Miracle-dz/UniFAR-FTUs huggingface dataset:
Environment regimes play an important role in structuring trait‐ and taxonomy‐based temporal beta diversity of riverine diatoms

A sound understanding of the community changes over time and its driving forces is at the centre of biodiversity conservation and ecology research. In this study, we examined: (i) the relative roles of turnover and nestedness components to trait‐ and taxonomy‐based temporal beta diversity of riverine diatoms; (ii) whether trait‐based temporal beta diversity provides complementary information to taxonomy‐based temporal beta diversity; (iii) the relative roles of hydrology (e.g. discharge, antecedent precipitation index), metal ions (e.g. Mg2+, Si2+) and nutrients (e.g. nitrogen, orthophosphate) to the both facets of temporal beta diversity and their components (i.e. total beta diversity, turnover and nestedness); and (iv) whether inclusion of environment regimes increase their explained variations. A total of 338 daily samples of riverine diatom communities were collected. We employed Mantel tests to evaluate the complementarities between trait‐ and taxonomy‐based temporal beta diversity. Using distance‐based redundancy analysis (db‐RDA) and variation partitioning, we investigated the relative roles of hydrology, metal ions and nutrients to each facet of temporal beta diversity and its components. Correlations between trait‐ and taxonomy‐based temporal beta diversity and their components were weak, which showed their complementary ecological information. Taxonomy‐based total beta diversity had a high contribution by turnover component, whereas trait‐based total beta diversity was largely driven by nestedness component. Results of variation partitioning demonstrated that the pure and shared fractions of hydrology, metal ions and nutrient differed among the components of trait‐ and taxonomy‐based temporal beta diversity. Furthermore, addition of environment regimes could dramatically increase the explained variation of temporal beta diversity and its components. Synthesis. Our results highlighted the importance of the two facets of temporal beta diversity as well as their decomposition for exploring diversity patterns of riverine diatoms in relation to abiotic factors, particularly the environment regimes. Although a high temporal taxonomic divergence was detected, the high level of temporal trait convergence indicated that species turnover with similar biological traits occurred during our study period. Our study, for the first time, provides a new perspective into temporal beta diversity of daily riverine diatom communities, which has not yet been documented by previous freshwater studies.
The Quality Detection of the Non-Mark Printing Image Based on HALCON

A new approach of quality detection of the printing image based on HALCON is proposed. Our design is based on HALCON,a machine vision software,which includes key processing steps such as chosing matching regions,shape-based matching,defects detection and so on. First,the matching region based on the region features is chosen,such as area,rectangle descriptor and circular descriptor.Then,fast image matching in the approach of the shape-based matching is realized. At last,the improved difference-matching algorithm to detect the printing defects is used. The result of the experiment shows that our approach can choose the proper matching regions from the non-mark printing image automatically,match the images with high accuracy and speed,and detect the printing defects efficiently.
Efficacy of Myopia Control and Distribution of Corneal Epithelial Thickness in Children Treated with Orthokeratology Assessed Using Optical Coherence Tomography

The association between myopia control efficacy in children treated with orthokeratology and corneal epithelial thickness is still unknown. The aim of this study was to explore the corneal epithelial thickness and its association with axial length changes in children treated with orthokeratology. This retrospective cohort study enrolled children aged from 9 to 15 years who had received orthokeratology for myopia control and had been followed up for at least 1 year. Anterior segment optical coherence tomography was performed to generate wide epithelial thickness maps of the patients. Annual axial length changes were calculated from the axial length at 6 months after the initiation of orthokeratology lens wear and at final measurements. Corneal epithelial thickness data were obtained from 24 sectors and a central 2 mm zone of the wide epithelial thickness map. Associations between annual axial length changes and corneal epithelial thickness for each sector/zone of the wide epithelial thickness map, and orthokeratology treatment data were determined by generalized estimating equations. Finally, a total of 83 eyes of 43 patients (mean age 11.2 years) were included in the analysis. The mean annual axial length change was 0.169 mm; when regressing demographic and ortho-k parameters to mean annual axial length changes, age and target power were both negatively associated with them (β = −14.43, p = 0.008; β = −0.26, p = 0.008, respectively). After adjusting for age and target power, the annual axial length changes were positively associated with the corneal epithelium thickness of IT1, I1, SN2, and S2 sectors of the wide epithelial thickness map, and negatively with that of the I3 sector. In conclusion, we identified associations between annual axial length changes and the corneal epithelium thickness of certain sectors in children treated with orthokeratology. This may facilitate the design of orthokeratology lenses with enhanced efficacy for myopia control.
Land Resource Evaluation for District Level Planning: An Approach

