Miracle-dz/UniFAR-FTUs huggingface dataset:
Population diversity of "Candidatus Liberibacter asiaticus" and Diaphorina citri in Sichuan: A case study for Huanglongbing monitoring and interception.

Citrus Huanglongbing (HLB) is present in 10 provinces in China and is associated with "Candidatus Liberibacter asiaticus" (CLas), which is transmitted by the Asian citrus psyllid (Diaphorina citri, ACP). To date, HLB and ACP have expanded to Yibin city of Sichuan Province, posing an imminent threat to the citrus belt of upper and middle reach of Yangtze River, an important late maturing citrus-producing area in China. To understand the epidemiological route of CLas and ACP in newly invaded regions of Sichuan and thereby better establish an HLB-interception zone ranging from Leibo to Yibin, we evaluated the molecular variability of 19 CLas draft genomes from citrus or dodder (Cuscuta campestris). They include three type-specific prophage loci, three variable numbers of tandem repeat (VNTR) loci, a miniature inverted-repeat transposable element (MITE) types, and population diversity of 44 ACP mitochondrial genomes. The results indicated that CLas isolates in the newly invaded area (Pingshan) were more diverse than those in the HLB endemic areas (Leibo and Ningnan). Phylogenetic analysis based on mitochondrial genomes demonstrated that ACPs in Leibo, Pingshan and Xuzhou (rural areas) represent a new group (MG4), distinguished by the three unique SNPs in cox1, nad4 and cytb. However, the ACPs sampled from the urban areas of Cuiping and Xuzhou belonged to the southeastern China group (MG2-1). Altogether, our study revealed multiple sources of ACP and CLas in the HLB-interception zone and proposed their transmission route. This study contributes to the formulation of precise HLB prevention and control strategies in the HLB-interception zone in Sichuan and could be useful for HLB management efforts in other regions.
GA-Net: A Guidance Aware Network for Skeleton-Based Early Activity Recognition

Early activity prediction, which aims to recognize class labels before actions are fully performed, is a very challenging task since partially observed action sequences contain insufficient class-discrimination information, and thus, many partial action sequences belonging to different categories may look very similar. Therefore, in this paper, we propose a novel guidance aware network (GA-Net) to boost the ability to distinguish different activities in diversified partially observed action sequences via metric learning. To mitigate the similarity problem of action segments at very early stages, the proposed guided metric learning module (GMLM) is able to encourage the feature extractor to mine class-discriminative information given partially observed sequences. Specifically, the GMLM is able to minimize the intraclass distance with a full-length guided direction approach and maximize the difference between interclass categories with different observation ratios. To enhance the similarities between the partial- and full-length sequences in the same action categories, we further introduce a distribution alignment module (DAM) that employs full-length guidance to pull the partially observed features closer to the global features. We evaluate our proposed method on three public human activity datasets and achieve competitive results compared with the state-of-the-art approaches.
PENGARUH PROMOSI, PERSEPSI KEMUDAHAN DAN PERSEPSI MANFAAT TERHADAP MINAT PENGGUNAAN E-WALLET DENGAN KEPERCAYAAN SEBAGAI VARIABEL MEDIASI PADA PENGGUNA E-WALLET DI KOTA BANJARMASIN

Abstrak: Penelitian ini bertujuan untuk menjelaskan pengaruh pengaruh promosi, persepsi kemudahan, dan persepsi manfaat terhadap minat penggunaan dengan kepercayaan sebagai variable mediasi. Penelitian ini dilakukan di Banjarmasin dan populasi pada penelitian ini adalah masyarakat pengguna e-wallet. Teknik pengambilan sampel yang digunakan pada penelitian ini adalah metode purposive sampling dengan jumlah responden 100 orang. Metode pengumpulan data menggunakan kuesioner melalui google form. Teknik analisis data yang digunakan adalah SEM (Structural Equation Modeling) untuk mengetahui hubungan antar variabel dengan aplikasi AMOS 24 dan Uji Sobel untuk mengetahui peran mediasi. Hasil penelitian ini menunjukkan bahwa promosi, persepsi kemudahan dan persepsi manfaat berpengaruh positif dan signifikan terhadap kepercayaan dan minat penggunaan, kepercayaan berpengaruh positif dan signifikan terhadap minat penggunaan e-wallet. Kepercayaan mampu memediasi secara positif dan signifikan pengaruh promosi, persepsi kemudahan dan persepsi manfaat terhadap minat pengunaan e-wallet. Kata kunci: promosi, persepsi kemudahan, persepsi manfaat, minat penggunaan
Chancen und Hemmnisse für den Metallschaumeinsatz

