SEM), Fourier Transform Infrared Spectrometer (FTIR), Thermal Gravity Analysis (TGA), Differential Scanning Calorimetry (DSC), and strength tester. The effects of TiO2 content on waterproofness, moisture permeability, and thermal stability of the composite membranes were studied. The experimental results show that with the increase of TiO2 content, the thermal stability of the composite membranes increased; waterproofness and moisture permeability performance also improved.
Structure Control and Application of Nanocellulose Aerogels
Authors: Wang Ziyang , Yang Xue , Liu Wei
Published: November 2022

Nanocellulose is a kind of renewable green material that comes mainly from plants. Nanocellulose aerogels have high porosity, excellent flexibility, and low thermal conductivity. They have broad application prospects in building insulation, sewage treatment, energy storage, aerospace, and other fields. The structure of nanocellulose aerogels has a significant influence on their properties, which further affects their application. In this paper, the present regulation methods of nanocellulose aerogel structure are reviewed, and the most widely used fields of nanocellulose aerogel are introduced in detail. In addition, research for improving the structure and applications of nanocellulose aerogels in the future is proposed.
Dyeing Properties of Polyester/Cotton Blended Fabric in the Silicone Non-Aqueous Dyeing System
Authors: Pei Liujun , Jiang Nan , Wang Jiping
Published: November 2022

Polyester/cotton blended fabrics have been extensively used in the textile industry. However, the dyeing process of polyester/ cotton blended fabrics is complex, and a large amount of water is consumed. To increase the dye uptake and dye fixation ratio, and reduce wastewater effluents, the dyeing performance of polyester/cotton blended fabric was studied in one bath and two steps using the silicone non-aqueous dyeing system. When dyeing 1 kg of polyester/cotton blended fabric, only 1.17 kg of water was consumed, and no wastewater was discharged after dyeing. The washing fastness, staining fastness, and dry and wet rubbing fastness of dyed fabric can reach high levels. The dyeing performance of two disperse dyes on the cotton and polyester components in the blended fabric was also studied.
Effect of Clothing Pressure on Exercise Fatigue Based on EEG
Authors: Wang Jiacheng , Li Yanmei
Published: November 2022

To optimize the use of compression clothing to alleviate sports fatigue, this review discusses the current research status on clothing pressure and fatigue relief, and the principle of clothing pressure to relieve fatigue. In addition, research developments on the application of electroencephalography (EEG) in clothing pressure and sports fatigue are discussed and the relationship between the clothing pressure, EEG, and sports fatigue is analyzed. The mechanism of sports fatigue can be understood more comprehensively via EEG. Building a garment pressure evaluation system provides avenues for the research and development of apparel to relieve fatigue.
Psychological insulin resistance and affecting factors in patients with type 2 diabetes
Authors: Çevik Aktura Seher , Özden Gürkan
Published: November 2022

Aim: The aim of this study was to investigate psychological insulin resistance and factors affecting it in patients with diabetes mellitus.
Method: This descriptive study was conducted in a university hospital in eastern Turkey. The population of the study consisted of patients diagnosed with type 2 DM in the internal medicine clinic of the said hospital. Data were collected using the Patient Identification Form, Problematic Areas in Diabetes, Treatment Compliance and Psychological Insulin Resistance Scales in Patients with Diabetes, which were used to determine the descriptive characteristics of the patients.
Findings: In the study, it was found that the mean score of the problematic areas in diabetes scale was 37.89 ± 5.81 and the patients did not experience emotional distress, the mean score of the treatment compliance scale was high (96.56 ± 13.28) and their compliance to treatment was low, the mean score of the psychological insulin resistance scale was 48.40 ± 8.79 and the psychological insulin value of the patients was high.
Conclusion: As a result of the study, it was determined that patients’ BMI, education level, employment status, problematic areas in diabetes scale and treatment compliance scale scores were important predictors for psychological insulin resistance.
 