Using the soil resource information of Buldhana district sixteen benchmark soils were identified. Using monthly rainfall, potential evapotranspiration in the area and available water capacity, the water balances were worked out for these benchmark soils. These indicated that parts of the district have three growing periods viz. 154, 184 and 215 days. Growing period zones with similar growing environment (soil and climate) were delineated. Considering the present land use, soil and climatic information, new land use options for each zone have been suggested.
Network Intrusion Detection: A Comprehensive Analysis of CIC-IDS2017

: With an ever increasing number of connected devices, network intrusion detection is more important than ever. Over the past few decades, several datasets were created to address this security issue. Analysis of older datasets, such as KDD-Cup99 and NSL-KDD, uncovered problems, paving the way for newer datasets that solved the identiﬁed issues. Among the recent datasets for network intrusion detection, CIC-IDS2017 is now widely used. It presents the advantage of being available as raw data and as ﬂow-based features in CSV ﬁles. In this paper, we analyze this dataset in detail and report several problems we discovered in the ﬂows extracted from the network packets. To address these issues, we propose a new feature extraction tool called LycoSTand, available as open source. We create LYCOS-IDS2017 dataset by extracting features from CIC-IDS2017 raw data ﬁles. The performance comparison between the original and the new datasets shows signiﬁcant improvements for all machine learning algorithms we tested. Beyond the improvements on CICIDS2017, we discuss other datasets that are affected by the same problems and for which LycoSTand could be used to generate improved network intrusion detection datasets.
Learning Configurations of Operating Environment of Autonomous Vehicles to Maximize their Collisions

Autonomous vehicles must operate safely in their dynamic and continuously-changing environment. However, the operating environment of an autonomous vehicle is complicated and full of various types of uncertainties. Additionally, the operating environment has many configurations, including static and dynamic obstacles with which an autonomous vehicle must avoid collisions. Though various approaches targeting environment configuration for autonomous vehicles have shown promising results, their effectiveness in dealing with a continuous-changing environment is limited. Thus, it is essential to learn realistic environment configurations of continuously-changing environment, under which an autonomous vehicle should be tested regarding its ability to avoid collisions. Featured with agents dynamically interacting with the environment, Reinforcement Learning (RL) has shown great potential in dealing with complicated problems requiring adapting to the environment. To this end, we present an RL-based environment configuration learning approach, i.e., DeepCollision, which intelligently learns environment configurations that lead an autonomous vehicle to crash. DeepCollision employs Deep Q-Learning as the RL solution, and selects collision probability as the safety measure, to construct the reward function. We trained four DeepCollision models and conducted an experiment to compare them with two baselines, i.e., random and greedy. Results show that DeepCollision demonstrated significantly better effectiveness in generating collisions compared with the baselines. We also provide recommendations on configuring DeepCollision with the most suitable time interval based on different road structures.
Free vibration analysis of tapered Timoshenko beam with higher order Haar wavelet method

In the current study, the higher order Haar wavelet method based formulation is developed for the analysis of the free vibrations of the tapered Timoshenko beam. The clamped-clamped and clamped-pinned boundary conditions are explored and the results with the 4th order and the 6th order of convergence are presented. The results are found to be in good agreement with the corresponding results of the Ritz method. The proposed approach can be considered as the principal improvement of the widely used Haar wavelet method providing the same accuracy with the several magnitudes lower mesh. Thus, the higher order Haar wavelet method has reduced the computational cost in comparison with the widely used Haar wavelet method since the computational complexity of both methods is determined by the mesh used. In the case of the fixed equal mesh used for both methods, the higher order Haar wavelet method results in the several magnitudes lower absolute error without a remarkable increase in computational complexity. The cost needed to pay for higher accuracy is hidden in a certain increase in the implementation complexity compared with the widely used Haar wavelet method.
Physio-mechanical properties and applications of natural fiber reinforced bio-composites