Materials represent more and more the initial key to market success. New developments in material research produce frequently innovative product designs. Metal foam is such an material innovation. It's been characterized by disintegrating solid structures into cellular structures. Metal foam combines excellent properties such as mass-rigidness-relation, vibration- and acoustic damping, crash-absorption and thermal insulation effects. Despite its characteristics there is not a single application known in mass production. To investigate its reasons was the purpose of a 1999 initiated opinion poll by the Fraunhofer-Institute in Chemnitz.
Selecting wastewater systems for sustainability in developing countries

This paper presents a methodology for systematically incorporating multi-dimensional sustainability considerations into the selection of wastewater options for developing countries and the evaluation and comparison of these options. Appropriate technologies for developing countries were screened based on their function and their use of operational sustainability features; this list of technologies can then be used to elaborate design options. Sustainability indicators are used to enable a parallel comparison of the options from environmental, economic, and socio-cultural perspectives. For illustration, the indicator approach is applied to a case study of the sanitation options for peri-urban/rural areas of the eThekwini Municipality in South Africa.
An Informetric Analysis of Relationship between Open Access Presence and Ranking of African Universities

This study was conducted to determine the relationship between open access presence and ranking of African universities. It adopted descriptive informetric to examine open access presence of African countries using Directory of Open Access Repositories (DOAR) and Research Gate scores (RGs) of the universities. Data was also extracted from the Journal Consortium (an African university ranking organisation) for metrics on African university ranking. Data on African open access presence was correlated with university rankings. Findings reveal that only twenty-four countries in Africa have records in DOAR and Research gate. Four of the countries (South Africa, Egypt, Kenya and Nigeria) contribute more over 85% of open access records in Africa and the same produced 68% of the top 100 universities in Africa. The study found a highly significant positive but moderate correlation between open access presence and ranking of African universities. It concludes that African universities need to review their science policy in line with open access initiative to enhance the visibility and ranking of the university globally.
Generalized-material-independent PML absorbers used for the FDTD simulation of electromagnetic waves in 3-D arbitrary anisotropic dielectric and magnetic media

By introducing the material-independent quantities (electric displacement D and flux density B) into the finite-difference time-domain (FDTD) model, a generalized-material-independent perfectly matched layer (GMIPML) absorber used to absorb electromagnetic waves propagating in three-dimensional (3-D) general anisotropic dielectric and magnetic media is proposed. Within the proposed GMIPML absorber, D and B are directly absorbed, whereas E and H are simultaneously absorbed through the relations between E and D, as well as H and B. It is shown that with the help of this GMIPML absorber, Berenger's perfectly matched layer (PML) absorbing boundary condition (ABC) can be simply and effectively extended to 3-D arbitrary anisotropic materials consisting of both arbitrary permittivity and permeability tensors.
New offsite production and business models in construction: priorities for the future research agenda

Despite the benefits offered by offsite construction, as a percentage, the offsite market is still relatively small. This phenomena is complex; but for brevity, includes a myriad of factors, not least: lack of awareness; supply chain challenges (capacity and knowledge); cultural perception; lack of viable business process models/solutions; and paucity of skills (design/manufacturing/construction). However, many governments are still promoting the offsite agenda through various conduits. Given this, a CIB Task Group (TG74) developed a research roadmap for new production and business models for the construction industry uptake. This paper summarises the work of TG74, where people, process and technology drivers were investigated for construction, manufacturing and design and mapped against three levels of priority and three timeframes. Results indicate that for people drivers, new skills are urgently needed in the design field within a 0–5 year timeframe (compared to a timeframe of 6–10 years for the manufacturing sector). Regarding process drivers, construction process was classed as high priority, followed by design process and manufacturing process. Finally, for technology drivers, construction technology was identified as being high priority, followed by design technology and manufacturing technology, all of which need to be addressed in the medium term. This study presents a roadmap for future uptake.
Wristbands in Home-Based Rehabilitation—Validation of Heart Rate Measurement