Özet
Amaç: Araştırma, diyabetli hastalarda psikolojik insülin direnci ve etkileyen faktörlerin incelenmesi amacıyla yapılmıştır.
Metot: Tanımlayıcı tipteki bu araştırma, Türkiye’nin doğusunda yer alan bir üniversite hastanesinde yürütülmüştür. Araştırmanın evrenini adı geçen hastanenin dahiliye kliniğinde tip 2 DM tanısı almış hastalar oluşturmuştur. Araştırma verileri, hastaların tanıtıcı özelliklerini belirlemek amacıyla kullanılan Hasta Tanıtım Formu, Diyabette Problemli Alanlar, Tedaviye Uyum ve Diyabetli Hastalarda Psikolojik İnsülin Direnci Ölçekleri ile toplanmıştır.
Bulgular: Araştırmada hastaların diyabette problemli alanlar ölçeği puan ortalamasının 37.89 ± 5.81 olduğu ve emosyonel distres yaşamadığı, tedavi uyum ölçeği puan ortalamasının yüksek olduğu (96.56 ± 13.28) ve tedaviye uyumlarının düşük olduğu, psikolojik insülin direnci ölçeği puan ortalamalarının 48.40 ± 8.79 olduğu ve hastaların psikolojik insülin değerinin yüksek olduğu bulunmuştur.
Sonuç: Araştırmanın sonucunda hastaların BKİ, eğitim düzeyi, çalışma durumu, diyabette problemli alanlar ölçeği ve tedavi uyum ölçeği skorlarının psikolojik insülin direnci için önemli yordayıcılar olduğu belirlenmiştir.
Clinical Course of COVID-19 and Cycle Threshold in Patients with Haematological Neoplasms
Authors: Santarelli Ignacio Martín , Sierra Mariela , Vaulet María Lucía Gallo , Fermepin Marcelo Rodríguez , Fernández Sofía Isabel
Published: November 2022

The SARS-CoV-2 viral load in a respiratory sample can be inversely quantified using the cycle threshold (Ct), defined as the number of amplification cycles required to detect the viral genome in a quantitative PCR assay using reverse transcriptase (RT-qPCR). It may be classified as high (Ct < 25), intermediate (25–30) and low (Ct > 30). We describe the clinical course of 3 patients with haematological neoplasms who contracted COVID-19. None of them had been vaccinated. Firstly, a 22-year-old male with a refractory acute lymphoblastic leukaemia experienced an oligosymptomatic COVID-19 and had a Ct of 23 with an ascending curve. Another male, aged 23, had recently begun treatment for a promyelocytic leukaemia. He had a subacute course with high oxygen requirements. His Ct dropped from 28, when he only experienced fever, to 14.8, during the most critical period and on the edge of ventilatory support. Viral clearance was documented 126 days after the beginning of the symptoms. Finally, a 60-year-old male had received rituximab as maintenance therapy for a follicular lymphoma 3 months before contracting COVID-19. He had a fulminant course and required mechanical ventilation a few days later. We highlight the association between the course of CoViD-19 and the Ct. Viral shedding was longer than in immunocompetent hosts.
A bibliometric analysis of botanical insecticides for Lepidopteran insects over the period 1985-2022
Authors: Sofia Siti Sa'adah Nadya , Sukirno Sukirno , Alwandri Hipny , Rini Nuringtyas Tri , Hartanto Nugroho Laurentius
Published: November 2022

Lepidoptera is an economically important insect pest that attacks many commercially important crops. Synthetic insecticides are currently most extensively utilized to control this pest. The use of massive doses of synthetic pesticides has resulted in resistance and resurgence. Therefore, developing an environmentally acceptable technique for controlling insect pest populations, such as using natural plant components as insecticides, can assist in mitigating the negative impacts of synthetic pesticides. Plant pesticides or botanical insecticides are becoming increasingly popular. This bibliometric research aimed to demonstrate the growth, awareness, importance, international cooperation or collaboration and knowledge gaps in developing synthetic botanical insect pesticides in the future. Information used in this research was culled from 138 scientific papers (Scopus database) and analyzed using VOSviewer 1.6.17. Descriptive statistics was used to identify the rate of botanical insecticide development in controlling these insect pests by analyzing the contributing documents by year, country and bibliometric analysis of country and keyword co-occurrence. The research started in 1985 and exponential growth occurred after 2006. In addition, the trend peaked in 2020 and is currently being maintained. The scientific papers were distributed from 41 countries, with Brazil being the most productive. The bibliographical network shows the relatedness of information about keywords between countries. The results obtained can help recognize existing knowledge gaps that need to be addressed and considered in developing botanical insecticides to control this lepidopteran pest.
Developing feedback literacy capabilities through an AI automated feedback tool
Authors: Tubino Laura , Adachi Chie
Published: November 2022