At present, natural or lignocellulosic fiber-based bio composites are the talk of the town due to their low density, cost effective, eco-friendly, renewable properties. Bio fibers such as jute, kenaf, pineapple, sugarcane, flax, leaf, hemp, wool, silk etc obtained from plants or nature which can be utilized to obtain new high performance polymer composite materials. The physical and mechanical characteristics of these bio fibers (e.g., tensile properties, flexural stress-strain behaviour, fracture strength, impact strength) make them more sustainable and attractive than synthetic fibers with a remarkable biodegradable characteristic. The aim of this review is to give a thorough overview on natural fibers and natural fiber reinforced bio composite materials, their major physical and mechanical properties and potential applications.
Alteration of Ethanol Reward by Prior Mephedrone Exposure: The Role of Age and Matrix Metalloproteinase-9 (MMP-9)

Mephedrone, a synthetic cathinone, is widely abused by adolescents and young adults. The aim of this study was to determine: (i) whether prior mephedrone exposure would alter ethanol reward and (ii) whether age and matrix metalloproteinase-9 (MMP-9) are important in this regard. In our research, male Wistar rats at postnatal day 30 (PND30) received mephedrone at the dose of 10 mg/kg, i.p., 3 times a day for 7 days. To clarify the role of MMP-9 in the mephedrone effects, one mephedrone-treated group received minocycline, as an MMP-9 antagonist. Animals were then assigned to conditioned place preference (CPP) procedure at PND38 (adolescent) or at PND69 (adult). After the CPP test (PND48/79), expression of dopamine D1 receptors (D1R), Cav1.2 (a subtype of L-type calcium channels), and MMP-9 was quantified in the rat ventral striatum (vSTR). The influence of mephedrone administration on the N-methyl-D-aspartate glutamate receptors (NMDAR) subunits (GluN1, GluN2A, and GluN2B) was then assessed in the vSTR of adult rats (only). These results indicate that, in contrast with adolescent rats, adult rats with prior mephedrone administration appear to be more sensitive to the ethanol effect in the CPP test under the drug-free state. The mephedrone effect in adult rats was associated with upregulation of D1R, NMDAR/GluN2B, MMP-9, and Cav1.2 signaling. MMP-9 appears to contribute to these changes in proteins expression because minocycline pretreatment blocked mephedrone-evoked sensitivity to ethanol reward. Thus, our results suggest that prior mephedrone exposure differentially alters ethanol reward in adolescent and adult rats.
Physicochemical characterization and in vitro evaluation of the antioxidant and anticandidal activities of Moroccan propolis