The possibility of using a smartwatch as a rehabilitation tool to monitor patients’ heart rates during exercise has gained the attention of many researchers. This study aimed to evaluate the accuracy and precision of the HR measurement performed by two wrist monitors: the Fitbit Charge 4 and the Xiaomi Mi Band 5. Thirty-one healthy volunteers were asked to perform a stress test on a treadmill. Their heart rates were recorded simultaneously by the wristbands and an electrocardiogram (ECG) at 1 min intervals. The mean absolute error percentage (MAPE), Lin’s concordance correlation coefficient (LCCC), and Bland–Altman analysis were calculated to compare the precision and accuracy of heart rate measurements. The estimated validation criteria were MAPE < 10% and LCCC < 0.8. The overall MAPE and LCCC of the Fitbit were 10.19% (±11.79%) and 0.753 (95% CI: 0.717–0.785), respectively. The MAPE and LCCC of the Xiaomi were 6.89% (±9.75) and 0.903 (0.886–0.917), respectively. The precision and accuracy of both devices decreased with the increased exercise intensity. The accuracy of wearable wrist-worn heart rate monitors varies and depends on the intensity of training. Therefore, the decision to use such a device as a heart rate monitor during in-home rehabilitation should be made with caution.
Investigating the Effect of Traffic Sampling on Machine Learning-Based Network Intrusion Detection Approaches

Machine Learning (ML) based Network Intrusion Systems (NIDSs) operate on flow features which are obtained from flow exporting protocols (i.e., NetFlow). Recent success of ML and Deep Learning (DL) based NIDS solutions assume such flow information (e.g., avg. packet size) is obtained from all packets of the flow. However, often in practice flow exporter is deployed on commodity devices where packet sampling is inevitable. As a result, applicability of such ML based NIDS solutions in the presence of sampling (i.e., when flow information is obtained from sampled set of packets instead of full traffic) is an open question. In this study, we explore the impact of packet sampling on the performance and efficiency of ML-based NIDSs. Unlike previous work, our proposed evaluation procedure is immune to different settings of flow export stage. Hence, it can provide a robust evaluation of NIDS even in the presence of sampling. Through sampling experiments we established that malicious flows with shorter size (i.e., number of packets) are likely to go unnoticed even with mild sampling rates such as 1/10 and 1/100. Next, using the proposed evaluation procedure we investigated the impact of various sampling techniques on NIDS detection rate and false alarm rate. Detection rate and false alarm rate is computed for three sampling rates (i.e., 1/10, 1/100, 1/1000), for four different sampling techniques and for three (two tree-based, one deep learning based) classifiers. Experimental results show that systematic linear sampler - SketFlow performs better compared to non-linear samplers such as Sketch Guided and Fast Filtered sampling. We also found that random forest classifier with SketchFlow sampling was a better combination. The combination showed higher detection rate and lower false alarm rate across multiple sampling rates compared to other sampler-classifier combinations. Our results are consistent in multiple sampling rates, exceptional case is observed for Sketch Guided Sampling (SGS) as it caused a drastic performance drop when sampling rate was changed from 1/100 to 1/1000. Our results provide valuable insights for network practitioners and researchers regarding on how packet sampling effects ML-based NIDS performance. In this regard full source code for sampling and ML experiments has been released: github.com/Jumabek/sampledFlowMeter and github.com/Jumabek/nids-with-sampling
A new scheme of a lensed fiber employing a wedge-shaped graded-index fiber tip for the coupling between high-power laser diodes and single-mode fibers