The use of Artificial Intelligence (AI) in teaching has mainly focused on providing students with immediate, and more, feedback while reducing teachers’ workload. In this paper, we propose a shift in thinking about the role AI can play in developing students’ feedback literacy. Through the reflection of a University wide T&L pilot project ran with an AI tool for automated feedback, we frame a discourse on the use of AI for teaching and learning to promote and further develop students’ feedback literacy capabilities, including the dispositions required for a meaningful partnership with their teachers in relation to feedback. This paper reports the interactions of higher education students with an AI automated feedback tool and discusses its affordances in relation to the development of students’ feedback literacy capabilities. Implications for further refinement of this tool are also presented.
‘Made good connections’: Amplifying teacher presence and belonging at scale through learning design and personalised feedback
Authors: Lim Lisa-Angelique , Atif Amara , Farmer Ian
Published: November 2022

While online learning offers much flexibility for students in terms of time and place, students’ experiences of online learning have been less than positive. A sense of belonging is key to students’ success and retention in any learning environment. Teaching or teacher presence is significant for setting a climate for belonging. However, few studies have documented how teachers can foster students’ sense of belonging in online settings and students’ experience of these initiatives. This paper presents an exploratory case study of a teacher’s initiatives to foster students’ belonging in an online subject by amplifying teacher presence through technology-mediated, personalised feedback embedded within interactive, engaging subject design. Students’ experiences of the subject and perceptions of their personalised feedback were captured through surveys and focus groups. Together, the findings indicate that the primary role of personalised feedback in fostering belonging was building connectedness between the teacher and students, thereby enhancing students’ motivation to learn in the subject. The findings also resonate with other research highlighting the importance of teacher presence throughout the subject, not just during synchronous classes.
Assessment of drug delivery devices working at microflow rates
Authors: Niemann Anders Koustrup , Batista Elsa , Geršl Jan , Bissig Hugo , Büker Oliver , Lee Seok Hwan , Graham Emmelyn , Stolt Krister , Afonso Joana , Benková Miroslava , Knotek Stanislav
Published: November 2022

Almost every medical department in hospitals around the world uses infusion devices to administer fluids, nutrition, and medications to patients to treat many different diseases and ailments. There have been several reports on adverse incidents caused by medication errors associated with infusion equipment. Such errors can result from malfunction or improper use, or even inaccuracy of the equipment, and can cause harm to patients’ health. Depending on the intended use of the equipment, e.g. if it is used for anaesthesia of adults or for medical treatment of premature infants, the accuracy of the equipment may be more or less important. A well-defined metrological infrastructure can help to ensure that infusion devices function properly and are as accurate as needed for their use. However, establishing a metrological infrastructure requires adequate knowledge of the performance of infusion devices in use. This paper presents the results of various tests conducted with two types of devices.
Bernoulli Free Boundary Problems Under Uncertainty: The Convex Case
Authors: Dambrine Marc , Harbrecht Helmut , Puig Benedicte
Published: November 2022

The present article is concerned with solving Bernoulli’s exterior
free boundary problem in the case of an interior boundary that is
random. We provide a new regularity result on the map that sends
a parametrization of the inner boundary to a parametrization of the
outer boundary. Moreover, assuming that the interior boundary
is convex, also the exterior boundary is convex, which enables to
identify the boundaries with support functions and to determine their
expectations. We in particular construct a confidence region for the
outer boundary based on Aumann’s expectation and provide a numerical
method to compute it.
Infinitely many solutions for quasilinear Schrödinger equations with sign-changing nonlinearity without the aid of 4-superlinear at infinity
Authors: Khiddi Mustapha , Essafi Lakbir
Published: November 2022

In this article, we will prove the existence of infinitely many solutions for a class of quasilinear Schrödinger equations without assuming the 4-superlinear at infinity on the nonlinearity. We achieve our goal by using the Fountain theorem.