Background and Aim: Human mycotic infections are one of the major health problems worldwide. Prolonged use of antimycotic drugs has contributed to the development of resistance in pathogenic fungi. This study was conducted to examine antioxidant and anticandidal activities of Moroccan propolis. Materials and Methods: Two ethanolic extracts of Moroccan propolis from the Fez-Meknes region were evaluated regarding the following physicochemical parameters: Yield, pH, total carbohydrates, total proteins, total lipids, minerals, total phenolic content, total flavonoid content, and antioxidant activity using ferric reducing antioxidant power (FRAP) and 2,2’-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) assays. In addition, we assessed the in vitro anticandidal activity against vulvovaginal candidiasis strains, that is, Candida albicans, Candida glabrata, Candida parapsilosis, and Candida krusei, using the broth micromethod according to the CLSI/M27-A3 reference guidelines. Results: The propolis samples exhibited a mean yield of 16%, with an acidic pH ranging from 4.8 to 5.9; the sample from the Oued Amlil area (OAPEE) contained high levels of resin, balsam, moisture, total carbohydrates, and total lipids: 59.8%, 0.71%, 2%, 1.01 gGlcEq/g, and 120 mg/g, respectively. Moreover, the sample from the Sefrou area (SFPEE) was richer in total proteins and minerals, with values of 2.5 g/100 g and 1.84%, respectively. The total polyphenol and flavonoid content in the propolis extracts were 117.38 and 194.68 mg of gallic acid equivalent/g, and 17.45–27.79 mg of quercetin equivalent/g, respectively. Regarding the antioxidant activity, the most effective propolis extract was the sample from the Sefrou area, at 72.5 μg/mL and 118.78 μmoL Fe2+/g for ABTS-half-maximal inhibitory concentration and FRAP-half maximal effective concentration, respectively. The analysis of phenolic compounds using high-performance liquid chromatography with a diode-array detector revealed the presence of 13 polyphenols. The main compound in the OAPEE sample was epicatechin (310 mg/g), whereas in the SFPEE sample was apigenin (410 mg/g). Regarding the antifungal activity against Candida species, the minimum inhibitory concentration and minimum fungicidal concentration of the Moroccan propolis ethanolic extracts ranged between 31.2 and 62.5 μg/mL and 62.5 and 125 μg/mL, respectively, comparable with fluconazole (as a reference antimycotic). Conclusion: This study suggests that Moroccan propolis (31.2 and 125 μg/mL) may be an important source of bioactive molecules with anticandidal activity. Propolis may be a promising naturally-occurring candidate for the development of antimycotic drugs.
Enhanced Path Loss Model by Image-Based Environmental Characterization

Accurate path loss (PL) models are critical for the design and optimization of wireless communication systems. The selection between empirical models and deterministic models are usually a tradeoff between accuracy and efficiency. In this letter, a novel environmental characterization method is defined by considering clutter information in the vector-based and image-based structures. Three PL models are proposed with different artificial neural network (ANN) architectures and two environmental characterizations. Comparative analysis shows that an image-based environmental characterization, which can reduce the influence of interference types, is better than a vector-based characterization. The combination of an image-based environmental characterization method and ANNs can enhance PL prediction in both accuracy and efficiency.
Application of R-T-S Optimal Smoothing Algorithm to the Post-Assessment of SINS Alignment

In strapdown inertial navigation system (SINS), an initial alignment Kalman filter is usually used to evaluate the misalignment angles. The precision of optimal smoother is higher than that of Kalman filter from the theory. This paper presented an application of R-T-S fixed-interval optimal smoothing technique to calculate the misalignment angles via post processing of alignment data, then used it as the reference misalignments to assess SINS alignment precision. The simulation was done with marine SINS and the simulation schematic figure was given. The results show that the precision of R-T-S smoothing is higher than that of Kalman filter and it can effectively evaluate the performance of SINS alignment.
A Systematic Review of Studies on Virtual Reality Use in Management of Pain

Background- Virtual reality (VR) is an effective drug-free tool for management of pain. However, its use remains elusive in developing countries like Nigeria.Objectives: To characterize studies conducted on using virtual reality in managing pain. Methods: A comprehensive systematic review was conducted for studies done globally from 2000 to 2016. Databases (Google, Pubmed, BioMed Central, Mendeley) were searched to identify eligible studies. Search terms included: Virtual reality, Virtual patients, and management of pain using VR. Data extracted included: Title/authors of articles, objectives, study design, methods, population, age group, primary disease conditions, VR equipment, environments, display technology/ senses needed, country of study, effect of VR plus pharmacologic analgesia, and study outcomes. Results: Out of 3821 potentially relevant articles identified 24(0.63%) were eligible. Fourteen (58.3%) and 8(33.3%) studies were Randomized Control Trials, and Case Studies/Reports respectively. A total of 8(33.3%) and 3(12.5%) studies were on Burn pain and Phantom limb pain respectively. Seventeen (70.8%) studies had adults as target population. Thirteen (54.2%) studies were done in the USA, 19 (79.2%) were Immersive VR, 15(62.5%) had head mounted display as display technology, and 22 (91.67%) had positive outcomes. VR plus pharmacologic analgesia 8 (33.37%) had positive outcomes. No study was found for Nigeria. Conclusion: This review demonstrates wide range of characteristics for studies encountered and VR is shown as effective for reducing pain in different disease conditions even when combined with pharmacological analgesia. The absence of studies on management of pain using VR in Nigeria calls for creation of awareness among major stakeholders.
Estudo comparativo entre Máquina de Vetores de Suporte e Rede Neural Convolucional na classificação do inseto Diaphorina citri