A novel lensed fiber employing a wedge-shaped graded-index fiber (GIF) is proposed. The characteristic of coupling loss as a function of the aspect ratio is numerically investigated. When the aspect ratio is seven, the coupling loss of a wedge-shaped GIF and a conventional wedge-shaped SMF are 0.22 dB and 0.60 dB, respectively, and when the aspect ratio is 13, they are 0.5 dB and 2.4 dB. The tolerance to laser diode (LD)-fiber displacement is also numerically investigated, and it is confirmed that the proposed fiber has larger tolerance than a conventional wedge-shaped single-mode fiber (SMF). The performance of the new lensed fiber is also experimentally verified.
Variability and trends in surface solar spectral ultraviolet irradiance in Italy: on the influence of geopotential height and lower-stratospheric ozone

Abstract. The short- and long-term variability of the surface spectral solar ultraviolet (UV) irradiance is investigated across Italy using high-quality ground-based measurements from three locations: Aosta (45.7∘ N, 7.4∘ E, 570 m a.s.l.), Rome (41.9∘ N, 12.5∘ E, 15 75 m a.s.l.), and Lampedusa (35.5∘ N, 12.6∘ E, 50 m a.s.l.). The three sites are characterized by different environmental conditions and represent almost the full latitudinal extent of the Italian territory. Data of two periods were analysed: 2006–2020 (all sites) and 1996–2020 (Rome only). The main objective of this study is to quantify the effect of the geopotential height (GPH) at 250 hPa on total ozone, and spectral irradiance at 307.5 and 324 nm. We first show that monthly anomalies in GPH, total ozone, and spectral irradiances are correlated amongst the three sites, suggesting that Italy is often affected by the same synoptical weather systems. We further find statistically significant anticorrelations between GPH and monthly anomalies in total ozone for all stations and months. Conversely, we identify positive correlations between GPH and monthly anomalies in spectral irradiance at 307.5 nm for most months. The influence of GPH on short-term variability also hold for long-term trends. For example, long-term changes in total ozone over the period 2006–2020 were associated with changes in GPH for all stations. This suggests that observed negative trends in total ozone were mainly driven by changes in lower-stratospheric ozone as upper-stratospheric ozone was increasing over this period. For several months of the year, positive trends in UV irradiance were observed, and we found that these trends were predominantly caused by changes in clouds and/or aerosols instead of total ozone. For the longer period of 1996–2020, a statistically significant annualized decrease in total ozone of ∼ 0.1 % per year was identified for Rome and could subsequently be attributed to decreasing lower-stratospheric ozone. While positive trends in spectral irradiance at 307.5 nm were observed for several months of this extended period, the negative trend in total ozone did not lead to a positive trend in the spectral irradiance at 307.5 nm in the deseasonalized data. Our study provides evidence that dynamical processes taking place in the troposphere lead to significant variability in total ozone and surface solar UV irradiance.
Aircraft collision avoidance based on GPS position broadcasts

The current airborne collision avoidance system provides pilots with approximate information on the relative location of nearby traffic, and with recommended escape maneuvers in the vertical plane. It relies on range measurements, and suffers from high false alarm rate. This paper studies a new collision avoidance system, which is based on periodic broadcasts of aircraft position as derived by an on-board GPS receiver. Several collision detection algorithms were evaluated by using a Monte Carlo simulation of random encounters in a free-flight environment. The algorithm selected uses the miss distance vector for both detection and avoidance. This approach can significantly improve the effectiveness of the current collision avoidance system, while lowering both the probability of false alarm and the probability of late alarm.
Gray-Level Co-occurrence Matrix Analysis for the Detection of Discrete, Ethanol-Induced, Structural Changes in Cell Nuclei: An Artificial Intelligence Approach

Abstract Gray-level co-occurrence matrix (GLCM) analysis is a contemporary and innovative computational method for the assessment of textural patterns, applicable in almost any area of microscopy. The aim of our research was to perform the GLCM analysis of cell nuclei in Saccharomyces cerevisiae yeast cells after the induction of sublethal cell damage with ethyl alcohol, and to evaluate the performance of various machine learning (ML) models regarding their ability to separate damaged from intact cells. For each cell nucleus, five GLCM parameters were calculated: angular second moment, inverse difference moment, GLCM contrast, GLCM correlation, and textural variance. Based on the obtained GLCM data, we applied three ML approaches: neural network, random trees, and binomial logistic regression. Statistically significant differences in GLCM features were observed between treated and untreated cells. The multilayer perceptron neural network had the highest classification accuracy. The model also showed a relatively high level of sensitivity and specificity, as well as an excellent discriminatory power in the separation of treated from untreated cells. To the best of our knowledge, this is the first study to demonstrate that it is possible to create a relatively sensitive GLCM-based ML model for the detection of alcohol-induced damage in Saccharomyces cerevisiae cell nuclei.
A new approach to three‐way decisions making based on fractional fuzzy decision‐theoretical rough set