O inseto Diaphorina citri é o principal propagador da doença dos citros Huanglongbing. Para o controle do problema, os insetos são capturados por armadilhas adesivas e contados manualmente, para ajuste da dosagem de inseticida. Assim, este trabalho teve como objetivo medir e analisar o desempenho da classificação automática do Diaphorina citri a partir de abordagens de Aprendizado de Máquina. Para o treinamento dos modelos foi criado um banco de imagens e utilizadas as abordagens de Máquina de Vetores de Suporte (SVM) e Rede Neural Convolucional (CNN). A CNN, com o modelo Inception v3, apresentou em média 99.37% de acurácia na classificação final do Diaphorina citri, resultado significativo em relação aos 97.99% apresentado pela SVM.
Performance of DGPS Smartphone Positioning with the Use of P(L1) vs. P(L5) Pseudorange Measurements

This paper presents numerical analyzes of code differential GPS positioning with the use of two Huawei P30 Pro mobile phones. Code observations on L1 and L5 frequencies were chosen for DGPS positioning analysis. For project purposes, we additionally used one high-class geodetic GNSS receiver (Javad Alpha) acting as a reference station. Smartphones were placed at the same distance of 0.5 m from the reference receiver. Such a close distance was specially planned by the authors in order to achieve identical observation conditions. Thus, it was possible to compare the DGPS positioning accuracy using the same satellites and the P(L1) and P(L5) code only, for single observation epochs and for sequential DGPS adjustment. Additionally, the precision of observations of the second differences in the observations P(L1) and P(L5) was analyzed. In general, the use of the P(L5) code to derive DGPS positions has made it possible to significantly increase the accuracy with respect to the positions derived using the P(L1) code. Average errors of horizontal and vertical coordinates were about 60–80% lower for the DGPS solution using the P(L5) code than using the P(L1) code. Based on the simulated statistical analyses, an accuracy of about 0.4 m (3D) with 16 satellites may be obtained using a smartphone with P(L5) code. An accuracy of about 0.3 m (3D) can be achieved with 26 satellites.
Research on the principle and simulation of grid-connected PV inverter based on MMC

Modular multilevel converter(MMC) topology has become the most attractive multilevel technology since it has been proposed. This paper analyzes the working principle of the grid-connected PV inverter with MMC as the core converter. The key technologies of MMC such as modulation and voltage balancing are studied and dynamic direct modulation method and simplified capacitor voltage sequencing are proposed. With the system level control using conventional double closed-loop controller, a simulation model of whole grid-connected PV inverter based on MMC is built. The simulation results confirm that the scheme of designing grid-connected PV inverter based on MMC technology and conventional system level controller is not only feasible but also has low harmonic advantage.
Simulation-based time and jerk optimisation for robotic press tending

Increased production rate and robot motion smoothness in a sheet metal press line are essential. Smooth robot motions avoid unplanned production interruptions and excessive wear of the robots. Reaching high production rate and smooth motions requires tuning of the tending press robot control to minimise the cycle time and jerk. Doing this for a press line with multiple robots is a complex large-scale problem. To model such problems for the optimisation process, computer simulations become almost essential. This work presents simulation-based optimisation of the time and jerk of robotic press tending operations and investigates the importance of including the robot motion's smoothness. An optimiser works in concert with a simulation model of a sheet metal press line and its parametrised control system. The effect of including jerk minimisation in the objective function is tested on a real-world problem concerning a sheet metal press line. The results illustrate the importance of including jerk-minimisation as an objective in the optimisation. Furthermore, the performance of this approach is compared with manual tuning by experienced operators. The results show that the proposed simulation-based optimisation approach outperforms manual tuning.