The main aim of the proposed work is to develop the new technique based on decision‐theoretical rough sets (DTRSs) and their applications in three‐way decision‐making problems. This study first develop a fractional fuzzy set (FFS) and their operations, the FFS is a more generalized and accurate tool for describing uncertainty in real‐life data information. A new form of decision technique for dealing with the issue of choice based on DTRSs is included in the three‐way decisions. The loss function of DTRSs is being used in the proposed decision method model. Initially, the idea of fractional fuzzy α‐covering (FF α‐covering), fractional fuzzy α–neighborhood (FF α–neighborhood) was introduced. Under the fractional fuzzy state, we integrated the loss function of DTRSs with covering‐based fractional fuzzy rough sets. Furthermore, we proposed and established performance characteristics for a new fractional fuzzy α‐covering decision‐theoretical rough sets model (FFCDTRSs). Then, according to the level of fractional fuzzy numbers (FFN's) positive and negative membership and related three‐way decision‐making, four methods to solve the expected loss expressed in the form of (FFNs) are described. We have developed a multicriteria decision algorithm (MCDM) based on FFCDTRS. Then an example is used to prove the feasibility of the four methods to solve the MCDM problem. Finally, the results of four distinct decision procedures with various loss functions are compared. The proposed three‐way decision‐making models are more accurate as compared with particular fuzzy sets.
Adverse events following influenza immunization: understanding the role of age and sex interactions

ABSTRACT Background Reduction of adverse events following immunization (AEFI) could improve vaccine uptake. Evidence suggests sex and age affect AEFI rates but, with limited understanding of their interaction, groups at higher risk for adverse reaction cannot be identified. Research Design and Methods Using deidentified data (n = 308,481) from Australians receiving influenza vaccinations in the 2020 calendar year, we analyzed the effects of independent predictors (i.e. age and sex), on experiencing an AEFI using logistic regression generalized additive modeling to capture any nonlinear relationships and adjusting for vaccine brand and concomitant vaccination. Results The overall reaction rate was 5.5%. Modeling revealed significant effects of age (p < 0.001), sex (p < 0.001), and age × sex (p < 0.001). Females were more likely than males to experience AEFIs between 7.5 and 87.5 years of age and exhibited peak odds at about 53 years, while peak odds for males occurred in infancy. Conclusion The results suggest there is a need for targeting AEFI reduction in females, particularly in 30–70-year-olds, to improve the vaccination experience. The results further suggest that reducing concomitant vaccination and choosing less reactogenic vaccine brands could reduce risk of AEFI, however, retaining concomitant vaccination may optimize vaccine uptake.
Lipid Alterations in African American Men with Prostate Cancer

African-American (AA) men are more than twice as likely to die of prostate cancer (PCa) than European American (EA) men. Previous in silico analysis revealed enrichment of altered lipid metabolic pathways in pan-cancer AA tumors. Here, we performed global unbiased lipidomics profiling on 48 matched localized PCa and benign adjacent tissues (30 AA, 24 ancestry-verified, and 18 EA, 8 ancestry verified) and quantified 429 lipids belonging to 14 lipid classes. Significant alterations in long chain polyunsaturated lipids were observed between PCa and benign adjacent tissues, low and high Gleason tumors, as well as associated with early biochemical recurrence, both in the entire cohort, and within AA patients. Alterations in cholesteryl esters, and phosphatidyl inositol classes of lipids delineated AA and EA PCa, while the levels of lipids belonging to triglycerides, phosphatidyl glycerol, phosphatidyl choline, phosphatidic acid, and cholesteryl esters distinguished AA and EA PCa patients with biochemical recurrence. These first-in-field results implicate lipid alterations as biological factors for prostate cancer disparities.